SOCGEN: Combining Social Science and Molecular Genetic Research to Examine Inequality and the Life Course

SOCGEN：结合社会科学和分子遗传学研究来审视不平等和生命历程

• 批准号: ES/N011856/1
• 负责人: Melinda Mills
• 金额: $ 74.66万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FN011856%2F1
• 关键词: SOCGEN; Combining; Social; Science; Molecular

Although there has been an explosion in the amount of the data in the UK that contains information that has both social science indicators (e.g., education, social status) and molecular genetic data (data with genetic markers), it has yet to be exploited by social scientists. Knowledge from social scientists about how to properly use this data to answer social science research questions and statistical tools to accommodate social science problems remains underdeveloped. Yet this new data will allow social scientists to examine fundamentally new research questions and has the potential for substantive breakthroughs. For the first time in history social scientists can uncover whether there is a genetic and biological component to many of the behaviours that have until now only largely been attributed to social factors. Increasing studies demonstrate that there is a genetic component to core social science topics such as educational level and wellbeing. There are, however, many pitfalls to conducting this type of research including lack of accessible learning and teaching material aimed at social scientists and appropriate statistical models or robustness checks of existing models. A primary objective of this project is to bring together substantive social science researchers in the field of inequality and the life course with expertise in statistics, biodemography, and quantitative molecular genetics to develop innovative learning resources, statistical models and packages to address the specific shortcomings in this substantive area of research. Developing accessible teaching resources and tailored statistical models and packages will allow UK social scientists to become trendsetting pioneers in answering new biosocial research questions. This will allow us to convey how insights from molecular genetic data and research can be integrated into life course (and social science) research.

尽管英国的数据量呈爆炸式增长，其中包含社会科学指标（例如教育、社会地位）和分子遗传数据（带有遗传标记的数据）的信息，但尚未被社会科学家利用。社会科学家关于如何正确使用这些数据来回答社会科学研究问题和解决社会科学问题的统计工具的知识仍然不发达。然而，这些新数据将使社会科学家能够检验全新的研究问题，并有可能取得实质性突破。社会科学家有史以来第一次能够揭示许多迄今为止主要归因于社会因素的行为是否存在遗传和生物学成分。越来越多的研究表明，教育水平和福祉等核心社会科学主题存在遗传成分。然而，进行此类研究存在许多陷阱，包括缺乏针对社会科学家的可用学习和教材以及适当的统计模型或现有模型的稳健性检查。该项目的主要目标是汇集不平等和生命历程领域具有统计学、生物人口学和定量分子遗传学专业知识的实质性社会科学研究人员，开发创新的学习资源、统计模型和软件包，以解决这一实质性研究领域的具体缺陷。开发可用的教学资源和定制的统计模型和软件包将使英国社会科学家成为回答新的生物社会研究问题的潮流先锋。这将使我们能够传达如何将分子遗传数据和研究的见解整合到生命历程（和社会科学）研究中。

项目成果

Causal Effects of the Timing of Life-course Events: Age at Retirement and Subsequent Health

生命历程事件发生时间的因果影响：退休年龄和随后的健康状况

• DOI: 10.1177/0049124117729697
• 发表时间: 2017
• 期刊: Sociological Methods & Research
• 影响因子: 6.3
• 作者: Barban N

Gene-environment dependencies lead to collider bias in models with polygenic scores.

• DOI: 10.1038/s41598-021-89020-x
• 发表时间: 2021-05-04
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Akimova ET;Breen R;Brazel DM;Mills MC
• 通讯作者: Mills MC

Cognitive development in children up to age 11 years born after ART-a longitudinal cohort study.

• DOI: 10.1093/humrep/dex102
• 发表时间: 2017-07-01
• 期刊: Human reproduction (Oxford, England)
• 作者: Barbuscia A;Mills MC
• 通讯作者: Mills MC

