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Graham, S. F.

Publications and source records attributed to Graham, S. F..

4 recordsLinked to original sources

Distinct Metabolic Signatures Linked to High-Resolution Computed Tomography Radiographic Phenotypes in Stable and Progressive Fibrotic Lung Disease

Rationale and ObjectivesThis study aimed to identify distinct metabolic signatures associated with disease progression by integrating high-resolution computed tomography (HRCT) visual scoring with comprehensive metabolomic profiling. Materials and MethodsThis single-center, cross-sectional study enrolled 60 idiopathic pulmonary fibrosis/interstitial lung disease (IPF/ILD) patients from December 2021 to October 2022. Participants underwent standardized pulmonary function testing, HRCT imaging, and peripheral blood collection for metabolomic analysis using one-dimensional hydrogen nuclear magnetic resonance (1H NMR) spectroscopy and ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS). A comprehensive HRCT scoring system quantified total HRCT composite scores. Linear regression analysis integrated radiographic scores with metabolomic profiles, adjusted for multiple covariates ResultsStable IPF/ILD exhibited moderate negative correlations between the six most significant metabolites and HRCT scores (r = -0.27 to -0.51), along with a high abundance of specific phospholipids (triacylglycerol, monoacylglycerol, phosphatidylglycerol, phosphatidylethanolamine, diacylglycerol), sphingomyelin, ceramide, and acylcarnitine. In contrast, progressive disease showed weak positive correlations between the six most significant metabolites and HRCT scores (r = 0.19-0.26), and moderate negative correlation between specific triacylglycerol species and HRCT scores (r = -0.37-0.4). Furthermore, metabolomic analysis in individuals with progressive disease revealed both high and low abundances of specific phospholipid species (including high and low triacylglycerol species, as well as low levels of phosphatidylglycerol, phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine, and phosphatidylinositol), along with high levels of certain sphingomyelin, ceramide, taurine, and purine bases, and low levels of xanthine and lactic acid observed. ConclusionIntegration of systematic HRCT visual scoring with metabolomic profiling successfully differentiated stable from progressive IPF/ILD through distinct molecular-radiographic signatures. FundingSupporting Effective Educator Development (SEED) grant

cell biology↗

Whole-genome DNA methylation profiling in COVID-19 positive patients reveals alterations in pathways linked to neurological dysfunction

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible RNA betacoronavirus, causing coronavirus disease-19 (COVID-19). Infection with SARS-CoV-2 can result in a broad spectrum of clinical outcomes, ranging from asymptomatic or mild to a severe, deadly illness. Emerging evidence suggests SARS-CoV-2 affects host gene regulation through epigenetic mechanisms, such as DNA methylation, potentially contributing to immune dysregulation and post-acute sequelae, including neurological and psychiatric disorders. However, the extent and functional relevance of these epigenetic changes remain uncertain. Methods and resultsWe employed whole-genome bisulfite sequencing to profile DNA methylation in peripheral blood from SARS-CoV-2-positive patients across a spectrum of symptom severity, ranging from asymptomatic to severe (n=101), in comparison to SARS-CoV-2-negative individuals (n=105). We observed a widespread hypomethylation in the genomes of infected individuals, which was more pronounced in severe cases. Notably, we identified differentially methylated genes in patients with mild (19 genes), moderate (19 genes), and severe (35 genes) symptoms. These genes included those involved in canonical immune responses as well as known to be linked to neurodegenerative diseases. Subsequent pathway enrichment analysis further supported the significant association between the differentially methylated genes and those implicated in Alzheimers and Parkinsons disease, as well as neuropsychiatric conditions, suggesting potential epigenetic links between acute SARS-CoV-2 infection and long-term neurological outcomes. This is one of the first studies to comprehensively map severity-stratified genome-wide DNA methylation changes in COVID-19 patients. ConclusionOur findings underscore the potential importance of epigenetic regulation in the acute responses to SARS-CoV-2 infection and highlight an overlap with epigenetic mechanisms relevant for neuropsychiatric disease processes.

neuroscience↗

Interlaboratory comparison of standardised metabolomics and lipidomics analyses in human and rodent blood using the MxP(R) Quant 500 kit

Metabolomics and lipidomics are pivotal in understanding phenotypic variations beyond genomics. However, quantification and comparability of mass spectrometry (MS)-derived data are challenging. Standardised assays can enhance data comparability, enabling applications in multi-center epidemiological and clinical studies. Here we evaluated the performance and reproducibility of the MxP(R) Quant 500 kit across 14 laboratories. The kit allows quantification of 634 different metabolites from 26 compound classes using triple quadrupole MS. Each laboratory analysed twelve samples, including human plasma and serum, lipaemic plasma, NIST SRM 1950, and mouse and rat plasma, in triplicates. 505 out of the 634 metabolites were measurable above the limit of detection in all laboratories, while eight metabolites were undetectable in our study. Out of the 505 metabolites, 412 were observed in both human and rodent samples. Overall, the kit exhibited high reproducibility with a median coefficient of variation (CV) of 14.3 %. CVs in NIST SRM 1950 reference plasma were below 25 % and 10 % for 494 and 138 metabolites, respectively. To facilitate further inspection of reproducibility for any compound, we provide detailed results from the in-depth evaluation of reproducibility across concentration ranges using Deming regression. Interlaboratory reproducibility was similar across sample types, with some species-, matrix-, and phenotype-specific differences due to variations in concentration ranges. Comparisons with previous studies on the performance of MS-based kits (including the AbsoluteIDQ p180 and the Lipidyzer) revealed good concordance of reproducibility results and measured absolute concentrations in NIST SRM 1950 for most metabolites, making the MxP(R) Quant 500 kit a relevant tool to apply metabolomics and lipidomics in multi-center studies.

biochemistry↗

Increased levels of circulating neurotoxic metabolites in patients with mild Covid19

SARS-CoV-2 corona virus causes a multi-faceted and poorly defined clinical and pathological phenotype involving hyperinflammation, cytokine release, and long-term cognitive deficits, with an undefined neuropathological mechanism. Inflammation increases the activity of the kynurenine pathway, which is linked to neurodegenerative and psychiatric disorders. We sought to determine whether the kynurenine pathway is impacted in patients with mild COVID-19, leading to elevated neurotoxic metabolites in blood, and whether such changes are associated with pro-inflammatory cytokines. Serum samples were taken from 150 patients and analyzed by ELISA and ultra-high performance liquid chromatography (UHPLC). The data were analyzed using multiple linear regression models adjusted for age and sex. We found increased levels of kynurenine, quinolinic acid and 3-hydroxykynurenine in serum from patients with mild COVID-19, together with increased levels of IL-6, ICAM-1, VCAM-1 and neopterin. The levels of neurotoxic metabolites were significantly associated with key inflammatory cytokines including IL-6 and TNF. The COVID-19 risk-factor hypertension was associated with the highest levels of neurotoxic metabolites in plasma. These neuroactive metabolites could be part of the pathological mechanisms underlying cognitive impairment during and post-COVID and should be explored as potential biomarkers for long-COVID symptoms.

neuroscience↗