Biology subjects

O'Sullivan, J. M.

Publications and source records attributed to O'Sullivan, J. M..

At least 19 recordsLinked to original sources

bioRxiv2026

Type 2B VWD substitutions trigger enhanced macrophage-mediated clearance that is attenuated by the BT200 aptamer

Type 2B von Willebrand disease (VWD) is characterized by missense variants in exon 28 of the von Willebrand factor (VWF) gene that encodes the VWF-A1 domain. These missense mutations result in single amino acid residue substitutions that cause activation of VWF-A1 and promote spontaneous interaction with platelet GPIba;. Importantly, enhanced VWF clearance has been shown to play a key pathogenic role in >90% patients with Type 2B VWD. Although this VWF clearance occurs via mechanisms that are independent of VWF-platelet complex formation, the biological mechanisms responsible for the increased clearance of type 2B VWD variants remain poorly understood. In this study, we investigated a series of different type 2B amino acid substitutions within the VWF-A1 domain (R1306W, R1308C, W1313C and R1379L). We demonstrate that these variants all exhibit significantly increased macrophage binding. In part, the enhanced macrophage interactions are mediated via increased binding of type 2B VWD variants to LRP1 extracellular cluster II and IV. Our findings further demonstrate that the K1405-K1408 lysine cluster in the VWF-A1 domain plays a key role in enabling enhanced LRP1 interactions for type 2B VWD variants. In addition, we show that type 2B VWF variants demonstrate significantly enhanced interaction with the macrophage MGL receptor. Finally, and importantly from a clinical perspective, we demonstrate that the increase in macrophage binding for type 2B variants is significantly attenuated in the presence of BT200. Collectively, our findings have direct translational relevance with respect to the clinical heterogeneity and treatment of type 2B VWD.

biochemistry↗

bioRxiv2025

Mendelian randomizations with spatial gene networks reveal shared and distinct drivers of risk in major skin cancer types

Skin cancer is the most common malignancy worldwide, comprising three major types: melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). A critical goal in advancing our understanding of skin cancer is to identify the shared and distinct biological mechanisms that drive the risk profiles for each skin cancer type. In this study, we integrated tissue-specific chromatin conformation and expression quantitative trait loci data (spatial eQTL) to construct gene regulatory networks (GRNs) for melanocytes, sun-exposed skin, not sun-exposed skin, and blood. These GRNs, which capture spatially regulated gene expressions, were used as instrumental variables along with GWAS summary statistics for melanoma, BCC and SCC, to infer causal relationships between specific gene expression changes and each type of skin cancer. These Mendelian randomization analyses identified 82, 62, and 125 causal genes for melanoma, BCC, and SCC, respectively, with many of these genes not evident from the GWAS data alone. Our analyses revealed distinct mechanisms for each skin cancer type: telomere maintenance and nevus pathways in melanoma, inherited immune traits in BCC, and p53 dysfunction in SCC. Notably, apoptosis and pigmentation emerged as shared biological processes across skin cancers. These findings provide new insights into the genetic drivers of three distinct skin cancers, highlighting new gene targets which can be used to increase diagnostic precision, as well as potential therapeutic targets.

bioinformatics↗

bioRxiv2024

Early life microbial succession in the gut follows common patterns in humans across the globe

Characterizing the dynamics of microbial community succession in the infant gut microbiome is crucial for understanding child health and development, but no normative model currently exists. Here, we estimate child age using gut microbial taxonomic relative abundances from metagenomes, with high temporal resolution ({+/-}3 months) for the first 1.5 years of life. Using 3,154 samples from 1,827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.61 months. We identified key taxonomic predictors of age, including declines in Bifidobacterium spp. and increases in Faecalibacterium prausnitzii and Lachnospiraceae. Microbial succession patterns are conserved across infants from diverse human populations, suggesting universal developmental trajectories. Functional analysis confirmed trends in key microbial genes involved in feeding transitions and dietary exposures. This model provides a normative benchmark of "microbiome age" for assessing early gut maturation that can be used alongside other measures of child development.

microbiology↗

bioRxiv2024

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes

Investigations of the non-coding region are essential for uncovering the full spectrum of genetic drivers in melanoma. Here, we map distal, non-coding, promoter-interacting regulatory elements using Hi-C data from melanoma cells and integrating these with whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes. We identified eight recurrently mutated hotspots that are melanoma-specific, alter transcription factor binding motifs, and affect the expression of genes (e.g. HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumor suppressors/oncogenes. Our study integrates multiple levels of biological data to uncover novel melanoma-specific non-coding candidate drivers beyond the well-characterized TERT promoter.

