Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection.

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B*15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B*15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the US (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B*15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

A power-based sliding window approach to evaluate the clinical impact of rare genetic variants in the nucleotide sequence or the spatial position of the folded protein.

Systematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between a gene and phenotype. Here we present Power Window (PW), a sliding window technique that identifies the impactful regions of a gene using population-scale clinico-genomic datasets. By sizing analysis windows on the number of variant carriers, rather than the number of variants or nucleotides, statistical power is held constant, enabling the localization of clinical phenotypes and removal of unassociated gene regions. The windows can be built by sliding across either the nucleotide sequence of the gene (through 1D space) or the positions of the amino acids in the folded protein (through 3D space). Using a training set of 350k exomes from the UK Biobank (UKB), we developed PW models for well-established gene-disease associations and tested their accuracy in two independent cohorts (117k UKB exomes and 65k exomes sequenced at Helix in the Healthy Nevada Project, myGenetics, or In Our DNA SC studies). The significant models retained a median of 49% of the qualifying variant carriers in each gene (range 2%-98%), with quantitative traits showing a median effect size improvement of 66% compared with aggregating variants across the entire gene, and binary traits' odds ratios improving by a median of 2.2-fold. PW showcases that electronic health record-based statistical analyses can accurately distinguish between novel coding variants in established genes that will have high phenotypic penetrance and those that will not, unlocking new potential for human genomics research, drug development, variant interpretation, and precision medicine.

The Potential of Genetics in Identifying Women at Lower Risk of Breast Cancer.

Importance: Genetic information is not being used to identify women at lower risk of breast cancer or other diseases in clinical practice. With the new US Preventive Services Task Force guidelines lowering the age for mammogram screening for all, there is a potential benefit in identifying women at lower risk of disease who may defer the start of mammographic screening. This genetic risk-based approach would help mitigate overscreening, associated costs, and anxiety. Objective: To assess breast cancer incidence and age of onset among women at low genetic risk compared with women at average risk and evaluate the potential to delay mammography on the basis of genetic risk stratification. Design, Setting, and Participants: This retrospective case-control study included 25 591 women from the Healthy Nevada Project sequenced by Helix between 2018 and 2022. Data extracted from electronic health records at the end of 2022 (mean length of electronic health record available was 12 years) were used for the analysis in 2023. Main Outcomes and Measures: Breast cancer diagnosis was identified from electronic health records. Classification to the low-risk genetic group required (1) the absence of pathogenic variants or a variant of uncertain significance in BRCA1, BRCA2, PALB2, ATM, or CHEK2, and (2) a low polygenic risk score (bottom 10%) using a 313-single-nucleotide variant model. Results: Of 25 591 women in the study (mean [SD] age was 53.8 [16.9] years), 2338 women (9.1%) were classified as having low risk for breast cancer; 410 women (1.6%) were classified as high risk; and 22 843 women (89.3%) as average risk. There was a significant reduction in breast cancer diagnosis among the low-risk group (hazard ratio, 0.39; 95% CI, 0.29-0.52; P < .001). By 45 years of age, 0.69% of women in the average-risk group were diagnosed with breast cancer, whereas women in the low-risk group reached this rate at 51 years. By 50 years of age, 1.41% of those in the average-risk group were diagnosed with breast cancer, whereas those in the low-risk group reached this rate at age 58 years. These findings suggest that deferring mammogram screening by 5 to 10 years for women at low risk of breast cancer aligns with new draft recommendations. Conclusions and Relevance: The findings of this retrospective case-control study underscore the value of genetics in individualizing the onset of breast cancer screening. Improving breast cancer risk stratification by implementing both high-risk and low-risk strategies in screening can refine preventive measures and optimize health care resource allocation.

Clinical case study meets population cohort: identification of a BRCA1 pathogenic founder variant in Orcadians.

