Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology

Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology Jiook Cha, Eunji Lee, Milenna van Dijk, Bogyeom Kim, Gakyung Kim, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4264742/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Sep, 2025 Read the published version in Molecular Psychiatry → Version 1 posted 9 You are reading this latest preprint version Abstract A family history of depression is a well-documented risk factor for offspring psychopathology. However, the genetic mechanisms underlying the intergenerational transmission of depression remain unclear. We used genetic, family history, and diagnostic data from 11,875 9–10 year-old children from the Adolescent Brain Cognitive Development study. We estimated and investigated the children’s polygenic scores (PGSs) for 30 distinct traits and their association with a family history of depression (including grandparents and parents) and the children's overall psychopathology through logistic regression analyses. We assessed the role of polygenic risk for psychiatric disorders in mediating the transmission of depression from one generation to the next. Among 11,875 multi-ancestry children, 8,111 participants had matching phenotypic and genotypic data (3,832 female [47.2%]; mean (SD) age, 9.5 (0.5) years), including 6,151 [71.4%] of European ancestry). Greater PGSs for depression (estimate = 0.129, 95% CI = 0.070–0.187) and bipolar disorder (estimate = 0.109, 95% CI = 0.051–0.168) were significantly associated with higher family history of depression (Bonferroni-corrected P < .05). Depression PGS was the only PGS that significantly associated with both family risk and offspring’s psychopathology, and robustly mediated the impact of family history of depression on several youth psychopathologies including anxiety disorders, suicidal ideation, and any psychiatric disorder (proportions mediated 1.39%-5.87% of the total effect on psychopathology; FDR-corrected P < .05). These findings suggest that increased polygenic risk for depression partially mediates the associations between family risk for depression and offspring psychopathology, showing a genetic basis for intergenerational transmission of depression. Future approaches that combine assessments of family risk with polygenic profiles may offer a more accurate method for identifying children at elevated risk. Health sciences/Biomarkers/Predictive markers Health sciences/Diseases/Psychiatric disorders/Depression Biological sciences/Genetics Biological sciences/Psychology Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Depression runs in families, often manifesting in various forms of mental disorders. Parental depression increases the offspring's risk of developing depression and other psychopathology, such as anxiety, disruptive disorders and substance use, by 2–5 times [ 1 – 3 ]. Children with a family history of depression often develop the disorder at a younger age, even in childhood [ 3 ]. Although the familial transmission of depression is established, the intricate mechanisms through which genetic predispositions and environmental factors contribute to the intergenerational transmission of depression and related psychopathologies are not yet fully understood [ 4 , 5 ]. Offspring with both a parent and at least one grandparent with depression are at an even higher risk for developing psychopathology [ 6 , 7 ]. We first found this using a longitudinal three-generational study, which used carefully crafted interview-based diagnoses for every family member, from children to adults [ 7 – 9 ] (Warner, Weissman et al., 1999), and these findings were confirmed by other moderate sized studies [ 10 , 11 ]. We recently generalized these findings to a large, diverse cohort of preadolescents in the Adolescent Brain and Cognitive Development (ABCD) study. This study showed a significant association between family history of depression and offspring's risk of psychopathology regardless of sociodemographic characteristics such as sex, socioeconomic status (SES), and race/ethnicity [ 6 ]. Psychiatric disorders have a high degree of heritability, estimated for depression around 30–50% [ 12 ] and up to 80% for schizophrenia [ 13 , 14 ]. These numbers came initially from twin studies [ 15 ], which cannot readily distinguish between genetic and intrauterine and perinatal factors or differences between parenting monozygotic versus dizygotic twins. Recent adoption studies, which found a larger component attributed to being reared by a depressed (step/adoptive) parent, questioned whether the genetic component of intergenerational depression was overestimated in these early twin studies [ 16 , 17 ]. A recent large-scale registry study, however, confirmed the initial heritability estimates [ 18 ]. These studies suggest a strong role for genetics in the transmission of depression between generations. Nonetheless, the variance explained by genetic components is not attributed to a few candidate genes or variants, but rather to the cumulative impact of numerous variants, each with small effects. As an example, a meta-analysis involving three independent depression genome-wide association studies (GWASs), with a total sample size of 807,553 participants, identified 102 genome-wide significant variants and 269 putative genes associated with depression [ 19 ]. Polygenic scores (PGSs) represent an estimate of relative cumulative genetic risk of an individual for the phenotype of interest, such as depression, based on the findings of GWAS. PGSs for psychiatric disorders are associated with increased risk for psychopathology in the general population [ 20 ]. Some studies have jointly examined PGS and family history in association with psychopathology, but the findings have been mixed. PGS for depression was associated with a continuous score of first-degree (parents and siblings) family history loading for depression [ 21 ], but two other studies found no association between first-degree family history and depression PGS [ 22 , 23 ], perhaps because they used the data from earlier and smaller GWASs. Furthermore, while various psychopathology PGSs were found to be associated with mood and psychotic disorder onsets, only non-psychopathology PGSs for neuroticism and wellbeing were associated with onsets independent of family history [ 24 ]. Thus, it remains unclear how family history for depression and PGSs are associated with offspring psychopathology onset. Importantly, to our best knowledge, no studies have yet reported whether family history of depression over two generations is linked to greater polygenic risk for mental disorders. In the present study, we first test whether multigenerational family risk for depression (having both a parent and a grandparent with depression) is independently associated with greater polygenic risk for psychiatric disorders. Then we test whether PGSs are associated with the presence of psychopathology. We hypothesize that as more previous generations have been affected by depression, a greater genetic risk for psychopathology and related behavioral vulnerabilities would have been accumulated in the offspring, Since psychiatric disorders are genetically correlated with non-psychiatric phenotypes such as educational attainment, subjective wellbeing, and risky behaviors [ 25 – 27 ], polygenic scores for a broad array of phenotypes were used to test our research questions. Lastly, we explore whether PGSs partially mediate the association between multigenerational family risk for depression and higher rates of psychiatric diagnoses in the offspring. We test this using a mediation model that incorporates depression PGS, alongside family risk and clinical data, in the ABCD study, which has the advantage of large sample size and generalizability, making it well-suited for rigorous genetic analyses. Methods Participants and Data Source This study used baseline data of 11,875 participants aged 9–10 years from the ABCD study release 2.01, collected September 2016-November 2018 [ 28 ] across 21 research sites in the United States. The genetic ancestry of children to categorize the sample was obtained from release 3.0 ( https://nda.nih.gov/study.html?id=901 ). All procedures for data collection were approved by the centralized institutional review board (IRB) at University of California, San Diego. Caretakers provided written informed consent and children provided assent. We imputed missing values of covariates and excluded participants without genotypes, family history, and clinical outcomes. After preprocessing genotype data and validating PGSs with a validation set, 8,620 samples remained. From 8,620 genotyped samples, we excluded anyone with missing values of family history (n = 493) and KSADS-5 (n = 507). The final sample (Fig. 1 ) included 8,111 unrelated multiethnic children, consisting of 6,151 [71.4%] participants of European ancestry, 1,285 [14.9%] African ancestry, 315 [3.7%] admixed American ancestry, 106 [1.2%] East Asian ancestry, and 254 [2.9%] unidentified ancestry. Polygenic Scores Genotyping was done using saliva samples of ABCD study participants at the baseline visit. See Supplementary Methods for Quality Assurance of the genotype data. We constructed the PGSs of 30 complex traits selected for their relationship to psychiatric disorders, using publicly available GWAS summary statistics: Attention-deficit/hyperactivity disorder (ADHD) [ 29 ], cognitive performance (CP) [ 30 ], educational attainment (EA) [ 30 ], major depressive disorder (MDD) [ 31 ], insomnia [ 32 ], snoring [ 32 ], intelligence quotient (IQ) [ 33 ], post-traumatic stress disorder (PTSD) [ 34 ], depression [ 19 , 35 ], body mass index (BMI) [ 36 , 37 ], alcohol dependence [ 38 ], autism spectrum disorder (ASD) [ 39 ], automobile speeding propensity (ASP) [ 25 ], bipolar disorder [ 40 ], cannabis during lifetime (cannabis use) [ 41 ], ever smoker [ 25 ], shared effects on five major psychiatric disorder (cross disorder) [ 42 ], alcoholic drinks consumption per week (drinking) [ 25 ], eating disorder [ 43 ], neuroticism [ 44 ], obsessive-compulsive disorder (OCD) [ 45 ], first principal components of four risky behaviors (risky behaviors) [ 25 ], general risk tolerance [ 25 ], schizophrenia [ 46 , 47 ], worrying [ 44 ], anxiety [ 48 ], subjective well-being (SWB) [ 26 ], general happiness, and general happiness for health (happiness-health) and meaningful life (happiness-life) ( http://www.nealelab.is/ukbiobank/ ). All GWASs were European-only samples. For depression, BMI, alcohol dependence, PTSD, and schizophrenia, non-European GWAS was also available, so a polygenic score calculated from multiple GWASs was constructed for these five traits. Therefore, for these traits, we estimated two different versions of each PGS; European GWAS-based PGSs and multiethnic GWAS-based PGSs. The posterior effect sizes of single nucleotide polymorphisms (SNPs) were estimated using PRS-CSx [ 49 ], a Bayesian approach that enables the merging of multiple GWAS summary statistics from diverse populations. The final scores were calculated using PLINK version 1.9 and controlled for the first ten genetic principal components. The optimal hyperparameter (global shrinkage hyperparameter in PRS-CSx) for PGSs was selected in a held-out validation set of 1,579 unrelated participants. These participants were genetically related to the final samples and therefore were excluded from the primary analyses. Details about the GWASs and validation procedures of PGSs are presented in Supplementary Table 1 and Supplementary Methods in Supplementary Material . Measures All assessments were reported previously in van Dijk et al. (2021) published in JAMA Psychiatry [ 6 ]. The ABCD Family History Assessment was used to collect caregivers’ reports on the history of grandparents (generation 1 [G1]) and parents (generation 2 [G2]) (Rice et al., 1995). We created a four-level depression risk variable, which describes risk levels of depression history from the two generations: (1) neither G1 nor G2 (G1-/G2-; a reference level), (2) only G1 (G1+/G2-), (3) only G2 (G1-/G2+), and (4) both