ABSTRACT
Muscle functional MRI identifies changes in metabolic activity in each muscle and provides a quantitative index of muscle activation and damage. No previous studies have analyzed the hamstrings activation over a football match. This study aimed at detecting different patterns of hamstring muscles activation after a football game, and to examine inter- and intramuscular differences (proximal-middle-distal) in hamstring muscles activation using transverse relaxation time (T2)-weighted magnetic resonance images. Eleven healthy football players were recruited for this study. T2 relaxation time mapping-MRI was performed before (2 hours) and immediately after a match (on average 13 min). The T2 values of each hamstring muscle at the distal, middle, and proximal portions were measured. The primary outcome measure was the increase in T2 relaxation time value after a match. Linear mixed models were used to detect differences pre and postmatch. MRI examination showed that there was no obvious abnormality in the shape and the conventional T2 weighted signal of the hamstring muscles after a match. On the other hand, muscle functional MRI T2 analysis revealed that T2 relaxation time significantly increased at distal and middle portions of the semitendinosus muscle (p = 0.0003 in both cases). By employing T2 relaxation time mapping, we have identified alterations within the hamstring muscles being the semitendinosus as the most engaged muscle, particularly within its middle and distal thirds. This investigation underscores the utility of T2 relaxation time mapping in evaluating muscle activation patterns during football matches, facilitating the detection of anomalous activation patterns that may warrant injury reduction interventions.
Subject(s)
Hamstring Muscles , Magnetic Resonance Imaging , Soccer , Humans , Magnetic Resonance Imaging/methods , Hamstring Muscles/physiology , Hamstring Muscles/diagnostic imaging , Male , Adult , Soccer/physiology , Young Adult , Football/injuries , Muscle, Skeletal/diagnostic imaging , Muscle, Skeletal/physiologyABSTRACT
INTRODUCTION: Phthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes. OBJECTIVE: In this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS). METHODS: The study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8 years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value < 1E-05) was done with the FUMA web-tool. RESULTS: We identified four genome-wide significant (p-value < 5E-08) loci at chromosome (chr) 3 (FECHP1 for oxo-MiNP_oh-MiNP ratio), chr6 (SLC17A1 for MECPP_MEHHP ratio), chr9 (RAPGEF1 for MBzP), and chr10 (CYP2C9 for MECPP_MEHHP ratio). Moreover, 115 additional loci were found at suggestive significance (p-value < 1E-05). Two CNVs located at chr11 (MRGPRX1 for oh-MiNP and SLC35F2 for MEP) were also identified. Functional annotation pointed to genes involved in phase I and phase II detoxification, molecular transfer across membranes, and renal excretion. CONCLUSION: Through genome-wide screenings we identified known and novel loci implicated in phthalate metabolism in children. Genes annotated to these loci participate in detoxification, transmembrane transfer, and renal excretion.
Subject(s)
DNA Copy Number Variations , Genome-Wide Association Study , Phthalic Acids , Polymorphism, Single Nucleotide , Humans , Phthalic Acids/urine , Child , DNA Copy Number Variations/genetics , Male , Female , Environmental Exposure , Environmental Pollutants/urineABSTRACT
PURPOSE: Injury prevention is a crucial aspect of sports, particularly in high-performance settings such as elite female football. This study aimed to develop an injury prediction model that incorporates clinical, Global-Positioning-System (GPS), and multiomics (genomics and metabolomics) data to better understand the factors associated with injury in elite female football players. METHODS: We designed a prospective cohort study over 2 seasons (2019-20 and 2021-22) of noncontact injuries in 24 elite female players in the Spanish Premiership competition. We used GPS data to determine external workload, genomic data to capture genetic susceptibility, and metabolomic data to measure internal workload. RESULTS: Forty noncontact injuries were recorded, the most frequent of which were muscle (63%) and ligament (20%) injuries. The baseline risk model included fat mass and the random effect of the player. Six genetic polymorphisms located at the DCN, ADAMTS5, ESRRB, VEGFA, and MMP1 genes were associated with injuries after adjusting for player load (P < .05). The genetic score created with these 6 variants determined groups of players with different profile risks (P = 3.1 × 10-4). Three metabolites (alanine, serotonin, and 5-hydroxy-tryptophan) correlated with injuries. The model comprising baseline variables, genetic score, and player load showed the best prediction capacity (C-index: .74). CONCLUSIONS: Our model could allow efficient, personalized interventions based on an athlete's vulnerability. However, we emphasize the necessity for further research in female athletes with an emphasis on validation studies involving other teams and individuals. By expanding the scope of our research and incorporating diverse populations, we can bolster the generalizability and robustness of our proposed model.
