IMPORTANCEUnexplained sudden cardiac death (SCD) describes SCD with no cause identified. Genetic testing helps to diagnose inherited cardiac diseases in unexplained SCD; however, the associations between pathogenic or likely pathogenic (P/LP) variants of inherited cardiomyopathies (CMs) and arrhythmia syndromes and the risk of unexplained SCD in both White and African American adults living the United States has never been systematically examined.OBJECTIVE To investigate cases of unexplained SCD to determine the frequency of P/LP genetic variants of inherited CMs and arrhythmia syndromes. DESIGN, SETTING, AND PARTICIPANTSThis genetic association study included 683 African American and White adults who died of unexplained SCD and were included in an autopsy registry. Overall, 413 individuals had DNA of acceptable quality for genetic sequencing. Data were collected from January 1995 to December 2015. A total of 30 CM genes and 38 arrhythmia genes were sequenced, and variants in these genes, curated as P/LP, were examined to study their frequency. Data analysis was performed from June 2018 to March 2021. MAIN OUTCOMES AND MEASURESThe frequency of P/LP variants for CM or arrhythmia in individuals with unexplained SCD. RESULTSThe median (interquartile range) age at death of the 413 included individuals was 41 (29-48) years, 259 (62.7%) were men, and 208 (50.4%) were African American adults. A total of 76 patients (18.4%) with unexplained SCD carried variants considered P/LP for CM and arrhythmia genes. In total, 52 patients (12.6%) had 49 P/LP variants for CM, 22 (5.3%) carried 23 P/LP variants for arrhythmia, and 2 (0.5%) had P/LP variants for both CM and arrhythmia. Overall, 41 P/LP variants for hypertrophic CM were found in 45 patients (10.9%), 9 P/LP variants for dilated CM were found in 11 patients (2.7%), and 10 P/LP variants for long QT syndrome were found in 11 patients (2.7%). No significant difference was found in clinical and heart characteristics between individuals with or without P/LP variants. African American and White patients were equally likely to harbor P/LP variants. CONCLUSIONS AND RELEVANCEIn this large genetic association study of community cases of unexplained SCD, nearly 20% of patients carried P/LP variants, suggesting that genetics may contribute to a significant number of cases of unexplained SCD. Our findings regarding both the association of unexplained SCD with CM genes and race-specific genetic variants suggest new avenues of study for this poorly understood entity.

Genetic testing for monogenic diabetes, essential for accurate diagnosis and appropriate treatment is underutilized. Obstacles include clinical overlap with type 1 and type 2 diabetes and difficulty distinguishing clinically significant (pathogenic/likely pathogenic; P/LP) from normal (benign/likely benign; B/LB) variation. The ClinGen Monogenic Diabetes Expert Panel (MDEP) was formed to adapt American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant interpretation guidelines to monogenic diabetes genes and enable depositing of expert panel variant reviews into ClinVar, a public database relating gene variants to phenotypes. MDEP includes endocrinologists, laboratory directors, genetic counselors, medical geneticists, clinical scientists and researchers from 37 academic and commercial institutions, allowing the panel to benefit from multiple expert perspectives and pooling of case-level data. Currently, MDEP is focusing on the three most commonly implicated monogenic diabetes genes: GCK, HNF1A and HNF4A. MDEP generated gene-specific modifications and/or strength adjustments to existing rules to provide guidance for the use of evidence, including molecular, phenotypic, segregation, functional, and minor allele frequency data. Our guidelines have so far been tested on 98 HNF1A variants, 15 HNF4A variants and 22 GCK variants selected from ClinVar and the literature. Fourteen of 31 variants of uncertain significance (VUS) in ClinVar were re-classified: nine to P/LP (enabling diagnosis and treatment) and five to B/LB (reducing ambiguity). Six LP variants and one LB variant from ClinVar were re-classified to VUS (stimulating further surveillance). MDEP’s work will improve accuracy, standardization and concordance of variant interpretation for monogenic diabetes and support wider implementation of precision medicine in diabetes. Disclosure H. Zhang: None. K.A. Maloney: None. F. Barbetti: Consultant; Self; Amring. S.W. Greeley: None. J.L.T. Kettunen: None. J.P. Miranda: None. U.L. Mirshahi: None. J. Molnes: None. R. Murphy: None. R.N. Naylor: None. R.E. Pakyz: None. L.H. Philipson: None. S. Prudente: None. T. Tuomi: None. M. Udler: None. K. Colclough: None. L. Jeng: None. T.I. Pollin: None. Funding National Institutes of Health (5U24HD093486, R01DK104942, P30DK020595 )

