1,267 results on '"Hanson, Robert L."'
Search Results
2. DNA methylation markers for kidney function and progression of diabetic kidney disease
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Li, Kelly Yichen, Tam, Claudia Ha Ting, Liu, Hongbo, Day, Samantha, Lim, Cadmon King Poo, So, Wing Yee, Huang, Chuiguo, Jiang, Guozhi, Shi, Mai, Lee, Heung Man, Lan, Hui-yao, Szeto, Cheuk-Chun, Hanson, Robert L., Nelson, Robert G., Susztak, Katalin, Chan, Juliana C. N., Yip, Kevin Y., and Ma, Ronald C. W.
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- 2023
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3. Identification and characterization of the long non-coding RNA NFIA-AS2 as a novel locus for body mass index in American Indians
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Bandesh, Khushdeep, Traurig, Michael, Chen, Peng, Hsueh, Wen-Chi, Hanson, Robert L., Piaggi, Paolo, and Baier, Leslie J.
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- 2023
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4. The utility of a type 2 diabetes polygenic score in addition to clinical variables for prediction of type 2 diabetes incidence in birth, youth and adult cohorts in an Indigenous study population
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Wedekind, Lauren E., Mahajan, Anubha, Hsueh, Wen-Chi, Chen, Peng, Olaiya, Muideen T., Kobes, Sayuko, Sinha, Madhumita, Baier, Leslie J., Knowler, William C., McCarthy, Mark I., and Hanson, Robert L.
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- 2023
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5. Mechanisms of weight loss-induced remission in people with prediabetes: a post-hoc analysis of the randomised, controlled, multicentre Prediabetes Lifestyle Intervention Study (PLIS)
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Sandforth, Arvid, von Schwartzenberg, Reiner Jumpertz, Arreola, Elsa Vazquez, Hanson, Robert L, Sancar, Gencer, Katzenstein, Sarah, Lange, Karl, Preißl, Hubert, Dreher, Simon I, Weigert, Cora, Wagner, Robert, Kantartzis, Kostantinos, Machann, Jürgen, Schick, Fritz, Lehmann, Rainer, Peter, Andreas, Katsouli, Nikoletta, Ntziachristos, Vasilis, Dannecker, Corinna, Fritsche, Louise, Perakakis, Nikolaos, Heni, Martin, Nawroth, Peter Paul, Kopf, Stefan, Pfeiffer, Andreas F H, Kabisch, Stefan, Stumvoll, Michael, Schwarz, Peter E H, Hauner, Hans, Lechner, Andreas, Seissler, Jochen, Yurchenko, Iryna, Icks, Andrea, Solimena, Michele, Häring, Hans-Ulrich, Szendroedi, Julia, Schürmann, Annette, de Angelis, Martin Hrabé, Blüher, Matthias, Roden, Michael, Bornstein, Stefan R, Stefan, Norbert, Fritsche, Andreas, and Birkenfeld, Andreas L
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- 2023
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6. Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium
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Lin, Bridget M, Grinde, Kelsey E, Brody, Jennifer A, Breeze, Charles E, Raffield, Laura M, Mychaleckyj, Josyf C, Thornton, Timothy A, Perry, James A, Baier, Leslie J, de las Fuentes, Lisa, Guo, Xiuqing, Heavner, Benjamin D, Hanson, Robert L, Hung, Yi-Jen, Qian, Huijun, Hsiung, Chao A, Hwang, Shih-Jen, Irvin, Margaret R, Jain, Deepti, Kelly, Tanika N, Kobes, Sayuko, Lange, Leslie, Lash, James P, Li, Yun, Liu, Xiaoming, Mi, Xuenan, Musani, Solomon K, Papanicolaou, George J, Parsa, Afshin, Reiner, Alex P, Salimi, Shabnam, Sheu, Wayne H-H, Shuldiner, Alan R, Taylor, Kent D, Smith, Albert V, Smith, Jennifer A, Tin, Adrienne, Vaidya, Dhananjay, Wallace, Robert B, Yamamoto, Kenichi, Sakaue, Saori, Matsuda, Koichi, Kamatani, Yoichiro, Momozawa, Yukihide, Yanek, Lisa R, Young, Betsi A, Zhao, Wei, Okada, Yukinori, Abecasis, Gonzalo, Psaty, Bruce M, Arnett, Donna K, Boerwinkle, Eric, Cai, Jianwen, Chen, Ida Yii-Der, Correa, Adolfo, Cupples, L Adrienne, He, Jiang, Kardia, Sharon LR, Kooperberg, Charles, Mathias, Rasika A, Mitchell, Braxton D, Nickerson, Deborah A, Turner, Steve T, Ramachandran, Vasan S, Rotter, Jerome I, Levy, Daniel, Kramer, Holly J, Köttgen, Anna, Consortium, NHLBI Trans-Omics for Precision Medicine, Group, TOPMed Kidney Working, Rich, Stephen S, Lin, Dan-Yu, Browning, Sharon R, and Franceschini, Nora
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Epidemiology ,Health Sciences ,Biotechnology ,Human Genome ,Genetics ,Aetiology ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Alleles ,Gene Frequency ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genomics ,Glomerular Filtration Rate ,Humans ,Male ,National Heart ,Lung ,and Blood Institute (U.S.) ,Polymorphism ,Single Nucleotide ,Precision Medicine ,Public Health Surveillance ,Quantitative Trait ,Heritable ,United States ,Whole Genome Sequencing ,Whole genome sequencing ,Kidney traits ,Rare variants ,Ancestry-specific variants ,Clinical Sciences ,Public Health and Health Services ,Clinical sciences - Abstract
BackgroundGenetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.MethodsWe combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.FindingsWhen testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10-11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10-9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10-9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10-9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10-9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.InterpretationThis study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.
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- 2021
7. Diagnostic criteria and etiopathogenesis of type 2 diabetes and its complications: Lessons from the Pima Indians
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Looker, Helen C, Chang, Douglas C, Baier, Leslie J, Hanson, Robert L, and Nelson, Robert G
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- 2023
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8. Functional characterization of a novel p.Ser76Thr variant in IGFBP4 that associates with body mass index in American Indians
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Muller, Yunhua L., Saporito, Michael, Day, Samantha, Bandesh, Khushdeep, Koroglu, Cigdem, Kobes, Sayuko, Knowler, William C., Hanson, Robert L., Van Hout, Cristopher V., Shuldiner, Alan R., Bogardus, Clifton, and Baier, Leslie J.
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- 2022
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9. An E115A missense variant in CERS2 is associated with increased sleeping energy expenditure and hepatic insulin resistance in American Indians
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Heinitz, Sascha, primary, Traurig, Michael, additional, Krakoff, Jonathan, additional, Rabe, Philipp, additional, Stäubert, Claudia, additional, Kobes, Sayuko, additional, Hanson, Robert L., additional, Stumvoll, Michael, additional, Blüher, Matthias, additional, Bogardus, Clifton, additional, Baier, Leslie, additional, and Piaggi, Paolo, additional
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- 2024
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10. Association of protein function-altering variants with cardiometabolic traits: the strong heart study
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Shan, Yue, Cole, Shelley A., Haack, Karin, Melton, Phillip E., Best, Lyle G., Bizon, Christopher, Kobes, Sayuko, Köroğlu, Çiğdem, Baier, Leslie J., Hanson, Robert L., Sanna, Serena, Li, Yun, and Franceschini, Nora
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- 2022
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11. Study protocol for Early Tracking of Childhood Health determinants (ETCHED): A longitudinal observational life course study.
