@article {9246, title = {Correlations between complex human phenotypes vary by genetic background, gender, and environment.}, journal = {Cell Rep Med}, volume = {3}, year = {2022}, month = {2022 Dec 20}, pages = {100844}, abstract = {

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet \~{}20{\texttimes} faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

}, keywords = {Female, Genetic Background, Humans, Male, Phenotype}, issn = {2666-3791}, doi = {10.1016/j.xcrm.2022.100844}, author = {Elgart, Michael and Goodman, Matthew O and Isasi, Carmen and Chen, Han and Morrison, Alanna C and de Vries, Paul S and Xu, Huichun and Manichaikul, Ani W and Guo, Xiuqing and Franceschini, Nora and Psaty, Bruce M and Rich, Stephen S and Rotter, Jerome I and Lloyd-Jones, Donald M and Fornage, Myriam and Correa, Adolfo and Heard-Costa, Nancy L and Vasan, Ramachandran S and Hernandez, Ryan and Kaplan, Robert C and Redline, Susan and Sofer, Tamar} } @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 {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 {9851, title = {The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup.}, journal = {medRxiv}, year = {2024}, month = {2024 Dec 20}, abstract = {

Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup. We define a metric called "expected PRS" (ePRS), the expected value of a PRS based on one{\textquoteright}s global or local admixture patterns. We further define the "residual PRS" (rPRS), measuring the deviation of the PRS from the ePRS. Simulation studies confirm that it suffices to adjust for ePRS to obtain nearly unbiased estimates of the PRS-outcome association without further adjusting for PCs. Using the TOPMed dataset, the estimated effect size of the rPRS adjusting for the ePRS is similar to the estimated effect of the PRS adjusting for genetic PCs. Similarly, we applied the ePRS framework to six cardiovascular-related traits in the All of Us dataset, and the results are consistent with those from the TOPMed analysis. The ePRS framework can protect from population stratification in association analysis and provide an equitable strategy to quantify genetic risk across diverse populations.

}, doi = {10.1101/2024.03.05.24303738}, author = {Huang, Yu-Jyun and Kurniansyah, Nuzulul and Goodman, Matthew O and Spitzer, Brian W and Wang, Jiongming and Stilp, Adrienne and Laurie, Cecelia and de Vries, Paul S and Chen, Han and Min, Yuan-I and Sims, Mario and Peloso, Gina M and Guo, Xiuqing and Bis, Joshua C and Brody, Jennifer A and Raffield, Laura M and Smith, Jennifer A and Zhao, Wei and Rotter, Jerome I and Rich, Stephen S and Redline, Susan and Fornage, Myriam and Kaplan, Robert and Franceschini, Nora and Levy, Daniel and Morrison, Alanna C and Boerwinkle, Eric and Smith, Nicholas L and Kooperberg, Charles and Psaty, Bruce M and Z{\"o}llner, Sebastian and Sofer, Tamar} }