%0 Journal Article %J Labour Economics %D 2021 %T The effect of education on spousal education: a genetic approach %A Nicola Barban %A De Cao, Elisabetta %A Oreffice, Sonia %A Quintana-Domeque, Climent %K Causality %K genes %K instrumental variables %K Matching %K Plausibly exogenous %X We investigate the causal effect of education on spousal education using a sample of couples from the Health and Retirement Study. We estimate reduced-form linear matching functions derived from a parsimonious matching model which links spouses’ education. Using OLS we find that an additional year in husband’s (resp. wife’s) education is associated with an average increase in wife’s (resp. husband’s) education of 0.41 years —95% CI: 0.37, 0.45 (resp. 0.63 years —95% CI: 0.57, 0.68). To deal with endogeneity issues due to measurement error and omitted variables, we use a measure of genetic propensity (polygenic score) for educational attainment as an instrumental variable. Assuming that our instrument is valid, our 2SLS estimate suggests that an additional year in husband’s (resp. wife’s) education increases wife’s (resp. husband’s) education by about 0.49 years —95% CI: 0.35, 0.62 (resp. 0.76 —95% CI: 0.56, 0.96). Since greater genetic propensity for educational attainment has been linked to a range of personality and cognitive skills, we allow for the possibility that the exclusion restriction is violated using the plausible exogenous approach by Conley et al. (2012). A positive causal effect of education on spousal education cannot be ruled out, as long as one standard deviation increase in husband’s (wife’s) genetic propensity for education directly increases wife’s (husband’s) education by less than 0.2 (0.3) years. %B Labour Economics %V 71 %P 102023 %@ 0927-5371 %G eng %R 10.1016/j.labeco.2021.102023 %0 Journal Article %J Preventive Medicine %D 2019 %T Educational attainment and allostatic load in later life: Evidence using genetic markers %A Ding, Xuejie %A Nicola Barban %A Melinda C Mills %K Allostatic load %K Instrumental variable %K Mendelian randomization %K Polygenic risk score %K Years of education %X Education is strongly correlated with health outcomes in older adulthood. Whether the impact of education expansion improves health remains unclear due to a lack of clarity over the causal relationship. Previous health research within the social sciences has tended to use specific activities of daily living or self-reported health status. This study uses a broader and objective health measure - allostatic load (AL) - to take into consideration the exposures that accumulate throughout the life course. This paper applies a Mendelian Randomization (MR) approach to identify causality in relation to education on health as measured by AL. Using the Health and Retirement Study 2008 (N = 3935), we adopt a polygenic score built from genetic variants associated with years of education. To test whether our analyses violate the exclusion assumption, we further run MR Egger regressions to test for bias from pleiotropy. We also explore the potential pathways between education and AL, including smoking, drinking, marital length, health insurance, etc. Using this genetic instrument, we find a 0.3 unit (19% of a standard deviation) reduction in AL per year of schooling. The effect is mainly driven by BMI and Hba1c. Smoking and marital stability are two potential pathways that also causally influenced by education. If our main and sensitivity analyses are valid, the results find support that a higher level of education is causally related to better health in older adulthood. %B Preventive Medicine %V 129 %P 105866 %8 DEC %G eng %9 Article %R 10.1016/j.ypmed.2019.105866 %0 Journal Article %J Soc Sci Med %D 2019 %T The relationship between cognitive decline and a genetic predictor of educational attainment. %A Ding, Xuejie %A Nicola Barban %A Felix C Tropf %A Melinda C Mills %K Cognitive decline %K Educational attainment %K Fluid/crystallised intelligence %K Genetic predictor %K Growth curve modelling %K Polygenic risk score %X

Genetic and environmental factors both make substantial contributions to the heterogeneity in individuals' levels of cognitive ability. Many studies have examined the relationship between educational attainment and cognitive performance and its rate of change. Yet there remains a gap in knowledge regarding whether the effect of genetic predictors on individual differences in cognition becomes more or less prominent over the life course. In this analysis of over 5000 older adults from the Health and Retirement Study (HRS) in the U.S., we measured the change in performance on global cognition, episodic memory, attention & concentration, and mental status over 14 years. Growth curve models are used to evaluate the association between a polygenic risk score for education (education PGS) and cognitive change. Using the most recent education PGS, we find that individuals with higher scores perform better across all measures of cognition in later life. Education PGS is associated with a faster decline in episodic memory in old age. The relationships are robust even after controlling for phenotypic educational attainment, and are unlikely to be driven by mortality bias. Future research should consider genetic effects when examining non-genetic factors in cognitive decline. Our findings represent a need to understand the mechanisms between genetic endowment of educational attainment and cognitive decline from a biological angle.

