Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure.

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.

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases.

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 an inversion association analysis 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 for 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.

Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits.

Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well-known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits.

Prenatal environmental exposures associated with sex differences in childhood obesity and neurodevelopment.

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.

teff: estimation of Treatment EFFects on transcriptomic data using causal random forest.

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.

scoreInvHap: Inversion genotyping for genome-wide association studies.

Polymorphic inversions contribute to adaptation and phenotypic variation. However, large multi-centric association studies of inversions remain challenging. We present scoreInvHap, a method to genotype inversions from SNP data for genome-wide association studies (GWASs), overcoming important limitations of current methods and outperforming them in accuracy and applicability. scoreInvHap calls individual inversion-genotypes from a similarity score to the SNPs of experimentally validated references. It can be used on different sources of SNP data, including those with low SNP coverage such as exome sequencing, and is easily adaptable to genotype new inversions, either in humans or in other species. We present 20 human inversions that can be reliably and easily genotyped with scoreInvHap to discover their role in complex human traits, and illustrate a first genome-wide association study of experimentally-validated human inversions. scoreInvHap is implemented in R and it is freely available from Bioconductor.

Benefits of the application of heat and pressure on peripheral venous cannulation in adults: A randomized controlled trial.

AIM: To evaluate the effectiveness of the application of topical heat, high pressure or a combination of both on antebrachial venous cannulation. DESIGN: A cross-over clinical trial blinded for haemolysis analysis. METHODS: This cross-over clinical trial with two periods was performed in the Clinical Trial Unit of Hospital Universitario de La Princesa (Madrid) during June-July of 2017 in 59 healthy adults who were randomly allocated to one of three interventions: (1) Using dry topical heat for 7 min produced by two hot seed bags (N = 21), (2) Applying controlled pressure from a sphygmomanometer inflated to 100 mmHg (N = 18) and (3) combining heat and pressure (N = 20) in one period out of two. All interventions were contrasted to standard clinical practice in the other period. The comparator involved a standard tourniquet around the upper arm to restrict venous blood flow. The primary outcome was effectiveness measured as vein cannulation at first attempt. Secondary outcomes were vein perception, pain, haemolysis in blood samples and adverse events. RESULTS: All the interventions were more effective than comparator. Vein perception was optimized in about all individuals. Moreover, pain relief was significantly higher when high pressure was applied. Haemolysis was not affected in any of the three interventions. In addition, no serious adverse events appeared. CONCLUSION: High pressure is determined to be the most effective in vein catheterization, pain relief, vein perception and quality of blood sample inalterability. Moreover, it is safe considering that only one adverse event appeared. IMPACT: Vein cannulation is a very common invasive technique, where repeated failures have been registered. Thus, we consider it relevant to develop interventions to achieve venous catheterization at first attempt to alleviate the pain and anxiety associated with this technique. We advocate using high pressure intervention for emergency, due to swiftest method and feasible in case of lacking resources, such as sphygmomanometers in the ambulance. Interventions can be extrapolated to healthy young adults, adults and patients who have healthy vein status perception. Pressure intervention could be an alternative to heat intervention when performing vein cannulation due to its lower risk of transient paresthesia for older people who often suffer from arterial hypertension.

MADloy: robust detection of mosaic loss of chromosome Y from genotype-array-intensity data.

BACKGROUND: Accurate protocols and methods to robustly detect the mosaic loss of chromosome Y (mLOY) are needed given its reported role in cancer, several age-related disorders and overall male mortality. Intensity SNP-array data have been used to infer mLOY status and to determine its prominent role in male disease. However, discrepancies of reported findings can be due to the uncertainty and variability of the methods used for mLOY detection and to the differences in the tissue-matrix used. RESULTS: We created a publicly available software tool called MADloy (Mosaic Alteration Detection for LOY) that incorporates existing methods and includes a new robust approach, allowing efficient calling in large studies and comparisons between methods. MADloy optimizes mLOY calling by correctly modeling the underlying reference population with no-mLOY status and incorporating B-deviation information. We observed improvements in the calling accuracy to previous methods, using experimentally validated samples, and an increment in the statistical power to detect associations with disease and mortality, using simulation studies and real dataset analyses. To understand discrepancies in mLOY detection across different tissues, we applied MADloy to detect the increment of mLOY cellularity in blood on 18 individuals after 3 years and to confirm that its detection in saliva was sub-optimal (41%). We additionally applied MADloy to detect the down-regulation genes in the chromosome Y in kidney and bladder tumors with mLOY, and to perform pathway analyses for the detection of mLOY in blood. CONCLUSIONS: MADloy is a new software tool implemented in R for the easy and robust calling of mLOY status across different tissues aimed to facilitate its study in large epidemiological studies.

