dementia research new zealand

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Dementia Prevention Research Clinic

The largest of Brain Research New Zealand’s (BRNZ) Dementia Prevention Research Clinics (DPRC) is based at the Centre for Brain Research.

The Clinic opened in 2016 and was the first of a national network of clinics established by BRNZ.

Led by Associate Professor Lynette Tippett and Dr Phil Wood, the Auckland Clinic is run collaboratively between expert clinicians and researchers from Brain Research New Zealand.

The DPRC is at the frontline of collaborative research studies involving individuals with mild cognitive impairment (MCI) and those with very early Alzheimer’s disease. The DPRC enables cutting-edge research to identify factors that influence the progression from MCI to dementia.

The clinics offer an exciting opportunity for people in the earliest stages of dementia to join a longitudinal study that holds promise for future research findings.

When patients and their families attend the dementia clinic, they will typically undergo a detailed characterisation of their brain health and lifestyle. Blood tests and MRI scans are conducted and this data provides invaluable information to neuroscientists and clinicians attempting to identify biomarkers and clinical markers of disease.

The DPRC collects holistic information by listening to the experiences of the research participants, family members and caregivers. Clinic participants are monitored longitudinally and are invited to participate in a broad range of studies and preliminary clinical trials by researchers at BRNZ.

This could include testing novel drugs, nutritional supplements, and cognitive, social and physical interventions designed to prevent, delay or ameliorate MCI and other related dementias.

Dementia Prevention Research Clinic Auckland Phone: +64 9 9236579 Email: dprc@uoa.auckland.ac.nz

The clinic is located at: The University of Auckland Grafton Campus, Building 507 22-30 Park Ave, Grafton

The Dementia Prevention Research Clinics

Uniting new zealand’s best clinicians, neuroscientists and the scientific brain research community to combat alzheimers..

60,000 New Zealanders suffer from Alzheimer’s disease or a related dementia.

New zealand’s alzheimer’s epidemic, today, more than 60,000 new zealanders suffer from alzheimer’s disease or a related dementia, a number that is expected to triple by 2050..

Alzheimer’s disease is a complex and challenging disease. We do not know the cause and currently there is no cure. Research offers hope that development of a range of novel treatments may delay the onset and progression of the disease and maximise quality of life. To have the biggest possible impact on people’s lives, we need to be able to diagnose those at risk of Alzheimer’s when the earliest biological changes occur – up to 15 years before clinical symptoms appear.

If we could delay the onset of Alzheimer’s disease by 5 years, we could reduce the incidence of dementia by 50%.

What are the Dementia Prevention Research Clinics?

The Dementia Prevention Research Clinics are a multi-year longitudinal study designed to identify processes causing memory and functional decline in older adults, and to test new interventions that may delay or prevent the onset and progression of dementia.

They were established by Brain Research New Zealand, a national Centre of Research Excellence, and are supported by the New Zealand Dementia Prevention Trust.  Through the clinics, we are recruiting people with memory problems, as well as healthy volunteers, and following them to find out which blood and brain biomarkers, cognitive characteristics, health and lifestyle factors influence the development and progression of dementia in New Zealanders. With this powerful data asset, the brain research community will be better able to develop tools, programmes and treatments to combat Alzheimer’s disease.

Progress and impact so far

Our researchers and clinicians have 28 research projects underway that are helping to further our understanding of alzheimer’s disease, and to test interventions that might delay its progression., our current research is focusing on:, early markers of change using mri and pet scans, quality of life and wellbeing, sensory functioning (hearing), intervention trials using low level brain stimulation, early markers of change from blood proteins, metabolites and genetics, changes in brain plasticity and connectivity using brain-wave recordings, understanding risk and protective factors for dementia in māori, sleep disturbance and progression of cognitive decline.

• Clinical team

The local clinics’ directors, Associate Professor Lynette Tippett and Dr Phil Wood (Auckland), Professor Tim Anderson and Professor John Dalrymple-Alford (Christchurch), and Dr Nick Cutfield (Dunedin), are supported by talented teams of medical specialists, neuroscientists, neuropsychologists, research nurses and research support staff.

Professor Lynette Tippett

National director, dementia prevention research clinics find out more >.

Professor Tim Anderson

Clinical director of the nz brain research institute find out more >.

Professor Dalrymple-Alford

New zealand brain research institute, christchurch find out more >.

Dr Nick Cutfield

Clinical deputy director, brain health research centre; senior lecturer; consultant neurologist and clinical lead find out more >.

Jane Govender

Clinics manager find out more >, philanthropist sir eion edgar set up the trust in 2015 in partnership with leading brain research scientist sir richard faull, with the objective of fundraising for the clinics..

Chair of the NZ Dementia Prevention Trust Find out more >

Sir Ralph Norris

Knzm d.bus (hon) find out more >.

Mark Stewart

Bcom (business administration) find out more >.

Ngaire Dixon

Director at mace consulting ltd find out more >, donate to help us, the new zealand dementia prevention trust directly supports the clinics in our effort to combat alzheimer’s disease and dementia. your donation will help fund the clinical team, and pay for brain and other scans that help us create a unique and powerful data asset that enables brain researchers to discover treatments and interventions to slow cognitive decline., if you would like to support our research, you can donate directly using the below links or to discuss a tailored giving program or bequest, please fill out the contact us form below., one-off donation, donate to help support our mission to combat alzheimers.  any amount is appreciated to assist with this important work., regular monthly donation, donate a regular monthly amount that will contribute directly to the monthly operating costs of the clinics., sponsor a participant, it costs nzd $5000 each per year for a participant to be included in the program. these costs are spread across clinical staff, premises, and various bio-marker data collection processes including pet and mri scans, bloodwork and more., sponsor a brain scan, a brain positron emission tomography (pet) scan is an imaging test of the brain, and is a key element of the clinics’ research to identify and monitor progression of disease in the brain. the cost of each pet scan is nzd $2,000., sponsor a mri, a magnetic resonance imaging (mri) scan is a method for capturing detailed internal images of the brain and is another key element of the clinics’ research to identify and monitor progression of disease in the brain. the cost of each mri scan is nzd $1,500., sponsor a data project, all of the data collected is input, analysed and managed to ensure it’s accessible but controlled, and ready for analysis by scientific brain researchers. if you are interested to sponsor one of the many distinct data projects that need funding, please use the contact us form to enquire and we’ll get back to you., the new zealand dementia prevention trust is incorporated as a charitable trust number 2628171, hence any donations will receive an official donation receipt that will convey a 33.33% tax credit on the donor’s taxable income., would you like to join our study, over the next two years we hope to recruit 400 volunteers with mild cognitive impairment to participate in our study. if you are interested in enrolling in the dprc, please have a look at our inclusion criteria below. you can also speak to your gp, specialist, or contact your nearest dprc team directly., you may be eligible to participate if:.

• You are aged over 55;
• You or others have noticed memory problems;
• You are fluent in English; and
• You are not living in long-term care;

Unfortunately you will NOT be eligible to participate if you have:

• Been diagnosed with dementia
• A history of significant alcohol and/or substance use
• Experienced a moderate to severe brain injury
• A pacemaker
• A significant neurological condition (e.g. Parkinson’s disease, stroke, epilepsy, brain tumour)

Participation in our Dementia Prevention Research Clinics is voluntary and for research purposes only. Participation is also free, and will not affect your usual medical care.  Contact us below.

• Research clinics
• Join our study

Dementia Prevention Research Clinic

We are part of part of a national network of Dementia Prevention Research Clinics investigating a wide range of factors that influence the development and progression of memory problems and Alzheimer’s disease in New Zealanders.

Christchurch Dementia Prevention Research Clinic

Christchurch is part of a national network of Dementia Prevention Research Clinics investigating a wide range of factors that influence the development and progression of memory problems and Alzheimer’s disease in New Zealanders.

Finding out what factors influence the development and progression of Alzheimer’s disease means that we can develop and test interventions to delay the disease or prevent its onset. We are looking for participants with memory problems or who have Mild Cognitive Impairment.

What is Mild Cognitive Impairment?

Mild Cognitive Impairment (MCI) is a condition that affects memory and thinking abilities (e.g. planning, word-finding, organising). Everyday tasks are not affected (e.g. work-related tasks, household tasks, driving). MCI is not in itself a disease. Some people with MCI go on to develop Alzheimer’s disease (a type of dementia), but not all people with MCI do. We want to find out why.

Participant requirements

You may be eligible to participate if:

• You are aged over 55;
• You or others have noticed memory problems;
• You are fluent in English; and
• You are not living in long-term care

Unfortunately you will NOT be eligible to participate if you have:

• Been diagnosed with dementia
• A history of significant alcohol and/or substance use
• Experienced a moderate to severe brain injury
• A pacemaker
• A significant neurological condition (e.g. Parkinson’s disease, stroke, epilepsy, brain tumour)

Participation in our Dementia Prevention Research Clinics is voluntary and for research purposes only. Participation is also free, and will not affect your usual medical care.

The Christchurch Dementia Prevention Research Clinic is hosted by the New Zealand Brain Research Institute, 66 Stewart St.  The Principal Investigators of the Christchurch Clinic are Professor Tim Anderson and Professor John Dalrymple-Alford.

If you are interested in finding out more about participating in the Clinic please contact Marie Goulden; [email protected] or Phone: 03 928 1331

Additional information is available via the Brain Research New Zealand website http://www.brnz.ac.nz/clinics

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Alzheimer’s Disease and Dementia

• More than 170,000 New Zealanders will be living with dementia by 2050.
• Dementia is now the third largest cause of death in New Zealand.  
• Dementia is a progressive condition which means the symptoms will gradually get worse. 

Dementia is a collective term that describes a series of symptoms associated with gradual mental decline. It is not one specific disease, rather a symptom of several underlying diseases and it is not a normal part of ageing. 

The most common form of dementia is Alzheimer’s disease, accounting for 60 to 80 percent of cases of dementia in New Zealand. The second most common cause is vascular dementia.

Signs and Symptoms:

Alzheimer’s is a degenerative disease, meaning symptoms start gradually and get worse over time. These symptoms include:

• Loss of memory
• Difficulty performing normal tasks
• Changes in personality
• Geographic disorientation
• Trouble forming sentences in conversation
• Loss of interest in normal activities

Causes and Treatment:

Alzheimer’s disease occurs when brain cells progressively degenerate and eventually die. The cause of Alzheimer’s disease is currently unknown, although scientists believe there is a causal connection between lifestyle and environmental factors that affect the brain over time.

Researchers have found several genes that increase the risk of Alzheimer’s, although less than 5 per cent of Alzheimer’s cases are believed to be linked to a specific genetic change.

There are drugs on the market that have been modestly successful at treating some of the symptoms of Alzheimer’s such as memory loss and attention skills. There is no known cure for Alzheimer’s, but as science progresses there is hope that medicines and other therapies can be developed to delay, prevent or maybe even reverse the disease. Clinical trials are currently underway into drugs and a vaccine that seek to solve some of the underlying problems that researchers believe cause Alzheimer’s. 

With your help, the Neurological Foundation can continue to fund key research that broadens our understanding of Alzheimer’s and will hopefully one day lead to a cure. 

Support Organisations:

• Alzheimer's New Zealand -  alzheimers.org.nz
• NZ Dementia Co-operative -  nzdementia.org
• Dementia New Zealand -  dementia.nz
• Harris List – Dementia Navigation - harrislist.co.nz  

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Recognising and managing early dementia

Dementia (mate wareware - see below) is a growing healthcare challenge. There are an estimated 70,000 people with dementia in New Zealand; this number is predicted to increase to over 170,000 by 2050, due to factors such as population growth and increased longevity. * Without a curative treatment or ability to prevent progression of dementia, the main management goal, as for other terminal conditions, is to help people maintain their quality of life for as long as possible. Early diagnosis enables patients and their family/whānau to access support, information and appropriate symptomatic treatments, and allows time to plan for the future.

* Estimates from the Alzheimers New Zealand/Deloitte Dementia Economic Impact report (2016)

Age-related cognitive decline: prevention and future planning

Initial consultation: take a clinical history and investigate reversible causes

Cognitive screening and assessment: when and how to administer, types of dementia, follow-up consultation: discussing the diagnosis, non-pharmacological interventions, pharmacological interventions: the role of dementia medicines.

Managing the behavioural and psychological symptoms of dementia

Understanding the role of palliative care for people with advanced dementia

Symptom management in palliative dementia care

National report and CME activities

Published: 21 February 2020 | Updated: 6 August 2020

What's changed?

6 August, 2020: MoCA replaced by Mini-ACE, now the preferred cognitive screening test in New Zealand

If you would like to know what changes were made when the article was updated please contact us

Mate wareware (pronounced “ ma-te wah-ree wah-ree”), meaning to become forgetful and unwell, was identified as a preferred term in te reo Māori for dementia in a large qualitative study including 223 kaumātua (elders). 1

Key practice points:

• Discussions about cognitive decline and dementia (mate wareware * ) can be difficult; patients or their family/whānau may be reluctant to disclose symptoms due to fear, embarrassment, shame or denial
• Symptoms of cognitive decline should be assessed when first reported or noticed. In many cases, reassurance that the symptoms are due to age-related cognitive decline will be appropriate. However, if the symptoms are indicative of a potentially clinically significant change in cognitive function or are affecting the person’s activities of daily living, they should be assessed for dementia.
• The initial consultation should focus on the clinical history (obtained from the patient and someone who knows them well), investigations to exclude other causes of cognitive impairment (e.g. medicine adverse effects, delirium, depression) and evaluation with a cognitive assessment tool.
• Most patients with dementia can be diagnosed and managed in primary care. Referral to secondary care is appropriate if there is diagnostic or management uncertainty.
• Allow additional time when discussing a dementia diagnosis with a patient and their family/whānau to explain what the diagnosis means, how it was made, the management plan and where to access support
• Strongly encourage early engagement with the local branch of Alzheimers New Zealand or Dementia New Zealand as these organisations are often the main providers of personal support, information, dementia service navigation, “living well” services and programmes such as cognitive stimulation treatment
• There are currently no treatments available that can cure or prevent the progression of the common subtypes of dementia such as Alzheimer’s disease or vascular dementia. Non-pharmacological and pharmacological interventions may help to delay or slow the development of cognitive and functional symptoms.

* A term for dementia in te reo Māori, meaning to become forgetful and unwell

Part 1: Making a dementia diagnosis

Dementia is not an inevitable part of ageing and not all changes in cognitive function are indicative of dementia, however, it is important that symptoms are investigated when first reported, e.g. by the patient or a family/whānau member, or noticed, e.g. by the primary care team. 2 Other scenarios where assessment of cognitive function should be considered in older patients include after a fall or other significant medical event, motor vehicle accident or a safety incident at home, e.g. unattended cooking causing a fire. Patients or their family/whānau may be reluctant to discuss the symptoms, e.g. due to fear, shame or denial, however, timely assessment enables primary care to provide reassurance to people who are experiencing normal age-related cognitive decline, prompt treatment to those with reversible causes of cognitive impairment, and earlier diagnosis in those with dementia.

Investigating the cause of cognitive impairment will usually require at least two consultations: an initial consultation where the patient history and clinical investigations are undertaken and a follow-up where the outcome is discussed.

The 15-minute consultation for a person with suspected dementia

The time constraints of primary care consultations can be particularly challenging when assessing a person with suspected dementia and it is likely that multiple consultations will be required when establishing a diagnosis and management plan. The key areas of focus of the initial consultation should be:

• Take a clinical history – establish the type, duration, pattern of symptoms and the impact on daily functioning; clinicians who have cared for patients and their family/whānau over some years will often already have an good understanding of the history and circumstances.
• If dementia is suspected, carry out a brief cognitive test, e.g. using the GPCOG (see: " Cognitive testing with the GPCOG ”). If impairment is indicated (GPCOG score ≤ 4), aconsider a follow-up appointment with a practice nurse for a more comprehensive cognitive assessment, e.g. with the Mini-ACE ” (see: “ Comprehensive cognitive assessment ”). However, Mini-ACE is much quicker to administer than the MoCA so it may be able to be completed during the first consultation.
• Exclude other causes of cognitive impairment, i.e. cardiovascular or neurological examination, depression screening, arrange appropriate investigations (see: “ Consider other explanations for changes in cognitive function ”)

The initial assessment of a person presenting with suspected cognitive decline should focus on the clinical history to establish the:

• Type of symptoms – cognitive, behavioural, psychological and neurological (see: “ Distinguishing age-related cognitive impairment from mild cognitive impairment and dementia ”)
• Duration of symptoms, i.e. when did they start, are they constant or intermittent
• Pattern of symptom onset, i.e. sudden or gradual
• Impact of the symptoms on the person’s functioning in their daily life
• Any other information that might suggest an alternative explanation for cognitive impairment, e.g. medicine adverse effects, delirium, depression (see: “ Consider other explanations for changes in cognitive function ”)

If possible, information should also be obtained from someone who knows the person well, e.g. a family/whānau member. A questionnaire, e.g. the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) or Functional Activities Questionnaire (FAQ), may be used to supplement this discussion (see below for links). 3

A list of questions that may be included as part of the patient history is available from: www.goodfellowunit.org/sites/default/files/dementia/History-taking_recommended_questions_for_patients_with_possible_dementia.pdf

Patient assessment questionnaires for family/whānau are available from:

• IQCODE: www.alzheimers.org.nz/getmedia/6c256fcf-65ec-4622-9233-e1ea4b05ae58/ShortIQcode.pdf/
• FAQ: www.alz.org/careplanning/downloads/functional-activities-questionnaire.pdf

Distinguishing age-related cognitive impairment from mild cognitive impairment and dementia

The main distinctions between cognitive impairment due to ageing and cognitive impairment due to dementia are that:

• Age-related cognitive impairment does not affect daily functioning or the ability to live independently
• Age-related cognitive impairments are less severe than those associated with dementia
• Dementia is always progressive

Mild cognitive impairment is a “grey area” between normal age-related memory loss and dementia where there is some impact on the person’s daily functioning, but it is not considered significant by the person or the people close to them. Approximately half of people with mild cognitive impairment will progress to a dementia syndrome.

