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Article ; Online: Adjusting for common variant polygenic scores improves yield in rare variant association analyses.

Jurgens, Sean J / Pirruccello, James P / Choi, Seung Hoan / Morrill, Valerie N / Chaffin, Mark / Lubitz, Steven A / Lunetta, Kathryn L / Ellinor, Patrick T

Nature genetics

2023 Volume 55, Issue 4, Page(s) 544–548

Abstract: With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests ... ...

Abstract	With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10
MeSH term(s)	Multifactorial Inheritance/genetics ; Phenotype ; Quantitative Trait Loci ; Polymorphism, Single Nucleotide/genetics ; Models, Genetic ; Genome-Wide Association Study
Language	English
Publishing date	2023-03-23
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-023-01342-w
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Article ; Online: Lipid levels and risk of acute pancreatitis using bidirectional Mendelian randomization.

Wang, Biqi / Dron, Jacqueline S / Wang, Yuxuan / Choi, Seung Hoan / Huffman, Jennifer E / Cho, Kelly / Wilson, Peter W F / Natarajan, Pradeep / Peloso, Gina M

Scientific reports

2024 Volume 14, Issue 1, Page(s) 6267

Abstract: Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol ...

Abstract	Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22-3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76-0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = - 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment.
MeSH term(s)	Humans ; Genome-Wide Association Study/methods ; Mendelian Randomization Analysis/methods ; Acute Disease ; Pancreatitis/genetics ; Polymorphism, Single Nucleotide ; Triglycerides ; Risk Factors ; Cholesterol, LDL/genetics ; Cholesterol, HDL/genetics
Chemical Substances	Triglycerides ; Cholesterol, LDL ; Cholesterol, HDL
Language	English
Publishing date	2024-03-15
Publishing country	England
Document type	Meta-Analysis ; Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-56946-x
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Article ; Online: Thrombosis Risk in Double Heterozygous Carriers of Factor V Leiden and Prothrombin G20210A in FinnGen and the UK Biobank.

Ryu, Justine / Rämö, Joel T / Jurgens, Sean Joseph / Niiranen, Teemu / Sanna-Cherchi, Simone / Bauer, Kenneth A / Haj, Amelia / Choi, Seung Hoan / Palotie, Aarno / Daly, Mark / Ellinor, Patrick T / Bendapudi, Pavan K

Blood

2024

Abstract: The Factor V Leiden (FVL, rs6025) and prothrombin G20210A (PTGM, rs1799963) polymorphisms are two of the most well-studied genetic risk factors for venous thromboembolism (VTE). However, double heterozygosity (DH) for FVL and PTGM remains poorly ... ...

Abstract	The Factor V Leiden (FVL, rs6025) and prothrombin G20210A (PTGM, rs1799963) polymorphisms are two of the most well-studied genetic risk factors for venous thromboembolism (VTE). However, double heterozygosity (DH) for FVL and PTGM remains poorly understood, with prior studies in marked disagreement about the thrombosis risk conferred by the DH genotype. Utilizing multi-dimensional data from the UK Biobank (UKB) and the FinnGen biorepositories, we evaluated the clinical impact of DH carrier status across 937,939 individuals. We found that 662 participants (0.07%) were DH carriers. After adjustment for age, sex, and ancestry, DH individuals experienced a markedly elevated risk of VTE compared to wild-type individuals (OR=5.24, 95% CI: 4.01 - 6.84; P=4.8 x 10-34), which approximated the risk conferred by FVL homozygosity. A secondary analysis restricted to UKB participants (N=445,144) found that effect size estimates for the DH genotype remained largely unchanged (OR=4.53, 95% CI: 3.42 - 5.90; P<1 x 10-16) after adjustment for commonly cited VTE risk factors such as body mass index, blood type, and markers of inflammation. By contrast, the DH genotype was not associated with a significantly higher risk of any arterial thrombosis phenotype, including stroke, myocardial infarction, and peripheral artery disease. In summary, we leveraged population-scale genomic datasets to conduct the largest study to date of the DH genotype and were able to establish far more precise effect size estimates than previously possible. Our findings indicate that the DH genotype may occur as frequently as FVL homozygosity and confers a similarly increased risk of VTE.
Language	English
Publishing date	2024-03-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	80069-7
ISSN	1528-0020 ; 0006-4971
ISSN (online)	1528-0020
ISSN	0006-4971
DOI	10.1182/blood.2023023326
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Article ; Online: Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data.

