Plasma-derived exosomal miR-34a-5p: a potential diagnostic biomarker for total colonic aganglionosis

Introduction

Hirschsprung’s disease (HSCR) is characterized by a deficiency of ganglion cells in the distal bowel, leading to delayed defecation and potentially fatal outcomes in newborns if untreated (1). The global incidence of HSCR is approximately 1 in 5,000 individuals, with a male-to-female ratio of 4:1 (2). Based on the extent of aganglionosis, HSCR is categorized into three subtypes: short-segment (80%); long-segment (15%); and total colonic aganglionosis (TCA) (3–7%) (3). In the rare subtype of TCA, ganglionic hyperplasia spans from the anus to at least 50 cm proximal to the ileocecal valve. Although TCA shares the fundamental feature of aganglionosis with other HSCR subtypes, it exhibits distinct differences that remain inadequately understood (4).

The extent of aganglionosis in HSCR does not consistently correlate with the severity of clinical symptoms. Several clinical aspects of HSCR remain unclear, creating challenges in both diagnosis and treatment. The absence of ganglion cells in the distal colon during infancy is predominantly confirmed through rectal biopsy. However, the accuracy of rectal biopsy is influenced by numerous factors and carries risks of complications such as bleeding, intestinal perforation, and infection (5). Diagnostic modalities such as contrast enema and anorectal manometry are recommended as supplementary tools for HSCR diagnosis but are limited by high false-positive rates and cannot reliably exclude the condition (1). Consequently, the development of a feasible, non-invasive diagnostic method for HSCR holds significant research value.

Exosomes are membrane-bound extracellular vesicles ranging from 30 to 100 nm in diameter, originating from endosomal pathways. Virtually all cell types can secrete exosomes under normal or stressed conditions (6). These vesicles carry various nucleic acids, including messenger RNA (mRNA) and non-coding RNAs, and play essential roles in intercellular communication, immune homeostasis, and tumor progression (7). Furthermore, exosomes are increasingly recognized as diagnostic and prognostic biomarkers for various diseases (8). Specifically, exosomal cargoes, such as long non-coding RNAs (lncRNAs) and microRNAs derived from plasma, have been dysregulated in HSCR (9,10).

The purpose of this study is to analyze the microRNA content in plasma-derived exosomes from patients with HSCR using microRNA sequencing and to predict the target genes through three commonly used databases. The identified microRNAs and their associated genes were further examined through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and interaction network analyses. Given TCA’s distinct characteristics when compared to other forms of HSCR, differentially expressed microRNAs (DEMs) between HSCR and TCA were assessed to identify changes specific to TCA. The findings of this study provide evidence supporting the potential use of plasma exosomal microRNAs as biomarkers for detecting TCA. We present this article in accordance with the STREGA reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-281/rc).

Methods

Sample collection

This study was conducted at Jiaxing Women and Children’s Hospital Affiliated to Jiaxing University and was approved by the institutional ethics committee [approval No. 2021(ethics)-88]. This study has also been registered as a bio-project on www.ncbi.nlm.nih.gov, register date: 01.28.2022, PRJNA801468). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Informed consent was obtained from all participants or their legal guardians prior to inclusion in the study. Plasma samples were collected from children diagnosed with HSCR between September 2019 and July 2022. During the same period, children without HSCR were recruited as controls.

The diagnosis of HSCR was initially confirmed through suction rectal biopsy performed prior to surgery, with postoperative pathology tests used to verify the diagnosis (10). TCA was diagnosed based on pathological findings indicating the absence of ganglion cells in colonic segments extending across the entire colon and up to 30 cm proximal to the ileocecal valve.

A total of 19 exosome samples were analyzed, comprising nine samples from children with HSCR (three of which were identified as TCA) and 10 from healthy controls. The HSCR group comprised of seven males and two females, with an average age of 5.7±0.6 months, while the normal group consisted of 10 males with an average age of 10.7±1.5 months.

