BIOME cohort: Multi‐system microbiome dynamics and clinical outcomes in massive burn injury patients

Massive burn injuries (MBIs) are associated with high mortality and disability rates, primarily due to microbial-driven sepsis from extensive skin barrier loss and subsequent scar formation. This makes MBI a compelling model for studying multi-system microbial dysbiosis following skin barrier destruction. We launched the Burn & Trauma Injury Organisms and Microbiome Ecology (BIOME) project, planning to enroll at least 150 MBI patients from 50 hospitals across 28 provinces, autonomous regions, and municipalities in China. The cohort includes skin swabs, intestinal and oral samples, and longitudinal clinical data collected from within 72 h post-injury through 1 year of follow-up. This multicenter, prospective, longitudinal cohort will establish a comprehensive clinical microbiota resource for patients with MBI. By integrating multi-system microbiome profiling with clinical outcomes, the BIOME project aims to elucidate the translational role of microbiota reconstruction as a potential target for diagnosis, prognosis, and therapeutic intervention in severe burn care. Burns and trauma are the leading causes of injury-related mortality among individuals under 45 years of age worldwide [1]. Among these, massive burn injuries (MBIs), defined as burns involving >50% of total body surface area (TBSA) or full-thickness burns affecting >20% TBSA, are associated with exceptionally high mortality and long-term disability [2, 3]. The MBI patient mortality is mainly due to sepsis, which is caused by endogenous or exogenous microbial infection [4]. Growing evidence indicates a potential role of the microbiome in sepsis and its promise as a therapeutic and monitoring target [5, 6]. MBIs profoundly disrupt the human microbiota, including skin, gut, and respiratory communities [3, 7]. Dysbiosis of the skin microbiota contributes to the development and progression of dermatological disorders, whereas microbiome reconstruction facilitates wound healing by restoring skin barrier function [8, 9]. Beyond its local effects, the skin microbiome is tightly interconnected with the gut, oral, and respiratory microbiota, collectively forming a systemic microbial network that supports immune homeostasis and host defense [8-10]. Disruption of this network can promote pathogen overgrowth and immune dysregulation, thereby increasing susceptibility to severe infections, sepsis, and subsequent multiple organ dysfunction syndrome, ultimately leading to poorer clinical outcomes and prognosis [11, 12]. However, most studies remain limited to observational associations or animal models, typically focused on single niches at single time points [6, 8, 9]. The lack of large-scale clinical cohorts capturing multi-ecosystem dynamics limits mechanistic understanding and hinders intervention development [8, 9]. To address these gaps, we initiated the Burn & Trauma Injury Organisms and Microbiome Ecology (BIOME) cohort: a multicenter, longitudinal, prospective study investigating microbiome dynamics during MBI treatment. The primary aims of the BIOME cohort are: (1) establishing a nationwide multicenter prospective cohort to investigate the longitudinal dynamic characteristics of multi-system microbiomes (skin, gut, and oral) in MBI patients; (2) exploring the associations between dynamic microbial alterations and new-onset sepsis and all-cause mortality. The secondary aims of the BIOME cohort include: (1) examining the relationships between microbiome dynamics and wound outcomes, focusing on wound healing trajectories and scar formation; (2) evaluating the predictive value of specific microbial signatures for clinical prognosis, aiming to identify early biomarkers for intervention. The BIOME cohort is a multicenter, prospective, longitudinal study conducted across 50 hospitals in 28 Chinese administrative regions (Figure 1A and Table S1). The participating centers are recognized for their expertise in managing MBIs. Participating centers cover all major geographical areas, ensuring national representation. To account for geographic microbiome variation, 20% of patients from geographical division of China will serve as a validation cohort [13]. The negative and positive control sampling of each center have been integrated into the study design. The study was approved by the Ethics Committee of The First Affiliated Hospital of Naval Medical University (Approval No. CHEC2025-071) and registered with the Chinese Clinical Trial Registry (ChiCTR2500099489). Comprehensive documentation including the study protocol, standard operating procedures (SOPs), and the statistical analysis plan were provided in the Supplementary Materials. The BIOME cohort plans to enroll at least 150 MBI patients (Figure 1B). The planned sample size was justified using both event-rate-based and events-per-variable (EPV) considerations for the two primary outcomes: all-cause mortality and new-onset sepsis. A large disaster-related MBIs' cohort from the 2014 Kunshan explosion (including 20 centers' data) reported an all-cause mortality of 44.8% and a sepsis incidence of 68.5% in patients with TBSA > 50% [14]. For event-rate-based considerations, assuming a two-sided significance level of α = 0.05 and a statistical power of: 1 – β = 0.80 (80%). The minimum required sample size to detect a clinically meaningful difference in mortality and sepsis between microbiome-defined subgroups was calculated to be 82 and 76 patients, respectively. These event counts allow inclusion of 6−7 variables for mortality models and 10−11 variables for sepsis models, providing sufficient power to evaluate microbial predictors while adjusting for major clinical confounders. Therefore, the planned enrollment of 150 patients is statistically adequate