genomics↗

bioRxiv2022

De novo discovery of traits co-occurring with chronic obstructive pulmonary disease

Epidemiological research indicates that chronic obstructive pulmonary disease (COPD) is a heterogeneous group of chronic lung conditions that are typically accompanied by cardiovascular disease, depression, lung cancer and other conditions. Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with COPD and the co-occuring conditions, suggesting common biological mechanisms underlying COPD and these co-occuring conditions. To identify them, we have integrated information across different biological levels (i.e. genetic variants, lung-specific 3D genome structure, gene expression and protein-protein interactions) to build lung-specific gene regulatory and protein-protein interaction networks. We have queried these networks using disease-associated SNPs for COPD, unipolar depression and coronary artery disease. Our results show that COPD-associated SNPs can control genes involved in the regulation of lung or pulmonary function, asthma, brain region volumes, cortical surface area, depressed affect, neuroticism, Parkinsons disease, white matter microstructure and smoking behaviour. We describe the regulatory connections, genes and biochemical pathways that underly these co-occuring trait-SNP-gene associations. Collectively, our findings provide new avenues for the investigation of the underlying biology and diverse clinical presentations of COPD. In so doing, we identify a collection of genetic variants and genes that may aid COPD patient stratification and treatment.

genomics↗

bioRxiv2021

Deciphering the genetic links between NAFLD and co-occurring conditions using a liver gene regulatory network

Background & AimsNon-alcoholic fatty liver disease (NAFLD) is a multi-system metabolic disease that co-occurs with various hepatic and extra-hepatic diseases. The phenotypic manifestation of NAFLD is primarily observed in the liver. Therefore, identifying liver-specific gene regulatory interactions between variants associated with NAFLD and multimorbid conditions may help to improve our understanding of underlying shared aetiology. MethodsHere, we constructed a liver-specific gene regulatory network (LGRN) consisting of genome-wide spatially constrained expression quantitative trait loci (eQTLs) and their target genes. The LGRN was used to identify regulatory interactions involving NAFLD-associated genetic modifiers and their inter-relationships to other complex traits. Results and ConclusionsWe demonstrate that MBOAT7 and IL32, which are associated with NAFLD progression, are regulated by spatially constrained eQTLs that are enriched for an association with liver enzyme levels. MBOAT7 transcript levels are also linked to eQTLs associated with cirrhosis, and other traits that commonly co-occur with NAFLD. In addition, genes that encode interacting partners of NAFLD-candidate genes within the liver-specific protein-protein interaction network were affected by eQTLs enriched for phenotypes relevant to NAFLD (e.g. IgG glycosylation patterns, OSA). Furthermore, we identified distinct gene regulatory networks formed by the NAFLD-associated eQTLs in normal versus diseased liver, consistent with the context-specificity of the eQTLs effects. Interestingly, genes targeted by NAFLD-associated eQTLs within the LGRN were also affected by eQTLs associated with NAFLD-related traits (e.g. obesity and body fat percentage). Overall, the genetic links identified between these traits expand our understanding of shared regulatory mechanisms underlying NAFLD multimorbidities.

genetics↗

bioRxiv2021

Genetic Variation as a Long-Distance Modulator of RAD21 Expression in Humans

Mutations and changes in expression in RAD21 are common across cancers types and outside of cancer can result in cohesinopathy. As such, exploration of variants that modify RAD21 enhancer activity, across the genome, may also provide insights into mechanisms by which distinct variants impact healthy human development and disease. We searched 42,953,834 genomic variants for a spatial-eQTL association with the transcription of RAD21. We identified 123 significant associations (FDR < 0.05), which are local (cis) or long-distance (trans) regulators of RAD21 expression. The 123 variants co-regulate a further seven genes, enriched for having Sp2 transcription factor binding sites in their promoter regions. The Sp2 transcription factor and six of the seven genes had previously been associated with cancer onset, progression, and metastasis. Our results suggest that genome-wide variation in non-coding regions impacts on RAD21 transcript levels in addition to other genes, which then could impact on oncogenesis and the process of ubiquitination. This identification of distant co-regulation of oncogenes represents a strategy for discovery of novel genetic regions which impact cancer onset and a potential for diagnostics.