If memory loss is accompanied by other signs of cognitive impairment, this may be suggestive of a more advanced stage of dementia and further investigation is necessary. Symptoms and signs include: 4

• Aphasia (impairment in producing and understanding speech)
• Apraxia (difficulty in performing motor tasks)
• Agnosia (inability to recognise familiar people, places and objects)
• Disturbance in executive function (difficulty sequencing, organising, abstracting, planning)
• Change in behaviour or mood (i.e. agitation, apathy, anxiety, disinhibition)
• Physical signs including gait disturbance, extrapyramidal symptoms, focal or lateralising neurological signs

N.B. Some of these symptoms and signs could indicate another neurological diagnosis, particularly if focal neurological signs are present; consider whether referral to secondary care is indicated.

For further information on age-related cognitive decline, see: “ Age-related cognitive decline: prevention and future planning ”

Consider other explanations for changes in cognitive function

There are many possible causes of cognitive impairment that must be considered when a person presents with memory loss or other cognitive changes, including: 5

• Medicines use, e.g. medicines with anticholinergic action or adverse effects, opioids, many psychotropic medicines, steroids
• Psychological causes, e.g. depression, anxiety, stress, psychosis
• Delirium – many potential causes including dehydration, infection, e.g. urinary tract infection or pneumonia, sensory impairment, adverse medicine reaction, immobility, metabolic disturbances, pain, chronic or severe constipation
• Alcohol or drug misuse – may also cause delirium
• Metabolic causes, e.g. vitamin B1 or B12 deficiency, folate deficiency, hyperglycaemic hyperosmolar ketosis, hyperthyroidism, hypothyroidism, hyponatremia, hypercalcaemia, hepatic encephalopathy, uraemia
• Structural brain disease, e.g. subdural haematoma, mass lesion, normal pressure hydrocephalus
• Neurological infections, e.g. HIV or syphilis
• Hearing or vision impairments
• Sleep apnoea –has been associated with white matter abnormalities and impaired cognition, mood and daytime alertness 5,6

Also see: “ Differentiating dementia, depression or delirium as the cause of cognitive impairment in older people ”

Investigations to rule out other potential causes of cognitive decline include:

• Five-minute neurological examination (see: www.goodfellowunit.org/sites/default/files/dementia/Five_minute_neurological_examination.pdf )
• Depression screening (see: “ Differentiating dementia, depression or delirium as the cause of cognitive impairment in older people ”)
• Full blood count
• Biochemistry tests – electrolytes, creatinine, corrected calcium, glucose, HbA 1c , renal and liver function
• Thyroid function tests
• Serum vitamin B12 and folate
• C-reactive protein (CRP)
• HIV and syphilis testing
• Mid-stream urinalysis – if a UTI is suspected

* Availability of test may vary; recommend to discuss with the testing laboratory/clinical biochemist before requesting

If a treatable cause is identified, manage this as appropriate and then reassess the patient’s cognitive function. It is possible that a treatable cause may have exacerbated the symptoms of previously unidentified dementia.

Consider arranging a head CT

Brain imaging with computed tomography (CT) is recommended when assessing people for dementia to exclude structural cerebral pathologies or potentially reversible conditions, and to assist with subtyping, management planning and as a clinical baseline if a dementia diagnosis is made. 8 If subtyping will not change the management plan or the prognosis, e.g. a person of advanced age with established severe dementia, then a head CT may not be necessary. 8

N.B. Referral processes, eligibility criteria and access to head CT varies across DHBs; refer to your local HealthPathways or seek advice from a geriatrician or neurologist.

Differentiating dementia, depression or delirium as the cause of cognitive impairment in older people

Delirium and depression share common symptoms with dementia (the “3Ds”) and often co-exist in older people. When an older person presents with cognitive impairment, depression and delirium must be ruled out as potential causes before a diagnosis of dementia is made. Table 1 shows some differential features. A key distinguishing feature is that delirium has a sudden onset, whereas dementia onset is insidious. If the clinical history suggests depression, consider using a depression screening tool validated for use in older people, e.g. Geriatric Depression Scale.

For information on identifying and managing depression in older people, see: www.bpac.org.nz/BPJ/2011/July/contents.aspx

The geriatric depression scale is automatically selected when using the bestpractice decision support Depression module in an older patient. The GDS is also available from: www.bpac.org.nz/BPJ/2011/July/appendices.aspx

Table 1. Differentiating features of dementia, depression and delirium. 9

The history, observation and examination will generally guide the clinician as to whether a formal cognitive assessment is indicated. Cognitive assessments can be used to help confirm and quantify cognitive impairments, and to monitor changes in the patient’s cognitive function over time.

Consider a brief test first, followed by a comprehensive cognitive assessment

If cognitive impairment is suspected but you are unsure, a brief cognitive test can be used initially as a screening tool, e.g. the General Practitioner Assessment of Cognition (GPCOG see: " Cognitive testing with the GPCOG "). The GPCOG takes less than five minutes to administer and is validated for use in primary care. If the results suggest impairment or it is already apparent that some impairment is present, a more comprehensive evaluation should be undertaken. The recommended test for use as part of this assessment is the Mini-Addenbrooke’s Cognitive Examination (Mini-ACE or M-ACE - see “ Comprehensive cognitive assessment ”). This test also takes about five minutes to administer and is validated for use. Mini-ACE will be the recommended test on the cognitive impairment pathway on local Community HealthPathways platforms once they are updated on 1 September, 2020.

If cognitive impairment is suspected, a brief cognitive test may be used initially, e.g. the general practitioner assessment of cognition (GPCOG) takes less than five minutes to administer and is validated for use in primary care (see: Cognitive testing with the GPCOG ). If the results suggest impairment, a more comprehensive evaluation should be undertaken, e.g. Montreal cognitive assessment ( MoCA - see “ Comprehensive cognitive assessment ”). If English is not the person’s first language and the MoCA has not been translated into this language, or the patient has a low literacy level, use the Rowland Universal Dementia Scale (RUDAS). N.B. The Mini-Mental State Examination (MMSE) has also been widely used for comprehensive cognitive assessment, however, this test is copyrighted, and users must pay for access. The MoCA is currently the preferred cognitive assessment tool listed by HealthPathways (see note below).

Consider the potential limitations of cognitive testing

There are limitations to cognitive testing, particularly in relation to potential biases that may arise due to the person’s educational level, language or cultural identity. A culturally appropriate cognitive assessment tool for Māori that incorporates knowledge from te ao Māori (Māori worldview) is under development. Another limitation of cognitive testing is that it is possible for a person to score quite well and still have significant cognitive impairment; conversely, a person who functions well can score poorly on a cognitive test, e.g. if they are anxious or have mild dysphasia. Therefore, cognitive assessment tools should not be used in isolation to diagnose dementia.

Cognitive testing with the GPCOG

The GPCOG has two components: a six-item cognitive assessment conducted with the patient (takes less than five minutes to administer) and an informant questionnaire (not always required).

View/download GPCOG patient examination 10

The original version of the GPCOG is available from: www.patient.info/doctor/general-practitioner-assessment-of-cognition-gpcog-score . For a PDF version, see: www.comprehensivecare.co.nz/wp-content/uploads/2013/01/GPCog-.pdf

Comprehensive cognitive assessment

Mini-Addenbrooke’s Cognitive Examination (Mini-ACE or M-ACE) will now be the recommended test for assessing cognitive function in New Zealand. Until recently, the Montreal Cognitive Assessment (MoCA) was the most frequently used cognitive screening tool in primary care in New Zealand and the preferred cognitive assessment tool listed by HealthPathways. However, from 1 September, 2020, the MoCA test will no longer be freely available and in New Zealand the recommended test will now be the Mini-ACE. The MoCA test can continue to be used if clinicians have paid for training and certification through the MoCA Institute.

For further information on the Mini-ACE, see: www.nzdementia.org/mini-ace . This website includes information on:

• How to download the New Zealand Mini-ACE test, and an administration and scoring guide
• Complete online training
• The full report from the Cognitive Impairment Assessment Review (CIAR) Working Group on how the recommendation was made
• Some alternative language versions (although these are not yet adapted for New Zealand)

N.B. A new Māori Assessment of Neuropsychological Abilities (MANA) tool is being developed and the aim is for this to be integrated into HealthPathways alongside the Mini-ACE in 2022. Currently there is not a te reo Māori version of Mini-ACE.

Rowland Universal Dementia Assessment Scale (RUDAS) . The RUDAS is designed to minimise the effects of cultural learning and language diversity of cognitive performance. The test takes approximately 20 minutes and a score of ≤ 22 out of 30 is indicative of cognitive impairment.

For further information on the RUDAS and to access the test, see: www.dementia.org.au/resources/rowland-universal-dementia-assessment-scale-rudas

Montreal cognitive assessment (MoCA). The MoCA takes approximately 30 minutes to complete. Given the time requirements, the patient would usually be referred to a practice nurse for this test. Scores of ≥ 26 out of 30 are indicative of normal cognitive function, scores of 21–25 indicate mild cognitive impairment and scores ≤ 20 indicate dementia.

For further information on the MoCA and access to the test, see: www.mocatest.org and www.nzgp-webdirectory.co.nz/site/nzgp-webdirectory2/files/pdfs/MoCA-Test-English_7_1.pdf

Important note about MoCA: The MoCA has been replaced by the Mini-Addenbrooke’s Cognitive Examination (Mini-ACE) as New Zealand’s recommended cognitive screening test. The Mini-ACE test will be available on HealthPathways from 1 September, 2020. Online training will be available from 1 August, 2020. Clinicians wishing to continue using the MoCA after 1 September, 2020, will be required to complete a training and certification program every two years at their own cost. For further information, see: https://www.nzdementia.org/Mini-ACE

Rowland Universal Dementia Assessment Scale (RUDAS). The RUDAS is designed to minimise the effects of cultural learning and language diversity of cognitive performance. The test takes approximately 20 minutes and a score of ≤ 22 out of 30 is indicative of cognitive impairment.

Dementia is a syndrome with a variety of causes. The symptoms of dementia and the rate of progression vary with subtype ( Table 2 ). Alzheimer’s disease is thought to be the most common subtype of dementia in New Zealand, followed by vascular dementia, but mixed pathology is also common. 11 Most patients with dementia can be diagnosed and managed in primary care.

When to refer to secondary care for diagnosis or management advice

Referral to secondary care is appropriate if there is diagnostic or management uncertainty, e.g. due to complexity (see below for examples), or to access management supports that are not available in primary care.

Complexities in people with suspected dementia where referral to secondary care is appropriate include: 7

• Severe behavioural or psychological symptoms, including psychotic symptoms
• Rapidly deteriorating cognitive function
• Younger age, e.g. aged < 65 years
• Atypical presentation
• History of a significant head injury
• Chronic neurological disorder, e.g. Parkinson’s disease, Huntington’s disease, Motor Neurone disease or multiple sclerosis
• Intellectual disability
• Specific deficits, e.g. speech only

Table 2. Common types of dementia and the distinguishing symptoms and signs 12,13

When delivering a dementia diagnosis to the patient and their family/whānau, the discussion should cover: 2, 7

• That the cognitive problems they have been experiencing are more than just normal ageing. It is important to use the terms dementia or mate wareware, rather than euphemistic descriptions, because this enables the patient and their family access to information, support and services.
• How the diagnosis was made, i.e. by explaining the information obtained from the history, assessment tool(s) and investigations
• General discussion about the course and prognosis of dementia
• Non-pharmacological and pharmacological treatment options for symptomatic management
• Referral for a Needs Assessment, if indicated
• How to access information and support from their local dementia organisation; either Alzheimers New Zealand or Dementia New Zealand, depending on location
• Medico-legal issues to consider, e.g. driving, appointing an Enduring Power of Attorney, developing or updating an advance care plan, preparing a will. N.B. These discussions are likely to be ongoing and may not be considered in detail, if at all, at the first follow up appointment.

Allow additional time for this type of consultation. The pace should be guided by the patient and their support people, it is often not possible or advisable to cover everything in one consultation. Provide written information that the patient and their family can take home with them. Alzheimers New Zealand has “About dementia”, “Living well with dementia” and “Supporting a person with dementia” booklets, available from: www.alzheimers.org.nz/information-and-support/information/booklets-and-fact-sheets . Information can also be accessed from Dementia New Zealand: www.dementia.nz

Acknowledge the impact of a dementia diagnosis

A diagnosis of dementia can have a significant impact on a person’s self-esteem, relationships, employment and future plans. When learning about the diagnosis, the patient and their family/whānau may experience a range of feelings including shock, disbelief, anger, fear, hopelessness, despair and grief. 14 Some may also feel relief at having an explanation for the changes that have been occurring. Empathy, understanding and sensitivity toward the person and their family/whānau are imperative when discussing the diagnosis and prognosis for a person with dementia. Although the realities of dementia must be discussed, this needs to be balanced by encouraging the person and their family/whānau to focus on what they can do and to keep actively engaged in life.

Diagnosing dementia early allows people to make decisions about their future care and to access support. It also allows for early engagement with interventions that may help to preserve their quality of life for as long as possible. For carers, early diagnosis allows more time for them to adjust to the patient’s changes in function, mood and personality, and to transition into their caregiving role. 14 Ensuring that carers have access to support and maintain their own health and wellbeing is a core component of dementia care.

Carers for a person with dementia can access support through the Supporting Families organisation, see: www.supportingfamilies.org.nz

Perspectives from patients who are living with dementia and their carers are available from: www.alzheimers.org.nz/getattachment/Our-voice/New-Zealand-data/Lived-experience-of-dementia-research/Report-This-is-our-story-(2).pdf

Part 2: Managing early-stage dementia

Management should focus on slowing symptom development and maintaining quality of life.

There are currently no interventions that can cure or prevent the progression of the more common causes of dementia, such as Alzheimer’s disease or vascular dementia. Therefore, the aim of dementia management is to slow the rate of symptom development and help the person maintain their best quality of life (also see: “ Providing dementia care for Māori ”). Key areas of focus for primary care should include: 2

• Management of co-morbidities and reducing cardiovascular disease (CVD) risk, e.g. stopping smoking, limiting alcohol intake, managing hypertension, diabetes and obesity, optimising diet (e.g. recommend the Mediterranean diet or Dietary Approaches to Stop Hypertension [DASH] diet (see link below). Reducing CVD risk is particularly important in people with vascular dementia.
• Ensuring annual vision and hearing checks, and timely management of sensory impairment; enlist the help of a partner or family/whānau member if they cannot arrange an appointment themselves
• Assessing nutrition and hydration (e.g. using the Mini Nutritional Assessment www.mna-elderly.com ). People with dementia are at risk for undernutrition (either generalised protein-energy malnutrition or specific micronutrient deficiency, especially B12 and folate) due to problems with meal planning, shopping, preparing food and eating regularly.
• Medicine reconciliation, i.e. reviewing medicines regimens and adjusting or stopping treatment as appropriate
• Risk assessment, e.g. safety while cooking, using electrical appliances, heavy machinery or firearms, driving, falls
• Reviewing how the patient is managing at home. Recommend strategies to help the patient manage memory loss (see link below). Refer for a Needs Assessment if there is significant carer stress or the patient needs support to remain living independently.
• Monitoring mental health, stress and coping – both the patient and their caregiver

Ideally, people with dementia, accompanied by their family/whānau or carer, should be reviewed every three to six months to monitor the management plan and address any concerns.

For further information on lifestyle strategies to slow cognitive decline, see: www.bpac.org.nz/2020/cognitive.aspx

For practical tips on how to manage memory loss symptoms, see: www.alzheimers.org.nz/information-and-support/support/living-well-with-dementia/managing-your-symptoms

Providing dementia care for Māori

Caring for Māori patients with mate wareware (dementia) and their whānau requires knowledge, respect and engagement with their beliefs, values and practices. The concepts of wairua (spirituality) and whānau (family) in particular are central to Māori understanding and experience of mate wareware. 1

Further discussion about Māori understanding of mate wareware is available from: https://www.researchgate.net/publication/336263561_Mate_wareware_Understanding_'dementia'_from_a_Maori_perspective

The Goodfellow Unit has developed a free online course for primary healthcare professionals on providing dementia care for Māori. Key points from the course have been summarised below; the full course is available from: www.goodfellowunit.org/courses/dementia-care-māori

Key considerations when caring for Māori patients with dementia and their whānau include:

• Māori may try to hide or diminish symptoms of cognitive impairment, e.g. memory problems, to maintain their mana (prestige, respect, authority). Whānau are often more willing to share information and should be included in the consultations as appropriate.
• The symptoms of cognitive impairment may be described in nuanced ways, e.g. whānau may express that their loved one can still recite the entire whakapapa (genealogy) of their whānau, but struggle to recall other things that should be remembered, e.g. what they did earlier that day. It is important to understand the significance of whakapapa, that it represents deep, long-term knowledge that persists the longest.
• Establish clear and authentic lines of communication when working with whānau
• Ensure sufficient time and space to build relationships and gather information from the patient and the whānau. Make sure the patient knows they can bring as many whānau members with them as they wish and take time at the beginning of a consultation to connect with the patient and their whānau.
• Consider the roles that the patient has within their whānau and what effect it will have on the whānau when they can no longer perform those roles
• Engage with patients around their beliefs in relation to traditional Māori healing practices, and to understand how those beliefs may be interacting with proposed plans of care
• Some Māori living with dementia may be able to engage more in te reo Maori if this is their first language. Introducing te reo Māori into the consultation could improve engagement with patients.
• Whānau play a role in maintaining the wairua (spirituality) of their loved one through waiata and karakia once a person with dementia loses the ability to consciously maintain their wairua themselves. Some whānau may not be connected to tikanga Māori, but whānau can also utilise other means to create a collective spirit around their loved one, which strengthens and maintains wairua.

For further information on Māori health and wellbeing: www.goodfellowunit.org/health-and-wellbeing-māori

Physical activity

People with dementia should be encouraged to engage in physical exercise both for their general health and wellbeing and as a way of slowing cognitive decline; this should ideally include a mix of aerobic and muscle strengthening exercises. Aerobic exercise, e.g. brisk walking, running, cycling, dancing, aerobics, swimming or aqua jogging, has been shown to be most beneficial in terms of cognitive functioning. 15, 16 A meta-analysis of 18 Randomised Control Trials (RCTs) including 802 people with dementia found that exercise interventions that included aerobic exercise (walking, running, cycling or dancing) improved cognition, independently of intervention frequency (i.e. <150 or >150 minutes per week). 16 Although the same cognitive benefits were not found with non-aerobic exercise interventions (Tai Chi, strength, balance or flexibility training), these exercises should still be recommended for falls prevention. 16

Psychosocial stimulation

Cognitive Stimulation Therapy (CST) is a group or individual talking-based intervention recommended for people with mild to moderate dementia. 3 CST uses reminiscence (discussing past activities and events), stimulation and reality orientation (understanding the present using visual prompts) tasks, and focuses on opinions and discussions to stimulate language, thoughts and associations. 17 A meta-analysis of 14 RCTs including 657 people with dementia found that CST significantly improved cognitive function, communication and social interaction, self-reported quality of life and wellbeing. 18 A 2015 pilot of group CST in people with dementia in Auckland found that CST (14 sessions) reduced symptoms of depression, improved quality of life (reported by families and caregivers but not the patients themselves) and showed a trend towards an improvement in memory. 19

Availability of CST around New Zealand is variable; check with the local Alzheimers New Zealand or Dementia New Zealand branch to see if a programme is available in your area.

Remaining mentally and socially active is important. All people with dementia should be encouraged to engage in cognitively and socially stimulating activities that are tailored to suit their interests and abilities, e.g. reading, quizzes, crosswords, sudoku, playing cards or board games, learning something new, playing music, dancing or cultural activities. For Māori, cultural activities and utilising te reo Māori are considered protective factors that optimise a person’s functioning within their whānau and community. 1 Encourage Māori patients to continue with their roles within the whānau and on the marae, where possible. 1

Information for patients about staying active and engaged following a dementia diagnosis is available from: www.alzheimers.org.nz/information-and-support/support/living-well-with-dementia/staying-involved-and-active

Acetylcholinesterase inhibitors

An acetylcholinesterase inhibitor such as donepezil (oral, funded), rivastigmine (transdermal patches funded with Special Authority approval – see: “ Rivastigmine patch brand change ”, oral not funded) or galantamine (oral, not funded) may be considered in people with Alzheimer’s-type dementia, vascular dementia where subcortical ischaemic changes are prominent and dementia associated with Parkinson’s disease/Dementia with Lewy Bodies (unapproved indication). Acetylcholinesterase inhibitors should not be prescribed to people with mild cognitive impairment. 2

The treatment effects of acetylcholinesterase inhibitors are generally modest; not all patients will respond to treatment and it is not possible to predict response. There is no evidence that acetylcholinesterase inhibitors prevent the progression of dementia, however, some people may have a temporary improvement in cognition and functionality. A meta-analysis of 43 RCTs including over 16,000 people with Alzheimer’s disease reported that acetylcholinesterase inhibitor treatment resulted in small to moderate improvements in cognitive function, global symptoms and functional capacity. 20 Data on neuropsychiatric symptoms are mixed, but suggests that there may be benefits for some symptoms (such as apathy and psychosis) but not others (such as anxiety and aggression). 20

Cautions to acetylcholinesterase inhibitor use include sick sinus syndrome or other supraventricular conduction abnormalities, e.g. atrioventricular or sinoatrial block, due to an increased risk of bradycardia. Perform an ECG in all patients prior to initiating treatment to check for pre-existing conduction abnormalities. 21, 22

Acetylcholinesterase inhibitors can cause dose-related cholinergic effects, e.g. nausea, bradycardia, vomiting, diarrhoea, dyspepsia, urinary incontinence, dizziness. 21 Treatment should be initiated at a low dose and titrated upwards, if tolerated. Patients who have intolerable nausea or vomiting with donepezil tablets can be prescribed transdermal rivastigmine patches.

N.B. The acetylcholinesterase inhibitors available have similar effectiveness; most people will be initiated on donepezil as it is fully funded. If donepezil is not effective, rivastigmine or galantamine may be trialled, taking into consideration the affordability of non-funded treatments. Only one acetylcholinesterase inhibitor should be used at a time.

Treatment effectiveness, adverse effects, adherence and symptom progression should be assessed one month after initiating a acetylcholinesterase inhibitor, and again at three months and six months, if treatment has been tolerated. 23 Family and caregivers are well-placed to observe treatment response and adverse effects, however, it is recommended that an objective measure, e.g. Mini-ACE , is also used to monitor treatment effectiveness. 23 There is limited guidance on the recommended duration of acetylcholinesterase inhibitor treatment. If the patient experiences significant adverse effects, has poor adherence to treatment or monitoring requirements, is no longer showing benefit from treatment or has not benefitted from treatment, the medicine should be discontinued. 23 It is recommended that the dose is stepped down over two to three weeks rather than stopping abruptly, and if there is significant decline, re-start the medicine promptly. 23

Refer to the NZF for further information on cautions, dosage, switching from oral to transdermal formulations and monitoring of acetylcholinesterase inhibitor treatment: www.nzf.org.nz/nzf_2879

Rivastigmine patch brand change

The funded brand of rivastigmine patches is changing from Exelon to Generic Partners. From 1 February, 2020, the Generic Partners patches will be available fully funded alongside the Exelon patches. From 1 April, 2020, the subsidy on the Exelon patches will reduce and they will no longer be funded from 1 July, 2020.

Key points to discuss with patients about the brand change:

• Generic Partners patches have the same active ingredient (rivastigmine) as other brands
• The new brand is just as safe and works in the same way as the old brand
• The Generic Partners patches are clear, whereas the Exelon patches are beige. This will not change how the medicine works.

For further information see: https://pharmac.govt.nz/medicine-funding-and-supply/medicine-notices/rivastigmine/?skipLink=DH

Memantine (not funded) may be considered for people with moderate Alzheimer’s disease who are intolerant of or have a contraindication to an acetylcholinesterase inhibitor, or who have severe Alzheimer’s disease. 2, 3 Memantine may also be used in combination with an acetylcholinesterase inhibitor by people with moderate to severe Alzheimer’s disease. 2, 3 As with acetylcholinesterase inhibitors, the effects of memantine are variable; some may experience benefit, e.g. improved function or slowed rate of decline, while others will not. Memantine is contraindicated in people with a history of seizures and should be avoided in people with severe hepatic or renal impairment. 21 Common adverse effects include constipation, hypertension, dyspnoea, headache, dizziness and drowsiness. 21

Refer to the NZF for further information on cautions and dosage: www.nzf.org.nz/nzf_2879

Future articles will cover the management of behavioural and psychological symptoms as dementia progresses and the role of primary care in supporting patients and their families during the palliative phase of dementia care.

Dementia resources for primary care health professionals are available here:

• A free online course on dementia diagnosis and management from the Goodfellow Unit: www.goodfellowunit.org/courses/dementia
• A series of presentations on managing the different stages of dementia from PHARMAC: www.pharmac.govt.nz/seminars/seminar-resources/dementia-update/
• A Goodfellow Unit podcast with Professor Ngaire Kerse on living well with dementia: www.goodfellowunit.org/podcast/living-well-dementia

National report

There is a national report associated with this article.

The purpose of this report is to provoke thought and discussion about how and why antipsychotic medicines are prescribed to older patients. The report includes national data, and practice points for reflection. View national report

CME activites

There are CME activites associated with this article.

• Clinical Audit: Reviewing the use of antipsychotic medicines in older people
• Quiz: Do quiz
• Peer group discussion: Cognitive impairment and dementia in older people

Acknowledgement

Thank you to Dr Matthew Croucher , Psychiatrist of Old Age, Canterbury DHB and Senior Clinical lecturer, University of Otago, Christchurch for expert review of this article.

Article supported by PHARMAC

N.B. Expert reviewers do not write the articles and are not responsible for the final content. bpac nz retains editorial oversight of all content.

• Dudley M, Menzies O, Elder H, et al. Mate wareware. Understanding ‘dementia’ from a Māori perspective. NZMJ 2019;132:66-74. Available from: https://www.researchgate.net/publication/336263561_Mate_wareware_Understanding_'dementia'_from_a_Maori_perspective
• Guideline Adaptation Committee. Clinical practice guidelines and principles of care for people with dementia. 2016. Available from: https://cdpc.sydney.edu.au/wp-content/uploads/2019/06/Dementia-Guideline-Recommendations-WEB-version.pdf (Accessed Jan, 2020).
• National Institute for Health and Care Excellence. Dementia: assessment, management and support for people living with dementia and their carers. 2018. Available from: https://www.nice.org.uk/guidance/ng97/chapter/Recommendations (Accessed Feb, 2020)
• bpacnz. Having a senior moment? 2009. Available from: https://bpac.org.nz/BPJ/2009/September/senior.aspx (Accessed Jan, 2020).
• Little MO. Reversible Dementias. Clinics in Geriatric Medicine 2018;34:537–62. http://dx.doi.org/10.1016/j.cger.2018.07.001
• Castronovo V, Scifo P, Castellano A, et al. White matter integrity in obstructive sleep Apnea before and after treatment. Sleep 2014;37:1465–75. http://dx.doi.org/10.5665/sleep.3994
• Ministry of Health. New Zealand framework for dementia care. 2013. Available from: https://www.health.govt.nz/system/files/documents/publications/new-zealand-framework-for-dementia-care-nov13.pdf (Accessed Jan, 2020).
• Croucher MJ. Should a CT Head be a standard part of the diagnostic process for dementia in New Zealand? N Z Med J 2016;129:15–22.
• Goodfellow Unit. Differentiating delirium, dementia and depression. 2016. Available from: " no longer available online "
• Brodaty H, Pond D, Kemp NM, et al. The GPCOG: a new screening test for dementia designed for general practice. J Am Geriatr Soc 2002;50:530–4. http://dx.doi.org/10.1046/j.1532-5415.2002.50122.x
• Neurological foundation. Alzheimer’s disease and dementia. 2019. Available from: https://neurological.org.nz/what-we-do/awareness-and-education/brain-disorders-and-support/alzheimers-disease-and-dementia/ (Accessed Jan, 2020).
• Alzheimer’s Society UK. The progression of Alzheimer’s disease and other dementias. 2019. Available from: https://www.alzheimers.org.uk/about-dementia/symptoms-and-diagnosis/how-dementia-progresses/progression-alzheimers-disease-dementia#content-start (Accessed Jan, 2020).
• Robinson L, Tang E, Taylor J-P. Dementia: timely diagnosis and early intervention. BMJ 2015;350:h3029–h3029. http://dx.doi.org/10.1136/bmj.h3029
• Rasmussen J, Langerman H. Alzheimer’s disease - why we need early diagnosis. Degener Neurol Neuromuscul Dis 2019;9:123–30. http://dx.doi.org/10.2147/DNND.S228939
• Panza GA, Taylor BA, MacDonald HV, et al. Can exercise improve cognitive symptoms of Alzheimer’s disease? J Am Geriatr Soc 2018;66:487–95. http://dx.doi.org/10.1111/jgs.15241
• Groot C, Hooghiemstra AM, Raijmakers PGHM, et al. The effect of physical activity on cognitive function in patients with dementia: A meta-analysis of randomized control trials. Ageing Research Reviews 2016;25:13–23. http://dx.doi.org/10.1016/j.arr.2015.11.005
• Turner T. Dementia care: an overview of available non-pharmacological therapies. The Pharmaceutical Journal 2016; [Epub ahead of print]. http://dx.doi.org/10.1211/PJ.2016.20201270
• Aguirre E, Woods RT, Spector A, et al. Cognitive stimulation for dementia: A systematic review of the evidence of effectiveness from randomised controlled trials. Ageing Research Reviews 2013;12:253–62. http://dx.doi.org/10.1016/j.arr.2012.07.001
• Cheung G, Peri K. Cognitive stimulation therapy: A New Zealand pilot. 2014. Available from: https://www.tepou.co.nz/uploads/files/resource-assets/cognitive-stimulation-therapy-a-new-zealand-pilot.pdf (Accessed Jan, 2020).
• Blanco-Silvente L, Castells X, Saez M, et al. Discontinuation, efficacy, and safety of cholinesterase inhibitors for Alzheimer’s disease: A meta-analysis and meta-regression of 43 randomized clinical trials enrolling 16 106 patients. International Journal of Neuropsychopharmacology 2017;20:519–28. http://dx.doi.org/10.1093/ijnp/pyx012
• New Zealand Formulary (NZF). NZF v92. Available from: http://www.nzf.org.nz (Accessed Mar, 2020).
• Cartmell N. Guidance on initiating the prescribing of donepezil in primary care. 2013. Available from: https://docplayer.net/24649228-Guidance-on-initiating-the-prescribing-of-donepezil-in-primary-care.html (Accessed Jan, 2020).
• Waitemata District Health Board. Saferx: Donepizil – Safe prescribing. 2015. Available from: http://www.saferx.co.nz/assets/Documents/full/c6a5f8cf85/donepezil.pdf (Accessed Jan, 2020).

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Lived Experience of Dementia in the New Zealand Indian Community: A Qualitative Study with Family Care Givers and People Living with Dementia

Rita v. krishnamurthi.

1 National Institute for Stroke and Applied Neurosciences, Auckland University of Technology, Auckland 0627, New Zealand; [email protected]

Ekta Singh Dahiya

Reshmi bala.

2 Department of Psychological Medicine, University of Auckland, Auckland 1142, New Zealand; zn.ca.inudnalkcua@618iars (R.B.); [email protected] (G.C.); [email protected] (S.Y.); [email protected] (S.C.)

Gary Cheung

Susan yates, sarah cullum, associated data.

Not applicable.

