The Genetic Epidemiology of Treated Major Depression in Sweden
Publication: American Journal of Psychiatry
Abstract
Objective:
The authors examined the heritability of treated major depression in a twin and full/half-sibling design, to describe key genetic epidemiological features of major depression and to determine which clinical indices of genetic liability optimally predict risk of depression in relatives.
Method:
The authors examined all treated cases of major depression in Sweden recorded in inpatient, specialist, and primary care registries and, using OpenMx, estimated the etiologic role of genetic and environmental factors from monozygotic and dizygotic twin pairs and full and half siblings reared together and apart (total N=1,718,863 pairs). Eight indices of genetic risk were examined in 875,010 proband-relative pairs.
Results:
The heritability of major depression in men and women was estimated at 0.41 (95% CI=0.21, 0.49) and 0.49 (95% CI=0.31, 0.56), respectively, in the twin design and 0.36 (95% CI=0.31, 0.38) and 0.51 (95% CI=0.51, 0.53), respectively, in the independent full/half-sibling design. The best estimate of the correlation in genetic effects across sexes was 0.89 (95% CI=0.87, 0.91). The results also showed evidence of modest shared environmental effects (0.02–0.05). Seven of the eight indices predicted risk for major depression in relatives, with stronger effects in those more closely related. The strongest indices were early age at onset, recurrence, comorbid anxiety disorder, and measures of clinical severity.
Conclusions:
In a large national sample, the heritability of major depression was similar when estimated from twin and full/half-sibling designs. The heritability of major depression was greater in women than in men, with the two sexes sharing most but not all genetic risk factors. In affected individuals, genetic risk for major depression could be meaningfully assessed from commonly available clinical indices.
Twin and family studies of major depression conducted over recent decades (1–6) have provided persuasive evidence that major depression is familial and moderately heritable, with an estimated heritability of 37% (7). While molecular approaches have become an increasing focus of genetic research in major depression, several issues remain that can best be addressed using genetic-epidemiological designs.
First, statistical methods are now being applied to molecular genetic data to estimate heritability for complex disorders like major depression (8–10). Such estimates—termed SNP heritability—for major depression are, as for other psychiatric disorders, considerably lower than heritability estimates derived from twin studies (9, 11–13). The difference has been termed the “missing heritability problem” (14). While SNP heritability might underestimate true heritability for many reasons, an additional explanation is that twin studies overestimate heritability (15–18). With Scandinavian registries, it has become possible to compare heritability estimates from twin studies with those obtained from other genetically informative relationships that are not susceptible to the methodological problems of twin studies, although they have potential limitations of their own (19, 20).
Second, questions remain about important genetic epidemiologic features of major depression that are relevant for the design of molecular genetic studies. Do genetic effects on major depression differ in men and women? While two of the largest-scale twin studies of major depression (6, 21) reported higher heritability in women than in men, a meta-analysis found no overall evidence for such effects (7). While two large twin studies (21, 22) suggested qualitative differences in genetic effects in the two sexes (i.e., risk genes for major depression not identical in men and women), two other studies (6, 23) found no support for such effects.
Third, molecular genetic studies often want to enrich cases for high genetic risk (11). The best way to achieve this for major depression remains uncertain. The literature suggests several potential indices (7, 24), but most reports are based on small samples or family studies that cannot distinguish indices of familial versus genetic risk.
In this study, we examined a population-based sample of individuals treated for major depression in all medical sectors in Sweden (25). Using these diagnosed cases, we first applied structural equation models to two independent informative samples of relatives (monozygotic and dizygotic pairs and full siblings and half siblings reared together and apart). We compared the resulting estimates of the effects of genetic and environmental factors on risk for major depression. Second, we identified all individuals treated for major depression and determined whether the presence of eight potential clinical indices of genetic liability predict risk for major depression in monozygotic co-twins, siblings, half siblings, and cousins. We also examined whether, as predicted for a genetic risk index, this prediction is stronger in closer relatives. We then constructed a multivariate genetic risk indicator and examined its prediction of major depression in relatives of affected probands.
Method
We collected information on individuals from Swedish population-based registries with national coverage, which were linked using each person’s unique personal identification number; to preserve confidentiality, personal identification numbers were replaced with serial numbers. We used the following sources: the Multi-Generation Register; Population and Housing Censuses; the Swedish Hospital Discharge Register (national coverage for 1987–2012 and partial coverage for 1969–1986); and the Outpatient Care Register (national coverage for 2001–2012). We also used a new Primary Care Registry, which included individual-level information on diagnoses from visits to primary health care centers in 15 of Sweden’s 21 counties: Blekinge (2009–2016), Värmland (2005–2015), Kalmar (2007–2016), Sörmland (1997–2017), Uppsala (2005–2015), Västernorrland (2008–2015), Norrbotten (2009–2016), Gävleborg (2010–2016), Halland (2007–2014), Jönköping (2008–2014), Kronoberg (2006–2016), Skåne (1998–2013), Östergötland (1997–2014), Stockholm (2003–2016), and Västergötland (2000–2013). Time periods for coverage differ because of the timing of the digitalization of records. In 2016, these 15 counties contained 87% of the Swedish population. We secured ethical approval for this study from the Regional Ethical Review Board of Lund University.