G1 and G2 (G1+/G2+). Having one parent or one grandparent was sufficient to be categorized as having a parent (G2+) or grandparent (G1+) with depression. Additionally, we developed a binary “any family history” indicator to simplify the analysis. This indicator contrasts families with no reported depression history in either generation (G1-/G2-) against those with a reported history in at least one generation, so collapsing G1+/G2-, G1-/G2+, and G1+/G2 + groups into one variable “FamHist+”. Furthermore, we introduced a parental history indicator (G2- vs. G2+), specifically to highlight the impact of having a parent with a history of depression. This indicator focuses on the more immediate familial influence, distinguishing between participants without a parental history of depression (G2-) and those with such a history (G2+). Childhood psychopathology was assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) [ 50 , 51 ] reported by parents and children. Parent and child reports were separately analyzed; therefore, a total of 36 clinical variables were included in the analyses. Further details for the measures are in the Supplementary Methods . Potential Confounders We used the following 13 covariates to adjust for potential confounding effects: child’s age, sex, race/ethnicity, sexual orientation reported by child and parent, gender identity, religious preference, country of birth, reporter’s relationship to child, total household income, and caregiver’s age, education level, and marital status. Multiple imputation method using the R package ‘mice’ v3.14.0 was employed to impute missing values in covariates (See Supplementary Methods ). Statistical Analysis We primarily analyzed (using R version 4.2.0.) the data of 8,111 multi-ancestry children. We repeated the analyses in 6,151 European-ancestry samples to test for ancestral bias. Bonferroni and false discovery rate (FDR) corrections for the number of tests were applied to each analysis with significance set at adjusted P < .05. We centered and scaled the PGSs and continuous variables of covariates to obtain standardized estimates from regression analyses. Association and Mediation Analysis . Association between family history of depression and PGSs was assessed using univariate linear models, with the family history indicator as the independent variable and PGS as the dependent variable. Firth logistic regression was used when KSADS was the outcome with family risk and/or PGS as predictors including covariates [ 52 ]. Firth‘s approach helps reduce bias in highly imbalanced data by penalizing the likelihood function. We computed 95% confidence intervals (CIs) and McFadden‘s pseudo R 2 with penalized log-likelihood [ 53 ]. For mediation analysis (using package ‘ mediation ’ v4.5.0), we selected the PGSs that were significantly associated with both clinical outcome and family history of depression and tested these as candidate mediator. The treatment variable was the familial risk of depression, considering the lowest risk (G1−/G2−) as the control condition and the others (either G1 + or G2+) as the treatment condition. Clinical outcomes that were significantly associated with both PGS and family history of depression were examined as outcome. We additionally tested the models with parental risk only. Significance of the direct effects of familial risk and the mediation effects of PGSs were estimated using bootstrap samples (n = 1,000). Additional Assessment/Sensitivity Analysis Our main analyses defined depression family history only by the depression question in the Family History Assessment. However, this does not exclude individuals who might have both depression and mania (e.g. likely bipolar disorder). Therefore, we performed a sensitivity analysis (n = 6,925 multi-ancestry participants, including n = 5,274 European-ancestry) removing children who have parents or grandparents with mania obtained from the Family History Assessment (Fig. 1 ). Results Participants The complete phenotype and genotype data from 8,111 unrelated multi-ancestry children were available for analysis, including 6,151 European-ancestry children. 8,111 multi-ancestry children consist of 3,832 [47.2%] females with a mean [SD] age at baseline of 9.48 [0.51] years. Of European-ancestry children, 2,860 [46.5%] were female, and the mean [SD] age was 9.48 [0.51] years (Table 1 ). Table 1 Demographics and family history of depression for multi-ancestry and European-ancestry participants Multi-ancestry (n = 8,111) European-ancestry (n = 6,151) Test statistics Child’s demographics N (%) Mean (SD) N (%) Mean (SD) t / χ 2 P Age 9.48 (0.51) 9.48 (0.51) 0.119 0.905 Sex Male 4,279 (52.76) 3,291 (53.50) 0.786 0.375 Female 3,832 (47.24) 2,860 (46.50) Race/Ethnicity Hispanic 1,772 (21.85) 1,204 (19.57) 958.460 < 0.001 Non-Hispanic black 1,203 (14.83) 45 (0.73) Non-Hispanic white 4,996 (61.60) 4,833 (78.57) Other 140 (1.73) 69 (1.12) Sexual Orientation (parent report) Yes 3 (0.04) 1 (0.02) 13.141 0.004 Maybe/Don’t know 648 (7.99) 595 (9.67) No 7,390 (91.11) 5,499 (89.40) Decline to answer 70 (0.86) 56 (0.91) Sexual Orientation (child report) Yes 31 (0.38) 26 (0.42) 2.338 0.505 Maybe 72 (0.89) 61 (0.99) No 6,006 (74.05) 4,488 (72.96) I do not understand this question 2,002 (24.68) 1,576 (25.62) Gender identity (parent report) Male 4,276 (52.72) 3,288 (53.45) 1.062 0.900 Female 3,828 (47.20) 2,856 (46.43) Trans male 0 (0.00) 0 (0.00) Trans female 2 (0.02) 2 (0.03) Gender queer 1 (0.01) 1 (0.02) Other identity 4 (0.05) 4 (0.07) Religious preference Agnostic/Atheist 379 (4.67) 366 (5.95) 15.863 < 0.001 Denominational 5,889 (72.61) 4,316 (70.17) Non-denominational 1,843 (22.72) 1,469 (23.88) Country of birth USA and territories 7,887 (97.24) 5,994 (97.45) 0.589 0.443 Other 224 (2.76) 157 (2.55) Caregiver’s demographics N (%) Mean (SD) N (%) Mean (SD) t / χ 2 P Relationship with child Biological mother 6,970 (85.93) 5,284 (85.90) 12.389 0.0147 Biological father 803 (9.90) 668 (10.86) Adoptive parent 158 (1.95) 85 (1.38) Custodial parent 78 (0.96) 45 (0.73) Other 102 (1.26) 69 (1.12) Age 39.96 (6.78) 40.72 (6.36) 0.123 0.902 Marital status Married 5,537 (68.27) 4,727 (76.85) 211.720 < 0.001 Widowed 60 (0.74) 41 (0.67) Divorced 742 (9.15) 571 (9.28) Separated 305 (3.76) 189 (3.07) Never married 968 (11.93) 342 (5.56) Living with partner 499 (6.15) 281 (4.57) Household income 7.16 (2.44) 7.77 (2.01) 0.736 0.462 Parental education 16.63 (2.75) 17.18 (2.34) 1.037 0.300 Family history of depression G1-/G2- 4,658 (57.43) 3,284 (53.39) 30.870 < 0.001 G1+/G2- 1,092 (13.46) 967 (15.72) G1-/G2+ 882 (10.87) 650 (10.57) G1+/G2+ 1,479 (18.23) 1,250 (20.32) G1, generation 1; G2, generation 2 Association between Familial Risks and Polygenic Scores First, we tested whether multigenerational family risk for depression is associated with greater polygenic risk. Our primary analysis included all children (a multi-ancestry sample), and our supporting analysis included only European-ancestry children to test for potential bias related to ancestry. Our analyses using linear regression without adjusting for potential confounders demonstrated a significant association between multigenerational family risk for depression and increased PGSs for depression (estimate, 0.143 [95% CI, 0.084–0.201]), neuroticism (estimate, 0.112 [95% CI, 0.053–0.170]), and bipolar disorder (estimate, 0.108 [95% CI, 0.050–0.167]; Bonferroni-corrected P < .05; Supplementary Fig. 1A ). Specifically, children from the highest familial risk category (G1+/G2+) displayed significantly elevated polygenic risks compared to those from the lowest risk category (G1-/G2-). However, no significant differences in PGS were observed among children with a history of depression in either parents or grandparents (FamHist+), as opposed to those with the lowest familial risk (G1-/G2-). When isolating parental history regardless of grandparental history (G2- vs. G2+), children with a parental history of depression showed significantly higher polygenic risks for depression (estimate, 0.103 [95% CI, 0.055–0.150]), neuroticism (estimate, 0.094 [95% CI, 0.046–0.141]), ever been a smoker (estimate, 0.082 [95% CI, 0.034–0.130]), and BMI (estimate, 0.081 [95% CI, 0.033–0.129]) compared to those without such a history ( Supplementary Fig. 1C ). These findings demonstrate that the effect sizes associated with multigenerational history for PGS are larger than those observed for parental history alone. Additionally, the same analyses conducted exclusively with European-ancestry children yielded results consistent with those from the multi-ancestry children ( Supplementary Fig. 2 ). Follow-up linear regression analyses revealed that family risk remained significantly associated with the PGSs for depression and bipolar disorder, after accounting for the potential confounding variables. Specifically, children with the highest familial risk exhibited significantly higher polygenic risk compared to those with the lowest risk (G1-/G2- vs. G1+/G2+; estimate for depression PGS, 0.129 [95% CI, 0.070–0.187]; estimate for bipolar disorder PGS, 0.109 [95% CI, 0.051–0.168]; Bonferroni-corrected P < .05; Fig. 2 A; Supplementary Table 2) . The binary any multigenerational family history (G1-/G2- vs. FamHist+) had a significant effect on depression PGS (estimate, 0.095 [95% CI, 0.051–0.139]; Bonferroni-corrected P < .05; Fig. 2 B; Supplementary Table 3 ). Any family history was not significantly associated with the other PGSs. Likewise, when considering only parental depression history but not grandparents’ history, the depression PGS was significantly associated with having a parent with depression (estimate, 0.087 [95% CI, 0.039–0.135]; Bonferroni-corrected P < .05; Fig. 2 C; Supplementary Table 4 ). Models with only European-ancestry children showed similar results (G1-/G2- vs. G1+/G2+; estimate for depression PGS, 0.136 [95% CI, 0.071–0.201]; estimate for bipolar disorder PGS, 0.126 [95% CI, 0.061–0.191]; Bonferroni-corrected P < .05; Supplementary Fig. 3 ). As a sensitivity analysis, we excluded children with family history of mania and repeated the analyses. With the four-level family risk, depression PGS showed a significant association, but bipolar disorder PGS did not (estimate, 0.115 [95% CI, 0.047–0.182]; FDR-corrected P < .05, not Bonferroni-significant; Supplementary Fig. 4A ). Likewise, binary any family history showed a significant association with depression PGS (estimate, 0.095 [95% CI, 0.047–0.143]; Bonferroni-corrected P < .05; Supplementary Fig. 4B ). No significant association was found in the regression models with parental depression history ( Supplementary Fig. 4C ). However, when analyses were confined to children of European ancestry, excluding those with a history of mania, no significant associations were observed ( Supplementary Fig. 5 ). Association between Psychopathology and Polygenic Scores We investigated whether the PGSs associated with family history of depression would similarly be associated with offspring’s psychopathology. Depression PGS was positively associated with parent (OR, 1.130 [95% CI, 1.075–1.188]) and child reports (OR, 1.116 [95% CI, 1.059–1.176]) of any psychiatric disorder, conduct/oppositional defiant disorder (OR, 1.148 [95% CI, 1.079–1.221]), parent report of any anxiety disorder (OR, 1.153 [95% CI, 1.073–1.238]), conduct disorder (OR, 1.280 [95% CI, 1.120–1.462]), ADHD (OR, 1.111 [95% CI, 1.049–1.177]), separation anxiety disorder (OR, 1.145 [95% CI, 1.062–1.234]), parent (OR, 1.141 [95% CI, 1.050–1.240]) and child reports (OR, 1.146 [95% CI 1.058–1.243]) of suicidal ideation (FDR-corrected P .05). Within the regression models, the variances explained by depression PGS ranged from 0.15–0.65%. In European-ancestry children, depression PGS was also positively associated with behavioral problems, suicidal behaviors, and any psychiatric disorder (FDR-corrected P < .05; Supplementary Fig. 6; Supplementary Table 6 ). Additionally, when testing associations between family history of depression and KSADS diagnoses, we observed that the risk for psychiatric disorders and suicidal behaviors increases as family risk increases both