Faculty Bibliography

OBJECTIVE: Atherosclerosis is exaggerated in African American (AA) systemic lupus erythematosus (SLE) patients, with doubled cardiovascular disease (CVD) risk compared to White patients. The extent to which common Apolipoprotein L1 (APOL1) risk alleles (RA) contribute to this trend is unknown. This retrospective cohort study assessed prevalent atherosclerotic disease across APOL1 genotypes in AA SLE patients. METHODS: One hundred thirteen AA SLE subjects were APOL1-genotyped and stratified as having: zero risk alleles, one risk allele, or two risk alleles. Chart review assessed CVD manifestations including abdominal aortic aneurysm, angina, carotid artery disease, coronary artery disease, myocardial infarction, peripheral vascular disease, stroke, and vascular calcifications. Associations between the genotypes and a composite endpoint defined as one or more CVD manifestations were calculated using logistic regression. Symptomatic atherosclerotic disease, excluding incidental vascular calcifications, was also assessed. RESULTS: The 0-risk-allele, 1-risk-allele and 2-risk-allele groups, respectively, comprised 34%, 53%, and 13% of the cohort. Respectively, 13.2%, 41.7%, and 60.0% of the 0-risk allele, 1-risk-allele, and 2-risk-allele groups met the composite endpoint of atherosclerotic CVD (p = 0.001). Adjusting for risk factors-including smoking, ESRD, BMI >25 and hypertension-we observed an association between carrying one or more RA and atherosclerotic CVD (OR = 7.1; p = 0.002). For symptomatic disease, the OR was 3.5 (p = 0.02). In a time-to-event analysis, the proportion of subjects free from the composite primary endpoint, symptomatic atherosclerotic CVD, was higher in the 0-risk-allele group compared to the 1-risk-allele and 2-risk-allele groups (chi2 = 6.5; p = 0.04). CONCLUSIONS: Taken together, the APOL1 RAs associate with prevalent atherosclerotic CVD in this cohort of AA SLE patients, perhaps reflecting a potentiating effect of SLE on APOL1-related cardiovascular phenotypes.

BACKGROUND:Prior work suggests that obesity may confer a survival advantage among persons with cardiovascular disease (CVD). This obesity "paradox" is frequently studied in the context of prevalent disease, a stage in the disease process when confounding from illness-related weight loss and selective survival are especially problematic. Our objective was to examine the association of obesity with mortality among persons with incident CVD, where biases are potentially reduced, and to compare these findings with those based on prevalent disease. METHODS:We used data from the Health and Retirement Study, an ongoing, nationally representative longitudinal survey of U.S. adults age 50 years and older initiated in 1992 and linked to Medicare claims. Cox proportional hazard models were used to estimate the association between weight status and mortality among persons with specific CVD diagnoses. CVD diagnoses were established by self-reported survey data as well as Medicare claims. Prevalent disease models used concurrent weight status, and incident disease models used pre-diagnosis weight status. RESULTS:We examined myocardial infarction, congestive heart failure, stroke, and ischemic heart disease. A strong and significant obesity paradox was consistently observed in prevalent disease models (hazard of death 18-36% lower for obese class I relative to normal weight), replicating prior findings. However, in incident disease models of the same conditions in the same dataset, there was no evidence of this survival benefit. Findings from models using survey- vs. claims-based diagnoses were largely consistent. CONCLUSION/CONCLUSIONS:We observed an obesity paradox in prevalent CVD, replicating prior findings in a population-based sample with longer-term follow-up. In incident CVD, however, we did not find evidence of a survival advantage for obesity. Our findings do not offer support for reevaluating clinical and public health guidelines in pursuit of a potential obesity paradox.

The number of individuals with prediabetes is expected to grow substantially and estimated to globally affect 482 million people by 2040. Therefore, effective methods for diagnosing prediabetes will be required to reduce the risk of progressing to diabetes and its complications. The current biomarkers, glycated hemoglobin (HbA1c), fructosamine, and glycated albumin have limitations including moderate sensitivity and specificity and are inaccurate in certain clinical conditions. Therefore, identification of additional biomarkers is being explored recognizing that any single biomarker will also likely have inherent limitations. Therefore, combining several biomarkers may more precisely identify those at high risk for developing prediabetes and subsequent progression to diabetes. This review describes recently identified biomarkers and their potential utility for addressing the burgeoning epidemic of dysglycemic disorders.

INTRODUCTION/BACKGROUND:The objective of this study was to investigate whether 10 phospholipids/metabolites previously identified as prospectively predictive of mild cognitive impairment (MCI) or dementia in whites would also be predictive in a mostly African-American cohort. METHODS:We repeatedly measured 188 phospholipids/metabolites in plasma samples of 221 participants of the Atherosclerosis Risk in Communities study, 97% African American, who were followed between 2004-2006 and 2011-2013. RESULTS:After a mean follow-up of 7.3 years, 77 were classified as having MCI and 18 as having dementia. Our study failed to replicate previous findings in this mostly African American cohort, in that the 10 phospholipids/metabolites only achieved a C statistic/AUC of 0.609 in predicting development of MCI or dementia (compared to 0.96) and 0.607 in distinguishing normal from MCI or dementia at the follow-up visit. CONCLUSION/CONCLUSIONS:A panel of 10 phospholipids/metabolites previously associated with incident dementia was not predictive of MCI or dementia in an independent cohort.

Genome-wide association studies (GWAS) using single nucleotide polymorphisms (SNPs) have identified more than 50 loci associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. However, significant SNPs account for a small proportion of eGFR variability. Other forms of genetic variation have not been comprehensively evaluated for association with eGFR. In this study, we assess whether changes in germline DNA copy number are associated with GFR estimated from serum creatinine, eGFRcrea. We used hidden Markov models (HMMs) to identify copy number polymorphic regions (CNPs) from high-throughput SNP arrays for 2,514 African (AA) and 8,645 European ancestry (EA) participants in the Atherosclerosis Risk in Communities (ARIC) study. Separately for the EA and AA cohorts, we used Bayesian Gaussian mixture models to estimate copy number at regions identified by the HMM or previously reported in the HapMap Project. We identified 312 and 464 autosomal CNPs among individuals of EA and AA, respectively. Multivariate models adjusted for SNP-derived covariates of population structure identified one CNP in the EA cohort near genome-wide statistical significance (Bonferroni-adjusted p = 0.067) located on chromosome 5 (876-880kb). Overall, our findings suggest a limited role of CNPs in explaining eGFR variability.