Faculty Bibliography

BACKGROUND:Vascular calcification is common among patients undergoing dialysis and is associated with mortality. Factors such as osteoprotegerin (OPG), osteopontin (OPN), bone morphogenic protein-7 (BMP-7), and fetuin-A are involved in vascular calcification. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS/METHODS:OPG, OPN, BMP-7, and fetuin-A were measured in blood samples from 602 incident dialysis patients recruited from United States dialysis centers between 1995 and 1998 as part of the Choices for Healthy Outcomes In Caring for ESRD Study. Their association with all-cause and cardiovascular mortality were assessed using Cox proportional hazards models adjusted for demographic characteristics, comorbidity, serum phosphate, and calcium. An interaction with diabetes was tested because of its known association with vascular calcification. Predictive accuracy of selected biomarkers was explored by C-statistics in nested models with training and validation subcohorts. RESULTS:Higher OPG and lower fetuin-A levels were associated with higher mortality over up to 13 years of follow-up (median, 3.4 years). The adjusted hazard ratios (HR) for highest versus lowest tertile were 1.49 (95% confidence interval [95% CI], 1.08 to 2.06) for OPG and 0.69 (95% CI, 0.52 to 0.92) for fetuin-A. In stratified models, the highest tertile of OPG was associated with higher mortality among patients without diabetes (HR, 2.42; 95% CI, 1.35 to 4.34), but not patients with diabetes (HR, 1.26; 95% CI, 0.82 to 1.93; P for interaction=0.001). In terms of cardiovascular mortality, higher fetuin-A was associated with lower risk (HR, 0.85 per 0.1 g/L: 95% CI, 0.75 to 0.96). In patients without diabetes, higher OPG was associated with greater risk (HR for highest versus lowest tertile, 2.91; 95% CI, 1.06 to 7.99), but not in patients with diabetes or overall. OPN and BMP-7 were not independently associated with outcomes overall. The addition of OPG and fetuin-A did not significantly improve predictive accuracy of mortality. CONCLUSIONS:OPG and fetuin-A may be risk factors for all-cause and cardiovascular mortality in patients undergoing dialysis, but do not improve risk prediction.

Estimating glomerular filtration rate (GFR) is essential for clinical practice, research, and public health. Appropriate interpretation of estimated GFR (eGFR) requires understanding the principles of physiology, laboratory medicine, epidemiology, and biostatistics used in the development and validation of GFR estimating equations. Equations developed in diverse populations are less biased at higher GFRs than equations developed in chronic kidney disease (CKD) populations and are more appropriate for general use. Equations that include multiple endogenous filtration markers are more precise than equations including a single filtration marker. The CKD-EPI (CKD Epidemiology Collaboration) equations are the most accurate GFR estimating equations that have been evaluated in large diverse populations and are applicable for general clinical use. The 2009 CKD-EPI creatinine equation is more accurate in estimating GFR and prognosis than the 2006 MDRD (Modification of Diet in Renal Disease) Study equation and provides lower estimates of prevalence of decreased eGFR. It is useful as a "first test" for decreased eGFR and should replace the MDRD Study equation for routine reporting of serum creatinine-based eGFR by clinical laboratories. The 2012 CKD-EPI cystatin C equation is as accurate as the 2009 CKD-EPI creatinine equation in estimating GFR, does not require specification of race, and may be more accurate in patients with decreased muscle mass. The 2012 CKD-EPI creatinine-cystatin C equation is more accurate than the 2009 CKD-EPI creatinine and 2012 CKD-EPI cystatin C equations and is useful as a confirmatory test for decreased eGFR as determined by serum creatinine-based eGFR. Further improvement in GFR estimating equations will require development in more broadly representative populations, including diverse racial and ethnic groups, use of multiple filtration markers, and evaluation using statistical techniques to compare eGFR to "true GFR."

