title: Selecting cases and controls for DNA sequencing studies using family histories of disease.
abstract: Recent improvements in sequencing technology have enabled the investigation of so-called missing heritability, and a large number of affected subjects have been sequenced in order to detect significant associations between human diseases and rare variants. However, the cost of genome sequencing is still high, and a statistically powerful strategy for selecting informative subjects would be useful. Therefore, in this report, we propose a new statistical method for selecting cases and controls for sequencing studies based on family history. We assume that disease status is determined by unobserved liability scores. Our method consists of two steps: first, the conditional means of liability are estimated with the liability threshold model given the individual's disease status and those of their relatives. Second, the informative subjects are selected with the estimated conditional means. Our simulation studies showed that statistical power is substantially affected by the subject selection strategy chosen, and power is maximized when affected (unaffected) subjects with high (low) risks are selected as cases (controls). The proposed method was successfully applied to genome-wide association studies for type 2 diabetes, and our analysis results reveal the practical value of the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.
authors.affiliation: Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Korea.
authors.forename: Wonji
authors.identifier: 0000-0002-1249-797X
authors.initials: W
authors.lastname: Kim
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
authors.forename: Dandi
authors.initials: D
authors.lastname: Qiao
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.|Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA.
authors.forename: Michael H
authors.initials: MH
authors.lastname: Cho
authors.affiliation: Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Soo Heon
authors.initials: SH
authors.lastname: Kwak
authors.affiliation: Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Kyong Soo
authors.initials: KS
authors.lastname: Park
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.|Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA.
authors.forename: Edwin K
authors.initials: EK
authors.lastname: Silverman
authors.affiliation: Department of Psychiatry, University of Hong Kong, Hong Kong, SAR, China.|Genome Research Centre, University of Hong Kong, Hong Kong, SAR, China.|State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, SAR, China.
authors.forename: Pak
authors.initials: P
authors.lastname: Sham
authors.affiliation: Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Korea.|Department of Public Health Science, Seoul National University, Seoul, Korea.|Institute of Health and Environment, Seoul National University, Seoul, Korea.|National Cancer Center, Seoul, Korea.
authors.forename: Sungho
authors.initials: S
authors.lastname: Won
mesh_terms: D000328:Adult; D016022:Case-Control Studies; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D005260:Female; D005787:Gene Frequency / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008487:Medical History Taking / Q000379:methods; D015233:Models, Statistical; D018579:Patient Selection; D010375:Pedigree; D056910:Republic of Korea; D012307:Risk Factors; D017422:Sequence Analysis, DNA / Q000379:methods
keywords: family history of disease; liability; risk prediction