TY - JOUR
T1 - Microbiome-based prediction of allogeneic hematopoietic stem cell transplantation outcome
AU - Shtossel, Oshrit
AU - Eshel, Adi
AU - Fried, Shalev
AU - Geva, Mika
AU - Danylesko, Ivetta
AU - Yerushalmi, Ronit
AU - Shem-Tov, Noga
AU - Fein, Joshua A.
AU - Fabbrini, Marco
AU - Shimoni, Avichai
AU - Turjeman, Sondra
AU - Louzoun, Yoram
AU - Nagler, Arnon
AU - Koren, Omry
AU - Shouval, Roni
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/7/17
Y1 - 2025/7/17
N2 - Background: Allogeneic hematopoietic stem cell transplantation (HSCT) is potentially curative for hematologic malignancies but is frequently complicated by relapse and immune-mediated complications, such as graft-versus-host disease (GVHD). Emerging evidence suggests a role for the intestinal and oral microbiome in modulating HSCT outcomes, yet predictive models incorporating microbiome data remain limited. Methods: We applied the RATIO (suRvival Analysis lefT barrIer lOss) model to longitudinal stool and saliva microbiome data from 204 adult HSCT recipients to predict the timing of seven outcomes: overall survival (OS), non-relapse mortality (NRM), relapse, acute GVHD (grades II–IV and III–IV), chronic GVHD, and oral chronic GVHD. A total of 514 stool and 1291 saliva samples were collected over 70 weeks post-HSCT. Model performance was evaluated using the concordance index (CI) and Spearman correlation coefficient (SCC), with SHAP (SHapley Additive exPlanations) analysis used for model interpretability. Results: Oral and stool microbial dysbiosis peaked within the first 2 weeks post-HSCT, followed by partial recovery. Using the RATIO model, we found that microbiome features from early time points (weeks 1–2) were most predictive of short-term complications such as acute GVHD, while later samples (weeks 36–70) were more informative for long-term outcomes, including overall survival. RATIO outperformed traditional survival models (Cox and Random Survival Forest) across most outcomes (median CI > 0.65), with stool microbiota showing greater predictive power than saliva. SHAP analysis identified specific stool genera, including Collinsella and Eggerthella, associated with shorter time to various complications. External validation using a pediatric GVHD cohort confirmed the model’s generalizability and reproducibility. External validation using a pediatric HSCT cohort (n = 90) confirmed the reproducibility and generalizability of these microbiome-based predictions. Conclusions: Microbiome profiling of stool and saliva samples offers robust, time-sensitive prediction of post-HSCT complications. The RATIO model enables interpretable, time-to-event prediction across multiple outcomes and may inform microbiome-guided interventions to improve transplant success.
AB - Background: Allogeneic hematopoietic stem cell transplantation (HSCT) is potentially curative for hematologic malignancies but is frequently complicated by relapse and immune-mediated complications, such as graft-versus-host disease (GVHD). Emerging evidence suggests a role for the intestinal and oral microbiome in modulating HSCT outcomes, yet predictive models incorporating microbiome data remain limited. Methods: We applied the RATIO (suRvival Analysis lefT barrIer lOss) model to longitudinal stool and saliva microbiome data from 204 adult HSCT recipients to predict the timing of seven outcomes: overall survival (OS), non-relapse mortality (NRM), relapse, acute GVHD (grades II–IV and III–IV), chronic GVHD, and oral chronic GVHD. A total of 514 stool and 1291 saliva samples were collected over 70 weeks post-HSCT. Model performance was evaluated using the concordance index (CI) and Spearman correlation coefficient (SCC), with SHAP (SHapley Additive exPlanations) analysis used for model interpretability. Results: Oral and stool microbial dysbiosis peaked within the first 2 weeks post-HSCT, followed by partial recovery. Using the RATIO model, we found that microbiome features from early time points (weeks 1–2) were most predictive of short-term complications such as acute GVHD, while later samples (weeks 36–70) were more informative for long-term outcomes, including overall survival. RATIO outperformed traditional survival models (Cox and Random Survival Forest) across most outcomes (median CI > 0.65), with stool microbiota showing greater predictive power than saliva. SHAP analysis identified specific stool genera, including Collinsella and Eggerthella, associated with shorter time to various complications. External validation using a pediatric GVHD cohort confirmed the model’s generalizability and reproducibility. External validation using a pediatric HSCT cohort (n = 90) confirmed the reproducibility and generalizability of these microbiome-based predictions. Conclusions: Microbiome profiling of stool and saliva samples offers robust, time-sensitive prediction of post-HSCT complications. The RATIO model enables interpretable, time-to-event prediction across multiple outcomes and may inform microbiome-guided interventions to improve transplant success.
KW - Graft-versus-host disease
KW - Hematopoietic stem cell transplantation
KW - Machine learning
KW - RATIO model
KW - Saliva microbiome
KW - Stool microbiome
KW - Time-to-event analysis
UR - https://www.scopus.com/pages/publications/105011098494
U2 - 10.1186/s13073-025-01507-8
DO - 10.1186/s13073-025-01507-8
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C2 - 40676635
AN - SCOPUS:105011098494
SN - 1756-994X
VL - 17
JO - Genome Medicine
JF - Genome Medicine
IS - 1
M1 - 80
ER -