Biomedical and Translational Informatics Laboratory
  • Ramdas, S., Judd, J., Graham, S. E., Kanoni, S., Wang, Y., Surakka, I., Wenz, B., Clarke, S. L., Chesi, A., Wells, A., Bhatti, K. F., Vedantam, S., Winkler, T. W., Locke, A. E., Marouli, E., Zajac, G. J. M., Wu, K.-H. H., Ntalla, I., Hui, Q., … Brown, C. D. (2022). A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. The American Journal of Human Genetics, 109(8), 1366–1387. https://doi.org/10.1016/j.ajhg.2022.06.012
  • Li, B., Sangkuhl, K., Keat, K., Whaley, R. M., Woon, M., Verma, S., Dudek, S., Tuteja, S., Verma, A., Whirl‐Carrillo, M., Ritchie, M. D., & Klein, T. E. (2022). How to run the pharmacogenomics clinical annotation tool (PharmCAT). Clinical Pharmacology & Therapeutics, 113(5), 1036–1047. https://doi.org/10.1002/cpt.2790
  • Hui, D., Xiao, B., Dikilitas, O., Freimuth, R. R., Irvin, M. R., Jarvik, G. P., Kottyan, L., Kullo, I., Limdi, N. A., Liu, C., Luo, Y., Namjou, B., Puckelwartz, M. J., Schaid, D., Tiwari, H., Wei, W.-Q., Verma, S., Kim, D., & Ritchie, M. D. (2022). Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index. Biocomputing 2023. https://doi.org/10.1142/9789811270611_0040
  • Keat, K., Hui, D., Xiao, B., Bradford, Y., Cindi, Z., Daar, E. S., Gulick, R., Riddler, S. A., Sinxadi, P., Haas, D. W., & Ritchie, M. D. (2022). Leveraging multi-ancestry polygenic risk scores for body mass index to predict antiretroviral therapy-induced weight gain. Biocomputing 2023. https://doi.org/10.1142/9789811270611_0022
  • Verma, S.S., Keat, K., Li, B. et al. Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population. J Transl Med 20, 550 (2022). https://doi.org/10.1186/s12967-022-03745-5
  • Chand, G. B., Singhal, P., Dwyer, D. B., Wen, J., Erus, G., Doshi, J., Srinivasan, D., Mamourian, E., Varol, E., Sotiras, A., Hwang, G., Dazzan, P., Kahn, R. S., Schnack, H. G., Zanetti, M. V., Meisenzahl, E., Busatto, G. F., Crespo-Facorro, B., Pantelis, C., … Davatzikos, C. (2022). Two schizophrenia imaging signatures and their associations with cognition, psychopathology, and Genetics in the general population. Medrxiv. https://doi.org/10.1101/2022.01.07.22268854
  • Lucas, A., Verma, A., & Ritchie, M. D. (2022). Hudson: A user-friendly R package to extend Manhattan plots. Biorxiv. https://doi.org/10.1101/2022.01.25.474274
  • Bellomo, T. R., Bone, W. P., Chen, B. Y., Gawronski, K. A. B., Zhang, D., Park, J., Levin, M., Tsao, N., Klarin, D., Lynch, J., Assimes, T. L., Gaziano, J. M., Wilson, P. W., Cho, K., Vujkovic, M., the VA Million Veteran Program, C. J., O’Donnell, K.-M., Chang, P. S., & Tsao, D. J. (2022). Multi-Trait Genome-Wide Association Study of Atherosclerosis Detects Novel Pleiotropic Loci. Frontiers in Genetics., 12. https://doi.org/10.3389/fgene.2021.787545
  • Xiao, B., Velez Edwards, D. R., Lucas, A., Drivas, T., Gray, K., Keating, B., Weng, C., Jarvik, G. P., Hakonarson, H., Kottyan, L., Elhadad, N., Wei, W.-Q., Luo, Y., Kim, D., Ritchie, M., & Verma, S. S. (2022). Inference of causal relationships based on the genetics of cardiometabolic traits and conditions unique to females in >50,000 participants. Medrxiv. https://doi.org/10.1101/2022.02.02.22269844
  • Levin, M. G., Huffman, J. E., Verma, A., Sullivan, K. A., Rodriguez, A. A., Kainer, D., Garvin, M. R., Lane, M., Won, H., Li, B., Luo, Y., Jarvik, G. P., Hakonarson, H., Jasper, E. A., Bick, A. G., Ritchie, M. D., Jacobson, D. A., Madduri, R. K., & Damrauer, S. M. (2022). Multi-ancestry genome-wide association study of Varicose Veins reveals polygenic architecture, genetic overlap with arterial and venous disease, and novel therapeutic opportunities. Medrxiv. https://doi.org/10.1101/2022.02.22.22271350
  • Wang, L., Desai, H., Verma, S. S., Le, A., Hausler, R., Verma, A., Judy, R., Doucette, A., Gabriel, P. E., Nathanson, K. L., Damrauer, S. M., Mowery, D. L., Ritchie, M. D., Kember, R. L., Maxwell, K. N., Abecasis, G., Bai, X., Balasubramanian, S., Baras, A., & Blumenfeld, A. (2022). Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank. Genetics in Medicine : Official Journal of the American College of Medical Genetics., 24(3), 601–609. https://doi.org/10.1016/j.gim.2021.10.015
