A deep catalogue of protein-coding variation in 983,578 individuals.

Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.

Common and rare variant associations with clonal haematopoiesis phenotypes.

Clonal haematopoiesis involves the expansion of certain blood cell lineages and has been associated with ageing and adverse health outcomes1-5. Here we use exome sequence data on 628,388 individuals to identify 40,208 carriers of clonal haematopoiesis of indeterminate potential (CHIP). Using genome-wide and exome-wide association analyses, we identify 24 loci (21 of which are novel) where germline genetic variation influences predisposition to CHIP, including missense variants in the lymphocytic antigen coding gene LY75, which are associated with reduced incidence of CHIP. We also identify novel rare variant associations with clonal haematopoiesis and telomere length. Analysis of 5,041 health traits from the UK Biobank (UKB) found relationships between CHIP and severe COVID-19 outcomes, cardiovascular disease, haematologic traits, malignancy, smoking, obesity, infection and all-cause mortality. Longitudinal and Mendelian randomization analyses revealed that CHIP is associated with solid cancers, including non-melanoma skin cancer and lung cancer, and that CHIP linked to DNMT3A is associated with the subsequent development of myeloid but not lymphoid leukaemias. Additionally, contrary to previous findings from the initial 50,000 UKB exomes6, our results in the full sample do not support a role for IL-6 inhibition in reducing the risk of cardiovascular disease among CHIP carriers. Our findings demonstrate that CHIP represents a complex set of heterogeneous phenotypes with shared and unique germline genetic causes and varied clinical implications.

Exome sequencing and analysis of 454,787 UK Biobank participants.

A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study2. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10-11. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene-trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Germline Mutations in CIDEB and Protection against Liver Disease.

BACKGROUND: Exome sequencing in hundreds of thousands of persons may enable the identification of rare protein-coding genetic variants associated with protection from human diseases like liver cirrhosis, providing a strategy for the discovery of new therapeutic targets. METHODS: We performed a multistage exome sequencing and genetic association analysis to identify genes in which rare protein-coding variants were associated with liver phenotypes. We conducted in vitro experiments to further characterize associations. RESULTS: The multistage analysis involved 542,904 persons with available data on liver aminotransferase levels, 24,944 patients with various types of liver disease, and 490,636 controls without liver disease. We found that rare coding variants in APOB, ABCB4, SLC30A10, and TM6SF2 were associated with increased aminotransferase levels and an increased risk of liver disease. We also found that variants in CIDEB, which encodes a structural protein found in hepatic lipid droplets, had a protective effect. The burden of rare predicted loss-of-function variants plus missense variants in CIDEB (combined carrier frequency, 0.7%) was associated with decreased alanine aminotransferase levels (beta per allele, -1.24 U per liter; 95% confidence interval [CI], -1.66 to -0.83; P = 4.8×10-9) and with 33% lower odds of liver disease of any cause (odds ratio per allele, 0.67; 95% CI, 0.57 to 0.79; P = 9.9×10-7). Rare coding variants in CIDEB were associated with a decreased risk of liver disease across different underlying causes and different degrees of severity, including cirrhosis of any cause (odds ratio per allele, 0.50; 95% CI, 0.36 to 0.70). Among 3599 patients who had undergone bariatric surgery, rare coding variants in CIDEB were associated with a decreased nonalcoholic fatty liver disease activity score (beta per allele in score units, -0.98; 95% CI, -1.54 to -0.41 [scores range from 0 to 8, with higher scores indicating more severe disease]). In human hepatoma cell lines challenged with oleate, CIDEB small interfering RNA knockdown prevented the buildup of large lipid droplets. CONCLUSIONS: Rare germline mutations in CIDEB conferred substantial protection from liver disease. (Funded by Regeneron Pharmaceuticals.).

The effect of tablet computer-based telemonitoring added to an established telephone disease management program on heart failure hospitalizations: The Specialized Primary and Networked Care in Heart Failure (SPAN-CHF) III Randomized Controlled Trial.

