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. 2026 Jan;23(1):e00792.
doi: 10.1016/j.neurot.2025.e00792. Epub 2025 Nov 19.

Butyrate modifies epigenetic and immune pathways in peripheral mononuclear cells from children with neurodevelopmental disorders associated with chromatin dysregulation

Affiliations

Butyrate modifies epigenetic and immune pathways in peripheral mononuclear cells from children with neurodevelopmental disorders associated with chromatin dysregulation

Jessica P Hayes et al. Neurotherapeutics. 2026 Jan.

Abstract

Pathogenic DNA variants in chromatin-related genes constitute an important minority of neurodevelopmental disorders (NDDs). Epigenetic mechanisms, including chromatin regulation driven by genetic or environmental factors, are increasingly recognised as key contributors to pathogenesis of diverse NDDs. We hypothesise that therapeutic strategies targeting chromatin dysregulation, such as histone deacetylase inhibition with butyrate, may be a potential disease modifying therapy for NDDs. We first performed peripheral blood bulk RNA sequencing (RNA-seq) to explore baseline gene regulation in children with chromatin-related NDDs (Kabuki syndrome (KMT2D, n ​= ​4), CHARGE syndrome (CHD7, n ​= ​2), and Rett syndrome (MECP2, n ​= ​5), and children with NDDs but without a monogenic diagnosis (non-monogenic, n ​= ​8), compared with sex-matched healthy controls (total n ​= ​21). Next, to explore the effects of butyrate, single-cell RNA sequencing (scRNA-seq) was performed on 101,539 peripheral immune cells from four selected patients (one per condition) and two controls, before and after butyrate treatment. At baseline, dysregulation of ribosomal and immune pathways was seen in all four NDD cohorts (KMT2D, CHD7, MECP2, non-monogenic) compared to controls. Butyrate largely reversed these pathways, normalising ribosomal and immune pathways in patient and control cells. Butyrate induced up-regulation of ribosome, GTPase, cytoskeletal, mitochondrial pathways, and down-regulation of epigenetic and immune pathways. In conclusion, we identified a common ribosomal-immune RNA signature in chromatin-related NDDs, and a similar signature in non-monogenic NDDs. We showed that butyrate modulates epigenetic and immune gene networks in monogenic and non-monogenic NDDs, positioning butyrate as a promising therapeutic modulator across diverse NDDs.

Keywords: Butyrate; Chromatin; Epigenetics; Histone deacetylase inhibition; Neurodevelopmental disorders; Neuroregression.

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Conflict of interest statement

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Russell Dale reports financial support was provided by National Health and Medical Research Council. Russell Dale reports financial support was provided by Petre Foundation. Russell Dale reports financial support was provided by National Foundation for Medical Research and Innovation. Russell Dale reports financial support was provided by Avant Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Top five up- (red) and down-regulated (blue) ORA GO pathways in bulk RNA sequencing of whole blood from NDD cohorts versus controls. The level of pathway enrichment is determined by -log10(FDR), where significant pathways have an FDR <0.05. The comparison of KMT2D cohort (n ​= ​4) versus controls (n ​= ​18) is presented as bar plots for (A) the top 5 upregulated ORA GO pathways (red), including immune and cellular function pathways, and (B) the top 5 downregulated ORA GO pathways (blue) including ribosomal and translation pathways. The comparison of CHD7 cohort (n ​= ​2) versus controls (n ​= ​14) is presented as bar plots for (C) the top 5 upregulated ORA GO pathways (red), including immune and cellular function pathways, and (D) the top 5 downregulated ORA GO pathways (blue) including ribosomal and mitochondrial pathways. The comparison of MECP2 cohort (n ​= ​5) versus controls (n ​= ​14) is presented as bar plots for (E) the top 5 upregulated ORA GO pathways (red), including immune and cellular function pathways, and (F) the top 5 downregulated ORA GO pathways (blue) including RNA pathways. The comparison of non-monogenic NDD cohort (n ​= ​8) versus controls (n ​= ​8) is presented as bar plots for (G) the top 5 upregulated ORA GO pathways (red), including immune and cellular function pathways, and (H) the top 5 downregulated ORA GO pathways (blue) including ribosomal and translation pathways.
Fig. 2
Fig. 2
Dot plot visualising the top 5 upregulated and downregulated ORA GO pathways in bulk RNA sequencing of whole blood from NDD cohorts versus controls. The top 5 upregulated and downregulated ORA GO pathways for each cohort were selected as representative GO terms. For comparison, significant pathways were also shown across all other cohorts relative to controls in the dot plot, even if they were not among the top five in those cohorts. Each cohort is labelled on the axis as KMT2D (n ​= ​4), CHD7 (n ​= ​2), MECP2 (n ​= ​5) or non-monogenic (n ​= ​8), and are compared to their respective healthy matched control groups (n ​= ​18, n ​= ​14, n ​= ​14, n ​= ​8, respectively). Red dots represent upregulated pathways, and blue dots represent downregulated pathways. The size of the dot represents the significance of pathway enrichment determined by -log10(padj) value, where padj is the adjusted p value. Enriched pathways are labelled on the left-hand y-axis. The pathways are clustered together based on similar function and then ranked according to enrichment. The pathways clusters are indicated by shading on the dot plot and labels to the right of the dot plot.
Fig. 3
Fig. 3
Dot plots visualising the top 10 upregulated and downregulated ORA GO pathways in untreated patient versus control PBMCs, and butyrate-treatedversus untreated patient PBMCs. The top 10 upregulated and downregulated ORA GO pathways for T cells and bulk cells were selected as representative GO terms and are presented on the dot plots. Both bulk analysis and T cell analysis are included, as labelled on the x-axis. The left-hand columns present the untreated patient versus control pathways, and the right-hand columns present the butyrate-treated versus untreated patient pathways. Red dots represent upregulated pathways, and blue dots represent downregulated pathways. The size of the dot represents the significance of pathway enrichment determined by -log10(padj) value, where padj is the adjusted p value. The pathways are clustered together based on similar function and then ranked according to enrichment. The pathway clusters are indicated by shading on the dot plot and labels to the right of the dot plot. There are separate plots for each NDD patient: (A)KMT2D (n ​= ​1), (B)CHD7 (n ​= ​1), (C)MECP2 (n ​= ​1), (D) Non-monogenic (n ​= ​1).
Fig. 4
Fig. 4
System wide effects of butyrate treatment on PBMCs from the selected non-monogenic NDD case. (A) Functional network groupings of top 10 enriched GO terms from each ontology (biological process, molecular function and cellular component) in butyrate-treated versus untreated PBMCs from the non-monogenic patient comparison. Gene set size (number of genes) is represented by the size of the dot and edges represent the overlap between gene sets. Upregulated GO pathways are represented in red and downregulated GO pathways are represented in blue. (B) Comparison of average expression of IFITM3, CX3CR1, FCGR3A, ISG15 immune genes between control PBMCs, NDD patient PBMCs and butyrate-treated NDD patient PBMCs. Statistical significance (p value) is indicated as line above graphs. Note difference in y-axis for ISG15.

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