@article {7583, title = {DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation.}, journal = {Am J Hum Genet}, volume = {101}, year = {2017}, month = {2017 Dec 07}, pages = {888-902}, abstract = {

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0~{\texttimes} 10-7; replication: N = 7,182, p~<~1.6~{\texttimes} 10-3). The replicated methylation sites are heritable (h2 > 30\%) and independent of known BP genetic variants, explaining an additional 1.4\% and 2.0\% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

}, keywords = {Aged, Blood Pressure, CpG Islands, Cross-Sectional Studies, DNA Methylation, Epigenesis, Genetic, Genetic Variation, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Middle Aged, Nerve Tissue Proteins, Quantitative Trait Loci, Tetraspanins}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2017.09.028}, author = {Richard, Melissa A and Huan, Tianxiao and Ligthart, Symen and Gondalia, Rahul and Jhun, Min A and Brody, Jennifer A and Irvin, Marguerite R and Marioni, Riccardo and Shen, Jincheng and Tsai, Pei-Chien and Montasser, May E and Jia, Yucheng and Syme, Catriona and Salfati, Elias L and Boerwinkle, Eric and Guan, Weihua and Mosley, Thomas H and Bressler, Jan and Morrison, Alanna C and Liu, Chunyu and Mendelson, Michael M and Uitterlinden, Andr{\'e} G and van Meurs, Joyce B and Franco, Oscar H and Zhang, Guosheng and Li, Yun and Stewart, James D and Bis, Joshua C and Psaty, Bruce M and Chen, Yii-Der Ida and Kardia, Sharon L R and Zhao, Wei and Turner, Stephen T and Absher, Devin and Aslibekyan, Stella and Starr, John M and McRae, Allan F and Hou, Lifang and Just, Allan C and Schwartz, Joel D and Vokonas, Pantel S and Menni, Cristina and Spector, Tim D and Shuldiner, Alan and Damcott, Coleen M and Rotter, Jerome I and Palmas, Walter and Liu, Yongmei and Paus, Tom{\'a}{\v s} and Horvath, Steve and O{\textquoteright}Connell, Jeffrey R and Guo, Xiuqing and Pausova, Zdenka and Assimes, Themistocles L and Sotoodehnia, Nona and Smith, Jennifer A and Arnett, Donna K and Deary, Ian J and Baccarelli, Andrea A and Bell, Jordana T and Whitsel, Eric and Dehghan, Abbas and Levy, Daniel and Fornage, Myriam} } @article {7572, title = {Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.}, journal = {PLoS Genet}, volume = {13}, year = {2017}, month = {2017 May}, pages = {e1006728}, abstract = {

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25{\texttimes}10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

}, keywords = {African Americans, Animals, Basic Helix-Loop-Helix Transcription Factors, Blood Pressure, Cadherins, Case-Control Studies, Female, Genetic Loci, Genome-Wide Association Study, Humans, Hypertension, Male, Membrane Proteins, Mice, Multifactorial Inheritance, Polymorphism, Single Nucleotide}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1006728}, author = {Liang, Jingjing and Le, Thu H and Edwards, Digna R Velez and Tayo, Bamidele O and Gaulton, Kyle J and Smith, Jennifer A and Lu, Yingchang and Jensen, Richard A and Chen, Guanjie and Yanek, Lisa R and Schwander, Karen and Tajuddin, Salman M and Sofer, Tamar and Kim, Wonji and Kayima, James and McKenzie, Colin A and Fox, Ervin and Nalls, Michael A and Young, J Hunter and Sun, Yan V and Lane, Jacqueline M and Cechova, Sylvia and Zhou, Jie and Tang, Hua and Fornage, Myriam and Musani, Solomon K and Wang, Heming and Lee, Juyoung and Adeyemo, Adebowale and Dreisbach, Albert W and Forrester, Terrence and Chu, Pei-Lun and Cappola, Anne and Evans, Michele K and Morrison, Alanna C and Martin, Lisa W and Wiggins, Kerri L and Hui, Qin and Zhao, Wei and Jackson, Rebecca D and Ware, Erin B and Faul, Jessica D and Reiner, Alex P and Bray, Michael and Denny, Joshua C and Mosley, Thomas H and Palmas, Walter and Guo, Xiuqing and Papanicolaou, George J and Penman, Alan D and Polak, Joseph F and Rice, Kenneth and Taylor, Ken D and Boerwinkle, Eric and Bottinger, Erwin P and Liu, Kiang and Risch, Neil and Hunt, Steven C and Kooperberg, Charles and Zonderman, Alan B and Laurie, Cathy C and Becker, Diane M and Cai, Jianwen and Loos, Ruth J F and Psaty, Bruce M and Weir, David R and Kardia, Sharon L R and Arnett, Donna K and Won, Sungho and Edwards, Todd L and Redline, Susan and Cooper, Richard S and Rao, D C and Rotter, Jerome I and Rotimi, Charles and Levy, Daniel and Chakravarti, Aravinda and Zhu, Xiaofeng and Franceschini, Nora} } @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 {9702, title = {Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.}, journal = {Sci Rep}, volume = {14}, year = {2024}, month = {2024 May 30}, pages = {12436}, abstract = {

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model{\textquoteright}s performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1\% (SBP) and 14.3\% to 17.4\% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1\% (SBP) and 4.7 to 5\% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3\% (SBP) and 5.7\% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

}, keywords = {Blood Pressure, Female, Genetic Predisposition to Disease, Genetic Risk Score, Genome-Wide Association Study, Humans, Hypertension, Machine Learning, Male, Middle Aged, Models, Genetic, Multifactorial Inheritance, Phenotype, Risk Factors}, issn = {2045-2322}, doi = {10.1038/s41598-024-62945-9}, author = {Hrytsenko, Yana and Shea, Benjamin and Elgart, Michael and Kurniansyah, Nuzulul and Lyons, Genevieve and Morrison, Alanna C and Carson, April P and Haring, Bernhard and Mitchell, Braxton D and Psaty, Bruce M and Jaeger, Byron C and Gu, C Charles and Kooperberg, Charles and Levy, Daniel and Lloyd-Jones, Donald and Choi, Eunhee and Brody, Jennifer A and Smith, Jennifer A and Rotter, Jerome I and Moll, Matthew and Fornage, Myriam and Simon, Noah and Castaldi, Peter and Casanova, Ramon and Chung, Ren-Hua and Kaplan, Robert and Loos, Ruth J F and Kardia, Sharon L R and Rich, Stephen S and Redline, Susan and Kelly, Tanika and O{\textquoteright}Connor, Timothy and Zhao, Wei and Kim, Wonji and Guo, Xiuqing and Ida Chen, Yii-Der and Sofer, Tamar} }