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1. A genome-wide search for linkage of estimated glomerular filtration rate (eGFR) in the family investigation of nephropathy and diabetes (FIND)

Author

Thameem, F, Igo, RP, Freedman, BI, Langefeld, C, Hanson, RL, Schelling, JR, Elston, RC, Duggirala, R, Nicholas, SB, Goddard, KAB, Divers, J, Guo, X, Ipp, E, Kimmel, PL, Meoni, LA, Shah, VO, Smith, MW, Winkler, CA, Zager, PG, Knowler, WC, Nelson, RG, Pahl, MV, Parekh, RS, Kao, WHL, Rasooly, RS, Adler, SG, Abboud, HE, Iyengar, SK, and Sedor, JR

Abstract

Objective: Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR. Methods: Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula. Results: The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10-5) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10-4) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10-4) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome. Conclusion: The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN. © 2013 Thameem et al.

Published
2013

2. Adiposity and risk of decline in glomerular filtration rate : Meta-analysis of individual participant data in a global consortium

Author

Chang AR, Grams ME, Ballew SH, Bilo H, Correa A, Evans M, Gutierrez OM, Hosseinpanah F, Iseki K, Kenealy T, Klein B, Kronenberg F, Lee BJ, Li Y, Miura K, Navaneethan SD, Roderick PJ, Valdivielso JM, Visseren FLJ, Zhang L, Gansevoort RT, Hallan SI, Levey AS, Matsushita K, Shalev V, Woodward M, Astor B, Appel L, Greene T, Chen T, Chalmers J, Arima H, Perkovic V, Yatsuya H, Tamakoshi K, Hirakawa Y, Coresh J, Sang Y, Polkinghorne K, Chadban S, Atkins R, Levin A, Djurdjev O, Klein R, Lee K, Liu L, Zhao M, Wang F, Wang J, Tang M, Heine G, Emrich I, Zawada A, Bauer L, Nally J, Schold J, Shlipak M, Sarnak M, Katz R, Hiramoto J, Iso H, Yamagishi K, Umesawa M, Muraki I, Fukagawa M, Maruyama S, Hamano T, Hasegawa T, Fujii N, Jafar T, Hatcher J, Poulter N, Chaturvedi N, Wheeler D, Emberson J, Townend J, Landray M, Brenner H, Schöttker B, Saum KU, Rothenbacher D, Fox C, Hwang SJ, Köttgen A, Schneider MP, Eckardt KU, Green J, Kirchner HL, Ito S, Miyazaki M, Nakayama M, Yamada G, Cirillo M, Romundstad S, Øvrehus M, Langlo KA, Irie F, Sairenchi T, Rebholz CM, Young B, Boulware LE, Ishikawa S, Yano Y, Kotani K, Nakamura T, Jee SH, Kimm H, Mok Y, Chodick G, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Bots M, Inker L, Peralta C, Kollerits B, Ritz E, Nitsch D, Fletcher A, Bottinger E, Nadkarni GN, Ellis SB, Nadukuru R, Fernandez E, Betriu A, Bermudez-Lopez M, Stengel B, Metzger M, Flamant M, Houillier P, Haymann JP, Froissart M, Ueshima H, Okayama A, Tanaka S, Okamura T, Elley CR, Collins JF, Drury PL, Ohkubo T, Asayama K, Metoki H, Kikuya M, Iseki C, Nelson RG, Knowler WC, Bakker SJL, Heerspink HJL, Brunskill N, Major R, Shepherd D, Medcalf J, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Kovesdy C, Kalantar-Zadeh K, Sumida K, Muntner P, Warnock D, Judd S, Panwar B, de Zeeuw D, Brenner B, Sedaghat S, Ikram MA, Hoorn EJ, Dehghan A, Wong TY, Sabanayagam C, Cheng CY, Banu R, Segelmark M, Stendahl M, Schön S, Tangri N, Sud M, Naimark D, Wen CP, Tsao CK, Tsai MK, Chen CH, Konta T, Hirayama A, Ichikawa K, Hadaegh F, Mirbolouk M, Azizi F, Solbu MD, Jenssen TG, Eriksen BO, Eggen AE, Lannfelt L, Larsson A, Ärnlöv J, Landman GWD, van Hateren KJJ, Kleefstra N, Chen J, Kwak L, Surapaneni A., Chang, Ar, Grams, Me, Ballew, Sh, Bilo, H, Correa, A, Evans, M, Gutierrez, Om, Hosseinpanah F, Iseki K, Kenealy, T, Klein, B, Kronenberg, F, Lee, Bj, Li, Y, Miura, K, Navaneethan, Sd, Roderick, Pj, Valdivielso, Jm, Visseren, Flj, Zhang, L, Gansevoort, Rt, Hallan, Si, Levey, A, Matsushita, K, Shalev, V, Woodward, M, Astor, B, Appel, L, Greene, T, Chen, T, Chalmers, J, Arima, H, Perkovic, V, Yatsuya, H, Tamakoshi, K, Hirakawa, Y, Coresh, J, Sang, Y, Polkinghorne, K, Chadban, S, Atkins, R, Levin, A, Djurdjev, O, Klein, R, Lee, K, Liu, L, Zhao, M, Wang, F, Wang, J, Tang, M, Heine, G, Emrich, I, Zawada, A, Bauer, L, Nally, J, Schold, J, Shlipak, M, Sarnak, M, Katz, R, Hiramoto, J, Iso, H, Yamagishi, K, Umesawa, M, Muraki, I, Fukagawa, M, Maruyama, S, Hamano, T, Hasegawa, T, Fujii, N, Jafar, T, Hatcher, J, Poulter, N, Chaturvedi, N, Wheeler, D, Emberson, J, Townend, J, Landray, M, Brenner, H, Schöttker, B, Saum, Ku, Rothenbacher, D, Fox, C, Hwang, Sj, Köttgen, A, Schneider, Mp, Eckardt, Ku, Green, J, Kirchner, Hl, Ito, S, Miyazaki, M, Nakayama, M, Yamada, G, Cirillo, M, Romundstad, S, Øvrehus, M, Langlo, Ka, Irie, F, Sairenchi, T, Rebholz, Cm, Young, B, Boulware, Le, Ishikawa, S, Yano, Y, Kotani, K, Nakamura, T, Jee, Sh, Kimm, H, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Bots, M, Inker, L, Peralta, C, Kollerits, B, Ritz, E, Nitsch, D, Fletcher, A, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Fernandez, E, Betriu, A, Bermudez-Lopez, M, Stengel, B, Metzger, M, Flamant, M, Houillier, P, Haymann, Jp, Froissart, M, Ueshima, H, Okayama, A, Tanaka, S, Okamura, T, Elley, Cr, Collins, Jf, Drury, Pl, Ohkubo, T, Asayama, K, Metoki, H, Kikuya, M, Iseki, C, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Heerspink, Hjl, Brunskill, N, Major, R, Shepherd, D, Medcalf, J, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Kovesdy, C, Kalantar-Zadeh, K, Sumida, K, Muntner, P, Warnock, D, Judd, S, Panwar, B, de Zeeuw, D, Brenner, B, Sedaghat, S, Ikram, Ma, Hoorn, Ej, Dehghan, A, Wong, Ty, Sabanayagam, C, Cheng, Cy, Banu, R, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Wen, Cp, Tsao, Ck, Tsai, Mk, Chen, Ch, Konta, T, Hirayama, A, Ichikawa, K, Hadaegh, F, Mirbolouk, M, Azizi, F, Solbu, Md, Jenssen, Tg, Eriksen, Bo, Eggen, Ae, Lannfelt, L, Larsson, A, Ärnlöv, J, Landman, Gwd, van Hateren, Kjj, Kleefstra, N, Chen, J, Kwak, L, Surapaneni, A., Lifestyle Medicine (LM), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Asayama, Kei, and Sedaghat, SeyyedMah

Subjects
CHRONIC KIDNEY-DISEASE, Male, 030232 urology & nephrology, 030204 cardiovascular system & hematology, OBESITY PARADOX, Body Mass Index, BMI, eGFR, CKD-PC, Cohort Studies, 0302 clinical medicine, Risk Factors, Urologi och njurmedicin, Medicine, ALL-CAUSE MORTALITY, Adiposity, 2. Zero hunger, Aged, 80 and over, Medicine(all), education.field_of_study, Hazard ratio, ASSOCIATION, General Medicine, Middle Aged, 3. Good health, Cohort, Female, Waist Circumference, Life Sciences & Biomedicine, WAIST CIRCUMFERENCE, Obesity paradox, Glomerular Filtration Rate, Adult, Waist, Population, Renal function, 03 medical and health sciences, Medicine, General & Internal, General & Internal Medicine, CKD, Urology and Nephrology, Humans, Mortality, education, Aged, Science & Technology, business.industry, Research, medicine.disease, Body Height, BODY-MASS INDEX, Kidney Failure, Chronic, WEIGHT, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Body mass index, Demography, Kidney disease
Abstract

ObjectiveTo evaluate the associations between adiposity measures (body mass index, waist circumference, and waist-to-height ratio) with decline in glomerular filtration rate (GFR) and with all cause mortality.DesignIndividual participant data meta-analysis.SettingCohorts from 40 countries with data collected between 1970 and 2017.ParticipantsAdults in 39 general population cohorts (n=5 459 014), of which 21 (n=594 496) had data on waist circumference; six cohorts with high cardiovascular risk (n=84 417); and 18 cohorts with chronic kidney disease (n=91 607).Main outcome measuresGFR decline (estimated GFR decline ≥40%, initiation of kidney replacement therapy or estimated GFR 2) and all cause mortality.ResultsOver a mean follow-up of eight years, 246 607 (5.6%) individuals in the general population cohorts had GFR decline (18 118 (0.4%) end stage kidney disease events) and 782 329 (14.7%) died. Adjusting for age, sex, race, and current smoking, the hazard ratios for GFR decline comparing body mass indices 30, 35, and 40 with body mass index 25 were 1.18 (95% confidence interval 1.09 to 1.27), 1.69 (1.51 to 1.89), and 2.02 (1.80 to 2.27), respectively. Results were similar in all subgroups of estimated GFR. Associations weakened after adjustment for additional comorbidities, with respective hazard ratios of 1.03 (0.95 to 1.11), 1.28 (1.14 to 1.44), and 1.46 (1.28 to 1.67). The association between body mass index and death was J shaped, with the lowest risk at body mass index of 25. In the cohorts with high cardiovascular risk and chronic kidney disease (mean follow-up of six and four years, respectively), risk associations between higher body mass index and GFR decline were weaker than in the general population, and the association between body mass index and death was also J shaped, with the lowest risk between body mass index 25 and 30. In all cohort types, associations between higher waist circumference and higher waist-to-height ratio with GFR decline were similar to that of body mass index; however, increased risk of death was not associated with lower waist circumference or waist-to-height ratio, as was seen with body mass index.ConclusionsElevated body mass index, waist circumference, and waist-to-height ratio are independent risk factors for GFR decline and death in individuals who have normal or reduced levels of estimated GFR.