Blood samples (8–10 mL) were collected into EDTA-coated collection tubes and gently mixed to ensure proper exposure to the coating of the tube. Plasma separation was conducted by centrifugation at 2,000 g for 15 minutes at room temperature using a standard clinical centrifuge. The clear plasma layer was transferred to labeled tubes and stored at −80 ℃ for subsequent analysis.

Ultracentrifugation-based exosome extraction

After rapid thawing, the plasma samples were centrifuged at 2,000 g at 4 ℃ for 30 minutes. The resulting supernatant from each sample was carefully transferred to new centrifuge tubes and subjected to further centrifugation at 12,000 g at 4 ℃ for 45 minutes. To remove large vesicles, the supernatant was filtered using a 0.45 µm filtration membrane. The filtrate was then pipetted to a new centrifuge tube and centrifuged at 110,000 g for 70 minutes at 4 ℃. Following this, the supernatant was discarded, followed by the addition of 10 mL of pre-cooled 1× PBS (Huankai Microbial, Guangzhou, China) to the pellet, which was centrifuged again at 110,000 g for an additional 70 minutes at 4 ℃. The final supernatant was resuspended in 100 µL of pre-cooled 1× PBS solution.

Isolated exosomes were resuspended in 30 µL HBSS (Biocreative, Beijing, China) and diluted with sterile PBS. Size distribution and concentration were determined on a ZetaView PMX 110 system running ZetaView 8.04.02 software. The instrument was calibrated with 110 nm polystyrene reference beads (Bioptic, Changzhou, China) and data were acquired at 11 fixed positions across the cell. Measurements were carried out at 25–27 ℃ under constant flow.

An enriched exosome suspension was diluted in filtered PBS, and 5 µL was applied to carbon-coated 200-mesh copper grids placed on Parafilm. After 1 min at room temperature, excess liquid was wicked off with filter paper. The grids were then floated on a 20-µL droplet of Uranyless^® stain (Head Biotechnology, Ltd., Beijing, China) for 1 min, blotted to remove surplus stain, and allowed to air-dry. Imaging was carried out on either a JEOL 100CX II (JEOL Ltd., Tokyo, Japan) or a Hitachi HT7800 (Hitachi High-Tech Corporation, Tokyo, Japan) transmission electron microscope operating at 100 kV. More than 90% of vesicles display cup-shaped morphology and diameters of 40–120 nm.

RNA extraction

Total RNA was extracted from exosome pellets using TRIzol reagent (Invitrogen/Life Technologies, Carlsbad, CA, USA) according to the instructions provided by the manufacturer. Exosome solution (100 µL) was lysed in 700 µL of TRIzol-LS (ABI, Foster City, CA, USA) reagent. Phase separation was conducted using 140 µL of chloroform, followed by RNA precipitation with 100% isopropanol. The RNA was then washed twice with 75% ethanol and subsequently eluted in 30 µL of RNase-free water. RNA concentration was measured using the Qsep100 system (Bioptic).

Library construction and microRNA sequencing

Following quality control, the samples were prepared for library construction using a small RNA sample preparation kit (RS-200-0012, Illumina, San Diego, CA, USA). Adaptors were directly ligated to both ends of the small RNA molecules, and reverse transcription was conducted to generate cDNA, accommodating the distinct structure of small RNA (a phosphate group at the 5' end and a hydroxyl group at the 3' end). Polymerase chain reaction (PCR) amplification, PAGE gel electrophoresis, and recycling were used to isolate the target complementary DNA (cDNA) fragment. The cDNA library was constructed using gel extraction.

To ensure quality, the prepared library was diluted to 1 ng/µL using Qubit 2.0 and assessed for insert size with an Agilent 2100 system. Library concentration was measured using qPCR, with an effective concentration threshold of >2 nM. Libraries that passed quality control were sequenced using the Illumina NovaSeq 6000 platform (Illumina).

