Biology subjects

Kultima, K.

Publications and source records attributed to Kultima, K..

7 recordsLinked to original sources

bioRxiv2024

Microbially produced bile acids are associated with high levels of IgG autoantibodies and worse mental wellbeingin fibromyalgia subjects

Fibromyalgia (FM) is a disease primarily associated with chronic widespread pain, but other common symptoms are anxiety and depression. We previously proposed that autoimmunity contributes to FM based on findings of increased immunoglobulin G binding to satellite glial cells (anti-SGC IgG) in FM subjects compared to healthy controls (HC). Emerging research suggests that an altered gut microbiota composition is connected to psychological symptoms in FM rather than pain. Gut microbiota can produce or alter bile acids (BAs) and short-chain fatty acids (SCFAs), which have immune and inflammatory functions. Here, we investigate alterations in BA and SCFA concentrations in FM subjects compared to healthy controls (HC) and potential associations with FM symptoms and anti-SGC IgG levels. Bile acids and SCFAs were quantified using liquid chromatography coupled with high-resolution mass spectrometry and anti-SGC IgG levels were assessed with immunocytochemistry. The correlations between FM symptoms, anti-SGC IgG levels, and serum concentrations of 24 BAs and 11 SCFAs in 35 FM subjects and 32 matched HC were examined. Fibromyalgia subjects had significantly higher levels of microbially produced BAs than HC. Strikingly, 11 out of 24 BAs were significantly elevated in FM subjects with high, compared to those with low, anti-SGC IgG levels. Concentrations of specific BAs were associated with increased disease severity and worse mental well-being. These results revealed increased levels of secondary BAs in FM subjects compared to HC. The strong association between BAs, anti-SGC IgG levels, and mental well-being may help elucidate the importance of BAs in the psychological symptoms of FM. Significance statementFibromyalgia (FM) is a chronic pain syndrome that significantly impacts an individuals quality of life. In addition to persistent pain, people with FM often experience depression, anxiety, and irritable bowel syndrome. Previously, we identified autoantibodies that bind to satellite glial cells in the dorsal root ganglia associated with more severe FM symptoms. Our current results demonstrate a novel association between these autoantibodies in FM and bile acids (BAs). Bile acids are essential for lipid metabolism but also act as signaling molecules. We show that patients with elevated levels of autoantibodies also exhibit increased levels of BAs. Furthermore, the BAs strongly correlate with worse FM symptom severity, particularly affecting mental well-being. Our study suggests that lowering BA levels could alleviate the psychological symptoms associated with FM.

neuroscience↗

bioRxiv2024

Fibromyalgia patients have altered lipid concentrations associated with disease symptom severity and anti-satellite glial cell IgG antibodies

Autoimmunity and immunoglobulin G (IgG) autoantibodies may contribute to pain in a subset of fibromyalgia (FM) patients. Previously, we saw that IgG from FM patients induces pain-like behavior in mice and binds to satellite glial cells (anti-SGC IgG). The anti-SGC IgG levels were also associated with more severe symptomatology. Lipid metabolism in FM subjects is altered with lysophosphatidylcholines (LPCs) acting as pain mediators. The relationship between autoantibodies, lipid metabolism, and FM symptomatology remains unclear. We analyzed serum lipidomics with liquid chromatography mass spectrometry, anti-SGC IgG levels, and clinical measures in 35 female FM subjects and 33 age- and body mass index-balanced healthy controls (HC). Fibromyalgia subjects with higher anti-SGC IgG levels experienced more intense pain than those with lower levels. Sixty-three lipids were significantly altered between FM subjects and HC or between FM subjects with severe (FM severe) and mild symptoms (FM mild). Compared to HC, FM subjects had lower concentrations of lipid species belonging to the classes LPC (n = 10), lysophosphatidylethanolamine (n = 7), phosphatidylcholine (n = 4), and triglyceride (n = 5), but higher concentrations of diglyceride (n = 3). Additionally, FM severe had higher LPC 19:0, 22:0, and 24:1 and lower sphingomyelin (n = 9) concentrations compared to FM mild. A positive association was seen for LPC 22:0 and 24:1 with pain intensity and anti-SGC IgG levels in FM subjects. Taken together, our results suggest an association between altered lipid metabolism and autoimmune mechanisms in FM. PerspectiveOur results suggest an association between the postulated autoimmunity in FM and lipids that can act as pain mediators.

neuroscience↗

bioRxiv2022

Fibromyalgia patients with high levels of anti-satellite glia cell IgG antibodies present with more severe symptoms

