Search

Introduction: Most genome-wide association studies (GWAS) of polygenic traits are based on the assumption that allelic effects are additive. Hundreds of loci associated with type 2 diabetes (T2D) have been identified using this approach, but a significant proportion of heritability remains unexplained. Many genetic variants behave in a recessive fashion, and rare variants of this type can be missed by additive analyses. Methods: We used a recessive model to conduct a GWAS of T2D in unrelated individuals of European ancestry in the UK Biobank and then meta-analyzed the results with publicly available data from five European-ancestry cohorts known collectively as 70KforT2D. We used approximate conditional analysis to identify distinct secondary signals within genome-wide significant loci. Results: In total, there were 30,661 cases and 267,948 controls. We identified 54 associated loci and 15 other conditionally independent signals. Six associations were distinct from the set of previously reported signals, including results from larger additive analyses, and three were over a million base pairs away from the closest known locus. Five of the novel variants - located near the genes PELO, ADAMTS6, JAZF1, IL7, and FCHSD2 - were rare, with allele frequencies under 5%, and had large effect sizes, with odds ratios for homozygous carriers ranging from 2.7 to 7.9. Conclusions: Our results demonstrate that recessive analysis identifies loci missed by additive GWAS, confirming the value of recessive analyses. Some of the variants we detected have large effect sizes and could be useful for patient risk stratification. Collectively they add to our knowledge of the genetic architecture of T2D. Disclosure M.J. O’Connor: None. P. Cortes-Sanchez: None. S. Bonàs-Guarch: None. J.B. Cole: None. D. Torrents: None. A. Leong: None. J.C. Florez: Advisory Panel; Self; Doris Duke Charitable Foundation. Other Relationship; Self; Novo Nordisk Inc., Park Street School. J.M. Mercader: None.

Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.91, p = 2.3*10−11). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.025 SD, 3.7*10−43), alkaline phosphatase (-0.025 SD, 1.2*10−37), total cholesterol (-0.030 SD, p = 1.9*10−36) and LDL cholesterol (-0.027 SD, p = 5.1*10−30) levels. We identified a series of additional MARC1 alleles (low-frequency missense p.M187K and rare protein-truncating p.R200Ter) that also associated with lower cholesterol levels, liver enzyme levels and reduced risk of cirrhosis (0 cirrhosis cases for 238 R200Ter carriers versus 17,046 cases of cirrhosis among 759,027 non-carriers, p = 0.04) suggesting that deficiency of the MARC1 enzyme may lower blood cholesterol levels and protect against cirrhosis., Author summary Cirrhosis is a leading cause of death worldwide. However, the genetic underpinnings of cirrhosis remain poorly understood. In this study, we analyze twelve thousand individuals with cirrhosis and identify a common missense variant in a gene called MARC1 that protects against cirrhosis. Carriers of this missense variant also have lower blood cholesterol levels, lower liver enzyme levels and reduced liver fat. We identify an additional two low-frequency coding variants in MARC1 that are also associated with lower cholesterol levels, lower liver enzyme levels and protection from cirrhosis. Finally, we identify an individual homozygous for a predicted loss-of-function variant in MARC1 who exhibits very low blood LDL cholesterol levels. These genetic findings suggest that MARC1 deficiency may lower blood cholesterol levels and protect against cirrhosis, pointing to MARC1 as a potential therapeutic target for liver disease.

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed the largest inversion association analysis to date, including 21 inversions and 25 obesity-related traits, on a total of 408,898 Europeans, and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2 and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes of obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.

Protein truncating variants (PTVs) are likely to modify gene function and have been linked to hundreds of Mendelian disorders. However, the impact of PTVs on complex traits has been limited by the available sample size of whole-exome sequencing studies (WES). Here we assemble WES data from 100,304 individuals to quantify the impact of rare PTVs on 13 quantitative traits and 10 diseases. We focus on those PTVs that occur in PTV-intolerant (PI) genes, as these are more likely to be pathogenic. Carriers of at least one PI-PTV were found to have an increased risk of autism, schizophrenia, bipolar disorder, intellectual disability and ADHD (P-value (p) range: 5x10-3-9x10-12). In controls, without these disorders, we found that this burden associated with increased risk of mental, behavioral and neurodevelopmental disorders as captured by electronic health record information. Furthermore, carriers of PI-PTVs tended to be shorter (p=2x10-5), have fewer years of education (p=2x10-4) and be younger (p=2x10-7); the latter observation possibly reflecting reduced survival or study participation. While other gene-sets derived from in vivo experiments did not show any associations with PTV-burden, gene sets implicated in GWAS of cardiovascular-related traits and inflammatory bowel disease showed a significant PTV-burden with corresponding traits, mainly driven by established genes involved in familial forms of these disorders. We leveraged population health registries from 14,117 individuals to study the phenome-wide impact of PI-PTVs and identified an increase in the number of hospital visits among PI-PTV carriers. In conclusion, we provide the most thorough investigation to date of the impact of rare deleterious coding variants on complex traits, suggesting widespread pleiotropic risk.

Type 2 diabetes (T2D) affects more than 415 million people worldwide, and its costs to the health care system continue to rise. To identify common or rare genetic variation with potential therapeutic implications for T2D, we analyzed and replicated genome-wide protein coding variation in a total of 8,227 individuals with T2D and 12,966 individuals without T2D of Latino descent. We identified a novel genetic variant in the IGF2 gene associated with ∼20% reduced risk for T2D. This variant, which has an allele frequency of 17% in the Mexican population but is rare in Europe, prevents splicing between IGF2 exons 1 and 2. We show in vitro and in human liver and adipose tissue that the variant is associated with a specific, allele-dosage–dependent reduction in the expression of IGF2 isoform 2. In individuals who do not carry the protective allele, expression of IGF2 isoform 2 in adipose is positively correlated with both incidence of T2D and increased plasma glycated hemoglobin in individuals without T2D, providing support that the protective effects are mediated by reductions in IGF2 isoform 2. Broad phenotypic examination of carriers of the protective variant revealed no association with other disease states or impaired reproductive health. These findings suggest that reducing IGF2 isoform 2 expression in relevant tissues has potential as a new therapeutic strategy for T2D, even beyond the Latin American population, with no major adverse effects on health or reproduction.

Many controversies regarding the association of liver miRNAs with obesity and nonalcoholic fatty liver diseases (NAFLD) call for additional validations. This study sought to investigate variations in genes and hepatic miRNAs in a sample of obese patients with or without NAFLD and human hepatocytes (HH).A total of 60 non-consecutive obese women following bariatric surgery were recruited. Subjects were classified as NAFLD (n=17), borderline (n=24) and controls (n=19) with normal enzymatic profile, liver histology and ultrasound assessments. Profiling of 744 miRNAs was performed in 8 obese women with no sign of hepatic disease and 11 NAFLD patients. Additional validation and expression of genes related to de novo fatty acid (FA) biosynthesis, uptake, transport and β-oxidation; glucose metabolism, and inflammation was tested in the extended sample. Induction of NAFLD-related genes and miRNAs was examined in HepG2 cells and primary HH treated with palmitic acid (PA), a combination of palmitate and oleic acid, or high glucose, and insulin (HG) mimicking insulin resistance in NAFLD.In the discovery sample, 14 miRNAs were associated with NAFLD. Analyses in the extended sample confirmed decreased miR-139-5p, miR-30b-5p, miR-122-5p and miR-422a, and increased miR-146b-5p in obese subjects with NAFLD. Multiple linear regression analyses disclosed that NAFLD contributed independently to explain miR-139-5p (P=0.005), miR-30b-5p (P=0.005), miR-122-5p (P=0.021), miR-422a (P=0.007) and miR-146a (P=0.033) expression variance after controlling for confounders. Decreased miR-122-5p in liver was associated with impaired FA usage. Expression of inflammatory and macrophage-related genes was opposite to decreased miR-30b-5p, miR-139-5p and miR-422a, whereas increased miR-146b-5p was associated with FABP4 and decreased glucose metabolism and FA mobilization. In partial agreement, PA (but not HG) led to decreased miR-139-5p, miR-30b-5p, miR-422a and miR-146a in vitro, in parallel with increased lipogenesis and FA transport, decreased glucose metabolism and diminished FA oxidation.This study confirms decreased liver glucose and lipid metabolism but increased FA biosynthesis coupled with changes in five unique miRNAs in obese patients with NAFLD.

