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Cognitive impairment in multiple sclerosis: lessons from cerebrospinal fluid biomarkers.

ABSTRACT: Cognitive impairment is a common clinical manifestation of multiple sclerosis, but its pathophysiology is not completely understood. White and grey matter injury together with synaptic dysfunction do play a role. The measurement of biomarkers in the cerebrospinal fluid and the study of their association with cognitive impairment may provide interesting in vivo evidence of the biological mechanisms underlying multiple sclerosis-related cognitive impairment. So far, only a few studies on this topic have been published, giving interesting results that deserve further investigation. Cerebrospinal fluid biomarkers of different pathophysiological mechanisms seem to reflect different neuropsychological patterns of cognitive deficits in multiple sclerosis. The aim of this review is to discuss the studies that have correlated cerebrospinal fluid markers of immune, glial and neuronal pathology with cognitive impairment in multiple sclerosis. Although preliminary, these findings suggest that cerebrospinal fluid biomarkers show some correlation with cognitive performance in multiple sclerosis, thus providing interesting insights into the mechanisms underlying the involvement of specific cognitive domains.

SUBMITTER: Gaetani L

PROVIDER: S-EPMC7818856 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Cognitive impairment in multiple sclerosis: lessons from cerebrospinal fluid biomarkers.

Gaetani Lorenzo L Salvadori Nicola N Chipi Elena E Gentili Lucia L Borrelli Angela A Parnetti Lucilla L Di Filippo Massimiliano M

Neural regeneration research 20210101 1

Cognitive impairment is a common clinical manifestation of multiple sclerosis, but its pathophysiology is not completely understood. White and grey matter injury together with synaptic dysfunction do play a role. The measurement of biomarkers in the cerebrospinal fluid and the study of their association with cognitive impairment may provide interesting in vivo evidence of the biological mechanisms underlying multiple sclerosis-related cognitive impairment. So far, only a few studies on this topi ...[more]

PMID: 32788445

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Project description:ObjectiveTo compare the effects of a 4-week high-saturated fat/high-glycemic index (HIGH) diet with a low-saturated fat/low-glycemic index (LOW) diet on insulin and lipid metabolism, cerebrospinal fluid (CSF) markers of Alzheimer disease, and cognition for healthy adults and adults with amnestic mild cognitive impairment (aMCI).DesignRandomized controlled trial.SettingVeterans Affairs Medical Center clinical research unit.ParticipantsForty-nine older adults (20 healthy adults with a mean [SD] age of 69.3 [7.4] years and 29 adults with aMCI with a mean [SD] age of 67.6 [6.8] years).InterventionParticipants received the HIGH diet (fat, 45% [saturated fat, > 25%]; carbohydrates, 35%-40% [glycemic index, > 70]; and protein, 15%-20%) or the LOW diet (fat, 25%; [saturated fat, < 7%]; carbohydrates, 55%-60% [glycemic index, < 55]; and protein, 15%-20%) for 4 weeks. Cognitive tests, an oral glucose tolerance test, and lumbar puncture were conducted at baseline and during the fourth week of the diet.Main outcome measuresThe CSF concentrations of β-amyloid (Aβ42 and Aβ40), tau protein, insulin, F2-isoprostanes, and apolipoprotein E, plasma lipids and insulin, and measures of cognition.ResultsFor the aMCI group, the LOW diet increased CSF Aβ42 concentrations, contrary to the pathologic pattern of lowered CSF Aβ42 typically observed in Alzheimer disease. The LOW diet had the opposite effect for healthy adults, ie, decreasing CSF Aβ42, whereas the HIGH diet increased CSF Aβ42. The CSF apolipoprotein E concentration was increased by the LOW diet and decreased by the HIGH diet for both groups. For the aMCI group, the CSF insulin concentration increased with the LOW diet, but the HIGH diet lowered the CSF insulin concentration for healthy adults. The HIGH diet increased and the LOW diet decreased plasma lipids, insulin, and CSF F2-isoprostane concentrations. Delayed visual memory improved for both groups after completion of 4 weeks of the LOW diet.ConclusionOur results suggest that diet may be a powerful environmental factor that modulates Alzheimer disease risk through its effects on central nervous system concentrations of Aβ42, lipoproteins, oxidative stress, and insulin.

