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Xu W, Xu X, Zhang M, Sun C. Association between HDL cholesterol with diabetic retinopathy in diabetic patients: a cross-sectional retrospective study. BMC Endocr Disord 2024; 24:65. [PMID: 38730329 PMCID: PMC11084017 DOI: 10.1186/s12902-024-01599-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 05/07/2024] [Indexed: 05/12/2024] Open
Abstract
OBJECTIVE Diabetic patients are often comorbid with dyslipidemia, however, the relationship between high-density lipoprotein cholesterol(HDL-C) and diabetic retinopathy (DR) in the adult diabetic population remains to be fully elucidated.The aim of this study is to evaluate the associations between HDL-C and DR in the United States adults with diabetes. METHODS A total of 1708 participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2008 were enrolled in the present study. Fundus images of all study subjects were captured and evaluated using a digital camera and an ophthalmic digital imaging system, and the diagnosis of DR was made by the severity scale of the Early Treatment Diabetic Retinopathy Study (ETDRS).Roche Diagnostics were used to measure serum HDL-C concentration. The relationship of DR with HDL-C was investigated using multivariable logistic regression. The potential non-line correlation was explored with smooth curve fitting approach. RESULTS The fully-adjusted model showed that HDL-C positively correlated with DR(OR:1.69, 95%CI: 1.25-2.31).However, an inverted U-shaped association between them was observed by applying the smooth curve fitted method. The inflection point of HDL-C(1.99mmol/l) was calculated by utilizing the two-piecewise logistic regression model. In the subgroup analysis, the inverted U-shaped nonlinear correlation between HDL-C and DR was also found in female, Non-Hispanic White, and lower age groups. CONCLUSION Our study revealed an inverted U-shaped positive relationship between HDL-C and DR.The findings may provide us with a more comprehensive understanding of the association between HDL-C and DR.
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Affiliation(s)
- Wuping Xu
- Department of Ophthalmology, The First People's Hospital of Jiangyin District, Wuxi, Jiangsu, 214400, People's Republic of China.
| | - Xuedong Xu
- Department of Ophthalmology, The First People's Hospital of Jiangyin District, Wuxi, Jiangsu, 214400, People's Republic of China
| | - Min Zhang
- Department of Ophthalmology, The First People's Hospital of Jiangyin District, Wuxi, Jiangsu, 214400, People's Republic of China
| | - Chiping Sun
- Department of Ophthalmology, The First People's Hospital of Jiangyin District, Wuxi, Jiangsu, 214400, People's Republic of China
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2
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Zhu Y, Liu X, Li N, Cui L, Zhang X, Liu X, Yu K, Chen Y, Wan Z, Yu Z. Association Between Iron Status and Risk of Chronic Kidney Disease in Chinese Adults. Front Med (Lausanne) 2020; 6:303. [PMID: 31998726 PMCID: PMC6961557 DOI: 10.3389/fmed.2019.00303] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 12/02/2019] [Indexed: 12/19/2022] Open
Abstract
Background: Even though it is well-known that iron deficiency is the result of chronic kidney disease (CKD), whether iron will affect kidney function and disease in the general population is not clear. We thus conducted a nationwide cross-sectional study using data from the China Health and Nutrition Survey (CHNS) to assess the relationship of iron status with estimated glomerular filtration rate (eGFR) and CKD among general adults. Methods: A total of 8,339 adults from the China Health and Nutrition Survey in the wave of 2009 were included to assess the association between iron status and eGFR/CKD. Serum ferritin (SF), transferrin, soluble transferrin receptor (sTfR), and hemoglobin (Hb) were measured. The relationship of iron status and eGFR was evaluated by using multi-variable linear regression model. The effect of iron status on the odds of CKD was calculated by logistic regression model. Results: For the association between iron status and eGFR, every 100 μg/L increase in SF was correlated with 0.26 ml/min per 1.73 m2 (95% CI: 0.08-0.44) decrease in eGFR, and every 5 mg/L increase in sTfR was associated with a decrease of 6.00 ml/min per 1.73 m2 (95% CI: 3.79-8.21) in eGFR. There were no significant associations between Hb or transferrin with eGFR. For the association between iron status and CKD, every 5 g/L increase in sTfR was associated with an odds ratio of 3.72 (95% CI: 2.16-6.13) for CKD. The concentrations of Hb were associated with the odds of CKD in a U-shaped manner, with the lowest risk in the Hb range of 136-141 g/L. There was a positive correlation between SF concentration and CKD prevalence but not in a dose-response manner. The odds of CKD for participants in the highest tertile increased by 28% (98% CI: 1-63%) compared with those in the lowest tertile. Conclusion: The concentration of SF and sTfR was positively correlated with the odds of CKD, and Hb was associated with the odds of CKD in a U-shaped manner. Further large prospective researches are warranted to confirm these findings.
