151 research outputs found

    Cognition in Context: Pathways and Compound Risk in a Sample of US Non-Hispanic Whites

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    The population of individuals with cognitive impairment and dementia is growing rapidly, necessitating etiological investigation. It is clear that individual differences in cognition later in life have both genetic and multi-level environmental correlates. Despite significant recent progress in cellular and molecular research, the exact mechanisms linking genes, brains, and cognition remain elusive. In relation to cognition, it is unlikely that genetic and environmental risk factors function in a vacuum, but rather interact and cluster together. The purpose of the present study was to examine whether aspects of individual socioeconomic status (SES) explain the cognitive genotype-phenotype association, and whether neighborhood SES modifies the effects of genes and individual SES on cognitive ability. Using data from non-Hispanic White participants in the 2016 wave of the Health and Retirement Study, a national sample of United States adults, we examined links between a polygenic score for general cognition and performance-based cognitive functioning. In a series of weighted linear regressions and formal tests of mediation, we observed a significant genotype-phenotype association that was partially attenuated after including individual education to the baseline model, although little reductions were observed for household wealth or census tract-level percent poverty. These findings suggest that genetic risk for poor cognition is partially explained by education, and this pathway is not modified by poverty-level of the neighborhood

    Exploring Rural-Urban Differences in Polygenic Associations for Health among Older Adults in the United States

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    A complex combination of genes and environment influence health and, as a result, both genes and environment can play a role in shaping health disparities. We consider distinctions in these influences across rural and urban settings, expanding upon work that shows lower genetic associations in rural compared to urban places by studying an older age group and examining more than the typical outcomes of alcohol/substance abuse. Using a sample of 14,994 adults from the 1992 through 2016 waves of the Health andRetirement Study, our results suggest genetic associations for BMI and heart conditions are significantly lower in rural compared to urban settings. We do not find evidence in support of this association for depression and smoking. In sum, the results suggest the gene-environment interaction may play a role in the well-documented disparities across rural and urban places within the United States, further highlighting the importance of the social, economic, and built environments for individual health

    The Association Between the MAOA 2R Genotype and Delinquency Over Time Among Men: The Interactive Role of Parental Closeness and Parental Incarceration

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    Using a panel of 6,001 males from the National Longitudinal Study of Adolescent and Adult Health, we examine potential moderation by paternal incarceration and parent-child closeness altering the relationship between the rare 2R MAOA genotype and delinquency. By jointly examining moderation patterns for both the mother and father with the transmission of the MAOA genotype from mother to son, we are able to make inferences about the specific genetic model that best explains these outcomes. In line with prior research, we find a direct relationship between the MAOA 2R genotype and delinquency, independent of parental incarceration and closeness. Examining moderation patterns, we find that delinquency risk for the 2R allele is buffered for males close to their biological or social father, but not their biological mother. We conclude that the 2R delinquency association is not due to passive gene-environment correlation but is best characterized as a social control gene-environment interaction

    Does Crime Trigger Genetic Risk for Type 2 Diabetes in Young Adults? A G x E Interaction Study Using National Data

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    Background Living in neighborhoods perceived as disordered exacerbates genetic risk for type 2 diabetes (T2D) among older adults. It is unknown whether this gene-neighborhood interaction extends to younger adults. The present study aims to investigate whether crime, an objectively measured indicator of neighborhood disorder, triggers genetic risk for T2D among younger adults, and whether this hypothesized triggering occurs through exposure to obesity. Methods Data were from the Wave I (2008) National Longitudinal Study of Adolescent to Adult Health. A standardized T2D polygenic score was created using 2014 GWAS meta-analysis results. Weighted mediation analyses using generalized structural equation models were conducted in a final sample of 7606 adults (age range: 25–34) to test the overall association of T2D polygenic scores with T2D, and the mediating path through obesity exposure in low, moderate, and high county crime-rate groups. Age, sex, ancestry, educational degree, household income, five genetic principal components, and county-level concentrated advantage and population density were adjusted. Results The overall association between T2D polygenic score and T2D was not significant in low-crime areas (p = 0.453), marginally significant in moderate-crime areas (p = 0.064), and statistically significant in high-crime areas (p = 0.007). The mediating path through obesity was not significant in low or moderate crime areas (ps = 0.560 and 0.261, respectively), but was statistically significant in high-crime areas (p = 0.023). The indirect path through obesity accounted for 12% of the overall association in high-crime area. Conclusion A gene-crime interaction in T2D was observed among younger adults, and this association was partially explained by exposure to obesity

    The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health

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    Our 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 5,000 American adolescents, we found evidence of social forces that act to make friends and schoolmates more genetically similar to one another compared with 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 person’s friends and schoolmates influenced their own education, even after accounting for the person’s own genetics

    Growing Old behind Bars: Health Profiles of the Older Male Inmate Population in the United States

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    Objective: This study examines patterns of multimorbidity among elderly male inmates across four domains of health (chronic medical conditions, drug- and alcohol-related diseases, impairments, and mental and behavioral health) to understand the complex health care needs of this growing population. Method: We use the 2004 Survey of Inmates in State Correctional Facilities and Latent Class Regression Analysis to examine 22 health problems among 1,026 men aged 50 and older. Results: There are four groups of elderly male inmates: (a) relatively healthy (45.1%), (b) substance users with behavioral health issues (23.4%), (c) chronic unhealthy with impairments and violence/injury (23.6%), and (d) very unhealthy across all domains (7.9%). These groups have unique sociodemographic background and incarceration history characteristics. Conclusion: This study demonstrates the complexity of health for elderly inmates. Prison health should continue to be monitored to aid correctional and community health programs in understanding clinical risks, exposures, and health care needs for this population

    A life course model of self-rated health through adolescence and young adulthood

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    This paper proposes and tests a life course model of self-rated health (SRH) extending from late childhood to young adulthood, drawing on three waves of panel data from the U.S. National Longitudinal Study of Adolescent Health (Add Health). Very little research has examined SRH during the early decades, or whether and how these self-assessments reflect experiences in the family of origin. Background characteristics (parental education, income, and family structure), parental health conditions (asthma, diabetes, obesity, migraines), and early health challenges (physical abuse, presence of a disability, and parental alcoholism and smoking) predict SRH from adolescence to young adulthood. These experiences in the family-of-origin are substantially mediated by the young person’s health and health behaviors (as indicated by obesity, depression, smoking, drinking, and inactivity), although direct effects remain (especially for early health challenges). Associations between SRH and these mediators (especially obesity) strengthen with age. In turn, efforts to promote healthy behaviors in young adulthood, after the completion of secondary school, may be especially strategic in the promotion of health in later adulthood

    Erratum: Testing the key assumption of heritability estimates based on genome-wide genetic relatedness

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    Comparing genetic and phenotypic similarity among unrelated individuals seems a promising way to quantify the genetic component of traits while avoiding the problematic assumptions plaguing twin- and other kin-based estimates of heritability. One approach uses a Genetic Relatedness Estimation through Maximum Likelihood (GREML) model for individuals who are related at less than .025 to predict their phenotypic similarity by their genetic similarity. Here we test the key underlying assumption of this approach: that genetic relatedness is orthogonal to environmental similarity. Using data from the Health and Retirement Study (and two other surveys), we show two unrelated individuals may be more likely to have been reared in a similar environment (urban versus non-urban setting) if they are genetically similar. This effect is not eliminated by controls for population structure. However, when we include this environmental confound in GREML models, heritabilities do not change substantially and thus potential bias in estimates of most biological phenotypes is probably minimal
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