2026 ECNP Congress

PS02-2147

Peripheral blood miRNA profiling by next-generation sequencing identifies a three-marker diagnostic panel for regressive autism spectrum disorder

Ozan Emre Aslan — B. Kardaş, T. Özer, C. Uğurtaş, T. Karakuş Aslan, T. Karakuş Aslan, N. Çine · Kocaeli University, Child and Adolescent Psychiatry, Kocaeli, Türkiye

Introduction

Autism spectrum disorder (ASD) affects approximately 1 in 31 children in the United States [1], yet substantial clinical heterogeneity hinders the development of targeted interventions. Roughly 30% of children with ASD exhibit a regressive phenotype, characterised by loss of previously acquired language and social skills typically between 15 and 30 months. Although regressive and non-regressive subtypes show comparable severity on standardised measures, they may represent distinct neurobiological trajectories. Current diagnostic algorithms rely on chromosomal microarray and FMR1 testing, with limited molecular yield in idiopathic cases [2]. While salivary and plasma miRNA studies have proposed peripheral biomarker panels for ASD as a whole [3,4], no peripheral molecular biomarker currently distinguishes the two subtypes. This is the first NGS-based small RNA sequencing study comparing regressive and non-regressive phenotypes in peripheral blood.

Aims

To identify peripheral blood miRNA biomarkers distinguishing regressive from non-regressive ASD using unbiased next-generation sequencing and to evaluate their diagnostic performance individually and as a combined panel.

Methods

Small RNA sequencing was performed on peripheral blood from 33 male participants aged 2-6 years: regressive ASD (n=12), non-regressive ASD (n=12), and typically developing controls (n=9). ASD diagnosis was confirmed using DSM-5 criteria and the Childhood Autism Rating Scale (CARS). Regression status was determined through a structured 21-item questionnaire covering communication, social, functional and motor domains. RNA extraction, NEBNext Small RNA library preparation and Illumina NovaSeq sequencing (50 bp single-end) were performed under standardised conditions. From 2,276 reference miRNAs, 304 passed quality filtering. Differential expression was analysed using edgeR with TMM normalisation and Benjamini-Hochberg FDR correction. Group comparisons used Kruskal-Wallis with Dunn post-hoc tests. Biomarker potential was assessed by ROC analysis with Youden’s J index; combined panels by logistic regression. Effect sizes were calculated using Cliff’s delta.

Results

Six miRNAs showed significant differential expression across groups (Kruskal-Wallis, p<0.05): hsa-miR-6852-5p, miR-100-5p, miR-328-3p, miR-495-3p, miR-433-3p, and miR-543-3p. Hsa-miR-6852-5p demonstrated the highest individual performance (AUC=0.944; sensitivity 83.3%; specificity 100%), representing the first report of this miRNA in any neurodevelopmental context. Hsa-miR-100-5p uniquely differentiated regressive from non-regressive ASD (Cliff’s delta=−0.528; 2.6-fold downregulation), with AUC=0.880 versus controls and AUC=0.764 versus non-regressive ASD. Logistic regression revealed that miR-100-5p alone achieved 76.2% accuracy; adding miR-6852-5p increased accuracy to 90.5% (Nagelkerke R²=0.766). A three-marker panel incorporating miR-139-5p achieved AUC=0.981 with 91.7% sensitivity and 100% specificity. Clinically, miR-100-5p correlated with CARS object use subscore (rho=+0.539; p=0.007) and CARS total score (rho=+0.427; p=0.038). Co-regulation analysis identified two miRNA clusters: a 14q32 DLK1-DIO3 imprinted locus cluster, previously implicated in neurodevelopmental imprinting disorders [5], and a sensory-neural miR-183/96/182 cluster.

Conclusions

This study presents the first NGS-based peripheral blood miRNA investigation distinguishing regressive from non-regressive ASD. The identification of miR-6852-5p as a novel ASD-associated miRNA and miR-100-5p as a regressive-specific biomarker provides new molecular insight into autism heterogeneity. The three-marker panel offers a potential blood-based diagnostic tool; independent qRT-PCR validation is planned. The established role of miR-100-5p as a translational suppressor of the mTOR pathway positions mTOR-targeted pharmacotherapy, including repurposing of clinically-approved agents such as everolimus, as a candidate strategy warranting investigation in regressive ASD.

References

  1. Shaw, K.A., Williams, S., Patrick, M.E., Valencia-Prado, M., Durkin, M.S., Howerton, E.M., et al., 2025. Prevalence and Early Identification of Autism Spectrum Disorder Among Children Aged 4 and 8 Years — Autism and Developmental Disabilities Monitoring Network, 16 Sites, United States, 2022. MMWR Surveill. Summ. 74 (2), 1-22.
  2. Tammimies, K., Marshall, C.R., Walker, S., Kaur, G., Thiruvahindrapuram, B., Lionel, A.C., et al., 2015. Molecular diagnostic yield of chromosomal microarray analysis and whole-exome sequencing in children with autism spectrum disorder. JAMA 314 (9), 895-903.
  3. Hicks, S.D., Carpenter, R.L., Wagner, K.E., Pauley, R., Barros, M., Tierney-Aves, C., et al., 2020. Saliva microRNA differentiates children with autism from peers with typical and atypical development. J. Am. Acad. Child Adolesc. Psychiatry 59 (2), 296-308.
  4. Salloum-Asfar, S., Ltaief, S.M., Taha, R.Z., Nour-Eldine, W., Abdulla, S.A., Al-Shammari, A.R., 2025. MicroRNA Profiling Identifies Age-Associated MicroRNAs and Potential Biomarkers for Early Diagnosis of Autism. Int. J. Mol. Sci. 26 (5), 2044.
  5. Gardiner, E., Beveridge, N.J., Wu, J.Q., Carr, V., Scott, R.J., Tooney, P.A., Cairns, M.J., 2012. Imprinted DLK1-DIO3 region of 14q32 defines a schizophrenia-associated miRNA signature in peripheral blood mononuclear cells. Mol. Psychiatry 17 (8), 827-840.