Human Skeletal Muscle Mitochondrial Uncoupling Is Associated with Cold Induced Adaptive Thermogenesis

Background: Mild cold exposure and overfeeding are known to elevate energy expenditure in mammals, including humans. This process is called adaptive thermogenesis. In small animals, adaptive thermogenesis is mainly caused by mitochondrial uncoupling in brown adipose tissue and regulated via the sympathetic nervous system. In humans, skeletal muscle is a candidate tissue, known to account for a large part of the epinephrine-induced increase in energy expenditure. However, mitochondrial uncoupling in skeletal muscle has not extensively been studied in relation to adaptive thermogenesis in humans. Therefore we hypothesized that cold-induced adaptive thermogenesis in humans is accompanied by an increase in mitochondrial uncoupling in skeletal muscle. Methodology/Principal Findings: The metabolic response to mild cold exposure in 11 lean, male subjects was measured in a respiration chamber at baseline and mild cold exposure. Skeletal muscle mitochondrial uncoupling (state 4) was measured in muscle biopsies taken at the end of the respiration chamber stays. Mild cold exposure caused a significant increase in 24h energy expenditure of 2.8 % (0.32 MJ/day, range of 20.21 to 1.66 MJ/day, p,0.05). The individual increases in energy expenditure correlated to state 4 respiration (p,0.02, R 2 = 0.50). Conclusions/Significance: This study for the first time shows that in humans, skeletal muscle has the intrinsic capacity for cold induced adaptive thermogenesis via mitochondrial uncoupling under physiological conditions. This opens possibilitie

Increased CD8+ T cell responses to apoptotic T cell-associated antigens in multiple sclerosis.

BACKGROUND: Here, we evaluated the hypothesis that CD8(+) T cell responses to caspase-cleaved antigens derived from effector T cells undergoing apoptosis, may contribute to multiple sclerosis (MS) immunopathology. METHODS: The percentage of autoreactive CD8(+) T effector cells specific for various apoptotic T cell-associated self-epitopes (apoptotic epitopes) were detected in the peripheral blood and cerebrospinal fluid (CSF) by both enzyme-linked immunospot and dextramers of class I molecules complexed with relevant apoptotic epitopes. Moreover, the capacity of dextramer(+) CD8(+) T cells to produce interferon (IFN)-γ and/or interleukin (IL)-17 in response to the relevant apoptotic epitopes was evaluated by the intracellular cytokine staining. Cross-presentation assay of apoptotic T cells by dendritic cells was also evaluated ex vivo. RESULTS: We found that polyfunctional (IFN-γ and/or IL-17 producing) autoreactive CD8(+) T cells specific for apoptotic epitopes were represented in MS patients with frequencies significantly higher than in healthy donors. These autoreactive CD8(+) T cells with a strong potential to produce IFN-γ or IL-17 in response to the relevant apoptotic epitopes were significantly accumulated in the CSF from the same patients. In addition, the frequencies of these autoreactive CD8(+) T cells correlated with the disease disability. Cross-presentation assay revealed that caspase-cleaved cellular proteins are required to activate apoptotic epitope-specific CD8(+) T cells ex vivo. CONCLUSION: Taken together, these data indicate that apoptotic epitope-specific CD8(+) T cells with strong inflammatory potential are recruited at the level of the inflammatory site, where they may be involved in MS immunopathology through the production of high levels of inflammatory cytokines

Nervous system and Fabry disease, from symptoms to diagnosis: damage evaluation and follow-up in adult patients, enzyme replacement, and support therapy

The X-linked genetic Fabry disease causes multiorgan lesions due to intracellular storage of the substrate globotriaosylceramide. Neurological involvement ranges from painful, small fiber neuropathy to cerebrovascular disorders to multifocal aggressive forms. Disease identification through proper differential diagnosis and timely assessment of organ damage should guide a careful treatment planning. Mainstay treatment, include enzyme replacement and support therapy. Neurologists have a pivotal role in early instrumental and clinical detection of organ damage. A panel of experts has developed a set of consensus recommendations to guide the approach of neurologists to Fabry disease

Molecular Refinement of Clinical Staging in Hepatocellular Carcinoma Patients Evaluated for Potentially Curative Therapies

