Rich, Stephen S.

Impact of common genetic determinants of hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis

Wheeler, E., Leong, A., Liu, C.-T., Hivert, M.-F., Strawbridge, R. J., Podmore, C., Li, M., Yao, J., Sim, X., Hong, J., et al. (2017) · PLOS Medicine

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 408

Precision medicine in diabetes: a consensus report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

Chung, W. K., Erion, K., Florez, J. C., Hattersley, A. T., Hivert, M.-F., Lee, C. G., McCarthy, M. I., Nolan, J. J., Norris, J. M., Pearson, E. R., et al. (2020) · Diabetes Care

Diabetes Management and ResearchDiabetes and associated disorders

Cited by 400

Pangenomics enables genotyping of known structural variants in 5202 diverse genomes

Sirén, J., Monlong, J., Chang, X., Novak, A. M., Eizenga, J. M., Markello, C., Sibbesen, J. A., Hickey, G., Chang, P.-C., Carroll, A., et al. (2021) · Science

Genomics and Phylogenetic StudiesGenomic variations and chromosomal abnormalities

Cited by 400

Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis

The UK-PSCSC Consortium, Liu, J. Z., The International IBD Genetics Consortium, The International PSC Study Group, Hov, J. R., Folseraas, T., Ellinghaus, E., Rushbrook, S. M., Doncheva, N. T., Andreassen, O. A., et al. (2013) · Nature Genetics

Liver Diseases and ImmunityGenetic Associations and Epidemiology

Cited by 391

Microbiota alteration is associated with the development of stress-induced despair behavior

Marin, I. A., Goertz, J. E., Ren, T., Rich, S. S., Onengut-Gumuscu, S., Farber, E., Wu, M., Overall, C. C., Kipnis, J., & Gaultier, A. (2017) · Scientific Reports

Gut microbiota and healthTryptophan and brain disorders

Cited by 369

Development and standardization of an improved type 1 diabetes genetic risk score for use in newborn screening and incident diagnosis

Sharp, S. A., Rich, S. S., Wood, A. R., Jones, S. E., Beaumont, R. N., Harrison, J. W., Schneider, D. A., Locke, J. M., Tyrrell, J., Weedon, M. N., et al. (2019) · Diabetes Care

Diabetes and associated disordersGenetic Associations and Epidemiology

Cited by 366

Functional IL6R 358Ala Allele Impairs Classical IL-6 Receptor Signaling and Influences Risk of Diverse Inflammatory Diseases

Ferreira, R. C., Freitag, D. F., Cutler, A. J., Howson, J. M. M., Rainbow, D. B., Smyth, D. J., Kaptoge, S., Clarke, P., Boreham, C., Coulson, R. M., et al. (2013) · PLoS Genetics

Cytokine Signaling Pathways and InteractionsGenetic Associations and Epidemiology

Cited by 316

Whole-Genome Sequencing to Characterize Monogenic and Polygenic Contributions in Patients Hospitalized With Early-Onset Myocardial Infarction

Khera, A. V., Chaffin, M., Zekavat, S. M., Collins, R. L., Roselli, C., Natarajan, P., Lichtman, J. H., D’Onofrio, G., Mattera, J., Dreyer, R., et al. (2019) · Circulation

Lipoproteins and Cardiovascular HealthGenetic Associations and Epidemiology

Cited by 315

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

Robertson, C. C., Inshaw, J. R. J., Onengut-Gumuscu, S., Chen, W.-M., Santa Cruz, D. F., Yang, H., Cutler, A. J., Crouch, D. J. M., Farber, E., Bridges, S. L., et al. (2021) · Nature Genetics

Diabetes and associated disordersGenetic Associations and Epidemiology

Cited by 302

Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy

Pirruccello, J. P., Bick, A., Wang, M., Chaffin, M., Friedman, S., Yao, J., Guo, X., Venkatesh, B. A., Taylor, K. D., Post, W. S., et al. (2020) · Nature Communications

Cardiomyopathy and Myosin StudiesGenetic Associations and Epidemiology

Cited by 267

Association of Low-Density Lipoprotein Cholesterol–Related Genetic Variants With Aortic Valve Calcium and Incident Aortic Stenosis

Smith, J. G., Luk, K., Schulz, C.-A., Engert, J. C., Do, R., Hindy, G., Rukh, G., Dufresne, L., Almgren, P., Owens, D. S., et al. (2014) · JAMA

Cardiac Valve Diseases and TreatmentsLipoproteins and Cardiovascular Health

Cited by 238

Association of clonal hematopoiesis with chronic obstructive pulmonary disease

Miller, P. G., Qiao, D., Rojas-Quintero, J., Honigberg, M. C., Sperling, A. S., Gibson, C. J., Bick, A. G., Niroula, A., McConkey, M. E., Sandoval, B., et al. (2022) · Blood

Chronic Obstructive Pulmonary Disease (COPD) ResearchAcute Myeloid Leukemia Research

