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| ID | Type | Description | Link |
|---|---|---|---|
| HG2025-023 | Other Identifier | Hallym Univ. Hangang Sacred Heart Hosp. IRB |
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This prospective observational cohort study aims to investigate the longitudinal changes in the skin and gut microbiome of burn patients after injury and compare them with healthy controls. Burn injuries are known to induce systemic physiological and immune responses that may lead to widespread microbial dysbiosis (microbial imbalance) beyond the injured site. However, the dynamics of microbial community changes in both burned and non-burned skin, as well as the gut, remain poorly understood.
In this study, a total of 660 participants will be enrolled, including 600 burn patients and 60 healthy controls. For burn patients, skin swabs from burned scars and matched non-burned skin, stool samples, and physiological skin measurements will be collected at multiple time points (baseline, 3 months, 6 months, 12 months, and 24 months). Healthy controls will provide skin and stool samples at baseline only.
Microbial profiling will be performed using 16S ribosomal RNA (rRNA) gene sequencing, and functional prediction will be analyzed using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt2). Physiological skin-barrier measurements, including transepidermal water loss (TEWL), hydration, pH, erythema, and elasticity, will be assessed using standardized instruments. Blood biomarkers, including C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), will also be measured.
The findings of this study will improve our understanding of burn-related microbial dysbiosis, provide insights into microbiome-driven skin-barrier recovery, and inform potential therapeutic strategies for long-term burn care.
This is a prospective, observational cohort study conducted at the Burn Institute of Hallym University Hangang Sacred Heart Hospital. The study aims to characterize temporal changes in the skin and gut microbiome of burn patients compared with healthy controls and to identify potential links between microbiome dynamics, skin-barrier recovery, and systemic immune responses.
A total of 660 participants will be enrolled, including 600 burn patients and 60 healthy controls. Burn patients will be followed longitudinally for 24 months, with sample collection and clinical measurements performed at baseline (within 7 days after hospital admission), 3 months, 6 months, 12 months, and 24 months after injury. Healthy controls will provide single-timepoint samples for comparison.
Sample Collection Skin Microbiome: Swabs will be collected from burned scars and matched non-burned skin sites.
Gut Microbiome: Stool samples will be collected for 16S ribosomal RNA (rRNA) gene sequencing.
Skin Physiological Measurements: Transepidermal water loss (TEWL), hydration, erythema, melanin index, elasticity, and pH levels will be measured using standardized instruments (Corneometer®, Tewameter®, Mexameter®, Cutometer®, and pH meter).
Blood Biomarkers: Erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), interleukin-6 (IL-6), and other systemic inflammatory markers will be analyzed.
Microbiome Profiling DNA extraction and 16S rRNA gene sequencing will be performed using Illumina sequencing platforms. Bioinformatic processing will be conducted using the Quantitative Insights Into Microbial Ecology 2 (QIIME2) pipeline. Functional prediction of microbial metabolic pathways will be analyzed with Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt2). Beta diversity and alpha diversity indices will be calculated, and taxonomic differences between groups will be assessed using Linear Discriminant Analysis Effect Size (LEfSe).