We multiply ascertained the BRCA1 pathogenic missense variant c.5207T > C; p.Val1736Ala (V1736A) in clinical investigation of breast and ovarian cancer families from Orkney in the Northern Isles of Scotland, UK. We sought to investigate the frequency and clinical relevance of this variant in those of Orcadian ancestry as an exemplar of the value of population cohorts in clinical care, especially in isolated populations. Oral history and birth, marriage and death registrations indicated genealogical linkage of the clinical cases to ancestors from the Isle of Westray, Orkney. Further clinical cases were identified through targeted testing for V1736A in women of Orcadian ancestry attending National Health Service (NHS) genetic clinics for breast and ovarian cancer family risk assessments. The variant segregates with female breast and ovarian cancer in clinically ascertained cases. Separately, exome sequence data from 2088 volunteer participants with three or more Orcadian grandparents, in the ORCADES research cohort, was interrogated to estimate the population prevalence of V1736A in Orcadians. The effects of the variant were assessed using Electronic Health Record (EHR) linkage. Twenty out of 2088 ORCADES research volunteers (~1%) carry V1736A, with a common haplotype around the variant. This allele frequency is ~480-fold higher than in UK Biobank participants. Cost-effectiveness of population screening for BRCA1 founder pathogenic variants has been demonstrated at a carrier frequency below the ~1% observed here. Thus we suggest that Orcadian women should be offered testing for the BRCA1 V1736A founder pathogenic variant, starting with those with known Westray ancestry.

Predictions of Arsenic in Domestic Well Water Sourced from Alluvial Aquifers of the Western Great Basin, USA.

Chronic exposure to high levels of arsenic in drinking water can have wide-ranging health effects and is a global health concern. The domestic well population of the western Great Basin (WGB) is at increased risk of exposure to arsenic due to the hydrologic, geologic, and climatic setting of the region. A logistic regression (LR) model was developed to predict the probability of elevated arsenic (≥5 µg/L) in alluvial aquifers and assess the potential geologic hazard level posed to domestic well populations. Alluvial aquifers are susceptible to arsenic contamination, which is a concern because they are the primary source of water for domestic well users of the WGB. The probability of elevated arsenic at a domestic well is strongly influenced by tectonic and geothermal variables, including the total Quaternary fault length in the hydrographic basin and the distance between the sampled well and a geothermal system. The model had an overall accuracy of 81%, sensitivity of 92%, and specificity of 55%. Results show a >50% probability of elevated arsenic in untreated well water for approximately 49 thousand (64%) alluvial-aquifer domestic well users in northern Nevada, northeastern California, and western Utah.

Cardiomyopathy prevalence exceeds 30% in individuals with TTN variants and early atrial fibrillation.

PURPOSE: TTN truncating variants (TTNtvs) represent the largest known genetic cause of dilated cardiomyopathies (DCMs), however their penetrance for DCM in general populations is low. More broadly, patients with cardiomyopathies (CMs) often exhibit other cardiac conditions, such as atrial fibrillation (Afib), which has also been linked to TTNtvs. This retrospective analysis aims to characterize the relationship between different cardiac conditions in those with TTNtvs and identify individuals with the highest risk of DCM. METHODS: In this work we leverage longitudinal electronic health record and exome sequencing data from approximately 450,000 individuals in 2 health systems to statistically confirm and pinpoint the genetic footprint of TTNtv-related diagnoses aside from CM, such as Afib, and determine whether vetting additional significantly associated phenotypes better stratifies CM risk across those with TTNtvs. We focused on TTNtvs in exons with a percentage spliced in >90% (hiPSI TTNtvs), a representation of constitutive cardiac expression. RESULTS: When controlling for CM and Afib, other cardiac conditions retained only nominal association with TTNtvs. A sliding window analysis of TTNtvs across the locus confirms that the association is specific to hiPSI exons for both CM and Afib, with no meaningful associations in percent spliced in ≤90% exons (loPSI TTNtvs). The combination of hiPSI TTNtv status and early Afib diagnosis (before age 60) found a subset of TTNtv individuals at high risk for CM. The prevalence of CM in this subset was 33%, a rate that was 3.5 fold higher than that in individuals with hiPSI TTNtvs (9% prevalence), 5-fold higher than that in individuals without TTNtvs with early Afib (6% prevalence), and 80-fold higher than that in the general population. CONCLUSION: Our retrospective analyses revealed that those with hiPSI TTNtvs and early Afib (∼1/2900) have a high prevalence of CM (33%), far exceeding that in other individuals with TTNtvs and in those without TTNtvs with an early Afib diagnosis. These results show that combining phenotypic information along with genomic population screening can identify patients at higher risk for progressing to symptomatic heart failure.

