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1,021 results on '"Phillips, Lawrence S"'

1. Large-scale multi-omics identifies drug targets for heart failure with reduced and preserved ejection fraction

Author

Rasooly, Danielle, Giambartolomei, Claudia, Peloso, Gina M., Dashti, Hesam, Ferolito, Brian R., Golden, Daniel, Horimoto, Andrea R. V. R., Pietzner, Maik, Farber-Eger, Eric H., Wells, Quinn Stanton, Bini, Giorgio, Proietti, Gabriele, Tartaglia, Gian Gaetano, Kosik, Nicole M., Wilson, Peter W. F., Phillips, Lawrence S., Munroe, Patricia B., Petersen, Steffen E., Cho, Kelly, Gaziano, J. Michael, Leach, Andrew R., Whittaker, John, Langenberg, Claudia, Aung, Nay, Sun, Yan V., Pereira, Alexandre C., Casas, Juan P., and Joseph, Jacob

Published
2025
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3. Adaptive selection at G6PD and disparities in diabetes complications

Author

Breeyear, Joseph H., Hellwege, Jacklyn N., Schroeder, Philip H., House, John S., Poisner, Hannah M., Mitchell, Sabrina L., Charest, Brian, Khakharia, Anjali, Basnet, Til B., Halladay, Christopher W., Reaven, Peter D., Meigs, James B., Rhee, Mary K., Sun, Yang, Lynch, Mary G., Bick, Alexander G., Wilson, Otis D., Hung, Adriana M., Nealon, Cari L., Iyengar, Sudha K., Rotroff, Daniel M., Buse, John B., Leong, Aaron, Mercader, Josep M., Sobrin, Lucia, Brantley, Jr., Milam A., Peachey, Neal S., Motsinger-Reif, Alison A., Wilson, Peter W., Sun, Yan V., Giri, Ayush, Phillips, Lawrence S., and Edwards, Todd L.

Published
2024
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5. A platform for phenotyping disease progression and associated longitudinal risk factors in large-scale EHRs, with application to incident diabetes complications in the UK Biobank

Author

Kim, Hyun, Jensen, Aubrey, Jones, Kelly, Raghavan, Sridharan, Phillips, Lawrence S, Hung, Adriana, Sun, Yan V, Li, Gang, Reaven, Peter, Zhou, Hua, and Zhou, Jin J

Subjects
Health Services and Systems, Health Sciences, Prevention, Diabetes, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, phenotyping, diabetes, diabetes complications, disease progression, electronic health records, time-to-event, Health services and systems
Abstract

ObjectiveModern healthcare data reflect massive multi-level and multi-scale information collected over many years. The majority of the existing phenotyping algorithms use case-control definitions of disease. This paper aims to study the time to disease onset and progression and identify the time-varying risk factors that drive them.Materials and methodsWe developed an algorithmic approach to phenotyping the incidence of diseases by consolidating data sources from the UK Biobank (UKB), including primary care electronic health records (EHRs). We focused on defining events, event dates, and their censoring time, including relevant terms and existing phenotypes, excluding generic, rare, or semantically distant terms, forward-mapping terminology terms, and expert review. We applied our approach to phenotyping diabetes complications, including a composite cardiovascular disease (CVD) outcome, diabetic kidney disease (DKD), and diabetic retinopathy (DR), in the UKB study.ResultsWe identified 49 049 participants with diabetes. Among them, 1023 had type 1 diabetes (T1D), and 40 193 had type 2 diabetes (T2D). A total of 23 833 diabetes subjects had linked primary care records. There were 3237, 3113, and 4922 patients with CVD, DKD, and DR events, respectively. The risk prediction performance for each outcome was assessed, and our results are consistent with the prediction area under the ROC (receiver operating characteristic) curve (AUC) of standard risk prediction models using cohort studies.Discussion and conclusionOur publicly available pipeline and platform enable streamlined curation of incidence events, identification of time-varying risk factors underlying disease progression, and the definition of a relevant cohort for time-to-event analyses. These important steps need to be considered simultaneously to study disease progression.

Published
2023

7. A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation

Author

Vujkovic, Marijana, Ramdas, Shweta, Lorenz, Kim M, Guo, Xiuqing, Darlay, Rebecca, Cordell, Heather J, He, Jing, Gindin, Yevgeniy, Chung, Chuhan, Myers, Robert P, Schneider, Carolin V, Park, Joseph, Lee, Kyung Min, Serper, Marina, Carr, Rotonya M, Kaplan, David E, Haas, Mary E, MacLean, Matthew T, Witschey, Walter R, Zhu, Xiang, Tcheandjieu, Catherine, Kember, Rachel L, Kranzler, Henry R, Verma, Anurag, Giri, Ayush, Klarin, Derek M, Sun, Yan V, Huang, Jie, Huffman, Jennifer E, Creasy, Kate Townsend, Hand, Nicholas J, Liu, Ching-Ti, Long, Michelle T, Yao, Jie, Budoff, Matthew, Tan, Jingyi, Li, Xiaohui, Lin, Henry J, Chen, Yii-Der Ida, Taylor, Kent D, Chang, Ruey-Kang, Krauss, Ronald M, Vilarinho, Silvia, Brancale, Joseph, Nielsen, Jonas B, Locke, Adam E, Jones, Marcus B, Verweij, Niek, Baras, Aris, Reddy, K Rajender, Neuschwander-Tetri, Brent A, Schwimmer, Jeffrey B, Sanyal, Arun J, Chalasani, Naga, Ryan, Kathleen A, Mitchell, Braxton D, Gill, Dipender, Wells, Andrew D, Manduchi, Elisabetta, Saiman, Yedidya, Mahmud, Nadim, Miller, Donald R, Reaven, Peter D, Phillips, Lawrence S, Muralidhar, Sumitra, DuVall, Scott L, Lee, Jennifer S, Assimes, Themistocles L, Pyarajan, Saiju, Cho, Kelly, Edwards, Todd L, Damrauer, Scott M, Wilson, Peter W, Gaziano, J Michael, O’Donnell, Christopher J, Khera, Amit V, Grant, Struan FA, Brown, Christopher D, Tsao, Philip S, Saleheen, Danish, Lotta, Luca A, Bastarache, Lisa, Anstee, Quentin M, Daly, Ann K, Meigs, James B, Rotter, Jerome I, Lynch, Julie A, Rader, Daniel J, Voight, Benjamin F, and Chang, Kyong-Mi

Subjects
Genetics, Liver Disease, Human Genome, Digestive Diseases, Chronic Liver Disease and Cirrhosis, Aetiology, 2.1 Biological and endogenous factors, Alanine Transaminase, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Genome-Wide Association Study, Humans, Intracellular Signaling Peptides and Proteins, Lipase, Membrane Proteins, Non-alcoholic Fatty Liver Disease, Polymorphism, Single Nucleotide, Protein Serine-Threonine Kinases, Regeneron Genetics Center, Geisinger-Regeneron DiscovEHR Collaboration, EPoS Consortium, VA Million Veteran Program, Biological Sciences, Medical and Health Sciences, Developmental Biology
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. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P

Published
2022

8. Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies.

Author

Kim, Juhyun, Jensen, Aubrey, Ko, Seyoon, Raghavan, Sridharan, Phillips, Lawrence S, Hung, Adriana, Sun, Yan, Zhou, Hua, Reaven, Peter, and Zhou, Jin J

Subjects
Biomedical and Clinical Sciences, Eye Disease and Disorders of Vision, Prevention, Genetics, Human Genome, Kidney Disease, Diabetes, Cardiovascular, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, Albuminuria, Biological Specimen Banks, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Diabetic Retinopathy, Female, Humans, Male, Risk Factors, United Kingdom, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Diabetes-related complications reflect longstanding damage to small and large vessels throughout the body. In addition to the duration of diabetes and poor glycemic control, genetic factors are important contributors to the variability in the development of vascular complications. Early heritability studies found strong familial clustering of both macrovascular and microvascular complications. However, they were limited by small sample sizes and large phenotypic heterogeneity, leading to less accurate estimates. We take advantage of two independent studies-UK Biobank and the Action to Control Cardiovascular Risk in Diabetes trial-to survey the single nucleotide polymorphism heritability for diabetes microvascular (diabetic kidney disease and diabetic retinopathy) and macrovascular (cardiovascular events) complications. Heritability for diabetic kidney disease was estimated at 29%. The heritability estimate for microalbuminuria ranged from 24 to 60% and was 41% for macroalbuminuria. Heritability estimates of diabetic retinopathy ranged from 6 to 33%, depending on the phenotype definition. More severe diabetes retinopathy possessed higher genetic contributions. We show, for the first time, that rare variants account for much of the heritability of diabetic retinopathy. This study suggests that a large portion of the genetic risk of diabetes complications is yet to be discovered and emphasizes the need for additional genetic studies of diabetes complications.