BACKGROUND:Excess weight gain throughout adulthood can lead to adverse clinical outcomes and are influenced by complex factors that are difficult to measure in free-living individuals. Metabolite profiling offers an opportunity to systematically discover new predictors for weight gain that are relatively easy to measure compared to traditional approaches. METHODS AND RESULTS:Using baseline metabolite profiling data of middle-aged individuals from the Framingham Heart Study (FHS; n = 1,508), we identified 42 metabolites associated (p < 0.05) with longitudinal change in body mass index (BMI). We performed stepwise linear regression to select 8 of these metabolites to build a metabolite risk score (MRS) for predicting future weight gain. We replicated the MRS using data from the Mexico City Diabetes Study (MCDS; n = 768), in which one standard deviation increase in the MRS corresponded to ~0.03 increase in BMI (kg/m2) per year (i.e. ~0.09 kg/year for a 1.7 m adult). We observed that none of the available anthropometric, lifestyle, and glycemic variables fully account for the MRS prediction of weight gain. Surprisingly, we found the MRS to be strongly correlated with baseline insulin sensitivity in both cohorts and to be negatively predictive of T2D in MCDS. Genome-wide association study of the MRS identified 2 genome-wide (p < 5 × 10-8) and 5 suggestively (p < 1 × 10-6) significant loci, several of which have been previously linked to obesity-related phenotypes. CONCLUSIONS:We have constructed and validated a generalizable MRS for future weight gain that is an independent predictor distinct from several other known risk factors. The MRS captures a composite biological picture of weight gain, perhaps hinting at the anabolic effects of preserved insulin sensitivity. Future investigation is required to assess the relationships between MRS-predicted weight gain and other obesity-related diseases.

Background Obesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analysis (Mendelian randomization) to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals. Methods We expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS. Results We identified 10 known metabolites that are more likely to be causes (e.g. alpha-hydroxybutyrate) or effects (e.g. valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g. glycine). Importantly, we also identified about 5 times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms. Conclusions These findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.

BackgroundObesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analyses to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals.MethodsWe expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify these metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS.ResultsWe identified 10 known metabolites that are more likely to be the causes (e.g. alpha-hydroxybutyrate) or effects (e.g. valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g. glycine). Importantly, we also identified about 5 times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms.ConclusionsThese findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals. This research was supported by the National Institute for Health Research Imperial Biomedical Research Centre. Work was funded by grants from the Wellcome Trust (nos. WT101033 to J.F. and WT205915 to I.P.), Horizon 2020 (Research and Innovation Programme nos. 667191, to J.F., 633595, to I.P., and 676556, to M.A.M.-R.; Marie Sklodowska-Curie 658145, to I.M.-E., and 43062 ZENCODE, to G.A.), European Research Council (nos. 789055, to J.F., and 609989, to M.A.M.-R.). Marató TV3 (no. 201611, to J.F. and M.A.M.-R.), Ministerio de Ciencia Innovación y Universidades (nos. BFU2014-54284-R, RTI2018-095666, to J.F., BFU2017-85926-P, to M.A.M.-R., IJCI-2015-23352, to I.F.), AGAUR (to M.A.M.-R.). UK Medical Research Council (no. MR/L007150/1, to P.F., MR/L02036X/1 to J.F.), World Cancer Research Fund (WCRF UK, to I.P.) and World Cancer Research Fund International (no. 2017/1641 to I.P.), Biobanking and Biomolecular Resources Research Infrastructure (nos. BBMRI-NL, NWO 184.021.007, to I.O.F.). Work in IDIBAPS, CRG and CNAG was supported by the CERCA Programme, Generalitat de Catalunya and Centros de Excelencia Severo Ochoa (no. SEV-2012-0208). Human islets were provided through the European islet distribution program for basic research supported by JDRF (no. 3-RSC-2016-160-I-X). We thank N. Ruiz-Gomez for technical assistance; R. L. Fernandes, T. Thorne (University of Reading) and A. Perdones-Montero (Imperial College London) for helpful discussions regarding Machine Learning approaches; B. Lenhard and M. Merkenschlager (London Institute of Medical Sciences, Imperial College London), F. Müller (University of Birmingham) and J. L. Gómez-Skarmeta (Centro Andaluz de Biología del Desarrollo) for critical comments on the draft; the CRG Genomics Unit; and the Imperial College High Performance Computing Service.

Birth weight (BW) variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. These associations have been proposed to reflect the lifelong consequences of an adverse intrauterine environment. In earlier work, we demonstrated that much of the negative correlation between BW and adult cardio-metabolic traits could instead be attributable to shared genetic effects. However, that work and other previous studies did not systematically distinguish the direct effects of an individual’s own genotype on BW and subsequent disease risk from indirect effects of their mother’s correlated genotype, mediated by the intrauterine environment. Here, we describe expanded genome-wide association analyses of own BW (n=321,223) and offspring BW (n=230,069 mothers), which identified 278 independent association signals influencing BW (214 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic influences on BW, implicating fetal- and maternal-specific mechanisms. We used Mendelian randomization to explore the causal relationships between factors influencing BW through fetal or maternal routes, for example, glycemic traits and blood pressure. Direct fetal genotype effects dominate the shared genetic contribution to the association between lower BW and higher type 2 diabetes risk, whereas the relationship between lower BW and higher later blood pressure (BP) is driven by a combination of indirect maternal and direct fetal genetic effects: indirect effects of maternal BP-raising genotypes act to reduce offspring BW, but only direct fetal genotype effects (once inherited) increase the offspring’s later BP. Instrumental variable analysis using maternal BW-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring BP. In successfully separating fetal from maternal genetic effects, this work represents an important advance in genetic studies of perinatal outcomes, and shows that the association between lower BW and higher adult BP is attributable to genetic effects, and not to intrauterine programming.