Currently, there are estimated to be 70,000 people living with dementia in Aotearoa, New Zealand (NZ). This figure is projected to more than double by 2040, but due to the more rapid growth of older age groups in non-European populations, prevalence will at least triple amongst the NZ Indian population. The impact of dementia in the NZ Indian community is currently unknown. The aim of this study was to explore the lived experiences of NZ Indians living with dementia and their caregivers. Ten caregivers (age range: 41–81) and five people living with mild dementia (age range: 65–77) were recruited from a hospital memory service and two not-for-profit community organisations in Auckland, Aotearoa, NZ. Semi-structured interviews were conducted by bilingual/bicultural researchers and transcribed for thematic analysis in the original languages. Dementia was predominantly thought of as being part of normal ageing. Getting a timely diagnosis was reported as difficult, with long waiting times. Cultural practices and religion played a large part in how both the diagnosis and ongoing care were managed. Caregivers expressed concerns about societal stigma and about managing their own health issues, but the majority also expressed a sense of duty in caring for their loved ones. Services were generally well-received, but gaps were identified in the provision of culturally appropriate services. Future health services should prioritise a timely diagnosis, and dementia care services should consider specific cultural needs to maximise uptake and benefit for Indian families living with dementia.

1. Introduction

Dementia is a rapidly growing health issue worldwide, with over 50 million people living with the condition [ 1 ]. Dementia has a significant health, psychological, and economic impact on the affected individuals and their family caregivers. People living with dementia are likely to become partially or fully dependent on others for support and care, while caregivers often suffer from caregiving burden resulting in health issues and economic losses themselves [ 2 ].

In Aotearoa, New Zealand (NZ), people of Indian origin comprise 4.7 percent of the total population, with about 2.5 percent born in India and 1 percent people of Indian ethnicity originating from the Fiji Islands [ 3 ]. The majority of Indians (approx. 75%) were born overseas. Indians in NZ are proportionally much more likely to be younger and have more post-high school qualifications than the national average. Approximately 60% are employed full-time; however, their mean income is lower than the national average. In terms of origin, the majority of Indians in NZ hail from India, while a smaller but substantial proportion are from Fiji (described as Fijian Indian). Fijian-Indians are an ethnic group from the Pacific Islands of Fiji. (Ref Stats NZ https://www.stats.govt.nz/tools/2018-census-ethnic-group-summaries/fijian-indian , accessed on 21 November 2021).

This study was conducted in Auckland, the largest city in Aotearoa, NZ, with the highest proportion of Indians in NZ at 10% of the population [ 4 ]. These numbers are expected to quadruple in the next 20 years due to longer life expectancy and migration. Currently, there are estimated to be 70,000 people living with dementia in Aotearoa, NZ. The prevalence of dementia in the whole NZ population is projected to more than double by 2040, but the greatest increase is expected in the Asian population due to more rapid demographic ageing [ 5 ].

No data have been published about the extent and impact of dementia in the Aotearoa, NZ Indian community. Anecdotal evidence (in Auckland) suggests increasing numbers of referrals of people from Indian and Fijian-Indian backgrounds to local memory services, but there is a lack of understanding of their specific experiences and needs. For these reasons, it is important to gain a better insight into this population’s understanding of dementia and their lived experiences, which could inform the design and implementation of culturally appropriate dementia care and support services as well as prevention strategies.

The aim of our study was to explore how dementia is perceived, experienced, and managed from the perspective of Indian people in Aotearoa, NZ with dementia and their family caregivers.

2. Materials and Methods

2.1. participants and settings.

Participants were recruited through three existing services. These included (1) the memory service at Middlemore Hospital (Counties Manukau Health), a large public hospital in South Auckland, (2) a not-for-profit community dementia care organisation (Dementia Auckland) that offers services and support to those at various stages of the journey with dementia, and (3) another non-profit organisation (Shanti Niwas Charitable Trust) which provides support services and community programmes to senior citizens of Indian origin in the Auckland region.

Potential participants from the memory service were initially contacted by a member of the clinical team who asked for consent to pass on contact details to the research team. Those who agreed to be contacted were approached by a member of the research team who gave further details before asking for consent. Participants from the not-for-profit organisations were informed about the study by their community coordinator, and those who agreed to be contacted were approached by a member of the research team. We aimed to be as inclusive as possible but excluded people who were residing in care homes or who could not be interviewed in English, Hindi, or Fijian Hindi. People with more severe dementia were not included in the study; however, their caregivers (regarded as the person most involved in the person living with dementia’s day-to-day life) were interviewed. A voucher worth NZ$50 was provided to the participant at the end of the interview to acknowledge their input in the study.

2.2. Semi-Structured Interviews

The interviews were conducted by a team of five lay interviewers (both male and female) who were bilingual and bicultural (Indian or Fijian Indian) with a mix of health research and public sector professional backgrounds. Interviewers attended five training workshops organised by the research team prior to study commencement. Training workshops included an introduction to qualitative research, semi-structured interviews, thematic analysis, the process of obtaining informed consent, discussion on potential questions, tips on managing difficult interviews, and the process of transcribing interviews. The topic guide ( Appendix A ) guided interviewers’ explorations of the understanding of dementia, experience of the diagnostic process, adjustments made to lifestyle, available support services, and any concerns or recommendations. Caregivers were also asked about their caregiving experiences, any concerns or issues they were facing, and their satisfaction with the level of formal and informal support received.

Interviews were conducted by one or two interviewers at the participant’s house in their preferred language, including Hindi, Fiji Hindi (a dialect of Hindi spoken by people of Indian origin born in Fiji), and English. The researchers introduced themselves to the participants and provided a brief background about themselves prior to the interview, including the reasons for their own interest in the area. Demographic information from the participant and their caregiver was collected. Face-to-face interviews were conducted between July 2018 and January 2019. A peer-review workshop was held after the first two interviews to discuss interviewer experiences and concerns. Each interview was audio-recorded and transcribed verbatim by the interviewers. The transcripts were uploaded into a Computer Assisted Qualitative Data Analysis Software, NVivo (Version 12, QSR International, Melbourne, Australia), to organise the data for coding [ 6 ].

2.3. Data Analysis

Interview transcripts were analysed by two researchers (RK and ESD) who are fluent in Hindi, Fiji Hindi, and English using the principles of thematic analysis [ 7 ]. Both RK and ESD brought their understanding of Indian culture and clinical knowledge in analysing and interpreting the data. The six phases as described by Braun and Clarke formed the basis of analysis: familiarization with the data, generating codes with deductive orientation, constructing themes, revising and defining themes, and producing the reports [ 7 ]. The transcripts were coded by both researchers independently and reviewed for recurrent themes during research team meetings.

All participants were assigned a participant identification (ID) number to maintain confidentiality while analysing the data. The relevant quotes used for the analysis were translated to English for the purpose of writing reports and referred to only their ID. A summary table was drafted based on the topic guide, and relevant codes along with specific quotes were added to it. Themes and subthemes were generated from recurring codes and refined further.

2.4. Ethics

Ethics approval was gained from the National Health and Disability Ethics Committee (reference number 17/CEM/126/AM01).

Sixteen participants were initially approached for participation in the study. Of these, a total of fifteen participants with an age range of 41 to 81 years agreed to be interviewed. Five of the interviews were with dyads including people with mild to moderate dementia (who had capacity to consent to participate in the study) and their caregivers, and five interviews were conducted with caregivers only (of people with more severe dementia who were unable to participate in the study). This was sufficient to reach data saturation.

In all but one interview, only the interviewers and interviewees were present, but in one interview, other family members were present (daughter and grandchildren); however, they did not participate. The average interview duration was 35 minutes but varied from 17 to 47 minutes.

The demographic details of all participants are shown in Table 1 . Table 2 lists the ethnicity and relationship to the person with dementia for each recruited family caregiver.

Demographic details of the person living with dementia and caregivers.

Characteristics of the 10 caregiver participants and their relationship to the person living with dementia.

3.1. Thematic Analyses

The findings from this study are summarised in Figure 1 by linking the main topic themes and subthemes related to caregivers and people living with dementias. There was an overlap of some of the sub-themes, particularly between the caregiver experiences and those of people living with dementia.

Summary of identified themes and subthemes. ARC: aged residential care.

We have not included the participant IDs with quotations in the report as it would have been easy to re-identify participants from the sociodemographic tables due to the small population living in the community.

3.1.1. Theme 1: Understanding of Dementia

• Subtheme 1.1: Dementia is a normal part of ageing

Participants were asked about their understanding of dementia. Most participants were not able to define the term “dementia” because there is no equivalent common spoken Hindi word for it. However, when the term was further described by the interviewers as “the illness of forgetfulness or being confused,” most participants were able to recognise the condition that was being described. Most participants described dementia as a natural consequence of ageing, and as weakness of the mind and body.

…this is normal…because he is getting older, he forgets. (C)

• Subtheme 1.2. Dementia may be caused by external stressors or ‘karma’

Other people associated the onset of dementia to stressful life events such as the loss of a job, overall stress, loneliness (particularly associated with migrating to another country), and a lack of physical and mental activities.

I see one person…he lost his job, he got dementia. (C)

There is loneliness here, without our own people. (C)

Dementia was also described as being due to ‘karma,’ a common perception of the causes of one’s destiny in the Indian culture, particularly amongst Hindus. The concept of karma says that life’s destiny, or fate (‘rekha’), is determined by a person’s past and present deeds. However, the concept of karma brought with it a feeling of acceptance, as karma is not in a person’s direct control. Participants and their families appeared to accept dementia as part of their destiny. However, attributing cognitive impairment to karma might also impact whether people access services in a timely fashion and receive the support they need.

You are (un)lucky to get Alzheimer or unlucky to get dementia (laughs) (hmm hmm). That’s your, know your karma, it a rekha aur hmm depending in the lifestyle also you get dementia or not get dementia you know. (C)

3.1.2. Theme 2: Diagnostic Process

• Subtheme 2.1: Difficulty in getting a dementia diagnosis

Most people living with dementia and/or their caregiver did not think they got a clear message about their diagnosis, much less about their prognosis. Investigations such as neuroimaging and laboratory tests were not clearly explained. Medications were taken without any real understanding of what they were for. Many found the experience of getting a diagnosis challenging, either because their doctor did not appear to take their concern seriously or because they could not get a timely appointment with a specialist. Caregivers were often told that their family member had an “age related condition” which was frustrating and may explain why many of the participants thought dementia was a normal part of ageing (Theme 1).

She was very aggressive and… so I took her to the GP and then the GP said ummm… “she’s fine and old age, nothing to…” you know that, but I told to GP “no she’s definitely got some kind of an issue because you know, uhh, cos I know, my mum”. (C)

Others who originated from India found it difficult to access timely services in Aotearoa, NZ and ended up travelling to India for their health assessment. They reported extensive delays in getting appointments in the public health system and little or no follow-up after their initial appointment with a doctor.

I had my scan in India, that’s what the doctors here used to diagnose me…doctor said its good you got the scan done. (P)

• Subtheme 2.2: Lack of information on services

The general perception observed was that people with dementia and their caregivers were not provided with sufficient information to process the diagnosis of dementia. Also, there was little or no follow-up made to monitor their condition. For example:

GP referred to someone else, a girl came from Middlemore about 5–6 months before and asked about memory loss problem…like you people are asking about…and did not contact again…. (P)

3.1.3. Theme 3: Impact on Personal and Social Life (of Person Living with Dementia)

• Subtheme 3.1: Losing independence

Participants with dementia talked about how dementia impacted their independence and reduced their ability to participate in everyday activities such as cooking, gardening, and going out for walks. Both participants living with dementia and their caregivers described these activities as being potentially unsafe, for example, the risk of leaving the stove on, wearing the wrong shoes, or falling over while walking. These changes had developed gradually with time and were ongoing, adding to the stress experienced by both the person living with dementia and the caregiver.

Cooking… has got stopped altogether for her. We used to prepare meals together earlier. She used to cook alone but children stopped it. Doctor also advised not to go near stove. (C)

She prepared dinner today. She manages if I am at home…had to remind her every time to have dinner. (C)

Like I use to do a job…so this is my car (pointing out to his car)…I use to drive this…yes…so I use to go and take interviews from people…hmmm…on health issues…hmm…so I use to like that so much that I didn’t want to sit, …yes…when I got stroke, my driving also stopped. (P)

• Subtheme 3.2: Conflict and frustration between the person with dementia and caregiver

The increasing inability to perform such activities was a source of ongoing conflict between the person with dementia and the caregiver.

Like the routine house chores, she feels that she does that…hmm…but body…her body doesn’t allow it…hmm… She is not able to walk but from inside she thinks that she prepare meal, do the chores. (C)

Not stable, it is increasing. Because, earlier he use to help in house a lot, like putting bins outside and getting it in…he takes lots of time in wearing shoes, will wear it wrong. When we ask him to get shoes off… means he is getting too slow, thinks about it. This is why we don’t allow him to put bins now in a fear that he will fall. (C)

• Subtheme 3.3: Feelings of loneliness

Although most participants with dementia were living with their family, they reported that they felt lonely at times. Having a partner or family member around gave them reassurance in case they forgot something. One caregiver mentioned that her husband was not supportive when she wanted to learn to drive. The husband (person with dementia) said he was fearful of feeling lonely if she went out on her own and left him behind at home.

If she learn how to drive a car then it will get difficult for me…I will be alone…how will I spend my time? (P)

• Subtheme 3.4: Social stigma and negativity

Most of the participants did not feel part of the group at the community centres they attended and did not wish to talk much about their condition when they were there. Their caregivers related this to feeling negative or being self-consciousness about their health condition.

She has a little negativity…hmm…she thinks like the other person is thinking bad about her…hmm…it’s her thinking, and feeling…hmm. So she don’t like that kind… of people there. (C)

• Subtheme 3.5: Acceptance and coping strategies

Some participants expressed a sense of acceptance about the fact that their health condition was gradually changing, both physically and mentally. They talked about working out plans to live with it, including developing coping strategies such as reading religious books, giving themselves reminders by making notes, and being happy with their family.

I have memory problems…just sometimes I forget…a date, where I put something, that’s all, nothing major. (P)

I noticed…like…recently I…we read Ramayan*…read Hindi God books…hmm…yes…so it happens sometimes that I have read till here, and why have I started reading that again? …so I do not take stress of this. (P)

3.1.4. Theme 4: Experience of Support Services

• Subtheme 4.1: Satisfaction with home support services

When asked about their home support services, most caregivers were satisfied with the help they received. Services had been arranged depending on the stage of dementia. For example, a person with dementia whose activities of daily living and personal care were restricted received daily home help, assisting them with showering, eating, and dressing.

First we take the service for 4 days, she goes to <support service> on Friday, hmm… but then she don’t want to go, hmm… then we introduced for fifth day then Saturday and Sunday. So now seven days coming. She got a fall in bathroom, hmmm…it’s pretty hard… so that’s why we put seven days for the shower as well. (C)

Yes they come at home sometime to give showers…we have asked for three times only. (C)

For others, services were provided for activities such as help in driving around and shopping as and when needed. The help was recommended and arranged by the participant’s general practitioner. They particularly liked services being provided in their homes, being subsidised by the government, and being able to talk in their local language with the home help carer and service provider.

It’s enough. We are getting more than enough …okay…because we are getting help from <support service>…they give help for her. (C)

There comes three or four things, like you need physio help…need prescription since I am diabetic…so I need nurse…hmm… so they are always ready. Then they have references…like they referred me for my problem…of this…brain. (P)

However, not all participants were satisfied with the support received. One described approaching several different services but not receiving adequate support. This led to the family paying someone privately for house cleaning and other domestic help:

He needs proper support every time people come over here they listen to us but no support … so many times he had a fall so many times we have had the same issue. …we seriously need some support I have someone who comes at the house and does cleaning and everything…. (C)

• Subtheme 4.2: Community centres more suited for people with mild dementia

Community centres were generally seen as useful opportunities for the person with dementia to leave the house. One caregiver mentioned that going to a community centre for Indian senior citizens once a week helped her husband vary his routine. However, she was always worried about him as he was not able to eat properly and was getting physically slow in general. For some people, interacting with other people of the same age group was a source of motivation. Day programmes also allowed caregivers or family members to seek assistance if they needed temporary care for the person with dementia. However, the general view was that the community centres were only suitable for people in the early stages of dementia. Participants reported noticing that with declining health, the attitudes of the people around them began to change, which eventually diminished their interest in attending the centre. It was suggested that the activities in the centres should be more inclusive and suited to people at different levels of cognitive abilities.