Major depression was identified in the Hospital Discharge, Outpatient (Specialist) Care, and Primary Care Registries by ICD code (ICD-8 codes 296.2, 298.0, and 300.4; ICD-9 codes 296.2, 296.4, 298.0, and 300.4; ICD-10 codes F32 and F33). The diagnosis could be registered at any time, although we required a first registration at age 15 or older. Individuals registered with schizophrenia (ICD-8 and ICD-9 code 295; ICD-10 code F20) or bipolar disorder (ICD-8 codes 296.1 and 296.3; ICD-9 codes 296.0, 296.1, and 296.4–8; ICD-10 codes F30 and F31) were censored from the sample.
For the first database, we selected from the Swedish Twin Registry all twin pairs with known zygosity and birth years between 1950 and 1990, and from the Swedish Multi-Generation Register all Swedish-born full- and half-sibling pairs born between 1950 and 1990 and within 5 years of each other. Zygosity was assigned using standard self-report items, which, when validated against biological markers, were 95%−99% accurate (25). Using the Swedish national census and population registers, we assessed cohabitation status for full- and half-sibling pairs as the proportion of possible years they lived in the same household until the oldest turned 16. We included pairs reared together and apart cohabiting for ≥80% or ≤20% of the possible years, respectively. Because the Primary Care Registry did not have complete national coverage, we required that both individuals in a pair have resided ≥8 years in a county that registered diagnoses in the Primary Care Registry before we included diagnoses from the register in our analyses.
Structural equation modeling was used to assess the contributions of genetic and environmental factors to liability for major depression, assuming a liability threshold model (26). In the first model, using monozygotic and dizygotic twins only, we assumed three sources of liability—additive genetic (A), shared environment (C), and unique environment (E)—and we assumed that monozygotic twins share all and dizygotic twins on average 50% of their genes identical by descent. Shared environment reflects family and community experiences that render the twins more similar for major depression, while unique environment includes environmental experiences not shared by twins, we well as error. In the second model, using full and half siblings, we employed the same modeling framework, assuming that full and half siblings share, on average 50% and 25% of genes, respectively, identical by descent. Shared environment (C) equaled 1 for pairs reared together and 0 pairs reared apart.
The second database was created by double-entering all cousin, half-sibling, full-sibling, and monozygotic twin pairs in the Swedish population in which both individuals in the pair were born in Sweden between 1970 and 1990, both were still residing in Sweden at age 15, the pair had no more than a 10-year age difference, and at least one of the pair (the proband) was registered for major depression. In concordant pairs in which both were registered with major depression, each was treated as a proband. Each pair was assigned their degree of genetic resemblance (1 for monozygotic twins; 0.5 for full siblings; 0.25 for half siblings; 0.125 for cousins). We also applied the same restriction as described above, including major depression diagnoses from the Primary Care Registry for pairs only when both members of the pair had resided at least 8 years in a county that used the Primary Care Registry.
Using Cox regression models, we investigated all pairs of relatives from age 15 until year of first registration of major depression in the relative, death or emigration of the relative, or end of follow-up (December 31, 2015), whichever came first. We examined eight putative indices of genetic risk for major depression in the proband: age at first registration, number of depressive episodes, lifetime history of an anxiety disorder (defined by ICD-9 codes 300.0 and 300.2 and ICD-10 codes F40 and F41), a history of antidepressant treatment, treatment by a psychiatrist, a history of ECT, sick-leave registration, and granting of early retirement. Details on these indices are provided in Table S1 in the online supplement .
In one model, we estimated results for each putative index in the four classes of relatives as a function of their genetic relationship. This model produced an estimated hazard ratio for each relative class and a measure of interaction—the significance of the difference of the hazard ratios across types of relatives. This model used data from all relatives to optimize the accuracy of hazard ratio estimates, which was especially important in monozygotic twin pairs, where the sample size was small. We controlled for the absolute age difference between the proband and relative, sex of the proband and the relative, and year of birth of the proband. Because there could be several pairs from the same cluster of relatives (e.g., sibships), we used robust standard errors to account for their nonindependence. In all models, we checked whether the regression coefficients varied over time. However, in no case were there substantial changes to our results.