Project description:BackgroundVerification of cerebrospinal fluid (CSF) biomarkers for multiple sclerosis and other neurological diseases is a major challenge due to a large number of candidates, limited sample material availability, disease and biological heterogeneity, and the lack of standardized assays. Furthermore, verification studies are often based on a low number of proteins from a single discovery experiment in medium-sized cohorts, where antibodies and surrogate peptides may differ, thus only providing an indication of proteins affected by the disease and not revealing the bigger picture or concluding on the validity of the markers. We here present a standard approach for locating promising biomarker candidates based on existing knowledge, resulting in high-quality assays covering the main biological processes affected by multiple sclerosis for comparable measurements over time.MethodsBiomarker candidates were located in CSF-PR (proteomics.uib.no/csf-pr), and further filtered based on estimated concentration in CSF and biological function. Peptide surrogates for internal standards were selected according to relevant criteria, parallel reaction monitoring (PRM) assays created, and extensive assay quality testing performed, i.e. intra- and inter-day variation, trypsin digestion status over time, and whether the peptides were able to separate multiple sclerosis patients and controls.ResultsAssays were developed for 25 proteins, represented by 72 peptides selected according to relevant guidelines and available literature and tested for assay peptide suitability. Stability testing revealed 64 peptides with low intra- and inter-day variations, with 44 also being stably digested after 16 h of trypsin digestion, and 37 furthermore showing a significant difference between multiple sclerosis and controls, thereby confirming literature findings. Calibration curves and the linear area of measurement have, so far, been determined for 17 of these peptides.ConclusionsWe present 37 high-quality PRM assays across 21 CSF-proteins found to be affected by multiple sclerosis, along with a recommended workflow for future development of new assays. The assays can directly be used by others, thus enabling better comparison between studies. Finally, the assays can robustly and stably monitor biological processes in multiple sclerosis patients over time, thus potentially aiding in diagnosis and prognosis, and ultimately in treatment decisions.

Project description:Eighty-five percent of multiple sclerosis cases begin with a discrete attack termed clinically isolated syndrome, but 37% of clinically isolated syndrome patients do not experience a relapse within 20 years of onset. Thus, the identification of biomarkers able to differentiate between individuals who are most likely to have a second clinical attack from those who remain in the clinically isolated syndrome stage is essential to apply a personalized medicine approach. We sought to identify biomarkers from biochemical, metabolic and proteomic screens that predict clinically defined conversion from clinically isolated syndrome to multiple sclerosis and generate a multi-omics-based algorithm with higher prognostic accuracy than any currently available test. An integrative multi-variate approach was applied to the analysis of cerebrospinal fluid samples taken from 54 individuals at the point of clinically isolated syndrome with 2-10 years of subsequent follow-up enabling stratification into clinical converters and non-converters. Leukocyte counts were significantly elevated at onset in the clinical converters and predict the occurrence of a second attack with 70% accuracy. Myo-inositol levels were significantly increased in clinical converters while glucose levels were decreased, predicting transition to multiple sclerosis with accuracies of 72% and 63%, respectively. Proteomics analysis identified 89 novel gene products related to conversion. The identified biochemical and protein biomarkers were combined to produce an algorithm with predictive accuracy of 83% for the transition to clinically defined multiple sclerosis, outperforming any individual biomarker in isolation including oligoclonal bands. The identified protein biomarkers are consistent with an exaggerated immune response, perturbed energy metabolism and multiple sclerosis pathology in the clinical converter group. The new biomarkers presented provide novel insight into the molecular pathways promoting disease while the multi-omics algorithm provides a means to more accurately predict whether an individual is likely to convert to clinically defined multiple sclerosis.

Dataset Information

Cognitive impairment in multiple sclerosis: lessons from cerebrospinal fluid biomarkers.

Publications

Cognitive impairment in multiple sclerosis: lessons from cerebrospinal fluid biomarkers.

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