Published
2022

9. Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study

Author

Downie, Carolina G, Dimos, Sofia F, Bien, Stephanie A, Hu, Yao, Darst, Burcu F, Polfus, Linda M, Wang, Yujie, Wojcik, Genevieve L, Tao, Ran, Raffield, Laura M, Armstrong, Nicole D, Polikowsky, Hannah G, Below, Jennifer E, Correa, Adolfo, Irvin, Marguerite R, Rasmussen-Torvik, Laura JF, Carlson, Christopher S, Phillips, Lawrence S, Liu, Simin, Pankow, James S, Rich, Stephen S, Rotter, Jerome I, Buyske, Steven, Matise, Tara C, North, Kari E, Avery, Christy L, Haiman, Christopher A, Loos, Ruth JF, Kooperberg, Charles, Graff, Mariaelisa, and Highland, Heather M

Subjects
Epidemiology, Health Sciences, Diabetes, Nutrition, Prevention, Clinical Research, Biotechnology, Health Disparities, Genetics, Minority Health, Human Genome, 2.1 Biological and endogenous factors, Metabolic and endocrine, Blood Glucose, Diabetes Mellitus, Type 2, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Fine-mapping, Genome-wide association study, Glucose, Glycaemic traits, HbA(1c), Insulin, Transethnic population, HbA1c, Clinical Sciences, Paediatrics and Reproductive Medicine, Public Health and Health Services, Endocrinology & Metabolism, Clinical sciences, Public health
Abstract

Aims/hypothesisType 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.MethodsWe conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.ResultsFour novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.Conclusions/interpretationOur findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.Data availabilityFull summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).

Published
2022

10. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J. F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A, Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L, Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C, Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S, Pleiness, Jacob, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D. C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Hui-Heng Sheu, Wayne, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent D., Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T, Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Lindstrom, Sara, Wang, Lu, Smith, Erin N., Gordon, William, van Hylckama Vlieg, Astrid, Brody, Jennifer A., Pattee, Jack W., Haessler, Jeffrey, Brumpton, Ben M., Chasman, Daniel I., Suchon, Pierre, Chen, Ming-Huei, Turman, Constance, Germain, Marine, Wiggins, Kerri L., MacDonald, James, Braekkan, Sigrid K., Armasu, Sebastian M., Pankratz, Nathan, Jackson, Rabecca D., Nielsen, Jonas B., Giulianini, Franco, Puurunen, Marja K., Ibrahim, Manal, Heckbert, Susan R., Bammler, Theo K., Frazer, Kelly A., McCauley, Bryan M., Taylor, Kent, Pankow, James S., Reiner, Alexander P., Gabrielsen, Maiken E., Deleuze, Jean-François, O'Donnell, Chris J., Kim, Jihye, McKnight, Barbara, Kraft, Peter, Hansen, John-Bjarne, Rosendaal, Frits R., Heit, John A., Psaty, Bruce M., Tang, Weihong, Hveem, Kristian, Ridker, Paul M., Morange, Pierre-Emmanuel, Johnson, Andrew D., Kabrhel, Christopher, AlexandreTrégouët, David, Smith, Nicholas L., de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc-Quynh, Bebo, Allison, Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Lewis, Joshua P., Rodriguez, Benjamin A. T., Polasek, Ozren, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David-Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Davies, Gail, Delgado, Graciela E., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., Osburn, William O., O'Connell, Jeffrey R., Beswick, Andrew, Kolcic, Ivana, Souto, Juan Carlos, Becker, Lewis C., Hansen, Torben, Doyle, Margaret F., Harris, Sarah E., Moissl, Angela P., Rich, Stephen S., Campbell, Harry, Stott, David J., Soria, Jose Manuel, de Maat, Moniek P. M., Brody, Lawrence C., Auer, Paul L., Ben-Shlomo, Yoav, Hayward, Caroline, Mathias, Rasika A., Kilpeläinen, Tuomas O., Lange, Leslie A., Cox, Simon R., März, Winfried, Rotter, Jerome I., Mook-Kanamori, Dennis O., Wilson, James F., van der Harst, Pim, Jukema, J. Wouter, Ikram, M. Arfan, Desch, Karl C., Sabater-Lleal, Maria, Lowenstein, Charles J., and Morrison, Alanna C.

Published
2024
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11. Metabolically Healthy/Unhealthy Overweight/Obesity Associations With Incident Heart Failure in Postmenopausal Women: The Women's Health Initiative.

Author

Cordola Hsu, Amber R, Xie, Bin, Peterson, Darleen V, LaMonte, Michael J, Garcia, Lorena, Eaton, Charles B, Going, Scott B, Phillips, Lawrence S, Manson, JoAnn E, Anton-Culver, Hoda, Wong, Nathan D, and WHI Investigators

Subjects
WHI Investigators, Humans, Hypertension, Diabetes Mellitus, Obesity, Lipids, Body Mass Index, Hospitalization, Incidence, Risk Assessment, Risk Factors, Postmenopause, Aged, Middle Aged, Female, Overweight, Heart Failure, Waist Circumference, diabetes, heart failure, obesity, postmenopause, women, Prevention, Nutrition, Aging, Clinical Research, Cardiovascular, Metabolic and endocrine, Cardiovascular System & Hematology, Biochemistry and Cell Biology, Cardiorespiratory Medicine and Haematology, Medical Physiology
Abstract

BackgroundObesity is associated with an increased risk of heart failure (HF); however, how metabolic weight groups relate to HF risk, especially in postmenopausal women, has not been demonstrated.MethodsWe included 19 412 postmenopausal women ages 50 to 79 without cardiovascular disease from the Women's Health Initiative. Normal weight was defined as a body mass index ≥18.5 and

Published
2021

12. Insulinemic and Inflammatory Dietary Patterns Show Enhanced Predictive Potential for Type 2 Diabetes Risk in Postmenopausal Women

Author

Jin, Qi, Shi, Ni, Aroke, Desmond, Lee, Dong Hoon, Joseph, Joshua J, Donneyong, Macarius, Conwell, Darwin L, Hart, Phil A, Zhang, Xuehong, Clinton, Steven K, Cruz-Monserrate, Zobeida, Brasky, Theodore M, Jackson, Rebecca, Tinker, Lesley F, Liu, Simin, Phillips, Lawrence S, Shadyab, Aladdin H, Nassir, Rami, Bao, Wei, and Tabung, Fred K

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Prevention, Aging, Diabetes, Metabolic and endocrine, Diabetes Mellitus, Type 2, Diet, Dietary Carbohydrates, Female, Glycemic Index, Humans, Postmenopause, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveThe empirical dietary index for hyperinsulinemia (EDIH) and empirical dietary inflammatory pattern (EDIP) scores assess the insulinemic and inflammatory potentials of habitual dietary patterns, irrespective of the macronutrient content, and are based on plasma insulin response or inflammatory biomarkers, respectively. The glycemic index (GI) and glycemic load (GL) assess postprandial glycemic potential based on dietary carbohydrate content. We tested the hypothesis that dietary patterns promoting hyperinsulinemia, chronic inflammation, or hyperglycemia may influence type 2 diabetes risk.Research design and methodsWe calculated dietary scores from baseline (1993-1998) food frequency questionnaires among 73,495 postmenopausal women in the Women's Health Initiative, followed through March 2019. We used multivariable-adjusted Cox regression to estimate hazard ratios (HRs) and 95% CIs for type 2 diabetes risk. We also estimated multivariable-adjusted absolute risk of type 2 diabetes.ResultsDuring a median 13.3 years of follow-up, 11,009 incident cases of type 2 diabetes were diagnosed. Participants consuming the most hyperinsulinemic or proinflammatory dietary patterns experienced greater risk of type 2 diabetes; HRs (95% CI) comparing highest to lowest dietary index quintiles were EDIH 1.49 (1.32-1.68; P trend < 0.0001) and EDIP 1.45 (1.29-1.63; P trend < 0.0001). The absolute excess incidence for the same comparison was 220 (EDIH) and 271 (EDIP) cases per 100,000 person-years. GI and GL were not associated with type 2 diabetes risk: GI 0.99 (0.88-1.12; P trend = 0.46) and GL 1.01 (0.89-1.16; P trend = 0.30).ConclusionsOur findings in this diverse cohort of postmenopausal women suggest that lowering the insulinemic and inflammatory potentials of the diet may be more effective in preventing type 2 diabetes than focusing on glycemic foods.

Published
2021

14. Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure

Author

Rasooly, Danielle, Peloso, Gina M., Pereira, Alexandre C., Dashti, Hesam, Giambartolomei, Claudia, Wheeler, Eleanor, Aung, Nay, Ferolito, Brian R., Pietzner, Maik, Farber-Eger, Eric H., Wells, Quinn Stanton, Kosik, Nicole M., Gaziano, Liam, Posner, Daniel C., Bento, A. Patrícia, Hui, Qin, Liu, Chang, Aragam, Krishna, Wang, Zeyuan, Charest, Brian, Huffman, Jennifer E., Wilson, Peter W. F., Phillips, Lawrence S., Whittaker, John, Munroe, Patricia B., Petersen, Steffen E., Cho, Kelly, Leach, Andrew R., Magariños, María Paula, Gaziano, John Michael, Langenberg, Claudia, Sun, Yan V., Joseph, Jacob, and Casas, Juan P.