Subject(s)
Athletic Injuries , Metabolomics , Soccer , Humans , Female , Prospective Studies , Soccer/injuries , Soccer/physiology , Athletic Injuries/genetics , Young Adult , Genomics , Genetic Predisposition to Disease , Risk Factors , Spain , Polymorphism, Genetic , MultiomicsABSTRACT
Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.
Subject(s)
DNA Methylation , Environmental Exposure , Humans , Female , Pregnancy , Infant, Newborn , Cohort Studies , Male , Fetal Blood/chemistry , Child , Birth CohortABSTRACT
The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people.
Subject(s)
COVID-19 , SARS-CoV-2 , Male , Humans , Aged , SARS-CoV-2/genetics , Mosaicism , COVID-19/genetics , Chromosomes, Human, Y , AgingABSTRACT
Epimutations are rare alterations of the normal DNA methylation pattern at specific loci, which can lead to rare diseases. Methylation microarrays enable genome-wide epimutation detection, but technical limitations prevent their use in clinical settings: methods applied to rare diseases' data cannot be easily incorporated to standard analyses pipelines, while epimutation methods implemented in R packages (ramr) have not been validated for rare diseases. We have developed epimutacions, a Bioconductor package (https://bioconductor.org/packages/release/bioc/html/epimutacions.html). epimutacions implements two previously reported methods and four new statistical approaches to detect epimutations, along with functions to annotate and visualize epimutations. Additionally, we have developed an user-friendly Shiny app to facilitate epimutations detection (https://github.com/isglobal-brge/epimutacionsShiny) to non-bioinformatician users. We first compared the performance of epimutacions and ramr packages using three public datasets with experimentally validated epimutations. Methods in epimutacions had a high performance at low sample sizes and outperformed methods in ramr. Second, we used two general population children cohorts (INMA and HELIX) to determine the technical and biological factors that affect epimutations detection, providing guidelines on how designing the experiments or preprocessing the data. In these cohorts, most epimutations did not correlate with detectable regional gene expression changes. Finally, we exemplified how epimutacions can be used in a clinical context. We run epimutacions in a cohort of children with autism disorder and identified novel recurrent epimutations in candidate genes for autism. Overall, we present epimutacions a new Bioconductor package for incorporating epimutations detection to rare disease diagnosis and provide guidelines for the design and data analyses.
Subject(s)
DNA Methylation , Software , Child , Humans , Rare Diseases , GenomeABSTRACT
Tobacco, alcohol, and marijuana consumption is an important public health problem because of their high use worldwide and their association with the risk of mortality and many health conditions, such as hypertension, which is the commonest risk factor for death throughout the world. A likely pathway of action of substance consumption leading to persistent hypertension is DNA methylation. Here, we evaluated the effects of tobacco, alcohol, and marijuana on DNA methylation in the same cohort (N = 3,424). Three epigenome-wide association studies (EWAS) were assessed in whole blood using the InfiniumHumanMethylationEPIC BeadChip. We also evaluated the mediation of the top CpG sites in the association between substance consumption and hypertension. Our analyses showed 2,569 CpG sites differentially methylated by alcohol drinking and 528 by tobacco smoking. We did not find significant associations with marijuana consumption after correcting for multiple comparisons. We found 61 genes overlapping between alcohol and tobacco that were enriched in biological processes involved in the nervous and cardiovascular systems. In the mediation analysis, we found 66 CpG sites that significantly mediated the effect of alcohol consumption on hypertension. The top alcohol-related CpG site (cg06690548, P-value = 5.9·10-83) mapped to SLC7A11 strongly mediated 70.5% of the effect of alcohol consumption on hypertension (P-value = 0.006). Our findings suggest that DNA methylation should be considered for new targets in hypertension prevention and management, particularly concerning alcohol consumption. Our data also encourage further research into the use of methylation in blood to study the neurological and cardiovascular effects of substance consumption.
