research on depression during childhood has shown that quizlet

15.7 Mood and Related Disorders

Learning objectives.

By the end of this section, you will be able to:

• Distinguish normal states of sadness and euphoria from states of depression and mania
• Describe the symptoms of major depressive disorder and bipolar disorder
• Understand the differences between major depressive disorder and persistent depressive disorder, and identify two subtypes of depression
• Define the criteria for a manic episode
• Understand genetic, biological, and psychological explanations of major depressive disorder
• Discuss the relationship between mood disorders and suicidal ideation, as well as factors associated with suicide

Blake cries all day and feeling that he is worthless and his life is hopeless, he cannot get out of bed. Crystal stays up all night, talks very rapidly, and went on a shopping spree in which she spent $3,000 on furniture, although she cannot afford it. Maria recently had a baby, and she feels overwhelmed, teary, anxious, and panicked, and believes she is a terrible mother—practically every day since the baby was born. All these individuals demonstrate symptoms of a potential mood disorder.

Mood disorders ( Figure 15.15 ) are characterized by severe disturbances in mood and emotions—most often depression, but also mania and elation (Rothschild, 1999). All of us experience fluctuations in our moods and emotional states, and often these fluctuations are caused by events in our lives. We become elated if our favorite team wins the World Series and dejected if a romantic relationship ends or if we lose our job. At times, we feel fantastic or miserable for no clear reason. People with mood disorders also experience mood fluctuations, but their fluctuations are extreme, distort their outlook on life, and impair their ability to function.

The DSM-5 lists two general categories of mood disorders. Depressive disorders are a group of disorders in which depression is the main feature. Depression is a vague term that, in everyday language, refers to an intense and persistent sadness. Depression is a heterogeneous mood state—it consists of a broad spectrum of symptoms that range in severity. Depressed people feel sad, discouraged, and hopeless. These individuals lose interest in activities once enjoyed, often experience a decrease in drives such as hunger and sex, and frequently doubt personal worth. Depressive disorders vary by degree, but this chapter highlights the most well-known: major depressive disorder (sometimes called unipolar depression).

Bipolar and related disorders are a group of disorders in which mania is the defining feature. Mania is a state of extreme elation and agitation. When people experience mania, they may become extremely talkative, behave recklessly, or attempt to take on many tasks simultaneously. The most recognized of these disorders is bipolar disorder.

Major Depressive Disorder

According to the DSM-5, the defining symptoms of major depressive disorder include “depressed mood most of the day, nearly every day” (feeling sad, empty, hopeless, or appearing tearful to others), and loss of interest and pleasure in usual activities (APA, 2013). In addition to feeling overwhelmingly sad most of each day, people with depression will no longer show interest or enjoyment in activities that previously were gratifying, such as hobbies, sports, sex, social events, time spent with family, and so on. Friends and family members may notice that the person has completely abandoned previously enjoyed hobbies; for example, an avid tennis player who develops major depressive disorder no longer plays tennis (Rothschild, 1999).

To receive a diagnosis of major depressive disorder, a person must, for at least two weeks, have a depressed mood and/or a loss of interest or pleasure in most activities. In addition, the person will show signs and symptoms of several of the following: significant weight loss or weight gain, insomnia or hypersomnia, psychomotor agitation (such as fidgeting, inability to sit, pacing, hand-wringing) or psychomotor retardation (such as talking and moving slowly), fatigue, feelings of worthlessness or guilt, difficulty concentrating or indecisiveness, and suicidal ideation .

Major depressive disorder is considered episodic: its symptoms are typically present at their full magnitude for a certain period of time and then gradually abate. Approximately 50%–60% of people who experience an episode of major depressive disorder will have a second episode at some point in the future; those who have had two episodes have a 70% chance of having a third episode, and those who have had three episodes have a 90% chance of having a fourth episode (Rothschild, 1999). Although the episodes can last for months, a majority of people diagnosed with this condition (around 70%) recover within a year. However, a substantial number do not recover; around 12% show serious signs of impairment associated with major depressive disorder after 5 years (Boland & Keller, 2009). In the long-term, many who do recover will still show minor symptoms that fluctuate in their severity (Judd, 2012).

Results of Major Depressive Disorder

Major depressive disorder is a serious and incapacitating condition that can have a devastating effect on the quality of one’s life. The person suffering from this disorder lives a profoundly miserable existence that often results in unavailability for work or education, abandonment of promising careers, and lost wages; occasionally, the condition requires hospitalization. The majority of those with major depressive disorder report having faced some kind of discrimination, and many report that having received such treatment has stopped them from initiating close relationships, applying for jobs for which they are qualified, and applying for education or training (Lasalvia et al., 2013). Major depressive disorder also takes a toll on health. Depression is a risk factor for the development of heart disease in healthy patients, as well as adverse cardiovascular outcomes in patients with preexisting heart disease (Whooley, 2006).

Risk Factors for Major Depressive Disorder

Major depressive disorder is often referred to as the common cold of psychiatric disorders. Around 6.6% of the U.S. population experiences major depressive disorder each year; 16.9% will experience the disorder during their lifetime (Kessler & Wang, 2009). It is more common among women than among men, affecting approximately 20% of women and 13% of men at some point in their life (National Comorbidity Survey, 2007). The greater risk among women is not accounted for by a tendency to report symptoms or to seek help more readily, suggesting that gender differences in the rates of major depressive disorder may reflect biological and gender-related environmental experiences (Kessler, 2003).

Lifetime rates of major depressive disorder tend to be highest in North and South America, Europe, and Australia; they are considerably lower in Asian countries (Hasin, Fenton, & Weissman, 2011). The rates of major depressive disorder are higher among younger age cohorts than among older cohorts, perhaps because people in younger age cohorts are more willing to admit depression (Kessler & Wang, 2009).

A number of risk factors are associated with major depressive disorder: unemployment (including homemakers); earning less than $20,000 per year; living in urban areas; or being separated, divorced, or widowed (Hasin et al., 2011). Comorbid disorders include anxiety disorders and substance abuse disorders (Kessler & Wang, 2009).

Subtypes of Depression

The DSM-5 lists several different subtypes of depression. These subtypes—what the DSM-5 refer to as specifiers—are not specific disorders; rather, they are labels used to indicate specific patterns of symptoms or to specify certain periods of time in which the symptoms may be present. One subtype, seasonal pattern , applies to situations in which a person experiences the symptoms of major depressive disorder only during a particular time of year (e.g., fall or winter). In everyday language, people often refer to this subtype as the winter blues.

Another subtype, peripartum onset (commonly referred to as postpartum depression ), applies to women who experience major depression during pregnancy or in the four weeks following the birth of their child (APA, 2013). These women often feel very anxious and may even have panic attacks. They may feel guilty, agitated, and be weepy. They may not want to hold or care for their newborn, even in cases in which the pregnancy was desired and intended. In extreme cases, the mother may have feelings of wanting to harm her child or herself. In a horrific illustration, a woman named Andrea Yates, who suffered from extreme peripartum-onset depression (as well as other mental illnesses), drowned her five children in a bathtub (Roche, 2002). Most women with peripartum-onset depression do not physically harm their children, but most do have difficulty being adequate caregivers (Fields, 2010). A surprisingly high number of women experience symptoms of peripartum-onset depression. A study of 10,000 women who had recently given birth found that 14% screened positive for peripartum-onset depression, and that nearly 20% reported having thoughts of wanting to harm themselves (Wisner et al., 2013).

People with persistent depressive disorder (previously known as dysthymia) experience depressed moods most of the day nearly every day for at least two years, as well as at least two of the other symptoms of major depressive disorder. People with persistent depressive disorder are chronically sad and melancholy, but do not meet all the criteria for major depression. However, episodes of full-blown major depressive disorder can occur during persistent depressive disorder (APA, 2013).

Bipolar Disorder

A person with bipolar disorder (commonly known as manic depression ) often experiences mood states that vacillate between depression and mania; that is, the person’s mood is said to alternate from one emotional extreme to the other (in contrast to unipolar, which indicates a persistently sad mood).

To be diagnosed with bipolar disorder, a person must have experienced a manic episode at least once in their life; although major depressive episodes are common in bipolar disorder, they are not required for a diagnosis (APA, 2013). According to the DSM-5, a manic episode is characterized as a “distinct period of abnormally and persistently elevated, expansive, or irritable mood and abnormally and persistently increased activity or energy lasting at least one week,” that lasts most of the time each day (APA, 2013, p. 124). During a manic episode, some experience a mood that is almost euphoric and become excessively talkative, sometimes spontaneously starting conversations with strangers; others become excessively irritable and complain or make hostile comments. The person may talk loudly and rapidly, exhibiting flight of ideas , abruptly switching from one topic to another. These individuals are easily distracted, which can make a conversation very difficult. They may exhibit grandiosity, in which they experience inflated but unjustified self-esteem and self-confidence. For example, they might quit a job in order to “strike it rich” in the stock market, despite lacking the knowledge, experience, and capital for such an endeavor. They may take on several tasks at the same time (e.g., several time-consuming projects at work) and yet show little, if any, need for sleep; some may go for days without sleep. Patients may also recklessly engage in pleasurable activities that could have harmful consequences, including spending sprees, reckless driving, making foolish investments, excessive gambling, or engaging in sexual encounters with strangers (APA, 2013).

During a manic episode, individuals usually feel as though they are not ill and do not need treatment. However, the reckless behaviors that often accompany these episodes—which can be antisocial, illegal, or physically threatening to others—may require involuntary hospitalization (APA, 2013). Some patients with bipolar disorder will experience a rapid-cycling subtype, which is characterized by at least four manic episodes (or some combination of at least four manic and major depressive episodes) within one year.

Link to Learning

In the 1997 independent film Sweetheart , actress Janeane Garofalo plays the part of Jasmine, a young woman with bipolar disorder. Watch this firsthand account from a person living with bipolar disorder to learn more.

Risk Factors for Bipolar Disorder

Bipolar disorder is considerably less frequent than major depressive disorder. In the United States, 1 out of every 167 people meets the criteria for bipolar disorder each year, and 1 out of 100 meet the criteria within their lifetime (Merikangas et al., 2011). The rates are higher in men than in women, and about half of those with this disorder report onset before the age of 25 (Merikangas et al., 2011). Around 90% of those with bipolar disorder have a comorbid disorder, most often an anxiety disorder or a substance abuse problem. Unfortunately, close to half of the people suffering from bipolar disorder do not receive treatment (Merikangas & Tohen, 2011). Suicide rates are extremely high among those with bipolar disorder: around 36% of individuals with this disorder attempt suicide at least once in their lifetime (Novick, Swartz, & Frank, 2010), and between 15%–19% die by suicide (Newman, 2004).

The Biological Basis of Mood and Bipolar Disorders

Mood disorders have been shown to have a strong genetic and biological basis. Relatives of those with major depressive disorder have double the risk of developing major depressive disorder, whereas relatives of patients with bipolar disorder have over nine times the risk (Merikangas et al., 2011). The rate of concordance for major depressive disorder is higher among identical twins than fraternal twins (50% vs. 38%, respectively), as is that of bipolar disorder (67% vs. 16%, respectively), suggesting that genetic factors play a stronger role in bipolar disorder than in major depressive disorder (Merikangas et al. 2011).

