Metabolites Associated With Uremic Symptoms in Patients With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: The toxins that contribute to uremic symptoms in patients with chronic kidney disease (CKD) are unknown. We sought to apply complementary statistical modeling approaches to data from untargeted plasma metabolomic profiling to identify solutes associated with uremic symptoms in patients with CKD. STUDY DESIGN: Cross-sectional. SETTING & PARTICIPANTS: 1,761 Chronic Renal Insufficiency Cohort (CRIC) participants with CKD not treated with dialysis. PREDICTORS: Measurement of 448 known plasma metabolites. OUTCOMES: The uremic symptoms of fatigue, anorexia, pruritus, nausea, paresthesia, and pain were assessed by single items on the Kidney Disease Quality of Life-36 instrument. ANALYTICAL APPROACH: Multivariable adjusted linear regression, least absolute shrinkage and selection operator linear regression, and random forest models were used to identify metabolites associated with symptom severity. After adjustment for multiple comparisons, metabolites selected in at least 2 of the 3 modeling approaches were deemed "overall significant." RESULTS: Participant mean estimated glomerular filtration rate was 43mL/min/1.73m2, with 44% self-identifying as female and 41% as non-Hispanic Black. The prevalence of uremic symptoms ranged from 22% to 55%. We identified 17 metabolites for which a higher level was associated with greater severity of at least one uremic symptom and 9 metabolites inversely associated with uremic symptom severity. Many of these metabolites exhibited at least a moderate correlation with estimated glomerular filtration rate (Pearson's r≥0.5), and some were also associated with the risk of developing kidney failure or death in multivariable adjusted Cox regression models. LIMITATIONS: Lack of a second independent cohort for external validation of our findings. CONCLUSIONS: Metabolomic profiling was used to identify multiple solutes associated with uremic symptoms in adults with CKD, but future validation and mechanistic studies are needed. PLAIN-LANGUAGE SUMMARY: Individuals living with chronic kidney disease (CKD) often experience symptoms related to CKD, traditionally called uremic symptoms. It is likely that CKD results in alterations in the levels of numerous circulating substances that, in turn, cause uremic symptoms; however, the identity of these solutes is not known. In this study, we used metabolomic profiling in patients with CKD to gain insights into the pathophysiology of uremic symptoms. We identified 26 metabolites whose levels were significantly associated with at least one of the symptoms of fatigue, anorexia, itchiness, nausea, paresthesia, and pain. The results of this study lay the groundwork for future research into the biological causes of symptoms in patients with CKD.

A generalized covariate-adjusted top-scoring pair algorithm with applications to diabetic kidney disease stage classification in the Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: The growing amount of high dimensional biomolecular data has spawned new statistical and computational models for risk prediction and disease classification. Yet, many of these methods do not yield biologically interpretable models, despite offering high classification accuracy. An exception, the top-scoring pair (TSP) algorithm derives parameter-free, biologically interpretable single pair decision rules that are accurate and robust in disease classification. However, standard TSP methods do not accommodate covariates that could heavily influence feature selection for the top-scoring pair. Herein, we propose a covariate-adjusted TSP method, which uses residuals from a regression of features on the covariates for identifying top scoring pairs. We conduct simulations and a data application to investigate our method, and compare it to existing classifiers, LASSO and random forests. RESULTS: Our simulations found that features that were highly correlated with clinical variables had high likelihood of being selected as top scoring pairs in the standard TSP setting. However, through residualization, our covariate-adjusted TSP was able to identify new top scoring pairs, that were largely uncorrelated with clinical variables. In the data application, using patients with diabetes (n = 977) selected for metabolomic profiling in the Chronic Renal Insufficiency Cohort (CRIC) study, the standard TSP algorithm identified (valine-betaine, dimethyl-arg) as the top-scoring metabolite pair for classifying diabetic kidney disease (DKD) severity, whereas the covariate-adjusted TSP method identified the pair (pipazethate, octaethylene glycol) as top-scoring. Valine-betaine and dimethyl-arg had, respectively, ≥ 0.4 absolute correlation with urine albumin and serum creatinine, known prognosticators of DKD. Thus without covariate-adjustment the top-scoring pair largely reflected known markers of disease severity, whereas covariate-adjusted TSP uncovered features liberated from confounding, and identified independent prognostic markers of DKD severity. Furthermore, TSP-based methods achieved competitive classification accuracy in DKD to LASSO and random forests, while providing more parsimonious models. CONCLUSIONS: We extended TSP-based methods to account for covariates, via a simple, easy to implement residualizing process. Our covariate-adjusted TSP method identified metabolite features, uncorrelated from clinical covariates, that discriminate DKD severity stage based on the relative ordering between two features, and thus provide insights into future studies on the order reversals in early vs advanced disease states.

