Events

Past Event

Logical Reasoning in Human Genetics course - Lecture 7

October 14, 2021
3:30 PM - 5:30 PM
Online (Tunis)

In partnership with scholars from Institut Pasteur Tunis, CGC Tunis will host Pr. Joseph Terwilliger, professor at the Department of Genetics and Development, Columbia University, and Pr. Joseph H. Lee, Professor in Epidemiology at the Columbia University Medical Center, Columbia University, along with a team of prominent geneticists to conduct a class on human genetics for participants from North Africa (and elsewhere).

This seventh lecture is scheduled for October 14th. A registration link will be available soon.

Once you register, you will receive the Zoom link details and to be added to our mailing lists to get each month’s lectures announcements and videos.

Course description, overview, and goals:  

This course is designed to examine the conceptual, empirical, and theoretical approaches to understanding the complex cause and effect relationships underlying human variation. Despite a century of quantitative research on evolutionary biology and genetics, our hypotheses about the phenogenetic (genotype + environment + culture -> phenotype) relationships underlying human variation seem poorly focused and often based on unnecessarily naïve models. The course will help participants review the basics of evolutionary biology, genetic epidemiology, gene mapping, and how to integrate these three disciplines to address questions of causality in human genetics. 

In this course, students will develop critical thinking and logical reasoning skills to learn from what negative experimental results tell us about the architecture of disease and to question the assumptions underlying their experimental approaches to develop better study designs based on better hypotheses for future studies. One common reason experiments "fail" is because the question was poorly posed or the hypotheses being tested were incompletely thought out and justified, not because of technical or analytical errors. In fact, the results have been a major success in showing that the causal landscape is more complex than had been widely expected, but is in fact consistent with biological and evolutionary theory. 

This course will introduce basic concepts of human evolution and population genetics — the processes that created the etiological architecture of complex human disease in today’s population. The course will try to explain why most human phenotypes are under the influence of an enormous number of (mostly individually rare) genetic factors that vary both within and between populations. The failures of genome-wide association studies to identify important risk factors for common disease will be shown to be completely consistent with what evolutionary theory actually predicts and is likewise consistent with real data from genetic studies in agriculture and model organisms.  Because a researcher cannot do genetic experiments in humans but is rather forced to work with observational data, students will further discuss how the researcher searches for and utilizes natural experiments that approximate the studies we would design if we had a more convenient species to study.  Since the evolutionary theory is so critical to understanding exposure distributions in genetic variation, it is critical for anyone working in genetic epidemiology to have a conceptual background in genetics.  

This is not a technical how-to course.  It is a conceptual trip through the ins and outs of human epidemiological genetics, from an evolutionary point of view, that tries to explain why we are finding what we are finding in genetic epidemiology, and examines why earlier dreams of genetically predictive personalized medicine have not come to fruition.  Rather than teaching students how to analyze data, how to do research, and so on, this course will focus on critical reading of the literature, and examination of the assumptions and occasional contradictions underlying the search for understanding of the relationships between genetic variation and human disease.