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

• DOI: 10.1038/ng.3698
• 发表时间: 2016-12
• 期刊: Nature genetics
• 影响因子: 30.8
• 作者: Barban N;Jansen R;de Vlaming R;Vaez A;Mandemakers JJ;Tropf FC;Shen X;Wilson JF;Chasman DI;Nolte IM;Tragante V;van der Laan SW;Perry JR;Kong A;BIOS Consortium;Ahluwalia TS;Albrecht E;Yerges-Armstrong L;Atzmon G;Auro K;Ayers K;Bakshi A;Ben-Avraham D;Berger K;Bergman A;Bertram L;Bielak LF;Bjornsdottir G;Bonder MJ;Broer L;Bui M;Barbieri C;Cavadino A;Chavarro JE;Turman C;Concas MP;Cordell HJ;Davies G;Eibich P;Eriksson N;Esko T;Eriksson J;Falahi F;Felix JF;Fontana MA;Franke L;Gandin I;Gaskins AJ;Gieger C;Gunderson EP;Guo X;Hayward C;He C;Hofer E;Huang H;Joshi PK;Kanoni S;Karlsson R;Kiechl S;Kifley A;Kluttig A;Kraft P;Lagou V;Lecoeur C;Lahti J;Li-Gao R;Lind PA;Liu T;Makalic E;Mamasoula C;Matteson L;Mbarek H;McArdle PF;McMahon G;Meddens SF;Mihailov E;Miller M;Missmer SA;Monnereau C;van der Most PJ;Myhre R;Nalls MA;Nutile T;Kalafati IP;Porcu E;Prokopenko I;Rajan KB;Rich-Edwards J;Rietveld CA;Robino A;Rose LM;Rueedi R;Ryan KA;Saba Y;Schmidt D;Smith JA;Stolk L;Streeten E;Tönjes A;Thorleifsson G;Ulivi S;Wedenoja J;Wellmann J;Willeit P;Yao J;Yengo L;Zhao JH;Zhao W;Zhernakova DV;Amin N;Andrews H;Balkau B;Barzilai N;Bergmann S;Biino G;Bisgaard H;Bønnelykke K;Boomsma DI;Buring JE;Campbell H;Cappellani S;Ciullo M;Cox SR;Cucca F;Toniolo D;Davey-Smith G;Deary IJ;Dedoussis G;Deloukas P;van Duijn CM;de Geus EJ;Eriksson JG;Evans DA;Faul JD;Sala CF;Froguel P;Gasparini P;Girotto G;Grabe HJ;Greiser KH;Groenen PJ;de Haan HG;Haerting J;Harris TB;Heath AC;Heikkilä K;Hofman A;Homuth G;Holliday EG;Hopper J;Hyppönen E;Jacobsson B;Jaddoe VW;Johannesson M;Jugessur A;Kähönen M;Kajantie E;Kardia SL;Keavney B;Kolcic I;Koponen P;Kovacs P;Kronenberg F;Kutalik Z;La Bianca M;Lachance G;Iacono WG;Lai S;Lehtimäki T;Liewald DC;LifeLines Cohort Study;Lindgren CM;Liu Y;Luben R;Lucht M;Luoto R;Magnus P;Magnusson PK;Martin NG;McGue M;McQuillan R;Medland SE;Meisinger C;Mellström D;Metspalu A;Traglia M;Milani L;Mitchell P;Montgomery GW;Mook-Kanamori D;de Mutsert R;Nohr EA;Ohlsson C;Olsen J;Ong KK;Paternoster L;Pattie A;Penninx BW;Perola M;Peyser PA;Pirastu M;Polasek O;Power C;Kaprio J;Raffel LJ;Räikkönen K;Raitakari O;Ridker PM;Ring SM;Roll K;Rudan I;Ruggiero D;Rujescu D;Salomaa V;Schlessinger D;Schmidt H;Schmidt R;Schupf N;Smit J;Sorice R;Spector TD;Starr JM;Stöckl D;Strauch K;Stumvoll M;Swertz MA;Thorsteinsdottir U;Thurik AR;Timpson NJ;Tung JY;Uitterlinden AG;Vaccargiu S;Viikari J;Vitart V;Völzke H;Vollenweider P;Vuckovic D;Waage J;Wagner GG;Wang JJ;Wareham NJ;Weir DR;Willemsen G;Willeit J;Wright AF;Zondervan KT;Stefansson K;Krueger RF;Lee JJ;Benjamin DJ;Cesarini D;Koellinger PD;den Hoed M;Snieder H;Mills MC
• 通讯作者: Mills MC

Analytical Family Demography

家庭人口统计分析

• 发表时间: 2018
• 作者: Barban N