  • Reza, N., Bone, W., Singhal, P., Yang, Y., Verma, A., Murthy, A., Denduluri, S., Adusumalli, S., Ritchie, M. D., & Cappola, T. P. (2022). A supervised learning method for the classification of electronic health record based heart failure phenotypes. Journal of the American College of Cardiology., 79(9). https://doi.org/10.1016/S0735-1097(22)01320-1
  • Li, R., Zhang, X., Li, B., Feng, Q., Kottyan, L., Luo, Y., Sawicki, K. T., Khan, A., Limdi, N., Puckelwartz, M., Wei, W.-Q., Weng, C., Chen, Y., Ritchie, M. D., & Moore, J. H. (2022). Polygenic Risk Vectors (PRV) improve genetic risk stratification for cardio-metabolic diseases. Medrxiv. https://doi.org/10.1101/2022.03.02.22271425
  • Horowitz, J.E., Kosmicki, J.A., Damask, A. et al. Genome-wide analysis provides genetic evidence that ACE2 influences COVID-19 risk and yields risk scores associated with severe disease. Nat Genet 54, 382–392 (2022). https://doi.org/10.1038/s41588-021-01006-7
  • Wen, J., Nasrallah, I., Abdulkadir, A., Satterthwaite, T., Erus, G., Robert-Fitzgerald, T., Singh, A., Sotiras, A., Boquet-Pujadas, A., Yang, Z., Mamourian, E., Doshi, J., Cui, Y., Sriniva, D., Bergman, M., Bao, J., Veturi, Y., Zhou, Z., Yang, S., … Davatzikos, C. (2022). Mega-Analysis of Brain Structural Covariance, Genetics, and Clinical Phenotypes. https://doi.org/10.21203/rs.3.rs-1503113/v1
  • Verma, A., Tsao, N. L., Thomann, L. O., Ho, Y.-L., Iyengar, S. K., Luoh, S.-W., Carr, R., Crawford, D. C., Efird, J. T., Huffman, J. E., Hung, A., Ivey, K. L., Levin, M. G., Lynch, J., Natarajan, P., Pyarajan, S., Bick, A. G., Costa, L., Genovese, G., … Liao, K. P. (2022). A phenome-wide association study of genes associated with covid-19 severity reveals shared genetics with complex diseases in the million veteran program. PLOS Genetics, 18(4). https://doi.org/10.1371/journal.pgen.1010113
  • Wen, J., Fu, C. H., Tosun, D., Veturi, Y., Yang, Z., Abdulkadir, A., Mamourian, E., Srinivasan, D., Skampardoni, I., Singh, A., Nawani, H., Bao, J., Erus, G., Shou, H., Habes, M., Doshi, J., Varol, E., Mackin, R. S., Sotiras, A., … Raj, B. A. (2022). Characterizing heterogeneity in neuroimaging, cognition, clinical symptoms, and genetics among patients with late-life depression. JAMA Psychiatry, 79(5), 464. https://doi.org/10.1001/jamapsychiatry.2022.0020
  • Chand, G., Singhal, P., Dwyer, D. B., Wen, J., Erus, G., Varol, E., Hwang, G., Dazzan, P., Kahn, R. S., Schnack, H. G., Zanetti, M. V., Busatto, G. F., Crespo-Facorro, B., Pantelis, C., Wood, S. J., Zhuo, C., Shou, H., Fan, Y., Koutsouleris, N., & Gur, R. (2022). P580. Two Schizophrenia Neuroanatomical Signatures From the PHENOM Consortium and Their Association With Psychopathology, Cognition, and Genetics in the Population-Level Samples. Biological Psychiatry., 91(9), S323–S324. https://doi.org/10.1016/j.biopsych.2022.02.817
  • Zhang, C., Verma, A., Feng, Y., Melo, M. C. R., McQuillan, M., Hansen, M., Lucas, A., Park, J., Ranciaro, A., Thompson, S., Rubel, M. A., Campbell, M. C., Beggs, W., Hirbo, J., Wata Mpoloka, S., George Mokone, G., Nyambo, T., Wolde Meskel, D., Belay, G., & Fokunang, C. (2022). Impact of natural selection on global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection. Proceedings of the National Academy of Sciences of the United States of America., 119(21). https://doi.org/10.1073/pnas.2123000119
  • Roychowdhury, T., Klarin, D., Levin, M. G., Spin, J. M., Rhee, Y. H., Deng, A., Headley, C. A., Surakka, I., Tsao, N. L., Gellatly, C., Zuber, V., Shen, F., Hornsby, W. E., Laursen, I. H., Verma, S. S., Locke, A. E., Einarsson, G., Thorleifsson, G., Graham, S. E., … Damrauer, S. M. (2022). Multi-ancestry gwas deciphers genetic architecture of abdominal aortic aneurysm and highlight pcsk9 as a therapeutic target. Medrxiv. https://doi.org/10.1101/2022.05.27.22275607
  • Tcheandjieu, C., Xiao, K., Tejeda, H. et al. High heritability of ascending aortic diameter and trans-ancestry prediction of thoracic aortic disease. Nat Genet 54, 772–782 (2022). https://doi.org/10.1038/s41588-022-01070-7
  • Gudiseva. (2022). Quantitative traits associated with primary open-angle glaucoma in African ancestry individuals. Investigative Ophthalmology & Visual Science., 63(7).