Lack of association between HLA and asymptomatic SARS-CoV-2 infection.

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B*15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B*15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the US (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B*15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified. These findings suggest that memory T-cell immunity to seasonal coronaviruses does not strongly influence the outcome of SARS-CoV-2 infection in unvaccinated individuals.

Using phenome-wide association studies and the SF-12 quality of life metric to identify profound consequences of adverse childhood experiences on adult mental and physical health in a Northern Nevadan population.

In this research, we examine and identify the implications of Adverse Childhood Experiences (ACEs) on a range of health outcomes, with particular focus on a number of mental health disorders. Many previous studies observed that traumatic childhood events are linked to long-term adult diseases using the standard Adverse Childhood Experience Questionnaire. The study cohort was derived from the Healthy Nevada Project, a volunteer-based population health study in which each adult participant is invited to take a retrospective questionnaire that includes the Adverse Childhood Experience Questionnaire, the 12-item Short Form Survey measuring quality of life, and self-reported incidence of nine mental disorders. Using participant's cross-referenced electronic health records, a phenome-wide association analysis of 1,703 phenotypes and the incidence of ACEs examined links between traumatic events in childhood and adult disease. These analyses showed that many mental disorders were significantly associated with ACEs in a dose-response manner. Similarly, a dose response between ACEs and obesity, chronic pain, migraine, and other physical phenotypes was identified. An examination of the prevalence of self-reported mental disorders and incidence of ACEs showed a positive relationship. Furthermore, participants with less adverse childhood events experienced a higher quality of life, both physically and mentally. The whole-phenotype approach confirms that ACEs are linked with many negative adult physical and mental health outcomes. With the nationwide prevalence of ACEs as high as 67%, these findings suggest a need for new public health resources: ACE-specific interventions and early childhood screenings.

Incomplete Penetrance of Population-Based Genetic Screening Results in Electronic Health Record.

The clinical value of population-based genetic screening projects depends on the actions taken on the findings. The Healthy Nevada Project (HNP) is an all-comer genetic screening and research project based in northern Nevada. HNP participants with CDC Tier 1 findings of hereditary breast and ovarian cancer syndrome (HBOC), Lynch syndrome (LS), or familial hypercholesterolemia (FH) are notified and provided with genetic counseling. However, the HNP subsequently takes a "hands-off" approach: it is the responsibility of notified participants to share their findings with their healthcare providers, and providers are expected to implement the recommended action plans. Thus, the HNP presents an opportunity to evaluate the efficiency of participant and provider responses to notification of important genetic findings, using electronic health records (EHRs) at Renown Health (a large regional hospital in northern Nevada). Out of 520 HNP participants with findings, we identified 250 participants who were notified of their findings and who had an EHR. 107 of these participants responded to a survey, with 76 (71%) indicating that they had shared their findings with their healthcare providers. However, a sufficiently specific genetic diagnosis appeared in the EHRs and problem lists of only 22 and 10%, respectively, of participants without prior knowledge. Furthermore, review of participant EHRs provided evidence of possible relevant changes in clinical care for only a handful of participants. Up to 19% of participants would have benefited from earlier screening due to prior presentation of their condition. These results suggest that continuous support for both participants and their providers is necessary to maximize the benefit of population-based genetic screening. We recommend that genetic screening projects require participants' consent to directly document their genetic findings in their EHRs. Additionally, we recommend that they provide healthcare providers with ongoing training regarding documentation of findings and with clinical decision support regarding subsequent care.

