Workshop 1: Family-based Genomic Studies

(September 17,2018 - September 19,2018 )

Organizers


Shili Lin
Statistics, The Ohio State University
Lara Sucheston-Campbell
Pharmacy Practice and Science, The Ohio State University
Asuman Turkmen
Department of Statistics, The Ohio State University

The field of Genetic Epidemiology has historically focused on the inheritance of genetic factors and phenotypes within families. However, the increase in ever improving technologies brought a shift from familial study designs to genome wide association studies (GWAS) utilizing samples of unrelated individuals. While GWAS has yielded greater knowledge of genomic structure and disease associated variants, the estimated effect sizes are small and often to not explain a large proportion of disease heritability. One of the explanations for the missing heritability is that the variants identified in GWAS are common (> 5%) and thus we are missing an entire class of variation (rare) that substantially contributes to disease risk. The innovation of next-generation sequencing technology made the comprehensive discovery of rare variants feasible, however the sample size of unrelated individuals needed to identify associations between these rare variants and diseases is in the thousands (> 10,000 samples are necessary to detect a variant showing evidence of modest association with minor allele frequency 0.1%). While sequencing costs have decreased, the financial burden is still nontrivial and sample heterogeneity can easily confound results. Thus, efficient study designs and improved statistical approaches are necessary to untangle the contribution of rare variation to complex disease. Family studies have always been robust to confounding and a powerful approach for identifying genetic variation. In the age of sequencing, family studies are again an appealing approach for studying the relationship between complex disease and genetic variation. 

This workshop will focus on the use of family studies in the hunt for disease associated genes, include the development of novel methodologies and statistics for assessing variant disease relationships as well as the important role of the family study design in a clinical sequencing setting. 

Accepted Speakers

Christopher Bartlett
Saonli Basu
Alyssa Clay
Jonathan Haines
Cheryl London
Catherine Stein
Population & Quantitative Health Sciences, Case Western Reserve University
William Stewart
Veronica Vieland
Pediatrics & Statistics, The Ohio State University
Meng Wang
Richard Wilson
Xiaofeng Zhu
Population and Quantitative Health Sciences, Case Western Reserve University
Monday, September 17, 2018
Time Session
Tuesday, September 18, 2018
Time Session
Wednesday, September 19, 2018
Time Session
Name Email Affiliation
Lin, Shili shili@stat.ohio-state.edu Statistics, The Ohio State University
Stein, Catherine catherine.stein@case.edu Population & Quantitative Health Sciences, Case Western Reserve University
Sucheston-Campbell, Lara sucheston-campbell.1@osu.edu Pharmacy Practice and Science, The Ohio State University
Turkmen, Asuman turkmen.2@osu.edu Department of Statistics, The Ohio State University
Vieland, Veronica veronica.vieland@nationwidechildrens.org Pediatrics & Statistics, The Ohio State University