@article {9167, title = {Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes.}, journal = {Nat Commun}, volume = {13}, year = {2022}, month = {2022 08 30}, pages = {5106}, abstract = {

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P < 0.001 for each trait) and discriminate pathogenic from non-pathogenic variants (area under the curve 0.82-0.84 across endophenotypes). An effect size threshold of >= 0.5 times the endophenotype standard deviation nominates up to 35\% of rare variants of uncertain significance or not in ClinVar in disease susceptibility genes with pathogenic potential. We propose that variant associations with quantitative endophenotypes for monogenic diseases can provide evidence supporting pathogenicity.

}, keywords = {Disease Susceptibility, Endophenotypes, Humans, Long QT Syndrome, Virulence}, issn = {2041-1723}, doi = {10.1038/s41467-022-32009-5}, author = {Halford, Jennifer L and Morrill, Valerie N and Choi, Seung Hoan and Jurgens, Sean J and Melloni, Giorgio and Marston, Nicholas A and Weng, Lu-Chen and Nauffal, Victor and Hall, Amelia W and Gunn, Sophia and Austin-Tse, Christina A and Pirruccello, James P and Khurshid, Shaan and Rehm, Heidi L and Benjamin, Emelia J and Boerwinkle, Eric and Brody, Jennifer A and Correa, Adolfo and Fornwalt, Brandon K and Gupta, Namrata and Haggerty, Christopher M and Harris, Stephanie and Heckbert, Susan R and Hong, Charles C and Kooperberg, Charles and Lin, Henry J and Loos, Ruth J F and Mitchell, Braxton D and Morrison, Alanna C and Post, Wendy and Psaty, Bruce M and Redline, Susan and Rice, Kenneth M and Rich, Stephen S and Rotter, Jerome I and Schnatz, Peter F and Soliman, Elsayed Z and Sotoodehnia, Nona and Wong, Eugene K and Sabatine, Marc S and Ruff, Christian T and Lunetta, Kathryn L and Ellinor, Patrick T and Lubitz, Steven A} } @article {9100, title = {A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.}, journal = {Nat Commun}, volume = {13}, year = {2022}, month = {2022 Jun 21}, pages = {3549}, abstract = {

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

}, keywords = {Adult, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hypertension, Multifactorial Inheritance, Prevalence, Risk Factors}, issn = {2041-1723}, doi = {10.1038/s41467-022-31080-2}, author = {Kurniansyah, Nuzulul and Goodman, Matthew O and Kelly, Tanika N and Elfassy, Tali and Wiggins, Kerri L and Bis, Joshua C and Guo, Xiuqing and Palmas, Walter and Taylor, Kent D and Lin, Henry J and Haessler, Jeffrey and Gao, Yan and Shimbo, Daichi and Smith, Jennifer A and Yu, Bing and Feofanova, Elena V and Smit, Roelof A J and Wang, Zhe and Hwang, Shih-Jen and Liu, Simin and Wassertheil-Smoller, Sylvia and Manson, JoAnn E and Lloyd-Jones, Donald M and Rich, Stephen S and Loos, Ruth J F and Redline, Susan and Correa, Adolfo and Kooperberg, Charles and Fornage, Myriam and Kaplan, Robert C and Psaty, Bruce M and Rotter, Jerome I and Arnett, Donna K and Morrison, Alanna C and Franceschini, Nora and Levy, Daniel and Sofer, Tamar} } @article {9161, title = {Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations.}, journal = {Commun Biol}, volume = {5}, year = {2022}, month = {2022 08 22}, pages = {856}, abstract = {

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to the standard, linear PRS model developed using PRSice, LDpred2, and lassosum2. Combining a PRS as a feature in an XGBoost model results in a relative increase in the percentage variance explained compared to the standard linear PRS model by 22\% for height, 27\% for HDL cholesterol, 43\% for body mass index, 50\% for sleep duration, 58\% for systolic blood pressure, 64\% for total cholesterol, 66\% for triglycerides, 77\% for LDL cholesterol, and 100\% for diastolic blood pressure. Multi-ancestry trained models perform similarly to specific racial/ethnic group trained models and are consistently superior to the standard linear PRS models. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.

}, keywords = {Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Machine Learning, Multifactorial Inheritance, Polymorphism, Single Nucleotide}, issn = {2399-3642}, doi = {10.1038/s42003-022-03812-z}, author = {Elgart, Michael and Lyons, Genevieve and Romero-Brufau, Santiago and Kurniansyah, Nuzulul and Brody, Jennifer A and Guo, Xiuqing and Lin, Henry J and Raffield, Laura and Gao, Yan and Chen, Han and de Vries, Paul and Lloyd-Jones, Donald M and Lange, Leslie A and Peloso, Gina M and Fornage, Myriam and Rotter, Jerome I and Rich, Stephen S and Morrison, Alanna C and Psaty, Bruce M and Levy, Daniel and Redline, Susan and Sofer, Tamar} } @article {9379, title = {Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups.}, journal = {Nat Commun}, volume = {14}, year = {2023}, month = {2023 Jun 02}, pages = {3202}, abstract = {