During adipogenesis, preadipocytes' cytoskeleton reorganizes in parallel with lipid accumulation. Failure to do so may impact the ability of adipose tissue (AT) to shift between lipid storage and mobilization. Here, we identify cytoskeletal transgelin 2 (TAGLN2) as a protein expressed in AT and associated with obesity and inflammation, being normalized upon weight loss. TAGLN2 was primarily found in the adipose stromovascular cell fraction, but inflammation, TGF-β, and estradiol also prompted increased expression in human adipocytes. Tagln2 knockdown revealed a key functional role, being required for proliferation and differentiation of fat cells, whereas transgenic mice overexpressing Tagln2 using the adipocyte protein 2 promoter disclosed remarkable sex-dependent variations, in which females displayed >healthy> obesity and hypertrophied adipocytes but preserved insulin sensitivity, and males exhibited physiologic changes suggestive of defective AT expandability, including increased number of small adipocytes, activation of immune cells, mitochondrial dysfunction, and impaired metabolism together with decreased insulin sensitivity. The metabolic relevance and sexual dimorphism of TAGLN2 was also outlined by genetic variants that may modulate its expression and are associated with obesity and the risk of ischemic heart disease in men. Collectively, current findings highlight the contribution of cytoskeletal TAGLN2 to the obese phenotype in a gender-dependent manner.-Ortega, F. J., Moreno-Navarrete, J. M., Mercader, J. M., Gómez-Serrano, M., García-Santos, E., Latorre, J., Lluch, A., Sabater, M., Caballano-Infantes, E., Guzmán, R., Macías-González, M., Buxo, M., Gironés, J., Vilallonga, R., Naon, D., Botas, P., Delgado, E., Corella, D., Burcelin, R., Frühbeck, G., Ricart, W., Simó, R., Castrillon-Rodríguez, I., Tinahones, F. J., Bosch, F., Vidal-Puig, A., Malagón, M. M., Peral, B., Zorzano, A., Fernández-Real, J. M. Cytoskeletal transgelin 2 contributes to gender-dependent adipose tissue expandability and immune function., GenDiab Consortium was constituted with funds from the Ministerio de Educación y Ciencia (Grant GEN2001‐4758). This work was also supported by research funds from the Instituto de Salud Carlos III (ISCIII; PI15/01934 to J.M.F‐R., and PI18/00550 to F.J.O.) and the Ministerio de Educación y Ciencia (SAF2008‐02073 to J.M.F.‐R., SAF2009‐10461 and SAF2012‐33014 to B.P.), the Instituto de Salud Carlos III (CIBEROBN and CIBERDEM), the Pla estratègic de recerca i innovació en salut and the Govern de la Generalitat (PERIS 2016 to F.J.O.), the Agènda de Gestió d'Ajuts Universitaris de Recerca (AGAUR, FI‐DGR 2015 to J.L.), the Universidad Autónoma de Madrid (FPI‐UAM to M.G.‐S.), and the Fondo Europeo de Desarrollo Regional (FEDER). J.M.M. was supported by a Beatriu de Pinós fellowship from the AGAUR. R.B. is recipient of funding from the Agence Nationale de la Recherche (Florinflam and Floradip programs) and the Institute Nationale du Diabète.

Coronary artery disease (CAD) is more frequent among individuals with dysglycemia. Preventive interventions for diabetes can improve cardiometabolic risk factors (CRFs), but it is unclear whether the benefits on CRFs are similar for individuals at different genetic risk for CAD. We built a 201-variant polygenic risk score (PRS) for CAD and tested for interaction with diabetes prevention strategies on 1-year changes in CRFs in 2,658 Diabetes Prevention Program (DPP) participants. We also examined whether separate lifestyle behaviors interact with PRS and affect changes in CRFs in each intervention group. Participants in both the lifestyle and metformin interventions had greater improvement in the majority of recognized CRFs compared with placebo (P < 0.001) irrespective of CAD genetic risk (Pinteraction > 0.05). We detected nominal significant interactions between PRS and dietary quality and physical activity on 1-year change in BMI, fasting glucose, triglycerides, and HDL cholesterol in individuals randomized to metformin or placebo, but none of them achieved the multiple-testing correction for significance. This study confirms that diabetes preventive interventions improve CRFs regardless of CAD genetic risk and delivers hypothesis-generating data on the varying benefit of increasing physical activity and improving diet on intermediate cardiovascular risk factors depending on individual CAD genetic risk profile.

Metabolomics is a powerful approach for discovering biomarkers and for characterizing the biochemical consequences of genetic variation. While untargeted metabolite profiling can measure thousands of signals in a single experiment, many biologically meaningful signals cannot be readily identified as known metabolites nor compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To overcome these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets and to generate metabolic pathway annotations for these signals. To pair up signals measured in different datasets, where retention times (RT) are often not comparable or even available, we implemented an imputation-based approach that only requires mass-to-charge ratios (m/z). As validation, we treated each shared known metabolite as an unmatched signal and showed that PAIRUP-MS correctly matched 70–88% of these metabolites from among thousands of signals, equaling or outperforming a standard m/z- and RT-based approach. We performed further validation using genetic data: the most stringent set of matched signals and shared knowns showed comparable consistency of genetic associations across datasets. Next, we developed a pathway reconstitution method to annotate unknown signals using curated metabolic pathways containing known metabolites. We performed genetic validation for the generated annotations, showing that annotated signals associated with gene variants were more likely to be enriched for pathways functionally related to the genes compared to random expectation. Finally, we applied PAIRUP-MS to study associations between metabolites and genetic variants or body mass index (BMI) across multiple datasets, identifying up to ~6 times more significant signals and many more BMI-associated pathways compared to the standard practice of only analyzing known metabolites. These results demonstrate that PAIRUP-MS enables analysis of unknown signals in a robust, biologically meaningful manner and provides a path to more comprehensive, well-powered studies of untargeted metabolomics data., Author summary Untargeted metabolomics can systematically profile thousands of metabolite signals in biological samples and is an increasingly popular approach for discovering biomarkers and predictors for human traits and diseases. However, currently, a significant portion of the measured signals cannot be identified as known metabolites or easily compared across datasets, and thus are usually excluded from downstream analyses. Here, we present PAIRUP-MS, a suite of computational methods designed to analyze unknown, unidentified signals across multiple mass spectrometry-based profiling datasets. Specifically, PAIRUP-MS contains a flexible imputation-based approach for pairing up unknown signals across datasets, allowing for meta-analysis of matched signals across studies that would otherwise be incompatible. PAIRUP-MS also offers a pathway annotation and enrichment analysis framework that links metabolite signals to plausible biological functions without using their chemical identities. Importantly, we validated both components of PAIRUP-MS using genetic data and applied them to study an example trait, body mass index. Overall, our results demonstrate that PAIRUP-MS enables previously infeasible analyses of unknown, unidentified signals across multiple datasets, thereby greatly improving power for discovery and biological inference.

ObjectivePsoriatic arthritis (PsA) is a chronic inflammatory arthritis affecting up to 30% of patients with psoriasis (Ps). To date, most of the known risk loci for PsA are shared with Ps, and identifying disease-specific variation has proven very challenging. The objective of the present study was to identify genetic variation specific for PsA.MethodsWe performed a genome-wide association study in a cohort of 835 patients with PsA and 1558 controls from Spain. Genetic association was tested at the single marker level and at the pathway level. Meta-analysis was performed with a case–control cohort of 2847 individuals from North America. To confirm the specificity of the genetic associations with PsA, we tested the associated variation using a purely cutaneous psoriasis cohort (PsC, n=614) and a rheumatoid arthritis cohort (RA, n=1191). Using network and drug-repurposing analyses, we further investigated the potential of the PsA-specific associations to guide the development of new drugs in PsA.ResultsWe identified a new PsA risk single-nucleotide polymorphism at B3GNT2 locus (p=1.10e-08). At the pathway level, we found 14 genetic pathways significantly associated with PsA (pFDRConclusionThese findings provide insights into the biological mechanisms that are specific for PsA and could contribute to develop more effective therapies.

The increasing size and diversity of genome-wide association studies provide an exciting opportunity to study how the genetics of complex traits vary among diverse populations. Here, we introduce covariate-adjusted LD score regression (cov-LDSC), a method to accurately estimate genetic heritability and its enrichment in both homogenous and admixed populations with summary statistics and in-sample LD estimates. In-sample LD can be estimated from a subset of the GWAS samples, allowing our method to be applied efficiently to very large cohorts. In simulations, we show that unadjusted LDSC underestimates by 10% − 60% in admixed populations; in contrast, cov-LDSC is robust to all simulation parameters. We apply cov-LDSC to genotyping data from approximately 170,000 Latino, 47,000 African American and 135,000 European individuals. We estimate and detect heritability enrichment in three quantitative and five dichotomous phenotypes respectively, making this, to our knowledge, the most comprehensive heritability-based analysis of admixed individuals. Our results show that most traits have high concordance of and consistent tissue-specific heritability enrichment among different populations. However, for age at menarche, we observe population-specific heritability estimates of . We observe consistent patterns of tissue-specific heritability enrichment across populations; for example, in the limbic system for BMI, the per-standardized-annotation effect size τ* is 0.16 ± 0.04, 0.28 ± 0.11 and 0.18 ± 0.03 in Latino, African American and European populations respectively. Our results demonstrate that our approach is a powerful way to analyze genetic data for complex traits from underrepresented populations.Author summaryAdmixed populations such as African Americans and Hispanic Americans bear a disproportionately high burden of disease but remain underrepresented in current genetic studies. It is important to extend current methodological advancements for understanding the genetic basis of complex traits in homogeneous populations to individuals with admixed genetic backgrounds. Here, we develop a computationally efficient method to answer two specific questions. First, does genetic variation contribute to the same amount of phenotypic variation (heritability) across diverse populations? Second, are the genetic mechanisms shared among different populations? To answer these questions, we use our novel method to conduct the first comprehensive heritability-based analysis of a large number of admixed individuals. We show that there is a high degree of concordance in total heritability and tissue-specific enrichment between different ancestral groups. However, traits such as age at menarche show a noticeable differences among populations. Our work provides a powerful way to analyze genetic data in admixed populations and may contribute to the applicability of genomic medicine to admixed population groups.