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Affiliation(s)
- Yongjian Zhu
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaozhuan Liu
- College of Food Science and Technology, Henan Agriculture University, Zhengzhou, China
| | - Ning Li
- College of Food Science and Technology, Henan Agriculture University, Zhengzhou, China
| | - Lingling Cui
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaofeng Zhang
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xinxin Liu
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Kailun Yu
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yao Chen
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhongxiao Wan
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zengli Yu
- School of Public Health, Zhengzhou University, Zhengzhou, China
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3
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Kelly CB, Yu JY, Jenkins AJ, Nankervis AJ, Hanssen KF, Garg SK, Scardo JA, Basu A, Hammad SM, Aston CE, Lyons TJ. Haptoglobin Phenotype Modulates Lipoprotein-Associated Risk for Preeclampsia in Women With Type 1 Diabetes. J Clin Endocrinol Metab 2019; 104:4743-4755. [PMID: 31219590 DOI: 10.1210/jc.2019-00723] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 06/14/2019] [Indexed: 02/13/2023]
Abstract
CONTEXT The incidence of preeclampsia (PE) is increased in women with diabetes (∼20% vs ∼5% in the general population), and first trimester lipoprotein profiles are predictive. Haptoglobin (Hp), a protein with functional genetic polymorphisms, has antioxidant, anti-inflammatory, and angiogenic effects. Among people with diabetes, the Hp 2-2 phenotype is associated with cardiorenal disease. OBJECTIVE To investigate whether Hp phenotype is associated with PE in type 1 diabetes mellitus (T1DM) and/or modulates lipoprotein-associated risks. DESIGN AND SETTING Multicenter prospective study of T1DM pregnancy. PATIENTS Pregnant women with T1DM (normal albuminuria, normotensive at enrolment, n = 47) studied at three visits, all preceding PE onset: 12.3 ± 1.9, 21.8 ± 1.5, and 31.5 ± 1.6 weeks' gestation (mean ± SD). MAIN OUTCOME MEASURES Hp phenotype and lipoprotein profiles in women with (n = 23) vs without (n = 24) subsequent PE. RESULTS Hp phenotype did not predict PE, but lipoprotein associations with subsequent PE were confined to women with Hp 2-2, in whom the following associations with PE were observed: increased low-density lipoprotein (LDL) cholesterol, LDL particle concentration, apolipoprotein B (APOB), triacylglycerol/high-density lipoprotein (HDL) cholesterol ratio, and APOB/apolipoprotein AI (APOA1) ratio; decreased HDL cholesterol, APOA1, large HDL particle concentration, and peripheral lipoprotein lipolysis (all P < 0.05). In women with one or two Hp-1 alleles, no such associations were observed. CONCLUSIONS In women with T1DM, although Hp phenotype did not predict PE risk, lipoprotein-related risks for PE were limited to those with the Hp 2-2 phenotype. Hp phenotype may modulate PE risk in diabetes.