The consumption of tobacco, alcohol, and marijuana is very high worldwide and is associated with common diseases, like cardiovascular and neurological disorders.This study found that tobacco and alcohol have large effects on genome wide DNA methylation while marijuana consumption has nonsignificant effects.The genes differentially methylated were enriched in pathways related to neurodevelopment, suggesting the mediation between recreational drug consumption and neurological disorders.More remarkably, 66 alcohol related CpG sites significantly mediated the association between heavy drinking and hypertension.Our findings suggest that DNA methylation changes should be considered for new targets in disease prevention for recreational drug consumers.
Subject(s)
Cannabis , Hypertension , Humans , DNA Methylation , Cannabis/genetics , Epigenesis, Genetic , Genome-Wide Association Study , Hypertension/genetics , DNA , Ethanol , CpG IslandsABSTRACT
BACKGROUND: Obesity and neurodevelopmental delay are complex traits that often co-occur and differ between boys and girls. Prenatal exposures are believed to influence children's obesity, but it is unknown whether exposures of pregnant mothers can confer a different risk of obesity between sexes, and whether they can affect neurodevelopment. METHODS: We analyzed data from 1044 children from the HELIX project, comprising 93 exposures during pregnancy, and clinical, neuropsychological, and methylation data during childhood (5-11 years). Using exposome-wide interaction analyses, we identified prenatal exposures with the highest sexual dimorphism in obesity risk, which were used to create a multiexposure profile. We applied causal random forest to classify individuals into two environments: E1 and E0. E1 consists of a combination of exposure levels where girls have significantly less risk of obesity than boys, as compared to E0, which consists of the remaining combination of exposure levels. We investigated whether the association between sex and neurodevelopmental delay also differed between E0 and E1. We used methylation data to perform an epigenome-wide association study between the environments to see the effect of belonging to E1 or E0 at the molecular level. RESULTS: We observed that E1 was defined by the combination of low dairy consumption, non-smokers' cotinine levels in blood, low facility richness, and the presence of green spaces during pregnancy (ORinteraction = 0.070, P = 2.59 × 10-5). E1 was also associated with a lower risk of neurodevelopmental delay in girls, based on neuropsychological tests of non-verbal intelligence (ORinteraction = 0.42, P = 0.047) and working memory (ORinteraction = 0.31, P = 0.02). In line with this, several neurodevelopmental functions were enriched in significant differentially methylated probes between E1 and E0. CONCLUSIONS: The risk of obesity can be different for boys and girls in certain prenatal environments. We identified an environment combining four exposure levels that protect girls from obesity and neurodevelopment delay. The combination of single exposures into multiexposure profiles using causal inference can help determine populations at risk.
