Philipp Koellinger

Socioeconomic status (SES) influences physical and mental health, however its relation with brain structure is less well documented. Here, we examine the role of SES on brain structure using Mendelian randomisation. First, we conduct a multivariate genome-wide association study of SES using individual, household, and area-based measures of SES, with an effective sample size of n=893,604. We identify 469 loci associated with SES and distil these loci into those that are common across measures of SES and those specific to each indicator. Second, using an independent sample of ~35,000 we provide evidence to suggest that total brain volume is a causal factor in higher SES, and that SES is protective against white matter hyperintensities as a proportion of intracranial volume (WMHicv). Third, we find evidence that whilst differences in cognitive ability explain some of the causal effect of SES on WMHicv, differences in SES still afford a protective effect against WMHicv, independent of that made by cognitive ability.

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 …

We conducted a genome-wide association study (GWAS) on income among individuals of European descent and leveraged the results to investigate the socio-economic health gradient (N= 668,288). We found 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes. Our GWAS-derived polygenic index captures 1-4% of income variance, with only one-fourth attributed to direct genetic effects. A phenome-wide association study using this polygenic index showed reduced risks for a broad spectrum of diseases, including hypertension, obesity, type 2 diabetes, coronary atherosclerosis, depression, asthma, and back pain. The income factor showed a substantial genetic correlation (0.92, se=. 006) with educational attainment (EA). Accounting for EA's genetic overlap with income revealed that the remaining genetic signal for higher income related to better mental health but reduced physical health benefits and increased participation in risky behaviours such as drinking and smoking.

We estimate the effect of genetic variants that are associated with differences in cognitive and non-cognitive skills on labor market and education outcomes by linking genetic data from individuals in the Swedish Twin Registry to government registry data. Genes are fixed over the life cycle and genetic differences between full siblings are random, making it possible to establish the causal effects of within-family genetic variation. We show that polygenic indices associated with cognitive skills and personality traits significantly affect income, occupation, and educational attainment. By comparing estimates that use only within-family variation to OLS estimates with and without socioeconomic controls, our results also provide indications of the degree of (residual) confounding, which can be useful for research conducted in datasets that do not contain sibling pairs. Overall, our results indicate that education and labor …

A large literature establishes that cognitive and non-cognitive skills are strongly correlated with educational attainment and professional achievement. Isolating the causal effects of these traits on career outcomes is made difficult by reverse causality and selection issues. We suggest a different approach: instead of using direct measures of individual traits, we use differences between individuals in the presence of genetic variants that are associated with differences in skills and personality traits. Genes are fixed over the life cycle and genetic differences between full siblings are random, making it possible to establish the causal effects of within-family genetic variation. We link genetic data from individuals in the Swedish Twin Registry to government registry data and find evidence for causal effects of genetic differences linked to cognitive skills, personality traits, and economic preferences on professional achievement and educational attainment. Our results also demonstrate that education and labor market outcomes are partially the result of a genetic lottery.

A large literature establishes that cognitive and non-cognitive skills are strongly correlated with educational attainment and professional achievement. Isolating the causal effects of these traits on career outcomes is made difficult by reverse causality and selection issues. We suggest a different approach: instead of using direct measures of individual traits, we use differences between individuals in the presence of genetic variants that are associated with differences in skills and personality traits. Genes are fixed over the life cycle and genetic differences between full siblings are random, making it possible to establish the causal effects of within-family genetic variation. We link genetic data from individuals in the Swedish Twin Registry to government registry data and find evidence for causal effects of genetic differences linked to cognitive skills, personality traits, and economic preferences on professional achievement and educational attainment. Our results also demonstrate that education and labor market outcomes are partially the result of a genetic lottery.

Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation …

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of private households in Germany. The sample provides a detailed life course perspective based on a rich collection of information about living conditions, socio-economic status, family relationships, personality, values, preferences, and health. We collected genetic data from 2,598 individuals in the SOEP Innovation Sample, yielding the first genotyped sample that is representative of the entire German population (Gene-SOEP). The Gene-SOEP sample is a longitudinal study that includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 parent-offspring trios that are overlapping with the parent-offspring pairs. We constructed a repository of 66 polygenic indices in the Gene-SOEP sample based on results from well-powered genome-wide association studies. The Gene-SOEP data provides a valuable resource to study individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and environment.

