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Despite rapid progress in characterizing the role of host genetics in SARS-Cov-2 infection, there is limited understanding of genes and pathways that contribute to COVID-19. Here, we integrated a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n=18,502). We identified 27 genes related to inflammation and coagulation pathways whose genetically predicted expression was associated with COVID-19 hospitalization. We functionally characterized the 27 genes using phenome- and laboratory-wide association scans in Vanderbilt Biobank (BioVU; n=85,460) and identified coagulation-related clinical symptoms, immunologic, and blood-cell-related biomarkers. We replicated these findings across trans-ethnic studies and observed consistent effects in individuals of diverse ancestral backgrounds in BioVU, pan-UK Biobank, and Biobank Japan. Our study highlights putative causal genes impacting COVID-19 severity and symptomology through the host inflammatory response.

DNA methylation is an epigenetic modification of cytosine nucleotides that represents a promising suite of aging markers with broad potential applications. In particular, determining an individual’s age from their skeletal remains is an enduring problem in the field of forensic anthropology, and one that epigenetic markers are particularly well-suited to address. However, all DNA methylation-based age prediction methods published so far focus on tissues other than bone. While high accuracy has been achieved for saliva, blood and sperm, which are easily accessible in living individuals, the highly tissue-specific nature of DNA methylation patterns means that age prediction models trained on these particular tissues may not be directly applicable to other tissues. Bone is a prime target for the development of DNA methylation-based forensic identification tools as skeletal remains are often recoverable for years post-mortem, and well after soft tissues have decomposed. In this study, we generate genome-wide DNA methylation data from 32 individual bone samples. We analyze this new dataset alongside published data from 133 additional bone donors, both living and deceased. We perform an epigenome-wide association study on this combined dataset to identify 108 sites of DNA methylation that show a significant relationship with age (FDR < 0.05). We also develop an age-prediction model using lasso regression that produces highly accurate estimates of age from bone spanning an age range of 49-112 years. Our study demonstrates that DNA methylation levels at specific CpG sites can serve as powerful markers of aging, and can yield more accurate predictions of chronological age in human adults than morphometric markers.

A major outstanding question in human prehistory is the fate of hunting and gathering populations following the rise of agriculture and pastoralism. Genomic analysis of ancient and contemporary Europeans suggests that autochthonous groups were either absorbed into or replaced by expanding farmer populations. Many of the hunter-gatherer populations persisting today live in Africa, perhaps because agropastoral transitions occurred later on the continent. Here, we present the first genomic data from the Chabu, a relatively isolated and marginalized hunting-and-gathering group from the Southwestern Ethiopian highlands. The Chabu are a distinct genetic population that carry the highest levels of Southwestern Ethiopian ancestry of any extant population studied thus far. This ancestry has been in situ for at least 4,500 years. We show that the Chabu are undergoing a severe population bottleneck which began around 40 generations ago. We also study other Eastern African populations and demonstrate divergent patterns of historical population size change over the past 60 generations between even closely related groups. We argue that these patterns demonstrate that, unlike in Europe, Africans hunter-gatherers responded to agropastoralism with diverse strategies.