Literature DB >> 18436617

Trends in diabetes, high cholesterol, and hypertension in chronic kidney disease among U.S. adults: 1988-1994 to 1999-2004.

Caroline S Fox1, Paul Muntner.   

Abstract

OBJECTIVE: The prevalence of chronic kidney disease (CKD) increased among U.S. adults from 1988-1994 to 1999-2004. We sought to explore the importance of trends in risk factors for CKD over time RESEARCH DESIGN AND METHODS: The prevalence of cigarette smoking, obesity, hypertension, high cholesterol, and diabetes among U.S. adults with stage 3 CKD (estimated glomerular filtration rate <60 ml/min per 1.73 m(2)) and albuminuria (urinary albumin-to-creatinine ratio >/=30 mg/g), separately, were determined for 1988-1994 and 1999-2004 using data from serial National Health and Nutrition Examination Surveys. The prevalence ratios (PRs) for stage 3 CKD and albuminuria by the presence of these risk factors were compared across survey periods.
RESULTS: The PR for CKD declined between 1988-1994 and 1999-2004 for obesity (PR 1.51 and 1.14 for 1988-1994 and 1999-2004, respectively; P for change = 0.010), hypertension (PR 2.60 and 1.70; P for change = 0.005), and high cholesterol (PR 1.58 and 1.20; P for change = 0.028). However, for diagnosed diabetes, the PR remained unchanged (1.64 and 1.62; P for change = 0.898). Similar results were observed for undiagnosed diabetes (PR of CKD 1.38 and 1.50; P for change = 0.373). The association of cigarette smoking was similar in each time period. Besides obesity, for which the association remained stable over time, similar patterns were observed for the PR of albuminuria.
CONCLUSIONS: In terms of CKD, improvements in hypertension and high cholesterol management have been offset by both diagnosed and undiagnosed diabetes. Further increases in CKD may occur if diabetes continues to increase.

Entities:  

Mesh:

Year:  2008        PMID: 18436617      PMCID: PMC2453673          DOI: 10.2337/dc07-2348

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


Chronic kidney disease (CKD) is a common condition, affecting a substantial proportion of adults in the U.S. and worldwide (1). A recent analysis documented a marked increase in CKD prevalence among U.S. adults over the past decade (2). Due to its impact on quality of life, cardiovascular disease (CVD) incidence, and mortality, CKD is an important public health challenge (3–5). Obesity, smoking, hypertension, high cholesterol, and diabetes are key risk factors for CKD (6–9). Awareness, treatment, and control of hypertension has improved over the past several decades (10,11). Significant reductions in mean cholesterol levels have occurred as well (12), likely due to dietary changes and increasing usage of cholesterol-lowering medications. However, the prevalence and incidence of diabetes continue to increase (13–16), fueled by marked increases in obesity (17). We hypothesized that CKD related to hypertension and high cholesterol has decreased over time, likely due to improvements in the management of these conditions. However, given an ongoing increase in the prevalence of diabetes without significant improvements in its treatment (18), we further hypothesized that CKD related to diabetes has increased. We tested these hypotheses by assessing trends in the association of cigarette smoking, obesity, hypertension, high cholesterol, and diabetes with CKD and albuminuria between 1988–1994 and 1999–2004 using data from the Third National Health and Nutrition Examination Survey (NHANES) III and NHANES 1999–2004.

RESEARCH DESIGN AND METHODS

Study sample

NHANES III and NHANES 1999–2004 are cross-sectional nationally representative surveys of the noninstitutionalized civilian population of the U.S. Briefly, each survey employs a multistage stratified probability sample based on selection of counties, blocks, households, and persons within households. Mexican-Americans, non-Hispanic blacks, and older adults were oversampled in order to improve the estimate precision for these groups. Each NHANES consisted of an in-home interview and medical evaluation and a blood sample collection in a mobile examination center. In NHANES III and NHANES 1999–2004, 18,825 and 15,332 participants, respectively, completed the medical evaluation and study interview. Exclusions for the current study included those without serum creatinine measurements, estimated glomerular filtration rate (GFR)< 30 ml/min per 1.73 m2, and women pregnant at the examination, resulting in 15,502 and 12,453 participants from NHANES III and NHANES 1999–2004, respectively, available for analysis of stage 3 CKD. For the analysis of albuminuria, individuals missing urinary albumin or creatinine measurements and pregnant or menstruating women were excluded, resulting in valid data from 15,216 and 12,778 participants from NHANES III and NHANES 1999–2004, respectively.