In a final analysis, each covariate was standardized with a mean of zero and a standard deviation of 1, and then summarized across each proband to a summary z-score. We categorized the z-score into 10 equally sized groups and used these categories as covariates (using the lowest-risk group as the reference) in a Cox regression analysis in which we included the interaction between the z-score group and familial resemblance. This model produced an estimated hazard ratio for each relative class and for each z-score group and a measure of an interaction between them—the significance of the difference of the hazard ratios across types of relatives.
Results
The sample sizes and lifetime prevalences for major depression in twin, full-sibling, and half-sibling pairs are summarized in Table 1. Our samples were largest for full siblings reared together, intermediate for half siblings reared together and apart, and smallest for twins and full siblings reared apart. Our twin and sibling/half-sibling analyses included 26,892 and 1,691,971 pairs, respectively. Prevalences for major depression were similar for the three groups from intact families (monozygotic and dizygotic twins and full siblings reared together), around 7% in males and 12% in females. In the three groups from non-intact families (half siblings reared together and apart and full siblings reared apart), the rates were similar across groups and were 40%−50% higher in both males and females.
| Sibling Group and Sex | Pairs (N) | Lifetime Prevalence of Major Depression (%) | Tetrachoric Correlation | SE |
|---|---|---|---|---|
| Monozygotic twins | ||||
| Male-male | 3,580 | 7.1 | 0.428 | 0.044 |
| Female-female | 4,229 | 12.2 | 0.510 | 0.029 |
| Dizygotic twins | ||||
| Male-male | 3,815 | 6.4 | 0.181 | 0.055 |
| Female-female | 3,905 | 12.1 | 0.264 | 0.037 |
| Male-female | 10,649 | Males, 6.7; females, 11.9 | 0.224 | 0.027 |
| Full siblings reared together | ||||
| Male-male | 407,939 | 6.7 | 0.225 | 0.005 |
| Female-female | 360,187 | 12.5 | 0.242 | 0.004 |
| Male-female | 760,347 | Males, 6.9; females, 12.4 | 0.218 | 0.003 |
| Full siblings reared apart | ||||
| Male-male | 3,564 | 10.6 | 0.145 | 0.045 |
| Female-female | 2,694 | 17.8 | 0.241 | 0.038 |
| Male-female | 6,512 | Males, 10.8; females, 17.1 | 0.129 | 0.029 |
| Half siblings reared together | ||||
| Male-male | 13,166 | 9.7 | 0.165 | 0.024 |
| Female-female | 12,432 | 17.8 | 0.173 | 0.018 |
| Male-female | 25,089 | Males, 10.3; females, 17.5 | 0.149 | 0.015 |
| Half siblings reared apart | ||||
| Male-male | 26,596 | 9.6 | 0.083 | 0.018 |
| Female-female | 23,811 | 17.1 | 0.145 | 0.014 |
| Male-female | 49,634 | Males, 9.6; females, 16.8 | 0.126 | 0.011 |
Tetrachoric correlations for treated major depression ranged from 0.40 to 0.50 in monozygotic twins, 0.15 to 0.25 in full siblings, and 0.08 to 0.15 in half siblings (Table 1). Correlations were consistently higher in female-female compared with male-male pairs, same-sex compared with opposite-sex pairs, and reared-together compared with reared-apart pairs.
Table 2 presents the model-fitting results in our two samples. Parameter estimates were similar, with overlapping confidence intervals. The heritability of major depression was estimated in the twins at 0.41 (95% CI=0.21, 0.49) in males and 0.49 (95% CI=0.31, 0.56) in females. Parallel estimates from the full/half-sibling sample were, respectively, 0.36 (95% CI=0.31, 0.38) and 0.51 (95% CI=0.51, 0.53). Estimates for the shared environment were present in three of the analyses (all but male twins) but were small (≤ 5%). While the genetic correlation between the sexes was estimated at 1.00 in the twins, this is known imprecisely (95% CI=0.83, 1.00) and is consistent with the more accurate estimate from our full- and half-sibling sample (0.89, 95% CI=0.87, 0.91).
| Group | a2m | 95% CI | c2m | 95% CI | e2m | 95% CI | a2f | 95% CI | c2f | 95% CI | e2f | 95% CI | r | 95% CI |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Twins | 0.41 | 0.19, 0.49 | 0.00 | 0.00, 0.13 | 0.59 | 0.51, 0.66 | 0.49 | 0.31, 0.56 | 0.02 | 0.00, 0.17 | 0.49 | 0.44, 0.55 | 1.00 | 0.79, 1.00 |
| Full and half siblings | 0.36 | 0.31, 0.38 | 0.05 | 0.05, 0.05 | 0.59 | 0.58, 0.61 | 0.51 | 0.51, 0.53 | 0.02 | 0.02, 0.02 | 0.47 | 0.46, 0.49 | 0.89 | 0.87, 0.91 |
a
a2 refers to additive genetic effects or heritability; c2 refers to shared environmental effects; e2 refers to individual specific environmental effect (and measurement error); the subscripts “m” and “f” indicate males and females, respectively; r refers to genetic correlation between the sexes.