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Arreola, Elsa Vazquez, Coonrod, Dean V., Roy Choudhury, Sourav, Knowler, William C., Hoskin, Mary, Wasak, Dorota, Williams, Rachel, Hanson, Robert L., Pack, Elena, Caballero, Rachel, Gonzalez, Amanda, and Sinha, Madhumita
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PREGNANT women ,FAMILY structure ,MINORITY youth ,HEALTH of minorities ,CHILDHOOD obesity - Abstract
Background: The prevalence of childhood obesity and diabetes continues to rise in the United States (US), especially among minority populations. The objective of the Early Tracking of Childhood Health Determinants (ETCHED) study is to investigate the role of adverse fetal and early-life risk exposures that contribute to the development of childhood obesity and metabolic risk. Methods: ETCHED is a longitudinal observational study of American Indian/Alaska Native (AI/AN) and Hispanic pregnant woman and their offspring. Pregnant mothers ≥ 18 years old are enrolled at a large public hospital system in the southwestern US. Enrolled mothers are followed through pregnancy, delivery, and the maternal/offspring dyad will be followed until the child's 18th birthday. At each maternal visit, questionnaires assessing medical history, diet, physical activity, sleep, perceived stress, and socioeconomic and sociocultural information are obtained. Standard laboratory tests during maternal visits include glycemic measures, lipids, and renal function. Additional bio samples obtained include venous blood samples and cord blood for obesity/metabolic biomarkers and genetic/epigenetic testing, urinalysis, placental tissue for examining functional pathways, breast milk for metabolomics, and stool for metabolites and microbiome analysis. The offspring will have 6 infant/toddler visits at 6–12 weeks, 4 months, 6 months, 18 months, 2 and 3 years respectively. Thereafter, they will undergo comprehensive research visits (major visits) at 4–5 years, 6–9 years, 10–13 years, and 14–17 years. The major visits in children include detailed medical history, anthropometry, developmental assessment, socioeconomic and environmental assessments (food insecurity, family structure, and childcare), feeding and activity, biochemical tests, genetics/epigenetic testing, and ultrasound elastography. Electronic health records will be reviewed for additional clinical information. The primary analysis will constitute estimation of correlation coefficients between continuous variables. The planned study duration in this ongoing study is 23-years. Discussion: This is a life course study that that will examine biological and environmental risk factors for obesity and cardiometabolic risk from the intrauterine period to early childhood and adolescence in a population with high-risk of obesity and type 2 diabetes in the United States. The ETCHED study would also provide a unique opportunity to combine multi-omics and clinical data to create novel integrative models to predict the cardiometabolic risk associated with childhood obesity and possibly identify etiopathogenetic mechanisms and future targets of intervention. Trial registration number: ClinicalTrials.gov identifier: NCT03481829. Updated July 19, 2024, https://clinicaltrials.gov/study/NCT03481829?cond=ETCHED&rank=1. [ABSTRACT FROM AUTHOR]
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- 2024
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12. Identification and functional validation of rare coding variants in genes linked to monogenic obesity.
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Köroğlu, Çiğdem, Traurig, Michael, Muller, Yunhua L., Day, Samantha E., Piaggi, Paolo, Wiedrich, Kim, Vazquez, Laura, Hanson, Robert L., Van Hout, Cristopher V., Alkelai, Anna, Shuldiner, Alan R., Bogardus, Clifton, and Baier, Leslie J.
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MISSENSE mutation ,GENETIC variation ,FUNCTIONAL analysis ,OBESITY ,ADULTS - Abstract
Objective: Rare cases of monogenic obesity, which may respond to specific therapeutics, can remain undetected in populations in which polygenic obesity is prevalent. This study examined rare DNA variation in established monogenic obesity genes within a community using whole‐exome sequence data from 6803 longitudinally studied individuals. Methods: Exome data across 15 monogenic obesity genes were analyzed for nonsynonymous variants observed in any child with a maximum BMI z score > 2 (N = 279) but not observed in a child with a maximum BMI z score ≤ 0 (n = 1542) or that occurred in adults in the top 5th percentile of BMI (n = 263) but not in adults below the median BMI (n = 2629). Variants were then functionally analyzed using luciferase assays. Results: The comparisons between cases of obesity and controls identified eight missense variants in six genes: DYRK1B, KSR2, MC4R, NTRK2, PCSK1, and SIM1. Among these, MC4R p.A303P and p.R165G were previously shown to impair MC4R function. Functional analyses of the remaining six variants suggest that KSR2 p.I402F and p.T193I and NTRK2 p.S249Y alter protein function. Conclusions: In addition to MC4R, rare missense variants in KSR2 and NTRK2 may potentially explain the severe obesity observed for the carriers. [ABSTRACT FROM AUTHOR]
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- 2024
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13. Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.
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Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei
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Epidemiology ,Biological Sciences ,Health Sciences ,Genetics - Abstract
A correction to this article has been published and is linked from the HTML version of this article.
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- 2017
14. Epistasis Between HLA-DRB1*16:02:01 and SLC16A11 T-C-G-T-T Reduces Odds for Type 2 Diabetes in Southwest American Indians
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Williams, Robert C., primary, Hanson, Robert L., additional, Peters, Bjoern, additional, Kearns, Kendall, additional, Knowler, William C., additional, Bogardus, Clifton, additional, and Baier, Leslie J., additional
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- 2024
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15. Role of Weight Loss Induced Prediabetes Remission in the Prevention of Type 2 Diabetes - Time to Improve Diabetes Prevention
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von Schwartzenberg, Reiner Jumpertz, primary, Arreola, Elsa Vazquez, additional, Sandforth, Arvid, additional, Hanson, Robert L., additional, and Birkenfeld, Andreas L., additional
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- 2024
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16. Novel signals and polygenic score for height are associated with pubertal growth traits in Southwestern American Indians
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Ramírez-Luzuriaga, Maria J, primary, Kobes, Sayuko, additional, Hsueh, Wen-Chi, additional, Baier, Leslie J, additional, and Hanson, Robert L, additional
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- 2024
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17. Insulin resistance before type 2 diabetes onset is associated with increased risk of albuminuria after diabetes onset: A prospective cohort study
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Willig, Meeah R., primary, Stinson, Emma J., additional, Looker, Helen C., additional, Piaggi, Paolo, additional, Mitchell, Cassie M., additional, Hanson, Robert L., additional, Nelson, Robert G., additional, Krakoff, Jonathan, additional, and Chang, Douglas C., additional
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- 2024
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18. Multilabel hybridization probes for sequence-specific detection of sepsis-related drug resistance genes in plasmids
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Hanson, Robert L., Lazalde, Elaine, Knob, Radim, Harris, David H., Akuoko, Yesman, Nielsen, Jacob B., and Woolley, Adam T.
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- 2021
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19. Next generation sequencing for HLA loci in full heritage Pima Indians of Arizona, Part II: HLA-A, -B, and -C with selected non-classical loci at 4-field resolution from whole genome sequences
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Williams, Robert C., Koroglu, Cigdem, Knowler, William C., Shuldiner, Alan R., Gosalia, Nehal, Van Hout, Cristopher, Hanson, Robert L., Bogardus, Clifton, and Baier, Leslie J.
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- 2021
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20. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.
