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Genome-wide association studies have identified a locus on chromosome 19 associated with plasma triglyceride (TG) concentration and nonalcoholic fatty liver disease. However, the identity and functional role of the gene(s) responsible for these associations remain unknown. Of 19 expressed genes contained in this locus, none has previously been implicated in lipid metabolism. We performed gene expression studies and expression quantitative trait locus analysis in 206 human liver samples to identify the putative causal gene. Transmembrane 6 superfamily member 2 (TM6SF2), a gene with hitherto unknown function, expressed predominantly in liver and intestine, was identified as the putative causal gene. TM6SF2 encodes a protein of 351 amino acids with 7–10 predicted transmembrane domains. Otherwise, no other protein features were identified which could help to elucidate the function of TM6SF2. Protein subcellular localization studies with confocal microscopy demonstrated that TM6SF2 is localized in the endoplasmic reticulum and the ER-Golgi intermediate compartment of human liver cells. Functional studies for secretion of TG-rich lipoproteins (TRLs) and lipid droplet content were performed in human hepatoma Huh7 and HepG2 cells using confocal microscopy and siRNA inhibition and overexpression techniques. In agreement with the genome-wide association data, it was found that TM6SF2 siRNA inhibition was associated with reduced secretion of TRLs and increased cellular TG concentration and lipid droplet content, whereas TM6SF2 overexpression reduced liver cell steatosis. We conclude that TM6SF2 is a regulator of liver fat metabolism with opposing effects on the secretion of TRLs and hepatic lipid droplet content.

While conventional LDL-C, HDL-C, and triglyceride measurements reflect aggregate properties of plasma lipoprotein fractions, NMR-based measurements more accurately reflect lipoprotein particle concentrations according to class (LDL, HDL, and VLDL) and particle size (small, medium, and large). The concentrations of these lipoprotein sub-fractions may be related to risk of cardiovascular disease and related metabolic disorders. We performed a genome-wide association study of 17 lipoprotein measures determined by NMR together with LDL-C, HDL-C, triglycerides, ApoA1, and ApoB in 17,296 women from the Women's Genome Health Study (WGHS). Among 36 loci with genome-wide significance (P<5x10(-8)) in primary and secondary analysis, ten (PCCB/STAG1 (3q22.3), GMPR/MYLIP (6p22.3), BTNL2 (6p21.32), KLF14 (7q32.2), 8p23.1, JMJD1C (10q21.3), SBF2 (11p15.4), 12q23.2, CCDC92/DNAH10/ZNF664 (12q24.31.B), and WIPI1 (17q24.2)) have not been reported in prior genome-wide association studies for plasma lipid concentration. Associations with mean lipoprotein particle size but not cholesterol content were found for LDL at four loci (7q11.23, LPL (8p21.3), 12q24.31.B, and LIPG (18q21.1)) and for HDL at one locus (GCKR (2p23.3)). In addition, genetic determinants of total IDL and total VLDL concentration were found at many loci, most strongly at LIPC (15q22.1) and APOC-APOE complex (19q13.32), respectively. Associations at seven more loci previously known for effects on conventional plasma lipid measures reveal additional genetic influences on lipoprotein profiles and bring the total number of loci to 43. Thus, genome-wide associations identified novel loci involved with lipoprotein metabolism-including loci that affect the NMR-based measures of concentration or size of LDL, HDL, and VLDL particles-all characteristics of lipoprotein profiles that may impact disease risk but are not available by conventional assay.

Several genome-wide association studies have recently linked a group of single nucleotide polymorphisms in the 9p21 region with cardiovascular disease. The molecular mechanisms of this link are not fully understood. We investigated five different expression microarray datasets in order to determine if the genotype had effect on expression of any gene transcript in aorta, mammary artery, carotid plaque and lymphoblastoid cells. After multiple testing correction, no genes were found to have relation to the rs2891168 risk genotype, either on a genome-wide scale or on a regional (8 MB) scale. The neighbouring ANRIL gene was found to have eight novel transcript variants not previously known from literature and these varied by tissue type. We therefore performed a detailed probe-level analysis and found small stretches of significant relation to genotype but no consistent associations. In all investigated tissues we found an inverse correlation between ANRIL and the MTAP gene and a positive correlation between ANRIL and CDKN2A and CDKN2B. Investigation of relation of the risk genotype to gene expression is complicated by the transcript complexity of the locus. With our investigation of a range of relevant tissue we wish to underscore the need for careful attention to the complexity of the alternative splicing issues in the region and its implications to the design of future gene expression studies.