Covariate data

Of relevance to the current analysis, variables collected during the in-home interview were age, race/ethnicity, sex, cigarette smoking, a history of diabetes, and pharmacologic treatment for hypertension, high cholesterol, or diabetes. Participants who reported having smoked ≥100 cigarettes during their lifetime were classified as current or former smokers if they answered affirmatively or negatively, respectively, to the question “Do you now smoke cigarettes?” A fixed stadiometer was used to measure height; a Toledo digital scale was used to measure weight with participants clothed in underwear, a disposable gown, and foam slippers. BMI was calculated as weight in kilograms divided by the square of height in meters; obesity was defined as BMI ≥30 kg/m2. Three blood pressure measurements were obtained using a standard protocol (American Heart Association) during the evaluation. While three additional blood pressure measurements were taken during the NHANES III in-home interview, for comparability, the current analyses were limited to blood pressure measurements from the medical evaluation. Using the mean of all available blood pressure measurements, systolic and/or diastolic blood pressure ≥140 mmHg and/or ≥90 mmHg, respectively, or current use of blood pressure–lowering medication was used to define hypertension.

Laboratory measurements and exposure definitions

Blood samples were stored at −20°C. For lipid analyses, samples were shipped to the Lipoprotein Analytical Laboratory (Johns Hopkins University, Baltimore, MD). Total cholesterol was measured with the Hitachi 704 Analyzer; high cholesterol was defined as levels ≥240 mg/dl or concurrent pharmacologic lipid-lowering treatment. Glucose was measured on previously frozen plasma at the University of Missouri at Columbia. Self-report of a prior diagnosis of diabetes with current use of an oral hypoglycemic agent or insulin was used to define diagnosed diabetes. For participants without diagnosed diabetes who attended a morning NHANES study visit after fasting 8 h or longer (n = 7,329 and 5,572 for NHANES III and NHANES 1999–2004, respectively), undiagnosed diabetes was defined as plasma glucose ≥126 mg/dl.

Outcome definitions

Serum creatinine was measured using the modified kinetic method of Jaffe (Hitachi 917 analyzer). Serum creatinine concentrations were calibrated to the assays used for the development of the modification of diet in renal disease (MDRD) equation (19). GFR was estimated with the simplified MDRD equation. Individuals with an estimated GFR (eGFR) of 30–59 ml/min per 1.73 m2 were considered to have stage 3 CKD. Urine albumin and creatinine concentrations were measured in the same laboratory during both surveys. Urinary albumin was measured using a solid-phase fluorescence immunoassay; urinary creatinine was measured using modified kinetic method of Jaffe (Astra Analyzer; Beckman Coulter Synchron). Albuminuria was defined as a urinary albumin–to–urinary creatinine ratio ≥30 mg/g. The protocols for NHANES III and NHANES 1999–2004 were approved by the National Center for Health Statistics of the Centers for Disease Control and Prevention Institutional Review Board.

Statistical methods

Characteristics of the populations with and without stage 3 CKD and with and without albuminuria were calculated for each time period. Characteristics included age, race/ethnicity, sex, mean levels of systolic and diastolic blood pressure, BMI, total cholesterol, glycated hemoglobin, use of blood pressure–and cholesterol-lowering medications, and prevalence of cigarette smoking, obesity, hypertension, high cholesterol, and diagnosed and undiagnosed diabetes. The statistical significance of differences in the means and prevalence estimates across the two surveys was determined using the Wald χ2 test. Test statistics were calculated as the difference in prevalence estimates divided by the standard error of the difference, calculated as the square root of the sum of each estimate's variance. The prevalence ratios (PRs) of stage 3 CKD and albuminuria associated with cigarette smoking, obesity, hypertension, high cholesterol, and diagnosed and undiagnosed diabetes were estimated for each time period, separately, using log-binomial regression models including adjustment for age, race, sex, hypertension, and self-reported diabetes. The statistical significance of changes in the PRs over time was calculated using two sample t tests (i.e., the difference in the β-coefficients from the regression models divided by the square root of the sum of their variance). Sample weights that account for the complex survey design of NHANES, including unequal probabilities of selection, over-sampling, and nonresponse, were applied for all analyses using SUDAAN (Version 9.1; Research Triangle Institute, Research Triangle Park, NC). Standard errors were estimated using the Taylor series linearization method.