Published
2019

3. A Genome-Wide Association Study Using a Custom Genotyping Array Identifies Variants in GPR158 Associated With Reduced Energy Expenditure in American Indians

Author

Piaggi, P, Masindova, I, Muller, Yl, Mercader, J, Wiessner, Gb, Chen, P, Sigma Type, 2 Diabetes Consortium, Kobes, S, Hsueh, Wc, Mongalo, M, Knowler, Wc, Krakoff, J, Hanson, Rl, Bogardus, C, and Baier, Lj

Subjects
Male, 0301 basic medicine, North American/*genetics Male Middle Aged Receptors, Endocrinology, Diabetes and Metabolism, Genome-wide association study, Body Mass Index, Receptors, G-Protein-Coupled, 0302 clinical medicine, Type 2/ethnology/genetics Energy Metabolism/*genetics Female Genetic Variation/*genetics Genome-Wide Association Study Humans Indians, Adiposity, Genetics, education.field_of_study, Arizona, Genetics/Genomes/Proteomics/Metabolomics, Middle Aged, Adiposity/genetics Adult Alleles Arizona Basal Metabolism/genetics Body Mass Index Calorimetry/methods Diabetes Mellitus, Type 2/ethnology/genetics Energy Metabolism/*genetics Female Genetic Variation/*genetics Genome-Wide Association Study Humans Indians, North American/*genetics Male Middle Aged Receptors, G-Protein-Coupled/*genetics, Female, medicine.symptom, Adult, medicine.medical_specialty, Population, 030209 endocrinology & metabolism, Calorimetry, Biology, 03 medical and health sciences, Internal medicine, Internal Medicine, medicine, Humans, Allele, education, Adiposity/genetics Adult Alleles Arizona Basal Metabolism/genetics Body Mass Index Calorimetry/methods Diabetes Mellitus, G-Protein-Coupled/*genetics, Genotyping, Alleles, Genetic Variation, nutritional and metabolic diseases, Heritability, medicine.disease, Obesity, 030104 developmental biology, Endocrinology, Diabetes Mellitus, Type 2, Basal metabolic rate, Indians, North American, Basal Metabolism, Energy Metabolism, Weight gain, Genome-Wide Association Study
Abstract

Pima Indians living in Arizona have a high prevalence of obesity, and we have previously shown that a relatively lower energy expenditure (EE) predicts weight and fat mass gain in this population. EE is a familial trait (heritability = 0.52); therefore, in the current study, we aimed to identify genetic variants that affect EE and thereby influence BMI and body fatness in Pima Indians. Genotypic data from 491,265 variants were analyzed for association with resting metabolic rate (RMR) and 24-h EE assessed in a whole-room calorimeter in 507 and 419 Pima Indians, respectively. Variants associated with both measures of EE were analyzed for association with maximum BMI and percent body fat (PFAT) in 5,870 and 912 Pima Indians, respectively. rs11014566 nominally associated with both measures of EE and both measures of adiposity in Pima Indians, where the G allele (frequency: Pima Indians = 0.60, Europeans

Published
2017
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4. Relative risks of Chronic Kidney Disease for mortality and End Stage Renal Disease across races is similar

Author

Wright, Jt, Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Coresh, J, Matsushita, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Liu, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, F, Curhan, G, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, J, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, L, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasard, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, J, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, L, Menon, V, Fried, Lf, Kramer, H, Boer, De, I, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, J, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Bakker, Sj, Bernardo, R, Kaur, Jassal, S, Barrett Connor, E, Bergstrom, J, Heerspink, Hj, Brenner, B, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Wu, Be, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, Br, Ballew, Sh, Grams, M, Sang, Y, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright, Jt, Jr, Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Coresh, J, Matsushita, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Liu, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, F, Curhan, G, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, J, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, L, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasard, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, J, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Levey, A, Inker, L, Menon, V, Fried, Lf, Kramer, H, De, Boer, I, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, J, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, De, Jong, Pe, Mahmoodi, Bk, Bakker, Sj, Bernardo, R, Kaur, Jassal, S, Barrett Connor, E, Bergstrom, J, Heerspink, Hj, Brenner, B, De, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Be, Wu, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, Br, Ballew, Sh, Grams, M, Sang, Y, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
Male, GLOMERULAR-FILTRATION-RATE, Cohort Studies, Risk Factors, eGFR, Odds Ratio, ASSOCIATIONS, African Continental Ancestry Group, Aged, 80 and over, education.field_of_study, end-stage renal disease, Hazard ratio, PROTEINURIA, Urology & Nephrology, Middle Aged, CKD-EPI EQUATION, 3. Good health, PREVALENCE, Nephrology, Cardiovascular Diseases, Creatinine, ethnicity, Female, medicine.symptom, epidemiology and outcomes, Glomerular Filtration Rate, Asian Continental Ancestry Group, Adult, medicine.medical_specialty, Population, European Continental Ancestry Group, Renal function, Black People, ALL-CAUSE, Article, White People, End stage renal disease, Asian People, Internal medicine, medicine, Chronic Kidney Disease Prognosis Consortium, Albuminuria, Humans, Renal Insufficiency, Chronic, education, Aged, business.industry, 1103 Clinical Sciences, Odds ratio, POPULATION COHORTS, medicine.disease, INDIVIDUALS, Endocrinology, Relative risk, COLLABORATIVE METAANALYSIS, mortality risk, Kidney Failure, Chronic, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, HIGHER ALBUMINURIA, chronic kidney disease, Kidney disease
Abstract

Item does not contain fulltext Some suggest race-specific cutpoints for kidney measures to define and stage chronic kidney disease (CKD), but evidence for race-specific clinical impact is limited. To address this issue, we compared hazard ratios of estimated glomerular filtration rates (eGFR) and albuminuria across races using meta-regression in 1.1 million adults (75% Asians, 21% Whites, and 4% Blacks) from 45 cohorts. Results came mainly from 25 general population cohorts comprising 0.9 million individuals. The associations of lower eGFR and higher albuminuria with mortality and end-stage renal disease (ESRD) were largely similar across races. For example, in Asians, Whites, and Blacks, the adjusted hazard ratios (95% confidence interval) for eGFR 45-59 versus 90-104 ml/min per 1.73 m(2) were 1.3 (1.2-1.3), 1.1 (1.0-1.2), and 1.3 (1.1-1.7) for all-cause mortality, 1.6 (1.5-1.7), 1.4 (1.2-1.7), and 1.4 (0.7-2.9) for cardiovascular mortality, and 27.6 (11.1-68.7), 11.2 (6.0-20.9), and 4.1 (2.2-7.5) for ESRD, respectively. The corresponding hazard ratios for urine albumin-to-creatinine ratio 30-299 mg/g or dipstick 1+ versus an albumin-to-creatinine ratio under 10 or dipstick negative were 1.6 (1.4-1.8), 1.7 (1.5-1.9), and 1.8 (1.7-2.1) for all-cause mortality, 1.7 (1.4-2.0), 1.8 (1.5-2.1), and 2.8 (2.2-3.6) for cardiovascular mortality, and 7.4 (2.0-27.6), 4.0 (2.8-5.9), and 5.6 (3.4-9.2) for ESRD, respectively. Thus, the relative mortality or ESRD risks of lower eGFR and higher albuminuria were largely similar among three major races, supporting similar clinical approach to CKD definition and staging, across races.

Published
2014

5. Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies

Author

Coresh, J, Heerspink, HJL, Sang, Y, Matsushita, K, Arnlov, J, Astor, BC, Black, C, Brunskill, NJ, Carrero, JJ, Feldman, HI, Fox, CS, Inker, LA, Ishani, A, Ito, S, Jassal, S, Konta, T, Polkinghorne, K, Romundstad, S, Solbu, MD, Stempniewicz, N, Stengel, B, Tonelli, M, Umesawa, M, Waikar, SS, Wen, CP, Wetzels, JFM, Woodward, M, Grams, ME, Kovesdy, CP, Levey, AS, Gansevoort, RT, Appel, LJ, Greene, T, Chen, TK, Chalmers, J, Arima, H, Perkovic, V, Levin, A, Djurdjev, O, Tang, M, Nally, J, Navaneethan, SD, Schold, JD, Weldegiorgis, M, Herrington, WG, Smith, M, Hsu, CY, Hwang, SJ, Chang, AR, Kirchner, HL, Green, JA, Ho, K, Marks, A, Prescott, G, Clark, LE, Fluck, N, Shalev, V, Chodick, G, Blankestijn, PJ, Van Zuilen, A, Van den Brand, JA, Sarnak, MJ, Bottinger, E, Nadkarni, GN, Ellis, SG, Nadukuru, R, Metzger, M, Flamant, M, Houillier, P, Haymann, JP, Froissart, M, Kenealy, T, Elley, RC, Collins, JF, Drury, PL, Cuddeback, JK, Ciemins, EL, Stempniewicz, R, Nelson, RG, Knowler, WC, Bakker, SJ, Major, RW, Medcalf, JF, Shepherd, D, Barrett-Connor, E, Bergstrom, J, Ix, JH, Molnar, MZ, Sumida, K, de Zeeuw, D, Brenner, B, Qureshi, AR, Elinder, CG, Runesson, B, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Naimark, DM, Tangri, N, Coresh, J, Heerspink, HJL, Sang, Y, Matsushita, K, Arnlov, J, Astor, BC, Black, C, Brunskill, NJ, Carrero, JJ, Feldman, HI, Fox, CS, Inker, LA, Ishani, A, Ito, S, Jassal, S, Konta, T, Polkinghorne, K, Romundstad, S, Solbu, MD, Stempniewicz, N, Stengel, B, Tonelli, M, Umesawa, M, Waikar, SS, Wen, CP, Wetzels, JFM, Woodward, M, Grams, ME, Kovesdy, CP, Levey, AS, Gansevoort, RT, Appel, LJ, Greene, T, Chen, TK, Chalmers, J, Arima, H, Perkovic, V, Levin, A, Djurdjev, O, Tang, M, Nally, J, Navaneethan, SD, Schold, JD, Weldegiorgis, M, Herrington, WG, Smith, M, Hsu, CY, Hwang, SJ, Chang, AR, Kirchner, HL, Green, JA, Ho, K, Marks, A, Prescott, G, Clark, LE, Fluck, N, Shalev, V, Chodick, G, Blankestijn, PJ, Van Zuilen, A, Van den Brand, JA, Sarnak, MJ, Bottinger, E, Nadkarni, GN, Ellis, SG, Nadukuru, R, Metzger, M, Flamant, M, Houillier, P, Haymann, JP, Froissart, M, Kenealy, T, Elley, RC, Collins, JF, Drury, PL, Cuddeback, JK, Ciemins, EL, Stempniewicz, R, Nelson, RG, Knowler, WC, Bakker, SJ, Major, RW, Medcalf, JF, Shepherd, D, Barrett-Connor, E, Bergstrom, J, Ix, JH, Molnar, MZ, Sumida, K, de Zeeuw, D, Brenner, B, Qureshi, AR, Elinder, CG, Runesson, B, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Naimark, DM, and Tangri, N