People with mood disorders often have imbalances in certain neurotransmitters, particularly norepinephrine and serotonin (Thase, 2009). These neurotransmitters are important regulators of the bodily functions that are disrupted in mood disorders, including appetite, sex drive, sleep, arousal, and mood. Medications that are used to treat major depressive disorder typically boost serotonin and norepinephrine activity, whereas lithium—used in the treatment of bipolar disorder—blocks norepinephrine activity at the synapses ( Figure 15.16 ).

Depression is linked to abnormal activity in several regions of the brain (Fitzgerald, Laird, Maller, & Daskalakis, 2008) including those important in assessing the emotional significance of stimuli and experiencing emotions (amygdala), and in regulating and controlling emotions (like the prefrontal cortex, or PFC) (LeMoult, Castonguay, Joormann, & McAleavey, 2013). People with depression show elevated amygdala activity (Drevets, Bogers, & Raichle, 2002), especially when presented with negative emotional stimuli, such as photos of sad faces ( Figure 15.17 ) (Surguladze et al., 2005). Interestingly, heightened amygdala activation to negative emotional stimuli among depressed persons occurs even when stimuli are presented outside of conscious awareness (Victor, Furey, Fromm, Öhman, & Drevets, 2010), and it persists even after the negative emotional stimuli are no longer present (Siegle, Thompson, Carter, Steinhauer, & Thase, 2007). Additionally, depressed individuals exhibit less activation in the prefrontal, particularly on the left side (Davidson, Pizzagalli, & Nitschke, 2009). Because the PFC can dampen amygdala activation, thereby enabling one to suppress negative emotions (Phan et al., 2005), decreased activation in certain regions of the PFC may inhibit its ability to override negative emotions that might then lead to more negative mood states (Davidson et al., 2009). These findings suggest that people with depression are more prone to react to emotionally negative stimuli, yet have greater difficulty controlling these reactions.

Since the 1950s, researchers have noted that depressed individuals have abnormal levels of cortisol, a stress hormone released into the blood by the neuroendocrine system during times of stress (Mackin & Young, 2004). When cortisol is released, the body initiates a fight-or-flight response in reaction to a threat or danger. Many people with depression show elevated cortisol levels (Holsboer & Ising, 2010), especially those reporting a history of early life trauma such as the loss of a parent or abuse during childhood (Baes, Tofoli, Martins, & Juruena, 2012). Such findings raise the question of whether high cortisol levels are a cause or a consequence of depression. High levels of cortisol are a risk factor for future depression (Halligan, Herbert, Goodyer, & Murray, 2007), and cortisol activates activity in the amygdala while deactivating activity in the PFC (McEwen, 2005)—both brain disturbances are connected to depression. Thus, high cortisol levels may have a causal effect on depression, as well as on its brain function abnormalities (van Praag, 2005). Also, because stress results in increased cortisol release (Michaud, Matheson, Kelly, Anisman, 2008), it is equally reasonable to assume that stress may precipitate depression.

A Diathesis-Stress Model and Major Depressive Disorders

Indeed, it has long been believed that stressful life events can trigger depression, and research has consistently supported this conclusion (Mazure, 1998). Stressful life events include significant losses, such as death of a loved one, divorce or separation, and serious health and money problems; life events such as these often precede the onset of depressive episodes (Brown & Harris, 1989). In particular, exit events—instances in which an important person departs (e.g., a death, divorce or separation, or a family member leaving home)—often occur prior to an episode (Paykel, 2003). Exit events are especially likely to trigger depression if these happenings occur in a way that humiliates or devalues the individual. For example, people who experience the breakup of a relationship initiated by the other person develop major depressive disorder at a rate more than 2 times that of people who experience the death of a loved one (Kendler, Hettema, Butera, Gardner, & Prescott, 2003).

Likewise, individuals who are exposed to traumatic stress during childhood—such as separation from a parent, family turmoil, and maltreatment (physical or sexual abuse)—are at a heightened risk of developing depression at any point in their lives (Kessler, 1997). A recent review of 16 studies involving over 23,000 subjects concluded that those who experience childhood maltreatment are more than 2 times as likely to develop recurring and persistent depression (Nanni, Uher, & Danese, 2012).

Of course, not everyone who experiences stressful life events or childhood adversities succumbs to depression—indeed, most do not. Clearly, a diathesis-stress interpretation of major depressive disorder, in which certain predispositions or vulnerability factors influence one’s reaction to stress, would seem logical. If so, what might such predispositions be? A study by Caspi and others (2003) suggests that an alteration in a specific gene that regulates serotonin (the 5-HTTLPR gene) might be one culprit. These investigators found that people who experienced several stressful life events were significantly more likely to experience episodes of major depression if they carried one or two short versions of this gene than if they carried two long versions. Those who carried one or two short versions of the 5-HTTLPR gene were unlikely to experience an episode, however, if they had experienced few or no stressful life events. Numerous studies have replicated these findings, including studies of people who experienced maltreatment during childhood (Goodman & Brand, 2009). In a recent investigation conducted in the United Kingdom (Brown & Harris, 2013), researchers found that childhood maltreatment before age 9 elevated the risk of chronic adult depression (a depression episode lasting for at least 12 months) among those individuals having one (LS) or two (SS) short versions of the 5-HTTLPR gene ( Figure 15.18 ). Childhood maltreatment did not increase the risk for chronic depression for those have two long (LL) versions of this gene. Thus, genetic vulnerability may be one mechanism through which stress potentially leads to depression.

Cognitive Theories of Depression

Cognitive theories of depression take the view that depression is triggered by negative thoughts, interpretations, self-evaluations, and expectations (Joormann, 2009). These diathesis-stress models propose that depression is triggered by a “cognitive vulnerability” (negative and maladaptive thinking) and by precipitating stressful life events (Gotlib & Joormann, 2010). Perhaps the most well-known cognitive theory of depression was developed in the 1960s by psychiatrist Aaron Beck, based on clinical observations and supported by research (Beck, 2008). Beck theorized that depression-prone people possess depressive schemas, or mental predispositions to think about most things in a negative way (Beck, 1976). Depressive schemas contain themes of loss, failure, rejection, worthlessness, and inadequacy, and may develop early in childhood in response to adverse experiences, then remain dormant until they are activated by stressful or negative life events. Depressive schemas prompt dysfunctional and pessimistic thoughts about the self, the world, and the future. Beck believed that this dysfunctional style of thinking is maintained by cognitive biases, or errors in how we process information about ourselves, which lead us to focus on negative aspects of experiences, interpret things negatively, and block positive memories (Beck, 2008). A person whose depressive schema consists of a theme of rejection might be overly attentive to social cues of rejection (more likely to notice another’s frown), and they might interpret this cue as a sign of rejection and automatically remember past incidents of rejection. Longitudinal studies have supported Beck’s theory, in showing that a preexisting tendency to engage in this negative, self-defeating style of thinking—when combined with life stress—over time predicts the onset of depression (Dozois & Beck, 2008). Cognitive therapies for depression, aimed at changing a depressed person’s negative thinking, were developed as an expansion of this theory (Beck, 1976).

Another cognitive theory of depression, hopelessness theory , postulates that a particular style of negative thinking leads to a sense of hopelessness, which then leads to depression (Abramson, Metalsky, & Alloy, 1989). According to this theory, hopelessness is an expectation that unpleasant outcomes will occur or that desired outcomes will not occur, and there is nothing one can do to prevent such outcomes. A key assumption of this theory is that hopelessness stems from a tendency to perceive negative life events as having stable (“It’s never going to change”) and global (“It’s going to affect my whole life”) causes, in contrast to unstable (“It’s fixable”) and specific (“It applies only to this particular situation”) causes, especially if these negative life events occur in important life realms, such as relationships, academic achievement, and the like. Suppose a student who wishes to go to law school does poorly on an admissions test. If the student infers negative life events as having stable and global causes, they may believe that their poor performance has a stable and global cause (“I lack intelligence, and it’s going to prevent me from ever finding a meaningful career”), as opposed to an unstable and specific cause (“I was sick the day of the exam, so my low score was a fluke”). Hopelessness theory predicts that people who exhibit this cognitive style in response to undesirable life events will view such events as having negative implications for their future and self-worth, thereby increasing the likelihood of hopelessness—the primary cause of depression (Abramson et al., 1989). One study testing hopelessness theory measured the tendency to make negative inferences for bad life effects in participants who were experiencing uncontrollable stressors. Over the ensuing six months, those with scores reflecting high cognitive vulnerability were 7 times more likely to develop depression compared to those with lower scores (Kleim, Gonzalo, & Ehlers, 2011).

A third cognitive theory of depression focuses on how people’s thoughts about their distressed moods—depressed symptoms in particular—can increase the risk and duration of depression. This theory, which focuses on rumination in the development of depression, was first described in the late 1980s to explain the higher rates of depression in women than in men (Nolen-Hoeksema, 1987). Rumination is the repetitive and passive focus on the fact that one is depressed and dwelling on depressed symptoms, rather that distracting one’s self from the symptoms or attempting to address them in an active, problem-solving manner (Nolen-Hoeksema, 1991). When people ruminate, they have thoughts such as “Why am I so unmotivated? I just can’t get going. I’m never going to get my work done feeling this way” (Nolen-Hoeksema & Hilt, 2009, p. 393). Women are more likely than men to ruminate when they are sad or depressed (Butler & Nolen-Hoeksema, 1994), and the tendency to ruminate is associated with increases in depression symptoms (Nolen-Hoeksema, Larson, & Grayson, 1999), heightened risk of major depressive episodes (Abela & Hankin, 2011), and chronicity of such episodes (Robinson & Alloy, 2003)

For some people with mood disorders, the extreme emotional pain they experience becomes unendurable. Overwhelmed by hopelessness, devastated by incapacitating feelings of worthlessness, and burdened with the inability to adequately cope with such feelings, they may consider suicide to be a reasonable way out. Suicide , defined by the CDC as “death caused by self-directed injurious behavior with any intent to die as the result of the behavior” (CDC, 2013a), in a sense represents an outcome of several things going wrong all at the same time (Crosby, Ortega, & Melanson, 2011). Not only must the person be biologically or psychologically vulnerable, but they must also have the means to perform the suicidal act, and they must lack the necessary protective factors (e.g., social support from friends and family, religion, coping skills, and problem-solving skills) that provide comfort and enable one to cope during times of crisis or great psychological pain (Berman, 2009).

Suicide is not listed as a disorder in the DSM-5; however, people with a mental disorder—especially a mood disorder—have the greatest risk for suicide. Around 90% of those who die by suicide have a diagnosis of at least one mental disorder, with mood disorders being the most frequent (Fleischman, Bertolote, Belfer, & Beautrais, 2005). In fact, the association between major depressive disorder and suicide is so strong that one of the criteria for the disorder is thoughts of suicide, as discussed above (APA, 2013).