BACKGROUND:Although obesity is an independent risk factor for heart failure (HF), once HF is established, obesity is associated with lower mortality. It is unclear if the weight loss due to advanced HF leads to this paradoxical finding. OBJECTIVES/OBJECTIVE:This study sought to evaluate the prognostic impact of pre-morbid obesity in patients with HF. METHODS:In the ARIC (Atherosclerosis Risk In Communities) study, we used body mass index (BMI) measured ≥6 months before incident HF (pre-morbid BMI) to evaluate the association of overweight (BMI 25 to <30 kg/m(2)) and obesity (BMI ≥30 kg/m(2)) compared with normal BMI (18.5 to <25 kg/m(2)) with mortality after incident HF. RESULTS:Among 1,487 patients with incident HF, 35% were overweight and 47% were obese by pre-morbid BMI measured 4.3 ± 3.1 years before HF diagnosis. Over 10-year follow-up after incident HF, 43% of patients died. After adjustment for demographics and comorbidities, being pre-morbidly overweight (hazard ratio [HR]: 0.72; 95% confidence interval [CI]: 0.58 to 0.90; p = 0.004) or obese (HR: 0.70; 95% CI: 0.56 to 0.87; p = 0.001) had a protective association with survival compared with normal BMI. The protective effect of overweight and obesity was consistent across subgroups on the basis of a history of cancer, smoking, and diabetes. CONCLUSIONS:Our results, for the first time, demonstrate that patients who were overweight or obese before HF development have lower mortality after HF diagnosis compared with normal BMI patients. Thus, weight loss due to advanced HF may not completely explain the protective effect of higher BMI in HF patients.

Phenotypes proximal to gene action generally reflect larger genetic effect sizes than those that are distant. The human metabolome, a result of multiple cellular and biological processes, are functional intermediate phenotypes proximal to gene action. Here, we present a genome-wide association study of 308 untargeted metabolite levels among African Americans from the Atherosclerosis Risk in Communities (ARIC) Study. Nineteen significant common variant-metabolite associations were identified, including 13 novel loci (p<1.6 × 10(-10)). These loci were associated with 7-50% of the difference in metabolite levels per allele, and the variance explained ranged from 4% to 20%. Fourteen genes were identified within the nineteen loci, and four of them contained non-synonymous substitutions in four enzyme-encoding genes (KLKB1, SIAE, CPS1, and NAT8); the other significant loci consist of eight other enzyme-encoding genes (ACE, GATM, ACY3, ACSM2B, THEM4, ADH4, UGT1A, TREH), a transporter gene (SLC6A13) and a polycystin protein gene (PKD2L1). In addition, four potential disease-associated paths were identified, including two direct longitudinal predictive relationships: NAT8 with N-acetylornithine, N-acetyl-1-methylhistidine and incident chronic kidney disease, and TREH with trehalose and incident diabetes. These results highlight the value of using endophenotypes proximal to gene function to discover new insights into biology and disease pathology.

OBJECTIVE:Traditional predictors suboptimally predict cardiovascular disease (CVD) in individuals with chronic kidney disease (CKD). This study compared 5 nontraditional cardiac and kidney markers on the improvement of cardiovascular prediction among those with CKD. APPROACH AND RESULTS/RESULTS:Among 8622 participants aged 52 to 75 years in the Atherosclerosis Risk in Communities (ARIC) Study, cardiac troponin T, N-terminal pro-B-type natriuretic peptide, cystatin C, β2-microglobulin, and β-trace protein were compared for improvement in predicting incident CVD after stratifying by CKD status (940 participants with CKD [kidney dysfunction or albuminuria]). During a median follow-up of 11.9 years, there were 1672 CVD events including coronary disease, stroke, and heart failure (336 cases in CKD). Every marker was independently associated with incident CVD in participants with and without CKD. The adjusted hazard ratios (per 1 SD) were larger for cardiac markers than for kidney markers, particularly in CKD (1.61 [95% confidence interval, 1.43-1.81] for cardiac troponin T, 1.50 [1.34-1.68] for N-terminal pro-B-type natriuretic peptide, and <1.26 for kidney markers). Particularly in CKD group, cardiac markers compared with kidney markers contributed to greater c-statistic increment (0.032-0.036 versus 0.012-0.015 from 0.679 with only conventional predictors in CKD and 0.008-0.011 versus 0.002-0.010 from 0.697 in non-CKD) and categorical net reclassification improvement (0.086-0.127 versus 0.020-0.066 in CKD and 0.057-0.077 versus 0.014-0.048 in non-CKD). The superiority of cardiac markers was largely consistent in individual CVD outcomes. CONCLUSIONS:A greater improvement in cardiovascular prediction was observed for cardiac markers than for kidney markers in people with CKD. These results suggest that cardiac troponin T and N-terminal pro-B-type natriuretic peptide are useful for better CVD risk classification in this population.