Published
2023
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15. Optimization of Metformin in the GRADE Cohort: Effect on Glycemia and Body Weight

Author

Sivitz, William I, Phillips, Lawrence S, Wexler, Deborah J, Fortmann, Stephen P, Camp, Anne W, Tiktin, Margaret, Perez, Magalys, Craig, Jacqueline, Hollander, Priscilla A, Cherrington, Andrea, Aroda, Vanita R, Tan, Meng Hee, Krakoff, Jonathan, Rasouli, Neda, Butera, Nicole M, Younes, Naji, Crandall, Jill P, Diane McKee, Melissa, Brown-Friday, Janet, Xhori, Entila, Ballentine-Cargill, Keisha, Duran, Sally, Lukin, Jennifer, Beringher, Stephanie, Gonzalez de la torre, Susana, Phillips, Lawrence, Burgess, Elizabeth, Olson, Darin, Rhee, Mary, Wilson, Peter, Stephanie Raines, Tasha, Costello, Julie, Gullett, Chona, Maher-Albertelli, Maxine, Morehead, Folayan, Mungara, Radhika, Person, Saranjit, Savoye, Louise, Sibymon, Mabil, Tanukonda, Sridhar, Ann White, Carol, Holloway, Leah, Adams, Cynthia, Ross, April, Balasubramanyam, Ashok, Gonzalez, Erica, Wright, Charlyne, Hollander, Priscilla, Roe, Erin, Uy, Analyn, Burt, Polly, Estrada, Lorie, Chionh, Kris, Ismail-Beigi, Faramarz, Falck-Ytter, Corinna, Sayyed Kassem, Laure, Sood, Ajay, Cramer, Bethany, Iacoboni, Jacalyn, Kononets, Maria V, Kulow, Tanya, Newman, Cynthia, Stancil, Katherine A, Sanders, Cristina, Tucker, Lisa, Werner, Amanda, Krol, Adrienne, McPhee, Gloria, Patel, Christine, Colosimo, Linda, Goland, Robin, Pring, James, Kringas, Patricia, Tejada, Jessica, Hausheer, Camille, Schneier, Harvey, Gumpel, Kelly, Kirpitch, Amanda, Green, Jennifer B, AbouAssi, Hiba, Chatterjee, Ranee, Feinglos, Mark N, English Jones, Jennifer, Khan, Shubi A, Kimpel, Jeanne B, Zimmer, Ronna P, Furst, Mary, Satterwhite, Barbara M, Thacker, Connie R, Evans Kreider, Kathryn, Mather, Kieren J, Lteif, Amale, Hamilton, Tonya, Patel, Nick, Riera, Gabriela, Jackson, Marcia, Pirics, Vivian, Howard, Devin, and Aguillar, Danielle

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Clinical Research, Diabetes, Nutrition, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Metabolic and endocrine, Adult, Aged, Blood Glucose, Body Weight, Calibration, Comparative Effectiveness Research, Diabetes Mellitus, Type 2, Dose-Response Relationship, Drug, Drug Therapy, Combination, Female, Glycated Hemoglobin, Humans, Hypoglycemic Agents, Insulin, Liraglutide, Male, Maximum Tolerated Dose, Metformin, Middle Aged, Sitagliptin Phosphate, Sulfonylurea Compounds, Weight Loss, GRADE Research Group, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveWe evaluated the effect of optimizing metformin dosing on glycemia and body weight in type 2 diabetes.Research design and methodsThis was a prespecified analysis of 6,823 participants in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) taking metformin as the sole glucose-lowering drug who completed a 4- to 14-week (mean ± SD 7.9 ± 2.4) run-in in which metformin was adjusted to 2,000 mg/day or a maximally tolerated lower dose. Participants had type 2 diabetes for

Published
2020

16. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthma

Author

Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K., Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P., Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Daniel, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J.F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A., Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L., Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C., Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S., Pleiness, Jacob, Pollin, Toni, Post, Wendy, Powers Becker, Julia, Preethi Boorgula, Meher, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D.C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Sheu, Wayne Hui-Heng, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent, Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T., Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Williams, Scott, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Recto, Kathryn, Kachroo, Priyadarshini, Huan, Tianxiao, Lee, Gha Young, Bui, Helena, Lee, Dong Heon, Gereige, Jessica, Yao, Chen, Hwang, Shih-Jen, Joehanes, Roby, O’Connor, George T., and DeMeo, Dawn L.

Published
2023
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17. Insulin Resistance and Cancer-Specific and All-Cause Mortality in Postmenopausal Women: The Women’s Health Initiative

Author

Pan, Kathy, Nelson, Rebecca A, Wactawski-Wende, Jean, Lee, Delphine J, Manson, JoAnn E, Aragaki, Aaron K, Mortimer, Joanne E, Phillips, Lawrence S, Rohan, Thomas, Ho, Gloria YF, Saquib, Nazmus, Shadyab, Aladdin H, Nassir, Rami, Rhee, Jinnie J, Hurria, Arti, and Chlebowski, Rowan T

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Cancer, Nutrition, Clinical Research, Aging, Diabetes, Women's Health, Good Health and Well Being, Aged, Aged, 80 and over, Body Mass Index, Cause of Death, Female, Follow-Up Studies, Humans, Insulin Resistance, Middle Aged, Neoplasms, Postmenopause, Proportional Hazards Models, Public Health Surveillance, Risk Factors, United States, Oncology and Carcinogenesis, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundInsulin resistance has been proposed as a mediator of the increased cancer incidence and mortality associated with obesity. However, prior studies included limited cancer deaths and had inconsistent findings. Therefore, we evaluated insulin resistance and cancer-specific and all-cause mortality in postmenopausal women participating in the Women's Health Initiative (WHI).MethodsEligible were a subsample of 22 837 WHI participants aged 50-79 years enrolled at 40 US clinical centers from 1993 to 1998 who had baseline fasting glucose and insulin levels. Baseline insulin resistance was measured by the homeostasis model assessment of insulin resistance (HOMA-IR). Cancers were verified by central medical record review and deaths verified by medical record and death certificate review enhanced by National Death Index queries. Cox proportional hazards regression models were used to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer-specific and all-cause mortality. All statistical tests were two-sided.ResultsDuring a median of 18.9 years of follow-up, 1820 cancer deaths and 7415 total deaths occurred. Higher HOMA-IR quartile was associated with higher cancer-specific mortality (Q4 vs Q1, HR = 1.26, 95% CI = 1.09 to 1.47; Ptrend = .003) and all-cause mortality (Q4 vs Q1, HR = 1.63, 95% CI = 1.51 to 1.76; Ptrend < .001). A sensitivity analysis for diabetes status did not change findings. Among women with body mass index less than 25 kg/m2, higher HOMA-IR quartile was associated with higher cancer mortality (Fine and Gray, P = .004).ConclusionsHigh insulin resistance, as measured by HOMA-IR, identifies postmenopausal women at higher risk for cancer-specific and all-cause mortality who could potentially benefit from early intervention.

Published
2020

20. Tuberculosis and Increased Incidence of Cardiovascular Disease: Cohort Study Using United States and United Kingdom Health Records.

Author

Critchley, Julia A, Limb, Elizabeth S, Khakharia, Anjali, Carey, Iain M, Auld, Sara C, Wilde, Stephen De, Harris, Tess, Phillips, Lawrence S, Cook, Derek G, Rhee, Mary K, Chaudhry, Umar A R, Bowen, Liza, and Magee, Matthew J

Subjects
TUBERCULOSIS complications, RISK assessment, CARDIOVASCULAR diseases, RESEARCH funding, CARDIOVASCULAR diseases risk factors, RETROSPECTIVE studies, LONGITUDINAL method, MEDICAL records, ACQUISITION of data
Abstract

Background Limited evidence suggests elevated risks of cardiovascular disease (CVD) among people diagnosed with tuberculosis (TB) disease, though studies have not adjusted for preexisting CVD risk. We carried out a cohort study using 2 separate datasets, estimating CVD incidence in people with TB versus those without. Methods Using data from the United States (Veterans Health Administration) and the United Kingdom (Clinical Practice Research Datalink) for 2000–2020, we matched adults with incident TB disease and no CVD history 2 years before TB diagnosis (US, n = 2121; UK, n = 15 820) with up to 10 people without TB on the basis of age, sex, race/ethnicity and healthcare practice. Participants were followed beginning 2 years before TB diagnosis and for 2 years subsequently. The acute period was defined as 3 months before/after TB diagnosis. TB, CVD, and covariates were identified from electronic routinely collected data (primary and secondary care; mortality). Poisson models estimated incident rate ratios for CVD events in people with TB compared to those without. Results CVD incidence was consistently higher in people with TB, including during the baseline period (pre-TB) and particularly in the acute period: incident rate ratios were US, 3.5 (95% confidence interval, 2.7–4.4), and UK, 2.7 (2.2–3.3). Rate ratios remained high after adjusting for differences in preexisting CVD risk: US, 3.2 (2.2–4.4); UK, 1.6 (1.2–2.1). Conclusions Increased CVD incidence was observed in people with TB versus those without, especially within months of TB diagnosis, persistent after adjustment for differences in preexisting risk. Enhancing CVD screening and risk management may improve long-term outcomes in people with TB. [ABSTRACT FROM AUTHOR]