Suicide rates can be difficult to interpret because some deaths that appear to be accidental may in fact be acts of suicide (e.g., automobile crash). Nevertheless, investigations into U.S. suicide rates have uncovered these facts:

• Suicide was the 10th leading cause of death for all ages in 2010 (Centers for Disease Control and Prevention [CDC], 2012).
• There were 38,364 suicides in 2010 in the United States—an average of 105 each day (CDC, 2012).
• Suicide among males is 4 times higher than among females and accounts for 79% of all suicides; firearms are the most commonly used method of suicide for males, whereas poisoning is the most commonly used method for females (CDC, 2012).
• From 1991 to 2003, suicide rates were consistently higher among those 65 years and older. Since 2001, however, suicide rates among those ages 25–64 have risen consistently, and, since 2006, suicide rates have been greater for those ages 65 and older (CDC, 2013b). This increase in suicide rates among middle-aged Americans has prompted concern in some quarters that baby boomers (individuals born between 1946–1964) who face economic worry and easy access to prescription medication may be particularly vulnerable to suicide (Parker-Pope, 2013).
• The highest rates of suicide within the United States are among American Indians/Alaskan natives and Non-Hispanic White people (CDC, 2013b).
• Suicide rates vary across the United States, with the highest rates consistently found in the mountain states of the west (Alaska, Montana, Nevada, Wyoming, Colorado, and Idaho) (Berman, 2009).

Contrary to popular belief, suicide rates peak during the springtime (April and May), not during the holiday season or winter. In fact, suicide rates are generally lowest during the winter months (Postolache et al., 2010).

Risk Factors For Suicide

Suicidal risk is especially high among people with substance use problems. Individuals with alcohol dependence are at 10 times greater risk for suicide than the general population (Wilcox, Conner, & Caine, 2004). The risk of suicidal behavior is especially high among those who have made a prior suicide attempt. Among those who attempt suicide, 16% make another attempt within a year and over 21% make another attempt within four years (Owens, Horrocks, & House, 2002). Suicidal individuals may be at high risk for terminating their life if they have a lethal means in which to act, such as a firearm in the home (Brent & Bridge, 2003). Withdrawal from social relationships, feeling as though one is a burden to others, and engaging in reckless and risk-taking behaviors may be precursors to suicidal behavior (Berman, 2009). A sense of entrapment or feeling unable to escape one’s miserable feelings or external circumstances (e.g., an abusive relationship with no perceived way out) predicts suicidal behavior (O’Connor, Smyth, Ferguson, Ryan, & Williams, 2013). Tragically, reports of suicides among adolescents following instances of cyberbullying have emerged in recent years. In one widely-publicized case a few years ago, Phoebe Prince, a 15-year-old Massachusetts high school student, died by suicide following incessant harassment and taunting from her classmates via texting and Facebook (McCabe, 2010).

Suicides can have a contagious effect on people. For example, another’s suicide, especially that of a family member, heightens one’s risk of suicide (Agerbo, Nordentoft, & Mortensen, 2002). Additionally, widely-publicized suicides tend to trigger additional suicides in some individuals. One study examining suicide statistics in the United States from 1947–1967 found that the rates of suicide increased significantly for the first month after a report about suicide was printed on the front page of the New York Times (Phillips, 1974). Austrian researchers found a significant increase in the number of suicides by firearms in the three weeks following extensive reports in Austria’s largest newspaper of a celebrity suicide by gun (Etzersdorfer, Voracek, & Sonneck, 2004). A review of 42 studies concluded that media coverage of celebrity suicides is more than 14 times more likely to trigger copycat suicides than is coverage of non-celebrity suicides (Stack, 2000). This review also demonstrated that the medium of coverage is important: televised stories are considerably less likely to prompt a surge in suicides than are newspaper stories. Research suggests that a trend appears to be emerging whereby people use online social media to leave suicide notes, although it is not clear to what extent suicide notes on such media might induce subsequent suicides (Ruder, Hatch, Ampanozi, Thali, & Fischer, 2011). Nevertheless, it is reasonable to conjecture that suicide notes left by individuals on social media may influence the decisions of other vulnerable people who encounter them (Luxton, June, & Fairall, 2012).

One possible contributing factor in suicide is brain chemistry. Contemporary neurological research shows that disturbances in the functioning of serotonin are linked to suicidal behavior (Pompili et al., 2010). Low levels of serotonin predict future suicide attempts and death by suicide, and low levels have been observed post-mortem among suicide victims (Mann, 2003). Serotonin dysfunction, as noted earlier, is also known to play an important role in depression; low levels of serotonin have also been linked to aggression and impulsivity (Stanley et al., 2000). The combination of these three characteristics constitutes a potential formula for suicide—especially violent suicide. A classic study conducted during the 1970s found that patients with major depressive disorder who had very low levels of serotonin attempted suicide more frequently and more violently than did patients with higher levels (Asberg, Thorén, Träskman, Bertilsson, & Ringberger, 1976; Mann, 2003).

Suicidal thoughts, plans, and even off-hand remarks (“I might kill myself this afternoon”) should always be taken extremely seriously. People who contemplate terminating their life need immediate help. Below is a link to an excellent website that contains resources (including hotlines) for people who are struggling with suicidal ideation, have loved ones who may be suicidal, or who have lost loved ones to suicide: http://www.afsp.org . You can also contact the 24-hour National Suicide Prevention Hotline by calling 1-800-273-8255 or texting HELLO to 741741 to access their Crisis Text Line.

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• Research article
• Open access
• Published: 29 March 2017

Parental separation in childhood as a risk factor for depression in adulthood: a community-based study of adolescents screened for depression and followed up after 15 years

• Hannes Bohman 1 , 2 , 3 , 4 ,
• Sara Brolin Låftman 5 ,
• Aivar Päären 1 &
• Ulf Jonsson 1 , 3  

BMC Psychiatry volume  17 , Article number:  117 ( 2017 ) Cite this article

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Earlier research has investigated the association between parental separation and long-term health outcomes among offspring, but few studies have assessed the potentially moderating role of mental health status in adolescence. The aim of this study was to analyze whether parental separation in childhood predicts depression in adulthood and whether the pattern differs between individuals with and without earlier depression.

A community-based sample of individuals with adolescent depression in 1991–93 and matched non-depressed peers were followed up using a structured diagnostic interview after 15 years. The participation rate was 65% (depressed n  = 227; non-depressed controls n  = 155). Information on parental separation and conditions in childhood and adolescence was collected at baseline. The outcome was depression between the ages 19–31 years; information on depression was collected at the follow-up diagnostic interview. The statistical method used was binary logistic regression.

Our analyses showed that depressed adolescents with separated parents had an excess risk of recurrence of depression in adulthood, compared with depressed adolescents with non-separated parents. In addition, among adolescents with depression, parental separation was associated with an increased risk of a switch to bipolar disorder in adulthood. Among the matched non-depressed peers, no associations between parental separation and adult depression or bipolar disorder were found.

Conclusions

Parental separation may have long-lasting health consequences for vulnerable individuals who suffer from mental illness already in adolescence.

Peer Review reports

Numerous cross-sectional studies have shown that children who do not live with two original parents in the same household report poorer mental health outcomes compared with their peers in nuclear families [ 1 – 3 ], although the overall effect sizes are rather small [ 4 ]. Prospective studies of the association between parental separation in childhood and later mental health have demonstrated that individuals with separated parents are more likely to suffer from adverse mental health outcomes in adulthood [ 5 – 10 ]. There are however also studies that do not show such a relationship. One Swedish prospective study demonstrated that individuals with divorced parents were more likely to appear in child and adolescent psychiatric care compared with their peers with non-divorced parents, but that there was no difference between the groups with regard to adult psychiatric care [ 11 ]. Another study by the same authors did not find any overall differences in depression and anxiety in adulthood between individuals whose parents had divorced in childhood and the comparison group of individuals with continuously married parents [ 12 ]. Thus, empirical findings concerning parental divorce in childhood and later mental health outcomes are not fully consistent. As underscored in a review by Hetherington and Stanley-Hagan [ 13 ], however, the effects of parental divorce in childhood may differ between individuals. Some children are more vulnerable while others are more resilient, where resilience is thought to be a function of several factors including the characteristics of the child, the family, and the surrounding environment. As a matter of fact, Di Manno et al. [ 14 ] call for more studies on moderating effects of parental divorce and offspring mental health and claim that “investigations of moderation are in their infancy and further research is needed to understand the varying trajectories of mental health outcomes, specifically depression and depressive symptoms, of children of divorced parents.” (Di Manno et al. [ 14 ], p. 78). We argue that one potentially important vulnerability factor to consider is whether the child suffers or has previously suffered from mental disorders like depression. Depressive disorders are common in adolescence with a one-year prevalence of 5–8% [ 15 ]. Depressive disorders are also a major contributor to the global burden of disease [ 16 ], and among 15- to 19-year-old males and females, depression is the most important cause of disability-adjusted life-years (DALYs) [ 17 ] and thus of major public health concern.

Any association between parental separation and poorer mental health (short- and long-term) among offspring could be caused by several mechanisms, including factors both preceding and following the actual separation. One potential mechanism is inter-parental conflict, and indeed, Olsson [ 15 ] demonstrated that the association between parental separation and adolescent depression was accounted for by inter-parental conflict. Analyses of large-scale survey data have shown that severe dissension in the childhood family is more commonly reported by individuals who experienced their parents’ separation than by those who grew up in nuclear families, and that it contributes to explaining the adverse mental health of the former group [ 18 ]. In addition, studies have shown that separated parents are more likely to have poorer relations with their children compared with those who are continuously married, supposedly as an effect of the stress linked with the separation as such or with single parenthood [ 4 ]. Poorer parental relations, in turn, have been linked to poorer mental health among offspring [ 19 ]. Furthermore, parental separation often involves a loss of resources for children, particularly for those who continue to live with only one parent. Accordingly, absolute poverty in terms of low income standard is more common among children in single-parent households than among those in two-parent families [ 20 ]. Studies have shown that economic strain following a divorce is linked to adverse outcomes among children [ 4 ]. Furthermore, parental separation can lead to residential moves, which for the children may entail entering a new school and having to make new friends in an already stressful situation [ 13 ]. Indeed, changing schools has been shown to be linked with an increased risk of adverse mental health [ 21 ]. Unsurprisingly, studies have shown that it is more common for individuals with separated parents to have moved during childhood [ 12 , 18 ]. Finally, the parents’ mental health should be considered. Marital distress and depression frequently co-occur, and it has been reported that the interaction of couples with a depressed partner is characterized by a higher frequency of negative communication and a lower frequency of positive communication [ 22 ]. Given that people with depression are more likely to divorce [ 23 ], and that parental psychopathology is a risk factor for mental disorders among offspring [ 24 ], any association between divorce and depression among offspring may partly be attributable to the heritability of depression. In addition, adults who have divorced tend to report poorer well-being compared with those who are continuously married [ 4 ]. This may negatively affect their ability to provide various kinds of social support to their children, with potentially negative implications for their children’s well-being. To conclude, as pointed out in the recent review by Di Manno et al. [ 14 ], it is important to investigate different types of moderating effects of parental separation on later depression. In the present study we focus on adolescent depression as a potential moderator.

Aim of the study

The aim of the present study was to analyze whether the experience of parental separation in childhood predicts major depression in adulthood; and more specifically whether the association between parental separation and later major depression differs among individuals with and without adolescent depression. To assess the extent to which any possible associations were accounted for by potential covariates, we adjusted for conflicts between and with parents, economic strain, family moves, and parental depression.

We formulated the following hypotheses:

H1. The experience of parental separation predicts adult depression.

H2. The association between the experience of parental separation in childhood and depression in adulthood is more prominent among individuals who had suffered from adolescent depression than among individuals without adolescent depression.