Wang, Yanbing / Sarnowski, Chloé / Lin, Honghuang / Pitsillides, Achilleas N / Heard-Costa, Nancy L / Choi, Seung Hoan / Wang, Dongyu / Bis, Joshua C / Blue, Elizabeth E / Boerwinkle, Eric / De Jager, Philip L / Fornage, Myriam / Wijsman, Ellen M / Seshadri, Sudha / Dupuis, Josée / Peloso, Gina M / DeStefano, Anita L

Alzheimer's & dementia : the journal of the Alzheimer's Association

2024

Abstract: Introduction: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates ...

Abstract	Introduction: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. Methods: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. Results: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. Discussion: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.
Language	English
Publishing date	2024-03-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2211627-8
ISSN	1552-5279 ; 1552-5260
ISSN (online)	1552-5279
ISSN	1552-5260
DOI	10.1002/alz.13705
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Zs.MO 540: Show issues

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Article ; Online: Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program.

Wang, Xin / Ryu, Justine / Kim, Jihoon / Ramirez, Andrea / Mayo, Kelsey R / Condon, Henry / Vaitinadin, Nataraja Sarma / Ohno-Machado, Lucila / Talavera, Greg A / Ellinor, Patrick T / Lubitz, Steven A / Choi, Seung Hoan

Journal of human genetics

2023 Volume 68, Issue 8, Page(s) 565–570

Abstract: All of Us is a biorepository aiming to advance biomedical research by providing various types of data in diverse human populations. Here we present a demonstration project validating the program's genomic data in 98,622 participants. We sought to ... ...

Abstract	All of Us is a biorepository aiming to advance biomedical research by providing various types of data in diverse human populations. Here we present a demonstration project validating the program's genomic data in 98,622 participants. We sought to replicate known genetic associations for three diseases (atrial fibrillation [AF], coronary artery disease, type 2 diabetes [T2D]) and two quantitative traits (height and low-density lipoprotein [LDL]) by conducting common and rare variant analyses. We identified one known risk locus for AF, five loci for T2D, 143 loci for height, and nine loci for LDL. In gene-based burden tests for rare loss-of-function variants, we replicated associations between TTN and AF, GIGYF1 and T2D, ADAMTS17, ACAN, NPR2 and height, APOB, LDLR, PCSK9 and LDL. Our results are consistent with previous literature, indicating that the All of Us program is a reliable resource for advancing the understanding of complex diseases in diverse human populations.
MeSH term(s)	Humans ; Proprotein Convertase 9/genetics ; Diabetes Mellitus, Type 2/epidemiology ; Diabetes Mellitus, Type 2/genetics ; Population Health ; Coronary Artery Disease/epidemiology ; Coronary Artery Disease/genetics ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Carrier Proteins/genetics
Chemical Substances	PCSK9 protein, human (EC 3.4.21.-) ; Proprotein Convertase 9 (EC 3.4.21.-) ; GIGYF1 protein, human ; Carrier Proteins
Language	English
Publishing date	2023-04-18
Publishing country	England
Document type	Journal Article
ZDB-ID	1425192-9
ISSN	1435-232X ; 1434-5161
ISSN (online)	1435-232X
ISSN	1434-5161
DOI	10.1038/s10038-023-01147-z
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Article ; Online: Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms.

Wang, Xin / Khurshid, Shaan / Choi, Seung Hoan / Friedman, Samuel / Weng, Lu-Chen / Reeder, Christopher / Pirruccello, James P / Singh, Pulkit / Lau, Emily S / Venn, Rachael / Diamant, Nate / Di Achille, Paolo / Philippakis, Anthony / Anderson, Christopher D / Ho, Jennifer E / Ellinor, Patrick T / Batra, Puneet / Lubitz, Steven A

Circulation. Genomic and precision medicine

2023 Volume 16, Issue 4, Page(s) 340–349

Abstract: Background: Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well ... ...

