Associations Between the Serum Metabolome and All-Cause Mortality Among African Americans in the Atherosclerosis Risk in Communities (ARIC) Study

Early and accurate identification of people at high risk of premature death may assist in the targeting of preventive therapies in order to improve overall health. To identify novel biomarkers for all-cause mortality, we performed untargeted metabolomics in the Atherosclerosis Risk in Communities (ARIC) Study. We included 1,887 eligible ARIC African Americans, and 671 deaths occurred during a median follow-up period of 22.5 years (1987–2011). Chromatography and mass spectroscopy identified and quantitated 204 serum metabolites, and Cox proportional hazards models were used to analyze the longitudinal associations with all-cause and cardiovascular mortality. Nine metabolites, including cotinine, mannose, glycocholate, pregnendiol disulfate, α-hydroxyisovalerate, N-acetylalanine, andro-steroid monosulfate 2, uridine, and γ-glutamyl-leucine, showed independent associations with all-cause mortality, with an average risk change of 18% per standard-deviation increase in metabolite level (P < 1.23 × 10−4). A metabolite risk score, created on the basis of the weighted levels of the identified metabolites, improved the predictive ability of all-cause mortality over traditional risk factors (bias-corrected Harrell's C statistic 0.752 vs. 0.730). Mannose and glycocholate were associated with cardiovascular mortality (P < 1.23 × 10−4), but predictive ability was not improved beyond the traditional risk factors. This metabolomic analysis revealed potential novel biomarkers for all-cause mortality beyond the traditional risk factors

Carotid Intima-Media Thickness and Incident ESRD: The Atherosclerosis Risk in Communities (ARIC) Study

Carotid intima-media thickness has been reported to predict kidney function decline. However, whether carotid intima-media thickness is associated with a hard kidney end point, ESRD, has not been investigated

Lifetime Risk of Lower-Extremity Peripheral Artery Disease Defined by Ankle-Brachial Index in the United States.

Background There are no available lifetime risk estimates of lower-extremity peripheral artery disease (PAD). Methods and Results Using data from 6 US community-based cohorts and the vital statistics, we estimated the prevalence and incidence of PAD, defined as an ankle-brachial index&nbsp;&lt;&nbsp;0.90, at each year of age from birth to 80&nbsp;years for white, black, and Hispanic men and women. Then, we used Markov Monte Carlo simulations in a simulated cohort of 100&nbsp;000 individuals to estimate lifetime risk of PAD. On the basis of odds ratios of PAD for traditional atherosclerotic risk factors (eg, diabetes mellitus and smoking), we developed a calculator providing residual lifetime risk of PAD. In an 80-year horizon, lifetime risks of PAD were 30.0% in black men and 27.6% in black women, but ≈19% in white men and women and ≈22% in Hispanic men and women. From another perspective, 9% of blacks were estimated to develop PAD by 60&nbsp;years of age, while the same proportion was seen at ≈70&nbsp;years for whites and Hispanics. The residual lifetime risk within the same race/ethnicity varied by 3.5- to 5-fold according to risk factors (eg, residual lifetime risk in 45-year-old black men was 19.9% when current smoking, diabetes mellitus, and history of cardiovascular disease were absent versus 70.4% when all were present). Conclusions In the United States, ≈30% of blacks are estimated to develop PAD during their lifetime, whereas the corresponding estimate is ≈20% for whites and Hispanics. The residual lifetime risk within the same race/ethnicity substantially varies according to traditional risk factors

A bidirectional Mendelian randomization study supports causal effects of kidney function on blood pressure

Blood pressure and kidney function have a bidirectional relation. Hypertension has long been considered as a risk factor for kidney function decline. However, whether intensive blood pressure control could promote kidney health has been uncertain. The kidney is known to have a major role in affecting blood pressure through sodium extraction and regulating electrolyte balance. This bidirectional relation makes causal inference between these two traits difficult. Therefore, to examine the causal relations between these two traits, we performed two-sample Mendelian randomization analyses using summary statistics of large-scale genome-wide association studies. We selected genetic instruments more likely to be specific for kidney function using meta-analyses of complementary kidney function biomarkers (glomerular filtration rate estimated from serum creatinine [eGFRcr], and blood urea nitrogen from the CKDGen Consortium). Systolic and diastolic blood pressure summary statistics were from the International Consortium for Blood Pressure and UK Biobank. Significant evidence supported the causal effects of higher kidney function on lower blood pressure. Based on the mode-based Mendelian randomization method, the effect estimates for one standard deviation (SD) higher in log-transformed eGFRcr was -0.17 SD unit (95 % confidence interval: -0.09 to -0.24) in systolic blood pressure and -0.15 SD unit (95% confidence interval: -0.07 to -0.22) in diastolic blood pressure. In contrast, the causal effects of blood pressure on kidney function were not statistically significant. Thus, our results support causal effects of higher kidney function on lower blood pressure and suggest preventing kidney function decline can reduce the public health burden of hypertension

