- Major Depression and Genetics
- Genetic link for depression found
- Where did the story come from?
- What kind of research was this?
- What did the research involve?
- What were the basic results?
- How did the researchers interpret the results?
- Links to the headlines
- Links to the science
- Genetically Predisposed to Depression? Get on the Treadmill!
- Environmental exposures and their genetic or environmental contribution to depression and fatigue: a twin study in Sri Lanka
- Study design and participants
- Data collection
- Phenotypic associations
- Aetiology of measured exposures
- Aetiology of the overlap between measured exposures and depression or fatigue
- Related posts:
Major Depression and Genetics
How common is major depression? At least 10% of people in the U.S. will experience major depressive disorder at some point in their lives. Two times as many women as men experience major depression.
How do we know that genes play a role in causing depression? Scientists look at patterns of illness in families to estimate their “heritability,” or roughly what percentage of their cause is due to genes. To do this we find people with the disease who have a twin, and then find out whether the twin is also ill. Identical (monozygotic) twins share 100% of their genes, while non-identical (“fraternal” or dizygotic) twins share 50% of their genes. If genes are part of the cause, we expect a patient’s identical twin to have a much higher risk of disease than a patient’s non-identical twin. That is the case for major depression. Heritability is probably 40-50%, and might be higher for severe depression.
This could mean that in most cases of depression, around 50% of the cause is genetic, and around 50% is unrelated to genes (psychological or physical factors). Or it could mean that in some cases, the tendency to become depressed is almost completely genetic, and in other cases it is not really genetic at all. We don’t know the answer yet.
We can also look at adoption studies, to see whether an adopted person’s risk of depression is greater if a biological parent had depression. This also seems to be the case.
What about non-genetic factors? There are probably many non-genetic factors that increase risk of depression, many of which are probably not yet known. Severe childhood physical or sexual abuse, childhood emotional and physical neglect, and severe life stress are probably all risk factors. Losing a parent early in life probably also increases risk to some extent.
If someone has a family history of depression, are they at very high risk? If someone has a parent or sibling with major depression, that person probably has a 2 or 3 times greater risk of developing depression compared with the average person (or around 20-30% instead of 10%).
The situation is a little different if the parent or sibling has had depression more than once (“recurrent depression”), and if the depression started relatively early in life (childhood, teens or twenties). This form of depression is less common – the exact percentage of the population is not known, but is probably around 3-5%. But the siblings and children of people with this form of depression probably develop it at a rate that is 4 or 5 times greater than the average person.
Is there a “depression gene”? Some diseases are caused by a single defective gene. Cystic fibrosis, several kinds of muscular dystrophy, and Huntington’s disease are examples. These are usually rare diseases. But many common disorders like depression, diabetes and high blood pressure are also influenced by genes. In these disorders, there seem to be combinations of genetic changes that predispose some people to become ill. We don’t yet know how many genes are involved in depression, but it is very doubtful that any one gene causes depression in any large number of people.
So no one simply “inherits” depression from their mother or father. Each person inherits a unique combination of genes from their mother and father, and certain combinations can predispose to a particular illness.
How are major depression and bipolar disorder related? Most people who suffer from depression do not have episodes of mania. We use the term major depression for depression without mania. Most people who experience mania also have major depression. We use the term bipolar disorder (or manic-depression) for this pattern. Major depressive disorder and bipolar disorder are the two “major mood disorders.” For more information on the symptoms of mania abd bipolar disorder, see the links at the bottom of this page. Most people with major depression do not have close relatives with bipolar disorder, but the relatives of people with bipolar disorder are at increased risk of both major depression and bipolar disorder.
What about major depression and anxiety disorders? There are probably genetic changes that can increase the predisposition to both major depression and to certain anxiety disorders including generalized anxiety disorder, panic disorder and social phobia. Also, some people have a more general lifelong tendency to experience unpleasant emotions and anxiety in response to stress. Psychologists use terms like “neuroticism” and “negative affectivity” to refer to this tendency, and people who have it are also more likely to experience major depression.
However, many people who develop major depression did not have this type of personality before their depression started.
