A computational approach for detecting physiological homogeneity in the midst of genetic heterogeneity.

Autor:	Zhang P; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA. Electronic address: pzhang@rockefeller.edu., Cobat A; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France., Lee YS; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA., Wu Y; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Bayrak CS; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Boccon-Gibod C; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA., Matuozzo D; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France., Lorenzo L; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France., Jain A; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Boucherit S; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France., Vallée L; Neuropediatric Department, Roger Salengro Hospital, Lille 59037, France., Stüve B; Clinics of the City of Cologne gGmbH, Cologne 53323, Germany., Chabrier S; CHU Saint-Étienne, French Centre for Pediatric Stroke, Saint-Étienne, France., Casanova JL; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France; Howard Hughes Medical Institute, New York, NY 10065, USA. Electronic address: casanova@rockefeller.edu., Abel L; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France., Zhang SY; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR1163, Paris 75015, France; University of Paris, Imagine Institute, Paris 75015, France., Itan Y; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Jazyk:	angličtina
Zdroj:	American journal of human genetics [Am J Hum Genet] 2021 Jun 03; Vol. 108 (6), pp. 1012-1025. Date of Electronic Publication: 2021 May 19.
DOI:	10.1016/j.ajhg.2021.04.023
Abstrakt:	The human genetic dissection of clinical phenotypes is complicated by genetic heterogeneity. Gene burden approaches that detect genetic signals in case-control studies are underpowered in genetically heterogeneous cohorts. We therefore developed a genome-wide computational method, network-based heterogeneity clustering (NHC), to detect physiological homogeneity in the midst of genetic heterogeneity. Simulation studies showed our method to be capable of systematically converging genes in biological proximity on the background biological interaction network, and capturing gene clusters harboring presumably deleterious variants, in an efficient and unbiased manner. We applied NHC to whole-exome sequencing data from a cohort of 122 individuals with herpes simplex encephalitis (HSE), including 13 individuals with previously published monogenic inborn errors of TLR3-dependent IFN-α/β immunity. The top gene cluster identified by our approach successfully detected and prioritized all causal variants of five TLR3 pathway genes in the 13 previously reported individuals. This approach also suggested candidate variants of three reported genes and four candidate genes from the same pathway in another ten previously unstudied individuals. TLR3 responsiveness was impaired in dermal fibroblasts from four of the five individuals tested, suggesting that the variants detected were causal for HSE. NHC is, therefore, an effective and unbiased approach for unraveling genetic heterogeneity by detecting physiological homogeneity. (Copyright © 2021 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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