Published
2025
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21. HEART FAILURE INCIDENCE ACCORDING TO PRESENCE OF METABOLICALLY HEALTHY/UNHEALTHY NORMAL WEIGHT AND OVERWEIGHT/OBESITY IN POSTMENOPAUSAL WOMEN: THE WOMEN'S HEALTH INITIATIVE (WHI)

Author

Hsu, Amber R Cordola, Ames, Susan L, Xie, Bin, Peterson, Darleen V, LaMonte, Michael J, Garcia, Lorena, Eaton, Charles B, Going, Scott B, Phillips, Lawrence S, Manson, Joann E, Anton-Culver, Hoda, and Wong, Nathan D

Subjects
Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology
Published
2019

22. Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure

Author

Levin, Michael G., Tsao, Noah L., Singhal, Pankhuri, Liu, Chang, Vy, Ha My T., Paranjpe, Ishan, Backman, Joshua D., Bellomo, Tiffany R., Bone, William P., Biddinger, Kiran J., Hui, Qin, Dikilitas, Ozan, Satterfield, Benjamin A., Yang, Yifan, Morley, Michael P., Bradford, Yuki, Burke, Megan, Reza, Nosheen, Charest, Brian, Judy, Renae L., Puckelwartz, Megan J., Hakonarson, Hakon, Khan, Atlas, Kottyan, Leah C., Kullo, Iftikhar, Luo, Yuan, McNally, Elizabeth M., Rasmussen-Torvik, Laura J., Day, Sharlene M., Do, Ron, Phillips, Lawrence S., Ellinor, Patrick T., Nadkarni, Girish N., Ritchie, Marylyn D., Arany, Zoltan, Cappola, Thomas P., Margulies, Kenneth B., Aragam, Krishna G., Haggerty, Christopher M., Joseph, Jacob, Sun, Yan V., Voight, Benjamin F., and Damrauer, Scott M.

Published
2022
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23. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author

Winkler, Thomas W., Rasheed, Humaira, Teumer, Alexander, Gorski, Mathias, Rowan, Bryce X., Stanzick, Kira J., Thomas, Laurent F., Tin, Adrienne, Hoppmann, Anselm, Chu, Audrey Y., Tayo, Bamidele, Thio, Chris H. L., Cusi, Daniele, Chai, Jin-Fang, Sieber, Karsten B., Horn, Katrin, Li, Man, Scholz, Markus, Cocca, Massimiliano, Wuttke, Matthias, van der Most, Peter J., Yang, Qiong, Ghasemi, Sahar, Nutile, Teresa, Li, Yong, Pontali, Giulia, Günther, Felix, Dehghan, Abbas, Correa, Adolfo, Parsa, Afshin, Feresin, Agnese, de Vries, Aiko P. J., Zonderman, Alan B., Smith, Albert V., Oldehinkel, Albertine J., De Grandi, Alessandro, Rosenkranz, Alexander R., Franke, Andre, Teren, Andrej, Metspalu, Andres, Hicks, Andrew A., Morris, Andrew P., Tönjes, Anke, Morgan, Anna, Podgornaia, Anna I., Peters, Annette, Körner, Antje, Mahajan, Anubha, Campbell, Archie, Freedman, Barry I., Spedicati, Beatrice, Ponte, Belen, Schöttker, Ben, Brumpton, Ben, Banas, Bernhard, Krämer, Bernhard K., Jung, Bettina, Åsvold, Bjørn Olav, Smith, Blair H., Ning, Boting, Penninx, Brenda W. J. H., Vanderwerff, Brett R., Psaty, Bruce M., Kammerer, Candace M., Langefeld, Carl D., Hayward, Caroline, Spracklen, Cassandra N., Robinson-Cohen, Cassianne, Hartman, Catharina A., Lindgren, Cecilia M., Wang, Chaolong, Sabanayagam, Charumathi, Heng, Chew-Kiat, Lanzani, Chiara, Khor, Chiea-Chuen, Cheng, Ching-Yu, Fuchsberger, Christian, Gieger, Christian, Shaffer, Christian M., Schulz, Christina-Alexandra, Willer, Cristen J., Chasman, Daniel I., Gudbjartsson, Daniel F., Ruggiero, Daniela, Toniolo, Daniela, Czamara, Darina, Porteous, David J., Waterworth, Dawn M., Mascalzoni, Deborah, Mook-Kanamori, Dennis O., Reilly, Dermot F., Daw, E. Warwick, Hofer, Edith, Boerwinkle, Eric, Salvi, Erika, Bottinger, Erwin P., Tai, E-Shyong, Catamo, Eulalia, Rizzi, Federica, Guo, Feng, Rivadeneira, Fernando, Guilianini, Franco, Sveinbjornsson, Gardar, Ehret, Georg, Waeber, Gerard, Biino, Ginevra, Girotto, Giorgia, Pistis, Giorgio, Nadkarni, Girish N., Delgado, Graciela E., Montgomery, Grant W., Snieder, Harold, Campbell, Harry, White, Harvey D., Gao, He, Stringham, Heather M., Schmidt, Helena, Li, Hengtong, Brenner, Hermann, Holm, Hilma, Kirsten, Holgen, Kramer, Holly, Rudan, Igor, Nolte, Ilja M., Tzoulaki, Ioanna, Olafsson, Isleifur, Martins, Jade, Cook, James P., Wilson, James F., Halbritter, Jan, Felix, Janine F., Divers, Jasmin, Kooner, Jaspal S., Lee, Jeannette Jen-Mai, O’Connell, Jeffrey, Rotter, Jerome I., Liu, Jianjun, Xu, Jie, Thiery, Joachim, Ärnlöv, Johan, Kuusisto, Johanna, Jakobsdottir, Johanna, Tremblay, Johanne, Chambers, John C., Whitfield, John B., Gaziano, John M., Marten, Jonathan, Coresh, Josef, Jonas, Jost B., Mychaleckyj, Josyf C., Christensen, Kaare, Eckardt, Kai-Uwe, Mohlke, Karen L., Endlich, Karlhans, Dittrich, Katalin, Ryan, Kathleen A., Rice, Kenneth M., Taylor, Kent D., Ho, Kevin, Nikus, Kjell, Matsuda, Koichi, Strauch, Konstantin, Miliku, Kozeta, Hveem, Kristian, Lind, Lars, Wallentin, Lars, Yerges-Armstrong, Laura M., Raffield, Laura M., Phillips, Lawrence S., Launer, Lenore J., Lyytikäinen, Leo-Pekka, Lange, Leslie A., Citterio, Lorena, Klaric, Lucija, Ikram, M. Arfan, Ising, Marcus, Kleber, Marcus E., Francescatto, Margherita, Concas, Maria Pina, Ciullo, Marina, Piratsu, Mario, Orho-Melander, Marju, Laakso, Markku, Loeffler, Markus, Perola, Markus, de Borst, Martin H., Gögele, Martin, Bianca, Martina La, Lukas, Mary Ann, Feitosa, Mary F., Biggs, Mary L., Wojczynski, Mary K., Kavousi, Maryam, Kanai, Masahiro, Akiyama, Masato, Yasuda, Masayuki, Nauck, Matthias, Waldenberger, Melanie, Chee, Miao-Li, Chee, Miao-Ling, Boehnke, Michael, Preuss, Michael H., Stumvoll, Michael, Province, Michael A., Evans, Michele K., O’Donoghue, Michelle L., Kubo, Michiaki, Kähönen, Mika, Kastarinen, Mika, Nalls, Mike A., Kuokkanen, Mikko, Ghanbari, Mohsen, Bochud, Murielle, Josyula, Navya Shilpa, Martin, Nicholas G., Tan, Nicholas Y. Q., Palmer, Nicholette D., Pirastu, Nicola, Schupf, Nicole, Verweij, Niek, Hutri-Kähönen, Nina, Mononen, Nina, Bansal, Nisha, Devuyst, Olivier, Melander, Olle, Raitakari, Olli T., Polasek, Ozren, Manunta, Paolo, Gasparini, Paolo, Mishra, Pashupati P., Sulem, Patrick, Magnusson, Patrik K. E., Elliott, Paul, Ridker, Paul M., Hamet, Pavel, Svensson, Per O., Joshi, Peter K., Kovacs, Peter, Pramstaller, Peter P., Rossing, Peter, Vollenweider, Peter, van der Harst, Pim, Dorajoo, Rajkumar, Sim, Ralene Z. H., Burkhardt, Ralph, Tao, Ran, Noordam, Raymond, Mägi, Reedik, Schmidt, Reinhold, de Mutsert, Renée, Rueedi, Rico, van Dam, Rob M., Carroll, Robert J., Gansevoort, Ron T., Loos, Ruth J. F., Felicita, Sala Cinzia, Sedaghat, Sanaz, Padmanabhan, Sandosh, Freitag-Wolf, Sandra, Pendergrass, Sarah A., Graham, Sarah E., Gordon, Scott D., Hwang, Shih-Jen, Kerr, Shona M., Vaccargiu, Simona, Patil, Snehal B., Hallan, Stein, Bakker, Stephan J. L., Lim, Su-Chi, Lucae, Susanne, Vogelezang, Suzanne, Bergmann, Sven, Corre, Tanguy, Ahluwalia, Tarunveer S., Lehtimäki, Terho, Boutin, Thibaud S., Meitinger, Thomas, Wong, Tien-Yin, Bergler, Tobias, Rabelink, Ton J., Esko, Tõnu, Haller, Toomas, Thorsteinsdottir, Unnur, Völker, Uwe, Foo, Valencia Hui Xian, Salomaa, Veikko, Vitart, Veronique, Giedraitis, Vilmantas, Gudnason, Vilmundur, Jaddoe, Vincent W. V., Huang, Wei, Zhang, Weihua, Wei, Wen Bin, Kiess, Wieland, März, Winfried, Koenig, Wolfgang, Lieb, Wolfgang, Gao, Xin, Sim, Xueling, Wang, Ya Xing, Friedlander, Yechiel, Tham, Yih-Chung, Kamatani, Yoichiro, Okada, Yukinori, Milaneschi, Yuri, Yu, Zhi, Stark, Klaus J., Stefansson, Kari, Böger, Carsten A., Hung, Adriana M., Kronenberg, Florian, Köttgen, Anna, Pattaro, Cristian, and Heid, Iris M.