Table 3 includes the sample sizes used for our analyses of indices of genetic liability for major depression, which included 875,010 pairs of relatives, as well as descriptive information about these indices. The mean age at first registration was around 29 years, and the mean number of episodes of major depression was 2.3. Approximately 50% of the sample had an anxiety disorder diagnosis, 77% had received prescriptions for antidepressants, 34% were granted sick leave, and 9% were granted early retirement. Sixty-four percent of the sample received their diagnoses of major depression from nonpsychiatric physicians, largely in primary care settings.
| Measure or Group | Monozygotic Twins (N=701 Pairs) | Full Siblings (N=175,808 Pairs) | Half Siblings (N=66,320 Pairs) | Cousins (N=632,181 Pairs) | ||||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | N | % | |
| Major depression in relative | 247 | 35.2 | 35,011 | 19.9 | 13,724 | 20.7 | 92,128 | 14.6 |
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | |
| Age at registration | 29.6 | 5.7 | 28.3 | 5.8 | 28.5 | 6.1 | 28.6 | 6.0 |
| Number of episodes | 2.30 | 1.9 | 2.25 | 1.9 | 2.26 | 1.9 | 2.24 | 1.9 |
| Year of birth | 1979 | 1980 | 1980 | 1980 | ||||
| N | % | N | % | N | % | N | % | |
| Male-male pairs | 215 | 31 | 32,114 | 18 | 12,490 | 19 | 116,686 | 18 |
| Female-female pairs | 486 | 69 | 55,124 | 31 | 20,335 | 31 | 197,093 | 31 |
| Male-female pairs | 30,727 | 17 | 11,872 | 18 | 110,422 | 17 | ||
| Female-male pairs | 57,843 | 33 | 21,623 | 33 | 207,980 | 33 | ||
| Anxiety disorder registration | 350 | 50 | 89,843 | 51 | 36,364 | 55 | 323,406 | 51 |
| Antidepressants | 547 | 78 | 136,171 | 77 | 52,349 | 79 | 494,495 | 78 |
| Electroconvulsive therapy | 5 | <1 | 959 | <1 | 337 | <1 | 3,370 | <1 |
| Sick leave | 239 | 34 | 60,667 | 35 | 24,893 | 38 | 228,190 | 36 |
| Early retirement | 62 | 9 | 14,862 | 8 | 7,363 | 11 | 58,528 | 9 |
| No psychiatric registration | 451 | 64 | 107,610 | 63 | 37,231 | 56 | 374,441 | 59 |
| Psychiatric registration in specialist care | 169 | 24 | 50,414 | 29 | 20,737 | 31 | 189,822 | 30 |
| Psychiatric registration in inpatient care | 81 | 12 | 17,784 | 10 | 8,352 | 13 | 67,918 | 11 |
The risk for major depression in our four classes of relatives as a function of the presence or absence of the indices of liability in the proband is summarized in Table 4. Seven of these indices (all but sick leave) behaved in the predicted manner. That is, risk for major depression increased in relatives of probands with major depression who had multiple episodes, younger age at first registration, were treated by psychiatrists, received antidepressants or ECT, had a comorbid anxiety diagnosis, or were granted early retirement. Furthermore, as predicted for a genetic index, the increased risk in relatives was strongest in monozygotic twins, intermediate in siblings, weaker in half siblings, and weakest in cousins. The difference in hazard ratios across the four groups of relatives was significant for all indices except ECT.