Abstract: Aim: VEGF and AFP mRNA determinations in the blood are promising prognostic factors for patients with HCC. This study explores their potential prognostic synergy in a cohort of HCC patients evaluated for potentially curative therapies. Methods: One hundred twenty-four patients with a diagnosis of HCC were prospectively enrolled in the study. Inclusion criteria were: (a) histological diagnosis of HCC and assessment of tumour grade and (b) determination of AFP mRNA status and VEGF levels in the blood before therapy. Results: At baseline evaluation, 40% of the study group had AFP mRNA in the blood (AFP mRNA positive), and 35% had VEGF > 23 pg ml(-1) (VEGF positive). Surgery was performed in 58 patients (47%), 54 (43%) had tumour ablation, and 12 had chemoembolisation (10%). Median follow-up and survival of the study group were 19 and 26 months (range, 1 to 60), respectively. The association of AFP mRNA and VEGF proved to be prognostically more accurate than their single use in discriminating the risk of death (ROC curve analysis) and survival probability (Cox analysis). In particular, we identified 3 main molecular stages (p < 0,0001): both negative (3-year survival = 63%), one positive (3-year survival = 40%), both positive (3-year survival = 16%). Multivariate analysis identified BCLC staging, surgery, and molecular staging as the most significant survival variables. Conclusions: The preoperative determination of AFP mRNA status and VEGF may potentially refine the prognostic evaluation of HCC patients and improve the selection process for potentially curative therapies

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies

A hierarchical and modular approach to the discovery of robust associations in genome-wide association studies from pooled DNA samples

[Background] One of the challenges of the analysis of pooling-based genome wide association studies is to identify authentic associations among potentially thousands of false positive associations. [Results] We present a hierarchical and modular approach to the analysis of genome wide genotype data that incorporates quality control, linkage disequilibrium, physical distance and gene ontology to identify authentic associations among those found by statistical association tests. The method is developed for the allelic association analysis of pooled DNA samples, but it can be easily generalized to the analysis of individually genotyped samples. We evaluate the approach using data sets from diverse genome wide association studies including fetal hemoglobin levels in sickle cell anemia and a sample of centenarians and show that the approach is highly reproducible and allows for discovery at different levels of synthesis. [Conclusion] Results from the integration of Bayesian tests and other machine learning techniques with linkage disequilibrium data suggest that we do not need to use too stringent thresholds to reduce the number of false positive associations. This method yields increased power even with relatively small samples. In fact, our evaluation shows that the method can reach almost 70% sensitivity with samples of only 100 subjects.Supported by NHLBI grants R21 HL080463 (PS); R01 HL68970 (MHS); K-24, AG025727 (TP); K23 AG026754 (D.T.)

Multiple Loci Are Associated with White Blood Cell Phenotypes

White blood cell (WBC) count is a common clinical measure from complete blood count assays, and it varies widely among healthy individuals. Total WBC count and its constituent subtypes have been shown to be moderately heritable, with the heritability estimates varying across cell types. We studied 19,509 subjects from seven cohorts in a discovery analysis, and 11,823 subjects from ten cohorts for replication analyses, to determine genetic factors influencing variability within the normal hematological range for total WBC count and five WBC subtype measures. Cohort specific data was supplied by the CHARGE, HeamGen, and INGI consortia, as well as independent collaborative studies. We identified and replicated ten associations with total WBC count and five WBC subtypes at seven different genomic loci (total WBC count—6p21 in the HLA region, 17q21 near ORMDL3, and CSF3; neutrophil count—17q21; basophil count- 3p21 near RPN1 and C3orf27; lymphocyte count—6p21, 19p13 at EPS15L1; monocyte count—2q31 at ITGA4, 3q21, 8q24 an intergenic region, 9q31 near EDG2), including three previously reported associations and seven novel associations. To investigate functional relationships among variants contributing to variability in the six WBC traits, we utilized gene expression- and pathways-based analyses. We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. Gene expression data from whole blood was utilized to show that significant biological consequences can be extracted from our genome-wide analyses, with effect estimates for significant loci from the meta-analyses being highly corellated with the proximal gene expression. In addition, collaborative efforts between the groups contributing to this study and related studies conducted by the COGENT and RIKEN groups allowed for the examination of effect homogeneity for genome-wide significant associations across populations of diverse ancestral backgrounds