BACKGROUND: Mobile health applications are becoming increasingly common. Prior work has demonstrated reduced heart failure (HF) hospitalizations with HF disease management programs; however, few of these programs have used tablet computer-based technology. METHODS: Participants with a diagnosis of HF and at least 1 high risk feature for hospitalization were randomized to either an established telephone-based disease management program or the same disease management program with the addition of remote monitoring of weight, blood pressure, heart rate and symptoms via a tablet computer for 90 days. The primary endpoint was the number of days hospitalized for HF assessed at 90 days. RESULTS: From August 2014 to April 2019, 212 participants from 3 hospitals in Massachusetts were randomized 3:1 to telemonitoring-based HF disease management (n = 159) or telephone-based HF disease management (n = 53) with 98% of individuals in both study groups completing the 90 days of follow-up. There was no significant difference in the number of days hospitalized for HF between the telemonitoring disease management group (0.88 ± 3.28 days per patient-90 days) and the telephone-based disease management group (1.00 ± 2.97 days per patient-90 days); incidence rate ratio 0.82 (95% confidence interval, 0.43-1.58; P = .442). CONCLUSIONS: The addition of tablet-based telemonitoring to an established HF telephone-based disease management program did not reduce HF hospitalizations; however, study power was limited.

Comparing Clinical Characteristics of Influenza and Common Coronavirus Infections Using Electronic Health Records.

BACKGROUND: We compared outcomes in inpatients and outpatients, pre-COVID-19, who were infected with either coronavirus or influenza. METHODS: Using deidentified electronic health records data from the Geisinger-Regeneron partnership, we compared patients with RT-PCR-positive tests for the 4 common coronaviruses (229E, HKU1, NL63, OC43) or influenza (A and B) from June 2016 to February 2019. RESULTS: Overall, 52 833 patients were tested for coronaviruses and influenza. For patients ≥21 years old, 1555 and 3991 patient encounters had confirmed positive coronavirus and influenza tests, respectively. Both groups had similar intensive care unit (ICU) admission rates (7.2% vs 6.1%, P = .12), although patients with coronavirus had significantly more pneumonia (15% vs 7.4%, P < .001) and higher death rate within 30 days (4.9% vs 3.0%, P < .001). After controlling for other covariates, coronavirus infection still had a higher risk of death and pneumonia than influenza (odds ratio, 1.64 and 2.05, P < .001), with no significant difference in ICU admission rates. CONCLUSIONS: Common coronaviruses cause significant morbidity, with potentially worse outcomes than influenza. Identifying a subset of patients who are more susceptible to poor outcomes from common coronavirus infections may help plan clinical interventions in patients with suspected infections.

Measuring Patient and Staff Satisfaction Before and After Implementation of a Paperless Registration System.

EXECUTIVE SUMMARY: While many aspects of patient care have transitioned to digital technology, the patient registration process often is still paper based. Several studies have examined the effects of changes in clinic workflows and appointment scheduling on patient satisfaction, but few have investigated changes from a paper-based to a paperless registration process. The authors measured patient and staff satisfaction before and after implementation of a new, tablet-based registration process at NYU Langone Health's Center for Women's Health in New York City. Mean preimplementation patient satisfaction scores on the six questions related to the registration process (1-5 scale, with 5 being the highest score) ranged from 4.0 to 4.5. Postimplementation satisfaction scores on the nine questions (six premeasure questions and three additional questions related to the tablet-based process) ranged from 4.4 to 4.6, with four of the six premeasures showing statistically significant improvement in patient satisfaction. Staff satisfaction was generally lower (2.8-3.6 preimplementation and 2.8-4 postimplementation), with no statistically significant difference between time frames. Patient satisfaction was relatively high under the paper registration process, and it improved significantly in some respects under the paperless process, while staff satisfaction did not change. The convenience and ease of use of a paperless registration system can help maintain or increase patient and staff satisfaction while introducing new workflows and improving the efficiency of the outpatient registration process. In adopting technology that can lead to changing workflows, organizations should train staff members and support them during the process.