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Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei
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Humans ,Thinness ,17-Hydroxysteroid Dehydrogenases ,Aldehyde Oxidoreductases ,Extracellular Matrix Proteins ,Body Composition ,Phenotype ,Polymorphism ,Single Nucleotide ,Quantitative Trait Loci ,Regulatory Elements ,Transcriptional ,Versicans ,Genome-Wide Association Study ,Insulin Receptor Substrate Proteins ,ADAMTS Proteins ,Alpha-Ketoglutarate-Dependent Dioxygenase FTO ,Human Genome ,Genetics ,1.1 Normal biological development and functioning - Abstract
Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p
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- 2017
21. Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND)
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Williams, Robert C, Elston, Robert C, Kumar, Pankaj, Knowler, William C, Abboud, Hanna E, Adler, Sharon, Bowden, Donald W, Divers, Jasmin, Freedman, Barry I, Igo, Robert P, Ipp, Eli, Iyengar, Sudha K, Kimmel, Paul L, Klag, Michael J, Kohn, Orly, Langefeld, Carl D, Leehey, David J, Nelson, Robert G, Nicholas, Susanne B, Pahl, Madeleine V, Parekh, Rulan S, Rotter, Jerome I, Schelling, Jeffrey R, Sedor, John R, Shah, Vallabh O, Smith, Michael W, Taylor, Kent D, Thameem, Farook, Thornley-Brown, Denyse, Winkler, Cheryl A, Guo, Xiuqing, Zager, Phillip, Hanson, Robert L, and the FIND Research Group
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Biological Sciences ,Genetics ,Diabetes ,Human Genome ,American Indian or Alaska Native ,Health Disparities ,Minority Health ,Metabolic and endocrine ,Black or African American ,Algorithms ,Chromosome Mapping ,Diabetic Nephropathies ,Genetic Markers ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Indians ,North American ,Likelihood Functions ,Mexican Americans ,Models ,Genetic ,Oligonucleotide Array Sequence Analysis ,Polymorphism ,Single Nucleotide ,Principal Component Analysis ,United States ,White People ,Individual genetic ancestry ,Population structure ,SNP ,Diabetic nephropathy ,FIND Research Group ,Information and Computing Sciences ,Medical and Health Sciences ,Bioinformatics ,Biological sciences ,Biomedical and clinical sciences - Abstract
BackgroundThe presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample.ResultsA fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy.ConclusionsThe identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.
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- 2016
22. Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes
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Bradfield, Jonathan P., Kember, Rachel L., Ulrich, Anna, Balkiyarova, Zhanna, Alyass, Akram, Aris, Izzuddin M., Bell, Joshua A., Broadaway, K. Alaine, Chen, Zhanghua, Chai, Jin Fang, Davies, Neil M., Fernandez-Orth, Dietmar, Bustamante, Mariona, Fore, Ruby, Ganguli, Amitavo, Heiskala, Anni, Hottenga, Jouke Jan, Íñiguez, Carmen, Kobes, Sayuko, Leinonen, Jaakko, Lowry, Estelle, Lyytikainen, Leo Pekka, Mahajan, Anubha, Pitkänen, Niina, Schnurr, Theresia M., Have, Christian Theil, Strachan, David P., Thiering, Elisabeth, Vogelezang, Suzanne, Wade, Kaitlin H., Wang, Carol A., Wong, Andrew, Holm, Louise Aas, Chesi, Alessandra, Choong, Catherine, Cruz, Miguel, Elliott, Paul, Franks, Steve, Frithioff-Bøjsøe, Christine, Gauderman, W. James, Glessner, Joseph T., Gilsanz, Vicente, Griesman, Kendra, Hanson, Robert L., Guxens, Mònica, Felix, Janine F., Hansen, Torben, Jaddoe, Vincent W.V., Perry, John R.B., Rivadeneira, Fernando, Bradfield, Jonathan P., Kember, Rachel L., Ulrich, Anna, Balkiyarova, Zhanna, Alyass, Akram, Aris, Izzuddin M., Bell, Joshua A., Broadaway, K. Alaine, Chen, Zhanghua, Chai, Jin Fang, Davies, Neil M., Fernandez-Orth, Dietmar, Bustamante, Mariona, Fore, Ruby, Ganguli, Amitavo, Heiskala, Anni, Hottenga, Jouke Jan, Íñiguez, Carmen, Kobes, Sayuko, Leinonen, Jaakko, Lowry, Estelle, Lyytikainen, Leo Pekka, Mahajan, Anubha, Pitkänen, Niina, Schnurr, Theresia M., Have, Christian Theil, Strachan, David P., Thiering, Elisabeth, Vogelezang, Suzanne, Wade, Kaitlin H., Wang, Carol A., Wong, Andrew, Holm, Louise Aas, Chesi, Alessandra, Choong, Catherine, Cruz, Miguel, Elliott, Paul, Franks, Steve, Frithioff-Bøjsøe, Christine, Gauderman, W. James, Glessner, Joseph T., Gilsanz, Vicente, Griesman, Kendra, Hanson, Robert L., Guxens, Mònica, Felix, Janine F., Hansen, Torben, Jaddoe, Vincent W.V., Perry, John R.B., and Rivadeneira, Fernando
- Abstract
BACKGROUND: Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. RESULTS: Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. CONCLUSION: We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern.
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- 2024
23. Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes
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Bradfield, Jonathan P, Kember, Rachel L, Ulrich, Anna, Balkiyarova, Zhanna, Alyass, Akram, Aris, Izzuddin M, Bell, Joshua A, Broadaway, K Alaine, Chen, Zhanghua, Chai, Jin-Fang, Davies, Neil M, Fernandez-Orth, Dietmar, Bustamante, Mariona, Fore, Ruby, Ganguli, Amitavo, Heiskala, Anni, Hottenga, Jouke-Jan, Íñiguez, Carmen, Kobes, Sayuko, Leinonen, Jaakko, Lowry, Estelle, Lyytikainen, Leo-Pekka, Mahajan, Anubha, Pitkänen, Niina, Schnurr, Theresia M, Have, Christian Theil, Strachan, David P, Thiering, Elisabeth, Vogelezang, Suzanne, Wade, Kaitlin H, Wang, Carol A, Wong, Andrew, Holm, Louise Aas, Chesi, Alessandra, Choong, Catherine, Cruz, Miguel, Elliott, Paul, Franks, Steve, Frithioff-Bøjsøe, Christine, Gauderman, W James, Glessner, Joseph T, Gilsanz, Vicente, Griesman, Kendra, Hanson, Robert L, Kaakinen, Marika, Kalkwarf, Heidi, Kelly, Andrea, Hansen, Torben, Holm, Jens-Christian, Sørensen, Thorkild I A, Grant, Struan F A, Cousminer, Diana L, Bradfield, Jonathan P, Kember, Rachel L, Ulrich, Anna, Balkiyarova, Zhanna, Alyass, Akram, Aris, Izzuddin M, Bell, Joshua A, Broadaway, K Alaine, Chen, Zhanghua, Chai, Jin-Fang, Davies, Neil M, Fernandez-Orth, Dietmar, Bustamante, Mariona, Fore, Ruby, Ganguli, Amitavo, Heiskala, Anni, Hottenga, Jouke-Jan, Íñiguez, Carmen, Kobes, Sayuko, Leinonen, Jaakko, Lowry, Estelle, Lyytikainen, Leo-Pekka, Mahajan, Anubha, Pitkänen, Niina, Schnurr, Theresia M, Have, Christian Theil, Strachan, David P, Thiering, Elisabeth, Vogelezang, Suzanne, Wade, Kaitlin H, Wang, Carol A, Wong, Andrew, Holm, Louise Aas, Chesi, Alessandra, Choong, Catherine, Cruz, Miguel, Elliott, Paul, Franks, Steve, Frithioff-Bøjsøe, Christine, Gauderman, W James, Glessner, Joseph T, Gilsanz, Vicente, Griesman, Kendra, Hanson, Robert L, Kaakinen, Marika, Kalkwarf, Heidi, Kelly, Andrea, Hansen, Torben, Holm, Jens-Christian, Sørensen, Thorkild I A, Grant, Struan F A, and Cousminer, Diana L
- Abstract
Background: Pubertal growth patterns correlate with future health outcomes. How‑ever, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Transla‑tion And Rotation (SITAR) growth curve analysis on~56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analy‑ses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. Results: Large-scale growth modeling enables an unprecedented view of adoles‑ cent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide signifcant loci and leverage trans-ancestry data to perform fnemapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with diferent growth trajectories correlated with dif‑ferent outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fbrillation. Conclusion: We report novel genetic associations with the tempo of pubertal growth and fnd that genetic determinants of growth are correlated with reproductive, glyce‑mic, respiratory, and cardiac traits in adulthood. These results aid in identifying specifc growth trajectories impacting lifelong health and show that there may not be a single “optimal” pubertal growth pattern., BACKGROUND: Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank.RESULTS: Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation.CONCLUSION: We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern.