bioinformatics↗

bioRxiv2021

Establishing gene regulatory networks from Parkinson's disease risk loci

The latest meta-analysis of genome wide association studies (GWAS) identified 90 independent single nucleotide polymorphisms (SNPs) across 78 genomic regions associated with Parkinsons disease (PD), yet the mechanisms by which these variants influence the development of the disease remains largely elusive. To establish the functional gene regulatory networks associated with PD-SNPs, we utilised an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci; eQTL) data. We identified 518 genes subject to regulation by 76 PD-SNPs across 49 tissues, that encompass 36 peripheral and 13 CNS tissues. Notably, one third of these genes were regulated via trans-acting mechanisms (distal; risk locus-gene separated by > 1Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-eQTL-gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and PD GWAS loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neuro-development specific eQTL-gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of PD. Through utilising Louvain clustering we extracted nine significant and highly intra-connected clusters within the entire gene regulatory network. The nine clusters are enriched for specific biological processes and pathways, some of which have not previously been associated with PD. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of PD-SNPs, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of PD.

genetics↗

bioRxiv2021

Unravelling the shared genetic mechanisms underlying 18 autoimmune diseases using a systems approach

Autoimmune diseases (AiDs) are complex heterogeneous diseases characterized by hyperactive immune responses against self. Genome-wide association studies have identified thousands of single nucleotide polymorphisms (SNPs) associated with several AiDs. While these studies have identified a handful of pleiotropic loci that confer risk to multiple AiDs, they lack the power to detect shared genetic factors residing outside of these loci. Here, we integrated chromatin contact, expression quantitative trait loci and protein-protein interaction (PPI) data to identify genes that are regulated by both pleiotropic and non-pleiotropic SNPs. The PPI analysis revealed complex interactions between the shared and disease-specific genes. Furthermore, pathway enrichment analysis demonstrated that the shared genes co-occur with disease-specific genes within the same biological pathways. In conclusion, our results are consistent with the hypothesis that genetic risk loci associated with multiple AiDs converge on a core set of biological processes that potentially contribute to the emergence of polyautoimmunity.

systems biology↗

bioRxiv2021

Autism spectrum disorder: understanding the impact of SNPs on biological pathways in the fetal and adult cortex.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by significant and complex genetic etiology. GWAS studies have identified genetic variants associated with ASD, but the functional impacts of these variants remain unknown. Here, we integrated four distinct levels of biological information (GWAS, eQTL, spatial genome organization and protein-protein interactions) to identify potential regulatory impacts of ASD-associated SNPs (p < 5x10-8) on biological pathways within fetal and adult cortical tissues. We found 80 and 58 SNPs that mark regulatory regions (i.e. expression quantitative trait loci or eQTLs) in the fetal and adult cortex, respectively. These eQTLs were also linked to other psychiatric disorders (e.g. schizophrenia, ADHD, bipolar disorder). Functional annotation of ASD-associated eQTLs revealed that they are involved in diverse regulatory processes. In particular, we found significant enrichment of eQTLs within regions repressed by Polycomb proteins in the fetal cortex compared to the adult cortex. Furthermore, we constructed fetal and adult cortex-specific protein-protein interaction networks and identified that ASD-associated regulatory SNPs impact on immune pathways, fatty acid metabolism, ribosome biogenesis, aminoacyl-tRNA biosynthesis and spliceosome in the fetal cortex. By contrast in the adult cortex, they largely affect immune pathways. Overall, our findings highlight potential regulatory mechanisms and pathways important for the etiology of ASD in early brain development and adulthood. This approach, in combination with clinical studies on ASD, will contribute to individualized mechanistic understanding of ASD development.

genomics↗

bioRxiv2021

A new method for determining ribosomal DNA copy number shows differences between Saccharomyces cerevisiae populations