H3. The association between the experience of parental separation and adult depression is (at least partly) accounted for by major conflicts between parents, major conflicts with parents, economic strain, family moves, and parental depression.

Study population and procedure

The data come from a study of adolescent depression conducted in the town of Uppsala, Sweden, in 1991–1992. The purpose of the project was to investigate the prevalence of depression in a certain population and set up a case–control study based on a screening of a depression. Accordingly, all students in the first year of upper secondary school (ages 16–17 years) and school dropouts of the same age group were invited to participate in a screening for depression. Of 2,465 individuals, 2,300 (93%) participated in the screening. Two self-evaluations of depression were used: the Beck Depression Inventory-Child [ 25 ] and the Centre for Epidemiological Studies-Depression Scale for Children [ 26 ]. Adolescents with high scores (BDI-C ≥ 16 or CES-DC ≥ 30) or who reported a suicide attempt were interviewed diagnostically using the revised adolescent version of the Diagnostic Interview for Children and Adolescents (DICA-R-A) according to the DSM-III-R criteria [ 27 ]. From individuals with scores under the cut-off (i.e. BDI-C < 16 and CES-DC < 30), a control group was created from an equal number of peers who were matched for sex, age, and school class, and was also diagnostically interviewed in the same manner, using the DICA-R-A. In total, 307 adolescents with depressive symptoms and 302 non-depressed controls were interviewed and consented to be contacted for follow-up. All interviews were conducted face to face by in total six persons (specialists in child psychiatry and psychology students) [ 28 ]. Comorbidity was common among the depressed (87% had also other diagnoses than depression, the most common ones being anxiety disorders, specific phobia, and conduct disorders) but less common among the non-depressed (33% had a diagnosis, the most common diagnosis being specific phobia) [ 29 ].

The participants also completed the Children’s Life Events Inventory [ 30 ], which includes questions on life events related to the individual’s family and social situation. More information on the original baseline study, including characteristics of participants and of those who did not participate, can be found elsewhere [ 15 , 31 ].

After 15 years, the depressed and non-depressed adolescents who had participated in the diagnostic interview as well as consented to participate in a follow-up study were contacted for a follow-up evaluation. This evaluation included the structured diagnostic interview Mini International Neuropsychiatric Interview Plus (M.I.N.I.) [ 32 ]. The follow-up interviews were conducted by a clinical psychologist, a psychiatrist, and three students in clinical psychology, who did not know whether the participants belonged to the depressed or the non-depressed control group (free-marginal Kappa of 0.93). A total of 409 of the 609 participants were re-interviewed (67%). Of all interviews, 81% were conducted face to face and 19% by telephone. For more information on the follow-up study, including details on participants and reasons for non-participation, see Jonsson et al. [ 33 ].

The present analyses are based on the 409 participants who participated in the follow-up. Participants with no identified depressive disorder or elevated depressive symptoms in adolescence were grouped together, while participants with an identified depressive disorder or elevated depressive symptoms were grouped together. The diagnostic interview in adolescence identified a previous depressive disorder before age 16 in a total of 44 of the non-depressed controls that were followed up, and these controls were accordingly transferred to the depression group. Participants with mania or hypomania in adolescence ( n  = 27) were excluded from the analyses because the etiology and mental health trajectory of bipolar disorder can differ from that of depressive disorders. Thus, the present study included 382 individuals; more specifically 227 individuals with prior depression and 155 non-depressed controls without prior depression or depressive symptoms. Figure  1 provides a description of the data collection procedure at baseline and at follow-up.

Chart outlining the data collection procedure at baseline (in adolescence) and at follow-up (in adulthood)

The dependent variable was major depression in adulthood , based on information gathered at the follow-up diagnostic interview through M.I.N.I. [ 32 ]. Major depression was a dichotomous measure indicating whether or not the individual had suffered from one or more major depressive episodes between age 19 and approximately 31. We also conducted additional analyses of a number of other DSM-IV mental disorders assessed at follow-up through M.I.N.I.: bipolar disorder, anxiety disorder , somatoform disorder , alcohol abuse , drug abuse , and psychotic episodes (referring to the period from age 19 and until approximately 31, with the exceptions of somatoform disorders and some anxiety disorders which only covered the time at the follow-up).

The independent variables were constructed from information collected through the Children’s Life Events Inventory [ 30 ] in the baseline investigation. The main independent variable of interest was parental separation , based on questions asking whether the parents had moved apart and whether the parents had divorced. For both questions, the respondents were asked to reply whether this had happened during the past year or earlier in life. Participants who had reported that parents had moved apart or divorced (at any time point) were coded as having separated parents. Potential covariates that were included were major conflicts between parents; major conflicts with parents; family income reduced considerably; and family moved to another city. For each of these life events as well, participants were asked whether it had happened during the past year or earlier in life. We combined the answers to create binary measures of whether or not each life event had happened at all. Parental depression was recorded from the follow-up interview, more specifically from a constructed standardized interview that recorded different psychiatric diagnoses in close relatives, reported by the person interviewed and was coded as at least one parent having suffered from depression.

We also assessed the significance of parental remarriage , based on information from the Children’s Life Events Inventory [ 30 ] (whether, among individuals with separated parents, the mother and/or the father had remarried or had a new live-in partner). Long-term depression (depression most of the last year) and somatic symptoms (≥5 somatic symptoms according to the Somatic Symptom Checklist Instrument [ 34 ] – which from our earlier studies were shown to be important predictors of depression in adulthood [ 33 , 35 ] – were included as markers of severity of the depression in adolescence.

Statistical method

Chi-square tests were used to assess differences between groups. T -test was used to compare mean values. To adjust for potential confounders we conducted binary logistic regression models. To compare differences between individuals with and without separated parents, logit coefficients as well as odds ratios are presented. Since it is problematic to compare estimates from logistic regression analyses across models [ 36 ], as a sensitivity check we also conducted linear probability models (i.e. linear regression analyses of a dichotomous outcome), resulting in patterns similar to the ones presented (results available upon request).

Descriptives

Descriptive statistics of the data are presented in Table  1 , separately for the non-depressed control group and the depressed group (henceforth “non-depressed controls” and “depressed,” respectively). Differences between the two groups were assessed by chi-square tests. The shares of males and females were similar in both groups. Parental separation, major conflicts between parents and with parents, and having had a considerably reduced family income, were more commonly experienced by adolescents with depression than by the non-depressed controls. Parental depression was also more common among adolescents with depression. In adulthood, experiences of major depression were more common among individuals with adolescent depression than among non-depressed controls.

Next, the covariates at baseline and depression in adulthood among non-depressed controls and depressed respectively, are demonstrated by parental separation in childhood (Table  2 ). Among both non-depressed controls and depressed, major conflicts between parents in childhood were significantly more frequent among those with separated parents. Major conflicts with parents in childhood were also more frequent among those with separated parents than among those whose parents were not separated, although the difference was statistically significant only in the depressed group. Among both non-depressed controls and depressed, those with separated parents to a greater extent reported that their family income had been considerably reduced, compared with participants whose parents were not separated. Neither among non-depressed controls nor among depressed were there any significant differences in family moved to another city or in parental depression by parental separation. With regard to depression in adulthood, the prevalence among non-depressed controls did not differ by parental separation. Among participants who had suffered from adolescent depression, however, adult depression was significantly more common among those with separated parents in childhood (68.1%) than among those whose parents had not separated (53.4%). We also checked whether the severity of depression in adolescence, as indicated by long-term depression and by somatic symptoms, differed by parental separation among the individuals in the depressed group. This did not turn out to be the case, as 39.9% of those with non-separated parents and 40.4% of those with separated parents suffered from long-term depression ( p  = 0.931); and those with non-separated parents had on average 2.87 somatic symptoms compared with 2.97 symptoms among those with separated parents ( p  = 0.774) (data not shown).

Parental separation and depression at baseline

In Table  3 , associations between parental separation and adolescent depression (i.e., depression at baseline) are presented. Logit coefficients and their standard errors, p-values, and odds ratios with 95% confidence intervals from binary logistic regressions are displayed, with “group” as the dependent variable (0 = non-depressed controls; 1 = depressed). Model 1 shows an excess risk of adolescent depression for those with separated parents (OR = 1.90, p  = 0.004). When including potential covariates, it is seen that major conflicts between parents account for a rather substantial part of the association (Model 2). The association is attenuated somewhat also when including major conflicts with parents (Model 3), family income considerably reduced (Model 4), family moved to another city (although to a very minor extent) (Model 5), and parental depression (Model 6). When including all the potential covariates simultaneously (Model 7), the estimate of parental separation is attenuated and non-significant (OR 1.22, p  = 0.428). All the included covariates except for family moves were significantly associated with depression at baseline (Models 2–6) but in the fully adjusted model (Model 7) only major conflicts between and with parents remained statistically significant. While the baseline investigation does provide information on whether the separation occurred during the past year or earlier in life, the limited number of cases in the former category prevents any meaningful analyses of time since parental separation. For adolescents whose parents separated last year ( n  = 13), we cannot rule out that some adolescent depression with very short duration may partly capture reactions of grief. Accordingly, we conducted sensitivity analyses where we excluded these individuals. The results were similar to the ones presented but with somewhat attenuated estimates for parental separation in all models (data not shown).

Parental separation and depression at follow-up

Results from the analyses of the associations between parental separation in childhood and depression in adulthood are displayed in Table  4 . Among the non-depressed controls, there was no significant association between parental divorce and adult depression (Model 1) (reflecting the descriptive statistics in Table  2 ) and the estimates did not change considerably when the covariates were included (Models 2–6). Among individuals with adolescent depression, however, there was an excess risk of adult depression among those whose parents were separated compared with those whose parents were not (Model 1, OR = 1.99, p  = 0.016). The association was not accounted for more than marginally by any of the potential covariates (Models 2–6). When adjusting simultaneously for all the potential covariates (Model 7), the odds ratio was attenuated and reached statistical significance only at the 10% level (OR = 1.74, p  = 0.081). Again, we performed sensitivity analyses where we excluded the 13 individuals whose parents separated the year before the baseline investigation, with results very similar to the ones demonstrated in Table  4 , with no visible attenuation (data not shown). Additional analyses of individuals with adolescent depression and separated parents (not shown) tested whether parental remarriage was associated with depression in adulthood. Results indicated a tendency for parental remarriage to be associated with a decreased risk of depression, although this was statistically significant at the 10% level only (OR = 0.41, p  = 0.092).

The purpose of the study was to assess whether there was an association between parental separation and depression in adulthood within the two studied groups, i.e., among the depressed and among the non-depressed controls, respectively. The analyses in Table  4 showed that parental separation was associated with depression in adulthood among the depressed but not among the non-depressed controls. In order to assess whether the association between parental separation and depression in adulthood also differed between these two groups, additional analyses (not shown) were performed. We performed logistic regression analyses of the pooled sample (i.e., the depressed and the non-depressed merged together) and tested for the interaction between adolescent depression and parental separation. The interaction term was borderline significant at the 5% level ( p  = 0.052) (data not shown).