Abstract

Background: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. Methods: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. Findings: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-P

Published
2019

6. Age and Association of Kidney Measures With Mortality and End-stage Renal Disease

Author

Wright, Jt, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Brenner, Be, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright JT Jr, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, de Jong PE, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
Male, BLOOD-PRESSURE, urologic and male genital diseases, Kidney, età, GLOMERULAR-FILTRATION-RATE, Cohort Studies, eGFR, Young adult, Renal disorder [IGMD 9], ALL-CAUSE MORTALITY, GENERAL-POPULATION, insufficienza renale, biology, CYSTATIN C, CARDIOVASCULAR RISK, Age Factors, General Medicine, Middle Aged, female genital diseases and pregnancy complications, RISK POPULATION COHORTS, medicine.anatomical_structure, Female, medicine.symptom, Glomerular Filtration Rate, albuminuria, rischio, mortalità, Adult, Risk, medicine.medical_specialty, Adolescent, Renal function, Context (language use), End stage renal disease, Young Adult, Internal medicine, medicine, Albuminuria, Humans, OLDER-ADULTS, Aged, urogenital system, business.industry, URINARY ALBUMIN EXCRETION, medicine.disease, Endocrinology, Cystatin C, COLLABORATIVE METAANALYSIS, biology.protein, Kidney Failure, Chronic, business, Kidney disease
Abstract

Context Chronic kidney disease (CKD) is prevalent in older individuals, but the risk implications of low estimated glomerular filtration rate (eGFR) and high albuminuria across the full age range are controversial.Objective To evaluate possible effect modification (interaction) by age of the association of eGFR and albuminuria with clinical risk, examining both relative and absolute risks.Design, Setting, and Participants Individual-level meta-analysis including 2 051 244 participants from 33 general population or high-risk (of vascular disease) cohorts and 13 CKD cohorts from Asia, Australasia, Europe, and North/South America, conducted in 1972-2011 with a mean follow-up time of 5.8 years (range, 0-31 years).Main Outcome Measures Hazard ratios (HRs) of mortality and end-stage renal disease (ESRD) according to eGFR and albuminuria were meta-analyzed across age categories after adjusting for sex, race, cardiovascular disease, diabetes, systolic blood pressure, cholesterol, body mass index, and smoking. Absolute risks were estimated using HRs and average incidence rates.Results Mortality (112 325 deaths) and ESRD (8411 events) risks were higher at lower eGFR and higher albuminuria in every age category. In general and high-risk cohorts, relative mortality risk for reduced eGFR decreased with increasing age; eg, adjusted HRs at an eGFR of 45 mL/min/1.73 m(2) vs 80 mL/min/1.73 m(2) were 3.50 (95% CI, 2.55-4.81), 2.21 (95% CI, 2.02-2.41), 1.59 (95% CI, 1.42-1.77), and 1.35 (95% CI, 1.23-1.48) in age categories 18-54, 55-64, 65-74, and >= 75 years, respectively (P Conclusions Both low eGFR and high albuminuria were independently associated with mortality and ESRD regardless of age across a wide range of populations. Mortality showed lower relative risk but higher absolute risk differences at older age.

Published
2012
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7. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis

Author

Fox, Cs, Matsushita, K, Woodward, M, Bilo, Hj, Chalmers, J, Heerspink, Hj, Lee, Bj, Perkins, Rm, Rossing, P, Sairenchi, T, Tonelli, M, Vassalotti, Ja, Yamagishi, K, Coresh, J, Jong, De, Wen, Cp, Nelson, Rg, Chronic, Kidney, Disease, Prognosis, Consortium, Investigators/collaborators:, Wright, J, Appel, L, Greene, T, Astor, Bc, Macmahon, S, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Hwang, Sj, Meigs, Jb, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Li, S, Chen, Sc, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Menon, V, Kramer, Hj, Boer, De, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Knowler, Wc, Gansevoort, Rt, Mahmoodi, Bk, Bakker, Sj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Lambers, Heerspink, Brenner, Be, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, B, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Groningen Kidney Center (GKC), Methods in Medicines evaluation & Outcomes research (M2O), Lifestyle Medicine (LM), Fox, C, Matsushita, K, Woodward, M, Bilo, Hj, Chalmers, J, Heerspink, Hj, Lee, Bj, Perkins, Rm, Rossing, P, Sairenchi, T, Tonelli, M, Vassalotti, Ja, Yamagishi, K, Coresh, J, de Jong PE, Wen, Cp, Nelson, Rg, Investigators/Collaborators: Wright J, Chronic Kidney Disease Prognosis Consortium, Appel, L, Greene, T, Astor, Bc, Macmahon, S, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Hwang, Sj, Meigs, Jb, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Li, S, Chen, Sc, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer IH, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Knowler, Wc, Gansevoort, Rt, Mahmoodi, Bk, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink HJ, Brenner, Be, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, B, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
medicine.medical_specialty, Population, UNITED-STATES, Renal function, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, albuminuria, End stage renal disease, Diabetic nephropathy, CKD-PC Consortium, Diabetes mellitus, Internal medicine, eGFR, Medicine, ESTIMATED GFR, education, Intensive care medicine, Renal disorder [IGMD 9], OUTCOMES, education.field_of_study, end-stage renal disease, diabetes, business.industry, Hazard ratio, PROTEINURIA, General Medicine, mortality, medicine.disease, RISK POPULATION COHORTS, PREVALENCE, diabete, COLLABORATIVE METAANALYSIS, Albuminuria, medicine.symptom, HIGHER ALBUMINURIA, business, Kidney disease
Abstract

Item does not contain fulltext BACKGROUND: Chronic kidney disease is characterised by low estimated glomerular filtration rate (eGFR) and high albuminuria, and is associated with adverse outcomes. Whether these risks are modified by diabetes is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and end-stage renal disease (ESRD) associated with eGFR and albuminuria in individuals with and without diabetes. FINDINGS: We analysed data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts. In the combined general population and high-risk cohorts with data for all-cause mortality, 75,306 deaths occurred during a mean follow-up of 8.5 years (SD 5.0). In the 23 studies with data for cardiovascular mortality, 21,237 deaths occurred from cardiovascular disease during a mean follow-up of 9.2 years (SD 4.9). In the general and high-risk cohorts, mortality risks were 1.2-1.9 times higher for participants with diabetes than for those without diabetes across the ranges of eGFR and albumin-to-creatinine ratio (ACR). With fixed eGFR and ACR reference points in the diabetes and no diabetes groups, HR of mortality outcomes according to lower eGFR and higher ACR were much the same in participants with and without diabetes (eg, for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) [vs 95 mL/min per 1.73 m(2)], HR 1.35; 95% CI 1.18-1.55; vs 1.33; 1.19-1.48 and at ACR 30 mg/g [vs 5 mg/g], 1.50; 1.35-1.65 vs 1.52; 1.38-1.67). The overall interactions were not significant. We identified much the same findings for ESRD in the chronic kidney disease cohorts. INTERPRETATION: Despite higher risks for mortality and ESRD in diabetes, the relative risks of these outcomes by eGFR and ACR are much the same irrespective of the presence or absence of diabetes, emphasising the importance of kidney disease as a predictor of clinical outcomes. FUNDING: US National Kidney Foundation.

Published
2012
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8. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate

Author

Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, As, Chronic, Kidney, Disease, Prognosis, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, Es, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Menon, V, Boer, De, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Jong, De, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, Zeeuw, De, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, A, Chronic, Kidney, Disease, Prognosi, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, E, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Menon, V, De, Boer, Ih, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, De, Jong, Pe, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, De, Zeeuw, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
CHRONIC KIDNEY-DISEASE, Gerontology, Male, EVALUATION PROGRAM KEEP, Population, Renal function, Black People, Ckd epi equation, urologic and male genital diseases, Risk Assessment, White People, Article, Decision Support Techniques, Cohort Studies, Sex Factors, Asian People, EPIDEMIOLOGY COLLABORATION EQUATION, Diabetes mellitus, CYSTATIN-C, Medicine, Humans, education, ALL-CAUSE MORTALITY, Cardiovascular mortality, Aged, Renal disorder [IGMD 9], GENERAL-POPULATION, education.field_of_study, business.industry, CARDIOVASCULAR RISK, Hazard ratio, STAGE RENAL-DISEASE, General Medicine, POPULATION COHORTS, Middle Aged, Models, Theoretical, medicine.disease, female genital diseases and pregnancy complications, Net reclassification improvement, SERUM CREATININE VALUES, Cardiovascular Diseases, Kidney Failure, Chronic, Female, business, Algorithms, Demography, Glomerular Filtration Rate
Abstract

Contains fulltext : 110640.pdf (Publisher’s version ) (Closed access) CONTEXT: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE: To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS: A meta-analysis of data from 1.1 million adults (aged >/= 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES: All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS: Estimated GFR was classified into 6 categories (>/=90, 60-89, 45-59, 30-44, 15-29, and /=65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION: The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.