Published
2022
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24. Genomics and phenomics of body mass index reveals a complex disease network

Author

Huang, Jie, Huffman, Jennifer E., Huang, Yunfeng, Do Valle, Ítalo, Assimes, Themistocles L., Raghavan, Sridharan, Voight, Benjamin F., Liu, Chang, Barabási, Albert-László, Huang, Rose D. L., Hui, Qin, Nguyen, Xuan-Mai T., Ho, Yuk-Lam, Djousse, Luc, Lynch, Julie A., Vujkovic, Marijana, Tcheandjieu, Catherine, Tang, Hua, Damrauer, Scott M., Reaven, Peter D., Miller, Donald, Phillips, Lawrence S., Ng, Maggie C. Y., Graff, Mariaelisa, Haiman, Christopher A., Loos, Ruth J. F., North, Kari E., Yengo, Loic, Smith, George Davey, Saleheen, Danish, Gaziano, J. Michael, Rader, Daniel J., Tsao, Philip S., Cho, Kelly, Chang, Kyong-Mi, Wilson, Peter W. F., Sun, Yan V., and O’Donnell, Christopher J.

Published
2022
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26. Branched-chain amino acid, meat intake and risk of type 2 diabetes in the Women’s Health Initiative

Author

Isanejad, Masoud, LaCroix, Andrea Z, Thomson, Cynthia A, Tinker, Lesley, Larson, Joseph C, Qi, Qibin, Qi, Lihong, Cooper-DeHoff, Rhonda M, Phillips, Lawrence S, Prentice, Ross L, and Beasley, Jeannette M

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Diabetes, Prevention, Metabolic and endocrine, Aged, Amino Acids, Branched-Chain, Diabetes Mellitus, Type 2, Diet, Dietary Proteins, Energy Intake, Feeding Behavior, Female, Follow-Up Studies, Humans, Meat, Middle Aged, Proportional Hazards Models, Risk Factors, Surveys and Questionnaires, Women's Health, Branched chained amino acids, Type 2 diabetes, Meat intake, Dietary protein intake, BCAA branched-chain amino acid, CT clinical trial, HR hazard ratios, NBS Nutritional Biomarkers Study, OS observational study, T2D type 2 diabetes, WHI Women’s Health Initiative, Animal Production, Food Sciences, Nutrition & Dietetics, Animal production, Food sciences, Nutrition and dietetics
Abstract

Knowledge regarding association of dietary branched-chain amino acid (BCAA) and type 2 diabetes (T2D), and the contribution of BCAA from meat to the risk of T2D are scarce. We evaluated associations between dietary BCAA intake, meat intake, interaction between BCAA and meat intake and risk of T2D. Data analyses were performed for 74 155 participants aged 50-79 years at baseline from the Women's Health Initiative for up to 15 years of follow-up. We excluded from analysis participants with treated T2D, and factors potentially associated with T2D or missing covariate data. The BCAA and total meat intake was estimated from FFQ. Using Cox proportional hazards models, we assessed the relationship between BCAA intake, meat intake, and T2D, adjusting for confounders. A 20 % increment in total BCAA intake (g/d and %energy) was associated with a 7 % higher risk for T2D (hazard ratio (HR) 1·07; 95 % CI 1·05, 1·09). For total meat intake, a 20 % increment was associated with a 4 % higher risk of T2D (HR 1·04; 95 % CI 1·03, 1·05). The associations between BCAA intake and T2D were attenuated but remained significant after adjustment for total meat intake. These relations did not materially differ with or without adjustment for BMI. Our results suggest that dietary BCAA and meat intake are positively associated with T2D among postmenopausal women. The association of BCAA and diabetes risk was attenuated but remained positive after adjustment for meat intake suggesting that BCAA intake in part but not in full is contributing to the association of meat with T2D risk.

Published
2017

27. Association between Dietary Energy Density and Incident Type 2 Diabetes in the Women’s Health Initiative

Author

Hingle, Melanie D, Wertheim, Betsy C, Neuhouser, Marian L, Tinker, Lesley F, Howard, Barbara V, Johnson, Karen, Liu, Simin, Phillips, Lawrence S, Qi, Lihong, Sarto, Gloria, Turner, Tami, Waring, Molly E, and Thomson, Cynthia A

Subjects
Biomedical and Clinical Sciences, Epidemiology, Public Health, Health Sciences, Nutrition and Dietetics, Clinical Research, Diabetes, Aging, Nutrition, Prevention, Obesity, Metabolic and endocrine, Aged, Body Mass Index, Diabetes Mellitus, Type 2, Diet, Energy Intake, Female, Humans, Middle Aged, Nutrition Assessment, Postmenopause, Prospective Studies, Risk Factors, Surveys and Questionnaires, United States, Waist Circumference, Women's Health, Dietary energy density, Type 2 diabetes, Postmenopausal women, Dietary behavior, Diabetes prevention, Clinical Sciences, Anthropology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundDietary energy density, or energy available in relation to gram intake, can inform disease risk.ObjectiveThe objective of this study was to investigate the association between baseline dietary energy density and risk of incident type 2 diabetes in postmenopausal women.DesignDietary energy density, weight status, and type 2 diabetes incidence were prospectively characterized in a large cohort of postmenopausal women participating in one or more clinical trials or an observational study.Participants/settingThe study involved 161,808 postmenopausal women recruited to the Women's Health Initiative observational study or clinical trials at 40 centers across the United States between 1993 and 1998.Main outcome measuresThe primary outcome was incident type 2 diabetes.Statistical analyses performedThe association between dietary energy density quintiles and incident diabetes was tested using Cox proportional hazards regression.ResultsA total of 143,204 participants without self-reported diabetes at enrollment completed baseline dietary assessment and were followed for 12.7±4.6 years. Risk of diabetes developing was 24% greater for women in the highest dietary energy density quintile compared with the lowest after adjusting for confounders (95% CI 1.17 to 1.32). Body mass index (calculated as kg/m2) and waist circumference mediated the relationship between dietary energy density and diabetes. In waist circumference-stratified analysis, women in dietary energy density quintiles 2 to 5 with waist circumferences >88 cm were at 9% to 12% greater risk of diabetes developing compared with women with waist circumference ≤88 cm.ConclusionsIn this prospective study, a higher baseline dietary energy density was associated with higher incidence of type 2 diabetes among postmenopausal women, both overall, and in women with elevated waist circumference.

Published
2017

28. Genetic discovery and risk characterization in type 2 diabetes across diverse populations

Author

Polfus, Linda M., Darst, Burcu F., Highland, Heather, Sheng, Xin, Ng, Maggie C.Y., Below, Jennifer E., Petty, Lauren, Bien, Stephanie, Sim, Xueling, Wang, Wei, Fontanillas, Pierre, Patel, Yesha, Preuss, Michael, Schurmann, Claudia, Du, Zhaohui, Lu, Yingchang, Rhie, Suhn K., Mercader, Joseph M., Tusie-Luna, Teresa, González-Villalpando, Clicerio, Orozco, Lorena, Spracklen, Cassandra N., Cade, Brian E., Jensen, Richard A., Sun, Meng, Joo, Yoonjung Yoonie, An, Ping, Yanek, Lisa R., Bielak, Lawrence F., Tajuddin, Salman, Nicolas, Aude, Chen, Guanjie, Raffield, Laura, Guo, Xiuqing, Chen, Wei-Min, Nadkarni, Girish N., Graff, Mariaelisa, Tao, Ran, Pankow, James S., Daviglus, Martha, Qi, Qibin, Boerwinkle, Eric A., Liu, Simin, Phillips, Lawrence S., Peters, Ulrike, Carlson, Chris, Wikens, Lynne R., Le Marchand, Loic, North, Kari E., Buyske, Steven, Kooperberg, Charles, Loos, Ruth J.F., Stram, Daniel O., and Haiman, Christopher A.

Published
2021
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29. Glycemia reduction in type 2 diabetes—Hypoglycemia outcomes: A randomized clinical trial.