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- 2024
24. Rapid and simple pressure-sensitive adhesive microdevice fabrication for sequence-specific capture and fluorescence detection of sepsis-related bacterial plasmid gene sequences
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Akuoko, Yesman, Hanson, Robert L., Harris, David H., Nielsen, Jacob B., Lazalde, Elaine, and Woolley, Adam T.
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- 2021
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25. Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans
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Schick, Ursula M, Jain, Deepti, Hodonsky, Chani J, Morrison, Jean V, Davis, James P, Brown, Lisa, Sofer, Tamar, Conomos, Matthew P, Schurmann, Claudia, McHugh, Caitlin P, Nelson, Sarah C, Vadlamudi, Swarooparani, Stilp, Adrienne, Plantinga, Anna, Baier, Leslie, Bien, Stephanie A, Gogarten, Stephanie M, Laurie, Cecelia A, Taylor, Kent D, Liu, Yongmei, Auer, Paul L, Franceschini, Nora, Szpiro, Adam, Rice, Ken, Kerr, Kathleen F, Rotter, Jerome I, Hanson, Robert L, Papanicolaou, George, Rich, Stephen S, Loos, Ruth JF, Browning, Brian L, Browning, Sharon R, Weir, Bruce S, Laurie, Cathy C, Mohlke, Karen L, North, Kari E, Thornton, Timothy A, and Reiner, Alex P
- Subjects
Biological Sciences ,Genetics ,Human Genome ,Clinical Research ,Hematology ,Underpinning research ,1.1 Normal biological development and functioning ,Blood ,Actinin ,Adolescent ,Adult ,Aged ,Alleles ,Gene Frequency ,Genetic Association Studies ,Genetic Loci ,Genotype ,Genotyping Techniques ,Hispanic or Latino ,Humans ,MEF2 Transcription Factors ,Membrane Proteins ,Middle Aged ,Phenotype ,Platelet Count ,Polymorphism ,Single Nucleotide ,Receptors ,GABA-B ,Young Adult ,Medical and Health Sciences ,Genetics & Heredity ,Biological sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10(-28)) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits.
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- 2016
26. Effects of theABCC8R1420H loss-of-function variant on beta-cell function, diabetes incidence, and retinopathy
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Vazquez Arreola, Elsa, primary, Knowler, William C, additional, Baier, Leslie J, additional, and Hanson, Robert L, additional
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- 2023
- Full Text
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27. Further evidence supporting a potential role for ADH1B in obesity
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Morales, Liza D., Cromack, Douglas T., Tripathy, Devjit, Fourcaudot, Marcel, Kumar, Satish, Curran, Joanne E., Carless, Melanie, Göring, Harald H. H., Hu, Shirley L., Lopez-Alvarenga, Juan Carlos, Garske, Kristina M., Pajukanta, Päivi, Small, Kerrin S., Glastonbury, Craig A., Das, Swapan K., Langefeld, Carl, Hanson, Robert L., Hsueh, Wen-Chi, Norton, Luke, Arya, Rector, Mummidi, Srinivas, Blangero, John, DeFronzo, Ralph A., Duggirala, Ravindranath, and Jenkinson, Christopher P.
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- 2021
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28. Epidemiology of Type 2 Diabetes in Indigenous Communities in the United States
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Wedekind, Lauren E., Mitchell, Cassie M., Andersen, Coley C., Knowler, William C., and Hanson, Robert L.
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- 2021
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29. Next generation sequencing and the classical HLA loci in full heritage Pima Indians of Arizona: Defining the core HLA variation for North American Paleo-Indians
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Williams, Robert C., Knowler, William C., Shuldiner, Alan R., Gosalia, Nehal, Van Hout, Cristopher, Regeneron Genetics Center, Hanson, Robert L., Bogardus, Clifton, and Baier, Leslie J.
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- 2019
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30. Weight tracking in childhood and adolescence and type 2 diabetes risk
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Olaiya, Muideen T., Knowler, William C., Sinha, Madhumita, Kobes, Sayuko, Nelson, Robert G., Baier, Leslie J., Muller, Yunhua L., and Hanson, Robert L.
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- 2020
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31. Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND).
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Iyengar, Sudha K, Sedor, John R, Freedman, Barry I, Kao, WH Linda, Kretzler, Matthias, Keller, Benjamin J, Abboud, Hanna E, Adler, Sharon G, Best, Lyle G, Bowden, Donald W, Burlock, Allison, Chen, Yii-Der Ida, Cole, Shelley A, Comeau, Mary E, Curtis, Jeffrey M, Divers, Jasmin, Drechsler, Christiane, Duggirala, Ravi, Elston, Robert C, Guo, Xiuqing, Huang, Huateng, Hoffmann, Michael Marcus, Howard, Barbara V, Ipp, Eli, Kimmel, Paul L, Klag, Michael J, Knowler, William C, Kohn, Orly F, Leak, Tennille S, Leehey, David J, Li, Man, Malhotra, Alka, März, Winfried, Nair, Viji, Nelson, Robert G, Nicholas, Susanne B, O'Brien, Stephen J, Pahl, Madeleine V, Parekh, Rulan S, Pezzolesi, Marcus G, Rasooly, Rebekah S, Rotimi, Charles N, Rotter, Jerome I, Schelling, Jeffrey R, Seldin, Michael F, Shah, Vallabh O, Smiles, Adam M, Smith, Michael W, Taylor, Kent D, Thameem, Farook, Thornley-Brown, Denyse P, Truitt, Barbara J, Wanner, Christoph, Weil, E Jennifer, Winkler, Cheryl A, Zager, Philip G, Igo, Robert P, Hanson, Robert L, Langefeld, Carl D, and Family Investigation of Nephropathy and Diabetes (FIND)
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Family Investigation of Nephropathy and Diabetes ,Humans ,Diabetic Nephropathies ,Diabetes Mellitus ,Type 2 ,Genetic Predisposition to Disease ,RNA-Binding Proteins ,African Americans ,Indians ,North American ,European Continental Ancestry Group ,Hispanic Americans ,United States ,Genome-Wide Association Study ,Diabetes ,Genetics ,Human Genome ,Clinical Research ,Kidney Disease ,American Indian or Alaska Native ,Prevention ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,Renal and urogenital ,Developmental Biology - Abstract
Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.
