Faculty Bibliography

BACKGROUNDMetabolomic profiling in individuals with chronic kidney disease (CKD) has the potential to identify novel biomarkers and provide insight into disease pathogenesis.METHODSWe examined the association between blood metabolites and CKD progression, defined as the subsequent development of end-stage renal disease (ESRD) or estimated glomerular filtrate rate (eGFR) halving, in 1,773 participants of the Chronic Renal Insufficiency Cohort (CRIC) study, 962 participants of the African-American Study of Kidney Disease and Hypertension (AASK), and 5,305 participants of the Atherosclerosis Risk in Communities (ARIC) study.RESULTSIn CRIC, more than half of the measured metabolites were associated with CKD progression in minimally adjusted Cox proportional hazards models, but the number and strength of associations were markedly attenuated by serial adjustment for covariates, particularly eGFR. Ten metabolites were significantly associated with CKD progression in fully adjusted models in CRIC; 3 of these metabolites were also significant in fully adjusted models in AASK and ARIC, highlighting potential markers of glomerular filtration (pseudouridine), histamine metabolism (methylimidazoleacetate), and azotemia (homocitrulline). Our findings also highlight N-acetylserine as a potential marker of kidney tubular function, with significant associations with CKD progression observed in CRIC and ARIC.CONCLUSIONOur findings demonstrate the application of metabolomics to identify potential biomarkers and causal pathways in CKD progression.FUNDINGThis study was supported by the NIH (U01 DK106981, U01 DK106982, U01 DK085689, R01 DK108803, and R01 DK124399).

RATIONALE & OBJECTIVE:Acute kidney injury (AKI) causes biochemical changes in the brain in animal models and is associated with adverse neurological complications in hospitalized patients. This study tested the association between AKI and incident dementia in a community-based cohort. STUDY DESIGN:Prospective cohort study. SETTING & PARTICIPANTS:Adult participants in the Atherosclerosis Risk in Communities (ARIC) study who experienced hospitalized AKI compared with participants hospitalized for other reasons (primary analysis, mean follow-up period 4.3 years) or participants without hospitalized AKI (secondary analysis). PREDICTORS:Incident AKI, defined by ICD codes from hospital records. OUTCOME:Incident dementia, diagnosed based on a combination of neurocognitive testing, informant interviews, ICD codes, and death certificates. ANALYTICAL APPROACH:In the primary analysis, we estimated the propensity for hospitalized AKI and matched these participants with those hospitalized for another reason to examine the association of AKI with subsequent onset of dementia (N = 1,708). In the secondary analysis, we estimated the association between time-varying hospitalized AKI and subsequent onset of dementia using multivariable Cox proportional hazards regression models, adjusted for age, sex, race/center, education, smoking status, body mass index, baseline estimated glomerular filtration rate, baseline urinary albumin-creatinine ratio, systolic blood pressure, coronary heart disease, diabetes, hypertension, apolipoprotein E (APOE) ε4 allele, and C-reactive protein. RESULTS:The mean age in the propensity-matched cohort was 76.1 ± 6.5 (SD) years, and 53.2% of the participants were women. People who were hospitalized with AKI had a higher risk of dementia (HR, 1.25 [95% CI, 1.02-1.52]; P = 0.03) compared with those without a hospitalization for AKI. The associations were slightly stronger in the time-varying analysis (HR, 1.69 [95% CI, 1.48-1.92]; P < 0.001). Other risk factors for dementia included older age, male sex, higher albuminuria, diabetes, current smoker status, and presence of the APOE risk alleles. LIMITATIONS:Observational study, with AKI identified through diagnosis codes. CONCLUSIONS:Participants who experienced a hospitalization for AKI were at increased risk of dementia.