Context: Molecular mechanisms associated with physiological variations in adipose tissue (AT) are not fully recognized. The most recent reports highlight the critical relevance of microRNAs (miRNAs) found in AT. Objective: To identify changes in messenger RNA (mRNA) and miRNA expressions and their interaction in human AT before and after surgery-induced weight loss. Research Design and Setting: Genome-wide mRNA and miRNA expressions were assessed by microarrays in abdominal subcutaneous AT of 16 morbidly obese women before and 2 years after laparoscopic Roux-en-Y gastric bypass. The association of changes in miRNAs with their respective mRNA targets was studied. The results were replicated in publicly available microarray datasets. Validation was made by real-time polymerase chain reaction in additional fat samples from 26 age-matched lean women and in isolated human adipocytes. Results: A total of 5018 different mRNA probe sets and 15 miRNAs were differentially expressed after surgery-induced weight loss. The clustering of similar expression patterns for gene products with related functions revealed molecular footprints that elucidate significant changes in cell cycle, development, lipid metabolism, and the inflammatory response. The participation of inflammation was demonstrated by results assessed in isolated adipocytes. Interestingly, when transcriptomes were analyzed taking into account the presence of miRNA target sites, miRNA target mRNAs were upregulated in obese AT (P value = 2 × 10−181) and inflamed adipocytes (P value = 4 × 10−61), according to the number of target sites harbored by each transcript. Conclusions: Current findings suggest impaired miRNA target gene expression in obese AT in close association with inflammation, both improving after weight loss.

Cytokinetic abscission facilitates the irreversible separation of daughter cells. This process requires the endosomal-sorting complexes required for transport (ESCRT) machinery and is tightly regulated by charged multivesicular body protein 4C (CHMP4C), an ESCRT-III subunit that engages the abscission checkpoint (NoCut) in response to mitotic problems such as persisting chromatin bridges within the midbody. Importantly, a human polymorphism in CHMP4C (rs35094336, CHMP4C T232 ) increases cancer susceptibility. Here, we explain the structural and functional basis for this cancer association: The CHMP4C T232 allele unwinds the C-terminal helix of CHMP4C, impairs binding to the early-acting ESCRT factor ALIX, and disrupts the abscission checkpoint. Cells expressing CHMP4C T232 exhibit increased levels of DNA damage and are sensitized to several conditions that increase chromosome missegregation, including DNA replication stress, inhibition of the mitotic checkpoint, and loss of p53. Our data demonstrate the biological importance of the abscission checkpoint and suggest that dysregulation of abscission by CHMP4C T232 may synergize with oncogene-induced mitotic stress to promote genomic instability and tumorigenesis.

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer regions (enhancer clusters, stretch enhancers or super-enhancers). So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in 3D-space. Furthermore, their target genes are generally unknown. We have now created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers with their target genes, often located hundreds of kilobases away. It further revealed sets of islet enhancers, super-enhancers and active promoters that form 3D higher-order hubs, some of which show coordinated glucose-dependent activity. Hub genetic variants impact the heritability of insulin secretion, and help identify individuals in whom genetic variation of islet function is important for T2D. Human islet 3D chromatin architecture thus provides a framework for interpretation of T2D GWAS signals.

In the version of this article initially published, in Fig. 3, the y-axis numbering did not match the log scale indicated in the axis label. The error has been corrected in the HTML and PDF version of the article.

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis. An Author Correction to this article was published on 16 August 2018. https://www.nature.com/articles/s41588-018-0197-6

Protein-coding genetic variants that strongly affect disease risk can provide important clues into disease pathogenesis. Here we report an exome sequence analysis of 20,791 type 2 diabetes (T2D) cases and 24,440 controls from five ancestries. We identify rare (minor allele frequency30 SLC30A8 alleles, and (b) within 12 gene sets, including those corresponding to T2D drug targets (p=6.1×10−3) and candidate genes from knockout mice (p=5.2×10−3). Within our study, the strongest T2D rare variant gene-level signals explain at most 25% of the heritability of the strongest common single-variant signals, and the rare variant gene-level effect sizes we observe in established T2D drug targets will require 110K-180K sequenced cases to exceed exome-wide significance. To help prioritize genes using associations from current smaller sample sizes, we present a Bayesian framework to recalibrate association p-values as posterior probabilities of association, estimating that reaching ppwww.type2diabetesgenetics.org.

Cytokinetic abscission facilitates the irreversible separation of daughter cells. This process requires the Endosomal Sorting Complexes Required for Transport (ESCRT) machinery and is tightly regulated by Charged Multivesicular body Protein 4C (CHMP4C), an ESCRT-III subunit that engages the abscission checkpoint (NoCut) in response to mitotic problems such as persisting chromatin bridges within the midbody. Importantly, a human polymorphism in CHMP4CT232 (rs35094336), increases cancer susceptibility. Here, we explain the structural and functional basis for this cancer association: the CHMP4CT232 allele unwinds the C-terminal helix of CHMP4C, impairs binding to the early-acting ESCRT factor ALIX, and disrupts the abscission checkpoint. Cells expressing CHMP4CT232 exhibit increased levels of DNA damage and are sensitized to several conditions that increase chromosome mis-segregation, including DNA replication stress, inhibition of the mitotic checkpoint, and loss of p53. Our data demonstrate the biological importance of the abscission checkpoint, and suggest that dysregulation of abscission by CHMP4CT232 may synergize with oncogene-induced mitotic stress to promote genomic instability and tumorigenesis.Significance StatementThe final step of cell division, abscission, is temporally regulated by the Aurora B kinase and CHMP4C in a conserved pathway called the abscission checkpoint which arrests abscission in the presence of lingering mitotic problems. Despite extensive study, the physiological importance of this pathway to human health has remained elusive. We now demonstrate that a cancer predisposing polymorphism in CHMP4C disrupts the abscission checkpoint and results in DNA damage accumulation. Moreover, deficits in this checkpoint synergize with p53 loss and generate aneuploidy under stress conditions that increase the frequency of chromosome missegregation. Therefore, cells expressing the cancer-associated polymorphism in CHMP4C are genetically unstable, thus suggesting a novel oncogenic mechanism that may involve the dysregulation of abscission.

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662075, associated with a twofold increased risk for T2D in males. rs146662075 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches., Genome-wide association studies have uncovered several loci associated with diabetes risk. Here, the authors reanalyse public type 2 diabetes GWAS data to fine map 50 known loci and identify seven new ones, including one near ATGR2 on the X-chromosome that doubles the risk of diabetes in men.

