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51. RISK FACTORS AND SECONDARY PREVENTION IN WOMEN WITH HEART DISEASE

Author: E, Vittinghoff, primary, G, Shlipak M, additional, and D, Varosy P, additional
Published: 2003
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52. Fetuin-A is not associated with mortality in chronic kidney disease.

Author: Ix, J. H., Shlipak, M. G., Sarnak, M. J., Beck, G. J., Greene, T., Wang, X., Kusek, J. W., Collins, A. J., Levey, A. S., and Menon, V.
Subjects: *KIDNEY diseases, *CHRONIC kidney failure, *CHRONIC diseases, *DIET in disease, *LABORATORY rats
Abstract: Fetuin-A is a serum protein that inhibits vascular calcification such that lower levels are associated with a higher prevalence of vascular calcification and mortality risk among end-stage renal disease populations. We analyzed data of 822 persons in the Modification of Diet in Renal Disease study, a randomized, controlled trial of persons with predominantly non-diabetic stage 3–4 chronic kidney disease (CKD). Serum fetuin-A levels were measured in baseline serum. Survival status and cause of death were determined by the National Death Index. Cox proportional hazard models evaluated the association of fetuin-A levels with all-cause and cardiovascular mortality. Glomerular filtration ranged from 13 to 55 ml per min per 1.73 m2. During a median follow-up of 9.5 years, 25% of persons died from any cause and 12% died from a cardiovascular cause. Compared to the lowest tertile, no association was found between the highest fetuin-A tertile and all-cause or cardiovascular mortality. Similarly, no association was found between fetuin-A as a continuous variable and all-cause or cardiovascular mortality. Our study shows that serum fetuin-A levels are not related to all-cause or cardiovascular mortality among persons with predominantly non-diabetic stage 3 or 4 CKD.Kidney International (2007) 72, 1394–1399; doi:10.1038/sj.ki.5002549; published online 19 September 2007 [ABSTRACT FROM AUTHOR]
Published: 2007
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53. Association of cystatin C with poor exercise capacity and heart rate recovery: data from the heart and soul study.

Author: McManus D, Shlipak M, Ix JH, Ali S, Whooley MA, McManus, David, Shlipak, Michael, Ix, Joachim H, Ali, Sadia, and Whooley, Mary A
Abstract: Background: Cystatin C, an alternative serum measure of kidney function, is a stronger predictor of cardiovascular events than creatinine or estimated glomerular filtration rate (eGFR). We hypothesized that serum cystatin C concentration would have a stronger more linear association with cardiovascular functional status than creatinine-based measures in outpatients with established coronary heart disease (CHD).Methods: We measured serum cystatin C, serum creatinine, and eGFR in 906 outpatients with established CHD. We examined the association of these 3 measures of kidney function with treadmill exercise capacity (metabolic equivalent tasks achieved) and heart rate recovery (HRR) between peak and 1 minute after exercise by using linear and logistic regression.Results: Higher cystatin C concentrations were associated linearly with worse treadmill exercise capacity and HRR. The proportion of participants with poor exercise capacity (metabolic equivalent tasks achieved < 5) was 45% (99 of 222 participants) among those with cystatin C levels in the highest quartile (>1.30 mg/L) compared with 12% (29 of 241 participants) among those with cystatin C levels in the lowest quartile (<0.92 mg/L; adjusted odds ratio, 3.2; 95% confidence interval, 1.6 to 6.5; P = 0.001). The proportion of participants with poor HRR (<16 beats/min) was 42% (92 of 214 participants) among those with cystatin C levels in the highest quartile compared with 16% (37 of 238 participants) among those with cystatin C levels in the lowest quartile (adjusted odds ratio, 2.2; 95% confidence interval, 1.2 to 4.0; P = 0.01). The lowest quartile of eGFR (<61.8 mL/min [<1.03 mL/s]) was associated with decreased exercise capacity and prolonged HRR, but no difference was observed across the upper 3 quartiles of eGFR.Conclusion: In patients with established CHD, cystatin C concentrations are associated linearly with worse exercise capacity and HRR. Cystatin C detects an association of impaired kidney function with decreased HRR and exercise capacity that is not fully captured using creatinine-based measurements. [ABSTRACT FROM AUTHOR]
Published: 2007
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54. Clinical evidence concise. Diabetic nephropathy.

Author: Shlipak M
Published: 2005

55. Hormone therapy and in-hospital survival after myocardial infarction in postmenopausal women.

Author: Shlipak, M G, Angeja, B G, Go, A S, Frederick, P D, Canto, J G, and Grady, D
Published: 2001

56. The incidence of unrecognized myocardial infarction in women with coronary heart disease.

Author: Shlipak MG, Elmouchi DA, Herrington DM, Lin F, Grady D, Hlatky MA, Heart and Estrogen/Progestin Replacement Study Research Group, Shlipak, M G, Elmouchi, D A, Herrington, D M, Lin, F, Grady, D, and Hlatky, M A
Abstract: Background: Several cohort studies in populations without coronary heart disease have demonstrated that up to 40% of incident myocardial infarctions are clinically unrecognized.Objective: To determine the incidence of unrecognized myocardial infarction in women with coronary heart disease in the Heart and Estrogen/progestin Replacement Study (HERS).Design: Randomized, double-blind, placebo-controlled trial of conjugated estrogens plus medroxyprogesterone or identical placebo with 4.1 years of follow-up.Settings: Outpatient and community settings at 20 U.S. clinical centers.Patients: 2763 postmenopausal women younger than 80 years of age with coronary heart disease and an intact uterus.Measurements: Annual electrocardiograms were obtained for all participants during follow-up (mean, 4.1 years) and were evaluated by using the NOVACODE computer algorithm and visual confirmation. A total of 13 715 electrocardiograms were obtained. Suspected unrecognized myocardial infarctions were investigated by comparing a participant's previous surveillance electrocardiograms with the electrocardiograms obtained from all of her intervening hospitalizations. Characteristics of patients with recognized and unrecognized myocardial infarction were compared.Results: Among the 256 nonfatal myocardial infarctions, 11 were unrecognized (4.3% [95% CI, 2.2% to 7.6%]). Seven occurred in women assigned to placebo and 4 occurred in women assigned to hormone therapy (P > 0.2). Women with unrecognized myocardial infarction were less likely to have diabetes mellitus or previous angina and were more likely to have had previous bypass surgery compared with women who had clinically recognized myocardial infarction.Conclusion: The incidence of unrecognized myocardial infarction in women with coronary disease was far lower than that observed in previous studies of populations without coronary heart disease. [ABSTRACT FROM AUTHOR]
Published: 2001
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57. Health and economic benefits of increased beta-blocker use following myocardial infarction.

Author: Phillips KA, Shlipak MG, Coxson P, Heidenreich PA, Hunink MGM, Goldman PA, Williams LW, Weinstein MC, Goldman L, Phillips, K A, Shlipak, M G, Coxson, P, Heidenreich, P A, Hunink, M G, Goldman, P A, Williams, L W, Weinstein, M C, and Goldman, L
Abstract: Context: beta-blockers are underused in patients who have myocardial infarction (MI), despite the proven efficacy of these agents. New evidence indicates that beta-blockers can have benefit in patients with conditions that have been considered relative contraindications. Understanding the consequences of underuse of beta-blockers is important because of the implications for current policy debates over quality-of-care measures and Medicare prescription drug coverage.Objective: To examine the potential health and economic impact of increased use of beta-blockers in patients who have had MI.Design and Setting: We used the Coronary Heart Disease (CHD) Policy Model, a computer-simulation Markov model of CHD in the US population, to estimate the epidemiological impact and cost-effectiveness of increased beta-blocker use from current to target levels among survivors of MI aged 35 to 84 years. Simulations included 1 cohort of MI survivors in 2000 followed up for 20 years and 20 successive annual cohorts of all first-MI survivors in 2000-2020. Mortality and morbidity from CHD were derived from published meta-analyses and recent studies. This analysis used a societal perspective.Main Outcome Measures: Prevented MIs, CHD mortality, life-years gained, and cost per quality-adjusted life-year (QALY) gained in 2000-2020.Results: Initiating beta-blocker use for all MI survivors except those with absolute contraindications in 2000 and continuing treatment for 20 years would result in 4300 fewer CHD deaths, 3500 MIs prevented, and 45,000 life-years gained compared with current use. The incremental cost per QALY gained would be $4500. If this increase in beta-blocker use were implemented in all first-MI survivors annually over 20 years, beta-blockers would save $18 million and result in 72,000 fewer CHD deaths, 62,000 MIs prevented, and 447,000 life-years gained. Sensitivity analyses demonstrated that the cost-effectiveness of beta-blocker therapy would always be less than $11,000 per QALY gained, even under unfavorable assumptions, and may even be cost saving. Restricting beta-blockers only to ideal patients (those without absolute or relative contraindications) would reduce the epidemiological impact of beta-blocker therapy by about 60%.Conclusions: Our simulation indicates that increased use of beta-blockers after MI would lead to impressive gains in health and would be potentially cost saving. JAMA. 2000;284:2748-2754. [ABSTRACT FROM AUTHOR]
Published: 2000

58. Estrogen and progestin, lipoprotein(a), and the risk of recurrent coronary heart disease events after menopause.

Author: Shlipak MG, Simon JA, Vittinghoff E, Lin F, Barrett-Connor E, Knopp RH, Levy RI, Hulley SB, Shlipak, M G, Simon, J A, Vittinghoff, E, Lin, F, Barrett-Connor, E, Knopp, R H, Levy, R I, and Hulley, S B
Abstract: Context: Lipoprotein(a) [Lp(a)] has been identified as an independent risk factor for coronary heart disease (CHD) events. However, few data exist on the clinical importance of Lp(a) lowering for CHD prevention. Hormone therapy with estrogen has been found to lower Lp(a) levels in women.Objective: To determine the relationships among treatment with estrogen and progestin, serum Lp(a) levels, and subsequent CHD events in postmenopausal women.Design and Setting: The Heart and Estrogen/progestin Replacement Study (HERS), a randomized, blinded, placebo-controlled secondary prevention trial conducted from January 1993 through July 1998 with a mean follow-up of 4.1 years at 20 centers.Participants: A total of 2763 postmenopausal women younger than 80 years with coronary artery disease and an intact uterus. Mean age was 66.7 years.Intervention: Participants were randomly assigned to receive either conjugated equine estrogens, 0.625 mg, plus medroxyprogesterone acetate, 2.5 mg, in 1 tablet daily (n = 1380), or identical placebo (n = 1383).Main Outcome Measures: Lipoprotein(a) levels and CHD events (nonfatal myocardial infarction and CHD death).Results: Increased baseline Lp(a) levels were associated with subsequent CHD events among women in the placebo arm. After multivariate adjustment, women in the second, third, and fourth quartiles of baseline Lp(a) level had relative hazards (RHs) (compared with the first quartile) of 1.01 (95% confidence interval [CI], 0.64-1.59), 1.31 (95% CI, 0.85-2.04), and 1.54 (95% CI, 0.99-2.39), respectively, compared with women in the lowest quartile (P for trend = .03). Treatment with estrogen and progestin reduced mean (SD) Lp(a) levels significantly (-5.8 [15] mg/dL) (-0.20 [0.53] micromol/L) compared with placebo (0.3 [17] mg/dL) (0.01 [0.60] micromol/L) (P<.001). In a randomized subgroup comparison, women with low baseline Lp(a) levels had less benefit from estrogen and progestin than women with high Lp(a) levels; the RH for women assigned to estrogen and progestin compared with placebo were 1.49 (95% CI, 0.97-2.26) in the lowest quartile and 1.05 (95% CI, 0.67-1.65), 0.78 (0.52-1.18), and 0.85 (0.58-1.25) in the second, third, and fourth quartiles, respectively (P for interaction trend = .03).Conclusions: Our data suggest that Lp(a) is an independent risk factor for recurrent CHD in postmenopausal women and that treatment with estrogen and progestin lowers Lp(a) levels. Estrogen and progestin therapy appears to have a more favorable effect (relative to placebo) in women with high initial Lp(a) levels than in women with low levels. This apparent interaction needs confirmation in other trials. [ABSTRACT FROM AUTHOR]
Published: 2000
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59. Should the electrocardiogram be used to guide therapy for patients with left bundle-branch block and suspected myocardial infarction?

Author: Shlipak, Michael G., Lyons, William L., Go, Alan S., Chou, Tony m., Evans, G. Thomas, Browner, Warren S., Shlipak, M G, Lyons, W L, Go, A S, Chou, T M, Evans, G T, and Browner, W S
Subjects: MYOCARDIAL infarction diagnosis, ALGORITHMS, ELECTROCARDIOGRAPHY, BUNDLE-branch block, SCIENCE, HERMENEUTICS, EQUIPMENT & supplies, DIAGNOSIS
Abstract: Context: Recently, an algorithm based on the electrocardiogram (ECG) was reported to predict myocardial infarction (MI) in patients with left bundle-branch block (LBBB), but the clinical impact of this testing strategy is unknown.Objective: To determine the diagnostic test characteristics and clinical utility of this ECG algorithm for patients with suspected MI.Design: Retrospective cohort study to which an algorithm was applied, followed by decision analysis regarding thrombolysis made with or without the algorithm.Setting: University emergency department, 1994 through 1997.Patients: Eighty-three patients with LBBB who presented 103 times with symptoms suggestive of MI.Main Outcome Measures: Myocardial infarction determined by serial cardiac enzyme analyses and stroke-free survival.Results: Of 9 ECG findings assessed, none effectively distinguished the 30% of patients with MI from those with other diagnoses. The ECG algorithm indicated positive findings in only 3% of presentations and had a sensitivity of 10% (95% confidence interval, 2%-26%). The decision analysis showed that among 1000 patients with LBBB and chest pain, 929 would survive without major stroke if all received thrombolysis compared with 918 if the ECG algorithm was used as a screening test.Conclusions: The ECG is a poor predictor of MI in a community-based cohort of patients with LBBB and acute cardiopulmonary symptoms. Acute thrombolytic therapy should be considered for all patients with LBBB who have symptoms consistent with MI. [ABSTRACT FROM AUTHOR]
Published: 1999
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60. Kidney function predicts the rate of bone loss in older individuals: The Cardiovascular Health Study

Author: Fried, L. F., Shlipak, M. G., Stehman-Breen, C., Mittalhenkle, A., Seliger, S., Sarnak, M., Robbins, J., Siscovick, D., Harris, T. B., Newman, A. B., and Jane A Cauley

61. Does physician specialty affect the survival of elderly patients with myocardial infarction?

Author: Frances, C. D., Shlipak, M. G., Haruko Noguchi, Heidenreich, P. A., and Mcclellan, M.
Subjects: Male, Age Factors, Cardiology, Myocardial Infarction, Confounding Factors, Epidemiologic, Comorbidity, Medicare, Severity of Illness Index, Survival Analysis, United States, Hospitalization, Data Interpretation, Statistical, Multivariate Analysis, Outcome Assessment, Health Care, Linear Models, Humans, Female, cardiovascular diseases, Health Services Research, Least-Squares Analysis, Models, Econometric, Research Article, Aged, Quality of Health Care, Retrospective Studies
Abstract: OBJECTIVE: To determine the effect of treatment by a cardiologist on mortality of elderly patients with acute myocardial infarction (AMI, heart attack), accounting for both measured confounding using risk-adjustment techniques and residual unmeasured confounding with instrumental variables (IV) methods. DATA SOURCES/STUDY SETTING: Medical chart data and longitudinal administrative hospital records and death records were obtained for 161,558 patients aged > or =65 admitted to a nonfederal acute care hospital with AMI from April 1994 to July 1995. Our principal measure of significant cardiologist treatment was whether a patient was admitted by a cardiologist. We use supplemental data to explore whether our analysis would differ substantially using alternative definitions of significant cardiologist treatment. STUDY DESIGN: This retrospective cohort study compared results using least squares (LS) multivariate regression with results from IV methods that accounted for additional unmeasured patient characteristics. Primary outcomes were 30-day and one-year mortality, and secondary outcomes included treatment with medications and revascularization procedures. DATA COLLECTION/EXTRACTION METHODS: Medical charts for the initial hospital stay of each AMI patient underwent a comprehensive abstraction, including dates of hospitalization, admitting physician, demographic characteristics, comorbid conditions, severity of clinical presentation, electrocardiographic and other diagnostic test results, contraindications to therapy, and treatments before and after AMI. PRINCIPAL FINDINGS: Patients admitted by cardiologists had fewer comorbid conditions and less severe AMIs. These patients had a 10 percent (95 percent CI: 9.5-10.8 percent) lower absolute mortality rate at one year. After multivariate adjustment with LS regression, the adjusted mortality difference was 2 percent (95 percent CI: 1.4-2.6 percent). Using IV methods to provide additional adjustment for unmeasured differences in risk, we found an even smaller, statistically insignificant association between physician specialty and one-year mortality, relative risk (RR) 0.96 (0.88-1.04). Patients admitted by a cardiologist were also significantly more likely to have a cardiologist consultation within the first day of admission and during the initial hospital stay, and also had a significantly larger share of their physician bills for inpatient treatment from cardiologists. IV analysis of treatments showed that patients treated by cardiologists were more likely to undergo revascularization procedures and to receive thrombolytic therapy, aspirin, and calcium channel-blockers, but less likely to receive beta-blockers. CONCLUSIONS: In a large population of elderly patients with AMI, we found significant treatment differences but no significant incremental mortality benefit associated with treatment by cardiologists.

62. Cystatin C as a marker of glomerular filtration rate in chronic kidney disease: influence of body composition.

Author: Shlipak, M. G.
Subjects: *HUMAN body composition, *PROTEASE inhibitors, *BIOMARKERS, *GLOMERULAR filtration rate, *CHRONIC kidney failure, *KIDNEY diseases
Abstract: BACKGROUND As a marker of glomerular filtration rate (GFR), cystatin C is thought to be independent of body composition because it is produced by all nucleated cells. OBJECTIVE To characterize the influence of body composition on cystatin C levels in patients with chronic kidney disease (CKD). DESIGN AND INTERVENTION A convenience sample of nondiabetic patients >18 years old with stage 1-4 CKD was selected for this UK study. If GFR was >60 ml/min/1.73 m², there was an additional inclusion criterion of kidney damage (e.g. albuminuria, hematuria or chronic glomerulonephritis). Cystatin C was quantified by turbidimetric immunoassay, GFR was measured by clearance of a bolus injection of inulin, and lean mass and fat mass were assessed by dual-energy X-ray absorptiometry. The contribution of age, gender, height, weight, lean mass and fat mass to variance in cystatin C levels was evaluated using multiple regression. Three GFR prediction equations were constructed, including the following variables: cystatin C level only; cystatin C level plus age, gender, height and weight; and cystatin C level plus age, gender, height, lean mass and fat mass. OUTCOME MEASURES Variance in serum cystatin C levels and performance of the GFR prediction equations were evaluated. RESULTS Among the 50 men and 27 women enrolled, mean ages were 66.4 years and 62.7 years, respectively. Overall mean GFR was 45.7 ±28.6 ml/min/1.73 m². GFR was not corrected for body surface area in the statistical analyses. In the multiple regression analysis, absolute GFR accounted for 48.6% of the variance in cystatin C levels (β statistic =-0.834; P= 0.000) and lean mass explained a further 6.0% of the variance (β statistic=0.280; P=0.003). None of age, gender, height, fat mass or weight contributed any further significant variance in cystatin C level. There was no significant difference between absolute GFR (as measured by inulin clearance) and GFR as estimated by the three equations. Nevertheless, the equation that included lean mass showed a higher Pearson correlation coefficient (r), less bias and better limits of agreement regarding absolute GFR value than the equation that included cystatin C alone (0.851 vs 0.689, -3.6 ml/min vs-5.0 ml/min, and 37.9ml/min vs 50.8ml/min, respectively), and predicted GFR to within 30% of the actual value in 66.2% of cases, compared with 51.9% of cases using the cystatin C alone equation. In the 35 patients with a body composition at the extremes of the range (total lean mass or fat mass >±1 SD of the whole sample), the difference between equations was more pronounced. In these patients, the equation that incorporated lean mass had an r value of 0.891, bias of -4.7 ml/min, limits of agreement of 41.7 ml/min and was 71.4% accurate to within 30% error; the corresponding values for the equation that included cystatin C alone were 0.691, -7.7 ml/min, 62.0 ml/min and 51.4% (to within 30%), respectively. CONCLUSION Lean body mass affects cystatin C level, and cystatin-C-based prediction of GFR improves when this variable is taken into account. [ABSTRACT FROM AUTHOR]
Published: 2007
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63. Blood-pressure-lowering treatment.