  • Zhang, X., Lucas, A.M., Veturi, Y. et al. Large-scale genomic analyses reveal insights into pleiotropy across circulatory system diseases and nervous system disorders. Nat Commun 13, 3428 (2022). https://doi.org/10.1038/s41467-022-30678-w
  • Verma, S., Guare, L., Gastounioti, A., Ehsan, S., Conant, E. F., Ritchie, M., Kontos, D., & McCarthy, A. M. (2022). Abstract 5871: Genome wide association study of breast density among women of African ancestry. Cancer Research., 82(12_Supplement), 5871–5871. https://doi.org/10.1158/1538-7445.AM2022-5871
  • Pividori, M., Ritchie, M. D., Milone, D. H., & Greene, C. S. (2022). An efficient not-only-linear correlation coefficient based on machine learning. Biorxiv. https://doi.org/10.1101/2022.06.15.496326
  • Haas, D. W., Abdelwahab, M. T., van Beek, S. W., Baker, P., Maartens, G., Bradford, Y., Ritchie, M. D., Wasserman, S., Meintjes, G., Beeri, K., Gandhi, N. R., Svensson, E. M., Denti, P., & Brust, J. C. (2022). Pharmacogenetics of between-individual variability in plasma clearance of Bedaquiline and Clofazimine in South Africa. The Journal of Infectious Diseases, 226(1), 147–156. https://doi.org/10.1093/infdis/jiac024
  • Liu, H., Doke, T., Guo, D. et al. Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease. Nat Genet 54, 950–962 (2022). https://doi.org/10.1038/s41588-022-01097-w
  • Kousathanas, A., Pairo-Castineira, E., Rawlik, K. et al. Whole-genome sequencing reveals host factors underlying critical COVID-19. Nature 607, 97–103 (2022). https://doi.org/10.1038/s41586-022-04576-6
  • Wen, J., Nasrallah, I. M., Abdulkadir, A., Satterthwaite, T. D., Yang, Z., Erus, G., Robert-Fitzgerald, T., Singh, A., Sotiras, A., Boquet-Pujadas, A., Mamourian, E., Doshi, J., Cui, Y., Srinivasan, D., Skampardoni, I., Chen, J., Hwang, G., Bergman, M., Bao, J., … Davatzikos, C. (2022). Novel genomic loci influence patterns of structural covariance in the human brain. Medrxiv. https://doi.org/10.1101/2022.07.20.22277727
  • Wiley, K., Findley, L., Goldrich, M., Rakhra-Burris, T. K., Stevens, A., Williams, P., Bult, C. J., Chisholm, R., Deverka, P., Ginsburg, G. S., Green, E. D., Jarvik, G., Mensah, G. A., Ramos, E., Relling, M. V., Roden, D. M., Rowley, R., Alterovitz, G., Aronson, S., … Williams, M. S. (2022). A research agenda to support the development and implementation of genomics-based Clinical Informatics Tools and resources. Journal of the American Medical Informatics Association, 29(8), 1342–1349. https://doi.org/10.1093/jamia/ocac057
  • Banday, A.R., Stanifer, M.L., Florez-Vargas, O. et al. Genetic regulation of OAS1 nonsense-mediated decay underlies association with COVID-19 hospitalization in patients of European and African ancestries. Nat Genet 54, 1103–1116 (2022). https://doi.org/10.1038/s41588-022-01113-z
  • Tcheandjieu, C., Zhu, X., Hilliard, A.T. et al. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med 28, 1679–1692 (2022). https://doi.org/10.1038/s41591-022-01891-3
  • Chand, G. B., Singhal, P., Dwyer, D. B., Wen, J., Erus, G., Doshi, J., Srinivasan, D., Mamourian, E., Varol, E., Sotiras, A., Hwang, G., Dazzan, P., Kahn, R. S., Schnack, H. G., Zanetti, M. V., Meisenzahl, E., Busatto, G. F., Crespo-Facorro, B., Pantelis, C., … Davatzikos, C. (2022). Schizophrenia imaging signatures and their associations with cognition, psychopathology, and Genetics in the general population. American Journal of Psychiatry, 179(9), 650–660. https://doi.org/10.1176/appi.ajp.21070686
