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

4.1. Survey and Data Acquisition

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Searches carried out in the databases using the keywords “human”, “whole blood”, “pbmc” and “peripheral blood” resulted in 87 potential studies. After applying the inclusion criteria defined in Section 3.1, only 12 studies were selected for analysis, as shown in Table 1.

Table 1 - List of studies selected for analysis.

*Número de Amostras Controle. Células em branco nas colunas de gênero são informações ausentes ou não informativas, como 0 ou 1.

Estudo

Base de Dados

Empresa

Plataforma

Tecido

N. Amostras*

Idade Mínima

Idade Máxima

N. Mulheres

N. Homens

GSE73089

GEO

Agilent

GPL4133

PBMC

120

40

97

64

56

E-TABM-305

Array Express

Illumina

A-MEXP-691

linfócitos

1240

14

81

GSE15573

GEO

Illumina

GPL6102

PBMC

15

45

67

10

5

GSE48556

GEO

Illumina

GPL6947

PBMC

33

44

76

24

9

GSE54514

GEO

Illumina

GPL6947

sangue total

36

24

70

24

12

GSE12288

GEO

Affymetrix

GPL96

sangue total

112

37

68

28

84

GSE18781

GEO

Affymetrix

GPL570

sangue total

25

22

83

20

5

GSE42057

GEO

Affymetrix

GPL570

PBMC

42

46

80

GSE22255

GEO

Affymetrix

GPL570

PBMC

20

45

73

10

10

GSE19314

GEO

Affymetrix

GPL570

PBMC

20

34

70

15

5

GSE16028

GEO

Affymetrix

GPL570

sangue total

109

23

64

59

50

GSE46097

GEO

Affymetrix

GPL571

sangue total

63

41

80

36

27

The selected studies are of 3 subtypes of blood tissue, performed on 7 different microarray platforms (Figure 4.1), from 3 companies (Agilent, Illumina and Affymetrix) and totalling 1835 samples.

Figura 4.1. Quantidade de Dados Disponíveis por Plataforma. Gráficos de barras representado quantidade de estudos (A) e amostras (B) para cada plataforma.