in multi-ancestry and European-ancestry children ( Supplementary Table 7–8 ), similar to what we have found previously [ 6 ]. With the four-level family risk variable included in the models with depression PGS, PGS for depression was still significantly associated with KSADS diagnoses such as any psychiatric disorder, conduct/oppositional defiant disorder, conduct disorder, any anxiety disorder, sleep problems, and suicidal ideation (FDR-corrected P < .05; Supplementary Table 9 ). The models including both depression PGS and family risk accounted for a slightly greater variance of KSADS diagnoses (parent-reported any psychiatric disorder; 2.59%) than the model including only family history of depression (2.41%). Likewise, in European-ancestry samples, depression PGS showed significant effects on similar KSADS diagnoses including both family history and depression PGS (FDR-corrected P < .05; Supplementary Table 10 ). Mediation Analysis with PGSs as Mediators Given that only the depression PGS was found to be significantly associated with both familial depression history and offspring’s psychopathology, we further investigated whether depression PGS mediated the effects of familial depression history on offspring’s psychopathology. The mediation models with the binary indicator of any family history (G1-/G2- vs. FamHist+) showed that depression PGS had significant mediation effects on all tested 14 clinical outcomes including parent- (estimate, 0.0021 [95% CI, 0.0009–0.0037]) and child-reported (estimate, 0.0019 [95% CI, 0.0008–0.0033]) any psychiatric disorders, any anxiety disorders (estimate, 0.0012 [95% CI, 0.0005–0.0007]), conduct/oppositional defiant disorder (estimate, 0.0016 [95% CI, 0.0006–0.0027]), ADHD (estimate, 0.0014 [95% CI, 0.0005–0.0018]), self-harm (estimate, 0.0007 [95% CI, 0.0002–0.0013]), sleep problems of parent report (estimate, 0.0009 [95% CI, 0.0002–0.0018]), and suicidal behaviors of child (estimate, 0.0009 [95% CI, 0.0002–0.0018]) and parent reports (estimate, 0.0008 [95% CI, 0.0002–0.0016]; FDR-corrected P < .05; Fig. 4 A ) . The proportions mediated by depression PGS relative to the total effects on each clinical outcome ranged from 1.39–5.87%. Similar results were observed with the mediation models of parental depression history. Depression PGS had significant mediation effects on all 14 KSADS diagnoses, except for parent report of suicidal ideation (Fig. 4 B ). Likewise, in European-ancestry samples, depression PGS significantly mediated the impact of multigenerational and parental family risk on KSADS diagnoses ( Supplementary Fig. 7 ). Discussion Familial history of depression increases risk for offspring psychiatric disorder. Therefore, we investigated whether polygenic risks for psychiatric disorders contribute to intergenerational transmission of depression. We found that multigenerational depression history was positively correlated with higher genome-wide PGSs for depression and bipolar disorder. Moreover, a greater PGS for depression significantly mediated the effects of familial history of depression on offspring’s mental health indexed by KSADS diagnoses. To our best knowledge, this is the first report showing polygenic risk for depression as a potential mechanism for the transgenerational transmission of depression. Addressing conflicting results from previous research on the association between first-degree family history and depression PGS [ 21 – 23 ], the present study utilized more recent and larger GWAS results for constructing the PGS of depression, which could partially account for the discrepancies between the findings as well as testing findings in a larger cohort. For the first time, our results reveal that higher depression PGS is significantly associated with a family history of depression spanning multiple generations, encompassing risks from both first- and second-degree family members. The children with two previous generations affected showed the highest PGS (estimate, 0.129 [95% CI, 0.070–0.187]) in line with the increased risk for psychopathology [ 6 ]. These offspring with two previous generations affected might form a subgroup of individuals with an exceptionally high genetic burden. We found a similar association for bipolar PGS (estimate, 0.109 [95% CI, 0.051–0.168]). But when we limited the sample to those with a family history of depression without mania, bipolar PGS lost its significance in the association with family history. This shows that the significant associations with bipolar PGS might be due to including children with a family history of bipolar disorder and that genetic risk for and familial aggregation of depression and bipolar disorder are separate. This is in line with recent literature showing an association between family history of bipolar disorder and higher bipolar PGS in offspring [ 54 – 56 ], reports of familial transmission being specific to type of mood disorder [ 57 ] and genetic differences between depression and bipolar disorder [ 58 ]. Our results also showed that depression PGS and family history of depression together accounted for significant variances of offspring’s psychopathology. These results extend previous findings from recent studies that showed family history and PGS are predictive of future cases of depression and including both factors in a model modestly increases the prognostic power in predicting depression [ 59 – 61 ]. The depression PGS was positively correlated with a wide range of KSADS diagnoses, including any psychiatric disorder, any anxiety disorder, suicidal ideation, ADHD, and conduct/oppositional defiant disorder (C/ODD). On the other hand, bipolar PGS showed no significant correlations with KSADS diagnoses. Despite not surviving correction for multiple comparisons, depression PGS was associated with any depressive disorder even at this young age of 9 to 10 years old (unadjusted P = .019). Depression often starts later in adolescence and early adulthood, but higher family and polygenic risk of depression have been shown to be associated with earlier onset [ 3 , 62 ]. Suicidal ideation and self-harm at this age, also associated with depression PGS, are becoming more common in recent years [ 63 ] and are predictive of later suicide attempts [ 64 ]. However, identifying those at risk for suicide is challenging. Our results indicate that the combination of family assessments and PGS for depression might increase predictive power in evaluating risk for suicidal thoughts and behaviors in children, especially as PGS are thought to be able to explain more variance in the future as GWASs include ever larger samples. PGS for depression significantly mediates the effects of family history on offspring’s depression. Moreover, the mediation effect was significant for a broad range of psychiatric disorders, including any psychiatric disorder, any anxiety disorder, suicidal thoughts and behaviors, C/ODD, and ADHD. This highlights a role for genetic liability in intergenerational transmission of childhood psychopathology in general and depression specifically in periadolescent children (9–10 years old). Future research may examine the brain correlates of family history of depression and depression PGS. Family history of depression may affect the offspring’s risk for psychiatric disorders through genetic or environmental pathways. Here we show that the genetic component is significant and scales with the number of generations affected. On the other hand, children of parents with depression may experience and even generate more stressful life events [ 65 , 66 ]. These events may exacerbate risks of psychiatric disorders. Further research could identify protective or vulnerability factors that may moderate the impact of family history of depression and depression PGS through gene-environment interactions. Furthermore, because we did not have access to parent and grandparent genotypes, we are unable to distinguish between direct genetic effects of the child’s genotype on their phenotype and indirect genetic effects through genetic nurture and other mechanisms. For example, the parent and the child may share a genotype associated with higher neuroticism, which could lead to less affectionate caregiving of the parent to the child [ 67 , 68 ]. This, in turn, might bias our estimates of the direct effect of the neuroticism PGS on child psychiatric outcomes through altered parenting. Strengths and Limitations: The current study has the strengths of a large, diverse multi-ancestry sample, multigenerational family history assessment, and the latest Bayesian polygenic prediction method to test our hypotheses. Limitations of this study include that in most GWASs, the PGSs were derived from European-ancestry samples and, therefore, the generalizability of the summary statistics to other ancestry samples might be limited. Nevertheless, our findings were consistent across the analyses of multi-ancestry and European-only samples. In addition, PGSs still only account for relatively small variances compared to the heritability of depression estimated from twin studies or DNA, but PGS may become stronger predictors in future. Family history was assessed retrospectively by the caregiver, which may bias reports and underestimate effect sizes compared to samples with gold-standard clinician-based diagnoses for all family members. However, this limitation is mitigated by the fact that we previously showed that clinical results were similar between an interview-based design study [ 7 , 8 ] and the ABCD study [ 6 ]. Lastly, the effect sizes that we found, while similar to those of prior polygenic score studies [ 69 , 70 ] are small, suggesting that these PGS do not yet have high clinical significance. As GWAS discovery samples become larger and include multiple genetic ancestries, clinical significance may improve. On the other hand, the children in our sample are still young and before the median age of onset of depression. Some of the currently unaffected children might develop psychiatric disorders as the cohort ages, forming a stronger association between PGS and psychiatric disorders, and increasing the effect sizes. In summary, we show that PGSs for depression and bipolar disorder are associated with family history of depression and that depression PGS mediates part of the association between (multigenerational) family history and offspring’s psychopathology. We demonstrate that having more previous generations affected with depression is linked to having higher polygenic risk for psychiatric disorders. The findings also implicate polygenic risk for depression as a potential mechanism for intergenerational transmission of depression, suggesting that integrating depression PGS with depression history may aid in identifying children at higher risk for psychopathology. Declarations Author Contributions : EL and MvD are co–first authors and contributed equally to this work. EL and MvD contributed to conceptual design, interpretation of findings, and writing and revision of the manuscript. EL contributed to statistical analysis. EL, BK, GK, and YJ contributed to generation of genome-wide polygenic scores. EM, AT, MMW, and JC contributed to conceptual design and revising the manuscript. MMW and JC supervised the study. Funding Statement : This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (JC, No. 2021R1C1C1006503, 2021K1A3A1A2103751212, 2021M3E5D2A01022515, RS-2023-00266787, RS-2023-00265406), by Creative-Pioneering Researchers Program through Seoul National University (JC, No. 200-20230058), by Semi-Supervised Learning Research Grant by SAMSUNG (JC, No.A0426-20220118), by Identify the network of brain preparation steps for concentration Research Grant by LooxidLabs (JC, No.339-20230001), by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (JC, No.2021-0-01343, Artificial Intelligence Graduate School Program of Seoul National University), by National Institute of Mental Health (MvD, No. K99MH129611; MMW, No. R01MH036197), and by AFSP Young Investigator Award (MvD, No. YIG-R-001-19). 