“Scientists have for the first time established a genetic cause for depression narrowing it down to a specific chromosome,” reported The Independent . It said that the study has found “clear evidence” that a region on chromosome 3 (called 3p25-26) is linked to severe recurrent depression.
This study looked at DNA from 971 sibling pairs who have European ancestry and who are affected by recurrent depression. Its findings are supported by another study published at the same time that found a link between the same region of chromosome 3 and depression in a sample of families of heavy smokers. This was reported to be the first time such a link had been independently confirmed in two studies.
One point worth noting is that these results may not apply to less severe, non-recurrent depression, or to individuals of non-European ancestry, who were not included in this study. Also, this finding does not mean that this is the only region containing genes that contribute to depression.
Furthermore, the study was not able to pinpoint single letter variations in the regions that were linked to severe recurrent depression, and the gene(s) involved have yet to be identified. Future work is likely to focus on studying the genes within the region, to identify which ones may be having an effect.
Where did the story come from?
The study was carried out by researchers from the Institute of Psychiatry at King’s College, London, and many other research centres in Europe and North America. Some of the researchers worked for GlaxoSmithKline, who also provided funding for the recruitment of participants and the collection DNA samples.
The study was published in the peer-reviewed American Journal of Psychiatry .
This story was covered by The Independent, Daily Mail, Financial Times and the Daily Mirror. The Independent and Financial Times provided balanced coverage, with The Independent noting the region identified may only contribute a small amount to a person’s susceptibility to depression. The Financial Times noted that many genes are likely to play a role. The Daily Mail suggested that ‘depression could be caused by a single rogue gene’ but this is not likely to be the case.
What kind of research was this?
This was a ‘genome wide linkage study’, called the Depression Network Study, which aimed to identify areas of DNA that might contain genes contributing to a person’s susceptibility to major depression. Both genetic and environmental factors are thought to play a role in the development of disorders such as depression. Studies have suggested that genetics play a greater role in depression that is severe and recurrent than in less severe, non-recurrent depression.
This type of study looks at DNA inheritance patterns within families that include sibling pairs affected by the disease in question. They use identifiable variations within the DNA called ‘markers’ to find pieces of DNA that are consistently passed on to the affected sibling pairs. Once such a region is identified the researchers look at the genes within that region in more detail, to see if they could be contributing to causing the disease.
This method is commonly used in looking for genes that cause diseases.
What did the research involve?
The researchers enrolled 839 families, which included 971 pairs of siblings who had recurrent major depression (the families also included 118 pairs where one sibling was affected but not the other), and 12 unaffected sibling pairs.
Adult siblings of European ancestry were recruited from eight sites across Europe and the UK. Sibling pairs were excluded if either sibling had ever had mania (bipolar), hypomania, schizophrenia or psychotic symptoms, or had intravenous drug dependency or depression associated with alcohol use. To be eligible, both siblings had to have experienced at least two depressive episodes of at least moderate severity, with the episodes separated by at least two months of remission, according to accepted criteria.
As well as the sibling pairs, the study recruited additional siblings and parents if they were available. All participants were interviewed using a standard clinical interview to assess the presence of psychiatric diagnoses. The interview also asked participants to rate the presence and severity of various symptoms during the worst four to six weeks of their worst and second worst episodes of depression. This information was used to categorise the severity of a person’s depression.
In total, 2,412 people were included:
- 2,164 of these had recurrent depression
- 1,447 were classified as having severe or worse recurrent depression
- 827 with very severe recurrent depression
Participants provided a blood sample for DNA extraction and their DNA was assessed for 1,130 genetic markers spread across the chromosomes. Statistical programmes were then used to analyse the results to identify regions of DNA that showed a pattern of inheritance consistent with the possibility that a gene contributing to the development of depression was nearby.
The researchers carried out separate analyses for the overall sample with recurrent depression, for severe recurrent depression and very severe recurrent depression.
Once the researchers identified a region of DNA that showed linkage to recurrent depression, they aimed to test these results using a case control analysis of a sample of 2,960 individuals with recurrent depression (cases) and 1,594 healthy individuals (controls).
The cases came from the current study, as well as 1,346 individuals with recurrent depression from another study of depression in the UK. The controls were from the UK Medical Research Council General Practice Research Framework, and staff and student volunteers from King’s College London. Using DNA samples from these individuals, the researchers looked at 1,878 single ‘letter’ variations in the region identified as being linked to recurrent depression in the first part of the study.