Common polymorphic inversions at 17q21.31 and 8p23.1 associate with cancer prognosis.

BACKGROUND: Chromosomal inversions are structural genetic variants where a chromosome segment changes its orientation. While sporadic de novo inversions are known genetic risk factors for cancer susceptibility, it is unknown if common polymorphic inversions are also associated with the prognosis of common tumors, as they have been linked to other complex diseases. We studied the association of two well-characterized human inversions at 17q21.31 and 8p23.1 with the prognosis of lung, liver, breast, colorectal, and stomach cancers. RESULTS: Using data from The Cancer Genome Atlas (TCGA), we observed that inv8p23.1 was associated with overall survival in breast cancer and that inv17q21.31 was associated with overall survival in stomach cancer. In the meta-analysis of two independent studies, inv17q21.31 heterozygosity was significantly associated with colorectal disease-free survival. We found that the association was mediated by the de-methylation of cg08283464 and cg03999934, also linked to lower disease-free survival. CONCLUSIONS: Our results suggest that chromosomal inversions are important genetic factors of tumor prognosis, likely affecting changes in methylation patterns.

The effects of aripiprazole and olanzapine on pupillary light reflex and its relationship with pharmacogenetics in a randomized multiple-dose trial.

AIMS: Pupillography is a noninvasive and cost-effective method to determine autonomic nerve activity. Genetic variants in cytochrome P450 (CYP), dopamine receptor (DRD2, DRD3), serotonin receptor (HTR2A, HTR2C) and ATP-binding cassette subfamily B (ABCB1) genes, among others, were previously associated with the pharmacokinetics and pharmacodynamics of antipsychotic drugs. Our aim was to evaluate the effects of aripiprazole and olanzapine on pupillary light reflex related to pharmacogenetics. METHODS: Twenty-four healthy volunteers receiving 5 oral doses of 10 mg aripiprazole and 5 mg olanzapine tablets were genotyped for 46 polymorphisms by quantitative polymerase chain reaction. Pupil examination was performed by automated pupillometry. Aripiprazole, dehydro-aripiprazole and olanzapine plasma concentrations were measured by high-performance liquid chromatography-tandem mass spectrometry. RESULTS: Aripiprazole affected pupil contraction: it caused dilatation after the administration of the first dose, then caused constriction after each dosing. It induced changes in all pupillometric parameters (P < .05). Olanzapine only altered minimum pupil size (P = .046). Polymorphisms in CYP3A, HTR2A, UGT1A1, DRD2 and ABCB1 affected pupil size, the time of onset of constriction, pupil recovery and constriction velocity. Aripiprazole, dehydro-aripiprazole and olanzapine pharmacokinetics were significantly affected by polymorphisms in CYP2D6, CYP3A, CYP1A2, ABCB1 and UGT1A1 genes. CONCLUSIONS: In conclusion, aripiprazole and its main metabolite, dehydro-aripiprazole altered pupil contraction, but olanzapine did not have such an effect. Many polymorphisms may influence pupillometric parameters and several polymorphisms had an effect on aripiprazole, dehydro-aripiprazole and olanzapine pharmacokinetics. Pupillography could be a useful tool for the determination of autonomic nerve activity during antipsychotic treatment.

A measure of agreement across numerous conditions: assessing when changes in network structures are tissue-specific.

BACKGROUND: There is great interest to study how gene pathways change their structure across different tissues. The assessment of inter-study reliability of pathway changes across tissues can inform on the fraction of tissues with specific functional changes in network structure. However, there is a lack of agreement measures among studies that independently observe how a group of observations change across conditions. We, therefore, propose λ, a new inter-study reliability measure that determines the consistency to distinguish observations by condition. RESULTS: We derived λ's distributional characteristics, determine its reliability properties and compared it with Cohen's κ. We studied the co-expression structure of 287 gene pathways across four brain regions in two transcriptomic studies and applied λ to assess the inter-study reliability of the pathways' brain-regional changes. Brain-related pathways showed highest λ; the top value was for the nicotine addiction pathway whose structure was reliably distinguishable among regions with dopaminergic projections. CONCLUSION: Our results offer novel substantial evidence that changes in network structure across tissues can be inferred independently of samples, algorithms and experiments (RNA-sequencing or microarrays). Reliability measures, such as λ, can inform on the tissues where changes in a network's structure are likely functional. An R package is available at https://github.com/isglobal-brge/lambda .