Background: Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with a complex genetic inheritance. Genome-wide association studies (GWAS) have significantly increased the number of significant loci associated with SLE risk. To date, however, established loci account for less than 30% of the disease heritability and additional risk variants have yet to be identified. Here we performed a GWAS followed by a meta-analysis to identify new genome-wide significant loci for SLE. Methods: We genotyped a cohort of 907 patients with SLE (cases) and 1524 healthy controls from Spain and performed imputation using the 1000 Genomes reference data. We tested for association using logistic regression with correction for the principal components of variation. Meta-analysis of the association results was subsequently performed on 7,110,321 variants using genetic data from a large cohort of 4036 patients with SLE and 6959 controls of Northern European ancestry. Genetic association was also tested at the pathway level after removing the effect of known risk loci using PASCAL software. Results: We identified five new loci associated with SLE at the genome-wide level of significance (p < 5 × 10? 8): GRB2, SMYD3, ST8SIA4, LAT2 and ARHGAP27. Pathway analysis revealed several biological processes significantly associated with SLE risk: B cell receptor signaling (p = 5.28 × 10? 6), CTLA4 co-stimulation during T cell activation (p = 3.06 × 10? 5), interleukin-4 signaling (p = 3.97 × 10? 5) and cell surface interactions at the vascular wall (p = 4.63 × 10? 5). Conclusions: Our results identify five novel loci for SLE susceptibility, and biologic pathways associated via multiple low-effect-size loci. This study was funded by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). This work has been also sponsored by the grant SEV-2011-00067 of Severo Ochoa Program, awarded by the Spanish Government. This work was supported by an EFSD/Lilly research fellowship. Josep M. Mercader was supported by Sara Borrell Fellowship from the Instituto Carlos III. Sílvia Bonàs was awarded an FI-DGR Fellowship from FI-DGR 2013 from Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya). The study sponsors had no role in the design of the study, collection, analysis or interpretation of the data.

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches., This work has been sponsored by the grant SEV-2011-00067 of Severo Ochoa Program, awarded by the Spanish Government. This work was supported by an EFSD/Lilly research fellowship. Josep M. Mercader was supported by Sara Borrell Fellowship from the Instituto Carlos III and Beatriu de Pinós fellowship from the Agency for Management of University and Research Grants (AGAUR). Sílvia Bonàs was FI-DGR Fellowship from FI-DGR 2013 from Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya). This study makes use of data generated by the WTCCC. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113. This study also makes use of data generated by the UK10K Consortium, derived from samples from UK10K COHORT IMPUTATION (EGAS00001000713). A full list of the investigators who contributed to the generation of the data is available in www.UK10K.org. Funding for UK10K was provided by the Wellcome Trust under award WT091310. We acknowledge PRACE for awarding us to access MareNostrum supercomputer, based in Spain at Barcelona. The technical support group, particularly Pablo Ródenas and Jorge Rodríguez, from the Barcelona Supercomputing Center is gratefully acknowledged. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 667191. Mercè Planas-Fèlix is funded by the Obra Social Fundación la Caixa fellowship under the Severo Ochoa 2013 program. Work from Irene Miguel-Escalada, Ignasi Moran, Goutham Atla, and Jorge Ferrer was supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre, the Wellcome Trust (WT101033), Ministerio de Economía y Competitividad (BFU2014-54284-R) and Horizon 2020 (667191). Irene Miguel-Escalada has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska–Curie grant agreement No 658145. We acknowledge Prof. Giulio Cossu (Institute of Inflammation and Repair, University of Manchester) for providing the muscle myoblast cell line. We also acknowledge the InterAct and SIGMA Type 2 Diabetes Consortia for access to the data to replicate the rs146662075 variant. A full list of the investigators of the SIGMA Type 2 Diabetes and the InterAct consortia is provided in Supplementary Notes 3 and 4. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent research center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). This research has been conducted using the UK Biobank Resource (application number 16803). We also acknowledge Bianca C. Porneala, MS for his technical assistance in the collection and curation of the genotype and phenotype data from Partners Biobank. We also thank Marcin von Grotthuss for their support for uploading the summary statistics data to the Type 2 Diabetes Genetic Portal (AMP-T2D portal). Finally, we thank all the Computational Genomics group at the BSC for their helpful discussions and valuable comments on the manuscript.

Objective The aim of the study was to investigate the relationship between germline variations as a prognosis biomarker in patients with advanced Non-Small-Cell-Lung-Cancer (NSCLC) subjected to first-line platinum-based treatment. Materials and Methods We carried out a two-stage genome-wide-association study in non-small-cell lung cancer patients with platinum-based chemotherapy in an exploratory sample of 181 NSCLC patients from Caucasian origin, followed by a validation on 356 NSCLC patients from the same ancestry (Valencia, Spain). Results We identified germline variants in SMYD2 as a prognostic factor for survival in patients with advanced NSCLC receiving chemotherapy. SMYD2 alleles are associated to a decreased overall survival and with a reduced Time to Progression. In addition, enrichment pathway analysis identified 361 variants in 40 genes to be involved in poorer outcome in advanced-stage NSCLC patients. Conclusion Germline SMYD2 alleles are associated with bad clinical outcome of first-line platinum-based treatment in advanced NSCLC patients. This result supports the role of SMYD2 in the carcinogenic process, and might be used as prognostic signature directing patient stratification and the choice of therapy. Microabstract A two-Stage Genome wide association study in Caucasian population reveals germline genetic variation in SMYD2 associated to progression disease in first-line platinum-based treatment in advanced NSCLC patients. SMYD2 profiling might have prognostic / predictive value directing choice of therapy and enlighten current knowledge on pathways involved in human carcinogenesis as well in resistance to chemotherapy.

BackgroundHeritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation.MethodsWe analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107).ResultsHeritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with LINC01432 (p=1.9×10−9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10−10) and variants in IRF4 (p=2.8×10−57), SLC45A2 (p=2.2×10−130), HERC2 (p=2.8×10−176), OCA2 (p=2.4×10−121) and MC1R (p=7.7×10−22) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold −9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9.ConclusionConsidering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits.

Background Consumption of long-chain polyunsaturated fatty acids (PUFAs), which are abundant in seafood and nuts, ameliorates components of the metabolic syndrome. Circulating microRNAs (miRNAs) have demonstrated to be valuable biomarkers of metabolic diseases. Here, we investigated whether a sustained nuts-enriched diet can lead to changes in circulating miRNAs, in parallel to the dietary modification of fatty acids (FAs). Methods and Results The profile of 192 common miRNAs was assessed (TaqMan low-density arrays) in plasma from 10 healthy women before and after an 8-week trial with a normocaloric diet enriched with PUFAs (30 g/day of almonds and walnuts). The most relevant miRNAs were validated in an extended sample of 30 participants (8 men and 22 women). Adiponectin was measured by immunoassay and FAs by gas liquid chromatography coupled to mass spectrometry. The percentage of both ω-3 ( P =.01) and ω-6 ( P =.029) PUFAs of dietary origin (as inferred from plasma FA concentrations) increased, whereas saturated FAs decreased ( P =.0008). Concomitantly with changes in circulating FAs, several miRNAs were modified by treatment, including decreased miR-328, miR-330-3p, miR-221 and miR-125a-5p, and increased miR-192, miR-486-5p, miR-19b, miR-106a, miR-769-5p, miR-130b and miR-18a. Interestingly, miR-106a variations in plasma correlated with changes in PUFAs, while miR-130b ( r =0.58, P =.003) and miR-221 ( r =0.46, P =.03) reflected changes in C-reactive protein. The dietary modulation of miR-125a-5p mirrored changes in fasting triglycerides ( r =−0.44, P =.019) and increased adiponectin ( r =0.43, P =.026). Conclusion Dietary FAs (as inferred from plasma FA concentration) are linked to changes in circulating miRNAs, which may be modified by a PUFAs-enriched diet.