What were the basic results?
The researchers identified a region on the short arm of chromosome 3 (called 3p25-26) that was linked to severe recurrent depression. Importantly, this link remained significant after the researchers took into account the fact that many markers had been tested for linkage. There were 214 genes within the region of chromosome 3 identified as being linked to severe recurrent depression.
Based on what is known about the proteins that these genes encode, a number of these genes seemed like strong potential candidates for being involved in depression. For example, some of the genes in the region encoded the receptors for various brain signalling chemicals.
Some other regions showed weaker signs of linkage to recurrent depression as a whole, or very severe recurrent depression, but only the region on chromosome 3 was investigated further as it showed the strongest linkage.
Because the linkage with the region on chromosome 3 was greatest in sibling pairs with severe recurrent depression, in their case-control analysis the researchers only analysed the 1,590 cases with severe recurrent depression, and 1,589 controls. The researchers found that 95 single letter genetic variations showed some evidence of an association with the cases. However, these associations lost their significance once the many statistical tests that were carried out were taken into account. They say that this lack of significant findings may be because there are multiple rare variations having an effect, or that their sample may not have been large enough to detect common variants each having a mild effect.
In their discussion, the researchers highlight another study published in the same journal, which has also found linkage with the same region of chromosome 3 in a sample of families of heavy smokers with depression.
How did the researchers interpret the results?
The researchers conclude that they have identified a region of chromosome 3 that shows linkage to recurrent depression. They say that this region includes genes that could plausibly be involved in this condition.
They researchers added that this is the first report of a region showing linkage to depression from a genome-wide study, which has then been supported by findings from an independent sample. They say that future work will involve determining the DNA sequence of this region in the affected siblings and their families, and assessing the region in other samples with severe recurrent depression.
Depression is thought to involve both genetic and environmental factors, with genetics playing a larger role in the type of depression that is severe and recurrent. This study has identified a region of DNA that may include a gene or genes that affect an individual’s susceptibility to severe recurrent depression.
One point worth noting is that these results may not apply to less severe, non-recurrent depression, or to individuals of non-European ancestry, who were not included in this study. Also, the regions identified in this study are unlikely to be the only ones containing genes that contribute to depression.
The authors have been appropriately circumspect with regard to their findings, noting that it is still possible these results are false positives, and their statistical results suggest there is a 1.5% chance this is the case. They say their results need replication in other studies, and for the genes actually responsible for this link to be identified. The fact that another study published concurrently has also found a link with the same region of chromosome 3 lends support to the findings but, ideally, further confirmation in other samples will be obtained.
This study appears to give an important clue to the genetic contribution to severe recurrent depression, and future work is likely to focus on studying the genes within the region, to identify which one(s) may be contributing.
Analysis by Bazian
Edited by NHS Website
Links to the headlines
Found: The rogue gene that could make you prone to depression.
Daily Mail, 16 May 2011
Financial Times, 16 May 2011
Gene could cause depression, say scientists.
Daily Mirror, 16 May 2011
Hope for depression sufferers as study links illness to genes.
The Independent, 16 May 2011
Links to the science
Breen G, Todd Webb B, Butler AW, et al.
A Genome-Wide Significant Linkage for Severe Depression on Chromosome 3: The Depression Network Study
Am J Psychiatry Published May 15, 2011
Genetically Predisposed to Depression? Get on the Treadmill!
Increased levels of physical activity can significantly reduce the odds of depression, even among people who are genetically predisposed to the condition, according to a new study from researchers at Massachusetts General Hospital (MGH). In a paper published in the journal Depression and Anxiety, the team reported that individuals who engaged in at least several hours of exercise each week were less likely to be diagnosed with a new episode of depression, even in the face of high genetic risk for the disorder.
Drawing on genomic and electronic health record data from nearly 8,000 participants in the Partners Healthcare Biobank, the new study is the first to show how physical activity can influence depression despite genetic risk. Researchers followed patients who filled out a survey about their lifestyle habits (including physical activity) when they enrolled in the Biobank. They then mined millions of electronic health record data points over the next two years and identified people who received diagnoses related to depression. They also calculated genetic risk scores for each participant, combining information across the entire genome into a single score that reflects a person’s inherited risk for depression.