Author

Seaquist, Elizabeth R., Phillips, Lawrence S., Ghosh, Alokananda, Baker, Chelsea, Bergenstal, Richard M., Crandall, Jill P., Goland, Robin S., Gramzinski, Michaela R., Hox, Sophia H., Hsia, Daniel S., Johnson, Mary L., Lachin, John M., Raskin, Philip, Valencia, Willy M., Waltje, Andrea H., and Younes, Naji

Subjects
*TYPE 2 diabetes, *CLINICAL trials, *HYPOGLYCEMIA, *SITAGLIPTIN, *GLYCOSYLATED hemoglobin
Abstract

Objective: Hypoglycemia is a major concern in type 2 diabetes (T2DM), but little is known about its likelihood compared across common therapies. We compared the likelihood of hypoglycemia among metformin-treated patients with T2DM randomized to the addition of one of 4 common therapies. Research design & methods: Randomized, controlled trial of 5,047 participants with T2DM of <10 years' duration, hemoglobin A1c (HbA1c) 6.8–8.5% (50.8–69.4 mmol/mol). Randomization to addition of glargine U100, glimepiride, liraglutide, or sitagliptin over 5.0 ± 1.3 (mean ± SD) years. HbA1c was measured quarterly; if a level >7.5% (>58.5 mmol/mol) was confirmed, rescue glargine and/or aspart insulin was added. We conducted a per-protocol analysis of 4,830, who attended at least one post-baseline visit and took at least one dose of assigned study medication. We assessed severe hypoglycemia events reported throughout the entire study. At quarterly visits, all participants were asked about hypoglycemic symptoms within the last 30 days, and those in the glargine and glimepiride groups were asked for any measured glucose <70 mg/dL (3.9 mmol/L) within this time period. Results: While participants were taking their assigned medications, severe hypoglycemia occurred in 10 (0.8%), 16 (1.3%), 6 (0.5%), and 4 (0.3%), (p<0.05) and hypoglycemic symptoms in 659 (54.2%), 833 (68.3%), 375 (32.4%), and 361 (29.1%) of participants following randomization to glargine, glimepiride, liraglutide, and sitagliptin, respectively (p<0.001). Conclusions: In metformin-treated patients with T2DM who add a second medication, hypoglycemia is most likely with addition of glimepiride, less with glargine, and least likely with liraglutide and sitagliptin. Trial registration: ClinicalTrials.gov Identifier: NCT01794143. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Review of methods for detecting glycemic disorders

Author

Bergman, Michael, Abdul-Ghani, Muhammad, DeFronzo, Ralph A., Manco, Melania, Sesti, Giorgio, Fiorentino, Teresa Vanessa, Ceriello, Antonio, Rhee, Mary, Phillips, Lawrence S., Chung, Stephanie, Cravalho, Celeste, Jagannathan, Ram, Monnier, Louis, Colette, Claude, Owens, David, Bianchi, Cristina, del Prato, Stefano, Monteiro, Mariana P., Neves, João Sérgio, Medina, Jose Luiz, Macedo, Maria Paula, Ribeiro, Rogério Tavares, Filipe Raposo, João, Dorcely, Brenda, Ibrahim, Nouran, and Buysschaert, Martin

Published
2020
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34. No Increase in Fractures After Stopping Hormone Therapy: Results From the Women’s Health Initiative

Author

Watts, Nelson B, Cauley, Jane A, Jackson, Rebecca D, LaCroix, Andrea Z, Lewis, Cora E, Manson, JoAnn E, Neuner, Joan M, Phillips, Lawrence S, Stefanick, Marcia L, Wactawski-Wende, Jean, and Crandall, Carolyn

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Clinical Sciences, Cancer, Clinical Trials and Supportive Activities, Estrogen, Clinical Research, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Good Health and Well Being, Female, Follow-Up Studies, Hip Fractures, Hormone Replacement Therapy, Humans, Middle Aged, Osteoporosis, Postmenopausal, Postmenopause, Prognosis, Withholding Treatment, Women's Health, Women’s Health Initiative Investigators, Paediatrics and Reproductive Medicine, Endocrinology & Metabolism, Clinical sciences
Abstract

ContextThe Women's Health Initiative (WHI) hormone therapy (HT) trials showed protection against hip and total fractures, but a later observational report suggested loss of benefit and a rebound increased risk after cessation of HT.ObjectiveThe purpose of this study was to examine fractures after discontinuation of HT.Design and settingTwo placebo-controlled randomized trials served as the study setting.PatientsStudy patients included WHI participants (N = 15,187) who continued active HT or placebo through the intervention period and who did not take HT in the postintervention period.InterventionsTrial interventions included conjugated equine estrogen (CEE) plus medroxyprogesterone acetate (MPA) in naturally menopausal women and CEE alone in women with prior hysterectomy.Main outcome measuresTotal fractures and hip fractures through 5 years after discontinuation of HT were recorded.ResultsHip fractures were infrequent (∼2.5 per 1000 person-years); this finding was similar between trials and in former HT and placebo groups. There was no difference in total fractures in the CEE + MPA trial for former HT vs former placebo users (28.9 per 1000 person-years and 29.9 per 1000 person-years, respectively; hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.87 to 1.09; P = 0.63); however, in the CEE-alone trial, total fractures were higher in former placebo users (36.9 per 1000 person-years) compared with the former active group (31.1 per 1000 person-years), a finding that was suggestive of a residual benefit of CEE against total fractures (HR, 0.85; 95% CI, 0.73 to 0.98; P = 0.03).ConclusionsWe found no evidence for increased fracture risk, either sustained or transient, for former HT users compared with former placebo users after stopping HT. There was residual benefit for total fractures in former HT users from the CEE-alone study.

Published
2017

35. Multiple Healthful Dietary Patterns and Type 2 Diabetes in the Women's Health Initiative

Author

Cespedes, Elizabeth M, Hu, Frank B, Tinker, Lesley, Rosner, Bernard, Redline, Susan, Garcia, Lorena, Hingle, Melanie, Van Horn, Linda, Howard, Barbara V, Levitan, Emily B, Li, Wenjun, Manson, JoAnn E, Phillips, Lawrence S, Rhee, Jinnie J, Waring, Molly E, and Neuhouser, Marian L

Subjects
Public Health, Health Sciences, Obesity, Diabetes, Aging, Nutrition, Prevention, Management of diseases and conditions, 7.1 Individual care needs, Cardiovascular, Metabolic and endocrine, Aged, Diabetes Mellitus, Type 2, Diet, Female, Follow-Up Studies, Humans, Middle Aged, Postmenopause, United States, Alternate Healthy Eating Index, Alternate Mediterranean Diet Index, Dietary Approaches to Stop Hypertension Index, dietary patterns, health disparities, Healthy Eating Index, type 2 diabetes, women's health, Mathematical Sciences, Medical and Health Sciences, Epidemiology
Abstract

The relationship between various diet quality indices and risk of type 2 diabetes (T2D) remains unsettled. We compared associations of 4 diet quality indices--the Alternate Mediterranean Diet Index, Healthy Eating Index 2010, Alternate Healthy Eating Index 2010, and the Dietary Approaches to Stop Hypertension (DASH) Index--with reported T2D in the Women's Health Initiative, overall, by race/ethnicity, and with/without adjustment for overweight/obesity at enrollment (a potential mediator). This cohort (n = 101,504) included postmenopausal women without T2D who completed a baseline food frequency questionnaire from which the 4 diet quality index scores were derived. Higher scores on the indices indicated a better diet. Cox regression was used to estimate multivariate hazard ratios for T2D. Pearson coefficients for correlation among the indices ranged from 0.55 to 0.74. Follow-up took place from 1993 to 2013. During a median 15 years of follow-up, 10,815 incident cases of T2D occurred. For each diet quality index, a 1-standard-deviation higher score was associated with 10%-14% lower T2D risk (P < 0.001). Adjusting for overweight/obesity at enrollment attenuated but did not eliminate associations to 5%-10% lower risk per 1-standard-deviation higher score (P < 0.001). For all 4 dietary indices examined, higher scores were inversely associated with T2D overall and across racial/ethnic groups. Multiple forms of a healthful diet were inversely associated with T2D in these postmenopausal women.