Type 2 diabetes (T2D) affects more than 415 million people worldwide, and its costs to the health care system continue to rise. To identify common or rare genetic variation with potential therapeutic implications for T2D, we analyzed and replicated genome-wide protein coding variation in a total of 8,227 individuals with T2D and 12,966 individuals without T2D of Latino descent. We identified a novel genetic variant in the IGF2 gene associated with ∼20% reduced risk for T2D. This variant, which has an allele frequency of 17% in the Mexican population but is rare in Europe, prevents splicing between IGF2 exons 1 and 2. We show in vitro and in human liver and adipose tissue that the variant is associated with a specific, allele-dosage–dependent reduction in the expression of IGF2 isoform 2. In individuals who do not carry the protective allele, expression of IGF2 isoform 2 in adipose is positively correlated with both incidence of T2D and increased plasma glycated hemoglobin in individuals without T2D, providing support that the protective effects are mediated by reductions in IGF2 isoform 2. Broad phenotypic examination of carriers of the protective variant revealed no association with other disease states or impaired reproductive health. These findings suggest that reducing IGF2 isoform 2 expression in relevant tissues has potential as a new therapeutic strategy for T2D, even beyond the Latin American population, with no major adverse effects on health or reproduction.

Background: MicroRNAs (miRNAs) are non-coding RNAs that regulate cellular processes by controlling protein translation and mRNA degradation. Objective: We aimed to explore the miRNA signature of multiple sclerosis (MS) patients versus controls and the possibility that patients with lipid-specific oligolconal IgM bands (LS_OCMB), a predictor of a more severe disease course, may have a distinct profile. Methods: An extensive profile of 754 miRNAs was evaluated in the cerebrospinal fluid (CSF) of 14 women using TaqMan low-density arrays. Differentially expressed miRNAs together with others previously identified in the literature were validated in an extended sample of 86 MS patients (39 LS_OCMB+) and 55 controls. Results: We detected higher levels of miR-150 in MS patients and especially in those with LS_OCMB+. Other miRNAs (miR-328, miR-30a-5p and miR-645) were up-regulated in MS patients compared to controls while miR-21, miR-199a-3p, miR-191, miR-365, miR-106a and miR-146a showed down-regulated expression. Considering only patients with LS_OCMB+, we also detected up-regulation of miR-30a-5p, miR-150 and miR-645 and down-regulation of miR-191 compared to controls. Conclusion: Our study confirms the recent findings regarding the deregulated expression of miR-150 not only with MS but also with the presence of LS_OCMB. This study highlights the potential utility of miRNAs in CSF as biomarkers for MS.

Metformin is widely used in the treatment of type 2 diabetes (T2D), but its mechanism of action is poorly defined. Recent evidence implicates the gut microbiota as a site of metformin action. In a double-blind study, we randomized individuals with treatment-naive T2D to placebo or metformin for 4 months and showed that metformin had strong effects on the gut microbiome. These results were verified in a subset of the placebo group that switched to metformin 6 months after the start of the trial. Transfer of fecal samples (obtained before and 4 months after treatment) from metformin-treated donors to germ-free mice showed that glucose tolerance was improved in mice that received metformin-altered microbiota. By directly investigating metformin–microbiota interactions in a gut simulator, we showed that metformin affected pathways with common biological functions in species from two different phyla, and many of the metformin-regulated genes in these species encoded metalloproteins or metal transporters. Our findings provide support for the notion that altered gut microbiota mediates some of metformin's antidiabetic effects.

Lambda interferons (IFNLs) have immunomodulatory functions at epithelial barrier surfaces. IFN-λ4, a recent member of this family is expressed only in a subset of the population due to a frameshift-causing DNA polymorphism rs368234815. We examined the association of this polymorphism with atopy (aeroallergen sensitization) and asthma in a Polish hospital-based case-control cohort comprising of well-characterized adult asthmatics (n = 326) and healthy controls (n = 111). In the combined cohort, we saw no association of the polymorphism with asthma and/or atopy. However, the IFN-λ4-generating ΔG allele protected older asthmatic women (>50 yr of age) from atopic sensitization. Further, ΔG allele significantly associated with features of less-severe asthma including bronchodilator response and corticosteroid usage in older women in this Polish cohort. We tested the association of related IFNL locus polymorphisms (rs12979860 and rs8099917) with atopy, allergic rhinitis and presence/absence of asthma in three population-based cohorts from Europe, but saw no significant association of the polymorphisms with any of the phenotypes in older women. The polymorphisms associated marginally with lower occurrence of asthma in men/older men after meta-analysis of data from all cohorts. Functional and well-designed replication studies may reveal the true positive nature of these results. SC was supported as a visiting scientist by Healthy Ageing Research Centre, Medical University of Lodz. This study was supported by Polish National Science Centre grant no. 2013/09/B/NZ6/00746 . The authors (SC, AW, MP, JM and MLK) have been partially supported by The Healthy Ageing Research Centre Project (REGPOT-2012-2013-1, 7FP). Inter99 and Health2006 study: TS was supported by a grant from the Lundbeck Foundation (Grant number R165-2013-15410), the Harboe Foundation (Grant number 16152), the A.P. Møller Foundation for the Advancement of Medical Science (Grant number 15-363), Aase and Einar Danielsen's Foundation (Grant number 10-001490), and the Weimann's grant. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). GERA study: This work has been sponsored by the grant SEV-2011-00067 of Severo Ochoa Program, awarded by the Spanish Government. This work was supported by an EFSD/Lilly research fellowship. Josep M. Mercader was supported by Sara Borrell Fellowship from the Instituto Carlos III. Sílvia Bonàs was FI-DGR Fellowship from FI-DGR 2013 from Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya). COPSAC2000 study: We greatly acknowledge the private and public research funding allocated to COPSAC and listed on www.copsac.com, with special thanks to The Lundbeck Foundation (Grant nr. R16-A1694); Ministry of Health (Grant nr. 903516); Danish Council for Strategic Research (Grant nr.: 0603-00280B); The Danish Council for Independent Research and The Capital Region Research Foundation as core supporters.

BACKGROUND Genomic studies have yielded important insights into the pathogenesis of obesity. Circulating microRNAs (miRNAs) are valuable biomarkers of systemic diseases and potential therapeutic targets. We sought to define the circulating pattern of miRNAs in obesity and examine changes after weight loss. METHODS We assessed the genomewide circulating miRNA profile cross-sectionally in 32 men and after surgery-induced weight loss in 6 morbidly obese patients. The most relevant miRNAs were cross-sectionally validated in 80 men and longitudinally in 22 patients (after surgery-induced weight loss). We evaluated the effects of diet-induced weight loss in 9 obese patients. Thirty-six circulating miRNAs were associated with anthropometric variables in the initial sample. RESULTS In the validation study, morbidly obese patients showed a marked increase of miR-140-5p, miR-142-3p (both P < 0.0001), and miR-222 (P = 0.0002) and decreased levels of miR-532–5p, miR-125b, miR-130b, miR-221, miR-15a, miR-423-5p, and miR-520c-3p (P < 0.0001 for all). Interestingly, in silico targets leukemia inhibitory factor receptor (LIFR) and transforming growth factor receptor (TGFR) of miR-140-5p, miR-142-3p, miR-15a, and miR-520c-3p circulated in association with their corresponding miRNAs. Moreover, a discriminant function of 3 miRNAs (miR-15a, miR-520c-3p, and miR-423-5p) was specific for morbid obesity, with an accuracy of 93.5%. Surgery-induced (but not diet-induced) weight loss led to a marked decrease of miR-140-5p, miR-122, miR-193a-5p, and miR-16-1 and upregulation of miR-221 and miR-199a-3p (P < 0.0001 for all). CONCLUSIONS Circulating miRNAs are deregulated in severe obesity. Weight loss–induced changes in this profile and the study of in silico targets support this observation and suggest a potential mechanistic relevance.