What they found was that people with higher genetic risk were more likely to be diagnosed with depression over the next two years. Significantly, though, people who were more physically active at baseline were less likely to develop depression, even after accounting for genetic risk. In addition, higher levels of physical activity were protective for people even with the highest genetic risk scores for depression.
“Our findings strongly suggest that, when it comes to depression, genes are not destiny and that being physically active has the potential to neutralize the added risk of future episodes in individuals who are genetically vulnerable,” says Karmel Choi, PhD, of MGH and the Harvard T.H. Chan School of Public Health, and lead author of the study. “On average, about 35 additional minutes of physical activity each day may help people to reduce their risk and protect against future depression episodes.”
The researchers found that both high-intensity forms of activity, such as aerobic exercise, dance and exercise machines, and lower-intensity forms, including yoga and stretching, were linked to decreased odds of depression. Overall, individuals could see a 17 percent reduction in odds of a new episode of depression for each added four-hour block of activity per week.
Depression represents the leading cause of disability worldwide. Despite its massive health burden, strategies to combat depression remain limited and the public’s understanding of robust and modifiable protective factors is incomplete. “We provide promising evidence that primary care and mental health providers can use to counsel and make recommendations to patients that here is something meaningful they can do to lower their risk even if they have a family history of depression,” says Choi.
Senior author Jordan Smoller MD, added, “In general our field has been lacking actionable ways of preventing depression and other mental health conditions. I think this research shows the value of real-world healthcare data and genomics to provide answers that can help us to reduce the burden of these diseases.”
Beyond physical activity, the MGH team continues to leverage the Partners Biobank and other large-scale studies to explore modifiable ways that individuals might reduce their risk of depression. “We believe there may be many factors could be part of an overall strategy for improving resilience and preventing depression,” emphasizes Choi. “The magnitude of depression around the world underscores the need for effective strategies that can impact as many people as possible.”
Reference: Choi, K. W., Zheutlin, A. B., Karlson, R. A., Wang, M.-J., Dunn, E. C., Stein, M. B., … Smoller, J. W. (n.d.). Physical activity offsets genetic risk for incident depression assessed via electronic health records in a biobank cohort study. Depression and Anxiety, n/a(n/a). https://doi.org/10.1002/da.22967
This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.
Scientists have discovered 17 separate genetic variations that increase the risk of a person developing depression.
The findings, which came from analysing DNA data collected from more than 300,000 people, are the first genetics links to the disease found in people of European ancestry.
The scientists say the research will contribute to a better understanding of the disease and could eventually lead to new treatments. They also hope it will reduce the stigma that can accompany depression.
According to Nice, up to 10% of people seen by practitioners in primary care have clinical depression, with symptoms including a continuously low mood, low self-esteem, difficulties making decisions and lack of energy.
Both environmental and genetic factors are thought to be behind depression, with the interaction between the two also thought to be important. But with a large number of genetic variants each thought to make a tiny contribution to the risk of developing the condition, unravelling their identity has proved challenging.
While previous studies have turned up a couple of regions in the genome of Chinese women that might increase the risk of depression, the variants didn’t appear to play a role in depression for people of European ancestry.
But now researchers in the US say they have identified 17 genetic variations associated with the condition in Europeans, spread across 15 regions of the genome.
“It just underscores that depression really is a brain disease,” said Roy Perlis, the co-author of the research from Massachusetts general hospital. “Depression is about biology and I think that will be helpful for some people in reducing stigma and changing how we think about depression.”
To unpick possible genetic associations, the researchers examined data collected by the consumer genetic testing company 23andme. Of the 300,000 people studied, 75,607 self-reported a clinical diagnosis of depression or were receiving treatment for the condition.
By comparing the frequency of common genetic variations in the people with depression compared to those without, the scientists discovered two genomic regions associated with the condition, one of which has previously been linked to epilepsy and intellectual disability.
