Faculty Bibliography

CONTEXT:Relative to European Americans, calcified atherosclerotic plaque (CP) is less prevalent and severe in African-Americans (AAs). OBJECTIVE:Predictors of progression of CP in the aorta, carotid, and coronary arteries were examined in AAs over a mean 5.3 ± 1.4-year interval. DESIGN:This is the African American-Diabetes Heart Study. SETTING:A type 2 diabetes (T2D)-affected cohort was included. PARTICIPANTS:A total of 300 unrelated AAs with T2D; 50% female, mean age 55 ± 9 years, baseline hemoglobin A1c 8.1 ± 1.8% was included. MAIN OUTCOME MEASURES:Glycemic control, renal parameters, vitamin D, and computed tomography-derived measures of adiposity, vascular CP, and volumetric bone mineral density (vBMD) in lumbar and thoracic vertebrae were obtained at baseline and follow-up. RESULTS:CP increased in incidence and quantity/mass in all three vascular beds over the 5-year study (P < .0001). Lower baseline lumbar and thoracic vBMD were associated with progression of abdominal aorta CP (P < .008), but not progression of carotid or coronary artery CP. Lower baseline estimated glomerular filtration rate was associated with progression of carotid artery CP (P = .0004), and higher baseline pericardial adipose volume was associated with progression of coronary artery (P = .001) and aorta (P = .0006) CP independent of body mass index. There was a trend for an inverse relationship between change in thoracic vBMD and change in aortic CP (P = .05). CONCLUSIONS:In this longitudinal study, lower baseline thoracic and lumbar vBMD and estimated glomerular filtration rate and higher pericardial adipose volumes were associated with increases in CP in AAs with T2D. Changes in these variables and baseline levels and/or changes in glycemic control, albuminuria, and vitamin D were not significantly associated with progression of CP.

PURPOSE:The development of a sustainable pediatric diabetes surveillance system for the United States requires a better understanding of issues related to case ascertainment. METHODS:Using the SEARCH for Diabetes in Youth registry, we examined whether time from diabetes diagnosis to case registration differed by diabetes type, patient demographics, and the type of provider reporting the case to the study. Plots for time from diagnosis to registration were developed, and differences by key variables were examined using the log-rank test. RESULTS:Compared with time to registration for type 1 cases, it took 2.6 (95% confidence interval [CI], 2.5-2.6) times longer to register 50% of type 2 diabetes cases, and 2.3 (95% CI, 2.0-2.5) times longer to register 90% of type 2 cases. For type 1 diabetes cases, a longer time to registration was associated with older age, minority race/ethnicity, and cases, where the referring provider was not an endocrinologist. For type 2 diabetes cases, older age, non-Hispanic white race/ethnicity, and cases reported by providers other than an endocrinologist took longer to identify and register. CONCLUSIONS:These findings highlight the need for continued childhood diabetes surveillance to identify future trends and influences on changes in prevalence and incidence.

OBJECTIVE:Assess cross-sectional relationships between body mass index (BMI), waist circumference (WC), pericardial (PAT), visceral (VAT), and subcutaneous adipose tissue (SAT) volumes with calcified plaque (CP) in African Americans (AAs) and European Americans (EAs) with type 2 diabetes. METHODS:Computed tomography measured PAT, VAT, SAT, and CP in coronary arteries (CAC), carotid arteries, and aorta. Generalized estimating equations models were fitted to test for associations between adiposity and CP, stratified by ethnicity while accounting for familial correlations. RESULTS:AAs (N = 753) vs. EAs (N = 562) had significantly lower PAT and VAT, despite equal or higher BMI. In multivariable models adjusting for age, gender, education, HbA1c, statins, smoking, cardiovascular disease, hypertension, nephropathy, and C-reactive protein, PAT positively associated with presence of CAC in AAs (P < 0.001), not EAs (P = 0.68; ethnicity interaction P < 0.01). Inverse associations were detected between SAT and severity of aorta CP (P < 0.01) in AAs and between BMI, WC, and SAT with severity of aorta CP in all participants. CONCLUSIONS:Ethnic- and gender-specific differences in BMI, WC, PAT, SAT, and VAT were present in AAs and EAs with diabetes. Only PAT was positively associated with CAC in AAs; paradoxical inverse associations were seen between several other adiposity measures and subclinical cardiovascular disease.

Relative to European Americans, evidence supports that African Americans with end-stage renal disease (ESRD) survive longer on dialysis. Renal-risk variants in the apolipoprotein L1 gene (APOL1), associated with nondiabetic nephropathy and less subclinical atherosclerosis, may contribute to dialysis outcomes. Here, APOL1 renal-risk variants were assessed for association with dialytic survival in 450 diabetic and 275 nondiabetic African American hemodialysis patients from Wake Forest and Emory School of Medicine outpatient facilities. Outcomes were provided by the ESRD Network 6-Southeastern Kidney Council Standardized Information Management System. Dates of death, receipt of a kidney transplant, and loss to follow-up were recorded. Outcomes were censored at the date of transplantation or through 1 July 2015. Multivariable Cox proportional hazards models were computed separately in patients with nondiabetic and diabetic ESRD, adjusting for the covariates age, gender, comorbidities, ancestry, and presence of an arteriovenous fistula or graft at dialysis initiation. In nondiabetic ESRD, patients with 2 (vs. 0/1) APOL1 renal-risk variants had significantly longer dialysis survival (hazard ratio 0.57), a pattern not observed in patients with diabetes-associated ESRD (hazard ratio 1.29). Thus, 2 APOL1 renal-risk variants are associated with longer dialysis survival in African Americans without diabetes, potentially relating to presence of renal-limited disease or less atherosclerosis.