Identification and treatment of abdominal aortic aneurysm (AAA) remain among the most prominent challenges in vascular medicine. MicroRNAs (miRNAs) are crucial regulators of cardiovascular pathology and represent intriguing targets to limit AAA expansion. Here we show, by using two established murine models of AAA disease along with human aortic tissue and plasma analysis, that miR-24 is a key regulator of vascular inflammation and AAA pathology. In vivo and in vitro studies reveal chitinase 3-like 1 (Chi3l1) to be a major target and effector under the control of miR-24, regulating cytokine synthesis in macrophages as well as their survival, promoting aortic smooth muscle cell migration and cytokine production, and stimulating adhesion molecule expression in vascular endothelial cells. We further show that modulation of miR-24 alters AAA progression in animal models, and that miR-24 and CHI3L1 represent novel plasma biomarkers of AAA disease progression in humans. Abdominal aortic aneurysm (AAA) is a potentially fatal and often asymptomatic disease whose causes remain unclear. Here the authors show that a microRNA, miR-24, and its target, the glycoprotein chitinase 3-like 1, represent key regulators of AAA development.

Genes Involved in Fatty Acid Partitioning and Binding, Lipolysis, Monocyte/Macrophage Recruitment, and Inflammation Are Overexpressed in the Human Fatty Liver of Insulin-Resistant Subjects Jukka Westerbacka 1 , Maria Kolak 2 , Tuula Kiviluoto 3 , Perttu Arkkila 4 , Jukka Sirén 3 , Anders Hamsten 2 , Rachel M. Fisher 2 and Hannele Yki-Järvinen 1 , 5 1 Department of Medicine, Division of Diabetes, University of Helsinki, Helsinki, Finland 2 Atherosclerosis Research Unit, King Gustaf V Research Institute, Karolinska Institutet, Stockholm, Sweden 3 Department of Surgery, University of Helsinki, Helsinki, Finland 4 Department of Medicine, Division of Gastroenterology, University of Helsinki, Helsinki, Finland 5 Minerva Foundation Institute for Medical Research, Helsinki, Finland Address correspondence and reprint requests to Jukka Westerbacka, MD, PhD, Department of Medicine, Division of Diabetes, University of Helsinki, P.O. Box 700, Room C418b, FIN-00029 HUCH, Helsinki, Finland. E-mail: jukka.westerbacka{at}helsinki.fi Abstract OBJECTIVE —The objective of this study is to quantitate expression of genes possibly contributing to insulin resistance and fat deposition in the human liver. RESEARCH DESIGN AND METHODS —A total of 24 subjects who had varying amounts of histologically determined fat in the liver ranging from normal ( n = 8) to steatosis due to a nonalcoholic fatty liver (NAFL) ( n = 16) were studied. The mRNA concentrations of 21 candidate genes associated with fatty acid metabolism, inflammation, and insulin sensitivity were quantitated in liver biopsies using real-time PCR. In addition, the subjects were characterized with respect to body composition and circulating markers of insulin sensitivity. RESULTS —The following genes were significantly upregulated in NAFL: peroxisome proliferator–activated receptor (PPAR)γ2 (2.8-fold), the monocyte-attracting chemokine CCL2 (monocyte chemoattractant protein [MCP]-1, 1.8-fold), and four genes associated with fatty acid metabolism (acyl-CoA synthetase long-chain family member 4 [ACSL4] [2.8-fold], fatty acid binding protein [FABP]4 [3.9-fold], FABP5 [2.5-fold], and lipoprotein lipase [LPL] [3.6-fold]). PPARγ coactivator 1 (PGC1) was significantly lower in subjects with NAFL than in those without. Genes significantly associated with obesity included nine genes: plasminogen activator inhibitor 1, PPARγ, PPARδ, MCP-1, CCL3 (macrophage inflammatory protein [MIP]-1α), PPARγ2, carnitine palmitoyltransferase (CPT1A), FABP4, and FABP5. The following parameters were associated with liver fat independent of obesity: serum adiponectin, insulin, C-peptide, and HDL cholesterol concentrations and the mRNA concentrations of MCP-1, MIP-1α, ACSL4, FABP4, FABP5, and LPL. CONCLUSIONS —Genes involved in fatty acid partitioning and binding, lipolysis, and monocyte/macrophage recruitment and inflammation are overexpressed in the human fatty liver. ADIPOR, adiponectin receptor CCR2, C-C motif chemokine receptor-2 FATP, fatty acid transport protein FABP, fatty acid binding protein FFA, free fatty acid LPL, lipoprotein lipase MCP, monocyte chemoattractant protein MIP, macrophage inflammatory protein NAFL, nonalcoholic fatty liver NAFLD, NAFL disease NASH, nonalcoholic steatohepatitis PAI-1, plasminogen activator inhibitor 1 PGC1, PPARγ coactivator 1 PPAR, peroxisome proliferator–activated receptor RPLP0, ribosomal protein, large P0 TBP, TATA-binding protein Footnotes Published ahead of print at http://diabetes.diabetesjournals.org on 17 August 2007. DOI: 10.2337/db07-0156. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Received March 18, 2007. Accepted August 10, 2007. DIABETES

CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 × 10 −5 ) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 × 10 −5 ) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.

Aims/hypothesis We selected the most informative protein biomarkers for the prediction of incident cardiovascular disease (CVD) in people with type 2 diabetes. Methods In this nested case–control study we measured 42 candidate CVD biomarkers in 1,123 incident CVD cases and 1,187 controls with type 2 diabetes selected from five European centres. Combinations of biomarkers were selected using cross-validated logistic regression models. Model prediction was assessed using the area under the receiver operating characteristic curve (AUROC). Results Sixteen biomarkers showed univariate associations with incident CVD. The most predictive subset selected by forward selection methods contained six biomarkers: N-terminal pro-B-type natriuretic peptide (OR 1.69 per 1 SD, 95% CI 1.47, 1.95), high-sensitivity troponin T (OR 1.29, 95% CI 1.11, 1.51), IL-6 (OR 1.13, 95% CI 1.02, 1.25), IL-15 (OR 1.15, 95% CI 1.01, 1.31), apolipoprotein C-III (OR 0.79, 95% CI 0.70, 0.88) and soluble receptor for AGE (OR 0.84, 95% CI 0.76, 0.94). The prediction of CVD beyond clinical covariates improved from an AUROC of 0.66 to 0.72 (AUROC for Framingham Risk Score covariates 0.59). In addition to the biomarkers, the most important clinical covariates for improving prediction beyond the Framingham covariates were estimated GFR, insulin therapy and HbA 1c . Conclusions/interpretation We identified six protein biomarkers that in combination with clinical covariates improved the prediction of our model beyond the Framingham Score covariates. Biomarkers can contribute to improved prediction of CVD in diabetes but clinical data including measures of renal function and diabetes-specific factors not included in the Framingham Risk Score are also needed.

Numerous genetic loci have been associated with measures of central fat accumulation, such as waist-to-hip ratio adjusted for body mass index (WHRadjBMI). However the mechanisms by which genetic variations influence obesity remain largely elusive. Lipolysis is a key process for regulation of lipid storage in adipocytes, thus is implicated in obesity and its metabolic complications. Here, genetic variants at 36 WHRadjBMI-associated loci were examined for their influence on abdominal subcutaneous adipocyte lipolysis. Fasting subcutaneous adipose tissue biopsies were collected from 789 volunteers (587 women and 202 men, body mass index (BMI) range 17.7-62.3 kg/m2). We quantified subcutaneous adipocyte lipolysis, both spontaneous and stimulated by the catecholamine isoprenaline or a cyclic AMP analogue. DNA was extracted from peripheral blood mononuclear cells and genotyping of SNPs associated with WHRadjBMI conducted. The effects on adipocyte lipolysis measures were assessed for SNPs individually and combined in a SNP score. The WHRadjBMI-associated loci CMIP, PLXND1, VEGFA and ZNRF3-KREMEN1 demonstrated nominal associations with spontaneous and/or stimulated lipolysis. Candidate genes in these loci have been reported to influence NFκB-signaling, fat cell size and Wnt signalling, all of which may influence lipolysis. This report provides evidence for specific WHRadjBMI-associated loci as candidates to modulate adipocyte lipolysis. Additionally, our data suggests that genetically increased central fat accumulation is unlikely to be a major cause of altered lipolysis in abdominal adipocytes.