Data pre-processing and DEMs identification

The pre-processed sequencing data were aligned to the hg38 obtained from the Ensembl database (http://ftp.ensembl.org/pub/release-104/fasta/homo_sapiens/dna/) using HISAT2 software (11). To generate the gene expression matrix, microRNA expression counts were obtained using FeatureCounts software, and FPKM values were calculated using StringTie software. DEMs between samples with HSCR and those without HSCR were identified using the R package DESeq2 (12). DEMs were defined based on the criteria of a P value <0.05 and |log₂ fold change (FC)| >1 (13).

Prediction of the target genes

The genes regulated by upregulated and downregulated DEMs with high |log₂FC| values were identified using the miRWalk repository and a retrieval system for microRNA data (14). The evaluation criteria included a score of 1, a P value <0.05, and 3'-untranslated regions as input parameters. Three frequently used databases—TargetScan, miRDB, and miRTarBase—were used to identify target genes (15-17). Target genes were selected only if they were supported by all three databases. Cytoscape software was employed to build a DEM-target interaction network for the three identified DEMs (18).

Pathway enrichment evaluation

Pathway enrichment evaluation was performed using the KEGG database (http://www.kegg.jp/), which is widely utilized for the systematic exploration of gene functions (19). Target genes associated with the selected DEMs were analyzed using the clusterProfiler package in R. A significance threshold of P<0.05 was applied to identify enriched pathways.

Quantitative real-time PCR assay

The extracted microRNAs were amplified using the Mx3000P qPCR System (Agilent, Santa Clara, CA, USA) along with the Bulge-Loop microRNA qRT-PCR Primer Set (RiboBio, Guangzhou, China). The RT reaction was conducted at 42 ℃ for 60 minutes, followed by incubation at 70 ℃ for 10 minutes. The PCR protocol consisted of an initial denaturation for 20 s at 95 ℃, followed by 40 cycles of denaturation for 10 s at 95 ℃, annealing/extension for 20 s at 60 ℃, and a final extension for 10 s at 70 ℃. Fluorescence levels of SYBR Green (QuantiTect SYBR Green RT-PCR Kit, Qiagen, Hilden, Germany) were measured to determine the concentration of PCR products.

Relative expression levels were quantified using the 2^−ΔΔCt method, normalized to cel-miR-39 as the endogenous reference. MicroRNAs in TCA samples were classified as differentially expressed if their expression levels demonstrated a fold of >1.5 or 0.67 compared to control samples and if the Wilcoxon test yielded a statistically significant P value.

Statistical analysis

Data entry was verified using a double-entry method. All statistical analyses were performed using Prism software. The normality of continuous variables was assessed using the F-test. Normally distributed data are presented as the mean ± standard deviation, while non-normally distributed data are expressed as the median (25th percentile, 75th percentile). Comparisons between groups for normally distributed variables were conducted using an independent samples t-test, whereas the Wilcoxon nonparametric test was employed for non-normally distributed variables. All tests were two-tailed, and a P value <0.05 was considered statistically significant.

Results

DEMs and their target genes analysis

By using the |log₂FC| and P value criteria, a total of 62 DEMs were identified, comprising of 31 upregulated and 31 downregulated microRNAs in patients with HSCR compared to controls, as depicted in Figure 1. Target gene prediction for these 62 DEMs was conducted using MiRWalk. Subsequently, TargetScan, miRDB, and miRTarBase assessed 884 DEM-target gene pairs corresponding to 36 DEMs. Among these, 22 upregulated DEMs were associated with 651 target gene pairs, while 14 downregulated DEMs corresponded to 233 target gene pairs. The remaining DEMs did not yield identifiable target genes under the selected search criteria.

Figure 1 Differentially expressed microRNAs. (A) The fold change and P value of all analyzed microRNAs are presented. Non-significant microRNAs are indicated in grey, while upregulated microRNAs are shown in red and downregulated microRNAs in blue. (B) t-SNE cluster analysis illustrates the grouping of two distinct cohorts: Sample A representing the control group and Sample B representing the HSCR group. (C) A heatmap depicts the expression profiles of 62 differentially expressed microRNAs. High expression levels are indicated in red, whereas low expression levels are represented in blue. HSCR, Hirschsprung’s disease.