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Affiliation(s)
- Clare B Kelly
- Division of Endocrinology, Medical University of South Carolina, Charleston, South Carolina
| | - Jeremy Y Yu
- Division of Endocrinology, Medical University of South Carolina, Charleston, South Carolina
| | - Alicia J Jenkins
- Division of Endocrinology, Medical University of South Carolina, Charleston, South Carolina
- NHMRC Clinical Trials Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Alison J Nankervis
- Diabetes Service, Royal Women's Hospital, Parkville, Victoria, Australia
| | - Kristian F Hanssen
- Department of Endocrinology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Satish K Garg
- Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado
| | - James A Scardo
- Spartanburg Regional Medical Center, Spartanburg, South Carolina
| | - Arpita Basu
- Department of Kinesiology and Nutrition Sciences, University of Nevada Las Vegas, Las Vegas, Nevada
| | - Samar M Hammad
- Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, South Carolina
| | - Christopher E Aston
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Timothy J Lyons
- Division of Endocrinology, Medical University of South Carolina, Charleston, South Carolina
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4
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Huang Y, Huang Y, Zhang R, Jin L, Zhang H, Hu C. Serum haptoglobin levels are associated with renal function decline in type 2 diabetes mellitus patients in a Chinese Han population. Diabetes Res Clin Pract 2019; 156:107865. [PMID: 31545979 DOI: 10.1016/j.diabres.2019.107865] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 09/06/2019] [Accepted: 09/18/2019] [Indexed: 02/06/2023]
Abstract
AIMS We investigated whether serum haptoglobin (Hp) levels play a role in the development and progression of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients in a Chinese Han population, which has not been previously investigated. METHODS We recruited 233 participants who had suffered from T2DM for more than 10 years, including 118 subjects with DKD (case) and 115 subjects without DKD (control). Serum Hp levels were measured by an enzyme-linked immunosorbent assay. RESULTS Serum Hp levels were significantly higher (P = 0.0258) in case group (2.74 (1.77, 3.48) g/L) than control (2.29 (0.98, 3.48) g/L). The serum Hp level was significantly positively associated with both logarithmically transformed (log-transformed) serum creatinine (r = 0.1663, P = 0.011) and albuminuria levels (r = 0.1793, P = 0.0062) and was negatively associated with the log-transformed estimated glomerular filtration rate (r = -0.1482, P = 0.0237). Multiple linear regression analysis revealed that serum Hp levels were significantly correlated with serum creatinine levels (P = 0.0088) after adjusting for confounding risk factors. CONCLUSIONS Our findings suggest that serum Hp levels may be used as a potential biomarker for the early diagnosis and monitoring of DKD in T2DM patients.
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Affiliation(s)
- Yeping Huang
- Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Huang
- National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu 210002, China
| | - Rong Zhang
- Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Li Jin
- National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu 210002, China
| | - Hong Zhang
- Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Cheng Hu
- Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Institute for Metabolic Diseases, Fengxian Central Hospital, The Third School of Clinical Medicine, Southern Medical University, Shanghai, China.
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5
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Zhu Y, Cai X, Liu Y, Hu M, Zhou L, Liu W, Wu J, Zhang R, Gao X, Yang W, Zhang S, Gong S, Luo Y, Li M, Gao L, Chen L, Chen J, Huang X, Ren Q, Zhang X, Zhou X, Han X, Ji L. Serum Albumin, but not Bilirubin, is Associated with Diabetic Chronic Vascular Complications in a Chinese Type 2 Diabetic Population. Sci Rep 2019; 9:12086. [PMID: 31427625 PMCID: PMC6700065 DOI: 10.1038/s41598-019-48486-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 08/01/2019] [Indexed: 12/21/2022] Open
Abstract
To identify the factors associated with serum total bilirubin (STB) and determine whether STB is independently associated with diabetic retinopathy (DR) or diabetic kidney disease (DKD), 1,665 Chinese patients with type 2 diabetes (T2DM) (248 outpatients newly diagnosed with T2DM [NDM] and 1,417 inpatients previously diagnosed with T2DM [PDM]) were studied. Clinical and biochemical information was collected, and a single nucleotide polymorphism (rs6704078) of the UGT1A1 gene was genotyped in 1,059 individuals. Multiple linear regression showed that STB was associated with haemoglobin concentration, platelet count, and serum triglyceride concentration in NDM and PDM patients, and with serum albumin, duration of diabetes, and smoking in PDM patients. In patients with PDM, multiple logistic regression revealed that serum albumin was associated with DR (odds ratio [OR] = 0.92, 95% confidence interval [CI]: 0.87-0.96, p = 0.001) and DKD (OR = 0.93, 95% CI: 0.88-0.98, p = 0.005) after adjustment for STB, STB-related factors, and risk factors for DR and DKD. In addition, patients with the T allele of rs6704078 had higher STB (13.2 [10.4-17.9] μmol/L versus 11.8 (9.4-14.8) μmol/L; p < 0.001) and similar risks of DR or DKD to those without the T allele. Thus, serum albumin, but not STB, is associated with DR and DKD.