Cited by 235

Visualizing Human Leukocyte Antigen Class II Risk Haplotypes in Human Systemic Lupus Erythematosus

Graham, R. R., Ortmann, W. A., Langefeld, C. D., Jawaheer, D., Selby, S. A., Rodine, P. R., Baechler, E. C., Rohlf, K. E., Shark, K. B., Espe, K. J., et al. (2002) · The American Journal of Human Genetics

Systemic Lupus Erythematosus ResearchGenetic Associations and Epidemiology

Cited by 223

Causal Effects of Body Mass Index on Cardiometabolic Traits and Events: A Mendelian Randomization Analysis

Holmes, M. V., Lange, L. A., Palmer, T., Lanktree, M. B., North, K. E., Almoguera, B., Buxbaum, S., Chandrupatla, H. R., Elbers, C. C., Guo, Y., et al. (2014) · The American Journal of Human Genetics

Genetic Associations and EpidemiologyDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 216

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

Chung, W. K., Erion, K., Florez, J. C., Hattersley, A. T., Hivert, M.-F., Lee, C. G., McCarthy, M. I., Nolan, J. J., Norris, J. M., Pearson, E. R., et al. (2020) · Diabetologia

Diabetes Management and ResearchDiabetes and associated disorders

Cited by 203

Comparison of Proteomic Assessment Methods in Multiple Cohort Studies

Raffield, L. M., Dang, H., Pratte, K. A., Jacobson, S., Gillenwater, L. A., Ampleford, E., Barjaktarevic, I., Basta, P., Clish, C. B., Comellas, A. P., et al. (2020) · PROTEOMICS

Advanced Biosensing Techniques and ApplicationsAdvanced Proteomics Techniques and Applications

Cited by 184

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Rusu, V., Hoch, E., Mercader, J. M., Tenen, D. E., Gymrek, M., Hartigan, C. R., DeRan, M., von Grotthuss, M., Fontanillas, P., Spooner, A., et al. (2017) · Cell

Genetic Associations and EpidemiologyMetabolism, Diabetes, and Cancer

Cited by 152

Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: a prospective study in children

Bonifacio, E., Beyerlein, A., Hippich, M., Winkler, C., Vehik, K., Weedon, M. N., Laimighofer, M., Hattersley, A. T., Krumsiek, J., Frohnert, B. I., et al. (2018) · PLOS Medicine

Diabetes and associated disordersGenetic Associations and Epidemiology

Cited by 148

Biomarkers of Dairy Fatty Acids and Risk of Cardiovascular Disease in the Multi‐Ethnic Study of Atherosclerosis

de Oliveira Otto, M. C., Nettleton, J. A., Lemaitre, R. N., M. Steffen, L., Kromhout, D., Rich, S. S., Y. Tsai, M., Jacobs, D. R., & Mozaffarian, D. (2013) · Journal of the American Heart Association

Fatty Acid Research and HealthNutritional Studies and Diet

Cited by 135

Monogenic Diabetes: From Genetic Insights to Population-Based Precision in Care. Reflections From a Diabetes Care Editors’ Expert Forum

Riddle, M. C., Philipson, L. H., Rich, S. S., Carlsson, A., Franks, P. W., Greeley, S. A. W., Nolan, J. J., Pearson, E. R., Zeitler, P. S., & Hattersley, A. T. (2020) · Diabetes Care

Diabetes and associated disordersDiabetes Management and Research

Cited by 117

Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants

Dashti, H. S., Follis, J. L., Smith, C. E., Tanaka, T., Cade, B. E., Gottlieb, D. J., Hruby, A., Jacques, P. F., Lamon-Fava, S., Richardson, K., et al. (2015) · The American Journal of Clinical Nutrition

Sleep and related disordersCircadian rhythm and melatonin

Cited by 112

TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data

Huang, L., Rosen, J. D., Sun, Q., Chen, J., Wheeler, M. M., Zhou, Y., Min, Y.-I., Kooperberg, C., Conomos, M. P., Stilp, A. M., et al. (2022) · The American Journal of Human Genetics

Genetic Associations and EpidemiologyForensic and Genetic Research

Cited by 97

Hierarchical order of distinct autoantibody spreading and progression to type 1 diabetes in the TEDDY study

Vehik, K., Bonifacio, E., Lernmark, Å., Yu, L., Williams, A., Schatz, D., Rewers, M., She, J.-X., Toppari, J., Hagopian, W., et al. (2020) · Diabetes Care

Diabetes and associated disordersDiabetes Management and Research

Cited by 87

Consensus Guidance for Monitoring Individuals With Islet Autoantibody–Positive Pre-Stage 3 Type 1 Diabetes

Phillip, M., Achenbach, P., Addala, A., Albanese-O’Neill, A., Battelino, T., Bell, K. J., Besser, R. E. J., Bonifacio, E., Colhoun, H. M., Couper, J. J., et al. (2024) · Diabetes Care

Diabetes and associated disordersDiabetes Management and Research

Cited by 79