Clinical Relevance Microbiome dysbiosis (microbial imbalance) after burn injury may extend beyond local wounds and affect non-burned skin and the gut, contributing to impaired skin-barrier function, immune dysregulation, and delayed recovery. Understanding these relationships may help develop microbiome-targeted therapeutic interventions, improve wound healing, and optimize long-term patient care.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Burn Patients Cohort | This cohort includes 600 adult burn patients who experienced partial- or full-thickness burns. Participants will provide skin swabs, stool samples, blood samples, and skin physiological measurements at baseline, 3, 6, 12, and 24 months after injury. The primary objective is to investigate longitudinal changes in the skin and gut microbiome and their association with skin barrier recovery and systemic inflammation. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No Intervention: Observational Cohort | Other | This is an observational cohort study with no interventions administered. Skin swabs, stool samples, blood samples, and skin physiological measurements will be collected at baseline, 3, 6, 12, and 24 months after burn injury to investigate longitudinal changes in the skin and gut microbiome. |
| Measure | Description | Time Frame |
|---|---|---|
| Change in Skin Microbiome Diversity | Alpha and beta diversity indices of the skin microbiome will be analyzed using 16S ribosomal RNA (rRNA) gene sequencing and Quantitative Insights Into Microbial Ecology 2 (QIIME2)-based bioinformatics pipeline. Unit of Measure: Shannon diversity index (unitless) | Baseline, 3, 6, 12, and 24 months after burn injury |
| Change in Gut Microbiome Diversity | Alpha and beta diversity indices of the gut microbiome will be analyzed using 16S ribosomal RNA (rRNA) gene sequencing and Quantitative Insights Into Microbial Ecology 2 (QIIME2)-based bioinformatics pipeline. Unit of Measure: Shannon diversity index (unitless) | Baseline, 3, 6, 12, and 24 months after burn injury |
| Measure | Description | Time Frame |
|---|---|---|
| Functional Prediction of Microbiome | Predicted microbial functional pathways will be identified using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt2) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Unit of Measure: Relative pathway abundance (percentage) | Baseline, 3, 6, 12, 24 months |
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Inclusion Criteria
Exclusion Criteria
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This study will enroll 600 adult burn patients aged 19 to 65 years who have experienced partial- or full-thickness burns. Participants will be recruited from the Burn Center at Hallym University Hangang Sacred Heart Hospital. All participants must provide written informed consent.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yoon Soo Cho, MD, PhD | Contact | +82-2-2639-5730 | yschorm@hallym.ac.kr | |
| YeonGyun Jung, PhD | Contact | +82-2-2639-5730 | jyg1076@gmail.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hallym University Hangang Sacred Heart Hospital | Recruiting | Seoul | 07247 | South Korea |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37129034 | Background | Jung Y, Cui HS, Joo SY, Lee EK, Seo CH, Cho YS. Sex differences in the skin microbiome of burn scars. Wound Repair Regen. 2023 Jul-Aug;31(4):547-558. doi: 10.1111/wrr.13088. Epub 2023 Jun 24. | |
| 37958976 | Background | Jung Y, Cui HS, Lee EK, Joo SY, Seo CH, Cho YS. Effects of Factors Influencing Scar Formation on the Scar Microbiome in Patients with Burns. Int J Mol Sci. 2023 Nov 6;24(21):15991. doi: 10.3390/ijms242115991. |
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Individual participant data (IPD) will not be shared because this study involves sensitive clinical and microbiome information from burn patients, and the IRB-approved protocol does not include explicit consent for data sharing.
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| ICF | No | No | Yes | Informed Consent Form | Sep 8, 2025 | Sep 29, 2025 | ICF_000.pdf |
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| ID | Term |
|---|---|
| D002056 | Burns |
| D012871 | Skin Diseases |
| D064806 | Dysbiosis |
| ID | Term |
|---|---|
| D014947 | Wounds and Injuries |
| D017437 | Skin and Connective Tissue Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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Skin swabs, stool samples, and blood samples will be collected from burn patients at multiple time points (baseline, 3, 6, 12, and 24 months).
Skin swabs will be taken from burned scars and matched non-burned skin areas. Stool samples will be used for gut microbiome profiling, and blood samples will be used for measuring systemic inflammatory biomarkers.
All specimens will be stored under controlled conditions for future microbiome and biomarker analyses, and DNA will be extracted from skin and stool samples for 16S rRNA sequencing.
