Katherine Wood Klinger

This study identifies 440 genes/proteins associated with atopic dermatitis severity through multi-omics analyses and highlights four with significant cross-evidence, including CEP85, which may contribute to severity via impaired phagocytosis.

This study conducts a GWAS to analyze acne severity, identifying two new loci and six novel genes associated with severity, while showing limited overlap with known acne risk loci.

This study identifies therapeutic targets by integrating GWAS with multi-omics data, finding enriched causal genes and novel associations like IL6ST in polymyalgia rheumatica.

This study conducts a GWAS of preeclampsia and hypertensive disorders of pregnancy, identifying 18 genome-wide significant loci, including novel associations with blood pressure and placental function.

This study identifies biomarkers predicting avascular osteonecrosis risk in Gaucher disease patients on enzyme replacement or substrate reduction therapy.

Finnish-enriched low-frequency variants, often coding, underlie many GWAS signals across 1,932 register endpoints in 218,792 Finns; a 15-disease meta-analysis with Estonian and UK biobanks adds 30 unreported associations.

The paper profiles single nuclei from human putamen in Parkinson's Disease and Multiple System Atrophy, revealing disease-specific oligodendrocyte heterogeneity and gene expression changes.

The paper constructs a single-cell atlas of human putamen tissue from healthy controls, Parkinson's Disease, and Multiple System Atrophy to identify cell-type specific disease changes.

The paper analyzes single-cell RNA-seq data from COVID-19 patients to identify the lysosomal-immune axis as a factor associated with disease severity.

This paper computes a genome-wide polygenic risk score for Parkinson's Disease using 6.2 million variants and finds it strongly associates with increased disease risk and earlier onset.

The paper identifies a conserved SNCA co-expression module in human brain single-nucleus RNA-seq data and links it to Parkinson's Disease risk loci through protein-protein interaction networks and CRISPR validation.