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Affiliation(s)
- Yu Zhu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Xiaoling Cai
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Yan Liu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Mengdie Hu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Lingli Zhou
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Wei Liu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Jing Wu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Rui Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Xueying Gao
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Wenjia Yang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Simin Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Siqian Gong
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Yingying Luo
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Meng Li
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Leili Gao
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Ling Chen
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Jing Chen
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Xiuting Huang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Qian Ren
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Xiuying Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Xianghai Zhou
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China
| | - Xueyao Han
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China.
| | - Linong Ji
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, 100044, China.
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6
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Guan M, Keaton JM, Dimitrov L, Hicks PJ, Xu J, Palmer ND, Ma L, Das SK, Chen YDI, Coresh J, Fornage M, Franceschini N, Kramer H, Langefeld CD, Mychaleckyj JC, Parekh RS, Post WS, Rasmussen-Torvik LJ, Rich SS, Rotter JI, Sedor JR, Thornley-Brown D, Tin A, Wilson JG, Freedman BI, Bowden DW, Ng MCY. Genome-wide association study identifies novel loci for type 2 diabetes-attributed end-stage kidney disease in African Americans. Hum Genomics 2019; 13:21. [PMID: 31092297 PMCID: PMC6521376 DOI: 10.1186/s40246-019-0205-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 04/11/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND End-stage kidney disease (ESKD) is a significant public health concern disproportionately affecting African Americans (AAs). Type 2 diabetes (T2D) is the leading cause of ESKD in the USA, and efforts to uncover genetic susceptibility to diabetic kidney disease (DKD) have had limited success. A prior genome-wide association study (GWAS) in AAs with T2D-ESKD was expanded with additional AA cases and controls and genotypes imputed to the higher density 1000 Genomes reference panel. The discovery analysis included 3432 T2D-ESKD cases and 6977 non-diabetic non-nephropathy controls (N = 10,409), followed by a discrimination analysis in 2756 T2D non-nephropathy controls to exclude T2D-associated variants. RESULTS Six independent variants located in or near RND3/RBM43, SLITRK3, ENPP7, GNG7, and APOL1 achieved genome-wide significant association (P < 5 × 10-8) with T2D-ESKD. Following extension analyses in 1910 non-diabetic ESKD cases and 908 non-diabetic non-nephropathy controls, a meta-analysis of 5342 AA all-cause ESKD cases and 6977 AA non-diabetic non-nephropathy controls revealed an additional novel all-cause ESKD locus at EFNB2 (rs77113398; P = 9.84 × 10-9; OR = 1.94). Exclusion of APOL1 renal-risk genotype carriers identified two additional genome-wide significant T2D-ESKD-associated loci at GRAMD3 and MGAT4C. A second variant at GNG7 (rs373971520; P = 2.17 × 10-8, OR = 1.46) remained associated with all-cause ESKD in the APOL1-negative analysis. CONCLUSIONS Findings provide further evidence for genetic factors associated with advanced kidney disease in AAs with T2D.