The Impact of ACEs on BMI: An Investigation of the Genotype-Environment Effects of BMI.

Adverse Childhood Experiences are stressful and traumatic events occurring before the age of eighteen shown to cause mental and physical health problems, including increased risk of obesity. Obesity remains an ongoing national challenge with no predicted solution. We examine a subset of the Healthy Nevada Project, focusing on a multi-ethnic cohort of 15,886 sequenced participants with recalled adverse childhood events, to study how ACEs and their genotype-environment interactions affect BMI. Specifically, the Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records and social health determinants questionnaire to identify: 1) the effect of ACEs on BMI in the absence of genetics; 2) the effect of genotype-environment interactions on BMI; 3) how these gene-environment interactions differ from standard genetic associations of BMI. The study found very strong significant associations between the number of adverse childhood experiences and adult obesity. Additionally, we identified fifty-five common and rare variants that exhibited gene-interaction effects including three variants in the CAMK1D gene and four variants in LHPP; both genes are linked to schizophrenia. Surprisingly, none of the variants identified with interactive effects were in canonical obesity-related genes. Here we show the delicate balance between genes and environment, and how the two strongly influence each other.

HLA-A∗03:01 is associated with increased risk of fever, chills, and stronger side effects from Pfizer-BioNTech COVID-19 vaccination.

COVID-19 vaccines are safe and highly effective, but some individuals experience unpleasant reactions to vaccination. As the majority of adults in the United States have received a COVID-19 vaccine this year, there is an unprecedented opportunity to study the genetics of reactions to vaccination via surveys of individuals who are already part of genetic research studies. Here, we have queried 17,440 participants in the Helix DNA Discovery Project and Healthy Nevada Project about their reactions to COVID-19 vaccination. Our genome-wide association study identifies an association between severe difficulties with daily routine after vaccination and HLA-A∗03:01. This association was statistically significant only for those who received the Pfizer-BioNTech vaccine (BNT162b2; n = 3,694; p = 4.70E-11; OR = 2.07 [95% CI 1.67-2.56]), and showed a smaller effect size in those who received the Moderna vaccine (mRNA-1273; n = 3,610; p = 0.005; OR = 1.32 [95% CI 1.09-1.59]). In Pfizer-BioNTech recipients, HLA-A∗03:01 was associated with a 2-fold increase in risk of self-reported severe difficulties with daily routine following vaccination. The effect was consistent across ages, sexes, and whether the person had previously had a COVID-19 infection. The reactions experienced by HLA-A∗03:01 carriers were driven by associations with chills, fever, fatigue, and generally feeling unwell.

Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records.

PURPOSE: To identify conditions that are candidates for population genetic screening based on population prevalence, penetrance of rare variants, and actionability. METHODS: We analyzed exome and medical record data from >220,000 participants across two large population health cohorts with different demographics. We performed a gene-based collapsing analysis of rare variants to identify genes significantly associated with disease status. RESULTS: We identify 74 statistically significant gene-disease associations across 27 genes. Seven of these conditions have a positive predictive value (PPV) of at least 30% in both cohorts. Three are already used in population screening programs (BRCA1, BRCA2, LDLR), and we also identify four new candidates for population screening: GCK with diabetes mellitus, HBB with ß-thalassemia minor and intermedia, PKD1 with cystic kidney disease, and MIP with cataracts. Importantly, the associations are actionable in that early genetic screening of each of these conditions is expected to improve outcomes. CONCLUSION: We identify seven genetic conditions where rare variation appears appropriate to assess in population screening, four of which are not yet used in screening programs. The addition of GCK, HBB, PKD1, and MIP rare variants into genetic screening programs would reach an additional 0.21% of participants with actionable disease risk, depending on the population.

