Genetics of environmental sensitivity to psychiatric and neurodevelopmental phenotypes: evidence from GWAS of monozygotic twins.

Individual sensitivity to environmental exposures may be genetically influenced. This genotype-by-environment interplay implies differences in phenotypic variance across genotypes. However, environmental sensitivity genetic variants have proven challenging to detect. GWAS of monozygotic twin differences is a family-based variance analysis method, which is more robust to systemic biases that impact population-based methods. We combined data from up to 21,792 monozygotic twins (10,896 pairs) from 11 studies to conduct the largest GWAS meta-analysis of monozygotic phenotypic differences in children and adolescents/adults for seven psychiatric and neurodevelopmental phenotypes: attention deficit hyperactivity disorder (ADHD) symptoms, autistic traits, anxiety and depression symptoms, psychotic-like experiences, neuroticism, and wellbeing. The SNP-heritability of variance in these phenotypes were estimated (h2: 0% to 18%), but were imprecise. We identified a total of 13 genome-wide significant associations (SNP, gene, and gene-set), including genes related to stress-reactivity for depression, growth factor-related genes for autistic traits and catecholamine uptake-related genes for psychotic-like experiences. Monozygotic twins are an important new source of evidence about the genetics of environmental sensitivity.

Differences in polygenic associations with educational attainment between West and East Germany before and after reunification.

Here we examine geographical and historical differences in polygenic associations with educational attainment in East and West Germany around reunification. We test this in n = 1902 25-85-year-olds from the German SOEP-G[ene] cohort. We leverage a DNA-based measure of genetic influence, a polygenic index calculated based on a previous genome-wide association study of educational attainment in individuals living in democratic countries. We find that polygenic associations with educational attainment were significantly stronger among East, but not West, Germans after but not before reunification. Negative control analyses of a polygenic index of height with educational attainment and height indicate that this gene-by-environemt interaction is specific to the educational domain. These findings suggest that the shift from an East German state-socialist to a free-market West German system increased the importance of genetic variants previously identified as important for education.

Self-control is associated with health-relevant disparities in buccal DNA-methylation measures of biological aging in older adults.

Self-control is a personality dimension that is associated with better physical health and a longer lifespan. Here, we examined (1) whether self-control is associated with buccal and saliva DNA-methylation (DNAm) measures of biological aging quantified in children, adolescents, and adults, and (2) whether biological aging measured in buccal DNAm is associated with self-reported health. Following preregistered analyses, we computed two DNAm measures of advanced biological age (principal-component PhenoAge and GrimAge Acceleration) and a DNAm measure of pace of aging (DunedinPACE) in buccal samples from the German Socioeconomic Panel Study (SOEP-G[ene], n = 1058, age range 0-72, Mage = 42.65) and saliva samples from the Texas Twin Project (TTP, n = 1327, age range 8-20, Mage = 13.50). We found that lower self-control was associated with advanced biological age in older adults (PhenoAge Acceleration ß = - .34, [- .51, - .17], p < .001; GrimAge Acceleration ß = - .34, [- .49, - .19], p < .001), but not young adults, adolescents or children. These associations remained statistically robust even after correcting for possible confounders such as socioeconomic contexts, BMI, or genetic correlates of low self-control. Moreover, a faster pace of aging and advanced biological age measured in buccal DNAm were associated with self-reported disease (PhenoAge Acceleration: ß = .13 [.06, .19], p < .001; GrimAge Acceleration: ß = .19 [.12, .26], p < .001; DunedinPACE: ß = .09 [.02, .17], p = .01). However, effect sizes were weaker than observations in blood, suggesting that customization of DNAm aging measures to buccal and saliva tissues may be necessary. Our findings are consistent with the hypothesis that self-control is associated with health via pathways that accelerate biological aging in older adults.

Beyond the factor indeterminacy problem using genome-wide association data.

Latent factors, such as general intelligence, depression and risk tolerance, are invoked in nearly all social science research where a construct is measured via aggregation of symptoms, question responses or other measurements. Because latent factors cannot be directly observed, they are inferred by fitting a specific model to empirical patterns of correlations among measured variables. A long-standing critique of latent factor theories is that the correlations used to infer latent factors can be produced by alternative data-generating mechanisms that do not include latent factors. This is referred to as the factor indeterminacy problem. Researchers have recently begun to overcome this problem by using information on the associations between individual genetic variants and measured variables. We review historical work on the factor indeterminacy problem and describe recent efforts in genomics to rigorously test the validity of latent factors, advancing the understanding of behavioural science constructs.

More than nature and nurture, indirect genetic effects on children's academic achievement are consequences of dynastic social processes.