Like today I went, there was a man aged 94 came…at <support service>…hmm… yes…so we feel very happy. Hmmm…he came on wheel chair…so we feel very happy, that this man also wants to live…yes…alright…someone who is 20 years older than me. (P)

People were cooperative, but as things are changing now, people are getting cut-off. (C)

• Subtheme 4.3: Aged Residential Care (ARC) does not meet cultural needs and expectations; culturally tailored ARC would make them feel at home

People with dementia and caregivers were asked about their experiences and thoughts about moving into ARC. Although the availability of ARC as an optional service was known, much of the feedback suggested there were several concerns. The concept of ARC, in general, does not fit well with the Indian culture and lifestyle. The two main issues identified were language-related communication barriers and the unavailability of Indian, particularly vegetarian, food. Out of all the caregivers interviewed, there was just one where the person living with dementia had recently been admitted to ARC on her General Practitioner’s (GP) recommendation. Others had either experienced these services during visits to a facility or had heard stories within their social circles. People living with dementia and their caregivers mentioned difficulty in communicating with the management due to not being provided with an interpreter at the facility. As the majority of the other nursing home residents spoke English, communication with other residents was difficult. Furthermore, speaking in different Indian-origin languages such as Hindi, Fiji Hindi, Punjabi, and Gujrati added another level of difficulty for older people.

Yes, the main problem is that if you are from Fiji then you need someone who speaks Fiji Hindi…Language is the main problem and communication. If you find anyone speaks in your language…so, this is my feeling. (C)

Two things are important. Food is important (yes) umm…my mother also and we also in fact everybody…whosoever goes there takes food with them or make food for them…umm and then …umm… talking is important. (C)

A caregiver whose mother had recently been placed in an ARC observed that the residents spent most of their time by themselves or watching television. He suggested that ARC facilities should have activities planned to make the residents more mobile and active. He also expressed that nursing homes should have tailored support and resources for older people with diverse cultural needs to make them feel more at home, such as being able to perform their religious prayers. Another person living with dementia suggested that there should be efforts made to enable mixing and mingling with other major ethnic community groups to extend their circle and learn more.

Besides I am thinking that there should be a community here where there should be activities like playing carrom (popular board game in India). He would get better in this way, he would talk or play or look around, there was nothing like this what I would wish to. Not like, you go there and sit, then someone would feed you on time, just keep watching tv. You can watch that while staying at home. (C)

3.1.5. Theme 5: Caregiver Experiences

The life of a caregiver tended to revolve around their relative, with much of their time spent with them. Out of the 10 families interviewed, caregivers of seven families had taken up the responsibility of caring for their relative. This involved a range of activities such as medication supervision, preparing meals, or reminding the person living with dementia to eat, and assisting and/or supervising during showers to ensure they did not fall or injure themselves in some way. Most had to take on these responsibilities by themselves with only a little help from external services or extended family members.

• Subtheme 5.1: Acceptance of duties and responsibilities

An aspect that came across clearly with caregivers was a sense of duty and responsibility to their relative and acceptance of their role as a caregiver. They acknowledged that their relative was suffering from an incurable condition, so they learnt to accept it, try not to react, and instead help them live through it. One caregiver mentioned her husband had a habit of constantly collecting things and placing them in a pile. She recognised this behaviour as part of the effect of dementia and therefore learned not to intervene or become upset by it:

He has collected so many things on its own. Hmm…So, I do not touch these…I will pick them; he will collect again. (C)

Most of the caregivers mentioned that they did not wish to admit their relative to ARC and would like to continue providing care for them at home as long as they can:

There are expectations and responsibility at the children’s end, that’s why she is at home. (C)

• Subtheme 5.2: Impact on caregiver’s personal and social life

Many caregivers expressed that the responsibility of caring for a family member living with dementia impacted their own personal and social life. Some caregivers had quit their jobs, and some were doing a lot of travelling to care for their loved ones, which resulted in strained personal relationships. A caregiver mentioned that their social circle has been restricted:

So we used to be party people but we slowly slowly restrict our social circle. (C)

Another caregiver said that their time was mostly spent at home looking after his wife; he mentioned sometimes getting restless staying inside the house and trying his best to go outside to feel better:

I get bored staying at home…going for a walk around, come back having a look around of the playground. (C)

• Subtheme 5.3: Worries about own health

Caregivers who were older females (spouses) expressed concern about the impact on their health and wellbeing. Older caregivers had their own health problems to deal with and were not receiving support for themselves:

Now that I have aged, I said I cannot work too much now. (C)

I also get tired beta (*child), I am 77, will be 78 in December. So, it’s not all possible for me doing as well. I have got severe arthritis. (C)

Have to remind again…that she is human as well, look at her…she is sick as well…hmm… I am also doing (work). (C)

Some caregivers mentioned a positive aspect of their role as they learned new ways to keep helping their relative and have family support when needed. For example, one caregiver had learnt to drive in order to take her husband for short walks and to shop. Another caregiver mentioned that taking care of her husband helped keep her active in her old age.

4. Discussion

Our study provided new insights into the understanding and experience of dementia from the perspective of the Indian community living in Aotearoa, NZ. The main themes were the understanding and conceptualisation of dementia; experience of diagnostic processes; impact on personal and social life (including loneliness, stigma, and community responses); experience of post-diagnostic support services; and the impact on the caregiver in terms of filial duty, stress, and their own well-being.

4.1. Understanding of Dementia

Our finding that dementia is commonly thought of as a part of normal ageing has also been described in other studies which included Indian populations living as ethnic minority groups in Western countries [ 8 , 9 ]. Similarly, medical illnesses and external forces as causes of dementia have also been described elsewhere among South Asian ethnic minorities [ 10 , 11 ]. A recent systematic review of understandings of dementia among indigenous people in low- and middle-income countries [ 12 ] highlighted that the early stage of dementia was rarely conceptualised as a biomedical condition but was instead seen as cognitive decline that is part of normal ageing, possibly associated with physical or psychological weakness which required traditional caregiving practices. However, if more challenging behavioural and psychological symptoms of dementia emerged then the community responses to dementia were influenced by the stigma associated with mental illness, which could sometimes result in feelings of shame in caregivers [ 13 , 14 ]. Knowledge about dementia might be expected to be better in high-income countries, but another recent systematic review reported that understanding was poor amongst ethnic minority groups, including Indians, in a number of countries, including the UK and USA [ 15 ]. This suggests that promoting health literacy around dementia in all countries is an important first step in improving dementia care.

Our study also identified several understandings of dementia that are possibly unique to the Indian culture. The notion of “karma” was spoken of as a way of accepting one’s fate due to their past deeds. This is a commonly held belief in the Indian culture, particularly those practicing the Hindu religion [ 16 ]. This belief appeared to allow some of the people in our study a greater sense of acceptance and peace with the type of life they were living.

4.2. Experience of the Diagnostic Process

Most participants experienced difficulties and delays in getting a clear diagnosis and/or understanding what the diagnosis meant. Reasons ranged from the reluctance of GPs to screen or refer patients to the long waiting times for scans or the high cost of private scans and tests. Caregivers often had to “push” for a diagnosis, as symptoms were dismissed as a normal part of ageing even by doctors. Delays in obtaining a diagnosis of dementia in ethnic minority groups have also been described elsewhere, with health professionals needing to be prompted and chased up by a family member or carer [ 9 ]. Excluding carers from medical appointments and communication meant further delays as people with dementia often forgot the details relayed.

Pathways to care are influenced by beliefs around illness and ageing, low awareness and knowledge of dementia, and stigma, preventing help-seeking for dementia care [ 9 ]. A recent qualitative study in Denmark found that ethnic minority populations (including Indian) did not access dementia care services due to poor awareness, stigma, and lack of culturally appropriate services [ 17 ]. However, clinical staff are also reported to require more education around dementia [ 18 ] as they are often reluctant to give a diagnosis [ 19 ] due to the perception that there is nothing more that can be offered.

4.3. Experience of Post-Diagnostic Support Services

In our study, the experience of post-diagnostic support services was predominantly positive in that carers were largely satisfied with the provision and level of home-based support services, tying in with their wish for their family member with dementia to remain at home, rather than be transferred to a care home facility. The provision of home support services such as help with showering, shopping, and cleaning was perceived as particularly beneficial by caregivers, allowing them some respite. Our findings differ from a study of South Asian (Indian and Pakistani origin) people living with dementia in Scotland that found overwhelmingly negative responses, reporting a severe lack of support and very little knowledge of dementia and how to manage it [ 20 ]. Carers in our study expressed concerns about aged care facilities not being able to cater to the dietary needs of Indian people with dementia and are unable to communicate in the person’s language, leaving them socially isolated. Studies in Indian populations elsewhere have also reported language to be a major barrier in seeking and receiving dementia health services [ 14 , 18 ].

4.4. Impact on Personal and Social Life of the Person Living with Dementia

Dementia has a significant impact of the personal and social lives of people living with dementia. Some people experience a loss of independence and fear of loneliness and stigmatisation. Caregivers often reported that, in order to protect the person living with dementia, the family might withdraw from social activities due to the feeling of “exclusion” and stigma they experienced and a perceived lack of understanding within their community. The concept of the stigma associated with dementia is expressed by people across many countries and cultures and often prevents or delays seeking care and secludes families from their wider circles [ 21 , 22 ].

4.5. Caregiver Experiences

Caregivers expressed a range of experiences and emotions. Younger caregivers appeared to cope better, even if they had made sacrifices such as giving up their employment and social life. Older caregivers (usually the female spouse) struggled both with the mental and emotional impact of observing their spouse declining in their mental capacity as well as their own health issues. Caregivers of parents with dementia accepted their role as part of their filial duty, a common concept in the Indian and South Asian society [ 23 ]. In Asian cultures families are expected to provide care for the person with dementia, either out of affection or out of duty, and to meet cultural needs that are sometimes beyond their capabilities of standard care services [ 4 , 24 , 25 ]. The concept of extended families is often seen as a way of keeping parents involved in the lives of their children and grandchildren, hence allowing a symbiotic relationship that often benefits the whole family [ 24 ]. On the other hand, such living arrangements may be a source of stress, particularly to the female caregivers in a family where one member has dementia and is no longer able to assist with childcare. The availability of home care support services was seen as a crucial service in these circumstances.

4.6. Strengths

This study had several strengths. This study captured insights from people with mild to moderate dementia rather than only the caregivers’ perspectives. The interviews were contextually rich as the interviewers were bilingual and were able to grasp the cultural context of the conversations. The interviewers were also aware of the preferred cultural protocols when addressing and speaking with community elders, such as imparting a sense of being respected as an elder during the interview process. The interviews were conducted in the participants’ homes, creating a safe cultural space and allowing participants to speak freely about their experiences. We followed the Consolidated criteria for reporting qualitative research (COREQ) guidelines [ 26 ] in the conduct of our study and reporting of our findings.

4.7. Limitations

There were some limitations in this study. First, the study was limited to the Auckland region with participants being identified through an Auckland-based memory service and two non-profit community organisations. Hence, the findings may not be generalizable to the whole of Aotearoa, NZ, particularly in relation to health and social services. Second, Indians speak multiple languages and their culture varies among different regions of India and other parts of the world including Fiji. These data may not have captured the whole range of experiences from the Indian diaspora, and language/culture-specific complexities may have been lost.

4.8. Implications for Future Research and Service Development

Our study findings were similar to those found in a recent report [ 27 ], which found that people with dementia and their caregivers of mostly European background living in Aotearoa, NZ also experienced challenges such as limited knowledge and understanding of dementia, societal stigma, and caregiver strain. Our findings showed that the Indian population had the additional challenges of a lack of culturally appropriate services for Indian people living with dementia and for their caregivers. These areas are addressed in the New Zealand Dementia Mate Wareware Action Plan 2020 to 2025 [ 28 ]. The Plan has four main themes: (1) reducing the incidence of dementia; (2) supporting people living with dementia and their caregivers to live their best possible lives, including access to timely diagnosis and support; (3) building accepting and understanding communities including addressing stigma and increasing awareness of dementia; (4) strengthening leadership and capability across the sector. Understanding the conceptualisation of dementia and dementia care in different cultures is an important starting point to enable culturally appropriate policy and service development in this area. The themes identified in this study provide support for implementing the actions to improve dementia care for the New Zealand Indian community.

5. Conclusions

In conclusion, this study identified a range of factors that impacted the understanding and lived experiences of dementia in NZ Indian families. Dementia as ‘forgetfulness’ was conceptualised as a normal part of ageing rather than a disease, which led to a level of acceptance. However, when more challenging symptoms of dementia emerged, stigma and responses from the community became a concern. People living with dementia expressed feelings of worry, loneliness, and a loss of independence. Caregiving was regarded as filial duty but older caregivers were also concerned about their own health needs. Getting a diagnosis was difficult, and culturally tailored dementia health and support services were regarded as important unmet needs for this community. These insights highlight the importance of co-creating care services with families living with dementia to maximise their benefit for different ethnic groups.

Acknowledgments

The authors wish to acknowledge the study participants for their contribution.

Topic guide.

Author Contributions

Conceptualization: R.V.K., G.C., S.Y. and S.C.; Methodology: R.V.K., G.C., S.Y. and S.C.; Formal Analysis: R.V.K. and E.S.D.; Investigation: R.V.K., E.S.D. and R.B.; Resources: S.Y. and S.C.; Data Curation: S.Y. and S.C.; Writing—Original Draft Preparation, R.V.K. and E.S.D.; Writing—Review & Editing: R.V.K., E.S.D., G.C., S.Y. and S.C.; Project Administration: S.Y. and S.C.; Funding Acquisition: S.C. All authors have read and agreed to the published version of the manuscript.

This study was funded by The University of Auckland Faculty Research Development Fund.

Institutional Review Board Statement

Informed consent statement.

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Risk factors for faster aging in the brain revealed in new study

Researchers from the Nuffield Department of Clinical Neurosciences at the University of Oxford have used data from UK Biobank participants to reveal that diabetes, traffic-related air pollution and alcohol intake are the most harmful out of 15 modifiable risk factors for dementia.

The researchers had previously identified a ‘weak spot’ in the brain, which is a specific network of higher-order regions that not only develop later during adolescence, but also show earlier degeneration in old age. They showed that this brain network is also particularly vulnerable to schizophrenia and Alzheimer’s disease.

In this new study, published in Nature Communications , they investigated the genetic and modifiable influences on these fragile brain regions by looking at the brain scans of 40,000 UK Biobank participants aged over 45.

The researchers examined 161 risk factors for dementia, and ranked their impact on this vulnerable brain network, over and above the natural effects of age. They classified these so-called ‘modifiable’ risk factors − as they can potentially be changed throughout life to reduce the risk of dementia − into 15 broad categories: blood pressure, cholesterol, diabetes, weight, alcohol consumption, smoking, depressive mood, inflammation, pollution, hearing, sleep, socialisation, diet, physical activity, and education.

Professor Gwenaëlle Douaud , who led this study, said: ‘We know that a constellation of brain regions degenerates earlier in aging, and in this new study we have shown that these specific parts of the brain are most vulnerable to diabetes, traffic-related air pollution − increasingly a major player in dementia − and alcohol, of all the common risk factors for dementia.’

‘We have found that several variations in the genome influence this brain network, and they are implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s diseases, as well as with the two antigens of a little-known blood group, the elusive XG antigen system, which was an entirely new and unexpected finding.’

Image caption: To the left of the figure, the red-yellow colour denotes the regions that degenerate earlier than the rest of the brain, and are vulnerable to Alzheimer’s disease. These brain areas are higher-order regions that process and combine information coming from our different senses. To the right of the figure, each dot represents the brain data from one UK Biobank participant. The overall curve shows that, in these particularly fragile regions of the brain, there is accelerated degeneration with age. Credit: G. Douaud and J. Manuello.

Professor Lloyd Elliott, a co-author from Simon Fraser University in Canada, concurs: ‘In fact, two of our seven genetic findings are located in this particular region containing the genes of the XG blood group, and that region is highly atypical because it is shared by both X and Y sex chromosomes. This is really quite intriguing as we do not know much about these parts of the genome; our work shows there is benefit in exploring further this genetic terra incognita.’

Importantly, as Professor Anderson Winkler, a co-author from the National Institutes of Health and The University of Texas Rio Grande Valley in the US, points out: ‘What makes this study special is that we examined the unique contribution of each modifiable risk factor by looking at all of them together to assess the resulting degeneration of this particular brain ‘weak spot’. It is with this kind of comprehensive, holistic approach − and once we had taken into account the effects of age and sex − that three emerged as the most harmful: diabetes, air pollution, and alcohol.’

This research sheds light on some of the most critical risk factors for dementia, and provides novel information that can contribute to prevention and future strategies for targeted intervention.

The paper ‘ The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease ’ is published in Nature Communications .

This research was funded by the UK Medical Research Council and the Wellcome Trust . The study was led by Professor Gwenaëlle Douaud , from the Wellcome Centre for Integrative Neuroimaging (WIN), an Associate Professor at the Nuffield Department of Clinical Neurosciences  (NDCN) and Research Fellow at Green Templeton College ,

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Untangling the threads of early onset dementia

Lynda De Widt

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Changes in personality, behavior and language are hallmarks of frontotemporal dementia (FTD) , the most common form of dementia in patients under the age of 65, which is associated with degeneration of the frontal and temporal lobes of the brain. Researchers have known that a less common protective variant of a gene called TMEM106B may slow disease progression, and now they have new insight into how parts of the protein produced by the TMEM106B gene may increase risk and cause the disease to accelerate.

