The association between deceased donor body mass index and liver steatosis, fibrosis, portal infiltrates and patients’ prognosis: a retrospective cohort study

Introduction

With the improvement of techniques in liver transplantation (LT), including living donor LT (LDLT) (1,2), it has become a life-saving procedure for patients with end-stage liver disease and certain acute liver conditions (3,4). The outcomes of LT are influenced by multiple factors, including patient characteristics, surgical techniques, postoperative management and immunosuppressive regimen (5). Recipient characteristics, such as the Model for End-Stage Liver Disease (MELD) score, age, comorbidities (e.g., diabetes, obesity), significantly affect postoperative outcomes (6,7). Postoperative management, particularly immunosuppression and infection prevention, is critical to minimizing complications such as rejection and sepsis (8). Disease-specific factors, notably in hepatocellular carcinoma (HCC) and alcohol-associated liver disease (ALD), also influence recurrence and survival, with biomarkers like alpha-fetoprotein (AFP) and neutrophil-to-lymphocyte ratio (NLR) emerging as key predictors (9). Donor-related variables, including donor age, liver steatosis, and the Donor Risk Index (DRI) (10), donor health and lifestyle, all can affect transplant outcomes (11). One such factor is the donor’s body mass index (BMI), which is increasingly being recognized as a crucial determinant of liver quality (12).

Higher BMI is associated with an increased risk of liver steatosis or fatty liver disease (13). Liver steatosis can range from mild to more severe grades based on the percentage of lipid droplet accumulation in the liver cell. Its two main phenotypes include macrovesicular and microvesicular steatosis, distinguished by the lipid drop size with widespread differences in molecular characterization in metabolic pathways (14,15). Liver fibrosis, often accompanied by steatosis, is the excessive accumulation of extracellular matrix proteins, ultimately leading to liver cirrhosis (16). Portal inflammatory infiltrate, which involves the infiltration of inflammatory cells into the liver’s portal tracts, refers to the immune-activated status of the donor’s liver and complicates the procedure of LT (17). Existing studies have primarily focused on the impact of donor BMI on liver histopathological features, such as steatosis and fibrosis, mainly within specific disease models, including metabolic dysfunction-associated steatotic liver disease (MASLD), viral hepatitis, and alcoholic hepatitis (13,16). However, a significant gap in research examining the differential effects of BMI on various steatosis subtypes (macrovesicular vs. microvesicular) and portal inflammatory infiltrate patterns, particularly in complex donor populations with multiple comorbidities, exists.

Understanding the relationship between donor BMI and liver histology is crucial for improving LT outcomes. Higher BMI is associated with an increased risk of liver steatosis and fibrosis (18), which can impair graft function and increase the risk of poor prognosis (19,20). Higher donor BMI is recognized as a risk factor for LT and European Association for the Study of the Liver (EASL) clinical practice guidelines recommend donor BMI should be <30 kg/m² (21), exerting no significant impact on post-transplant prognosis based on two-level BMI grade (BMI >30 kg/m² and BMI ≤30 kg/m²) (22). However, the controversy comes out with a recent systematic meta-analysis by Alnagar et al. (23), including six studies with 5,071 liver transplant recipients, found no negative impact of donor obesity on graft or patient outcomes. The authors attributed this contrasting outcome to potential selection bias, as grafts from obese donors often undergo a biopsy to exclude steatosis, and recipients are typically at low risk. Existing research lacks detailed subgroup analysis for donors with BMI <30 kg/m², particularly in distinguishing finer BMI gradations within this range, which may contribute to this controversy. There is a remarkable gap between long-term follow-up data and large-cohort studies focusing on this population.

To address these gaps, we analyzed data from the United Network for Organ Sharing (UNOS), encompassing a larger sample size from diverse populations. The aim of this study was to analyze its relationship with four key histological liver parameters: macrovesicular and microvesicular steatosis, liver fibrosis, and portal inflammatory infiltrate, based on a four-level BMI grading system. The insights from this study can refine the criteria for selecting donor livers based on BMI and other related factors, leading to more accurate recipient matching and, ultimately, improved LT success rates. We present this article in accordance with the STROBE reporting checklist (available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-19/rc).

Methods

Database and study cohort

The data analyzed in this study were from the UNOS (unos.org), the contractor for the Organ Procurement and Transplantation Network, released on April 1, 2024. All data were anonymized and handled following stringent data use agreements and security protocols. Perspectives and conclusions presented in this manuscript reflect the authors’ views and do not represent the official stance of any government.