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Additional Declarations Dr.Weissman receives book royalties from Perseus Press and Oxford Press. Supplementary Files 0familyhistorySupplementaryMethodsandFiguresMP.docx 0familyhistorySupplementaryTablesMP.pdf Cite Share Download PDF Status: Published Journal Publication published 08 Sep, 2025 Read the published version in Molecular Psychiatry → Version 1 posted Editorial decision: revise 19 Sep, 2024 Review # 2 received at journal 10 Jul, 2024 Reviewer # 2 agreed at journal 26 Jun, 2024 Reviewer # 1 agreed at journal 24 Jun, 2024 Reviewers invited by journal 18 Jun, 2024 Editor assigned by journal 17 Apr, 2024 Submission checks completed at journal 16 Apr, 2024 First submitted to journal 15 Apr, 2024 Unknown event 15 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4264742","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":316137775,"identity":"62bdeaa5-9823-4da0-b7a4-d6af2a83a8d1","order_by":0,"name":"Jiook Cha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYHAD5gNQBhtRyg1AKhNI1sJjQJwW/vbeYw8+1PyR023v+fy5sI1Bnr+BLe0DPi0SZ86lG844ZmBsdubsNumZbQyGMw6wHZ6B10USOWbSvA0Gidtu5G5j5m1jYNzAwN6M3xMgLX9BWu6/efwZqMWeOC2MYFt4GKSBWhI3MLAdxqtF4swZM8meY8ZAv6SZSfOck0iecZgtGa8W/vYeM4kfNXJyZscPP/7MU2Zj29/eZoxXC4atwFRAkoZRMApGwSgYBdgAAA89QHqYputoAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-5314-7992","institution":"Seoul National University","correspondingAuthor":true,"prefix":"","firstName":"Jiook","middleName":"","lastName":"Cha","suffix":""},{"id":316137776,"identity":"26a393b4-c3a9-41d8-b73f-d3316bc58af9","order_by":1,"name":"Eunji Lee","email":"","orcid":"https://orcid.org/0000-0002-2589-5395","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Eunji","middleName":"","lastName":"Lee","suffix":""},{"id":316137777,"identity":"b2032180-9e5a-4a57-8ffa-9a0877895113","order_by":2,"name":"Milenna van Dijk","email":"","orcid":"","institution":"Academic Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Milenna","middleName":"van","lastName":"Dijk","suffix":""},{"id":316137778,"identity":"c082f29b-580f-49a6-8a38-56e1c6ec8928","order_by":3,"name":"Bogyeom Kim","email":"","orcid":"https://orcid.org/0000-0003-2685-877X","institution":"Department of Psychology, Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Bogyeom","middleName":"","lastName":"Kim","suffix":""},{"id":316137779,"identity":"b504c6bc-b396-4d3f-b547-3eb9c1685dbd","order_by":4,"name":"Gakyung Kim","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Gakyung","middleName":"","lastName":"Kim","suffix":""},{"id":316137780,"identity":"51063892-360c-4448-a78e-4a77111cb66d","order_by":5,"name":"Eleanor Murphy","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Eleanor","middleName":"","lastName":"Murphy","suffix":""},{"id":316137781,"identity":"3b39f227-c3da-4ab1-9bd5-ac97731dcfee","order_by":6,"name":"Ardesheer Talati","email":"","orcid":"","institution":"Columbia University","correspondingAuthor":false,"prefix":"","firstName":"Ardesheer","middleName":"","lastName":"Talati","suffix":""},{"id":316137782,"identity":"4a0609d6-989e-4301-80f3-c6a3c0fcf65b","order_by":7,"name":"Yoonjung Joo","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yoonjung","middleName":"","lastName":"Joo","suffix":""},{"id":316137783,"identity":"007f79c2-3911-463b-9927-1f7245d824b4","order_by":8,"name":"Myrna Weissman","email":"","orcid":"https://orcid.org/0000-0003-3490-3075","institution":"Columbia University Vagelos College of Physicians and Surgeons","correspondingAuthor":false,"prefix":"","firstName":"Myrna","middleName":"","lastName":"Weissman","suffix":""}],"badges":[],"createdAt":"2024-04-14 11:30:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4264742/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4264742/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41380-025-03221-8","type":"published","date":"2025-09-08T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60529414,"identity":"e1a0c394-a9e8-4828-9018-9e3b011f0af0","added_by":"auto","created_at":"2024-07-17 19:59:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":104920,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCONSORT diagram\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data from 11,875 children between the ages of 9 and 10 years old were initially evaluated, collected during the baseline visit of the Adolescent Brain and Cognitive Development study. After the quality control procedure for genotype data and removing missing values in the family history and clinical measures, the primary analysis involved examining complete phenotype, genotype, and confounder data for a multi-ancestry cohort of 8,111 children, 6,151 of whom were of European ancestry. Following the exclusion of children with a family history of mania, a sensitivity analysis was conducted on a sample of 6,925 multi-ancestry children, of which 5,274 were of European ancestry.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/305e32744d501bdc7acf2d00.png"},{"id":60529415,"identity":"4a7cd1cc-4782-4781-a5e8-d2fe994e19fa","added_by":"auto","created_at":"2024-07-17 19:59:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":236549,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of family history of depression on residualized polygenic scores in multi-ancestry children\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDashed red line indicates 0.05 of unadjusted \u003cem\u003eP\u003c/em\u003e. Solid red line indicates 0.05 of Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e. Each triangle represents a PGS with the odds ratio (OR) of family risk. Triangles filled with color denote PGSs with FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026lt;.05. \u003cem\u003eP\u003c/em\u003e values were adjusted for 30 tests. \u003cstrong\u003e(A)\u003c/strong\u003e Regression of four-level family risk from the two generations: neither G1 nor G2 (G1−/G2−; reference level), only G1 (G1+/G2−), only G2 (G1−/G2+), and both G1 and G2 (G1+/G2+). Detailed information underlying this figure are available in Supplementary Table 2. \u003cstrong\u003e(B)\u003c/strong\u003eRegression of binary any family history: neither G1 nor G2 (G1−/G2−; reference level) and the rest of the groups (FamHist+). Detailed information underlying this figure are available in Supplementary Table 3. \u003cstrong\u003e(C)\u003c/strong\u003e Regression of parental depression history: no history in the parent (G2–; reference level) and depression in the parent (G2+). Detailed information underlying this figure are available in Supplementary Table 4.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/aec3576197a87375391f1610.png"},{"id":60530765,"identity":"fee51451-e9d1-4c95-a72c-cadb5dc3127f","added_by":"auto","created_at":"2024-07-17 20:07:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103863,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of depression PGS on clinical outcomes in multi-ancestry children\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003ereported by child; otherwise reported by parent\u003c/p\u003e\n\u003cp\u003ePresented results in the figure were from the models with significant effects of depression PGS after the FDR correction. No significant result was found with bipolar disorder PGS. Error bar indicates 95% confidence interval. \u003cem\u003eP\u003c/em\u003e values were adjusted for 72 tests (36 outcomes and 2 PGSs of depression and bipolar disorder). Detailed information underlying this figure are available in Supplementary Table 5. DMcFadden’s \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e, the proportion of variance explained by polygenic score; ADHD, attention-deficit/hyperactivity disorder\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/b3e8cb0f3b620b1afb047443.png"},{"id":60529418,"identity":"9b0c0692-1004-4738-83c5-ad917743105b","added_by":"auto","created_at":"2024-07-17 19:59:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":397511,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMediation analysis with depression PGS in multi-ancestry children\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003ereported by child; otherwise reported by parent\u003c/p\u003e\n\u003cp\u003e(A) Multigenerational family history of depression as treatment variable (G1-/G2- vs. FamHist+). (B) Parental history of depression as treatment variable (G2- vs. G2+). All tested effects were with FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026lt;.05. \u003cem\u003eP\u003c/em\u003e values were adjusted for 28 tests (2 versions of family history and 14 clinical outcomes).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/afb37ab1dfc20a6472653ba7.png"},{"id":90865411,"identity":"22bc51dc-012d-4348-8325-c13105b0bd05","added_by":"auto","created_at":"2025-09-09 07:10:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2180233,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/dddb0d66-823b-443d-b872-35c553272bf7.pdf"},{"id":60529416,"identity":"24257c4d-9766-4c8f-900b-24473dd4baef","added_by":"auto","created_at":"2024-07-17 19:59:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12109910,"visible":true,"origin":"","legend":"","description":"","filename":"0familyhistorySupplementaryMethodsandFiguresMP.docx","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/dbbdc2ee2fef48c3977b3953.docx"},{"id":60529419,"identity":"dfd09b01-cd98-4c12-a2ba-0f523831714b","added_by":"auto","created_at":"2024-07-17 19:59:40","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":201929,"visible":true,"origin":"","legend":"","description":"","filename":"0familyhistorySupplementaryTablesMP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4264742/v1/a85be3b200b4a11a43ae5060.pdf"}],"financialInterests":"\nDr.Weissman receives book royalties from Perseus Press and Oxford Press.","formattedTitle":"Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDepression runs in families, often manifesting in various forms of mental disorders. Parental depression increases the offspring's risk of developing depression and other psychopathology, such as anxiety, disruptive disorders and substance use, by 2\u0026ndash;5 times [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Children with a family history of depression often develop the disorder at a younger age, even in childhood [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although the familial transmission of depression is established, the intricate mechanisms through which genetic predispositions and environmental factors contribute to the intergenerational transmission of depression and related psychopathologies are not yet fully understood [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOffspring with both a parent and at least one grandparent with depression are at an even higher risk for developing psychopathology [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. We first found this using a longitudinal three-generational study, which used carefully crafted interview-based diagnoses for every family member, from children to adults [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] (Warner, Weissman et al., 1999), and these findings were confirmed by other moderate sized studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. We recently generalized these findings to a large, diverse cohort of preadolescents in the Adolescent Brain and Cognitive Development (ABCD) study. This study showed a significant association between family history of depression and offspring's risk of psychopathology regardless of sociodemographic characteristics such as sex, socioeconomic status (SES), and race/ethnicity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePsychiatric disorders have a high degree of heritability, estimated for depression around 30\u0026ndash;50% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and up to 80% for schizophrenia [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These numbers came initially from twin studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which cannot readily distinguish between genetic and intrauterine and perinatal factors or differences between parenting monozygotic versus dizygotic twins. Recent adoption studies, which found a larger component attributed to being reared by a depressed (step/adoptive) parent, questioned