Author: Shlipak, M G and Hulley, S B
Subjects: *CALCIUM antagonists, *ANTIHYPERTENSIVE agents, *HYPERTENSION, *META-analysis, *STATISTICS, *DATA analysis, *RESEARCH bias, *THERAPEUTICS
Published: 2001
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64. Kidney function and multiple hemostatic markers: cross sectional associations in the multi-ethnic study of atherosclerosis

Author: Peralta Carmen A, Palmas Walter, Fried Linda F, Folsom Aaron R, Cushman Mary, Dubin Ruth, Wassel Christina, and Shlipak Michael G
Subjects: Diseases of the genitourinary system. Urology, RC870-923
Abstract: Abstract Background Defined as estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2, chronic kidney disease (CKD) is strongly and independently associated with cardiovascular and overall mortality. We hypothesized that reduced kidney function would be characterized by abnormalities of hemostasis. Methods We tested cross-sectional associations between (eGFR) and multiple hemostatic markers among 6751 participants representing a broad spectrum of kidney function in the Multi-Ethnic Study of Atherosclerosis (MESA). Kidney function was measured using cystatin C (eGFRcys) or creatinine, using CKD Epidemiology Collaboration (eGFRcr). Hemostatic markers included soluble thrombomodulin (sTM), soluble tissue factor (sTF), D-Dimer, von Willebrand factor (vWF), factor VIII, plasmin-antiplasmin complex (PAP), tissue factor pathway inhibitor (TFPI), plasminogen activator inhibitor-1 (PAI-1), and fibrinogen. Associations were tested using multivariable linear regression with adjustment for demographics and comorbidities. Results In comparison to persons with eGFRcys >90 ml/min/1.73 m2, subjects with eGFRcys < 60 ml/min/1.73 m2 had adjusted levels of sTM, sTF, D-Dimer, PAP, Factor VIII, TFPI, vWF and fibrinogen that were respectively 86%, 68%, 44%, 22%, 17%, 15%, 12% and 6% higher. Subjects with eGFRcys 60-90 ml/min/1.73 m2 had adjusted levels that were respectively 16%, 14%, 12%, 6%, 6%, 6%, 11% and 4% higher (p < 0.05 for all). Percent differences were not significantly different when groups were categorized by eGFRcr. Conclusions Throughout a broad spectrum of kidney function, lower eGFR was associated with higher levels of hemostatic markers. Dysregulation of hemostasis may be a mechanism by which reduced kidney function promotes higher cardiovascular risk.
Published: 2011
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65. Uromodulin concentrations are not associated with incident CKD among persons with coronary artery disease

Author: Coresh Josef, Fox Caroline, Li Yongmei, Shlipak Michael G, Grunfeld Carl, and Whooley Mary
Subjects: Diseases of the genitourinary system. Urology, RC870-923
Abstract: Abstract Background A common variant of the UMOD gene was linked with prevalent chronic kidney disease (CKD) in large, genomics consortia. One community-based study found that urine concentrations of the uromodulin protein forecast risk of incident CKD. This study within persons with known coronary artery disease (CAD) evaluated whether uromodulin concentrations could distinguish CKD risk. Methods In the Heart and Soul Study, the UMOD snp (12917707) was genotyped in 879 individuals with baseline creatinine clearance (CrCl) measured from a 24-hour urine collection. Uromodulin protein was measured from stored urine specimens among a subset of 120 participants, balanced by genotype. Incident CKD cases (N = 102) were defined by an initial CrCl > 70 ml/min and a 5-year follow-up CrCl Results Among 527 self-described White participants with DNA, 373 (71%) were homozygous for the dominant allele (G/G), 133 (25%) were heterozygous (G/T) and only 21 (4%) were homozygous for the minor allele (T/T). The T/T genotype had an approximately 11 ml/min higher CrCl than the other 2 groups, but this difference did not reach statistical significance (p = 0.20). The T/T genotype had significantly lower uromodulin levels than the common G/G genotype, and the G/T genotype had intermediate levels. However, uromodulin concentrations were similar between cases and controls (44 vs. 48 mg/dL, p = 0.88). Conclusions This study among a cohort of persons with established CAD found no association between urine uromodulin and incident CKD, although UMOD genotype was associated with urine uromodulin concentrations.
Published: 2011
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66. Association of kidney function with inflammatory and procoagulant markers in a diverse cohort: A cross-sectional analysis from the Multi-Ethnic Study of Atherosclerosis (MESA)

Author: Cushman Mary, Katz Ronit, Keller Christopher, Fried Linda F, and Shlipak Michael
Subjects: Diseases of the genitourinary system. Urology, RC870-923
Abstract: Abstract Background Prior studies using creatinine-based estimated glomerular filtration rate (eGFR) have found limited associations between kidney function and markers of inflammation. Using eGFR and cystatin C, a novel marker of kidney function, the authors investigated the association of kidney function with multiple biomarkers in a diverse cohort. Methods The Multi-Ethnic Study of Atherosclerosis consists of 6,814 participants of white, African-American, Hispanic, and Chinese descent, enrolled from 2000–2002 from six U.S. communities. Measurements at the enrollment visit included serum creatinine, cystatin C, and six inflammatory and procoagulant biomarkers. Creatinine-based eGFR was estimated using the four-variable Modification of Diet in Renal Disease equation, and chronic kidney disease was defined by an eGFR < 60 mL/min/1.73 m2. Results Adjusted partial correlations between cystatin C and all biomarkers were statistically significant: C-reactive protein (r = 0.08), interleukin-6 (r = 0.16), tumor necrosis factor-α soluble receptor 1 (TNF-αR1; r = 0.75), intercellular adhesion molecule-1 (r = 0.21), fibrinogen (r = 0.14), and factor VIII (r = 0.11; two-sided p < 0.01 for all). In participants without chronic kidney disease, higher creatinine-based eGFR was associated only with higher TNF-αR1 levels. Conclusion In a cohort characterized by ethnic diversity, cystatin C was directly associated with multiple procoagulant and inflammatory markers. Creatinine-based eGFR had similar associations with these biomarkers among subjects with chronic kidney disease.
Published: 2008
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67. Prevalence of CKD and comorbid illness in elderly patients in the United States: results from the Kidney Early Evaluation Program (KEEP).

Author: Stevens LA, Li S, Wang C, Huang C, Becker BN, Bomback AS, Brown WW, Burrows NR, Jurkovitz CT, McFarlane SI, Norris KC, Shlipak M, Whaley-Connell AT, Chen SC, Bakris GL, McCullough PA, Stevens, Lesley A, Li, Suying, Wang, Changchun, and Huang, Cindy
Abstract: Background: Elderly individuals with chronic kidney disease (CKD) have high rates of comorbid conditions, including cardiovascular disease and its risk factors, and CKD-related complications. In individuals aged > or = 65 years, we sought to describe the prevalence of CKD determined from laboratory test results in the Kidney Early Evaluation Program (KEEP; n = 27,017) and National Health and Nutrition Examination Survey (NHANES) 1999-2006 (n = 5,538) and the prevalence of diagnosed CKD determined from billing codes in the Medicare 5% sample (n = 1,236,946). In all 3 data sources, we also explored comorbid conditions and CKD-related complications.Methods: CKD was identified as decreased estimated glomerular filtration rate (<60 mL/min/1.73 m(2)) or increased albumin-creatinine ratio in KEEP and NHANES; CKD was identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes in Medicare. Investigated comorbid conditions included diabetes, hypertension, high cholesterol level, coronary artery disease, congestive heart failure, cerebrovascular disease, peripheral vascular disease, and cancer, and CKD-related complications included anemia, hypocalcemia, hyperphosphatemia, and hyperparathyroidism.Results: The prevalence of CKD was approximately 44% in both KEEP and NHANES participants, and the prevalence of diagnosed CKD was 7% in Medicare beneficiaries. In all 3 data sets, the prevalence of CKD or diagnosed CKD was higher in participants aged > or = 80 years and those with comorbid conditions. For KEEP and NHANES participants, the prevalence of most comorbid conditions and CKD complications increased with decreasing estimated glomerular filtration rate. For participants with CKD stages 3-5, a total of 29.2% (95% CI, 27.8-30.6) in KEEP and 19.9% (95% CI, 17.0-23.1) in NHANES had anemia, 0.7% (95% CI, 0.4-0.9) and 0.6% (95% CI, 0.3-1.3) had hypocalcemia, 5.4% (95% CI, 4.7-6.1) and 6.4% (95% CI, 5.1-8.0) had hyperphosphatemia, and 52.0% (95% CI, 50.4-53.6) and 30.0% (95% CI, 25.9-34.3) had hyperparathyroidism, respectively.Conclusions: CKD is common in the elderly population and is associated with high frequencies of concomitant comorbid conditions and biochemical abnormalities. Because CKD is not commonly diagnosed, greater emphasis on physician education may be beneficial. [ABSTRACT FROM AUTHOR]
Published: 2010
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68. Can A New Blood Test Help Predict Who Is At Risk for Developing Heart Failure?

Author: Sarnak, M. J., Katz, R., Stehman-Breen, C. O., Fried, L. F., Jenny, N. Swords, Psaty, B. M., Newman, A. B., Siscovick, D., and Shlipak, M. G.
Subjects: HEART disease risk factors, HEART failure, CARDIAC arrest, MYOCARDIAL infarction, BLOOD pressure, THERAPEUTICS
Abstract: The article reports on determining whether new bloods test help predict who is at risk for developing heart failure. In heart failure, the heart cannot pump enough blood to supply the body's needs. Risk factors include high blood pressure and a previous heart attack. Low kidney function may also increase risk. The easiest way to detect low kidney function is to measure creatinine, a protein in the blood that increases when kidney function decreases. However, creatinine levels are not always accurate.
Published: 2005
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69. Possible Causes of the Increasing Incidence of End-Stage Renal Disease.

Author: Hsu, C. Y., Vittinghoff, E., Lin, F., and Shlipak, M. G.
Subjects: CHRONIC kidney failure, CHRONIC diseases, KIDNEY diseases, DISEASES, MEDICINE
Abstract: Presents the summary of the study "The Incidence of End-Stage Renal Disease Is Increasing Faster Than the Prevalence of Chronic Renal Insufficiency," which was published in the July 20, 2004 issue of Annals of Internal Medicine.
Published: 2004
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70. Genetic studies of body mass index yield new insights for obesity biology

Author: Locke, Adam E, Kahali, Bratati, Croteau-Chonka, Damien C, Doney, Alex S F, He, Bing, Heikkilä, Outi, Hietala, Kustaa, Kytö, Janne, Lahermo, Päivi, Lehto, Markku, Österholm, Anne-May, Parkkonen, Maija, Pitkäniemi, Janne, Rosengård-Bärlund, Milla, Eklund, Niina, Saraheimo, Markku, Sarti, Cinzia, Söderlund, Jenny, Soro-Paavonen, Aino, Syreeni, Anna, Thorn, Lena M, Tikkanen, Heikki, Tolonen, Nina, Tryggvason, Karl, Tuomilehto, Jaakko, Estrada, Karol, Wadén, Johan, Gill, Geoffrey V, Prior, Sarah, Guiducci, Candace, Mirel, Daniel B, Taylor, Andrew, Hosseini, Mohsen, Parving, Hans-Henrik, Rossing, Peter, Tarnow, Lise, Eury, Elodie, Ladenvall, Claes, Alhenc-Gelas, François, Lefebvre, Pierre, Rigalleau, Vincent, Roussel, Ronan, Tregouet, David-Alexandre, Maestroni, Anna, Maestroni, Silvia, Falhammar, Henrik, Gu, Tianwei, Folkersen, Lasse, Möllsten, Anna, Cimponeriu, Dan, Mihai, Ioana, Mota, Maria, Mota, Eugen, Serafinceanu, Cristian, Stavarachi, Monica, Hanson, Robert L, Nelson, Robert G, Kretzler, Matthias, Fraser, Ross M, Colhoun, Helen M, Panduru, Nicolae Mircea, Gu, Harvest F, Brismar, Kerstin, Zerbini, Gianpaolo, Hadjadj, Samy, Marre, Michel, Groop, Leif, Lajer, Maria, Bull, Shelley B, Garcia, Melissa E, Waggott, Daryl, Paterson, Andrew D, Savage, David A, Bain, Stephen C, Martin, Finian, Hirschhorn, Joel N, Godson, Catherine, Florez, Jose C, Groop, Per-Henrik, Maxwell, Alexander P, Geller, Frank, Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Giedraitis, Vilmantas, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Y, Demirkan, Ayşe, Den Hertog, Heleen M, Do, Ron, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Gigante, Bruna, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Esko, Tonu, Go, Alan S, Johansson, Åsa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik K E, Mangino, Massimo, Golay, Alain, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Goodall, Alison H, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Gordon, Scott D, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Gorski, Mathias, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doring, Angela, Elliott, Paul, Grabe, Hans-Jörgen, Epstein, Stephen E, Eyjolfsson, Gudmundur Ingi, 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EN., Warrington, NM., Alavere, H., Barroso, I., Berenson, GS., Blackburn, H., Busonero, F., Chen, W., Couper, D., Easton, DF., Eriksson, J., Foroud, T., Geller, F., Hernandez, DG., Kilpeläinen, TO., Li, S., Melbye, M., Murray, JC., Murray, SS., Nelis, M., Ness, AR., Northstone, K., Peacock, M., Pennell, CE., Pharoah, P., Rafnar, T., Rice, JP., Ring, SM., Schork, NJ., Segrè, AV., Sovio, U., Srinivasan, SR., Tammesoo, ML., Tyrer, J., van Meurs JB., Weedon, MN., Wichmann, H., Young, L., Bierut, LJ., Boyd, HA., Econs, MJ., Van T'Hooft, Ferdinand M., Njølstad, Inger, Abecasis, Gonçalo R., Barroso, Inɥ, The MIGEN Consortium, Investigator, Casari, GIORGIO NEVIO, Other departments, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Landsteiner Laboratory, Clinical Haematology, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life 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Mangino, M, Leach, I, Medina-Gomez, C, Medland, S, Nalls, M, Palmer, C, Pasko, D, Pechlivanis, S, Peters, M, Prokopenko, I, Shungin, D, Stancakova, A, Strawbridge, R, Sung, Y, Tanaka, T, Teumer, A, Trompet, S, van der Laan, S, van Setten, J, Van Vliet-Ostaptchouk, J, Wang, Z, Yengo, L, Zhang, W, Isaacs, A, Albrecht, E, Arnlov, J, Arscott, G, Attwood, A, Bandinelli, S, Barrett, A, Bas, I, Bellis, C, Bennett, A, Berne, C, Blagieva, R, Bluher, M, Bohringer, S, Bonnycastle, L, Bottcher, Y, Boyd, H, Bruinenberg, M, Caspersen, I, Chen, Y, Clarke, R, Daw, E, de Craen, A, Delgado, G, Dimitriou, M, Doney, A, Eklund, N, Estrada, K, Eury, E, Folkersen, L, Fraser, R, Garcia, M, Geller, F, Giedraitis, V, Gigante, B, Go, A, Golay, A, Goodall, A, Gordon, S, Gorski, M, Grabe, H, Grallert, H, Grammer, T, Grassler, J, Gronberg, H, Groves, C, Gusto, G, Haessler, J, Hall, P, Haller, T, Hallmans, G, Hartman, C, Hassinen, M, Hayward, C, Heard-Costa, N, Helmer, Q, Hengstenberg, C, Holmen, O, Hottenga, J, James, A, Jeff, J, Johansson, A, Jolley, J, Juliusdottir, T, Kinnunen, L, Koenig, W, Koskenvuo, M, Kratzer, W, Laitinen, J, Lamina, C, Leander, K, Lee, N, Lichtner, P, Lind, L, Lindstrom, J, Lo, K, Lobbens, S, Lorbeer, R, Lu, Y, Mach, F, Magnusson, P, Mahajan, A, Mcardle, W, Mclachlan, S, Menni, C, Merger, S, Mihailov, E, Milani, L, Moayyeri, A, Monda, K, Morken, M, Mulas, A, Muller, G, Muller-Nurasyid, M, Musk, A, Nagaraja, R, Nothen, M, Nolte, I, Pilz, S, Rayner, N, Renstrom, F, Rettig, R, Ried, J, Ripke, S, Robertson, N, Rose, L, Sanna, S, Scharnagl, H, Scholtens, S, Schumacher, F, Scott, W, Seufferlein, T, Shi, J, Smith, A, Smolonska, J, Stanton, A, Steinthorsdottir, V, Stirrups, K, Stringham, H, Sundstrom, J, Swertz, M, Swift, A, Syvanen, A, Tan, S, Tayo, B, Thorand, B, Thorleifsson, G, Tyrer, J, Uh, H, Vandenput, L, Verhulst, F, Vermeulen, S, Verweij, N, Vonk, J, Waite, L, Warren, H, Waterworth, D, Weedon, M, Wilkens, L, Willenborg, C, Wilsgaard, T, Wojczynski, M, Wong, A, Wright, A, Zhang, Q, Brennan, E, Choi, M, Dastani, Z, Drong, A, Eriksson, P, Franco-Cereceda, A, Gadin, J, Gharavi, A, Goddard, M, Handsaker, R, Huang, J, Karpe, F, Kathiresan, S, Keildson, S, Kiryluk, K, Kubo, M, Lee, J, Liang, L, Lifton, R, Ma, B, Mccarroll, S, Mcknight, A, Min, J, Moffatt, M, Montgomery, G, Murabito, J, Nicholson, G, Nyholt, D, Okada, Y, Perry, J, Dorajoo, R, Reinmaa, E, Salem, R, Sandholm, N, Scott, R, Stolk, L, Takahashi, A, Van't Hooft, F, Vinkhuyzen, A, Westra, H, Zheng, W, Zondervan, K, Heath, A, Arveiler, D, Bakker, S, Beilby, J, Bergman, R, Blangero, J, Bovet, P, Campbell, H, Caulfield, M, Cesana, G, Chakravarti, A, Chasman, D, Chines, P, Collins, F, Crawford, D, Cupples, L, Cusi, D, Danesh, J, de Faire, U, Den Ruijter, H, Dominiczak, A, Erbel, R, Erdmann, J, Eriksson, J, Farrall, M, Felix, S, Ferrannini, E, Ferrieres, J, Ford, I, Forouhi, N, Forrester, T, Franco, O, Gansevoort, R, Gejman, P, Gieger, C, Gottesman, O, Gudnason, V, Gyllensten, U, Hall, A, Harris, T, Hattersley, A, Hicks, A, Hindorff, L, Hingorani, A, Hofman, A, Homuth, G, Hovingh, G, Humphries, S, Hunt, S, Hypponen, E, Illig, T, Jacobs, K, Jarvelin, M, Jockel, K, Johansen, B, Jousilahti, P, Jukema, J, Jula, A, Kaprio, J, Kastelein, J, Keinanen-Kiukaanniemi, S, Kiemeney, L, Knekt, P, Kooner, J, Kooperberg, C, Kovacs, P, Kraja, A, Kumari, M, Kuusisto, J, Lakka, T, Langenberg, C, Marchand, L, Lehtimaki, T, Lyssenko, V, Mannisto, S, Marette, A, Matise, T, Mckenzie, C, Mcknight, B, Moll, F, Morris, A, Murray, J, Nelis, M, Ohlsson, C, Oldehinkel, A, Ong, K, Madden, P, Pasterkamp, G, Peden, J, Peters, A, Postma, D, Pramstaller, P, Price, J, Qi, L, Raitakari, O, Rankinen, T, Rao, D, Rice, T, Ridker, P, Rioux, J, Ritchie, M, Rudan, I, Salomaa, V, Samani, N, Saramies, J, Sarzynski, M, Schunkert, H, Schwarz, P, Sever, P, Shuldiner, A, Sinisalo, J, Stolk, R, Strauch, K, Tonjes, A, Tregouet, D, Tremblay, A, Tremoli, E, Virtamo, J, Vohl, M, Volker, U, Waeber, G, Willemsen, G, 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Mccarthy, M, Visscher, P, Scherag, A, Willer, C, Boehnke, M, Mohlke, K, Lindgren, C, Beckmann, J, Barroso, I, North, K, Ingelsson, E, Hirschhorn, J, Loos, R, Speliotes, E, Thompson, J, Goldstein, B, Konig, I, Cazier, J, Grundberg, E, Havulinna, A, Ho, W, Hopewell, J, Eriksson, N, Lundmark, P, Lyytikainen, L, Rafelt, S, Tikkanen, E, Van Zuydam, N, Voight, B, Ziegler, A, Altshuler, D, Balmforth, A, Braund, P, Burgdorf, C, Claudi-Boehm, S, Cox, D, Do, R, El Mokhtari, N, Fontanillas, P, Hager, J, Han, B, Kang, H, Kessler, T, Knowles, J, Kolovou, G, Langford, C, Lokki, M, Lundmark, A, Meisinger, C, Melander, O, Maouche, S, Nikus, K, Rasheed, A, Rosinger, S, Rubin, D, Rumpf, M, Schafer, A, Sivananthan, M, Song, C, Stewart, A, Thorgeirsson, G, van der Schoot, C, Wagner, P, Wells, G, Wild, P, Tsun-Po, Y, Basart, H, Brambilla, P, Cambien, F, Cupples, A, Dehghan, A, Diemert, P, Epstein, S, Evans, A, Ferrario, M, Gauguier, D, Hazen, S, Holm, H, Iribarren, C, Jang, Y, Kahonen, M, Kee, F, Kim, H, 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Kroemer, H, Nauck, M, Stracke, S, Volzke, H, Aulchenko, Y, Polasek, O, Hastie, N, Vitart, V, Helmer, C, Wang, J, Ruggiero, D, Bergmann, S, Viikari, J, Nikopensius, T, Province, M, Ketkar, S, Colhoun, H, Robino, A, Giulianini, F, Kramer, B, Portas, L, Buckley, B, Adam, M, Thun, G, Paulweber, B, Haun, M, Sala, C, Metzger, M, Mitchell, P, Ciullo, M, Kim, S, Vollenweider, P, Gasparini, P, Pirastu, M, Probst-Hensch, N, Kronenberg, F, Toniolo, D, Coresh, J, Schmidt, R, Siscovick, D, Kardia, S, Curhan, G, Franke, A, Parsa, A, Goessling, W, Kao, W, de Boer, I, Peralta, C, Akylbekova, E, Kramer, H, Arking, D, Franceschini, N, Egan, J, Hernandez, D, Townsend, R, Lumley, T, Psaty, B, Kestenbaum, B, Haritunians, T, Mooser, V, Florez, J, Meigs, J, Lu, X, Leak, T, Aasarod, K, Skorpen, F, Baumert, J, Devuyst, O, Mychaleckyj, J, Kedenko, L, Coassin, S, Hallan, S, Navis, G, Shlipak, M, Bull, S, Paterson, A, Rotter, J, Dreisbach, A, Anderson, C, Guo, Q, Henders, A, Lambert, A, Lee, S, Kraft, P, Kennedy, S, Macgregor, S, Missmer, S, Painter, J, Roseman, F, Treloar, S, Wallace, L, Forsblom, C, Isakova, T, Mckay, G, Williams, W, Sadlier, D, Makinen, V, Swan, E, Boright, A, Ahlqvist, E, Keller, B, Huang, H, Ahola, A, Fagerholm, E, Gordin, D, Harjutsalo, V, He, B, Heikkila, O, Hietala, K, Kyto, J, Lahermo, P, Lehto, M, Osterholm, A, Parkkonen, M, Pitkaniemi, J, Rosengard-Barlund, M, Saraheimo, M, Sarti, C, Soderlund, J, Soro-Paavonen, A, Syreeni, A, Thorn, L, Tikkanen, H, Tolonen, N, Tryggvason, K, Waden, J, Gill, G, Prior, S, Guiducci, C, Mirel, D, Taylor, A, Hosseini, M, Parving, H, Rossing, P, Tarnow, L, Ladenvall, C, Alhenc-Gelas, F, Lefebvre, P, Rigalleau, V, Roussel, R, Maestroni, A, Maestroni, S, Falhammar, H, Gu, T, Mollsten, A, Cimponeriu, D, Mihai, I, Mota, M, Mota, E, Serafinceanu, C, Stavarachi, M, Hanson, R, Nelson, R, Kretzler, M, Panduru, N, Gu, H, Brismar, K, Zerbini, G, Hadjadj, S, Marre, M, Lajer, M, Waggott, D, Savage, D, Bain, S, Martin, F, Godson, C, Groop, P, Maxwell, A, Sengupta, S, Peloso, G, Ganna, A, Mora, S, Chang, H, Den Hertog, H, Donnelly, L, Freitag, D, Gurdasani, D, Heikkila, K, Johnson, T, Kaakinen, M, Kettunen, J, Li, X, Montasser, M, Petersen, A, Saxena, R, Service, S, Sidore, C, Surakka, I, Teslovich, T, Van den Herik, E, Volcik, K, Wu, Y, Asiki, G, Been, L, Burnett, M, Elliott, P, Eyjolfsson, G, Goodarzi, M, Gravito, M, Hartikainen, A, Hung, Y, Jones, M, Kaleebu, P, Khaw, K, Kim, E, Komulainen, P, Lin, S, Narisu, N, Nieminen, T, Nsubuga, R, Olafsson, I, Palotie, A, Papamarkou, T, Pomilla, C, Pouta, A, Ruokonen, A, Seeley, J, Silander, K, Tiret, L, van Pelt, L, Wainwright, N, Wijmenga, C, Young, E, Bennett, F, Boomsma, D, Burnier, M, Feranil, A, Freimer, N, Hsiung, C, Kesaniemi, A, Koudstaal, P, Krauss, R, Kyvik, K, Meneton, P, Moilanen, L, Sanghera, D, Sheu, W, Whitfield, J, Wolffenbuttel, B, Ordovas, J, Rich, S, Johnson, L, Larson, M, Levy, D, Newton-Cheh, C, O'Reilly, P, Palmas, W, Rice, K, Snider, H, Tobin, M, Verwoert, G, Pihur, V, Heath, S, Sober, S, Arora, P, Zhang, F, Lucas, G, Milaneschi, Y, Parker, A, Fava, C, Fox, E, Go, M, Sjogren, M, Vinay, D, Alexander, M, Tabara, Y, Shaw-Hawkins, S, Whincup, P, Shi, G, Seielstad, M, Sim, X, Nguyen, K, Matullo, G, Gaunt, T, Onland-Moret, N, Cooper, M, Platou, C, Org, E, Hardy, R, Dahgam, S, Palmen, J, Kuznetsova, T, Uiterwaal, C, Adeyemo, A, Ludwig, B, Tomaszewski, M, Tzoulaki, I, Palmer, N, Chang, Y, Steinle, N, Grobbee, D, Morrison, A, Najjar, S, Hadley, D, Brown, M, Connell, J, Day, I, Lawlor, D, Lawrence, R, Ongen, H, Li, Y, Young, J, Bis, J, Chaturvedi, N, Islam, M, Jafar, T, Kulkarni, S, Howard, P, Guarrera, S, Ricceri, F, Emilsson, V, Plump, A, Weder, A, Sun, Y, Scott, L, Peltonen, L, Vartiainen, E, Brand, S, Staessen, J, Wang, T, Burton, P, Artigas, M, Dong, Y, Wang, X, Zhu, H, Rudock, M, Heckbert, S, Smith, N, Wiggins, K, Doumatey, A, Shriner, D, Veldre, G, Viigimaa, M, Kinra, S, Prabhakaran, D, Tripathy, V, Langefeld, C, Rosengren, A, Thelle, D, Corsi, A, Singleton, A, Hilton, G, Salako, T, Iwai, N, Kita, Y, Ogihara, T, Ohkubo, T, Okamura, T, Ueshima, H, Umemura, S, Eyheramendy, S, Meitinger, T, Cho, Y, Scott, J, Sehmi, J, Hedblad, B, Nilsson, P, Smith, G, Raffel, L, Yao, J, Schwartz, S, Ikram, M, W, L, Mosley, T, Seshadri, S, Shrine, N, Wain, L, Zitting, P, Cooper, J, van Gilst, W, Janipalli, C, Mani, K, Yajnik, C, Mattace-Raso, F, Lakatta, E, Orru, M, Scuteri, A, Ala-Korpela, M, Kangas, A, Soininen, P, Tukiainen, T, Wurtz, P, Ong, R, Dorr, M, Galan, P, Hercberg, S, Lathrop, M, Zelenika, D, Zhai, G, Meschia, J, Sharma, P, Terzic, J, Kumar, M, Denniff, M, Zukowska-Szczechowska, E, Wagenknecht, L, Fowkes, F, Charchar, F, Guo, X, Rotimi, C, Bots, M, Brand, E, Talmud, P, Nyberg, F, Laan, M, Palmer, L, van der Schouw, Y, Casas, J, Vineis, P, Ganesh, S, Wong, T, Tai, E, Morris, R, Marmot, M, Miki, T, Chandak, G, Zhu, X, Elosua, R, Soranzo, N, Sijbrands, E, Uda, M, Vasan, R, Alizadeh, B, de Boer, R, Boezen, H, Hillege, H, van der Klauw, M, Ormel, J, Rosmalen, J, Slaets, J, Lagou, V, Welch, R, Wheeler, E, Rehnberg, E, Rasmussen-Torvik, L, Lecoeur, C, Johnson, P, Sennblad, B, Salo, P, Timpson, N, Evans, D, St Pourcain, B, Bielak, L, Horikoshi, M, Navarro, P, Raychaudhuri, S, Chen, H, Rybin, D, Willems, S, Song, K, An, P, Marullo, L, Jansen, H, Pankow, J, Edkins, S, Varga, T, Oksa, H, Antonella, M, Kong, A, Herder, C, Antti, J, Small, K, Miljkovic, I, Atalay, M, Kiess, W, Smit, J, Campbell, S, Fowkes, G, Rathmann, W, Maerz, W, Watanabe, R, de Geus, E, Penninx, B, Toenjes, A, Peyser, P, Korner, A, Dupuis, J, Cucca, F, Balkau, B, Bouatia-Naji, N, Purcell, S, Musunuru, K, Ardissino, D, Mannucci, P, Anand, S, Engert, J, Morgan, T, Spertus, J, Stoll, M, Girelli, D, Mckeown, P, Patterson, C, Merlini, P, Berzuini, C, Bernardinelli, L, Peyvandi, F, Tubaro, M, Celli, P, Fetiveau, R, Marziliano, N, Casari, G, Galli, M, Ribichini, F, Rossi, M, Bernardi, F, Zonzin, P, Piazza, A, Yee, J, Friedlander, Y, Marrugat, J, Subirana, I, Sala, J, Ramos, R, Williams, G, Nathan, D, Macrae, C, Berglund, G, Asselta, R, Duga, S, Spreafico, M, Daly, M, Nemesh, J, Korn, J, Surti, A, Gianniny, L, Parkin, M, Burtt, N, Gabriel, S, Wright, B, Ball, S, Schunkert, I, Linsel-Nitschke, P, Lieb, W, Fischer, M, Grosshennig, A, Preuss, M, Scholz, M, Chen, Z, Wilensky, R, Matthai, W, Qasim, A, Hakonarson, H, Devaney, J, Pichard, A, Kent, K, Satler, L, Lindsay, J, Waksman, R, Knouff, C, Scheffold, T, Berger, K, Huge, A, Martinelli, N, Olivieri, O, Corrocher, R, Xie, C, Ahmadi, K, Ainali, C, Bataille, V, Bell, J, Buil, A, Dermitzakis, E, Dimas, A, Durbin, R, Glass, D, Hassanali, N, Ingle, C, Knowles, D, Krestyaninova, M, Lowe, C, Meduri, E, Di Meglio, P, Montgomery, S, Nestle, F, Nica, A, Nisbet, J, O'Rahilly, S, Parts, L, Potter, S, Sekowska, M, Shin, S, Surdulescu, G, Travers, M, Tsaprouni, L, Tsoka, S, Wilk, A, Yang, T, Higashio, J, Williams, R, Nato, A, Ambite, J, Deelman, E, Manolio, T, Heiss, G, Taylor, K, Avery, C, Graff, M, Lin, D, Quibrera, M, Cochran, B, Kao, L, Umans, J, Cole, S, Maccluer, J, Person, S, Gross, M, Fornage, M, Durda, P, Jenny, N, Patsy, B, Arnold, A, Buzkova, P, Haines, J, Murdock, D, Glenn, K, Brown-Gentry, K, Thornton-Wells, T, Dumitrescu, L, Bush, W, Mitchell, S, Goodloe, R, Wilson, S, Boston, J, Malinowski, J, Restrepo, N, Oetjens, M, Fowke, J, Spencer, K, Pendergrass, S, Le Marchand, L, Park, L, Tiirikainen, M, Kolonel, L, Cheng, I, Wang, H, Shohet, R, Stram, D, Henderson, B, Monroe, K, Anderson, G, Carlson, C, Prentice, R, Lacroix, A, Wu, C, Carty, C, Rosse, S, Young, A, Kocarnik, J, Lin, Y, Jackson, R, Duggan, D, Kuller, L, He, C, Sulem, P, Barbalic, M, Broer, L, Byrne, E, Gudbjartsson, D, Mcardle, P, Porcu, E, van Wingerden, S, Zhuang, W, Lauc, L, Broekmans, F, Burri, A, Chen, C, Corre, T, Coviello, A, D'Adamo, P, Davies, G, Deary, I, Ebrahim, S, Fauser, B, Ferreli, L, Folsom, A, Hankinson, S, Hass, M, Janssens, A, Karasik, D, Keyzer, J, Kiel, D, Lahti, J, Lai, S, Laisk, T, Laven, J, Liu, J, Lopez, L, Louwers, Y, Marongiu, M, Klaric, I, Masciullo, C, Melzer, D, Newman, A, Pare, G, Peeters, P, Pop, V, Raikkonen, K, Salumets, A, Stacey, S, Starr, J, Stathopoulou, M, Styrkarsdottir, U, Tenesa, A, Tryggvadottir, L, Tsui, K, van Dam, R, van Gils, C, van Nierop, P, Vink, J, Voorhuis, M, Widen, E, Wijnands-Van Gent, C, Yerges-Armstrong, L, Zgaga, L, Zygmunt, M, Buring, J, Crisponi, L, Demerath, E, Streeten, E, Murray, A, Visser, J, Lunetta, K, Elks, C, Cousminer, D, Koller, D, Lin, P, Smith, E, Warrington, N, Alavere, H, Berenson, G, Blackburn, H, Busonero, F, Chen, W, Couper, D, Easton, D, Foroud, T, Kilpelainen, T, Li, S, Murray, S, Ness, A, Northstone, K, Peacock, M, Pennell, C, Pharoah, P, Rafnar, T, Rice, J, Ring, S, Schork, N, Segre, A, Sovio, U, Srinivasan, S, Tammesoo, M, van Meurs, J, Young, L, Bierut, L, Econs, M, The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GLGC, The ICBP, The MAGIC Investigators, The MuTHER Consortium, The MIGen Consortium, The PAGE Consortium, The ReproGen Consortium, The GENIE Consortium, The International Endogene Consortium, Berndt, Sonja I, Justice, Anne E, Hyppönen, Elina Tuulikki, Epidemiology and Data Science, NCA - Neurobiology of mental health, and EMGO - Lifestyle, overweight and diabetes
Subjects: Male, LOCI, Genome-wide association study, Continental Population Groups/genetics, VARIANTS, Body Mass Index, Insulin Secretion, Insulin, Age Factor, Adiposity, ddc:616, Adipogenesis, Genetic Predisposition to Disease/genetics, Synapse, 3. Good health, Continental Population Group, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], GENOME-WIDE ASSOCIATIONPROVIDES INSIGHTSGLYCEMIC TRAITSLOCIMETAANALYSISVARIANTSINDIVIDUALSHIPPOCAMPALARCHITECTURETOPIRAMATE, ddc:500, Adipogenesis/genetics, Single Nucleotide/genetics, Age Factors, Continental Population Groups, Energy Metabolism, Europe, Female, Genetic Predisposition to Disease, Glutamic Acid, Humans, Obesity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Synapses, Genome-Wide Association Study, Multidisciplinary, genetics [Adiposity], Human, Socio-culturale, genetics [Energy Metabolism], ta3111, genetic, body mass index, obesity, SDG 3 - Good Health and Well-being, GLYCEMIC TRAITS, genetics [Continental Population Groups], Genetic variability, Polymorphism, GENOME-WIDE ASSOCIATION, genetics [Adipogenesis], METAANALYSIS, Genetic association, Adipogenesi, genetics [Quantitative Trait Loci], ta1184, metabolism [Glutamic Acid], ta1182, PATHWAYS, metabolism [Synapses], ta3121, medicine.disease, metabolism [Insulin], Adiposity/genetics, Clinical Medicine, Quantitative Trait Loci/genetics, Body mass index, HUMAN HEIGHT, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, Synapses/metabolism, Medizin, Obesity/genetics, Bioinformatics, genetic basis, Obesity/metabolism, genetics [Obesity], body mass index (BMI), genetics [Genetic Predisposition to Disease], ethnology [Europe], 2. Zero hunger, Genetics, ARCHITECTURE, Genetics of obesity, Medicine (all), Single Nucleotide, Polymorphism, Single Nucleotide/genetics, Insulin/metabolism/secretion, Glutamic Acid/metabolism, genetics [Polymorphism, Single Nucleotide], EXPRESSION, Insulin/metabolism, PROVIDES INSIGHTS, genetics [Racial Groups], Biology, Obesity/genetics/metabolism, Europe/ethnology, metabolism [Obesity], Mendelian randomization, medicine, Energy Metabolism/genetics, body mass, genetic analysis, obesity, Klinisk medicin
Abstract: Item does not contain fulltext Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 x 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for approximately 2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
Published: 2015

