A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance is a common complication of HIV protease inhibitors. Diabetes mellitus is relatively uncommon.

No abstract

BackgroundThe identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model.ResultsWe show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons.ConclusionsThe agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing.For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.Electronic supplementary materialThe online version of this article (doi:10.1186/1756-8935-8-6) contains supplementary material, which is available to authorized users.

No abstract

OBJECTIVE -Metabolic syndrome is a cluster of risk factors for cardiovascular disease and type 2 diabetes. Definitions exist to identify those "at risk." Treatment of HIV infection with highly active antiretroviral therapy can induce severe metabolic complications including lipodystrophy, dyslipidemia, and insulin resistance. The purpose of this study was to report the prevalence of metabolic syndrome in HIV-infected patients and compare insulin resistance and total body, limb, and visceral fat and adipokines in those with and without metabolic syndrome. RESEARCH DESIGN AND METHODS-This was an international cross-sectional study of a well-characterized cohort of 788 HIV-infected adults recruited at 32 centers. Metabolic syndrome prevalence was examined using International Diabetes Federation (IDF) and U.S. National Cholesterol Education Program Adult Treatment Panel III (ATPIII) criteria, relative to body composition (whole-body dual-energy X-ray absorptiometry and abdominal computed tomography), lipids, glycemic parameters, insulin resistance, leptin, adiponectin, and C-reactive protein (CRP).RESULTS -The prevalence of metabolic syndrome was 14% (n ϭ 114; 83 men) by IDF criteria and 18% (n ϭ 139; 118 men) by ATPIII criteria; the concordance was significant but only moderate ( ϭ 0.46, P Ͻ 0.0001). Many patients (49%) had at least two features of metabolic syndrome but were not classified as having metabolic syndrome as their waist circumferences or waist-to-hip ratios were in the non-metabolic syndrome range. Metabolic syndrome was more common in those currently receiving protease inhibitors (P ϭ 0.04). Type 2 diabetes prevalence was five-to ninefold higher in those with metabolic syndrome. With IDF criteria, subjects with metabolic syndrome showed disturbances in inflammation and adipokines: they had higher CRP (5.5 Ϯ 7.0 vs. 3.9 Ϯ 6.0 mg/l, P Ͻ 0.003) and leptin (9 Ϯ 9 vs. 4 Ϯ 6 ng/ml, P Ͻ 0.0001) and lower adiponectin (12 Ϯ 8 vs. 15 Ϯ 10 g/ml, P Ͻ 0.0001) levels. By ATPIII criteria, those with metabolic syndrome had higher leptin (6 Ϯ 8 ng/ml, P ϭ 0.006) and lower adiponectin (15 Ϯ 10 vs. 18 Ϯ 8 g/ml, P Ͻ 0.0001) levels.CONCLUSIONS -Metabolic syndrome prevalence in HIV-positive adults was lower than that reported for the general population. Metabolic syndrome was associated with a substantially increased prevalence of type 2 diabetes in this specific cohort. Many subjects without metabolic syndrome had at least two metabolic syndrome components (particularly elevated lipid levels) but did not meet waist circumference or waist-to-hip ratio cutoff metabolic syndrome criteria in this group with high rates of body fat partitioning disturbances. Diabetes Care 30:113-119, 2007H ighly active antiretroviral therapy (HAART) in HIV infection produces a spectrum of metabolic complications, including dyslipidemia, insulin resistance, and changes in body fat compartmentalization (peripheral lipoatrophy and central fat accumulation). We first described and characterized the lipid and metabolic abnormalities associated with...

A lifestyle and life skills intervention delivered as part of standard care attenuated antipsychotic-induced weight gain in young people with FEP. The intervention was acceptable to the young people referred to the service. Such interventions may prevent the seeding of future disease risk and in the long-term help reduce the life expectancy gap for people living with serious mental illness.

No abstract

Type 2 diabetes mellitus (T2D) is predicted by central obesity and circulating adipokines regulating inflammation. We hypothesized that visceral adipose tissue (VAT) in T2D expresses greater levels of proinflammatory molecules. Paired samples of subcutaneous (SAT) and VAT were excised at elective surgery (n = 16, 6 with T2D, n = 8 age‐ and gender‐ matched controls). Metabolic parameters were measured in the fasted state: body composition by dual‐energy X‐ray absorptiometry and insulin action by hyperinsulinemic–euglycemic clamp. Adipose tissue mRNA gene expression was measured by quantitative reverse transcriptase‐PCR. Subjects with T2D had higher VAT expression of molecules regulating inflammation (tumor necrosis factor‐α (TNFα), macrophage inflammatory protein (MIP), interleukin‐8 (IL‐8)). Fasting glucose related to VAT expression of TNFα, MIP, serum amyloid A (SAA), IL‐1α, IL‐1β, IL‐8, and IL‐8 receptor. Abdominal fat mass was related to VAT expression of MIP, SAA, cAMP response element–binding protein (CREBP), IL‐1β, and IL‐8. Insulin action related inversely to VAT complement C3 expression only. There were depot‐specific differences in expression of serum T2D predictors: VAT expressed higher levels of complement C3; SAT expressed higher levels of retinol‐binding protein‐4 (RBP4), adiponectin, and leptin. In summary, VAT in T2D expresses higher levels of adipokines involved in inflammation. VAT expression of these molecules is related to fasting glucose and insulin action. Increased production of these proinflammatory molecules by VAT may explain the links observed between visceral obesity, insulin resistance, and diabetes risk.