Publications by authors named "Chris Haley"

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  • Scientists studied how certain genes affect height and body mass index (BMI) by looking at families with siblings.
  • They found that links between genes and these traits could be seen both in family studies and in studies that look at a lot of DNA variations (called SNPs).
  • They discovered that there are still many genetic factors influencing height and BMI that haven't been identified yet, showing that genetics is really complex and involves many genes working together.
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  • The FarmGTEx project aims to create a public database of genetic variants in livestock to connect genetic differences with physical traits, benefiting both animal breeding and human health research.
  • The pilot phase, PigGTEx, involved analyzing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs, leading to the development of a genotype imputation panel and associations between millions of genetic variants and transcriptomic traits across 34 different tissues.
  • The study highlights the tissue-specific regulatory effects of these variants, revealing molecular mechanisms affecting 207 complex pig traits while also demonstrating the relevance of pigs as models for understanding human gene expression and genetic regulation.
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  • The study investigates how early life events impact aging through specific genomic regions influenced by both genetic and environmental factors, focusing on parent-of-origin effects (POE) on DNA methylation.
  • Researchers conducted a wide-ranging analysis identifying 92 associations between POE-influenced methylation and various health and aging traits, with a notable concentration on the effects of maternal smoking and cognitive functions.
  • The findings support the idea that atypical POE influences on DNA methylation are linked to aging mechanisms, highlighting the importance of early development in determining health outcomes in later life.
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Variation in the rate at which humans age may be rooted in early life events acting through genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions either enriched for genetically controlled imprinting effects (the typical type of POE) or atypical POE introduced by environmental effects associated with parents. This part of the methylome is heavily influenced by early life events, making it a potential route connecting early environmental exposures, the epigenome and the rate of aging.

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  • - The study analyzes the relationship between self-reported trauma exposure and major depressive disorder (MDD), considering the influence of genetic factors, using comprehensive genomic data from the UK Biobank to enhance understanding of these interactions.
  • - Participants included over 148,000 individuals who provided data on their trauma experiences, depressive symptoms, and genetics, allowing researchers to apply advanced statistical models to explore the connections.
  • - Results indicated that various types of trauma significantly contributed to the variance of MDD, estimating the heritability of the disorder at around 16%, suggesting a notable genetic influence alongside trauma exposure.
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Background: Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes.

Results: Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle.

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Background: Single-step genomic best linear unbiased prediction (ssGBLUP) allows the inclusion of information from genotyped and ungenotyped individuals in a single analysis. This avoids the need to genotype all candidates with the potential benefit of reducing overall costs. The aim of this study was to assess the effect of genotyping strategies, the proportion of genotyped candidates and the genotyping criterion to rank candidates to be genotyped, when using ssGBLUP evaluation.

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Biological age (BA), a measure of functional capacity and prognostic of health outcomes that discriminates between individuals of the same chronological age (chronAge), has been estimated using a variety of biomarkers. Previous comparative studies have mainly used epigenetic models (clocks), we use ~1000 participants to compare fifteen omics ageing clocks, with correlations of 0.21-0.

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We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM).

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  • Parent-of-origin effects (POE) influence complex diseases, and it's crucial to examine how both genetic and environmental factors can modify these effects and their associated variations.
  • The study screened 101 factors to assess their impact on POE regulation using data from a large Scottish health study, ultimately identifying three specific CpGs that can be modified by certain exposures.
  • The findings highlight how lifestyle choices and specific gene expressions can alter DNA methylation processes, paving the way for further research into how these modifiers contribute to the understanding of complex diseases.
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Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals.

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  • The study examines how genetic factors influence DNA methylation (DNAm), which is crucial for understanding gene regulation and diseases, using data from 32,851 participants.
  • Researchers identified genetic variants linked to DNAm at over 420,000 sites and created a database of more than 270,000 independent mQTLs, highlighting the complexity and polygenic nature of DNAm levels.
  • The findings suggest that while some shared genetic variants are linked to both DNAm and complex diseases, only a few cases indicate a direct causal relationship, revealing a complicated connection between genetics and phenotypes.
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The ever-growing genome-wide association studies (GWAS) have revealed widespread pleiotropy. To exploit this, various methods that jointly consider associations of a genetic variant with multiple traits have been developed. Most efforts have been made concerning improving GWAS discovery power.