KEGG pathway enrichment analysis was conducted on the target genes of both upregulated and downregulated DEMs. For upregulated DEMs, the target genes showed significant enrichment in cancer-associated pathways (Figure 2), including transcriptional dysregulation in prostate, pancreatic, and bladder cancers. In contrast, downregulated DEMs had fewer enriched genes and higher P values, including transcriptional dysregulation in cancer, adrenergic signaling in cardiomyocytes, and the cAMP signaling pathway.

Figure 2 KEGG pathway enrichment analyses of up-regulated and down-regulated differentially expressed microRNAs. KEGG, Kyoto Encyclopedia of Genes and Genomes.

Pathway enrichment analysis

A single microRNA can target hundreds of genes, and KEGG pathway enrichment analysis was conducted for the target genes of each upregulated and downregulated microRNA. Figure 3 depicts the KEGG pathways with P values <0.05. Among the upregulated DEMs, enrichment was observed in 14 for cancer-related proteoglycan pathways, 11 for adherens junctions, 11 for the cell cycle, 11 for the Hippo signaling pathway, and 11 for lysine degradation (as depicted in Figure 3A). In the downregulated DEMs, 10 were enriched in ECM-receptor interaction, 10 in glioma, and 9 in the Hippo signaling pathway (as depicted in Figure 3B). Notably, the fatty acid biosynthesis pathway was enriched in the target genes of both the upregulated and downregulated DEMs.

Figure 3 KEGG pathway enrichment analyses of each DEM. (A) KEGG pathway enrichment analysis of upregulated DEMs: (B) KEGG pathway enrichment analysis of downregulated DEMs. DEMs, differentially expressed microRNAs; KEGG, Kyoto Encyclopedia of Genes and Genomes.

The expression of microRNA in TCA

TCA represents a distinct subtype of HSCR. Differences in microRNA expression between TCA and other HSCR subtypes were analyzed, identifying 12 DEMs (as depicted in Figure 4A). Among these, 5 were upregulated, and 7 were downregulated. Notably, 4 of these 12 microRNAs were differentially expressed between HSCR and healthy controls (as depicted in Figure 4B).

Figure 4 Differentially expressed miRNAs among different types of Hirschsprung’s disease. (A) Heatmap of 12 DEMs: A heatmap depicting the expression levels of 12 DEMs identified between TCA and other types of HSCR. (B) Heatmap of 4 selected DEMs: a focused heatmap displaying the expression levels of 4 of the 12 DEMs that were significantly different between TCA and other HSCR subtypes. (C) qPCR analysis of miR-34a-5p expression. (D) Interaction network analysis: A network diagram illustrating the predicted target gene interactions for three selected microRNAs, emphasizing their potential regulatory roles. *, P<0.05; ****, P<0.0001. DEMs, differentially expressed microRNAs; HSCR, Hirschsprung’s disease; miRNA, messenger RNA; qPCR, quantitative polymerase chain reaction; TCA, total colonic aganglionosis.

As for miR-106b-5p and miR-375-3p, they exhibited higher expression levels in patients with HSCR compared to the control group; however, their expression levels were relatively lower in TCA compared to other HSCR subtypes. In contrast, miR-34a-5p and miR-205-5p revealed mild expression in the control group, moderate expression in other HSCR subtypes, and significantly higher expression in TCA (as depicted in Figure 4B).

To validate these findings, the expression of miR-34a-5p was further examined in plasma-derived exosome samples using quantitative reverse transcription polymerase chain reaction (qRT-PCR). The results confirmed low expression levels of miR-34a-5p in other HSCR subtypes and significantly elevated expression in TCA (as depicted in Figure 4C). Differences in age and gender have no significant impact on miRNA expression.

Interaction network analysis

Interaction networks were built for the target genes of miR-106b-5p, miR-205-5p, and miR-34a-5p, but not for miR-375-3p, due to screening criteria. The interaction network for miR-106b-5p included 97 interaction pairs, miR-205-5p was associated with 11 interaction pairs, and miR-34a-5p had 23 interaction pairs (as depicted in Figure 4D).