Abstract	Background: Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well understood. We hypothesized that there might be a genetic basis for an AI algorithm for predicting the 5-year risk of new-onset AF using 12-lead ECGs (ECG-AI)-based risk estimates. Methods: We applied a validated ECG-AI model for predicting incident AF to ECGs from 39 986 UK Biobank participants without AF. We then performed a genome-wide association study (GWAS) of the predicted AF risk and compared it with an AF GWAS and a GWAS of risk estimates from a clinical variable model. Results: In the ECG-AI GWAS, we identified 3 signals ( Conclusions: Predicted AF risk from an ECG-AI model is influenced by genetic variation implicating sarcomeric, ion channel and body height pathways. ECG-AI models may identify individuals at risk for disease via specific biological pathways.
MeSH term(s)	Humans ; Atrial Fibrillation/diagnosis ; Atrial Fibrillation/genetics ; Genetic Predisposition to Disease ; Artificial Intelligence ; Genome-Wide Association Study ; Deep Learning ; Electrocardiography
Language	English
Publishing date	2023-06-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ISSN	2574-8300
ISSN (online)	2574-8300
DOI	10.1161/CIRCGEN.122.003808
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Article ; Online: Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass.

Khurshid, Shaan / Lazarte, Julieta / Pirruccello, James P / Weng, Lu-Chen / Choi, Seung Hoan / Hall, Amelia W / Wang, Xin / Friedman, Samuel F / Nauffal, Victor / Biddinger, Kiran J / Aragam, Krishna G / Batra, Puneet / Ho, Jennifer E / Philippakis, Anthony A / Ellinor, Patrick T / Lubitz, Steven A

Nature communications

2023 Volume 14, Issue 1, Page(s) 1558

Abstract: Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use ... ...

Abstract	Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90
MeSH term(s)	Humans ; Genome-Wide Association Study ; Deep Learning ; Magnetic Resonance Imaging, Cine ; Cardiomyopathies ; Magnetic Resonance Spectroscopy ; Predictive Value of Tests
Language	English
Publishing date	2023-03-21
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-37173-w
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Article: Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data.

medRxiv : the preprint server for health sciences

2023

Abstract	Introduction: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. Methods: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases=2,184, N controls=2,383) and targeted analyses in sub-populations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. Results: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. Discussion: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.
Language	English
Publishing date	2023-08-29
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.28.23294631
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Article ; Online: The Genetic Determinants of Aortic Distention.

Pirruccello, James P / Rämö, Joel T / Choi, Seung Hoan / Chaffin, Mark D / Kany, Shinwan / Nekoui, Mahan / Chou, Elizabeth L / Jurgens, Sean J / Friedman, Samuel F / Juric, Dejan / Stone, James R / Batra, Puneet / Ng, Kenney / Philippakis, Anthony A / Lindsay, Mark E / Ellinor, Patrick T

Journal of the American College of Cardiology

2023 Volume 81, Issue 14, Page(s) 1320–1335

Abstract: Background: As the largest conduit vessel, the aorta is responsible for the conversion of phasic systolic inflow from ventricular ejection into more continuous peripheral blood delivery. Systolic distention and diastolic recoil conserve energy and are ... ...

Abstract	Background: As the largest conduit vessel, the aorta is responsible for the conversion of phasic systolic inflow from ventricular ejection into more continuous peripheral blood delivery. Systolic distention and diastolic recoil conserve energy and are enabled by the specialized composition of the aortic extracellular matrix. Aortic distensibility decreases with age and vascular disease. Objectives: In this study, we sought to discover epidemiologic correlates and genetic determinants of aortic distensibility and strain. Methods: We trained a deep learning model to quantify thoracic aortic area throughout the cardiac cycle from cardiac magnetic resonance images and calculated aortic distensibility and strain in 42,342 UK Biobank participants. Results: Descending aortic distensibility was inversely associated with future incidence of cardiovascular diseases, such as stroke (HR: 0.59 per SD; P = 0.00031). The heritabilities of aortic distensibility and strain were 22% to 25% and 30% to 33%, respectively. Common variant analyses identified 12 and 26 loci for ascending and 11 and 21 loci for descending aortic distensibility and strain, respectively. Of the newly identified loci, 22 were not significantly associated with thoracic aortic diameter. Nearby genes were involved in elastogenesis and atherosclerosis. Aortic strain and distensibility polygenic scores had modest effect sizes for predicting cardiovascular outcomes (delaying or accelerating disease onset by 2%-18% per SD change in scores) and remained statistically significant predictors after accounting for aortic diameter polygenic scores. Conclusions: Genetic determinants of aortic function influence risk for stroke and coronary artery disease and may lead to novel targets for medical intervention.
MeSH term(s)	Humans ; Aorta, Thoracic ; Aorta ; Aortic Diseases/pathology ; Magnetic Resonance Imaging ; Stroke
Language	English
Publishing date	2023-04-03
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	605507-2
ISSN	1558-3597 ; 0735-1097
ISSN (online)	1558-3597
ISSN	0735-1097
DOI	10.1016/j.jacc.2023.01.044
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Article ; Online: Rare and Common Genetic Variation Underlying the Risk of Hypertrophic Cardiomyopathy in a National Biobank.