Parental separation and other mental disorders at follow-up

It is possible that the experience of parental separation predicts other mental illnesses than depression. Accordingly, we conducted additional analyses of parental separation in childhood and bipolar disorder, anxiety disorder, somatoform disorder, alcohol and substance abuse as well as the occurrence of psychotic episodes in adulthood, among non-depressed controls and depressed, respectively (Table  5 ). The only detected statistically significant association indicated that among individuals who had suffered from depression in adolescence, there was an excess risk for bipolar disorders in adulthood (OR 2.37, p  = 0.048). The association was slightly attenuated and turned non-significant when adjusting for all the potential confounders (OR 2.18, p  = 0.103) (data not shown). In addition, a separate analysis (not shown) of the non-depressed controls who suffered from anxiety disorder in childhood or adolescence showed that parental separation was associated with a statistically significant excess risk of continuation of anxiety in adulthood. In this particular subgroup, 14.3% of those with non-separated parents and 60.0% of those with separated parents met the criteria for an anxiety disorder in adulthood ( p  = 0.019). Among adolescents with depression and anxiety, parental separation was not significantly associated with anxiety in adulthood ( p  = 0.335) (data not shown).

The aim of this study was to investigate whether parental separation in childhood was associated with major depression in adulthood. In order to assess whether such an association was particularly prominent among individuals who had suffered from depression in adolescence, we utilized data from a community-based study of adolescents with depression and non-depressed controls followed prospectively 15 years after baseline. The results showed that parental separation was not associated with an excess risk of depressive disorder among the non-depressed controls. However, among individuals who had suffered from depression in adolescence, parental separation was linked with an excess risk of recurrence of depression in adulthood, albeit with a moderate effect size. Thus, while the negative effects of parental divorce are relatively small on average [ 4 ], the present study shows that they may be greater for specific vulnerable groups and smaller or even non-existent for others.

While earlier studies of Swedish data found that, overall, parental divorce was not associated with later mental illness [ 12 ] or adult psychiatric care [ 11 ], the present study adds to the previous literature by assessing whether the “effect” of parental separation may differ between groups, as has been suggested [ 13 ]. The association between parental separation and depression in adulthood in this vulnerable group was only to a limited extent accounted for by potential covariates: conflicts between and with parents, that the family’s income had been considerably reduced, that the family had moved to another city, or that one or both parents had suffered from depression. Thus, there are probably other mechanisms that we were not able to include in the present study. We found that inter-parental conflicts accounted for part of the association between parental separation and adolescent depression at baseline, but this did not contribute much to explaining the association between parental separation and depression in adulthood. This is in contrast to the findings reported by Gähler and Palmtag [ 18 ], who showed that the poorer mental health found among adults whose parents had divorced during their childhood was accounted for by economic difficulties and greater family dissension. A possible explanation of why our results differ from those of Gähler and Palmtag [ 18 ] may relate to the different designs of the data materials used. While the present study used a community-based sample of adolescents with depression and matched non-depressed peers who were followed-up prospectively and assessed with clinical mental health diagnoses, Gähler and Palmtag’s study was based on a representative sample of the adult population in Sweden, using retrospective data (implying the risk of recall bias), and with a self-reported mental health measure. Thus, it is possible that parental conflict accounts for the association between parental separation and less severe mental health problems but in case of major depression there seem to be also other mechanisms at work.

What, then, are the underlying reasons for the excess risk of depression in adulthood among individuals who had suffered from depression in adolescence and whose parents were divorced? One possible explanation may be that living in a single-parent family (which the majority of the individuals with separated parents had likely done for a shorter or longer period) often entails limited resources, both in terms of poorer socioeconomic resources but also with regard to less provision of social support and monitoring, which, in turn, are likely to be linked to poorer mental health outcomes among offspring. The finding that parental remarriage possibly seemed to be protective of relapse into depression (although only at the 10% level, data not shown) supports the interpretation that conditions associated with single parenthood may drive the associations between parental separation and later depression in the subgroup of depressed adolescents. The elevated risk of depression in adulthood among individuals with adolescent depression and separated parents could also potentially be an effect of a more severe adolescent depression in this subgroup. However, neither long depression nor somatic symptoms differed between these two subgroups, thus indicating that the adolescent depression was not more severe among individuals with separated parents than among those with non-separated parents. Other possible pathways in the association between parental separation and relapse into depression may include inflated self-concept and problematic interpersonal coping strategies. Assessing such potential mechanisms is a task for future research.

An incidental finding was that among individuals with adolescent depression, parental separation was linked with an excess risk not only of major depression but also of bipolar disorder in adulthood. This implies that parental separation seems to be associated with increased risk of chronicity of disorders already present in the individual, as well as with an increased risk of switching to a bipolar disorder. Future research is however needed to confirm this finding. Previous analyses of the same cohort have shown that a family history of bipolar disorder was a strong significant risk factor for bipolar disorder in adulthood [ 37 ]. The number of individuals in the data material with bipolar disorder in adulthood is however too small to disentangle relationships between parents’ bipolar disorder, parental separation, and the individual’s depression and bipolar disorder. Consequently, exploring the possible mechanisms using a larger data material is a promising task for future research.

Furthermore, the interpretation that parental separation is linked to a risk of chronicity in illnesses already present in the individual is supported by our analyses of anxiety disorder, which showed that among non-depressed controls with anxiety disorder in childhood or adolescence according to DICA-R-A, parental separation was linked with an excess risk of recurrence of anxiety in adulthood.

Strengths and limitations

The data used have several strengths. The data collected at baseline were community-based and included 2,300 adolescents of the same age with a high participation rate in the depression screening (93%). The non-depressed controls were matched to the depressed by sex, age, and school class. The data included clinical interview diagnoses both at baseline and at follow-up. One limitation is that only about two thirds of participants in the original investigation also took part in the follow-up. Still, the participation rate can be seen as reasonably high in relation to the follow-up period of 15 years. Furthermore, the attrition was evenly distributed between the non-depressed control and the depressed group. In addition, Jonsson et al. [ 33 ], using the same data, concluded that the studied baseline characteristics did not indicate that the attrition between baseline and follow-up resulted in biased findings. Their analyses using a multiple imputation approach showed overall similar results to those from analyses containing only complete cases. Nevertheless, Jonsson et al. [ 33 ] did not rule out the possibility that there could be bias due to other factors. Another limitation is that we lack proper measures of socioeconomic conditions in childhood. We also lack information on the time point of the parental separation, which may be relevant to include as a measure of time spent in a non-nuclear family. As recently highlighted in a review, earlier research has not been able to identify that experiencing parental separation at a particular age or development stage is especially critical for developing later depression [ 14 ]. Higher distress scores have been recorded for those who experienced separation at younger ages (0–16 years) than at older ages (17–33 years) [ 38 ] but it has also been shown that father absence in early childhood (child <5 years of age) predicted self-reported depressive symptoms at age 14, whereas father absence in middle childhood (child ≥5 years of age) did not [ 39 ]. As a sensitivity check, we performed additional analyses where we excluded individuals whose parents had separated the year before the baseline investigation. For the cross-sectional analyses of baseline data, it was shown that the “effect” of parental divorce on concurrent depression was somewhat weaker than in the analyses which included these individuals. For the prospective analyses of depression in adulthood, the results were however very similar irrespective of whether or not these individuals were included. Accordingly, our crude measure of the timing of parental separation did not seem to have a moderating role for the risk of depression in adulthood. Nevertheless, information on the timing of separation would indeed have been valuable in order to better distinguish between our covariates as confounders or as mediators. We believe this is important to consider in future inquiry about the links between parental divorce and later depression in different subgroups. Another limitation is the increased risk of type I errors stemming from multiple comparisons. However, we still judge that the general pattern of results is valid. Finally, even though we used community-based data, the generalizability of our findings to other populations than the one investigated is not straightforward and thus further studies are needed to corroborate the results in other contexts.

Adolescent depression appears to be a moderator in the association between parental separation and adult depression. Among depressed adolescents, parental separation seems to predict relapse into depression in adulthood. By contrast, among non-depressed adolescents, parental separation does not appear to be associated with an excess risk of suffering from future depression.

As a consequence, among adolescents with major depression, attention should be paid to those who also have separated parents. These adolescents in particular might benefit from qualified treatment and longer follow-up periods. Additionally to standard treatment like antidepressant medication and cognitive behavior therapy other treatment and supportive strategies might be added, for instance, family interventions and, if needed, cooperation with the social services. For example, previous studies have shown that parental sensitivity can be strengthened and work as a buffer against the risk of future depressive episodes among children [ 14 ].

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Acknowledgements

We are grateful to Hans Arinell for statistical advice and to Carina Mood for valuable comments on an earlier draft.

The Clas Groschinsky Memorial Foundation (SF14 10) and the Swedish Research Council for Health, Working Life and Welfare (Forte) (2012–1741) financially supported this work.

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Bohman, H., Låftman, S.B., Päären, A. et al. Parental separation in childhood as a risk factor for depression in adulthood: a community-based study of adolescents screened for depression and followed up after 15 years. BMC Psychiatry 17 , 117 (2017). https://doi.org/10.1186/s12888-017-1252-z

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Early Childhood Depression May Impact Brain Development in Later Years

Joan L. Luby, M.D.

Samuel and Mae S. Ludwig Professor of Psychiatry (Child)

Director and Founder, Early Emotional Development Program

Washington University School of Medicine in St. Louis

Scientific Council Member (Joined 2018)

2020 Ruane Prize for Outstanding Achievement in Child and Adolescent Psychiatric Research

2008, 2004 Independent Investigator Grant

2004 Klerman Prize for Exceptional Clinical Research

1999 Young Investigator Grant

Story highlights

Young adolescents who were diagnosed with depression in their preschool years have less gray matter in brain areas important for emotional processing than children unaffected by the disorder.

Research suggests early childhood depression can impact the course of brain development. Tweet >

From The Quarterly, May 2016

Over the past decade, it has become clear that even very young children can suffer from clinical depression . Now, research published December 16, 2015 in the journal JAMA Psychiatry suggests that early childhood depression can impact the course of brain development, underscoring the importance of identifying and treating children with the disorder.

According to the study, which followed children diagnosed with major depressive disorder between the ages of three and six, early childhood depression is associated with disruptions in brain development that continue into early adolescence. Periodic brain imaging revealed that in comparison with children unaffected by the disorder, children who had suffered from depression in their preschool years had lower volumes of gray matter—which contains the neural connections through which brain cells communicate—in the cortex of their brains. This change may have a lasting effect on emotional processing and make a child vulnerable to problems later in life, the researchers say.

Joan L. Luby, M.D. , a 2004 and 2008 Independent Investigator and Young Investigator in 1999, now at Washington University in St. Louis, has led research establishing that depression can occur in children as young as three years-old. Like adults with major depressive disorder, preschool-aged children with depression experience changes in sleep, appetite, and activity level and an inability to experience pleasure. These symptoms often continue later in childhood.

In the new study, Dr. Luby and her team, including 2013 Distinguished Investigator Deanna M. Barch, Ph.D. , (also a 1995 and 2000 Young Investigator, 2006 Independent Investigator), along with 1997 Young Investigator and 2005 Independent Investigator Kelly N. Botteron, M.D. , also at Washington University, wanted to understand whether those early experiences of depression impact brain development.

To find out, the researchers followed a group of 193 children, including 90 diagnosed with major depressive disorder during their preschool years, for up to 11 years. The scientists used magnetic resonance imaging (MRI) to watch how activity in each child’s brain changed as he or she aged. Up to three scans were collected for each child, beginning between the ages of six and eight and with the final scan occurring between the ages of 12 and 15.

