Evidence map›Paper›PMID 27321816›Full record

ArticleGenetic epidemiology2016

A Clustered Multiclass Likelihood-Ratio Ensemble Method for Family-Based Association Analysis Accounting for Phenotypic Heterogeneity.

Yalu Wen, Qing Lu

Abstract read
In one paragraph

Article in Genetic epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Yalu WenDepartment of Statistics, University of Auckland, Auckland, New Zealand.
Qing LuDepartment of Epidemiology and Biostatics, Michigan State University, East Lansing, Michigan, United States of America.

Funding

Gene-Gene/Gene-Environment Interactions Associated with Nicotine DependenceK01DA033346 · NIDA · MICHIGAN STATE UNIVERSITY · PI LU, QING · 2013 to 2017
$833k
High-dimensional Statistical Genetic Approach for Family-based Orofacial CleftsR03DE022379 · NIDCR · MICHIGAN STATE UNIVERSITY · PI LU, QING · 2012 to 2013
$441k
NIDA NIH HHS K01 DA033346NIDCR NIH HHS R03 DE022379
6 · The paper itself

Abstract

Although compelling evidence suggests that the genetic etiology of complex diseases could be heterogeneous in subphenotype groups, little attention has been paid to phenotypic heterogeneity in genetic association analysis of complex diseases. Simply ignoring phenotypic heterogeneity in association analysis could result in attenuated estimates of genetic effects and low power of association tests if subphenotypes with similar clinical manifestations have heterogeneous underlying genetic etiologies. To facilitate the family-based association analysis allowing for phenotypic heterogeneity, we propose a clustered multiclass likelihood-ratio ensemble (CMLRE) method. The proposed method provides an alternative way to model the complex relationship between disease outcomes and genetic variants. It allows for heterogeneous genetic causes of disease subphenotypes and can be applied to various pedigree structures. Through simulations, we found CMLRE outperformed the commonly adopted strategies in a variety of underlying disease scenarios. We further applied CMLRE to a family-based dataset from the International Consortium to Identify Genes and Interactions Controlling Oral Clefts (ICOC) to investigate the genetic variants and interactions predisposing to subphenotypes of oral clefts. The analysis suggested that two subphenotypes, nonsyndromic cleft lip without palate (CL) and cleft lip with palate (CLP), shared similar genetic etiologies, while cleft palate only (CP) had its own genetic mechanism. The analysis further revealed that rs10863790 (IRF6), rs7017252 (8q24), and rs7078160 (VAX1) were jointly associated with CL/CLP, while rs7969932 (TBK1), rs227731 (17q22), and rs2141765 (TBK1) jointly contributed to CP.

Indexed as

Cleft LipCleft PalateGenetic LociGenetic VariationHumansInterferon Regulatory FactorsLinkage DisequilibriumModels, GeneticPhenotypeProtein Serine-Threonine KinasesInterferon Regulatory FactorsIRF6 protein, humanProtein Serine-Threonine KinasesTBK1 protein, humanfamily-based studynonparametric methodoral cleftssubphenotypes

Identifiers

PMID27321816
PMCPMC5289649

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.