Published
2016

36. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis

Author

Vujkovic, Marijana, Keaton, Jacob M., Lynch, Julie A., Miller, Donald R., Zhou, Jin, Tcheandjieu, Catherine, Huffman, Jennifer E., Assimes, Themistocles L., Lorenz, Kimberly, Zhu, Xiang, Hilliard, Austin T., Judy, Renae L., Huang, Jie, Lee, Kyung M., Klarin, Derek, Pyarajan, Saiju, Danesh, John, Melander, Olle, Rasheed, Asif, Mallick, Nadeem H., Hameed, Shahid, Qureshi, Irshad H., Afzal, Muhammad Naeem, Malik, Uzma, Jalal, Anjum, Abbas, Shahid, Sheng, Xin, Gao, Long, Kaestner, Klaus H., Susztak, Katalin, Sun, Yan V., DuVall, Scott L., Cho, Kelly, Lee, Jennifer S., Gaziano, J. Michael, Phillips, Lawrence S., Meigs, James B., Reaven, Peter D., Wilson, Peter W., Edwards, Todd L., Rader, Daniel J., Damrauer, Scott M., O’Donnell, Christopher J., Tsao, Philip S., Chang, Kyong-Mi, Voight, Benjamin F., and Saleheen, Danish

Published
2020
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37. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

Author

Abe, Namiko, Abecasis, Goncalo, Albert, Christine, Palmer Allred, Nicholette (Nichole), Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Arking, Dan, Arnett, Donna K., Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Beaty, Terri, Becker, Diane, Becker, Lewis, Beer, Rebecca, Begum, Ferdouse, Beitelshees, Amber, Benjamin, Emelia, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Borecki, Ingrid, Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Burchard, Esteban, Cardwell, Jonathan, Carty, Cara, Casaburi, Richard, Casella, James, Chaffin, Mark, Chang, Christy, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Chen, Yii-Der Ida, Cho, Michael H., Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, Das, Sayantan, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Do, Ron, Duan, Qing, Duggirala, Ravi, Durda, Peter, Dutcher, Susan, Eaton, Charles, Ekunwe, Lynette, Ellinor, Patrick, Emery, Leslie, Farber, Charles, Farnam, Leanna, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Yan, Gass, Margery, Gelb, Bruce, Geng, Xiaoqi (Priscilla), Germer, Soren, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Haessler, Jeff, Hall, Michael, Harris, Daniel, Hawley, Nicola, He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hokanson, John, Holly, Kramer, Hong, Elliott, Hoth, Karin, (Agnes) Hsiung, Chao, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Jhun, Min A., Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kachroo, Priyadarshini, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kathiresan, Sekar, Kaufman, Laura, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Krauter, Stephanie, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Seunggeun Shawn, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Yun, Lin, Honghuang, Lin, Keng Han, Liu, Simin, Liu, Yongmei, Loos, Ruth, Lubitz, Steven, Lunetta, Kathryn, Luo, James, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manson, JoAnn, Margolin, Lauren, Martin, Lisa, Mathai, Susan, Mathias, Rasika, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, Mei, Hao, Meyers, Deborah A., Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L., Mitchell, Braxton, Montasser, May E., Musani, Solomon, Mwasongwe, Stanford, Mychaleckyj, Josyf C., Nadkarni, Girish, Naik, Rakhi, Natarajan, Pradeep, Nekhai, Sergei, Nickerson, Deborah, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Pankow, James, Papanicolaou, George, Parker, Margaret, Parsa, Afshin, Penchev, Sara, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S., Phillips, Sam, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Prokopenko, Dmitry, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Ramachandran, Vasan, Rao, D.C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Regan, Elizabeth, Reiner, Alex, Rice, Ken, Rich, Stephen, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sakornsakolpat, Phuwanat, Salimi, Shabnam, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay, Scheller, Christopher, Schmidt, Ellen, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sheehan, Vivien, Shetty, Amol, Shetty, Aniket, Sheu, Wayne Hui-Heng, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne, Streeten, Elizabeth, Sung, Yun Ju, Su-Lasky, Jessica, Sylvia, Jody, Szpiro, Adam, Sztalryd, Carole, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wan, Emily, Wang, Fei Fei, Watson, Karol, Weeks, Daniel E., Weir, Bruce, Weiss, Scott, Weng, Lu-Chen, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Wong, Quenna, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yang, Rongze, Zaghloul, Norann, Zekavat, Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zheng, Xiuwen, Zhi, Degui, Zhou, Xiang, Zody, Michael, Zoellner, Sebastian, Hecker, Julian, Chawes, Bo L., Ahluwalia, Tarunveer S., Kelly, Rachel S., Chu, Su H., Virkud, Yamini V., Huang, Mengna, Barnes, Kathleen C., Burchard, Esteban G., Eng, Celeste, Hu, Donglei, Celedón, Juan C., Levin, Albert M., Gui, Hongsheng, Forno, Erick, Mak, Angel C.Y., Avila, Lydiana, Soto-Quiros, Manuel E., Cloutier, Michelle M., Acosta-Pérez, Edna, Canino, Glorisa, Bønnelykke, Klaus, Bisgaard, Hans, Raby, Benjamin A., Weiss, Scott T., and Lasky-Su, Jessica A.

Published
2019
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40. A Multivariable Mendelian Randomization Study of Systolic and Diastolic Blood Pressure, Lipid Profile, and Heart Failure Subtypes.

Author

Liu, Chang, Hui, Qin, Wells, Quinn S., Farber-Eger, Eric, Gaziano, John Michael, Wilson, Peter W. F., Quyyumi, Arshed A., Vaccarino, Viola, Hu, Yi-Juan, Benkeser, David, Phillips, Lawrence S., Joseph, Jacob, and Sun, Yan V.

Subjects
DIASTOLIC blood pressure, LDL cholesterol, GENOME-wide association studies, BLOOD lipids, BLOOD pressure, NEPRILYSIN
Abstract

Heart failure (HF) is a significant health burden, with two major clinical subtypes: HF with reduced (HFrEF) and preserved ejection fraction (HFpEF). Blood pressure and lipid profile are established risk factors of HF. We performed univariable and multivariable Mendelian randomization (MR) analyses to assess potential causal effects of blood pressures and lipids on HF subtypes. Genetic instruments for blood pressures and lipids were derived from genome-wide association studies (GWASs) among the European participants of the UK Biobank. GWAS summaries of HFrEF and HFpEF were obtained from the meta-analysis of the European participants from the Million Veteran Program and the Vanderbilt University DNA Databank. Systolic blood pressure exhibited a supportive MR association primarily with HFpEF (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.04–1.23), while diastolic blood pressure had an independent MR association with HFrEF (OR, 1.43; 95% CI, 1.13–1.77). MR associations also supported the observation that higher levels of low-density lipoprotein cholesterol increase the risk for both subtypes (HFrEF OR, 1.10 and 95% CI, 1.05–1.17; HFpEF OR, 1.05 and 95% CI, 1.02–1.09). These findings underscore differences in HF subtype-specific risk profiles and mechanisms, which may lead to different interventional strategies for different HF subtypes. [ABSTRACT FROM AUTHOR]

Published
2024
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42. All-Cause, Cardiovascular, and Cancer Mortality Rates in Postmenopausal White, Black, Hispanic, and Asian Women With and Without Diabetes in the United StatesThe Women's Health Initiative, 1993–2009

Author

Ma, Yunsheng, Hébert, James R, Balasubramanian, Raji, Wedick, Nicole M, Howard, Barbara V, Rosal, Milagros C, Liu, Simin, Bird, Chloe E, Olendzki, Barbara C, Ockene, Judith K, Wactawski-Wende, Jean, Phillips, Lawrence S, LaMonte, Michael J, Schneider, Kristin L, Garcia, Lorena, Ockene, Ira S, Merriam, Philip A, Sepavich, Deidre M, Mackey, Rachel H, Johnson, Karen C, and Manson, JoAnn E

Subjects
Aging, Prevention, Diabetes, Cancer, Clinical Research, Metabolic and endocrine, Good Health and Well Being, African Americans, Aged, Asian Americans, Body Weights and Measures, Cardiovascular Diseases, Diabetes Mellitus, Diet, Estrogen Replacement Therapy, Exercise, Female, Hispanic or Latino, Humans, Middle Aged, Neoplasms, Postmenopause, Proportional Hazards Models, Racial Groups, Residence Characteristics, Risk Factors, Smoking, United States, Whites, diabetes, health disparities, menopause, mortality, obesity, womens health, White People, Black or African American, Asian, women's health, Mathematical Sciences, Medical and Health Sciences, Epidemiology
Abstract

Using data from the Women's Health Initiative (1993-2009; n = 158,833 participants, of whom 84.1% were white, 9.2% were black, 4.1% were Hispanic, and 2.6% were Asian), we compared all-cause, cardiovascular, and cancer mortality rates in white, black, Hispanic, and Asian postmenopausal women with and without diabetes. Cox proportional hazard models were used for the comparison from which hazard ratios and 95% confidence intervals were computed. Within each racial/ethnic subgroup, women with diabetes had an approximately 2-3 times higher risk of all-cause, cardiovascular, and cancer mortality than did those without diabetes. However, the hazard ratios for mortality outcomes were not significantly different between racial/ethnic subgroups. Population attributable risk percentages (PARPs) take into account both the prevalence of diabetes and hazard ratios. For all-cause mortality, whites had the lowest PARP (11.1, 95% confidence interval (CI): 10.1, 12.1), followed by Asians (12.9, 95% CI: 4.7, 20.9), blacks (19.4, 95% CI: 15.0, 23.7), and Hispanics (23.2, 95% CI: 14.8, 31.2). To our knowledge, the present study is the first to show that hazard ratios for mortality outcomes were not significantly different between racial/ethnic subgroups when stratified by diabetes status. Because of the "amplifying" effect of diabetes prevalence, efforts to reduce racial/ethnic disparities in the rate of death from diabetes should focus on prevention of diabetes.

Published
2013

43. All-cause, cardiovascular, and cancer mortality rates in postmenopausal white, black, Hispanic, and Asian women with and without diabetes in the United States: the Women's Health Initiative, 1993-2009.