Ribosomal DNA genes (rDNA) encode the major ribosomal RNAs (rRNA) and in eukaryotic genomes are typically present as one or more arrays of tandem repeats. Species have characteristic rDNA copy numbers, ranging from tens to thousands of copies, with the number thought to be redundant for rRNA production. However, the tandem rDNA repeats are prone to recombination-mediated changes in copy number, resulting in substantial intra-species copy number variation. There is growing evidence that these copy number differences can have phenotypic consequences. However, we lack a comprehensive understanding of what determines rDNA copy number, how it evolves, and what the consequences are, in part because of difficulties in quantifying copy number. Here, we developed a genomic sequence read approach that estimates rDNA copy number from the modal coverage of the rDNA and whole genome to help overcome limitations in quantifying copy number with existing mean coverage-based approaches. We validated our method using strains of the yeast Saccharomyces cerevisiae with previously-determined rDNA copy numbers, and then applied our pipeline to investigate rDNA copy number in a global sample of 788 yeast isolates. We found that wild yeast have a mean copy number of 92, consistent with what is reported for other fungi but much lower than in laboratory strains. We also show that different populations have different rDNA copy numbers. These differences can partially be explained by phylogeny, but other factors such as environment are also likely to contribute to population differences in copy number. Our results demonstrate the utility of the modal coverage method, and highlight the high level of rDNA copy number variation within and between populations. Author summaryThe ribosomal RNA gene repeats (rDNA) form large tandem repeat arrays in most eukaryote genomes. Their tandem arrangement makes the rDNA prone to copy number variation, and there is increasing evidence that this copy number variation has phenotypic consequences. However, difficulties in measuring rDNA copy number hamper investigation into rDNA copy number dynamics and their significance. Here we developed a novel bioinformatics method for measuring rDNA copy number from whole genome sequence data that is based on the modal sequence read coverage. We established parameters for optimal performance of the method and validated it using yeast strains of known rDNA copy numbers. We then applied the method to a dataset of almost 800 global yeast isolates and demonstrate that yeast populations have different rDNA copy numbers that partially correlate with phylogeny. Our work provides a simple and accurate method for determining rDNA copy number that leverages the growing number of whole genome datasets, and highlights the dynamic nature of rDNA copy number.

genomics↗

bioRxiv2020

A transcription regulatory network within the ACE2 locus may promote a pro-viral environment for SARS-CoV-2 by modulating expression of host factors.

IntroductionA novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was recently identified as the pathogen responsible for the COVID-19 outbreak. SARS-CoV-2 triggers severe pneumonia, which leads to acute respiratory distress syndrome and death in severe cases. As reported, SARS-CoV-2 is 80% genetically identical to the 2003 SARS-CoV virus. Angiotensin-converting enzyme 2 (ACE2) has been identified as the main receptor for entry of both SARS-CoV and SARS-CoV-2 into human cells. ACE2 is normally expressed in cardiovascular and lung type II alveolar epithelial cells, where it positively modulates the RAS system that regulates blood flow, pressure, and fluid homeostasis. Thus, virus-induced reduction of ACE2 gene expression is considered to make a significant contribution to severe acute respiratory failure. Chromatin remodeling plays a significant role in the regulation of ACE2 gene expression and the activity of regulatory elements within the genome. MethodsHere, we integrated data on physical chromatin interactions within the genome organization (captured by Hi-C) with tissue-specific gene expression data to identify spatial expression quantitative trait loci (eQTLs) and thus regulatory elements located within the ACE2 gene. ResultsWe identified regulatory elements within ACE2 that control the expression of PIR, CA5B, and VPS13C in the lung. The gene products of these genes are involved in inflammatory responses, de novo pyrimidine and polyamine synthesis, and the endoplasmic reticulum, respectively. ConclusionOur study, although limited by the fact that the identification of the regulatory interactions is putative until proven by targeted experiments, supports the hypothesis that viral silencing of ACE2 alters the activity of gene regulatory regions and promotes an intra-cellular environment suitable for viral replication.

genomics↗

bioRxiv2020

Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways

Variants in DNA regulatory elements can alter the regulation of distant genes through spatial-regulatory connections. In humans, these spatial-regulatory connections are largely set during early development, when the cohesin complex plays an essential role in genome organisation and cell division. A full complement of the cohesin complex and its regulators is important for normal development, since heterozygous mutations in genes encoding these components are often sufficient to produce a disease phenotype. The implication that genes encoding the cohesin complex and cohesin regulators must be tightly controlled and resistant to variability in expression has not yet been formally tested. Here, we identify spatial-regulatory connections with potential to regulate expression of cohesin loci, including linking their expression to that of other genes. Connections that centre on the cohesin ring subunits (Mitotic: SMC1A, SMC3, STAG1, STAG2, RAD21/RAD21-AS; Meiotic: SMC1B, STAG3, REC8, RAD21L1), cohesin-ring support genes (NIPBL, MAU2, WAPL, PDS5A and PDS5B), and CTCF provide evidence of coordinated regulation that has little tolerance for perturbation. We identified transcriptional changes across a set of genes co-regulated with the cohesin loci that include biological pathways such as extracellular matrix production and proteasome-mediated protein degradation. Remarkably, many of the genes that are co-regulated with cohesin loci are themselves intolerant to loss-of-function. The results highlight the importance of robust regulation of cohesin genes, indicating novel pathways that may be important in the human cohesinopathy disorders.

