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  1. AU="He, Yi Jie"
  2. AU="Sarkar, Bidhan Chandra"
  3. AU="Glenn, Christensen"
  4. AU="Korobov, A. A."
  5. AU="Farzaneh Ashrafi"
  6. AU="Mitamura, Yasuhito"
  7. AU="Mayfield, Margaret M"
  8. AU="Rebsomen, L"
  9. AU="Abtie Abebaw"
  10. AU="Treitz, Christian"
  11. AU=Abd-Elsayed Alaa
  12. AU="Vesajoki, Marja" AU="Vesajoki, Marja"
  13. AU=Lewiecki E Michael
  14. AU=von Bubnoff Nikolas
  15. AU="Tang, Walfred W C"
  16. AU=Hashitani Hikaru
  17. AU="Löw, Martina"
  18. AU="Robertson, Leon S"
  19. AU="Wright, Aaron T"
  20. AU="Jones, T. B."
  21. AU=Shirtliff Mark E.
  22. AU="Riis, Kamilla R"
  23. AU="Xu, Leyao"
  24. AU="Udayakumar, Karthikrajan Parasuraman"
  25. AU="Fry, Brian"

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  1. Artikel: Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis.

    Wang, Yong Heng / Luo, Pan Pan / Geng, Ao Yi / Li, Xinwei / Liu, Tai-Hang / He, Yi Jie / Huang, Lin / Tang, Ya Qin

    Frontiers in aging neuroscience

    2023  Band 15, Seite(n) 1183119

    Abstract: Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult ...

    Abstract Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.
    Sprache Englisch
    Erscheinungsdatum 2023-06-21
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2558898-9
    ISSN 1663-4365
    ISSN 1663-4365
    DOI 10.3389/fnagi.2023.1183119
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: Discovery and validation of Ferroptosis-related molecular patterns and immune characteristics in Alzheimer's disease.

    He, Yi-Jie / Cong, Lin / Liang, Song-Lan / Ma, Xu / Tian, Jia-Nan / Li, Hui / Wu, Yun

    Frontiers in aging neuroscience

    2022  Band 14, Seite(n) 1056312

    Abstract: Background: To date, the pathogenesis of Alzheimer's disease is still not fully elucidated. Much evidence suggests that Ferroptosis plays a crucial role in the pathogenesis of AD, but little is known about its molecular immunological mechanisms. ... ...

    Abstract Background: To date, the pathogenesis of Alzheimer's disease is still not fully elucidated. Much evidence suggests that Ferroptosis plays a crucial role in the pathogenesis of AD, but little is known about its molecular immunological mechanisms. Therefore, this study aims to comprehensively analyse and explore the molecular mechanisms and immunological features of Ferroptosis-related genes in the pathogenesis of AD.
    Materials and methods: We obtained the brain tissue dataset for AD from the GEO database and downloaded the Ferroptosis-related gene set from FerrDb for analysis. The most relevant Hub genes for AD were obtained using two machine learning algorithms (Least absolute shrinkage and selection operator (LASSO) and multiple support vector machine recursive feature elimination (mSVM-RFE)). The study of the Hub gene was divided into two parts. In the first part, AD patients were genotyped by unsupervised cluster analysis, and the different clusters' immune characteristics were analysed. A PCA approach was used to quantify the FRGscore. In the second part: we elucidate the biological functions involved in the Hub genes and their role in the immune microenvironment by integrating algorithms (GSEA, GSVA and CIBERSORT). Analysis of Hub gene-based drug regulatory networks and mRNA-miRNA-lncRNA regulatory networks using Cytoscape. Hub genes were further analysed using logistic regression models.
    Results: Based on two machine learning algorithms, we obtained a total of 10 Hub genes. Unsupervised clustering successfully identified two different clusters, and immune infiltration analysis showed a significantly higher degree of immune infiltration in type A than in type B, indicating that type A may be at the peak of AD neuroinflammation. Secondly, a Hub gene-based Gene-Drug regulatory network and a ceRNA regulatory network were successfully constructed. Finally, a logistic regression algorithm-based AD diagnosis model and Nomogram diagram were developed.
    Conclusion: Our study provides new insights into the role of Ferroptosis-related molecular patterns and immune mechanisms in AD, as well as providing a theoretical basis for the addition of diagnostic markers for AD.
    Sprache Englisch
    Erscheinungsdatum 2022-11-23
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2558898-9
    ISSN 1663-4365
    ISSN 1663-4365
    DOI 10.3389/fnagi.2022.1056312
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Zusatzmaterialien

    Kategorien

    Über subito bestellen

    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

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