Dataset Information

COVID-19 patients and Dementia: Frontal cortex transcriptomic data.

ABSTRACT: Since the association of SARS-Cov-2 infection with Nervous System (NS) manifestations, we performed RNA-sequencing analysis in Frontal Cortex of COVID-19 positive or negative individuals and affected or not by Dementia individuals. We examined gene expression differences in individuals with COVID-19 and Dementia compared to Dementia only patients by collecting transcript counts in each sample and performing Differential Expression analysis. We found eleven genes satisfying our significance criteria, all of them being protein coding genes. These data are suitable for integration with supplemental samples and for analysis according to different individuals' classification. Also, differential expression evaluation may be implemented with other scientific purposes, such as research of unannotated genes, mRNA splicing and genes isoforms. The analysis of Differential Expressed genes in COVID-19 positive patients compared to non-COVID-19 patients is published in: S. Gagliardi, E.T. Poloni, C. Pandini, M. Garofalo, F. Dragoni, V. Medici, A. Davin, S.D. Visonà, M. Moretti, D. Sproviero, O. Pansarasa, A. Guaita, M. Ceroni, L. Tronconi, C. Cereda, Detection of SARS-CoV-2 genome and whole transcriptome sequencing in frontal cortex of COVID-19 patients., Brain. Behav. Immun. (2021). https://doi.org/10.1016/j.bbi.2021.05.012.

SUBMITTER: Garofalo M

PROVIDER: S-EPMC8479506 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Frontotemporal dementia is clinically and neuropathologically heterogeneous, but neuroinflammation, atrophy and cognitive impairment occur in all of its principal syndromes. Across the clinical spectrum of frontotemporal dementia, we assess the predictive value of in vivo neuroimaging measures of microglial activation and grey-matter volume on the rate of future cognitive decline. We hypothesized that inflammation is detrimental to cognitive performance, in addition to the effect of atrophy. Thirty patients with a clinical diagnosis of frontotemporal dementia underwent a baseline multimodal imaging assessment, including [11C]PK11195 PET to index microglial activation and structural MRI to quantify grey-matter volume. Ten people had behavioural variant frontotemporal dementia, 10 had the semantic variant of primary progressive aphasia and 10 had the non-fluent agrammatic variant of primary progressive aphasia. Cognition was assessed at baseline and longitudinally with the revised Addenbrooke's Cognitive Examination, at an average of 7-month intervals (for an average of ∼2 years, up to ∼5 years). Regional [11C]PK11195 binding potential and grey-matter volume were determined, and these were averaged within four hypothesis-driven regions of interest: bilateral frontal and temporal lobes. Linear mixed-effect models were applied to the longitudinal cognitive test scores, with [11C]PK11195 binding potentials and grey-matter volumes as predictors of cognitive performance, with age, education and baseline cognitive performance as covariates. Faster cognitive decline was associated with reduced baseline grey-matter volume and increased microglial activation in frontal regions, bilaterally. In frontal regions, microglial activation and grey-matter volume were negatively correlated, but provided independent information, with inflammation the stronger predictor of the rate of cognitive decline. When clinical diagnosis was included as a factor in the models, a significant predictive effect was found for [11C]PK11195 BPND in the left frontal lobe (-0.70, P = 0.01), but not for grey-matter volumes (P > 0.05), suggesting that inflammation severity in this region relates to cognitive decline regardless of clinical variant. The main results were validated by two-step prediction frequentist and Bayesian estimation of correlations, showing significant associations between the estimated rate of cognitive change (slope) and baseline microglial activation in the frontal lobe. These findings support preclinical models in which neuroinflammation (by microglial activation) accelerates the neurodegenerative disease trajectory. We highlight the potential for immunomodulatory treatment strategies in frontotemporal dementia, in which measures of microglial activation may also improve stratification for clinical trials.

Dataset Information

COVID-19 patients and Dementia: Frontal cortex transcriptomic data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets