Cited by 143Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksGenetic and phenotypic traits in livestock

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Statistical methods to detect pleiotropy in human complex traits

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Hackinger, Sophie, Zeggini, Eleftheria·2017·Open Biology

DOI 10.1098/rsob.170125PMC PMC5717338

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Abstract

In recent years pleiotropy, the phenomenon of one genetic locus influencing several traits, has become a widely researched field in human genetics. With the increasing availability of genome-wide association study summary statistics, as well as the establishment of deeply phenotyped sample collections, it is now possible to systematically assess the genetic overlap between multiple traits and diseases. In addition to increasing power to detect associated variants, multi-trait methods can also aid our understanding of how different disorders are aetiologically linked by highlighting relevant biological pathways. A plethora of available tools to perform such analyses exists, each with their own advantages and limitations. In this review, we outline some of the currently available methods to conduct multi-trait analyses. First, we briefly introduce the concept of pleiotropy and outline the current landscape of pleiotropy research in human genetics; second, we describe analytical considerations and analysis methods; finally, we discuss future directions for the field.

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Authors: Hackinger, S., & Zeggini, E.
Affiliations: Wellcome Sanger Institute (GB)
Corresponding author: Zeggini, Eleftheria
ORCID: Hackinger, Sophie
Zeggini, Eleftheria
Venue: Open Biology
Publisher: The Royal Society
Published: 2017-11
Volume: 7
Issue: 11
ISSN: 2046-2441 (ISSN-L)
DOI: 10.1098/rsob.170125
PMC: PMC5717338
OpenAlex: W2766556645
Cited by: 143
References: 155
Citations by year: 2026: 7 · 2025: 7 · 2024: 12 · 2023: 19 · 2022: 36 · 2021: 15 · 2020: 23 · 2019: 17 · 2018: 7
FWCI: 1.65
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
creativecommons.org/licenses/by/4.0/ (tdm)
Locations: Open Biology (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: Wellcome Trust (WT098051)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords: pleiotropy, multi-trait analysis, genetic overlap, complex traits, biological pathways, statistical analysis
MeSH terms: Humans, Quantitative Trait, Heritable, Quantitative Trait Loci, Genome-Wide Association Study, Genetic Pleiotropy

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Statistical methods to detect pleiotropy in human complex traits

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