Subject(s)
Pediatric Obesity , Prenatal Exposure Delayed Effects , Pregnancy , Child , Humans , Male , Female , Sex Characteristics , Prenatal Exposure Delayed Effects/epidemiology , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Child DevelopmentABSTRACT
The survival of malaria parasites in the changing human blood environment largely depends on their ability to alter gene expression by epigenetic mechanisms. The active state of Plasmodium falciparum clonally variant genes (CVGs) is associated with euchromatin characterized by the histone mark H3K9ac, whereas the silenced state is characterized by H3K9me3-based heterochromatin. Expression switches are linked to euchromatin-heterochromatin transitions, but these transitions have not been characterized for the majority of CVGs. To define the heterochromatin distribution patterns associated with the alternative transcriptional states of CVGs, we compared H3K9me3 occupancy at a genome-wide level among several parasite subclones of the same genetic background that differed in the transcriptional state of many CVGs. We found that de novo heterochromatin formation or the complete disruption of a heterochromatin domain is a relatively rare event, and for the majority of CVGs, expression switches can be explained by the expansion or retraction of heterochromatin domains. We identified different modalities of heterochromatin changes linked to transcriptional differences, but despite this complexity, heterochromatin distribution patterns generally enable the prediction of the transcriptional state of specific CVGs. We also found that in some subclones, several var genes were simultaneously in an active state. Furthermore, the heterochromatin levels in the putative regulatory region of the gdv1 antisense noncoding RNA, a regulator of sexual commitment, varied between parasite lines with different sexual conversion rates. IMPORTANCE The malaria parasite P. falciparum is responsible for more than half a million deaths every year. P. falciparum clonally variant genes (CVGs) mediate fundamental host-parasite interactions and play a key role in parasite adaptation to fluctuations in the conditions of the human host. The expression of CVGs is regulated at the epigenetic level by changes in the distribution of a type of chromatin called heterochromatin. Here, we describe at a genome-wide level the changes in the heterochromatin distribution associated with the different transcriptional states of CVGs. Our results also reveal a likely role for heterochromatin at a particular locus in determining the parasite investment in transmission to mosquitoes. Additionally, this data set will enable the prediction of the transcriptional state of CVGs from epigenomic data, which is important for the study of parasite adaptation to the conditions of the host in natural malaria infections.
Subject(s)
Malaria, Falciparum , Plasmodium falciparum , Animals , Humans , Plasmodium falciparum/genetics , Plasmodium falciparum/metabolism , Heterochromatin/genetics , Heterochromatin/metabolism , Euchromatin/metabolism , Protozoan Proteins/genetics , Protozoan Proteins/metabolism , Malaria, Falciparum/parasitology , Gene Expression RegulationABSTRACT
Environmental exposures during early life play a critical role in life-course health, yet the molecular phenotypes underlying environmental effects on health are poorly understood. In the Human Early Life Exposome (HELIX) project, a multi-centre cohort of 1301 mother-child pairs, we associate individual exposomes consisting of >100 chemical, outdoor, social and lifestyle exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome, transcriptome, proteins and metabolites) in childhood. We identify 1170 associations, 249 in pregnancy and 921 in childhood, which reveal potential biological responses and sources of exposure. Pregnancy exposures, including maternal smoking, cadmium and molybdenum, are predominantly associated with child DNA methylation changes. In contrast, childhood exposures are associated with features across all omics layers, most frequently the serum metabolome, revealing signatures for diet, toxic chemical compounds, essential trace elements, and weather conditions, among others. Our comprehensive and unique resource of all associations ( https://helixomics.isglobal.org/ ) will serve to guide future investigation into the biological imprints of the early life exposome.
Subject(s)
Exposome , Pregnancy , Female , Humans , Environmental Exposure/adverse effects , Cohort Studies , Metabolome , TranscriptomeABSTRACT
The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P > 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother-child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field.
Subject(s)
Exposome , Humans , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Bayes Theorem , Environmental Health , MetabolomicsABSTRACT
Latent liver stages termed hypnozoites cause relapsing Plasmodium vivax malaria infection and represent a major obstacle in the goal of malaria elimination. Hypnozoites are clinically undetectable, and presently, there are no biomarkers of this persistent parasite reservoir in the human liver. Here, we have identified parasite and human proteins associated with extracellular vesicles (EVs) secreted from in vivo infections exclusively containing hypnozoites. We used P. vivax-infected human liver-chimeric (huHEP) FRG KO mice treated with the schizonticidal experimental drug MMV048 as hypnozoite infection model. Immunofluorescence-based quantification of P. vivax liver forms showed that MMV048 removed schizonts from chimeric mice livers. Proteomic analysis of EVs derived from FRG huHEP mice showed that human EV cargo from infected FRG huHEP mice contain inflammation markers associated with active schizont replication and identified 66 P. vivax proteins. To identify hypnozoite-specific proteins associated with EVs, we mined the proteome data from MMV048-treated mice and performed an analysis involving intragroup and intergroup comparisons across all experimental conditions followed by a peptide compatibility analysis with predicted spectra to warrant robust identification. Only one protein fulfilled this stringent top-down selection, a putative filamin domain-containing protein. This study sets the stage to unveil biological features of human liver infections and identify biomarkers of hypnozoite infection associated with EVs.
