Using Systems Biology to understand Immunosenescen
  • Using Systems Biology to Understand Immunosenescence
  • Background
    • Introduction
    • 1.1. Aging in Society and in the Individual
    • 1.2. Aging and its Molecular Mechanisms
    • 1.3.The Remodeling of the Immune System: Immunosenescence
    • 1.4. Changes in the Immune System Related to Immunosenescence
    • 1.5 Chronic Inflammation During Aging: Inflammaging
    • 1.6 The Immune Risk Phenotype (IRP)
    • 1.6. Systems Biology
  • Objectives
  • Methods
    • Overall Methodology
    • 3.1 Survey of Studies
    • 3.2. Reannotation of Probes in Microarrays
    • 3.3. Data acquisition and pre-processing
    • 3.4. Creation of age-representative samples: AgeCollapsed
    • 3.5. Detection of Highly Age-Related Transcripts: AgingGenes
    • 3.6. Lifetime Co-Expressed Transcript Analysis: AgingNet
    • 3.7. Detection of Change Points in Age-Related Modules
  • Results
    • 4.1. Survey and Data Acquisition
    • 4.2. Reannotation of Platforms
    • 4.3. AgeCollapsed Pre-Processing and Creation
    • 4.4. Assessment of the Agreement of the Relationships of Transcripts with Age between the Sexes
    • 4.5. AgingGenes and AgingNet Reviews
    • 4.6 Aging Co-Expression Network: AgingNet
  • Discussion
    • Main Regards
    • AgingGenes
    • Análise de Co-Expressão: AgingNet
  • Conclusions
    • Final Regards
  • Citations
    • References
  • Appendix
    • Supplementary Files
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  1. Results

4.4. Assessment of the Agreement of the Relationships of Transcripts with Age between the Sexes

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Before any analysis, the influence of sex in the context of gene expression throughout life was evaluated to remove transcripts with different behaviours between men and women. More specifically, it was evaluated whether the transcripts had the same correlation direction (Spearman) between their expression profile and age for both sexes. For this, two datasets were created, similar to ageCollapsed, each containing only samples of each gender (1003 samples of women and 761 of men). Then, the direction of the transcripts correlated with age (|Rho| > 0.35) was evaluated and 38 transcripts with opposite directions, called SexGenes, were identified. The SexGenes, which were removed from the following analyses, are listed in the supplementary table (Appendix A - SexGenes Table) and represented by the black dots in Figure 4.5.

Figura 4.5. Concordância das Correlações entre os Sexos. Cada ponto representa um transcrito, os eixos representam os valores de correlações (Spearman) com a idade dos transcritos, para cada sexo, e as cores demonstram a intensidade da correlação.