RESULTS

Demographic and risk factors among individuals with and without stage 3 CKD

Demographic characteristics, risk factor levels, and the prevalence of risk factors among individuals with and without stage 3 CKD in the two time periods are shown in Table 1. Among individuals with stage 3 CKD, the prevalence of cigarette smoking declined and obesity, hypertension, and high cholesterol remained stable. However, the prevalence of diagnosed diabetes increased (13.0 and 16.8% for NHANES III and NHANES 1999–2004, respectively), although this did not reach statistical significance (P = 0.093). Among individuals without CKD, the prevalence of obesity, hypertension, high cholesterol, and diagnosed diabetes increased, whereas the prevalence of undiagnosed diabetes was stable.
Table 1—

CVD factors among NHANES III and NHANES 1999–2004 participants 20 years of age and older with and without stage 3 CKD

Stage 3 CKD
No stage 3 CKD
NHANES IIINHANES 1999–2004Age-adjusted P for time-period differenceNHANES IIINHANES 1999–2004Age-adjusted P for time-period difference
n88299413,49911,459
Mean age (years)71.5 (0.8)70.7 (0.6)0.42444.0 (0.4)45.0 (0.3)0.050
Male sex36.6 (3.0)36.1 (1.4)0.83949.1 (0.4)49.9 (0.4)0.552
Black race7.0 (0.8)6.7 (0.9)0.79210.4 (0.6)10.6 (1.0)0.878
Mean SBP (mmHg)140.8 (1.1)138.9 (0.9)0.303120.2 (0.4)122.8 (0.4)0.001
Mean DBP (mmHg)72.9 (0.6)68.3 (0.6)<0.00173.2 (0.3)72.7 (0.2)<0.001
On anti-HT medications*71.0 (2.5)79.0 (2.2)0.01650.4 (1.2)60.0 (1.6)<0.001
Mean BMI (kg/m2)27.6 (0.2)28.7 (0.3)0.01326.5 (0.1)28.0 (0.1)<0.001
Mean total cholesterol (mg/dl)232.1 (3.0)206.8 (1.8)<0.001203.1 (0.8)202.2 (0.7)<0.001
On cholesterol-lowering medication22.9 (3.9)61.8 (2.5)<0.00113.5 (1.0)38.3 (1.4)<0.001
Glycated hemoglobin (%)6.03 (0.07)5.83 (0.04)0.0135.35 (0.02)5.46 (0.02)0.405
Cigarette smokers12.4 (1.8)8.1 (1.5)0.03329.1 (0.8)21.6 (0.7)<0.001
Obese31.6 (2.2)32.2 (1.6)0.75522.1 (0.7)29.8 (0.8)<0.001
Hypertension72.7 (2.0)70.5 (1.8)0.62221.6 (0.8)27.2 (0.8)<0.001
High cholesterol46.8 (2.6)44.4 (2.0)0.32620.5 (0.6)24.4 (0.6)<0.001
Diabetes
    Diagnosed13.0 (1.3)16.8 (1.8)0.0933.3 (0.2)5.0 (0.3)0.039
    Undiagnosed10.6 (2.1)10.3 (1.7)0.5833.2 (0.3)3.6 (0.3)0.882

Data are n (%) unless otherwise indicated.

Among participants with a diagnosis of hypertension;

among participants with a diagnosis of high cholesterol. All P values (except age) for comparing mean levels and prevalence between NHANES III and NHANES 1999–2004 are age adjusted. DBP, diastolic blood pressure; HT, hypertensive; SBP, systolic blood pressure.