Subject(s)
Extracellular Vesicles , Malaria, Vivax , Parasites , Humans , Mice , Animals , Malaria, Vivax/drug therapy , Malaria, Vivax/parasitology , Plasmodium vivax , Proteomics , Proteome , Filamins , Liver , Biomarkers , Mass SpectrometryABSTRACT
Time-kill curves are used to study antibiotic combinations, but the colony count method to obtain the results is time-consuming. The aim of the study was to validate an ATP assay as an alternative to the conventional colony count method in studies of antibiotic combinations. The cutoff point for synergy and bactericidal effect to categorize the results using this alternative method were determined in Pseudomonas aeruginosa. The ATP assay was performed using the GloMax 96 microplate luminometer (Promega), which measures bioluminescence in relative light units (RLU). To standardize this assay, background, linearity, and the detection limit were determined with one strain each of multidrug-resistant P. aeruginosa and Klebsiella pneumoniae. Twenty-four-hour time-kill curves were performed in parallel by both methods with 12 strains of P. aeruginosa. The conventional method was used as a "gold" standard to establish the pharmacodynamic cutoff points in the ATP method. Normal saline solution was established as washing/dilution medium. RLU signal correlated with CFU when the assay was performed within the linear range. The categorization of the pharmacodynamic parameters using the ATP assay was equivalent to that of the colony count method. The bactericidal effect and synergy cutoff points were 1.348 (93% sensitivity, 81% specificity) and 1.065 (95% sensitivity, 89% specificity) log RLU/mL, respectively. The ATP assay was useful to determine the effectiveness of antibiotic combinations in time-kill curves. This method, less laborious and faster than the colony count method, could be implemented in the clinical laboratory workflow. IMPORTANCE Combining antibiotics is one of the few strategies available to overcome infections caused by multidrug-resistant bacteria. Time-kill curves are usually performed to evaluate antibiotic combinations, but obtaining results is too laborious to be routinely performed in a clinical laboratory. Our results support the utility of an ATP measurement assay using bioluminescence to determine the effectiveness of antibiotic combinations in time-kill curves. This method may be implemented in the clinical laboratory workflow as it is less laborious and faster than the conventional colony count method. Shortening the obtention of results to 24 h would also allow an earlier guided combined antibiotic treatment.
Subject(s)
Pseudomonas Infections , Pseudomonas aeruginosa , Adenosine Triphosphate , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Drug Resistance, Multiple, Bacterial , Humans , Microbial Sensitivity Tests , Pseudomonas Infections/drug therapy , Pseudomonas Infections/microbiologyABSTRACT
BACKGROUND: Among children, sex-specific differences in disease prevalence, age of onset, and susceptibility have been observed in health conditions including asthma, immune response, metabolic health, some pediatric and adult cancers, and psychiatric disorders. Epigenetic modifications such as DNA methylation may play a role in the sexual differences observed in diseases and other physiological traits. METHODS: We performed a meta-analysis of the association of sex and cord blood DNA methylation at over 450,000 CpG sites in 8438 newborns from 17 cohorts participating in the Pregnancy And Childhood Epigenetics (PACE) Consortium. We also examined associations of child sex with DNA methylation in older children ages 5.5-10 years from 8 cohorts (n = 4268). RESULTS: In newborn blood, sex was associated at Bonferroni level significance with differences in DNA methylation at 46,979 autosomal CpG sites (p < 1.3 × 10-7) after adjusting for white blood cell proportions and batch. Most of those sites had lower methylation levels in males than in females. Of the differentially methylated CpG sites identified in newborn blood, 68% (31,727) met look-up level significance (p < 1.1 × 10-6) in older children and had methylation differences in the same direction. CONCLUSIONS: This is a large-scale meta-analysis examining sex differences in DNA methylation in newborns and older children. Expanding upon previous studies, we replicated previous findings and identified additional autosomal sites with sex-specific differences in DNA methylation. Differentially methylated sites were enriched in genes involved in cancer, psychiatric disorders, and cardiovascular phenotypes.
