All time references are in CEST
Collection of Genetic Information in Panel Surveys |
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| Session Organiser | Professor David Richter (SHARE Berlin Institute) |
| Time | Tuesday 18 July, 09:00 - 10:30 |
| Room | |
The influence of social context, particularly during childhood and adolescence, is critical for human development. The socio-economic status of a family, cultural norms, and community resources further shape the social context, influencing access to educational opportunities, healthcare, and recreational activities. In addition to the social context, genetic predispositions provide the biological foundation upon which various traits and behaviors are built. This genetic framework is often viewed as a "fixed" component, setting certain limits and potentials for an individual’s development. However, the interaction between genetic predispositions and the (changing) social context is where much of developmental potential and diversity arise.
The dynamic interplay between genes and environment suggests that neither genetics nor environment alone can fully explain developmental outcomes. Therefore, the connection of genetic information and survey data is crucial. It allows researchers to examine how genetic predispositions interact with environmental factors, offering a more comprehensive understanding of human behavior and health outcomes. This interdisciplinary approach can lead to more personalized and effective interventions in public health, education, and social policy.
Incorporating genetic data into social panel surveys presents significant ethical challenges. Ensuring informed consent, maintaining willingness to participate as well as confidentiality, and addressing potential stigmatization or discrimination based on genetic information are some of the issues that need to be addressed. Researchers must navigate these ethical concerns carefully to protect participants' rights and promote trust in the research process.
This session aims to address the conference theme by showcasing the integration of novel data sources (genetic information) with traditional survey methods. We will discuss the benefits of combining genetic information with traditional survey data to enhance the understanding of complex traits and behaviors. Topics include the logistics of collecting biological samples, ethical considerations, data integration techniques, and the potential for genetic data to enrich social research.
Keywords: Gene-Environment Interaction, Genetic Information, Data Collection, Ethical Survey Practices
Professor David Richter (SHARE Berlin Institute) - Presenting Author
Dr Jan Goebel (DIW Berlin)
The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). Consent rates for genetic sampling were 58% for adults but lower for children (26%), reflecting parental hesitance.
Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socioeconomic status, and health.
In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, lifecourse development, health, and interactions between genetic predispositions and the environment.
Dr Evelina Akimova (Purdue University)
Dr Ramina Sotoudeh (Yale University) - Presenting Author
Social science research has entered a new era with the integration of genetic data into major longitudinal surveys worldwide. While this development offers unprecedented opportunities for interdisciplinary research, it also raises important methodological concerns about selection bias in genetic sampling. This study examines how sociodemographic, attitudinal, and behavioral factors influence participation in genetic data collection across six comparable surveys from the United States and United Kingdom. We analyze three pairs of datasets with similar sampling designs: the Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA), which sample older adults; the Future of Families and Child Wellbeing Study (FFCWS) and Avon Longitudinal Study of Parents and Children (ALSPAC), which are birth cohort studies conducted during the same period; and the National Longitudinal Study of Adolescent to Adult Health (Add Health) and the UK Household Longitudinal Study (Understanding Society), which are broader population samples. Initial analyses reveal that participants who provide genetic samples differ from non-participants across multiple dimensions. While some differences align with previously hypothesized factors such as the "healthy volunteer effect," we also identify several previously undocumented selection factors. We discuss implications for analyses and inference from these non-generalizable samples.