71. New genetic loci link adipose and insulin biology to body fat distribution

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Laura, Mencej-Bedrac, Simona, Helmer, Quinta, Nguyen, Tuan V, Nogues, Xavier, Patel, Millan S, Prezelj, Janez, Rose, Lynda M, Scollen, Serena, Siggeirsdottir, Kristin, Smith, Albert V, Svensson, Olle, Trompet, Stella, Hillege, Hans L, Trummer, Olivia, van Schoor, Natasja M, Woo, Jean, Zhu, Kun, Balcells, Susana, Brandi, Maria Luisa, Buckley, Brendan M, Cheng, Sulin, Christiansen, Claus, Cooper, Cyrus, Holmen, Oddgeir, Dedoussis, George, Ford, Ian, Frost, Morten, Goltzman, David, González-Macías, Jesús, Kähönen, Mika, Karlsson, Magnus, Khusnutdinova, Elza, Koh, Jung-Min, Kollia, Panagoula, Hunt, Steven C, Langdahl, Bente Lomholt, Leslie, William D, Lips, Paul, Ljunggren, Östen, Lorenc, Roman S, Marc, Janja, Mellström, Dan, Obermayer-Pietsch, Barbara, Olmos, José M, Pettersson-Kymmer, Ulrika, Isaacs, Aaron, Reid, David M, Riancho, José A, Ridker, Paul M, Rousseau, François, Slagboom, P Eline, Tang, Nelson L S, Urreizti, Roser, Van Hul, Wim, Viikari, Jorma, Zarrabeitia, María T, Wu, 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S, North, Kari E, Forouhi, Nita G, Edkins, Sarah, Varga, Tibor V, Oksa, Heikki, Antonella, Mulas, Moffatt, Miriam F, Kong, Augustine, Herder, Christian, Antti, Jula, Small, Kerrin, Miljkovic, Iva, Atalay, Mustafa, Kiess, Wieland, Murabito, Joanne M, Smit, Johannes H, Campbell, Susan, Fowkes, Gerard R, Nicholson, George, Kovacs, Peter, Zemunik, Tatijana, Basart, Hanneke V, Rathmann, Wolfgang, Maerz, Winfried, Peters, Annette, Province, Michael A, Hastie, Nicholas D, Olsson, Christian, Stumvoll, Michael, Waterworth, Dawn M, Watanabe, Richard M, de Geus, Eco J C, Penninx, Brenda W, Perry, John Rb, Reinmaa, Eva, Dedoussis, George V, Kutalik, Zoltán, Toenjes, Anke, Peyser, Patricia A, Körner, Antje, Keinanen-Kiukaanniemi, Sirkka M, Schadt, Eric E, Saaristo, Timo E, Dupuis, Josée, Sattar, Naveed, Cucca, Francesco, Balkau, Beverley, Froguel, Philippe, Jarvelin, Marjo-Riitta, Bouatia-Naji, Nabila, Stolk, Lisette, Meigs, James B, Ahmadi, Kourosh R, Ainali, Chrysanthi, Barrett, Amy, Vallejo, Edgar E, Bataille, Veronique, Bell, Jordana T, Buil, Alfonso, Dermitzakis, Emmanouil T, Dimas, Antigone S, Durbin, Richard, Glass, Daniel, Hassanali, Neelam, Westra, Harm-Jan, Ingle, Catherine, Knowles, David, Krestyaninova, Maria, Lowe, Christopher E, Meduri, Eshwar, di Meglio, Paola, Montgomery, Stephen B, Nestle, Frank O, Nica, Alexandra C, Nisbet, James, O'Rahilly, Stephen, Parts, Leopold, Potter, Simon, Sekowska, Magdalena, Shin, So-Youn, Consortium, ADIPOGen, Small, Kerrin S, Surdulescu, Gabriela, Travers, Mary E, Tsaprouni, Loukia, Tsoka, Sophia, Wilk, Alicja, Yang, Tsun-Po, Consortium, CARDIOGRAMplusC4D, Matise, Tara, Buyske, Steve, Higashio, Julia, Williams, Rasheeda, Nato, Andrew, Ambite, Jose Luis, Deelman, Ewa, Manolio, Teri, Hindorff, Lucia, Consortium, CKDGen, Heiss, Gerardo, Taylor, Kira, Franceschini, Nora, Avery, Christy, Graff, Misa, Lin, Danyu, Quibrera, Miguel, Cochran, Barbara, Kao, Linda, Umans, Jason, Consortium, GEFOS, Cole, Shelley, MacCluer, Jean, Person, 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P., Esko, T., Fall, T., Chen, H., Robertson, N., Rybin, D., Chines, PS., Song, K., An, P., Marullo, L., Jansen, H., Oldehinkel, AJ., North, KE., Forouhi, NG., Edkins, S., Varga, TV., Oksa, H., Antonella, M., Kong, A., Herder, C., Antti, J., Miljkovic, I., Atalay, M., Kiess, W., James, AL., Smit, JH., Campbell, S., Fowkes, GR., Basart, HV., Rathmann, W., Maerz, W., Province, MA., Watanabe, RM., de Geus EJ., Penninx, BW., Oostra, B., Toenjes, A., Peyser, PA., Körner, A., Keinanen-Kiukaanniemi, SM., Saaristo, TE., Boomsma, D., Cucca, F., Balkau, B., Froguel, P., Jarvelin, MR., Bouatia-Naji, N., Ahmadi, KR., Ainali, C., Barrett, A., Bataille, V., Bell, JT., Buil, A., Dermitzakis, ET., Dimas, AS., Durbin, R., Glass, D., Hassanali, N., Hedman£££Åsa K£££ ÅK., Ingle, C., Keildson, S., Knowles, D., Krestyaninova, M., Lowe, CE., Meduri, E., di Meglio, P., Min, JL., Montgomery, SB., Nestle, FO., Nica, AC., Nisbet, J., O'Rahilly, S., Parts, L., Potter, S., Sekowska, M., Shin, SY., Small, KS., 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Zgaga, L., Zygmunt, M., Arnold, AM., Buring, JE., Crisponi, L., Demerath, EW., Hunter, DJ., Schlessinger, D., Murray, A., Murabito, JM., Visser, JA., Lunetta, KL., Elks, CE., Cousminer, DL., Feenstra, B., Lin, P., van Wingerden SW., Smith, EN., Warrington, NM., Alavere, H., Barroso, I., Berenson, GS., Blackburn, H., Busonero, F., Chen, W., Couper, D., Easton, DF., Foroud, T., Geller, F., Hernandez, DG., Kilpeläinen, TO., Li, S., Melbye, M., Murray, JC., Murray, SS., Nelis, M., Ness, AR., Northstone, K., Pennell, CE., Pharoah, P., Rafnar, T., Rice, JP., Ring, SM., Schork, NJ., Segrè, AV., Sovio, U., Srinivasan, SR., Tammesoo, ML., Tyrer, J., Weedon, MN., Wichmann, H., Young, L., Zhuang, WV., Bierut, LJ., Boyd, HA., Department of Clinical Sciences, Lund University [Lund], Genetic Epidemiology and Clinical Research Group, Umea University Hospital, Department of Odontology, Umeå University, Signalisation et Transports Ioniques Membranaires (STIM), Université de Poitiers-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS), Department of Medical Sciences, Center for Biological Sequence Analysis [Lyngby], Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Laboratory of Image Science and Technology [Nanjing] (LIST), Southeast University [Jiangsu]-School of Computer Science and Engineering, Limnology, Ecology, Estonian Genome and Medicine, University of Tartu, Institute of Molecular and Cell Biology, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], Department of Medical Genetics, Université de Lausanne = University of Lausanne (UNIL), Institute of Medical Informatics, Biometry and Epidemiology, Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Centre d'Immunologie de Marseille - Luminy (CIML), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Genetic Epidemiology Unit, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Space Sciences Laboratory [Berkeley] (SSL), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Department of Biostatistics and Center for Statistical Genetics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Division of Statistical Genomics, Washington University School of Medicine, King‘s College London, Department of Medicine, University of Eastern Finland-Kuopio University Hospital, Molecular Genetics Section, University of Groningen [Groningen]-University Medical Centre Groningen, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze, Department of Pharmacy Sciences, Creighton University Medical Center, Medical Department III, Universität Leipzig, Foie, métabolismes et cancer, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Department of Epidemiology, Erasmus Medical Centre, Netherlands Genomics Initiative (NGI), Netherlands Genomics Initiative, Institute of Epidemiology [Neuherberg] (EPI), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Department of Public Health and Clinical Medicine, Medstar Research Institute, Genetics and Pathology, Finnish Institute of Occupational Health, Epidemiology, University Medical Centre Groningen, Departments of Microbiology & Molecular Genetics and Molecular Biology & Biochemistry, University of California [Irvine] (UC Irvine), Department of Odontology, Cariology, Institute of Human Genetics, Helmholtz Zentrum München = German Research Center for Environmental Health, Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Division of Cardiology, Geneva University Hospital (HUG), Department of Psychiatry and Psychotherapy, Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Physics, Indian Institute of Technology Kanpur (IIT Kanpur), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Department of Genomics, Life and Brain Center, Universität Bonn = University of Bonn, Anaesthesia and Intensive care, Royal Aberdeen Childrens Hospital, UCL Institute of neurology, UCL Institute of Neurology, Human Genetics, The Wellcome Trust Sanger Institute [Cambridge], 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(BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Endocrinology and Metabolism, The Churchill Hospital-Oxford Centre for Diabetes, Landsteiner Laboratory, Clinical Haematology, Other departments, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Lund University Diabetes Centre-Lund University [Lund], Université de Tours-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers, Technical University of Denmark [Lyngby] (DTU), Université de Lausanne (UNIL), Universität Duisburg-Essen [Essen], Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), University of California [Berkeley], University of California-University of California, Génomique Intégrative et Modélisation des Maladies Métaboliques (EGID), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), Universität Leipzig [Leipzig], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), University of California [Irvine] (UCI), German Research Center for Environmental Health, University of Bonn, Czech Academy of Sciences [Prague] (ASCR), Yale University School of Medicine, University of Oxford [Oxford], German Research Center for Environmental Health-Helmholtz-Zentrum München (HZM), Laval University, Laval University [Québec], Turku University Hospital, Lausanne university hospital, Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Institut de biologie de Lille - IBL (IBLI), Université de Lille, Sciences et Technologies-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), University of Helsinki-University of Helsinki, Helmholtz-Zentrum München (HZM), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), Internal Medicine, Child and Adolescent Psychiatry / Psychology, Clinical Genetics, Medical Informatics, Obstetrics & Gynecology, Lund University [Lund]-Lund University Diabetes Centre, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institute of Medicine-University of Gothenburg (GU), Signalisation et Transports Ioniques Membranaires ( STIM ), Université de Poitiers-Centre National de la Recherche Scientifique ( CNRS ), Technical University of Denmark [Lyngby] ( DTU ), Laboratory of Image Science and Technology [Nanjing] ( LIST ), Department of Medical Epidemiology and Biostatistics ( MEB ), University of Lausanne, Centre d'Immunologie de Marseille - Luminy ( CIML ), Aix Marseille Université ( AMU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Erasmus MC, Space Sciences Laboratory [Berkeley] ( SSL ), Génomique Intégrative et Modélisation des Maladies Métaboliques ( EGID ), Université de Lille-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Pasteur de Lille, Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP ) -Centre National de la Recherche Scientifique ( CNRS ) -Centre Hospitalier Régional Universitaire [Lille] ( CHRU Lille ), University of Leipzig, Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Institute of Epidemiology [Neuherberg] ( EPI ), University of California [Irvine] ( UCI ), Génétique des maladies multifactorielles ( GMM ), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), Geneva University Hospital ( HUG ), Bonn Universität [Bonn], Indian Institute of Technology Kanpur ( IIT Kanpur ), The University of North Carolina at Chapel Hill, Université de Bonn, Wellcome Trust Sanger Institute, Harvard University School of Public Health, Czech Academy of Sciences [Prague] ( ASCR ), deCODE genetics, University of Groningen [Groningen]-University Medical Center Groningen-Beatrix Children's Hospital-Groningen Research Institute for Asthma and COPD, Yale School of Medicine, National Heart and Lung Institute ( NHLI ), Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université de Lille, Droit et Santé, University Medical Center Groningen, University of Cambridge [UK] ( CAM ), Wellcome Trust Centre for Human Genetics, University of Pisa [Pisa], University of Cambridge [UK] ( CAM ) -Institute of Metabolic Science, German Research Center for Environmental Health-Helmholtz-Zentrum München ( HZM ), University of Otago, University of Greifswald, University College of London [London] ( UCL ), National Institute for Health and Welfare, Queen's University [Belfast] ( QUB ), University of Hawaii at Manoa ( UHM ), University of Gothenburg ( GU ) -Institute of Medicine, Recherches en Psychopathologie, nouveaux symptômes et lien social ( EA 4050 ), Université de Poitiers-Université de Brest ( UBO ) -Université Catholique de l'Ouest-Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ), Institut de biologie de Lille - IBL ( IBLI ), Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP ) -Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), University Medicine Greifswald,-HELIOS Hospital Stralsund, Finland Institute for Molecular Medicine ( FIMM ), Georgia Prevention Institute, Netherlands Consortium for Healthy Aging, Helmholtz-Zentrum München ( HZM ), National Institutes of Health ( NIH ) -National Cancer Institute ( NIH ), Massachusetts General Hospital, Children's Hospital, Boston, Broad Institute, Cambridge, MA, The University of North Carolina at Chapel Hill-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, Shungin D, Winkler TW, Adipogen, Consortium, Cardiogramplusc4d, Consortium, Ckdgen, Consortium, Gefos, Consortium, Genie, Consortium, Glgc, Icbp, International, Endogene Consortium, Lifelines, Cohort Study, Magic, Investigator, Muther, Consortium, Consortium, Page, ReproGen Consortium, Amouyel P, D'Adamo, ADAMO PIO, Gasparini, Paolo, Shungin, Dmitry, Winkler, Thomas W, Croteau-Chonka, Damien C, Ferreira, Teresa, Hypponen, Elina, Mohlke, Karen L, ADIPOGEN Consortium, Int Endogene Consortium, Lee Kong Chian School of Medicine (LKCMedicine), Epidemiologie, RS: CARIM - R3.02 - Hypertension and target organ damage, Université de Tours-Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Lifestyle, Overweight and Diabetes, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Research Institute for Asthma and COPD (GRIAC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Center for Liver, Digestive and Metabolic Diseases (CLDM), Stem Cell Aging Leukemia and Lymphoma (SALL), Shungin, D, Winkler, T, Croteau Chonka, D, Ferreira, T, Locke, A, Mägi, R, Strawbridge, R, Pers, T, Fischer, K, Justice, A, Workalemahu, T, Wu, J, Buchkovich, M, Heard Costa, N, Roman, T, Drong, A, Song, C, Gustafsson, S, Day, F, Esko, T, Fall, T, Kutalik, Z, Luan, J, Randall, J, Scherag, A, Vedantam, S, Wood, A, Chen, J, Fehrmann, R, Karjalainen, J, Kahali, B, Liu, C, Schmidt, E, Absher, D, Amin, N, Anderson, D, Beekman, M, Bragg Gresham, J, Buyske, S, Demirkan, A, Ehret, G, Feitosa, M, Goel, A, Jackson, A, Johnson, T, Kleber, M, Kristiansson, K, Mangino, M, Leach, I, Medina Gomez, C, Palmer, C, Pasko, D, Pechlivanis, S, Peters, M, Prokopenko, I, Stanca'Kova', A, Sung, Y, Tanaka, T, Teumer, A, Van Vliet Ostaptchouk, J, Yengo, L, Zhang, W, Albrecht, E, Ärnlöv, J, Arscott, G, Bandinelli, S, Barrett, A, Bellis, C, Bennett, A, Berne, C, Blüher, M, Böhringer, S, Bonnet, F, Böttcher, Y, Bruinenberg, M, Carba, D, Caspersen, I, Clarke, R, Daw, E, Deelen, J, Deelman, E, Delgado, G, Doney, A, Eklund, N, Erdos, M, Estrada, K, Eury, E, Friedrich, N, Garcia, M, Giedraitis, V, Gigante, B, Go, A, Golay, A, Grallert, H, Grammer, T, Gräsler, J, Grewal, J, Groves, C, Haller, T, Hallmans, G, Hartman, C, Hassinen, M, Hayward, C, Heikkilä, K, Herzig, K, Helmer, Q, Hillege, H, Holmen, O, Hunt, S, Isaacs, A, Ittermann, T, James, A, Johansson, I, Juliusdottir, T, Kalafati, I, Kinnunen, L, Koenig, W, Kooner, I, Kratzer, W, Lamina, C, Leander, K, Lee, N, Lichtner, P, Lind, L, Lindström, J, Lobbens, S, Lorentzon, M, Mach, F, Magnusson, P, Mahajan, A, Mcardle, W, Menni, C, Merger, S, Mihailov, E, Milani, L, Mills, R, Moayyeri, A, Monda, K, Mooijaart, S, Mühleisen, T, Mulas, A, Müller, G, Müller Nurasyid, M, Nagaraja, R, Nalls, M, Narisu, N, Glorioso, N, Nolte, I, Olden, M, Rayner, N, Renstrom, F, Ried, J, Robertson, N, Rose, L, Sanna, S, Scharnagl, H, Scholtens, S, Sennblad, B, Seufferlein, T, Sitlani, C, Smith, A, Stirrups, K, Stringham, H, Sundström, J, Swertz, M, Swift, A, Syvänen, A, Tayo, B, Thorand, B, Thorleifsson, G, Tomaschitz, A, Troffa, C, Van Oort, F, Verweij, N, Vonk, J, Waite, L, Wennauer, R, Wilsgaard, T, Wojczynski, M, Wong, A, Zhang, Q, Zhao, J, Brennan, E, Choi, M, Eriksson, P, Folkersen, L, Franco Cereceda, A, Gharavi, A, Hedman, A, Hivert, M, Huang, J, Kanoni, S, Karpe, F, Keildson, S, Kiryluk, K, Liang, L, Lifton, R, Ma, B, Mcknight, A, Mcpherson, R, Metspalu, A, Min, J, Moffatt, M, Montgomery, G, Murabito, J, Nicholson, G, Nyholt, D, Olsson, C, Perry, J, Reinmaa, E, Salem, R, Sandholm, N, Schadt, E, Scott, R, Stolk, L, Vallejo, E, Westra, H, Zondervan, K, Amouyel, P, Arveiler, D, Bakker, S, Beilby, J, Bergman, R, Blangero, J, Brown, M, Burnier, M, Campbell, H, Chakravarti, A, Chines, P, Claudi Boehm, S, Collins, F, Crawford, D, Danesh, J, De Faire, U, De Geus, E, Dörr, M, Erbel, R, Eriksson, J, Farrall, M, Ferrannini, E, Ferrières, J, Forouhi, N, Forrester, T, Franco, O, Gansevoort, R, Gieger, C, Gudnason, V, Haiman, C, Harris, T, Hattersley, A, Heliövaara, M, Hicks, A, Hingorani, A, Hoffmann, W, Hofman, A, Homuth, G, Humphries, S, Hyppönen, E, Illig, T, Jarvelin, M, Johansen, B, Jousilahti, P, Jula, A, Kaprio, J, Kee, F, Keinanen Kiukaanniemi, S, Kooner, J, Kooperberg, C, Kovacs, P, Kraja, A, Kumari, M, Kuulasmaa, K, Kuusisto, J, Lakka, T, Langenberg, C, Le Marchand, L, Lehtimäki, T, Lyssenko, V, Männistö, S, Marette, A, Matise, T, Mckenzie, C, Mcknight, B, Musk, A, Möhlenkamp, S, Morris, A, Nelis, M, Ohlsson, C, Oldehinkel, A, Ong, K, Palmer, L, Penninx, B, Peters, A, Pramstaller, P, Raitakari, O, Rankinen, T, Rao, D, Rice, T, Ridker, P, Ritchie, M, Rudan, I, Salomaa, V, Samani, N, Saramies, J, Sarzynski, M, Schwarz, P, Shuldiner, A, Staessen, J, Steinthorsdottir, V, Stolk, R, Strauch, K, Tönjes, A, Tremblay, A, Tremoli, E, Vohl, M, Völker, U, Vollenweider, P, Wilson, J, Witteman, J, Adair, L, Bochud, M, Boehm, B, Bornstein, S, Bouchard, C, Cauchi, S, Caulfield, M, Chambers, J, Chasman, D, Cooper, R, Dedoussis, G, Ferrucci, L, Froguel, P, Grabe, H, Hamsten, A, Hui, J, Hveem, K, Jöckel, K, Kivimaki, M, Kuh, D, Laakso, M, Liu, Y, März, W, Munroe, P, Njolstad, I, Oostra, B, Pedersen, N, Perola, M, Pe'Russe, L, Peters, U, Power, C, Quertermous, T, Rauramaa, R, Rivadeneira, F, Saaristo, T, Saleheen, D, Sinisalo, J, Slagboom, P, Snieder, H, Spector, T, Thorsteinsdottir, U, Stumvoll, M, Tuomilehto, J, Uitterlinden, A, Uusitupa, M, Van