Further analysis, including 23andme data from another 150,000 individuals, as well as clinical data from a worldwide multi-institutional collaboration involving nearly 19,000 individuals, threw up more results, with scientists identifying 17 genetic variants in 15 genome regions associated with depression. The findings are published in the journal Nature Genetics.
While the genetic variants found are thought to contribute, at most, a few percent to the overall risk for depression, the results are valuable, said Perlis. “It is a very small proportion of risk, this is not the sort of finding that can be used to make a diagnostic test or predict depression. The reason this kind of genetics is important is it points us towards a biology of disease,” he said. Understanding what the genes do and how they interact, he adds, could lead to better treatments for depression.
Elisabeth Binder from the Max Planck Institute of Psychiatry in Germany, and who was not involved in the study, agrees. “With this paper alone we cannot explain very much about depression but it is the first really substantial and valid genetic hits and now we can go in and look at these hits, look at connected hits and really start to understand the disease,” she said.
But, says Binder, the new research doesn’t shed light on sub-groups of depression, while it is likely that there are many genetic variants associated with depression that have not yet been found. However, she believes the new results could help researchers probe how genetic and environmental risk factors are connected.
What’s more, she says, with each genetic variant thought to contribute only a minuscule increase in risk for the disorder, and huge sample sizes needed to spot them, the research highlights the value of data from genetics companies. “I think the beauty of this study is that they were using data from the company 23andme and thereby really boosted the sample sizes in numbers that were unachievable using other types of studies that were ongoing in the regular research community,” she said.
But Jonathan Flint, from the University of California in Los Angeles, warns that the use of data based on self-reports of diagnosis is problematic. Not only are many individuals with major depressive disorders likely to never have received a diagnosis, others might have been diagnosed who do not meet the criteria for the condition.
“What we might be identifying here is something much more to do with help-seeking behaviour than anything to do with a psychiatric illness,” he said.
“In general that would tend to make it less likely rather than more likely that we would find associations,” Perlis said, adding that the researchers found a strong link in the cohort between depression and other related conditions such as anxiety, obesity and sleeplessness. “These are the people who ultimately we would like to be able to develop other treatments for – not research participants, but people who get diagnosed with depression and treated for depression.”
Environmental exposures and their genetic or environmental contribution to depression and fatigue: a twin study in Sri Lanka
The study received approvals from the Institute of Psychiatry, King’s College London Research Ethics Committee; the Ethical Review Committee, University of Sri Jayewardanepura; and the World Health Organisation’s Research Ethics Committee.
Study design and participants
This was a population based twin study, the twin component of the Colombo Twin And Singleton Study (CoTaSS). Full details of the design and implementation of the study are described elsewhere . Briefly, the study took place in the Colombo District of Sri Lanka, an area with population of 2.2 M which includes the island’s capital, and varies from urban to semi-urban areas. We added a question to the update of the annual census, asking whether the householder knew of any twins, and identified 19,302 individual twins by this method. Of these, we randomly selected 4,387 individual twins who were at least 15 years old to take part in the project on common mental disorders. Four thousand and twenty four (91.7%) participated, including 1,954 complete twin pairs. We included all consenting individuals aged 15 years or older who spoke sufficient Sinhala to understand the interview. Among men, the mean age was 33 years (s.d. 13); among women the mean age was 35 years (s.d. 14); 46% of the participants were men.
Specially trained research workers visited the subjects’ homes to interview them each separately. Interviews and questionnaires were translated. We used the Composite International Diagnostic Interview , because it is a structured diagnostic interview for use by lay interviewers, capable of giving DSM/ICD life-time diagnoses for mental disorders. We defined depression according to DSM-IV guidelines except we disregarded the requirement for functional impairment (this was because it was found to be too restrictive in defining depression in this population) . We also did not include opt-outs due to bereavement or mixed states. The current analyses pertain to lifetime-ever history of depression, rather than current depression.
The Chalder Fatigue Questionnaire was administered. ‘Abnormal fatigue’ was defined as having at least three of the 11 symptoms present at least ‘more than usual’ over the past month. There were no medical exclusions.
The interview also measured numerous exposures that are potential risk factors for depression or fatigue. Early school leaving and standard of living were examined because they were identified as potential causal factors in an epidemiological analysis of depression in this sample ; life events and parental care were added because they have been heavily implicated as risk factors for depression and fatigue respectively .