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- 2015
32. Association of urinary KIM-1, L-FABP, NAG and NGAL with incident end-stage renal disease and mortality in American Indians with type 2 diabetes mellitus
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Fufaa, Gudeta D, Weil, E Jennifer, Nelson, Robert G, Hanson, Robert L, Bonventre, Joseph V, Sabbisetti, Venkata, Waikar, Sushrut S, Mifflin, Theodore E, Zhang, Xiaoming, Xie, Dawei, Hsu, Chi-yuan, Feldman, Harold I, Coresh, Josef, Vasan, Ramachandran S, Kimmel, Paul L, Liu, Kathleen D, and for the Chronic Kidney Disease Biomarkers Consortium Investigators
- Subjects
Epidemiology ,Biomedical and Clinical Sciences ,Health Sciences ,Kidney Disease ,Renal and urogenital ,Good Health and Well Being ,Acute-Phase Proteins ,Adolescent ,Adult ,Aged ,Diabetes Mellitus ,Type 2 ,Diabetic Nephropathies ,Fatty Acid-Binding Proteins ,Female ,Hepatitis A Virus Cellular Receptor 1 ,Humans ,Incidence ,Indians ,North American ,Kidney Failure ,Chronic ,Lipocalin-2 ,Lipocalins ,Male ,Membrane Glycoproteins ,Middle Aged ,Neoplasm Proteins ,Proto-Oncogene Proteins ,Receptors ,Virus ,Young Adult ,Biomarkers ,End-stage renal disease ,Mortality ,Type 2 diabetes ,Chronic Kidney Disease Biomarkers Consortium Investigators ,Clinical Sciences ,Paediatrics and Reproductive Medicine ,Public Health and Health Services ,Endocrinology & Metabolism ,Clinical sciences ,Public health - Abstract
Aims/hypothesisKidney injury molecule 1 (KIM-1), liver fatty acid-binding protein (L-FABP), N-acetyl-β-D-glucosaminidase (NAG) and neutrophil gelatinase-associated lipocalin (NGAL) are urinary biomarkers of renal tubular injury. We examined their association with incident end-stage renal disease (ESRD) and all-cause mortality in American Indians with type 2 diabetes.MethodsBiomarker concentrations were measured in baseline urine samples in 260 Pima Indians who were followed for a median of 14 years. HRs were reported per SD of creatinine (Cr)-normalised log-transformed KIM-1, NAG and NGAL, and for three categories of L-FABP.ResultsDuring follow-up, 74 participants developed ESRD and 101 died. Median concentrations of KIM-1/Cr, NAG/Cr and NGAL/Cr and the proportion of detectable L-FABP were highest in those with macroalbuminuria (p
- Published
- 2015
33. Use of graded Semmes Weinstein monofilament testing for ascertaining peripheral neuropathy in people with and without diabetes
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Olaiya, Muideen T., Hanson, Robert L., Kavena, Karen G., Sinha, Madhumita, Clary, Dawn, Horton, Mark B., Nelson, Robert G., and Knowler, William C.
- Published
- 2019
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34. A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND)
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Thameem, Farook, Igo, Robert P, Freedman, Barry I, Langefeld, Carl, Hanson, Robert L, Schelling, Jeffrey R, Elston, Robert C, Duggirala, Ravindranath, Nicholas, Susanne B, Goddard, Katrina A. B, Divers, Jasmin, Guo, Xiuqing, Ipp, Eli, Kimmel, Paul L, Meoni, Lucy A, Shah, Vallabh O, Smith, Michael W, Winkler, Cheryl A, Zager, Philip G, Knowler, William C, Nelson, Robert G, Pahl, Madeline V, Parekh, Rulan S, Kao, W. H. Linda, Rasooly, Rebekah S, Adler, Sharon G, Abboud, Hanna E, Iyengar, Sudha K, Sedor, John R, and Cai, Tao
- Subjects
Chronic Kidney-Disease ,Renal-Function ,Mexican-Americans ,Genetic-Variants ,Serum Creatinine ,Identifies 6 ,Association ,Loci ,Albuminuria ,Traits - Published
- 2013
35. Sequence-specific sepsis-related DNA capture and fluorescent labeling in monoliths prepared by single-step photopolymerization in microfluidic devices
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Knob, Radim, Hanson, Robert L., Tateoka, Olivia B., Wood, Ryan L., Guerrero-Arguero, Israel, Robison, Richard A., Pitt, William G., and Woolley, Adam T.
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- 2018
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36. Racial/ethnic differences in the burden of type 2 diabetes over the life course: a focus on the USA and India
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Golden, Sherita H., Yajnik, Chittaranjan, Phatak, Sanat, Hanson, Robert L., and Knowler, William C.
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- 2019
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37. Association of CREBRF variants with obesity and diabetes in Pacific Islanders from Guam and Saipan
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Hanson, Robert L., Safabakhsh, Saied, Curtis, Jeffrey M., Hsueh, Wen-Chi, Jones, Lois I., Aflague, Tanisha F., Duenas Sarmiento, Jenny, Kumar, Satish, Blackburn, Nicholas B., Curran, Joanne E., Mahkee, Darin, Baier, Leslie J., Knowler, William C., and Nelson, Robert G.
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- 2019
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38. Birthweight and early-onset type 2 diabetes in American Indians: differential effects in adolescents and young adults and additive effects of genotype, BMI and maternal diabetes
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Olaiya, Muideen T., Wedekind, Lauren E., Hanson, Robert L., Sinha, Madhumita, Kobes, Sayuko, Nelson, Robert G., Baier, Leslie J., and Knowler, William C.
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- 2019
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- View/download PDF
39. Genomewide linkage scan for diabetic renal failure and albuminuria: the FIND study.
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Igo, Robert P, Jr, Iyengar, Sudha K, Nicholas, Susanne B, Goddard, Katrina A B, Langefeld, Carl D, Hanson, Robert L, Duggirala, Ravindranath, Divers, Jasmin, Abboud, Hanna, Adler, Sharon G, Arar, Nedal H, Horvath, Amanda, Elston, Robert C, Bowden, Donald W, Guo, Xiuqing, Ipp, Eli, Kao, W H Linda, Kimmel, Paul L, Knowler, William C, Meoni, Lucy A, Molineros, Julio, Nelson, Robert G, Pahl, Madeline V, Parekh, Rulan S, Rasooly, Rebekah S, Schelling, Jeffrey R, Shah, Vallabh O, Smith, Michael W, Winkler, Cheryl A, Zager, Philip G, Sedor, John R, and Freedman, Barry I
- Subjects
Aged ,Albuminuria: genetics ,metabolism ,Chromosome Mapping ,Diabetic Nephropathies: genetics ,metabolism ,Ethnic Groups ,Female ,Genetic Linkage ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Male ,Middle Aged ,Pedigree ,Polymorphism ,Single Nucleotide ,Renal Insufficiency: genetics ,metabolism ,Risk ,Time Factors - Abstract
Diabetic nephropathy (DN) is a leading cause of mortality and morbidity in patients with type 1 and type 2 diabetes. The multicenter FIND consortium aims to identify genes for DN and its associated quantitative traits, e.g. the urine albumin:creatinine ratio (ACR). Herein, the results of whole-genome linkage analysis and a sparse association scan for ACR and a dichotomous DN phenotype are reported in diabetic individuals.A genomewide scan comprising more than 5,500 autosomal single nucleotide polymorphism markers (average spacing of 0.6 cM) was performed on 1,235 nuclear and extended pedigrees (3,972 diabetic participants) ascertained for DN from African-American (AA), American-Indian (AI), European-American (EA) and Mexican-American (MA) populations.Strong evidence for linkage to DN was detected on chromosome 6p (p = 8.0 × 10(-5), LOD = 3.09) in EA families as well as suggestive evidence for linkage to chromosome 7p in AI families. Regions on chromosomes 3p in AA, 7q in EA, 16q in AA and 22q in MA displayed suggestive evidence of linkage for urine ACR. The linkage peak on chromosome 22q overlaps the MYH9/APOL1 gene region, previously implicated in AA diabetic and nondiabetic nephropathies.These results strengthen the evidence for previously identified genomic regions and implicate several novel loci potentially involved in the pathogenesis of DN.
- Published
- 2011
40. Glycemic Measures in Childhood as Predictors of Future Diabetes-Related Microvascular Complications in an Indigenous American Population
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Vazquez, Laura, primary, Vazquez Arreola, Elsa, additional, Hanson, Robert L., additional, and Sinha, Madhumita, additional
- Published
- 2023
- Full Text
- View/download PDF
41. Association Studies to Map Genes for Disease-Related Traits in Humans
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Hanson, Robert L., Malhotra, Alka, Kole, Chittaranjan, Series editor, Duggirala, Ravindranath, editor, Almasy, Laura, editor, Williams-Blangero, Sarah, editor, and Paul, Solomon F.D., editor
- Published
- 2015
- Full Text
- View/download PDF
42. Functional and association analysis of an Amerindian-derived population-specific p.(Thr280Met) variant in RBPJL, a component of the PTF1 complex
- Author
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Nair, Anup K., Sutherland, Jeff R., Traurig, Michael, Piaggi, Paolo, Chen, Peng, Kobes, Sayuko, Hanson, Robert L., Bogardus, Clifton, and Baier, Leslie J.