Donor study population and exclusion criteria

Data from a total of 291,377 deceased donors were procured between 1987 and 2024. Inclusion and exclusion criteria were as follows: Donors with hepatic microsteatosis and macrosteatosis (n=61,848) were enrolled. Donors without liver fibrosis and portal inflammatory infiltrate records (n=22,921), other missing variables (n=2,812), and donors under 18 years of age (n=586) were excluded. A final cohort 1 of 35,529 donors, stratified by donor BMI as recorded in UNOS, was analyzed. We included cohort 2 of LT recipients, comprising 79,968 patients, excluding donor age <18 years, lack of HCC diagnosis, and lack of survival time (lost to follow-up). The flow chart illustrates the donor selection process for the final cohort (Figure 1). Ethics approval for the study protocol was exempted by the Ethics Review Committee of The First Affiliated Hospital of Kunming Medical University because the OPTN database is deidentified and publicly available. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Figure 1 Flow chart showing the process of donor selection and exclusion. GTIME, graft survival time; HCC, hepatocellular carcinoma; KM, Kaplan-Meier; PTIME, patient survival time; RCS, Restricted Cubic Spline; UNOS, United Network for Organ Sharing.

BMI classification

We utilized the criteria of weight for adults for BMI classification (24). Given the large sample size, the dose-response relationship between BMI and donor liver quality could be assessed in detail. The BMI categories were defined as follows: <18 kg/m² (lean), 18–25 kg/m² (normal), 25–30 kg/m² (overweight), and >30 kg/m² (obese).

Quality assessment of donor liver and outcomes

After procurement, the donor liver quality was assessed by biopsy pre-transplantation, including evaluation for macrosteatosis and microsteatosis, liver fibrosis, and portal inflammatory infiltrate. UNOS mandates that participating institutions stain for histopathology using standardized protocols with hematoxylin and eosin, as well as fat-specific methods (Oil red O) to identify and quantify fatty deposits in the parenchyma (25). Steatosis grading was based on cross-sectional hepatic histology with varying threshold percentages: mild (<30%) and moderate-to-severe (≥30%) for both macrosteatosis and microsteatosis. Donor fibrosis was valued by the Ishak criteria (26). Significant fibrosis was indicated by grade 3 or more, and portal inflammatory infiltrate was classified as positive for grades 0–4. The primary outcomes for this study were: ≥30% for both macrosteatosis and microsteatosis, significant fibrosis, portal inflammatory infiltrate in donor liver, graft, and patient survival.

Covariates

In cohort 1, potential confounders included baseline age (continuous), sex (male or female), ethnicity (white, non-Hispanic, Hispanic/Latino, or others), history of hypertension (yes or no), history of coronary artery disease (yes or no), history of myocardial infarction, history of diabetes (yes or no), status of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, alcohol heavy consumption (yes or no), smoking status (never, past, or current within six months and 20 packs/year), and liver function tests at procurement [serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), and total bilirubin (TBILI); continuous]. In cohort 2, recipient age, sex, and HCC were the confounders.

Owing to the retrospective design, there may be a potential for selection bias. To mitigate this shortcoming, we employed specific inclusion and exclusion criteria to ensure a representative sample. We conducted subgroup and sensitivity analyses with multivariables to assess the robustness of our findings.

Statistical analysis

Baseline characteristics are presented as means (standard deviation) or medians [interquartile range (IQR)] for continuous variables and as frequencies (percentages) for categorical variables, stratified by BMI category. We assessed the impact of BMI on survival outcomes post-transplantation, including both patient and graft survival. A multi-model logistic regression was employed to explore the association between different BMI categories and liver conditions, while considering potential modifying effects of donor-related factors. A restricted cubic spline (RCS) regression model was used to assess the potential nonlinear relationship between BMI and changes in liver histology. Estimates were adjusted for donor sex, age, hypertension, coronary artery disease (CAD), MI, diabetes, status of HBV and HCV, alcohol, and smoking. Differences in these characteristics were assessed using analysis of variance (ANOVA) or Kruskal-Wallis H tests for continuous variables and chi-squared tests for categorical variables. All statistical tests were two-tailed. The significance level was set at P<0.05. Statistical analyses were performed using R Studio (version 4.3).

Results

Baseline characteristics

Baseline characteristics of donors in each group based on BMI categories are shown in Table 1. Liver quality varied across BMI categories. Moderate-severe macrosteatosis percentages increased with BMI: lean (7.88%), normal (10.70%), overweight (14.13%), and obesity (20.90%) (P<0.001). Moderate-to-severe microsteatosis showed a similar trend: lean (6.68%), normal (10.10%), overweight (12.82%), and obesity (15.86%) (P<0.001). Significant fibrosis (Grade 3–6) percentages differed across BMI categories: lean (5.48%), normal (5.99%), overweight (4.86%), and obesity (4.68%) (P<0.001). The percentage of grades 1–4 portal inflammatory infiltrate increased with BMI: lean (51.71%), normal (53.11%), overweight (56.88%), and obesity (57.99%) (P<0.001).

