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Articles by Nicholas Hand
G4mer: An RNA language model for transcriptome-wide identification of G-quadruplexes and disease variants from population-scale genetic data - Nature Communications
Abstract RNA G-quadruplexes (rG4s) are key regulatory elements in gene expression, yet the effects of genetic variants on rG4 formation remain underexplored. Here, we introduce G4mer, an RNA language model that predicts rG4 formation, classifies rG4 subtypes, and evaluates the effects of genetic variants across the transcriptome.
A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation | Nature Genetics
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Abstract Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls.
By Marijana Vujkovic, Kim Lorenz, Xiuqing Guo, Heather J. Cordell, Joseph Park, Kyung Min Lee, David Kaplan, Xiang Zhu, Catherine Tcheandjieu, Rachel L. Kember, Henry R Kranzler, Ayush Giri, Derek Klarin, Yan Sun, Jie Huang, Jennifer Huffman Verified, Kate Townsend Creasy, Nicholas Hand, Ching-Ti Liu, Matthew J. Budoff, Henry Lin, Silvia Vilarinho Verified, Adam E. Locke, Aris Baras, Brent A Neuschwander-Tetri, Kathleen Ryan, Dipender Gill, Elisabetta Manduchi, Donald Miller, Peter D. Reaven, Lawrence Phillips, Scott Duvall, Themistocles L. Assimes, Todd L. Edwards, Scott M. Damrauer, Amit V. Khera, Philip S. Tsao, Danish Saleheen, Julie Lynch, Daniel Rader, Kyong-Mi Chang, Walter R. Witschey, Geisinger-regeneron DiscovEhr Collaboration
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Nature
Verified
Systematically Sifting Big Data to Identify Novel Causal Genes for Human Traits
Widespread technological advances have propelled human genetics into a “big data” era, in which genome-wide data from extremely large cohorts can be integrated with other “-omics” datasets from humans and model systems. Li et al. (2020) Li Z. Votava J.A. Zajac G.J.M. Nguyen J.N. Leyva Jaimes F.B. Ly S.M. Brinkman J.A. De Giorgi M. Kaul S. Green C.L. et al. Integrating mouse and human genetic data to move beyond GWAS and identify causal genes in cholesterol metabolism. Cell Metab.
From Loci to Biology
Genome-wide association studies have provided a rich collection of ≈58 coronary artery disease (CAD) loci that suggest the existence of previously unsuspected new biology relevant to atherosclerosis. However, these studies only identify genomic loci associated with CAD, and many questions remain even after a genomic locus is definitively implicated, including the nature of the causal variant(s) and the causal gene(s), as well as the directionality of effect.
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