Pre-transplant hepatic steatosis (fatty liver) is associated with chronic graft-vs-host disease but not mortality

Metabolic syndrome prevalence and impact on outcomes in patients with chronic graft-versus-host disease

Patients with chronic graft-versus-host disease (cGVHD) are at heightened risk for components of metabolic syndrome (MetS), yet the prevalence and impact of MetS in the cGVHD patient population remain unknown. Adult patients (n = 229) with cGVHD enrolled in the cross-sectional NIH cGVHD Natural History Study (NCT00092235) were evaluated for MetS at enrollment and for variables associated with MetS. A majority (54.1%, 124/229) of the cohort met the diagnostic criteria for MetS. Patients with higher body mass index and lower performance status scores were more likely to have MetS (P < 0.0001; P = 0.026; respectively). Higher circulating erythrocyte sedimentation rate, C-reactive protein, and creatinine concentrations, along with lower estimated glomerular filtration rate, were associated with MetS (P < 0.001; P < 0.004; P = 0.02; P = 0.002; respectively). Patients with MetS compared to patients without MetS had no statistical differences in survival or NRM (5-year OS: 64% [95% CI: 54.8-71.8%] vs. 75.1% [95% CI: 65.6-82.3%]; respectively; overall P = 0.20; 5-year NRM: 21.7% [95% CI: 13.6-30.9%] vs. 10.1% [95% CI: 4.4-18.7%]; respectively; overall P = 0.12). Additionally, there was no difference in cGVHD severity between the two groups. Given the high prevalence of MetS in this cohort, clinicians should screen for its presence before it develops into comorbidities that complicate the course of cGVHD treatment.

Hepatic graft-versus-host disease: what we know, when to biopsy, and how to diagnose

Graft-versus-host disease (GVHD) is one of the serious complications that may develop after hematopoietic cell transplantation (HCT), for hematologic malignancies, solid organ transplantation, and other hematologic disorders. GVHD develops due to T lymphocytes present in the graft attacking the host antigens, which results in tissue damage. A significant number of HCT patients develop acute or chronic GVHD, which may affect multiple organs including the liver. The diagnosis of hepatic GVHD (hGVHD) is challenging as many other conditions in HCT patients may lead to liver dysfunction. Particularly challenging among the various conditions that give rise to liver dysfunction is differentiating sinusoidal obstruction syndrome and drug-induced liver injury (DILI) from hGVHD on clinical grounds and laboratory tests. Despite the minimal risks involved in performing a liver biopsy, the information gleaned from the histopathologic changes may help in the management of these very complex patients. There is a spectrum of histologic features found in hGVHD, and most involve histopathologic changes affecting the interlobular bile ducts. These include nuclear and cytoplasmic abnormalities including dysmorphic bile ducts, apoptosis, and cholangiocyte necrosis, among others. The hepatitic form of hGVHD typically shows severe acute hepatitis. With chronic hGVHD, there is progressive bile duct loss and eventually fibrosis. Accurate diagnosis of hGVHD is paramount so that timely treatment and management can be initiated. Techniques to prevent and lower the risk of GVHD from developing have recently evolved. If a diagnosis of acute GVHD is made, the first-line of treatment is steroids. Recurrence is common and steroid resistance or dependency is not unusual in this setting. Second-line therapies differ among institutions and have not been uniformly established. The development of GVHD, particularly hGVHD, is associated with increased morbidity and mortality.

Novel pre-clinical mouse models for chronic Graft-versus-Host Disease

Despite considerable progress in allogeneic hematopoietic cell transplantation (allo-HCT) has been achieved over the past years, chronic Graft-versus-Host Disease (cGvHD) still contributes to high morbidity rates, thus remaining a major hurdle in allo-HCT patients. To understand the complex pathophysiology of cGvHD and to develop refined prophylaxis and treatment strategies, improved pre-clinical models are needed. In this study, we developed two murine cGvHD models, which display high long-term morbidity but low mortality and depict the heterogeneous clinical manifestations of cGvHD seen in patients. We established a haploidentical C57BL/6→B6D2F1 allo-HCT model that uses myeloablative radiation and G-CSF-mobilized splenocytes as stem cell source and a sub-lethally irradiated Xenograft model, which utilizes the transfer of human peripheral blood mononuclear cells (PBMCs) into NOD scid gamma (NSG)-recipients. We characterized both mouse models to exhibit diverse clinical and histopathological signs of human cGvHD as extensive tissue damage, fibrosis/sclerosis, inflammation and B cell infiltration in cGvHD target organs skin, liver, lung and colon and found a decelerated immune cell reconstitution in the late phase after HCT. Our pre-clinical models can help to gain a deeper understanding of the target structures and mechanisms of cGvHD pathology and may enable a more reliable translation of experimental findings into the human setting of allo-HCT.

Acute Graft-Versus-Host Disease After Orthotopic Liver Transplantation: Predicting This Rare Complication Using Machine Learning

Acute graft-versus-host disease (GVHD) is a rare complication after orthotopic liver transplantation (OLT) that carries high mortality. We hypothesized that machine-learning algorithms to predict rare events would identify patients at high risk for developing GVHD. To develop a predictive model, we retrospectively evaluated the clinical features of 1938 donor-recipient pairs at the time they underwent OLT at our center; 19 (1.0%) of these recipients developed GVHD. This population was divided into training (70%) and test (30%) sets. A total of 7 machine-learning classification algorithms were built based on the training data set to identify patients at high risk for GVHD. The C5.0, heterogeneous ensemble, and generalized gradient boosting machine (GGBM) algorithms predicted that 21% to 28% of the recipients in the test data set were at high risk for developing GVHD, with an area under the receiver operating characteristic curve (AUROC) of 0.83 to 0.86. The 7 algorithms were then evaluated in a validation data set of 75 more recent donor-recipient pairs who underwent OLT at our center; 2 of these recipients developed GVHD. The logistic regression, heterogeneous ensemble, and GGBM algorithms predicted that 9% to 11% of the validation recipients were at high risk for developing GVHD, with an AUROC of 0.93 to 0.96 that included the 2 recipients who developed GVHD. In conclusion, we present a practical model that can identify patients at high risk for GVHD who may warrant additional monitoring with peripheral blood chimerism testing.