Bioimpedance Analysis-Guided Volume Expansion for the Prevention of Contrast-Induced Acute Kidney Injury (the BELIEVE Pilot Randomized Controlled Trial)

Introduction: Peri-procedural i.v. fluid administration is important for the prevention of contrast-induced acute kidney injury (CI-AKI). However, standardized fluid management protocols may not be suitable for all patients. We therefore wished to determine whether an individualized fluid administration protocol guided by measuring extracellular water (ECW) using bioimpedance analysis (BIA) would be safe and would reduce the incidence CI-AKI compared to a standardized fluid administration prescription. Methods: In this pilot, randomized, parallel-group, single-blind, controlled trial, we compared the effect of BIA-guided isotonic bicarbonate administration according to the ratio of ECW to total body water (ECW/TBW) to our standard isotonic bicarbonate protocol in regard to the safety and efficacy of preventing CI-AKI in chronic kidney disease patients undergoing elective cardiac angiography. Our primary outcome was the incidence of CI-AKI, which was defined as a ≥0.3 mg/dl or 150% increase in serum creatinine concentration within 48 to 72 hours after cardiac angiography. Results: We studied 61 patients, 30 in the bioimpedance group and 31 in the control group. Age was similar (72.5 ± 7 vs. 71.4 ± 7.9 years), as were body mass index (25.5 vs. 25.8 kg/m2) and baseline serum creatinine (1.3 ± 0.3 vs. 1.4 ± 0.4 mg/dl). The peri-procedural fluid volume administered was significantly greater in the BIA-guided hydration group (899.0 ± 252.7 ml vs. 594.4 ± 125.9 ml, P < .01). The incidence of CI-AKI was 3.3% in BIA-guided hydration group and 6.5% in the control group (relative risk = 0.52, 95% confidence interval = 0.05−5.40, P = 1.00). Adverse events reported were comparable between groups (6.7% vs. 6.5%, P = 1.00). Conclusions: The overall incidence of CI-AKI after cardiac angiography in our patients with mild-to-moderate renal insufficiency was lower than anticipated. Isotonic bicarbonate administration guided by bioimpedance measurements was safe, and probably led to a lower incidence of CI-AKI, although this not reach statistical significance

TCF7L2 polymorphisms and inflammatory markers before and after treatment with fenofibrate

<p>Abstract</p> <p>Background</p> <p>Inflammation is implicated in causing diabetes. We tested whether transcription factor 7 like-2 (TCF7L2) gene polymorphisms (rs12255372 and rs7903146), consistently associated with type 2 diabetes, are associated with plasma concentrations of inflammatory markers before and after three weeks of daily treatment with fenofibrate.</p> <p>Methods</p> <p>Men and women in the Genetics of Lipid-Lowering Drugs and Diet Network study (n = 1025, age 49 ± 16 y) were included. All participants suspended use of lipid-lowering drugs for three weeks and were then given 160 mg/day of fenofibrate for three weeks. Inflammatory markers and lipids were measured before and after fenofibrate. ANOVA was used to test for differences across TCF7L2 genotypes.</p> <p>Results</p> <p>Under the additive or dominant model, there were no significant differences (<it>P </it>> 0.05) in the concentrations of inflammatory markers (hsCRP, IL-2, IL-6, TNF-α and MCP-1) across TCF7L2 genotypes in the period before or after treatment. For both rs12255372 and rs7903146, homozygote T-allele carriers had significantly higher (<it>P </it>< 0.05) post-fenofibrate concentrations of MCP-1 in the recessive model. No other significant associations were detected.</p> <p>Conclusion</p> <p>Overall these data show no association between TCF7L2 polymorphisms and the inflammatory markers suggesting that the effects of TCF7L2 on diabetes may not be via inflammation.</p

A High Intake of Saturated Fatty Acids Strengthens the Association between the Fat Mass and Obesity-Associated Gene and BMI123

Evidence that physical activity (PA) modulates the association between the fat mass and obesity-associated gene (FTO) and BMI is emerging; however, information about dietary factors modulating this association is scarce. We investigated whether fat and carbohydrate intake modified the association of FTO gene variation with BMI in two populations, including participants in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 1069) and in the Boston Puerto Rican Health (BPRHS) study (n = 1094). We assessed energy, nutrient intake, and PA using validated questionnaires. Genetic variability at the FTO locus was characterized by polymorphisms rs9939609 (in the GOLDN) and rs1121980 (in the GOLDN and BPRHS). We found significant interactions between PA and FTO on BMI in the GOLDN but not in the BPRHS. We found a significant interaction between SFA intake and FTO on BMI, which was stronger than that of total fat and was present in both populations (P-interaction = 0.007 in the GOLDN and P-interaction = 0.014 in BPRHS for categorical; and P-interaction = 0.028 in the GOLDN and P-interaction = 0.041 in BPRHS for continuous SFA). Thus, homozygous participants for the FTO-risk allele had a higher mean BMI than the other genotypes only when they had a high-SFA intake (above the population mean: 29.7 ± 0.7 vs. 28.1 ± 0.5 kg/m2; P = 0.037 in the GOLDN and 33.6. ± 0.8 vs. 31.2 ± 0.4 kg/m2; P = 0.006 in BPRHS). No associations with BMI were found at lower SFA intakes. We found no significant interactions with carbohydrate intake. In conclusion, SFA intake modulates the association between FTO and BMI in American populations