The PR for CKD associated with cigarette smoking was similar in both time periods, while the PR for CKD associated with obesity, hypertension, and high cholesterol was significantly lower in 1999–2004 compared with 1988–1994 (Fig. 1). For example, the PR for CKD associated with hypertension was 2.60 (95% CI 2.00–3.38) in NHANES III and decreased to 1.70 (1.43–2.02) in NHANES 1999–2004 (P for change = 0.005). However, for CKD associated with diagnosed diabetes, the PR remained unchanged (1.64 in NHANES III and 1.62 in NHANES 1999–2004; P for change = 0.898). Similar results were observed for undiagnosed diabetes: the PR for CKD was 1.38 and 1.50 in NHANES III and NHANES 1999–2004, respectively; P for change = 0.373).
Figure 1—

PRs of CKD associated with selected risk factors in 1988–1994 (NHANES III) and in 1999–2004 (NHANES 1999–2004). Adjusted for age, race, sex, hypertension, and self-reported diabetes (except hypertension, which is adjusted for age, race, sex, and diabetes, and diabetes, which is adjusted for age, race, sex, and hypertension). P represents changes in the PRs over time.

Risk factors among individuals with and without albuminuria

Among individuals with albuminuria, the prevalence of cigarette smoking decreased between 1988–1994 and 1999–2004. The prevalence of hypertension, high cholesterol, and undiagnosed diabetes remained stable, whereas the prevalence of obesity and diagnosed diabetes increased (Table 2). The PRs for albuminuria associated with cigarette smoking and obesity was similar for 1988–1994 and 1999–2004 (Fig. 2). However, the PRs for albuminuria associated with hypertension and high cholesterol decreased over the time period under study (P = 0.024 and 0.020, respectively). The PR for albuminuria associated with diagnosed diabetes decreased from 3.28 to 2.69 (P = 0.079), whereas the PR for albuminuria associated with undiagnosed diabetes increased nonsignificantly P = 0.594).
Table 2—

CVD risk factors among NHANES III and NHANES 1999–2004 participants 20 years of age and older with and without albuminuria

Albuminuria
No albuminuria
NHANES IIINHANES 1999–2004Age-adjusted P for time-period differenceNHANES IIINHANES 1999–2004Age-adjusted P for time-period difference
n1,8101,71113,40611,067
Mean age (years)57.3 (0.9)56.3 (0.7)0.38044.2 (0.5)45.6 (0.3)0.016
Male sex43.6 (2.3)47.9 (1.3)0.05351.2 (0.4)50.3 (0.4)0.778
Black race15.8 (1.2)14.3 (1.6)0.410.4 (0.6)10.4 (1.0)1.00
Mean SBP (mmHg)137.9 (1.1)138.2 (0.8)0.346120.0 (0.4)122.6 (0.4)0.021
Mean DBP (mmHg)77.0 (0.5)74.2 (0.6)<0.00173.1 (0.3)72.4 (0.2)<0.001
On anti-HT medications60.0 (2.2)66.8 (2.0)0.00551.5 (1.3)61.4 (1.5)<0.001
Mean BMI (kg/m2)28.0 (0.3)29.3 (0.4)<0.00126.5 (0.1)27.9 (0.1)<0.001
Mean total cholesterol (mg/dl)220.3 (1.7)206.3 (2.1)<0.001203.4 (0.9)202.4 (0.6)<0.001
On cholesterol lowering medications18.0 (2.8)51.8 (2.8)<0.00111.9 (1.0)39.6 (1.6)<0.001
Glycated hemoglobin (%)6.24 (0.08)6.16 (0.05)0.2675.31 (0.02)5.41 (0.01)1.00
Cigarette smokers27.0 (1.8)20.5 (1.4)0.00228.8 (0.9)20.7 (0.7)<0.001
Obese32.2 (1.7)39.3 (2.2)0.00122.0 (0.6)29.0 (0.7)<0.001
Hypertension57.6 (2.3)57.4 (1.8)0.49621.2 (0.8)27.4 (0.8)<0.001
High cholesterol37.3 (1.9)33.6 (1.7)0.65823.5 (0.7)25.1 (0.6)0.044
Diabetes
    Diagnosed18.0 (1.3)21.6 (1.1)0.012.4 (0.2)4.3 (0.2)0.014
    Undiagnosed11.6 (1.9)14.1 (2.3)0.8223.0 (0.3)2.9 (0.3)0.861

Data are n (%) unless otherwise indicated. All P values (except age) for comparing mean levels and prevalence between NHANES III and NHANES 1999–2004 are age adjusted. DBP, diastolic blood pressure; HT, hypertensive; SBP, systolic blood pressure.