KEGG pathway analysis indicated that the target genes of miR-106b-5p were enriched in pathways associated with prion diseases, while those of miR-34a-5p were enriched in fatty acid biosynthesis. Beta-2 syntrophin (SNTB2) was the only shared target gene between miR-106b-5p and miR-34a-5p. Including target genes supported by at least one database increased the number of shared targets, identifying four common protein-coding genes among the three microRNAs.

The following interactions were confirmed with experimental evidence from miRTarBase: miR-205-5p targeting AF4/FMR2 family member 4 (AFF4), miR-34a-5p targeting myotubularin-related protein (MTMR), miR-106b-5p targeting myotubularin-related protein 9 (MTMR9), and miR-34a-5p targeting POU-domain class 2 transcription factor 1 (POU2F1).

Discussion

HSCR is a prevalent congenital disorder in infants, featuring impaired intestinal motility (19). Clinical manifestations often include constipation, vomiting, malnutrition, and delayed meconium excretion, which are indicative of gastrointestinal motility disorders (1). However, these symptoms can also occur in healthy children, complicating the decision-making process for appropriate diagnostic assessments. Existing diagnostic techniques for HSCR, such as rectal biopsy, contrast enema, and rectal manometry, have notable limitations. Although rectal biopsy remains the gold standard for diagnosing HSCR, it is associated with significant morbidity, affecting up to 2% of patients. The incidence of complications associated with rectal biopsy is notably higher in younger patients compared to older children (20). Consequently, the identification of reliable biomarkers that can accurately assess HSCR progression and facilitate auxiliary diagnosis is of critical importance.

Previous studies have sought to identify diagnostic biomarkers for HSCR by analyzing DEMs in the serum of affected individuals compared to controls (21). However, the heterogeneous origins of microRNAs in blood contribute to substantial variability, increasing statistical uncertainty (22). Current evidence suggests that circulating microRNAs exist either within membrane-bound vesicles, such as exosomes, or as components of protein complexes. These distinct populations of microRNAs are thought to originate from various cell types and reflect different release mechanisms (23).

The use of plasma-derived exosomes for diagnostic purposes offers several advantages. Isolation of microRNAs from plasma samples enables the bypassing of challenges such as spatial variability and difficulty in obtaining tissue samples, while allowing for the detection of HSCR progression over time. Furthermore, microRNAs encapsulated within exosomes exhibit greater stability compared to those circulating freely in blood, due to the protective exosomal bilayer structure (24).

In this study, DEMs were identified through the analysis of plasma-derived exosomes from healthy controls and patients with HSCR. A comprehensive bioinformatics approach was employed to elucidate the pathophysiology of HSCR. This analysis revealed 62 DEMs, of which 31 were upregulated and 31 were downregulated in the HSCR group. Comparative analysis between TCA and other HSCR subtypes identified miR-106b-5p, miR-205-5p, miR-375-3p, and miR-34a-5p as key microRNAs. Specifically, miR-205-5p and miR-34a-5p exhibited low expression levels in controls, moderate levels in other HSCR subtypes, and significantly elevated levels in TCA. Validation through qRT-PCR demonstrated elevated expression of miR-34a-5p in the TCA group.

Previous research has demonstrated that miR-34a-5p impedes cell migration, proliferation, and invasion (25-27). This points to the possibility that miR-34a-5p may be involved in TCA pathogenesis by interfering with the cell cycle or cancer-related pathways. RET, a critical gene implicated in HSCR pathogenesis, binds to the 3'UTR region of miR-34a-5p, according to the TargetScan database predictions. Proteins encoded by RET and associated pathways primarily influence the movement of neural crest cells through the gastrointestinal tract during embryonic development (28). The association between miR-34a-5p and RET indicates its potential involvement in TCA pathogenesis, warranting further investigation into the regulatory effects of plasma-derived exosomal miR-34a-5p on RET.