Approximately 2% of diabetes mellitus, or at least 500,000 cases in the United States, has a monogenic, rather than multifactorial, etiology (Hattersley et al., 2018; Pihoker et al., 2013). The most common form of monogenic diabetes is maturity-onset diabetes of the young (MODY), followed by neonatal diabetes and syndromic forms (ADA, 2016; Hattersley et al., 2018). Treatment options and prognoses for certain types of monogenic diabetes are distinct from those for type 1 and type 2 diabetes (T1D and T2D). Molecular diagnosis of the

Background - In population-based research exome sequencing (ES), the path from variant discovery to return of results (rROR) is not well established. Variants discovered by research ES have the potential to improve population health. Methods - Population-based ES and agnostic ExWAS were performed 5,521 Amish individuals. Additional phenotyping and in vitro studies enabled reclassification of a KCNQ1 variant from VUS to pathogenic. Results were returned to participants in a community setting. Results - A missense variant was identified in KCNQ1 (c.671C>T, p.T224M), a gene associated with long QT syndrome (LQTS) type 1 (LQT1), which can cause syncope and sudden cardiac death (SCD). The p.T224M variant, present in 1/45 Amish individuals is rare in the general population (1/248,566 in gnomAD) and was highly associated with QTc on EKG (p = 5.53E-24, β=20.2 ms/allele). Because of the potential importance of this variant to the health of the population, additional phenotyping was performed in 88 p.T224M carriers and 54 non-carriers. There was stronger clinical evidence of LQTS in carriers (38.6% vs 5.5%, p = 0.0006), greater history of syncope (32% vs 17%, p = 0.020), and higher rate of SCD in 1 st degree relatives < age 30 (4.5% vs 0%, p = 0.026). Expression of p.T224M KCNQ1 in CHO cells showed near complete loss of protein function. Our clinical and functional data enabled reclassification of p.T224M from a variant of unknown significance (VUS) to pathogenic. Of the 88 carriers, 93% met criteria for beta-blocker treatment and 5/88 (5.7%) were on medications that may further prolong QTc. Carriers were provided a CLIA confirmed report, genetic counseling and treatment recommendations. Follow up care was coordinated with local physicians. Conclusions - This work provides a framework by which research ES can be rapidly translated in a culturally appropriate manner to directly benefit research participants and enable population precision health.

Founder populations may be enriched with certain genetic variants of high clinical impact compared to nonfounder populations due to bottleneck events and genetic drift. Using exome sequencing (ES), we quantified the load of pathogenic variants that may be clinically actionable in 6136 apparently healthy adults living in the Lancaster, PA Old Order Amish settlement. We focused on variants in 78 genes deemed clinically actionable by the American College of Medical Genetics and Genomics (ACMG) or Geisinger's MyCode Health Initiative. ES revealed 3191 total variants among these genes including 480 nonsynonymous variants. After quality control and filtering, we applied the ACMG/AMP guidelines for variant interpretation and classified seven variants, across seven genes, as either pathogenic or likely pathogenic. Through genetic drift, all seven variants, are highly enriched in the Amish compared to nonfounder populations. In total, 14.7% of Lancaster Amish individuals carry at least one of these variants, largely explained by the 13% who harbor a copy of a single variant in APOB. Other studies report combined frequencies of pathogenic/likely pathogenic (P/LP) variants in actionable genes between 2.0% and 6.2% in outbred populations. The Amish population harbors fewer actionable variants compared to similarly characterized nonfounder populations but have a higher frequency of each variant identified, offering opportunities for efficient and cost‐effective targeted precision medicine.

