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

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          Abstract

          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.

          One Sentence Summary:

          We find that polygenic associations with educational attainment were significantly stronger among East, but not West, Germans after but not before reunification.

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          Principal components analysis corrects for stratification in genome-wide association studies.

          Alkes L. Price, Nick Patterson, Robert Plenge … (2006)
          Population stratification--allele frequency differences between cases and controls due to systematic ancestry differences-can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers.
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            Defining the role of common variation in the genomic and biological architecture of adult human height

            Andrew R Wood, Tõnu Esko, Jian Yang … (2015)
            Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explain one-fifth of heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured the majority (60%) of heritability. The 697 variants clustered in 423 loci enriched for genes, pathways, and tissue-types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin, and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
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              The German Socio-Economic Panel (SOEP)

              Jan Goebel, Markus M Grabka, Stefan Liebig … (2019)
              Article 0 comments Cited 131 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): bioRxiv
                Journal ID (publisher-id): BIORXIV
                Title: bioRxiv
                Publisher: Cold Spring Harbor Laboratory
                Publication date (Electronic): 26 March 2024
                Electronic Location Identifier: 2024.03.21.585839
                Affiliations
                [1 ]Max Planck Research Group Biosocial – Biology, Social Disparities, and Development; Max Planck Institute for Human Development; Lentzeallee 94, 14195 Berlin, Germany
                [2 ]School of Business and Economics, Economics Fellow, Tinbergen Institute, Amsterdam
                [3 ]Amsterdam Neuroscience, Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam
                [4 ]Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam
                [5 ]Max Planck Institute for Human Development, Berlin
                [6 ]Department of Psychology, The University of Texas, Austin
                [7 ]Population Research Center, The University of Texas, Austin
                Author notes
                Corresponding author: Dr. Laurel Raffington; Max Planck Research Group Biosocial – Biology, Social Disparities, and Development; Max Planck Institute for Human Development; Lentzeallee 94, 14195 Berlin, Germany; raffington@ 123456mpib-berlin.mpg.de
                Author information
                http://orcid.org/0009-0007-3446-9367
                http://orcid.org/0000-0002-5747-0164
                http://orcid.org/0000-0002-0144-5605
                Article
                DOI: 10.1101/2024.03.21.585839
                PMC ID: 10996480
                PubMed ID: 38585898
                SO-VID: 280099ed-8fca-46ee-a427-e11d9690bdfc
                License:

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

                History
                Funding
                During his work on this paper, DF was a pre-doctoral fellow of the International Max Planck Research School on the Life Course (LIFE, www.imprs-life.mpg.de; participating institutions: Max Planck Institute for Human Development, Freie Universität Berlin, Humboldt-Universität zu Berlin, University of Michigan, University of Virginia, University of Zurich). EMTD was supported by the National Institutes of Health (NIH) grants RF1AG073593, R01MH120219, and R01HD092548. EMTD and KPH are Faculty Research Associate of the Population Research Center (PRC), which is supported by a NIH grant P2CHD042849. EMTD is Faculty Research Associate of the Center for Aging and Populations Sciences (CAPS), which is supported by NIH grant P30AG066614. KPH was supported by NIH grants R01HD083613 and R01HD092548. PK received funding from the University of Amsterdam. RH and GGW received funding from the German Research Foundation DFG and the Max Planck Society. LR is faculty member at LIFE and received funding from the Max Planck Society. Funders/support had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Categories
                Subject: Article

                Keywords: education,genetics,gene-environment interaction,german reunification
                Data availability:
                Keywords: education, genetics, gene-environment interaction, german reunification

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