- Published
- 2018
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- View/download PDF
43. The Effect of Interventions to Prevent Type 2 Diabetes on the Development of Diabetic Retinopathy: The DPP/DPPOS Experience
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White, Neil H., Pan, Qing, Knowler, William C., Schroeder, Emily B., Dabelea, Dana, Chew, Emily Y., Blodi, Barbara, Goldberg, Ronald B., Pi-Sunyer, Xavier, Darwin, Christine, Schlögl, Mathias, Nathan, David M., Goldstein, Barry J., Furlong, Kevin, Smith, Kellie A., Mendoza, Jewel, Wildman, Wendi, Simmons, Marsha, Jensen, Genine, Liberoni, Renee, Spandorfer, John, Pepe, Constance, Donahue, Richard P., Prineas, Ronald, Rowe, Patricia, Giannella, Anna, Calles, Jeanette, Sanguily, Juliet, Cassanova-Romero, Paul, Castillo-Florez, Sumaya, Florez, Hermes J., Garg, Rajesh, Kirby, Lascelles, Lara, Olga, Larreal, Carmen, McLymont, Valerie, Mendez, Jadell, Perry, Arlette, Saab, Patrice, Veciana, Bertha, Haffner, Steven M., Hazuda, Helen P., Montez, Maria G., Isaac, Juan, Hattaway, Kathy, Lorenzo, Carlos, Martinez, Arlene, Salazar, Monica, Walker, Tatiana, Hamman, Richard F., Nash, Patricia V., Steinke, Sheila C., Testaverde, Lisa, Truong, Jennifer, Anderson, Denise R., Ballonoff, Larry B., Bouffard, Alexis, Boxer, Rebecca S., Bucca, Brian, Calonge, B. Ned, Delve, Lynne, Farago, Martha, Hill, James O., Hoyer, Shelley R., Jenkins, Tonya, Jortberg, Bonnie T., Lenz, Dione, Miller, Marsha, Nilan, Thomas, Perreault, Leigh, Price, David W., Regensteiner, Judith G., Seagle, Helen, Smith, Carissa M., VanDorsten, Brent, Horton, Edward S., Munshi, Medha, Lawton, Kathleen E., Poirier, Catherine S., Swift, Kati, Jackson, Sharon D., Arky, Ronald A., Bryant, Marybeth, Burke, Jacqueline P., Caballero, Enrique, Callaphan, Karen M., Fargnoli, Barbara, Franklin, Therese, Ganda, Om P., Guidi, Ashley, Guido, Mathew, Jacobsen, Alan M., Kula, Lyn M., Kocal, Margaret, Lambert, Lori, Ledbury, Sarah, Malloy, Maureen A., Middelbeek, Roeland J.W., Nicosia, Maryanne, Oldmixon, Cathryn F., Pan, Jocelyn, Quitingon, Marizel, Rainville, Riley, Rubtchinsky, Stacy, Seely, Ellen W., Sansoucy, Jessica, Schweizer, Dana, Simonson, Donald, Smith, Fannie, Solomon, Caren G., Spellman, Jeanne, Warram, James, Kahn, Steven E., Montgomery, Brenda K., Fattaleh, Basma, Colegrove, Celeste, Fujimoto, Wilfred, Knopp, Robert H., Lipkin, Edward W., Marr, Michelle, Morgan-Taggart, Ivy, Murillo, Anne, O’Neal, Kayla, Trence, Dace, Taylor, Lonnese, Thomas, April, Tsai, Elaine C., Kitabchi, Abbas E., Dagogo-Jack, Samuel, Murphy, Mary E., Taylor, Laura, Dolgoff, Jennifer, Hampton, Ethel Faye, Applegate, William B., Bryer-Ash, Michael, Clark, Debra, Frieson, Sandra L., Ibebuogu, Uzoma, Imseis, Raed, Lambeth, Helen, Lichtermann, Lynne C., Oktaei, Hooman, Ricks, Harriet, Rutledge, Lily M.K., Sherman, Amy R., Smith, Clara M., Soberman, Judith E., Williamsleaves, Beverly, Patel, Avnisha, Nyenwe, Ebenezer A., Metzger, Boyd E., Molitch, Mark E., Wallia, Amisha, Johnson, Mariana K., VanderMolen, Sarah, Adelman, Daphne T., Behrends, Catherine, Cook, Michelle, Fitzgibbon, Marian, Giles, Mimi M., Hartmuller, Monica, Johnson, Cheryl K.H., Larsen, Diane, Lowe, Anne, Lyman, Megan, McPherson, David, Penn, Samsam C., Pitts, Thomas, Reinhart, Renee, Roston, Susan, Schinleber, Pamela A., McKitrick, Charles, Turgeon, Heather, Larkin, Mary, Mugford, Marielle, Thangthaeng, Nopporn, Leander, Fernelle, Abbott, Kathy, Anderson, Ellen, Bissett, Laurie, Bondi, Kristy, Cagliero, Enrico, Florez, Jose C., Delahanty, Linda, Goldman, Valerie, Grassa, Elaine, Gurry, Lindsey, D’Anna, Kali, Leandre, Fernelle, Lou, Peter, Poulos, Alexandra, Raymond, Elyse, Ripley, Valerie, Stevens, Christine, Tseng, Beverly, Olefsky, Jerrold M., Barrettonnor, Elizabeth, Mudaliar, Sunder, Rosario Araneta, Maria, Carrion-Petersen, Mary Lou, Vejvoda, Karen, Bassiouni, Sarah, Beltran, Madeline, Claravall, Lauren N., Dowden, Jonalle M., Edelman, Steven V., Garimella, Pranav, Henry, Robert R., Horne, Javiva, Lamkin, Marycie, Szerdi Janesch, Simona, Leos, Diana, Polonsky, William, Ruiz, Rosa, Smith, Jean, Torio-Hurley, Jennifer, Pi-Sunyer, F. Xavier, Laferrere, Blandine, Lee, Jane E., Hagamen, Susan, Kelly-Dinham, Kim, Allison, David B., Agharanya, Nnenna, Aronoff, Nancy J., Baldo, Maria, Crandall, Jill P., Foo, Sandra T., Luchsinger, Jose A., Pal, Carmen, Parkes, Kathy, Pena, Mary Beth, Roman, Julie, Rooney, Ellen S., VanWye, Gretchen E.H., Viscovich, Kristine A., Prince, Melvin J., Marrero, David G., Mather, Kieren J., De Groot, Mary, Kelly, Susie M., Jackson, Marcia A., McAtee, Gina, Putenney, Paula, Ackermann, Ronald T., Cantrell, Carolyn M., Dotson, Yolanda F., Fineberg, Edwin S., Fultz, Megan, Guare, John C., Hadden, Angela, Ignaut, James M., Kirkman, Marion S., O’Kelly Phillips, Erin, Pinner, Kisha L., Porter, Beverly D., Roach, Paris J., Rowland, Nancy D., Wheeler, Madelyn L., Ratner, Robert E., Aroda, Vanita, Magee, Michelle, Youssef, Gretchen, Shapiro, Sue, Andon, Natalie, Bavido-Arrage, Catherine, Boggs, Geraldine, Bronsord, Marjorie, Brown, Ernestine, Love Burkott, Holly, Cheatham, Wayman W., Cola, Susan, Evans, Cindy, Gibbs, Peggy, Kellum, Tracy, Leon, Lilia, Lagarda, Milvia, Levatan, Claresa, Lindsay, Milajurine, Nair, Asha K., Park, Jean, Passaro, Maureen, Silverman, Angela, Uwaifo, Gabriel, Wells-Thayer, Debra, Wiggins, Renee, Saad, Mohammed F., Watson, Karol, Budget, Maria, Jinagouda, Sujata, Botrous, Medhat, Sosa, Anthony, Tadros, Sameh, Akbar, Khan, Conzues, Claudia, Magpuri, Perpetua, Ngo, Kathy, Rassam, Amer, Waters, Debra, Xapthalamous, Kathy, Santiago, Julio V., Brown, Angela L., Santiago, Ana, Das, Samia, Khare-Ranade, Prajakta, Stich, Tamara, Fisher, Edwin, Hurt, Emma, Jones, Jackie, Jones, Tracy, Kerr, Michelle, McCowan, Sherri, Ryder, Lucy, Wernimont, Cormarie, Saudek, Christopher D., Hill Golden, Sherita, Bradley, Vanessa, Sullivan, Emily, Whittington, Tracy, Abbas, Caroline, Allen, Adrienne, Brancati, Frederick L., Cappelli, Sharon, Clark, Jeanne M., Charleston, Jeanne B., Freel, Janice, Horak, Katherine, Greene, Alicia, Jiggetts, Dawn, Johnson, Delois, Joseph, Hope, Kalyani, Rita, Loman, Kimberly, Mathioudakis, Nestoras, Maruthur, Nisa, Mosley, Henry, Reusing, John, Rubin, Richard R., Samuels, Alafia, Shields, Thomas, Stephens, Shawne, Stewart, Kerry J., Thomas, LeeLana, Utsey, Evonne, Williamson, Paula, Schade, David S., Adams, Karwyn S., Johannes, Carolyn, Hemphill, Claire, Hyde, Penny, Canady, Janene