Iterative Outlier Removal: A Method for Identifying Outliers in Laboratory Recalibration Studies

Extreme values that arise for any reason, including through non-laboratory measurement procedure-related processes (inadequate mixing, evaporation, mislabeling), lead to outliers and inflate errors in recalibration studies. We present an approach termed iterative outlier removal (IOR) for identifying such outliers

Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

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/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48-2.44) in high-risk CKD (e.g., eGFR 45-59 ml/min/1.73m2 with albuminuria 30-299 mg/g), and 1.37 (1.14-1.69) in moderate risk CKD (e.g., eGFR 60-89 ml/min/1.73m2 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

Treating Early-Stage CKD With New Medication Therapies:Results of a CKD Patient Survey Informing the 2020 NKF-FDA Scientific Workshop on Clinical Trial Considerations for Developing Treatments for Early Stages of Common, Chronic Kidney Diseases

RATIONALE & OBJECTIVE: With a growing number of medications and therapies available to treat chronic kidney disease (CKD), risk-versus-benefit discussions are increasingly critical. Balancing risks and benefits requires assessing patients’ understanding of these, as well as incorporating patient preferences and tolerance for side effects into shared decision making. STUDY DESIGN: A 26-question online survey was sent to people in the National Kidney Foundation patient email list and posted on associated social media pages to assess the respondents’ willingness and comfort with taking preventative medications during earlier-stage CKD to inform a December 2020 scientific workshop co-sponsored by the National Kidney Foundation and the US Food and Drug Administration on clinical trial considerations in developing treatments for individuals with early stages of CKD. SETTING & POPULATION: Online survey of CKD patients, including broad demographic data and responses to risk-benefit scenarios, with surveys emailed to 20,249 people not identified as currently receiving kidney replacement therapy. ANALYTICAL APPROACH: Survey results are presented as descriptive data. RESULTS: Of 1,029 respondents, 45 self-identified as at risk for CKD, 566 had CKD, 267 had received kidney transplants, 51 were receiving dialysis, and 100 replied other or did not answer. Respondents reported being willing to assume some risk with the goal of preventing the progression of CKD, with a greater willingness to assume risk and treatment burdens the closer they came to late-stage disease. Clinician recommendations regarding kidney therapies and clinician willingness to work with patients to address any side effects were important in respondents’ willingness to initiate and persevere with a new medication. LIMITATIONS: Approximately 10% response rate with limited data on respondents. CONCLUSIONS: Risk-versus-benefit discussions appear key to patients and their care partners making well-informed decisions about taking a new medication that may or may not help the progression of their kidney disease. Future tools and strategies are needed to facilitate informed discussions of treatment in early-stage kidney disease

Serum Metabolomic Markers of Protein-Rich Foods and Incident CKD: Results From the Atherosclerosis Risk in Communities Study

RATIONALE & OBJECTIVE: While urine excretion of nitrogen estimates the total protein intake, biomarkers of specific dietary protein sources have been sparsely studied. Using untargeted metabolomics, this study aimed to identify serum metabolomic markers of 6 protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD). STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 3,726 participants from the Atherosclerosis Risk in Communities study without CKD at baseline. EXPOSURES: Dietary intake of 6 protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, and poultry), serum metabolites. OUTCOMES: Incident CKD (estimated glomerular filtration rate \u3c 60 mL/min/1.73 m ANALYTICAL APPROACH: Multivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C statistics assessed the ability of the metabolites to improve the discrimination of highest versus lower 3 quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and the intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident CKD. RESULTS: Thirty significant associations were identified between protein-rich foods and serum metabolites (fish, n = 8; nuts, n = 5; legumes, n = 0; red and processed meat, n = 5; eggs, n = 3; and poultry, n = 9). Metabolites collectively and significantly improved the discrimination of high intake of protein-rich foods compared with covariates alone (difference in C statistics = 0.033, 0.051, 0.003, 0.024, and 0.025 for fish, nuts, red and processed meat, eggs, and poultry-related metabolites, respectively; LIMITATIONS: Residual confounding and sample-storage duration. CONCLUSIONS: We identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with a lower risk of CKD

Genome-Wide association Study of Serum Metabolites in the african american Study of Kidney Disease and Hypertension

The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. to date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73

Identification of Incident CKD Stage 3 in Research Studies

In epidemiologic research, incident chronic kidney disease (CKD) is commonly determined by laboratory tests performed at planned study visits. Given the morbidity and mortality associated with CKD, persons with incident disease may be less likely to attend scheduled visits, affecting observed associations. The objective of this study was to quantify loss-to-follow-up by CKD status, and to determine whether supplementation with diagnostic code data improves capture of incident CKD