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This study evaluates whether gut microbiota characteristics can stratify chronic insomnia disorder (CID) severity. Sixty-five CID patients were grouped by PSQI into S-CID and M-CID, with 30 healthy controls. Polysomnography and clinical assessments were combined with 16S rRNA sequencing, genus selection (LASSO/Boruta), correlation tests, PICRUSt2 functional prediction, and random-forest classification.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/distinct-gut-microbiota-profiles-reflect-severity-in-chronic-insomnia-disorder/413978/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/distinct-gut-microbiota-profiles-reflect-severity-in-chronic-insomnia-disorder/413978.png","ImageObject",300,407,{"name":92,"@type":93},"Finn","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-01","2026-09-28",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",13,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"How were chronic insomnia disorder patients grouped in this study?","Question",{"text":113,"@type":114},"Sixty-five CID patients were divided into S-CID and M-CID based on Pittsburgh Sleep Quality Index (PSQI) scores. Healthy controls were included as a reference group.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What methods were used to analyze gut microbiota and link it to sleep measures?",{"text":118,"@type":114},"Fecal 16S rRNA gene sequencing characterized microbial structure. Key bacterial genera were identified using LASSO regression and the Boruta algorithm, then correlations with sleep parameters were assessed using Spearman analysis. Functional pathways were predicted with PICRUSt2.",{"name":120,"@type":111,"acceptedAnswer":121},"What were the main findings about gut microbiota differences by insomnia severity?",{"text":122,"@type":114},"S-CID patients showed significant gut microbial diversity and composition changes versus healthy controls, while M-CID differences were less pronounced. 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Given the established association between chronic insomnia disorder (CID) and gut microbiota, this study aimed to evaluate the utility of gut microbiota characteristics for stratifying CID severity.  \nMethods: A total of 65 patients with CID were categorized into two groups based on Pittsburgh Sleep Quality Index (PSQI) scores: S-CID (more severe poor sleep quality; median age: 36, IQR: 30–47; M/F: 12/22) and M-CID (milder poor sleep quality; median age: 33, IQR: 25–43; M/F: 11/20) . Thirty healthy controls (HC; median age: 32, IQR: 26–48; M/F: 8/22) were also included. All participants underwent polysomnography and clinical assessments. Fecal samples were collected and analyzed via 16S rRNA gene sequencing. We compared microbial structure across severity groups, identified key bacterial genera using LASSO regression and the Boruta algorithm, and examined their correlations with sleep parameters via Spearman analysis. Functional pathway predictions were performed with PICRUSt2. A random forest model was constructed to evaluate severity-stratified discriminative capacity.  \nResults: Significant alterations in gut microbial diversity and composition were observed in S-CID patients compared to HC, whereas M-CID patients showed less pronounced differences. Seven key bacterial genera were identified and consistently correlated with sleep parameters. Functional perturbations in glutamate/butanoate metabolism and branched-chain amino acid degradation pathways differed by severity. The random forest model demonstrated moderate efficacy (AUC = 0.711–0.730) in distinguishing S-CID patients based on microbial signatures.  \nConclusion: This study reveals distinct gut microbial signatures associated with varying severity levels of CID, providing insights that may support the development of microbiota-based diagnostic and therapeutic interventions.  \n\n| Yaxi Liu, Yixian Cai, and Xian Shi have contributed equally to this work.\u003Cbr>|\n| --- |\n| This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.\u003Cbr>© 2025 The Author(s). Brain and Behavior published by Wiley Periodicals LLC. |\n\nBrain and Behavior, 2026; 16:e71155 1 of 14  \n[https://doi.org/10.1002/brb3.71155](https://doi.org/10.1002/brb3.71155)  \n1  Introduction  \nInsomnia disorder is the most prevalent sleep disorder, characterized by difficulty initiating or maintaining sleep despite having sufficient sleep opportunities, leading to daytime functional impairment (Perlis et al. 2022). The ","cbCaiuivP2ywpA2Y","https://ap.wps.com/l/cbCaiuivP2ywpA2Y","pdf",2103027,15,"English","# Introduction\n## Methods\n## Results\n## Conclusion","[{\"question\":\"How were chronic insomnia disorder patients grouped in this study?\",\"answer\":\"Sixty-five CID patients were divided into S-CID and M-CID based on Pittsburgh Sleep Quality Index (PSQI) scores. Healthy controls were included as a reference group.\"},{\"question\":\"What methods were used to analyze gut microbiota and link it to sleep measures?\",\"answer\":\"Fecal 16S rRNA gene sequencing characterized microbial structure. Key bacterial genera were identified using LASSO regression and the Boruta algorithm, then correlations with sleep parameters were assessed using Spearman analysis. Functional pathways were predicted with PICRUSt2.\"},{\"question\":\"What were the main findings about gut microbiota differences by insomnia severity?\",\"answer\":\"S-CID patients showed significant gut microbial diversity and composition changes versus healthy controls, while M-CID differences were less pronounced. Seven key genera correlated with sleep parameters, and severity-related functional pathway differences were observed, with a random-forest model showing moderate discrimination for S-CID.\"}]","Distinct Gut Microbiota Profiles Reflect Severity in Chronic Insomnia Disorder | PDF",1790596295,38]