Subject(s)
DNA Methylation , Epigenome , Adolescent , Child , DNA Methylation/genetics , Epigenesis, Genetic , Epigenomics , Female , Humans , Infant, Newborn , Male , Pregnancy , Sex CharacteristicsABSTRACT
Polymorphic genomic inversions are chromosomal variants with intrinsic variability that play important roles in evolution, environmental adaptation, and complex traits. We investigated the DNA methylation patterns of three common human inversions, at 8p23.1, 16p11.2, and 17q21.31 in 1,009 blood samples from children from the Human Early Life Exposome (HELIX) project and in 39 prenatal heart tissue samples. We found inversion-state specific methylation patterns within and nearby flanking each inversion region in both datasets. Additionally, numerous inversion-exposure interactions on methylation levels were identified from early-life exposome data comprising 64 exposures. For instance, children homozygous at inv-8p23.1 and higher meat intake were more susceptible to TDH hypermethylation (P = 3.8 × 10-22); being the inversion, exposure, and gene known risk factors for adult obesity. Inv-8p23.1 associated hypermethylation of GATA4 was also detected across numerous exposures. Our data suggests that the pleiotropic influence of inversions during development and lifetime could be substantially mediated by allele-specific methylation patterns which can be modulated by the exposome.
Subject(s)
DNA Methylation , Exposome , Adult , Alleles , Child , Chromosome Inversion , Fetus , Humans , Obesity/geneticsABSTRACT
Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%).
Subject(s)
Genomics , Rare Diseases , Computational Biology , Exome , Humans , Rare Diseases/diagnosis , Rare Diseases/genetics , Exome SequencingABSTRACT
MOTIVATION: Causal inference on high-dimensional feature data can be used to find a profile of patients who will benefit the most from treatment rather than no treatment. However, there is a need for usable implementations for transcriptomic data. We developed teff that applies random causal forest on gene expression data to target individuals with high expected treatment effects. RESULTS: We extracted a profile of high benefit of treating psoriasis with brodalumab and observed that it was associated with higher T cell abundance in non-lesional skin at baseline and a lower response for etanercept in an independent study. Individual patient targeting with causal inference profiling can inform patients on choosing between treatments before the intervention begins. AVAILABILITY AND IMPLEMENTATION: teff is an R package available at https://teff-package.github.io. The data underlying this article are available in GEO, at https://www.ncbi.nlm.nih.gov/geo/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Eragrostis , Transcriptome , HumansABSTRACT
Background: The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children's blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods: Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results: We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at <250 kb from eGene's TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. In 40.4% of the eQTMs, the CpG and the eGene were both associated with at least one genetic variant. The overlap of autosomal cis eQTMs in children's blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants. Conclusions: This catalogue of autosomal cis eQTMs in children's blood can help the biological interpretation of EWAS findings and is publicly available at https://helixomics.isglobal.org/ and at Dryad (doi:10.5061/dryad.fxpnvx0t0). Funding: The study has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project); the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project); from the European Union's Horizon 2020 research and innovation programme under grant agreement no 733206 (LIFECYCLE project), and from the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL and Instituto de Salud Carlos III) under the grant agreement no AC18/00006 (NutriPROGRAM project). The genotyping was supported by the projects PI17/01225 and PI17/01935, funded by the Instituto de Salud Carlos III and co-funded by European Union (ERDF, "A way to make Europe") and the Centro Nacional de Genotipado-CEGEN (PRB2-ISCIII). BiB received core infrastructure funding from the Wellcome Trust (WT101597MA) and a joint grant from the UK Medical Research Council (MRC) and Economic and Social Science Research Council (ESRC) (MR/N024397/1). INMA data collections were supported by grants from the Instituto de Salud Carlos III, CIBERESP, and the Generalitat de Catalunya-CIRIT. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009- single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU- FP7- HEALTH-2012 Proposal No 308333 HELIX), and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011-2014; "Rhea Plus": Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15). We acknowledge support from the Spanish Ministry of Science and Innovation through the "Centro de Excelencia Severo Ochoa 2019-2023" Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. MV-U and CR-A were supported by a FI fellowship from the Catalan Government (FI-DGR 2015 and #016FI_B 00272). MC received funding from Instituto Carlos III (Ministry of Economy and Competitiveness) (CD12/00563 and MS16/00128).