| Monozygotic Twins | Full Siblings | Half Siblings | Cousins | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Measure | Hazard Ratio | 95% CI | Hazard Ratio | 95% CI | Hazard Ratio | 95% CI | Hazard Ratio | 95% CI | pb |
| Number of episodes | |||||||||
| 1 | Ref | Ref | Ref | Ref | |||||
| 2 | 1.23 | 1.16, 1.32 | 1.13 | 1.10, 1.16 | 1.08 | 1.06, 1.09 | 1.05 | 1.04, 1.07 | <0.001 |
| 3–4 | 1.44 | 1.35, 1.54 | 1.22 | 1.19, 1.25 | 1.12 | 1.10, 1.14 | 1.07 | 1.06, 1.09 | <0.001 |
| ≥5 | 1.86 | 1.72, 2.01 | 1.36 | 1.32, 1.41 | 1.17 | 1.15, 1.19 | 1.18 | 1.06, 1.10 | <0.001 |
| Age at diagnosis | |||||||||
| Impact of 1-year decrease in age at diagnosis | 1.05 | 1.04, 1.05 | 1.02 | 1.02, 1.02 | 1.00 | 1.00, 1.01 | 1.00 | 1.00, 1.00 | <0.001 |
| ≤21 years versus older | 1.78 | 1.65, 1.91 | 1.25 | 1.21, 1.29 | 1.04 | 1.03, 1.06 | 0.96 | 0.94, 0.97 | <0.001 |
| ≤25 years versus older | 1.63 | 1.55, 1.72 | 1.22 | 1.19, 1.25 | 1.05 | 1.04, 1.07 | 0.98 | 0.96, 1.00 | <0.001 |
| Antidepressants | 1.49 | 1.40, 1.58 | 1.18 | 1.15, 1.21 | 1.05 | 1.04, 1.07 | 1.00 | 0.98, 1.01 | <0.001 |
| ECT | 1.26 | 0.91, 1.76 | 1.05 | 0.92, 1.20 | 0.96 | 0.89, 1.04 | 0.92 | 0.84, 1.00 | 0.09 |
| Specialist or inpatient care | |||||||||
| None | Ref | Ref | Ref | Ref | |||||
| Specialist care | 1.18 | 1.12, 1.25 | 0.98 | 0.96, 1.01 | 0.90 | 0.89, 0.91 | 0.86 | 0.84, 0.87 | <0.001 |
| Inpatient care | 1.22 | 1.13, 1.33 | 1.01 | 0.97, 1.04 | 0.91 | 0.90, 0.093 | 0.87 | 0.85, 0.89 | <0.001 |
| Anxiety disorder | 1.47 | 1.40, 1.55 | 1.22 | 1.20, 1.25 | 1.11 | 1.10, 1.13 | 1.06 | 1.05, 1.08 | <0.001 |
| Sick leave | 0.91 | 0.86, 0.96 | 0.98 | 0.96, 1.00 | 1.01 | 1.01, 1.02 | 1.03 | 1.02, 1.04 | <0.001 |
| Early retirement | 1.40 | 1.28, 1.52 | 1.16 | 1.12, 1.20 | 1.06 | 1.04, 1.08 | 1.01 | 0.99, 1.03 | <0.001 |
a
Analyses controlled for year of birth, sex, and age difference in relative pairs. The results presented are from a model applied to all four groups of relatives.
b
The p value is for the interaction between genetic resemblance and predictor.
We combined all our risk indices (except sick leave) into a single weighted score, calculated deciles of probands on that score, and examined risk of major depression in their relatives. The results are depicted in Figure S1 and Table S2 in the online supplement . Compared with relatives of probands at lowest genetic risk, the risk for major depression in the top decile was 2.82 higher in monozygotic co-twins and 1.53 times higher in full siblings of probands.
To estimate the contribution of individual risk indices, we included all of them except sick leave in a multivariate model predicting risk of illness in our classes of relatives and indexed their effect size by the chi-square value of their individual effects on risk in monozygotic co-twins. In order, the chi-square values were 339.6 for age at first registration, 147.7 for number of episodes, 109.8 for comorbid anxiety disorder, 77.3 for referral to psychiatric care, 38.2 for treatment with antidepressants, and 15.2 for having been granted early retirement. Receipt of ECT was not significantly associated with estimated risk (χ2=0.5).
Discussion
This study addressed three major questions, which we review in turn.
Estimation of Heritability in Twin Studies
First, for several decades concerns have been repeatedly raised that twin studies overestimate heritability (15–18). This issue has taken on new urgency with the “missing heritability problem” in genome-wide association studies (14). Numerous empirical attempts have been made to test these putative biases (e.g., 29–31), with results typically suggesting little if any effect on parameter estimates. In this study, we took a different approach by utilizing an independent genetic-epidemiological design in the same population using the same diagnostic methods.
Like monozygotic and dizygotic twins, full siblings and half siblings differ in their sharing of genes identical by descent. Half siblings have the additional advantage of being the only common same-generation human relationship for which large proportions are reared together in the same family and reared apart. Unlike twins, neither full nor half siblings are the product of the same pregnancy, so concerns about differences in intrauterine experiences (e.g., a substantial proportion of monozygotic twins share the same placenta, whereas no dizygotic pairs do [32]) or the increased rates of prematurity and birth defects in both monozygotic and dizygotic twins are not relevant (32). Siblings rarely have the striking physical resemblance seen in monozygotic twins, which has raised concerns about the specialness of their social environment and the degree to which it is more similar than that experienced by dizygotic twins. Siblings are not born at the same time, do not share de novo variants, and are not subject to possible differences in parenting that may occur in twins, where monozygotic twins are more likely to be regarded as a pair (e.g., “the twins”) while dizygotic twins are more often seen as separate individuals (33).
