A loss-of-function variant in HSD17B13 was associated with a reduced risk of chronic liver disease and of progression from steatosis to steatohepatitis. (Funded by Regeneron Pharmaceuticals and others.).

BackgroundMutations in PKD1 or PKD2 cause typical autosomal dominant polycystic kidney disease (ADPKD), the most common monogenic kidney disease. Dominantly inherited polycystic kidney and liver diseases on the ADPKD spectrum are also caused by mutations in at least six other genes required for protein biogenesis in the endoplasmic reticulum, the loss of which results in defective production of the PKD1 gene product, the membrane protein polycystin-1 (PC1).MethodsWe used whole-exome sequencing in a cohort of 122 patients with genetically unresolved clinical diagnosis of ADPKD or polycystic liver disease to identify a candidate gene, ALG9, and in vitro cell-based assays of PC1 protein maturation to functionally validate it. For further validation, we identified carriers of ALG9 loss-of-function mutations and noncarrier matched controls in a large exome-sequenced population-based cohort and evaluated the occurrence of polycystic phenotypes in both groups.ResultsTwo patients in the clinically defined cohort had rare loss-of-function variants in ALG9, which encodes a protein required for addition of specific mannose molecules to the assembling N-glycan precursors in the endoplasmic reticulum lumen. In vitro assays showed that inactivation of Alg9 results in impaired maturation and defective glycosylation of PC1. Seven of the eight (88%) cases selected from the population-based cohort based on ALG9 mutation carrier state who had abdominal imaging after age 50; seven (88%) had at least four kidney cysts, compared with none in matched controls without ALG9 mutations.ConclusionsALG9 is a novel disease gene in the genetically heterogeneous ADPKD spectrum. This study supports the utility of phenotype characterization in genetically-defined cohorts to validate novel disease genes, and provide much-needed genotype-phenotype correlations.

Background Empirical data on conditions that increase risk of coronavirus disease 2019 (COVID-19) progression are needed to identify high risk individuals. We performed a comprehensive quantitative assessment of pre-existing clinical phenotypes associated with COVID-19-related hospitalization. Methods Phenome-wide association study (PheWAS) of SARS-CoV-2-positive patients from an integrated health system (Geisinger) with system-level outpatient/inpatient COVID-19 testing capacity and retrospective electronic health record (EHR) data to assess pre-COVID-19 pandemic clinical phenotypes associated with hospital admission (hospitalization). Results Of 12,971 individuals tested for SARS-CoV-2 with sufficient pre-COVID-19 pandemic EHR data at Geisinger, 1604 were SARS-CoV-2 positive and 354 required hospitalization. We identified 21 clinical phenotypes in 5 disease categories meeting phenome-wide significance (P<1.60x10-4), including: six kidney phenotypes, e.g. end stage renal disease or stage 5 CKD (OR = 11.07, p = 1.96x10-8), six cardiovascular phenotypes, e.g. congestive heart failure (OR = 3.8, p = 3.24x10-5), five respiratory phenotypes, e.g. chronic airway obstruction (OR = 2.54, p = 3.71x10-5), and three metabolic phenotypes, e.g. type 2 diabetes (OR = 1.80, p = 7.51x10-5). Additional analyses defining CKD based on estimated glomerular filtration rate, confirmed high risk of hospitalization associated with pre-existing stage 4 CKD (OR 2.90, 95% CI: 1.47, 5.74), stage 5 CKD/dialysis (OR 8.83, 95% CI: 2.76, 28.27), and kidney transplant (OR 14.98, 95% CI: 2.77, 80.8) but not stage 3 CKD (OR 1.03, 95% CI: 0.71, 1.48). Conclusions This study provides quantitative estimates of the contribution of pre-existing clinical phenotypes to COVID-19 hospitalization and highlights kidney disorders as the strongest factors associated with hospitalization in an integrated US healthcare system.

Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10−09), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin βE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.

Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results (RoR) is unclear. In addition, the majority of discovered variants are currently classified as Variants of Uncertain Significance (VUS), limiting clinical actionability. Methods: The eMERGE-III study is a multi-center prospective cohort which included 21,846 participants without prior indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with Electronic Health Record (EHR)-derived phenotypes and follow-up clinical examination. Selected VUS (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had pathogenic or likely pathogenic (P/LP) variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared to non-carriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their EHRs. Fifty four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long QT syndrome), and 12/19 of these diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance (VUS), we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, EHR phenotypes, and in vitro functional studies.