Cells can fine-tune which genes they activate, when and at which levels using a range of chemical marks on the DNA and certain proteins that help to organise the genome. One well-known example of such 'epigenetic tags' is DNA methylation, whereby a methyl group is added onto particular positions in the genome. Many factors including environmental effects such as diet control DNA methylation, allowing an organism to adapt to ever-changing conditions. An expression quantitative trait methylation (eQTM) is a specific position of the genome whose DNA methylation status regulates the activity of a given gene. A catalogue of eQTMs would be useful in helping to reveal how the environment and disease impacts the way cells work. Yet, currently, the relationships between most epigenetic tags and gene activity remains unclear, especially in children. To fill this gap, Ruiz-Arenas et al. studied DNA methylation in blood samples from over 800 healthy children across Europe. Amongst all tested DNA methylation sites, 22,000 (5.7% of total) were associated with the expression of a gene and therefore were eQTMs; reciprocally, 9,000 genes (15.3% of all tested genes) were linked to at least one methylation site, leading to a total of 40,000 pairs of DNA methylation sites and genes. Most often, eQTMs regulated the expression of nearby genes but only half controlled the gene that was the closest to them. Age and the genetic background of the individuals influenced the nature of eQTMs. This catalogue is a useful resource for the scientific community to start understanding the relationship between epigenetics and gene activity. Similar studies are now needed for other tissues and age ranges. Overall, extending our knowledge of eQTMs may help reveal how life events lead to illness, and could inform prevention efforts.
Subject(s)
DNA Methylation , Epigenome , Adult , Child, Preschool , Cohort Studies , Europe , Humans , PhenotypeABSTRACT
Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.
Subject(s)
Genome-Wide Association Study , Genome , Genome-Wide Association Study/methods , Genomics/methods , Genotype , Humans , Linkage Disequilibrium , Polymorphism, Single NucleotideABSTRACT
BACKGROUND: Single-nucleotide polymorphisms (SNPs) in collagen genes are predisposing factors for anterior cruciate ligament (ACL) rupture. Although these events are more frequent in females, the sex-specific risk of reported SNPs has not been evaluated. PURPOSE: We aimed to assess the sex-specific risk of historic non-contact ACL rupture considering candidate SNPs in genes previously associated with muscle, tendon, ligament and ACL injury in elite footballers. STUDY DESIGN: This was a cohort genetic association study. METHODS: Forty-six (twenty-four females) footballers playing for the first team of FC Barcelona (Spain) during the 2020-21 season were included in the study. We evaluated the association between a history of non-contact ACL rupture before July 2022 and 108 selected SNPs, stratified by sex. SNPs with nominally significant associations in one sex were then tested for their interactions with sex on ACL. RESULTS: Seven female (29%) and one male (4%) participants had experienced non-contact ACL rupture during their professional football career before the last date of observation. We found a significant association between the rs13946 C/C genotype and ACL injury in women footballers (p = 0.017). No significant associations were found in male footballers. The interaction between rs13946 and sex was significant (p = 0.027). We found that the C-allele of rs13946 was exclusive to one haplotype of five SNPs spanning COL5A1. CONCLUSIONS: The present study suggests the role of SNPs in genes encoding for collagens as female risk factors for ACL injury in football players. CLINICAL RELEVANCE: The genetic profiling of athletes at high risk of ACL rupture can contribute to sex-specific strategies for injury prevention in footballers.