Elevated Levels of Plasma IgA Autoantibodies against Oxidized LDL Found in Proliferative Diabetic Retinopathy but Not in Nonproliferative Retinopathy

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Elevated Levels of Plasma IgA Autoantibodies against Oxidized LDL Found in Proliferative Diabetic Retinopathy but Not in Nonproliferative Retinopathy

Aims. This study investigated the association of autoantibodies binding to oxidized low-density lipoproteins (oxLDL) in diabetic retinopathy (DR). Methods. Plasma from 229 types 1 and 2 patients with DR including diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR) was analysed with ELISA-based assay to determine IgA, IgG, and IgM autoantibody levels binding to oxLDL. The controls were 106 diabetic patients without retinopathy (NoDR) and 139 nondiabetic controls (C). Results. PDR group had significantly higher IgA autoantibody levels than DME or NoDR: mean 94.9 (SD 54.7) for PDR, 75.5 (41.8) for DME ( = 0.001), and 76.1 (48.2) for NoDR ( = 0.008). There were no differences in IgG, IgM, or IgA that would be specific for DR or for DME. Type 2 diabetic patients had higher levels of IgA autoantibodies than type 1 diabetic patients (86.0 and 65.5, resp., = 0.004) and the highest levels in IgA were found in type 2 diabetic patients with PDR (119.1, > 0.001). Conclusions. IgA autoantibodies were increased in PDR, especially in type 2 diabetes. The high levels of IgA in PDR, and especially in type 2 PDR patients, reflect the inflammatory process and enlighten the role of oxLDL and its autoantibodies in PDR

Characterization of metabolic interrelationships and in silico phenotyping of lipoprotein particles using self-organizing maps

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A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data

<p>Abstract</p> <p>Background</p> <p>A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk assessment and diagnostics. Here we focus on clinically relevant estimation of lipoprotein lipids by ¹H NMR spectroscopy of serum.</p> <p>Results</p> <p>A Bayesian methodology, with a biochemical motivation, is presented for a real ¹H NMR metabonomics data set of 75 serum samples. Lipoprotein lipid concentrations were independently obtained for these samples via ultracentrifugation and specific biochemical assays. The Bayesian models were constructed by Markov chain Monte Carlo (MCMC) and they showed remarkably good quantitative performance, the predictive R-values being 0.985 for the very low density lipoprotein triglycerides (VLDL-TG), 0.787 for the intermediate, 0.943 for the low, and 0.933 for the high density lipoprotein cholesterol (IDL-C, LDL-C and HDL-C, respectively). The modelling produced a kernel-based reformulation of the data, the parameters of which coincided with the well-known biochemical characteristics of the ¹H NMR spectra; particularly for VLDL-TG and HDL-C the Bayesian methodology was able to clearly identify the most characteristic resonances within the heavily overlapping information in the spectra. For IDL-C and LDL-C the resulting model kernels were more complex than those for VLDL-TG and HDL-C, probably reflecting the severe overlap of the IDL and LDL resonances in the ¹H NMR spectra.</p> <p>Conclusion</p> <p>The systematic use of Bayesian MCMC analysis is computationally demanding. Nevertheless, the combination of high-quality quantification and the biochemical rationale of the resulting models is expected to be useful in the field of metabonomics.</p

Associations of reported bruxism with insomnia and insufficient sleep symptoms among media personnel with or without irregular shift work