Author

Ma, Yunsheng, Hébert, James R, Balasubramanian, Raji, Wedick, Nicole M, Howard, Barbara V, Rosal, Milagros C, Liu, Simin, Bird, Chloe E, Olendzki, Barbara C, Ockene, Judith K, Wactawski-Wende, Jean, Phillips, Lawrence S, Lamonte, Michael J, Schneider, Kristin L, Garcia, Lorena, Ockene, Ira S, Merriam, Philip A, Sepavich, Deidre M, Mackey, Rachel H, Johnson, Karen C, and Manson, Joann E

Subjects
Humans, Neoplasms, Cardiovascular Diseases, Diabetes Mellitus, Body Weights and Measures, Estrogen Replacement Therapy, Exercise, Diet, Proportional Hazards Models, Risk Factors, Smoking, Residence Characteristics, Postmenopause, Aged, Middle Aged, Continental Population Groups, African Americans, Asian Americans, European Continental Ancestry Group, Hispanic Americans, United States, Female, diabetes, health disparities, menopause, mortality, obesity, women's health, womens health, Mathematical Sciences, Medical and Health Sciences, Epidemiology
Abstract

Using data from the Women's Health Initiative (1993-2009; n = 158,833 participants, of whom 84.1% were white, 9.2% were black, 4.1% were Hispanic, and 2.6% were Asian), we compared all-cause, cardiovascular, and cancer mortality rates in white, black, Hispanic, and Asian postmenopausal women with and without diabetes. Cox proportional hazard models were used for the comparison from which hazard ratios and 95% confidence intervals were computed. Within each racial/ethnic subgroup, women with diabetes had an approximately 2-3 times higher risk of all-cause, cardiovascular, and cancer mortality than did those without diabetes. However, the hazard ratios for mortality outcomes were not significantly different between racial/ethnic subgroups. Population attributable risk percentages (PARPs) take into account both the prevalence of diabetes and hazard ratios. For all-cause mortality, whites had the lowest PARP (11.1, 95% confidence interval (CI): 10.1, 12.1), followed by Asians (12.9, 95% CI: 4.7, 20.9), blacks (19.4, 95% CI: 15.0, 23.7), and Hispanics (23.2, 95% CI: 14.8, 31.2). To our knowledge, the present study is the first to show that hazard ratios for mortality outcomes were not significantly different between racial/ethnic subgroups when stratified by diabetes status. Because of the "amplifying" effect of diabetes prevalence, efforts to reduce racial/ethnic disparities in the rate of death from diabetes should focus on prevention of diabetes.

Published
2013

44. Diabetes and risk of pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium

Author

Elena, Joanne W, Steplowski, Emily, Yu, Kai, Hartge, Patricia, Tobias, Geoffrey S, Brotzman, Michelle J, Chanock, Stephen J, Stolzenberg-Solomon, Rachael Z, Arslan, Alan A, Bueno-de-Mesquita, H Bas, Helzlsouer, Kathy, Jacobs, Eric J, LaCroix, Andrea, Petersen, Gloria, Zheng, Wei, Albanes, Demetrius, Allen, Naomi E, Amundadottir, Laufey, Bao, Ying, Boeing, Heiner, Boutron-Ruault, Marie-Christine, Buring, Julie E, Gaziano, J Michael, Giovannucci, Edward L, Duell, Eric J, Hallmans, Göran, Howard, Barbara V, Hunter, David J, Hutchinson, Amy, Jacobs, Kevin B, Kooperberg, Charles, Kraft, Peter, Mendelsohn, Julie B, Michaud, Dominique S, Palli, Domenico, Phillips, Lawrence S, Overvad, Kim, Patel, Alpa V, Sansbury, Leah, Shu, Xiao-Ou, Simon, Michael S, Slimani, Nadia, Trichopoulos, Dimitrios, Visvanathan, Kala, Virtamo, Jarmo, Wolpin, Brian M, Zeleniuch-Jacquotte, Anne, Fuchs, Charles S, Hoover, Robert N, and Gross, Myron

Subjects
Biomedical and Clinical Sciences, Epidemiology, Health Services and Systems, Health Sciences, Oncology and Carcinogenesis, Obesity, Rare Diseases, Digestive Diseases, Pancreatic Cancer, Prevention, Cancer, Diabetes, 2.1 Biological and endogenous factors, Good Health and Well Being, Adenocarcinoma, Adult, Aged, Aged, 80 and over, Case-Control Studies, Cohort Studies, Diabetes Complications, Diabetes Mellitus, Female, Humans, Male, Middle Aged, Pancreatic Neoplasms, Risk Factors, Public Health and Health Services, Oncology and carcinogenesis
Abstract

PurposeDiabetes is a suspected risk factor for pancreatic cancer, but questions remain about whether it is a risk factor or a result of the disease. This study prospectively examined the association between diabetes and the risk of pancreatic adenocarcinoma in pooled data from the NCI pancreatic cancer cohort consortium (PanScan).MethodsThe pooled data included 1,621 pancreatic adenocarcinoma cases and 1,719 matched controls from twelve cohorts using a nested case-control study design. Subjects who were diagnosed with diabetes near the time (

Published
2013

45. Determinants of Racial/Ethnic Disparities in Incidence of Diabetes in Postmenopausal Women in the U.S. The Women’s Health Initiative 1993–2009

Author

Ma, Yunsheng, Hébert, James R, Manson, JoAnn E, Balasubramanian, Raji, Liu, Simin, Lamonte, Michael J, Bird, Chloe E, Ockene, Judith K, Qiao, Yongxia, Olendzki, Barbara, Schneider, Kristin L, Rosal, Milagros C, Sepavich, Deidre M, Wactawski-Wende, Jean, Stefanick, Marcia L, Phillips, Lawrence S, Ockene, Ira S, Kaplan, Robert C, Sarto, Gloria E, Garcia, Lorena, and Howard, Barbara V

Subjects
Epidemiology, Biomedical and Clinical Sciences, Public Health, Health Sciences, Diabetes, Nutrition, Minority Health, Prevention, Metabolic and endocrine, Aged, Diabetes Mellitus, Female, Humans, Incidence, Middle Aged, Postmenopause, United States, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveTo examine determinants of racial/ethnic differences in diabetes incidence among postmenopausal women participating in the Women's Health Initiative.Research design and methodsData on race/ethnicity, baseline diabetes prevalence, and incident diabetes were obtained from 158,833 women recruited from 1993-1998 and followed through August 2009. The relationship between race/ethnicity, other potential risk factors, and the risk of incident diabetes was estimated using Cox proportional hazards models from which hazard ratios (HRs) and 95% CIs were computed.ResultsParticipants were aged 63 years on average at baseline. The racial/ethnic distribution was 84.1% non-Hispanic white, 9.2% non-Hispanic black, 4.1% Hispanic, and 2.6% Asian. After an average of 10.4 years of follow-up, compared with whites and adjusting for potential confounders, the HRs for incident diabetes were 1.55 for blacks (95% CI 1.47-1.63), 1.67 for Hispanics (1.54-1.81), and 1.86 for Asians (1.68-2.06). Whites, blacks, and Hispanics with all factors (i.e., weight, physical activity, dietary quality, and smoking) in the low-risk category had 60, 69, and 63% lower risk for incident diabetes. Although contributions of different risk factors varied slightly by race/ethnicity, most findings were similar across groups, and women who had both a healthy weight and were in the highest tertile of physical activity had less than one-third the risk of diabetes compared with obese and inactive women.ConclusionsDespite large racial/ethnic differences in diabetes incidence, most variability could be attributed to lifestyle factors. Our findings show that the majority of diabetes cases are preventable, and risk reduction strategies can be effectively applied to all racial/ethnic groups.

Published
2012

47. FRI615 The 1-Hour OGTT Plasma Glucose As A Biomarker Of β-cell Function

Author

Thomas Legvold, Brian, primary, Zhang, Amanda, additional, Marie Utzschneider, Kristina, additional, Kyung Rhee, Mary, additional, Staimez, Lisa R, additional, Easley, Kirk A, additional, Van Greevenbroek, Marleen M J, additional, Van Der Kallen, Carla J H, additional, Schalkwijk, Casper G, additional, Stehouwer, Coen D A, additional, and Phillips, Lawrence S, additional

Published
2023
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48. Adaptive selection at G6PDand disparities in diabetes complications

Author

Breeyear, Joseph H., Hellwege, Jacklyn N., Schroeder, Philip H., House, John S., Poisner, Hannah M., Mitchell, Sabrina L., Charest, Brian, Khakharia, Anjali, Basnet, Til B., Halladay, Christopher W., Reaven, Peter D., Meigs, James B., Rhee, Mary K., Sun, Yang, Lynch, Mary G., Bick, Alexander G., Wilson, Otis D., Hung, Adriana M., Nealon, Cari L., Iyengar, Sudha K., Rotroff, Daniel M., Buse, John B., Leong, Aaron, Mercader, Josep M., Sobrin, Lucia, Brantley, Milam A., Peachey, Neal S., Motsinger-Reif, Alison A., Wilson, Peter W., Sun, Yan V., Giri, Ayush, Phillips, Lawrence S., and Edwards, Todd L.

Abstract

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828-T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828-T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828-T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles.

Published
2024
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