The genome portal of the Department of Energy Joint Genome Institute: 2014 updates.

The U.S. Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization. The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. Here we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI.

Determining the natural history of pancreatic cystic neoplasms: a Manitoban cohort study.

BACKGROUND: Most pancreatic cystic neoplasms (PCN) are thought to harbor a low malignant potential. This historical cohort study attempts to describe the natural history of these lesions in a provincial cohort, to assess the safety of non-surgical management. Pathological diagnosis of malignancy was the primary outcome measure of interest. METHODS: All adult patients (age 18+) with PCN seen between 2000 and 2012 by the two main institutions in Manitoba were included in this study. PCN were graded as high and low risk, which dictated initial treatment plan (surgery or observation). Predictors of initial surgical treatment, delayed surgery in the observation group and the clinical/radiological predictors of malignancy were determined. RESULTS: 497 patients were included in this study. 43 (8.7%) high-risk lesions underwent initial surgery, with 13 (30.2%) cases of malignancy discovered. 450 (90.5%) low-risk cysts were observed for a median of 17.3 months (range: 0.00-142.3). 29 (6.4%) cases of delayed surgery occurred, with malignancy discovered in five (17.2%). CONCLUSIONS: This study supports current selection criteria for management of PCNs. Due to the low incidence of malignancy in low-risk PCN, it appears that long-term observation is safe and should be the treatment modality of choice in the absence of high-risk features.

Elviz - exploration of metagenome assemblies with an interactive visualization tool.

BACKGROUND: Metagenomics, the sequencing of DNA collected from an entire microbial community, enables the study of natural microbial consortia in their native habitats. Metagenomics studies produce huge volumes of data, including both the sequences themselves and metadata describing their abundance, assembly, predicted functional characteristics and environmental parameters. The ability to explore these data visually is critically important to meaningful biological interpretation. Current genomics applications cannot effectively integrate sequence data, assembly metadata, and annotation to support both genome and community-level inquiry. RESULTS: Elviz (Environmental Laboratory Visualization) is an interactive web-based tool for the visual exploration of assembled metagenomes and their complex metadata. Elviz allows scientists to navigate metagenome assemblies across multiple dimensions and scales, plotting parameters such as GC content, relative abundance, phylogenetic affiliation and assembled contig length. Furthermore Elviz enables interactive exploration using real-time plot navigation, search, filters, axis selection, and the ability to drill from a whole-community profile down to individual gene annotations. Thus scientists engage in a rapid feedback loop of visual pattern identification, hypothesis generation, and hypothesis testing. CONCLUSIONS: Compared to the current alternative of generating a succession of static figures, Elviz can greatly accelerate the speed of metagenome analysis. Elviz can be used to explore both user-submitted datasets and numerous metagenome studies publicly available at the Joint Genome Institute (JGI). Elviz is freely available at http://genome.jgi.doe.gov/viz and runs on most current web-browsers.

A Letter to My Friend and Chaplain Colleague Imam Sohaib Sultan, Zichrono Livracha (of Blessed Memory).

I am a Jewish chaplain and I felt moved to write this letter to my esteemed colleague Imam Sohaib Sultan, of blessed memory. Sohaib and I each experienced our first unit of Clinical Pastoral Education together as part of the same cohort in the summer of 2008. Sohaib died tragically in 2021. Here, I reflect on how we might respond to the current Israel-Hamas War.

Genetic risk factors for COVID-19 and influenza are largely distinct.