for all primary analyses. Multi-system samples, including skin swabs, intestinal and oral samples, and control specimens, will be collected for shotgun metagenomic sequencing and analyzed with clinical outcomes (Figure 1C). This study is designed as a single, unified cohort. Skin, gut, and oral are all collected concurrently from the same set of patients to support integrated downstream analyses, rather than assigning participants to separate sub-cohorts. Sample and data collection will occur at predefined time points: 1−2, 3, 7, 14, and 28 days (±1 day) post-burn, wound healing day, and 3, 6, and 12 months (±7 days) post-burn. Additional samples will be collected for 3 days following a sepsis diagnosis (ABA criteria) [15]. Demographic information, injury characteristics, treatment details, and outcomes/endpoints will be collected and recorded in the Electronic Data Capture (EDC) system of the Case Report Form. Recruitment runs from July 1, 2025 to June 30, 2028. Patient enrollment, sepsis diagnosis, wound healing assessments, and key clinical outcomes will be jointly determined by two senior clinicians. One being the principal investigator at each participating center, and the other from The First Affiliated Hospital of Naval Medical University. If their evaluations differ, a third senior clinician from the independent adjudication committee will provide the final judgment. All enrollment decisions, diagnostic records, and wound assessment materials will be documented in the EDC system, and the independent adjudication committee will conduct a final review before data analysis and database lock. Written informed consent is mandatory. Age 18−65 years; MBI patients with >50% TBSA who were admitted to the hospital within 72 h of burn injury; Patients or designated agents and guardians agreed to participate in this study and signed an informed consent form. Patients with underlying endocrine disorders (e.g., diabetes mellitus, hyperthyroidism); Patients diagnosed with hematologic diseases or malignancies of the skin or internal organs; Patients with autoimmune diseases, immunodeficiency disorders, or immunosuppression (e.g., patients undergoing high-dose immunosuppressive therapy); Patients with pre-existing dermatologic conditions (e.g., psoriasis, vitiligo) in combination; Pregnant or lactating women; Any other conditions deemed by the investigators to potentially affect study outcomes. Skin swab samples from burned and unburned regions of the torso and radial side of the extremities, Intestinal samples (fecal specimens or anal swabs), Oral swab samples, Demographic information, injury characteristics, treatment details, outcomes/endpoints. To ensure consistency and minimize technical variability, all participating centers will use standardized nucleic acid preservation reagents, sample tubes, and sterile saline, which will be centrally distributed by The First Affiliated Hospital of Naval Medical University on a quarterly basis. In addition to the regular biological sampling, strict quality control measures, including the collection of environmental surface swabs, air blanks, reagent negative controls, and mock community positive controls, are mandatory in all participating centers to monitor contamination and validate sequencing accuracy. Detailed SOPs for sample acquisition and negative control handling are provided in the Supplementary Information. To ensure longitudinal continuity, the core sampling schedule will proceed as planned, irrespective of the patient's clinical setting (ICU, general ward, or outpatient). Sample collection will only be definitively terminated in the event of patient death, withdrawal of informed consent, or loss to follow-up. To further reduce both technical variability and systemic error, all centers will employ standardized biospecimen collection kits, also distributed quarterly by The First Affiliated Hospital of Naval Medical University. As of September 21, 2025, a total of 44 patients had been enrolled in the BIOME cohort, representing 29.3% of the target sample size of 150 cases (Figure 2). Patients are recruited from multiple regions of China, with 50.0% from the eastern region, 45.0% from the central region, and 5.0% from the western region (Figure 2A,B). The mean age of the enrolled patients was 43.6 ± 12.9 years, with 32 males (72.7%) and 12 females (27.3%) (Figure 2C). Injury characteristics: the primary causes of injury were fire (70.5%), hydrotherm (11.4%), explosion (6.8%), electricity (4.5%), electric arc (2.3%), and other causes (4.5%). The mean body mass index (BMI) of the cohort was 24.78 ± 3.75, with a median of 24.86 (range: 16.8–32.14). The mean total burn surface area (TBSA) was 78.12 ± 13.94%, with a median of 80% (range: 50%−98%) (Figure 2C,D). Early treatment information: The median time from injury to hospital admission was 3 h (interquartile range: 3.12; range: 0–56). Additionally, 61.4% of patients retained intact unburned scalp areas, and 79.5% presented with concomitant inhalation injury. Cryotherapy was initiated within 1 h after injury in 20.5% of patients, within 1−3 h in 2.3%, and after more than 3 h in 4.5%. Notably, 72.7% of patients did not receive any cryotherapy. Airway interventions (intubation or tracheotomy) were performed in 40.9% of patients during the acute phase (Figure 2C,D). Outcome information: During hospitalization, 6.8% of patients developed sepsis. At follow-up, the mortality rate was 11.4%, while 88.6% of patients survived (Figure 2D). The progress of biological sampling is shown in Figure 2E. As a nationwide, multicenter, prospective cohort of patients with MBIs, the BIOME project was officially proposed on October 18, 2024. The MBI represents a unique clinical model of systemic stress, ideal for investigating cross-organ microbial interactions. A recent pivotal