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Background: The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised.

Methods: Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date.

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Host-mediated lung inflammation is present, and drives mortality, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units.

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Most patients with chronic pain do not find adequate pain relief with a single treatment, and accumulating evidence points to the added benefits of rational combinations of different treatments. Given that psychological therapies, such as mindfulness-based interventions (MBIs), are often delivered in conjunction with concomitant analgesic drug therapies (CADTs), this systematic scoping review examines the evidence for any interactions between MBIs and CADTs. The protocol for this review has been published and registered.

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  • Circulating proteins play a key role in human health and are used as biomarkers for disease and drug targets; this study maps protein quantitative trait loci (pQTLs) for 90 cardiovascular proteins in over 30,000 people, discovering 451 pQTLs for 85 proteins.
  • The researchers verified their findings with mouse studies and clinical trials, establishing the regulatory roles of certain genes on these proteins.
  • They also identified 11 proteins with potential causal links to diseases, suggesting new drug targets and opportunities for repositioning existing drugs, thus enhancing the understanding of the genetics of proteins in relation to health.
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To efficiently transform genetic associations into drug targets requires evidence that a particular gene, and its encoded protein, contribute causally to a disease. To achieve this, we employ a three-step proteome-by-phenome Mendelian Randomization (MR) approach. In step one, 154 protein quantitative trait loci (pQTLs) were identified and independently replicated.

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Background: Smoking status, alcohol consumption and HPV infection (acquired through sexual activity) are the predominant risk factors for oropharyngeal cancer and are thought to alter the prognosis of the disease. Here, we conducted single-site and differentially methylated region (DMR) epigenome-wide association studies (EWAS) of these factors, in addition to ∼ 3-year survival, using Illumina Methylation EPIC DNA methylation profiles from whole blood in 409 individuals as part of the Head and Neck 5000 (HN5000) study. Overlapping sites between each factor and survival were then assessed using two-step Mendelian randomization to assess whether methylation at these positions causally affected survival.

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Linking epigenetic marks to clinical outcomes improves insight into molecular processes, disease prediction, and therapeutic target identification. Here, a statistical approach is presented to infer the epigenetic architecture of complex disease, determine the variation captured by epigenetic effects, and estimate phenotype-epigenetic probe associations jointly. Implicitly adjusting for probe correlations, data structure (cell-count or relatedness), and single-nucleotide polymorphism (SNP) marker effects, improves association estimates and in 9,448 individuals, 75.

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Introduction: Most current chronic pain treatment strategies have limitations in effectiveness and tolerability, and accumulating evidence points to the added benefits of rational combinations of different therapies. However, most published clinical trials of treatment combinations have involved combinations of 2 drugs, whereas very little research has been performed to characterize interactions between drug and nondrug interventions. Mindfulness-based interventions (MBIs) have been emerging as a safe and potentially effective treatment option in the management of chronic pain, but it is unclear how MBIs can and should be integrated with various other pain treatment interventions.

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Human population isolates provide a snapshot of the impact of historical demographic processes on population genetics. Such data facilitate studies of the functional impact of rare sequence variants on biomedical phenotypes, as strong genetic drift can result in higher frequencies of variants that are otherwise rare. We present the first whole genome sequencing (WGS) study of the VIKING cohort, a representative collection of samples from the isolated Shetland population in northern Scotland, and explore how its genetic characteristics compare to a mainland Scottish population.

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Article Synopsis
  • The study aimed to identify genomic regions associated with intramuscular fat (IMF) content in two rabbit populations that have been selectively bred for this trait using a large genotyping dataset.
  • Analysis revealed significant genomic regions on chromosomes OCU1, OCU8, and OCU13, with the highest variance explained found on OCU8 (7.34%), pointing to multiple potential candidate genes involved in fat metabolism and adipose cell function.
  • Results suggest that the differences in IMF content are influenced by many genes, indicating a polygenic effect, and further research is needed to confirm these findings and assess their usefulness for breeding programs.
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