When pitch adds to volume: coregulation of transcript diversity predicts gene function.

BACKGROUND: Genes corregulate their overall transcript volumes to perform their physiological functions. However, it is unknown if they additionally coregulate their transcript diversities. We studied the reliability, consistency and functional associations of co-splicing correlations of genes of interest, across two independent studies, multiple tissues and two statistical methods. We thoroughly investigated the reproducibility of co-splicing correlations of APP, the candidate gene of Azheimer's disease (AD). We then studied how co-splicing correlations in different tissues contributed to predict functional interactions of three other genes and finally computed co-splicing frequency for 17 thousand genes across 52 human tissues. RESULTS: We replicated co-splicing correlations between APP and 5 AD-related genes and reproduced expected enrichment of APP co-splicing in synaptic vesicle cycle and proteosome pathways. We observed novel associations for tissue vulnerability to disease with enrichment in APP co-splicing, co-expression and epistasis in AD. APP co-splicing was the strongest predictor and replicated between studies. We confirmed known gene interactions of PRPF8 and GRIA1 in testis and brain cortex, and observed a novel interaction of FGFR2, in breast and prostate, modulated by cancer risk-variants. We produced a co-splicing map across 52 human tissues to help predict the function of over 17 thousand genes. CONCLUSIONS: We show that coregulation of transcript diversities provides novel biological insights in gene physiology and helps to interpret GWAS results. Co-splicing correlations are reliable and frequent and should be further pursued to help predict gene function. Our results additionally support current AD interventions aiming at the ubiquitin proteosome pathway but unveil the need to consider transcript diversity in addition to volume to assess treatment response and susceptibility to the disease.

A common 16p11.2 inversion underlies the joint susceptibility to asthma and obesity.

The prevalence of asthma and obesity is increasing worldwide, and obesity is a well-documented risk factor for asthma. The mechanisms underlying this association and parallel time trends remain largely unknown but genetic factors may be involved. Here, we report on a common ~0.45 Mb genomic inversion at 16p11.2 that can be accurately genotyped via SNP array data. We show that the inversion allele protects against the joint occurrence of asthma and obesity in five large independent studies (combined sample size of 317 cases and 543 controls drawn from a total of 5,809 samples; combined OR = 0.48, p = 5.5 × 10(-6)). Allele frequencies show remarkable worldwide population stratification, ranging from 10% in East Africa to 49% in Northern Europe, consistent with discordant and extreme genetic drifts or adaptive selections after human migration out of Africa. Inversion alleles strongly correlate with expression levels of neighboring genes, especially TUFM (p = 3.0 × 10(-40)) that encodes a mitochondrial protein regulator of energy balance and inhibitor of type 1 interferon, and other candidates for asthma (IL27) and obesity (APOB48R and SH2B1). Therefore, by affecting gene expression, the ~0.45 Mb 16p11.2 inversion provides a genetic basis for the joint susceptibility to asthma and obesity, with a population attributable risk of 39.7%. Differential mitochondrial function and basal energy balance of inversion alleles might also underlie the potential selection signature that led to their uneven distribution in world populations.

Following the footprints of polymorphic inversions on SNP data: from detection to association tests.

Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease.

APOE and MS4A6A interact with GnRH signaling in Alzheimer's disease: Enrichment of epistatic effects.

INTRODUCTION: It is unknown if risk loci, identified by genome-wide association studies of late-onset Alzheimer's disease (LOAD), are linked to common molecular mechanisms through epistatic effects. METHODS: We performed genome-wide interaction studies of five risk variants for LOAD followed by enrichment analyses to find if there are pathways that simultaneously interact with more than one variant. This novel approach was applied to four independent cohorts (5393 cases and 3746 controls). RESULTS: We found enrichment of epistasis in gonadotropin-releasing hormone signaling with risk single-nucleotide polymorphisms in APOE and MS4A6A (P value = 3.7 × 10-5, P value = 5.6 × 10-6); vascular smooth muscle contraction pathway was also enriched in epistasis with these loci (P value = 9.6 × 10-5, P value = 2.4 × 10-7). MS4A6A risk variant also interacted with dilated cardiomyopathy pathway (P value = 3.1 × 10-7). DISCUSSION: In addition to APOE, MS4A6A polymorphisms should be considered in hormone trials targeting gonadotropins. Interactions of risk variants with neurovascular pathways may also be important in LOAD pathology.