whether the genetic component of intergenerational depression was overestimated in these early twin studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A recent large-scale registry study, however, confirmed the initial heritability estimates [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These studies suggest a strong role for genetics in the transmission of depression between generations. Nonetheless, the variance explained by genetic components is not attributed to a few candidate genes or variants, but rather to the cumulative impact of numerous variants, each with small effects. As an example, a meta-analysis involving three independent depression genome-wide association studies (GWASs), with a total sample size of 807,553 participants, identified 102 genome-wide significant variants and 269 putative genes associated with depression [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Polygenic scores (PGSs) represent an estimate of relative cumulative genetic risk of an individual for the phenotype of interest, such as depression, based on the findings of GWAS. PGSs for psychiatric disorders are associated with increased risk for psychopathology in the general population [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Some studies have jointly examined PGS and family history in association with psychopathology, but the findings have been mixed. PGS for depression was associated with a continuous score of first-degree (parents and siblings) family history loading for depression [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], but two other studies found no association between first-degree family history and depression PGS [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], perhaps because they used the data from earlier and smaller GWASs. Furthermore, while various psychopathology PGSs were found to be associated with mood and psychotic disorder onsets, only non-psychopathology PGSs for neuroticism and wellbeing were associated with onsets independent of family history [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Thus, it remains unclear how family history for depression and PGSs are associated with offspring psychopathology onset. Importantly, to our best knowledge, no studies have yet reported whether family history of depression over two generations is linked to greater polygenic risk for mental disorders.\u003c/p\u003e \u003cp\u003eIn the present study, we first test whether multigenerational family risk for depression (having both a parent and a grandparent with depression) is independently associated with greater polygenic risk for psychiatric disorders. Then we test whether PGSs are associated with the presence of psychopathology. We hypothesize that as more previous generations have been affected by depression, a greater genetic risk for psychopathology and related behavioral vulnerabilities would have been accumulated in the offspring, Since psychiatric disorders are genetically correlated with non-psychiatric phenotypes such as educational attainment, subjective wellbeing, and risky behaviors [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], polygenic scores for a broad array of phenotypes were used to test our research questions. Lastly, we explore whether PGSs partially mediate the association between multigenerational family risk for depression and higher rates of psychiatric diagnoses in the offspring. We test this using a mediation model that incorporates depression PGS, alongside family risk and clinical data, in the ABCD study, which has the advantage of large sample size and generalizability, making it well-suited for rigorous genetic analyses.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and Data Source\u003c/h2\u003e \u003cp\u003eThis study used baseline data of 11,875 participants aged 9\u0026ndash;10 years from the ABCD study release 2.01, collected September 2016-November 2018 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] across 21 research sites in the United States. The genetic ancestry of children to categorize the sample was obtained from release 3.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nda.nih.gov/study.html?id=901\u003c/span\u003e\u003cspan address=\"https://nda.nih.gov/study.html?id=901\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e All procedures for data collection were approved by the centralized institutional review board (IRB) at University of California, San Diego. Caretakers provided written informed consent and children provided assent. We imputed missing values of covariates and excluded participants without genotypes, family history, and clinical outcomes. After preprocessing genotype data and validating PGSs with a validation set, 8,620 samples remained. From 8,620 genotyped samples, we excluded anyone with missing values of family history (n\u0026thinsp;=\u0026thinsp;493) and KSADS-5 (n\u0026thinsp;=\u0026thinsp;507). The final sample (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) included 8,111 unrelated multiethnic children, consisting of 6,151 [71.4%] participants of European ancestry, 1,285 [14.9%] African ancestry, 315 [3.7%] admixed American ancestry, 106 [1.2%] East Asian ancestry, and 254 [2.9%] unidentified ancestry.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePolygenic Scores\u003c/h2\u003e \u003cp\u003e Genotyping was done using saliva samples of ABCD study participants at the baseline visit. See Supplementary Methods for Quality Assurance of the genotype data. We constructed the PGSs of 30 complex traits selected for their relationship to psychiatric disorders, using publicly available GWAS summary statistics: Attention-deficit/hyperactivity disorder (ADHD) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], cognitive performance (CP) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], educational attainment (EA) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], major depressive disorder (MDD) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], insomnia [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], snoring [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], intelligence quotient (IQ) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], post-traumatic stress disorder (PTSD) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], depression [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], body mass index (BMI) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], alcohol dependence [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], autism spectrum disorder (ASD) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], automobile speeding propensity (ASP) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], bipolar disorder [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], cannabis during lifetime (cannabis use) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], ever smoker [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], shared effects on five major psychiatric disorder (cross disorder) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], alcoholic drinks consumption per week (drinking) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], eating disorder [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], neuroticism [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], obsessive-compulsive disorder (OCD) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], first principal components of four risky behaviors (risky behaviors) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], general risk tolerance [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], schizophrenia [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], worrying [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], anxiety [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], subjective well-being (SWB) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], general happiness, and general happiness for health (happiness-health) and meaningful life (happiness-life) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.nealelab.is/ukbiobank/\u003c/span\u003e\u003cspan address=\"http://www.nealelab.is/ukbiobank/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e All GWASs were European-only samples. For depression, BMI, alcohol dependence, PTSD, and schizophrenia, non-European GWAS was also available, so a polygenic score calculated from multiple GWASs was constructed for these five traits. Therefore, for these traits, we estimated two different versions of each PGS; European GWAS-based PGSs and multiethnic GWAS-based PGSs.\u003c/p\u003e \u003cp\u003eThe posterior effect sizes of single nucleotide polymorphisms (SNPs) were estimated using PRS-CSx [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], a Bayesian approach that enables the merging of multiple GWAS summary statistics from diverse populations. The final scores were calculated using PLINK version 1.9 and controlled for the first ten genetic principal components. The optimal hyperparameter (global shrinkage hyperparameter in PRS-CSx) for PGSs was selected in a held-out validation set of 1,579 unrelated participants. These participants were genetically related to the final samples and therefore were excluded from the primary analyses. Details about the GWASs and validation procedures of PGSs are presented in \u003cb\u003eSupplementary Table\u0026nbsp;1 and Supplementary Methods in Supplementary Material\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eAll assessments were reported previously in van Dijk et al. (2021) published in JAMA Psychiatry [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The ABCD Family History Assessment was used to collect caregivers\u0026rsquo; reports on the history of grandparents (generation 1 [G1]) and parents (generation 2 [G2]) (Rice et al., 1995). We created a four-level depression risk variable, which describes risk levels of depression history from the two generations: (1) neither G1 nor G2 (G1-/G2-; a reference level), (2) only G1 (G1+/G2-), (3) only G2 (G1-/G2+), and (4) both G1 and G2 (G1+/G2+). Having one parent or one grandparent was sufficient to be categorized as having a parent (G2+) or grandparent (G1+) with depression. Additionally, we developed a binary \u0026ldquo;any family history\u0026rdquo; indicator to simplify the analysis. This indicator contrasts families with no reported depression history in either generation (G1-/G2-) against those with a reported history in at least one generation, so collapsing G1+/G2-, G1-/G2+, and G1+/G2\u0026thinsp;+\u0026thinsp;groups into one variable \u0026ldquo;FamHist+\u0026rdquo;. Furthermore, we introduced a parental history indicator (G2- vs. G2+), specifically to highlight the impact of having a parent with a history of depression. This indicator focuses on the more immediate familial influence, distinguishing between participants without a parental history of depression (G2-) and those with such a history (G2+).\u003c/p\u003e \u003cp\u003eChildhood psychopathology was assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] reported by parents and children. Parent and child reports were separately analyzed; therefore, a total of 36 clinical variables were included in the analyses. Further details for the measures are in the \u003cb\u003eSupplementary Methods\u003c/b\u003e.