The brain’s gray matter begins to form before birth, but continues to develop during childhood, reaching its greatest volume around puberty. After this peak, cells are pruned back to eliminate redundant connections, reducing gray matter volume. The research team observed this normal and expected decline in gray matter in all the children in their study, but it was most dramatic in those who had suffered depression. What’s more, the decline was steepest in those whose depression symptoms had been most severe.

The researchers stress that further research is needed to identify effective ways to treat depression in young children and to determine whether early intervention can restore normal patterns of brain development.

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Science News

Why it’s key to identify preschoolers with anxiety and depression.

New research shows these kids have mental and physical problems as they grow older

PRESCHOOL MENTAL HEALTH  Even 3-year-olds can experience depression and anxiety. Yet diagnosis is difficult, making it hard to treat such children early and potentially ward off later physical and mental health problems.

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By Sujata Gupta

February 3, 2019 at 8:00 am

The task was designed to scare the kids. One by one, adults guided children, ranging in age from 3 to 7, into a dimly lit room containing a mysterious covered mound. To build anticipation, the adults intoned, “I have something in here to show you,” or “Let’s be quiet so it doesn’t wake up.” The adult then uncovered the mound — revealed to be a terrarium — and pulled out a realistic looking plastic snake.

Throughout the 90-second setup, each child wore a small motion sensor affixed to his or her belt. Those sensors measured the child’s movements, such as when they sped up or twisted around, at 100 times per second. Researchers wanted to see if the movements during a scary situation differed between children diagnosed with depression or anxiety and children without such a diagnosis. It turns out they did. Children with a diagnosis turned further away from the perceived threat — the covered terrarium — than those without a diagnosis.

In fact, the sensors could identify very young children who have depression or anxiety about 80 percent of the time, researchers report January 16 in PLOS One . Such a tool could be useful because, even as it’s become widely accepted that children as young as age 3 can suffer from mental health disorders, diagnosis remains difficult. Such children often escape notice because they hold their emotions inside.

It’s increasingly clear, though, that these children are at risk of mental and physical health problems later in life, says Lisabeth DiLalla, a developmental psychologist at Southern Illinois University School of Medicine in Carbondale. “The question is: ‘Can we turn that around?’”

Maybe, says Joan Luby, a psychiatrist at the Washington University School of Medicine in St. Louis. Luby’s research has shown that treating preschoolers with depression helps the youngsters feel joy again, at least in the short term. “When you identify young children early” as needing help, Luby says, “you can treat them better.”

Fearful little bodies

Sensors reveal that anxious and depressed children turn farther away from a perceived threat than healthy children. The difference between where the children are supposed to be going and where their body is turned is known as the yaw angle.  

How kids react during an anxiety-inducing task

Source: R.S. McGinnis et al/ PLOS ONE 2019

Early onset

Few experts believed young children were capable of experiencing depression or anxiety until 1980, when researchers found that children as young as 7 could indeed get depressed . By the 1990s, it was clear that depression and anxiety could start in children as young as age 3. But for many children, the symptoms of depression show up in seemingly unrelated ways, such as aggression, difficulty eating or hyperactivity. As a result, these so-called “internalizing disorders” are more likely to go undiagnosed in the younger years.

Though estimates vary widely, some 10 to 20 percent of preschool- and kindergarten-age children are thought to suffer from an anxiety disorder and about 2 percent from depression, with some even expressing suicidal feelings. The real rates, though, are likely higher. Because children under age 8 or so cannot articulate their own feelings, clinicians must rely on caregiver accounts of a child’s behavior. But children with anxiety or depression are often so quiet and unobtrusive that caregivers and teachers overlook their difficulties.

These kids “are not the squeaky wheels,” says Ellen McGinnis, a clinical psychologist at the University of Vermont Medical Center in Burlington.

She and others have focused their research on finding objective ways to identify children with such conditions. This research can be laborious and time-consuming. As a graduate student, McGinnis recorded children during the snake or other similar anxiety-inducing tasks. Multiple research assistants would then evaluate those videos to gauge the children’s reactions. It took McGinnis two years to assess 10 children. “I was like, ‘This is ridiculous,’” she recalls.

So she teamed up with her husband, UVM biomedical engineer Ryan McGinnis, to find a faster, better way to identify children with depression or anxiety. The result: The pairing of the classic snake anxiety test with a commercially available motion sensor.

Of 63 children recruited to take the test, 21 had been diagnosed with anxiety or depression following a 90-minute interview between a trained clinician and caregiver — the current gold standard for assessment, says Ellen McGinnis.

In the snake test, the researchers found that the most telling moments picked up by the sensors came from the 20 or so seconds of anticipation leading up to the reveal. When faced with the covered terrarium, children with either anxiety or depression turned their bodies up to 180 degrees away from the scary object. “Children that had a diagnosis turned further away from this potentially threatening situation than kids who didn’t,” says Ryan McGinnis.

He was surprised that, after the big reveal, the sensors detected no difference between children with and without a diagnosis. “It surprised me how many kids were super excited to see the snake,” Ryan McGinnis says.  

The researchers were able to use the sensor data to correctly flag 14 of the 21 children. The rate of false positives was also low, with the sensors categorizing only five children without a clinical diagnosis as having depression or anxiety.  

That’s not gold standard, the researchers say, but it’s better than a widely used questionnaire in which parents report their child’s problems. The Child Behavior Checklist correctly identified only eight of the 21 children with diagnoses.

Because the task was simple and the sensor technology easily accessible (the unit price is less than $4 and the components needed to measure body motion are already present in most mobile phones), Ryan McGinnis thinks coupling technology with behavioral tasks has enormous potential. “You can really deploy something like this for universal screening,” he says.  

Depression test

But inducing fear, as in the snake task, relates more to anxiety than depression, says Sara Bufferd, a clinical psychologist at California State University San Marcos whose research also focuses on identifying preschoolers with internalizing disorders. Bufferd would like to see if the sensors would work on kids during a task that heightens feelings of sadness, helplessness or frustration. “I’m not sure whether responses to a task like that would induce motion in the same way as the fear task,” she says.

Many researchers working to identify children with mental health problems early are also following those children for years. That way they can see if and how such early mental health problems carry over to later life. In 2014, Bufferd and her team showed that children with depressive signs at age 3 were more likely to be depressed three years later . Related research on older children has shown similar continuity. 

New research now shows that very young children with mental health problems may also be prone to more physical health problems in adolescence. From 1994 to 2001, DiLalla measured internalizing behaviors in 326 children at age 5 using the Child Behavior Checklist. Though the kids showed some signs of depression and anxiety, their behaviors did not reach clinical levels. 

In a Jan. 25 study in Frontiers in Psychology, DiLalla and lab member Matthew Jamnik report that children with higher rates of internalization at age 5 were about 30 percent more likely to suffer from physical health problems , such as bad sleep, headaches and stomachaches seven to 12 years later, with varying rates for gender and temperament. Those with higher internalization scores in their early years were also about 30 percent more likely to eat mindlessly in adolescence. Mental health at age 5 impacts physical health later in life, Jamnik says.

Early treatment

With evidence mounting that mental health problems in preschool carry over into adulthood, researchers have begun looking into treating the very young. Work out of Luby’s lab, which focuses almost exclusively on preschool depression, is indicative.

In 2016, Luby showed that children with depression reacted less to rewards than their peers without depression. Her team hooked 78 children ranging in age from 4 to 7 to an electroencephelogram (EEG), a non-invasive machine that measures electrical activity in the brain. Fifty-three of those children had been diagnosed with depression.

Response to reward

When children with depression were hooked up to a machine that measures electrical activity in the brain (through little electrodes placed around the skull), their striatums — the part of the brain that activates during a reward — lit up less than those of healthy children.

Comparing children’s brain activity in reaction to reward

The children played a guessing game on a computer. Children who gave more correct answers, as indicated by a green, upward facing arrow (compared to a red, downward-facing arrow for the wrong answer), gained more points and ultimately better prizes. The EEG revealed that even after choosing correctly, the depressed children showed less brain activity than their healthy peers — a sign that their responses to rewards were muted, Luby reported in October 2016 the Journal of the American Academy of Child and Adolescent Psychiatry . Similar inhibited responses to rewards have been linked to depression in adolescents and adults.  

Meanwhile, Luby also studied children receiving a modified form of an established psychotherapy known as Parent-Child Interaction Therapy, or PCIT. In this early intervention for children with behavioral problems, a therapist coaches caregivers on how to help children manage disruptive behaviors and tantrums. The therapist observes the parent and child through a one-way mirror and communicates with the adult through a mic in the ear. Similarly, in Luby’s study, preschoolers and their caregivers followed the PCIT setup but with a focus on reducing the feelings of guilt and shame that tend to accompany depression.

Children receiving the treatment showed lower rates of depression and less severe depression than children placed in a group waiting for the treatment, Luby found. In addition, children who received the modified form of PCIT began to show the same response to rewards, as measured by an EEG, as children without depression. “The treatment changed the response to reward,” says Luby of her unpublished work.

But will that newfound joy carry over into later childhood and even the angsty teen years? Luby hopes she’ll have some answers once those kids grow old enough.      

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Gender Differences in Depression: Evidence From Genetics

Lihong zhao.

1 Jilin Provincial Key Laboratory on Molecular and Chemical Genetics, Second Hospital of Jilin University, Changchun, China

Guanghong Han

2 Department of Oral Geriatrics, Hospital of Stomatology, Jilin University, Changchun, China

Yinghao Zhao

Tongtong ge.

3 Department of Neurosurgery, First Hospital of Jilin University, Changchun, China

Compared with men, female accounts for a larger proportion of patients with depression. Behavioral genetics researches find gender differences in genetic underpinnings of depression. We found that gender differences exist in heritability and the gene associated with depression after reviewing relevant research. Both genes and gene-environment interactions contribute to the risk of depression in a gender-specific manner. We detailed the relationships between serotonin transporter gene-linked promoter region (5-HTTLPR) and depression. However, the results of these studies are very different. We explored the reasons for the contradictory conclusions and provided some suggestions for future research on the gender differences in genetic underpinnings of depression.

Introduction

Depression is a prevalent mental illness that seriously affects physical and mental health ( Krishnan and Nestler, 2008 ; Ge et al., 2018 ; Ren et al., 2020 ). Women are more likely to suffer from depression ( Young et al., 1990 ; Harkness et al., 2010 ; Wang et al., 2019 ). The susceptibility to depression is affected by diverse hereditary, epigenetic, environmental, and endocrine risk factors ( Duman et al., 2016 ). With the rise of developmental behavioral genetics (using the research methods and techniques of psychology and behavioral genetics to examine the influence of genetics and environment on the development of human psychology and behavior), more and more researchers began to pay attention to the role of genetic factors in the occurrence of gender differences in depression. Behavioral genetics research methods include quantitative genetics (mainly through twins and adoption research to find evidence that genetics and the environment affect human psychology and behavior) and molecular genetics [identify susceptibility genes associated with specific psychology and behavior, including candidate gene association studies and genome-wide association studies (GWAS)]. Twin studies show differences in the heritability of depression between men and women, and molecular genetics studies show gender differences in depression caused by specific genes and their interaction with the environment. However, these findings are not consistent.