Der Harst, P, Veronesi, G, Walker, M, Wareham, N, Watkins, H, Wichmann, H, Abecasis, G, Assimes, T, Berndt, S, Boehnke, M, Borecki, I, Deloukas, P, Franke, L, Frayling, T, Groop, L, Hunter, D, Kaplan, R, O'Connell, J, Qi, L, Schlessinger, D, Strachan, D, Stefansson, K, Van Duijn, C, Willer, C, Visscher, P, Yang, J, Hirschhorn, J, Zillikens, M, Mccarthy, M, Speliotes, E, North, K, Fox, C, Barroso, I, Franks, P, Ingelsson, E, Heid, I, Loos, R, Cupples, L, Lindgren, C, Mohlke, K, Dastani, Z, Timpson, N, Yuan, X, Henneman, P, Kizer, J, Lyytikainen, L, Fuchsberger, C, Small, K, Coassin, S, Lohman, K, Pankow, J, Uh, H, Wu, Y, Bidulescu, A, Rasmussen Torvik, L, Greenwood, C, Ladouceur, M, Grimsby, J, Manning, A, Mooser, V, Kapur, K, Frants, R, Willemsvan vanDijk, K, Willems, S, Psaty, B, Tracy, R, Brody, J, Chen, I, Viikari, J, Kähönen, M, Evans, D, St Pourcain, B, Sattar, N, Carlson, O, Egan, J, van Heemst, D, Kedenko, L, Nuotio, M, Loo, B, Kanaya, A, Haun, M, Klopp, N, Katsareli, E, Couper, D, Duncan, B, Kloppenburg, M, Borja, J, Musani, S, Guo, X, Semple, R, Teslovich, T, Allison, M, Redline, S, Buxbaum, S, Meulenbelt, I, Ballantyne, C, Hu, F, Paulweber, B, Florez, J, Smith, G, Siscovick, D, Kronenberg, F, van Duijn, C, Waterworth, D, Meigs, J, Dupuis, J, Richards, J, Willenborg, C, Thompson, J, Erdmann, J, Goldstein, B, König, I, Cazier, J, Johansson, Å, Hall, A, Lee, J, Grundberg, E, Havulinna, A, Ho, W, Hopewell, J, Eriksson, N, Lundmark, P, Lyytikäinen, L, Rafelt, S, Tikkanen, E, Van Zuydam, N, Voight, B, Ziegler, A, Altshuler, D, Balmforth, A, Braund, P, Burgdorf, C, Cox, D, Dimitriou, M, Do, R, El Mokhtari, N, Fontanillas, P, Hager, J, Han, B, Kang, H, Kessler, T, Knowles, J, Kolovou, G, Langford, C, Lokki, M, Lundmark, A, Meisinger, C, Melander, O, Maouche, S, Nikus, K, Peden, J, Rasheed, A, Rosinger, S, Rubin, D, Rumpf, M, Schäfer, A, Sivananthan, M, Stewart, A, Tan, S, Thorgeirsson, G, van der Schoot, C, Wagner, P, Wells, G, Wild, P, Yang, T, Basart, H, Boerwinkle, E, Brambilla, P, Cambien, F, Cupples, A, de Faire, U, Dehghan, A, Diemert, P, Epstein, S, Evans, A, Ferrario, M, Gauguier, D, Goodall, A, Hazen, S, Holm, H, Iribarren, C, Jang, Y, Kim, H, Laaksonen, R, Ouwehand, W, Parish, S, Park, J, Rader, D, Shah, S, Stark, K, Trégouët, D, Virtamo, J, Wallentin, L, Zimmermann, M, Nieminen, M, Hengstenberg, C, Sandhu, M, Pastinen, T, Hovingh, G, Zalloua, P, Siegbahn, A, Schreiber, S, Ripatti, S, Blankenberg, S, O'Donnell, C, Reilly, M, Collins, R, Kathiresan, S, Roberts, R, Schunkert, H, Pattaro, C, Köttgen, A, Garnaas, M, Böger, C, Chen, M, Tin, A, Taliun, D, Li, M, Gao, X, Gorski, M, Yang, Q, Hundertmark, C, Foster, M, O'Seaghdha, C, Glazer, N, Struchalin, M, Li, G, Johnson, A, Gierman, H, Hwang, S, Atkinson, E, Cornelis, M, Chouraki, V, Holliday, E, Sorice, R, Deshmukh, H, Ulivi, S, Chu, A, Murgia, F, Trompet, S, Imboden, M, Kollerits, B, Pistis, G, Launer, L, Aspelund, T, Eiriksdottir, G, Mitchell, B, Schmidt, H, Cavalieri, M, Rao, M, de Andrade, M, Turner, S, Ding, J, Andrews, J, Freedman, B, Döring, A, Kolcic, I, Zemunik, T, Boban, M, Minelli, C, Wheeler, H, Igl, W, Zaboli, G, Wild, S, Wright, A, Ellinghaus, D, Nöthlings, U, Jacobs, G, Biffar, R, Endlich, K, Ernst, F, Kroemer, H, Nauck, M, Stracke, S, Völzke, H, Aulchenko, Y, Polasek, O, Hastie, N, Vitart, V, Helmer, C, Wang, J, Ruggiero, D, Bergmann, S, Nikopensius, T, Province, M, Ketkar, S, Colhoun, H, Robino, A, Giulianini, F, Krämer, B, Portas, L, Ford, I, Buckley, B, Adam, M, Thun, G, Sala, C, Metzger, M, Mitchell, P, Ciullo, M, Kim, S, Gasparini, P, Pirastu, M, Jukema, J, Probst Hensch, N, Toniolo, D, Coresh, J, Schmidt, R, Kardia, S, Curhan, G, Gyllensten, U, Franke, A, Rettig, R, Parsa, A, Goessling, W, Kao, W, de Boer, I, Peralta, C, Akylbekova, E, Kramer, H, van der Harst, P, Arking, D, Franceschini, N, Hernandez, D, Townsend, R, Lumley, T, Kestenbaum, B, Haritunians, T, Waeber, G, Lu, X, Leak, T, Aasarød, K, Skorpen, F, Baumert, J, Devuyst, O, Mychaleckyj, J, Hallan, S, Navis, G, Shlipak, M, Bull, S, Paterson, A, Rotter, J, Beckmann, J, Dreisbach, A, Styrkarsdottir, U, Evangelou, E, Hsu, Y, Duncan, E, Ntzani, E, Oei, L, Albagha, O, Kemp, J, Koller, D, Minster, R, Vandenput, L, Willner, D, Xiao, S, Yerges Armstrong, L, Zheng, H, Alonso, N, Kammerer, C, Kaptoge, S, Leo, P, Wilson, S, Aalto, V, Alen, M, Aragaki, A, Center, J, Dailiana, Z, Duggan, D, Garcia Giralt, N, Giroux, S, Hocking, L, Husted, L, Jameson, K, Khusainova, R, Kim, G, Koromila, T, Kruk, M, Laaksonen, M, Lacroix, A, Lee, S, Leung, P, Lewis, J, Masi, L, Mencej Bedrac, S, Nguyen, T, Nogues, X, Patel, M, Prezelj, J, Scollen, S, Siggeirsdottir, K, Svensson, O, Trummer, O, van Schoor, N, Woo, J, Zhu, K, Balcells, S, Brandi, M, Cheng, S, Christiansen, C, Cooper, C, Frost, M, Goltzman, D, González Macías, J, Karlsson, M, Khusnutdinova, E, Koh, J, Kollia, P, Langdahl, B, Leslie, W, Lips, P, Ljunggren, Ö, Lorenc, R, Marc, J, Mellström, D, Obermayer Pietsch, B, Olmos, J, Pettersson Kymmer, U, Reid, D, Riancho, J, Rousseau, F, Tang, N, Urreizti, R, Van Hul, W, Zarrabeitia, M, Castano Betancourt, M, Herrera, L, Ingvarsson, T, Johannsdottir, H, Kwan, T, Li, R, Luben, R, Medina Gómez, C, Palsson, S, Reppe, S, Sigurdsson, G, van Meurs, J, Verlaan, D, Williams, F, Zhou, Y, Gautvik, K, Raychaudhuri, S, Cauley, J, Clark, G, Cummings, S, Danoy, P, Dennison, E, Eastell, R, Eisman, J, Jackson, R, Jones, G, Khaw, K, Mccloskey, E, Nandakumar, K, Peacock, M, Pols, H, Prince, R, Reid, I, Robbins, J, Sambrook, P, Sham, P, Tylavsky, F, Econs, M, Kung, A, Reeve, J, Streeten, E, Karasik, D, Ralston, S, Ioannidis, J, Kiel, D, Forsblom, C, Isakova, T, Mckay, G, Williams, W, Sadlier, D, Mäkinen, V, Swan, E, Boright, A, Ahlqvist, E, Keller, B, Huang, H, Ahola, A, Fagerholm, E, Gordin, D, Harjutsalo, V, He, B, Heikkilä, O, Hietala, K, Kytö, J, Lahermo, P, Lehto, M, Österholm, A, Parkkonen, M, Pitkäniemi, J, Rosengård Bärlund, M, Saraheimo, M, Sarti, C, Söderlund, J, Soro Paavonen, A, Syreeni, A, Thorn, L, Tikkanen, H, Tolonen, N, Tryggvason, K, Wadén, J, Gill, G, Prior, S, Guiducci, C, Mirel, D, Taylor, A, Hosseini, M, Parving, H, Rossing, P, Tarnow, L, Ladenvall, C, Alhenc Gelas, F, Lefebvre, P, Rigalleau, V, Roussel, R, Tregouet, D, Maestroni, A, Maestroni, S, Falhammar, H, Gu, T, Möllsten, A, Cimponeriu, D, Mihai, I, Mota, M, Mota, E, Serafinceanu, C, Stavarachi, M, Hanson, R, Nelson, R, Kretzler, M, Panduru, N, Gu, H, Brismar, K, Zerbini, G, Hadjadj, S, Marre, M, Lajer, M, Waggott, D, Savage, D, Bain, S, Martin, F, Godson, C, Groop, P, Maxwell, A, Sengupta, S, Peloso, G, Ganna, A, Mora, S, Chang, H, Den Hertog, H, Donnelly, L, Fraser, R, Freitag, D, Gurdasani, D, Kaakinen, M, Kettunen, J, Li, X, Montasser, M, Petersen, A, Saxena, R, Service, S, Sidore, C, Surakka, I, Van den Herik, E, Volcik, K, Asiki, G, Been, L, Bolton, J, Bonnycastle, L, Burnett, M, Cesana, G, Elliott, P, Eyjolfsson, G, Goodarzi, M, Gravito, M, Hartikainen, A, Hung, Y, Jones, M, Kaleebu, P, Kastelein, J, Kim, E, Komulainen, P, Lin, S, Nieminen, T, Nsubuga, R, Olafsson, I, Palotie, A, Papamarkou, T, Pomilla, C, Pouta, A, Ruokonen, A, Seeley, J, Silander, K, Stančáková, A, Tiret, L, van Pelt, L, Wainwright, N, Wijmenga, C, Willemsen, G, Young, E, Bennett, F, Boomsma, D, Bovet, P, Chen, Y, Feranil, A, Freimer, N, Hsiung, C, Järvelin, M, Kesäniemi, A, Koudstaal, P, Krauss, R, Kyvik, K, Martin, N, Meneton, P, Moilanen, L, Njølstad, I, Price, J, Sanghera, D, Sheu, W, Whitfield, J, Wolffenbuttel, B, Ordovas, J, Rich, S, Johnson, L, Larson, M, Levy, D, Newton Cheh, C, O'Reilly, P, Palmas, W, Rice, K, Snider, H, Tobin, M, Verwoert, G, Pihur, V, Heath, S, Sõber, S, Arora, P, Zhang, F, Lucas, G, Milaneschi, Y, Parker, A, Fava, C, Fox, E, Go, M, Sjögren, M, Vinay, D, Alexander, M, Tabara, Y, Shaw Hawkins, S, Whincup, P, Shi, G, Seielstad, M, Sim, X, Nguyen, K, Matullo, G, Gaunt, T, Onland Moret, N, Cooper, M, Platou, C, Org, E, Hardy, R, Dahgam, S, Palmen, J, Kuznetsova, T, Uiterwaal, C, Adeyemo, A, Ludwig, B, Tomaszewski, M, Tzoulaki, I, Palmer, N, Chang, Y, Steinle, N, Grobbee, D, Morrison, A, Najjar, S, Hadley, D, Connell, J, Day, I, Lawlor, D, Lawrence, R, Ongen, H, Li, Y, Young, J, Bis, J, Chaturvedi, N, Islam, M, Jafar, T, Kulkarni, S, Grässler, J, Howard, P, Guarrera, S, Ricceri, F, Emilsson, V, Plump, A, Weder, A, Sun, Y, Scott, L, Peltonen, L, Vartiainen, E, Brand, S, Wang, T, Burton, P, Artigas, M, Dong, Y, Wang, X, Zhu, H, Rudock, M, Heckbert, S, Smith, N, Wiggins, K, Doumatey, A, Shriner, D, Veldre, G, Viigimaa, M, Kinra, S, Prabhakaran, D, Tripathy, V, Langefeld, C, Rosengren, A, Thelle, D, Corsi, A, Singleton, A, Hilton, G, Salako, T, Iwai, N, Kita, Y, Ogihara, T, Ohkubo, T, Okamura, T, Ueshima, H, Umemura, S, Eyheramendy, S, Meitinger, T, Cho, Y, Scott, J, Sehmi, J, Hedblad, B, Nilsson, P, Stanèáková, A, Raffel, L, Yao, J, Schwartz, S, Ikram, M, Longstreth W., J, Mosley, T, Seshadri, S, Shrine, N, Wain, L, Morken, M, Laitinen, J, Zitting, P, Cooper, J, van Gilst, W, Janipalli, C, Mani, K, Yajnik, C, Mattace Raso, F, Lakatta, E, Orru, M, Scuteri, A, Ala Korpela, M, Kangas, A, Soininen, P, Tukiainen, T, Würtz, P, Ong, R, Galan, P, Hercberg, S, Lathrop, M, Zelenika, D, Zhai, G, Meschia, J, Sharma, P, Terzic, J, Kumar, M, Denniff, M, Zukowska Szczechowska, E, Wagenknecht, L, Fowkes, F, Charchar, F, Rotimi, C, Bots, M, Brand, E, Talmud, P, Nyberg, F, Laan, M, van der Schouw, Y, Casas, J, Vineis, P, Ganesh, S, Wong, T, Tai, E, Morris, R, Dominiczak, A, Marmot, M, Miki, T, Chandak, G, Zhu, X, Elosua, R, Soranzo, N, Sijbrands, E, Uda, M, Vasan, R, Anderson, C, Gordon, S, Guo, Q, Henders, A, Lambert, A, Kraft, P, Kennedy, S, Macgregor, S, Missmer, S, Painter, J, Roseman, F, Treloar, S, Wallace, L, Alizadeh, B, de Boer, R, Boezen, H, van der Klauw, M, Ormel, J, Postma, D, Rosmalen, J, Slaets, J, Lagou, V, Welch, R, Wheeler, E, Rehnberg, E, Lecoeur, C, Johnson, P, Hottenga, J, Salo, P, Bielak, L, Zhao, W, Horikoshi, M, Navarro, P, Chen, H, Rybin, D, Song, K, An, P, Marullo, L, Jansen, H, Edkins, S, Varga, T, Oksa, H, Antonella, M, Kong, A, Herder, C, Antti, J, Miljkovic, I, Atalay, M, Kiess, W, Smit, J, Campbell, S, Fowkes, G, Rathmann, W, Maerz, W, Watanabe, R, de Geus, E, Toenjes, A, Peyser, P, Körner, A, Cucca, F, Balkau, B, Bouatia Naji, N, Ahmadi, K, Ainali, C, Bataille, V, Bell, J, Buil, A, Dermitzakis, E, Dimas, A, Durbin, R, Glass, D, Hassanali, N, Hedman, Å, Ingle, C, Knowles, D, Krestyaninova, M, Lowe, C, Meduri, E, di Meglio, P, Montgomery, S, Nestle, F, Nica, A, Nisbet, J, O'Rahilly, S, Parts, L, Potter, S, Sekowska, M, Shin, S, Surdulescu, G, Travers, M, Tsaprouni, L, Tsoka, S, Wilk, A, Higashio, J, Williams, R, Nato, A, Ambite, J, Manolio, T, Hindorff, L, Heiss, G, Taylor, K, Avery, C, Graff, M, Lin, D, Quibrera, M, Cochran, B, Kao, L, Umans, J, Cole, S, Maccluer, J, Person, S, Gross, M, Fornage, M, Durda, P, Jenny, N, Patsy, B, Arnold, A, Buzkova, P, Haines, J, Murdock, D, Glenn, K, Brown Gentry, K, Thornton Wells, T, Dumitrescu, L, Jeff, J, Bush, W, Mitchell, S, Goodloe, R, Boston, J, Malinowski, J, Restrepo, N, Oetjens, M, Fowke, J, Zheng, W, Spencer, K, Pendergrass, S, Wilkens, L, Park, L, Tiirikainen, M, Kolonel, L, Lim, U, Cheng, I, Wang, H, Shohet, R, Stram, D, Henderson, B, Monroe, K, Schumacher, F, Anderson, G, Carlson, C, Prentice, R, Wu, C, Carty, C, Gong, J, Rosse, S, Young, A, Haessler, J, Kocarnik, J, Lin, Y, Kuller, L, He, C, Sulem, P, Barbalic, M, Broer, L, Byrne, E, Gudbjartsson, D, Mcardle, P, Porcu, E, van Wingerden, S, Zhuang, W, Lauc, L, Broekmans, F, Burri, A, Chanock, S, Chen, C, Corre, T, Coviello, A, D'Adamo, P, Davies, G, Deary, I, Ebrahim, S, Fauser, B, Ferreli, L, Folsom, A, Hall, P, Hankinson, S, Hass, M, Heath, A, Janssens, A, Keyzer, J, Lahti, J, Lai, S, Laisk, T, Laven, J, Liu, J, Lopez, L, Louwers, Y, Marongiu, M, Klaric, I, Masciullo, C, Medland, S, Melzer, D, Newman, A, Paré, G, Peeters, P, Pop, V, Räikkönen, K, Salumets, A, Smith, J, Stacey, S, Starr, J, Stathopoulou, M, Tenesa, A, Tryggvadottir, L, Tsui, K, van Dam, R, van Gils, C, van Nierop, P, Vink, J, Voorhuis, M, Wallaschofski, H, Widen, E, Wijnands van Gent, C, Zgaga, L, Zygmunt, M, Buring, J, Crisponi, L, Demerath, E, Murray, A, Visser, J, Lunetta, K, Elks, C, Cousminer, D, Feenstra, B, Lin, P, Smith, E, Warrington, N, Alavere, H, Berenson, G, Blackburn, H, Busonero, F, Chen, W, Easton, D, Foroud, T, Geller, F, Kilpeläinen, T, Li, S, Melbye, M, Murray, J, Murray, S, Ness, A, Northstone, K, Pennell, C, Pharoah, P, Rafnar, T, Rice, J, Ring, S, Schork, N, Segrè, A, Sovio, U, Srinivasan, S, Tammesoo, M, Tyrer, J, Weedon, M, Young, L, Bierut, L, Boyd, H, Psychiatry, NCA - Neurobiology of mental health, and EMGO - Lifestyle, overweight and diabetes
Subjects: Adipose Tissue/metabolism, Male, genetic association, subcutaneous fat, Transcription, Genetic, Adipocytes, Adipogenesis, Adipose Tissue, Age Factors, Body Mass Index, Continental Population Groups, Epigenesis, Genetic, Europe, Female, Genome, Human, Humans, Insulin, Insulin Resistance, Models, Biological, Neovascularization, Physiologic, Obesity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sex Characteristics, Waist-Hip Ratio, Body Fat Distribution, Genome-Wide Association Study, Multidisciplinary, Insulin Resistance/genetics, Genome-wide association study, Continental Population Groups/genetics, genetic analysis, heritability, gene cluster, Science::Biological sciences::Human anatomy and physiology [DRNTU], 0302 clinical medicine, high density lipoprotein cholesterol, Models, genetics [Insulin Resistance], histone modification, Age Factor, insulin receptor, 0303 health sciences, Adipocyte, Human/genetics, CARDIOGRAMplusC4D Consortium, ADIPOGENIC DIFFERENTIATION, genetic correlation, body fat, Continental Population Group, priority journal, 5 trisphosphate 3 phosphatase, GEFOS Consortium, meta analysis (topic), Science & Technology - Other Topics, ddc:500, transcription regulation, Adipogenesis/genetics, Single Nucleotide/genetics, Human, medicine.medical_specialty, Waist, phosphatidylinositol 3, European, ta3111, genetic regulation, Article, developmental biology, 03 medical and health sciences, MAGIC Investigators, transcription initiation site, SDG 3 - Good Health and Well-being, Genetic, genomics, GLYCEMIC TRAITS, genetics [Continental Population Groups], Polymorphism, GENOME-WIDE ASSOCIATION, Physiologic, genetics [Adipogenesis], Adipocytes/metabolism, Europe/ethnology, Genome, Human/genetics, Insulin/metabolism, Neovascularization, Physiologic/genetics, Obesity/genetics, Polymorphism, Single Nucleotide/genetics, Quantitative Trait Loci/genetics, Transcription, Genetic/genetics, Genetic/genetics, Adipogenesi, Science & Technology, adiponectin, [ SDV ] Life Sciences [q-bio], vasculotropin, genetics [Quantitative Trait Loci], ta1184, Racial Groups, ta1182, gene mapping, ta3121, triacylglycerol blood level, medicine.disease, Biological, major clinical study, amino acid sequence, metabolism [Insulin], Endocrinology, metabolism [Adipocytes], genetic loci, insulin, body fat, GLGC, International Endogene Consortium, metabolism [Adipose Tissue], Body mass index, HUMAN HEIGHT, Epigenesis, LifeLines Cohort Study, ReproGen Consortium, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, tissue level, Physiologic/genetics, [SDV]Life Sciences [q-bio], Medizin, Adipose tissue, low density lipoprotein cholesterol, PAGE Consortium, COMMON SNPS, angiogenesis, Waist–hip ratio, genetics [Obesity], MESH: Adipocytes/metabolism Adipogenesis/genetics Adipose Tissue/metabolism* Age Factors Body Fat Distribution* Body Mass Index Continental Population Groups/genetics Epigenesis, Genetic Europe/ethnology Female Genome, Human/genetics Genome-Wide Association Study* Humans Insulin/metabolism* Insulin Resistance/genetics Male Models, Biological Neovascularization, Physiologic/genetics Obesity/genetics Polymorphism, Single Nucleotide/genetics Quantitative Trait Loci/genetics* Sex Characteristics Transcription, Genetic/genetics Waist-Hip Ratio, single nucleotide polymorphism, fat, genetic variability, molecular biology, body mass index (BMI), ethnology [Europe], peroxisome proliferator activated receptor, 2. Zero hunger, Genetics, Genome, Single Nucleotide, waist circumference, insulin, phosphatidylinositol 3,4,5 trisphosphate 3 phosphatase, triacylglycerol, vasculotropin, developmental biology, gene expression, genome, numerical model, adipocyte, adipose tissue, body fat distribution, body mass, female, gene locus, gene structure, hip circumference, human, insulin resistance, lipoprotein blood level, male, obesity, protein protein interaction, sex difference, waist hip ratio, Multidisciplinary Sciences, genetics [Transcription, Genetic], genetics [Polymorphism, Single Nucleotide], ADIPOGen Consortium, genetics [Neovascularization, Physiologic], Transcription, SUSCEPTIBILITY LOCI, General Science & Technology, ICBP, 030209 endocrinology & metabolism, Biology, adipocyte, MESH : Adipocytes/metabolism Adipogenesis/genetics Adipose Tissue/metabolism* Age Factors Body Fat Distribution* Body Mass Index Continental Population Groups/genetics Epigenesis, Genetic Europe/ethnology Female Genome, Human/genetics Genome-Wide Association Study* Humans Insulin/metabolism* Insulin Resistance/genetics Male Models, Biological Neovascularization, Physiologic/genetics Obesity/genetics Polymorphism, Single Nucleotide/genetics Quantitative Trait Loci/genetics* Sex Characteristics Transcription, Genetic/genetics Waist-Hip Ratio, MESENCHYMAL STEM-CELLS, GENIE Consortium, SEXUAL-DIMORPHISM, Insulin resistance, Internal medicine, medicine, genetics [Genome, Human], ABDOMINAL ADIPOSITY, Neovascularization, 030304 developmental biology, FALSE DISCOVERY, CKDGen Consortium, Sex Characteristic, MuTHER Consortium, numerical model
Abstract: Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P
Published: 2015

