Hugo Zeberg

This study uses deep learning to predict cis-regulatory effects of human-specific mutations across 305 tissues, revealing their role in gene expression evolution.

This study identifies a genetic association between thromboembolism risk and long COVID in individuals of European ancestry, suggesting thromboembolism as a potential contributor to long COVID pathogenesis.

This paper presents a second high-quality Denisovan genome from a 200,000-year-old molar, revealing genetic contributions from multiple Denisovan groups and refining the Denisovan genetic lineage.

The paper identifies nephronectin as a mediator of obesity's effect on COVID-19 severity using proteome-wide Mendelian randomization and validates its expression in lung cells.

This study identifies ELF5 as a risk gene for severe COVID-19 using genetic and single-cell expression data, showing its specific expression in respiratory epithelial cells.

The paper identifies an alternative splicing variant of OAS1 that provides protection against severe COVID-19 in people of African ancestry, independent of Neanderthal haplotypes.

The paper develops a machine learning model to predict COVID-19 severity using exonic variants from whole exome sequencing data, finding that variants across all frequency categories contribute to severity.

This study examines how a major genetic risk factor for COVID-19 affects mortality and severity, finding stronger effects in younger adults.

This study identifies OAS1 as a protective factor against COVID-19 severity and susceptibility using Mendelian randomization and case-control analyses.

The paper identifies a Neandertal-derived DPP4 gene variant that increases the risk of severe COVID-19 illness.

The paper identifies a Neandertal-derived haplotype that is protective against severe COVID-19, found globally outside Africa.

The paper identifies a Neandertal-inherited genomic segment as the major genetic risk factor for severe SARS-CoV-2 infection and hospitalization.