Dataset Information

The Consortium for the early identification of Alzheimer's disease-Quebec (CIMA-Q).

ABSTRACT:

Introduction

The Consortium for the early identification of Alzheimer's disease-Quebec (CIMA-Q) created a research infrastructure to recruit, characterize, and track disease progression in individuals at risk of dementia.

Methods

CIMA-Q established standardized clinical, neuropsychological, neuroimaging, blood (plasma, serum, RNA, genomic DNA), cryopreserved peripheral blood mononuclear cells, and cerebrospinal fluid collection protocols. These data and biological materials are available to the research community.

Results

In phase 1, 115 persons with subjective cognitive decline, 88 with mild cognitive impairment, 31 with early probable Alzheimer's disease, and 56 older adults with no worries nor impairments received detailed clinical and cognitive evaluations as well as blood and peripheral blood mononuclear cells collections. Among them, 142 underwent magnetic resonance imaging, 29 a ¹⁸fluorodeoxyglucose positron emission tomography, and 60 a lumbar puncture.

Discussion

CIMA-Q provides procedures and resources to identify early biomarkers and novel therapeutic targets, and holds promise for detecting cognitive decline in Alzheimer's disease.

SUBMITTER: Belleville S

PROVIDER: S-EPMC6880140 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Publications

The Consortium for the early identification of Alzheimer's disease-Quebec (CIMA-Q).

Belleville Sylvie S LeBlanc Andréa C AC Kergoat Marie-Jeanne MJ Calon Frédéric F Gaudreau Pierrette P Hébert Sébastien S SS Hudon Carol C Leclerc Nicole N Mechawar Naguib N Duchesne Simon S Gauthier Serge S

Alzheimer's & dementia (Amsterdam, Netherlands) 20191120

<h4>Introduction</h4>The Consortium for the early identification of Alzheimer's disease-Quebec (CIMA-Q) created a research infrastructure to recruit, characterize, and track disease progression in individuals at risk of dementia.<h4>Methods</h4>CIMA-Q established standardized clinical, neuropsychological, neuroimaging, blood (plasma, serum, RNA, genomic DNA), cryopreserved peripheral blood mononuclear cells, and cerebrospinal fluid collection protocols. These data and biological materials are av ...[more]

PMID: 31788534

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Project description:IntroductionAlzheimer's disease (AD) is one of the most prevalent forms of dementia globally and remains an incurable condition that often leads to death. PANoptosis represents an emerging paradigm in programmed cell death, integrating three critical processes: pyroptosis, apoptosis, and necroptosis. Studies have shown that apoptosis, necroptosis, and pyroptosis play important roles in AD development. Therefore, targeting PANoptosis genes might lead to novel therapeutic targets and clinically relevant therapeutic approaches. This study aims to identify different molecular subtypes of AD and potential drugs for treating AD based on PANoptosis.MethodsDifferentially expressed PANoptosis genes associated with AD were identified via Gene Expression Omnibus (GEO) dataset GSE48350, GSE5281, and GSE122063. Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to construct a risk model linked to these PANoptosis genes. Consensus clustering analysis was conducted to define AD subtypes based on these genes. We further performed gene set variation analysis (GSVA), functional enrichment analysis, and immune cell infiltration analysis to investigate differences between the identified AD subtypes. Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and the DGIdb database was consulted to identify potential therapeutic compounds targeting these hub genes. Single-cell RNA sequencing analysis was utilized to assess differences in gene expression at the cellular level across subtypes.ResultsA total of 24 differentially expressed PANoptosis genes (APANRGs) were identified in AD, leading to the classification of two distinct AD subgroups. The results indicate that these subgroups exhibit varying disease progression states, with the early subtype primarily linked to dysfunctional synaptic signaling. Furthermore, we identified hub genes from the differentially expressed genes (DEGs) between the two clusters and predicted 38 candidate drugs and compounds for early AD treatment based on these hub genes. Single-cell RNA sequencing analysis revealed that key genes associated with the early subtype are predominantly expressed in neuronal cells, while the differential genes for the metabolic subtype are primarily found in endothelial cells and astrocytes.ConclusionIn summary, we identified two subtypes, including the AD early synaptic abnormality subtype as well as the immune-metabolic subtype. Additionally, ten hub genes, SLC17A7, SNAP25, GAD1, SLC17A6, SLC32A1, PVALB, SYP, GRIN2A, SLC12A5, and SYN2, were identified as marker genes for the early subtype. These findings may provide valuable insights for the early diagnosis of AD and contribute to the development of innovative therapeutic strategies.

Dataset Information

The Consortium for the early identification of Alzheimer's disease-Quebec (CIMA-Q).

Introduction

Methods

Results

Discussion

Publications

The Consortium for the early identification of Alzheimer's disease-Quebec (CIMA-Q).

Similar Datasets

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