<p>Abstract</p> <p>Background</p> <p>The aims were to investigate the prevalence of perceived sleep quality and insufficient sleep complaints, and to analyze whether self-reported bruxism was associated with perceptions of sleep, and awake consequences of disturbed sleep, while controlling confounding factors relative to poor sleep.</p> <p>Methods</p> <p>A standardized questionnaire was mailed to all employees of the Finnish Broadcasting Company with irregular shift work (n = 750) and to an equal number of randomly selected controls in the same company with regular eight-hour daytime work.</p> <p>Results</p> <p>The response rate in the irregular shift work group was 82.3% (56.6% men) and in the regular daytime work group 34.3% (46.7% men). Self-reported bruxism occurred frequently (often or continually) in 10.6% of all subjects. Altogether 16.8% reported difficulties initiating sleep (DIS), 43.6% disrupted sleep (DS), and 10.3% early morning awakenings (EMA). The corresponding figures for non-restorative sleep (NRS), tiredness, and sleep deprivation (SLD) were 36.2%, 26.1%, and 23.7%, respectively. According to logistic regression, female gender was a significant independent factor for all insomnia symptoms, and older age for DS and EMA. Frequent bruxism was significantly associated with DIS (p = 0.019) and DS (p = 0.021). Dissatisfaction with current work shift schedule and frequent bruxism were both significant independent factors for all variables describing insufficient sleep consequences.</p> <p>Conclusion</p> <p>Self-reported bruxism may indicate sleep problems and their adherent awake consequences in non-patient populations.</p

GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.Peer reviewe

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

This is the final version. Available on open access from AAAS via the DOI in this recordData and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.Medical Research Council (MRC)Wellcome TrustNational Institutes of Health (NIH)Danish National Research FoundationLundbeck FoundationDanish Medical Research Counci

3 years of liraglutide versus placebo for type 2 diabetes risk reduction and weight management in individuals with prediabetes: a randomised, double-blind trial

Background: Liraglutide 3·0 mg was shown to reduce bodyweight and improve glucose metabolism after the 56-week period of this trial, one of four trials in the SCALE programme. In the 3-year assessment of the SCALE Obesity and Prediabetes trial we aimed to evaluate the proportion of individuals with prediabetes who were diagnosed with type 2 diabetes. Methods: In this randomised, double-blind, placebo-controlled trial, adults with prediabetes and a body-mass index of at least 30 kg/m2, or at least 27 kg/m2 with comorbidities, were randomised 2:1, using a telephone or web-based system, to once-daily subcutaneous liraglutide 3·0 mg or matched placebo, as an adjunct to a reduced-calorie diet and increased physical activity. Time to diabetes onset by 160 weeks was the primary outcome, evaluated in all randomised treated individuals with at least one post-baseline assessment. The trial was conducted at 191 clinical research sites in 27 countries and is registered with ClinicalTrials.gov, number NCT01272219. Findings: The study ran between June 1, 2011, and March 2, 2015. We randomly assigned 2254 patients to receive liraglutide (n=1505) or placebo (n=749). 1128 (50%) participants completed the study up to week 160, after withdrawal of 714 (47%) participants in the liraglutide group and 412 (55%) participants in the placebo group. By week 160, 26 (2%) of 1472 individuals in the liraglutide group versus 46 (6%) of 738 in the placebo group were diagnosed with diabetes while on treatment. The mean time from randomisation to diagnosis was 99 (SD 47) weeks for the 26 individuals in the liraglutide group versus 87 (47) weeks for the 46 individuals in the placebo group. Taking the different diagnosis frequencies between the treatment groups into account, the time to onset of diabetes over 160 weeks among all randomised individuals was 2·7 times longer with liraglutide than with placebo (95% CI 1·9 to 3·9, p&lt;0·0001), corresponding with a hazard ratio of 0·21 (95% CI 0·13–0·34). Liraglutide induced greater weight loss than placebo at week 160 (–6·1 [SD 7·3] vs −1·9% [6·3]; estimated treatment difference −4·3%, 95% CI −4·9 to −3·7, p&lt;0·0001). Serious adverse events were reported by 227 (15%) of 1501 randomised treated individuals in the liraglutide group versus 96 (13%) of 747 individuals in the placebo group. Interpretation: In this trial, we provide results for 3 years of treatment, with the limitation that withdrawn individuals were not followed up after discontinuation. Liraglutide 3·0 mg might provide health benefits in terms of reduced risk of diabetes in individuals with obesity and prediabetes. Funding: Novo Nordisk, Denmark