Published
2012

9. Past Decline Versus Current eGFR and Subsequent Mortality Risk

Author

Naimark DMJ, Grams ME, Matsushita K, Black C, Drion I, Fox CS, Inker LA, Ishani A, Jee SA, Kitamura A, Lea JP, Nally J, Peralta CA, Rothenbacher D, Ryu S, Tonelli M, Yatsuya H, Coresh J, Gansevoort RT, Warnock DG, Woodward M, de Jong PE, the CKD Prognosis Consortium, Wright JTJr, Appel LJ, Greene T, MacMahon S, Chalmers J, Arima H, Yamashita K, Toyoshima H, Tamakoshi K, Hemmelgarn B, James M, Sang Y, Atkins RC, Polkinghorne KR, Chadban S, Shankar A, Klein R, Klein BEK, Lee KE, Levin A, Djurdjev O, Sacks FM, Curhan GC, Zawada AM, Rogacev KS, Seiler S, Heine GH, Navaneethan SD, Schold JD, Shlipak M, Sarnak MJ, Katz R, Imano H, Yamagishi K, Wheeler DC, Emberson J, Townend JN, Landray MJ, Brenner H, Müller H, Schöttker B, Hwang S-J, Meigs JB, Uphadhay A, Green J, Kirchner HL, Perkins R, Chang AR, Fluck N, Prescott GJ, Cirillo M, Hallan S, Aasarød K, Øien CM, Radtke M, Irie F, Iso H, Sairenchi T, Smith DH, Thorp ML, Johnson ES, Lee BJ, Guallar E, Chang SY, Cho J, Shin H, Chodick G, Shalev V, Birnbaum YC, Shainberg B, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Levey AS, Neaton JD, Froissart M, Stengel B, Metzger M, Haymann J-P, Houillier P, Flamant M, Elley CR, Kenealy T, Moyes SA, Collins JF, Drury PL, Ohkubo T, Metoki H, Nakayama M, Imai Y, Iseki K, Nelson RG, Knowler WC, Bakker SJL, LHillege H, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Heerspink HJL, Brenner BE, de Zeeuw D, Kimm H, Mok Y, Tangri N, Wen C-P, Wen S-F, Tsao C-K, Tsai M-K, Ärnlöv J, Lannfelt L, Larsson A, Kovesdy CP, Kalantar-Zadeh K, Bilo HJ, Kleefstra N, Groenier KH, Joosten H, Ballew SH, Naimark, Dmj, Grams, Me, Matsushita, K, Black, C, Drion, I, Fox, C, Inker, La, Ishani, A, Jee, Sa, Kitamura, A, Lea, Jp, Nally, J, Peralta, Ca, Rothenbacher, D, Ryu, S, Tonelli, M, Yatsuya, H, Coresh, J, Gansevoort, Rt, Warnock, Dg, Woodward, M, de Jong, Pe, the CKD Prognosis, Consortium, Wright, Jtjr, Appel, Lj, Greene, T, Macmahon, S, Chalmers, J, Arima, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Hemmelgarn, B, James, M, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Zawada, Am, Rogacev, K, Seiler, S, Heine, Gh, Navaneethan, Sd, Schold, Jd, Shlipak, M, Sarnak, Mj, Katz, R, Imano, H, Yamagishi, K, Wheeler, Dc, Emberson, J, Townend, Jn, Landray, Mj, Brenner, H, Müller, H, Schöttker, B, Hwang, S-J, Meigs, Jb, Uphadhay, A, Green, J, Kirchner, Hl, Perkins, R, Chang, Ar, Fluck, N, Prescott, Gj, Cirillo, M, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Iso, H, Sairenchi, T, Smith, Dh, Thorp, Ml, Johnson, E, Lee, Bj, Guallar, E, Chang, Sy, Cho, J, Shin, H, Chodick, G, Shalev, V, Birnbaum, Yc, Shainberg, B, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Levey, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Elley, Cr, Kenealy, T, Moyes, Sa, Collins, Jf, Drury, Pl, Ohkubo, T, Metoki, H, Nakayama, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Lhillege, H, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Heerspink, Hjl, Brenner, Be, de Zeeuw, D, Kimm, H, Mok, Y, Tangri, N, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Ärnlöv, J, Lannfelt, L, Larsson, A, Kovesdy, Cp, Kalantar-Zadeh, K, Bilo, Hj, Kleefstra, N, Groenier, Kh, Joosten, H, Ballew, Sh, Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
Gerontology, Male, CHRONIC KIDNEY-DISEASE, medicine.medical_specialty, Time Factors, 030232 urology & nephrology, Renal function, 030204 cardiovascular system & hematology, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Cause of Death, Epidemiology, Risk of mortality, medicine, EQUATION, Humans, Clinical Epidemiology, Renal Insufficiency, Chronic, Aged, Proportional Hazards Models, business.industry, Hazard ratio, STAGE RENAL-DISEASE, DEATH, General Medicine, Middle Aged, POPULATION COHORTS, Confidence interval, Increased risk, Nephrology, CARDIOVASCULAR-DISEASE, COLLABORATIVE METAANALYSIS, Female, business, HIGHER ALBUMINURIA, All cause mortality, Glomerular Filtration Rate
Abstract

A single determination of eGFR associates with subsequent mortality risk. Prior decline in eGFR indicates loss of kidney function, but the relationship to mortality risk is uncertain. We conducted an individual-level meta-analysis of the risk of mortality associated with antecedent eGFR slope, adjusting for established risk factors, including last eGFR, among 1.2 million subjects from 12 CKD and 22 other cohorts within the CKD Prognosis Consortium. Over a 3-year antecedent period, 12% of participants in the CKD cohorts and 11% in the other cohorts had an eGFR slope-5 ml/min per 1.73 m(2) per year, whereas 7% and 4% had a slope5 ml/min per 1.73 m(2) per year, respectively. Compared with a slope of 0 ml/min per 1.73 m(2) per year, a slope of -6 ml/min per 1.73 m(2) per year associated with adjusted hazard ratios for all-cause mortality of 1.25 (95% confidence interval [95% CI], 1.09 to 1.44) among CKD cohorts and 1.15 (95% CI, 1.01 to 1.31) among other cohorts during a follow-up of 3.2 years. A slope of +6 ml/min per 1.73 m(2) per year also associated with higher all-cause mortality risk, with adjusted hazard ratios of 1.58 (95% CI, 1.29 to 1.95) among CKD cohorts and 1.43 (95% CI, 1.11 to 1.84) among other cohorts. Results were similar for cardiovascular and noncardiovascular causes of death and stronger for longer antecedent periods (3 versus3 years). We conclude that prior decline or rise in eGFR associates with an increased risk of mortality, independent of current eGFR.

Published
2016

11. Common variation in the LMNA gene (encoding lamin A/C) and type 2 diabetes: association analyses in 9,518 subjects

Author

Owen, KR, Groves, CJ, Hanson, RL, Knowler, WC, Shuldiner, AR, Elbein, SC, Mitchell, BD, Froguel, P, Ng, MC, Chan, JC, Jia, W, Deloukas, P, Hitman, GA, Walker, M, Frayling, TM, Hattersley, AT, Zeggini, E, and McCarthy, MI

Abstract

Mutations in the LMNA gene (encoding lamin A/C) underlie familial partial lipodystrophy, a syndrome of monogenic insulin resistance and diabetes. LMNA maps to the well-replicated diabetes-linkage region on chromosome 1q, and there are reported associations between LMNA single nucleotide polymorphisms (SNPs) (particularly rs4641; H566H) and metabolic syndrome components. We examined the relationship between LMNA variation and type 2 diabetes (using six tag SNPs capturing >90% of common variation) in several large datasets. Analysis of 2,490 U.K. diabetic case and 2,556 control subjects revealed no significant associations at either genotype or haplotype level: the minor allele at rs4641 was no more frequent in case subjects (allelic odds ratio [OR] 1.07 [95% CI 0.98-1.17], P = 0.15). In 390 U.K. trios, family-based association analyses revealed nominally significant overtransmission of the major allele at rs12063564 (P = 0.01), which was not corroborated in other samples. Finally, genotypes for 2,817 additional subjects from the International 1q Consortium revealed no consistent case-control or family-based associations with LMNA variants. Across all our data, the OR for the rs4641 minor allele approached but did not attain significance (1.07 [0.99-1.15], P = 0.08). Our data do not therefore support a major effect of LMNA variation on diabetes risk. However, in a meta-analysis including other available data, there is evidence that rs4641 has a modest effect on diabetes susceptibility (1.10 [1.04-1.16], P = 0.001).

Published
2016
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12. Selecting SNPs informative for African, American Indian and European Ancestry: Application to the Family Investigation of Nephropathy and Diabetes (FIND)

Author

Williams, RC, Elston, RC, Kumar, P, Knowler, WC, Abboud, HE, Adler, S, Bowden, DW, Divers, J, Freedman, BI, Igo, RP, Ipp, E, Iyengar, SK, Kimmel, PL, Klag, MJ, Kohn, O, Langefeld, CD, Leehey, DJ, Nelson, RG, Nicholas, SB, Pahl, MV, Parekh, RS, Rotter, JI, Schelling, JR, Sedor, JR, Shah, VO, Smith, MW, Taylor, KD, Thameem, F, Thornley-Brown, D, Winkler, CA, Guo, X, Zager, P, Hanson, RL, FIND Research Group, S.K. Iyengar, Goddard, KAB, Olson, JM, Ialacci, S, Fondran, J, Horvath, A, Igo, R, Jun, G, Kramp, K, Molineros, J, Quade, SRE, Schelling, J, Pickens, A, Humbert, L, Getz-Fradley, L, Pahl, M, Seldin, MF, Snyder, S, Tayek, J, Hernandez, E, LaPage, J, Garcia, C, Gonzalez, J, Aguilar, M, Klag, M, Parekh, R, Kao, L, Meoni, L, Whitehead, T, Chester, J, Wolford, J, Jones, L, Juan, R, Lovelace, R, Luethe, C, Phillips, LM, Sewemaenewa, J, Sili, I, Waseta, B, Saad, MF, Chen, YDI, Rotter, J, Taylor, K, Budgett, M, Hariri, F, Shah, V, Scavini, M, Bobelu, A, Abboud, H, Arar, N, Duggirala, R, Kasinath, BS, and Stern, M

Subjects
Individual genetic ancestry, SNP, Diabetic nephropathy, Population structure
Abstract

© 2016 Williams et al. Background: The 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. Results: A 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. Conclusions: The 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.

Published
2016
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13. Lifestyle and metformin ameliorate insulin sensitivity independently of the genetic burden of established insulin resistance variants in diabetes prevention program participants

Author

Hivert, MF, Christophi, CA, Franks, PW, Jablonski, KA, Ehrmann, DA, Kahn, SE, Horton, ES, Pollin, TI, Mather, KJ, Perreault, L, Barrett-Connor, E, Knowler, WC, and Florez, JC

Subjects
endocrine system diseases, nutritional and metabolic diseases, humanities
Abstract

© 2016 by the American Diabetes Association.Large genome-wide association studies of glycemic traits have identified genetics variants that are associated with insulin resistance (IR) in the general population. It is unknown whether people with genetic enrichment for these IR variants respond differently to interventions that aim to improve insulin sensitivity. We built a genetic risk score (GRS) based on 17 established IR variants and effect sizes (weighted IR-GRS) in 2,713 participants of the Diabetes Prevention Program (DPP) with genetic consent. We tested associations between the weighted IR-GRS and insulin sensitivity index (ISI) at baseline in all participants, and with change in ISI over 1 year of follow-up in the DPP intervention (metformin and lifestyle) and control (placebo) arms. All models were adjusted for age, sex, ethnicity, and waist circumference at baseline (plus baseline ISI for 1-year ISI change models). A higher IR-GRS was associated with lower baseline ISI (β = 20.754 [SE = 0.229] log-ISI per unit, P = 0.001 in fully adjusted models). There was no differential effect of treatment for the association between the IR-GRS on the change in ISI; higher IR-GRS was associated with an attenuation in ISI improvement over 1 year (β = 20.520 [SE = 0.233], P = 0.03 in fully adjusted models; all treatment arms). Lifestyle intervention and metformin treatment improved the ISI, regardless of the genetic burden of IR variants.

Published
2016
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15. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis

Author

Mahmoodi, Bk, Matsushita, K., Woodward, M., Blankestijn, Pj, Cirillo, Massimo, Ohkubo, T., Rossing, P., Sarnak, Mj, Stengel, B., Yamagishi, K., Yamashita, K., Zhang, L., Coresh, J., PE de Jong, Wright, BC Astor for the Chronic Kidney Disease Prognosis C. o. n. s. o. r. t. i. u. m. Investigators/Collaborators: J., Appel, L., Greene, T., Astor, Bc, Chalmers, J., Macmahon, S., Arima, H., Yatsuya, H., Toyoshima, H., Tamakoshi, K., Sang, Y., Atkins, R. C., Polkinghorne, Kr, Chadban, S., Shankar, A., Klein, R., Bek, Klein, Lee, Ke, Wang, H., Wang, F., Zuo, L., Levin, A., Djurdjev, O., Tonelli, M., Sacks, Fm, Curhan, Gc, Shlipak, M., Peralta, C., Katz, R., Fried, L., Iso, H., Kitamura, A., Ohira, T., Jafar, Th, Islam, M., Hatcher, J., Poulter, N., Chaturvedi, N., Landray, M. J., Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D., Brenner, H., Muller, H., Schottker, B., Fox, Cs, Hwang, S. J., Meigs, Jb, Perkins, Rm, Fluck, N., Clark, Le, Prescott, Gj, Marks, A., Black, C., Hallan, S., Aasarod, K., Oien, Cm, Radtke, M., Irie, F., Sairenchi, T., Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S., Chen, S. C., Lee, Bj, Wetzels, Jf, AD van Zuilen, Sarnak, M., Levey, As, Menon, V., Kramer, Hj, IH de Boer, Kronenberg, F., Kollerits, B., Roderick, E. R. i. t. z. P., Nitsch, D., Fletcher, A., Bulpitt, C., Ishani, A., Neaton, Jd, Froissart, M., Metzger, M., Haymann, J. P., Houillier, P., Flamant, M., Metoki, H., Nakayama, M., Kikuya, M., Imai, Y., Iseki, K., Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H., Jassal, Sk, Barrett Connor, E., Bergstrom, J., HJ Lambers Heerspink, Brenner, Be, de Zeeuw, D., Warnock, Dg, Muntner, P., Judd, S., Mcclellan, W., Jee, Sh, Kimm, H., Jo, J., Mok, Y., Parving, H. H., Tangri, N., Naimark, D., Wen, C. P., Wen, S. F., Tsao, C. K., Tsai, M. K., Arnlov, J., Lannfelt, L., Larsson, A., Bilo, Hj, Joosten, H., Kleefstra, N., Groenier, Kh, Steering Committee: BC Astor, I. D. r. i. o. n., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M. W. o. o. d. w. a. r. d., Grams, M., Camarata, L., Hui, X., Seltzer, J., Winegrad, H., Mahmoodi, Bk, Matsushita, K, Woodward, M, Blankestijn, Pj, Cirillo, M, Ohkubo, T, Rossing, P, Sarnak, Mj, Stengel, B, Yamagishi, K, Yamashita, K, Zhang, L, Coresh, J, de Jong, Pe, Investigators/Collaborators: J Wright, BC Astor for the Chronic Kidney Disease Prognosis Consortium., Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Sang, Y, C Atkins, R, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Wang, H, Wang, F, Zuo, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, J Landray, M, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Muller, H, Schottker, B, Fox, C, Hwang, S-J, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Hallan, S, Aasarod, K, Oien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, S-C, Lee, Bj, Wetzels, Jf, van Zuilen, Ad, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer, Ih, Kronenberg, F, Kollerits, B, P Roderick, E Ritz., Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink, Hj, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Parving, H-H, Tangri, N, Naimark, D, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Arnlov, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Steering Committee: BC Astor, I Drion., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M Woodward., Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad., H

Subjects
Male, medicine.medical_specialty, hypertension, Blood Pressure, BLOOD-PRESSURE, GLOMERULAR-FILTRATION-RATE, Article, albuminuria, DIABETIC-NEPHROPATHY, End stage renal disease, CKD-PC Consortium, Risk Factors, Cause of Death, Internal medicine, REVERSE EPIDEMIOLOGY, eGFR, EQUATION, medicine, Humans, Intensive care medicine, Aged, Proportional Hazards Models, ALL-CAUSE MORTALITY, Renal disorder [IGMD 9], Aged, 80 and over, end-stage renal disease, business.industry, General Medicine, Middle Aged, medicine.disease, mortality, RISK POPULATION COHORTS, PREVALENCE, Chronic Disease, COLLABORATIVE METAANALYSIS, Kidney Failure, Chronic, Female, HIGHER ALBUMINURIA, business, Glomerular Filtration Rate, Kidney disease
Abstract

Item does not contain fulltext BACKGROUND: Hypertension is the most prevalent comorbidity in individuals with chronic kidney disease. However, whether the association of the kidney disease measures, estimated glomerular filtration rate (eGFR) and albuminuria, with mortality or end-stage renal disease (ESRD) differs by hypertensive status is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and ESRD associated with eGFR and albuminuria in individuals with and without hypertension. FINDINGS: We analysed data for 45 cohorts (25 general population, seven high-risk, and 13 chronic kidney disease) with 1,127,656 participants, 364,344 of whom had hypertension. Low eGFR and high albuminuria were associated with mortality irrespective of hypertensive status in the general population and high-risk cohorts. All-cause mortality risk was 1.1-1.2 times higher in individuals with hypertension than in those without hypertension at preserved eGFR. A steeper relative risk gradient in individuals without hypertension than in those with hypertension at eGFR range 45-75 mL/min per 1.73 m(2) led to much the same mortality risk at lower eGFR. With a reference eGFR of 95 mL/min per 1.73 m(2) in each group to explicitly assess interaction, adjusted HR for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) was 1.77 (95% CI 1.57-1.99) in individuals without hypertension versus 1.24 (1.11-1.39) in those with hypertension (p for overall interaction=0.0003). Similarly, for albumin-creatinine ratio of 300 mg/g (vs 5 mg/g), HR was 2.30 (1.98-2.68) in individuals without hypertension versus 2.08 (1.84-2.35) in those with hypertension (p for overall interaction=0.019). We recorded much the same results for cardiovascular mortality. The associations of eGFR and albuminuria with ESRD, however, did not differ by hypertensive status. Results for chronic kidney disease cohorts were similar to those for general and high-risk population cohorts. INTERPRETATION: Chronic kidney disease should be regarded as at least an equally relevant risk factor for mortality and ESRD in individuals without hypertension as it is in those with hypertension. FUNDING: US National Kidney Foundation.

Published
2012

22. Impact of weight loss on ankle-brachial index and interartery blood pressures

Author

Espeland, MA, Lewis, CE, Bahnson, J, Knowler, WC, Regensteiner, JG, Gaussoin, SA, Beavers, D, and Johnson, KC

Subjects
Male, INTER-ARM DIFFERENCES, Blood Pressure, Comorbidity, Endocrinology & Metabolism, Peripheral Arterial Disease, Behavior Therapy, Risk Factors, Weight Loss, MD Multidisciplinary, Humans, Ankle Brachial Index, Carotid Stenosis, Longitudinal Studies, Obesity, Life Style, POPULATION, Aged, Science & Technology, Nutrition & Dietetics, PERIPHERAL ARTERIAL-DISEASE, Incidence, Look AHEAD Research Group, VASCULAR-DISEASE, STIFFNESS, ASSOCIATION, ADULTS, Middle Aged, DIFFERENCE, PREVALENCE, Diabetes Mellitus, Type 2, Hypertension, RISK-FACTORS, Female, Life Sciences & Biomedicine
Abstract

Objective To assess whether weight loss improves markers of peripheral artery disease and vascular stenosis. Methods The Action for Health in Diabetes randomized clinical trial compared intensive lifestyle intervention (ILI) for weight loss to a control condition of diabetes support and education (DSE) in overweight or obese adults with type 2 diabetes. Annual ankle and brachial blood pressures over four years were used to compute ankle‐brachial indices (ABIs) and to assess interartery blood pressure differences in 5018 participants. Results ILI, compared to DSE, produced 7.8% (Year 1) to 3.6% (Year 4) greater weight losses. These did not affect prevalence of low (1.40) ABI (7.52% in DSE versus 7.59% in ILI: P = 0.90), but produced smaller mean (SE) maximum interartery systolic blood pressure differences among ankle sites [19.7 (0.2) mmHg for ILI versus 20.6 (0.2) mmHg for DSE (P < 0.001)] and between arms [5.8 (0.1) mmHg for ILI versus 6.1 (0.1) mmHg for DSE (P = 0.01)]. Conclusions Four years of intensive behavioral weight loss intervention did not significantly alter prevalence of abnormal ABI, however, it did reduce differences in systolic blood pressures among arterial sites.

Published
2013

23. Erratum: Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci (American Journal of Human Genetics (2012) 90 (410-425))

Author

Saxena, R, Elbers, CC, Guo, Y, Peter, I, Gaunt, TR, Mega, JL, Lanktree, MB, Tare, A, Castillo, BA, Li, YR, Johnson, T, Bruinenberg, M, Gilbert-Diamond, D, Rajagopalan, R, Voight, BF, Balasubramanyam, A, Barnard, J, Bauer, F, Baumert, J, Bhangale, T, Böhm, BO, Braund, PS, Burton, PR, Chandrupatla, HR, Clarke, R, Cooper-Dehoff, RM, Crook, ED, Davey-Smith, G, Day, IN, De Boer, A, De Groot, MCH, Drenos, F, Ferguson, J, Fox, CS, Furlong, CE, Gibson, Q, Gieger, C, Gilhuijs-Pederson, LA, Glessner, JT, Goel, A, Gong, Y, Grant, SFA, Grobbee, DE, Hastie, C, Humphries, SE, Kim, CE, Kivimaki, M, Kleber, M, Meisinger, C, Kumari, M, Langaee, TY, Lawlor, DA, Li, M, Lobmeyer, MT, Maitland-Van Der Zee, A-H, Meijs, MFL, Molony, CM, Morrow, DA, Murugesan, G, Musani, SK, Nelson, CP, Newhouse, SJ, O'Connell, JR, Padmanabhan, S, Palmen, J, Patel, SR, Pepine, CJ, Pettinger, M, Price, TS, Rafelt, S, Ranchalis, J, Rasheed, A, Rosenthal, E, Ruczinski, I, Shah, S, Shen, H, Silbernagel, G, Smith, EN, Spijkerman, AWM, Stanton, A, Steffes, MW, Thorand, B, Trip, M, Van Der Harst, P, Van Der A, DL, Van Iperen, EPA, Van Setten, J, Van Vliet-Ostaptchouk, JV, Verweij, N, Wolffenbuttel, BHR, Young, T, Hadi Zafarmand, M, Zmuda, JM, Boehnke, M, Altshuler, D, McCarthy, M, Linda Kao, WH, Pankow, JS, Cappola, TP, Sever, P, Poulter, N, Caulfield, M, Dominiczak, A, Shields, DC, Bhatt, DL, Zhang, L, Curtis, SP, Danesh, J, Casas, JP, Van Der Schouw, YT, Onland-Moret, NC, Doevendans, PA, Dorn II, GW, Farrall, M, Fitzgerald, GA, Robert Hegele, AH, Hingorani, AD, Hofker, MH, Huggins, GS, Illig, T, Jarvik, GP, Johnson, JA, Klungel, OH, Knowler, WC, Koenig, W, März, W, Meigs, JB, Melander, O, Munroe, PB, Mitchell, BD, Bielinski, SJ, Rader, DJ, Reilly, MP, Rich, SS, Rotter, JI, Saleheen, D, Samani, NJ, Schadt, EE, Shuldiner, AR, Silverstein, R, Kottke-Marchant, K, Talmud, PJ, Watkins, H, Asselbergs, FW, De Bakker, PIW, McCaffery, J, Wijmenga, C, Sabatine, MS, Wilson, JG, Reiner, A, Bowden, DW, Hakonarson, H, Siscovick, DS, and Keating, BJ

Published
2012

24. Assessing gene-treatment interactions at the FTO and INSIG2 loci on obesity-related traits in the Diabetes Prevention Program

Author

Franks, Paul W, Jablonski, KA, Delahanty, LM, McAteer, JB, Kahn, SE, Knowler, WC, Florez, JC, Franks, Paul W, Jablonski, KA, Delahanty, LM, McAteer, JB, Kahn, SE, Knowler, WC, and Florez, JC

Abstract

AIMS/HYPOTHESIS: The single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity associated gene (FTO) and the rs7566605 SNP located 10 kb upstream of the insulin-induced gene 2 gene (INSIG2) have been proposed as risk factors for common obesity. METHODS: We tested for genotype-treatment interactions on changes in obesity-related traits in the Diabetes Prevention Program (DPP). The DPP is a randomised controlled trial of 3,548 high-risk individuals from 27 participating centres throughout the USA who were originally randomised to receive metformin, troglitazone, intensive lifestyle modification or placebo to prevent the development of type 2 diabetes. Measures of adiposity from computed tomography were available in a subsample (n = 908). This report focuses on the baseline and 1 year results. RESULTS: The minor A allele at FTO rs9939609 was positively associated with baseline BMI (p = 0.003), but not with baseline adiposity or the change at 1 year in any anthropometric trait. For the INSIG2 rs7566605 genotype, the minor C allele was associated with more subcutaneous adiposity (second and third lumbar vertebrae [L2/3]) at baseline (p = 0.04). During follow-up, CC homozygotes lost more weight than G allele carriers (p = 0.009). In an additive model, we observed nominally significant gene-lifestyle interactions on weight change (p = 0.02) and subcutaneous (L2/3 [p = 0.01] and L4/5 [p = 0.03]) and visceral (L2/3 [p = 0.02]) adipose areas. No statistical evidence of association with physical activity energy expenditure or energy intake was observed for either genotype. CONCLUSIONS/INTERPRETATION: Within the DPP study population, common variants in FTO and INSIG2 are nominally associated with quantitative measures of obesity, directly and possibly by interacting with metformin or lifestyle intervention.

Published
2008
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28. The C allele of ATM rs11212617 does not associate with metformin response in the Diabetes Prevention Program.

Author

Florez JC, Jablonski KA, Taylor A, Mather K, Horton E, White NH, Barrett-Connor E, Knowler WC, Shuldiner AR, Pollin TI, Diabetes Prevention Program Research Group, Florez, Jose C, Jablonski, Kathleen A, Taylor, Andrew, Mather, Kieren, Horton, Edward, White, Neil H, Barrett-Connor, Elizabeth, Knowler, William C, and Shuldiner, Alan R

Abstract

Objective: The C allele at the rs11212617 polymorphism in the ataxia-telangiectasia-mutated (ATM) gene has been associated with greater clinical response to metformin in people with type 2 diabetes. We tested whether this variant modified the effect of metformin in the Diabetes Prevention Program (DPP), in which metformin reduced diabetes incidence by 31% in volunteers with impaired glucose tolerance.Research Design and Methods: We genotyped rs11212617 in 2,994 DPP participants and analyzed its effects on diabetes incidence and related traits.Results: Contrary to expectations, C carriers enjoyed no preventive advantage on metformin; their hazard ratio, compared with A carriers, was 1.17 ([95% CI 0.96-1.42], P = 0.13) under metformin. There were no significant differences by genotype in metformin's effects on insulin sensitivity, fasting glucose, glycated hemoglobin, or disposition index.Conclusions: The reported association of rs11212617 with metformin response was not confirmed for diabetes prevention or for effects on relevant physiologic parameters in the DPP. [ABSTRACT FROM AUTHOR]

Published
2012
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29. Parental longevity and diabetes risk in the Diabetes Prevention Program.

Author

Florez H, Ma Y, Crandall JP, Perreault L, Marcovina SM, Bray GA, Saudek CD, Barrett-Connor E, Knowler WC, Diabetes Prevention Program Research Group, Florez, Hermes, Ma, Yong, Crandall, Jill P, Perreault, Leigh, Marcovina, Santica M, Bray, George A, Saudek, Christopher D, Barrett-Connor, Elizabeth, and Knowler, William C

Abstract

Background: Longevity clusters in families, and parental longevity may be associated with lower risk of chronic diseases in their children. It is unknown if diabetes risk is associated with parental longevity.Methods: We evaluated participants in the Diabetes Prevention Program with a parental history questionnaire at study entry. We classified them into five groups: premature death (parental death at age < 50 years), parental longevity (living to at least 80 years), and three intermediate groups (alive by age 49 but dying at age 50-59, 60-69, or 70-79). Those with alive parents and younger than 80 years were excluded. We analyzed separately effects of paternal (n = 2,165) and maternal (n = 1,739) longevity on diabetes incidence and risk after an average follow-up of 3.2 years.Results: At baseline, more diabetes risk factors (parental history of diabetes, coronary heart disease, higher body mass index, homeostasis model assessment for insulin resistance, and corrected insulin response) were found in participants whose parents died prematurely. Diabetes incidence was 9.5 cases/100 person-years in the 229 whose fathers died prematurely. In the 618 with paternal longevity, the rate was 6.6 cases/100 person-years (hazard ratio [95% confidence interval] = 0.68 [0.49-0.94]). The rates were 10.7 cases/100 person-years (n = 156) and 7.3 cases/100 person-years (n = 699, hazard ratio = 0.67 [95% confidence interval 0.47-0.95]) for those with maternal premature death or longevity, respectively. Associations with demographic and diabetes risk factors had minimal influence on the reduced risk found in those with paternal (adjusted hazard ratio = 0.78, 95% confidence interval 0.52-1.16) and maternal (adjusted hazard ratio = 0.64, 95% confidence interval 0.41-1.01) longevity.Conclusion: Parental longevity is associated with lower diabetes incidence in adults at high risk of type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2011
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30. Effectiveness of lifestyle interventions for individuals with severe obesity and type 2 diabetes: results from the Look AHEAD trial.

Author

Unick JL, Beavers D, Jakicic JM, Kitabchi AE, Knowler WC, Wadden TA, Wing RR, Look AHEAD Research Group, Unick, Jessica L, Beavers, Daniel, Jakicic, John M, Kitabchi, Abbas E, Knowler, William C, Wadden, Thomas A, and Wing, Rena R

Abstract

Objective: Rates of severe obesity (BMI ≥40 kg/m(2)) are on the rise, and effective treatment options are needed. We examined the effect of an intensive lifestyle intervention (ILI) on weight loss, cardiovascular disease (CVD) risk, and program adherence in participants with type 2 diabetes who were severely obese compared with overweight (BMI 25 to <30 kg/m(2)), class I (BMI 30 to <35 kg/m(2)), and class II (BMI 35 to <40 kg/m(2)) obese participants.Research Design and Methods: Participants in the Action for Health in Diabetes (Look AHEAD) trial were randomly assigned to ILI or diabetes support and education (DSE). DSE participants received a less intense educational intervention, whereas ILI participants received an intensive behavioral treatment to increase physical activity (PA) and reduce caloric intake. This article focuses on the 2,503 ILI participants (age 58.6 ± 6.8 years).Results: At 1 year, severely obese participants in the ILI group lost -9.04 ± 7.6% of initial body weight, which was significantly greater (P < 0.05) than ILI participants who were overweight (-7.43 ± 5.6%) and comparable to class I (-8.72 ± 6.4%) and class II obese (-8.64 ± 7.4%) participants. All BMI groups had comparable improvements in fitness, PA, LDL cholesterol, triglycerides, blood pressure, fasting glucose, and HbA(1c) at 1 year. ILI treatment session attendance was excellent and did not differ among weight categories (severe obese 80% vs. others 83%; P = 0.43).Conclusions: Severely obese participants in the ILI group had similar adherence, percentage of weight loss, and improvement in CVD risk compared with less obese participants. Behavioral weight loss programs should be considered an effective option for this population. [ABSTRACT FROM AUTHOR]

Published
2011
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33. Predictive power of sequential measures of albuminuria for progression to ESRD or death in Pima Indians with type 2 diabetes.

