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Kathleen Mullan Harris

Publications and source records attributed to Kathleen Mullan Harris.

2 recordsLinked to original sources

Genomic loci and molecular genetic mechanisms for hidradenitis suppurativa.

BACKGROUND: Hidradenitis suppurativa (HS) is a common, chronic and debilitating inflammatory disease that most commonly affects intertriginous skin. Despite its high heritability, the genetic underpinnings of HS remain poorly understood. OBJECTIVES: To identify genetic signals associated with HS, determine genetic relationships with other diseases and investigate potential molecular genetic mechanisms. METHODS: We performed a genome-wide association meta-analysis of six studies, totalling 4540 patients with HS and > 1 million control participants, and identified genetic correlations with other common diseases. We integrated the HS data with expression quantitative trait loci from 10 trait-relevant tissues, epigenomic and transcriptomic data from human scalp, differential expression data from HS lesions vs. adjacent skin and mesenchymal Hi-C chromatin looping data. To identify functional noncoding variants, we performed transcriptional reporter assays for signals near KLF5 and SOX9. RESULTS: We identified 11 significant HS signals across 7 loci: 4 corresponded to previously reported associations, 4 represented novel signals within known loci and 3 were signals in newly implicated loci. We identified significant genetic correlations between HS and other inflammatory conditions, particularly inflammatory bowel disease, rheumatoid arthritis, type 2 diabetes mellitus and asthma. We prioritized candidate genes for the 11 signals. The risk allele at KLF5 exhibited 10-fold greater transcriptional activity than the nonrisk allele, while risk alleles at SOX9 showed significantly reduced transcriptional activity. CONCLUSIONS: Our results provide insights into potential genetic mechanisms underlying HS and suggest potential therapeutic targets for this challenging condition.

Humans

An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference.

Polygenic indexes (PGIs) - DNA-based predictors of individual phenotypes - have become essential tools across biomedical and social sciences. We introduce Version 2 of the Polygenic Index Repository, which expands phenotype coverage from 47 to 61, increases the number of participating datasets from 11 to 20, and adopts a more consistent and improved methodology for PGI construction. For 16 phenotypes, we leverage summary statistics from an updated GWAS meta-analysis with greater statistical power compared to the original release, thereby improving the PGI's predictive power. To improve power for family-based analyses, we provide imputed parental PGIs in all datasets with first-degree relatives and offer a framework for interpreting results from analyses that control for parental PGIs. We illustrate the utility of parental PGIs using two applications: (1) comparing PGI associations with and without parental PGI controls for all phenotypes in two Repository datasets with family data, and (2) for BMI and diastolic blood pressure, exploring the contribution of causal versus non-causal components of PGI associations to the imperfect portability of PGIs across subgroups within a genetic ancestry. Collectively, the updates enhance predictive performance, broaden the Repository's scope, and introduce novel resources that reduce confounding bias and improve interpretability.

Journal Article