Calgranulin B (S100A9) was recognized as a candidate type 2 diabetes (T2D) gene in the genomic profiling of muscle from a rodent model of T2D and identifying the human orthologs of genes localized in T2D susceptibility regions. Circulating and S100A9 expressions in muscle and adipose tissue, isolated fat cells, and mouse models were evaluated. A common 5'-upstream single-nucleotide polymorphism (SNP; rs3014866) for S100A9 was analyzed, as well as the effects of weight loss and treatments in vitro with recombinant S100A9. S100a9 expression was increased in muscle of diabetic mice (1.6-fold, p = 0.002), and in muscle from subjects with impaired glucose tolerance (∼4-fold, p = 0.028; n = 34). The rs3014866 SNP was associated with circulating S100A9 and the risk of T2D, having TT carriers at 28 % (p = 0.03) lower risk (n = 1,450). Indeed, increased circulating S100A9 (∼4-fold, p = 0.03; n = 206) and subcutaneous (2-fold, p = 0.01) and omental (1.4-fold, p = 0.04) S100A9 gene expressions (n = 83) in TT carriers run in parallel to decreased fasting glucose and glycated hemoglobin. Accordingly, metformin led to increased S100A9 mRNA in ex vivo-treated adipose tissue explants (n = 5/treatment). Otherwise, obese subjects showed a compensatory increase in circulating and S100A9 expressions in adipose (n = 126), as further demonstrated by decreased levels after diet- (-34 %, p = 0.002; n = 20) and surgery-induced (-58 %, p = 0.02; n = 8) weight loss. Lipopolysaccharide led to increased S100A9 in adipose from mice (n = 5/treatment) while recombinant S100A9 downregulated inflammation in adipocytes (n = 3/treatment). Current findings support the strategy of testing differentially expressed genes in mice and human orthologs associated with T2D. The increased S100A9 reported for obesity and insulin resistance may be envisioned as a compensatory mechanism for inflammation.

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P&thinsp

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicine

Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P, 論文

Background Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D. Methods and findings In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), “lipodystrophy-like” fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry. Conclusion Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management., Using a clustering Bayesian approach applied to GWAS, Jose Florez and colleagues identify traits and loci associated with type 2 diabetes that may be used to classify patients., Author summary Why was this study done? Clinical experience and physiological phenotyping suggest that type 2 diabetes (T2D) is a heterogeneous disease. Recent studies leveraged phenotypic data to identify subtypes of individuals with T2D but have not included genetic data as a driving component of the clustering process. Previous efforts to cluster T2D genetic loci used unsupervised hierarchical clustering, a “hard clustering” method that restricts the membership of a given genetic locus to a single cluster. What did the researchers do and find? We applied a novel “soft clustering” method termed Bayesian nonnegative matrix factorization to cluster variant-trait associations ascertained from publicly available genome-wide association studies for 94 known T2D variants and 47 diabetes-related traits. We identified five novel robust clusters of T2D loci, two related to insulin deficiency and three related to insulin resistance, and showed that these clusters are differentially enriched for relevant tissue-specific enhancers and promoters. In up to 17,365 individuals with T2D from four distinct studies, about 30% of individuals have a genetic risk score in the top decile of uniquely one cluster, and these individuals have cluster-specific phenotypic traits that distinguish them from others with T2D. What do these findings mean? Soft clustering of genetic loci associated with T2D produced biologically supported mechanistic pathways, illuminating how loci might impact T2D risk. Classification of individuals by these genetic pathways may offer a step toward genetically anchored but physiologically informed diagnosis, surveillance, and management of patients with T2D.

Eur J Clin Invest 2010; 40 (7): 600–607 Abstract Background Iron is involved in oxidative stress and type 2 diabetes (T2D). Transferrin receptor (TFRC) constitutes the major receptor by which most cells take up iron. The aim of this study was to evaluate whether TFRC gene polymorphisms are associated with T2D. Materials and methods We evaluated TFRC gene polymorphism (rs3817672, 210AG, S142G) in a sample of T2D patients and nondiabetic controls (n = 722), and 39 SNPs within the TFRC genomic region analysed by the Welcome Trust Case Control Consortium (WTCCC) (1921 T2D subjects and 3000 controls). In a subset of subjects, glucose tolerance and insulin sensitivity were also studied. Results The frequency of the G allele at the position 210 of the TFRC gene was significantly higher in T2D patients. Both GG and GA genotypes had a 69% (P

The anx/anx mouse displays poor appetite and lean appearance and is considered a good model for the study of anorexia nervosa. To identify new genes involved in feeding behavior and body weight regulation we performed an expression profiling in the hypothalamus of the anx/anx mice. Using commercial microarrays we detected 156 differentially expressed genes and validated 92 of those using TaqMan low-density arrays. The expression of a set of 87 candidate genes selected based on literature evidences was also quantified by TaqMan low-density arrays. Our results showed enrichment in deregulated genes involved in cell death, cell morphology, and cancer, as well as an alteration of several signaling circuits involved in energy balance including neuropeptide Y and melanocortin signaling. The expression profile along with the phenotype led us to conclude that anx/anx mice resemble the anorexia-cachexia syndrome typically observed in cancer, infection with human immunodeficiency virus or chronic diseases, rather than starvation, and that anx/anx mice could be considered a good model for the treatment and investigation of this condition.

Background There is an increasing recognition that the pathophysiology of mental disorders could be the result of deregulation of synaptic plasticity with alterations of neurotrophins. The valine (Val)66-to-methionine (Met) variant, located in the pro brain-derived neurotrophic factor (BDNF) sequence, has been extensively studied through linkage and association approaches in several psychiatric disorders. Methods We performed a meta-analysis restricted to individual case-control studies in different categories of mental disorders and BDNF Val66Met polymorphism. We included data from 39 case-control studies encompassing psychiatric phenotypes: eating disorders, substance-related disorders, mood disorders, and schizophrenia, among others. Results The association of Val66Met was confined to three diagnoses: substance-related disorders, eating disorders, and schizophrenia. The Val/Met and the Met/Met genotypes increase the risk for eating disorders up to 33%, while these same genotypes confer a 21% protective effect in substance-related disorders. The homozygous carriers Met/Met showed a 19% increased risk of schizophrenia with respect to the heterozygous state. Conclusions The study confirms the association of Val66Met to substance-related disorders, eating disorders, and schizophrenia. It remains to be determined if other variants in tight linkage disequilibrium with Val66Met could configure an extended functional haplotype that would explain observed discrepancies in risk estimations across studies.

Background It has been shown in a number of metagenomic studies that the addition and removal of specific genes have allowed microbiomes to adapt to specific environmental conditions by losing and gaining specific functions. But it is not known whether and how the regulation of gene expression also contributes to adaptation. Results We have here characterized and analyzed the metaregulome of three different environments, as well as their impact in the adaptation to particular variable physico-chemical conditions. For this, we have developed a computational protocol to extract regulatory regions and their corresponding transcription factors binding sites directly from metagenomic reads and applied it to three well known environments: Acid Mine, Whale Fall, and Waseca Farm. Taking the density of regulatory sites in promoters as a measure of the potential and complexity of gene regulation, we found it to be quantitatively the same in all three environments, despite their different physico-chemical conditions and species composition. However, we found that each environment distributes their regulatory potential differently across their functional space. Among the functions with highest regulatory potential in each niche, we found significant enrichment of processes related to sensing and buffering external variable factors specific to each environment, like for example, the availability of co-factors in deep sea, of oligosaccharides in soil and the regulation of pH in the acid mine. Conclusions These results highlight the potential impact of gene regulation in the adaptation of bacteria to the different habitats through the distribution of their regulatory potential among specific functions, and point to critical environmental factors that challenge the growth of any microbial community. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-877) contains supplementary material, which is available to authorized users.