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

}, keywords = {Blood Pressure, Ethnicity, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Multifactorial Inheritance, Population Health, Risk Factors}, issn = {2041-1723}, doi = {10.1038/s41467-023-38990-9}, author = {Kurniansyah, Nuzulul and Goodman, Matthew O and Khan, Alyna T and Wang, Jiongming and Feofanova, Elena and Bis, Joshua C and Wiggins, Kerri L and Huffman, Jennifer E and Kelly, Tanika and Elfassy, Tali and Guo, Xiuqing and Palmas, Walter and Lin, Henry J and Hwang, Shih-Jen and Gao, Yan and Young, Kendra and Kinney, Gregory L and Smith, Jennifer A and Yu, Bing and Liu, Simin and Wassertheil-Smoller, Sylvia and Manson, JoAnn E and Zhu, Xiaofeng and Chen, Yii-Der Ida and Lee, I-Te and Gu, C Charles and Lloyd-Jones, Donald M and Z{\"o}llner, Sebastian and Fornage, Myriam and Kooperberg, Charles and Correa, Adolfo and Psaty, Bruce M and Arnett, Donna K and Isasi, Carmen R and Rich, Stephen S and Kaplan, Robert C and Redline, Susan and Mitchell, Braxton D and Franceschini, Nora and Levy, Daniel and Rotter, Jerome I and Morrison, Alanna C and Sofer, Tamar} } @article {9322, title = {Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.}, journal = {Nat Commun}, volume = {14}, year = {2023}, month = {2023 Mar 14}, pages = {1411}, abstract = {

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration.~Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism~and~genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle~and~their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

}, keywords = {Arrhythmias, Cardiac, Atrioventricular Block, Biomarkers, Cardiovascular Diseases, Electrocardiography, Genome-Wide Association Study, Humans, Risk Factors}, issn = {2041-1723}, doi = {10.1038/s41467-023-36997-w}, author = {Young, William J and Haessler, Jeffrey and Benjamins, Jan-Walter and Repetto, Linda and Yao, Jie and Isaacs, Aaron and Harper, Andrew R and Ramirez, Julia and Garnier, Sophie and Van Duijvenboden, Stefan and Baldassari, Antoine R and Concas, Maria Pina and Duong, ThuyVy and Foco, Luisa and Isaksen, Jonas L and Mei, Hao and Noordam, Raymond and Nursyifa, Casia and Richmond, Anne and Santolalla, Meddly L and Sitlani, Colleen M and Soroush, Negin and Th{\'e}riault, S{\'e}bastien and Trompet, Stella and Aeschbacher, Stefanie and Ahmadizar, Fariba and Alonso, Alvaro and Brody, Jennifer A and Campbell, Archie and Correa, Adolfo and Darbar, Dawood and De Luca, Antonio and Deleuze, Jean-Francois and Ellervik, Christina and Fuchsberger, Christian and Goel, Anuj and Grace, Christopher and Guo, Xiuqing and Hansen, Torben and Heckbert, Susan R and Jackson, Rebecca D and Kors, Jan A and Lima-Costa, Maria Fernanda and Linneberg, Allan and Macfarlane, Peter W and Morrison, Alanna C and Navarro, Pau and Porteous, David J and Pramstaller, Peter P and Reiner, Alexander P and Risch, Lorenz and Schotten, Ulrich and Shen, Xia and Sinagra, Gianfranco and Soliman, Elsayed Z and Stoll, Monika and Tarazona-Santos, Eduardo and Tinker, Andrew and Trajanoska, Katerina and Villard, Eric and Warren, Helen R and Whitsel, Eric A and Wiggins, Kerri L and Arking, Dan E and Avery, Christy L and Conen, David and Girotto, Giorgia and Grarup, Niels and Hayward, Caroline and Jukema, J Wouter and Mook-Kanamori, Dennis O and Olesen, Morten Salling and Padmanabhan, Sandosh and Psaty, Bruce M and Pattaro, Cristian and Ribeiro, Antonio Luiz P and Rotter, Jerome I and Stricker, Bruno H and van der Harst, Pim and van Duijn, Cornelia M and Verweij, Niek and Wilson, James G and Orini, Michele and Charron, Philippe and Watkins, Hugh and Kooperberg, Charles and Lin, Henry J and Wilson, James F and Kanters, J{\o}rgen K and Sotoodehnia, Nona and Mifsud, Borbala and Lambiase, Pier D and Tereshchenko, Larisa G and Munroe, Patricia B} } @article {9914, title = {Meta-analysis of genome-wide associations and polygenic risk prediction for atrial fibrillation in more than 180,000 cases.}, journal = {Nat Genet}, volume = {57}, year = {2025}, month = {2025 Mar}, pages = {539-547}, abstract = {

Atrial fibrillation (AF) is the most common heart rhythm abnormality and is a leading cause of heart failure and stroke. This large-scale meta-analysis of genome-wide association studies increased the power to detect single-nucleotide variant associations and found more than 350 AF-associated genetic loci. We identified candidate genes related to muscle contractility, cardiac muscle development and cell-cell communication at 139 loci. Furthermore, we assayed chromatin accessibility using assay for transposase-accessible chromatin with sequencing and histone H3 lysine 4 trimethylation in stem cell-derived atrial cardiomyocytes. We observed a marked increase in chromatin accessibility for our sentinel variants and prioritized genes in atrial cardiomyocytes. Finally, a polygenic risk score (PRS) based on our updated effect estimates improved AF risk prediction compared to the CHARGE-AF clinical risk score and a previously reported PRS for AF. The doubling of known risk loci will facilitate a greater understanding of the pathways underlying AF.

