TY - JOUR
T1 - Robust kernel association testing (RobKAT)
AU - Martinez, Kara
AU - Maity, Arnab
AU - Yolken, Robert H.
AU - Sullivan, Patrick F.
AU - Tzeng, Jung Ying
N1 - Funding Information:
Data used in the preparation of this article were obtained from the limited access data sets distributed from the NIH‐supported “Clinical Antipsychotic Trials of Intervention Effectiveness in Alzheimer's Disease” (CATIE‐AD). This is a multisite, clinical trial of persons with Alzheimer s Disease comparing the effectiveness of randomly assigned medication treatment. The study was supported by NIMH Contract #N01MH90001 to the University of North Carolina at Chapel Hill, and the ClinicalTrials.gov identifier is NCT00015548. The data that support the findings of this NIMH study are available on request via the appropriate Data Use Certification pertaining to this trial.
Funding Information:
The authors thank the editor and anonymous referees from Genetic Epidemiology who provided helpful comments and suggestions that greatly improved this article. This study was partially supported by National Institutes of Health grant P01CA142538 (to J.‐Y. T.) and National Institutes of Health training grant T32GM081057, Biostatistics Training in the Omics Era (to K. M.).
Funding Information:
The authors thank the editor and anonymous referees from Genetic Epidemiology who provided helpful comments and suggestions that greatly improved this article. This study was partially supported by National Institutes of Health grant P01CA142538 (to J.-Y. T.) and National Institutes of Health training grant T32GM081057, Biostatistics Training in the Omics Era (to K. M.).
PY - 2020/4/1
Y1 - 2020/4/1
N2 - Testing the association between single-nucleotide polymorphism (SNP) effects and a response is often carried out through kernel machine methods based on least squares, such as the sequence kernel association test (SKAT). However, these least-squares procedures are designed for a normally distributed conditional response, which may not apply. Other robust procedures such as the quantile regression kernel machine (QRKM) restrict the choice of the loss function and only allow inference on conditional quantiles. We propose a general and robust kernel association test with a flexible choice of the loss function, no distributional assumptions, and has SKAT and QRKM as special cases. We evaluate our proposed robust association test (RobKAT) across various data distributions through a simulation study. When errors are normally distributed, RobKAT controls type I error and shows comparable power with SKAT. In all other distributional settings investigated, our robust test has similar or greater power than SKAT. Finally, we apply our robust testing method to data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) clinical trial to detect associations between selected genes including the major histocompatibility complex (MHC) region on chromosome six and neurotropic herpesvirus antibody levels in schizophrenia patients. RobKAT detected significant association with four SNP sets (HST1H2BJ, MHC, POM12L2, and SLC17A1), three of which were undetected by SKAT.
AB - Testing the association between single-nucleotide polymorphism (SNP) effects and a response is often carried out through kernel machine methods based on least squares, such as the sequence kernel association test (SKAT). However, these least-squares procedures are designed for a normally distributed conditional response, which may not apply. Other robust procedures such as the quantile regression kernel machine (QRKM) restrict the choice of the loss function and only allow inference on conditional quantiles. We propose a general and robust kernel association test with a flexible choice of the loss function, no distributional assumptions, and has SKAT and QRKM as special cases. We evaluate our proposed robust association test (RobKAT) across various data distributions through a simulation study. When errors are normally distributed, RobKAT controls type I error and shows comparable power with SKAT. In all other distributional settings investigated, our robust test has similar or greater power than SKAT. Finally, we apply our robust testing method to data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) clinical trial to detect associations between selected genes including the major histocompatibility complex (MHC) region on chromosome six and neurotropic herpesvirus antibody levels in schizophrenia patients. RobKAT detected significant association with four SNP sets (HST1H2BJ, MHC, POM12L2, and SLC17A1), three of which were undetected by SKAT.
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U2 - 10.1002/gepi.22280
DO - 10.1002/gepi.22280
M3 - Article
C2 - 31943371
AN - SCOPUS:85077904457
VL - 44
SP - 272
EP - 282
JO - Genetic Epidemiology
JF - Genetic Epidemiology
SN - 0741-0395
IS - 3
ER -