Author

Pavkov ME, Knowler WC, Hanson RL, Bennett PH, Nelson RG, Pavkov, Meda E, Knowler, William C, Hanson, Robert L, Bennett, Peter H, and Nelson, Robert G

Abstract

Background: To determine whether historic albuminuria measurements provide additional predictive value for diabetic end-stage renal disease (ESRD) and natural mortality over the most recent measurement, ie, whether "regression" from high albuminuria has a different prognosis than stability at the lower level.Study Design: Observational longitudinal study.Setting& Participants: Pima Indians 15 years or older with type 2 diabetes and at least 2 consecutive measurements of urinary albumin-creatinine ratio (ACR) within 6 years.Predictors: Sequential measurements of urinary ACR.Outcomes& Measurements: Proportional hazards analyses were used to estimate the risk of ESRD and natural death associated with the first and second ACR measurement. The ability of these highly correlated variables to predict outcome was compared with receiver operating characteristic curves calculated by means of the generalized c statistic.Results: In 983 subjects, 136 developed ESRD and 180 died of natural causes during a maximum follow-up of 12.6 years. Each doubling in the second ACR was associated with a 1.71-fold greater incidence of ESRD (95% confidence interval, 1.54 to 1.89) and 1.16-fold greater natural mortality (95% confidence interval, 1.07 to 1.27) adjusted for age, sex, diabetes duration, and antihypertensive medication. The addition of the first ACR measurement to the model did not add to the predictive value for ESRD or mortality. In pairwise comparisons of c statistics, the second ACR was a significantly better predictor of ESRD than the first ACR.Limitations: The predictive value of ACR measurements is decreased to the extent that its precision is based on a single measure.Conclusion: The predictive power of the latest ACR for ESRD and natural mortality in patients with diabetes is not enhanced by knowledge of the preceding ACR. Therefore, ACR changes over time, ie, regression or progression, add minimal predictive value beyond the latest measurement in the series. [ABSTRACT FROM AUTHOR]

Published
2008
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34. TCF7L2 is not a major susceptibility gene for type 2 diabetes in Pima Indians: analysis of 3,501 individuals.

Author

Guo T, Hanson RL, Traurig M, Muller YL, Ma L, Mack J, Kobes S, Knowler WC, Bogardus C, and Baier LJ

Subjects
OBESITY complications, PROTEINS, OBESITY, REFERENCE values, GENETICS, TYPE 2 diabetes, DISEASE susceptibility, PIMA (North American people), BODY mass index, LONGITUDINAL method, DISEASE complications
Abstract

OBJECTIVE: The transcription factor 7-like 2 (TCF7L2) gene was initially reported to be associated with type 2 diabetes in Icelandic, Danish, and U.S. populations. We investigated whether TCF7L2 also has a role in type 2 diabetes susceptibility in Pima Indians. RESEARCH DESIGN AND METHODS: The six variants reported to be associated with type 2 diabetes in the Icelandic study were genotyped in a population-based sample of 3,501 Pima Indians (1,561 subjects had type 2 diabetes, and 1,940 did not have diabetes). In addition, the coding and promoter regions of TCF7L2 were sequenced in 24 Pima subjects. The one variant identified by sequencing, 35 additional database variants positioned in introns, and the six variants reported in the Icelandic study were genotyped in Pima families to determine the haplotype structure of TCF7L2 among Pima Indians. Fourteen representative variants were selected and genotyped in 3,501 Pima Indians. RESULTS: The six variants initially reported to be associated with type 2 diabetes were less common in Pima Indians compared with samples of European origin, and none were associated with type 2 diabetes. One representative variant, rs1225404, was nominally associated with type 2 diabetes in a general model (additive P = 0.03, dominant P = 0.005) but not in a within-family analysis (additive P = 0.2, dominant P = 0.07). However, several variants were associated with BMI; in particular, rs12255372 was associated in both general and within-family analyses (both P = 0.0007). Modest associations were also found with traits predictive for type 2 diabetes. CONCLUSIONS: Variation within TCF7L2 does not confer major risk for type 2 diabetes among the Pima Indian population. [ABSTRACT FROM AUTHOR]

Published
2007
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35. Genome-wide scans for diabetic nephropathy and albuminuria in multiethnic populations: the family investigation of nephropathy and diabetes (FIND)

Author

Iyengar SK, Abboud HE, Goddard KAB, Saad MF, Adler SG, Arar NH, Bowden DW, Duggirala R, Elston RC, Hanson RL, Ipp E, Kao WHL, Kimmel PL, Klag MJ, Knowler WC, Meoni LA, Nelson RG, Nicholas SB, Pahl MV, and Parekh RS

Abstract

The Family Investigation of Nephropathy and Diabetes (FIND) was initiated to map genes underlying susceptibility to diabetic nephropathy. A total of 11 centers participated under a single collection protocol to recruit large numbers of diabetic sibling pairs concordant and discordant for diabetic nephropathy. We report the findings from the first-phase genetic analyses in 1,227 participants from 378 pedigrees of European-American, African-American, Mexican-American, and American Indian descent recruited from eight centers. Model-free linkage analyses, using a dichotomous definition for diabetic nephropathy in 397 sibling pairs, as well as the quantitative trait urinary albumin-to-creatinine ratio (ACR), were performed using the Haseman-Elston linkage test on 404 microsatellite markers. The strongest evidence of linkage to the diabetic nephropathy trait was on chromosomes 7q21.3, 10p15.3, 14q23.1, and 18q22.3. In ACR (883 diabetic sibling pairs), the strongest linkage signals were on chromosomes 2q14.1, 7q21.1, and 15q26.3. These results confirm regions of linkage to diabetic nephropathy on chromosomes 7q, 10p, and 18q from prior reports, making it important that genes underlying these peaks be evaluated for their contribution to nephropathy susceptibility. Large family collections consisting of multiple members with diabetes and advanced nephropathy are likely to accelerate the identification of genes causing diabetic nephropathy, a life-threatening complication of diabetes. [ABSTRACT FROM AUTHOR]

Published
2007
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36. Identification of PVT1 as a candidate gene for end-stage renal disease in type 2 diabetes using a pooling-based genome-wide single nucleotide plymorphism association study.

Author

Hanson RL, Craig DW, Millis MP, Yeatts KA, Kobes S, Pearson JV, Lee AM, Knowler WC, Nelson RG, and Wolford JK

Abstract

To identify genetic variants contributing to end-stage renal disease (ESRD) in type 2 diabetes, we performed a genome-wide analysis of 115,352 single nucleotide polymorphisms (SNPs) in pools of 105 unrelated case subjects with ESRD and 102 unrelated control subjects who have had type 2 diabetes for >/=10 years without macroalbuminuria. Using a sliding window statistic of ranked SNPs, we identified a 200-kb region on 8q24 harboring three SNPs showing substantial differences in allelic frequency between case and control pools. These SNPs were genotyped in individuals comprising each pool, and strong evidence for association was found with rs2720709 (P = 0.000021; odds ratio 2.57 [95% CI 1.66-3.96]), which is located in the plasmacytoma variant translocation gene PVT1. We sequenced all exons, exon-intron boundaries, and the promoter of PVT1 and identified 47 variants, 11 of which represented nonredundant markers with minor allele frequency >/=0.05. We subsequently genotyped these 11 variants and an additional 87 SNPs identified through public databases in 319-kb flanking rs2720709 ( approximately 1 SNP/3.5 kb); 23 markers were associated with ESRD at P < 0.01. The strongest evidence for association was found for rs2648875 (P = 0.0000018; 2.97 [1.90-4.65]), which maps to intron 8 of PVT1. Together, these results suggest that PVT1 may contribute to ESRD susceptibility in diabetes. [ABSTRACT FROM AUTHOR]

Published
2007
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37. Common variation in the LMNA gene (encoding lamin A/C) and type 2 diabetes: association analyses in 9,518 subjects.

Author

Owen KR, Groves CJ, Hanson RL, Knowler WC, Shuldiner AR, Elbein SC, Mitchell BD, Froguel P, Ng MC, Chan JC, Jia W, Deloukas P, Hitman GA, Walker M, Frayling TM, Hattersley AT, Zeggini E, McCarthy MI, Owen, Katharine R, and Groves, Christopher J

Abstract

Mutations in the LMNA gene (encoding lamin A/C) underlie familial partial lipodystrophy, a syndrome of monogenic insulin resistance and diabetes. LMNA maps to the well-replicated diabetes-linkage region on chromosome 1q, and there are reported associations between LMNA single nucleotide polymorphisms (SNPs) (particularly rs4641; H566H) and metabolic syndrome components. We examined the relationship between LMNA variation and type 2 diabetes (using six tag SNPs capturing >90% of common variation) in several large datasets. Analysis of 2,490 U.K. diabetic case and 2,556 control subjects revealed no significant associations at either genotype or haplotype level: the minor allele at rs4641 was no more frequent in case subjects (allelic odds ratio [OR] 1.07 [95% CI 0.98-1.17], P = 0.15). In 390 U.K. trios, family-based association analyses revealed nominally significant overtransmission of the major allele at rs12063564 (P = 0.01), which was not corroborated in other samples. Finally, genotypes for 2,817 additional subjects from the International 1q Consortium revealed no consistent case-control or family-based associations with LMNA variants. Across all our data, the OR for the rs4641 minor allele approached but did not attain significance (1.07 [0.99-1.15], P = 0.08). Our data do not therefore support a major effect of LMNA variation on diabetes risk. However, in a meta-analysis including other available data, there is evidence that rs4641 has a modest effect on diabetes susceptibility (1.10 [1.04-1.16], P = 0.001). [ABSTRACT FROM AUTHOR]

Published
2007
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38. Homocysteine and vitamin B12 concentrations and mortality rates in type 2 diabetes.

Author

Looker HC, Fagot-Campagna A, Gunter EW, Pfeiffer CM, Sievers ML, Bennett PH, Nelson RG, Hanson RL, and Knowler WC

Abstract

OBJECTIVE: To assess the role of homocysteine as a risk factor for mortality in diabetic subjects. METHODS: Homocysteine, vitamin B(12), and folate concentrations were measured in stored sera of 396 diabetic Pima Indians aged > or = 40 years when examined between 1982 and 1985. Vital status was assessed through 2001. RESULTS AND CONCLUSIONS: Over a median follow-up of 15.7 years, there were 221 deaths-76 were due to cardiovascular disease (CVD), 36 to diabetes/nephropathy and 34 to infections. Homocysteine was positively associated with mortality from all causes (hazard rate ratio (HRR) for highest versus lowest tertile of homocysteine = 1.70, 95% confidence interval (CI) 1.18-2.46), from diabetes/nephropathy (HRR = 2.39, 95% CI 0.94-6.11) and from infectious diseases (HRR = 3.39, 95% CI 1.19-9.70), but not from CVD (HRR = 1.16, 95% CI 0.62-2.17) after adjustment for age, sex and diabetes duration. Homocysteine correlated with serum creatinine (r = 0.50), and the relationships with mortality rates were not significant after adjustment for creatinine. Vitamin B(12) was positively associated with all-cause mortality (HRR for 100 pg/mL difference adjusted for age, sex and diabetes duration = 1.15, 95% CI 1.08-1.22) and death from diabetes/nephropathy (HRR = 1.27, 95% CI 1.10-1.46). The association between homocysteine and mortality in type 2 diabetes is not causal, but is confounded by renal disease in Pima Indians. [ABSTRACT FROM AUTHOR]

Published
2007
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39. Albuminuria within the 'normal' range and risk of cardiovascular disease and death in American Indians: the Strong Heart Study.

