Dataset Information

Genome-wide network-based pathway analysis of CSF t-tau/A?1-42 ratio in the ADNI cohort.

ABSTRACT: BACKGROUND:The cerebrospinal fluid (CSF) levels of total tau (t-tau) and A?1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. RESULTS:The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/A?1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value???0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). CONCLUSIONS:This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/A?1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta production but also multiple genes enriching several KEGG pathways such as Alzheimer's disease, colorectal cancer, gliomas, renal cell carcinoma, Huntington's disease, and others. This study demonstrated that integration of gene-level associations with CMs could yield statistically significant findings to offer valuable biological insights (e.g., functional interaction among the protein products of these genes) and suggest high confidence candidates for subsequent analyses.

SUBMITTER: Cong W

PROVIDER: S-EPMC5450240 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

Cong Wang W Meng Xianglian X Li Jin J Zhang Qiushi Q Chen Feng F Liu Wenjie W Wang Ying Y Cheng Sipu S Yao Xiaohui X Yan Jingwen J Kim Sungeun S Saykin Andrew J AJ Liang Hong H Shen Li L

BMC genomics 20170530 1

<h4>Background</h4>The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ<sub>1-42</sub> are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this s ...[more]

PMID: 28558704

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Project description:BackgroundDelirium and dementia share symptoms of cognitive dysfunctions, and mechanisms of neuroinflammation appear involved in both conditions. Triggering receptor expressed on myeloid cells 2 (TREM2) is linked to dementia and neurodegenerative disease. It encodes expression of an innate immune receptor in the brain expressed by microglia. The level of the soluble fragment of TREM2 (sTREM2) is reported to increase in the cerebrospinal fluid (CSF) already in prodromal and asymptomatic Alzheimer's disease.MethodsWe analyzed the level of CSF sTREM2 in relation to delirium and dementia. The study included patients with or without pre-existing dementia who underwent acute hip fracture surgery (n?=?120), and some of the patients developed delirium (n?=?65). A medical delirium cohort (n?=?26) was also examined. ELISA was used to determine the level of sTREM2 in CSF.ResultsDelirium was associated with a higher level of CSF sTREM2 only among those without pre-existing dementia (p?=?0.046, n?=?15, n?=?44), particularly among patients developing delirium after CSF sampling (p?=?0.02, n?=?7, n?=?44). Between patients with dementia, there was no group difference, but the CSF sTREM2 level increased with waiting time for surgery (rS?=?0.39, p?=?0.002, n?=?60) and correlated well with the CSF Alzheimer's disease biomarkers, A?42, and t-tau/p-tau (rS?=?0.40, p?=?0.002, rS?=?0.46, p?<?0.001/ rS?=?0.49, p?<?0.001, n?=?60). Among patients with dementia, the level of A?38 and A?40 also correlated positively with sTREM2 in CSF (A?38MSDrS?=?0.44, p?=?0.001; A?40MSDrS?=?0.48, p?<?0.001; A?42MSDrS?=?0.43, p?<?0.001, n?=?60).ConclusionThe findings reinforce the involvement of neuroinflammation in delirium, yet with separate responses in patients with or without pre-existing dementia. Our findings support the concept of primed microglia in neurodegenerative disease and central immune activation after a peripheral trauma in such patients. A CSF biomarker panel of neuroinflammation might be valuable to prevent delirium by identifying patients at risk.

Project description:BACKGROUND:A relationship quantitative trait locus exists when the correlation between multiple traits varies by genotype for that locus. Relationship quantitative trait loci (rQTL) are often involved in gene-by-gene (G×G) interactions or gene-by-environmental interactions, making them a powerful tool for detecting G×G. METHODS:We performed genome-wide association studies to identify rQTL between tau and A?42 and ptau and A?42 with over 3000 individuals using age, gender, series, APOE ?2, APOE ?4, and two principal components for population structure as covariates. Each significant rQTL was separately screened for interactions with other loci for each trait in the rQTL model. Parametric bootstrapping was used to assess significance. RESULTS:We found four significant tau/A?42 rQTL from three unique locations and six ptau/A?42 rQTL from five unique locations. G×G screens with these rQTL produced four significant G×G interactions (one A?42, two ptau, and one tau) with four rQTL where each second locus was from a unique location. On follow-up, rs1036819 and rs74025622 were associated with Alzheimer's disease (AD) case/control status; rs15205 and rs79099429 were associated with rate of decline. CONCLUSIONS:The two most significant rQTL (rs8027714 and rs1036819) for ptau/A?42 are on different chromosomes and both are strong hits for pelvic organ prolapse. While diseases of the nervous system can cause pelvic organ prolapse, it is unlikely related to the ptau/A?42 relationship but may suggest that these two loci share a pathway. In addition to a ptau/A?42 rQTL and association with AD case/control status, rs1036819 is a strong rQTL for case/control status/A?42 and for tau/A?42. It resides in the ZFAT gene, which is related to autoimmune thyroid disease. For tau, rs9817620 interacts with the tau/A?42 rQTL rs74025622. It is in the CHL1 gene, which is a neural cell adhesion molecule and may be involved in signal transduction pathways. CHL1 is related to BACE1, which is a ?-secretase enzyme that initiates production of the ?-amyloid peptide involved in AD and is a primary drug target. Overall, there are numerous loci that affect the relationship between these important AD endophenotypes and some are due to interactions with other loci. Some affect the risk of AD and/or rate of progression.

Dataset Information

Genome-wide network-based pathway analysis of CSF t-tau/A?1-42 ratio in the ADNI cohort.

Publications

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

Similar Datasets

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