Families transmit genes and environments across generations. When parents' genetics affect their children's environments, these two modes of inheritance can produce an 'indirect genetic effect'. Such indirect genetic effects may account for up to half of the estimated genetic variance in educational attainment. Here we tested if indirect genetic effects reflect within-nuclear-family transmission ('genetic nurture') or instead a multi-generational process of social stratification ('dynastic effects'). We analysed indirect genetic effects on children's academic achievement in their fifth to ninth years of schooling in N = 37,117 parent-offspring trios in the Norwegian Mother, Father, and Child Cohort Study (MoBa). We used pairs of genetically related families (parents were siblings, children were cousins; N = 10,913) to distinguish within-nuclear-family genetic-nurture effects from dynastic effects shared by cousins in different nuclear families. We found that indirect genetic effects on children's academic achievement cannot be explained by processes that operate exclusively within the nuclear family.

Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort.

Importance: Many psychiatric outcomes share a common etiologic pathway reflecting behavioral disinhibition, generally referred to as externalizing (EXT) disorders. Recent genome-wide association studies (GWASs) have demonstrated the overlap between EXT disorders and important aspects of veterans' health, such as suicide-related behaviors and substance use disorders (SUDs). Objective: To explore correlates of risk for EXT disorders within the Veterans Health Administration (VA) Million Veteran Program (MVP). Design, Setting, and Participants: A series of phenome-wide association studies (PheWASs) of polygenic risk scores (PGSs) for EXT disorders was conducted using electronic health records. First, ancestry-specific PheWASs of EXT PGSs were conducted in the African, European, and Hispanic or Latin American ancestries. Next, a conditional PheWAS, covarying for PGSs of comorbid psychiatric problems (depression, schizophrenia, and suicide attempt; European ancestries only), was performed. Lastly, to adjust for unmeasured confounders, a within-family analysis of significant associations from the main PheWAS was performed in full siblings (European ancestries only). This study included the electronic health record data from US veterans from VA health care centers enrolled in MVP. Analyses took place from February 2022 to August 2023 covering a period from October 1999 to January 2020. Exposures: PGSs for EXT, depression, schizophrenia, and suicide attempt. Main Outcomes and Measures: Phecodes for diagnoses derived from the International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification, codes from electronic health records. Results: Within the MVP (560 824 patients; mean [SD] age, 67.9 [14.3] years; 512 593 male [91.4%]), the EXT PGS was associated with 619 outcomes, of which 188 were independent of risk for comorbid problems or PGSs (from odds ratio [OR], 1.02; 95% CI, 1.01-1.03 for overweight/obesity to OR, 1.44; 95% CI, 1.42-1.47 for viral hepatitis C). Of the significant outcomes, 73 (11.9%) were significant in the African results and 26 (4.5%) were significant in the Hispanic or Latin American results. Within-family analyses uncovered robust associations between EXT PGS and consequences of SUDs, including liver disease, chronic airway obstruction, and viral hepatitis C. Conclusions and Relevance: Results of this cohort study suggest a shared polygenic basis of EXT disorders, independent of risk for other psychiatric problems. In addition, this study found associations between EXT PGS and diagnoses related to SUDs and their sequelae. Overall, this study highlighted the potential negative consequences of EXT disorders for health and functioning in the US veteran population.

Stability of DNA-Methylation Profiles of Biological Aging in Children and Adolescents.

Background and Objectives: Methylation profile scores (MPSs) index biological aging and aging-related disease in adults and are cross-sectionally associated with social determinants of health in childhood. MPSs thus provide an opportunity to trace how aging-related biology responds to environmental changes in early life. Information regarding the stability of MPSs in early life is currently lacking. Method: We use longitudinal data from children and adolescents ages 8-18 (N = 428, M age = 12.15 years) from the Texas Twin Project. Participants contributed two waves of salivary DNA-methylation data (mean lag = 3.94 years), which were used to construct four MPSs reflecting multi-system physiological decline and mortality risk (PhenoAgeAccel and GrimAgeAccel), pace of biological aging (DunedinPACE), and cognitive function (Epigenetic-g). Furthermore, we exploit variation among participants in whether they were exposed to the COVID-19 pandemic during the course of study participation, in order to test how a historical period characterized by environmental disruption might affect children's aging-related MPSs. Results: All MPSs showed moderate longitudinal stability (test-retest rs = 0.42, 0.44, 0.46, 0.51 for PhenoAgeAccel, GrimAgeAccel, and Epigenetic-g, and DunedinPACE, respectively). No differences in the stability of MPSs were apparent between those whose second assessment took place after the onset of the COVID-19 pandemic vs. those for whom both assessments took place prior to the pandemic. Conclusions: Aging-related DNA-methylation patterns are less stable in childhood than has been previously observed in adulthood. Further developmental research on the methylome is necessary to understand which environmental perturbations in childhood impact trajectories of biological aging and when children are most sensitive to those impacts.

Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G).

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.

Salivary Epigenetic Measures of Body Mass Index and Social Determinants of Health Across Childhood and Adolescence.

Importance: Children who are socioeconomically disadvantaged are at increased risk for high body mass index (BMI) and multiple diseases in adulthood. The developmental origins of health and disease hypothesis proposes that early life conditions affect later-life health in a manner that is only partially modifiable by later-life experiences. Objective: To examine whether epigenetic measures of BMI developed in adults are valid biomarkers of childhood BMI and if they are sensitive to early life social determinants of health. Design, Setting, and Participants: This population-based study of over 3200 children and adolescents aged 8 to 18 years included data from 2 demographically diverse US pediatric cohort studies that combine longitudinal and twin study designs. Analyses were conducted from 2021 to 2022. Exposures: Socioeconomic status, marginalized groups. Main Outcome and Measure: Salivary epigenetic BMI, BMI. Analyses were conducted to validate the use of saliva epigenetic BMI as a potential biomarker of child BMI and to examine associations between epigenetic BMI and social determinants of health. Results: Salivary epigenetic BMI was calculated from 2 cohorts: (1) 1183 individuals aged 8 to 18 years (609 female [51%]; mean age, 13.4 years) from the Texas Twin Project and (2) 2020 children (1011 female [50%]) measured at 9 years of age and 15 years of age from the Future of Families and Child Well-Being Study. Salivary epigenetic BMI was associated with children's BMI (r = 0.36; 95% CI, 0.31-0.40 to r = 0.50; 95% CI, 0.42-0.59). Longitudinal analysis found that epigenetic BMI was highly stable across adolescence but remained both a leading and lagging indicator of BMI change. Twin analyses showed that epigenetic BMI captured differences in BMI between monozygotic twins. Moreover, children from more disadvantaged socioeconomic status (b = -0.13 to -0.15 across samples) and marginalized racial and ethnic groups (b = 0.08-0.34 across samples) had higher epigenetic BMI, even when controlling for concurrent BMI, pubertal development, and tobacco exposure. Socioeconomic status at birth relative to concurrent socioeconomic status best predicted epigenetic BMI in childhood and adolescence (b = -0.15; 95% CI, -0.20 to -0.09). Conclusion and Relevance: This study demonstrated that epigenetic measures of BMI calculated from pediatric saliva samples were valid biomarkers of childhood BMI and may be associated with early-life social inequalities. The findings are in line with the hypothesis that early-life conditions are especially important factors in epigenetic regulation of later-life health. Research showing that health later in life is linked to early-life conditions has important implications for the development of early-life interventions that could significantly extend healthy life span.

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics.

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, although down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci; the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses were found robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who generate and share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.

Self-control is associated with health-relevant disparities in buccal DNA-methylation measures of biological aging in older adults.

Self-control is a personality dimension that is associated with better physical health and a longer lifespan. Here we examined (1) whether self-control is associated with buccal and saliva DNA-methylation (DNAm) measures of biological aging quantified in children, adolescents, and adults, and (2) whether biological aging measured in buccal DNAm is associated with self-reported health. Following preregistered analyses, we computed two DNAm measures of advanced biological age (PhenoAge and GrimAge Acceleration) and a DNAm measure of pace of aging (DunedinPACE) in buccal samples from the German Socioeconomic Panel Study (SOEP-G[ene], n = 1058, age range 0-72, Mage = 42.65) and saliva samples from the Texas Twin Project (TTP, n = 1327, age range 8-20, Mage = 13.50). We found that lower self-control was associated with advanced biological age in older adults (ß =-.34), but not young adults, adolescents or children. This association was not accounted for by statistical correction for socioeconomic contexts, BMI, or genetic correlates of low self-control. Moreover, a faster pace of aging and advanced biological age measured in buccal DNAm were associated with worse self-reported health (ß =.13 to ß = .19). But, effect sizes were weaker than observations in blood, thus customization of DNAm aging measures to buccal and saliva tissues may be necessary. Our findings are consistent with the hypothesis that self-control is associated with health via pathways that accelerate biological aging in older adults.

Causal complexity in human research: On the shared challenges of behavior genetics, medical genetics, and environmentally oriented social science.

We received 23 spirited commentaries on our target article from across the disciplines of philosophy, economics, evolutionary genetics, molecular biology, criminology, epidemiology, and law. We organize our reply around three overarching questions: (1) What is a cause? (2) How are randomized controlled trials (RCTs) and within-family genome-wide association studies (GWASs) alike and unalike? (3) Is behavior genetics a qualitatively different enterprise? Throughout our discussion of these questions, we advocate for the idea that behavior genetics shares many of the same pitfalls and promises as environmentally oriented research, medical genetics, and other arenas of the social and behavioral sciences.

A multivariate approach to understanding the genetic overlap between externalizing phenotypes and substance use disorders.

Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioural under-control, termed externalizing phenotypes. In this study, we used genomic structural equation modelling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate genome-wide association studies of an externalizing and an addiction risk factor, respectively. We first evaluated five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures and a bifactor model. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. Finally, we quantified the degree of polygenic overlap between externalizing and addiction risk using MiXeR. We found that the common and two-factor structures provided the best fit to the data, evidenced by high factor loadings, good factor reliability and no evidence of concerning model characteristics. The two-factor models yielded high genetic correlations between factors (rg s ≥ 0.87), and between the effect sizes of genetic correlations with external traits (rg  ≥ 0.95). Nevertheless, 21 of the 84 correlations with external criteria showed small, significant differences between externalizing and addiction risk factors. MiXer results showed that approximately 81% of influential externalizing variants were shared with addiction risk, whereas addiction risk shared 56% of its influential variants with externalizing. These results suggest that externalizing and addiction genetic risk are largely shared, though both constructs also retain meaningful unshared genetic variance. These results can inform future efforts to identify specific genetic influences on externalizing and SUDs.

Do polygenic indices capture "direct" effects on child externalizing behavior? Within-family analyses in two longitudinal birth cohorts.

Behaviors and disorders characterized by difficulties with self-regulation, such as problematic substance use, antisocial behavior, and symptoms of attention-deficit/hyperactivity disorder (ADHD), incur high costs for individuals, families, and communities. These externalizing behaviors often appear early in the life course and can have far-reaching consequences. Researchers have long been interested in direct measurements of genetic risk for externalizing behaviors, which can be incorporated alongside other known risk factors to improve efforts at early identification and intervention. In a preregistered analysis drawing on data from the Environmental Risk (E-Risk) Longitudinal Twin Study (N=862 twins) and the Millennium Cohort Study (MCS; N=2,824 parent-child trios), two longitudinal cohorts from the UK, we leveraged molecular genetic data and within-family designs to test for genetic effects on externalizing behavior that are unbiased by the common sources of environmental confounding. Results are consistent with the conclusion that an externalizing polygenic index (PGI) captures causal effects of genetic variants on externalizing problems in children and adolescents, with an effect size that is comparable to those observed for other established risk factors in the research literature on externalizing behavior. Additionally, we find that polygenic associations vary across development (peaking from age 5-10 years), that parental genetics (assortment and parent-specific effects) and family-level covariates affect prediction little, and that sex differences in polygenic prediction are present but only detectable using within-family comparisons. Based on these findings, we believe that the PGI for externalizing behavior is a promising means for studying the development of disruptive behaviors across child development.

Genetic contributions of noncognitive skills to academic development.

Noncognitive skills such as motivation and self-regulation, predict academic achievement beyond cognitive skills. However, the role of genetic and environmental factors and of their interplay in these developmental associations remains unclear. We provide a comprehensive account of how cognitive and noncognitive skills contribute to academic achievement from ages 7 to 16 in a sample of >10,000 children from England and Wales. Results indicated that noncognitive skills become increasingly predictive of academic achievement across development. Triangulating genetic methods, including twin analyses and polygenic scores (PGS), we found that the contribution of noncognitive genetics to academic achievement becomes stronger over development. The PGS for noncognitive skills predicted academic achievement developmentally, with prediction nearly doubling by age 16, pointing to gene-environment correlation (rGE). Within-family analyses indicated both passive and active/evocative rGE processes driven by noncognitive genetics. By studying genetic effects through a developmental lens, we provide novel insights into the role of noncognitive skills in academic development.

Genetic contributions of noncognitive skills to academic development.