L., Atler, Leslie F., Boyle, Patrick J., Burge, Mark R., Chai, Lisa, Colleran, Kathleen, Fondino, Ateka, Gonzales, Ysela, Hernandez-McGinnis, Doris A., Katz, Patricia, King, Carolyn, Middendorf, Julia, Rubinchik, Sofya, Senter, Willette, Shamoon, Harry, Crandall, Jill, Brown, Janet O., Trandafirescu, Gilda, Powell, Danielle, Adorno, Elsie, Cox, Liane, Duffy, Helena, Engel, Samuel, Friedler, Allison, Goldstein, Angela, Howardentury, Crystal J., Lukin, Jennifer, Kloiber, Stacey, Longchamp, Nadege, Martinez, Helen, Pompi, Dorothy, Scheindlin, Jonathan, Tomuta, Norica, Violino, Elissa, Walker, Elizabeth A., Wylie-Rosett, Judith, Zimmerman, Elise, Zonszein, Joel, Wing, Rena R., Orchard, Trevor, Venditti, Elizabeth, Koenning, Gaye, Kramer, M. Kaye, Smith, Marie, Jeffries, Susan, Weinzierl, Valarie, Barr, Susan, Benchoff, Catherine, Boraz, Miriam, Clifford, Lisa, Culyba, Rebecca, Frazier, Marlene, Gilligan, Ryan, Guimond, Stephanie, Harrier, Susan, Harris, Louann, Kriska, Andrea, Manjoo, Qurashia, Mullen, Monica, Noel, Alicia, Otto, Amy, Pettigrew, Jessica, Rockette-Wagner, Bonny, Rubinstein, Debra, Semler, Linda, Smith, Cheryl F., Williams, Katherine V., Wilson, Tara, Arakaki, Richard F., Mau, Marjorie K., Latimer, Renee W., Isonaga, Mae K., Baker-Ladao, Narleen K., Bow, Ralph, Bermudez, Nina E., Dias, Lorna, Inouye, Jillian, Melish, John S., Mikami, Kathy, Mohideen, Pharis, Odom, Sharon K., Perry, Raynette U., Yamamoto, Robin E., Hanson, Robert L., Shah, Vallabh, Hoskin, Mary A., Percy, Carol A., Cooeyate, Norman, Natewa, Camille, Dodge, Charlotte, Enote, Alvera, Anderson, Harelda, Acton, Kelly J., Andre, Vickie L., Barber, Rosalyn, Begay, Shandiin, Bennett, Peter H., Benson, Mary Beth, Bird, Evelyn C., Broussard, Brenda A., Bucca, Brian C., Chavez, Marcella, Cook, Sherron, Curtis, Jeff, Dacawyma, Tara, Doughty, Matthew S., Duncan, Roberta, Edgerton, Cyndy, Ghahate, Jacqueline M., Glass, Justin, Glass, Martia, Gohdes, Dorothy, Grant, Wendy, Horse, Ellie, Ingraham, Louise E., Jackson, Merry, Jay, Priscilla, Kaskalla, Roylen S., Kavena, Karen, Kessler, David, Kobus, Kathleen M., Krakoff, Jonathan, Kurland, Jason, Manus, Catherine, McCabe, Cherie, Michaels, Sara, Morgan, Tina, Nashboo, Yolanda, Nelson, Julie A., Poirier, Steven, Polczynski, Evette, Piromalli, Christopher, Reidy, Mike, Roumain, Jeanine, Rowse, Debra, Roy, Robert J., Sangster, Sandra, Sewenemewa, Janet, Smart, Miranda, Spencer, Chelsea, Tonemah, Darryl, Williams, Rachel, Wilson, Charlton, Yazzie, Michelle, Bain, Raymond, Fowler, Sarah, Larsen, Michael D., Jablonski, Kathleen, Temprosa, Marinella, Brenneman, Tina, Edelstein, Sharon L., Abebe, Solome, Bamdad, Julie, Barkalow, Melanie, Bethepu, Joel, Bezabeh, Tsedenia, Bowers, Anna, Butler, Nicole, Callaghan, Jackie, Carter, Caitlin E., Christophi, Costas, Dwyer, Gregory M., Foulkes, Mary, Gao, Yuping, Gooding, Robert, Gottlieb, Adrienne, Grimes, Kristina L., Grover-Fairchild, Nisha, Haffner, Lori, Hoffman, Heather, Jones, Steve, Jones, Tara L., Katz, Richard, Kolinjivadi, Preethy, Lachin, John M., Ma, Yong, Mucik, Pamela, Orlosky, Robert, Reamer, Susan, Rochon, James, Sapozhnikova, Alla, Sherif, Hanna, Stimpson, Charlotte, Hogan Tjaden, Ashley, Walker-Murray, Fredricka, Venditti, Elizabeth M., Kriska, Andrea M., Weinzierl, Valerie, Marcovina, Santica, Aldrich, F. Alan, Harting, Jessica, Albers, John, Strylewicz, Greg, Killeen, Anthony, Gabrielson, Deanna, Eastman, R., Fradkin, Judith, Garfield, Sanford, Lee, Christine, Gregg, Edward, Zhang, Ping, O’Leary, Dan, Evans, Gregory, Budoff, Matthew, Dailing, Chris, Stamm, Elizabeth, Schwartz, Ann, Navy, Caroline, Palermo, Lisa, Rautaharju, Pentti, Prineas, Ronald J., Soliman, Elsayed Z., Alexander, Teresa, Campbell, Charles, Hall, Sharon, Li, Yabing, Mills, Margaret, Pemberton, Nancy, Rautaharju, Farida, Zhang, Zhuming, Hu, Julie, Hensley, Susan, Keasler, Lisa, Taylor, Tonya, Danis, Ronald, Davis, Matthew, Hubbard, Larry, Endres, Ryan, Elsas, Deborah, Johnson, Samantha, Myers, Dawn, Barrett, Nancy, Baumhauer, Heather, Benz, Wendy, Cohn, Holly, Corkery, Ellie, Dohm, Kristi, Domalpally, Amitha, Gama, Vonnie, Goulding, Anne, Ewen, Andy, Hurtenbach, Cynthia, Lawrence, Daniel, McDaniel, Kyle, Pak, Jeong, Reimers, James, Shaw, Ruth, Swift, Maria, Vargo, Pamela, Watson, Sheila, Manly, Jennifer, Mayer-Davis, Elizabeth, Moran, Robert R., Ganiats, Ted, David, Kristin, Sarkin, Andrew J., Groessl, Erik, Katzir, Naomi, Chong, Helen, Herman, William H., Brändle, Michael, Brown, Morton B., Altshuler, David, Billings, Liana K., Chen, Ling, Harden, Maegan, Pollin, Toni I., Shuldiner, Alan R., Franks, Paul W., and Hivert, Marie-France
- Subjects
Advanced and Specialized Nursing ,Endocrinology, Diabetes and Metabolism ,Internal Medicine ,Pathophysiology/Complications - Abstract
OBJECTIVE To determine whether interventions that slow or prevent the development of type 2 diabetes in those at risk reduce the subsequent prevalence of diabetic retinopathy. RESEARCH DESIGN AND METHODS The Diabetes Prevention Program (DPP) randomized subjects at risk for developing type 2 diabetes because of overweight/obesity and dysglycemia to metformin (MET), intensive lifestyle intervention (ILS), or placebo (PLB) to assess the prevention of diabetes. During the DPP and DPP Outcome Study (DPPOS), we performed fundus photography over time on study participants, regardless of their diabetes status. Fundus photographs were graded using the Early Treatment Diabetic Retinopathy Study grading system, with diabetic retinopathy defined as typical lesions of diabetic retinopathy (microaneurysms, exudates, or hemorrhage, or worse) in either eye. RESULTS Despite reduced progression to diabetes in the ILS and MET groups compared with PLB, there was no difference in the prevalence of diabetic retinopathy between treatment groups after 1, 5, 11, or 16 years of follow-up. No treatment group differences in retinopathy were found within prespecified subgroups (baseline age, sex, race/ethnicity, baseline BMI). In addition, there was no difference in the prevalence of diabetic retinopathy between those exposed to metformin and those not exposed to metformin, regardless of treatment group assignment. CONCLUSIONS Interventions that delay or prevent the onset of type 2 diabetes in overweight/obese subjects with dysglycemia who are at risk for diabetes do not reduce the development of diabetic retinopathy for up to 20 years.
