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Professor Merchant is a historian of science, technology, and medicine in the twentieth and twenty-first centuries, focusing on the quantitative human sciences and the technologies of human measurement. Her first book, Building the Population Bomb, examines how human population growth became a subject of scientific expertise and an object of governmental and philanthropic intervention in the twentieth century. Her current project focuses on the scientific efforts over the past 100 years to identify the genetic antecedents to intelligence. It uses archival research, oral history, computational text analysis, and participant observation to trace the intellectual and institutional continuities and discontinuities from the eugenics of the beginning of the twentieth century, through the differential psychology (intelligence testing) of the first half of the century and the behavior genetics (heritability studies using twins and adoptees) of the second half, to the sociogenomics of the beginning of the twenty-first. Her talk will review this work and highlight the significance of the historical context in which work at IGSS is presented.
Dr. Lu's research focuses on developing statistical methods to dissect the genetic architecture of complex human traits. In particular, areas of expertise in Dr. Lu's group include genome-wide association studies, post-GWAS variant prioritization, genetic correlation estimation, gene-environment interaction, and genetic risk prediction. His work has appeared in the leading general science, statistical genetics, and biology journals. In particular, his recent publication in Nature Communications introduces the X-Wing approach to polygenic score (PGS) construction which not only provides an important nod to the Rebel Alliance in Star Wars, but is providing the most reliable and valid estimates across different ancestral groups. The past decade has witnessed a great deal of progress in the construction of PGS related to complex human traits. Each approach has different strengths and weaknesses, and it is critical for researchers using these summary scores to have a better understanding of the differences prior to utilizing pre-constructed PGS as covariates in their analyses. Workshop participants will have an opportunity to evaluate the consistency of empirical findings linking PGS to a specific phenotype using the different techniques to better understand the meaning of their results.