Coronavirus disease 2019 (COVID-19) and influenza are respiratory illnesses caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses, respectively. Both diseases share symptoms and clinical risk factors1, but the extent to which these conditions have a common genetic etiology is unknown. This is partly because host genetic risk factors are well characterized for COVID-19 but not for influenza, with the largest published genome-wide association studies for these conditions including >2 million individuals2 and about 1,000 individuals3-6, respectively. Shared genetic risk factors could point to targets to prevent or treat both infections. Through a genetic study of 18,334 cases with a positive test for influenza and 276,295 controls, we show that published COVID-19 risk variants are not associated with influenza. Furthermore, we discovered and replicated an association between influenza infection and noncoding variants in B3GALT5 and ST6GAL1, neither of which was associated with COVID-19. In vitro small interfering RNA knockdown of ST6GAL1-an enzyme that adds sialic acid to the cell surface, which is used for viral entry-reduced influenza infectivity by 57%. These results mirror the observation that variants that downregulate ACE2, the SARS-CoV-2 receptor, protect against COVID-19 (ref. 7). Collectively, these findings highlight downregulation of key cell surface receptors used for viral entry as treatment opportunities to prevent COVID-19 and influenza.

NOTCH3 p.Arg1231Cys is markedly enriched in South Asians and associated with stroke.

The genetic factors of stroke in South Asians are largely unexplored. Exome-wide sequencing and association analysis (ExWAS) in 75 K Pakistanis identified NM_000435.3(NOTCH3):c.3691 C > T, encoding the missense amino acid substitution p.Arg1231Cys, enriched in South Asians (alternate allele frequency = 0.58% compared to 0.019% in Western Europeans), and associated with subcortical hemorrhagic stroke [odds ratio (OR) = 3.39, 95% confidence interval (CI) = [2.26, 5.10], p = 3.87 × 10-9), and all strokes (OR [CI] = 2.30 [1.77, 3.01], p = 7.79 × 10-10). NOTCH3 p.Arg231Cys was strongly associated with white matter hyperintensity on MRI in United Kingdom Biobank (UKB) participants (effect [95% CI] in SD units = 1.1 [0.61, 1.5], p = 3.0 × 10-6). The variant is attributable for approximately 2.0% of hemorrhagic strokes and 1.1% of all strokes in South Asians. These findings highlight the value of diversity in genetic studies and have major implications for genomic medicine and therapeutic development in South Asian populations.

Visualizing genomes: techniques and challenges.

As our ability to generate sequencing data continues to increase, data analysis is replacing data generation as the rate-limiting step in genomics studies. Here we provide a guide to genomic data visualization tools that facilitate analysis tasks by enabling researchers to explore, interpret and manipulate their data, and in some cases perform on-the-fly computations. We will discuss graphical methods designed for the analysis of de novo sequencing assemblies and read alignments, genome browsing, and comparative genomics, highlighting the strengths and limitations of these approaches and the challenges ahead.

Analysis of eligibility criteria representation in industry-standard clinical trial protocols.

Previous research on standardization of eligibility criteria and its feasibility has traditionally been conducted on clinical trial protocols from ClinicalTrials.gov (CT). The portability and use of such standardization for full-text industry-standard protocols has not been studied in-depth. Towards this end, in this study we first compare the representation characteristics and textual complexity of a set of Pfizer's internal full-text protocols to their corresponding entries in CT. Next, we identify clusters of similar criteria sentences from both full-text and CT protocols and outline methods for standardized representation of eligibility criteria. We also study the distribution of eligibility criteria in full-text and CT protocols with respect to pre-defined semantic classes used for eligibility criteria classification. We find that in comparison to full-text protocols, CT protocols are not only more condensed but also convey less information. We also find no correlation between the variations in word-counts of the ClinicalTrials.gov and full-text protocols. While we identify 65 and 103 clusters of inclusion and exclusion criteria from full text protocols, our methods found only 36 and 63 corresponding clusters from CT protocols. For both the full-text and CT protocols we are able to identify 'templates' for standardized representations with full-text standardization being more challenging of the two. In our exploration of the semantic class distributions we find that the majority of the inclusion criteria from both full-text and CT protocols belong to the semantic class "Diagnostic and Lab Results" while "Disease, Sign or Symptom" forms the majority for exclusion criteria. Overall, we show that developing a template set of eligibility criteria for clinical trials, specifically in their full-text form, is feasible and could lead to more efficient clinical trial protocol design.