Figure 2—

PRs of albuminuria associated with selected risk factors in 1988–1994 (NHANES III) and in 1999–2004 (NHANES 1999–2004). Adjusted for age, race, sex, hypertension, and self-reported diabetes (except hypertension, which is adjusted for age, race, sex, and diabetes, and diabetes, which is adjusted for age, race, sex, and hypertension). P represents changes in the PRs over time.

Self-reported diabetes

In a secondary analysis, diagnosed diabetes was redefined to include participants who self-reported diabetes regardless of whether they were on medication. Using this definition, the prevalence of diabetes increased between 1988–1994 and 1999–2004 from 16.0 to 19.1% among those with CKD and from 4.9 to 6.2% among adults without CKD. Also, the prevalence of diabetes increased from 21.4 to 24.1% and from 3.9 to 5.3% among adults with and without albuminuria, respectively. Similar to the main results, the PRs of CKD and albuminuria associated with self-reported diabetes did not change significantly over time (each P > 0.30; data not shown).

CONCLUSIONS

Principal findings

The current study suggests that the association of obesity, hypertension, and high cholesterol with CKD has declined over time. Conversely, we observed no change in the association between diabetes and CKD. With the exception of obesity, for which the association with albuminuria did not change over time, similar trend results were observed for albuminuria. In the present study, we demonstrate significant declines in the PRs for CKD associated with obesity, hypertension, and high cholesterol, suggesting that improvements have been made in terms of risk factor management. However, we observed no change in the PR of CKD due to diabetes over time. These findings suggest that similar improvements for diabetes management have not occurred. The association between obesity and CKD declined over the time period under study. National trends data have demonstrated improvements in blood pressure and lipid values across categories of BMI over time (20). Therefore, despite increasing rates of obesity, improved risk factor management may partially account for the present findings.

In the context of the current literature

Diabetes is a critical risk factor for CKD and albuminuria (6,21,22) and accounts for nearly half of all incident cases of end-stage renal disease in the U.S. (8). Numerous studies have shown that the prevalence and incidence of diabetes continue to increase (13–16). The increase in number of U.S. adults with diabetes has lead to an increase in the attributable risk for diabetes as a CVD risk factor relative to other traditional risk factors (23). Rates of treatment and control of CVD risk factors among people with diabetes remains poor (18). Although U.S. vital statistics document a marked decline in cardiovascular mortality over the past several decades, recent data suggest that individuals with diabetes have not experienced the same mortality reductions (24). We extend these findings to relations between diabetes and CKD and show that the PR for CKD did not decline over the past decade. In contrast, results for hypertension and high cholesterol are more encouraging. While hypertension has increased among U.S. adults over the past decade (11), rates of hypertension treatment and control have also increased. The improvement in overall management of hypertension, despite its increasing prevalence, is reflected in the reduced PR for hypertension as a CKD risk factor. Rates of high cholesterol have decreased over time (12). Dietary improvements are likely partially responsible for these trends as well. Similar to the results for hypertension, our results indicate that an added benefit of these interventions may be the reduced risk of CKD and albuminuria associated with high cholesterol.

Strengths and limitations

Strengths of the current study include the well-characterized NHANES datasets, large sample size, and nationally representative data. We were able to examine CKD as defined by reduced eGFR as well as albuminuria, a well-established risk factor for CKD (25,26). Further, albuminuria identifies different subsets of individuals at risk for CVD and all-cause mortality as compared with CKD alone (27). Limitations include the use of the MDRD equation to estimate GFR instead of a direct measurement (28), which would not be feasible in a large population-based study. Further, the MDRD equation underestimates eGFR in healthy individuals (29); how this impacts the dichotomous classification of CKD is uncertain. We used a study design that incorporated serial cross-sectional studies and therefore cannot infer causality between risk factors and CKD. However, we believe that this study design is the most powerful for determining overall trends in disease burden. Our sample was limited to individuals with stage 3 CKD due to small numbers of individuals with more severe CKD. Measures of albuminuria were based on a spot-urine collection. However, the correlation between 24-h collections and spot urine is acceptable (30). We relied on fasting plasma glucose and not an oral glucose tolerance test to define diabetes. Therefore, we may have underestimated the prevalence of undiagnosed diabetes in our sample. However, it is unlikely that this occurred differentially between NHANES III and NHANES 1999–2004. Therefore, this is unlikely to account for the observed findings.