  • Chen, B. Y., Bone, W. P., Lorenz, K., Levin, M., Ritchie, M. D., & Voight, B. F. (2022). Colocquial: A QTL-GWAS colocalization pipeline. Bioinformatics, 38(18), 4409–4411. https://doi.org/10.1093/bioinformatics/btac512

  • Zhou, W., Kanai, M., Wu, K.-H. H., Rasheed, H., Tsuo, K., Hirbo, J. B., Wang, Y., Bhattacharya, A., Zhao, H., Namba, S., Surakka, I., Wolford, B. N., Lo Faro, V., Lopera-Maya, E. A., Läll, K., Favé, M.-J., Partanen, J. J., Chapman, S. B., Karjalainen, J., & Kurki, M. (2022). Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease. Cell Genomics., 2(10). https://doi.org/10.1016/j.xgen.2022.100192

  • Ding, Z., Ritchie, M.D., Voight, B.F. et al. Estimating the effect size of a hidden causal factor between SNPs and a continuous trait: a mediation model approach. BMC Bioinformatics 23, 420 (2022). https://doi.org/10.1186/s12859-022-04977-4
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  • Reza, N., Yang, Y., Bone, W. P., Singhal, P., Verma, A., Denduluri, S., Adusumalli, S., Ritchie, M. D., & Cappola, T. P. (2022). Unsupervised clustering applied to electronic health record-derived phenotypes in patients with heart failure. Medrxiv. https://doi.org/10.1101/2022.10.31.22281772
  • Cindi, Z., Kawuma, A. N., Maartens, G., Bradford, Y., Venter, F., Sokhela, S., Chandiwana, N., Wasmann, R. E., Denti, P., Wiesner, L., Ritchie, M. D., Haas, D. W., & Sinxadi, P. (2022). Pharmacogenetics of dolutegravir plasma exposure among southern Africans with human immunodeficiency virus. The Journal of Infectious Diseases, 226(9), 1616–1625. https://doi.org/10.1093/infdis/jiac174
  • Lau-Min, K. S., McKenna, D., Asher, S. B., Bardakjian, T., Wollack, C., Bleznuck, J., Biros, D., Anantharajah, A., Clark, D. F., Condit, C., Ebrahimzadeh, J. E., Long, J. M., Powers, J., Raper, A., Schoenbaum, A., Feldman, M., Steinfeld, L., Tuteja, S., VanZandbergen, C., & Domchek, S. M. (2022). Impact of integrating genomic data into the electronic health record on genetics care delivery. Genetics in Medicine : Official Journal of the American College of Medical Genetics., 24(11), 2338–2350. https://doi.org/10.1016/j.gim.2022.08.009
  • Truong, V. Q., Woerner, J. A., Cherlin, T. A., Bradford, Y., Lucas, A. M., Okeh, C. C., Shivakumar, M. K., Hui, D. H., Kumar, R., Pividori, M., Jones, S. C., Bossa, A. C., Turner, S. D., Ritchie, M. D., & Verma, S. S. (2022). Quality Control Procedures for genome‐wide association studies. Current Protocols, 2(11). https://doi.org/10.1002/cpz1.603
  • Reza, N., Levin, M., Vidula, M. K., Bravo, P. E., Damrauer, S. M., Ritchie, M., Cntr, R. G., Chahal, A. A., & Owens, A. T. (2022). Abstract 11772: Prevalence of Pathogenic Variants in Dilated Cardiomyopathy-Associated Genes in Patients Evaluated for Cardiac Sarcoidosis. Circulation., 146(Suppl_1). https://doi.org/10.1161/circ.146.suppl_1.11772
  • Singhal, P., Guare, L., Morse, C., Byrska-Bishop, M., Guerraty, M. A., Kim, D., Ritchie, M. D., & Verma, A. (2022). Detect: Feature extraction method for disease trajectory modeling. Medrxiv. https://doi.org/10.1101/2022.11.06.22281817
  • Levin, M.G., Tsao, N.L., Singhal, P. et al. Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure. Nat Commun 13, 6914 (2022). https://doi.org/10.1038/s41467-022-34216-6
  1. Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population.
  2. The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population.
  3. Genetic heterogeneity of four MCI/AD neuroanatomical dimensions discovered via deep learning.
  4. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution.

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Publications