A culturally informed model to enhance breast, cervical, and colorectal cancer screenings: perspectives of American Indian adults and healthcare providers in rural New Mexico.

PURPOSE: American Indian/Alaska Native (AI/AN) populations have some of the lowest cancer screening rates compared to other racial/ethnic populations. Using community-based participatory research methods, we sought to characterize knowledge, attitudes, beliefs, and approaches to enhance breast, colorectal, and cervical cancer screening. METHODS: We conducted 12 focus groups between October 2018 and September 2019 with 96 eligible AI adults and healthcare providers, recruited using non-probability purposive sampling methods from the Zuni Pueblo in rural New Mexico. We used the Multi-level Health Outcomes Framework (MHOF) to conduct a qualitative content analysis identifying mutable systems- and individual- level constructs important for behavior change that we crosslinked with the Community Preventive Services Task Force (CPSTF) recommended evidence-based interventions (EBIs) or approaches. RESULTS: Salient systems-level factors that limited uptake of cancer screenings included inflexible clinic hours, transportation barriers, no on-demand service and reminder systems, and brief doctor-patient encounters. Individual-level barriers included variable cancer-specific knowledge that translated into fatalistic beliefs, fear, and denial. Interventions to enhance community demand and access for screening should include one-on-one and group education, small media, mailed screening tests, and home visitations by public health nurses. Interventions to enhance provider delivery of screening services should include translation and case management services. CONCLUSIONS: The MHOF constructs crosslinked with CPSTF recommended EBIs or approaches provided a unique perspective to frame barriers and promoters of screening utilization and insights for intervention development. Findings inform the development of culturally tailored, theoretically informed, multi-component interventions concordant with CPSTF recommended EBIs or approaches aimed at improving cancer screening.

The Otago Exercise Program compared to falls prevention education in Zuni elders: a randomized controlled trial.

BACKGROUND: When a Zuni elder sustains a fall-related injury, the closest tribal skilled nursing facility is 100 miles from the Pueblo and no physical therapy services are available. Thus, fall prevention strategies as a primary intervention to avert injurious falls and preserve aging in place are needed. The objective of the study is to compare the effectiveness of a community health representative (CHR)-delivered, culturally-adapted Otago Exercise Program (OEP) fall prevention program compared to the standard of care education-based fall risk management. METHODS: "Standing Strong in Tribal Communities: Assessing Elder Falls Disparity" is mixed-methods research with a randomized controlled trial. The CHRs will be trained to deliver the culturally-adapted OEP trial and offer advantages of speaking "Shiwi" (Zuni tribal language) and understanding Zuni traditions, family structures, and elders' preferences for receiving health information. Focus groups will be conducted to assure all materials are culturally appropriate, and adapted. A physical therapist will train CHRs to screen elders for falls risk and to deliver the OEP to the intervention group and education to the control group. Up to 400 Zuni elders will be screened by the CHRs for falls risk and 200 elders will be enrolled into the study (1:1 random allocation by household). The intervention is 6 months with measurements at baseline, 3, 6 and 12 months. The primary outcome is improved strength and balance (timed up and go, sit to stand and 4 stage balance test), secondary outcomes include falls incidence, self-efficacy using Attitudes to Falls-Related Interventions Scale, Medical Outcomes Study Short Form 12 (SF-12v2) and Self-Efficacy for Managing Daily Activities. DISCUSSION: Fall prevention for Zuni elders was identified as a tribal priority and this trial is built upon longstanding collaborations between the investigative team, Zuni tribal leaders, and multiple tribal health programs. Delivery by the CHRs make this model more acceptable, and thus, more sustainable long term. This study has the potential to change best practice for elder care in tribal and rural areas with limited access to physical therapist-delivered fall prevention interventions and aligns with tribal goals to avert fall-related injury, reduce healthcare disparity, and preserve elder's independence. TRIAL REGISTRATION: NCT04876729.

Assessing Knowledge and Perceptions About Cancer Among American Indians of the Zuni Pueblo, NM.