They think the key may lie in the formation of fibrils, or tiny fiber-like structures produced by part of this protein, that sometimes get tangled up in the brain through an unknown process. Researchers observed that in most people with FTD whom they studied, these structures pile up, but in those with the protective form, they are virtually absent. The research could pave the way for better treatments in the future.

They report their findings in the journal Science Translational Medicine .

Only recently has the research community discovered that the TMEM106B protein forms these thread-like structures in the brain.

Mayo Clinic researchers in Florida and colleagues set out to determine the link between these TMEM106B structures, the protective TMEM106B genetic variant and FTD. First, they compared disease duration in deceased FTD patients who had donated their brain tissue to the Mayo Clinic Brain Bank . They found that those with the protective variant lived an average of three years longer. This suggests that the disease progressed slower in those patients.

Then, they created an antibody that would allow them to detect the amount of fiber-like structures in the human brain tissue.

Across all FTD cases that researchers analyzed from the brain bank — more than 250 samples — they found that most patients had a relatively high level of these thread-like structures in their brains. However, those with only the protective variant of TMEM106B had little to none. There was a positive correlation between the amount of TMEM106B structures and the level of another pathologic protein called TDP-43, which is strongly associated with FTD.

"It was striking to see that there was no buildup of fibrils in those with the protective variant. We think that likely has something to do with how TMEM106B protects against FTD or alters the disease course, but more work needs to be done to investigate that," says Jordan Marks, an M.D.–Ph.D. student with the Mayo Clinic Graduate School of Biomedical Sciences and first author of the paper. "We also think that these fibrils could one day serve as biomarkers to help clinicians determine FTD prognosis or severity."

The researchers say the findings have implications for future clinical studies.

"Our research provides evidence that genetic variants in TMEM106B are an essential factor to consider in study groups of patients with FTD," says Casey Cook, Ph.D. , a Mayo Clinic neuroscientist and co-corresponding author of the paper. "The work also suggests novel therapeutic interventions to prevent the buildup of the tangled fiber-like structures might one day reduce disease risk or slow disease progression."

The next steps in the team's research include validating these results in additional patient study groups and examining the network of interacting proteins associated with FTD to provide further insight into how the TMEM106B protein buildup contributes to disease.

In a related study , also published in Science Translational Medicine, Mayo Clinic researchers and collaborators discovered novel peptides in brain and cerebrospinal fluid produced when TDP-43, also implicated in amyotrophic lateral sclerosis (ALS) , or Lou Gehrig's disease, becomes dysfunctional. Their findings could provide the framework for the development of clinical-grade tests to measure TDP-43 pathology in living patients.

Funding for the research on TMEM106B was supported in part by the National Institutes of Health's National Institute on Aging, National Institute of Neurological Disorders and Stroke, Alzheimer's Association, ALLFTD , Cure Alzheimer's Fund, Mayo Clinic Alzheimer's Disease Research Center and Mayo Clinic Foundation. For a full list of authors and disclosures, see the paper .

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Alzheimer’s disease (ad).

Alzheimer’s disease (AD) is the most common form of dementia. It is a degenerative brain disorder mostly found in older adults that progressively impairs memory, thinking and reasoning skills, and eventually a person’s ability to live independently. In New Zealand, it is estimated that AD affects about 10% of people over 65 years, and almost 25% of people over 85 years.

The symptoms of AD vary and often relate to the age at which the disease first occurs. People affected by AD before the age of 65 may experience early difficulties with spatial perception and disorientation. However, in the majority of people with AD, memory problems are one of the first symptoms to appear, usually in their mid-60s. Other common signals of early stage AD include visuospatial issues (e.g. getting lost in familiar places), impaired reasoning or judgement, and problems with word-finding (i.e. difficulty choosing or finding the right word to express a thought). As AD progresses, people can experience greater memory loss, changes in their personality and behaviour, and they can struggle to complete normal daily tasks.

While the precise causes of AD remain largely unknown, there is a genetic component in a very small percentage of cases that typically leads to early-onset AD, where disease occurs between a person’s 40s to mid-60s.

Late-onset AD, in which symptoms appear in the mid-60s or later, is thought to be caused by a combination of genetic, environmental and lifestyle factors. These factors trigger changes to the brain involving a build-up of amyloid-beta protein and tau protein that ultimately lead to brain cell death and tissue loss.

Currently, there is no cure for AD. Drug and non-drug treatments may help with both cognitive and behavioural symptoms, but these interventions do not prevent disease progression.

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• Published: 27 March 2024

The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease

• Jordi Manuello   ORCID: orcid.org/0000-0002-9928-0924 1 , 2 ,
• Joosung Min   ORCID: orcid.org/0000-0002-5541-5014 3 ,
• Paul McCarthy 1 ,
• Fidel Alfaro-Almagro 1 ,
• Soojin Lee 1 , 4 ,
• Stephen Smith 1 ,
• Lloyd T. Elliott 3   na1 ,
• Anderson M. Winkler 5 , 6   na1 &
• Gwenaëlle Douaud   ORCID: orcid.org/0000-0003-1981-391X 1  

Nature Communications volume  15 , Article number:  2576 ( 2024 ) Cite this article

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• Genetics research
• Neuroscience
• Risk factors

We have previously identified a network of higher-order brain regions particularly vulnerable to the ageing process, schizophrenia and Alzheimer’s disease. However, it remains unknown what the genetic influences on this fragile brain network are, and whether it can be altered by the most common modifiable risk factors for dementia. Here, in ~40,000 UK Biobank participants, we first show significant genome-wide associations between this brain network and seven genetic clusters implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s disease, and with the two antigens of the XG blood group located in the pseudoautosomal region of the sex chromosomes. We further reveal that the most deleterious modifiable risk factors for this vulnerable brain network are diabetes, nitrogen dioxide – a proxy for traffic-related air pollution – and alcohol intake frequency. The extent of these associations was uncovered by examining these modifiable risk factors in a single model to assess the unique contribution of each on the vulnerable brain network, above and beyond the dominating effects of age and sex. These results provide a comprehensive picture of the role played by genetic and modifiable risk factors on these fragile parts of the brain.

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Introduction

The development of preventative strategies based on modifying risk factors might prove to be a successful approach in ensuring healthy ageing. Factors particularly scrutinised in dementia and unhealthy ageing have included cerebrovascular factors such as high blood pressure, diabetes and obesity, but also lifestyle ones such as alcohol consumption, and protective factors such as exercise 1 . Assessing these modifiable risk factors together makes it possible to identify the unique contribution of each of these factors on the brain or on cognitive decline. A Lancet commission, updated in 2020 to include, e.g., pollution for its possible role in the incidence of dementia 2 , examined the relative impact of 12 modifiable risk factors for dementia, and showed that these 12 factors may account for 40% of the cases worldwide 3 . Conversely, genetic factors are non-modifiable in nature, but can inform us about the mechanisms underlying the phenotypes of interest. These mechanisms sometimes can be shared across these phenotypes. For instance, genetic overlap has been found for Alzheimer’s and Parkinson’s diseases at a locus in the MAPT region 4 . Likewise, one of the most pleiotropic variants, in the SLC39A8 / ZIP8 gene, shows genome-wide associations with both schizophrenia and fluid intelligence, amongst many other phenotypes 5 , 6 .

One way to objectively and robustly assess susceptibility for unhealthy ageing is to look non-invasively at brain imaging markers 7 . Using a data-driven approach on a lifespan cohort, we previously identified an ensemble of higher-order, ‘transmodal’ brain regions that degenerates earlier and faster than the rest of the brain 8 . The very same areas also develop relatively late during adolescence, thus supporting the ‘last in, first out’ (LIFO) hypothesis, which posits that the process of age-related brain decline mirrors developmental maturation. Importantly, this network of brain regions further demonstrated heightened vulnerability to schizophrenia and Alzheimer’s disease, two disorders that impact on brain structure during adolescence and ageing respectively. Accordingly, this LIFO network was strongly associated with cognitive traits whose impairment is specifically related to these two disorders, namely fluid intelligence and long-term memory 8 .

Here, our main objective was to assess both the genetic and modifiable risk factors’ contributions to the vulnerability of these most fragile parts of the brain. We conducted a genome-wide association study on a prospective cohort of nearly 40,000 participants of the UK Biobank study who had received brain imaging, and in total evaluated the association between the LIFO brain network and 161 modifiable risk factors, classified according to 15 broad categories: blood pressure, cholesterol, diabetes, weight, alcohol consumption, smoking, depressive mood, inflammation, pollution, hearing, sleep, socialisation, diet, physical activity and education.

The vulnerable LIFO brain network in UK Biobank

Similar to our previously observed results 8 , the loadings of the LIFO brain network, i.e., the normalised grey matter volume in the network after regressing out the effects of all the other brain maps (see Methods), demonstrated a strong quadratic association with age in the UK Biobank cohort of 39,676 participants ( R 2  = 0.30, P  < 2.23 × 10 −308 , Fig.  1 ). These higher-order regions thus show an accelerated decrease of grey matter volume compared with the rest of the brain. Furthermore, these areas define a network mainly involved in behavioural tasks related to execution, working memory, and attention (Fig.  1 , Supplementary Information ).

Top left, spatial map of the LIFO network (in red-yellow, thresholded at Z  > 4 for visualisation) used to extract the loadings from every scanned participant from UK Biobank ( n  = 39,676). Top right, these LIFO loadings (in arbitrary units) show a strong quadratic association with age in the UK Biobank cohort, i.e. grey matter volume decreases quadratically with older age in these specific regions ( R 2  = 0.30, P  < 2.23 × 10 −308 ; inset: residual scatterplot). Bottom, the vulnerable network appears to encompass areas mainly involved in execution, working memory, and attention (using the BrainMap taxonomy 60 , and with the LIFO brain network thresholded at both Z  = 4 and Z  = 10, see  Supplementary Information ).

Genetic influences over the vulnerable LIFO brain network

Using a minor allele frequency filter of 1% and a –log 10 (P) threshold of 7.5, we found, in the 39,676 participants, genome-wide associations between the LIFO brain network and seven genetic clusters whose top variants were all replicated (Table  1 /Supplementary Data  1 , Fig.  2 ).

Top row, Manhattan plot showing the 7 significant genetic clusters associated with the LIFO brain network (–log 10 ( P ) > 7.5). Second and third rows, regional association plots of the top variants for each of the 5 autosomal genetic clusters: rs6540873 on chromosome (Chr) 1 ( KCNK2 ), rs13107325 on Chr4 ( SLC39A8 ), rs2677109 on Chr6 ( RUNX2 ) (as a proxy in high LD R 2  = 0.86 with indel 6:45442860_TA_T), rs12146713 on Chr12 ( NUAK1 ), and rs2532395 on Chr17 ( MAPT , KANSL1 )(highest variant after tri-allelic rs2693333; see Supplementary Data  4 for a complete list of significant variants in this 5th MAPT genetic cluster). Bottom row, regional association plots of the top variants for the two genetic clusters in the pseudo-autosomal region PAR1 of the X chromosome: rs312238 ( XG , CD99 ) and rs2857316 ( XG )(UK Biobank has no genotyped variants on the 3’ side). Based on Human Genome build hg19. P -values are derived from a two-sided linear association test.

The first autosomal genetic cluster, on chromosome 1, included two variants (lead variant: rs6540873, β  = 0.06, P  = 1.71 × 10 −8 , and rs1452628, with posterior probabilities of inclusion in the causal variant set of 0.56 and 0.45, respectively) close to, and eQTL of, KCNK2 ( TREK1 ). This gene regulates immune-cell trafficking into the central nervous system, controls inflammation, and plays a major role in the neuroprotection against ischemia. Of relevance, these two loci are in particular related in UK Biobank participants with the amount of alcohol consumed, insulin levels, inflammation with interleukin-8 levels, as well as, crucially, with late-onset Alzheimer’s disease (Table  1 /Supplementary Data  1 ).

The second autosomal genetic cluster on chromosome 4 was made of 7 loci, with the lead variant rs13107325 in an exon of SLC39A8/ZIP8 ( β  = 0.14, P  = 2.82 × 10 −13 , posterior probability: 0.99). This locus is one of the most pleiotropic SNPs identified in GWAS, and is, amongst many other associations, related in UK Biobank with cholesterol, blood pressure, weight, inflammation with C-reactive proteins levels, diabetes with insuline-like growth factor 1 levels, alcohol intake, sleep duration, and cognitive performance/impairment, including prospective memory (Table 1 /Supplementary Data  1 ).

The third locus was an indel in chromosome 6 in an intron, and eQTL, of RUNX2 (rs35187443, β  = 0.06, P  = 9.03 × 10 −9 ), which plays a key role in differentiating osteoblasts, and has been very recently shown to limit neurogenesis and oligodendrogenesis in a cellular model of Alzheimer’s disease 9 .

The fourth locus was a SNP in chromosome 12, in an intron of NUAK1 (rs12146713, β  = −0.10, P  = 1.26 × 10 −9 ), and remarkably its top association in UK Biobank was with the contrast between schizophrenia and major depressive disorder 10 , and it was also associated with insulin-like growth factor 1 levels (Table 1 /Supplementary Data  1 ).

The final genetic autosomal genetic cluster was made of 3,906 variants in the MAPT region. Its lead non-triallelic variant, rs2532395 ( β  = −0.09, P  = 3.56 × 10 −15 ) was more specifically <10 kb from KANSL1 and an eQTL of KANSL1 , MAPT and other genes in brain tissues (Table 1 /Supplementary Data  1 , Supplementary Data 4 ). This locus was also associated in UK Biobank with tiredness and alcohol intake. MAPT is in 17q21.31, a chromosomal band involved with a common chromosome 17 inversion 11 . Adding chromosome 17 inversion status as a confounder reduced the significance of the association ( β  = −0.15, P  = 8.45 × 10 −3 ). Since the genotype for rs2532395 was also strongly correlated with chromosome 17 inversion in our dataset (Pearson correlation r  = 0.98, P  < 2 × 10 −16 ), this would suggest that the association between MAPT and the LIFO network is not independent from chromosome 17 inversion. As this extended genetic region is known for its pathological association with many neurodegenerative disorders including Alzheimer’s disease, we investigated whether the LIFO brain regions mediated the effect of the MAPT genetic cluster (using the lead bi-allelic variant rs2532395) on Alzheimer’s disease (see Methods). Despite small average causal mediated effect (ACME) sizes, we found a significant effect for both the dominant model (ACME β  = 1.16 × 10 −4 ; 95% CI = [5.19 × 10 −5 , 1.99 × 10 −4 ]; P  = 4 × 10 −5 ) and the recessive model (ACME β  = 1.55 × 10 −4 ; 95% CI = [3.96 × 10 −5 , 3.74 × 10 −4 ]; P  = 4 × 10 −5 ; full output of the mediation package on the dominant and recessive models in  Supplementary Information ).

The two last genetic clusters of 8 and 9 variants respectively were found on the X chromosome, notably in a pseudo-autosomal region (PAR1), which is interestingly hit at a higher rate than the rest of the genome ( P  = 1.56 × 10 −5 , see  Supplementary Information ). The top variants for these clusters were related to two homologous genes coding for the two antigens of the XG blood group: rs312238 ( β  = −0.05, P  = 1.77 × 10 −10 ) ~ 10 kb from, and an eQTL of, CD99/MIC2 , and rs2857316 ( β  = −0.08, P  = 2.27 × 10 −29 ) in an intron and eQTL of XG  (Table 1 /Supplementary Data  1 ). Since chromosome X has hardly been explored, we carried out our own association analyses between these two top variants and non-imaging variables in UK Biobank. Intriguingly, the first of these two PAR1 loci, rs312238, was found to be significantly associated in the genotyped participants who had not been scanned (out-of-sample analysis in n  = 374,230 UK Biobank participants) with nitrogen dioxide air pollution, our ‘best’ MRF for pollution (see below), and many other environmental, socioeconomic, and early life factors (such as urban or rural setting, distance from the coast, place of birth, number of siblings, breastfed as a baby, maternal smoking around birth), as well as health outcomes (Supplementary Data  2 ). In particular, amongst the more easily interpretable findings of the most associated variables with rs312238, the T allele of this locus was associated with two increased measures of deprivation and/or disability (worse socioeconomic status), the ‘Townsend deprivation index’ and the ‘Health score’, but also with ‘Nitrogen dioxide air pollution’, ‘Maternal smoking around birth’, as well as ‘Number of full brothers’ and ‘Number of full sisters’, thus showing consistent signs of association between this variant and these phenotypes.