OBJECTIVE:To predict adverse kidney outcomes for use in optimizing medical management and clinical trial design. RESEARCH DESIGN AND METHODS/METHODS:In this meta-analysis of individual participant data, 43 cohorts (N = 1,621,817) from research studies, electronic medical records, and clinical trials with global representation were separated into development and validation cohorts. Models were developed and validated within strata of diabetes mellitus (presence or absence) and estimated glomerular filtration rate (eGFR; ≥60 or <60 mL/min/1.73 m2) to predict a composite of ≥40% decline in eGFR or kidney failure (i.e., receipt of kidney replacement therapy) over 2-3 years. RESULTS:There were 17,399 and 24,591 events in development and validation cohorts, respectively. Models predicting ≥40% eGFR decline or kidney failure incorporated age, sex, eGFR, albuminuria, systolic blood pressure, antihypertensive medication use, history of heart failure, coronary heart disease, atrial fibrillation, smoking status, and BMI, and, in those with diabetes, hemoglobin A1c, insulin use, and oral diabetes medication use. The median C-statistic was 0.774 (interquartile range [IQR] = 0.753, 0.782) in the diabetes and higher-eGFR validation cohorts; 0.769 (IQR = 0.758, 0.808) in the diabetes and lower-eGFR validation cohorts; 0.740 (IQR = 0.717, 0.763) in the no diabetes and higher-eGFR validation cohorts; and 0.750 (IQR = 0.731, 0.785) in the no diabetes and lower-eGFR validation cohorts. Incorporating the previous 2-year eGFR slope minimally improved model performance, and then only in the higher-eGFR cohorts. CONCLUSIONS:Novel prediction equations for a decline of ≥40% in eGFR can be applied successfully for use in the general population in persons with and without diabetes with higher or lower eGFR.

RATIONALE & OBJECTIVE/UNASSIGNED:Novel metabolite biomarkers of kidney failure with replacement therapy (KFRT) may help identify people at high risk for adverse kidney outcomes and implicated pathways may aid in developing targeted therapeutics. STUDY DESIGN/UNASSIGNED:Prospective cohort. SETTING & PARTICIPANTS/UNASSIGNED:The cohort included 3,799 Atherosclerosis Risk in Communities study participants with serum samples available for measurement at visit 1 (1987-1989). EXPOSURE/UNASSIGNED:Baseline serum levels of 318 metabolites. OUTCOMES/UNASSIGNED:, or death from kidney disease). ANALYTICAL APPROACH/UNASSIGNED:Because metabolites are often intercorrelated and represent shared pathways, we used a high dimension reduction technique called Netboost to cluster metabolites. Longitudinal associations between clusters of metabolites and KFRT and kidney failure were estimated using a Cox proportional hazards model. RESULTS/UNASSIGNED:Mean age of study participants was 53 years, 61% were African American, and 13% had diabetes. There were 160 KFRT cases and 357 kidney failure cases over a mean of 23 years. The 314 metabolites were grouped in 43 clusters. Four clusters were significantly associated with risk of KFRT and 6 were associated with kidney failure (including 3 shared clusters). The 3 shared clusters suggested potential pathways perturbed early in kidney disease: cluster 5 (15 metabolites involved in alanine, aspartate, and glutamate metabolism as well as 5-oxoproline and several gamma-glutamyl amino acids), cluster 26 (6 metabolites involved in sugar and inositol phosphate metabolism), and cluster 34 (21 metabolites involved in glycerophospholipid metabolism). Several individual metabolites were also significantly associated with both KFRT and kidney failure, including glucose and mannose, which were associated with higher risk of both outcomes, and 5-oxoproline, gamma-glutamyl amino acids, linoleoylglycerophosphocholine, 1,5-anhydroglucitol, which were associated with lower risk of both outcomes. LIMITATIONS/UNASSIGNED:Inability to determine if the metabolites cause or are a consequence of changes in kidney function. CONCLUSIONS/UNASSIGNED:We identified several clusters of metabolites reproducibly associated with development of KFRT. Future experimental studies are needed to validate our findings as well as continue unraveling metabolic pathways involved in kidney function decline.

BACKGROUND:Despite reports of hematuria and proteinuria with rosuvastatin use at the time of its approval by the US Food and Drug Association (FDA), little postmarketing surveillance exists to assess real-world risk. Current labeling suggests dose reduction (maximum daily dose of 10 mg) for patients with severe CKD. METHODS:Using deidentified electronic health record data, we analyzed 152,101 and 795,799 new users of rosuvastatin and atorvastatin, respectively, from 2011 to 2019. We estimated inverse probability of treatment-weighted hazard ratios (HRs) of hematuria, proteinuria, and kidney failure with replacement therapy (KFRT) associated with rosuvastatin. We reported the initial rosuvastatin dose across eGFR categories and evaluated for a dose effect on hematuria and proteinuria. RESULTS:was prescribed high-dose rosuvastatin (20 or 40 mg daily). Risk was higher with higher rosuvastatin dose. CONCLUSIONS:, 44% were prescribed a rosuvastatin daily dose exceeding the FDA's recommended 10 mg daily dose. Our findings suggest the need for greater care in prescribing and monitoring rosuvastatin, particularly in patients who receive high doses, or who have severe CKD.