American Indians (AIs) in New Mexico have lower cancer screening rates compared to other populations and are more likely to be diagnosed with cancer at an advanced stage of the disease as reported by Li et al. (Archives of Internal Medicine 163(1):49-56, 2003). AIs also have the lowest 5-year cancer survival rates compared to any ethnic/racial group in the USA as reported by Clegg et al. (Arch Intern Med 162:1985-1993, 2002) and Edwards et al. (Cancer 97:1407-1427, 2005). Numerous barriers such as cultural beliefs, fear, fatalism, mistrust, stigma, and lack of culturally appropriate interventions could contribute to low cancer screening rates as reported by Daley et al. (J Health Dispar Res Pract 5(2), 2012); Filippi et al. (J Prim Care Community Health 4(3):160-166, 2013); James et al. (Prev Chronic Dis 10:E170, 2013); and Schumacher et al. (Cancer Causes Control 19(7):725-737, 2008). Trained Community Health Representatives (CHRs) from the Zuni Pueblo and native Zuni undergraduate students led six 1-h focus group sessions using a structured focus group guide with probes. The focus groups were conducted among 51 participants from different age groups (20-29 years, n = 19; 30-49 years, n = 17; and 50 years and older, n = 15) stratified by sex. Focus groups were conducted in both English and Shiwi (Zuni) languages. Sessions were audio recorded, and team members took notes. CHRs transcribed the notes and audio recordings, and created a codebook for qualitative data analysis. In the focus groups, participants provided Zuni-specific cultural context, opinion, and experience regarding (1) general knowledge about cancer, (2) cancer risk, (3) cancer risk reduction, (4) personal experiences with cancer, and (5) culturally competent delivery of cancer information and resources. Understanding the perceptions of cancer within the Zuni Pueblo is an essential component in the development of interventional/preventative measures and improvement of current care. Ultimately, this information will provide a basis for the next steps in culturally sensitive cancer care for the Zuni Pueblo.

High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets.

BACKGROUND: Converting electronic health record (EHR) entries to useful clinical inferences requires one to address the poor scalability of existing implementations of Generalized Linear Mixed Models (GLMM) for repeated measures. The major computational bottleneck concerns the numerical evaluation of multivariable integrals, which even for the simplest EHR analyses may involve millions of dimensions (one for each patient). The hierarchical likelihood (h-lik) approach to GLMMs is a methodologically rigorous framework for the estimation of GLMMs that is based on the Laplace Approximation (LA), which replaces integration with numerical optimization, and thus scales very well with dimensionality. METHODS: We present a high-performance, direct implementation of the h-lik for GLMMs in the R package TMB. Using this approach, we examined the relation of repeated serum potassium measurements and survival in the Cerner Real World Data (CRWD) EHR database. Analyzing this data requires the evaluation of an integral in over 3 million dimensions, putting this problem beyond the reach of conventional approaches. We also assessed the scalability and accuracy of LA in smaller samples of 1 and 10% size of the full dataset that were analyzed via the a) original, interconnected Generalized Linear Models (iGLM), approach to h-lik, b) Adaptive Gaussian Hermite (AGH) and c) the gold standard for multivariate integration Markov Chain Monte Carlo (MCMC). RESULTS: Random effects estimates generated by the LA were within 10% of the values obtained by the iGLMs, AGH and MCMC techniques. The H-lik approach was 4-30 times faster than AGH and nearly 800 times faster than MCMC. The major clinical inferences in this problem are the establishment of the non-linear relationship between the potassium level and the risk of mortality, as well as estimates of the individual and health care facility sources of variations for mortality risk in CRWD. CONCLUSIONS: We found that the direct implementation of the h-lik offers a computationally efficient, numerically accurate approach for the analysis of extremely large, real world repeated measures data via the h-lik approach to GLMMs. The clinical inference from our analysis may guide choices of treatment thresholds for treating potassium disorders in the clinic.

Early Patient-Centered Outcomes Research Experience With the Use of Telehealth to Address Disparities: Scoping Review.