We found that the heritability of the LIFO network was significant, with h 2  = 0.15 (se = 0.01). The genetic co-heritability between the LIFO network and Alzheimer’s disease or schizophrenia was not statistically significant (coefficient of co-heritability = −0.12, se = 0.10; P  = 0.23; coefficient of co-heritability = −0.16, se = 0.04, P  = 0.07, respectively).

Modifiable risk factors’ associations with the vulnerable LIFO brain network

Including the modifiable risk factors (MRFs) in a single general linear model allows us to assess the unique contribution of each factor on the LIFO brain network. Not all UK Biobank participants have data available for all of the MRF variables however. An analysis limited to those with complete data for all MRFs would be biased, and based on a relatively small, low-powered sample. We addressed this issue via a two-stage analysis in which: (i) we first identified which variable within each of the 15 MRF categories best represented associations of that category with the LIFO brain network loadings (based on two criteria: significance and <5% missing values), (ii) we investigated the unique contribution of that MRF category, over and above all other categories and the dominating effects of age and sex, to the LIFO loadings.

From the first stage of our analysis, 12 of the 15 categories of MRFs had at least one ‘best’ MRF, i.e., with a significant effect on the LIFO brain network and enough non-missing values across all scanned participants to be investigated further (Table  2 /Supplementary Data  3 ). The contribution of the MRFs on the vulnerable brain network differed vastly depending on whether confounding effects of age, sex and head size were taken into account. The effect size and significance of some MRFs diminished because of some clear collinearity with the confounders. For instance, for the category of blood pressure, the most significant MRF was first “systolic blood pressure, automatic (second) reading” ( r  = −0.20, P  < 2.23 × 10 −308 ), but after regressing out the confounders, the ‘best’ MRF for this category was “medication for blood pressure” ( r  = −0.05, P  = 7.55 × 10 −22 ). Conversely, regressing out the effects of age served to unmask the significant deleterious effects of pollution on the vulnerable brain regions, such as nitrogen dioxide air pollution or particulate matter air pollution (Table  2 /Supplementary Data  3 ).

When considered together in a single model in the second stage of the analysis, 3 best MRFs had an effect on the LIFO brain network that remained significant beyond the dominating effects of age and sex, and of the 9 other best MRFs: diabetes (“diabetes diagnosed by doctor”, r  = −0.05, P  = 1.13 × 10 −24 ), pollution (“nitrogen dioxide air pollution in 2005”, r  = −0.05, P  = 5.39 × 10 −20 ) and alcohol (“alcohol intake frequency”, r  = −0.04, P  = 3.81 × 10 −17 ) (Table  3 ). No MRFs showed any bias in their sub-sampling distribution, i.e., any significant difference between the original sample and the reduced sample of 35,527 participants who had values for all 18 variables considered (the 12 best MRFs and 6 confounders: age, sex, age 2 , age × sex, age 2  × sex, head size; Supplementary Information ). In total, the 12 best MRFs explained 1.5% of the effect on the vulnerable brain network ( F 12;35509  = 43.5).

While 6 out of the 7 genetic clusters associated with the LIFO network were correlated with many variables related to each of the 15 MRF categories, including diabetes, alcohol consumption and traffic pollution (Supplementary Data  1 ), we also found some genetic overlap between the very specific best MRF of “alcohol intake frequency” and the LIFO network in the pleiotropic rs13107325 variant (cluster 2), as well as rs17690703, part of the large genetic cluster 5 in MAPT (Supplementary Data  4 ). No genetic overlap was found for the precise “nitrogen dioxide air pollution in 2005” or “diabetes diagnosed by doctor”, nor for approximate variables.

This study reveals, in a cohort of nearly 40,000 UK Biobank participants, the genetic and modifiable risk factors’ associations with brain regions in a ‘last in, first out’ (LIFO) network that show earlier and accelerated ageing and are particularly vulnerable to disease processes such as that of Alzheimer’s disease 8 . Seven genetic clusters, two of which in the pseudo-autosomal region of the sex chromosomes coding for two antigens of the XG blood system, were found significantly associated and replicated genome-wide. In addition, after accounting for age and sex effects, diabetes, traffic-related pollution and alcohol were the most deleterious modifiable risk factors (MRFs) on these particularly vulnerable brain regions.

Three lead variants for our significant genetic clusters have been previously associated with ageing-related brain imaging measures in recent studies: one, in cluster 1, an eQTL of KCNK2 ( TREK1 ) 12 , 13 , whose increase in expression mediates neuroprotection during ischemia 14 , the ubiquitous rs13107325 (cluster 2), and one, in cluster 4, in an intron of NUAK1 ( ARK5 ) 15 , 16 , 17 , which has been associated with tau pathology 18 (Table  1 /Supplementary Data  1 ). On the other hand, of the seven genetic clusters, three were entirely novel (clusters 3, 6 and 7), and not found in other brain imaging studies, including our most recent work that expanded on our previous GWAS of all of the brain IDPs available in UK Biobank 19 by including more participants—in fact, the same number of participants as analysed in this present work—and, crucially, by also including the X chromosome 20 (Table  1 /Supplementary Data  1 ). This suggests that, beyond the genetic hits that were meaningfully associated with the LIFO brain network and an array of relevant risk factors, lifestyle variables and brain disorders, and found in a few other imaging GWAS, some of the genetic underpinnings of the LIFO network are intrinsically specific to it and to no other pre-existing imaging phenotype.

All five autosomal genetic clusters identified through the GWAS of the LIFO phenotype had relevant associations with risk factors for dementia (Results; Supplementary Data  1 ), including precisely two of the best MRFs (for clusters 2 and 5), and three of them directly related in UK Biobank to the two diseases showing a pattern of brain abnormalities following the LIFO network: schizophrenia (clusters 2 and 4) and Alzheimer’s disease (cluster 1) (Supplementary Data  1 ). In particular, cluster 2 has its lead variant rs13107325 in an exon of one of the most pleiotropic genes ZIP8 , which codes for a zinc and metal transporter. Considering the vulnerability of the LIFO brain network to adolescent-onset schizophrenia and its significant association with fluid intelligence that we previously demonstrated 8 , it is notable that this variant has been associated genome-wide with schizophrenia 6 , as well as intelligence, educational attainment and mathematics ability 5 , 21 . In line with the LIFO brain network being both prone to accelerated ageing and susceptible to Alzheimer’s disease, this genetic locus has also been associated genome-wide with well-known risk factors for dementia. These comprise alcohol—including the exact same variable of “alcohol intake frequency” as identified as one of the best MRFs—cholesterol, weight, sleep—including “sleep duration”—and blood pressure 22 , 23 , 24 , 25 , 26 , all of which significantly contribute to modulating the LIFO brain network when considered separately (Table  2 /Supplementary Data  3 ). Of relevance, this genetic locus is also associated to an increased risk of cardiovascular death 27 . Cluster 5, a large genetic cluster in the MAPT region (Microtubule-Associated Protein Tau), comprised in total 3906 significant variants (Supplementary Data  4 ). This genetic region plays a role in various neurodegenerative disorders related to mutations of the protein tau, such as frontotemporal dementia 28 and progressive supranuclear palsy 29 , but also, of particular pertinence to the LIFO brain network, Alzheimer’s and Parkinson’s disease, with a genetic overlap between these two diseases in a locus included in our significant cluster 5 (rs393152, β  = −0.09, P  = 6.35 × 10 −14 ) 4 . Despite the relatively low number of people with diagnosed Alzheimer’s disease in the genetic discovery cohort, we were able to establish—albeit with small effect sizes—a significant mediation role for the LIFO brain regions between the lead bi-allelic variant for cluster 5 and this Alzheimer’s diagnosis, suggesting once more the importance played by these vulnerable brain areas in unhealthy ageing.

Finally, of the seven clusters, two were located in the pseudo-autosomal region (PAR1) of the sex chromosomes corresponding to the genes XG and CD99 , coding for the two antigens of the XG blood group. This blood group system has been largely neglected, its main contribution related to the mapping of the X chromosome itself, and its clinical role remains elusive 30 . In order to investigate further the possible role of these two variants of the XG blood group, we examined out-of-sample their associations with thousands of non-imaging phenotypes. This analysis revealed that the first of these two loci was significantly and consistently associated with early life factors, environmental factors and health outcomes, including particulate matter and nitrogen dioxide air pollution, the second most deleterious MRF to the LIFO brain network (Supplementary Data  2 ). Whether these associations are due to stratification or genotyping artefacts, or to the fact that this specific variant, which is inherited from a parent, has a parental impact that modulates the effect of early life environment of the UK Biobank participants, the so-called “nature of nurture”, will need further investigation 31 .

Intriguingly, an analysis revealed that the genes involved in the loci associated with the LIFO network (Table  1 /Supplementary Data  1 ) are enriched for the gene ontology terms of leucocyte extravasation, namely “positive regulation of neutrophil extravasation” ( P  = 4.75 × 10 −6 ) and “T cell extravasation” ( P  = 4.75 × 10 −6 ). This result held when removing the genes included in the MAPT extended region (with P  = 2.54 × 10 −6 and P  = 2.54 × 10 −6 , respectively). Leucocyte extravasation facilitates the immune and inflammatory response, and there has been renewed focus on the fact that a breakdown of the blood-brain barrier together with leukocyte extravasation might contribute to both Alzheimer’s disease and schizophrenia 32 , 33 . In line with the enrichment findings, 4 out of the 7 genetic clusters associated with the LIFO network are correlated in UK Biobank blood assays with percentage or count of immune cells (neutrophil, lymphocyte, platelet, monocyte, etc.; Supplementary Data  1 ).

Regarding MRFs’ effects on the LIFO brain network, diabetes and alcohol consumption have been consistently shown to be associated with both cerebral and cognitive decline 34 , 35 . On the other hand, pollution—and notably that of nitrogen oxides—has emerged more recently as a potential MRF for dementia 2 , 36 . In particular, the increase of dementia risk due to nitrogen oxide pollution, a proxy for traffic-related air pollution, seems to be enhanced by cardiovascular disease 37 . In this study, we found that nitrogen dioxide pollution has one of the most deleterious effects onto the fragile LIFO brain regions. This effect could only be unmasked by regressing out the effects of age and sex, as traffic-related air pollution is modestly inversely-correlated with age (Supplementary Data  5 ). It is also worth noting that including age and sex as confounding variables in the first stage of our analysis reduced considerably the contribution of what had appeared at first—before regression—as the most harmful risk factors: blood pressure, cholesterol and weight (Table  2 /Supplementary Data  3 ). Furthermore, the benefit of examining these MRFs in a single model in the second stage of our analysis is that we can assess the unique contribution of each of these factors on the LIFO brain network; in doing so, blood pressure, cholesterol and weight were no longer significant (Table  3 ).

One defining characteristic of the LIFO brain network is how much age explains its variance. Indeed, in the dataset covering most of the lifespan that was initially used to identify the LIFO and spatially define it 8 , age explained 50%. In the UK Biobank imaging project, where imaged participants are over 45 years old, age explained 30% (Fig.  1 ). It is thus perhaps unsurprising that, while the explained variance by each of the MRFs varies widely (Table  2 /Supplementary Data  3 ), it reduces notably once the effect of age and other confounders has been regressed out (without confounders included in the model: maximum 8.4%; with confounders: maximum 0.5%). Combined, the 12 best MRFs explained a significant 1.5% of the effect on the vulnerable brain network after regressing out age, head size and sex effects. Regarding the genetic hits, we found a significant heritability with h 2  = 0.15, in keeping with our results for structural brain phenotypes (except for subcortical and global brain volumes, which demonstrate higher heritability 19 ).

The uniqueness of this study relies on the fact that we combined the strengths of two different cohorts: the first, which revealed the LIFO grey matter network, is lifespan, demonstrating the mirroring of developmental and ageing processes in the LIFO brain areas, something that could never be achieved with UK Biobank because of its limited age range. Of note, for this initial work with the lifespan cohort 8 , we not only included grey matter partial volume images, as done in this current study, but also Freesurfer information of cortical thickness and surface area. The LIFO network showed no contribution from Freesurfer cortical thickness or area. This might hint at processes that only partial volume maps are able to detect due to the LIFO network’s specific localisation, including in the cerebellum and subcortical structures, which are not included in the area and thickness surface methods from Freesurfer.

Limitations of our study pertain to the nature of the data itself and the way each variable is encoded in the UK Biobank (binary, ordinal, categorical, continuous), the number of missing values, what is offered as variables for each modifiable risk factor category (e.g. we chose not to create any compound variables, such as the ratio of cholesterol levels or systolic and diastolic blood pressures), and the curation of each of these variables. Some of the factors might be proxies for another category, but including the ‘best’ ones in a single model alleviate these issues to some extent. Another limitation is the assumption in our models that each risk factor has a linear, additive effect on the vulnerable LIFO brain network. It is also important to note that cross-sectional and longitudinal patterns of brain ageing can differ, as has been shown for instance for adult span trajectories of episodic and semantic memory, especially in younger adults 38 . A recent study has also demonstrated a specific ‘brain age’ imaging measure to be more related to early life influences on brain structure than within-person rates of change in the ageing brain 39 . Further work will be needed to establish how the LIFO network data changes in terms of within-person trends, for instance by investigating the growing UK Biobank longitudinal imaging database. While we took care of assessing the replicability of our genetic results by randomly assigning a third of our dataset for such purposes (all our significant genetic hits were replicated), this was performed within the UK Biobank cohort that exhibits well-documented biases, being well-educated, less deprived, and healthier than the general population, especially for its imaging arm 40 . Independent replications will be needed to confirm the existence of the LIFO-associated genetic loci.

In conclusion, our study reveals the modifiable and non-modifiable factors associated with some of the most fragile parts of the brain particularly vulnerable to ageing and disease process. It shows that, above and beyond the effect of age and sex, the most deleterious modifiable risk factors to this brain network of higher-order regions are diabetes, pollution and alcohol intake. Genetic factors are related to immune and inflammatory response, tau pathology, metal transport and vascular dysfunction, as well as to the XG blood group system from the pseudo-autosomal region of the sex chromosomes, and meaningfully associated with relevant modifiable risk factors for dementia. The unprecedented genome-wide discovery of the two variants on the sex chromosomes in this relatively unexplored blood group opens the way for further investigation into its possible role in underlying unhealthy ageing.

Supplementary Information is available for this paper.

For the present work the imaging cohort of UK Biobank was used and we included 39,676 subjects who had been scanned and for whom the brain scans had been preprocessed at the time of the final set of analyses (M/F 47–53%; 44–82 years, mean age 64 ± 7 years; as of October 2020) 41 , 42 . Structural T1-weighted scans for each participant were processed using the FSL-VBM automated tool to extract their grey matter map 43 , 44 . The ‘last in, first out’ (LIFO) network of mainly higher-order brain regions was initially identified by performing a linked independent component analysis on the grey matter images of another, lifespan observational cohort of 484 subjects 8 , 45 , 46 . This map of interest, along with the other 69 generated by the analysis, was first realigned to the UK Biobank ‘standard’ space defined by the grey matter average across the first 15,000 participants, then regressed into the UK Biobank participants’ grey matter data, to extract weighted average values of grey matter normalised volume inside each of the z-maps, using the z-score as weighting factor. This made it possible to assess the unique contribution of this specific LIFO map, above and beyond all the rest of the brain represented in the other 69 maps. At the end of this process, we obtained a single imaging measure for each of the 39,676 participants, i.e. a ‘loading’ corresponding to their amount of grey matter normalised volume in the LIFO brain network.

Human participants: UK Biobank has approval from the North West Multi-Centre Research Ethics Committee (MREC) to obtain and disseminate data and samples from the participants ( http://www.ukbiobank.ac.uk/ethics/ ), and these ethical regulations cover the work in this study. Written informed consent was obtained from all of the participants.

Modifiable risk factors selection

The following 15 categories of modifiable risk factors (MRFs) for dementia were investigated based on previous literature: blood pressure, diabetes, cholesterol, weight, alcohol, smoking, depression, hearing, inflammation, pollution, sleep, exercise, diet/supplementation, socialisation, and education. These included well-documented cerebrovascular risk factors, and in particular included all of the 12 modifiable risk factors considered in the updated Lancet commission on dementia, with the sole exception of traumatic brain injury 3 . For each category, several MRF variables from UK Biobank were very minimally pre-processed ( Supplementary Information ). In total, 161 MRF variables were obtained. To optimise the interpretability of the results, and to be able to relate them to previous findings, we did not carry out any data reduction, which would have prevented us from identifying exactly which variable—and subsequently, which genetic component for this specific variable—contribute to the effect. For these same reasons, we did not create any compound variable.

Statistical analyses

Genome-wide association study.

