Convergent transcriptomic and genomic evidence supporting a dysregulation of CXCL16 and CCL5 in Alzheimer's disease

Abstract

Background: Neuroinflammatory factors, especially chemokines, have been widely reported to be involved in the pathogenesis of Alzheimer's disease (AD). It is unclear how chemokines are altered in AD, and whether dysregulation of chemokines is the cause, or the consequence, of the disease.

Methods: We initially screened the transcriptomic profiles of chemokines from publicly available datasets of brain tissues of AD patients and mouse models. Expression alteration of chemokines in the blood from AD patients was also measured to explore whether any chemokine might be used as a potential biomarker for AD. We further analyzed the association between the coding variants of chemokine genes and genetic susceptibility of AD by targeted sequencing of a Han Chinese case-control cohort. Mendelian randomization (MR) was performed to infer the causal association of chemokine dysregulation with AD development.

Results: Three chemokine genes (CCL5, CXCL1, and CXCL16) were consistently upregulated in brain tissues from AD patients and the mouse models and were positively correlated with Aβ and tau pathology in AD mice. Peripheral blood mRNA expression of CXCL16 was upregulated in mild cognitive impairment (MCI) and AD patients, indicating the potential of CXCL16 as a biomarker for AD development. None of the coding variants within any chemokine gene conferred a genetic risk to AD. MR analysis confirmed a causal role of CCL5 dysregulation in AD mediated by trans-regulatory variants.

Conclusions: In summary, we have provided transcriptomic and genomic evidence supporting an active role of dysregulated CXCL16 and CCL5 during AD development.

Keywords: Alzheimer’s disease; Chemokine; Mendelian randomization; Pathology; Targeted sequencing; mRNA expression.

Fig. 1

Study design for integrative analysis and for identifying AD-associated chemokines. The mRNA expression profiling of 31 chemokine genes was analyzed by using the compiled microarray data of four brain regions (entorhinal cortex, hippocampus, frontal cortex, and temporal cortex) of AD patients and controls [41], two microarray data (GSE63060 and GSE63061) from peripheral blood of patients with mild cognitive impairment (MCI) or AD and controls [42], and expression data of AD mouse models [43]. The gene-based burden test and single-variant association analysis were performed using Han Chinese cohorts in this study and reported datasets [6, 44]. Mendelian randomization (MR) was used to assess the causal effect of the most significantly AD-associated chemokine genes on AD

Fig. 2

Upregulated mRNA expression levels of chemokine genes in brain tissues of AD patients. A–D The mRNA expression data were retrieved from the AlzData (www.alzdata.org) [41]. Data of CXCL16 was not available in the frontal cortex tissues. Data from min to max were presented by dots. The lower and upper hinges of the boxes represent the first and third quantiles, the whiskers extend from min to max, and the line represents the median. EC, entorhinal cortex; HP, hippocampus; TC, temporal cortex; FC, frontal cortex; Ns, not significant. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; two-tailed Student’s t-test

Fig. 3

Correlation of upregulated mRNA levels of Ccl5 (A), Cxcl1 (B), and Cxcl16 (C) with Aβ and tau pathology in AD mouse models. Original data were retrieved from Mouseac (www.mouseac.org) [43]. The age-related mRNA expression level was measured in 114 brain tissues from wild-type mice (WILD), 44 brain tissues from homozygous APP/PSEN1 double mutant mice (HO_TASTPM), and 45 brain tissues from mutant human MAPT mice (TAU) at different ages. The scores of Aβ pathology and tau pathology were based on 44 brain tissues of HO_TASTPM mice and 45 brain tissues of TAU mice, respectively. Error bars represent the population standard deviation. **, P < 0.01; ****, P < 0.0001; two-tailed Student’s t-test for comparison of mRNA expression between AD transgenic mice and WILD mice at month 18. The correlation between mRNA expression levels and pathology was measured using the Pearson correlation analysis. The solid and dashed lines represent the slope and the 95% confidence intervals in linear regression

Fig. 4

Upregulated mRNA expression of CXCL16 in peripheral blood of patients with MCI and AD. Datasets of (A) GSE63060 (104 controls, 80 MCI, and 145 AD patients) and (B) GSE63061 (134 controls, 109 MCI, and 139 AD patients) [42] were used for determining CXCL16 mRNA expression levels. Data from min to max were presented by dots. *, P < 0.05; **, P < 0.01; two-tailed Student’s t-test