BACKGROUND: Health systems and providers across America are increasingly employing telehealth technologies to better serve medically underserved low-income, minority, and rural populations at the highest risk for health disparities. The Patient-Centered Outcomes Research Institute (PCORI) has invested US $386 million in comparative effectiveness research in telehealth, yet little is known about the key early lessons garnered from this research regarding the best practices in using telehealth to address disparities. OBJECTIVE: This paper describes preliminary lessons from the body of research using study findings and case studies drawn from PCORI seminal patient-centered outcomes research (PCOR) initiatives. The primary purpose was to identify common barriers and facilitators to implementing telehealth technologies in populations at risk for disparities. METHODS: A systematic scoping review of telehealth studies addressing disparities was performed. It was guided by the Arksey and O'Malley Scoping Review Framework and focused on PCORI's active portfolio of telehealth studies and key PCOR identified by study investigators. We drew on this broad literature using illustrative examples from early PCOR experience and published literature to assess barriers and facilitators to implementing telehealth in populations at risk for disparities, using the active implementation framework to extract data. Major themes regarding how telehealth interventions can overcome barriers to telehealth adoption and implementation were identified through this review using an iterative Delphi process to achieve consensus among the PCORI investigators participating in the study. RESULTS: PCORI has funded 89 comparative effectiveness studies in telehealth, of which 41 assessed the use of telehealth to improve outcomes for populations at risk for health disparities. These 41 studies employed various overlapping modalities including mobile devices (29/41, 71%), web-based interventions (30/41, 73%), real-time videoconferencing (15/41, 37%), remote patient monitoring (8/41, 20%), and store-and-forward (ie, asynchronous electronic transmission) interventions (4/41, 10%). The studies targeted one or more of PCORI's priority populations, including racial and ethnic minorities (31/41, 41%), people living in rural areas, and those with low income/low socioeconomic status, low health literacy, or disabilities. Major themes identified across these studies included the importance of patient-centered design, cultural tailoring of telehealth solutions, delivering telehealth through trusted intermediaries, partnering with payers to expand telehealth reimbursement, and ensuring confidential sharing of private information. CONCLUSIONS: Early PCOR evidence suggests that the most effective health system- and provider-level telehealth implementation solutions to address disparities employ patient-centered and culturally tailored telehealth solutions whose development is actively guided by the patients themselves to meet the needs of specific communities and populations. Further, this evidence shows that the best practices in telehealth implementation include delivery of telehealth through trusted intermediaries, close partnership with payers to facilitate reimbursement and sustainability, and safeguards to ensure patient-guided confidential sharing of personal health information.

American Indian chronic Renal insufficiency cohort study (AI-CRIC study).

BACKGROUND: Chronic kidney disease (CKD) is an increasing epidemic globally that is associated with adverse health outcomes including end stage kidney disease (ESKD), cardiovascular disease (CVD), and death. American Indians (AIs) have a higher prevalence of CKD than most other racial/ethnic groups, due in part to a high prevalence of type 2 diabetes. Other genetic and environmental factors not yet identified may also contribute to the disproportionate burden of CKD in AIs. METHOD: We will establish 3 clinical centers to recruit AIs from the Southwest United States (US) to expand the Chronic Renal Insufficiency Cohort (CRIC) study. We will follow the current CRIC protocol for kidney and cardiovascular measures and outcomes, which include ambulatory monitoring of kidney function and the use of mobile health technologies for CVD sub-phenotyping, and compare the outcomes in AIs with those in other racial/ethnic groups in CRIC. DISCUSSION: AI-CRIC will identify the role of various risk factors for rapid loss of kidney function among AIs of the Southwest US. In addition, to better understand the natural history of CKD and CVD in this high-risk population, we will identify unique risk factors for CKD and CVD progression in AIs. We will also compare event rates and risk factors for kidney and cardiovascular events in AIs with the other populations represented in CRIC.

Impact of Isolyte Versus 0.9% Saline on Postoperative Event of Acute Kidney Injury Assayed by Urinary [TIMP-2] × [IGFBP7] in Patients Undergoing Cardiac Surgery.