BACKGROUND:Identifying individuals at risk for sudden cardiac death (SCD) is of critical importance. Electrocardiographic (ECG) deep terminal negativity of P wave in V1 (DTNPV1), a marker of left atrial abnormality, has been associated with increased risk of all-cause and cardiovascular mortality. We hypothesized that DTNPV1 is associated with increased risk of sudden cardiac death (SCD). METHODS AND RESULTS/RESULTS:This analysis included 15 375 participants (54.1±5.8 years, 45% men, 73% whites) from the Atherosclerosis Risk in Communities (ARIC) study. DTNPV1 was defined from the resting 12-lead ECG as presence of biphasic P wave (positive/negative) in V1 with the amplitude of the terminal negative phase >100 μV, or one small box on ECG scale. After a median of 14 years of follow-up, 311 cases of SCD occurred. In unadjusted Cox regression, DTNPV1 was associated with an 8-fold increased risk of SCD (HR 8.21; [95%CI 5.27 to 12.79]). Stratified by race and study center, and adjusted for age, sex, coronary heart disease (CHD), and ECG risk factors, as well as atrial fibrillation (AF), stroke, CHD, and heart failure (HF) as time-updated variables, the risk of SCD associated with DTNPV1 remained significant (2.49, [1.51-4.10]). DTNPV1 improved reclassification: additional 3.4% of individuals were appropriately reclassified into a higher SCD risk group, as compared with traditional CHD risk factors alone. In fully adjusted models DTNPV1 was associated with increased risk of non-fatal events: AF (5.02[3.23-7.80]), CHD (2.24[1.43-3.53]), HF (1.90[1.19-3.04]), and trended towards increased risk of stroke (1.88[0.99-3.57]). CONCLUSION/CONCLUSIONS:DTNPV1 is predictive of SCD suggesting its potential utility in risk stratification in the general population.

BACKGROUND:There is interest in surrogate end points for clinical trials of chronic kidney disease progression because currently established end points-end-stage renal disease (ESRD) and doubling of serum creatinine level-are late events, requiring large clinical trials with long follow-up. Doubling of serum creatinine level is equivalent to a 57% decline in estimated glomerular filtration rate (eGFR). We evaluated type 1 error and required sample size for clinical trials using surrogate end points based on lesser eGFR declines. STUDY DESIGN/METHODS:Simulation study. SETTING & PARTICIPANTS/METHODS:Simulations evaluating 3,060 scenarios representative of 19 treatment comparisons in 13 chronic kidney disease clinical trials. INDEX TESTS/METHODS:Surrogate end points defined as composite end points based on ESRD and either 30% or 40% eGFR declines. REFERENCE TEST/METHODS:Clinical outcome (ESRD) for type 1 error. Established end point (composite of ESRD and 57% eGFR decline) for required sample size. RESULTS:Use of the 40% versus 57% eGFR decline end point consistently led to a reduction in sample size > 20% while maintaining risk for type 1 error < 10% in the presence of a small acute effect (<1.25mL/min/1.73m(2)) for: (1) 2-, 3-, or 5-year trials with a high mean baseline eGFR (67.5mL/min/1.73m(2)), and (2) 2-year trials with an intermediate mean baseline eGFR (42.5mL/min/1.73m(2)). Use of the 30% versus the 40% eGFR decline end point often led to moderately larger reductions in sample size in the absence of an acute effect, but not in the presence of acute effects. LIMITATIONS/CONCLUSIONS:The complexity of eGFR trajectories prevented evaluation of all scenarios for clinical trials. CONCLUSIONS:Use of end points based on 30% or 40% eGFR declines is an appropriate strategy to reduce sample size in certain situations. However, risk for type 1 error is increased in the presence of acute effects, particularly for 30% eGFR declines. The decision to use these end points should be made after thorough evaluation of their expected performance under the conditions of specific clinical trials.

