Discovery of shared genomic loci using the conditional false discovery rate approach

doi:10.1007/s00439-019-02060-2

Review

. 2020 Jan;139(1):85-94.

doi: 10.1007/s00439-019-02060-2. Epub 2019 Sep 13.

Discovery of shared genomic loci using the conditional false discovery rate approach

Olav B Smeland¹, Oleksandr Frei², Alexey Shadrin², Kevin O'Connell², Chun-Chieh Fan^{3

4}, Shahram Bahrami², Dominic Holland^{4

5

6}, Srdjan Djurovic^{7

8}, Wesley K Thompson⁹, Anders M Dale^{3

4

5

6}, Ole A Andreassen¹⁰

Affiliations

¹ NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway. o.b.smeland@medisin.uio.no.
² NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
³ Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.
⁴ Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.
⁵ Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.
⁶ Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA.
⁷ Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.
⁸ NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway.
⁹ Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.
¹⁰ NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway. o.a.andreassen@medisin.uio.no.

PMID: 31520123
DOI: 10.1007/s00439-019-02060-2

Review

Discovery of shared genomic loci using the conditional false discovery rate approach

Olav B Smeland et al. Hum Genet. 2020 Jan.

. 2020 Jan;139(1):85-94.

doi: 10.1007/s00439-019-02060-2. Epub 2019 Sep 13.

Authors

Affiliations

¹ NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway. o.b.smeland@medisin.uio.no.
² NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
³ Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.
⁴ Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.
⁵ Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.
⁶ Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA.
⁷ Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.
⁸ NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway.
⁹ Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.
¹⁰ NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway. o.a.andreassen@medisin.uio.no.

PMID: 31520123
DOI: 10.1007/s00439-019-02060-2

Abstract

In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes.

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[1] Hypertension. 2014 Apr;63(4):819-26 - PubMed

[2] Hypertension. 2014 Apr;63(4):819-26 - PubMed

[3] Nat Rev Genet. 2017 Feb;18(2):117-127 - PubMed

[4] Nat Rev Genet. 2017 Feb;18(2):117-127 - PubMed

[5] Am J Hum Genet. 2015 Jan 8;96(1):104-20 - PubMed

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[8] Schizophr Bull. 2014 Jan;40(1):13-7 - PubMed

[9] Genome Med. 2016 Jul 19;8(1):78 - PubMed

[10] Genome Med. 2016 Jul 19;8(1):78 - PubMed

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Discovery of shared genomic loci using the conditional false discovery rate approach

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Discovery of shared genomic loci using the conditional false discovery rate approach

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Abstract

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