Changes in cognitive ability and serum microRNAs during aging in mice
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE249248 | GEO | 2023/12/06
REPOSITORIES: GEO
Similar Datasets
Project description:Background: Mild cognitive impairment (MCI) is an intermediate state between normal aging, and Alzheimer’s disease, and other dementias. Early detection of dementia, and MCI, is a crucial issue in terms of secondary prevention. Blood biomarker detection is a possible way for early detection of MCI. Although disease biomarkers are detected by, in general, using single molecular analysis such as t-test, another possible approach is based on interaction between molecules. Results: Differential correlation analysis, which detects difference on correlation of two variables in case/control study, was carried out to the dataset with 745 microRNAs (miRNAs) from plasma samples of 30 age-matched controls and 23 MCI patients in Japan. The 20 pairs of miRNAs, which consist of 20 miRNAs, were selected as MCI markers. Two pairs of miRNAs (hsa-miR-191 and hsa-miR-101, and hsa-miR-103 and hsa-miR-222) out of 20 attained the highest area under the curve (AUC) value of 0.962 for MCI detection. Other two miRNA pairs that include hsa-miR-191 and hsa-miR-125b also attained high AUC value of ≥ 0.95. Pathway analysis was performed to the MCI markers for further understanding of biological implications. As a result, collapsed correlation on hsa-miR-191 and emerged correlation on hsa-miR-125b may have key role in MCI, and dementia progression. Conclusion: Differential correlation analysis, a bioinformatics tool to elucidate complicated and interdependent biological systems behind diseases, detects effective MCI markers that cannot be found by single molecule analysis such as t-test.
2016-12-10 | GSE90828 | GEO
Project description:To identify the potential biomarkers of Alzheimer's disease (AD) based on circulating microRNAs (miRNAs), we developed a new approach using feature selection and linear mixed model. The miRNA sequencing data of 105 plasma and 112 serum samples from 112 subjects including 28 AD cases, 63 mild cognitive impairment (MCI), and 21 controls were used to identify cerebrospinal fluid biomarkers associated miRNAs. The potential of these miRNAs as biomarkers of AD or MCI was researched and validated via both internal and external dataset. Patient classification was effectuated in compliance with the NIA-AA criteria for “MCI due to AD” and “Dementia due to AD”.
2024-02-26 | GSE215789 | GEO
Project description:Criteria for the diagnosis of amnestic MCI included: (i) memory complaint documented by the patient and collateral source; (ii) impairment in 1 or more of the 4 cognitive domains (memory, executive functioning/attention, visuospatial, or language); (iii) essentially normal functional activities of daily living; and (iv) absence of dementia. In general, the amnestic MCI determination is made when the memory measures fall 1.0⿿1.5 SD below the means for age and education appropriate individuals in our community; however, rigid cutoffs on psychometric scores were not used to establish the diagnosis of amnestic MCI which was made on clinical grounds. The diagnosis of dementia was made using DSM-IV criteria, and the diagnosis of AD was made using established criteria. Subjects were considered to be CN if they performed within the normative range and did not meet criteria for MCI or dementia.
2014-03-24 | ST000047 | MetabolomicsWorkbench
Project description:Criteria for the diagnosis of amnestic MCI included: (i) memory complaint documented by the patient and collateral source; (ii) impairment in 1 or more of the 4 cognitive domains (memory, executive functioning/attention, visuospatial, or language); (iii) essentially normal functional activities of daily living; and (iv) absence of dementia. In general, the amnestic MCI determination is made when the memory measures fall 1.0â1.5 SD below the means for age and education appropriate individuals in our community; however, rigid cutoffs on psychometric scores were not used to establish the diagnosis of amnestic MCI which was made on clinical grounds. The diagnosis of dementia was made using DSM-IV criteria, and the diagnosis of AD was made using established criteria. Subjects were considered to be CN if they performed within the normative range and did not meet criteria for MCI or dementia.
2014-03-24 | ST000046 | MetabolomicsWorkbench
Project description:Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and is the one of the few cancers in which a continued increase in incidence has been observed over several years. HCC associated with chronic liver disease evolves from precancerous lesion and early HCC to overt cancer, and identifying key molecules contributing to early stage HCC is an urgent need. α-Fetoprotein (AFP) is the best serum biomarker for diagnosis of HCC, but sensitivity is low, particularly in detection of early-stage HCC. Therefore, novel and reliable diagnostic biomarkers to complement AFP are needed to improve HCC diagnosis. We aim to determine transcriptome-based molecular signature of multistep hepatocarcinogenesis, and to identify novel serum biomarkers to diagnose early stage HCC patient.
2020-12-31 | GSE114564 | GEO
Project description:With the aging population, there is a growing focus on dementia, especially Alzheimer’s disease (AD). The molecular basis underlying the pathogenesis of AD is gradually being elucidated. Increasing evidence has shown that the immunological function of leukocytes plays a crucial role in the development of neurodegenerative disorders. However, there have been few studies among the Taiwanese population. The aim of this study was to investigate potential biomarkers for early diagnosis of Alzheimer’s disease from blood leukocytes. Experiment Overall Design: The peripheral blood mononuclear cells (PBMC) transcriptomes from 5 patients with mild cognitive impairment (MCI), 4 AD, as well as 4 normal controls (NC), were analyzed by microarray analysis.
