Avanços no diagnóstico da síndrome do intestino irritável: biomarcadores emergentes e o papel do eixo cérebro-intestino-microbiota
DOI:
https://doi.org/10.5281/zenodo.23585334Palavras-chave:
Síndrome do Intestino Irritável, Biomarcadores, Microbioma Intestinal, Eixo Cérebro-Intestino-Microbiota, Inteligência Artificial, Medicina de PrecisãoResumo
Introdução: A Síndrome do Intestino Irritável (SII) é um distúrbio da interação cérebro-intestino de alta prevalência, cujo diagnóstico é essencialmente clínico, baseado nos Critérios de Roma. A ausência de biomarcadores confirmatórios e a heterogeneidade fisiopatológica impulsionam a busca por novas ferramentas diagnósticas. Objetivo: Analisar avanços recentes no diagnóstico da SII, com ênfase em biomarcadores emergentes e no eixo cérebro-intestino-microbiota. Metodologia: Revisão integrativa da literatura com relato orientado pelo PRISMA 2020, nas bases PubMed, Embase, Scopus, Web of Science e BVS. Utilizaram-se descritores relacionados à SII, biomarcadores, microbioma e metabolômica. Foram incluídos estudos de 2021 a 2026, com quatro publicações de 2020 admitidas excepcionalmente, totalizando 26 publicações. Resultados: Identificaram-se biomarcadores séricos, fecais, microbiômicos, metabolômicos e neurobiológicos, além de abordagens multiômicas e inteligência artificial. A calprotectina fecal destacou-se no diagnóstico diferencial com doença inflamatória intestinal. Marcadores inflamatórios e painéis fecais mostraram utilidade complementar. Alterações do microbioma e metaboloma associaram-se a subtipos da SII, com melhor desempenho quando integrados. Achados de neuroimagem e neuroendócrinos reforçaram o eixo cérebro-intestino-microbiota. Modelos de inteligência artificial demonstraram potencial para integração de dados e estratificação clínica. Conclusão: O diagnóstico da SII permanece clínico, com biomarcadores e ferramentas computacionais em fase emergente e complementar. A integração multiômica representa uma perspectiva promissora para medicina de precisão, embora limitações metodológicas e ausência de validação externa ainda restrinjam sua aplicação clínica.
Referências
BARANDOUZI, Z. A. et al. Associations of neurotransmitters and the gut microbiome with emotional distress in mixed type of irritable bowel syndrome. Scientific Reports, v. 12, n. 1, art. 1648, 2022. DOI: 10.1038/s41598-022-05756-0.
BHAGAVATHULA, A. S.; AL QADY, A. M.; ALDHALEEI, W. A. Diagnostic accuracy and quality of artificial intelligence models in irritable bowel syndrome: a systematic review. World Journal of Gastroenterology, v. 31, n. 23, art. 106836, 2025. DOI: 10.3748/wjg.v31.i23.106836.
BURNS, G. L. et al. Serological and faecal markers of irritable bowel syndrome: a systematic review and meta-analysis. eBioMedicine, v. 126, art. 106198, 2026. DOI: 10.1016/j.ebiom.2026.106198.
CAMILLERI, M. Diagnosis and treatment of irritable bowel syndrome: a review. JAMA, v. 325, n. 9, p. 865–877, 2021. DOI: 10.1001/jama.2020.22532.
CAMILLERI, M.; BOECKXSTAENS, G. Irritable bowel syndrome: treatment based on pathophysiology and biomarkers. Gut, v. 72, n. 3, p. 590–599, 2023. DOI: 10.1136/gutjnl-2022-328515.
DAJTI, E. et al. Systematic review with meta-analysis: diagnostic performance of faecal calprotectin in distinguishing inflammatory bowel disease from irritable bowel syndrome in adults. Alimentary Pharmacology & Therapeutics, v. 58, n. 11–12, p. 1120–1131, 2023. DOI: 10.1111/apt.17754.
FORD, A. C. et al. Irritable bowel syndrome. The Lancet, v. 396, n. 10263, p. 1675–1688, 2020. DOI: 10.1016/S0140-6736(20)31548-8.
FUKUI, H. et al. Usefulness of machine learning-based gut microbiome analysis for identifying patients with irritable bowels syndrome. Journal of Clinical Medicine, v. 9, n. 8, art. 2403, 2020. DOI: 10.3390/jcm9082403.
GUAN, M.; CHANG, L. Biomarkers in irritable bowel syndrome: rationale and practical use. Gastroenterology Clinics of North America, v. 55, n. 1, p. 91–105, 2026. DOI: 10.1016/j.gtc.2025.08.002.
HUNG, K. W. et al. AGA Institute quality indicator development for irritable bowel syndrome. Gastroenterology, v. 168, n. 3, p. 612–622.e4, 2025. DOI: 10.1053/j.gastro.2024.11.003.
