ArticleGenetic epidemiology2014
Efficient generalized least squares method for mixed population and family-based samples in genome-wide association studies.
Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- Americas Association of Sarcoidosis and other granulomatous disorders 2024 conference highlights.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2025Article
- Identification of Environmental Exposures Associated with Risk of Sarcoidosis in African Americans.Annals of the American Thoracic Society · 2023Article
- Genetics of neurosarcoidosis.Journal of neuroimmunology · 2022Review
- Epigenetics and sarcoidosis.European respiratory review : an official journal of the European Respiratory Society · 2021Review
- Genome-Wide Association Study of Ocular Sarcoidosis Confirms HLA Associations and Implicates Barrier Function and Autoimmunity in African Americans.Ocular immunology and inflammation · 2021Article
- Recent advances in sarcoidosis genomics: epigenetics, gene expression, and gene by environment (G × E) interaction studies.Current opinion in pulmonary medicine · 2020Review
- Single Cell Transcriptomics Implicate Novel Monocyte and T Cell Immune Dysregulation in Sarcoidosis.Frontiers in immunology · 2020Article
- Extended methods for gene-environment-wide interaction scans in studies of admixed individuals with varying degrees of relationships.Genetic epidemiology · 2019Article
- Genetic, Immunologic, and Environmental Basis of Sarcoidosis.Annals of the American Thoracic Society · 2017Review
- Association of HLA-DRB1 with Sarcoidosis Susceptibility and Progression in African Americans.American journal of respiratory cell and molecular biology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
Genome-wide association studies (GWAS) that draw samples from multiple studies with a mixture of relationship structures are becoming more common. Analytical methods exist for using mixed-sample data, but few methods have been proposed for the analysis of genotype-by-environment (G×E) interactions. Using GWAS data from a study of sarcoidosis susceptibility genes in related and unrelated African Americans, we explored the current analytic options for genotype association testing in studies using both unrelated and family-based designs. We propose a novel method-generalized least squares (GLX)-to estimate both SNP and G×E interaction effects for categorical environmental covariates and compared this method to generalized estimating equations (GEE), logistic regression, the Cochran-Armitage trend test, and the WQLS and MQLS methods. We used simulation to demonstrate that the GLX method reduces type I error under a variety of pedigree structures. We also demonstrate its superior power to detect SNP effects while offering computational advantages and comparable power to detect G×E interactions versus GEE. Using this method, we found two novel SNPs that demonstrate a significant genome-wide interaction with insecticide exposure-rs10499003 and rs7745248, located in the intronic and 3' UTR regions of the FUT9 gene on chromosome 6q16.1.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.