Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies.

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Genetic epidemiology. 2016 Jun 17 [Epub ahead of print]

Nicholas B Larson, Shannon McDonnell, Lisa Cannon Albright, Craig Teerlink, Janet Stanford, Elaine A Ostrander, William B Isaacs, Jianfeng Xu, Kathleen A Cooney, Ethan Lange, Johanna Schleutker, John D Carpten, Isaac Powell, Joan Bailey-Wilson, Olivier Cussenot, Geraldine Cancel-Tassin, Graham Giles, Robert MacInnis, Christiane Maier, Alice S Whittemore, Chih-Lin Hsieh, Fredrik Wiklund, William J Catolona, William Foulkes, Diptasri Mandal, Rosalind Eeles, Zsofia Kote-Jarai, Michael J Ackerman, Timothy M Olson, Christopher J Klein, Stephen N Thibodeau, Daniel J Schaid

Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America., Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America., Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America., Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America., Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America., National Human Genome Research Institute, Bethesda, Maryland, United States of America., Department of Urology, Johns Hopkins Hospital, Baltimore, Maryland, United States of America., NorthShore University HealthSystem Research Institute, Chicago, Illinois, United States of America., Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America., Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America., Department of Medical Biochemistry and Genetics, Institute of Biomedicine, University of Turku, Finland., Integrated Cancer Genomics Division, The Translational Genomics Research Institute, Phoenix, Arizona, United States of America., Wayne State University, Detroit, Michigan, United States of America., Statistical Genetics Section, National Human Genome Research Institute, Bethesda, Maryland, United States of America., CeRePP, Hopital Tenon, Paris, France., CeRePP, Hopital Tenon, Paris, France., Cancer Epidemiology Centre, Cancer Council Victoria, University of Melbourne, Melbourne, Australia., Cancer Epidemiology Centre, Cancer Council Victoria, University of Melbourne, Melbourne, Australia., Department of Urology, University of Ulm, Ulm, Germany., Department of Health Research and Policy, Stanford University, Stanford, California, United States of America., Department of Urology, University of Southern California, Los Angeles, California, United States of America., Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden., Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America., Department of Oncology and Human Genetics, Montreal General Hospital, Montreal, QC, Canada., Department of Genetics, LSU Health Sciences Center, New Orleans, Louisiana, United States of America., Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, United Kingdom., Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, United Kingdom., Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, United States of America., Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, United States of America., Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America., Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, United States of America., Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America.