Opportunities and challenges of big data for the social sciences: The case of genomic data

Efficient Federated Kinship Relationship Identification

Kinship relationship estimation plays a significant role in today's genome studies. Since genetic data are mostly stored and protected in different silos, retrieving the desirable kinship relationships across federated data warehouses is a non-trivial problem. The ability to identify and connect related individuals is important for both research and clinical applications. In this work, we propose a new privacy-preserving kinship relationship estimation framework: Incremental Update Kinship Identification (INK). The proposed framework includes three key components that allow us to control the balance between privacy and accuracy (of kinship estimation): an incremental process coupled with the use of auxiliary information and informative scores. Our empirical evaluation shows that INK can achieve higher kinship identification correctness while exposing fewer genetic markers.

Ethical Issues in Social Science Research Employing Big Data

This paper analyzes the ethics of social science research (SSR) employing big data. We begin by highlighting the research gap found on the intersection between big data ethics, SSR and research ethics. We then discuss three aspects of big data SSR which make it warrant special attention from a research ethics angle: (1) the interpretative character of both SSR and big data, (2) complexities of anticipating and managing risks in publication and reuse of big data SSR, and (3) the paucity of regulatory oversight and ethical recommendations on protecting individual subjects as well as societies when conducting big data SSR. Against this backdrop, we propose using David Resnik's research ethics framework to analyze some of the most pressing ethical issues of big data SSR. Focusing on the principles of honesty, carefulness, openness, efficiency, respect for subjects, and social responsibility, we discuss three clusters of ethical issues: those related to methodological biases and personal prejudices, those connected to risks arising from data availability and reuse, and those leading to individual and social harms. Finally, we advance considerations to observe in developing future ethical guidelines about big data SSR.

Incarceration, polygenic risk, and depressive symptoms among males in late adulthood

This study demonstrates how social and genetic factors jointly influence depression in late adulthood. We focus on the effect of incarceration, a major life event consistently found to be associated with mental health problems. Drawing on data from males in the Wisconsin Longitudinal Study and the Health and Retirement Study, we conduct a polygenic score analysis based on a genome-wide association study on depressive symptoms. Our analysis produces two important findings. First, incarceration experience mediates the association between the depression polygenic score and depressive symptoms in late adulthood (i.e., greater polygenic scores are associated with elevated incarceration risk, which increases depressive symptoms in late adulthood). Second, about one-fifth of the association between incarceration experience and late-adulthood depressive symptoms is accounted for by the depression polygenic score and childhood depression. These findings reveal complex biological and social mechanisms in the development of depression and, more broadly, provide important insights for causal inference in social science research.

Cognitive Differences and Influencing Factors of Chinese People's Old-Age Care Responsibility against the Ageing Background

With the rapid increase in the ageing population (60+) in China since 1999, the problem of supporting the aged is facing increasingly severe challenges. Based on the 2072 valid samples from the Chinese General Social Survey (CGSS) of 2017, a non-sequential multinomial logistic regression model was established to analyse the changing trends and micro-influencing factors of Chinese people's cognition of old-age care responsibility (COACR). The result shows that offspring responsibility still is a common COACR, but this concept has been gradually weakened and been replaced by the responsibility of the government and the aged. Individual characteristics and relationships with relatives in the models all significantly affect people's COACR. It is obviously unrealistic for China to completely rely on government and society to provide for the aged. The traditional ethical role of inter-generational responsibility in providing for the aged should be brought into play. Reshaping the inter-generational responsibility ethics of old-age care requires the joint efforts of government, society, families, individuals and other responsible subjects to construct a diversified old-age care service system.

The Intergenerational Transmission of Early Educational Advantages: New Results Based on an Adoption Design

Sociological research has traditionally emphasized the importance of post-birth factors (i.e., social, economic, and cultural capital) in the intergenerational transmission of educational advantages, to the neglect of potentially consequential pre-birth endowments (e.g., heritable traits) that are passed from parent to child. In this study, we leverage an experiment of nurture-children who were adopted at birth into nonrelative families-in an effort to simultaneously model the effects associated with both pathways. To do so, we fit a series of simple linear regression models that relate the academic achievement of adopted children to the educational attainments of their adoptive and biological parents, using U.S. data from a recent nationwide sample of birth and adoptive families (the Early Growth and Development Study). Because our dataset includes both "genetic" and "environmental" relatives, but not "genetic-and-environmental" relatives, the separate contributions of each pathway can be identified, as well as possible interactions between the two. Our results show that children's early achievements are influenced not only by the attainments of their adoptive parents, but also the attainments of their birth parents-suggesting the presence of environmental and genetically mediated effects. Supplementary analyses provide little evidence of effect moderation, using both distal and proximate measures of the childhood environment to model gene-by-environment interactions. These findings are robust to a variety of parameterizations, withstand a series of auxiliary checks, and remain intact even after controlling for intrauterine exposures and other measurable variables that could compromise our design. The implications of our results for theory and research in the stratification literature, and for those interested in educational mobility, are discussed.

Genetic architecture of socioeconomic outcomes: Educational attainment, occupational status, and wealth

This study takes a socio-genomic approach to examine the complex relationships among three important socioeconomic outcomes: educational attainment, occupational status, and wealth. Using more than 8,000 genetic samples from the Health and Retirement study, it first estimates the collective influence of genetic variants across the whole human genome to each of the three socioeconomic outcomes. It then tests genetic correlations among three socioeconomic outcomes, and examines the extent to which genetic influences on occupational status and wealth are mediated by educational attainment. Analyses using the genomic-relatedness-matrix restricted maximum likelihood method show significant genetic correlations among the three outcomes, and provide evidence for both mediated and independent genetic influences. A polygenic score analysis demonstrates the utility of findings in socio-genomic studies to address genetic confounding in causal relationships among the three socioeconomic outcomes.

Every contact leaves a trace: contact with the criminal justice system, life outcomes, and the intersection with genetics

Contact with the criminal justice (CJ) system is a relatively common occurrence in the United States. Criminologists and sociologists have long considered the impact of contact with the CJ system on later-in-life outcomes. This body of work has revealed a great deal of heterogeneity in life outcomes, suggesting individual differences are important to consider. At the same time, recent advances in the genomic sciences have allowed researchers to gather information from across the entire genome and to summarize that information into polygenic scores. In the present review, we consider how polygenic scores might be used to advance research into the impact of CJ system contact on life outcomes. In particular, we emphasize the importance of gene-environment interaction (G × E). We suggest that contact with the CJ system might represent a substantively important environmental moderator of polygenic risks. But we caution that studying the moderating role of contact with the CJ system will have its own complications-points that scholars must begin to consider and discuss now that the genomic era has reached the social sciences.