24 research outputs found
Prediction of waves, wakes and offshore wind - the results of the POW'WOW project
International audienceThe POWWOW project (Prediction of Waves, Wakes and Offshore Wind, a EU Coordination Action) aimed to develop synergy in the fields of wind and wave predictions from short to resource timescales by integrating modelling approaches currently used by the communities separately. The project aimed to help these research communities by establishing virtual laboratories, offering specialised workshops, and setting up expert groups with large outreach in the mentioned fields. In this paper, the main results of POWWOW are summarised
Pancreatic steatosis and iron overload increases cardiovascular risk in non-alcoholic fatty liver disease
ObjectiveTo assess the prevalence of pancreatic steatosis and iron overload in non-alcoholic fatty liver disease (NAFLD) and their correlation with liver histology severity and the risk of cardiometabolic diseases.MethodA prospective, multicenter study including NAFLD patients with biopsy and paired Magnetic Resonance Imaging (MRI) was performed. Liver biopsies were evaluated according to NASH Clinical Research Network, hepatic iron storages were scored, and digital pathology quantified the tissue proportionate areas of fat and iron. MRI-biomarkers of fat fraction (PDFF) and iron accumulation (R2*) were obtained from the liver and pancreas. Different metabolic traits were evaluated, cardiovascular disease (CVD) risk was estimated with the atherosclerotic CVD score, and the severity of iron metabolism alteration was determined by grading metabolic hiperferritinemia (MHF). Associations between CVD, histology and MRI were investigated.ResultsIn total, 324 patients were included. MRI-determined pancreatic iron overload and moderate-to severe steatosis were present in 45% and 25%, respectively. Liver and pancreatic MRI-biomarkers showed a weak correlation (r=0.32 for PDFF, r=0.17 for R2*). Pancreatic PDFF increased with hepatic histologic steatosis grades and NASH diagnosis (p<0.001). Prevalence of pancreatic steatosis and iron overload increased with the number of metabolic traits (p<0.001). Liver R2* significantly correlated with MHF (AUC=0.77 [0.72-0.82]). MRI-determined pancreatic steatosis (OR=3.15 [1.63-6.09]), and iron overload (OR=2.39 [1.32-4.37]) were independently associated with high-risk CVD. Histologic diagnosis of NASH and advanced fibrosis were also associated with high-risk CVD.ConclusionPancreatic steatosis and iron overload could be of utility in clinical decision-making and prognostication of NAFLD
Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information
Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/
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)
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets
Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD.
Objective To investigate what genes and genomic processes underlie the risk of sporadic PD.
Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks.
Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role.
Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance.
Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies
Mitochondrial RNA methyltransferase TRMT61B is a new, potential biomarker and therapeutic target for highly aneuploid cancers
La versión final de este artículo está disponible en: https://doi.org/10.1038/s41418-022-01044-6 (Martín, A., Epifano, C., Vilaplana-Marti, B. et al. Mitochondrial RNA methyltransferase TRMT61B is a new, potential biomarker and therapeutic target for highly aneuploid cancers. Cell Death Differ 30, 37–53 (2023))Chromosomal instability (CIN) is an important source of genetic and phenotypic variation that has been extensively reported as a critical cancer related property that improves tumor cell adaptation and survival. CIN and its immediate consequence, aneuploidy, provoke adverse effects on cellular homeostasis that need to be overcome by developing efficient anti-stress mechanisms. Perturbations in these safeguard responses might be detrimental for cancer cells and represent an important tumor specific Achilles heel since CIN and aneuploidy are very rare events in normal cells. On the other hand, epitranscriptomic marks catalyzed by different RNA modifying enzymes have been found to change under several stress insults. Although CIN and aneuploidy are important intracellular stressors, their biological connection with RNA modifications is pending to be determined. In an in silico search for new cancer biomarkers, we have identified TRMT61B, a mitochondrial RNA methyltransferase enzyme, to be associated with high levels of aneuploidy. In the present work, we study the connection of this molecule with cancer and aneuploidy. First, we show increased protein amounts of TRMT61B in tumor cell lines with imbalanced karyotype as well as in different tumor types compared to unaffected control tissues. In addition, we demonstrate that depletion of TRMT61B in melanoma cells reduces cell proliferation either by fostering apoptosis and inhibiting autophagy in high-aneuploid (ANEhigh) cells or by inducing senescence in the case of low-aneuploid (ANElow) cell lines. Further, TRMT61B elimination compromises mitochondrial function and reduces the expression of several mitochondrial encoded proteins that are part of the electron transport chain. Finally, transwell and xenograft experiments revealed a reduced invasive and tumorigenic capacity upon TRMT61B depletion that strengthen the therapeutic value of this aneuploidy-associated biomarker. These results, which connect tumorigenesis, aneuploidy and mitochondrial RNA methylation, bring to the cancer field a new putative strategy to specifically target high aneuploid tumors.AM was a recipient of a postdoctoral fellowship from the Fundación Española Contra el Cáncer (AECC). This study was supported by grants from the Spanish Ministry of Science and Innovation (to IPC, SAF2016-76929-R) and from the Acción Estratégica de Salud Intramural (to A.M., PI17CIII/00010)N
The Genetic Architecture of Parkinson Disease in Spain: Characterizing Population‐Specific Risk, Differential Haplotype Structures, and Providing Etiologic Insight
The Iberian Peninsula stands out as having variable levels of population admixture and isolation, making Spain an interesting setting for studying the genetic architecture of neurodegenerative diseases. To perform the largest PD genome-wide association study restricted to a single country. We performed a GWAS for both risk of PD and age at onset in 7,849 Spanish individuals. Further analyses included population-specific risk haplotype assessments, polygenic risk scoring through machine learning, Mendelian randomization of expression, and methylation data to gain insight into disease-associated loci, heritability estimates, genetic correlations, and burden analyses. We identified a novel population-specific genome-wide association study signal at PARK2 associated with age at onset, which was likely dependent on the c.155delA mutation. We replicated four genome-wide independent signals associated with PD risk, including SNCA, LRRK2, KANSL1/MAPT, and HLA-DQB1. A significant trend for smaller risk haplotypes at known loci was found compared to similar studies of non-Spanish origin. Seventeen PD-related genes showed functional consequence by two-sample Mendelian randomization in expression and methylation data sets. Long runs of homozygosity at 28 known genes/loci were found to be enriched in cases versus controls. Our data demonstrate the utility of the Spanish risk haplotype substructure for future fine-mapping efforts, showing how leveraging unique and diverse population histories can benefit genetic studies of complex diseases. The present study points to PARK2 as a major hallmark of PD etiology in Spain. © 2019 International Parkinson and Movement Disorder Society