Current standard of living was assessed based on a government questionnaire which formed part of the national census. Items tapped into a wide spectrum of household characteristics rather than just detecting the lowest end of the distribution. However, certain items were particularly associated with a history of depression, but only in men . These were: informal structural materials of the abode (e.g. metal sheet roof), poor toilet or water facilities (e.g. pit latrine toilet, toilet shared with other households or drinking water source shared with other households), and hunger due to poverty in the past three months. The first two were assessed by interviewers’ ratings, the last through the subject’s self report. These three risk variables correlated with one other 0.37-0.53 within individuals (polychoric correlations). A binary indicator ‘standard of living’ was created based on a positive score for any of these three environmental risks. We also asked how many months each participant had worked over the past year, because income might account for much of the association between standard of living and history of depression, in the reverse causal direction, particularly in men.
A separate item assessed the length of schooling the subject had received. This was dichotomised to index previously identified risk: those with 10 or fewer years of education were more likely to report a history of depression (‘early school leaving’) .
Life events were assessed using the List of Threatening Experiences (Brief Life Events Questionnaire) over the past 12 months. For the current study we used only those items that could be potentially considered behaviour-dependent, in order to assess the potential of the individual subject to elicit his/her own negative experiences. Also, events that could be ‘shared’ across both twins in a pair, such as parental death, were not included. Thus the items used were: Separation due to marital difficulties or broken off a steady relationship; serious problem with close friend, neighbour or relative; made redundant or sacked from job; became unemployed or seeking work unsuccessfully for more than one month; major financial crisis; problems with the police involving a court appearance. Each participant received a score indicating having had 0, 1 or 2 or more such experiences over the past year.
The Childhood Experience of Care and Abuse Questionnaire (CECA-Q) was used to assess retrospective self-reports of Neglect (8 items) and Antipathy (8 items) (each of the items were scored on a 5 point scale from “definitely” to “not at all”). These were highly correlated (r > 0.70) and also strongly correlated across reports for mother and father (r:0.45-0.58), so these data were combined into one overall variable ‘parental care’ in order to reduce collinearity and multiple testing. Age and sex mean effects were regressed out separately within same-sex and opposite-sex pairs.
Zygosity was assessed using a validated questionnaire administered to both twins.
31.0% of male twins and 25.5% of female twins reported living in the same household as one another. These twins will necessarily share aspects of their ‘standard of living’ rating (structural materials, and toilet and water facilities of the abode).
A payment of 300 Rupees (approximately £1.50) was offered in compensation for participants’ time, at the end of the interview (compensatory payment was not mentioned in the information provided prior to the interview). A substantial percentage of the participants refused the payment and instead requested it to be donated back to the research project .
A database was constructed and regression analyses were performed in Stata version 10.1 for Windows. These analyses were corrected for the non-independence of twins within pairs, using the ‘cluster’ option in Stata. Structural equation model fitting was performed in Mx.
Odds ratios with depression (history) or fatigue were calculated for each of the four measured exposures (standard of living, early school leaving, life events, and parental care). These were adjusted for age, sex and ethnicity, on the basis that these factors exist prior to illness onset and cannot be an outcome of illness. The odds ratios were also fully adjusted so as to be independent of the other three measured exposures. Moderation by sex was assessed for each association (controlling for age and ethnicity).
Aetiology of measured exposures
Structural equation models were run to decompose the variance in the measured exposures into that due to genetic (A), shared (family) environmental (C) and unique environmental (E) influences. For the analysis of the continuous variable (parental care), sex effects were tested in the order: i) variance difference; ii) qualitative aetiological difference (whether the same genes and environmental factors are important in both sexes, which is tested by equating genetic and environmental correlations, r A and r C, across opposite- and same-sex DZ pairs); iii) quantitative aetiological difference (whether the magnitude of the genetic and environmental influences is constant across sex). Binary variables are assessed assuming a normally distributed latent liability to the exposure, and hence it was not possible to test for sex differences in variance distributions in standard of living, early school leaving and life events, but qualitative and quantitative aetiological sex differences were tested. In addition, a correction parameter to control for age was added to the model for the thresholds for the binary analysis of early school leaving (beta = 0.25, t = 12.44, p < 0.001), because this risk exposure was more common among older participants.