Importance: Latino populations have one of the highest prevalences of type 2 diabetes worldwide. Objectives: To investigate the association between rare protein-coding genetic variants and prevalence of type 2 diabetes in a large Latino population and to explore potential molecular and physiological mechanisms for the observed relationships. Design, Setting, and Participants: Whole-exome sequencing was performed on DNA samples from 3756 Mexican and US Latino individuals (1794 with type 2 diabetes and 1962 without diabetes) recruited from 1993 to 2013. One variant was further tested for allele frequency and association with type 2 diabetes in large multiethnic data sets of 14 276 participants and characterized in experimental assays. Main Outcome and Measures: Prevalence of type 2 diabetes. Secondary outcomes included age of onset, body mass index, and effect on protein function. Results: A single rare missense variant (c.1522G>A [p.E508K]) was associated with type 2 diabetes prevalence (odds ratio [OR], 5.48; 95% CI, 2.83-10.61; P = 4.4 × 10−7) in hepatocyte nuclear factor 1-α (HNF1A), the gene responsible for maturity onset diabetes of the young type 3 (MODY3). This variant was observed in 0.36% of participants without type 2 diabetes and 2.1% of participants with it. In multiethnic replication data sets, the p.E508K variant was seen only in Latino patients (n = 1443 with type 2 diabetes and 1673 without it) and was associated with type 2 diabetes (OR, 4.16; 95% CI, 1.75-9.92; P = .0013). In experimental assays, HNF-1A protein encoding the p.E508K mutant demonstrated reduced transactivation activity of its target promoter compared with a wild-type protein. In our data, carriers and noncarriers of the p.E508K mutation with type 2 diabetes had no significant differences in compared clinical characteristics, including age at onset. The mean (SD) age for carriers was 45.3 years (11.2) vs 47.5 years (11.5) for noncarriers (P = .49) and the mean (SD) BMI for carriers was 28.2 (5.5) vs 29.3 (5.3) for noncarriers (P = .19). Conclusions and Relevance: Using whole-exome sequencing, we identified a single low-frequency variant in the MODY3-causing gene HNF1A that is associated with type 2 diabetes in Latino populations and may affect protein function. This finding may have implications for screening and therapeutic modification in this population, but additional studies are required. publishedVersion

OBJECTIVE This study sought to identify the profile of circulating microRNAs (miRNAs) in type 2 diabetes (T2D) and its response to changes in insulin sensitivity. RESEARCH DESIGN AND METHODS The circulating miRNA profile was assessed in a pilot study of 12 men: 6 with normal glucose tolerance (NGT) and 6 T2D patients. The association of 10 circulating miRNAs with T2D was cross-sectionally validated in an extended sample of 45 NGT vs. 48 T2D subjects (65 nonobese and 28 obese men) and longitudinally in 35 T2D patients who were recruited in a randomized, double-blinded, and placebo-controlled 3-month trial of metformin treatment. Circulating miRNAs were also measured in seven healthy volunteers before and after a 6-h hyperinsulinemic-euglycemic clamp and insulin plus intralipid/heparin infusion. RESULTS Cross-sectional studies disclosed a marked increase of miR-140-5p, miR-142-3p, and miR-222 and decreased miR-423-5p, miR-125b, miR-192, miR-195, miR-130b, miR-532-5p, and miR-126 in T2D patients. Multiple linear regression analyses revealed that miR-140-5p and miR-423-5p contributed independently to explain 49.5% (P < 0.0001) of fasting glucose variance after controlling for confounders. A discriminant function of four miRNAs (miR-140-5p, miR-423-5p, miR-195, and miR-126) was specific for T2D with an accuracy of 89.2% (P < 0.0001). Metformin (but not placebo) led to significant changes in circulating miR-192 (49.5%; P = 0.022), miR-140-5p (−15.8%; P = 0.004), and miR-222 (−47.2%; P = 0.03), in parallel to decreased fasting glucose and HbA1c. Furthermore, while insulin infusion during clamp decreased miR-222 (−62%; P = 0.002), the intralipid/heparin mixture increased circulating miR-222 (163%; P = 0.015) and miR-140-5p (67.5%; P = 0.05). CONCLUSIONS This study depicts the close association between variations in circulating miRNAs and T2D and their potential relevance in insulin sensitivity.

Asthma exacerbations are among the most frequent causes of hospitalization during childhood, but the underlying mechanisms are poorly understood. We performed a genome-wide association study of a specific asthma phenotype characterized by recurrent, severe exacerbations occurring between 2 and 6 years of age in a total of 1,173 cases and 2,522 controls. Cases were identified from national health registries of hospitalization, and DNA was obtained from the Danish Neonatal Screening Biobank. We identified five loci with genome-wide significant association. Four of these, GSDMB, IL33, RAD50 and IL1RL1, were previously reported as asthma susceptibility loci, but the effect sizes for these loci in our cohort were considerably larger than in the previous genome-wide association studies of asthma. We also obtained strong evidence for a new susceptibility gene, CDHR3 (encoding cadherin-related family member 3), which is highly expressed in airway epithelium. These results demonstrate the strength of applying specific phenotyping in the search for asthma susceptibility genes.

Context: Circulating microRNAs (miRNAs) are valuable biomarkers of metabolic diseases and potential therapeutic targets in this field. Objective: Our objective was to define the circulating pattern of miRNAs in childhood obesity. Design, Settings, and Main Outcome Measure: The genome-wide circulating miRNA profile was assessed by RT-PCR in 10 boys (5 lean and 5 obese children). The most relevant miRNAs were cross-sectionally validated in 85 lean versus 40 obese children (63 boys and 62 girls) and longitudinally evaluated in samples from the same children when they were ∼7 and ∼10 years old (23 boys and 22 girls). Results: The cross-sectional validation study disclosed that 15 specific circulating miRNAs were significantly deregulated in prepubertal obesity, including the decreased miR-221 and miR-28-3p and increased concentrations in plasma of miR-486-5p, miR-486-3p, miR-142-3p, miR-130b, and miR-423-5p (all P < .0001). The circulating concentration of these miRNAs was significantly associated with body mass index and other measures of obesity such as percent fat mass, waist, regional fat distribution and with laboratory parameters such as homeostasis model assessment of insulin resistance, high-molecular-weight adiponectin, C-reactive protein, and circulating lipids in concordance with anthropometric associations. Plasma concentrations of 10 of these circulating miRNAs changed significantly and differently during the 3-year follow-up in children who increased or decreased their normalized weight. Conclusion: This study provides the first evidence that circulating miRNAs are deregulated in prepubertal obese children. Thus, the very early detection of an abnormal circulating miRNA profile may be a promising strategy to identify obese children who may suffer from metabolic abnormalities.

Although protein recognition of DNA motifs in promoter regions has been traditionally considered as a critical regulatory element in transcription, the location of promoters, and in particular transcription start sites (TSSs), still remains a challenge. Here we perform a comprehensive analysis of putative core promoter sequences relative to non-annotated predicted TSSs along the human genome, which were defined by distinct DNA physical properties implemented in our ProStar computational algorithm. A representative sampling of predicted regions was subjected to extensive experimental validation and analyses. Interestingly, the vast majority proved to be transcriptionally active despite the lack of specific sequence motifs, indicating that physical signaling is indeed able to detect promoter activity beyond conventional TSS prediction methods. Furthermore, highly active regions displayed typical chromatin features associated to promoters of housekeeping genes. Our results enable to redefine the promoter signatures and analyze the diversity, evolutionary conservation and dynamic regulation of human core promoters at large-scale. Moreover, the present study strongly supports the hypothesis of an ancient regulatory mechanism encoded by the intrinsic physical properties of the DNA that may contribute to the complexity of transcription regulation in the human genome. This work was supported by the Spanish Ministry of Science and Innovation [BIO2012-32868 and Consolider E-Science Project]; Instituto de Salud Carlos III (Instituto Nacional de Bioinformática);/nEuropean Research Council (ERC) Advanced Grant; Fundación Marcelino Botín. M.O. is an Institució Catalana de Recerca i Estudis Avançats (ICREA) Academia Researcher. Funding for open access charge: Fundación Marcelino Botín