Implications

Increases in obesity have lead to rises in the prevalence of diabetes. As diabetes continues to increase, the prevalence and incidence of CKD may continue to increase as well. Currently, individuals with diabetes are suboptimally managed with respect to CVD risk factors and overall glucose management (18). Less than half of individuals with CKD in the Framingham Heart Study had optimal A1C levels (31). Further, among individuals with CKD, diabetes, hypertension, and dyslipidemia, less than 10% of participants had optimal management of all of their risk factors. Improvement in CVD risk factor management, particularly diabetes, will be necessary to prevent further increases in CKD prevalence. Whether interventions focusing on weight loss and cholesterol reduction will reduce the risk of CKD require further study. In conclusion, improvements in hypertension and high cholesterol management have been offset by both diagnosed and undiagnosed diabetes. Further increases in CKD may occur if diabetes continues to increase.
  29 in total

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4.  Kidney function as a predictor of noncardiovascular mortality.

Authors:  Linda F Fried; Ronit Katz; Mark J Sarnak; Michael G Shlipak; Paulo H M Chaves; Nancy Swords Jenny; Catherine Stehman-Breen; Dan Gillen; Anthony J Bleyer; Calvin Hirsch; David Siscovick; Anne B Newman
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9.  Cardiovascular disease risk factors in chronic kidney disease: overall burden and rates of treatment and control.

Authors:  Nisha I Parikh; Shih-Jen Hwang; Martin G Larson; James B Meigs; Daniel Levy; Caroline S Fox
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10.  Prevalence, awareness, treatment, and control of hypertension among United States adults 1999-2004.

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Journal:  Nat Genet       Date:  2010-04-11       Impact factor: 38.330

8.  Genetic association for renal traits among participants of African ancestry reveals new loci for renal function.

Authors:  Ching-Ti Liu; Maija K Garnaas; Adrienne Tin; Anna Kottgen; Nora Franceschini; Carmen A Peralta; Ian H de Boer; Xiaoning Lu; Elizabeth Atkinson; Jingzhong Ding; Michael Nalls; Daniel Shriner; Josef Coresh; Abdullah Kutlar; Kirsten Bibbins-Domingo; David Siscovick; Ermeg Akylbekova; Sharon Wyatt; Brad Astor; Josef Mychaleckjy; Man Li; Muredach P Reilly; Raymond R Townsend; Adebowale Adeyemo; Alan B Zonderman; Mariza de Andrade; Stephen T Turner; Thomas H Mosley; Tamara B Harris; Charles N Rotimi; Yongmei Liu; Sharon L R Kardia; Michele K Evans; Michael G Shlipak; Holly Kramer; Michael F Flessner; Albert W Dreisbach; Wolfram Goessling; L Adrienne Cupples; W Linda Kao; Caroline S Fox
Journal:  PLoS Genet       Date:  2011-09-08       Impact factor: 5.917

9.  Association of eGFR-Related Loci Identified by GWAS with Incident CKD and ESRD.

Authors:  Carsten A Böger; Mathias Gorski; Man Li; Michael M Hoffmann; Chunmei Huang; Qiong Yang; Alexander Teumer; Vera Krane; Conall M O'Seaghdha; Zoltán Kutalik; H-Erich Wichmann; Thomas Haak; Eva Boes; Stefan Coassin; Josef Coresh; Barbara Kollerits; Margot Haun; Bernhard Paulweber; Anna Köttgen; Guo Li; Michael G Shlipak; Neil Powe; Shih-Jen Hwang; Abbas Dehghan; Fernando Rivadeneira; André Uitterlinden; Albert Hofman; Jacques S Beckmann; Bernhard K Krämer; Jacqueline Witteman; Murielle Bochud; David Siscovick; Rainer Rettig; Florian Kronenberg; Christoph Wanner; Ravi I Thadhani; Iris M Heid; Caroline S Fox; W H Kao
Journal:  PLoS Genet       Date:  2011-09-29       Impact factor: 5.917