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003ePotential Confounders\u003c/h2\u003e \u003cp\u003eWe used the following 13 covariates to adjust for potential confounding effects: child\u0026rsquo;s age, sex, race/ethnicity, sexual orientation reported by child and parent, gender identity, religious preference, country of birth, reporter\u0026rsquo;s relationship to child, total household income, and caregiver\u0026rsquo;s age, education level, and marital status. Multiple imputation method using the R package \u003cem\u003e\u0026lsquo;mice\u0026rsquo;\u003c/em\u003e v3.14.0 was employed to impute missing values in covariates (See \u003cb\u003eSupplementary Methods\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eWe primarily analyzed (using R version 4.2.0.) the data of 8,111 multi-ancestry children. We repeated the analyses in 6,151 European-ancestry samples to test for ancestral bias. Bonferroni and false discovery rate (FDR) corrections for the number of tests were applied to each analysis with significance set at adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05. We centered and scaled the PGSs and continuous variables of covariates to obtain standardized estimates from regression analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssociation and Mediation Analysis\u003c/h2\u003e \u003cp\u003e. Association between family history of depression and PGSs was assessed using univariate linear models, with the family history indicator as the independent variable and PGS as the dependent variable. Firth logistic regression was used when KSADS was the outcome with family risk and/or PGS as predictors including covariates [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Firth\u0026lsquo;s approach helps reduce bias in highly imbalanced data by penalizing the likelihood function. We computed 95% confidence intervals (CIs) and McFadden\u0026lsquo;s pseudo \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e with penalized log-likelihood [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor mediation analysis (using package \u0026lsquo;\u003cem\u003emediation\u003c/em\u003e\u0026rsquo; v4.5.0), we selected the PGSs that were significantly associated with both clinical outcome and family history of depression and tested these as candidate mediator. The treatment variable was the familial risk of depression, considering the lowest risk (G1\u0026minus;/G2\u0026minus;) as the control condition and the others (either G1\u0026thinsp;+\u0026thinsp;or G2+) as the treatment condition. Clinical outcomes that were significantly associated with both PGS and family history of depression were examined as outcome. We additionally tested the models with parental risk only. Significance of the direct effects of familial risk and the mediation effects of PGSs were estimated using bootstrap samples (n\u0026thinsp;=\u0026thinsp;1,000).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAdditional Assessment/Sensitivity Analysis\u003c/h2\u003e \u003cp\u003eOur main analyses defined depression family history only by the depression question in the Family History Assessment. However, this does not exclude individuals who might have both depression and mania (e.g. likely bipolar disorder). Therefore, we performed a sensitivity analysis (n\u0026thinsp;=\u0026thinsp;6,925 multi-ancestry participants, including n\u0026thinsp;=\u0026thinsp;5,274 European-ancestry) removing children who have parents or grandparents with mania obtained from the Family History Assessment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe complete phenotype and genotype data from 8,111 unrelated multi-ancestry children were available for analysis, including 6,151 European-ancestry children. 8,111 multi-ancestry children consist of 3,832 [47.2%] females with a mean [SD] age at baseline of 9.48 [0.51] years. Of European-ancestry children, 2,860 [46.5%] were female, and the mean [SD] age was 9.48 [0.51] years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and family history of depression for multi-ancestry and European-ancestry participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMulti-ancestry (n\u0026thinsp;=\u0026thinsp;8,111)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEuropean-ancestry (n\u0026thinsp;=\u0026thinsp;6,151)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTest statistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild\u0026rsquo;s demographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003et / χ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.48 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.48 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,279 (52.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,291 (53.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,832 (47.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,860 (46.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace/Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,772 (21.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,204 (19.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e958.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,203 (14.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic white\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,996 (61.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,833 (78.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140 (1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual Orientation (parent report)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e13.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaybe/Don\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e648 (7.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e595 (9.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,390 (91.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,499 (89.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecline to answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual Orientation (child report)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaybe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,006 (74.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,488 (72.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI do not understand\u003c/p\u003e \u003cp\u003ethis question\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,002 (24.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,576 (25.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender identity (parent report)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,276 (52.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,288 (53.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e1.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,828 (47.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,856 (46.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrans male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrans female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender queer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther identity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligious preference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgnostic/Atheist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e379 (4.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e366 (5.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e15.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDenominational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,889 (72.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,316 (70.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-denominational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,843 (22.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,469 (23.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry of birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSA and territories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,887 (97.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,994 (97.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224 (2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157 (2.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaregiver\u0026rsquo;s demographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eN (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003et / χ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelationship with child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiological mother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,970 (85.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,284 (85.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e12.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.0147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiological father\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e803 (9.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e668 (10.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdoptive parent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (1.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCustodial parent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.96 (6.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.72 (6.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,537 (68.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,727 (76.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e211.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e742 (9.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e571 (9.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305 (3.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e189 (3.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e968 (11.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e342 (5.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e499 (6.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e281 (4.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.16 (2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.77 (2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.63 (2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.18 (2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1-/G2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,658 (57.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,284 (53.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e30.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1+/G2-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,092 (13.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e967 (15.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1-/G2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e882 (10.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e650 (10.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1+/G2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,479 (18.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,250 (20.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eG1, generation 1; G2, generation 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between Familial Risks and Polygenic Scores\u003c/h2\u003e \u003cp\u003eFirst, we tested whether multigenerational family risk for depression is associated with greater polygenic risk. Our primary analysis included all children (a multi-ancestry sample), and our supporting analysis included only European-ancestry children to test for potential bias related to ancestry. Our analyses using linear regression without adjusting for potential confounders demonstrated a significant association between multigenerational family risk for depression and increased PGSs for depression (estimate, 0.143 [95% CI, 0.084\u0026ndash;0.201]), neuroticism (estimate, 0.112 [95% CI, 0.053\u0026ndash;0.170]), and bipolar disorder (estimate, 0.108 [95% CI, 0.050\u0026ndash;0.167]; Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; \u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e). Specifically, children from the highest familial risk category (G1+/G2+) displayed significantly elevated polygenic risks compared to those from the lowest risk category (G1-/G2-). However, no significant differences in PGS were observed among children with a history of depression in either parents or grandparents (FamHist+), as opposed to those with the lowest familial risk (G1-/G2-). When isolating parental history regardless of grandparental history (G2- vs. G2+), children with a parental history of depression showed significantly higher polygenic risks for depression (estimate, 0.103 [95% CI, 0.055\u0026ndash;0.150]), neuroticism (estimate, 0.094 [95% CI, 0.046\u0026ndash;0.141]), ever been a smoker (estimate, 0.082 [95% CI, 0.034\u0026ndash;0.130]), and BMI (estimate, 0.081 [95% CI, 0.033\u0026ndash;0.129]) compared to those without such a history (\u003cb\u003eSupplementary Fig.