2022 Dec 12
Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744737/
Abstract
While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N = 129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N = 24) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p < 0.0001) in an independent longitudinal cohort (N = 98), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.
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MS
Re: MS
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Re: MS
2022 Dec 14.
Department of Kinesiology and Nutrition, College of Applied Health Sciences, University of Illinois Chicago, Chicago, IL, USA
Oxygen cost of walking and its relationship with body composition in multiple sclerosis
https://pubmed.ncbi.nlm.nih.gov/36517575/
Abstract
Background/objectives: This cross-sectional study examined the relationship between the oxygen (O2) cost of walking and body composition metrics, while considering potential covariates such as disability status, step length, and cadence, in persons with multiple sclerosis (MS).
Subjects/methods: The sample included 63 persons with MS across a wide distribution of body mass index (BMI). O2 cost of walking was assessed using portable, indirect calorimetry, and percent body fat (%Fat), fat-free mass (FFM), bone mineral content, bone mineral density (BMD), and weight/FFM were determined from dual-energy x-ray absorptiometry. Other outcome measures included step length, cadence, physical activity, and disability status.
Results: The O2 cost of walking had small-to-moderate associations with BMI (rs = -31, p = 0.015), %Fat (rs = -0.26, p = 0.041), and BMD (rs = -0.31, p = 0.013). O2 cost of walking was significantly associated with these outcomes even after controlling for age, sex, disability status, and gait outcomes. The O2 cost of walking was further significantly associated with shorter step length (rs = -0.40, p = 0.001), slower cadence (rs = -0.38, p = 0.002), and higher disability status (rs = 0.44, p < 0.001), but not physical activity. Body composition metrics were not associated with gait parameters, physical activity or disability status in our sample of persons with mild-to-moderate MS.
Conclusions: The results indicated that higher O2 cost of walking was associated with lower fat and worse bone health after taking factors such as disability status into consideration. Researchers may focus on interventions that change body composition, or perhaps gait profiles, as possible approaches for changing O2 cost of walking and its consequences such as disability status in persons with MS.
Department of Kinesiology and Nutrition, College of Applied Health Sciences, University of Illinois Chicago, Chicago, IL, USA
Oxygen cost of walking and its relationship with body composition in multiple sclerosis
https://pubmed.ncbi.nlm.nih.gov/36517575/
Abstract
Background/objectives: This cross-sectional study examined the relationship between the oxygen (O2) cost of walking and body composition metrics, while considering potential covariates such as disability status, step length, and cadence, in persons with multiple sclerosis (MS).
Subjects/methods: The sample included 63 persons with MS across a wide distribution of body mass index (BMI). O2 cost of walking was assessed using portable, indirect calorimetry, and percent body fat (%Fat), fat-free mass (FFM), bone mineral content, bone mineral density (BMD), and weight/FFM were determined from dual-energy x-ray absorptiometry. Other outcome measures included step length, cadence, physical activity, and disability status.
Results: The O2 cost of walking had small-to-moderate associations with BMI (rs = -31, p = 0.015), %Fat (rs = -0.26, p = 0.041), and BMD (rs = -0.31, p = 0.013). O2 cost of walking was significantly associated with these outcomes even after controlling for age, sex, disability status, and gait outcomes. The O2 cost of walking was further significantly associated with shorter step length (rs = -0.40, p = 0.001), slower cadence (rs = -0.38, p = 0.002), and higher disability status (rs = 0.44, p < 0.001), but not physical activity. Body composition metrics were not associated with gait parameters, physical activity or disability status in our sample of persons with mild-to-moderate MS.
Conclusions: The results indicated that higher O2 cost of walking was associated with lower fat and worse bone health after taking factors such as disability status into consideration. Researchers may focus on interventions that change body composition, or perhaps gait profiles, as possible approaches for changing O2 cost of walking and its consequences such as disability status in persons with MS.
https://www.eboro.cz
Re: MS
2022 Dec 16
Infection, Immunity, Inflammation Research Theme, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
Integrating transcriptomic datasets across neurological disease identifies unique myeloid subpopulations driving disease-specific signatures
Abstract
Microglia and bone marrow-derived monocytes are key elements of central nervous system (CNS) inflammation, both capable of enhancing and dampening immune-mediated pathology. However, the study-specific focus on individual cell types, disease models or experimental approaches has limited our ability to infer common and disease-specific responses. This meta-analysis integrates bulk and single-cell transcriptomic datasets of microglia and monocytes from disease models of autoimmunity, neurodegeneration, sterile injury, and infection to build a comprehensive resource connecting myeloid responses across CNS disease. We demonstrate that the bulk microglial and monocyte program is highly contingent on the disease environment, challenging the notion of a universal microglial disease signature. Integration of six single-cell RNA-sequencing datasets revealed that these disease-specific signatures are likely driven by differing proportions of unique myeloid subpopulations that were individually expanded in different disease settings. These subsets were functionally-defined as neurodegeneration-associated, inflammatory, interferon-responsive, phagocytic, antigen-presenting, and lipopolysaccharide-responsive cellular states, revealing a core set of myeloid responses at the single-cell level that are conserved across CNS pathology. Showcasing the predictive and practical value of this resource, we performed differential expression analysis on microglia and monocytes across disease and identified Cd81 as a new neuroinflammatory-stable gene that accurately identified microglia and distinguished them from monocyte-derived cells across all experimental models at both the bulk and single-cell level. Together, this resource dissects the influence of disease environment on shared immune response programmes to build a unified perspective of myeloid behavior across CNS pathology.
Infection, Immunity, Inflammation Research Theme, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
Integrating transcriptomic datasets across neurological disease identifies unique myeloid subpopulations driving disease-specific signatures
Abstract
Microglia and bone marrow-derived monocytes are key elements of central nervous system (CNS) inflammation, both capable of enhancing and dampening immune-mediated pathology. However, the study-specific focus on individual cell types, disease models or experimental approaches has limited our ability to infer common and disease-specific responses. This meta-analysis integrates bulk and single-cell transcriptomic datasets of microglia and monocytes from disease models of autoimmunity, neurodegeneration, sterile injury, and infection to build a comprehensive resource connecting myeloid responses across CNS disease. We demonstrate that the bulk microglial and monocyte program is highly contingent on the disease environment, challenging the notion of a universal microglial disease signature. Integration of six single-cell RNA-sequencing datasets revealed that these disease-specific signatures are likely driven by differing proportions of unique myeloid subpopulations that were individually expanded in different disease settings. These subsets were functionally-defined as neurodegeneration-associated, inflammatory, interferon-responsive, phagocytic, antigen-presenting, and lipopolysaccharide-responsive cellular states, revealing a core set of myeloid responses at the single-cell level that are conserved across CNS pathology. Showcasing the predictive and practical value of this resource, we performed differential expression analysis on microglia and monocytes across disease and identified Cd81 as a new neuroinflammatory-stable gene that accurately identified microglia and distinguished them from monocyte-derived cells across all experimental models at both the bulk and single-cell level. Together, this resource dissects the influence of disease environment on shared immune response programmes to build a unified perspective of myeloid behavior across CNS pathology.
https://www.eboro.cz