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Domingue, B. W.

Publications and source records attributed to Domingue, B. W..

12 recordsLinked to original sources

Social mobility and biological aging among older adults in the United States

Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may therefore extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We analyzed blood-chemistry and DNA methylation (DNAm) data from n=9286 participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study to test associations of life-course social mobility with biological aging. We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using three DNA methylation "clocks" and three blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ~0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility revealed differential effects by racial identity, suggesting that mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging. Significance StatementUpward social mobility may disrupt effects of early-life disadvantage on aging-related health decline. However, the stresses of crossing social boundaries can have biological costs. To investigate the balance of these forces, we analyzed social mobility from reports of childhood circumstances, education, and later-life wealth in 9,286 older adults in the US Health and Retirement Study. We quantified life-course health impacts of social mobility from blood-chemistry and DNA-methylation analysis of biological aging. We found that educational mobility alone benefited Black Americans less than White Americans, whereas mobility that produced accumulation of wealth into later-life was associated with delayed biological aging across social categories. Black-White disparities in healthy-aging outcomes of educational mobility may reflect inequalities in social gains realized from education.

physiology↗

Parental influences on offspring education: indirect genetic effects of non-cognitive skills

Understanding how parents cognitive and non-cognitive skills influence offspring education is vital for educational, family and economic policy. We use genetics (GWAS-by-subtraction) to assess a latent, broad non-cognitive skills dimension. To index parental effects controlling for genetic transmission, we estimate indirect parental genetic effects of polygenic scores on childhood and adulthood educational outcomes, using siblings (N=47,459), adoptees (N=6,407), and parent-offspring trios (N=2,534) in three UK and Dutch cohorts. We find that parental cognitive and non-cognitive skills affect offspring education through their environment: on average across cohorts and designs, indirect genetic effects explain 36-40% of population polygenic score associations. However, indirect genetic effects are lower for achievement in the Dutch cohort, and for the adoption design. We identify causes of higher sibling- and trio-based estimates: prenatal indirect genetic effects, population stratification, and assortative mating. Our phenotype-agnostic, genetically sensitive approach has established overall environmental effects of parents skills, facilitating future mechanistic work.

genetics↗

Heteroscedastic regression modeling elucidates gene-by-environment interaction

Genotype-by-environment interaction (GxE) occurs when the size of a genetic effect varies systematically across levels of the environment and when the size of an environmental effect varies systematically across levels of the genotype. However, total variance in the phenotype may shift as a function of the moderator irrespective of its etiology such that the proportional effect of the predictor is constant. We expand the traditional GxE regression model to directly account for heteroscedasticity associated with both the genotype and the measured environment. We then derive a test statistic,{xi} , for inferring whether GxE can be attributed to an effect of the moderator on the dispersion of the phenotype. We apply this method to identify genotype-by-birth year interactions for Body Mass Index (BMI) that are distinguishable from general secular increases in the variance of BMI or associations of the genetic predictors (both PGS and individual loci) with BMI variance. We provide software for analyzing such models.

genetics↗

Measuring reading ability in the web-browser with a lexical decision task

An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the web-browser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2-3 minutes) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resource-intensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.

animal behavior and cognition↗

Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated lifecourse mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n=7,193) and educational outcomes for adopted (n=855) and biological (n=20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on "genetic nurture" by showing associations of parental polygenic scores with adopted childrens schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.

genomics↗

Genetic Associations with Mathematics Tracking and Persistence in Secondary School

Maximizing the flow of students through the science, technology, engineering, and math (STEM) pipeline is important to promoting human capital development and reducing economic inequality1. A critical juncture in the STEM pipeline is the highly-cumulative sequence of secondary school math courses2-5. Students from disadvantaged schools are less likely to complete advanced math courses, but debate continues about why6,7. Here, we address this question using student polygenic scores, which are DNA-based indicators of propensity to succeed in education8. We integrated genetic and official school transcript data from over 3,000 European-ancestry students from U.S. high schools. We used polygenic scores as a molecular tracer to understand how the flow of students through the high school math pipeline differs in socioeconomically advantaged versus disadvantaged schools. Students with higher education polygenic scores were tracked to more advanced math already at the beginning of high school and persisted in math for more years. Molecular tracer analyses revealed that the dynamics of the math pipeline differed by school advantage. Compared to disadvantaged schools, advantaged schools tracked more students with high polygenic scores into advanced math classes at the start of high school, and they buffered students with low polygenic scores from dropping out of math. Across all schools, even students with exceptional polygenic scores (top 2%) were unlikely to take the most advanced math classes, suggesting substantial room for improvement in the development of potential STEM talent. These results link new molecular genetic discoveries to a common target of educational-policy reforms.

genetics↗

Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores

Summary statistics from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS). For complex, behavioral traits, the correlation between an individuals PGS and their phenotype may contain bias alongside the causal effect of the individuals genes (due to geographic, ancestral, and/or socioeconomic confounding). We formalize the recent introduction of a different source of bias in regression models using PGSs: the effects of parental genes on offspring outcomes, also known as genetic nurture. GWAS do not discriminate between the various pathways through which genes influence outcomes, meaning existing PGSs capture both direct genetic effects and genetic nurture effects. We construct a theoretical model for genetic effects and show that, unlike other sources of bias in PGSs, the presence of genetic nurture biases PGS coefficients from both naive OLS (between-family) and family fixed effects (within-family) regressions. This bias is in opposite directions; while naive OLS estimates are biased upwards, family fixed effects estimates are biased downwards. We quantify this bias for a given trait using two novel parameters that we identify and discuss: (1) the genetic correlation between the direct and nurture effects and (2) the ratio of the SNP heritabilities for the direct and nurture effects.