JACOBS, J. P. et al. Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes. Microbiome, v. 11, art. 5, 2023. DOI: 10.1186/s40168-022-01450-5.
JEFFERY, I. B. et al. Differences in fecal microbiomes and metabolomes of people with vs without irritable bowel syndrome and bile acid malabsorption. Gastroenterology, v. 158, n. 4, p. 1016–1028.e8, 2020. DOI: 10.1053/j.gastro.2019.11.301.
LACY, B. E. et al. ACG Clinical Guideline: management of irritable bowel syndrome. American Journal of Gastroenterology, v. 116, n. 1, p. 17–44, 2021. DOI: 10.14309/ajg.0000000000001036.
LEE, G. et al. Prediction of irritable bowel syndrome by integrating urine metabolites and gut microbiota. Scientific Reports, v. 15, n. 1, art. 38246, 2025. DOI: 10.1038/s41598-025-22068-1.
LI, L. et al. Artificial intelligence-driven gastrointestinal functional assessment: multimodal imaging, digital biomarkers, and real-time monitoring. Frontiers in Physiology, v. 17, art. 1778235, 2026. DOI: 10.3389/fphys.2026.1778235.
LI, Z. et al. Irritable bowel syndrome is associated with brain health by neuroimaging, behavioral, biochemical, and genetic analyses. Biological Psychiatry, v. 95, n. 12, p. 1122–1132, 2024. DOI: 10.1016/j.biopsych.2023.12.024.
MATIJAŠIĆ, M. et al. Serum proteins and faecal microbiota as potential biomarkers in newly diagnosed, treatment-naïve inflammatory bowel disease and irritable bowel syndrome patients. Journal of Molecular Medicine, v. 103, n. 8, p. 963–974, 2025. DOI: 10.1007/s00109-025-02558-5.
MAYER, E. A.; RYU, H. J.; BHATT, R. R. The neurobiology of irritable bowel syndrome. Molecular Psychiatry, v. 28, n. 4, p. 1451–1465, 2023. DOI: 10.1038/s41380-023-01972-w.
MOU, J. et al. Diagnostic accuracy of biomarkers for irritable bowel syndrome: a systematic review and meta-analysis. Clinical Biochemistry, v. 141, art. 111061, 2026. DOI: 10.1016/j.clinbiochem.2025.111061.
MOUSAVI, E. et al. Exploring new subgroups for irritable bowel syndrome using a machine learning algorithm. Scientific Reports, v. 13, n. 1, art. 18483, 2023. DOI: 10.1038/s41598-023-45605-2.
OSADCHIY, V. et al. Analysis of brain networks and fecal metabolites reveals brain-gut alterations in premenopausal females with irritable bowel syndrome. Translational Psychiatry, v. 10, n. 1, art. 367, 2020. DOI: 10.1038/s41398-020-01071-2.
PAGE, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, v. 372, art. n71, 2021. DOI: 10.1136/bmj.n71.
SARNOFF, R. P. et al. A multi-omic brain gut microbiome signature differs between IBS subjects with different bowel habits. Neuropharmacology, v. 225, art. 109381, 2023. DOI: 10.1016/j.neuropharm.2022.109381.
SHIN, A. S. et al. Microbiota and short chain fatty acid relationships underlie clinical heterogeneity and identify key microbial targets in irritable bowel syndrome (IBS). Scientific Reports, v. 15, n. 1, art. 35375, 2025. DOI: 10.1038/s41598-025-19363-2.
SINGH, S. V. et al. Molecular signalling during cross talk between gut brain axis regulation and progression of irritable bowel syndrome: a comprehensive review. World Journal of Clinical Cases, v. 11, n. 19, p. 4458–4476, 2023. DOI: 10.12998/wjcc.v11.i19.4458.
YADAV, Y. S.; ESLICK, G. D.; TALLEY, N. J. Review article: irritable bowel syndrome: natural history, bowel habit stability and overlap with other gastrointestinal disorders. Alimentary Pharmacology & Therapeutics, v. 54, supl. 1, p. S24–S32, 2021. DOI: 10.1111/apt.16624.
YANG, B. et al. Brain-targeted therapies for irritable bowel syndrome: mechanisms and strategies. Current Neuropharmacology, v. 24, publicação online antecipada, 2026. DOI: 10.2174/011570159X461707260327112414.
ZHANG, X.; JIN, W.-W.; WANG, H.-G. Correlation between the neuroendocrine axis, microbial species, inflammatory response, and gastrointestinal symptoms in irritable bowel syndrome. World Journal of Gastroenterology, v. 30, n. 35, p. 3985–3995, 2024. DOI: 10.3748/wjg.v30.i35.3985.