bioinformatics↗

bioRxiv2020

Targeting CXCR1 and CXCR2 to overcome radiotherapy resistance in PTEN-deficient prostate carcinoma

ABSTRACTFunctional impairment of the tumour-suppressor PTEN is common in primary-prostate cancer and has been linked to relapse post-radiotherapy (RT). Pre-clinical modelling supports elevated CXC-chemokine signaling as a critical mediator of PTEN-depleted disease progression and therapeutic resistance. We assessed the correlation of PTEN-deficiency with CXC-chemokine signaling and its association with clinical outcomes. Gene expression analysis characterized a PTENLOW/CXCR1HIGH/CXCR2HIGH cluster of tumors that associates with earlier time-to-biochemical recurrence (HR 5.87 and HR 2.65 respectively) and development of systemic metastasis (HR 3.51). In vitro, CXCL-signaling was further amplified following exposure of PTEN-deficient prostate cancer cell lines to ionizing radiation (IR). Inhibition of CXCR1/2-signaling in PTEN-depleted cell-based models increased IR-sensitivity. In vivo, administration of a CXCR1/2-targeted pepducin (x1/2pal-i3), or CXCR2-specific antagonist (AZD5069), in combination with IR to PTEN-deficient xenografts attenuated tumor growth and progression compared to control or IR alone. Post-mortem analysis confirmed that x1/2pal-i3 administration attenuated IR-induced CXCL-signaling and anti-apoptotic protein expression. Interventions targeting CXC-chemokine signaling may provide an effective strategy to combine with radiotherapy, in both locally-advanced and oligometastatic-prostate cancers, with known presence of PTEN-deficient foci.

cancer biology↗

bioRxiv2019

Decoding the multimorbidities among psychiatric disorders and cognitive functioning

The regulatory contribution that single-nucleotide polymorphisms (SNPs) associated with psychiatric and cognitive phenotypes make to multimorbidity is unknown. Here, we integrate 3D genome organization and expression quantitative trait (eQTL) analyses to identify the genes and biological pathways that are functionally impacted by 2,893 GWAS SNPs associated with cognitive functioning and five psychiatric disorders (i.e. attention deficit hyperactivity disorder (ADHD), anxiety, bipolar disorder (BD), unipolar depression (UD) and schizophrenia (SCZ)). The analysis revealed 33 genes and 62 pathways that were commonly affected by the gene regulatory interactions associated with all six phenotypes despite there being no common SNPs and eQTLs. 38 ADHD-, 78 anxiety-, 81 BD-, 169 UD-, 225 SCZ- and 185 cognition-associated genes represent known drug targets. Four genes were affected by eQTLs from all six phenotypes. Collectively, our results represent the foundation for a shift from a gene-targeted towards a pathway-based approach to the treatment of multimorbid conditions.

neuroscience↗

bioRxiv2019

Shared regulatory pathways reveal novel genetic correlations between grip strength and neuromuscular disorders