72. Executive summary of the KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease: known knowns and known unknowns.

Author: Levin A, Ahmed SB, Carrero JJ, Foster B, Francis A, Hall RK, Herrington WG, Hill G, Inker LA, Kazancıoğlu R, Lamb E, Lin P, Madero M, McIntyre N, Morrow K, Roberts G, Sabanayagam D, Schaeffner E, Shlipak M, Shroff R, Tangri N, Thanachayanont T, Ulasi I, Wong G, Yang CW, Zhang L, Robinson KA, Wilson L, Wilson RF, Kasiske BL, Cheung M, Earley A, and Stevens PE
Subjects: Humans, Renal Dialysis adverse effects, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic therapy, Renal Insufficiency, Chronic complications, Kidney Transplantation adverse effects, Nephrology
Abstract: The Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease (CKD) updates the KDIGO 2012 guideline and has been developed with patient partners, clinicians, and researchers around the world, using robust methodology. This update, based on a substantially broader base of evidence than has previously been available, reflects an exciting time in nephrology. New therapies and strategies have been tested in large and diverse populations that help to inform care; however, this guideline is not intended for people receiving dialysis nor those who have a kidney transplant. The document is sensitive to international considerations, CKD across the lifespan, and discusses special considerations in implementation. The scope includes chapters dedicated to the evaluation and risk assessment of people with CKD, management to delay CKD progression and its complications, medication management and drug stewardship in CKD, and optimal models of CKD care. Treatment approaches and actionable guideline recommendations are based on systematic reviews of relevant studies and appraisal of the quality of the evidence and the strength of recommendations which followed the "Grading of Recommendations Assessment, Development, and Evaluation" (GRADE) approach. The limitations of the evidence are discussed. The guideline also provides practice points, which serve to direct clinical care or activities for which a systematic review was not conducted, and it includes useful infographics and describes an important research agenda for the future. It targets a broad audience of people with CKD and their healthcare, while being mindful of implications for policy and payment., (Copyright © 2023 Kidney Disease: Improving Global Outcomes (KDIGO). Published by Elsevier Inc. All rights reserved.)
Published: 2024
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73. Association of Kidney Tubule Biomarkers With Cardiac Structure and Function in the Multiethnic Study of Atherosclerosis.

Author: Wettersten N, Katz R, Greenberg JH, Gutierrez OM, Lima JAC, Sarnak MJ, Schrauben S, Deo R, Bonventre J, Vasan RS, Kimmel PL, Shlipak M, and Ix JH
Subjects: Male, Humans, Middle Aged, Aged, Female, Receptors, Urokinase Plasminogen Activator, Stroke Volume, Albuminuria complications, Ventricular Function, Left, Kidney Tubules, Glomerular Filtration Rate, Inflammation, Biomarkers, Renal Insufficiency, Chronic complications, Cardiovascular Diseases, Atherosclerosis complications
Abstract: Markers of glomerular disease, estimated glomerular filtration rate (eGFR) and albuminuria, are associated with cardiac structural abnormalities and incident cardiovascular disease (CVD). We aimed to determine whether biomarkers of kidney tubule injury, function, and systemic inflammation are associated with cardiac structural abnormalities. Among 393 Multi-Ethnic Study of Atherosclerosis participants without diabetes, CVD, or chronic kidney disease, we assessed the association of 12 biomarkers of kidney tubule injury, function, and systemic inflammation with the left ventricular mass/volume ratio (LVmvr) and left ventricular ejection fraction (LVEF) on cardiac magnetic resonance imaging using linear regression. The average age was 60 ± 10 years; 48% were men; mean eGFR was 96±16 ml/min/1.73 m 2 ; mean LVmvr was 0.93±0.18 g/ml, and mean LVEF was 62±6%. Each twofold greater concentration of plasma soluble urokinase plasminogen activator receptor was associated with a 0.04 g/ml (95% confidence interval [CI] 0.01 to 0.08 g/ml) higher LVmvr and 2.1% (95% CI 0.6 to 3.5%) lower LVEF, independent of risk factors for CVD, eGFR, and albuminuria. Each twofold greater plasma monocyte chemoattractant protein 1 was associated with higher LVmvr with a similar coefficient to that of plasma soluble urokinase plasminogen activator receptor. Each twofold greater concentration of plasma chitinase-3-like protein 1 and urine alpha-1-microglobulin was associated with a 1.1% (95% CI 0.4 to 1.7%) and 1.2% (95% CI 0.2 to 2.2%) lower LVEF, respectively. In conclusion, abnormal kidney tubule health may lead to cardiac dysfunction above and beyond eGFR and albuminuria., Competing Interests: Disclosures Dr. Gutierrez receives grant funding and honoraria from Amgen and Akebia. He receives honoraria from AstraZeneca, Reata, and Ardelyx and serves on a Data Monitoring Committee for QED Therapeutics. Dr. Bonventre is cofounder and holds equity in Goldfinch Bio and Autonomous Medical Devices, is coinventor on KIM-1 patents assigned to Mass General Brigham, and has received consulting income and/or equity from Cadent, Renalytix, Sarepta, and Seagen and laboratory support from Kantum Pharma. He has equity in Pacific Biosciences, DxNow, and MediBeacon. Dr. Bonventre's interests were reviewed and are managed by BWH and MGB in accordance with their conflict-of-interest policies. Dr. Kimmel is a coeditor with Mark Rosenberg of Chronic Renal Disease Academic Press and a coeditor with Daniel Cukor and Scott D. Cohen of Psychosocial Aspects of Chronic Kidney Disease Academic Press. Dr. Shlipak is on advisory boards and receives honoraria from Bayer, Boehringer-Ingelheim, Astra-Zeneca. He receives grant support from Bayer. Dr. Ix has grant support from Baxter International. He is on advisory boards for Akebia, AstraZeneka, Ardelyx, Alpha Young, and Bayer. He serves on a Data and Safety Monitoring Board from Sanifit International. The remaining authors have no conflicts of interest to declare., (Published by Elsevier Inc.)
Published: 2023
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74. Associations between eGFR and albuminuria with right ventricular measures: the MESA-Right Ventricle study.

Author: Husain-Syed F, DiFrancesco MF, Deo R, Barr RG, Scialla JJ, Bluemke DA, Kronmal RA, Lima JAC, Praestgaard A, Tracy RP, Shlipak M, Kawut SM, and Kim JS
Abstract: Background: Chronic kidney disease (CKD) is associated with an increased risk of pulmonary hypertension, which may lead to right ventricular (RV) pressure overload and RV dysfunction. However, the presence of subclinical changes in RV structure or function in early CKD and the influence of these changes on mortality are not well studied. We hypothesized that early CKD, as indicated by elevated albuminuria or mild reductions in estimated glomerular filtration rate (eGFR), is associated with greater RV dilation and RV mass., Methods: We included 4063 participants (age 45-84 years) without baseline clinical cardiovascular disease from the Multi-Ethnic Study of Atherosclerosis. The associations of baseline creatinine-cystatin C-based eGFR and albuminuria with cardiac magnetic resonance-derived RV measures (2000-02) were examined cross-sectionally with linear regression models. Cox regression models were used to examine whether RV parameters modified the associations of eGFR and albuminuria with all-cause mortality., Results: Participants with reductions in eGFR primarily within the 60-89 mL/min/1.73 m 2 category had smaller RV end-diastolic and end-systolic volumes and stroke volume (all adjusted P -trends <.001) than those with eGFR ≥90 mL/min/1.73 m 2 , an association that was predominantly seen in participants with albuminuria below 30 mg/g creatinine. Albuminuria was more strongly associated with death among those with lower RV volumes ( P -values for interaction <.03)., Conclusions: Among community-dwelling adults, reductions in eGFR primarily within the normal range were associated with smaller RV volumes and the association of albuminuria with worse survival was stronger among those with smaller RV volumes. Further studies are needed to elucidate the underlying mechanistic pathways that link kidney measures and RV morphology., Competing Interests: J.S.K. receives grant support from the National Heart, Lung, and Blood Institute (NHLBI). All other authors have declared that no conflict of interests exists. The results presented in this paper have not been presented or published previously in whole or part nor in abstract form., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)
Published: 2023
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75. A Machine Learning Model for Predicting Mortality within 90 Days of Dialysis Initiation.

