Hippocampal subregions exhibit both distinct and shared transcriptomic responses to aging and nonneurodegenerative cognitive decline

Abstract

Impairment of hippocampal-dependent spatial learning and memory with aging affects a large segment of the aged population. Hippocampal subregions (CA1, CA3, and DG) have been previously reported to express both common and specific morphological, functional, and gene/protein alterations with aging and cognitive decline. To comprehensively assess gene expression with aging and cognitive decline, transcriptomic analysis of CA1, CA3, and DG was conducted using Adult (12M) and Aged (26M) F344xBN rats behaviorally characterized by Morris water maze performance. Each subregion demonstrated a specific pattern of responses with aging and with cognitive performance. The CA1 and CA3 demonstrating the greatest degree of shared gene expression changes. Analysis of the pathways, processes, and regulators of these transcriptomic changes also exhibit a similar pattern of commonalities and differences across subregions. Gene expression changes between Aged cognitively Intact and Aged cognitively Impaired rats often showed an inversion of the changes between Adult and Aged rats. This failure to adapt rather than an exacerbation of the aging phenotype questions a conventional view that cognitive decline is exaggerated aging. These results are a resource for investigators studying cognitive decline and also demonstrate the need to individually examine hippocampal subregions in molecular analyses of aging and cognitive decline.

Keywords: Aging; Cognitive impairment.; Gene expression; Hippocampus.

Figure 1.

Relationship between hippocampal subregion transcriptomes with aging. (A) The majority of genes detected as expressed in Adult animals were detected in each subregion, but transcripts specific to each subregion were also observed. Additional transcripts were detected in two of the three subregions with CA1 and CA3 sharing more commonly expressed genes than the DG. When subjected to hierarchical clustering (each color-coded line represents an individual animal), the expression pattern of detected genes was more similar between CA1 and CA3. Similarly, when visualized in a principal component analysis, each subregion separated uniquely, with the pyramidal regions (CA1 and CA3) demonstrating a more similar overall pattern of gene expression than with the DG. (B) A similar pattern of commonly expressed and subregion-specific gene expression was observed in Aged animals.

Figure 2.

Aging-related changes in gene expression. (A) Differences in gene expression with aging were determined for each. The most changes were identified in CA1, followed by CA3 and DG (circle areas are proportional). Both when examined as total changes (A) and when separated into upregulated (B) and downregulated (C) changes, more commonalities were evident between CA1 and CA3 than with the DG. In every case, expression changes common to CA1 and CA3 (highlighted in red) occurred in the same direction. (D) When age-related changes in each subregion were compared to changes observed in the second cohort from a whole hippocampus dissection, only minority of the subregion changes could be observed.

Figure 3.

Pathway, function, and regulatory analysis of transcriptomic changes. Age-related gene expression changes were analyzed with Ingenuity Knowledge Base for differentially regulated pathways (A), functions (B), and regulators (C). The significance of the association between the data set and canonical pathways was measured in two ways: (1) a ratio of the number of molecules from the data set that map to the pathway divided by the total number of molecules that map to the canonical pathway is displayed and (2) Fisher’s Exact Test was used to calculate a p value determining the probability that the association between the genes in the dataset and the canonical pathway is explained by chance alone. A subset of commonly regulated functions and pathways is shown. For regulation analysis, the manner of change was included to determine where sets of genes where coordinately regulated. The likelihood of the association given the data set was assessed by Fisher’s Exact Test, ***p < .001, **p < .01, *p < .05. Z-scores are based on prior knowledge of known regulatory functions and direction of changes in the current dataset. Z-scores >2 indicate significant activation with aging and <−2 indicate significant inhibition with aging. Examples of common regulators in CA1, CA3, and DG are shown.

Figure 4.

Confirmation of selected target genes by qPCR. Genes identified as regulated with age in the microarray analysis in multiple hippocampal subregions (A) or in only one subregion (B) were confirmed by gene-specific qPCR. ***p < .001, **p < .01, *p < .05, t-test by region with Benjamini–Hochberg multiple testing correction. Arhgap9 = Rho GTPase activating protein 9; Bmp7 = bone morphogenetic protein 7; Cobl = cordon-bleu protein; EMP3 = epithelial membrane protein 3; Fgf12 = fibroblast growth factor 12; Fxyd1 = FXYD domain containing ion transport regulator 1; Fxyd3 = FXYD domain containing ion transport regulator 3; Glra2 = glycine receptor, alpha 2; Gipr = gastric inhibitory polypeptide receptor; Hapln2 = hyaluronan and proteoglycan link protein 2; Ms4a6a = membrane-spanning 4-domains, subfamily A, member 6A; Ncf1 = neutrophil cytosolic factor 1; Prg4 = proteoglycan 4.

Figure 5.

Cognitive impairment-related changes in gene expression. (A) Differences in gene expression between Aged Intact and Aged Impaired were determined for each subregion. A similar number of changes were observed in CA1 and CA3 with limited coregulation overlap between CA1 and CA3 (B and C) and none with DG. Age-regulated and cognition-regulated genes within each brain region were compared (D–F) and only a small number of genes were identified as regulated with both aging and cognition. These common genes in each subregion (G–I) in all cases, but one demonstrated an opposing direction of change with aging and cognitive impairment.

Figure 6.

Pathway, function, and regulatory analysis of cognition-related changes. A moderate number of pathways, functions, and upstream regulators were identified from the cognition-related gene expression changes. Among the pathways (A) with a significant overrepresentation in cognition-related changes, some of the same pathways (eg, Complement and Fcγ phagocytosis) as the age-related analysis were evident, with additional novel pathways not observed in the aging analysis. In the functional analysis (B), a similar pattern of functions observed with aging and novel functions were observed. Importantly, functions observed with aging were predicted to be inversely affected with cognition than was observed with aging (eg, leukocyte migration and quantity of Ca²⁺). Analogously, upstream regulators identified (C) were oppositely affected in cognitively Impaired and Intact rats (eg, INFG and TRIM24). The likelihood of the association given the data set was assessed by Fisher’s Exact Test, ***p < .001, **p < .01, *p < .05. Z-scores are based on prior knowledge of known regulatory functions and direction of changes in the current dataset. Z-scores >2 indicate activation with cognitive impairment and <−2 indicate inhibition with cognitive impairment.

Figure 7.

Orthoginal confirmation of cognition-related suppression of transthyretin. Transthyretin (Ttr) expression (A) was confirmed across all three groups and brain regions. In both the CA3 and DG, a significantly lower level of Ttr expression was observed, with a similar trend in CA1 (analysis of variance, SNK post hoc **p < .01, *p < .05, n = 5–7 Aged, n = 8–9 Aged Intact, n = 11–12 Aged Impaired). To treat the behavioral performance as a continuum rather than as two populations, Ttr expression was correlated to behavioral performance in Aged animals. In both the CA3 (B) and DG (C), Ttr expression negatively correlated to mean proximity to platform distance in the probe trial, that is, lower Ttr expression was associated with worse behavioral performance. Pearson correlation, *p < .05, **p < .01, n = 21 CA3, n = 19 DG.