10.  Common variants in Mendelian kidney disease genes and their association with renal function.

Authors:  Afshin Parsa; Christian Fuchsberger; Anna Köttgen; Conall M O'Seaghdha; Cristian Pattaro; Mariza de Andrade; Daniel I Chasman; Alexander Teumer; Karlhans Endlich; Matthias Olden; Ming-Huei Chen; Adrienne Tin; Young J Kim; Daniel Taliun; Man Li; Mary Feitosa; Mathias Gorski; Qiong Yang; Claudia Hundertmark; Meredith C Foster; Nicole Glazer; Aaron Isaacs; Madhumathi Rao; Albert V Smith; Jeffrey R O'Connell; Maksim Struchalin; Toshiko Tanaka; Guo Li; Shih-Jen Hwang; Elizabeth J Atkinson; Kurt Lohman; Marilyn C Cornelis; Asa Johansson; Anke Tönjes; Abbas Dehghan; Vincent Couraki; Elizabeth G Holliday; Rossella Sorice; Zoltan Kutalik; Terho Lehtimäki; Tõnu Esko; Harshal Deshmukh; Sheila Ulivi; Audrey Y Chu; Federico Murgia; Stella Trompet; Medea Imboden; Barbara Kollerits; Giorgio Pistis; Tamara B Harris; Lenore J Launer; Thor Aspelund; Gudny Eiriksdottir; Braxton D Mitchell; Eric Boerwinkle; Helena Schmidt; Edith Hofer; Frank Hu; Ayse Demirkan; Ben A Oostra; Stephen T Turner; Jingzhong Ding; Jeanette S Andrews; Barry I Freedman; Franco Giulianini; Wolfgang Koenig; Thomas Illig; Angela Döring; H-Erich Wichmann; Lina Zgaga; Tatijana Zemunik; Mladen Boban; Cosetta Minelli; Heather E Wheeler; Wilmar Igl; Ghazal Zaboli; Sarah H Wild; Alan F Wright; Harry Campbell; David Ellinghaus; Ute Nöthlings; Gunnar Jacobs; Reiner Biffar; Florian Ernst; Georg Homuth; Heyo K Kroemer; Matthias Nauck; Sylvia Stracke; Uwe Völker; Henry Völzke; Peter Kovacs; Michael Stumvoll; Reedik Mägi; Albert Hofman; Andre G Uitterlinden; Fernando Rivadeneira; Yurii S Aulchenko; Ozren Polasek; Nick Hastie; Veronique Vitart; Catherine Helmer; Jie Jin Wang; Bénédicte Stengel; Daniela Ruggiero; Sven Bergmann; Mika Kähönen; Jorma Viikari; Tiit Nikopensius; Michael Province; Helen Colhoun; Alex Doney; Antonietta Robino; Bernhard K Krämer; Laura Portas; Ian Ford; Brendan M Buckley; Martin Adam; Gian-Andri Thun; Bernhard Paulweber; Margot Haun; Cinzia Sala; Paul Mitchell; Marina Ciullo; Peter Vollenweider; Olli Raitakari; Andres Metspalu; Colin Palmer; Paolo Gasparini; Mario Pirastu; J Wouter Jukema; Nicole M Probst-Hensch; Florian Kronenberg; Daniela Toniolo; Vilmundur Gudnason; Alan R Shuldiner; Josef Coresh; Reinhold Schmidt; Luigi Ferrucci; Cornelia M van Duijn; Ingrid Borecki; Sharon L R Kardia; Yongmei Liu; Gary C Curhan; Igor Rudan; Ulf Gyllensten; James F Wilson; Andre Franke; Peter P Pramstaller; Rainer Rettig; Inga Prokopenko; Jacqueline Witteman; Caroline Hayward; Paul M Ridker; Murielle Bochud; Iris M Heid; David S Siscovick; Caroline S Fox; W Linda Kao; Carsten A Böger
Journal:  J Am Soc Nephrol       Date:  2013-09-12       Impact factor: 10.121

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