Bringing memory fMRI to the clinic: comparison of seven memory fMRI protocols in temporal lobe epilepsy.

fMRI is increasingly implemented in the clinic to assess memory function. There are multiple approaches to memory fMRI, but limited data on advantages and reliability of different methods. Here, we compared effect size, activation lateralisation, and between-sessions reliability of seven memory fMRI protocols: Hometown Walking (block design), Scene encoding (block design and event-related design), Picture encoding (block and event-related), and Word encoding (block and event-related). All protocols were performed on three occasions in 16 patients with temporal lobe epilepsy (TLE). Group T-maps showed activity bilaterally in medial temporal lobe for all protocols. Using ANOVA, there was an interaction between hemisphere and seizure-onset lateralisation (P = 0.009) and between hemisphere, protocol and seizure-onset lateralisation (P = 0.002), showing that the distribution of memory-related activity between left and right temporal lobes differed between protocols and between patients with left-onset and right-onset seizures. Using voxelwise intraclass Correlation Coefficient, between-sessions reliability was best for Hometown and Scenes (block and event). The between-sessions spatial overlap of activated voxels was also greatest for Hometown and Scenes. Lateralisation of activity between hemispheres was most reliable for Scenes (block and event) and Words (event). Using receiver operating characteristic analysis to explore the ability of each fMRI protocol to classify patients as left-onset or right-onset TLE, only the Words (event) protocol achieved a significantly above-chance classification of patients at all three sessions. We conclude that Words (event) protocol shows the best combination of between-sessions reliability of the distribution of activity between hemispheres and reliable ability to distinguish between left-onset and right-onset patients.

Fraction of exhaled nitric oxide values in childhood are associated with 17q11.2-q12 and 17q12-q21 variants.

BACKGROUND: The fraction of exhaled nitric oxide (Feno) value is a biomarker of eosinophilic airway inflammation and is associated with childhood asthma. Identification of common genetic variants associated with childhood Feno values might help to define biological mechanisms related to specific asthma phenotypes. OBJECTIVE: We sought to identify the genetic variants associated with childhood Feno values and their relation with asthma. METHODS: Feno values were measured in children age 5 to 15 years. In 14 genome-wide association studies (N = 8,858), we examined the associations of approximately 2.5 million single nucleotide polymorphisms (SNPs) with Feno values. Subsequently, we assessed whether significant SNPs were expression quantitative trait loci in genome-wide expression data sets of lymphoblastoid cell lines (n = 1,830) and were related to asthma in a previously published genome-wide association data set (cases, n = 10,365; control subjects: n = 16,110). RESULTS: We identified 3 SNPs associated with Feno values: rs3751972 in LYR motif containing 9 (LYRM9; P = 1.97 × 10(-10)) and rs944722 in inducible nitric oxide synthase 2 (NOS2; P = 1.28 × 10(-9)), both of which are located at 17q11.2-q12, and rs8069176 near gasdermin B (GSDMB; P = 1.88 × 10(-8)) at 17q12-q21. We found a cis expression quantitative trait locus for the transcript soluble galactoside-binding lectin 9 (LGALS9) that is in linkage disequilibrium with rs944722. rs8069176 was associated with GSDMB and ORM1-like 3 (ORMDL3) expression. rs8069176 at 17q12-q21, but not rs3751972 and rs944722 at 17q11.2-q12, were associated with physician-diagnosed asthma. CONCLUSION: This study identified 3 variants associated with Feno values, explaining 0.95% of the variance. Identification of functional SNPs and haplotypes in these regions might provide novel insight into the regulation of Feno values. This study highlights that both shared and distinct genetic factors affect Feno values and childhood asthma.

Distinguishability and agreement with continuous data.

The analysis of concordance among repeated measures has received a huge amount of attention in the statistical literature leading to a range of different approaches. However, because all the approaches are able to assess the closeness among the readings taken on the same subject, the conclusions about the degree of concordance should be similar regardless the approach applied. Here, two indices to assess the concordance among continuous repeated measures, the intraclass correlation coefficient and the total deviation index, are applied and compared in two case examples. The first example concerns the repeatability of individual nutrient allocation strategy assessed by stable isotope analysis. The second example dealt with the assessment of the concordance of functional magnetic resonance imaging data that shows spatial correlation. The results differ depending upon the approach applied leading to contradictory conclusions about the degree of concordance. The reason behind these results is discussed reaching the conclusion that the total deviation index is just assessing agreement among repeated measurements, whereas the intraclass correlation coefficient assesses the concept of distinguishability among subjects that involves agreement among repeated measurements and spread of subjects at once. Therefore, the best way to select the right approach is to understand the right question behind the research hypothesis.

Predicting Injuries in Elite Female Football Players With Global-Positioning-System and Multiomics Data.

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.

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2.

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.