Suggestion for linkage of chromosome 1p35.2 and 3q28 to plasma adiponectin concentrations in the GOLDN Study

<p>Abstract</p> <p>Background</p> <p>Adiponectin is inversely associated with obesity, insulin resistance, and atherosclerosis, but little is known about the genetic pathways that regulate the plasma level of this protein. To find novel genes that influence circulating levels of adiponectin, a genome-wide linkage scan was performed on plasma adiponectin concentrations before and after 3 weeks of treatment with fenofibrate (160 mg daily) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study. We studied Caucasian individuals (n = 1121) from 190 families in Utah and Minnesota. Of these, 859 individuals from 175 families had both baseline and post-fenofibrate treatment measurements for adiponectin. Plasma adiponectin concentrations were measured with an ELISA assay. All participants were typed for microsatellite markers included in the Marshfield Mammalian Genotyping Service marker set 12, which includes 407 markers spaced at approximately 10 cM regions across the genome. Variance components analysis was used to estimate heritability and to perform genome-wide scans. Adiponectin was adjusted for age, sex, and field center. Additional models also included BMI adjustment.</p> <p>Results</p> <p>Baseline and post-fenofibrate adiponectin measurements were highly correlated (r = 0.95). Suggestive (LOD > 2) peaks were found on chromosomes 1p35.2 and 3q28 (near the location of the adiponectin gene).</p> <p>Conclusion</p> <p>Two candidate genes, <it>IL22RA1 </it>and <it>IL28RA</it>, lie under the chromosome 1 peak; further analyses are needed to identify the specific genetic variants in this region that influence circulating adiponectin concentrations.</p

Single nucleotide polymorphisms at the ADIPOQ gene locus interact with age and dietary intake of fat to determine serum adiponectin in subjects at risk of the metabolic syndrome

Background: Adiponectin gene expression is modulated by peroxisome proliferator–activated receptor γ, which is a transcription factor activated by unsaturated fatty acids. Objective: We investigated the effect of the interaction between variants at the ADIPOQ gene locus, age, sex, body mass index (BMI), ethnicity, and the replacement of dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) or carbohydrates on serum adiponectin concentrations. Design: The RISCK (Reading, Imperial, Surrey, Cambridge, and Kings) study is a parallel-design, randomized controlled trial. Serum adiponectin concentrations were measured after a 4-wk high-SFA (HS) diet and a 24-wk intervention with reference (HS), high-MUFA (HM), and low-fat (LF) diets. Single nucleotide polymorphisms at the ADIPOQ locus −11391 G/A (rs17300539), −10066 G/A (rs182052), −7734 A/C (rs16861209), and +276 G/T (rs1501299) were genotyped in 448 participants. Results: In white Europeans, +276 T was associated with higher serum adiponectin concentrations (n = 340; P = 0.006) and −10066 A was associated with lower serum adiponectin concentrations (n = 360; P = 0.03), after adjustment for age, BMI, and sex. After the HM diet, −10066 G/G subjects showed a 3.8% increase (95% CI: −0.1%, 7.7%) and G/A+A/A subjects a 2.6% decrease (95% CI: −5.6%, 0.4%) in serum adiponectin (P = 0.006 for difference after adjustment for the change in BMI, age, and sex). In −10066 G/G homozygotes, serum adiponectin increased with age after the HM diet and decreased after the LF diet. Conclusion: In white −10066 G/G homozygotes, an HM diet may help to increase adiponectin concentrations with advancing age. This trial was registered at clinicaltrials.gov as ISRCTN29111298

Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins

Understanding the genetic architecture of gene expression is an intermediate step in understanding the genetic architecture of complex diseases. RNA sequencing technologies have improved the quantification of gene expression and allow measurement of allele-specific expression (ASE). ASE is hypothesized to result from the direct effect of cis regulatory variants, but a proper estimation of the causes of ASE has not been performed thus far. In this study, we take advantage of a sample of twins to measure the relative contributions of genetic and environmental effects to ASE, and we find substantial effects from gene × gene (G×G) and gene × environment (G×E) interactions. We propose a model where ASE requires genetic variability in cis, a difference in the sequence of both alleles, but where the magnitude of the ASE effect depends on trans genetic and environmental factors that interact with the cis genetic variants