Noncognitive skills such as motivation and self-regulation, are partly heritable and predict academic achievement beyond cognitive skills. However, how the relationship between noncognitive skills and academic achievement changes over development is unclear. The current study examined how cognitive and noncognitive skills contribute to academic achievement from ages 7 to 16 in a sample of over 10,000 children from England and Wales. Noncognitive skills were increasingly predictive of academic achievement across development. Twin and polygenic scores analyses found that the contribution of noncognitive genetics to academic achievement became stronger over the school years. Results from within-family analyses indicated that associations with noncognitive genetics could not simply be attributed to confounding by environmental differences between nuclear families and are consistent with a possible role for evocative/active gene-environment correlations. By studying genetic effects through a developmental lens, we provide novel insights into the role of noncognitive skills in academic development.

Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort.

Background: Many psychiatric outcomes are thought to share a common etiological pathway reflecting behavioral disinhibition, generally referred to as externalizing disorders (EXT). Recent genome-wide association studies (GWAS) have demonstrated the overlap between EXT and important aspects of veterans' health, such as suicide-related behaviors, substance use disorders, and other medical conditions. Methods: We conducted a series of phenome-wide association studies (PheWAS) of polygenic scores (PGS) for EXT, and comorbid psychiatric problems (depression, schizophrenia, and suicide attempt) in an ancestrally diverse cohort of U.S. veterans (N = 560,824), using diagnostic codes from electronic health records. We conducted ancestry-specific PheWASs of EXT PGS in the European, African, and Hispanic/Latin American ancestries. To determine if associations were driven by risk for other comorbid problems, we performed a conditional PheWAS, covarying for comorbid psychiatric problems (European ancestries only). Lastly, to adjust for unmeasured confounders we performed a within-family analysis of significant associations from the main PheWAS in full-siblings (N = 12,127, European ancestries only). Results: The EXT PGS was associated with 619 outcomes across all bodily systems, of which, 188 were independent of risk for comorbid problems of PGS. Effect sizes ranged from OR = 1.02 (95% CI = 1.01, 1.03) for overweight/obesity to OR = 1.44 (95% CI = 1.42, 1.47) for viral hepatitis C. Of the significant outcomes 73 (11.9%) and 26 (4.5%) were significant in the African and Hispanic/Latin American results, respectively. Within-family analyses uncovered robust associations between EXT and consequences of substance use disorders, including liver disease, chronic airway obstruction, and viral hepatitis C. Conclusion: Our results demonstrate a shared polygenic basis of EXT across populations of diverse ancestries and independent of risk for other psychiatric problems. The strongest associations with EXT were for diagnoses related to substance use disorders and their sequelae. Overall, we highlight the potential negative consequences of EXT for health and functioning in the US veteran population.

Associations of socioeconomic disparities with buccal DNA-methylation measures of biological aging.

BACKGROUND: Individuals who are socioeconomically disadvantaged are at increased risk for aging-related diseases and perform less well on tests of cognitive function. The weathering hypothesis proposes that these disparities in physical and cognitive health arise from an acceleration of biological processes of aging. Theories of how life adversity is biologically embedded identify epigenetic alterations, including DNA methylation (DNAm), as a mechanistic interface between the environment and health. Consistent with the weathering hypothesis and theories of biological embedding, recently developed DNAm algorithms have revealed profiles reflective of more advanced aging and lower cognitive function among socioeconomically-at-risk groups. These DNAm algorithms were developed using blood-DNA, but social and behavioral science research commonly collect saliva or cheek-swab DNA. This discrepancy is a potential barrier to research to elucidate mechanisms through which socioeconomic disadvantage affects aging and cognition. We therefore tested if social gradients observed in blood DNAm measures could be reproduced using buccal-cell DNA obtained from cheek swabs. RESULTS: We analyzed three DNAm measures of biological aging and one DNAm measure of cognitive performance, all of which showed socioeconomic gradients in previous studies: the PhenoAge and GrimAge DNAm clocks, DunedinPACE, and Epigenetic-g. We first computed blood-buccal cross-tissue correlations in n = 21 adults (GEO111165). Cross-tissue correlations were low-to-moderate (r = .25 to r = .48). We next conducted analyses of socioeconomic gradients using buccal DNAm data from SOEP-G (n = 1128, 57% female; age mean = 42 yrs, SD = 21.56, range 0-72). Associations of socioeconomic status with DNAm measures of aging were in the expected direction, but were smaller as compared to reports from blood DNAm datasets (r = - .08 to r = - .13). CONCLUSIONS: Our findings are consistent with the hypothesis that socioeconomic disadvantage is associated with DNAm indicators of worse physical health. However, relatively low cross-tissue correlations and attenuated effect sizes for socioeconomic gradients in buccal DNAm compared with reports from analysis of blood DNAm suggest that in order to take full advantage of buccal DNA samples, DNAm algorithms customized to buccal DNAm are needed.

Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility.

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics.

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.