- Published
- 2022
44. Adolescent Growth Spurt and Type 2 Diabetes Risk in Southwestern American Indians
- Author
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Ramirez-Luzuriaga, Maria J, primary, Kobes, Sayuko, additional, Sinha, Madhumita, additional, Knowler, William C, additional, and Hanson, Robert L, additional
- Published
- 2023
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45. Glycemia affects glomerular filtration rate in people with type 2 diabetes
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Weil, E. Jennifer, Kobes, Sayuko, Jones, Lois I., and Hanson, Robert L.
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- 2019
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46. Kidney cytosine methylation changes improve renal function decline estimation in patients with diabetic kidney disease
- Author
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Gluck, Caroline, Qiu, Chengxiang, Han, Sang Youb, Palmer, Matthew, Park, Jihwan, Ko, Yi-An, Guan, Yuting, Sheng, Xin, Hanson, Robert L., Huang, Jing, Chen, Yong, Park, Ae Seo Deok, Izquierdo, Maria Concepcion, Mantzaris, Ioannis, Verma, Amit, Pullman, James, Li, Hongzhe, and Susztak, Katalin
- Published
- 2019
- Full Text
- View/download PDF
47. Identification of Genetic Variation Influencing Metformin Response in a Multiancestry Genome-Wide Association Study in the Diabetes Prevention Program (DPP).
- Author
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Li, Josephine H., Perry, James A., Jablonski, Kathleen A., Srinivasan, Shylaja, Chen, Ling, Todd, Jennifer N., Harden, Maegan, Mercader, Josep M., Pan, Qing, Dawed, Adem Y., Yee, Sook Wah, Pearson, Ewan R., Giacomini, Kathleen M., Giri, Ayush, Hung, Adriana M., Xiao, Shujie, Williams, L. Keoki, Franks, Paul W., Hanson, Robert L., and Kahn, Steven E.
- Subjects
GENOME-wide association studies ,GENETIC variation ,GLYCOSYLATED hemoglobin ,TYPE 2 diabetes ,PROPORTIONAL hazards models - Abstract
Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not been replicated in the Diabetes Prevention Program (DPP). To assess pharmacogenetic interactions in prediabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in the metformin (MET; n = 876) and placebo (PBO; n = 887) arms. Multiple linear regression assessed association with 1-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes incidence. We identified four genome-wide significant variants after correcting for correlated traits (P < 9 × 10
−9 ). In the MET arm, rs144322333 near ENOSF1 (minor allele frequency [MAF]AFR = 0.07; MAFEUR = 0.002) was associated with an increase in percentage of glycated hemoglobin (per minor allele, β = 0.39 [95% CI 0.28, 0.50]; P = 2.8 × 10−12 ). rs145591055 near OMSR (MAF = 0.10 in American Indians) was associated with weight loss (kilograms) (per G allele, β = −7.55 [95% CI −9.88, −5.22]; P = 3.2 × 10−10 ) in the MET arm. Neither variant was significant in PBO; gene-by-treatment interaction was significant for both variants [P(G×T) < 1.0 × 10−4 ]. Replication in individuals with diabetes did not yield significant findings. A GWAS for metformin response in prediabetes revealed novel ethnic-specific associations that require further investigation but may have implications for tailored therapy. [ABSTRACT FROM AUTHOR]- Published
- 2023
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- View/download PDF
48. Identification of genetic variation influencing metformin response in a multi-ancestry genome-wide association study in the Diabetes Prevention Program (DPP)
- Author
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Li, Josephine, primary, Perry, James A., primary, Jablonski, Kathleen A., primary, Srinivasan, Shylaja, primary, Chen, Ling, primary, Todd, Jennifer N., primary, Harden, Maegan, primary, Mercader, Josep M., primary, Pan, Qing, primary, Dawed, Adem Y., primary, Yee, Sook Wah, primary, Pearson, Ewan R., primary, Giacomini, Kathleen M., primary, Giri, Ayush, primary, Hung, Adriana M., primary, Xiao, Shujie, primary, Williams, L. Keoki, primary, Franks, Paul W., primary, Hanson, Robert L., primary, Kahn, Steven E., primary, Knowler, William C., primary, Pollin, Toni I., primary, Florez, Jose C., primary, and Group, Diabetes Prevention Program Research, primary
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- 2023
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49. Autoantibodies against PFDN2 are associated with an increased risk of type 2 diabetes: A case‐control study
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Chang, Douglas C., Piaggi, Paolo, Hanson, Robert L., Knowler, William C., Bogardus, Clifton, and Krakoff, Jonathan
- Published
- 2017
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50. Identification of genetic variation influencing metformin response in a multi-ancestry genome-wide association study in the Diabetes Prevention Program (DPP)
- Author
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Li, Josephine, primary, Perry, James A., primary, Jablonski, Kathleen A., primary, Srinivasan, Shylaja, primary, Chen, Ling, primary, Todd, Jennifer N., primary, Harden, Maegan, primary, Mercader, Josep M., primary, Pan, Qing, primary, Dawed, Adem Y., primary, Yee, Sook Wah, primary, Pearson, Ewan R., primary, Giacomini, Kathleen M., primary, Giri, Ayush, primary, Hung, Adriana M., primary, Xiao, Shujie, primary, Williams, L. Keoki, primary, Franks, Paul W., primary, Hanson, Robert L., primary, Kahn, Steven E., primary, Knowler, William C., primary, Pollin, Toni I., primary, Florez, Jose C., primary, and Group, Diabetes Prevention Program Research, primary
- Published
- 2022
- Full Text
- View/download PDF
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