Aetiology of the overlap between measured exposures and depression or fatigue
Any phenotypic correlation between an exposure and a disorder must at root be due either to genes or environments. The correlation can also be divided into nonfamilial influences that have different impacts on each twin in a pair (E, chiefly found by examining dissimilarities within MZ pairs), or familial influences that make twins similar to one another which includes shared upbringing (C) plus the extent to which they share genetic inheritance (A). Familial influences are assessed by looking for similarity within pairs of twins. Cross-twin logistic regression models, making use of zygosity information, were run to examine the aetiology of the relationship between the measured exposures and depression or abnormal fatigue.
Unique environment (E) and potential reverse causation
We first examined the extent to which differences in measured exposures within MZ pairs were associated with differences in phenotype, using an ordered logistic regression model (“MZ differences” model). This would indicate a role for ‘E’ in the overlap between the exposure and the disorder, in other words whether the exposure is associated with the disorder, unconfounded by genes or shared family upbringing. This suggests a causal association, but it is still possible that the causal direction could run from the disorder to the exposure. Such a reverse causal direction is unlikely to be the case as regards associations with early school leaving assuming post-childhood onset in the majority of cases reporting history of depression, because 95% of the risk group – people reporting 10 or fewer years in education – had left school by age 16, and 100% of these had left school by 21. However, there could still be earlier influences accounting for such associations, such as childhood deprivation. Any ‘E’ association between lifetime-ever depression and past-year life events is likely to represent a mix of causes and outcomes of depression, but such ‘reverse causality’ is less likely to be a problem between past-year life events and past-month fatigue. Current standard of living might be an outcome of health status; thus where we found an “MZ differences” association between standard of living and disorder, we tested this further. Finally, although parental care is temporally prior to the assessment of the disorders, current mood could have biased its retrospective reporting.
Note that whilst the ‘E’ component of the univariate models incorporates the error of measurement in individual variables, this is not the case in the “MZ differences” models that examine the aetiology of the association between the measured exposure and the disorder (unless measurement error is correlated across the exposure and the disorder, or across their reporting).
Using both MZ and DZ pairs, we examined to what extent a person’s disorder status was associated with their co-twin’s exposure, using logistic regression models. This tests whether depression (lifetime-ever) or fatigue is associated with familial susceptibility to the exposure. We next tested whether the familial effect was greater in MZ than in DZ pairs. This would indicate genetic mediation of the familial effect, meaning that the same genes lead to both the exposure and the disorder (r GE).
If no genetic effect is found, then the familial association between exposure and disorder is likely due to environmental effects of the family of origin (C), through shared upbringing or influence of the family later in life. However, if this is the case, it would not be clear whether the measured exposure is directly involved as the causal component in the family’s influence, or if there is a degree of confounding by other environmental factors influenced by the family. Either way, such a result would suggest that there is an overall familial influence (C) on the disorder, a finding that is typically difficult to detect in the classical twin design.
The temporal order of familial associations is unlikely to point to reverse causality: an exposure in one twin is unlikely the result of his co-twin having the disorder. Thus these associations represent some form of familial vulnerability that influences both exposure to an environment and susceptibility to a disorder.
The above models were run separately for men and women when examining history of depression, due to sex differences in the univariate heritability of depression in this population . This was not the case for abnormal fatigue (submitted: ) so the models were run combined across men and women as well as separately for each sex.
These logistic regression models do not assume underlying bivariate normality between the exposure and the depressive outcome, as would be the case in structural equation models (SEM) based around polychoric correlations. Prior analyses showed the importance of step-wise relationships between measured exposures and history of depression, rather than an association across the whole continuum of exposures . Thus, these models can be more intuitively interpreted than those based on bivariate normality. Also, focusing on exposure risk categories, and cases versus controls in logistic regression (rather than SEM based on polychoric correlations) allowed sufficient power to examine the associations using narrower definitions of depression (with lower prevalence), and when the associations were only modest . Finally, regression models can be more flexibly used to find out whether A, C or E are involved in an association, whilst controlling for measured potential confounding factors.