Improving imputation in disease-relevant regions: lessons from cystic fibrosis

Naim Panjwani; Bowei Xiao; Lizhen Xu; Jiafen Gong; Katherine Keenan; Fan Lin; Gengming He; Zeynep Baskurt; Sangook Kim; Lin Zhang; Mohsen Esmaeili; Scott Blackman; Stephen W Scherer; Harriet Corvol; Mitchell Drumm; Michael Knowles; Garry Cutting; Johanna M Rommens; Lei Sun; Lisa J Strug

doi:10.1038/s41525-018-0047-6

Improving imputation in disease-relevant regions: lessons from cystic fibrosis

NPJ Genom Med. 2018 Mar 20:3:8. doi: 10.1038/s41525-018-0047-6. eCollection 2018.

Authors

Naim Panjwani^#¹, Bowei Xiao^#¹, Lizhen Xu², Jiafen Gong¹, Katherine Keenan³, Fan Lin¹, Gengming He¹, Zeynep Baskurt¹, Sangook Kim⁴, Lin Zhang⁵, Mohsen Esmaeili¹, Scott Blackman⁶, Stephen W Scherer^{2

7}, Harriet Corvol^{8

9}, Mitchell Drumm^{10

11}, Michael Knowles¹², Garry Cutting^{6

13}, Johanna M Rommens^{1

14}, Lei Sun^{4

5}, Lisa J Strug^{1

2

4}

Affiliations

¹ 1Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON Canada.
² 2The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada.
³ 3Program in Physiology and Experimental Medicine, The Hospital for Sick Children, Toronto, ON Canada.
⁴ 4Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON Canada.
⁵ 5Department of Statistics, University of Toronto, Toronto, ON Canada.
⁶ 6Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MA USA.
⁷ 7McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON Canada.
⁸ 8Pediatric Pulmonary Department, Hospital Trousseau, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France.
⁹ 9Sorbonne Universités, UPMC Univ Paris 06, INSERM, Centre de Recherche Saint-Antoine (CRSA), Paris, France.
¹⁰ 10Department of Pediatrics, Case Western Reserve University, Cleveland, OH USA.
¹¹ 11Department of Genetics, Case Western Reserve University, Cleveland, OH USA.
¹² 12Cystic Fibrosis Pulmonary Research and Treatment Center, University of North Carolina, Chapel Hill, NC USA.
¹³ 13McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD USA.
¹⁴ 14Department of Molecular Genetics, University of Toronto, Toronto, ON Canada.

^# Contributed equally.

Abstract

Does genotype imputation with public reference panels identify variants contributing to disease? Genotype imputation using the 1000 Genomes Project (1KG; 2504 individuals) displayed poor coverage at the causal cystic fibrosis (CF) transmembrane conductance regulator (CFTR) locus for the International CF Gene Modifier Consortium. Imputation with the larger Haplotype Reference Consortium (HRC; 32,470 individuals) displayed improved coverage but low sensitivity of variants clinically relevant for CF. A hybrid reference that combined whole genome sequencing (WGS) from 101 CF individuals with the 1KG imputed a greater number of single-nucleotide variants (SNVs) that would be analyzed in a genetic association study (r² ≥ 0.3 and MAF ≥ 0.5%) than imputation with the HRC, while the HRC excelled in the lower frequency spectrum. Using the 1KG or HRC as reference panels missed the most common CF-causing variants or displayed low imputation accuracy. Designs that incorporate population-specific WGS can improve imputation accuracy at disease-specific loci, while imputation using public data sets can omit disease-relevant genotypes.

Grants and funding

R01 DK044003/DK/NIDDK NIH HHS/United States