Stem Cells as Potential Targets of Polyphenols in Multiple Sclerosis and Alzheimer's Disease.
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ABSTRACT:
SUBMITTER: Tandon A
PROVIDER: S-EPMC6077677 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
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Stem Cells as Potential Targets of Polyphenols in Multiple Sclerosis and Alzheimer's Disease.
Tandon Ankit A Singh Sangh Jyoti SJ Chaturvedi Rajnish Kumar RK
BioMed research international 20180712
Alzheimer's disease (AD) and multiple sclerosis are major neurodegenerative diseases, which are characterized by the accumulation of abnormal pathogenic proteins due to oxidative stress, mitochondrial dysfunction, impaired autophagy, and pathogens, leading to neurodegeneration and behavioral deficits. Herein, we reviewed the utility of plant polyphenols in regulating proliferation and differentiation of stem cells for inducing brain self-repair in AD and multiple sclerosis. Firstly, we discussed ...[more]
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Project description:Multiple sclerosis is a complex autoimmune disease, and several therapies for multiple sclerosis have been developed and widely used. However, existing medications for multiple sclerosis were far from satisfactory due to their failure to suppress relapses and alleviate disease progression. Novel drug targets for multiple sclerosis prevention are still needed. We performed Mendelian randomization to explore potential drug targets for multiple sclerosis using summary statistics from the International Multiple Sclerosis Genetics Consortium (nCase = 47 429, nControl = 68 374) and further replicated in UK Biobank (nCase = 1356, nControl = 395 209) and FinnGen cohorts (nCase = 1326, nControl = 359 815). Genetic instruments for 734 plasma and 154 CSF proteins were obtained from recently published genome-wide association studies. The reverse causality detection using bidirectional Mendelian randomization analysis and Steiger filtering, Bayesian co-localization, and phenotype scanning that searched previously reported genetic variant-trait associations were implemented to consolidate the Mendelian randomization findings further. In addition, the protein-protein interaction network was performed to reveal potential associations among proteins and/or present multiple sclerosis medications. At Bonferroni significance (P < 5.63 × 10-5), Mendelian randomization analysis revealed six protein-multiple sclerosis pairs. In plasma, per standard deviation increase in FCRL3, TYMP and AHSG had a protective effect. Odds ratios for the proteins above were 0.83 (95% CI, 0.79-0.89), 0.59 (95% CI, 0.48-0.71) and 0.88 (95% CI, 0.83-0.94), respectively. In CSF, per 10-fold increase in MMEL1 (OR, 5.03; 95% CI, 3.42-7.41) increased the risk of multiple sclerosis, while SLAMF7 (OR, 0.42; 95% CI, 0.29-0.60) and CD5L (OR, 0.30; 95%CI, 0.18-0.52) decreased the risk. None of the six proteins had reverse causality. Bayesian co-localization suggested that FCRL3 [coloc.abf-posterior probability of hypothesis 4 (PPH4) = 0.889], TYMP (coloc.susie-PPH4 = 0.896), AHSG (coloc.abf-PPH4 = 0.957, coloc.susie-PPH4 = 0.973), MMEL1 (coloc.abf-PPH4 = 0.930) and SLAMF7 (coloc.abf-PPH4 = 0.947) shared the same variant with multiple sclerosis. FCRL3, TYMP and SLAMF7 interacted with target proteins of current multiple sclerosis medications. MMEL1 was replicated in both UK Biobank and FinnGen cohorts. Our integrative analysis suggested that genetically determined levels of circulating FCRL3, TYMP, AHSG, CSF MMEL1 and SLAMF7 had causal effects on multiple sclerosis risk. These findings suggested those five proteins might be promising drug targets for multiple sclerosis and warrant further clinical investigation, especially FCRL3 and SLAMF7.
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Project description:BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has had an unprecedented impact on the healthcare system, economy, and society. Studies have reported that COVID-19 may cause various neurologic symptoms, including cognitive impairment. We aimed to assess the causal effect of COVID-19 on neurodegenerative diseases using two-sample Mendelian randomization (MR) study.MethodsGenetic variants were obtained from genome-wide association studies (GWAS) summary-level data and meta-analyses. We used the inverse variance-weighted (IVW) method as the primary analysis to estimate causal effects. Sensitivity analyses were performed to make the conclusions more robust and reliable.ResultsWe found that the COVID-19 infection phenotype was associated with a higher risk of AD and inverse associated with the risk of ALS and MS. The hospitalized COVID-19 phenotype was associated with the risk of AD and wasn't associated with ALS and MS. We also found that the severe COVID-19 (main analysis) phenotype was associated with the AD outcome from UK biobank datasets but was not associated with other outcomes. The severe COVID-19 infection phenotype, the severe COVID-19 (subtype analysis) phenotype and the hospitalization risk of COVID-19 were not associated with each outcome.ConclusionThis MR study suggests a potential association between genetically predicted COVID-19 and a higher risk of AD and a reduced risk of ALS and MS. Further elucidations of this association and underlying mechanisms may inform public health messages to prevent COVID-19 and AD.
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| S-EPMC4650727 | biostudies-other