OBJECTIVE: Administration of excess chloride in 0.9% normal saline (NS) decreases renal perfusion and glomerular filtration rate, thereby increasing the risk for acute kidney injury (AKI). In this study, the effect of NS versus Isolyte use during cardiac surgery on urinary levels of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor-binding protein 7 [TIMP-2] × [IGFBP7] and postoperative risk of AKI were examined. DESIGN: Prospective, randomized, and single-blinded trial. SETTING: Single university medical center. PARTICIPANTS: Thirty patients over 18 years without chronic renal insufficiency or recent AKI undergoing elective cardiac surgery. INTERVENTIONS: Subjects were randomized to receive either NS or Isolyte during the intraoperative period. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the change in urinary levels of [TIMP2] × [IGFBP7] from before surgery to 24 hours postoperatively. Secondary outcomes included serum creatinine pre- and postoperatively at 24 and 48 hours, serum chloride pre- and postoperatively at 24 and 48 hours, need for dialysis prior to discharge, and arterial pH measured 24 hours postoperatively. Sixteen patients received NS and 14 patients received Isolyte. Three patients developed AKI within the first 3 postoperative days, all in the NS group. The authors found increases in [TIMP-2] × [IGFBP7] in both groups. However, the difference in this increase between study arms was not significant (p = 0.92; -0.097 to 0.107). CONCLUSION: The authors observed no change in urinary [TIMP-] × [IGFBP7] levels in patients receiving NS versus Isolyte during cardiac surgery. Future larger studies in patients at higher risk for AKI are recommended to evaluate the impact of high- versus lower-chloride solutions on the risk of postoperative AKI after cardiac surgery.

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND).

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.

Using the Centers for Disease Control and Prevention's Stay Independent Checklist to Engage a Community of American Indians and Raise Awareness About Risk of Falls, 2016.

BACKGROUND: The unintentional death rate from falls is higher among American Indians from the US Southwest than from other regions in the country. The Zuni Pueblo is a geographically isolated, rural American Indian community located in western New Mexico. Education and screening for falls risk is lacking in this community and may be needed to reduce falls and falls-related illness and death. COMMUNITY CONTEXT: Building on a 17-year relationship with the Zuni Health Initiative, meetings were held with Zuni tribal leadership, staff from the Zuni Senior Center and Zuni Home Health Services, members of the Zuni Comprehensive Community Health Center, Indian Health Service, and Zuni community health representatives (CHRs) to discuss elder falls in the community. Existing infrastructure, including CHRs who were already trained and certified in diabetes education and prevention, provided support for the study. METHODS: Tribal leadership agreed that CHRs would be trained to administer the Centers for Disease Control and Prevention's (CDC's) Stay Independent checklist to assess falls risk. They administered the checklist during one-on-one interviews in Shiwi (Zuni native language), English, or both to a convenience sample of 50 Zuni elders. OUTCOMES: Mean age of participants was 72 (standard deviation, 7.4) years, and 78% were women. Fifty-two percent reported at least 1 fall during the past year; 66% scored 4 or more on the CDC Stay Independent checklist, indicating elevated risk for falls. CHRs reported that the checklist was easy to administer and culturally accepted by the elder participants. INTERPRETATION: This study broadened the Zuni Health Initiative to include falls risk screening. Self-reported falls were common in this small sample, and the incidence was significantly higher than the national rate. These results highlight the need for community engagement, using culturally acceptable falls screening, to promote falls education and implement falls prevention programs.

Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND).

BACKGROUND: The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample. RESULTS: A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy. CONCLUSIONS: The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.

PERFORMANCE OF A1C VERSUS OGTT FOR THE DIAGNOSIS OF PREDIABETES IN A COMMUNITY-BASED SCREENING.

OBJECTIVE: Reliable identification of individuals at risk for developing diabetes is critical to instituting preventative strategies. Studies suggest that the accuracy of using hemoglobin A1c as a sole diagnostic criterion for diabetes may be variable across different ethnic groups. We postulate that there will be lack of concordance between A1c and the oral glucose tolerance test (OGTT) for diagnosing prediabetes across Hispanic and non-Hispanic white (NHW) populations. METHODS: A total of 218 asymptomatic adults at risk for type 2 diabetes (T2D) were assessed with A1c and OGTT for the diagnosis of prediabetes. Glucose homeostasis status was assigned as no diabetes (A1c <5.7% [39 mmol/mol]), prediabetes (A1c 5.7 to 6.4% [46 mmol/mol]), and T2D (A1c >6.4% [46 mmol/mol]). Inclusion criteria were age >18 years and at least one of the following: a family history of diabetes, a history of gestational diabetes, Hispanic ethnicity, non-Caucasian race, or obesity. Subjects received a fasting 75-g OGTT and A1c on the same day. Bowker's test of symmetry was employed to determine agreement between the tests. RESULTS: Data from 99 Hispanic patients and 79 NHW patients were analyzed. There was no concordance between A1c and OGTT for Hispanic (P = .002) or NHW individuals (P = .003) with prediabetes. CONCLUSION: A1c is discordant with OGTT among Hispanic and NHW subjects for the diagnosis of prediabetes. Sole use of A1c to designate glycemic status will result in a greater prevalence of prediabetes among Hispanic and NHW New Mexicans. ABBREVIATIONS: A1c = hemoglobin A1c BMI = body mass index CDC = Centers for Disease Control CI = confidence interval FPG = fasting plasma glucose NHW = non-Hispanic white OGTT = oral glucose tolerance test T2D = type 2 diabetes WHO = World Health Organization.