The estimation of heritability in the full/half-sibling design is conceptually identical to that used in twin studies comparing relatives with a mean of 50% and 25% genetic similarity rather than 100% and 50%. However, estimation of shared environment is different, with the full/half-sibling design being methodologically stronger. Instead of inferring effects of shared environment from patterns of similarity of reared-together twin pairs, we directly compare full and half siblings raised together and those raised apart.
Our heritability estimates for major depression from our twin and full/half-sibling analyses were very similar, with overlapping confidence intervals. These results provide no support for the hypothesis that twin studies overestimate the heritability of major depression. Our results are consistent with previous analyses using sibling designs that found that standard twin models do not overestimate the heritability of alcohol use disorder, drug abuse, or criminality (19). Inflated estimates from twin studies for the heritability of major depression are unlikely contributors to the “missing heritability problem.”
The Genetic Epidemiology of Major Depression
Our second goal was to examine, in the largest sample studied to date, important features of the genetic epidemiology of major depression. Consistent with most (6, 21) but not all previous studies (7) or with the major meta-analysis that has been published (7), we found strong evidence for a higher heritability for major depression in women than in men. In our powerful full/half-sibling sample, we could reject the hypothesis that the genetic risk factors for major depression were entirely the same or acted in the same manner in the two sexes. However, the estimate of the genetic correlation was relatively high (0.89), and it was higher than that estimated in previous twin studies (21, 22), which detected qualitative sex effects. Given that the genetic correlation needs to be squared to estimate the proportion of shared genetic effects, our study suggests that ∼80% of the genetic variance for major depression is shared between men and women.
Interestingly, previous twin studies of major depression have consistently failed to detect shared/familial environmental effects. This may be due to the low power to detect such effects in the presence of appreciable genetic influences (34). However, for both full and half siblings, we saw clear trends for the similarity of major depression to be stronger in reared-together than reared-apart pairs. As expected given this pattern, we found modest evidence for shared environmental effects for both men and women in our sibling analyses. These findings are consistent with our recent results from an extended adoption study of major depression in Sweden (35), which found significant correlations between major depression in adoptive and stepparents and their nonbiological children.
Finally, our estimates of the heritability of major depression are modestly higher than those from previous twin samples. In the major meta-analysis (7), which incorporated results from both males and females, the aggregate estimate was 37% (95% CI=31, 42). In the one large-scale personal interview study published since then (21), heritability was estimated at 29% in men and 42% in women. The most plausible explanation for this discrepancy is differential sampling. Most twin studies of major depression have utilized epidemiological samples (7, 21), whereas we studied a treated sample. Given evidence that multiple indices of clinical severity predict genetic loading for major depression, our modestly higher heritability probably arises from the fact that the depressive cases in our sample were more severe on average.
Clinical Indices of Genetic Risk in Major Depression
Can we, using commonly available clinical indices, meaningfully assess the level of genetic liability of patients with major depression? The literature (7, 24) suggests that early onset, recurrence, impairment, clinical severity, and comorbidity in depressed probands are among the most consistent predictors of risk in their relatives. However, not all studies found such effects, many were underpowered, and a substantial proportion of them were family studies that could not discriminate whether these indices reflected familial or genetic risk.
Using over 875,000 pairs of relatives, we found that seven of our eight putative indices of genetic liability predicted risk for major depression in relatives of affected probands and predicted risk significantly more strongly in closely related relatives. Consistent with previous results, these seven risk indices were divisible into four categories: early age at onset, recurrence, comorbidity with anxiety disorder, and severity, as indexed by referral to psychiatric care, receipt of antidepressants or ECT, and provision of early retirement in response to psychosocial dysfunction. In our multivariate models, age at onset, recurrence, and comorbid anxiety disorders were the strongest predictors of risk for major depression in relatives, but three of the four indices of clinical severity (all but ECT) also contributed significantly to the prediction.
When we formed these seven indices into a single risk score, the aggregate predictive power was appreciable. In the most informative relationship—monozygotic twins—the risk for major depression in the co-twin of a monozygotic twin with major depression in the lowest and highest deciles was estimated at 23.5% and 53.0%, respectively.