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Novel biomarkers that more accurately reflect kidney function and predict future CKD are needed. The human metabolome is the product of multiple physiologic or pathophysiologic processes and may provide novel insight into disease etiology and progression. This study investigated whether estimated kidney function would be associated with multiple metabolites and whether selected metabolomic factors would be independent risk factors for incident CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS/METHODS:In total, 1921 African Americans free of CKD with a median of 19.6 years follow-up among the Atherosclerosis Risk in Communities Study were included. A total of 204 serum metabolites quantified by untargeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry was analyzed by both linear regression for the cross-sectional associations with eGFR (specified by the Chronic Kidney Disease Epidemiology Collaboration equation) and Cox proportional hazards model for the longitudinal associations with incident CKD. RESULTS:Forty named and 34 unnamed metabolites were found to be associated with eGFR specified by the Chronic Kidney Disease Epidemiology Collaboration equation with creatine and 3-indoxyl sulfate showing the strongest positive (2.8 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, 2.1 to 3.5) and negative association (-14.2 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, -17.0 to -11.3), respectively. Two hundred four incident CKD events with a median follow-up time of 19.6 years were included in the survival analyses. Higher levels of 5-oxoproline (hazard ratio, 0.70; 95% confidence interval, 0.60 to 0.82) and 1,5-anhydroglucitol (hazard ratio, 0.68; 95% confidence interval, 0.58 to 0.80) were significantly related to lower risk of incident CKD, and the associations did not appreciably change when mutually adjusted. CONCLUSIONS:These data identify a large number of metabolites associated with kidney function as well as two metabolites that are candidate risk factors for CKD and may provide new insights into CKD biomarker identification.

BACKGROUND:Lower estimated glomerular filtration rate (eGFR) on a single occasion is associated with risk of cardiovascular events; whether the degree of change in eGFR during a 1-year period adds prognostic information is unknown. METHODS AND RESULTS/RESULTS:We included adults who had ≥2 outpatient eGFR measurements (≥6 months apart) during a 1-year accrual period in Alberta, Canada. According to recent guidelines, we used a change in eGFR category (≥90, 60 to 89, 45 to 59, 30 to 44, 15 to 29, and <15 mL/min per 1.73 m(2)), and the presence/absence of a ≥25% change from baseline to classify participants into 5 groups: certain drop, uncertain drop, stable (no change), uncertain rise, and certain rise. We calculated adjusted rates of cardiovascular events (per 10 000 person-years) for each group. We estimated the adjusted risks of cardiovascular events associated with each category of change in eGFR, in reference to stable kidney function. Among the 526 388 participants, 76.1% (n=400 560) had stable, 2.6% (n=13 668) had a certain drop, and 3.3% (n=17 499) had a certain rise in eGFR. Compared with participants with stable kidney function, adjusted risks of myocardial infarction, heart failure, and stroke were 27%, 51%, and 20% higher, respectively, for those with a certain drop in kidney function. After adjusting for the last eGFR at the end of the accrual period, the observed association diminished. CONCLUSION/CONCLUSIONS:Clinically relevant changes in eGFR are associated with increased risk of cardiovascular events. However, most of the apparent increase in risk can be accounted for by assessing comorbidity and baseline kidney function.