Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

Serum Uric Acid and Adiposity: Deciphering Causality Using a Bidirectional Mendelian Randomization Approach

Background: Although the relationship between serum uric acid (SUA) and adiposity is well established, the direction of the causality is still unclear in the presence of conflicting evidences. We used a bidirectional Mendelian randomization approach to explore the nature and direction of causality between SUA and adiposity in a population-based study of Caucasians aged 35 to 75 years. Methods and Findings: We used, as instrumental variables, rs6855911 within the SUA gene SLC2A9 in one direction, and combinations of SNPs within the adiposity genes FTO, MC4R and TMEM18 in the other direction. Adiposity markers included weight, body mass index, waist circumference and fat mass. We applied a two-stage least squares regression: a regression of SUA/adiposity markers on our instruments in the first stage and a regression of the response of interest on the fitted values from the first stage regression in the second stage. SUA explained by the SLC2A9 instrument was not associated to fat mass (regression coefficient [95 % confidence interval]: 0.05 [20.10, 0.19] for fat mass) contrasting with the ordinary least square estimate (0.37 [0.34, 0.40]). By contrast, fat mass explained by genetic variants of the FTO, MC4R and TMEM18 genes was positively and significantly associated to SUA (0.31 [0.01, 0.62]), similar to the ordinary least square estimate (0.27 [0.25, 0.29]). Results were similar for the other adiposity markers. Conclusions: Using a bidirectional Mendelian randomization approach in adult Caucasians, our findings suggest tha

Differences between Human Plasma and Serum Metabolite Profiles

BACKGROUND: Human plasma and serum are widely used matrices in clinical and biological studies. However, different collecting procedures and the coagulation cascade influence concentrations of both proteins and metabolites in these matrices. The effects on metabolite concentration profiles have not been fully characterized. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed the concentrations of 163 metabolites in plasma and serum samples collected simultaneously from 377 fasting individuals. To ensure data quality, 41 metabolites with low measurement stability were excluded from further analysis. In addition, plasma and corresponding serum samples from 83 individuals were re-measured in the same plates and mean correlation coefficients (r) of all metabolites between the duplicates were 0.83 and 0.80 in plasma and serum, respectively, indicating significantly better stability of plasma compared to serum (p = 0.01). Metabolite profiles from plasma and serum were clearly distinct with 104 metabolites showing significantly higher concentrations in serum. In particular, 9 metabolites showed relative concentration differences larger than 20%. Despite differences in absolute concentration between the two matrices, for most metabolites the overall correlation was high (mean r = 0.81±0.10), which reflects a proportional change in concentration. Furthermore, when two groups of individuals with different phenotypes were compared with each other using both matrices, more metabolites with significantly different concentrations could be identified in serum than in plasma. For example, when 51 type 2 diabetes (T2D) patients were compared with 326 non-T2D individuals, 15 more significantly different metabolites were found in serum, in addition to the 25 common to both matrices. CONCLUSIONS/SIGNIFICANCE: Our study shows that reproducibility was good in both plasma and serum, and better in plasma. Furthermore, as long as the same blood preparation procedure is used, either matrix should generate similar results in clinical and biological studies. The higher metabolite concentrations in serum, however, make it possible to provide more sensitive results in biomarker detection

Recognition and diagnosis of sleep disorders in Parkinson's disease

Contains fulltext : 109296.pdf (publisher's version ) (Open Access)Sleep disturbances are among the most frequent and incapacitating non-motor symptoms of Parkinson's disease (PD), and are increasingly recognized as an important determinant of impaired quality of life. Here we review several recent developments regarding the recognition and diagnosis of sleep disorders in PD. In addition, we provide a practical and easily applicable approach to the diagnostic process as a basis for tailored therapeutic interventions. This includes a stepwise scheme that guides the clinical interview and subsequent ancillary investigations. In this scheme, the various possible sleep disorders are arranged not in order of prevalence, but in a 'differential diagnostic' order. We also provide recommendations for the use of sleep registrations such as polysomnography. Furthermore, we point out when a sleep specialist could be consulted to provide additional diagnostic and therapeutic input. This structured approach facilitates early detection of sleep disturbances in PD, so treatment can be initiated promptly

Defective CFTR Expression and Function Are Detectable in Blood Monocytes: Development of a New Blood Test for Cystic Fibrosis

BACKGROUND: Evaluation of cystic fibrosis transmembrane conductance regulator (CFTR) functional activity to assess new therapies and define diagnosis of cystic fibrosis (CF) is cumbersome. It is known that leukocytes express detectable levels of CFTR but the molecule has not been characterized in these cells. In this study we aim at setting up and validating a blood test to evaluate CFTR expression and function in leukocytes. DESCRIPTION: Western blot, PCR, immunofluorescence and cell membrane depolarization analysis by single-cell fluorescence imaging, using the potential-sensitive DiSBAC(2)(3) probe were utilized. Expression of PKA phosphorylated, cell membrane-localized CFTR was detected in non-CF monocytes, being undetectable or present in truncated form in monocytes derived from CF patients presenting with nonsense mutations. CFTR agonist administration induced membrane depolarization in monocytes isolated from non-CF donors (31 subjects) and, to a lesser extent, obligate CFTR heterozygous carriers (HTZ: 15 subjects), but it failed in monocytes from CF patients (44 subjects). We propose an index, which values in CF patients are significantly (p<0.001) lower than in the other two groups. Nasal Potential Difference, measured in selected subjects had concordant results with monocytes assay (Kappa statistic 0.93, 95%CI: 0.80-1.00). RESULTS AND SIGNIFICANCE: CFTR is detectable and is functional in human monocytes. We also showed that CFTR-associated activity can be evaluated in 5 ml of peripheral blood and devise an index potentially applicable for diagnostic purposes and both basic and translational research: from drug development to evaluation of functional outcomes in clinical trials

Multiple FadD Acyl-CoA Synthetases Contribute to Differential Fatty Acid Degradation and Virulence in Pseudomonas aeruginosa

A close interconnection between nutrient metabolism and virulence factor expression contributes to the pathophysiology of Pseudomonas aeruginosa as a successful pathogen. P. aeruginosa fatty acid (FA) degradation is complicated with multiple acyl-CoA synthetase homologs (FadDs) expressed in vivo in lung tissue during cystic fibrosis infections. The promoters of two genetically linked P. aeruginosa fadD genes (fadD1 and fadD2) were mapped and northern blot analysis indicated they could exist on two different transcripts. These FadDs contain ATP/AMP signature and FA-binding motifs highly homologous to those of the Escherichia coli FadD. Upon introduction into an E. coli fadD-/fadR- double mutant, both P. aeruginosa fadDs functionally complemented the E. coli fadD-/fadR- mutant, allowing degradation of different chain-length FAs. Chromosomal mutagenesis, growth analysis, induction studies, and determination of kinetic parameters suggested that FadD1 has a substrate preference for long-chain FAs while FadD2 prefers shorter-chain FAs. When compared to the wild type strain, the fadD2 mutant exhibited decreased production of lipase, protease, rhamnolipid and phospholipase, and retardation of both swimming and swarming motilities. Interestingly, fadD1 mutant showed only increased swarming motility. Growth analysis of the fadD mutants showed noticeable deficiencies in utilizing FAs and phosphatidylcholine (major components of lung surfactant) as the sole carbon source. This defect translated into decreased in vivo fitness of P. aeruginosa in a BALB/c mouse lung infection model, supporting the role of lipids as a significant nutrient source for this bacterium in vivo