2009-12-04 | E-GEOD-18309 | biostudies-arrayexpress
Project description:Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities, such as language or virtual/spatial comprehension. This cognitive decline is mostly ob-served with the aging of individuals. Recently, MCI has been considered as a prodromal phase of Alzheimer’s disease (AD), with a 10-15% conversion rate. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of serum N-glycan expression could represent essential con-tributors to the overall pathophysiology of neurodegenerative diseases and be used as a poten-tial marker to assess MCI diagnosis using non-invasive procedures. Herein, we undertook an LC-MS/MS glycomics approach to determine and characterize potential N-glycan markers in de-pleted blood serum samples from MCI patients. For the first time, we profiled the isomeric gly-come of the low abundant serum glycoproteins extracted from serum samples of control and MCI patients using an LC-MS/MS analytical strategy. Additionally, the MRM validation of the identified data showed five isomeric N-glycans with the ability to discriminate between healthy and MCI patients: the sialylated N-glycans HexNAc5,Hex6,Neu5Ac3 and HexNAc6,Hex7,Neu5Ac4 with single AUCs of 0.92 and 0.87 respectively, and combined AUC of 0.96; and the sialylat-ed-fucosylated N-glycans HexNAc4,Hex5,Fuc,Neu5Ac, HexNAc5,Hex6,Fuc,Neu5Ac2 and HexNAc6,Hex7,Fuc,Neu5Ac3 with single AUCs of 0.94, 0.67, and 0.88 respectively, and combined AUC of 0.98. According to ingenuity pathway analysis (IPA) and in line with recent publications the identified N-glycans may play an important role in neuroinflammation. Process that plays a fundamental role in the progression of neurodegenerative diseases.
2023-03-11 | PXD036704 | Pride
Project description:Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer’s disease (AD). Many MCI subjects convert to AD, although others remain stable as MCI or sometimes return to cognitive normal. Currently, there are no curative treatments for patients who are already in AD, and therefore biomarkers for early detection of high risk MCI-to-AD conversion subjects are rapidly required. Here, we investigated potential biomarkers from blood-based miRNA (miR) expression profiles and genomic data of 197 Japanese MCI patients. Using the candidate biomarkers, we constructed a prognosis prediction model based on a Cox proportional hazard model. The final prediction model, composed of 24 miR-eQTLs (i.e. SNP-miRNA pairs) and three clinical factors (age, sex and ApoE ε4 carriers), successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion (log-rank trend test P=3.44×10^(-4)), and achieved a concordance index of 0.702 on an independent test set. Network-based meta-analysis using target genes of the miR-eQTLs further revealed four important hub genes (SHC1, FOXO1, GSK3B, and PTEN) associated with the pathogenesis of AD. Statistically significant differences were observed in PTEN expression between MCI and AD and SHC1 expression between cognitively normal elder subjects (CN) and AD when examining RNA-seq data from 610 blood samples (PTEN, P=0.023; SHC1, P=0.049), although FOXO1 and GSK3B showed low levels of expression in blood. Accurate prediction of MCI-to-AD conversion enables earlier appropriate intervention for those MCI patients and can lead to a reduction of MCI patients that convert to AD with high risk. We believe that further investigation with larger sample sizes will contribute to practical clinical use of our approach in MCI-to-AD conversion in the near future.
2020-11-11 | GSE150693 | GEO
Project description:Alzheimer’s disease (AD), the predominant cause of late-life dementia, has a multifactorial etiology. Since there are few therapeutic options for symptomatic AD, research is increasingly focused on the identification of pre-symptomatic biomarkers. Recently, evaluation of neuron-derived exosomal markers has emerged as a promising novel approach for determining neuronal dysfunction. We aimed to identify novel neuron-derived exosomal markers that signify a transition from normal aging to Mild Cognitive Impairment (MCI) and then to clinically established AD, a sequence we refer to as AD progression. By using a Tandem Mass Tag-based quantitative proteomic approach, we identified a total of 360 neuron-derived exosomal proteins. Subsequent fuzzy c-means clustering revealed two clusters of proteins displaying trends of gradually increasing/decreasing expression over the period of AD progression (normal to MCI to AD), both of which were mainly involved in immune response-associated pathways, proteins within these clusters were defined as bridge proteins. Several differentially expressed proteins (DEPs) were identified in the progression of AD. The intersections of bridge proteins and DEPs were defined as key proteins, including C7 (Complement component 7), FERMT3 (Fermitin Family Member 3), CAP1 (Adenylyl cyclase-associated protein 1), ENO1 (Enolase 1) and ZYX (Zyxin), among which the expression patterns of C7 and ZYX were almost consistent with the proteomic results. Collectively, we propose that C7 and ZYX might be two novel neuron-derived exosomal protein markers, expression of which might be used to evaluate cognitive decline before a clinical diagnosis of AD is warranted.
2022-02-17 | PXD027561 | Pride
Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Late presentation of disease at the time of diagnosis is one of the major reasons for dismal prognostic outcomes for PDAC patients. Currently, there is a lack of clinical biomarkers which can be used to diagnose PDAC patients at an early resectable stage. This study performed proteomic mass spectrometry to identify novel blood-based biomarkers for early diagnosis of PDAC.
2024-03-05 | PXD046438 | Pride