Author: Rankin S, Han L, Scherzer R, Tenney S, Keating M, Genberg K, Rahn M, Wilkins K, Shlipak M, and Estrella M
Subjects: Adult, Cohort Studies, Female, Humans, Male, Reproducibility of Results, Risk Assessment, Time Factors, Treatment Outcome, United States epidemiology, Kidney Failure, Chronic ethnology, Kidney Failure, Chronic mortality, Kidney Failure, Chronic therapy, Machine Learning, Models, Statistical, Renal Dialysis methods, Renal Dialysis statistics & numerical data
Abstract: Background: The first 90 days after dialysis initiation are associated with high morbidity and mortality in end-stage kidney disease (ESKD) patients. A machine learning-based tool for predicting mortality could inform patient-clinician shared decision making on whether to initiate dialysis or pursue medical management. We used the eXtreme Gradient Boosting (XGBoost) algorithm to predict mortality in the first 90 days after dialysis initiation in a nationally representative population from the United States Renal Data System., Methods: A cohort of adults initiating dialysis between 2008-2017 were studied for outcome of death within 90 days of dialysis initiation. The study dataset included 188 candidate predictors prognostic of early mortality that were known on or before the first day of dialysis and was partitioned into training (70%) and testing (30%) subsets. XGBoost modeling used a complete-case set and a dataset obtained from multiple imputation. Model performance was evaluated by c-statistics overall and stratified by subgroups of age, sex, race, and dialysis modality., Results: The analysis included 1,150,195 patients with ESKD, of whom 86,083 (8%) died in the first 90 days after dialysis initiation. The XGBoost models discriminated mortality risk in the nonimputed ( c =0.826, 95% CI, 0.823 to 0.828) and imputed ( c =0.827, 95% CI, 0.823 to 0.827) models and performed well across nearly every subgroup (race, age, sex, and dialysis modality) evaluated ( c >0.75). Across predicted risk thresholds of 10%-50%, higher risk thresholds showed declining sensitivity (0.69-0.04) with improving specificity (0.79-0.99); similarly, positive likelihood ratio was highest at the 40% threshold, whereas the negative likelihood ratio was lowest at the 10% threshold. After calibration using isotonic regression, the model accurately estimated the probability of mortality across all ranges of predicted risk., Conclusions: The XGBoost-based model developed in this study discriminated risk of early mortality after dialysis initiation with excellent calibration and performed well across key subgroups., Competing Interests: M. Estrella reports being an employee of the University of California, San Francisco, and San Francisco VA Health Care System; consultancy for Eiland & Bonnin (PC); research funding from Bayer, Inc., and Booz Allen Hamilton; honoraria from the American Kidney Fund, AstraZeneca, Boehringer Ingelheim, and the National Kidney Foundation; and other interests or relationships with American Journal of Kidney Diseases, CJASN, and the National Kidney Foundation. K. Genberg reports being an employee of Booz Allen Hamilton and IBM, and ownership interest in Booz Allen and IBM. L. Han reports being an employee of Booz Allen Hamilton. M. Keating reports being an employee of Booz Allen Hamilton; consultancy for Booz Allen Hamilton; and ownership interest in Booz Allen Hamilton and Kimbell Royalty Partners. M. Rahn reports being an employee of HHS/Office of the National Coordinator for Health IT, and an advisory or leadership role for the Office of the National Coordinator for Health IT. S. Rankin reports being an employee of Booz Allen Hamilton. R. Scherzer reports being an employee of UCSF, and an advisory or leadership role (editorial board) for CJASN, JAIDS, and Kidney360. M.G. Shlipak reports consultancy agreements with Cricket Health; Intercept Pharmaceuticals, University of Washington—Cardiovascular Health Study, and Veterans Medical; research funding from Bayer Pharmaceuticals; honoraria from AstraZeneca, Bayer, and Boeringer Ingelheim; being a scientific advisor for or membership of the American Journal of Kidney Disease, Circulation, and JASN; and being a board member of the Northern California Institute for Research and Education. S. Tenney reports being an employee of Booz Allen Hamilton. K.J. Wilkins reports an advisory or leadership role for the International Journal of Obesity (editorial board [unpaid]); and has previously made commitments to involve members of the following kidney patient/advocacy organizations in kidney research methods-focused scientific conferences or technical expert panels: American Association of Kidney Patients (via board member Jenny Kitsen) and Renal Support Network (via President and Founder Lori Hartwell); the only one to have taken place within last 24 months is Voice of the Patient (via founder Kevin Fowler)., (Copyright © 2022 by the American Society of Nephrology.)
Published: 2022
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76. Association of circulating cardiac biomarkers with electrocardiographic abnormalities in chronic kidney disease.

Author: Kula AJ, Katz R, Zelnick LR, Soliman E, Go A, Shlipak M, Deo R, Ky B, DeBoer I, Anderson A, Christenson R, Seliger SL, Defilippi C, Feldman HI, Wolf M, Kusek J, Shafi T, He J, and Bansal N
Subjects: Biomarkers, Cross-Sectional Studies, Humans, Natriuretic Peptide, Brain, Peptide Fragments, Atrial Fibrillation, Heart Failure, Renal Insufficiency, Chronic diagnosis
Abstract: Background: Among patients with chronic kidney disease (CKD), the circulating cardiac biomarkers soluble ST2 (SST2), galectin-3, growth differentiation factor-15 (GDF-15), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin-T (hsTnT) possibly reflect pathophysiologic processes and are associated with clinical cardiovascular disease. Whether these biomarkers are associated with electrocardiographic findings is not known. The aim of this study was to test the association between serum cardiac biomarkers and the presence of electrocardiographic changes potentially indicative of subclinical myocardial disease in patients with CKD., Methods: We performed a cross-sectional analysis using 3048 participants from the Chronic Renal Insufficiency Cohort (CRIC) without atrial fibrillation, atrioventricular block, bundle branch block or a pacemaker at the baseline visit. Using logistic regression, we tested the association of each of the five cardiac biomarkers with baseline electrocardiogram (ECG) findings: PR interval >200 ms, QRS interval >100 ms and a prolonged QTc interval. Models were adjusted for demographic variables, measures of kidney function, prevalent cardiovascular disease and cardiovascular risk factors., Results: In adjusted models, hsTnT levels associated with prolonged PR {odds ratio [OR] 1.23 [95% confidence interval (CI) 1.08-1.40]}, QRS [OR 1.28 (95% CI 1.16-1.42)] and QTc [OR 1.94 (95% CI 1.50-2.51)] intervals. NT-proBNP levels were associated with prolonged QRS [OR 1.11 (95% CI 1.06-1.16)] and QTc [OR 1.82 (95% CI 1.58-2.10)] intervals. SST2, galectin-3 and GDF-15 were not significantly associated with any of the ECG parameters., Conclusions: hsTnT and NT-proBNP were associated with ECG measures indicative of subclinical myocardial dysfunction. These results may support future research investigating the significance of myocardial ischemia and volume overload in the pathogenesis of dysfunctional myocardial conduction in CKD., (© The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)
Published: 2021
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77. Association of Urine Biomarkers of Kidney Tubule Injury and Dysfunction With Frailty Index and Cognitive Function in Persons With CKD in SPRINT.

Author: Miller LM, Rifkin D, Lee AK, Kurella Tamura M, Pajewski NM, Weiner DE, Al-Rousan T, Shlipak M, and Ix JH
Subjects: Aged, Aged, 80 and over, Biomarkers urine, Chemokine CCL2 urine, Cross-Sectional Studies, Female, Frailty diagnosis, Frailty epidemiology, Glomerular Filtration Rate physiology, Hepatitis A Virus Cellular Receptor 1 metabolism, Humans, Kidney Tubules pathology, Male, Middle Aged, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic epidemiology, Blood Pressure physiology, Cognition physiology, Frailty urine, Kidney Tubules injuries, Kidney Tubules metabolism, Renal Insufficiency, Chronic urine
Abstract: Rationale & Objective: The associations of the glomerular markers of kidney disease, estimated glomerular filtration rate (eGFR) and albuminuria, with frailty and cognition are well established. However, the relationship of kidney tubule injury and dysfunction with frailty and cognition is unknown., Study Design: Observational cross-sectional study., Setting & Participants: 2,253 participants with eGFR<60mL/min/1.73m 2 in the Systolic Blood Pressure Intervention Trial (SPRINT)., Exposure: Eight urine biomarkers: interleukin 18 (IL-18), kidney injury molecule 1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), chitinase-3-like protein 1 (YKL-40), monocyte chemoattractant protein 1 (MCP-1), α 1 -microglobulin (A1M), β 2 -microglobulin (B2M), and uromodulin (Umod)., Outcome: Frailty was measured using a previously validated frailty index (FI), categorized as fit (FI≤0.10), less fit (0.100.21). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA)., Analytical Approach: Associations between kidney tubule biomarkers with categorical FI were evaluated using multinomial logistic regression with the fit group as the reference. Cognitive function was evaluated using linear regression. Models were adjusted for demographic, behavioral, and clinical variables including eGFR and urine albumin., Results: Three of the 8 urine biomarkers of tubule injury and dysfunction were independently associated with FI. Each 2-fold higher level of urine KIM-1, a marker of tubule injury, was associated with a 1.22 (95% CI, 1.01-1.49) greater odds of being in the frail group. MCP-1, a marker of tubulointerstitial fibrosis, was associated with a 1.30 (95% CI, 1.04-1.64) greater odds of being in the frail group, and A1M, a marker of tubule reabsorptive capacity, was associated with a 1.48 (95% CI, 1.11-1.96) greater odds of being in the frail group. These associations were independent of confounders including eGFR and urine albumin, and were stronger than those of urine albumin with FI (1.15 [95% CI, 0.99-1.34]). Higher urine B2M, another marker of tubule reabsorptive capacity, was associated with worse cognitive scores at baseline (β: -0.09 [95% CI, -0.17 to-0.01]). Urine albumin was not associated with cognitive function., Limitations: Cross-sectional design, and FI may not be generalizable in other populations., Conclusions: Urine biomarkers of tubule injury, fibrosis, and proximal tubule reabsorptive capacity are variably associated with FI and worse cognition, independent of glomerular markers of kidney health. Future studies are needed to validate these results among other patient populations., (Published by Elsevier Inc.)
Published: 2021
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78. Kidney tubule health scores and their associations with incident CKD in women living with HIV.

Author: Ascher SB, Scherzer R, Estrella MM, Muiru AN, Jotwani VK, Grunfeld C, Shigenaga J, Spaulding KA, Ng DK, Gustafson D, Spence AB, Sharma A, Cohen MH, Parikh CR, Ix JH, and Shlipak MG
Subjects: Biomarkers, Female, Glomerular Filtration Rate, Humans, Kidney, Kidney Tubules injuries, Risk Factors, HIV Infections complications, Renal Insufficiency, Chronic epidemiology
Abstract: Objectives: Individual kidney tubule biomarkers are associated with chronic kidney disease (CKD) risk in people living with HIV (PLWH). Whether a combination of kidney biomarkers can be integrated into informative summary scores for PLWH is unknown., Methods: We measured eight urine biomarkers of kidney tubule health at two visits over a 3-year period in 647 women living with HIV in the Women's Interagency Health Study. We integrated biomarkers into factor scores using exploratory factor analysis. We evaluated associations between CKD risk factors and factor scores, and used generalized estimating equations to determine associations between factor scores and risk of incident CKD., Results: Factor analysis identified two unique factor scores: a tubule reabsorption score comprising alpha-1-microglobulin, beta-2-microglobulin and trefoil factor-3; and a tubule injury score comprising interleukin-18 and kidney injury molecule-1. We modelled the two factor scores in combination with urine epidermal growth factor (EGF) and urine albumin. Predominantly HIV-related CKD risk factors were independently associated with worsening tubule reabsorption scores and tubule injury scores. During a median follow-up of 7 years, 9.7% (63/647) developed CKD. In multivariable time-updated models that adjusted for other factor scores and biomarkers simultaneously, higher tubule reabsorption scores [risk ratio (RR) = 1.27, 95% confidence interval (CI): 1.01-1.59 per 1 SD higher time-updated score], higher tubule injury scores (RR = 1.36, 95% CI: 1.05-1.76), lower urine EGF (RR = 0.75, 95% CI: 0.64-0.87), and higher urine albumin (RR = 1.20, 95% CI: 1.02-1.40) were jointly associated with risk of incident CKD., Conclusions: We identified two novel and distinct dimensions of kidney tubule health that appear to quantify informative metrics of CKD risk in PLWH., (© 2021 British HIV Association.)
Published: 2021
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79. Kidney Function Following Left Ventricular Assist Device Implantation: An Observational Cohort Study.

Author: Wettersten N, Estrella M, Brambatti M, Horiuchi Y, Adler E, Pretorius V, Murray PT, Shlipak M, and Ix JH
Abstract: Rationale & Objective: Nearly half the patients with heart failure have chronic kidney disease. Implantation of a left ventricular assist device (LVAD) improves kidney function in some but not all patients, and lack of improvement is associated with worse outcomes. Preimplantation factors that predict change in kidney function after LVAD placement are not well described., Study Design: Single-center observational study., Setting & Participants: Consecutive patients undergoing LVAD implantation., Predictors: 48 diverse preimplantation variables including demographic, clinical, laboratory, hemodynamic, and echocardiographic variables., Outcomes: The primary outcome was change in estimated glomerular filtration rate (eGFR) at 1 month after implantation. Secondary outcomes included eGFR changes at 3, 6, and 12 months., Analytic Approach: Univariable and multivariable linear regression., Results: Among 131 patients, average age was 60 ± 13 years, 83% were men, 47% had pre-existing chronic kidney disease, and mean preimplantation eGFR was 57 ± 23 mL/min/1.73 m 2 . At 1-month following LVAD implantation, eGFR improved in 98 (75%) patients. Variables associated with 1-month increases in eGFR were younger age, absence of diabetes mellitus (DM), use of inotropes, lower implantation eGFR, and higher implantation serum urea nitrogen, alanine aminotransferase, bilirubin, and creatinine levels. In multivariable models, younger age (β = 7.14 mL/min/1.73 m 2 per SD; 95% CI, 3.17-11.10), lower eGFR (β = 7.72 mL/min/1.73 m 2 per SD; 95% CI, 3.10-12.34), and absence of DM (β = 10.36 mL/min/1.73 m 2 ; 95% CI, 2.99-17.74) were each independently associated with 1-month improvement in eGFR. Only younger age and lower eGFR were associated with improvements in eGFR at later months., Limitations: Single-center study. Loss to follow-up from heart transplantation and death over duration of study., Conclusions: Only younger age, lower eGFR, and absence of DM were associated with improvement in eGFR at 1 month. Thus, prediction of eGFR change at 1 month and beyond is limited by using preimplantation variables.
Published: 2021
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80. A systematic review and participant-level meta-analysis found little association of retinal microvascular caliber with reduced kidney function.

Author: Lye WK, Paterson E, Patterson CC, Maxwell AP, Binte Mohammed Abdul RB, Tai ES, Cheng CY, Kayama T, Yamashita H, Sarnak M, Shlipak M, Matsushita K, Mutlu U, Ikram MA, Klaver C, Kifley A, Mitchell P, Myers C, Klein BE, Klein R, Wong TY, Sabanayagam C, and McKay GJ
Subjects: Arterioles, Cross-Sectional Studies, Glomerular Filtration Rate, Humans, Risk Factors, Kidney, Retinal Vessels diagnostic imaging
Abstract: Previously, variation in retinal vascular caliber has been reported in association with chronic kidney disease (CKD) but findings remain inconsistent. To help clarify this we conducted individual participant data meta-analysis and aggregate data meta-analysis on summary estimates to evaluate cross-sectional associations between retinal vascular caliber and CKD. A systematic review was performed using Medline and EMBASE for articles published until October 2018. The aggregate analysis used a two-stage approach combining summary estimates from eleven studies (44,803 patients) while the individual participant analysis used a one-stage approach combining raw data from nine studies (33,222 patients). CKD stages 3-5 was defined as an estimated glomerular filtration rate under 60 mL/min/1.73m 2 . Retinal arteriolar and venular caliber (central retinal arteriolar and venular equivalent) were assessed from retinal photographs using computer-assisted methods. Logistic regression estimated relative risk of CKD stages 3-5 associated with a 20 μm decrease (approximately one standard deviation) in central retinal arteriolar and venular equivalent. Prevalence of CKD stages 3-5 was 11.2% of 33,222 and 11.3% of 44,803 patients in the individual participant and aggregate data analysis, respectively. No significant associations were detected in adjusted analyses between central retinal arteriolar and venular equivalent and CKD stages 3-5 in the aggregate analysis for central retinal arteriolar relative risk (0.98, 95% confidence interval 0.94-1.03); venular equivalent (0.99, 0.95-1.04) or individual participant central retinal arteriolar (0.99, 0.95-1.04) or venular equivalent (1.01, 0.97-1.05). Thus, meta-analysis provided little evidence to suggest that cross sectional direct measurements of retinal vascular caliber was associated with CKD stages 3-5 in the general population. Hence, meta-analyses of longitudinal studies evaluating the association between retinal parameters and CKD stages 3-5 may be warranted., (Copyright © 2020 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)
Published: 2021
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81. FGF23, Frailty, and Falls in SPRINT.

Author: Jovanovich A, Ginsberg C, You Z, Katz R, Ambrosius WT, Berlowitz D, Cheung AK, Cho M, Lee AK, Punzi H, Rehman S, Roumie C, Supiano MA, Wright CB, Shlipak M, Ix JH, and Chonchol M
Subjects: Aged, Biomarkers blood, Correlation of Data, Cross-Sectional Studies, Female, Fibroblast Growth Factor-23, Glomerular Filtration Rate, Humans, Male, Accidental Falls statistics & numerical data, Fibroblast Growth Factors blood, Frailty blood, Frailty epidemiology, Frailty etiology, Frailty physiopathology, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic complications, Renal Insufficiency, Chronic physiopathology
Abstract: Background/objectives: Chronic kidney disease (CKD) is associated with frailty. Fibroblast growth factor 23 (FGF23) is elevated in CKD and associated with frailty among non-CKD older adults and individuals with human immunodeficiency virus. Whether FGF23 is associated with frailty and falls in CKD is unknown., Design: Cross-sectional and longitudinal observational study., Setting: Systolic Blood Pressure Intervention Trial (SPRINT), a randomized trial evaluating standard (systolic blood pressure [SBP] <140 mm Hg) versus intensive (SBP <120 mm Hg) blood pressure lowering on cardiovascular and cognitive outcomes among older adults without diabetes mellitus., Participants: A total of 2,376 participants with CKD (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m 2 )., Measurements: The exposure variable was intact FGF23. We used multinomial logistic regression to determine the cross-sectional association of intact FGF23 with frailty and Cox proportional hazards analysis to determine the longitudinal association with incident falls. Models were adjusted for demographics, comorbidities, randomization group, antihypertensives, eGFR, mineral metabolism markers, and frailty., Results: After adjustment, the odds ratio for prevalent frailty versus non-frailty per twofold higher FGF23 was 1.34 (95% confidence interval [CI] = 1.01-1.77). FGF23 levels in the highest quartile versus the lowest quartile demonstrated more than a twofold increased fall risk (hazard ratio [HR] = 2.32; 95% CI = 1.26-4.26), and the HR per twofold higher FGF23 was 1.99 (95% CI = 1.48-2.68)., Conclusion: Among SPRINT participants with CKD, FGF23 was associated with prevalent frailty and falls., (© 2020 The American Geriatrics Society.)
Published: 2021
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82. Chronic kidney disease as a risk factor for peripheral nerve impairment in older adults: A longitudinal analysis of Health, Aging and Body Composition (Health ABC) study.

Author: Doshi S, Moorthi RN, Fried LF, Sarnak MJ, Satterfield S, Shlipak M, Lange-Maia BS, Newman AB, and Strotmeyer ES
Subjects: Aged, Aging, Female, Follow-Up Studies, Humans, Longitudinal Studies, Male, Neural Conduction physiology, Peripheral Nervous System Diseases diagnosis, Peripheral Nervous System Diseases etiology, Peripheral Nervous System Diseases physiopathology, Renal Insufficiency, Chronic complications, Renal Insufficiency, Chronic physiopathology, Risk Factors, Self Report statistics & numerical data, Sensory Thresholds physiology, White People, Peripheral Nerves physiopathology, Peripheral Nervous System Diseases epidemiology, Renal Insufficiency, Chronic epidemiology
Abstract: Introduction: Sensory and motor nerve deficits are prevalent in older adults and are associated with loss of functional independence. We hypothesize that chronic kidney disease predisposes to worsening sensorimotor nerve function over time., Materials and Methods: Participants were from the Health, Aging and Body Composition Study (N = 1121) with longitudinal data between 2000-01 (initial visit) and 2007-08 (follow-up visit). Only participants with non-impaired nerve function at the initial visit were included. The predictor was presence of CKD (estimated GFR ≤ 60 ml/min/1.73m2) from the 1999-2000 visit. Peripheral nerve function outcomes at 7-year follow-up were 1) Motor: "new" impairments in motor parameters (nerve conduction velocity NCV < 40 m/s or peroneal compound motor action potential < 1 mv) at follow-up, and 2) Sensory: "new" impairment defined as insensitivity to standard 10-g monofilament or light 1.4-g monofilament at the great toe and "worsening" as a change from light to standard touch insensitivity over time. The association between CKD and "new" or "worsening" peripheral nerve impairment was studied using logistic regression., Results: The study population was 45.9% male, 34.3% Black and median age 75 y. CKD participants (15.6%) were older, more hypertensive, higher in BMI and had 2.37 (95% CI 1.30-4.34) fold higher adjusted odds of developing new motor nerve impairments in NCV. CKD was associated with a 2.02 (95% CI 1.01-4.03) fold higher odds of worsening monofilament insensitivity. CKD was not associated with development of new monofilament insensitivity., Conclusions: Pre-existing CKD leads to new and worsening sensorimotor nerve impairments over a 7-year time period in community-dwelling older adults., Competing Interests: The authors have declared that no competing interests exist.
Published: 2020
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83. Fibroblast growth factor 23 and cognitive impairment: The health, aging, and body composition study.

