Featured Publications

  • A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma

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  • Leveraging electronic health record data for endometriosis research

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  • Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets

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2024

SVerma et al. (2024) . A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma. https://doi.org/10.1016/j.cell.2023.12.006

DePaolo et al. (2024).Titin-Truncating variants Predispose to Dilated Cardiomyopathy in Diverse Populations. https://doi.org/10.1101/2024.01.17.24301405

Jee et al. (2024). Multi-ancestry polygenic risk scores for venous thromboembolism. https://doi.org/10.1101/2024.01.09.24300914

2023

Singhal et al. (2023). Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets. https://doi.org/10.1016/j.ajhg.2023.03.007

SVerma et al. (2023). Genome-Wide Association Study of Breast Density among Women of African Ancestry. https://doi.org/10.3390/cancers15102776

Penrod et al. (2023). Leveraging electronic health record data for endometriosis research. https://doi.org/10.3389/fdgth.2023.1150687

Xiao et al. (2023) Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions. https://doi.org/10.1161/JAHA.121.026561

2022

SVerma et al. (2022) Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population. https://doi.org/10.1186/s12967-022-03745-5

Turong, Woemer & Cherlin et al. (2022). Quality control procedures for genome‐wide association studies.  https://doi-org.proxy.library.upenn.edu/10.1002/cpz1.603

Hui and Xiao et al(2022). Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index. https://doi.org/10.1142/9789811270611_0040

Pre-2021

SVerma et al. (2020). Research on COVID-19 through patient-reported data: a survey for observational studies in the COVID-19 pandemic. https://doi.org/10.1017/cts.2020.509

SVerma et al. (2018). Another Round of “Clue” to Uncover the Mystery of Complex Traits.  https://doi.org/10.3390/genes9020061

SVerma et al. (2018). Rare variants in drug target genes contributing to complex diseases, phenome-wide.https://doi.org/10.1038/s41598-018-22834-4

SVerma et al. (2017).Identifying Genetic Associations With Variability In Metabolic Health And Blood Count Laboratory Values: Diving Into The Quantitative Traits By Leveraging Longitudinal Data From An EHR. https://doi.org/10.1142/9789813207813_0049

SVerma et al. (2016). Epistatic gene-based interaction analyses for glaucoma in eMERGE and NEIGHBOR consortium. https://doi.org/10.1371/journal.pgen.1006186

SVerma et al. (2014). Imputation and quality control steps for combining multiple genome-wide datasets. https://doi.org/10.3389/fgene.2014.00370