Epidemic of end-stage renal disease in people with diabetes in the United States population: Do we know the cause?

Epidemic of end-stage renal disease in people with diabetes in the United States population: Do we know the cause?BackgroundThe number of individuals initiating renal replacement therapy in the United States population grew exponentially over the past two decades. Cases of end-stage renal diseae (ESRD) attributed to diabetes accounted for most of this increase. In this report we examined factors that may account for the increase to determine whether it truly represents an epidemic of ESRD due to diabetes.MethodsWe reviewed time trends in data of the United States Renal Data system, the Diabetes Surveillance Program of the Centers for Disease Control and Prevention, and diabetes literature.ResultsRecent growth of the number of individuals with diabetes accounted for less than 10% of the increase in the number of diabetes-related ESRD. Instead, most of it was due to a threefold increase in risk of ESRD in people with diabetes and, therefore, qualifies as an epidemic. Curiously, this epidemic occurred despite widening implementation of effective renoprotective therapies. Individuals with type 2 diabetes, regardless of gender, age, or race, experienced the greatest increase in risk. There is no evidence that diabetic patients have been surviving longer, so the increased risk was not attributable to the high risk associated with long duration diabetes.ConclusionWe hypothesize that an epidemic of ESRD has occurred in people with diabetes in the United States population over the last two decades. The nature of the factor responsible for the epidemic and the reasons it affects patients with type 2 diabetes particularly are unknown. Research efforts to identify the putative factor deserve high priority, as does a commitment of resources to provide care for the burgeoning number of patients with ESRD and type 2 diabetes

Genome-Wide Association Scan for Diabetic Nephropathy Susceptibility Genes in Type 1 Diabetes

OBJECTIVE—Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection. RESEARCH DESIGN AND METHODS—We genotyped 360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes- associated complications. RESULTS—A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P1105. The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR]1.45, P5.0107). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR 1.36, P3.1106). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR]1.33, P0.02, and HR1.32, P 0.01, respectively). We demonstrated expression of both FRMD3 and CARS in human kidney. CONCLUSIONS—We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes

Food Insecurity Prevalence Across Diverse Sites During COVID-19: A Year of Comprehensive Data

Key Findings NFACT includes 18 study sites in 15 states as well as a national poll, collectively representing a sample size of more than 26,000 people. Some sites have implemented multiple survey rounds, here we report results from 22 separate surveys conducted during the year since the COVID-19 pandemic began in March 2020. 18 out of 19 surveys in 14 sites with data for before and since the pandemic began found an increase in food insecurity since the start of the COVID-19 pandemic as compared to before the pandemic. In nearly all surveys (18/19) that measured food insecurity both before and during the pandemic, more Black, Indigenous, and People of Color (BIPOC) were classified as food insecure during the pandemic as compared to before it began. Prevalence of food insecurity for BIPOC respondents was higher than the overall population in the majority of surveys (19/20) sampling a general population. In almost all surveys (21/22), the prevalence of food insecurity for households with children was higher than the overall prevalence of food insecurity. Food insecurity prevalence was higher for households experiencing a negative job impact during the pandemic (i.e. job loss, furlough, reduction in hours) in nearly all surveys and study sites (21/22). Food insecurity prevalence in most sites was significantly higher before COVID-19 than estimates from that time period. Reporting a percent change between pre and during COVID-19 prevalence may provide additional information about the rate of change in food insecurity since the start of the pandemic, which absolute prevalence of food insecurity may not capture. Results highlight consistent trends in food insecurity outcomes since the start of the COVID-19 pandemic, across diverse study sites, methodological approaches, and time

A Novel Framework for Sib Pair Linkage Analysis

Sib pair linkage analysis of a dichotomous trait is a popular method for narrowing the search for genes that influence complex diseases. Although the pedigree structures are uncomplicated and the underlying genetic principles straightforward, a surprising degree of complexity is involved in implementing a sib pair study and interpreting the results. Ascertainment may be based on affected, discordant, or unaffected sib pairs, as well as on pairs defined by threshold values for quantitative traits, such as extreme discordant sib pairs. To optimize power, various domain restrictions and null hypotheses have been proposed for each of these designs, yielding a wide array of choices for the analyst. To begin, we systematically classify the major sources of discretion in sib pair linkage analysis. Then, we extend the work of Kruglyak and Lander (1995), to bring the various forms into a unified framework and to facilitate a more general approach to the analysis. Finally, we describe a new, freely available computer program, Splat (Sib Pair Linkage Analysis Testing), that can perform any sib pair statistical test currently in use, as well as any user-defined test yet to be proposed. Splat uses the expectation maximization algorithm to calculate maximum-likelihood estimates of sharing (subject to user-specified conditions) and then plots LOD scores versus chromosomal position. It includes a novel grid-scanning capability that enables simultaneous visualization of multiple test statistics. This can lead to further insight into the genetic basis of the disease process under consideration. In addition, phenotype definitions can be modified without the recalculation of inheritance vectors, thereby providing considerable flexibility for exploratory analysis. The application of Splat will be illustrated with data from studies on the genetics of diabetic nephropathy

Pro-Inflammatory Interleukin-1 Genotypes Potentiate the Risk of Coronary Artery Disease and Cardiovascular Events Mediated by Oxidized Phospholipids and Lipoprotein(a)

ObjectivesThe aim of this study was to assess the influence of pro-inflammatory interleukin (IL)-1 genotype status on the risk for coronary artery disease (CAD), defined as >50% diameter stenosis, and cardiovascular events mediated by oxidized phospholipids (OxPLs) and lipoprotein (Lp) (a).BackgroundOxPLs are pro-inflammatory, circulate on Lp(a), and mediate CAD. Genetic variations in the IL-1 region are associated with increased inflammatory mediators.MethodsIL-1 genotypes, OxPL on apolipoprotein B-100 (OxPL/apoB), and Lp(a) levels were measured in 499 patients undergoing coronary angiography. The composite genotype termed IL-1(+) was defined by 3 single-nucleotide polymorphisms in the IL-1 gene cluster associated with higher levels of pro-inflammatory cytokines. All other IL-1 genotypes were termed IL-1(−).ResultsAmong IL-1(+) patients, the highest quartile of OxPL/apoB was significantly associated with a higher risk for CAD compared with the lowest quartile (odds ratio [OR]: 2.84; p = 0.001). This effect was accentuated in patients age ≤60 years (OR: 7.03; p < 0.001). In IL-1(−) patients, OxPL/apoB levels showed no association with CAD. The interaction was significant for OxPL/apoB (OR: 1.99; p = 0.004) and Lp(a) (OR: 1.96; p < 0.001) in the IL-1(+) group versus the IL-1(−) group in patients age ≤60 years but not in those age >60 years. In IL-1(+) patients age ≤60 years, after adjustment for established risk factors, high-sensitivity C-reactive protein, and Lp(a), OxPL/apoB remained an independent predictor of CAD. IL-1(+) patients above the median OxPL/apoB presented to the cardiac catheterization laboratory a mean of 3.9 years earlier (p = 0.002) and had worse 4-year event-free survival (death, myocardial infarction, stroke, and need for revascularization) compared with other groups (p = 0.006).ConclusionsOur study suggests that IL-1 genotype status can stratify population risk for CAD and cardiovascular events mediated by OxPL. These data suggest a clinically relevant biological link between pro-inflammatory IL-1 genotype, oxidation of phospholipids, Lp(a), and genetic predisposition to CAD and cardiovascular events