Figure 1.
Pathways associated with activation of toll-like receptors TLR-2 and TLR-4, the IL-1 receptor IL-1R1, and the TNFα receptor, TNFRSF1A.
IL-1β binding to the IL-1R1 leads to recruitment of IL-1 receptor accessory protein (IL-1RAP), and can be blocked by the naturally occurring IL-1 receptor antagonist, IL-1RN. The IL-1R1/1β/RAP signaling complex is capable of recruiting interleukin receptor-associated kinase (IRAK), IL-1 receptor accessory protein (IL-1RAP), and myeloid differentiation factor 88 (MYD88). IRAK can be phosphorylated and subsequently dissociate from the receptor complex to interact with tumor necrosis factor receptor-associated factor (TRAF6) and TGF-β activated kinase 1 (TAK1)/MAP3K7 binding protein 2 (TAB2) complex. The TLR2 and TLR4 cascades are simplified in Figure 1 into a single cascade. However, gram-negative bacterial lipopolysaccharide (LPS) can activate TLR4, which associates with lymphocyte antigen-96 (MD-2) while gram-positive bacteria are recognized by TLR2 [115]. Their activation effects converge with those of the IL-1R and TNFα receptor on the TRAF6 complex. IL-1R and all TLRs except TLR3 exhibit the same Toll/interleukin-1 receptor (TIR) region that allows recruitment of MYD88 upon activation [116]. Nuclear I kappa kinase (NIK) and various mitogen-activated protein kinases (MAPKs) can promote activation of cytoplasmic nuclear factor-kappa B (NF-κB). Activated NF-κB then can enter the nucleus of the cell to regulate transcription of various genes by binding to their promoter regions. RELA (p65) and p50, proteins in NF-κB family; AP-2: transcription factor AP-2 alpha (activating enhancer binding protein 2 alpha); A20: tumor necrosis factor, alpha-induced protein 3; NFKBIA: nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha; COX-2: cyclooxygenase-2; cPLA2: phospholipase A2 (cytosolic, calcium-dependent); sPLA2: phospholipase A2 (secretory).
Figure 2.
Statistically significant correlations with age in Development and/or Aging intervals.
Graphical identification of genes with statistically significant (p<0.05) Pearson r correlations in expression level during Development (x axis) and Aging (y axis) intervals. Gene expressions negatively correlated with age during Development are to the left, while genes positively correlated are to the right of the vertical line. Genes that were negatively correlated with age in the Aging group are below the horizontal line, while genes positively correlated are above line. Development: n = 87; Aging: n = 144.
Figure 3.
Significant linear regressions of gene expression during both Development and Aging intervals (top), and Aging interval alone (bottom).
Scatterplots illustrating log2 gene expression over age in years. An increase or decrease of 1 on the log2 scale (y-axis) represents a two-fold change in gene expression in the positive or negative direction, respectively. Each data point represents observation from one brain (Development: n = 87; Aging: n = 144). Gene name (p-value during Development, p-value during Aging) - CX3CR1 (p<0.0001, p<0.0001), NGF (p = 0.006, p = 0.002), MOBP (p<0.0001, p = 0.02), NFκB1 (p = 0.01, p = 0.01), SNCA (p<0.0001, p = 0.002). Genes significant in only Aging interval – GFAP (p<0.0001), TSPO (p = 0.006), BDNF (p<0.0001), PTGS2 (p = 0.0003), CX3CR1 (p = 0.03).
Figure 4.
Nonlinear fits for expression levels with age of eight genes during Development.
Fitted line added to expression data following equation for 0 to 21 years, Y = (Y0−Plateau)*exp(−K*A)+Plateau, where Y = expression level at age A, and Y0 expression level at A = 0 years). An increase or decrease of 1 on the log2 scale (y-axis) represents a two-fold change in expression in the positive or negative direction, respectively.
Table 1.
Statistically significant mean gene expression differences between Aging and Development Periods (Multiple ANOVA results).
Figure 5.
Similarity matrices (hierarchically clustered heat maps) of Pearson's r correlations of gene expression levels with age in Development (A) and Aging (B) groups.
Red indicates negatively correlated associations; green are positively correlated associations, while black represents non-significant associations between gene pairs. Genes are clustered hierarchically along the left y-axis, which is mirrored above in each heat map.
Table 2.
Highly significant (r≥|0.6|) pair-wise correlations in age-related gene expression during Development and Aging intervals.