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Grants
- HHSN268201300026C NHLBI NIH HHS
- N01HC95160 NHLBI NIH HHS
- U01 DK057300 NIDDK NIH HHS
- N01HC95169 NHLBI NIH HHS
- R01 DK117445 NIDDK NIH HHS
- HHSN268201700001I NHLBI NIH HHS
- N01HC95159 NHLBI NIH HHS
- N01HC95167 NHLBI NIH HHS
- HHSC268200782096C, DK081350, DK066358, DK053591, DK087914, DK105556, HL56266, DK070941 NIH HHS
- UL1 TR001881 NCATS NIH HHS
- HHSN268201700003I NHLBI NIH HHS
- U01 DK070657 NIDDK NIH HHS
- HHSN268201500003C NHLBI NIH HHS
- U01 DK057304 NIDDK NIH HHS
- R01 DK070941 NIDDK NIH HHS
- UL1 TR002548 NCATS NIH HHS
- U01 DK057298 NIDDK NIH HHS
- UL1 RR025005 NCRR NIH HHS
- N01HC95163 NHLBI NIH HHS
- HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, HHSN268200900041C, AG0005, N01-HC-65226 NIH HHS
- UL1 TR001079 NCATS NIH HHS
- U01 DK057295 NIDDK NIH HHS
- U01 DK105556 NIDDK NIH HHS
- R01 HL086694 NHLBI NIH HHS
- U01 DK057303 NIDDK NIH HHS
- P30 DK079626 NIDDK NIH HHS
- HHSN268201300048C NHLBI NIH HHS
- U01 HG004402 NHGRI NIH HHS
- N01HC95164 NHLBI NIH HHS
- HHSN268201300025C NHLBI NIH HHS
- N02HL64278 NHLBI NIH HHS
- N01HC95162 NHLBI NIH HHS
- N01HC95168 NHLBI NIH HHS
- R01 DK087914 NIDDK NIH HHS
- U01 DK057249 NIDDK NIH HHS
- P30 DK063491 NIDDK NIH HHS
- HHSN268201300027C NHLBI NIH HHS
- K99 DK081350 NIDDK NIH HHS
- HHSN268201300049C NHLBI NIH HHS
- R01 DK066358 NIDDK NIH HHS
- HHSN268200900041C NHLBI NIH HHS
- HHSN268201300028C NHLBI NIH HHS
- U01DK57292, U01DK57329, U01DK057300, U01DK057298, U01DK057249, U01DK57295, U01DK070657, U01DK057303, U01DK070657, U01DK57304, DK07024 NIH HHS
- HHSN268201700004I NHLBI NIH HHS
- N01HC95165 NHLBI NIH HHS
- N01HC95161 NHLBI NIH HHS
- HHSN268201300047C NHLBI NIH HHS
- UL1 TR001420 NCATS NIH HHS
- HHSN268201300050C NHLBI NIH HHS
- N01HC65226 NHLBI NIH HHS
- U01 DK057329 NIDDK NIH HHS
- M01 RR007122 NCRR NIH HHS
- R01 DK053591 NIDDK NIH HHS
- R01 MD012765 NIMHD NIH HHS
- UL1 TR000040 NCATS NIH HHS
- HHSN268201300046C NHLBI NIH HHS
- HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, DK063491, N02-HL-64278, UL1TR001881, DK063491 NIH HHS
- HHSN268201300049C, HHSN268201300050C, HHSN268201300048C, HHSN268201300046C, HHSN268201300047C NIH HHS
- HHSN268201700002I NHLBI NIH HHS
- HHSN268201700005I NHLBI NIH HHS
- U01 DK057292 NIDDK NIH HHS
- N01HC95166 NHLBI NIH HHS
- HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, HHSN268201700005I, R01HL087641, R01HL086694, U01HG004402, HHSN268200625226C, UL1RR025005 NIH HHS
- HHSN268201300029C NHLBI NIH HHS
- R01 HL087641 NHLBI NIH HHS
- National Institutes of Health
- Wake Forest School of Medicine
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Affiliation(s)
- Meijian Guan
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jacob M Keaton
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Pamela J Hicks
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jianzhao Xu
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Nicholette D Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Lijun Ma
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Swapan K Das
- Department of Internal Medicine, Section on Endocrinology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Holly Kramer
- Departments of Public Health Sciences and Medicine, Division of Nephrology and Hypertension, Loyola University Chicago, Maywood, IL, USA
- Department of Medicine, Hines Veteran's Affairs Medical Center, Hines, IL, USA
| | - Carl D Langefeld
- Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Rulan S Parekh
- Departments of Paediatrics and Medicine, Hospital for Sick Children, University Health Network and the University of Toronto, Toronto, ON, Canada
| | - Wendy S Post
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Division of Genomic Outcomes, Departments of Pediatrics and Medicine, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - John R Sedor
- Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA
- Glickman Urology and Kidney Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | | | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA.
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA.
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA.
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