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Molecular genetic contributions to socioeconomic status and intelligence.

ABSTRACT: Education, socioeconomic status, and intelligence are commonly used as predictors of health outcomes, social environment, and mortality. Education and socioeconomic status are typically viewed as environmental variables although both correlate with intelligence, which has a substantial genetic basis. Using data from 6815 unrelated subjects from the Generation Scotland study, we examined the genetic contributions to these variables and their genetic correlations. Subjects underwent genome-wide testing for common single nucleotide polymorphisms (SNPs). DNA-derived heritability estimates and genetic correlations were calculated using the 'Genome-wide Complex Trait Analyses' (GCTA) procedures. 21% of the variation in education, 18% of the variation in socioeconomic status, and 29% of the variation in general cognitive ability was explained by variation in common SNPs (SEs ~ 5%). The SNP-based genetic correlations of education and socioeconomic status with general intelligence were 0.95 (SE 0.13) and 0.26 (0.16), respectively. There are genetic contributions to intelligence and education with near-complete overlap between common additive SNP effects on these traits (genetic correlation ~ 1). Genetic influences on socioeconomic status are also associated with the genetic foundations of intelligence. The results are also compatible with substantial environmental contributions to socioeconomic status.

SUBMITTER: Marioni RE

PROVIDER: S-EPMC4051988 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Molecular genetic contributions to socioeconomic status and intelligence.

Marioni Riccardo E RE Davies Gail G Hayward Caroline C Liewald Dave D Kerr Shona M SM Campbell Archie A Luciano Michelle M Smith Blair H BH Padmanabhan Sandosh S Hocking Lynne J LJ Hastie Nicholas D ND Wright Alan F AF Porteous David J DJ Visscher Peter M PM Deary Ian J IJ

Intelligence 20140501 100

Education, socioeconomic status, and intelligence are commonly used as predictors of health outcomes, social environment, and mortality. Education and socioeconomic status are typically viewed as environmental variables although both correlate with intelligence, which has a substantial genetic basis. Using data from 6815 unrelated subjects from the Generation Scotland study, we examined the genetic contributions to these variables and their genetic correlations. Subjects underwent genome-wide te ...[more]

PMID: 24944428

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Project description:BackgroundSubjective "ladder" measurements of socio-economic status (SES) are easy-to-administer tools that ask respondents to rate their own SES, allowing them to evaluate their own material resources and determine where it places them relative to their community. Here, we sought to compare the MacArthur Scale of Subjective Social status to the WAMI, an objective measure of SES that includes data on water and sanitation, asset ownership, education, and income.MethodsLeveraging a study of 595 tuberculosis patients in Lima, Peru, we compared the MacArthur ladder score to the WAMI score using weighted Kappa scores and Spearman's rank correlation coefficient. We identified outliers that fell outside the 95th percentile and assessed the durability of the inconsistencies between scores by re-testing a subset of participants. We then used Akaike information criterion (AIC) to compare the predictability of logistic regression models evaluating the association between the two SES scoring systems and history of asthma.ResultsThe correlation coefficient between the MacArthur ladder and WAMI scores was 0.37 and the weighted Kappa was 0.26. The correlation coefficients differed by less than 0.04 and the Kappa ranged from 0.26 to 0.34, indicating fair agreement. When we replaced the initial MacArthur ladder scores with retest scores, the number of individuals with disagreements between the two scores decreased from 21 to 10 and the correlation coefficient and weighted Kappa both increased by at least 0.03. Lastly, we found that when we categorized WAMI and MacArthur ladder scores into three groups, both had a linear trend association with history of asthma with effect sizes and AICs that differed by less than 15% and 2 points, respectively.ConclusionOur findings demonstrated fair agreement between the MacArthur ladder and WAMI scores. The agreement between the two SES measurements increased when they were further categorized into 3-5 categories, the form in which SES is often used in epidemiologic studies. The MacArthur score also performed similarly to WAMI in predicting a socio-economically sensitive health outcome. Researchers should consider subjective SES tools as an alternative method for measuring SES, particularly in large health studies where data collection is a burden.

Project description:Background: Disparities in socioeconomic status have been associated with adverse pregnancy outcomes, including preterm birth and fetal growth restriction. As the barrier between maternal exposures and the fetus, the placenta has been proposed to play a role in the mechanisms leading to poor health outcomes seen with socioeconomic disadvantage. We hypothesized that exposure to lower SES during pregnancy may lead to altered placental DNA methylation (DNAme) that is in turn associated with other pregnancy outcomes. Methods: Placental samples from the Stress, Pregnancy, and Health Study (SPAH) study (n=493) were processed for DNAme analysis using the Illumina Infinium MethylationEPIC BeadChip array. Linear modelling was used to assess whether placental DNAme was associated with Socioeconomic Position, Financial Resources, and/or Disadvantage. Results: At FDR <0.05 and |∆β| >0.05, we observed only 2 CpGs associated with Socioeconomic Position after correcting for gestational age and ancestry, while at a less stringent |∆β| >0.02 threshold there were 77 and 22 CpG associations with Socioeconomic Position and Disadvantage respectively. However, these changes seemed to be explained by genetic variation influencing DNAme in combination with population stratification by socioeconomic status. We did observe associations between socioeconomic status and DNAme-inferred cell composition and epigenetic age acceleration, with intrinsic (p=0.047) and extrinsic (p=0.050) age acceleration being slightly accelerated with lower levels of Socioeconomic Position. Financial Resources and Disadvantage SES trended in the same direction as Social Position, with lower socioeconomic status seen with higher levels of age acceleration, though not reaching significance. No meaningful associations in sex stratified analyses were identified, although XX placentas showed higher cytotrophoblast:syncytiotrophoblast ratio than XY placentas (p=0.00013). Conclusions: Our results emphasize the importance in placental studies involving diverse cohorts to account for genetic variation in order to avoid false findings. This study also demonstrates the challenges with elucidating mechanisms underlying socioeconomic associated outcomes, given the complex nature of correlated variables. Further investigation is required to elucidate whether epigenetic age acceleration is an adverse effect of exposure to prenatal maternal stress associated with socioeconomic disparities, or alternatively, if placental epigenetic aging is a potential healthy adaption to pregnancy complications that increase the risk of preterm delivery.

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Molecular genetic contributions to socioeconomic status and intelligence.

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Molecular genetic contributions to socioeconomic status and intelligence.

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