We followed the same protocol we had developed for the first genome-wide association study (GWAS) with imaging carried out on UK Biobank 19 . Briefly, we examined imputed UK Biobank genotype data 47 , and restricted the analysis to samples that were unrelated (thereby setting aside only ~450 participants), without aneuploidy and with recent UK ancestry. To account for population stratification, 40 genetic principal components were used in the genetic association tests as is recommended for UK Biobank genetic studies 19 , 20 , 47 . We excluded genetic variants with minor allele frequency <0.01 or INFO score <0.03 or Hardy-Weinberg equilibrium –log 10 ( P ) > 7. We then randomly split the samples into a discovery set with 2/3 of the samples ( n  = 22,128) and a replication set with 1/3 of the samples ( n  = 11,083). We also examined the X chromosome with the same filters, additionally excluding participants with sex chromosome aneuploidy: 12 in non-pseudoautosomal region (PAR) and 9 in PAR for the discovery set, 3 in non-PAR and 6 in PAR for the replication set. Variants were considered significant at –log 10 ( P ) > 7.5, and replicated at P  < 0.05.

Modifiable risk factor study

In the first stage, the general linear model was used to investigate, separately, the association between each of these 161 MRFs and the LIFO network loadings in all the scanned UK Biobank participants ( n  = 39,676). We ran each model twice: once as is, and once adding 6 confounders: age, age 2 , sex, age × sex, age 2 × sex, and head size, to estimate the contribution of these MRFs on the LIFO network above and beyond the dominating effects of age and sex. Sex was based on the population characteristics entry of UK Biobank. This is a mixture of the sex the NHS had recorded for the participant at recruitment, and updated self-reported sex. For the GWAS, both sex and genetic sex were used (the sample was excluded in case of a mismatch). In total, 32 variables tailored to structural imaging had been considered as possible confounders, and we retained those with the strongest association ( R 2  ≥ 0.01; see  Supplementary Information ). Socioeconomic status via the Townsend deprivation index was also considered as a possible confounding variable but explained little variance ( R 2  < 0.001) and thus was not included as a confounder.

MRFs were not considered further if they were not significant—not surviving Bonferroni-correction, i.e., P  > 1.55 × 10 −4 —and if more than 5% of the subjects had their MRF values missing. For each category, a single ‘best’ MRF was then selected as the variable with the highest R 2 among those remaining, after regressing out the confounding effects of age and sex.

In the second stage, all these best MRFs were then included in a single general linear model, together with the same 6 confounders used in the first stage, to assess the unique contribution of each factor on the LIFO brain network loadings. A prerequisite to carry out this single general linear model analysis was to only include participants who would have values for all best MRFs and confounders. This explains the additional criterion of only including MRFs that had no more than 5% of values missing, to ensure that the final sample of participants who had values for all these best and confounding factors would not be biased compared with the original sample—something we formally tested (see  Supplementary Information )—especially as data are not missing at random in UK Biobank, and exhibit some genetic structure 48 . The sample was therefore reduced to a total of 35,527 participants for this second stage analysis (M/F 17,290–18,237; 45–82 years, mean 64 ± 7 years). The effect of these best MRFs taken altogether was considered significant with a very conservative Bonferroni correction for multiple comparisons across all combinations of every possible MRF from each of the initial 15 MRF categories ( P  < 4.62 × 10 −17 , see  Supplementary Information for more details). In addition, both full and partial correlations were computed for the same set of best MRFs and confounders, in order to assess possible relationships between variables.

Post hoc genetic analyses

Chromosome 17 inversion.

We investigated chromosome 17 inversion status of the participants in the discovery cohort by considering their genotype on 32 variants that tag chromosome 17 inversion according to Steinberg et al. 11 . Of these 32 variants, 24 were present in our genetic data. We labelled the participants homozygous inverted, heterozygous, or homozygous direct (not inverted) when all 24 of these alleles indicated the same zygosity. This yielded an unambiguous inversion status for 21,969 participants (99% of the discovery cohort). To examine if the association between the non-triallelic lead variant of the MAPT genetic cluster (rs2532395, Table  1 /Supplementary Data  1 ) and the LIFO network was independent from this common inversion, we determined inversion/direct status of the discovery cohort and: 1. repeated the association test between rs2532395 and the LIFO phenotype, with chromosome 17 inversion status added as a confounder; and 2. correlated the genotype for rs2532395 with chromosome 17 inversion.

Causality within each genetic cluster

We used CAVIAR (Causal Variants Identification in Associated Regions 49 ) to assess causality of variants that passed the genome-wide significance threshold in each of the genetic clusters we report. CAVIAR uses a Bayesian model and the local linkage disequilibrium structure to assign posterior probabilities of causality to each variant in a region, given summary statistics for an association. We did not perform CAVIAR analysis on the genetic cluster on chromosome 17, as its non-triallelic lead variant (rs2532395) was strongly correlated with chromosome 17 inversion, and the LD matrix was large and low rank. We excluded the X chromosome loci from this analysis due to the difficulty in assessing LD in this chromosome.

Enrichment analysis

Based on the genes listed in the ‘Genes’ column of Table  1 /Supplementary Data  1 , we performed an enrichment analysis for the genes associated with the LIFO brain network using PANTHER 50 . PANTHER determines whether a gene function is overrepresented in a set of genes, according to the gene ontology consortium 51 , 52 .

Mediation analysis between MAPT top variant and Alzheimer’s disease, via the LIFO brain network

As the gene MAPT is associated with Alzheimer’s disease, and as we found a significant association between MAPT and the LIFO brain network, we examined to what extent the effect of MAPT is mediated by the LIFO brain regions. We conducted a mediation analysis using the counterfactual framework in which the average indirect effect of the treatment on the outcome through the mediator is nonparametrically identified (version 4.5.0 of the R package ‘mediation' 53 ). This is a general approach that encompasses the classical linear structural equation modelling framework for causal mediation, allowing both linear and non-linear relationships. In this analysis, the genotype for the lead bi-allelic variant of the MAPT association was used as the treatment, the LIFO loadings as the mediator, and Alzheimer’s disease diagnosis as the outcome.

From the ~43 K UK Biobank participants who had been scanned, we searched for those who had been diagnosed with Alzheimer’s disease specifically, regardless of whether this diagnosis occurred before, or after their brain scans. Based on hospital inpatient records (ICD10: F000, F001, F002, F009, G300, G301, G308, and G309 and ICD9: 3310) and primary care (GP) data (Eu00., Eu000, Eu001, Eu002, Eu00z, F110., F1100, F1101, Fyu30, X002x, X002y, X002z, X0030, X0031, X0032, X0033, XaIKB, XaIKC, and XE17j), we identified 65 such cases— UK Biobank being healthier than the general population, and those scanned showing an even stronger healthy bias—of which 34 were included in the discovery set after QC.

We considered two conditions for the effect of the treatment on the outcome. First, a dominant condition in which the minor allele is assumed to be dominant and for which at least one copy of the minor allele is considered treated. Second, a recessive condition in which the minor allele is assumed to be recessive. We considered that either condition was nominally significant if the confidence interval of the average causal mediated effect did not intersect zero, and had an associated P  < 0.05 ÷ 2 (correcting for the two conditions). We assessed confidence intervals and P -values using 50,000 bootstrapped samples.

Associations between the LIFO brain network’s genetic hits and the MRFs

First, we reported in Table  1 / Supplementary Data  1 the significant associations between the LIFO genetic hits and UK Biobank variables related to the 15 categories listed for the MRFs. For this, we used the Open Targets Genetics website, which reports the GWAS carried out in UK Biobank ( https://genetics .opentargets.org/ ). Second, we assessed whether there was any genetic overlap between the known genetic components of the 3 best MRFs and the LIFO phenotype. Again, we used the Open Targets Genetics website outputs for these 3 very specific UK Biobank variables, and compared the significant hits for these 3 best MRFs within ±250 kbp of, or in high LD (>0.8) with, our own LIFO variants. If reported hits were limited, we also searched online for GWAS done on similar variables. Finally, we also included the list of significant hits for diabetes 54 , which focused on a potential genetic overlap between diabetes and Alzheimer’s disease.

Post hoc association for the sex chromosomes variants

The allele counts of each participant for two specific significant variants of the sex chromosomes not—or hardly—available in open databases such as https://genetics.opentargets.org/ 55 were further associated out-of-sample with all non-imaging phenotypes of UK Biobank ( n  = 16,924). This analysis was carried out in the entire genotyped, quality-controlled sample where participants who had been scanned were removed (final sample: 374,230 participants), taking into account the population structure (40 genetic principal components), as well as the confounding effects of age, sex, age x sex, age 2 and age 2 x sex. Results were corrected for multiple comparisons across all non-imaging phenotypes and the two variants.

Heritability

We examined the heritability of the LIFO phenotype, and the coheritability between the LIFO network and Alzheimer’s disease or schizophrenia using LDSC 56 . This method uses regression on summary statistics to determine narrow sense heritability h 2 of a trait, or the shared genetic architecture between two traits. LDSC corrects for bias LD structure using LD calculated from a reference panel (we used LD from the Thousand Genomes Project Phase 1 57 ). We obtained summary statistics for a meta-analysis of Alzheimer’s disease involving 71,880 cases and 383,378 controls 58 . The number of genetic variants in the intersection between the summary statistics was 1,122,435. For schizophrenia, the summary statistics were obtained from a meta-analysis involving 53,386 cases and 77,258 controls 59 . A total of 1,171,319 genetic variants were in the intersection with the summary statistics for LIFO. For both Alzheimer’s and schizophrenia, the X chromosome was not included in the heritability calculation, as it was excluded from the meta-analysis that we sourced the summary statistics from.

Reproducibility

No data was excluded for the MRF analyses. For the genetic analyses, these were restricted to samples that were unrelated, without aneuploidy and with recent UK ancestry (see above).

No statistical method was used to predetermine sample size. The experiments were not randomised. The Investigators were not blinded to allocation during experiments and outcome assessment.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All the FLICA decomposition maps − including the LIFO grey matter network − in UK Biobank standard space, the UK Biobank grey matter template, scripts, and the LIFO loadings for all of the participants are freely available on a dedicated webpage: open.win.ox.ac.uk/pages/douaud/ukb-lifo-flica/ .

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Acknowledgements

We are grateful to Profs Christian K. Tamnes, Lars T. Westlye, Kristine B. Walhovd and Anders M. Fjell, and Dr Andreas Engvig for providing the lifespan cohort which was used to initially derive the original ‘last in, first out’ brain network map, and to Prof Augustine Kong for helpful discussion on the associations between the PAR hit and early life and environmental factors. G.D. was supported by a UK MRC Career Development Fellowship (MR/K006673/1) and a Wellcome Collaborative Award (215573/Z/19/Z). S.S. was supported by Wellcome (203139/Z/16/Z; 215573/Z/19/Z). L.E. was funded by NSERC grants (RGPIN/05484-2019; DGECR/00118-2019) and a Michael Smith Health Research BC Scholar Award. A.M.W. received support through the NIH Intramural Research Program (ZIA-MH002781; ZIA-MH002782). This research was funded in whole, or in part, by the Wellcome Trust (215573/Z/19/Z; 203139/Z/16/Z; 203139/A/16/Z). For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. This research was also supported by the NIHR Oxford Health Biomedical Research Centre (NIHR203316). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z and 203139/A/16/Z).

Author information

These authors contributed equally: Lloyd T. Elliott, Anderson M. Winkler.

Authors and Affiliations

FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK

Jordi Manuello, Paul McCarthy, Fidel Alfaro-Almagro, Soojin Lee, Stephen Smith & Gwenaëlle Douaud

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy

Jordi Manuello

Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada

Joosung Min & Lloyd T. Elliott

Pacific Parkinson’s Research Centre, The University of British Columbia, Vancouver, BC, Canada

National Institutes of Mental Health, National Institutes of Health, Bethesda, MD, USA

Anderson M. Winkler

Department of Human Genetics, University of Texas Rio Grande Valley, Brownsville, TX, USA

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G.D. conceived and supervised the work, and carried out some of the genetic and modifiable risk factors analyses. J.Ma. carried out most of the genetic and modifiable risk factors analyses. J.Mi., S.L., A.M.W., and L.T.E. carried out additional genetics analyses. G.D., P. McC., F.A.-A., S.S., and L.T.E. created/extracted the imaging and genetics data, and organised the non-imaging data and confound variables. L.T.E. co-supervised the genetic analyses. A.M.W. co-supervised the modifiable risk factor analyses. G.D. interpreted the results and wrote the paper. J.Ma., S.S., L.T.E., and A.M.W. revised the paper.

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Manuello, J., Min, J., McCarthy, P. et al. The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease. Nat Commun 15 , 2576 (2024). https://doi.org/10.1038/s41467-024-46344-2

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DOI : https://doi.org/10.1038/s41467-024-46344-2

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New Research Links Mind Diet to a Slower Pace of Aging, Reduced Dementia Risk

By Columbia University's Mailman School of Public Health April 6, 2024

A study by Columbia University reveals that a healthy diet contributes to a lower risk of dementia and slower aging, with the MIND diet specifically showing significant benefits. This relationship is partly mediated by a deceleration in the biological aging process, highlighting the importance of dietary choices in cognitive health and longevity. Further research is needed to fully understand the underlying mechanisms.

A healthier diet is associated with a reduced dementia risk and slower pace of aging, according to a new study at Columbia University Mailman School of Public Health and The Robert Butler Columbia Aging Center. The findings show that a diet-dementia association was at least partially facilitated by multi-system processes of aging.

While literature had suggested that people who followed a healthy diet experienced a slowdown in the processes of biological aging and were less likely to develop dementia, until now the biological mechanism of this protection was not well understood. The findings are published in the Annals of Neurology .

“Much attention to nutrition in dementia research focuses on the way specific nutrients affect the brain,” said Daniel Belsky, PhD, associate professor of Epidemiology at Columbia School of Public Health and the Columbia Aging Center, and a senior author of the study. “We tested the hypothesis that a healthy diet protects against dementia by slowing down the body’s overall pace of biological aging.”

Study Methodology and Data Analysis

The researchers used data from the second generation of the Framingham Heart Study, the Offspring Cohort. Originating in 1971, participants in the latter were 60 years of age or older, were free of dementia, and also had available dietary, epigenetic, and follow-up data. The Offspring Cohort were followed up at nine examinations, approximately every 4 to 7 years. At each follow-up visit, data collection included a physical examination, lifestyle-related questionnaires, blood sampling, and, starting in 1991, neurocognitive testing.

Of 1,644 participants included in the analyses, 140 of the participants developed dementia. To measure the pace of aging, the researchers used an epigenetic clock called DunedinPACE developed by Belsky and colleagues at Duke University and the University of Otago. The clock measures how fast a person’s body is deteriorating as they grow older, “like a speedometer for the biological processes of aging,” explained Belsky.

Findings and Implications

“We have some strong evidence that a healthy diet can protect against dementia,” said Yian Gu, Ph.D., associate professor of Neurological Sciences at Columbia University Irving Medical Center and the other senior author of the study, “But the mechanism of this protection is not well understood.” Past research linked both diet and dementia risk to an accelerated pace of biological aging.

“Testing the hypothesis that multi-system biological aging is a mechanism of underlying diet-dementia associations was the logical next step,” explained Belsky. The research determined that higher adherence to the Mediterranean-Dash Intervention for Neurodegenerative Delay diet (MIND) slowed the pace of aging as measured by DunedinPACE and reduced risks for dementia and mortality. Furthermore, slower DunedinPACE accounted for 27 percent of the diet-dementia association and 57 percent of the diet-mortality association.

“Our findings suggest that a slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk, and therefore, monitoring the pace of aging may inform dementia prevention,” said first author Aline Thomas, Ph.D., a Postdoc at the Columbia Department of Neurology and Taub Institute for Research on Alzheimer’s Disease and the Aging Brain. “However, a portion of the diet-dementia association remains unexplained, therefore we believe that continued investigation of brain-specific mechanisms in well-designed mediation studies is warranted.”

“We suggest that additional observational studies be conducted to investigate direct associations of nutrients with brain aging, and if our observations are also confirmed in more diverse populations, monitoring biological aging, may indeed, inform dementia prevention,” noted Belsky.

Reference: “Diet, Pace of Biological Aging, and Risk of Dementia in the Framingham Heart Study” by Aline Thomas, Calen P. Ryan, Avshalom Caspi, Zhonghua Liu, Terrie E. Moffitt, Karen Sugden, Jiayi Zhou, Daniel W. Belsky and Yian Gu, 26 February 2024, Annals of Neurology . DOI: 10.1002/ana.26900

Co-authors are Calen Ryan and Jiayi Zhou, Columbia Aging Center; and Avshalom Caspi, Terrie Moffitt, and Karen Sugden, Duke University.

The study was supported by the National Institute on Aging grants R01AG061378, R01AG073402, R01AG059013, R01AG061008, R01AG073207 and R01AG049789.

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