%B Soc Sci Med %V 239 %P 112549 %8 2019 Sep 13 %G eng %U https://www.ncbi.nlm.nih.gov/pubmed/31546143 %1 http://www.ncbi.nlm.nih.gov/pubmed/31546143?dopt=Abstract %R 10.1016/j.socscimed.2019.112549 %0 Journal Article %J Frontiers in Sociology %D 2019 %T Using Polygenic Scores in Social Science Research: Unraveling Childlessness %A Verweij, Renske M. %A Melinda C Mills %A Stulp, Gert %A Ilja M Nolte %A Nicola Barban %A Felix C Tropf %A Carrell, Douglas T. %A Aston, Kenneth I. %A Krina T Zondervan %A Rahmioglu, Nilufer %A Dalgaard, Marlene %A Skaarup, Carina %A Hayes, M. Geoffrey %A Dunaif, Andrea %A Guo, Guang %A Snieder, Harold %K childlessness %K polygenic score %K social science %X Biological, genetic, and socio-demographic factors are all important in explaining reproductive behavior, yet these factors are typically studied in isolation. In this study, we explore an innovative sociogenomic approach, which entails including key socio-demographic (marriage, education, occupation, religion, cohort) and genetic factors related to both behavioral [age at first birth (AFB), number of children ever born (NEB)] and biological fecundity-related outcomes (endometriosis, age at menopause and menarche, polycystic ovary syndrome, azoospermia, testicular dysgenesis syndrome) to explain childlessness. We examine the association of all sets of factors with childlessness as well as the interplay between them. We derive polygenic scores (PGS) from recent genome-wide association studies (GWAS) and apply these in the Health and Retirement Study (N = 10,686) and Wisconsin Longitudinal Study (N = 8,284). Both socio-demographic and genetic factors were associated with childlessness. Whilst socio-demographic factors explain 19–46% in childlessness, the current PGS explains <1% of the variance, and only PGSs from large GWASs are related to childlessness. Our findings also indicate that genetic and socio-demographic factors are not independent, with PGSs for AFB and NEB related to education and age at marriage. The explained variance by polygenic scores on childlessness is limited since it is largely a behavioral trait, with genetic explanations expected to increase somewhat in the future with better-powered GWASs. As genotyping of individuals in social science surveys becomes more prevalent, the method described in this study can be applied to other outcomes. %B Frontiers in Sociology %V 4 %P 74 %G eng %U https://www.frontiersin.org/article/10.3389/fsoc.2019.00074 %R 10.3389/fsoc.2019.00074 %0 Report %D 2016 %T Assortative Mating on Education: A Genetic Assessment %A Nicola Barban %A De Cao, Elisabetta %A Oreffice, Sonia %A Quintana-Domeque, Climent %K Aging %K Education %K Gender Differences %K Marriage %X Social scientists have overwhelmingly documented a strong and increasing educational homogamy between spouses. When estimating sorting by education, the presence of measurement error in the education variables or random factors in the matching process may underestimate the actual degree of assortative mating, simultaneity bias may overestimate it, while omitting other individual characteristics relevant