This manuscript reviews relevant studies on the genetic underpinnings of gender differences in depression. Besides, we explored the reasons for the contradictory conclusions and provided some suggestions for future research on the genetic underpinnings of gender differences in the depression. We hope this manuscript will help scientists better understand and study genetic underpinnings of gender differences in the depression.

Epidemiology

Many national and international studies display that sex ratio (women: men) of depressive disorders over 1.7 for lifetime prevalence and 1.4 for 12-month prevalence after the age of 18 ( Kuehner, 2017 ). The gender difference in depression rates first emerge in adolescence and continues into old age ( Angold and Worthman, 1993 ), although the gender gap of the adult is smaller than it is at younger ages ( Patten et al., 2016 ; Kiely et al., 2019 ). Similar gender differences exist in different income countries, although significant cross-national variation exists ( Van de Velde et al., 2010 ). But, gender differences do not exist across all race-ethnic groups ( Kessler, 2003 ; Yancu, 2011 ). The female predominate in the incidence of depressive disorders; instead, there appears to be no gender difference in recurrence, remission, or chronicity of depression ( Kessler, 2003 ; Otte et al., 2016 ). The symptom profile of men and women with depression is different. Women are more likely to show increased appetite, hypersomnia, somatic symptoms, etc. ( Piepenburg et al., 2019 ). Especially, comorbidity of peripartum depression with anxiety disorders, obsessive-compulsive disorder, and post-traumatic stress disorder worth attention ( Kuehner, 2017 ).

Gender Differences in Heritability

The family pedigree study finds depression is hereditary. According to reports, children of depressed parents have increased symptoms of depression and internalization ( Rice et al., 2002 ). Later, the twin study divided the sources of phenotypic variation of depression into three aspects: genetic, shared environment, and non-shared environment, which provided the possibility of separating the role of genetic and environmental.

Most Scholars use the twin paradigm in quantitative genetics to investigate gender differences in the genetic basis of depressive symptoms. Research on gender differences in heritability of depressive symptoms mainly focuses on adolescents in European and American countries. Adolescence is a particularly good time when many people will experience the first onset ( Eley et al., 2004 ). During adolescence, the prevalence rate of depression in men and women has begun to rise dramatically, especially in girls. Similarly, the heritability of depression increased from childhood to adolescents ( Ksinan and Vazsonyi, 2019 ). Biological and pubertal changes, cognitive maturity occurs during adolescence, some genetic factors may be “switched on” to promote these changes, which in turn affect depressive symptoms ( Lau and Eley, 2006 ). Jacobson and Rowe (1999) show that the heritability in depressed mood is higher in female adolescents than in male adolescents (self-rated depressive symptoms), however, Rice et al. (2002) shows the opposite result (self-rated depressive symptoms). McCaffery et al. (2008) reported that non-shared environment and the genetic factors contribute to the correlation of depressive symptoms in female adolescents and cigarette smoking; but In male adolescents, only non-shared environment. In an older twin study, the heritability of women was also higher than that of men, although no statistically significant ( Jansson et al., 2004 ). Scourfield et al. (2003) show higher heritability for young girls (children) than young boys only from parent-rated depressive symptoms, not self-rated depressive symptoms. Some methodological differences exist in these surveys, including measurement methods, source of information (informant), the age range of the sample, number of samples, sibling-pairs sample, demographic characteristics ( Table 1 ), which limits comparability between surveys. We are not sure whether the difference in the heritability of depressive symptoms exists between gender.

Gender differences in heritability.

Several reasons can explain the divergence of the above conclusions. First, the genetic factors on depressive symptom vary according to the individual’s developmental stage (such as childhood and adolescence) or age: Both self-reports and parent reports show that individuals with early adolescence have a higher heritability in depressed mood than individuals with mid-adolescence ( Hou et al., 2012 ); genetic factors become more important from childhood to adolescence or less important ( Rice et al., 2002 ; Scourfield et al., 2003 ). Most studies have analyzed adolescents at different developmental stages of adolescence and may have overlooked the change in genetic interpretation of depressive symptoms during adolescence. Like most complex behaviors, depression does not simply follow Mendel’s single gene inheritance law but is affected by multiple genes, known as quantitative trait locus (QTL). Different genes are turned on in different time, the interaction between genes and the interaction between genes and the environment show different patterns at different stages of development, so the influence of genetics and environment on adolescents’ depression is dynamically changing ( Hou et al., 2012 ). Second, The inheritance rate varies according to the reporter and genetic influences may be less important for child-rated depression symptoms than for parent-rated symptoms ( Rice et al., 2002 ): Proxy ratings can be influenced by the informant’s symptoms of depression and anxiety; Self-reports and parental reports may have evaluated different aspects of depressive symptom or depressive symptom at different moments; in parents-report, parents need to rate two twins. In this process, two twins will be inevitably compared with each other, or the two children will be rated more similarly, or the rating will be less similar. In self-reporting, a child only needs to report themselves’ emotional experience. Third, the small number of subjects may not be sufficient to produce convincing results. Modest heritability (30–40%) ( Sullivan et al., 2000 ), clinical heterogeneity and complicated genetic architecture for major depression requires a larger sample size. In order to generate replicable and statistically significant findings, 75,000–100,000 major depressive disorder cases are needed in GWAS to identify gene loci involved major depressive disorder ( Duman et al., 2016 ). Also, maximizing sample sizes is more informative to understand genetic heterogeneity of depression ( Hall et al., 2018 ).

Gender Differences in the Gene Associated With Depression

The twin studies found that the genetic factor affect depressive symptom of adolescents but gender difference in heritability of depressive symptom remains to be further studied. Molecular genetics attempts to locate the genes for gender differences in depression. At present, most candidate gene association studies have examined the relationship between serotonin system genes, dopamine system genes and depression ( Table 2 ): loci implicated in the serotonin (5HT) system including serotonin (5-HT) transporter gene-linked promoter region (5-HTTLPR), 5HT receptor 2A (5HT2A), 5HT receptor 2C (5HT2C), monoamine oxidase type A ( MAOA ), tryptophan hydroxylase ( TPH1 ). loci implicated in the dopamine system including catechol- O -methyltransferase ( COMT ), dopamine receptor genes DRD1-DRD5 . Related candidate genes can regulate the level of neurotransmitters (serotonin or dopamine) in the synaptic space through degradation (e.g., MAOA , COMT ) and transport (such as 5-HTTLPR), and can also change the number of receptors in the brain (5HT2A, DRD2 gene) to regulate signal transmission, which in turn affects the level of individual depression.

5-HTTLPR alone and interaction with the environment contribute to the risk of depression.

Recently, extensive works of literature have investigated the relationships between 5-HTTLPR and depression, the serotonin transporter gene-linked promoter region (5-HTTLPR) is a variable number tandem repeats (VNTR) located in the promoter region of SLC6A4 (the human 5-HTT-encoding gene) ( Iurescia et al., 2016 ). In addition to most common alleles: the short (S, 14 repeats) and the long (L, 16 repeats), there are less common alleles: extra-long (XL, 17–24 repeats) and extra-short (XS, 11–13 repeats). The L allele possesses higher transcriptional activity and serotonin uptake rate than S allele positively affects serotonin reuptake rate. Also, two nearby single nucleotide polymorphisms (SNPs) rs25531 and 25532 (located in the 5-HTTLPR) contribute to the functional variations of SLC6A4 expression ( Iurescia et al., 2016 ; Figure 1 ). The 5-HT transporter (5-HTT), an integral membrane protein, moves 5-HT from synaptic space into presynaptic neurons ( Damsbo et al., 2019 ; Möller et al., 2019 ). And then 5-HT was degraded by MAOA or recycled into synaptic vesicles. Duration and magnitude of 5-HT biological actions are closely related to 5HTT ( Coleman et al., 2019 ). Also, effective drugs selective serotonin reuptake inhibitors (SSRIs), act on 5-HT transporter ( Ananth et al., 2018 ; Kulikov et al., 2018 ). So, dysfunction in 5HTT leads to psychiatric disorders including depression.

SLC6A4 L and S allelic.

Genes Directly Affect Depression in a Gender-Specific Manner

Different genes may directly affect depression in a gender-specific manner. 5HT2A, TPH may be a risk gene for depression in women, and COMT may have a greater impact on men. The relationship between 5-HTTLPR genotype and depression is highly controversial: although females carrying short alleles had a lower risk of depression than other genotypes ( Table 2 ), these research results show inconsistent conclusions on specific genotypes ( Eley et al., 2004 ; Aslund et al., 2009 ; Uddin et al., 2010 ). Animal studies have shown that individuals carrying short alleles, especially female animals, are more vulnerable to chronic stressors ( Spinelli et al., 2012 ). But, Others showed no main effect of 5-HTTLPR on depression, which means 5-HTTLPR genotype cannot predict depression risk ( Aslund et al., 2009 ; Risch et al., 2009 ; Ming et al., 2013 ). The study also indicated the main effects of 5HT2A, TPH on depression group exist in female subjects only ( Eley et al., 2004 ). However, another study found direct effects of certain depression-related genes only exist in the male population. Individuals carrying the Met/Met of COMT genotype are less likely to suffer depression than those carrying the Val/Val genotype ( Baekken et al., 2008 ).

In addition to candidate gene association studies, GWAS is another research strategy in the field of molecular genetics to find genes associated with individual psychological or behavioral phenotypes. Recent GWAS has identified 14 independent and replicated loci that were associated with MDD at the genome-wide level ( Maul et al., 2020 ). Only a few scientists have reported gene loci related to gender differences in depression: SNP rs6602398, presented in interleukin receptor 2A gene (IL2RA), was significantly associated with males MDD ( Powers et al., 2016 ); 2 SNPs rs619002 and rs644926, presented in the EH-domain containing 3 (EHD3) gene, were associated with female MDD ( Wang et al., 2014 ). However, some scientists showed no evidence for genetic heterogeneity between the gender using GWAS summary statistics ( Trzaskowski et al., 2019 ).

Candidate gene association studies and Genome-wide association studies (GWAS) are research methods in developmental-behavioral genetic, aiming to find out whether genetics and environment affect human psychology and behavior development. Candidate gene association research is to directly select genes that may be related to individual psychological or behavioral phenotype variation based on existing genetic related information, biological related information, or empirical research results and then to determine whether a candidate gene is associated with this phenotype by case-control study or population-based association analysis. GWAS selects SNPs associated with individual psychological or behavioral phenotypes from sequence variations (single nucleotide polymorphism, SNP) throughout the human genome. The difference from candidate gene research strategies is that you do not need to know the function and characteristics of genes in advance. Also, there are no preset research assumptions. It offers opportunities for finding unknown susceptibility genes. Though more and more depression loci are identified, most GWAS has not yet made a replicable discovery of MDD ( Hyde and Mezulis, 2020 ). Also, the GWAS study of depression has not achieved the same success as other mental illnesses; the complexity of the genetics and phenotype of depression may mean that a GWAS study will require a sample of thousands of participants ( Howard et al., 2019 ). Compared with the huge cost of GWAS, candidate gene association studies are more economica and faster.

