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Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes

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Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes. / Rohde, Palle Duun; Demontis, Ditte; Castro Dias Cuyabano, Beatriz; Børglum, Anders; Sørensen, Peter.

I: Genetics (Print), Bind 203, Nr. 4, 01.08.2016, s. 1901-1913.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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@article{60cba28854d7452082d4b24d746ec44c,
title = "Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes",
abstract = "Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case–control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies.",
author = "Rohde, {Palle Duun} and Ditte Demontis and {Castro Dias Cuyabano}, Beatriz and Anders B{\o}rglum and Peter S{\o}rensen",
year = "2016",
month = aug,
day = "1",
doi = "10.1534/genetics.116.189498",
language = "English",
volume = "203",
pages = "1901--1913",
journal = "Genetics",
issn = "1943-2631",
publisher = "The Genetics Society of America (GSA)",
number = "4",

}

RIS

TY - JOUR

T1 - Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes

AU - Rohde, Palle Duun

AU - Demontis, Ditte

AU - Castro Dias Cuyabano, Beatriz

AU - Børglum, Anders

AU - Sørensen, Peter

PY - 2016/8/1

Y1 - 2016/8/1

N2 - Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case–control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies.

AB - Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case–control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies.

U2 - 10.1534/genetics.116.189498

DO - 10.1534/genetics.116.189498

M3 - Journal article

C2 - 27317683

VL - 203

SP - 1901

EP - 1913

JO - Genetics

JF - Genetics

SN - 1943-2631

IS - 4

ER -