ORCID Profile
0000-0002-6158-827X
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Publisher: Wiley
Date: 16-05-2018
DOI: 10.1111/TPJ.13915
Publisher: Elsevier BV
Date: 02-2020
DOI: 10.1016/J.JSTROKECEREBROVASDIS.2019.104476
Abstract: To search for novel pathophysiological pathways related to ischemic stroke using a metabolomics approach. We identified 204 metabolites in plasma by liquid chromatography mass spectrometry in 3 independent population-based s les (TwinGene, Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) and Uppsala Longitudinal Study of Adult Men). TwinGene was used for discovery and the other 2 s les were meta-analyzed as replication. In PIVUS, traditional cardiovascular (CV) risk factors, multiple markers of subclinical CV disease, markers of coagulation/fibrinolysis were measured and analyzed in relation to top metabolites. In TwinGene (177 incident cases, median follow-up 4.3 years), levels of 28 metabolites were associated with incident ischemic stroke at a false discover rate (FDR) of 5%. In the replication (together 194 incident cases, follow-up 10 and 12 years, respectively), only sphingomyelin (32:1) was significantly associated (HR .69 per SD change, 95% CI .57-0.83, P value = .00014 FDR <5%) when adjusted for systolic blood pressure, diabetes, smoking, low density lipoportein (LDL)- and high density lipoprotein (HDL), body mass index (BMI) and atrial fibrillation. In PIVUS, sphingomyelin (32:1) levels were significantly related to both LDL- and HDL-cholesterol in a positive fashion, and to serum triglycerides, BMI and diabetes in a negative fashion. Furthermore, sphingomyelin (32:1) levels were related to vasodilation in the forearm resistance vessels, and inversely to leukocyte count (P < .0069 and .0026, respectively). An inverse relationship between sphingomyelin (32:1) and incident ischemic stroke was identified, replicated, and characterized. A possible protective role for sphingomyelins in stroke development has to be further investigated in additional experimental and clinical studies.
Publisher: American Chemical Society (ACS)
Date: 13-11-2020
Publisher: MDPI AG
Date: 23-09-2019
Abstract: Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 19-01-2021
Abstract: The molecular mechanisms involved in atrial fibrillation are not well known. We used plasma metabolomics to investigate if we could identify novel biomarkers and pathophysiological pathways of incident atrial fibrillation. We identified 200 endogenous metabolites in plasma/serum by nontargeted ultra‐performance liquid chromatography coupled to time‐of‐flight mass spectrometry in 3 independent population‐based s les (TwinGene, n=1935, mean age 68, 43% females PIVUS [Prospective Investigation of the Vasculature in Uppsala Seniors], n=897, mean age 70, 51% females and ULSAM [Uppsala Longitudinal Study of Adult Men], n=1118, mean age 71, all males), with available data on incident atrial fibrillation during 10 to 12 years of follow‐up. A meta‐analysis of ULSAM and PIVUS was used as a discovery s le and TwinGene was used for validation. In PIVUS, we also investigated associations between metabolites of interest and echocardiographic indices of myocardial geometry and function. Genome‐wide association studies were performed in all 3 cohorts for metabolites of interest. In the meta‐analysis of PIVUS and ULSAM with 430 incident cases, 4 metabolites were associated with incident atrial fibrillation at a false discovery rate %. Of those, only 9‐decenoylcarnitine was associated with incident atrial fibrillation and replicated in the TwinGene s le (288 cases) following adjustment for traditional risk factors (hazard ratio, 1.24 per unit 95% CI, 1.06–1.45, P =0.0061). A meta‐analysis of all 3 cohorts disclosed another 4 significant metabolites. In PIVUS, 9‐decenoylcarnitine was related to left atrium size and left ventricular mass. A Mendelian randomization analysis did not suggest a causal role of 9‐decenoylcarnitine in atrial fibrillation. A nontargeted metabolomics analysis disclosed 1 novel replicated biomarker for atrial fibrillation, 9‐Decenoylcarnitine, but this acetylcarnitine is likely not causally related to atrial fibrillation.
Location: United States of America
No related grants have been discovered for Corey Broeckling.