Author: Drew DA, Katz R, Kritchevsky S, Ix JH, Shlipak M, Newman AB, Hoofnagle A, Fried L, Gutiérrez OM, and Sarnak M
Subjects: Aged, Cognition, Cognitive Dysfunction physiopathology, Female, Fibroblast Growth Factor-23, Humans, Male, Aging blood, Body Composition, Cognitive Dysfunction blood, Fibroblast Growth Factors blood, Health
Abstract: Background: Concentrations of fibroblast growth factor 23 (FGF-23), a hormone that regulates phosphorus and vitamin D metabolism, increase as kidney function declines. Excess fibroblast growth factor 23 may impact brain function through promotion of vascular disease or through direct effects on neuronal tissue., Methods: In the Healthy Aging and Body Composition Study, a longitudinal observational cohort of well-functioning older adults, intact serum FGF-23 was assayed in 2,738 individuals. Cognitive function was assessed at baseline and longitudinally at years 3, 5, and 8 by administration of the Modified Mini Mental State Examination (3MSE), a test of global cognitive function, and the Digit Symbol Substitution Test (DSST), a test primarily of executive function. The associations between FGF-23 and baseline cognitive function and incident cognitive impairment were evaluated using logistic and Poisson regression respectively, and were adjusted for demographics, baseline estimated glomerular filtration rate (eGFR), urine albumin/creatinine ratio, comorbidity, and other measures of mineral metabolism including soluble klotho., Results: The mean (SD) age was 74(3) years, with 51% female, and 39% black. The median (25th, 75th) FGF-23 concentration was 47 pg/mL (37, 60). Three hundred ninety-two individuals had prevalent cognitive impairment by the 3MSE and 461 by the DSST. There was no observed association between FGF-23 and baseline cognitive function for either cognitive test. There were 277 persons with incident cognitive impairment by 3MSE, and 333 persons with incident cognitive impairment by DSST. In fully adjusted models, each two-fold higher concentration of baseline FGF-23 was not associated with incident cognitive impairment by the 3MSE (IRR = 1.02[0.88, 1.19] fully adjusted model) or by the DSST (IRR = 0.98 [0.84, 1.15]. We saw no difference when analyses were stratified by eGFR greater than or less than 60 ml/min/1.73m2., Conclusion: Intact FGF-23 was not associated with baseline cognitive function or incident cognitive impairment in this cohort well-functioning older adults., Competing Interests: Dr. Gutierrez reports receiving grant funding and consulting fees from Akebia; grant funding and consulting fees from Amgen; grant funding from GSK; and consulting fees from QED Therapeutics. These interests do not alter our adherence to the PLOS ONE policies on sharing data and materials.
Published: 2020
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84. Association of Lower Urinary Tract Symptom Severity with Kidney Function among Community Dwelling Older Men.

Author: Bauer SR, Scherzer R, Zhao S, Breyer BN, Kenfield SA, Shlipak M, and Marshall LM
Subjects: Aged, Aged, 80 and over, Albuminuria diagnosis, Confounding Factors, Epidemiologic, Creatinine blood, Creatinine urine, Cross-Sectional Studies, Cystatin C blood, Glomerular Filtration Rate physiology, Humans, Lower Urinary Tract Symptoms complications, Lower Urinary Tract Symptoms diagnosis, Lower Urinary Tract Symptoms physiopathology, Male, Prevalence, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic etiology, Severity of Illness Index, Urination physiology, Independent Living statistics & numerical data, Lower Urinary Tract Symptoms epidemiology, Renal Insufficiency, Chronic epidemiology
Abstract: Purpose: Most international practice guidelines recommend screening for chronic kidney disease among older men with lower urinary tract symptoms. However, prior studies supporting these guidelines are insufficient due to incomplete assessments of kidney function and inadequate adjustment for confounding factors., Materials and Methods: We conducted a cross-sectional study among 5,530 American men older than 65 years in the multicenter Osteoporotic Fractures in Men Study. Chronic kidney disease was defined per international guidelines as estimated glomerular filtration rate less than 60 ml/minute/1.73 m 2 based on serum creatinine or cystatin C, or urinary albumin-to-creatinine ratio 30 mg/gm or greater. Lower urinary tract symptoms were assessed with the American Urological Association Symptom Index. Associations were estimated using multivariable linear and modified Poisson regression models., Results: Chronic kidney disease prevalence was 16% among 5,530 men with serum creatinine, 24% among 1,504 men with serum cystatin C and 14% among 1,487 men with urinary albumin-to-creatinine measurements. Lower urinary tract symptoms were not associated with lower estimated glomerular filtration rate based on serum creatinine or cystatin C. Although symptom severity was modestly associated with a higher prevalence of chronic kidney disease in age/site adjusted analyses, confidence intervals were wide and associations using all 3 definitions were not statistically significant after adjustment for important confounders, including cardiovascular disease and analgesic use., Conclusions: Lower urinary tract symptoms are not independently associated with multiple measures of kidney dysfunction or prevalence of chronic kidney disease among older community dwelling men. Our results do not support recommendations for kidney function testing among older men with lower urinary tract symptoms.
Published: 2020
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85. Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets.

Author: Matsushita K, Jassal SK, Sang Y, Ballew SH, Grams ME, Surapaneni A, Arnlov J, Bansal N, Bozic M, Brenner H, Brunskill NJ, Chang AR, Chinnadurai R, Cirillo M, Correa A, Ebert N, Eckardt KU, Gansevoort RT, Gutierrez O, Hadaegh F, He J, Hwang SJ, Jafar TH, Kayama T, Kovesdy CP, Landman GW, Levey AS, Lloyd-Jones DM, Major RW, Miura K, Muntner P, Nadkarni GN, Naimark DM, Nowak C, Ohkubo T, Pena MJ, Polkinghorne KR, Sabanayagam C, Sairenchi T, Schneider MP, Shalev V, Shlipak M, Solbu MD, Stempniewicz N, Tollitt J, Valdivielso JM, van der Leeuw J, Wang AY, Wen CP, Woodward M, Yamagishi K, Yatsuya H, Zhang L, Schaeffner E, and Coresh J
Abstract: Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. "CKD Patch" is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures., Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several "CKD Patches" incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch., Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018-0.036] and 0.010 [0.007-0.013] and categorical net reclassification improvement 0.080 [0.032-0.127] and 0.056 [0.044-0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89-3.40) in very high-risk CKD (e.g., eGFR 30-44 ml/min/1.73m 2 with albuminuria ≥30 mg/g), 1.86 (1.48-2.44) in high-risk CKD (e.g., eGFR 45-59 ml/min/1.73m 2 with albuminuria 30-299 mg/g), and 1.37 (1.14-1.69) in moderate risk CKD (e.g., eGFR 60-89 ml/min/1.73m 2 with albuminuria 30-299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37-1.81), 1.24 (1.10-1.54), and 1.21 (0.98-1.46)., Interpretation: The "CKD Patch" can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available., Funding: US National Kidney Foundation and the NIDDK., Competing Interests: Dr. Matsushita reports grants from NIH during the conduct of the study; grants and personal fees from Kyowa Kirin and personal fees from Akebia outside the submitted work. Dr. Grams reports grants from NKF and grants from NIH during the conduct of the study and received travel funds to speak at DCI Director's meeting. Dr. Ärnlöv reports personal fees from AstraZeneca outside the submitted work. Dr. Ebert reports personal fees from Bayer AG, personal fees from Siemens Healthineers, and personal fees from Roche Diagnostics outside the submitted work. Dr. Eckardt reports grants from Astra Zeneca, grants from Bayer, grants from FMC, and grants from Vifor during the conduct of the study; personal fees from Akebia, personal fees from Astellas, personal fees from Bayer, and personal fees from Vifor outside the submitted work. Dr. Gutierrez reports grants and personal fees from Akebia, grants and personal fees from Amgen, grants from GSK, personal fees from QED, grants from National Institutes of Health, and grants from American Heart Association outside the submitted work. Dr. Kovesdy reports personal fees from Amgen, personal fees from Sanofi-Aventis, personal fees from Fresenius Medical Care, personal fees from Keryx, grants from Shire, personal fees from Bayer, personal fees from Abbott, personal fees from Abbvie, personal fees from Dr. Schar, personal fees from Astra-Zeneca, personal fees from Takeda, personal fees from Tricida, and personal fees from Reata outside the submitted work. Dr. Levey reports grants from NIDDK during the conduct of the study. Dr. Lloyd-Jones reports grants from NIH during the conduct of the study. Dr. Muntner reports grant support and consulting fees unrelated to this project. Dr. Nadkarni reports grants, personal fees, non-financial support and other from Renalytix AI, non-financial support and other from Pensieve Health, personal fees from Reata, personal fees from AstraZeneca, and personal fees from GLG Consulting outside the submitted work. Dr. Ohkubo reports grants from Omron Healthcare Co. Ltd. outside the submitted work. Dr. Shlipak reports consultancy fees from Cricket Health and Intercept Pharmaceuticals and stocks/stock options from TAI Diagnostics where he is a Scientific Advisor outside the submitted work. Dr. Woodward reports personal fees from Amgen and personal fees from Kirin outside the submitted work. Dr. Zhang reports grants from National Natural Science Foundation of China, grants from Beijing Nova Program Interdisciplinary Cooperation Project, grants from University of Michigan Health System-Peking University Health Science Center Joint Institute for Translational and Clinical Research, grants from PKU-Baidu Fund, grants from Peking University, and grants from AstraZeneca during the conduct of the study. Dr. Schaeffner reports other from Siemens Healthineers, other support from Fresenius Kabi and other support from Fresenius Medical Care outside the submitted work. Dr. Coresh reports grants from NIH and grants from National Kidney Foundation during the conduct of the study; personal fees and other support from Healthy.io outside the submitted work. All other coauthors have nothing to disclose., (© 2020 The Authors.)
Published: 2020
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86. Cardiac Biomarkers and Risk of Mortality in CKD (the CRIC Study).

Author: Wang K, Zelnick LR, Anderson A, Cohen J, Dobre M, Deo R, Feldman H, Go A, Hsu J, Jaar B, Kansal M, Shlipak M, Soliman E, Rao P, Weir M, and Bansal N
Abstract: Introduction: Cardiovascular disease (CVD) is the leading cause of mortality among individuals with chronic kidney disease (CKD). Cardiac biomarkers of myocardial distention, injury, and inflammation may signal unique pathways underlying CVD in CKD. In this analysis, we studied the association of baseline levels and changes in 4 traditional and novel cardiac biomarkers with risk of all-cause, CV, and non-CV mortality in a large cohort of patients with CKD., Methods: Among 3664 adults with CKD enrolled in the Chronic Renal Insufficiency Cohort Study, we conducted a cohort study to examine the associations of baseline levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), cardiac high-sensitivity troponin T (hsTnT), growth differentiation factor-15 (GDF-15), and soluble ST-2 (sST-2) with risks of all-cause and cardiovascular (CV) mortality. Among a subcohort of 842 participants, we further examined the associations between change in biomarker levels over 2 years with risk of all-cause mortality. We used Cox proportional hazards regression models and adjusted for demographics, kidney function measures, cardiovascular risk factors, and medication use., Results: After adjustment, elevated baseline levels of each cardiac biomarker were associated with increased risk of all-cause mortality: NT-proBNP (hazard ratio [HR] = 1.92, 95% confidence interval [CI] = 1.73-2.12); hsTnT (HR = 1.62, 95% CI = 1.48, 1.78]); GDF-15 (HR = 1.61, 95% CI = 1.46-1.78]); and sST-2 (HR = 1.26, CI = 1.16-1.37). Higher baseline levels of all 4 cardiac biomarkers were also associated with increased risk of CV. Declines in NT-proBNP (adjusted HR = 0.55, 95% CI = 0.36-0.86) and sST2 (HR = 0.55, 95% CI = 0.36-0.86]) over 2 years were associated with lower risk of all-cause mortality., Conclusion: In a large cohort of CKD participants, elevations of NT-proBNP, hsTnT, GDF-15, and sST-2 were independently associated with greater risks of all-cause and CV mortality., (© 2020 International Society of Nephrology. Published by Elsevier Inc.)
Published: 2020
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87. Impact of Race on the Association of Mineral Metabolism With Heart Failure: the Multi-Ethnic Study of Atherosclerosis.

Author: Robinson-Cohen C, Shlipak M, Sarnak M, Katz R, Peralta C, Young B, Hoofnagle AN, Szklo M, Ix JH, Psaty BM, de Boer IH, Kestenbaum B, and Bansal N
Subjects: Aged, Aged, 80 and over, Atherosclerosis metabolism, Atherosclerosis pathology, Female, Fibroblast Growth Factor-23, Follow-Up Studies, Heart Failure, Humans, Incidence, Male, Middle Aged, Prognosis, Prospective Studies, United States epidemiology, Atherosclerosis epidemiology, Biomarkers blood, Ethnicity statistics & numerical data, Fibroblast Growth Factors blood, Minerals metabolism, Parathyroid Hormone blood, Phosphorus blood
Abstract: Background: Alterations in mineral metabolism, such as high phosphorus, high parathyroid hormone (PTH), and high fibroblast growth factor-23 (FGF-23) have been identified as potential risk factors for heart failure (HF). Important differences in the prevalence of mineral metabolism abnormalities and in the risk of HF have been reported across race and/or ethnic groups. In this study, we evaluated whether the associations of mineral metabolism markers with HF differed by race and/or ethnicity., Methods: We included participants free of cardiovascular disease from the Multi-Ethnic Study of Atherosclerosis to quantify rates of HF overall and across race and/or ethnic groups. Using Cox models, we tested associations of baseline higher phosphorus (>4 mg/dL), PTH greater than 65 pg/mL, and FGF-23 greater than 46.5 pg/mL with incident HF, and for interactions by race and/or ethnicity, adjusting for sociodemographic and cardiovascular risk factors., Results: Among the 6413 participants, median follow-up time was 14.9 years. The incidence rate for HF was highest for African Americans and lowest for Chinese (4.71 and 2.42 per 1000 person-years, respectively). The prevalence of elevated PTH (18.8% vs 7.4%) but not FGF-23 (23.1% vs 28.8%) was higher in African Americans vs Whites. In multivariable models, the associations of elevated PTH (hazard ratio [HR] 1.50, 95% CI: 1.13-1.99) and FGF-23 (HR 1.37, 95% CI: 1.07-1.75) with incident HF were statistically significant. However, the interactions by race and/or ethnicity were not statistically significant., Conclusions: In a multiethnic population, higher PTH and FGF-23 were associated with risk of HF in African American and Hispanic individuals. There is no evidence that race and/or ethnicity modifies the association of altered mineral metabolism with risk of HF., (© Endocrine Society 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Published: 2020
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88. Novel associations between blood metabolites and kidney function among Bogalusa Heart Study and Multi-Ethnic Study of Atherosclerosis participants.

Author: Nierenberg JL, He J, Li C, Gu X, Shi M, Razavi AC, Mi X, Li S, Bazzano LA, Anderson AH, He H, Chen W, Kinchen JM, Rebholz CM, Coresh J, Levey AS, Inker LA, Shlipak M, and Kelly TN
Subjects: Aged, Aged, 80 and over, Atherosclerosis complications, Atherosclerosis metabolism, Chromatography, Liquid methods, Creatinine blood, Female, Glomerular Filtration Rate physiology, Humans, Kidney Function Tests methods, Longitudinal Studies, Male, Metabolomics methods, Middle Aged, Renal Insufficiency, Chronic physiopathology, Biomarkers blood, Renal Insufficiency, Chronic metabolism
Abstract: Introduction: Chronic kidney disease (CKD) is a major public health challenge given its high global prevalence and associated risks of cardiovascular disease and progression to end stage renal disease. Although it is known that numerous metabolic changes occur in CKD patients, identifying novel metabolite associations with kidney function may enhance our understanding of the physiologic pathways relating to CKD., Objectives: The objective of this study was to elucidate novel metabolite associations with kidney function among participants of two community-based cohorts with carefully ascertained metabolomics, kidney function, and covariate data., Methods: Untargeted ultrahigh-performance liquid chromatography-tandem mass spectrometry was used to detect and quantify blood metabolites. We used multivariate adjusted linear regression to examine associations between single metabolites and creatinine-based estimated glomerular filtration rate (eGFRcr) among 1243 Bogalusa Heart Study (BHS) participants (median eGFRcr: 94.4, 5th-95th percentile: 66.0-119.6 mL/min/1.73 m 2 ). Replication, determined by statistical significance and consistent effect direction, was tested using gold standard measured glomerular filtration rate (mGFR) among 260 Multi-Ethnic Study of Atherosclerosis (MESA) participants (median mGFR: 72.0, 5th-95th percentile: 43.5-105.0 mL/min/1.73 m 2 ). All analyses used Bonferroni-corrected alpha thresholds., Results: Fifty-one novel metabolite associations with kidney function were identified, including 12 from previously unrelated sub-pathways: N6-carboxymethyllysine, gulonate, quinolinate, gamma-CEHC-glucuronide, retinol, methylmalonate, 3-hydroxy-3-methylglutarate, 3-aminoisobutyrate, N-methylpipecolate, hydroquinone sulfate, and glycine conjugates of C 10 H 12 O 2 and C 10 H 14 O 2 (1). Significant metabolites were generally inversely associated with kidney function and smaller in mass-to-charge ratio than non-significant metabolites., Conclusion: The 51 novel metabolites identified may serve as early, clinically relevant, kidney function biomarkers.
Published: 2019
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89. Cardiac Biomarkers and Risk of Incident Heart Failure in Chronic Kidney Disease: The CRIC (Chronic Renal Insufficiency Cohort) Study.

Author: Bansal N, Zelnick L, Go A, Anderson A, Christenson R, Deo R, Defilippi C, Lash J, He J, Ky B, Seliger S, Soliman E, and Shlipak M
Subjects: Adult, Aged, Biomarkers blood, Cohort Studies, Female, Heart Failure epidemiology, Humans, Male, Middle Aged, Prospective Studies, Risk Assessment, Heart Failure blood, Heart Failure etiology, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic complications
Abstract: Background Cardiac biomarkers may signal mechanistic pathways involved in heart failure (HF), a leading complication in chronic kidney disease. We tested the associations of NT-proBNP (N-terminal pro-B-type natriuretic peptide), high-sensitivity troponin T (hsTnT), galectin-3, growth differentiation factor-15 (GDF-15), and soluble ST2 (sST2) with incident HF in chronic kidney disease. Methods and Results We examined adults with chronic kidney disease enrolled in a prospective, multicenter study. All biomarkers were measured at baseline. The primary outcome was incident HF. Secondary outcomes included HF with preserved ejection fraction (EF≥50%) and reduced ejection fraction (EF<50%). Cox models were used to test the association of each cardiac biomarker with HF, adjusting for demographics, kidney function, cardiovascular risk factors, and medication use. Among 3314 participants, all biomarkers, with the exception of galectin-3, were significantly associated with increased risk of incident HF (hazard ratio per SD higher concentration of log-transformed biomarker): NT-proBNP (hazard ratio, 2.07; 95% CI, 1.79-2.39); hsTnT (hazard ratio, 1.38; 95% CI, 1.21-1.56); GDF-15 (hazard ratio, 1.44; 95% CI, 1.26-1.66) and sST2 (hazard ratio, 1.19; 95% CI, 1.05-1.35). Higher NT-proBNP, hsTnT, and GDF-15 were also associated with a greater risk of HF with reduced EF; while higher NT-proBNP GDF-15 and sST2 were associated with HF with preserved EF. Galectin-3 was not associated with either HF with reduced EF or HF with preserved EF. Conclusions In chronic kidney disease, elevations of NT-proBNP, hsTnT, GDF-15, sST2 were associated with incident HF. There was a borderline association of galectin-3 with incident HF. NT-proBNP and hsTnT were more strongly associated with HF with reduced EF, while the associations of the newer biomarkers GDF-15 and sST2 were stronger for HF with preserved EF.
Published: 2019
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90. Novel "Predictor Patch" Method for Adding Predictors Using Estimates From Outside Datasets　- A Proof-of-Concept Study Adding Kidney Measures to Cardiovascular Mortality Prediction.

Author: Matsushita K, Sang Y, Chen J, Ballew SH, Shlipak M, Coresh J, Peralta CA, and Woodward M
Subjects: Adult, Aged, Aged, 80 and over, Albuminuria mortality, Albuminuria physiopathology, Cardiovascular Diseases diagnosis, Cardiovascular Diseases physiopathology, Cause of Death, Female, Humans, Male, Middle Aged, Multicenter Studies as Topic, Nutrition Surveys, Predictive Value of Tests, Prognosis, Proof of Concept Study, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic physiopathology, Risk Assessment, Risk Factors, United States epidemiology, Cardiovascular Diseases mortality, Data Mining, Databases, Factual, Decision Support Techniques, Glomerular Filtration Rate, Kidney physiopathology, Renal Insufficiency, Chronic mortality
Abstract: Background: Cardiovascular guidelines include risk prediction models for decision making that lack the capacity to include novel predictors., Methods and results: We explored a new "predictor patch" approach to calibrating the predicted risk from a base model according to 2 components from outside datasets: (1) the difference in observed vs. expected values of novel predictors and (2) the hazard ratios (HRs) for novel predictors, in a scenario of adding kidney measures for cardiovascular mortality. Using 4 US cohorts (n=54,425) we alternately chose 1 as the base dataset and constructed a base prediction model with traditional predictors for cross-validation. In the 3 other "outside" datasets, we developed a linear regression model with traditional predictors for estimating expected values of glomerular filtration rate and albuminuria and obtained their adjusted HRs of cardiovascular mortality, together constituting a "patch" for adding kidney measures to the base model. The base model predicted cardiovascular mortality well in each cohort (c-statistic 0.78-0.91). The addition of kidney measures using a patch significantly improved discrimination (cross-validated ∆c-statistic 0.006 [0.004-0.008]) to a similar degree as refitting these kidney measures in each base dataset., Conclusions: The addition of kidney measures using our new "predictor patch" approach based on estimates from outside datasets improved cardiovascular mortality prediction based on traditional predictors, providing an option to incorporate novel predictors to an existing prediction model.
Published: 2019
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91. Chronic kidney disease and peripheral nerve function in the Health, Aging and Body Composition Study.

Author: Moorthi RN, Doshi S, Fried LF, Moe SM, Sarnak MJ, Satterfield S, Schwartz AV, Shlipak M, Lange-Maia BS, Harris TB, Newman AB, and Strotmeyer ES
Subjects: Age Factors, Aged, Cohort Studies, Creatinine blood, Cystatin C blood, Female, Humans, Male, Renal Insufficiency, Chronic metabolism, Body Composition, Glomerular Filtration Rate, Peripheral Nerves physiopathology, Renal Insufficiency, Chronic pathology
Abstract: Background: Chronic kidney disease (CKD) is associated with poor mobility. Peripheral nerve function alterations play a significant role in low mobility. We tested the hypothesis that early CKD is associated with altered sensory, motor and autonomic nerve function., Methods: Participants in the Health, Aging and Body Composition cohort who had kidney function measures in Year 3 (1999-2000) and nerve function measurements at Year 4 (2000-01) were analyzed (n = 2290). Sensory (vibration threshold, monofilament insensitivity to light and standard touch), motor [compound motor action potentials (CMAPs), nerve conduction velocities (NCVs)] and autonomic (heart rate response and recovery after a 400-m walk test) nerve function as well as participant characteristics were compared across cystatin C- and creatinine-based estimated glomerular filtration rate categorized as ≤60 (CKD) or >60 mL/min/1.73 m2 (non-CKD). The association between CKD and nerve function was examined with logistic regression adjusted for covariates., Results: Participants with CKD (n = 476) were older (77 ± 3 versus 75 ± 3 years; P < 0.05) and had a higher prevalence of diabetes (20.6% versus 13.1%; P < 0.001). CKD was associated with higher odds for vibration detection threshold {odds ratio [OR] 1.7 [95% confidence interval (CI) 1.1-2.7]} and light touch insensitivity [OR 1.4 (95% CI 1.1-1.7)]. CMAPs and NCVs were not significantly different between CKD and non-CKD patients. In adjusted analyses, participants with CKD had higher odds of an abnormal heart rate response [OR 1.6 (95% CI 1.1-2.2)] and poor heart rate recovery [OR 1.5 (95% CI 1.1-2.0)]., Conclusions: CKD is associated with changes in sensory and autonomic nerve function, even after adjustment for demographics and comorbidities, including diabetes. Longitudinal studies in CKD are needed to determine the contribution of nerve impairments to clinically important outcomes., (© The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)
Published: 2019
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92. Chronic inflammation and risk of lung cancer in older adults in the health, aging and body composition cohort study.