ObjectiveTransferring fibromyalgia patient IgG to mice induces pain-like behaviour and fibromyalgia IgG binds mouse and human satellite glia cells (SGCs). These findings suggest that autoantibodies could be part of fibromyalgia pathology. However, it is unknown how frequently fibromyalgia patients have anti-SGC antibodies and how anti-SGC antibodies associate with disease severity. MethodsWe quantified serum or plasma anti-SGC IgG levels in two fibromyalgia cohorts from Sweden and Canada using an indirect immunofluorescence murine cell culture assay. Fibromyalgia serum IgG binding to human SGCs in human dorsal root ganglia tissue sections was assessed by immunofluorescence (n=14/group). ResultsIn the cell culture assay anti-SGC IgG levels were increased in both fibromyalgia cohorts compared to controls. Elevated anti-SGC IgG was associated with higher levels of self-reported pain in both cohorts, and higher fibromyalgia impact questionnaire scores and increased pressure sensitivity in the Swedish cohort. Anti-SGC IgG levels were not associated with fibromyalgia duration. Swedish FM patients were clustered into FM-severe and FM-mild groups and the FM-severe group had elevated anti-SGC IgG compared to the FM-mild and controls. Anti-SGC IgG levels detected in culture were positively correlated with increased binding to human SGCs. Moreover, the FM-severe group had elevated IgG binding to human SGCs compared to the FM-mild and control groups. ConclusionsA subset of fibromyalgia patients have elevated levels of anti-SGC antibodies, and the antibodies are associated with more severe fibromyalgia severity. Screening fibromyalgia patients for anti-SGC antibodies could provide a path to personalized treatment options that target autoantibodies and autoantibody production.

neuroscience↗

bioRxiv2021

Lysophophatidyl-choline 16:0 mediates persistent joint pain through Acid-Sensing Ion Channel 3: preclinical and clinical evidences

Rheumatic diseases are often associated to debilitating chronic joint pain, which remains difficult to treat and requires new therapeutic strategies. Here, we describe increased content of lysophosphatidyl-choline (LPC) 16:0 in the knee synovial fluids of two independent cohorts of patients with painful joint diseases. If LPC16:0 levels correlated with pain in patients with osteoarthritis (OA), they do not appear to be the hallmark of a particular joint disease. We found that intra-articular injections of LPC16:0 in mouse produce chronic pain and anxiety-like behaviors in both males and females with no apparent inflammation, peripheral nerve sprouting and damage, nor bone alterations. LPC16:0-induced persistent pain state is dependent on peripheral Acid-Sensing Ion Channel 3 (ASIC3), ultimately leading to central sensitization. LPC16:0 and ASIC3 thus appear as key players of chronic joint pain with potential implications in OA and possibly across others rheumatic diseases.

neuroscience↗

bioRxiv2018

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

BackgroundMetabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organisms metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent - and sometimes incompatible - analysis methods that are difficult to connect into a useful and complete data analysis solution.\n\nFindingsThe PhenoMeNal (Phenome and Metabolome aNalysis) e-infrastructure provides a complete, workflow-oriented, interoperable metabolomics data analysis solution for a modern infrastructure-as-a-service (IaaS) cloud platform. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the projects continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm.\n\nConclusionsPhenoMeNal constitutes a keystone solution in cloud infrastructures available for metabolomics. It provides scientists with a ready-to-use, workflow-driven, reproducible and shareable data analysis platform harmonizing the software installation and configuration through user-friendly web interfaces. The deployed cloud environments can be dynamically scaled to enable large-scale analyses which are interfaced through standard data formats, versioned, and have been tested for reproducibility and interoperability. The flexible implementation of PhenoMeNal allows easy adaptation of the infrastructure to other application areas and omics research domains.

bioinformatics↗

bioRxiv2018

Container-based bioinformatics with Pachyderm

MotivationComputational biologists face many challenges related to data size, and they need to manage complicated analyses often including multiple stages and multiple tools, all of which must be deployed to modern infrastructures. To address these challenges and maintain reproducibility of results, researchers need (i) a reliable way to run processing stages in any computational environment, (ii) a well-defined way to orchestrate those processing stages, and (iii) a data management layer that tracks data as it moves through the processing pipeline.\n\nResultsPachyderm is an open-source workflow system and data management framework that fulfills these needs by creating a data pipelining and data versioning layer on top of projects from the container ecosystem, having Kubernetes as the backbone for container orchestration. We adapted Pachyderm and demonstrated its attractive properties in bioinformatics. A Helm Chart was created so that researchers can use Pachyderm in multiple scenarios. The Pachyderm File System was extended to support block storage. A wrapper for initiating Pachyderm on cloud-agnostic virtual infrastructures was created. The benefits of Pachyderm are illustrated via a large metabolomics workflow, demonstrating that Pachyderm enables efficient and sustainable data science workflows while maintaining reproducibility and scalability.\n\nAvailabilityPachyderm is available from https://github.com/pachyderm/pachyderm. The Pachyderm Helm Chart is available from https://github.com/kubernetes/charts/tree/master/stable/pachyderm. Pachyderm is available out-of-the-box from the PhenoMeNal VRE (https://github.com/phnmnl/KubeNow-plugin) and general Kubernetes environments instantiated via KubeNow. The code of the workflow used for the analysis is available on GitHub (https://github.com/pharmbio/LC-MS-Pachyderm).\n\nContactjon.novella@farmbio.uu.se

bioinformatics↗

bioRxiv2017

Interoperable and scalable metabolomics data analysis with microservices

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The access point is a virtual research environment which can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and established workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry studies, one nuclear magnetic resonance spectroscopy study and one fluxomics study, showing that the method scales dynamically with increasing availability of computational resources. We achieved a complete integration of the major software suites resulting in the first turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, multivariate statistics, and metabolite identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.

bioinformatics↗