Limitations
These results need to be considered in the context of six potentially important methodological limitations. First, we studied only treated major depression. No large-sample epidemiological studies of psychiatric illness have been performed in Sweden. However, an interview-based assessment utilizing modified DSM-IV criteria was performed on over 40,000 twins and produced lifetime estimates for major depression of 25.1% in women and 13.2% in men (21). These results are broadly similar to those obtained using DSM-III-R criteria in an epidemiological interview survey in Norway: 24.0% and 9.9%, respectively (36). When compared with the rates of treated major depression found in the present study (12.2% and 7.1%, respectively), these results suggest that in Sweden, as in other high-income countries (37–39), some 50%−60% of individuals with lifetime depression seek treatment for their condition. Second, half siblings reared together are typically the product of families separated by premature death or divorce and have elevated rates of a broad range of psychopathologies (40). This is statistically controlled for in our analyses by setting different thresholds on the liability distribution. But in this regard, these pairs are not perfectly matched to the reared-together full siblings. Third, we did not distinguish between maternal and paternal half siblings in our models, largely because of the rarity of reared-together paternal half siblings. However, as outlined in Table S3 in the online supplement , among the reared-apart half siblings, correlations for major depression were quite similar in the maternal and paternal pairs. Fourth, our definition of reared-together and reared-apart half siblings was arbitrary. We explored other definitions (see Table S4 in the online supplement ) and showed that they had little effect on our results. Fifth, because we wanted to study classical cases of “unipolar” major depression, we excluded individuals who had a lifetime diagnosis of bipolar illness or schizophrenia. To see if this decision had a meaningful impact on our findings, we repeated all analyses without this exclusion (see Tables S5–S8 and Figure S1 in the online supplement ). Our results were altered only slightly. Finally, our conclusion about the accuracy of the heritability estimation in the twin method was based on the congruence of findings from the twin and full/half-sibling method. If the latter substantially overestimates heritability, then our inference regarding the accuracy of the twin method would be faulty.
Acknowledgments
The authors thank the Swedish Twin Registry at Karolinska Institute, which provided the twin data for this study.
Supplementary Material
File (appi.ajp.2018.17111251.ds001.pdf)
- View/Download
- 230.66 KB
References
1.
Gershon ES, Weissman MM, Guroff JJ, et al: Validation of criteria for major depression through controlled family study. J Affect Disord 1986; 11:125–131
2.
Weissman MM, Wickramaratne P, Merikangas KR, et al: Onset of major depression in early adulthood: increased familial loading and specificity. Arch Gen Psychiatry 1984; 41:1136–1143
3.
McGuffin P, Katz R, Watkins S, et al: A hospital-based twin register of the heritability of DSM-IV unipolar depression. Arch Gen Psychiatry 1996; 53:129–136
4.
Kendler KS, Neale MC, Kessler RC, et al: A population-based twin study of major depression in women: the impact of varying definitions of illness. Arch Gen Psychiatry 1992; 49:257–266
5.
Kendler KS, Prescott CA: A population-based twin study of lifetime major depression in men and women. Arch Gen Psychiatry 1999; 56:39–44
6.
Bierut LJ, Heath AC, Bucholz KK, et al: Major depressive disorder in a community-based twin sample: are there different genetic and environmental contributions for men and women? Arch Gen Psychiatry 1999; 56:557–563
7.
Sullivan PF, Neale MC, Kendler KS: Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry 2000; 157:1552–1562
8.
Yang J, Zeng J, Goddard ME, et al: Concepts, estimation, and interpretation of SNP-based heritability. Nat Genet 2017; 49:1304–1310
9.
Lee SH, Ripke S, Neale BM, et al: Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet 2013; 45:984–994
10.
Wray NR, Lee SH, Mehta D, et al: Research review: polygenic methods and their application to psychiatric traits. J Child Psychol Psychiatry 2014; 55:1068–1087
11.
CONVERGE consortium: Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature 2015; 523:588–591
12.
Hyde CL, Nagle MW, Tian C, et al: Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet 2016; 48:1031–1036
13.
Wray NR, Ripke S, Mattheisen M, et al: Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet 2018; 50:668–681
14.
Manolio TA, Collins FS, Cox NJ, et al: Finding the missing heritability of complex diseases. Nature 2009; 461:747–753
15.
Chen X, Kuja-Halkola R, Rahman I, et al: Dominant genetic variation and missing heritability for human complex traits: insights from twin versus genome-wide common SNP models. Am J Hum Genet 2015; 97:708–714
16.
Joseph J: Twin studies in psychiatry and psychology: science or pseudoscience? Psychiatr Q 2002; 73:71–82
17.
Pam A, Kemker SS, Ross CA, et al: The “equal environments assumption” in MZ-DZ twin comparisons: an untenable premise of psychiatric genetics? Acta Genet Med Gemellol (Roma) 1996; 45:349–360
18.
Taylor PJ: Nature-Nurture? No: Moving the Sciences of Variation and Heredity Beyond the Gaps. Arlington, Mass, Pumping Station, 2014
19.