OBJECTIVE To implement, disseminate, and evaluate a sustainable method for identifying, diagnosing, and promoting individualized therapy for monogenic diabetes. RESEARCH DESIGN AND METHODS Patients were recruited into the implementation study through a screening questionnaire completed in the waiting room or through the patient portal, physician recognition, or self-referral. Patients suspected of having monogenic diabetes based on the processing of their questionnaire and other data through an algorithm underwent next-generation sequencing for 40 genes implicated in monogenic diabetes and related conditions. RESULTS Three hundred thirteen probands with suspected monogenic diabetes (but most diagnosed with type 2 diabetes) were enrolled from October 2014 to January 2019. Sequencing identified 38 individuals with monogenic diabetes, with most variants found in GCK or HNF1A. Positivity rates for ascertainment methods were 3.1% for clinic screening, 5.3% for electronic health record portal screening, 16.5% for physician recognition, and 32.4% for self-referral. The algorithmic criterion of non–type 1 diabetes before age 30 years had an overall positivity rate of 15.0%. CONCLUSIONS We successfully modeled the efficient incorporation of monogenic diabetes diagnosis into the diabetes care setting, using multiple strategies to screen and identify a subpopulation with a 12.1% prevalence of monogenic diabetes by molecular testing. Self-referral was particularly efficient (32% prevalence), suggesting that educating the lay public in addition to clinicians may be the most effective way to increase the diagnosis rate in monogenic diabetes. Scaling up this model will assure access to diagnosis and customized treatment among those with monogenic diabetes and, more broadly, access to personalized medicine across disease areas.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier will develop the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we applied clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias displayed effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers averaged below 60% in both studies for all conditions except monogenic diabetes. We assessed additional epidemiologic and genetic factors contributing to risk prediction, demonstrating that inclusion of common polygenic variation significantly improved biomarker estimation for two monogenic dyslipidemias.

Diagnosing and distinguishing monogenic diabetes, including some MODY (maturity-onset diabetes of the young), from type 1 or type 2 diabetes can have profound clinical implications: sulfonylureas vs. insulin or metformin for HNF1A- and HNF4A- diabetes, and no treatment for GCK-diabetes. Since 1996, the number of monogenic diabetes genes has expanded from three to 60 or more, with 14 called MODY genes; however newer evidence has called some of these gene associations into question. Monogenic diabetes is currently underdiagnosed, but the decreasing cost of sequencing and the ability to create multi-gene next-generation sequencing panels may increase access to testing and a proper diagnosis. For the testing to be useful, it is important that the genes chosen for these panels have appropriate evidence as causal genes. The NIH Clinical Genome Resource (ClinGen) Monogenic Diabetes Gene Curation Expert Panel was convened to bring together experts in clinical and laboratory aspects of monogenic diabetes and gene curation to publish curations for the ClinGen website based on evidence from clinical and molecular studies and population databases. To date, we have published evidence-based gene curation summaries for Gene-Disease Validity for HNF1A and HNF4A (both classified as Definitive for monogenic diabetes) and are in the process of curating and publishing curations for GCK (Definitive for monogenic diabetes), INS (Definitive for monogenic diabetes and permanent neonatal diabetes), HNF1B (Definitive for renal cysts and diabetes), and KLF11 (Disputed for monogenic diabetes due to limited evidence and high population frequencies of variants previously asserted as causative). Curation of additional genes is in progress. Accurate curations will inform appropriate testing panel content to reduce ambiguous results and assure variants identified are clinically relevant for informing the care of diabetes in patients and their families. Disclosure T.I. Pollin: None. M.A. Mayers: None. S.W. Greeley: None. K.A. Maloney: None. R.N. Naylor: None. R.E. Pakyz: None. K.A. Patel: None. M. Udler: None. H. Zhang: None. K. Colclough: None. C. Thaxton: None. Funding National Institutes of Health (U24HD093486)