Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data.

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Robust characterization of mitochondrial variation provides an opportunity to map regions under high constraint, and identify essential functional domains. We sequenced the mitochondrial genomes of 196,554 unrelated individuals, and identified 15,035 unique variants. We found that 47% of the mitochondrial genome was invariant across the population, and generated a map of constrained mitochondrial regions. We find that the longest intervals in the mitochondrial genome without any variant were in the two rRNA genes (26 of 40 intervals >10bp long). We also showed that the 13 protein-coding genes in the mitochondrial genome did not tolerate loss-of-function variants. The only frameshift or nonsense variant observed at homoplasmic levels was a nonsense at the start codon of MT-ND1 , which may be rescued by the methionine at amino acid position 3. Lastly, we applied these data to variants reported to be pathogenic for Leber's Hereditary Optic Neuropathy (LHON). We found that 42% of variants (19 of the 45) reported to be pathogenic have a frequency above the maximum credible population allele frequency for an LHON-causing variant, including the primary LHON mutation m.14484T>C, which suggests that m.14484T>C cannot be causing LHON by itself. This result showed that allele frequency information across a large unselected population is important to assess the pathogenicity of variants in the context of rare mitochondrial disorders. We made HelixMTdb -the list of variants and their allele frequency in 196,554 unrelated individuals --publicly available.

Background Air pollution has been linked to increased susceptibility to SARS-CoV-2. Thus, it has been suggested that wildfire smoke events may exacerbate the COVID-19 pandemic. Objectives Our goal was to examine whether wildfire smoke from the 2020 wildfires in the western United States was associated with an increased rate of SARS-CoV-2 infections in Reno, Nevada. Methods We conducted a time-series analysis using generalized additive models to examine the relationship between the SARS-CoV-2 test positivity rate at a large regional hospital in Reno and ambient PM2.5 from 15 May to 20 Oct 2020. Results We found that a 10 µg/m3 increase in the 7-day average PM2.5 concentration was associated with a 6.3% relative increase in the SARS-CoV-2 test positivity rate, with a 95% confidence interval (CI) of 2.5 to 10.3%. This corresponded to an estimated 17.7% (CI: 14.4–20.1%) increase in the number of cases during the time period most affected by wildfire smoke, from 16 Aug to 10 Oct. Significance Wildfire smoke may have greatly increased the number of COVID-19 cases in Reno. Thus, our results substantiate the role of air pollution in exacerbating the pandemic and can help guide the development of public preparedness policies in areas affected by wildfire smoke, as wildfires are likely to coincide with the COVID-19 pandemic in 2021.