Gene-Environment Interaction Contribute to the Risk of Depression

Many studies suggest 5HTTLPR-negative environment interaction contributes to the risk of depression in the child, adolescent, and adult populations in a gender-specific manner ( Table 2 ). Also, sex modulates 5-HTTLPR genotype-childhood adversity interaction on hippocampal volume [reducing hippocampal volume in depressed patients ( Maller et al., 2018 )] ( Everaerd et al., 2012 ). But, results remain inconclusive. Some studies have shown females rather than males carrying the SS genotype of 5-HTTLPR tended to develop depressive symptoms under negative environment ( Eley et al., 2004 ; Aslund et al., 2009 ; Hammen et al., 2010 ; Ming et al., 2013 ) or females carrying S allele are easier to develop depressive symptoms under negative environment ( Sjöberg et al., 2006 ; Brummett et al., 2008 ; Hammen et al., 2010 ; Ming et al., 2013 ). However, many contradictions about 5HTTLPR-negative environment exist in males: the l allele-stressor interaction contributes to higher depression scores as compared to those control group and s allele ( Brummett et al., 2008 ); Uddin et al. (2010) showed an interaction between SL genotype and deprived counties predicted lowered risk of depressive symptoms in males; Li et al. (2013) showed the interaction between poor family support and SL genotype predicted more symptoms of depression in males; Other studies showed SS genotype-negative environment interaction predicted higher risks of depression, a statistically significant only in males ( Li et al., 2013 ; Haberstick et al., 2016 ; Chang et al., 2017 ). Basically consistent conclusion exist in the females but not males. Under negative environment, females carrying S alleles have higher depression levels. But, A Meta-Analysis of Interaction between 5-HTTLPR, stressful life events, and risk of depression, published in 2009, neither 5-HTTLPR genotypes alone or interaction with stressful life events predicted an increased risk of depression in females alone, males alone, or in both genders combined. The Meta-Analysis across 14 studies, subjects of most studies are adults ( Risch et al., 2009 ).

Several reasons can explain the divergence of the above conclusions. First, Different countries and races have different distributions of alleles and genotypes of the 5-HTTLPR: e.g., different frequency of S/S and L/L genotype between older Taiwanese adults and western groups ( Goldman et al., 2010 ); the higher frequency of S alleles in Asians than in Caucasians ( Iurescia et al., 2016 ). Second, the dichotomous classification (S/L) of 5-HTTLPR genotypes may lead to influenced research results. Increased length of the 5HTTLPR may be associated with increased gene expression (S < L < XL) ( Vijayendran et al., 2012 ). But, dichotomous classification of 5-HTTLPR genotypes exists in most studies ( Table 2 ). Third, neglecting the two nearby SNPs rs25531 and 25532 may lead to a contradictory conclusion. SNP rs25531 contributes to different allelic subtypes S A , S G , L A , and L G . The different expression abilities exist in L A /L A genotype AND S/S, S/L G , L G /L G , L A /L G . Fourth, gene-environment interaction may be more successful for studies that study a single gene with big environmental impact. For example, uninfected control group subjects, carrying 32 mutation in the ΔCCR5 chemokine receptor, were less infected with human immunodeficiency virus when they were highly exposed to the virus ( Risch et al., 2009 ). However, The inheritance of depression does not follow a single-gene inheritance pattern like Huntington’s disease but has a non-Mendelian, polygenic underpinning. As a complex psychological problem, depression is most likely the result of the synergistic effects of multiple genetic and environmental factors ( Cao et al., 2018 ). In recent years, the studies of polygenic risk scores and gene-gene interaction studies have proved additive and interactive genetic effects of depression. Also, multi-genes affect the development of depression through interaction with environmental factors and gender differences exist in this complex interaction ( Cao et al., 2016 ). e.g., Girls rather than boys possessed low-expression MAOA-uVNTR alleles and S 5-HTTLPR alleles, more likely to show increased depressive symptoms under stressful life events ( Priess-Groben and Hyde, 2013 ). The interaction of both plasticity genotype (5-HTTLPR S and val66met Met allele)- early family environment quality predicted more depressive symptoms than either or neither plasticity genotype only in females ( Dalton et al., 2014 ). Fifth, different study design, longitudinal study, and cross-sectional study have their advantages and disadvantages ( Table 3 ). The cross-sectional study is a comparative study of people of different age groups at the same time (intergroup comparison), and the longitudinal study is a continuous study of the same population in various years (self-comparison). Sixth, different gene-environment results between objective measures (i.e., independent of the participants’ report) and subjective measures (i.e., self-report) ( Uddin et al., 2011 ), results of self-reported are more subjective ( Sjöberg et al., 2006 ). Moreover, gene-environment interaction has a dynamic effect on depression. In a study of the influence of BDNF Val66met and 5-HTTLPR on depressive symptoms, Scientists report that the gene-environment interaction conforms to differential susceptibility model when women are 15 years and that gene-environment interaction conforms to the diathesis-stress model after 15 years ( Figure 2 ). Finally, measurement instruments, environmental factors, and source of information (informant) highly divergent across studies, so limiting the comparability and replication of the studies.

Comparison of advantages and disadvantages between longitudinal research and cross-sectional research.

Schematic diagram of the model of differential susceptibility and diathesis-stress: the abscissa represents the transition of environment factors from negative to positive; the ordinate indicates that the outcome variable range from negative to positive. (A) Diathesis-stress model points out that individuals with “risk” allele are only more likely to be negatively affected and to develop poorly than those with the “non-risk” allele. (B) Differential susceptibility model view, compared with the “non-plastic” allele carriers, “plastic” alleles individual has better sensitivity, more sensitive to both positive and negative environment accordingly develop better or worse.

Besides, a SNP of the HTR2C gene, rs6318 (Ser23Cys), is Related to women’s depressive symptoms with high stress levels and different cortisol release ( Brummett et al., 2014 ). related genes of dopamine system ( DRD2 , COMT ) ( Vaske et al., 2009 ; Nyman et al., 2011 ), HPA axis system ( CRHR1 ) ( Roy et al., 2018 ), and immune system (IL-1β SNP) ( McQuaid et al., 2019 ), can also interact with the environment to affect the occurrence of depression in a gender-specific manner ( Table 4 ). Chinese scientists longitudinally studied the relationship of BDNF Val66Met ( Fan et al., 2017 ), Preproghrelin Leu72Met ( Su et al., 2017 ), oestrogen receptor alpha gene ( ESR1 ) rs9340799 ( Feng et al., 2017 ), adiponectin rs1501299 ( Wang et al., 2015 ), tumor necrosis factor receptor-II (TNF-RII) rs1061622 ( Memon et al., 2018 ) and insertion/deletion polymorphism at angiotensin-converting enzyme gene (ACE I/D) ( Fan et al., 2018 )with depression in adolescents after the 2008 Wenchuan earthquake. Results showed gene-environment interaction contributes to the risk of depression after the earthquake in a gender- and time-dependent manner. Dynamic genetic effects on depression across development were proved once again. However, the scientists also explained that their research is either different from previous research results or rarely reported. Therefore, we cannot yet draw a definitive conclusion on gender differences.

Gene-environment interaction contribute to the risk of depression.

Future Directions

To date, few pieces of research have investigated gender differences in the polygenetic mechanisms of depression, and ignoring gender specificity may lead to inconsistent results. As a complex psychological problem, depression is most likely the result of the synergistic effects of multiple genetic and environmental factors ( Cao et al., 2018 ). Therefore, future studies should further investigate the role of gender in the regulation of polygene genetic mechanisms ( Cao et al., 2016 ). Second, gender differences in the genetic basis of depression may be caused by differences in the sensitivity of individuals to different types of environments ( Cao et al., 2013 ). Future studies should examine the interaction between different types of the environment and genetic genes that affect gender differences in depression. The theoretical basis of the existing molecular genetics research on depression is mostly the “diathesis-stress model” because the many scientists believe that when individuals are under stress or high pressure, psychological and behavioral problems are prone to occur in individuals with a certain type of poor genetic quality, so studies based on this model mostly use the negative environment such as stressful life events as indicators to investigate the G × E effect of depression. However, the newly emerging theoretical model, the “differential susceptibility model,” clearly puts forward and proves that individuals of certain genotypes are also more susceptible to the effects of positive growth environments and perform well or the opposite ( Figure 2 ). Also, the existing research based on the “diathesis-stress model” fails to reveal multiple possible ways of G × E interaction. Whether there is a gender difference in the sensitivity of individuals with different genotypes to the positive environment is also needed for future research. Third, developmental behavioral genetics can investigate in depth whether genetics and the environment have an impact on human psychological and behavioral development and whether the effects were moderated by age. Compared to younger aged youth, older aged adolescents carrying SS/SL genotype has a higher risk of depressive episodes with greater chronic peer stress over the 3 years ( Hankin et al., 2015 ). Besides, Depression is developmentally dynamic and may be affected by some new genetic factors across development ( Figure 3 ). some new genetic factors emerge in depressive symptoms ( Lau and Eley, 2006 ) or symptoms of anxiety and depression ( Nivard et al., 2015 ) in adolescence. Compared with the 5-month-old baby, the negative emotionality of an 18-month-old baby was affected by persistent and new genetic factors ( Schumann et al., 2017 ). So, it is necessary to use a longitudinal cohort design to investigate the gender differences in the genetic basis of depression at different ages and their developmental changes. Forth, Subjects suffering from mental disorders or various physical diseases may rate disease inaccurately ( Chang et al., 2017 ). So, Selecting physically and mentally healthy, drug-free subjects to minimize these confounding factors and reveal the effect of the gene on depression more accurately. Finally, It is worth mentioning that to reduce the interference of confounding factors (e.g., ethnicity, gender, age, socioeconomic status), researchers should add the covariate × environment and covariate × gene interaction terms to the same model that tests the G × E interaction ( Keller, 2014 ).

The continuity and variability of genetic factors for depression.

There is not enough evidence for genetic heterogeneity in men and women with major depression ( Piccinelli and Wilkinson, 2000 ; Maciej et al., 2019 ). Genetic markers of major depression have not been successfully identified. Similarly, specific susceptibility genes on the X chromosome have not been successfully identified ( Hyde and Mezulis, 2020 ). As a heterogeneous and multifactorial disease, the gender gap in depression may be caused by many biological, psychological, micro and macro environmental factors with varying interactions ( Piccinelli and Wilkinson, 2000 ; Kuehner, 2017 ). Heredity may play a role in explaining gender differences. But, no sufficient evidence can explain the gender difference in depression from genetic underpinnings. In future research, scientists should pay attention to the influence of confounding factors on the results. such as different types of environments (positive or negative), demographic characteristics, measurement instruments, study design and so on.

Author Contributions

LZ wrote the first draft and participated in the discussion of the manuscript. LZ, GH, YZ, YJ, TG, WY, RC, SX, and BL made major revisions to the logic of this manuscript and provided the critical revisions. All authors approved the final version of the manuscript for submission.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. This work was supported by grants from the National Natural Science Foundation of China (NSFC) (81871070 and 81971276), the National Key R&D Program of China (Grant No. 2018YFC1311600), the Jilin Province Medical and Health Talents (2017F012, 2019SCZT007, and 2019SCZT013), the Jilin Science and Technology Agency (20170204049SF, 20190701078GH, 20200201465JC, and 20200301005RQ), and Scientific Research Foundation of the Education Department of Jilin Province (Grant No. JJKH20201107KJ).

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