Adipose Tissue Inflammation and Increased Ceramide Content Characterize Subjects With High Liver Fat Content Independent of Obesity Maria Kolak 1 , Jukka Westerbacka 2 , Vidya R. Velagapudi 3 , Dick Wågsäter 1 , Laxman Yetukuri 3 , Janne Makkonen 2 4 , Aila Rissanen 5 , Anna-Maija Häkkinen 6 , Monica Lindell 1 , Robert Bergholm 2 4 , Anders Hamsten 1 , Per Eriksson 1 , Rachel M. Fisher 1 , Matej Orešic̆ 3 and Hannele Yki-Järvinen 1 2 1 Atherosclerosis Research Unit, Department of Medicine, King Gustaf V. Research Institute, Karolinska Institutet, Stockholm, Sweden 2 Division of Diabetes, Department of Medicine, University of Helsinki, Helsinki, Finland 3 VTT Technical Research Centre of Finland, Espoo, Finland 4 Minerva Medical Research Institute, Helsinki, Finland 5 Obesity Research Unit, University of Helsinki, Helsinki, Finland 6 Department of Oncology, University of Helsinki, Helsinki, Finland Address correspondence and reprint requests to Hannele Yki-Järvinen, MD, P.O. Box 700, Room C426B, Biomedicum, Haartmaninkatu 8, 00029 HUS, Helsinki, Finland. E-mail: ykijarvi{at}cc.helsinki.fi Abstract OBJECTIVE— We sought to determine whether adipose tissue is inflamed in individuals with increased liver fat (LFAT) independently of obesity. RESEARCH DESIGN AND METHODS— A total of 20 nondiabetic, healthy, obese women were divided into normal and high LFAT groups based on their median LFAT level (2.3 ± 0.3 vs. 14.4 ± 2.9%). Surgical subcutaneous adipose tissue biopsies were studied using quantitative PCR, immunohistochemistry, and a lipidomics approach to search for putative mediators of insulin resistance and inflammation. The groups were matched for age and BMI. The high LFAT group had increased insulin ( P = 0.0025) and lower HDL cholesterol ( P = 0.02) concentrations. RESULTS— Expression levels of the macrophage marker CD68, the chemokines monocyte chemoattractant protein-1 and macrophage inflammatory protein-1α, and plasminogen activator inhibitor-1 were significantly increased, and those of peroxisome proliferator–activated receptor-γ and adiponectin decreased in the high LFAT group. CD68 expression correlated with the number of macrophages and crown-like structures (multiple macrophages fused around dead adipocytes). Concentrations of 154 lipid species in adipose tissue revealed several differences between the groups, with the most striking being increased concentrations of triacylglycerols, particularly long chain, and ceramides, specifically Cer(d18:1/24:1) ( P = 0.01), in the high LFAT group. Expression of sphingomyelinases SMPD1 and SMPD3 were also significantly increased in the high compared with normal LFAT group. CONCLUSIONS— Adipose tissue is infiltrated with macrophages, and its content of long-chain triacylglycerols and ceramides is increased in subjects with increased LFAT compared with equally obese subjects with normal LFAT content. Ceramides or their metabolites could contribute to adverse effects of long-chain fatty acids on insulin resistance and inflammation. LFAT, liver fat MCP-1, monocyte chemoattractant protein-1 MIP-1α, macrophage inflammatory protein-1α PAI, plasminogen activator inhibitor PPAR, proliferator–activated receptor TNF-α, tumor necrosis factor-α Footnotes Published ahead of print at http://diabetes.diabetesjournals.org on 9 July 2007. DOI: 10.2337/db07-0111. M.K. and J.W. contributed equally to this work. Additional information for this article can be found in an online appendix at http://dx.doi.org/10.2337/db07-0111 . This work is part of the project Hepatic and Adipose Tissue and Functions in the Metabolic Syndrome (HEPADIP) ( http://www.hepadip.org/ ), which is supported by the European Commission as an integrated project under the 6th Framework Programme (contract LSHM-CT-2005-018734). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Accepted May 9, 2007. Received January 25, 2007. DIABETES

Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.