Author

Xu J, Knowler WC, Devereux RB, Yeh J, Umans JG, Begum M, Fabsitz RR, and Lee ET

Abstract

BACKGROUND: 'Normal' albuminuria has been defined as urinary albumin-creatinine ratio (UACR) less than 30 mg/g (3.4 mg/mmol). Whether higher UACR within this range independently predicts cardiovascular disease (CVD) and CVD death is uncertain. METHODS: A total of 3,000 participants aged 45 to 74 years with a UACR less than 30 mg/g and free of CVD at the baseline examination of the Strong Heart Study (SHS) were evaluated. Survival time was calculated from the baseline examination to the first nonfatal CVD, fatal CVD, or December 31, 2002. RESULTS: During follow-up (average, 10.4 years), 383 incident nonfatal CVD and 145 fatal CVD cases were ascertained. After adjustment for conventional CVD risk factors, participants with a UACR in the third (UACR >or= 5.4 to <10.2 mg/g [>or=0.6 to <1.1 mg/mmol] in men, >or=7.6 to <12.9 mg/g [>or=0.9 to <1.4 mg/mmol] in women) and the fourth (UACR >or=10.2 to <30 mg/g in men, >or=12.9 to <30 mg/g in women) quartiles had 41% and 72% greater risks of all CVD events and 118% and 199% greater risks of CVD mortality than those in the lowest quartile (UACR < 2.7 mg/g [<0.3 mg/mmol] in men, <4.3 mg/g [<0.5 mg/mmol] in women), respectively. In subgroup analysis, these associations were more pronounced in persons with diabetes. CONCLUSION: In the SHS cohort of middle-aged to elderly American Indians, albuminuria levels less than the traditional cutoff value predict CVD. Our findings agree with a growing number of studies questioning the concept that UACR less than 30 mg/g is normal. Copyright © 2007 by the National Kidney Foundation, Inc. [ABSTRACT FROM AUTHOR]

Published
2007

40. Variants in the gene encoding aldose reductase (AKR1B1) and diabetic nephropathy in American Indians.

Author

Wolford JK, Yeatts KA, Eagle AR, Nelson RG, Knowler WC, and Hanson RL

Abstract

AIMS: The aldose reductase gene (AKR1B1) is a strong candidate for diabetic nephropathy, and the T allele at rs759853 and the Z-2 allele at an [AC]n microsatellite are associated with diabetic kidney disease in some populations. As AKR1B1 is located on 7q35, where we have previously reported linkage to diabetic nephropathy in Pima Indians, this study examined the association of AKR1B1 variants with diabetic nephropathy in this population. METHODS: AKR1B1 variants were identified by sequencing and genotyped using allelic discrimination and pyrosequencing. Genotype distributions were compared between 107 cases with diabetic end-stage renal disease and 108 control subjects with diabetes for > or = 10 years and no evidence of nephropathy, and between 141 individuals with nephropathy and 416 individuals without heavy proteinuria in a family study of 257 sibships. RESULTS: We identified 11 AKR1B1 single nucleotide polymorphisms (SNPs) and the [AC]n microsatellite polymorphism. Three SNPs were rare and two were in 100% genotypic concordance; thus, eight polymorphisms were genotyped. No variant was associated with diabetic kidney disease in the case-control or family-based study. For example, the T allele at rs759853 had an allele frequency of 0.165 in cases and 0.171 in control subjects (OR = 0.96, 95% CI, 0.57-1.59, P = 0.86); in the family study its frequency was 0.140 and 0.169 in affected and unaffected individuals, respectively (OR = 0.90, 95% CI, 0.53-1.54 P = 0.71). Corresponding values for the Z-2 allele at the [AC]n microsatellite were OR = 1.09 (95% CI 0.72-1.66, P = 0.67) and OR = 1.25 (95% CI 0.81-1.95, P = 0.31) in the case-control and family studies, respectively. CONCLUSIONS: Common AKR1B1 polymorphisms are unlikely to be major determinants of diabetic nephropathy in this population. [ABSTRACT FROM AUTHOR]

Published
2006
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41. Association of albuminuria with all-cause and cardiovascular disease mortality in diabetes: the Strong Heart Study.

Author

Xu J, Lee ET, Best LG, Begum M, Knowler WC, Fabsitz RR, and Howard BV

Abstract

Objectives-To estimate the relative risks of albuminuria with all-cause and cardiovascular disease (CVD) mortality in a large cohort of American Indians with diabetes. Methods-A total of 1,953 diabetic participants in the Strong Heart Study were evaluated based on albuminuria categories at baseline examination. The Cox proportional hazards model was used to examine associations. Results-Of the 1,953 participants, 605 (31%) and 410 (21%) had microalbuminuria and macroalbuminuria, respectively, at baseline examination. Microalbuminuria (HR=1.42, 95% CI 1.15-1.77 for all-cause, and HR=1.48, CI 1.01-2.17 for CVD), and macroalbuminuria (HR=3.39, CI 2.71-4.25 for all-cause, and HR=3.74, CI 2.56-5.47 for CVD) were significant predictors for all-cause and CVD mortality after adjustment for other CVD risk factors. Conclusions-Results from the present study suggest that albuminuria is a strong independent predictor of all-cause and CVD mortality in American Indians with diabetes. [ABSTRACT FROM AUTHOR]

Published
2005

42. Components of the "metabolic syndrome" and incidence of type 2 diabetes.

Author

Hanson RL, Imperatore G, Bennett PH, Knowler WC, Hanson, Robert L, Imperatore, Giuseppina, Bennett, Peter H, and Knowler, William C

Abstract

The combination of insulin resistance, dyslipidemia, hypertension, and obesity has been described as a "metabolic syndrome" that is a strong determinant of type 2 diabetes. Factor analysis was used to identify components of this syndrome in 1,918 Pima Indians. Prospective analyses were conducted to evaluate associations of identified factors with incidence of diabetes. Factor analysis identified 4 factors that accounted for 79% of the variance in the original 10 variables. Each of these factors reflected a proposed component of the metabolic syndrome: insulinemia, body size, blood pressure, and lipid metabolism. Among 890 originally nondiabetic participants with follow-up data, 144 developed diabetes in a median follow-up of 4.1 years. The insulinemia factor was strongly associated with diabetes incidence (incidence rate ratio [IRR] for a 1-SD difference in factor scores = 1.81, P < 0.01). The body size and lipids factors also significantly predicted diabetes (IRR 1.52 and 1.37, respectively, P < 0.01 for both), whereas the blood pressure factor did not (IRR 1.11, P = 0.20). Identification of four unique factors with different associations with incidence of diabetes suggests that the correlations among these variables reflect distinct metabolic processes, about which substantial information may be lost in the attempt to combine them into a single entity. [ABSTRACT FROM AUTHOR]

Published
2002
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43. Type 2 diabetes and low birth weight: the role of paternal inheritance in the association of low birth weight and diabetes.

Author

Lindsay RS, Dabelea D, Roumain J, Hanson RL, Bennett PH, Knowler WC, Lindsay, R S, Dabelea, D, Roumain, J, Hanson, R L, Bennett, P H, and Knowler, W C

Abstract

Lower birth weight is associated with an increased occurrence of type 2 diabetes in later life. Whether this relationship is explained by environmental or genetic factors is unknown. We have examined the potential for genetic influences by determining whether parental diabetes is associated with lower birth weight in 1,608 children of known birth weight and gestational age born between 1941 and 1993 in the Gila River Indian Community in Arizona. The previously described relationships of maternal diabetes to increased birth weight and offspring diabetes were observed. In contrast to this we have determined novel relationships between low birth weight and paternal diabetes. The offspring of diabetic fathers were, on average, 78 g lighter than the offspring of nondiabetic fathers. For fathers, lower birth weight in their offspring was associated with an increased risk of later diabetes, i.e., fathers of offspring in the lowest quintile of birth weight, who were not diabetic at the time of birth of their child, had a 1.8-fold increased risk of developing diabetes later in life (95% CI 1.2-2.7; P = 0.004). For children, lower birth weight predicted diabetes in the offspring if paternal but not maternal diabetes was present, but it was not associated with higher plasma glucose if neither parent had diabetes. We conclude that the risk of diabetes associated with low birth weight is strongly related to the development of paternal diabetes, suggesting a genetic link between lower birth weight and later diabetes. [ABSTRACT FROM AUTHOR]

Published
2000
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46. High incidence and prevalence of rheumatoid arthritis in Pima Indians

Author

DEL PUENTE, ANTONIO, Knowler WC, Pettitt DJ, Bennett PH, DEL PUENTE, Antonio, Knowler, Wc, Pettitt, Dj, and Bennett, Ph

Subjects
rheumatoid arthritis, Gerontology, Adult, Male, medicine.medical_specialty, Epidemiology, Cross-sectional study, Population, Arthritis, Arthritis, Rheumatoid, Cohort Studies, medicine, Humans, Longitudinal Studies, Risk factor, education, Aged, education.field_of_study, business.industry, Incidence (epidemiology), Arizona, Middle Aged, medicine.disease, Cross-Sectional Studies, Rheumatoid arthritis, Indians, North American, Female, business, Demography, Cohort study
Abstract

A longitudinal epidemiologic study has been conducted to estimate the incidence and prevalence of rheumatoid arthritis in an American Indian population, the Pima and Papago Indians of Arizona. Clinical, serologic, and radiologic data were collected during biennial examinations of subjects aged 20 years or more during the period 1967-1986. Rheumatoid arthritis was diagnosed by criteria for the active and the inactive disease. Age-adjusted to the 1980 US population at least 20 years of age, the prevalence of classical and definite rheumatoid arthritis in 1984 was 5.3% (3.23% in males and 6.95% in females), a rate appreciably higher than that reported in studies in Rochester, Minnesota, and in Hiroshima and Nagasaki, Japan. Among Pimas, during the study period, 70 incident cases of rheumatoid arthritis occurred. The age-adjusted incidence rate was 42.2 cases per 10,000 person-years (29.7 in males and 51.8 in females), 10.3 times as high as the age-adjusted rate in Rochester (4.1/10,000 person-years), and 5.7 times as high as in Japan (7.4/10,000 person-years). Rates generally increased with age. No secular trend was found. On the basis of both prevalence and incidence data, this study confirms that rheumatoid arthritis does not have uniform occurrence in different populations. This has to be taken into account in the search for the factors related to the differences in risk of disease.

Published
1989

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