experimental study identified a “skin-to-gut axis,” demonstrating that dermal injury can directly disrupt the intestinal microbiome and immune homeostasis in mice [10]. The BIOME cohort extends these mechanistic insights into the clinical setting by enabling high-resolution, longitudinal, multisystem profiling of the skin, gut, and respiratory microbiomes in human patients. Collectively, the BIOME project provides an unprecedented clinical resource for elucidating microbiome-mediated mechanisms underlying post-burn complications, including sepsis, and for identifying microbial biomarkers with diagnostic and prognostic potential. Despite these strengths, we acknowledge certain limitations. First, regarding patient inclusion and demographics, potential biases in geographical location and gender may limit generalizability. MBIs are predominantly caused by accidental events, such as industrial explosions and residential fires, which may result in uneven regional and gender representation. In addition, microbial signatures identified in this cohort may not be directly generalizable to populations with different ethnic, dietary, or environmental backgrounds [16, 17]. To mitigate regional bias, the BIOME cohort has been expanded to include 50 leading burn centers across 28 provinces, with ongoing efforts to increase recruitment from underrepresented western and northern regions. Second, concerning sampling methodology, MBI patients frequently suffer from paralytic ileus due to burn shock, and high-dose opioid analgesics (especially the first 72 h), necessitating the use of anal swabs as a substitute. Third, regarding clinical treatment, the administration of antibiotics, comorbidities, and variations in treatment protocols introduce unavoidable confounding factors [18]. Disentangling disease-induced dysbiosis from medication effects remains a universal challenge in critical care microbiome research [18]. To reduce these treatment and source heterogeneity, we apply established statistical frameworks, including Linear Mixed Models (LMM), Multivariate Association with Linear Models (MaAsLin2), and subgroup and sensitivity analyses to enhance the robustness of our findings [19]. Finally, as an observational cohort, the BIOME cohort is inherently limited in its ability to infer causality. While robust associations between microbiome features and clinical outcomes can be identified, mechanistic validation will require future experimental studies using animal models, organoids, or fecal microbiota transplantation approaches. Runzhi Huang: Conceptualization; methodology; software; data curation; supervision; formal analysis; validation; investigation; funding acquisition; visualization; project administration; writing—review and editing; writing—original draft. Yixu Li: Conceptualization; methodology; data curation; investigation; validation; supervision; resources; project administration; visualization; writing—original draft. Xiaoliang Li: Conceptualization; investigation; writing—original draft; methodology; validation; visualization; data curation; supervision; resources; project administration. Xulin Chen: Conceptualization; methodology; data curation; supervision; investigation; validation; project administration; resources; writing—review and editing. Gang Xu: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Shurun Huang: Data curation; supervision; resources; project administration; writing—review and editing; methodology; validation; conceptualization; investigation. Weixi Yang: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Xiaodong Li: Data curation; supervision; resources; project administration; writing—review and editing; validation; methodology; investigation; conceptualization. Haiming Xin: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Jianqiang Jiao: Data curation; supervision; resources; project administration; methodology; validation; investigation; conceptualization; writing—review and editing. Hui Chen: Project administration; writing—review and editing; validation; methodology; investigation; conceptualization; resources; supervision; data curation. Yuguo Xie: Data curation; supervision; resources; project administration; writing—review and editing; validation; methodology; investigation; conceptualization. Peng Duan: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Wenjun Liu: Data curation; supervision; resources; project administration; writing—review and editing; validation; methodology; conceptualization; investigation. Xiangdong Deng: Conceptualization; investigation; methodology; writing—review and editing; validation; project administration; resources; supervision; data curation. Zongyu Li: Data curation; supervision; resources; project administration; writing—review and editing; validation; methodology; investigation; conceptualization. Yiping Xiu: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Jiansheng Zheng: Data curation; supervision; resources; project administration; writing—review and editing; investigation; conceptualization; methodology; validation. Rujun Chen: Data curation; supervision; resources; project administration; writing—review and editing; validation; methodology; investigation; conceptualization. Zhaohong Chen: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Xingang Wang: Data curation; supervision; resources; project administration; writing—review and editing; methodology; validation; investigation; conceptualization. Xiaojian Li: Conceptualization; investigation; methodology; validation; writing—review and editing; project administration; resources; supervision; data curation. Gaoxing Data curation; supervision; resources; project administration; writing—review and editing; validation; methodology; conceptualization; investigation. 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