Importance:At a given estimated glomerular filtration rate (eGFR), individuals who are Black have higher rates of mortality and kidney failure with replacement therapy (KFRT) compared with those who are non-Black. Whether the recently adopted eGFR equations without race preserve racial differences in risk of mortality and KFRT at a given eGFR is unknown. Objective:To assess whether eGFR equations with and without race and cystatin C document racial differences in risk of KFRT and mortality in populations including Black and non-Black participants. Design, Setting, and Participants:Retrospective individual-level data analysis of 62 011 participants from 5 general population and 3 chronic kidney disease (CKD) US-based cohorts with serum creatinine, cystatin C, and follow-up for KFRT and mortality from 1988 to 2018. Exposures:Chronic Kidney Disease Epidemiology Collaboration equation with serum creatinine (eGFRcr with and without race), cystatin C (eGFRcys without race), or both markers (eGFRcr-cys without race). Main Outcomes and Measures:The prevalence of decreased eGFR at baseline and hazard ratios of KFRT and mortality in Black vs non-Black participants were calculated, adjusted for age and sex. Analyses were performed within each cohort and with random-effect meta-analyses of the models. Results:Among 62 011 participants (20 773 Black and 41 238 non-Black; mean age, 63 years; 53% women), the prevalence ratio (95% CI; percent prevalences) of eGFR less than 60 mL/min/1.73 m2 comparing Black with non-Black participants was 0.98 (95% CI, 0.93-1.03; 11% vs 12%) for eGFRcr with race, 0.95 (95% CI, 0.91-0.98; 17% vs 18%) for eGFRcys, and 1.2 (95% CI, 1.2-1.3; 13% vs 11%) for eGFRcr-cys but was 1.8 (95% CI, 1.7-1.8; 15% vs 9%) for eGFRcr without race. During a mean follow-up of 13 years, 8% and 4% of Black and non-Black participants experienced KFRT and 34% and 39% died, respectively. Decreased eGFR was associated with significantly greater risk of both outcomes for all equations. At an eGFR of 60 mL/min/1.73 m2, the hazard ratios for KFRT comparing Black with non-Black participants were 2.8 (95% CI, 1.6-4.9) for eGFRcr with race, 3.0 (95% CI, 1.5-5.8) for eGFRcys, and 2.8 (95% CI, 1.4-5.4) for eGFRcr-cys vs 1.3 (95% CI, 0.8-2.1) for eGFRcr without race. The 5-year absolute risk differences for KFRT comparing Black with non-Black participants were 1.4% (95% CI, 0.2%-2.6%) for eGFRcr with race, 1.1% (95% CI, 0.2%-1.9%) for eGFRcys, and 1.3% (95% CI, 0%-2.6%) for eGFRcr-cys vs 0.37% (95% CI, -0.32% to 1.05%) for eGFRcr without race. Similar patterns were observed for mortality. Conclusions and Relevance:In this retrospective analysis of 8 US cohorts including Black and non-Black individuals, the eGFR equation without race that included creatinine and cystatin C, but not the eGFR equation without race that included creatinine without cystatin C, demonstrated racial differences in the risk of KFRT and mortality throughout the range of eGFR. The eGFRcr-cys equation may be preferable to the eGFRcr equation without race for assessing racial differences in the risk of KFRT and mortality associated with low eGFR.

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m² in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Novel aptamer-based technologies can identify >7000 analytes per sample, offering a high-throughput alternative to traditional immunoassays in biomarker discovery. However, the specificity for distinct proteins has not been thoroughly studied in the context of CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS/METHODS:We assessed the use of SOMAscan, an aptamer-based technology, for the quantification of eight immune activation biomarkers and cystatin C among 498 African American Study of Kidney Disease and Hypertension (AASK) participants using immunoassays as the gold standard. We evaluated correlations of serum proteins as measured by SOMAscan versus immunoassays with each other and with iothalamate-measured GFR. We then compared associations between proteins measurement with risks of incident kidney failure and all-cause mortality. RESULTS:both methods. On average, immunoassay measurements were more strongly associated with adverse outcomes than their SOMAscan counterparts. CONCLUSIONS:SOMAscan is an efficient and relatively reliable technique for quantifying IL-8, TNFRSF1B, cystatin C, and TNFRSF1A in CKD and detecting their potential associations with clinical outcomes.PodcastThis article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_02_23_CJN11700921.mp3.

BACKGROUND:Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (eGFR). The relationship between polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. METHODS:=8866) with incident CKD, ESKD, kidney failure, and AKI. We also examined associations between the PRS and 4877 plasma proteins measured at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. RESULTS:-1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for five proteins, including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. CONCLUSIONS:A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.

[Figure: see text].