BackgroundMuscle weakness and muscle wasting can be a consequence of aging (sarcopenia) and neuromuscular disorders (NMD). Genome-wide association (GWA) studies have identified genetic variants associated with grip strength (GS, an inverse measure of muscle weakness) and NMD (multiple sclerosis (MS), myasthenia gravis (MG) and amyotrophic lateral sclerosis (ALS)). However, how these variants contribute to the muscle weakness caused by aging or NMD remains obscure.\n\nMethodsWe have integrated GS and NMD associated SNPs in a multimorbid analysis that leverages high-throughput chromatin interaction (Hi-C) data and expression quantitative trait loci (eQTL) data to identify allele-specific gene regulation (i.e. eGenes). Pathways and shared drug targets that are enriched by colocalised eGenes were then identified using pathway and drug enrichment analysis.\n\nResultsWe identified gene regulatory mechanisms (eQTL-eGene effects) associated with GS, MG, MS and ALS. The eQTLs associated with GS regulate a subset of eGenes that are also regulated by the eQTLs of MS, MG and ALS. Yet, we did not find any eGenes commonly regulated by all four phenotypes associated eQTLs. By contrast, we identified three pathways (mTOR signaling, axon guidance, and alcoholism) that are commonly affected by the gene regulatory mechanisms associated with all four phenotypes. 13% of the eGenes we identified were known drug targets, and GS shares at least one druggable eGene and pathway with each of the NMD phenotypes.\n\nConclusionsCollectively, these findings identify significant biological overlaps between GS and NMD, demonstrating the potential for spatial genetic analysis to identify mechanisms underlying muscle weakness due to aging and NMD.

genetics↗

bioRxiv2019

Genomic dissection of 43 serum urate-associated loci provides multiple insights into molecular mechanisms of urate control.

Serum urate is the end-product of purine metabolism. Elevated serum urate is causal of gout and a predictor of renal disease, cardiovascular disease and other metabolic conditions. Genome-wide association studies (GWAS) have reported dozens of loci associated with serum urate control, however there has been little progress in understanding the molecular basis of the associated loci. Here we employed trans-ancestral meta-analysis using data from European and East Asian populations to identify ten new loci for serum urate levels. Genome-wide colocalization with cis-expression quantitative trait loci (eQTL) identified a further five new loci. By cis- and trans-eQTL colocalization analysis we identified 24 and 20 genes respectively where the causal eQTL variant has a high likelihood that it is shared with the serum urate-associated locus. One new locus identified was SLC22A9 that encodes organic anion transporter 7 (OAT7). We demonstrate that OAT7 is a very weak urate-butyrate exchanger. Newly implicated genes identified in the eQTL analysis include those encoding proteins that make up the dystrophin complex, a scaffold for signaling proteins and transporters at the cell membrane; MLXIP that, with the previously identified MLXIPL, is a transcription factor that may regulate serum urate via the pentose-phosphate pathway; and MRPS7 and IDH2 that encode proteins necessary for mitochondrial function. Trans-ancestral functional fine-mapping identified six loci (RREB1, INHBC, HLF, UBE2Q2, SFMBT1, HNF4G) with colocalized eQTL that contained putative causal SNPs (posterior probability of causality > 0.8). This systematic analysis of serum urate GWAS loci has identified candidate causal genes at 19 loci and a network of previously unidentified genes likely involved in control of serum urate levels, further illuminating the molecular mechanisms of urate control.\n\nAuthor SummaryHigh serum urate is a prerequisite for gout and a risk factor for metabolic disease. Previous GWAS have identified numerous loci that are associated with serum urate control, however, only a small handful of these loci have known molecular consequences. The majority of loci are within the non-coding regions of the genome and therefore it is difficult to ascertain how these variants might influence serum urate levels without tangible links to gene expression and / or protein function. We have applied a novel bioinformatic pipeline where we combined population-specific GWAS data with gene expression and genome connectivity information to identify putative causal genes for serum urate associated loci. Overall, we identified 15 novel serum urate loci and show that these loci along with previously identified loci are linked to the expression of 44 genes. We show that some of the variants within these loci have strong predicted regulatory function which can be further tested in functional analyses. This study expands on previous GWAS by identifying further loci implicated in serum urate control and new causal mechanisms supported by gene expression changes.

genetics↗

bioRxiv2019

Quantitative profiling of 1-Carbon Metabolites, Amino Acids and Precursors, and Plasmalogens in human plasma using Ultra-High-Pressure Liquid Chromatography coupled with Tandem Mass Spectrometry and robotic compound extraction

Amino acids (AAs) and one-carbon (1-C) compounds are involved in a range of key metabolic pathways, and mediate numerous health and disease processes in the human body. Previous assays have quantified a limited selection of these compounds. Here, we describe an analytical method for the simultaneous quantification of 37 1-C metabolites, amino acids, precursors, and plasmalogens using reversed-phase ultra-high pressure liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). Compound extraction from human plasma was tested manually before being robotically automated. The final analytical panel was validated on human plasma samples. Our automated and multiplexed method holds promise for application to large cohort studies.

biochemistry↗