in the marriage market may under- or overestimate it. We address these issues using an instrumental variables approach based on exploiting genetic variation in polygenic scores and controlling for population stratification. Specifically, we instrument spousal education with his/her educational polygenic score while controlling for own educational polygenic score. If the exclusion restriction is satisfied, our findings indicate that (1) assortative mating is underestimated when using OLS, and that (2) male education is correlated with other matching-relevant socioeconomic characteristics, while female education is productive per se in the matching. If the exclusion restriction is not satisfied, our evidence is consistent with (2). This suggests that individual socioeconomic attractiveness in the marriage market is multidimensional for men, but can be summarized with education for women. %B University of Oxford Department of Economics Discussion Paper Series %I Department of Economics, University of Oxford %C Oxford %P 1-42 %G eng %U http://epubs.surrey.ac.uk/810373/1/paper-791.pdf %0 Journal Article %J Nat Genet %D 2016 %T Genome-wide analysis identifies 12 loci influencing human reproductive behavior. %A Nicola Barban %A Jansen, Rick %A de Vlaming, Ronald %A Vaez, Ahmad %A Mandemakers, Jornt J %A Felix C Tropf %A Shen, Xia %A James F Wilson %A Daniel I Chasman %A Ilja M Nolte %A Tragante, Vinicius %A van der Laan, Sander W %A Perry, John R B %A Kong, Augustine %A Ahluwalia, Tarunveer S %A Albrecht, Eva %A Laura M Yerges-Armstrong %A Atzmon, Gil %A Auro, Kirsi %A Kristin L. Ayers %A Bakshi, Andrew %A Ben-Avraham, Danny %A Klaus Berger %A Bergman, Aviv %A Bertram, Lars %A Bielak, Lawrence F %A Bjornsdottir, Gyda %A Bonder, Marc Jan %A Broer, Linda %A Bui, Minh %A Barbieri, Caterina %A Cavadino, Alana %A Chavarro, Jorge E %A Turman, Constance %A Maria Pina Concas %A Cordell, Heather J %A Gail Davies %A Eibich, Peter %A Eriksson, Nicholas %A Tõnu Esko %A Eriksson, Joel %A Falahi, Fahimeh %A Felix, Janine F %A Mark Alan Fontana %A Lude L Franke %A Gandin, Ilaria %A Gaskins, Audrey J %A Gieger, Christian %A Gunderson, Erica P %A Guo, Xiuqing %A Caroline Hayward %A He, Chunyan %A Edith Hofer %A Huang, Hongyan %A Joshi, Peter K %A Kanoni, Stavroula %A Karlsson, Robert %A Kiechl, Stefan %A Kifley, Annette %A Kluttig, Alexander %A Kraft, Peter %A Lagou, Vasiliki %A Lecoeur, Cecile %A Lahti, Jari %A Li-Gao, Ruifang %A Penelope A Lind %A Tian Liu %A Makalic, Enes %A Mamasoula, Crysovalanto %A Lindsay K Matteson %A Mbarek, Hamdi %A McArdle, Patrick F %A McMahon, George %A Meddens, S Fleur W %A Mihailov, Evelin %A Michael B Miller %A Missmer, Stacey A %A Monnereau, Claire %A van der Most, Peter J %A Myhre, Ronny %A Michael A Nalls %A Nutile, Teresa %A Ioanna Panagiota Kalafati %A Porcu, Eleonora %A Prokopenko, Inga %A Rajan, Kumar B %A Rich-Edwards, Janet %A Cornelius A Rietveld %A Robino, Antonietta %A Rose, Lynda M %A Rueedi, Rico %A Ryan, Kathleen A %A Saba, Yasaman %A Schmidt, Daniel %A Jennifer A Smith %A Stolk, Lisette %A Streeten, Elizabeth %A Tönjes, Anke %A Thorleifsson, Gudmar %A Ulivi, Sheila %A Wedenoja, Juho %A Jürgen Wellmann %A Willeit, Peter %A Yao, Jie %A Yengo, Loic %A Jing Hua Zhao %A Wei Zhao %A Zhernakova, Daria V %A Amin, Najaf %A Andrews, Howard %A Balkau, Beverley %A Barzilai, Nir %A Bergmann, Sven %A Biino, Ginevra %A Bisgaard, Hans %A Bønnelykke, Klaus %A Dorret I Boomsma %A Buring, Julie E %A Campbell, Harry %A Cappellani, Stefania %A Ciullo, Marina %A Cox, Simon R %A Francesco Cucca %A Toniolo, Daniela %A Davey-Smith, George %A Ian J Deary %A George Dedoussis %A Deloukas, Panos %A Cornelia M van Duijn %A Eco J. C. de Geus %A Johan G Eriksson %A Jessica Faul %A Cinzia Felicita Sala %A Froguel, Philippe %A Paolo P. Gasparini %A Giorgia G Girotto %A Hans-Jörgen Grabe %A Greiser, Karin Halina %A Groenen, Patrick J F %A de Haan, Hugoline G %A Haerting, Johannes %A Tamara B Harris %A Andrew C Heath %A Heikkilä, Kauko %A Hofman, Albert %A Homuth, Georg %A Holliday, Elizabeth G %A John L Hopper %A Hyppönen, Elina %A Jacobsson, Bo %A Vincent Jaddoe %A Johannesson, Magnus %A Jugessur, Astanand %A Kähönen, Mika %A Kajantie, Eero %A Sharon L R Kardia %A Keavney, Bernard %A Kolcic, Ivana %A Koponen, Päivikki %A Kovacs, Peter %A Kronenberg, Florian %A Kutalik, Zoltán %A La Bianca, Martina %A Lachance, Genevieve %A Iacono, William G %A Lai, Sandra %A Lehtimäki, Terho %A David C Liewald %A Lindgren, Cecilia M %A Yongmei Liu %A Luben, Robert %A Lucht, Michael %A Luoto, Riitta %A Magnus, Per %A Patrik K E Magnusson %A Nicholas G Martin %A McGue, Matt %A McQuillan, Ruth %A Sarah E Medland %A Meisinger, Christa %A Mellström, Dan %A Andres Metspalu %A Traglia, Michela %A Lili Milani %A Mitchell, Paul %A Grant W Montgomery %A Dennis O Mook-Kanamori %A de Mutsert, Renée %A Nohr, Ellen A %A Ohlsson, Claes %A Olsen, Jørn %A Ong, Ken K %A Paternoster, Lavinia %A Pattie, Alison %A Brenda W J H Penninx %A Markus Perola %A Peyser, Patricia A %A Pirastu, Mario %A Polasek, Ozren %A Power, Chris %A Kaprio, Jaakko %A Raffel, Leslie J %A Katri Räikkönen %A Olli T Raitakari %A Ridker, Paul M %A Ring, Susan M %A Roll, Kathryn %A Rudan, Igor %A Ruggiero, Daniela %A Rujescu, Dan %A Veikko Salomaa %A Schlessinger, David %A Schmidt, Helena %A Schmidt, Reinhold %A Schupf, Nicole %A Johannes H Smit %A Sorice, Rossella %A Timothy Spector %A John M Starr %A Stöckl, Doris %A Strauch, Konstantin %A Stumvoll, Michael %A Swertz, Morris A %A Thorsteinsdottir, Unnur %A A. Roy Thurik %A Nicholas J Timpson %A Tung, Joyce Y %A André G Uitterlinden %A Vaccargiu, Simona %A Viikari, Jorma %A Vitart, Veronique %A Völzke, Henry %A Vollenweider, Peter %A Vuckovic, Dragana %A Waage, Johannes %A Wagner, Gert G %A Wang, Jie Jin %A Wareham, Nicholas J %A David R Weir %A Gonneke Willemsen %A Willeit, Johann %A Alan F Wright %A Krina T Zondervan %A Stefansson, Kari %A Krueger, Robert F %A Lee, James J %A Daniel J. Benjamin %A Cesarini, David %A Philipp D Koellinger %A den Hoed, Marcel %A Snieder, Harold %A Melinda C Mills %X

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

%B Nat Genet %V 48 %P 1462-1472 %8 2016 Dec %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/27798627?dopt=Abstract %R 10.1038/ng.3698