SARS-CoV-2 test positivity rate in Reno, Nevada: association with PM2.5 during the 2020 wildfire smoke events in the western United States.

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.

Comprehensive Allele Genotyping in Critical Pharmacogenes Reduces Residual Clinical Risk in Diverse Populations.

Genomic-guided pharmaceutical prescribing is increasingly recognized as an important clinical application of genetics. Accurate genotyping of pharmacogenomic (PGx) genes can be difficult, owing to their complex genetic architecture involving combinations of single-nucleotide polymorphisms and structural variation. Here, we introduce the Helix PGx database, an open-source star allele, genotype, and resulting metabolic phenotype frequency database for CYP2C9, CYP2C19, CYP2D6, and CYP4F2, based on short-read sequencing of >86,000 unrelated individuals enrolled in the Helix DNA Discovery Project. The database is annotated using a pipeline that is clinically validated against a broad range of alleles and designed to call CYP2D6 structural variants with high (98%) accuracy. We find that CYP2D6 has greater allelic diversity than the other genes, manifest in both a long tail of low-frequency star alleles, as well as a disproportionate fraction (36%) of all novel predicted loss-of-function variants identified. Across genes, we observe that many rare alleles (<0.1% frequency) in the overall cohort have 10 times higher frequency in one or more subgroups with non-European genetic ancestry. Extending these PGx genotypes to predicted metabolic phenotypes, we demonstrate that >90% of the cohort harbors a high-risk variant in one of the four pharmacogenes. Based on the recorded prescriptions for >30,000 individuals in the Healthy Nevada Project, combined with predicted PGx metabolic phenotypes, we anticipate that standard-of-care screening of these 4 pharmacogenes could impact nearly half of the general population.

Inhibition of HECT E3 ligases as potential therapy for COVID-19.

SARS-CoV-2 is responsible for the ongoing world-wide pandemic which has already taken more than two million lives. Effective treatments are urgently needed. The enzymatic activity of the HECT-E3 ligase family members has been implicated in the cell egression phase of deadly RNA viruses such as Ebola through direct interaction of its VP40 Protein. Here we report that HECT-E3 ligase family members such as NEDD4 and WWP1 interact with and ubiquitylate the SARS-CoV-2 Spike protein. Furthermore, we find that HECT family members are overexpressed in primary samples derived from COVID-19 infected patients and COVID-19 mouse models. Importantly, rare germline activating variants in the NEDD4 and WWP1 genes are associated with severe COVID-19 cases. Critically, I3C, a natural NEDD4 and WWP1 inhibitor from Brassicaceae, displays potent antiviral effects and inhibits viral egression. In conclusion, we identify the HECT family members of E3 ligases as likely novel biomarkers for COVID-19, as well as new potential targets of therapeutic strategy easily testable in clinical trials in view of the established well-tolerated nature of the Brassicaceae natural compounds.

Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population.

Clinical conditions correlated with elevated triglyceride levels are well-known: coronary heart disease, hypertension, and diabetes. Underlying genetic and phenotypic mechanisms are not fully understood, partially due to lack of coordinated genotypic-phenotypic data. Here we use a subset of the Healthy Nevada Project, a population of 9,183 sequenced participants with longitudinal electronic health records to examine consequences of altered triglyceride levels. Specifically, Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records to identify: (1) rare and common single-variant genome-wide associations; (2) gene-based associations using a Sequence Kernel Association Test; (3) phenome-wide associations with triglyceride levels; and (4) pleiotropic variants linked to triglyceride levels. The study identified 549 significant single-variant associations (p < 8.75 × 10-9), many in chromosome 11's triglyceride hotspot: ZPR1, BUD13, APOC3, APOA5. A well-known protective loss-of-function variant in APOC3 (R19X) was associated with a 51% decrease in triglyceride levels in the cohort. Sixteen gene-based triglyceride associations were identified; six of these genes surprisingly did not include a single variant with significant associations. Results at the variant and gene level were validated with the UK Biobank. The combination of a single-variant genome-wide association, a gene-based association method, and phenome wide-association studies identified rare and common variants, genes, and phenotypes associated with elevated triglyceride levels, some of which may have been overlooked with standard approaches.

