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Genet Epidemiol. 2019 Sep;43(6):704-716. doi: 10.1002/gepi.22214. Epub 2019 Jun 6.

A systematic genetic analysis and visualization of phenotypic heterogeneity among orofacial cleft GWAS signals.

Author information

1
Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
2
Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
3
Department of Biological Sciences, University of Delaware, Newark, Delaware.
4
Department of Oral Pathology, Radiology and Medicine, University of Iowa, Iowa, Iowa.
5
Dental and Craniofacial Genomics Core, School of Dental Medicine, University of Puerto Rico, San Juan, Puerto Rico.
6
Department of Epidemiology, Institute of Public Health, University of Southern Denmark, Odense, Denmark.
7
UCHealth Plastic and Reconstructive Surgery, Colorado Springs, Colorado.
8
Department of Pediatrics, McGovern Medical School and School of Dentistry UT Health at Houston, Houston, Texas.
9
Department of Orthodontics, College of Dentistry, University of Iowa, Iowa, Iowa.
10
INAGEMP (National Institute of Population Medical Genetics), Porto Alegre, Brazil.
11
ECLAMC (Latin American Collaborative Study of Congenital Malformations) at Department of Genetics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
12
Department of Pediatrics, College of Medicine, Institute of Human Genetics, National Institutes of Health, University of the Philippines Manila, Manila, The Philippines.
13
Philippine Genome Center, University of the Philippines System, Quezon, The Philippines.
14
Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
15
Department of Health Management and Policy, College of Public Health, University of Iowa, Iowa, Iowa.
16
Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
17
Department of Pediatrics, Carver College of Medicine, University of Iowa, Iowa, Iowa.
18
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
19
Department of Anatomy and Cell Biology, University of Kansas Medical Center, Kansas, Kansas.
20
Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delware.
21
Department of Human Genetics, Emory University School of Medicine, Emory University, Atlanta, Georgia.

Abstract

Phenotypic heterogeneity is a hallmark of complex traits, and genetic studies of such traits may focus on them as a single diagnostic entity or by analyzing specific components. For example, in orofacial clefting (OFC), three subtypes-cleft lip (CL), cleft lip and palate (CLP), and cleft palate (CP) have been studied separately and in combination. To further dissect the genetic architecture of OFCs and how a given associated locus may be contributing to distinct subtypes of a trait we developed a framework for quantifying and interpreting evidence of subtype-specific or shared genetic effects in complex traits. We applied this technique to create a "cleft map" of the association of 30 genetic loci with three OFC subtypes. In addition to new associations, we found loci with subtype-specific effects (e.g., GRHL3 [CP], WNT5A [CLP]), as well as loci associated with two or all three subtypes. We cross-referenced these results with mouse craniofacial gene expression datasets, which identified additional promising candidate genes. However, we found no strong correlation between OFC subtypes and expression patterns. In aggregate, the cleft map revealed that neither subtype-specific nor shared genetic effects operate in isolation in OFC architecture. Our approach can be easily applied to any complex trait with distinct phenotypic subgroups.

KEYWORDS:

birth defects; genome-wide association studies; orofacial clefts; subtypes

PMID:
31172578
PMCID:
PMC6687557
[Available on 2020-09-01]
DOI:
10.1002/gepi.22214

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