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 …

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 …

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between …

Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (n ≈ 10,000 UK Biobank participants). Individuals with higher SES, compared with those with lower SES, showed a pattern of increased region volumes in the left brain and decreased region volumes in the right brain. The analogous lateralization pattern emerged for the fiber structure of anatomical white matter tracts. Our multimodal findings suggest hemispheric asymmetry as an SES-related brain signature, which was consistent across six different indicators …

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of~ 3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12–16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (ie, controlling for parental PGIs) explain roughly half the PGI’s magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Heavy alcohol consumption has been associated with brain atrophy, neuronal loss, and poorer white matter fiber integrity. However, there is conflicting evidence on whether light-to-moderate alcohol consumption shows similar negative associations with brain structure. To address this, we examine the associations between alcohol intake and brain structure using multimodal imaging data from 36,678 generally healthy middle-aged and older adults from the UK Biobank, controlling for numerous potential confounds. Consistent with prior literature, we find negative associations between alcohol intake and brain macrostructure and microstructure. Specifically, alcohol intake is negatively associated with global brain volume measures, regional gray matter volumes, and white matter microstructure. Here, we show that the negative associations between alcohol intake and brain macrostructure and microstructure are …

Understanding which biological pathways are specific versus general across diagnostic categories and levels of symptom severity is critical to improving nosology and treatment of psychopathology. Here, we combine transdiagnostic and dimensional approaches to genetic discovery for the first time, conducting a novel multivariate genome-wide association study of eight psychiatric symptoms and disorders broadly related to mood disturbance and psychosis. We identify two transdiagnostic genetic liabilities that distinguish between common forms of psychopathology versus rarer forms of serious mental illness. Biological annotation revealed divergent genetic architectures that differentially implicated prenatal neurodevelopment and neuronal function and regulation. These findings inform psychiatric nosology and biological models of psychopathology, as they suggest that the severity of mood and psychotic …

Genetic tests that predict the lifetime risk of common medical conditions are fast becoming more accurate and affordable. The life insurance industry is interested in using predictive genetic tests in the underwriting process, but more research is needed to establish whether this nascent form of genetic testing can refine the process over conventional underwriting factors. Here, we perform Cox regression of survival on a battery of genetic risk scores for common medical conditions and mortality risks in the Health and Retirement Study, without returning results to participants. Adjusted for covariates in a relevant insurance scenario, the scores could improve mortality risk classification by identifying 2.6 years shorter median lifespan in the highest decile of total genetic liability. We conclude that existing genetic risk scores can already improve life insurance underwriting, which stresses the urgency of policymakers to …

Socioeconomic status (SES) correlates with brain structure, a relation of interest given the long-observed relations of SES to cognitive abilities and health. Yet, major questions remain open, in particular, the pattern of causality that underlies this relation. In an unprecedently large study, here, we assess genetic and environmental contributions to SES differences in neuroanatomy. We first establish robust SES–gray matter relations across a number of brain regions, cortical and subcortical. These regional correlates are parsed into predominantly genetic factors and those potentially due to the environment. We show that genetic effects are stronger in some areas (prefrontal cortex, insula) than others. In areas showing less genetic effect (cerebellum, lateral temporal), environmental factors are likely to be influential. Our results imply a complex interplay of genetic and environmental factors that influence the SES-brain …

Two family-specific lotteries take place during conception—a social lottery that determines who our parents are and which environment we grow up in, and a genetic lottery that determines which part of their genomes our parents pass on to us. The outcomes of these lotteries create inequalities of opportunity that can translate into disparities in health and socioeconomic status. Here, we estimate a lower bound for the relevance of these two lotteries for differences in education, income and body mass index in a sample of 38,698 siblings in the UK who were born between 1937 and 1970. Our estimates are based on models that combine family-specific effects with gene-by-environment interactions. We find that the random differences between siblings in their genetic endowments clearly contribute towards inequalities in the outcomes we study. Our rough proxy of the environment people grew up in, which we derived from their place of birth, are also predictive of the studied outcomes, but not beyond the relevance of family environment. Our estimates suggest that at least 13 to 17 percent of the inequalities in education, wages and BMI in the UK are due to inequalities in opportunity that arise from the outcomes of the social and the genetic lottery.

Several substance use and psychiatric disorders, and associated behavioral challenges, are related to self-regulation, including substance use disorders, childhood behavior problems, and risky sexual behavior. These disorders have profound individual and societal costs. Previous twin-family studies have indicated that there is a strong heritable component shared across behaviors and disorders characterized by behavioral undercontrol. We applied multivariate genomic structural equation modeling to study the underlying genetic liability that influences this spectrum of externalizing disorders, identifying 579 independent loci. To evaluate medical outcomes associated with genetic liability to externalizing, we conducted a phenome-wide association study (PheWAS) in 66,915 genotyped individuals of European-ancestry in the BioVU biorepository, a US-based biobank of electronic health records from the …

Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.