genomics↗

Genetics & the Geography of Health, Behavior, and Attainment

Peoples life chances can be predicted by their neighborhoods. This observation is driving efforts to improve lives by changing neighborhoods. Some neighborhood effects may be causal, supporting neighborhood-level interventions. Other neighborhood effects may reflect selection of families with different characteristics into different neighborhoods, supporting interventions that target families/individuals directly. To test how selection affects different neighborhood-linked problems, we linked neighborhood data with genetic, health, and social-outcome data for >7,000 European-descent UK and US young people in the E-Risk and Add Health Studies. We tested selection/concentration of genetic risks for obesity, schizophrenia, teen-pregnancy, and poor educational outcomes in high-risk neighborhoods, including genetic analysis of neighborhood mobility. Findings argue against genetic selection/concentration as an explanation for neighborhood gradients in obesity and mental-health problems, suggesting neighborhoods may be causal. In contrast, modest genetic selection/concentration was evident for teen-pregnancy and poor educational outcomes, suggesting neighborhood effects for these outcomes should be interpreted with care.

genetics↗

A family-based method for leveraging random genetic variation to identify variance-controlling loci

The propensity of a trait to vary within a population may have evolutionary, ecological, or clinical significance. In the present study we deploy sibling models to offer a novel and unbiased way to ascertain loci associated with the extent to which phenotypes vary (variance-controlling quantitative trait loci, or vQTLs). Previous methods for vQTL-mapping either exclude genetically related individuals or treat genetic relatedness among individuals as a complicating factor addressed by adjusting estimates for non-independence in phenotypes. The present method uses genetic relatedness as a tool to obtain unbiased estimates of variance effects rather than as a nuisance. The family-based approach, which utilizes random variation between siblings in minor allele counts at a locus, also allows controls for parental genotype, mean effects, and non-linear (dominance) effects that may spuriously appear to generate variation.\n\nSimulations show that the approach performs equally well as two existing methods (squared Z-score and DGLM) in controlling type I error rates when there is no unobserved confounding, and performs significantly better than these methods in the presence of confounding. Using height and BMI as empirical applications, we investigate SNPs that alter within-family variation in height and BMI, as well as pathways that appear to be enriched. One significant SNP for BMI variability, in the MAST4 gene, replicated. Pathway analysis revealed one gene set, encoding members of several signaling pathways related to gap junction function, which appears significantly enriched for associations with within-family height variation in both datasets (while not enriched in analysis of mean levels). We recommend approximating laboratory random assignment of genotype using family data and more careful attention to the possible conflation of mean and variance effects.

genetics↗

Father Absence And Accelerated Reproductive Development

Evidence shows that girls who experience father absence in childhood experience accelerated reproductive development in comparison to peers with present fathers. One hypothesis advanced to explain this empirical pattern is genetic confounding, wherein gene-environment correlation (rGE) causes a spurious relationship between father absence and reproductive timing. We test this hypothesis by constructing polygenic scores for age at menarche and first birth using recently available genome wide association study results and molecular genetic data on a sample of non-Hispanic white females from the National Longitudinal Study of Adolescent to Adult Health. Young womens accelerated menarche polygenic scores were unrelated to their exposure to father absence. In contrast, earlier first-birth polygenic scores tended to be higher in young women raised in homes with absent fathers. Nevertheless, father absence and the polygenic scores independently and additively predict reproductive timing. We find limited evidence in support of the gene-environment correlation hypothesis.

genetics↗

Analysis of genetic similarity among friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health (Add Health)

Humans tend to form social relationships with others who resemble them. Whether this sorting of like with like arises from historical patterns of migration, meso-level social structures in modern society, or individual-level selection of similar peers remains unsettled. Recent research has evaluated the possibility that unobserved genotypes may play an important role in the creation of homophilous relationships. We extend this work by using data from 9,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic similarities among pairs of friends. While there is some evidence that friends have correlated genotypes, both at the whole-genome level as well as at trait-associated loci (via polygenic scores), further analysis suggests that meso-level forces, such as school assignment, are a principal source of genetic similarity between friends. We also observe apparent social-genetic effects in which polygenic scores of an individuals friends and schoolmates predict the individuals own educational attainment. In contrast, an individuals height is unassociated with the height genetics of peers.\n\nSignificanceOur study reported significant findings of a \"social genome\" that can be quantified and studied to understand human health and behavior. In a national sample of more than 9,000 American adolescents, we found evidence of social forces that act to make friends and schoolmates more genetically similar to one another as compared to random pairs of unrelated individuals. This subtle genetic similarity was observed across the entire genome and at sets of genomic locations linked with specific traits--educational attainment and body-mass index--a phenomenon we term \"social-genetic correlation.\" We also find evidence of a \"social-genetic effect\" such that the genetics of a persons friends and schoolmates influenced their own education, even after accounting for the persons own genetics.

genetics↗

A broad sense measure of health and its properties in the HRS

Measuring health is a crucial component of much social research. Two approaches are typical. Health may be measured via either narrowly targeted questions about aspects of disability or chronic conditions. Alternatively, individuals may be asked to self-report their health in some global sense. Both approaches have potential drawbacks. We consider a broad sense measure of health constructed by items from five different batteries related to physical and mental wellbeing. We demonstrate that this measure predicts time until death better than self-reported health, especially for females. Although this measure has promise, we argue that future surveys on health would benefit from the inclusion of additional items focusing on issues salient to younger individuals or other non-disabled respondents.

epidemiology↗