Author: Demb J, Wei EK, Izano M, Kritchevsky S, Swede H, Newman AB, Shlipak M, Akinyemiju T, Gregorich S, and Braithwaite D
Subjects: Black or African American, Aged, Aged, 80 and over, Biomarkers, Chronic Disease, Cohort Studies, Female, Humans, Incidence, Inflammation epidemiology, Male, Multivariate Analysis, Proportional Hazards Models, Prospective Studies, Risk Factors, United States epidemiology, White People, C-Reactive Protein metabolism, Inflammation metabolism, Interleukin-6 metabolism, Lung Neoplasms epidemiology, Tumor Necrosis Factor-alpha metabolism
Abstract: Objectives: We examined the association between three inflammatory markers (Interleukin (IL)-6, C-reactive protein (CRP), tumor necrosis factor (TNF)-α) and incident lung cancer using baseline, updated, and averaged inflammatory measures in older adults., Methods: We fitted multivariable Cox models to assess whether circulating levels of inflammation markers were associated with incident lung cancers in the Health Aging, Body and Composition (HealthABC) prospective cohort of 3075 older adults aged 70-79 years at baseline. IL-6 and CRP were measured biennially, whereas TNF-α was measured at baseline., Results: Baseline levels of IL-6 were significantly associated with incident lung cancer risk in a model that adjusted for age, gender, race, and site (Model 1) (Hazard Ratio T3 vs. T1 : 3.34, 95% Confidence Interval: 1.91, 5.85) and in a model adjusted for health factors linked to chronic inflammation (Model 2) (HR T3 vs. T1 : 2.57, 95% CI: 1.41, 4.65). The associations observed in time-updated IL-6 (HR T3 vs. T1 : 2.47, 95% CI: 1.43, 4.28), cumulatively averaged IL-6 (HR T3 vs. T1 : 2.47, 95% CI: 1.43, 4.35), and baseline CRP levels (HR T3 vs. T1 : 1.85, 95% CI: 1.11, 3.08) with incident lung cancer in Model 1 were not statistically significant in Model 2., Conclusions: Baseline CRP and IL-6 levels were associated with increased risk of lung cancer in Model 1 and both models, respectively. Chronic IL-6 inflammation, as quantified by repeated measures was associated with incident lung cancer in Model 1, but not Model 2. Further research is needed to understand the role of CRP and IL-6 in lung carcinogenesis., (Copyright © 2018 Elsevier Inc. All rights reserved.)
Published: 2019
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93. Albuminuria, Lung Function Decline, and Risk of Incident Chronic Obstructive Pulmonary Disease. The NHLBI Pooled Cohorts Study.

Author: Oelsner EC, Balte PP, Grams ME, Cassano PA, Jacobs DR, Barr RG, Burkart KM, Kalhan R, Kronmal R, Loehr LR, O'Connor GT, Schwartz JE, Shlipak M, Tracy RP, Tsai MY, White W, and Yende S
Subjects: Aged, Albuminuria physiopathology, Cohort Studies, Comorbidity, Female, Humans, Incidence, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Pulmonary Disease, Chronic Obstructive physiopathology, Respiratory Function Tests, Risk Factors, United States epidemiology, Albuminuria epidemiology, Lung physiopathology, Pulmonary Disease, Chronic Obstructive epidemiology
Abstract: Rationale: Chronic lower respiratory diseases (CLRDs), including chronic obstructive pulmonary disease (COPD) and asthma, are the fourth leading cause of death. Prior studies suggest that albuminuria, a biomarker of endothelial injury, is increased in patients with COPD., Objectives: To test whether albuminuria was associated with lung function decline and incident CLRDs., Methods: Six U.S. population-based cohorts were harmonized and pooled. Participants with prevalent clinical lung disease were excluded. Albuminuria (urine albumin-to-creatinine ratio) was measured in spot samples. Lung function was assessed by spirometry. Incident CLRD-related hospitalizations and deaths were classified via adjudication and/or administrative criteria. Mixed and proportional hazards models were used to test individual-level associations adjusted for age, height, weight, sex, race/ethnicity, education, birth year, cohort, smoking status, pack-years of smoking, renal function, hypertension, diabetes, and medications., Measurements and Main Results: Among 10,961 participants with preserved lung function, mean age at albuminuria measurement was 60 years, 51% were never-smokers, median albuminuria was 5.6 mg/g, and mean FEV 1 decline was 31.5 ml/yr. For each SD increase in log-transformed albuminuria, there was 2.81% greater FEV 1 decline (95% confidence interval [CI], 0.86-4.76%; P = 0.0047), 11.02% greater FEV 1 /FVC decline (95% CI, 4.43-17.62%; P = 0.0011), and 15% increased hazard of incident spirometry-defined moderate-to-severe COPD (95% CI, 2-31%, P = 0.0021). Each SD log-transformed albuminuria increased hazards of incident COPD-related hospitalization/mortality by 26% (95% CI, 18-34%, P < 0.0001) among 14,213 participants followed for events. Asthma events were not significantly associated. Associations persisted in participants without current smoking, diabetes, hypertension, or cardiovascular disease., Conclusions: Albuminuria was associated with greater lung function decline, incident spirometry-defined COPD, and incident COPD-related events in a U.S. population-based sample.
Published: 2019
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94. Association of Soluble TNFR-1 Concentrations with Long-Term Decline in Kidney Function: The Multi-Ethnic Study of Atherosclerosis.

Author: Bhatraju PK, Zelnick LR, Shlipak M, Katz R, and Kestenbaum B
Subjects: Aged, Aged, 80 and over, Atherosclerosis blood, Atherosclerosis complications, Biomarkers blood, Cohort Studies, Creatinine blood, Disease Progression, Ethnicity, Female, Follow-Up Studies, Glomerular Filtration Rate, Humans, Kidney Function Tests, Male, Middle Aged, Prospective Studies, Renal Artery diagnostic imaging, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic etiology, Renal Insufficiency, Chronic physiopathology, Risk Factors, Solubility, Vascular Calcification diagnostic imaging, Atherosclerosis physiopathology, Kidney physiopathology, Receptors, Tumor Necrosis Factor, Type I blood
Abstract: Background: TNF receptor-1 (TNFR-1), which plays a causative role in endothelial cell dysfunction and inflammation, is expressed on the cell surface in glomerular and peritubular capillary endothelium of the kidneys. Higher soluble TNF receptor-1 (sTNFR-1) concentrations are associated with kidney disease progression among persons with established diabetic kidney disease. However, no studies have assessed sTNFR-1's role in long-term kidney function changes in a multiethnic population without cardiovascular disease at baseline., Methods: We tested associations between baseline sTNFR-1 concentrations and 10-year decline in eGFR (incident ≥40% decline and annual proportional decline) among 2548 participants in the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective cohort study. Serum creatinine concentrations were determined at enrollment and study years 3, 5, and 10., Results: Mean age of participants was 61 years old, 53% were women, and mean baseline eGFR was 79 ml/min per 1.73 m 2 . Serum sTNFR-1 was inversely associated with baseline eGFR. Over median follow-up of 9.3 years, 110 participants developed ≥40% decline in eGFR; each SD higher concentration of sTNFR1 was associated with higher risk of 40% eGFR decline (adjusted hazard ratio, 1.43; 95% confidence interval [95% CI], 1.16 to 1.77; P <0.001). The highest sTNFR-1 tertile was associated with adjusted annualized decline in eGFR of 1.94% (95% CI, 1.79 to 2.09). Associations persisted across subgroups defined by demographics, hypertension, diabetes, and baseline CKD status., Conclusions: Elevated serum sTNFR-1 concentrations are associated with faster declines in eGFR over the course of a decade in a multiethnic population, independent of previously known risk factors for kidney disease progression., (Copyright © 2018 by the American Society of Nephrology.)
Published: 2018
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95. Changes in Blood Pressure During Young Adulthood and Subsequent Kidney Function Decline: Findings From the Coronary Artery Risk Development in Young Adulthood (CARDIA) Study.

Author: Ku E, Vittinghoff E, Jacobs DR Jr, Lewis CE, Allen NB, Bibbins-Domingo K, Shlipak M, Kramer H, and Peralta CA
Subjects: Adolescent, Adult, Age Factors, Cohort Studies, Coronary Artery Disease diagnosis, Coronary Artery Disease epidemiology, Female, Humans, Hypertension diagnosis, Hypertension epidemiology, Kidney Diseases diagnosis, Kidney Diseases epidemiology, Male, Prospective Studies, Risk Factors, Young Adult, Blood Pressure physiology, Coronary Artery Disease physiopathology, Glomerular Filtration Rate physiology, Hypertension physiopathology, Kidney Diseases physiopathology
Abstract: Background: Many studies have focused on the association between a single blood pressure (BP) measurement and risk for adverse outcomes. However, the association of BP trajectories during young adulthood with subsequent decline in kidney function has not been well defined., Study Design: Observational cohort study., Setting & Participants: 3,429 participants in the Coronary Artery Risk Development in Young Adulthood (CARDIA) Study enrolled between the ages of 18 and 30 years., Predictors: BP slope during the first 10 years of participation in CARDIA, derived from linear mixed models incorporating all repeated BP measures., Outcome: Decline in estimated glomerular filtration rate (eGFR) during the interval between years 10 and 20 of CARDIA participation using cystatin C measured at years 10, 15, and 20., Results: Mean age of CARDIA participants at year 0 was 25.1 years, 56% were women, and 53% were white. Every 10-mmHg higher level of systolic (SBP) and diastolic BP (DBP) in year 10 was associated with change in eGFR of -0.09 (95% CI, -0.13 to -0.06) and -0.07 (95% CI, -0.12 to -0.03) mL/min/1.73m 2 per year, respectively. Every 10-mmHg increase in SBP slope between years 0 and 10 was associated with a subsequent -0.52 (95% CI, -1.02 to -0.03) mL/min/1.73m 2 per year change in kidney function after adjustment for comorbid conditions and SBP at year 10. Similarly, every 10-mmHg increase in DBP slope between years 0 and 10 was associated with a subsequent change in kidney function of -0.65 (95% CI, -1.23 to -0.07) mL/min/1.73m 2 per year, after adjustment for comorbid conditions and DBP in year 10., Limitations: Observational design., Conclusions: During young adulthood, increasing SBP and DBP are associated with a higher rate of subsequent kidney function decline, independent of BP measured at the beginning of eGFR assessment., (Copyright © 2018 National Kidney Foundation, Inc. All rights reserved.)
Published: 2018
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96. Association between N-terminal Pro-Brain Natriuretic Peptide levels, glomerular filtration rate, and heart failure in the Multi-Ethnic Study of Atherosclerosis.

Author: Syed D, Peshenko S, Liu K, Durazo-Arvizu R, Rosas SE, Shlipak M, Sarnak M, Jacobs D, Sickovick D, Lima J, Kronmal R, and Kramer H
Abstract: Background: This study examined the complementary prognostic role of NT-proBNP and eGFR for predicting heart failure (HF) in adults with and without chronic kidney disease (CKD) defined as eGFR<60 ml/min/1.73m2., Methods: We used data from the Multi-Ethnic Study of Atherosclerosis, a cohort of 6814 adults without baseline clinical cardiovascular disease. Five-year risk prediction of HF based on clinical HF risk variables (HFRV) plus NT-proBNP, eGFR or both was assessed using the C-statistic and the net reclassification index (NRI) after stratifying by CKD status., Results: Mean age at baseline was 62.3±10.3 years and CKD were present in 5.9%. A total of 39 and 180 HF events occurred in participants with and without CKD, respectively. Among adults with CKD, the C-statistic for HF risk prediction increased significantly (P =0.04) from 0.71 (95% CI 0.64, 0.78) with HFRV alone to 0.78 (95% CI 0.71, 0.85) with addition of NT-proBNP. In the non-CKD group, the C-statistic increased from 0.77 (95% CI 0.74, 0.80) with HFRV alone to 0.83 (95% CI 0.80, 0.85) with addition of NT-proBNP. Further addition of eGFR to the model did not alter the C-statistic regardless of CKD status. NRI improved by 23.1% and 10.2% in CKD and non-CKD, respectively, with the addition of NT-proBNP alone and findings were similar when both eGFR and NT-proBNP were both added to model., Conclusions: In adults without clinical cardiovascular disease, the addition of NT-proBNP but not eGFR to established HFRV improves HF risk prediction in adults with and without CKD.
Published: 2018
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97. Urinary Tubular Injury Biomarkers Are Associated With ESRD and Death in the REGARDS Study.

Author: Dubin RF, Judd S, Scherzer R, Shlipak M, Warnock DG, Cushman M, Sarnak M, Parikh C, Bennett M, Powe N, and Peralta CA
Abstract: Introduction: Urinary neutrophil gelatinase-associated lipocalin (uNGAL) and urinary kidney injury molecule-1 (uKIM-1) are established markers of subclinical acute kidney injury. In persons with reduced estimated glomerular filtration rate (eGFR) and albuminuria who are at high risk for end-stage renal disease (ESRD) and death, the associations of these urinary markers with incident ESRD or death is an area of active investigation., Methods: Among 1472 black and white participants from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study with eGFR ≤60 ml/min per 1.73 m 2 (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] cystatin, 2012) and albumin-to-creatinine ratio (ACR) ≥30 mg/g, we evaluated the associations of baseline uNGAL and uKIM-1 with progression to ESRD and all-cause death. Cox models were sequentially adjusted for urinary creatinine, traditional risk factors, C-reactive protein, ACR, and eGFR., Results: There were 257 ESRD events and 819 deaths over a median follow-up of 5.7 and 6.5 years, respectively. In demographic adjusted models, higher levels of uNGAL were associated with increased risk of ESRD and death, but these associations were attenuated in fully adjusted models including baseline eGFR for both ESRD (hazard ratio [HR] = 1.06 per doubling, 95% confidence interval [CI] 0.98-1.14) and death (HR = 1.04, 95% CI = 1.00-1.08). Higher levels of uKIM-1 were associated with increased risk of ESRD and death in demographic-adjusted models, and although attenuated in fully adjusted models, remained statistically significant for both ESRD (HR = 1.24 per doubling, 95% CI = 1.08-1.42) and death (HR = 1.10, 95% CI =1.03-1.19)., Conclusion: In this cohort of high-risk patients with baseline eGFR ≤60 ml/min per 1.73 m 2 and albuminuria, renal tubular injury is associated with higher mortality and progression to ESRD. Further studies are necessary to investigate the mechanism underlying this increased risk.
Published: 2018
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98. Patterns of blood pressure response during intensive BP lowering and clinical events: results from the secondary prevention of small subcortical strokes trial.

Author: Ku E, Scherzer R, Odden MC, Shlipak M, White CL, Field TS, Benavente O, Pergola PE, and Peralta CA
Subjects: Aged, Female, Humans, Hypertension physiopathology, Male, Middle Aged, Blood Pressure physiology, Blood Pressure Determination methods, Stroke prevention & control
Abstract: Purpose: We applied cluster analysis to identify discrete patterns of concomitant responses of systolic (SBP), diastolic (DBP) and pulse pressure (PP) during intensive BP lowering; and to evaluate their clinical relevance and association with risk of mortality, major vascular events (MVEs), and stroke., Material and Methods: We used an unsupervised cluster procedure to identify distinct patterns of BP change during the first 9 months of anti-hypertensive therapy intensification among 1,331 participants in the Secondary Prevention of Small Subcortical Strokes Trial who were previously randomized to lower BP target (SBP < 130 mm Hg) after lacunar stroke., Results: The cluster procedure partitioned participants into three groups in the lower SBP target arm, persons with: 1) mildly elevated baseline SBP and minimal visit-to-visit BP variability (mild reducers); 2) moderately elevated baseline SBP and moderate visit-to-visit BP variability (moderate reducers); and 3) very elevated baseline SBP with very large visit-to-visit BP variability during intensification (large reducers). In the lower SBP target group, moderate reducers had a higher risk of death (adjusted HR 1.6 [95% CI 1.0-2.7]), MVE (adjusted HR 2.1 [95% CI 1.4-3.2]), and stroke (adjusted HR 2.6[95% CI 1.7-4.1]) compared to mild reducers. Large reducers had the highest risk of death (adjusted HR 2.3 [95% CI 1.2-4.4]), but risk of MVE (HR = 1.7 [95%CI 0.9-3.1]) and stroke (HR = 1.6 [95%CI: 0.8-3.5]) were not statistically significantly different compared to mild reducers., Conclusions: Among persons with prior lacunar stroke, baseline BP levels, and BP variability in the setting of intensive BP lowering can identify discrete groups of persons at higher risk of adverse outcomes.
Published: 2018
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99. Changes in Kidney Function Associated With Daily Tenofovir Disoproxil Fumarate/Emtricitabine for HIV Preexposure Prophylaxis Use in the United States Demonstration Project.

Author: Tang EC, Vittinghoff E, Anderson PL, Cohen SE, Doblecki-Lewis S, Bacon O, Coleman ME, Buchbinder SP, Chege W, Kolber MA, Elion R, Shlipak M, and Liu AY
Subjects: Adolescent, Adult, Aged, Anti-HIV Agents administration & dosage, Creatinine blood, Disease Transmission, Infectious prevention & control, Emtricitabine administration & dosage, Female, Glomerular Filtration Rate, HIV Infections transmission, Homosexuality, Male, Humans, Male, Metabolic Clearance Rate, Middle Aged, Prospective Studies, Proteins analysis, Tenofovir administration & dosage, Transgender Persons, United States, Urinalysis, Young Adult, Anti-HIV Agents adverse effects, Emtricitabine adverse effects, HIV Infections prevention & control, Kidney Function Tests, Pre-Exposure Prophylaxis methods, Renal Insufficiency chemically induced, Tenofovir adverse effects
Abstract: Background: HIV preexposure prophylaxis (PrEP) using daily oral tenofovir-disoproxil-fumarate/emtricitabine (TDF/FTC) is effective for preventing HIV acquisition, but concerns remain about its potential kidney toxicity. This study examined kidney function in individuals using PrEP in real-world clinical settings., Setting: Demonstration project in 2 sexually transmitted infection clinics and a community health center., Methods: We evaluated kidney function among men who have sex with men and transgender women taking tenofovir-disoproxil-fumarate/emtricitabine PrEP for up to 48 weeks. Serum creatinine and urine dipstick for protein were obtained at 12-week intervals. Kidney function was estimated using creatinine clearance (CrCl) (Cockcroft-Gault) and estimated glomerular filtration rate (eGFR) (CKD-EPI)., Results: From October 2012 to January 2014, we enrolled 557 participants (median age 33). Mean creatinine increased from baseline to week 12 by 0.03 mg/dL (4.6%) (P < 0.0001); mean CrCl decreased by 4.8 mL/min (3.0%) (P < 0.0001). These changes remained stable through week 48 (P = 0.81, P = 0.71 respectively). There were 75/478 (15.7%) participants who developed worsening proteinuria at week 12 compared with baseline (P < 0.0001), and this percent remained stable through week 48 (P = 0.73). Twenty-five participants (5.1%) developed new-onset eGFR <70 mL/min/1.73 m; independent predictors of this outcome were age ≥40 years (OR 3.79, 95% CI: 1.43 to 10.03) and baseline eGFR <90 mL/min/1.73 m (OR 9.59, 3.69-24.94)., Conclusions: In a demonstration setting, daily tenofovir-disoproxil-fumarate/emtricitabine PrEP leads to reduced CrCl and eGFR; however, these eGFR changes are based on very small changes in serum creatinine and seem to be nonprogressive after the first 12 weeks. Future studies are needed to understand the prognostic significance of these small changes.
Published: 2018
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100. Interleukin-8 and Tumor Necrosis Factor Predict Acute Kidney Injury After Pediatric Cardiac Surgery.

Author: de Fontnouvelle CA, Greenberg JH, Thiessen-Philbrook HR, Zappitelli M, Roth J, Kerr KF, Devarajan P, Shlipak M, Coca S, and Parikh CR
Subjects: Acute Kidney Injury blood, Acute Kidney Injury etiology, Adolescent, Biomarkers blood, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Male, Postoperative Complications, Prognosis, Prospective Studies, Acute Kidney Injury diagnosis, Cardiac Surgical Procedures adverse effects, Heart Defects, Congenital surgery, Interleukin-8 blood
Abstract: Background: Inflammation is a key component of both acute kidney injury (AKI) and response to cardiopulmonary bypass. Because AKI poses risks to children after cardiac surgery, we investigated the value of inflammatory biomarkers interleukin-8 (IL-8) and tumor necrosis factor alpha (TNFα) for predicting AKI and other complications., Methods: We enrolled 412 children between the ages of 1 month and 18 years undergoing cardiopulmonary bypass for cardiac surgery. We collected blood both preoperatively and postoperatively (within 6 hours post-surgery) and measured plasma IL-8 and TNFα., Results: IL-8 and TNFα did not predict AKI in children <2 years, but were strongly associated with AKI in children ≥2 years. There were significant associations between biomarker levels and age (<2 or ≥2 years). In children ≥2 years, patients in the highest tertile of preoperative IL-8 and postoperative TNFα had 4.9-fold (95% CI: 1.8-13.2) and 3.3-fold (95% CI: 1.2-9.0) higher odds of AKI compared with those in the lowest tertile. Children <2 years with higher biomarker levels also had higher odds of AKI, but the difference was not significant. We also found that postoperative TNFα levels were significantly higher in patients with longer hospital stays, and that both postoperative IL-8 and TNFα levels were significantly higher in patients with longer ventilation lengths. There was no evidence that biomarker levels mediated the association between AKI and length of ventilation; they appear to be independent predictors., Conclusions: Preoperative IL-8 and postoperative TNFα are significantly associated with higher odds of AKI and greater lengths of hospital stays and ventilator use in children 2 years and older., (Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)
Published: 2017
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