}, keywords = {Atrial Fibrillation, Chromatin, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Multifactorial Inheritance, Myocytes, Cardiac, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-1718}, doi = {10.1038/s41588-024-02072-3}, author = {Roselli, Carolina and Surakka, Ida and Olesen, Morten S and Sveinbjornsson, Gardar and Marston, Nicholas A and Choi, Seung Hoan and Holm, Hilma and Chaffin, Mark and Gudbjartsson, Daniel and Hill, Matthew C and Aegisdottir, Hildur and Albert, Christine M and Alonso, Alvaro and Anderson, Christopher D and Arking, Dan E and Arnar, David O and Barnard, John and Benjamin, Emelia J and Braunwald, Eugene and Brumpton, Ben and Campbell, Archie and Chami, Nathalie and Chasman, Daniel I and Cho, Kelly and Choi, Eue-Keun and Christophersen, Ingrid E and Chung, Mina K and Conen, David and Crijns, Harry J and Cutler, Michael J and Czuba, Tomasz and Damrauer, Scott M and Dichgans, Martin and D{\"o}rr, Marcus and Dudink, Elton and Duong, ThuyVy and Erikstrup, Christian and Esko, T{\~o}nu and Fatkin, Diane and Faul, Jessica D and Ferreira, Manuel and Freitag, Daniel F and Ganesh, Santhi K and Gaziano, J Michael and Geelhoed, Bastiaan and Ghouse, Jonas and Gieger, Christian and Giulianini, Franco and Graham, Sarah E and Gudnason, Vilmundur and Guo, Xiuqing and Haggerty, Christopher and Hayward, Caroline and Heckbert, Susan R and Hveem, Kristian and Ito, Kaoru and Johnson, Renee and Jukema, J Wouter and Jurgens, Sean J and K{\"a}{\"a}b, Stefan and Kane, John P and Kany, Shinwan and Kardia, Sharon L R and Kavousi, Maryam and Khurshid, Shaan and Kamanu, Frederick K and Kirchhof, Paulus and Kleber, Marcus E and Knight, Stacey and Komuro, Issei and Krieger, Jose E and Launer, Lenore J and Li, Dadong and Lin, Honghuang and Lin, Henry J and Loos, Ruth J F and Lotta, Luca and Lubitz, Steven A and Lunetta, Kathryn L and Macfarlane, Peter W and Magnusson, Patrik K E and Malik, Rainer and Mantineo, Helene and Marcus, Gregory M and M{\"a}rz, Winfried and McManus, David D and Melander, Olle and Melloni, Giorgio E M and Meyre, Pascal B and Miyazawa, Kazuo and Mohanty, Sanghamitra and Monfort, Laia M and M{\"u}ller-Nurasyid, Martina and Nafissi, Navid A and Natale, Andrea and Nazarian, Saman and Ostrowski, Sisse R and Pak, Hui-Nam and Pang, Shichao and Pedersen, Ole B and Pedersen, Nancy L and Pereira, Alexandre C and Pirruccello, James P and Preuss, Michael and Psaty, Bruce M and Pullinger, Clive R and Rader, Daniel J and R{\"a}m{\"o}, Joel T and Ridker, Paul M and Rienstra, Michiel and Risch, Lorenz and Roden, Dan M and Rotter, Jerome I and Sabatine, Marc S and Schunkert, Heribert and Shah, Svati H and Shim, Jaemin and Shoemaker, M Benjamin and Simonson, Bridget and Sinner, Moritz F and Smit, Roelof A J and Smith, Jennifer A and Smith, Nicholas L and Smith, J Gustav and Soliman, Elsayed Z and S{\o}rensen, Erik and Sotoodehnia, Nona and Strbian, Daniel and Stricker, Bruno H and Teder-Laving, Maris and Sun, Yan V and Th{\'e}riault, S{\'e}bastien and Thorolfsdottir, Rosa B and Thorsteinsdottir, Unnur and Tveit, Arnljot and van der Harst, Pim and van Meurs, Joyce and Wang, Biqi and Weiss, Stefan and Wells, Quinn S and Weng, Lu-Chen and Wilson, Peter W and Xiao, Ling and Yang, Pil-Sung and Yao, Jie and Yoneda, Zachary T and Zeller, Tanja and Zeng, Lingyao and Zhao, Wei and Zhou, Xiang and Z{\"o}llner, Sebastian and Ruff, Christian T and Bundgaard, Henning and Willer, Cristen and Stefansson, Kari and Ellinor, Patrick T} }