\u0026nbsp;1C\u003c/b\u003e). These findings demonstrate that the effect sizes associated with multigenerational history for PGS are larger than those observed for parental history alone. Additionally, the same analyses conducted exclusively with European-ancestry children yielded results consistent with those from the multi-ancestry children (\u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eFollow-up linear regression analyses revealed that family risk remained significantly associated with the PGSs for depression and bipolar disorder, after accounting for the potential confounding variables. Specifically, children with the highest familial risk exhibited significantly higher polygenic risk compared to those with the lowest risk (G1-/G2- vs. G1+/G2+; estimate for depression PGS, 0.129 [95% CI, 0.070\u0026ndash;0.187]; estimate for bipolar disorder PGS, 0.109 [95% CI, 0.051\u0026ndash;0.168]; Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; \u003cb\u003eSupplementary Table\u0026nbsp;2)\u003c/b\u003e. The binary any multigenerational family history (G1-/G2- vs. FamHist+) had a significant effect on depression PGS (estimate, 0.095 [95% CI, 0.051\u0026ndash;0.139]; Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB; \u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e). Any family history was not significantly associated with the other PGSs. Likewise, when considering only parental depression history but not grandparents\u0026rsquo; history, the depression PGS was significantly associated with having a parent with depression (estimate, 0.087 [95% CI, 0.039\u0026ndash;0.135]; Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC; \u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e). Models with only European-ancestry children showed similar results (G1-/G2- vs. G1+/G2+; estimate for depression PGS, 0.136 [95% CI, 0.071\u0026ndash;0.201]; estimate for bipolar disorder PGS, 0.126 [95% CI, 0.061\u0026ndash;0.191]; Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; \u003cb\u003eSupplementary Fig.\u0026nbsp;3\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs a sensitivity analysis, we excluded children with family history of mania and repeated the analyses. With the four-level family risk, depression PGS showed a significant association, but bipolar disorder PGS did not (estimate, 0.115 [95% CI, 0.047\u0026ndash;0.182]; FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05, not Bonferroni-significant; \u003cb\u003eSupplementary Fig.\u0026nbsp;4A\u003c/b\u003e). Likewise, binary any family history showed a significant association with depression PGS (estimate, 0.095 [95% CI, 0.047\u0026ndash;0.143]; Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; \u003cb\u003eSupplementary Fig.\u0026nbsp;4B\u003c/b\u003e). No significant association was found in the regression models with parental depression history (\u003cb\u003eSupplementary Fig.\u0026nbsp;4C\u003c/b\u003e). However, when analyses were confined to children of European ancestry, excluding those with a history of mania, no significant associations were observed (\u003cb\u003eSupplementary Fig.\u0026nbsp;5\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between Psychopathology and Polygenic Scores\u003c/h2\u003e \u003cp\u003eWe investigated whether the PGSs associated with family history of depression would similarly be associated with offspring\u0026rsquo;s psychopathology. Depression PGS was positively associated with parent (OR, 1.130 [95% CI, 1.075\u0026ndash;1.188]) and child reports (OR, 1.116 [95% CI, 1.059\u0026ndash;1.176]) of any psychiatric disorder, conduct/oppositional defiant disorder (OR, 1.148 [95% CI, 1.079\u0026ndash;1.221]), parent report of any anxiety disorder (OR, 1.153 [95% CI, 1.073\u0026ndash;1.238]), conduct disorder (OR, 1.280 [95% CI, 1.120\u0026ndash;1.462]), ADHD (OR, 1.111 [95% CI, 1.049\u0026ndash;1.177]), separation anxiety disorder (OR, 1.145 [95% CI, 1.062\u0026ndash;1.234]), parent (OR, 1.141 [95% CI, 1.050\u0026ndash;1.240]) and child reports (OR, 1.146 [95% CI 1.058\u0026ndash;1.243]) of suicidal ideation (FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; \u003cb\u003eSupplementary Table\u0026nbsp;5\u003c/b\u003e). However, bipolar disorder PGS was not associated with any clinical outcomes (unadjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05). Within the regression models, the variances explained by depression PGS ranged from 0.15\u0026ndash;0.65%. In European-ancestry children, depression PGS was also positively associated with behavioral problems, suicidal behaviors, and any psychiatric disorder (FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; \u003cb\u003eSupplementary Fig.\u0026nbsp;6; Supplementary Table\u0026nbsp;6\u003c/b\u003e). Additionally, when testing associations between family history of depression and KSADS diagnoses, we observed that the risk for psychiatric disorders and suicidal behaviors increases as family risk increases both in multi-ancestry and European-ancestry children (\u003cb\u003eSupplementary Table\u0026nbsp;7\u0026ndash;8\u003c/b\u003e), similar to what we have found previously [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWith the four-level family risk variable included in the models with depression PGS, PGS for depression was still significantly associated with KSADS diagnoses such as any psychiatric disorder, conduct/oppositional defiant disorder, conduct disorder, any anxiety disorder, sleep problems, and suicidal ideation (FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; \u003cb\u003eSupplementary Table\u0026nbsp;9\u003c/b\u003e). The models including both depression PGS and family risk accounted for a slightly greater variance of KSADS diagnoses (parent-reported any psychiatric disorder; 2.59%) than the model including only family history of depression (2.41%). Likewise, in European-ancestry samples, depression PGS showed significant effects on similar KSADS diagnoses including both family history and depression PGS (FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; \u003cb\u003eSupplementary Table\u0026nbsp;10\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMediation Analysis with PGSs as Mediators\u003c/h2\u003e \u003cp\u003eGiven that only the depression PGS was found to be significantly associated with both familial depression history and offspring\u0026rsquo;s psychopathology, we further investigated whether depression PGS mediated the effects of familial depression history on offspring\u0026rsquo;s psychopathology.\u003c/p\u003e \u003cp\u003eThe mediation models with the binary indicator of any family history (G1-/G2- vs. FamHist+) showed that depression PGS had significant mediation effects on all tested 14 clinical outcomes including parent- (estimate, 0.0021 [95% CI, 0.0009\u0026ndash;0.0037]) and child-reported (estimate, 0.0019 [95% CI, 0.0008\u0026ndash;0.0033]) any psychiatric disorders, any anxiety disorders (estimate, 0.0012 [95% CI, 0.0005\u0026ndash;0.0007]), conduct/oppositional defiant disorder (estimate, 0.0016 [95% CI, 0.0006\u0026ndash;0.0027]), ADHD (estimate, 0.0014 [95% CI, 0.0005\u0026ndash;0.0018]), self-harm (estimate, 0.0007 [95% CI, 0.0002\u0026ndash;0.0013]), sleep problems of parent report (estimate, 0.0009 [95% CI, 0.0002\u0026ndash;0.0018]), and suicidal behaviors of child (estimate, 0.0009 [95% CI, 0.0002\u0026ndash;0.0018]) and parent reports (estimate, 0.0008 [95% CI, 0.0002\u0026ndash;0.0016]; FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The proportions mediated by depression PGS relative to the total effects on each clinical outcome ranged from 1.39\u0026ndash;5.87%. Similar results were observed with the mediation models of parental depression history. Depression PGS had significant mediation effects on all 14 KSADS diagnoses, except for parent report of suicidal ideation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e Likewise, in European-ancestry samples, depression PGS significantly mediated the impact of multigenerational and parental family risk on KSADS diagnoses (\u003cb\u003eSupplementary Fig.\u0026nbsp;7\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eFamilial history of depression increases risk for offspring psychiatric disorder. Therefore, we investigated whether polygenic risks for psychiatric disorders contribute to intergenerational transmission of depression. We found that multigenerational depression history was positively correlated with higher genome-wide PGSs for depression and bipolar disorder. Moreover, a greater PGS for depression significantly mediated the effects of familial history of depression on offspring\u0026rsquo;s mental health indexed by KSADS diagnoses. To our best knowledge, this is the first report showing polygenic risk for depression as a potential mechanism for the transgenerational transmission of depression.\u003c/p\u003e \u003cp\u003eAddressing conflicting results from previous research on the association between first-degree family history and depression PGS [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], the present study utilized more recent and larger GWAS results for constructing the PGS of depression, which could partially account for the discrepancies between the findings as well as testing findings in a larger cohort. For the first time, our results reveal that higher depression PGS is significantly associated with a family history of depression spanning multiple generations, encompassing risks from both first- and second-degree family members. The children with two previous generations affected showed the highest PGS (estimate, 0.129 [95% CI, 0.070\u0026ndash;0.187]) in line with the increased risk for psychopathology [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These offspring with two previous generations affected might form a subgroup of individuals with an exceptionally high genetic burden.\u003c/p\u003e \u003cp\u003eWe found a similar association for bipolar PGS (estimate, 0.109 [95% CI, 0.051\u0026ndash;0.168]). But when we limited the sample to those with a family history of depression \u003cem\u003ewithout\u003c/em\u003e mania, bipolar PGS lost its significance in the association with family history. This shows that the significant associations with bipolar PGS might be due to including children with a family history of bipolar disorder and that genetic risk for and familial aggregation of depression and bipolar disorder are separate. This is in line with recent literature showing an association between family history of bipolar disorder and higher bipolar PGS in offspring [\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], reports of familial transmission being specific to type of mood disorder [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and genetic differences between depression and bipolar disorder [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur results also showed that depression PGS and family history of depression together accounted for significant variances of offspring\u0026rsquo;s psychopathology. These results extend previous findings from recent studies that showed family history and PGS are predictive of future cases of depression and including both factors in a model modestly increases the prognostic power in predicting depression [\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe depression PGS was positively correlated with a wide range of KSADS diagnoses, including any psychiatric disorder, any anxiety disorder, suicidal ideation, ADHD, and conduct/oppositional defiant disorder (C/ODD). On the other hand, bipolar PGS showed no significant correlations with KSADS diagnoses. Despite not surviving correction for multiple comparisons, depression PGS was associated with any depressive disorder even at this young age of 9 to 10 years old (unadjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.019). Depression often starts later in adolescence and early adulthood, but higher family and polygenic risk of depression have been shown to be associated with earlier onset [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Suicidal ideation and self-harm at this age, also associated with depression PGS, are becoming more common in recent years [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] and are predictive of later suicide attempts [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. However, identifying those at risk for suicide is challenging. Our results indicate that the combination of family assessments and PGS for depression might increase predictive power in evaluating risk for suicidal thoughts and behaviors in children, especially as PGS are thought to be able to explain more variance in the future as GWASs include ever larger samples.