In April 2016 Manchester eScholar was replaced by the University of Manchester’s new Research Information Management System, Pure. In the autumn the University’s research outputs will be available to search and browse via a new Research Portal. Until then the University’s full publication record can be accessed via a temporary portal and the old eScholar content is available to search and browse via this archive.

Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and immunochip data.

Chen, Guo-Bo; Lee, Sang Hong; Brion, Marie-Jo A; Montgomery, Grant W; Wray, Naomi R; Radford-Smith, Graham L; Visscher, Peter M;

Human molecular genetics. 2014;23(17):4710-20.

Access to files

Full-text and supplementary files are not available from Manchester eScholar. Full-text is available externally using the following links:

Full-text held externally

Abstract

As custom arrays are cheaper than generic GWAS arrays, larger sample size is achievable for gene discovery. Custom arrays can tag more variants through denser genotyping of SNPs at associated loci, but at the cost of losing genome-wide coverage. Balancing this trade-off is important for maximizing experimental designs. We quantified both the gain in captured SNP-heritability at known candidate regions and the loss due to imperfect genome-wide coverage for inflammatory bowel disease using immunochip (iChip) and imputed GWAS data on 61,251 and 38.550 samples, respectively. For Crohn's disease (CD), the iChip and GWAS data explained 19 and 26% of variation in liability, respectively, and SNPs in the densely genotyped iChip regions explained 13% of the SNP-heritability for both the iChip and GWAS data. For ulcerative colitis (UC), the iChip and GWAS data explained 15 and 19% of variation in liability, respectively, and the dense iChip regions explained 10 and 9% of the SNP-heritability in the iChip and the GWAS data. From bivariate analyses, estimates of the genetic correlation in risk between CD and UC were 0.75 (SE 0.017) and 0.62 (SE 0.042) for the iChip and GWAS data, respectively. We also quantified the SNP-heritability of genomic regions that did or did not contain the previous 163 GWAS hits for CD and UC, and SNP-heritability of the overlapping loci between the densely genotyped iChip regions and the 163 GWAS hits. For both diseases, over different genomic partitioning, the densely genotyped regions on the iChip tagged at least as much variation in liability as in the corresponding regions in the GWAS data, however a certain amount of tagged SNP-heritability in the GWAS data was lost using the iChip due to the low coverage at unselected regions. These results imply that custom arrays with a GWAS backbone will facilitate more gene discovery, both at associated and novel loci.

Bibliographic metadata

Type of resource:
Content type:
Publication type:
Collaborator(s):
Published date:
Journal title:
Abbreviated journal title:
ISSN:
Place of publication:
England
Volume:
23
Issue:
17
Pagination:
4710-20
Digital Object Identifier:
10.1093/hmg/ddu174
Pubmed Identifier:
24728037
Pii Identifier:
ddu174
Access state:
Active

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:236601
Created by:
Newman, William
Created:
9th October, 2014, 18:05:51
Last modified by:
Newman, William
Last modified:
9th October, 2014, 18:05:51

Can we help?

The library chat service will be available from 11am-3pm Monday to Friday (excluding Bank Holidays). You can also email your enquiry to us.