Prognostic utility of rhythmic components in 24-h ambulatory blood pressure monitoring for the risk stratification of chronic kidney disease patients with cardiovascular co-morbidity.

Chronic kidney disease (CKD) represents a significant global burden. Hypertension is a modifiable risk factor for rapid progression of CKD. We extend the risk stratification by introducing the non-parametric determination of rhythmic components in 24-h profiles of ambulatory blood pressure monitoring (ABPM) in the Chronic Renal Insufficiency Cohort (CRIC) and the African American Study for Kidney Disease and Hypertension (AASK) cohort using Cox proportional hazards models. We find that rhythmic profiling of BP through JTK_CYCLE analysis identifies subgroups of CRIC participants that were more likely to die due to cardiovascular causes. While our fully adjusted model shows a trend towards a significant association between absent cyclic components and cardiovascular death in the full CRIC cohort (HR: 1.71,95% CI: 0.99-2.97, p = 0.056), CRIC participants with a history of cardiovascular disease (CVD) and absent cyclic components in their BP profile had at any time a 3.4-times higher risk of cardiovascular death than CVD patients with cyclic components present in their BP profile (HR: 3.37, 95% CI: 1.45-7.87, p = 0.005). This increased risk was not explained by the dipping or non-dipping pattern in ABPM. Due to the large differences in patient characteristics, the results do not replicate in the AASK cohort. This study suggests rhythmic blood pressure components as a potential novel biomarker to unmask excess risk among CKD patients with prior cardiovascular disease.

Prognostic utility of rhythmic components in 24-hour ambulatory blood pressure monitoring for the risk stratification of chronic kidney disease patients with cardiovascular co-morbidity.

Background: Chronic kidney disease (CKD) represents a significant global burden. Hypertension is a modifiable risk factor for rapid progression of CKD. Methods: We extend the risk stratification by introducing the non-parametric determination of rhythmic components in 24-hour profiles of ambulatory blood pressure monitoring (ABPM) in the African American Study for Kidney Disease and Hypertension (AASK) cohort and the Chronic Renal Insufficiency Cohort (CRIC) using Cox proportional hazards models. Results: We find that rhythmic profiling of BP through JTK_Cycle analysis identifies subgroups of CRIC participants at advanced risk of cardiovascular death. CRIC participants with a history of cardiovascular disease (CVD) and absent cyclic components in their BP profile had at any time a 3.4-times higher risk of cardiovascular death than CVD patients with cyclic components present in their BP profile (HR: 3.38, 95% CI: 1.45-7.88, p=0.005). This substantially increased risk was independent of whether ABPM followed a dipping or non-dipping pattern whereby non-dipping or reverse dipping were not significantly associated with cardiovascular death in patients with prior CVD (p>0.1). In the AASK cohort, unadjusted models demonstrate a higher risk in reaching end stage renal disease among participants without rhythmic ABPM components (HR:1.80, 95% CI: 1.10-2.96); however, full adjustment abolished this association. Conclusions: This study proposes rhythmic blood pressure components as a novel biomarker to unmask excess risk among CKD patients with prior cardiovascular disease.

Heritability of serum sodium concentration: evidence for sex- and ethnic-specific effects.