\u003c/p\u003e \u003cp\u003ePGS for depression significantly mediates the effects of family history on offspring\u0026rsquo;s depression. Moreover, the mediation effect was significant for a broad range of psychiatric disorders, including any psychiatric disorder, any anxiety disorder, suicidal thoughts and behaviors, C/ODD, and ADHD. This highlights a role for genetic liability in intergenerational transmission of childhood psychopathology in general and depression specifically in periadolescent children (9\u0026ndash;10 years old). Future research may examine the brain correlates of family history of depression and depression PGS.\u003c/p\u003e \u003cp\u003eFamily history of depression may affect the offspring\u0026rsquo;s risk for psychiatric disorders through genetic or environmental pathways. Here we show that the genetic component is significant and scales with the number of generations affected. On the other hand, children of parents with depression may experience and even generate more stressful life events [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. These events may exacerbate risks of psychiatric disorders. Further research could identify protective or vulnerability factors that may moderate the impact of family history of depression and depression PGS through gene-environment interactions. Furthermore, because we did not have access to parent and grandparent genotypes, we are unable to distinguish between direct genetic effects of the child\u0026rsquo;s genotype on their phenotype and indirect genetic effects through genetic nurture and other mechanisms. For example, the parent and the child may share a genotype associated with higher neuroticism, which could lead to less affectionate caregiving of the parent to the child [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. This, in turn, might bias our estimates of the direct effect of the neuroticism PGS on child psychiatric outcomes through altered parenting.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations:\u003c/h2\u003e \u003cp\u003eThe current study has the strengths of a large, diverse multi-ancestry sample, multigenerational family history assessment, and the latest Bayesian polygenic prediction method to test our hypotheses. Limitations of this study include that in most GWASs, the PGSs were derived from European-ancestry samples and, therefore, the generalizability of the summary statistics to other ancestry samples might be limited. Nevertheless, our findings were consistent across the analyses of multi-ancestry and European-only samples. In addition, PGSs still only account for relatively small variances compared to the heritability of depression estimated from twin studies or DNA, but PGS may become stronger predictors in future. Family history was assessed retrospectively by the caregiver, which may bias reports and underestimate effect sizes compared to samples with gold-standard clinician-based diagnoses for all family members. However, this limitation is mitigated by the fact that we previously showed that clinical results were similar between an interview-based design study [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and the ABCD study [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Lastly, the effect sizes that we found, while similar to those of prior polygenic score studies [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] are small, suggesting that these PGS do not yet have high clinical significance. As GWAS discovery samples become larger and include multiple genetic ancestries, clinical significance may improve. On the other hand, the children in our sample are still young and before the median age of onset of depression. Some of the currently unaffected children might develop psychiatric disorders as the cohort ages, forming a stronger association between PGS and psychiatric disorders, and increasing the effect sizes.\u003c/p\u003e \u003cp\u003eIn summary, we show that PGSs for depression and bipolar disorder are associated with family history of depression and that depression PGS mediates part of the association between (multigenerational) family history and offspring\u0026rsquo;s psychopathology. We demonstrate that having more previous generations affected with depression is linked to having higher polygenic risk for psychiatric disorders. The findings also implicate polygenic risk for depression as a potential mechanism for intergenerational transmission of depression, suggesting that integrating depression PGS with depression history may aid in identifying children at higher risk for psychopathology.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: \u0026nbsp; EL and MvD are co–first authors and contributed equally to this work.\u003c/p\u003e\n\u003cp\u003eEL and MvD contributed to conceptual design, interpretation of findings, and writing and revision of the manuscript. EL contributed to statistical analysis. EL, BK, GK, and YJ contributed to generation of genome-wide polygenic scores. EM, AT, MMW, and JC contributed to conceptual design and revising the manuscript. MMW and JC supervised the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (JC, No. 2021R1C1C1006503, 2021K1A3A1A2103751212, 2021M3E5D2A01022515, RS-2023-00266787, RS-2023-00265406), by Creative-Pioneering Researchers Program through Seoul National University (JC, No. 200-20230058), by Semi-Supervised Learning Research Grant by SAMSUNG (JC, No.A0426-20220118), by Identify the network of brain preparation steps for concentration Research Grant by LooxidLabs (JC, No.339-20230001), by Institute of Information \u0026amp; communications Technology Planning \u0026amp; Evaluation (IITP) grant funded by the Korea government (MSIT) (JC, No.2021-0-01343, Artificial Intelligence Graduate School Program of Seoul National University), by National Institute of Mental Health (MvD, No. K99MH129611; MMW, No. R01MH036197), and by AFSP Young Investigator Award (MvD, No. YIG-R-001-19).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e: Dr.Weissman receives book royalties from Perseus Press and Oxford Press.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHammen C, Brennan PA. 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Journal of Child Psychology and Psychiatry. 2023;64(4):693-707.\u003c/li\u003e\n\u003cli\u003eCheesman R, Eilertsen EM, Ahmadzadeh YI, Gjerde LC, Hannigan LJ, Havdahl A, et al. How important are parents in the development of child anxiety and depression? A genomic analysis of parent-offspring trios in the Norwegian Mother Father and Child Cohort Study (MoBa). BMC medicine. 2020;18:1-11.\u003c/li\u003e\n\u003cli\u003eNi G, Zeng J, Revez JA, Wang Y, Zheng Z, Ge T, et al. A comparison of ten polygenic score methods for psychiatric disorders applied across multiple cohorts. Biological psychiatry. 2021;90(9):611-20.\u003c/li\u003e\n\u003cli\u003eWray NR, Lin T, Austin J, Mcgrath JJ, Hickie IB, Murray GK, et al. From Basic Science to Clinical Application of Polygenic Risk Scores. JAMA Psychiatry. 2021;78(1):101.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"mp","sideBox":"Learn more about [Molecular Psychiatry](http://www.nature.com/mp/)","snPcode":"41380","submissionUrl":"https://mts-mp.nature.com/cgi-bin/main.plex","title":"Molecular Psychiatry","twitterHandle":"@molpsychiatry","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4264742/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4264742/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA family history of depression is a well-documented risk factor for offspring psychopathology. However, the genetic mechanisms underlying the intergenerational transmission of depression remain unclear. We used genetic, family history, and diagnostic data from 11,875 9\u0026ndash;10 year-old children from the Adolescent Brain Cognitive Development study. We estimated and investigated the children\u0026rsquo;s polygenic scores (PGSs) for 30 distinct traits and their association with a family history of depression (including grandparents and parents) and the children's overall psychopathology through logistic regression analyses. We assessed the role of polygenic risk for psychiatric disorders in mediating the transmission of depression from one generation to the next. Among 11,875 multi-ancestry children, 8,111 participants had matching phenotypic and genotypic data (3,832 female [47.2%]; mean (SD) age, 9.5 (0.5) years), including 6,151 [71.4%] of European ancestry). Greater PGSs for depression (estimate\u0026thinsp;=\u0026thinsp;0.129, 95% CI\u0026thinsp;=\u0026thinsp;0.070\u0026ndash;0.187) and bipolar disorder (estimate\u0026thinsp;=\u0026thinsp;0.109, 95% CI\u0026thinsp;=\u0026thinsp;0.051\u0026ndash;0.168) were significantly associated with higher family history of depression (Bonferroni-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05). Depression PGS was the only PGS that significantly associated with both family risk and offspring\u0026rsquo;s psychopathology, and robustly mediated the impact of family history of depression on several youth psychopathologies including anxiety disorders, suicidal ideation, and any psychiatric disorder (proportions mediated 1.39%-5.87% of the total effect on psychopathology; FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05). These findings suggest that increased polygenic risk for depression partially mediates the associations between family risk for depression and offspring psychopathology, showing a genetic basis for intergenerational transmission of depression. Future approaches that combine assessments of family risk with polygenic profiles may offer a more accurate method for identifying children at elevated risk.\u003c/p\u003e","manuscriptTitle":"Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-17 19:59:34","doi":"10.21203/rs.3.rs-4264742/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-09-19T14:30:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-07-10T09:32:10+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-06-26T13:02:43+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-06-24T07:46:55+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-06-19T01:00:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-17T09:24:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-16T09:58:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Psychiatry","date":"2024-04-15T13:35:26+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2024-04-15T10:04:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"mp","sideBox":"Learn more about [Molecular Psychiatry](http://www.nature.com/mp/)","snPcode":"41380","submissionUrl":"https://mts-mp.nature.com/cgi-bin/main.plex","title":"Molecular Psychiatry","twitterHandle":"@molpsychiatry","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f62c93e1-6d8f-48d7-9e14-2ce8103f9fc6","owner":[],"postedDate":"July 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33431397,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":33431398,"name":"Health sciences/Diseases/Psychiatric disorders/Depression"},{"id":33431399,"name":"Biological sciences/Genetics"},{"id":33431400,"name":"Biological sciences/Psychology"}],"tags":[],"updatedAt":"2025-09-09T07:09:55+00:00","versionOfRecord":{"articleIdentity":"rs-4264742","link":"https://doi.org/10.1038/s41380-025-03221-8","journal":{"identity":"molecular-psychiatry","isVorOnly":false,"title":"Molecular Psychiatry"},"publishedOn":"2025-09-08 04:00:00","publishedOnDateReadable":"September 8th, 2025"},"versionCreatedAt":"2024-07-17 19:59:34","video":"","vorDoi":"10.1038/s41380-025-03221-8","vorDoiUrl":"https://doi.org/10.1038/s41380-025-03221-8","workflowStages":[]},"version":"v1","identity":"rs-4264742","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4264742","identity":"rs-4264742","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}