Additionally, the Ednrb/Edn3 pathway plays a key role in neural crest precursor migration from the neural tube. This pathway regulates the migration of neural crest precursors during embryonic neural development, impacting digestive tract formation (29). Interestingly, mutations in the Ednrb and Edn3 genes have been identified in cases of short-segment HSCR but are absent in the general population and in long-segment HSCR cases (30). These findings underscore the importance of investigating the interactions between miR-34a-5p, RET, and Ednrb/Edn3 pathway in elucidating the pathogenic mechanisms underlying TCA. The objective of future research should be to examine the regulatory mechanisms of these molecules in neural crest cell migration, providing a deeper understanding of the development and progression of TCA.

Over the years, numerous researchers have attempted to elucidate the pathological network underlying HSCR; however, its precise mechanisms remain incompletely understood. The complexity of the gene regulatory systems involved continues to present challenges in fully deciphering the pathophysiology of the disease. The identification of microRNAs that target mRNAs encoding components of the HSCR regulatory network holds significant potential to enhance our understanding of gene regulation during the progression of this disease.

In the current study, miR-106b-5p expression was markedly reduced in the TCA group, indicating that TCA exhibits unique molecular characteristics. Additionally, miR-106b-5p shows significant enrichment in the prion disease pathway, where it enhances cell proliferation and prevents apoptosis via regulation of B cell translocation gene 3 (BTG3) (31). The interaction network analysis of three microRNAs revealed the most complex network of predicted target genes for miR-106b-5p, further supporting its potential role in TCA pathogenesis.

MiR-205-5p and miR-106b-5p shared four target genes: AFF4, MTMR9, POU2F1, and WWC2. AFF4, a component of the super elongation complex, serves as a central scaffold that recruits other factors through direct interactions with ELL proteins and the P-TEFb complex (32). MTMR9 encodes a protein with a double-helical motif resembling the SET interaction domain, which is involved in the regulation of cell proliferation (33). During herpes simplex virus infection, POU2F1 forms a multiprotein-DNA complex with viral proteins HCFC1 and VP16, enhancing viral gene transcription in the early stages (34). WWC2 is a regulator of cell division during meiosis and early mitosis that governs cell lineage specification determination during the development of mouse blastocysts (35). The functions of these target genes suggest that the invasion of exogenous pathogens and abnormal cell differentiation might be involved in the pathogenesis of TCA.

This study still has some limitations. First of all, given the rarity of TCA, which results in a low incidence rate within the population, the sample size included in this study is relatively small. This has had a certain adverse impact on the demonstration of the conclusions. In our future research, we will continue to increase the disease sample size and explore related animal models. Furthermore, due to the lack of corresponding mechanism research, the results of this study are still at the speculative stage. In the subsequent research, we will further refine the subsequent mechanism studies to determine and verify the functional role of miR-34a-5p in TCA.

Conclusions

This study identified specific microRNAs, including miR-106b-5p, miR-205-5p, miR-375-3p, and miR-34a-5p, as selectively enriched in exosomes derived from patients with HSCR. Notably, miR-34a-5p demonstrated significantly elevated levels in the plasma of patients with TCA. These findings suggest that circulating exosomal microRNA profiles hold potential as companion diagnostic tools for TCA, which is hoped to surpass and replace enema and rectal manometry, playing a more important role in the diagnosis of TCA. And it has a lower false positive rate. However, the final diagnosis still relies on a biopsy. Future studies should prioritize the functional characterization and mechanistic investigation of these microRNAs and their target genes, both in human colon tissues and relevant animal models.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STREGA reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-281/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-281/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-281/prf

Funding: This study was supported by Medical Health Science and Technology Project of Zhejiang Provincial Health Commission (No. 2022KY390).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-281/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was approved by the institutional ethics committee of Jiaxing Women and Children’s Hospital Affiliated to Jiaxing University [approval No. 2021(ethics)-88]. This study was conducted in accordance with the declaration of Helsinki and its subsequent amendments. Informed consent was obtained from all participants or their legal guardians prior to inclusion in the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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