Serum sodium concentration is the clinical index of systemic water balance. Although disordered water balance is common and morbid, little is known about genetic effects on serum sodium concentration at the population level. Prior studies addressed only participants of European descent and either failed to demonstrate significant heritability or showed only modest effect. We investigated heritability of serum sodium concentration in large cohorts reflecting a range of races/ethnicities, including the Framingham Heart Study (FHS, non-Hispanic Caucasian), the Heredity and Phenotype Intervention Heart Study (HAPI, Amish Caucasian), the Jackson Heart Study (JHS, African American), the Strong Heart Family Study (SHFS, American Indian), and the Genetics of Kidney Disease in Zuni Indians Study (GKDZI, American Indian). Serum sodium was transformed for the osmotic effect of glucose, and participants with markedly elevated glucose or reduced estimated glomerular filtration rate (eGFR) were excluded. Using a standard variance components method, incorporating covariates of age, glucose, and eGFR, we found heritability to be high in African American and American Indian populations and much more modest in non-Hispanic Caucasian populations. Estimates among females increased after stratification on sex and were suggestive among female participants in FHS (0.18 ± 0.12, P = 0.057) and male participants in JHS (0.24 ± 0.16, P = 0.067) and statistically significant among female participants in JHS (0.44 ± 0.09, P = 1 × 10 ⁻7), SHFS (0.59 ± 0.05, P = 9.4 × 10⁻46), and GKDZI (0.46 ± 0.15, P = 1.7 × 10⁻4), and male participants in HAPI (0.18 ± 0.12, P = 0.03) and SHFS (0.67 ± 0.07, P = 5.4 × 10⁻²6). Exclusion of diuretic users increased heritability among females and was significant in all cohorts where data were available. In aggregate, these data strongly support the heritability of systemic water balance and underscore sex and ethnicity-specific effects.

Examining associations of circulating endotoxin with nutritional status, inflammation, and mortality in hemodialysis patients.

OBJECTIVE: Lipopolysaccharide or endotoxin constitutes most part of the outer portion of the cell wall in the gram-negative bacteria. Subclinical endotoxemia could contribute to increased inflammation and mortality in hemodialysis (HD) patients. Endotoxin level and clinical effect are determined by its soluble receptor sCD14 and high-density lipoprotein. We examine the hypothesis that endotoxin level correlates with mortality. METHODS: In this cohort study, endotoxin levels were measured in 306 long-term HD patients who were then followed up for a maximum of 42 months. Soluble CD14 and cytokines levels were also measured. RESULTS: The mean (±SD) endotoxin level was 2.31 ± 3.10 EU/mL (minimum: 0.26 EU/mL, maximum: 22.94 EU/mL, interquartile range: 1.33 EU/mL, median: 1.27 EU/mL). Endotoxin correlated with C-reactive protein (r = 0.11, P < .04). On multivariate logistic regression analysis, high body mass index and low high-density lipoprotein (HDL) cholesterol levels were associated with higher endotoxemia (endotoxin below or above of median). In multivariate Cox regression analysis adjusted for case-mix and nutritional/inflammatory confounders, endotoxin levels in the third quartile versus first quartile were associated with a trend toward increased hazard ratio for death (hazard ratio: 1.83, 95% confidence interval: 0.93 to 3.6, P = .08). CONCLUSIONS: In this HD cohort, we found associations between endotoxemia and C-reactive protein, body composition, and HDL. Moderately high endotoxin levels tended to correlate with increased mortality than the highest circulating endotoxin level. Additional studies are required to assess the effect of endotoxemia on mortality in dialysis population.

Albuminuria, cognition, and MRI biomarkers of cerebrovascular disease in American Indians of the Zuni Pueblo.

Background: Elevated urine albumin to creatinine ratio (UACR) is associated with cerebrovascular disease and cognitive impairment in older adults, though few studies have evaluated these relationships in midlife. This is particularly important to assess in American Indian populations, which are disproportionately impacted by diabetes and kidney disease. Additionally, evidence suggests that biomarkers may perform differently in underrepresented groups, thus, it is crucial to validate biomarkers in this unique population. Methods: Twenty-five participants from the Zuni Pueblo underwent neuropsychological assessment and an MRI that included fluid attenuated inversion recovery (FLAIR) and diffusion imaging to calculate recently developed MRI markers of cerebrovascular small vessel disease (Peak width of Skeletonized Mean Diffusivity (PSMD), mean free-water fraction (mFW), white matter hyperintensity (WMH)). Results: Regression analyses indicated no significant associations between UACR, MRI biomarkers and cognitive outcomes. Analyses of covariance indicated that the Zuni Indian cohort exhibited reduced white matter damage relative to an existing cohort of older adults with vascular cognitive impairment when accounting for age, sex, and education. Slower processing speed was associated with greater white matter disease across all measures examined. Conclusions: Our pilot study validated the use of MRI biomarkers of cerebrovascular disease in this unique cohort of American Indians.