|
| Transepidermal Water Loss (TEWL) | TEWL will be measured using Tewameter® to assess skin barrier integrity. Unit of Measure: grams per square meter per hour (g/m²/h) | Baseline, 3, 6, 12, 24 months |
| Skin Hydration | Skin hydration will be measured using Corneometer® to assess stratum corneum moisture levels. Unit of Measure: arbitrary units (a.u.) | Baseline, 3, 6, 12, and 24 months after burn injury |
| Skin Elasticity | Skin elasticity will be measured using Cutometer® to assess biomechanical recovery of scar tissue. Unit of Measure: arbitrary units (a.u.) | Baseline, 3, 6, 12, and 24 months after burn injury |
| Serum C-Reactive Protein (CRP) Concentration | Serum CRP concentration will be measured as a systemic inflammatory biomarker. Unit of Measure: milligrams per liter (mg/L) | Baseline, 3, 6, 12, 24 months |
| Erythrocyte Sedimentation Rate (ESR) | ESR will be measured from peripheral blood samples to assess systemic inflammation. Unit of Measure: millimeters per hour (mm/hr) | Baseline, 3, 6, 12, and 24 months after burn injury |
| 37759587 | Background | Ersanli C, Tzora A, Voidarou CC, Skoufos S, Zeugolis DI, Skoufos I. Biodiversity of Skin Microbiota as an Important Biomarker for Wound Healing. Biology (Basel). 2023 Aug 30;12(9):1187. doi: 10.3390/biology12091187. |
| 32821744 | Background | Corcione S, Lupia T, De Rosa FG; Host and Microbiota Interaction Study Group (ESGHAMI) of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). Microbiome in the setting of burn patients: implications for infections and clinical outcomes. Burns Trauma. 2020 Aug 14;8:tkaa033. doi: 10.1093/burnst/tkaa033. eCollection 2020. |
| 30587610 | Background | Nakai K, Kubota Y, Soma GI, Kohchi C. The Effect of Lipopolysaccharide-containing Moisturizing Cream on Skin Care in Patients With Mild Atopic Dermatitis. In Vivo. 2019 Jan-Feb;33(1):109-114. doi: 10.21873/invivo.11446. |
| 27959277 | Background | Ogawa R, Akaishi S. Endothelial dysfunction may play a key role in keloid and hypertrophic scar pathogenesis - Keloids and hypertrophic scars may be vascular disorders. Med Hypotheses. 2016 Nov;96:51-60. doi: 10.1016/j.mehy.2016.09.024. Epub 2016 Sep 28. |
| 28669672 | Background | Gimblet C, Meisel JS, Loesche MA, Cole SD, Horwinski J, Novais FO, Misic AM, Bradley CW, Beiting DP, Rankin SC, Carvalho LP, Carvalho EM, Scott P, Grice EA. Cutaneous Leishmaniasis Induces a Transmissible Dysbiotic Skin Microbiota that Promotes Skin Inflammation. Cell Host Microbe. 2017 Jul 12;22(1):13-24.e4. doi: 10.1016/j.chom.2017.06.006. Epub 2017 Jun 29. |
| 29663582 | Background | Liu SH, Huang YC, Chen LY, Yu SC, Yu HY, Chuang SS. The skin microbiome of wound scars and unaffected skin in patients with moderate to severe burns in the subacute phase. Wound Repair Regen. 2018 Mar;26(2):182-191. doi: 10.1111/wrr.12632. Epub 2018 May 21. |
| 28095528 | Background | Baldwin HE, Bhatia ND, Friedman A, Eng RM, Seite S. The Role of Cutaneous Microbiota Harmony in Maintaining a Functional Skin Barrier. J Drugs Dermatol. 2017 Jan 1;16(1):12-18. |
| 28361981 | Background | Lehtimaki J, Karkman A, Laatikainen T, Paalanen L, von Hertzen L, Haahtela T, Hanski I, Ruokolainen L. Patterns in the skin microbiota differ in children and teenagers between rural and urban environments. Sci Rep. 2017 Mar 31;7:45651. doi: 10.1038/srep45651. |
| 19478181 | Background | Grice EA, Kong HH, Conlan S, Deming CB, Davis J, Young AC; NISC Comparative Sequencing Program; Bouffard GG, Blakesley RW, Murray PR, Green ED, Turner ML, Segre JA. Topographical and temporal diversity of the human skin microbiome. Science. 2009 May 29;324(5931):1190-2. doi: 10.1126/science.1171700. |
| 28034303 | Background | Rogers MB, Firek B, Shi M, Yeh A, Brower-Sinning R, Aveson V, Kohl BL, Fabio A, Carcillo JA, Morowitz MJ. Disruption of the microbiota across multiple body sites in critically ill children. Microbiome. 2016 Dec 29;4(1):66. doi: 10.1186/s40168-016-0211-0. |
| 24451201 | Background | Alekseyenko AV, Perez-Perez GI, De Souza A, Strober B, Gao Z, Bihan M, Li K, Methe BA, Blaser MJ. Community differentiation of the cutaneous microbiota in psoriasis. Microbiome. 2013 Dec 23;1(1):31. doi: 10.1186/2049-2618-1-31. |