Heterozygous germline BLM mutations increase susceptibility to asbestos and mesothelioma.

Rare biallelic BLM gene mutations cause Bloom syndrome. Whether BLM heterozygous germline mutations (BLM+/-) cause human cancer remains unclear. We sequenced the germline DNA of 155 mesothelioma patients (33 familial and 122 sporadic). We found 2 deleterious germline BLM+/- mutations within 2 of 33 families with multiple cases of mesothelioma, one from Turkey (c.569_570del; p.R191Kfs*4) and one from the United States (c.968A>G; p.K323R). Some of the relatives who inherited these mutations developed mesothelioma, while none with nonmutated BLM were affected. Furthermore, among 122 patients with sporadic mesothelioma treated at the US National Cancer Institute, 5 carried pathogenic germline BLM+/- mutations. Therefore, 7 of 155 apparently unrelated mesothelioma patients carried BLM+/- mutations, significantly higher (P = 6.7E-10) than the expected frequency in a general, unrelated population from the gnomAD database, and 2 of 7 carried the same missense pathogenic mutation c.968A>G (P = 0.0017 given a 0.00039 allele frequency). Experiments in primary mesothelial cells from Blm+/- mice and in primary human mesothelial cells in which we silenced BLM revealed that reduced BLM levels promote genomic instability while protecting from cell death and promoted TNF-α release. Blm+/- mice injected intraperitoneally with asbestos had higher levels of proinflammatory M1 macrophages and of TNF-α, IL-1ß, IL-3, IL-10, and IL-12 in the peritoneal lavage, findings linked to asbestos carcinogenesis. Blm+/- mice exposed to asbestos had a significantly shorter survival and higher incidence of mesothelioma compared to controls. We propose that germline BLM+/- mutations increase the susceptibility to asbestos carcinogenesis, enhancing the risk of developing mesothelioma.

Pathogenic variants in actionable MODY genes are associated with type 2 diabetes.

Genome-wide association studies have identified 240 independent loci associated with type 2 diabetes (T2D) risk, but this knowledge has not advanced precision medicine. In contrast, the genetic diagnosis of monogenic forms of diabetes (including maturity-onset diabetes of the young (MODY)) are textbook cases of genomic medicine. Recent studies trying to bridge the gap between monogenic diabetes and T2D have been inconclusive. Here, we show a significant burden of pathogenic variants in genes linked with monogenic diabetes among people with common T2D, particularly in actionable MODY genes, thus implying that there should be a substantial change in care for carriers with T2D. We show that, among 74,629 individuals, this burden is probably driven by the pathogenic variants found in GCK, and to a lesser extent in HNF4A, KCNJ11, HNF1B and ABCC8. The carriers with T2D are leaner, which evidences a functional metabolic effect of these mutations. Pathogenic variants in actionable MODY genes are more frequent than was previously expected in common T2D. These results open avenues for future interventions assessing the clinical interest of these pathogenic mutations in precision medicine.

Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts.

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.

A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort.

The aggregation of Electronic Health Records (EHR) and personalized genetics leads to powerful discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant SNPs, BMI, and incidence of extreme obesity. The first GWAS examines associations with BMI in a cohort with no type 2 diabetics, focusing exclusively on BMI. The second GWAS examines associations with BMI in a cohort that includes type 2 diabetics. In the second GWAS, type 2 diabetes is a comorbidity, and thus becomes a covariate in the statistical model. The intersection of significant variants of these two studies is surprising. The third GWAS is a case vs. control study, with cases defined as extremely obese (Class 2 or 3 obesity), and controls defined as participants with BMI between 18.5 and 25. This last GWAS identifies strong associations with extreme obesity, including established variants in the FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR database to validate known associations and identify putative novel links with BMI and obesity.