To assess apolipoprotein L1 gene (APOL1) renal-risk-variant effects on the brain, magnetic resonance imaging (MRI)-based cerebral volumes and cognitive function were assessed in 517 African American-Diabetes Heart Study (AA-DHS) Memory IN Diabetes (MIND) and 2568 hypertensive African American Systolic Blood Pressure Intervention Trial (SPRINT) participants without diabetes. Within these cohorts, 483 and 197 had cerebral MRI, respectively. AA-DHS participants were characterized as follows: 60.9% female, mean age of 58.6 years, diabetes duration 13.1 years, estimated glomerular filtration rate of 88.2 ml/min/1.73 m(2), and a median spot urine albumin to creatinine ratio of 10.0 mg/g. In additive genetic models adjusting for age, sex, ancestry, scanner, intracranial volume, body mass index, hemoglobin A1c, statins, nephropathy, smoking, hypertension, and cardiovascular disease, APOL1 renal-risk-variants were positively associated with gray matter volume (β = 3.4 × 10(-3)) and negatively associated with white matter lesion volume (β = -0.303) (an indicator of cerebral small vessel disease) and cerebrospinal fluid volume (β= -30707) (all significant), but not with white matter volume or cognitive function. Significant associations corresponding to adjusted effect sizes (β/SE) were observed with gray matter volume (0.16) and white matter lesion volume (-0.208), but not with cerebrospinal fluid volume (-0.251). Meta-analysis results with SPRINT Memory and Cognition in Decreased Hypertension (MIND) participants who had cerebral MRI were confirmatory. Thus, APOL1 renal-risk-variants are associated with larger gray matter volume and lower white matter lesion volume suggesting lower intracranial small vessel disease.

Coefficient omega and alpha are both measures of the composite reliability for a set of items. Unlike coefficient alpha, coefficient omega remains unbiased with congeneric items with uncorrelated errors. Despite this ability, coefficient omega is not as widely used and cited in the literature as coefficient alpha. Reasons for coefficient omega's underutilization include a limited knowledge of its statistical properties. However, consistent efforts to understand the statistical properties of coefficient omega can help improve its utilization in research efforts. Here, six approaches for estimating confidence intervals for coefficient omega with unidimensional congeneric items were evaluated through a Monte Carlo simulation. The evaluations were made through simulation conditions that mimic realistic conditions that investigators are likely to face in applied work, including items that are not normally distributed and small sample size(s). Overall, the normal theory bootstrap confidence interval had the best performance across all simulation conditions that included sample sizes less than 100. However, most methods had sound coverage with sample sizes of 100 or more.

BACKGROUND:Insulin resistance is associated with microalbuminuria among youth with diabetes mellitus. We sought to determine the dose-response effect of insulin sensitivity (IS) on the magnitude of albuminuria and whether there is a threshold below which urine albumin excretion increases. METHODS:These analyses included participants from the SEARCH for Diabetes in Youth Study with incident diabetes who completed a baseline study visit (n = 2988). We estimated IS using a validated equation incorporating waist circumference, HbA1C, and fasting serum triglycerides. Multivariate regression analyses were performed to assess the effect of IS on urine albumin creatinine ratio (UACR), stratified by diabetes type. The IS threshold was then determined using segmented regressions within each diabetes type and incorporated into the multivariate model. RESULTS:There was an association between IS and UACR in type 2 diabetes only (beta = -0.39; p < 0.001). There was strong statistical evidence for a threshold effect of IS score on UACR in the group of youth with type 2 (beta = 0.40; p < 0.001) but not type 1 diabetes (p = 0.3). CONCLUSIONS:In cross-sectional analyses, there is a negative association between IS and UACR in youth with type 2 but not type 1 diabetes, and this association likely includes a threshold effect of IS on UACR.

Vitamin D and intact parathyroid hormone (iPTH) concentrations differ between individuals of African and European descent and may play a role in observed racial differences in bone mineral density (BMD). These findings suggest that mapping by admixture linkage disequilibrium (MALD) may be informative for identifying genetic variants contributing to these ethnic disparities. Admixture mapping was performed for serum 25-hydroxyvitamin D, 1,25-dihydroxyvitamin D, vitamin D-binding protein (VDBP), bioavailable vitamin D, and iPTH concentrations and computed tomography measured thoracic and lumbar vertebral volumetric BMD in 552 unrelated African Americans with type 2 diabetes from the African American-Diabetes Heart Study. Genotyping was performed using a custom Illumina ancestry informative marker (AIM) panel. For each AIM, the probability of inheriting 0, 1, or 2 copies of a European-derived allele was determined. Non-parametric linkage analysis was performed by testing for association between each AIM using these probabilities among phenotypes, accounting for global ancestry, age, and gender. Fine-mapping of MALD peaks was facilitated by genome-wide association study (GWAS) data. VDBP levels were significantly linked in proximity to the protein coding locus (rs7689609, LOD=11.05). Two loci exhibited significant linkage signals for 1,25-dihydroxyvitamin D on 13q21.2 (rs1622710, LOD=3.20) and 12q13.2 (rs11171526, LOD=3.10). iPTH was significantly linked on 9q31.3 (rs7854368, LOD=3.14). Fine-mapping with GWAS data revealed significant known (rs7041 with VDBP, P=1.38×10(-82)) and novel (rs12741813 and rs10863774 with VDBP, P<6.43×10(-5)) loci with plausible biological roles. Admixture mapping in combination with fine-mapping has focused efforts to identify loci contributing to ethnic differences in vitamin D-related traits.

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.

This review identifies 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and "P-value hacking," 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. It is hoped that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician.