Universität zu Köln

Adesoji, Oluyomi M., Schulz, Herbert, May, Patrick ORCID: 0000-0001-8698-3770, Krause, Roland ORCID: 0000-0001-9938-7126, Lerche, Holger and Nothnagel, Michael ORCID: 0000-0001-8305-7114 (2022). Benchmarking of univariate pleiotropy detection methods applied to epilepsy. Hum. Mutat., 43 (9). S. 1314 - 1333. LONDON: WILEY-HINDAWI. ISSN 1098-1004

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Abstract

Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, conditional false discovery rate (cFDR), cross-phenotype Bayes (CPBayes), and pleiotropic analysis under the composite null hypothesis (PLACO), by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published International League Against Epilepsy (ILAE) consortium data set on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression, and regulatory function analysis as well as Bayesian colocalization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Adesoji, Oluyomi M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Schulz, Herbert UNSPECIFIED UNSPECIFIED UNSPECIFIED May, Patrick UNSPECIFIED orcid.org/0000-0001-8698-3770 UNSPECIFIED Krause, Roland UNSPECIFIED orcid.org/0000-0001-9938-7126 UNSPECIFIED Lerche, Holger UNSPECIFIED UNSPECIFIED UNSPECIFIED Nothnagel, Michael UNSPECIFIED orcid.org/0000-0001-8305-7114 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-680718
DOI:	10.1002/humu.24417
Journal or Publication Title:	Hum. Mutat.
Volume:	43
Number:	9
Page Range:	S. 1314 - 1333
Date:	2022
Publisher:	WILEY-HINDAWI
Place of Publication:	LONDON
ISSN:	1098-1004
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language GENOME-WIDE ASSOCIATION; COLORECTAL-CANCER; POWERFUL APPROACH; ENCEPHALOPATHY; METAANALYSIS; SIMULATION; RS6983267; VARIANT; SCAN; LOCI Multiple languages Genetics & Heredity Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68071