Protocol for finding genetic variation associated with unmeasured traits through GenomicSEM common-factor GWAS
Here, we present a protocol for finding genetic variation associated with unmeasured traits using common-factor genome-wide association study (GWAS) using genomic structural equation modeling (GenomicSEM), applied here to nociplastic pain. We use existing GWAS for six chronic overlapping pain condition traits. We describe steps for preparing the computing environment and packages, identifying relevant GWAS and retrieving summary statistics, preparing summary statistics for multivariable Linkage Disequilibrium-score regression, and running common-factor GWAS using GenomicSEM without and with individual single-nucleotide polymorphism (SNP) effects. For complete details on the use and execution of this protocol, please refer to Johnston et al.<sup>1</sup>.
Authors
- Laura M. Huckins (ORCID: https://orcid.org/0000-0002-5369-6502)
- Keira J.A. Johnston (ORCID: https://orcid.org/0000-0002-1370-3149)
- Rebecca Signer (ORCID: https://orcid.org/0000-0001-8564-4267)
Institutions
- Yale University (US)
- Icahn School of Medicine at Mount Sinai (US)
Publication Details
- Journal
- STAR Protocols
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1016/j.xpro.2025.103905
- Primary Topic
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Defense
- National Institute of Mental Health
- National Institute of Environmental Health Sciences