In this study we investigated enriched immune and inflammatory pathways in post-mortem brain tissue of individuals with ASD and TS, as well as pathways common to both disorders. Differential gene expression of the PFC region in ASD revealed that the majority (912 genes) of the top selected 1000 DEGs were up-regulated compared to normal controls. Analogous to this, in the striatum of TS, the majority (711 genes) of the identified top 1000 DEGs were also up-regulated compared to normal controls. This analysis validates the previous studies of up-regulated genes in post-mortem brains of individuals with ASD and TS28, 42.
The identified dominant signal of immune response and inflammation from the ASD GO enrichment analysis, aligns with studies investigating brain transcriptome and pathology of individuals with ASD, and supports the involvement of astrocytes and activated microglia26, 42, 43. Of interest, the top GO term (by FDR) was response to lipopolysaccharide (LPS), a TLR4 agonist which stimulates an aberrant innate immune response in preclinical and clinical studies of NDDs44, 45. For example, studies have highlighted a differential innate immune response when monocytic cells from children with ASD are treated with LPS, characterised by dysregulated levels of cytokines including IL1B, vital in the neuro-immune crosstalk46–48.
The enriched pathways established by the KEGG and Reactome analyses in the ASD cases identified major cellular pathways with therapeutic potential. The differential expression of central immune genes comprising cytokines, and CD cell markers (such as IL1B, IL6, CD80, CD40), support the reports of dysregulated cytokine levels in brains of individuals with ASD25, 49. Next, involvement of complement genes vital in phagocytosis (C1QB, C1QC, C1R, C1S), which play a central role in immunity, response to infection as well as synaptic pruning, further implicate the involvement of the immune system in ASD50–52. In addition, the enrichment of histone subunits fundamental to gene expression and epigenetic regulation (H3C13, H3C7, H2BC11, H2BC3), supports the concept of potential association between epigenetic regulation and inflammation53.
Analysis of the TS differentially expressed genes using GO identified numerous enriched immune response and inflammatory signalling terms. The enriched pathways highlighted by the KEGG and Reactome analyses in TS identified up-regulated DEGs involved in the immune response such as cytokine signalling (IL1B, CXCL10, TNF, CCL2)24. In addition, pathways involving genes within major histocompatibility complexes II (i.e., ICAM1, HLA-DRB1, HLA-DOA) and the complement system (i.e., complement components C3, C1, and complement factor B) were enriched. These findings were similarly observed in the original analysis of these TS cases28.
Given the substantial comorbidity and overlap between NDDs, we identified genes and pathways common to both ASD and TS. We identified 133 common DEGs, five of which were determined hub genes: CSF2RB, HCK, HCLS1, LCP2, and PLEK, which were all up-regulated in both disorders. Interestingly, the first four genes are either tyrosine kinases or associated with tyrosine kinase activity, and the fifth is a protein kinase substrate, which are key regulatory proteins involved in cell signalling, and are therapeutically targetable54, 55. The use of tyrosine kinase modulators in many oncologic diseases is well established, however these agents have also shown promise in preclinical models of non-oncologic neurological disorders such as Alzheimer’s disease and Parkinson’s disease, where inflammation and microglia are central to the pathogenesis55–57.
Our investigation has confirmed immune and inflammatory pathways are commonly enriched by up-regulated genes in ASD and TS. To further explore these intersecting findings, the 133 genes common to ASD and TS were analysed separately, which repeatedly identified enriched inflammatory pathways involving cytokine signalling and the complement system. These pathways involved immune genes (IL1B, ICAM1, and JAK3) and genes of the complement system (C1QB, C1QC, C4B), the latter of which is particularly relevant to NDDs, due to the importance of complement in neurodevelopmental processes such as neurogenesis and synaptic pruning58. We utilised this approach as it allowed for comparison of the same genes within both disorders, while employing the distinct p values from each analysis, offering insight into the strength of each disorder’s signal.
Our current study identified commonly enriched inflammatory pathways, however, several questions regarding the involvement of the immune response in ASD and TS remain unanswered. The cause of the identified inflammatory signals is still ambiguous, in addition to its nature. Research investigating the source of inflammation in NDDs has suggested it is an environmental or secondary component, rather than genetic28, 42. In particular, the influence of MIA, which could create a neuroinflammatory environment in offspring, may alter immune signalling pathways and epigenetic control of cell function during the critical periods of development16. In addition, the identified inflammatory signal might be casual and pathogenic, or alternatively reactive or protective in origin, which cannot be deduced from the current investigation. Further functional and mechanistic explorations of tissue from individuals with NDDs might elucidate the nature of this inflammation.
Despite our findings, this study has a number of caveats. Firstly, our analysis involved different brain regions from the two disorders, prefrontal cortex for ASD, and caudate and putamen for TS, as corresponding brain region data was not available for the two disorders at the time of analysis.
Secondly, the majority of the samples within the two datasets were not children, as cohorts of paediatric post-mortem brain samples are scarce. Therefore, our analysis represents late-stage disease, and it is unclear if the findings will be reflected in younger cohorts. It is not known whether the inflammatory signal seen in ASD and TS accumulates over the course of life, or is present in childhood.
Finally, the approach taken to identify differentially expressed genes differs from other statistical analysis often used in DGE analysis. Most cases of ASD and TS, along with other NDDs, are understood to involve the accumulation of many common risk variants in converging biological pathways, therefore we analysed the DGE of the top 1000 genes rather than employing a stringent statistical cut-off in order to unravel a wide range of genes. Although this approach may identify false positives where individual genes are not statistically dysregulated, it improves the cumulative power of pathway analysis, enabling many genes with small changes to be included.