Kendler KS, Ohlsson H, Edwards AC, et al: A novel sibling-based design to quantify genetic and shared environmental effects: application to drug abuse, alcohol use disorder, and criminal behavior. Psychol Med 2016; 46:1639–1650
20.
Pettersson E, Larsson H, Lichtenstein P: Common psychiatric disorders share the same genetic origin: a multivariate sibling study of the Swedish population. Mol Psychiatry 2016; 21:717–721
21.
Kendler KS, Gatz M, Gardner CO, et al: A Swedish national twin study of lifetime major depression. Am J Psychiatry 2006; 163:109–114
22.
Kendler KS, Gardner CO, Neale MC, et al: Genetic risk factors for major depression in men and women: similar or different heritabilities and same or partly distinct genes? Psychol Med 2001; 31:605–616
23.
Kendler KS, Pedersen N, Johnson L, et al: A pilot Swedish twin study of affective illness, including hospital- and population-ascertained subsamples. Arch Gen Psychiatry 1993; 50:699–700
24.
Kendler KS, Gatz M, Gardner CO, et al: Clinical indices of familial depression in the Swedish Twin Registry. Acta Psychiatr Scand 2007; 115:214–220
25.
Sundquist J, Ohlsson H, Sundquist K, et al: Common adult psychiatric disorders in Swedish primary care where most mental health patients are treated. BMC Psychiatry 2017; 17:235
26.
Falconer DS: The inheritance of liability to certain diseases, estimated from the incidence among relatives. Ann Hum Genet 1965; 29:51–76
27.
SAS/STAT Online Documentation: Version 9.4. Cary, NC, SAS Institute, 2012
28.
Neale MC, Hunter MD, Pritikin JN, et al: OpenMx 2.0: extended structural equation and statistical modeling. Psychometrika 2016; 81:535–549
29.
Kendler KS, Prescott CA: Genes, Environment, and Psychopathology: Understanding the Causes of Psychiatric and Substance Use Disorders. New York, Guilford, 2006
30.
Conley D, Rauscher E, Dawes C, et al: Heritability and the equal environments assumption: evidence from multiple samples of misclassified twins. Behav Genet 2013; 43:415–426
31.
Barnes JC, Wright JP, Boutwell BB, et al: Demonstrating the validity of twin research in criminology. Criminology 2014; 52:588–626
32.
Keith LG, Papiernik E, Keith DM, et al. (eds): Multiple Pregnancy, Epidemiology, Gestation, and Perinatal Outcome. New York, Parthenon, 1995
33.
Kendler KS, Neale MC, Kessler RC, et al: Parental treatment and the equal environment assumption in twin studies of psychiatric illness. Psychol Med 1994; 24:579–590
34.
Neale MC, Eaves LJ, Kendler KS: The power of the classical twin study to resolve variation in threshold traits. Behav Genet 1994; 24:239–258
35.
Kendler KS, Ohlsson H, Sundquist K, et al: Sources of parent-offspring resemblance for major depression in a national Swedish extended adoption study. JAMA Psychiatry 2018; 75:194–200
36.
Kringlen E, Torgersen S, Cramer V: A Norwegian psychiatric epidemiological study. Am J Psychiatry 2001; 158:1091–1098
37.
Olfson M, Marcus SC, Druss B, et al: National trends in the outpatient treatment of depression. JAMA 2002; 287:203–209
38.
Kessler RC, Berglund P, Demler O, et al: The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 2003; 289:3095–3105
39.
Bromet EJ, Andrade LH, Bruffaerts R, et al: Major Depressive Disorder, in Mental Disorders Around the World: Facts and Figures From the World Mental Health Surveys. Edited by Scott KM, de Jonge P, Stein D, et al. New York, Cambridge University Press, 2018, pp 41–56
40.
Kendler KS, PirouziFard M, Lönn S, et al: A national Swedish twin-sibling study of alcohol use disorders. Twin Res Hum Genet 2016; 19:430–437
Information & Authors
Information
Published In
History
Received: 19 November 2017
Revision received: 19 February 2018
Revision received: 6 April 2018
Accepted: 19 April 2018
Published online: 19 July 2018
Published in print: November 01, 2018
Keywords
Authors
Competing Interests
The authors report no financial relationships with commercial interests.
Funding Information
Supported by the Swedish Research Council (2014-2517, 2014-10134, and 2016-01176) and ALF funding from Region Skåne.
Metrics & Citations
Metrics
Citations
Export Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
For more information or tips please see 'Downloading to a citation manager' in the Help menu.
View Options
View options
PDF/EPUB
View PDF/EPUBGet Access
Login options
Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.
Personal login Institutional Login Open Athens loginNot a subscriber?
PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.
Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).