Biddinger, Kiran J / Jurgens, Sean J / Maamari, Dimitri / Gaziano, Liam / Choi, Seung Hoan / Morrill, Valerie N / Halford, Jennifer L / Khera, Amit V / Lubitz, Steven A / Ellinor, Patrick T / Aragam, Krishna G

JAMA cardiology

2022 Volume 7, Issue 7, Page(s) 715–722

Abstract: Importance: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in young people. Although rare genetic variants are well-established contributors to HCM risk, common genetic variants have recently been implicated in disease ... ...

Abstract	Importance: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in young people. Although rare genetic variants are well-established contributors to HCM risk, common genetic variants have recently been implicated in disease pathogenesis. Objective: To assess the contributions of rare and common genetic variation to risk of HCM in the general population. Design, setting, and participants: This cohort study of the UK Biobank (data from 2006-2010) and the Mass General Brigham Biobank (2010-2019) assessed the relative and joint contributions of rare genetic variants and a common variant (polygenic) score to risk of HCM. Both rare and common variant predictors were then evaluated in the context of relevant clinical risk factors. Data analysis was conducted from May 2021 to February 2022. Exposures: Pathogenic rare variants, common-variant (polygenic) score, and clinical risk factors. Main outcomes and measures: Risk of HCM. Results: The primary study population comprised 184 511 individuals from the UK Biobank. Mean (SD) age was 56 (8) years, 83 690 (45%) of participants were men, and 204 (0.1%) participants had HCM. Of 51 genes included in clinical genetic testing panels for HCM, pathogenic or likely pathogenic variants in 14 core genes (designated by the American College of Medical Genetics and Genomics [ACMG]) were associated with 55-fold higher odds (95% CI, 35-83) of HCM, while those in the remaining 37 non-ACMG genes were not significantly associated with HCM (OR, 1.8; 95% CI, 0.6-4.0). ClinVar pathogenic or likely pathogenic mutations in MYBPC3 (OR, 72; 95% CI, 39-124) and MYH7 (OR, 61; 95% CI, 26-121) were strongly associated with HCM, as were loss-of-function variants in ALPK3 (OR, 13; 95% CI, 4.4-28). A polygenic score was strongly associated with HCM (OR per SD increase in score, 1.6; 95% CI, 1.4-1.8), with concordant results in the Mass General Brigham Biobank. Genetic factors enhanced clinical risk prediction for HCM: addition of rare variant carrier status and the polygenic score to clinical risk factors (obesity, hypertension, atrial fibrillation, and coronary artery disease) improved the area under the receiver operator characteristic curve from 0.71 (95% CI, 0.65-0.77) to 0.82 (95% CI, 0.77-0.87). Conclusions and relevance: Both rare and common genetic variants contribute substantially to HCM susceptibility in the general population and improve HCM risk prediction beyond that achieved with clinical factors.
MeSH term(s)	Adolescent ; Biological Specimen Banks ; Cardiomyopathy, Hypertrophic/genetics ; Cohort Studies ; Death, Sudden, Cardiac ; Female ; Humans ; Male ; Middle Aged ; Mutation
Language	English
Publishing date	2022-05-18
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2380-6591
ISSN (online)	2380-6591
DOI	10.1001/jamacardio.2022.1061
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