Metformin intervention prevents cardiac dysfunction in a murine model of adult congenital heart disease.

OBJECTIVE: Congenital heart disease (CHD) is the most frequent birth defect worldwide. The number of adult patients with CHD, now referred to as ACHD, is increasing with improved surgical and treatment interventions. However the mechanisms whereby ACHD predisposes patients to heart dysfunction are still unclear. ACHD is strongly associated with metabolic syndrome, but how ACHD interacts with poor modern lifestyle choices and other comorbidities, such as hypertension, obesity, and diabetes, is mostly unknown. METHODS: We used a newly characterized mouse genetic model of ACHD to investigate the consequences and the mechanisms associated with combined obesity and ACHD predisposition. Metformin intervention was used to further evaluate potential therapeutic amelioration of cardiac dysfunction in this model. RESULTS: ACHD mice placed under metabolic stress (high fat diet) displayed decreased left ventricular ejection fraction. Comprehensive physiological, biochemical, and molecular analysis showed that ACHD hearts exhibited early changes in energy metabolism with increased glucose dependence as main cardiac energy source. These changes preceded cardiac dysfunction mediated by exposure to high fat diet and were associated with increased disease severity. Restoration of metabolic balance by metformin administration prevented the development of heart dysfunction in ACHD predisposed mice. CONCLUSIONS: This study reveals that early metabolic impairment reinforces heart dysfunction in ACHD predisposed individuals and diet or pharmacological interventions can be used to modulate heart function and attenuate heart failure. Our study suggests that interactions between genetic and metabolic disturbances ultimately lead to the clinical presentation of heart failure in patients with ACHD. Early manipulation of energy metabolism may be an important avenue for intervention in ACHD patients to prevent or delay onset of heart failure and secondary comorbidities. These interactions raise the prospect for a translational reassessment of ACHD presentation in the clinic

The politics of vibrant matter: consistency, containment and the concrete of Mussolini’s bunker

This article explores the idea of how vibrancy can be produced. Specifically, the attempt is to investigate the multiplicities of vibrancy by considering one of Mussolini’s bunkers. The author examines the location of the bunker in the EUR (Esposizione Universale Romana) neighbourhood in Rome, the bunker’s materiality, and the context and social meaning of the bunker through a contemporary art exhibition called ‘Confronti’ (Confrontations) that took place in the bunker in 2009. The article argues that while emphasizing matter’s inherent vibrancy may be useful in some cases, there is also merit in further unpacking the ways in which vibrancy is produced. In this example, the concrete bunker expresses vibrancy through the processes involved in the emergent material form, and in the sustained politics and social considerations embedded in valuing tangible urban heritage

Identification of unannotated exons of low abundance transcripts in Drosophila melanogaster and cloning of a new serine protease gene upregulated upon injury

<p>Abstract</p> <p>Background</p> <p>The sequencing of the <it>D.melanogaster </it>genome revealed an unexpected small number of genes (~ 14,000) indicating that mechanisms acting on generation of transcript diversity must have played a major role in the evolution of complex metazoans. Among the most extensively used mechanisms that accounts for this diversity is alternative splicing. It is estimated that over 40% of <it>Drosophila </it>protein-coding genes contain one or more alternative exons. A recent transcription map of the <it>Drosophila </it>embryogenesis indicates that 30% of the transcribed regions are unannotated, and that 1/3 of this is estimated as missed or alternative exons of previously characterized protein-coding genes. Therefore, the identification of the variety of expressed transcripts depends on experimental data for its final validation and is continuously being performed using different approaches. We applied the Open Reading Frame Expressed Sequence Tags (ORESTES) methodology, which is capable of generating cDNA data from the central portion of rare transcripts, in order to investigate the presence of hitherto unnanotated regions of <it>Drosophila </it>transcriptome.</p> <p>Results</p> <p>Bioinformatic analysis of 1,303 <it>Drosophila </it>ORESTES clusters identified 68 sequences derived from unannotated regions in the current <it>Drosophila </it>genome version (4.3). Of these, a set of 38 was analysed by polyA⁺northern blot hybridization, validating 17 (50%) new exons of low abundance transcripts. For one of these ESTs, we obtained the cDNA encompassing the complete coding sequence of a new serine protease, named SP212. The <it>SP212 </it>gene is part of a serine protease gene cluster located in the chromosome region 88A12-B1. This cluster includes the predicted genes CG9631, CG9649 and CG31326, which were previously identified as up-regulated after immune challenges in genomic-scale microarray analysis. In agreement with the proposal that this <it>locus </it>is co-regulated in response to microorganisms infection, we show here that SP212 is also up-regulated upon injury.</p> <p>Conclusion</p> <p>Using the ORESTES methodology we identified 17 novel exons from low abundance <it>Drosophila </it>transcripts, and through a PCR approach the complete CDS of one of these transcripts was defined. Our results show that the computational identification and manual inspection are not sufficient to annotate a genome in the absence of experimentally derived data.</p

The Plant Pathogen Pseudomonas syringae pv. tomato Is Genetically Monomorphic and under Strong Selection to Evade Tomato Immunity

Recently, genome sequencing of many isolates of genetically monomorphic bacterial human pathogens has given new insights into pathogen microevolution and phylogeography. Here, we report a genome-based micro-evolutionary study of a bacterial plant pathogen, Pseudomonas syringae pv. tomato. Only 267 mutations were identified between five sequenced isolates in 3,543,009 nt of analyzed genome sequence, which suggests a recent evolutionary origin of this pathogen. Further analysis with genome-derived markers of 89 world-wide isolates showed that several genotypes exist in North America and in Europe indicating frequent pathogen movement between these world regions. Genome-derived markers and molecular analyses of key pathogen loci important for virulence and motility both suggest ongoing adaptation to the tomato host. A mutational hotspot was found in the type III-secreted effector gene hopM1. These mutations abolish the cell death triggering activity of the full-length protein indicating strong selection for loss of function of this effector, which was previously considered a virulence factor. Two non-synonymous mutations in the flagellin-encoding gene fliC allowed identifying a new microbe associated molecular pattern (MAMP) in a region distinct from the known MAMP flg22. Interestingly, the ancestral allele of this MAMP induces a stronger tomato immune response than the derived alleles. The ancestral allele has largely disappeared from today's Pto populations suggesting that flagellin-triggered immunity limits pathogen fitness even in highly virulent pathogens. An additional non-synonymous mutation was identified in flg22 in South American isolates. Therefore, MAMPs are more variable than expected differing even between otherwise almost identical isolates of the same pathogen strain

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

Common Genetic Variation And Age at Onset Of Anorexia Nervosa

Background Genetics and biology may influence the age at onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to AN age at onset and to investigate the genetic associations between age at onset of AN and age at menarche. Methods A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed which included 9,335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age at onset, early-onset AN (< 13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (SNP-h2) were 0.01-0.04 for age at onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age at onset and early-onset AN estimated from independent GWASs significantly predicted age at onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions Our results provide evidence consistent with a common variant genetic basis for age at onset and implicate biological pathways regulating menarche and reproduction.Peer reviewe

Shared genetic risk between eating disorder- and substance-use-related phenotypes:Evidence from genome-wide association studies

First published: 16 February 202

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe