How SSGAC Can Help
The SSGAC facilitates large-scale GWAS meta-analysis for social-scientific phenotypes, including attitudes, behaviors, economic preferences, and socioeconomic outcomes. The SSGAC provides an infrastructure for conducting well-powered meta-GWA studies, is involved in developing harmonized survey measures of social-scientific phenotypes, and also supports the initiatives of other research consortia.
Harmonized Survey Measures
The SSGAC investigators have extensive experience designing social-science survey measures. We have developed survey items for a number of cohorts, including the Wisconsin Longitudinal Study (WLS), the Swedish Twin Registry (STR), the Rotterdam Study (RS), LifeLines, 23andMe, Risk Evaluation For INfarct Estimates (REFINE Reykjavik Study), the Helsinki Birth Cohort Study (HBCS), the Northern Finland Birth Cohort (NFBC66),and the Lab for Behavioral and Biological Economics and Social Science (B2ESS). We seek to facilitate the development of harmonized phenotype measures that can be modified to accommodate cohort-specific space and time constraints.
Phenotypes of Interest
Because of the statistical power problem [see section 4.6.4. in Benjamin et al. 2012], the SSGAC only conducts studies on phenotypes that are available in large samples. All else equal, it is always better to use harmonized measures, and developing such measures is one of our priorities (see above). The SSGAC recognizes that there is a tradeoff between sample size and phenotypic quality and that when designing studies, it is important to assess this tradeoff quantitatively. The first generation of studies conducted by the SSGAC are therefore conducted on phenotypes that are widely available. We are currently prioritizing the following phenotypes:
Fertility (number / timing of children)
The GWAS of fertility is being led by our partners, Sociogenome.
Phenotype Data Collection
Most of the prioritized phenotypes are available in sample sizes of at least 30,000, and there are ongoing efforts to gather additional data in several of our cohorts.
If you would like to participate in any of our meta-analyses or would like us to help you design instruments to collect new phenotype data, please contact one of the principal investigators or contact SSGAC directly at email@example.com.