Association between BMI and hepatic histology

In logistic regression analysis based on BMI grade, types of covariates were sequentially included to explore confounding factors (Figure 2). Model 1 is a crude model; in Model 2, sex, age, metabolic diseases (e.g., hypertension, coronary heart disease, diabetes), viral hepatitis (HBV, HCV), and lifestyle factors (e.g., alcohol abuse and smoking) were added. The association between BMI and histology outcomes (macrosteatosis, microsteatosis, fibrosis, portal inflammatory infiltrate) remained significant after adjusting for different covariates. In Model 1 (crude model), obesity showed increased risk for moderate to severe macrosteatosis [odds ratio (OR): 2.2, 95% confidence interval (CI): 2.04–2.39, P<0.001], moderate-to-severe microsteatosis (OR: 1.68, 95% CI: 1.55–1.82, P<0.001), and portal inflammatory infiltrate (OR: 1.22, 95% CI: 1.16–1.28, P<0.001). After adjustment, obesity remained associated with macrosteatosis (OR: 2.29, 95% CI: 2.11–2.49, P<0.001), microsteatosis (OR: 1.71, 95% CI: 1.57–1.87, P<0.001), and portal inflammatory infiltrate (OR: 1.37, 95% CI: 1.30–1.45, P<0.001), showing independent risk for moderate-to-severe macrosteatosis, microsteatosis, and portal inflammatory infiltrate. Obesity was not a significant risk factor for fibrosis in the crude model; however, after adjusting for several covariates, obesity significantly influenced fibrosis (OR: 1.2, 95% CI: 1.07–1.36, P<0.01), compared with the overweight group. The normal group showed significant risk in model 1 (OR: 1.3, 95% CI: 1.14–1.48, P<0.001) and model 2 (OR: 1.26, 95% CI: 1.1–1.43, P<0.001).

Figure 2 Associations of donor BMI with liver histology. Model 1: crude. Model 2: adjust—sex, age, hypertension, CAD, MI, diabetes, HBV, HCV, heavy alcohol consumption, smoking. BMI, body mass index; CAD, coronary artery disease; CI, confidence interval; Fibrosis, G3–6 fibrosis; HBV, hepatitis B virus; HCV, hepatitis C virus; Infiltrate, G1–4 portal inflammatory infiltrate; Macrosteatosis, moderate-severe macrosteatosis; MI, myocardial infarction; Microsteatosis, moderate-severe microsteatosis; OR, odds ratio.

We applied an RCS regression model to explore the potential nonlinear association of continuous BMI with liver steatosis and other outcomes (Figure 3). Distinct associations between BMI and donor liver histology are shown. For moderate-to-severe macrosteatosis (Figure 3A) and portal inflammatory infiltrate (Figure 3D), an S-shaped relationship was observed, with reference points at BMI equal to 29.6 kg/m² (P for all <0.001, P for nonlinearity <0.001 and P for all <0.001, P for nonlinearity <0.01, respectively). For moderate-to-severe microsteatosis (Figure 3B), an upside-down U-shaped relationship was observed, with the highest OR in the 30–60 kg/m² range (P for all <0.001, P for nonlinearity <0.001). G3-6 fibrosis (Figure 3C) followed a U-shaped relationship, with OR peaking at low and high BMI levels (P for all <0.001, P for nonlinearity <0.01). Further analysis of the curve showed a BMI value of 25.37 and 29.40 kg/m² as the critical inflection point, marking a shift in the pattern of the association.

Figure 3 Association of BMI with liver macrosteatosis and microsteatosis, significant fibrosis, and portal inflammatory infiltrate. Figures show associations of BMI with moderate-severe macrosteatosis (A), with moderate-severe microsteatosis (B), with liver G3–6 fibrosis (C), with G1–4 portal inflammatory infiltrate (D). Estimates were adjusted for donor sex, age, hypertension, CAD, MI, diabetes, status of HBV and HCV, alcohol, and smoking. Solid lines are multivariable adjusted ORs, with the area showing 95% CIs derived from restricted cubic spline regressions with four knots. The dashed line indicates a reference for no association at a hazard ratio of 1.0. The curve indicates a BMI value of 25.37 kg/m² and 29.40 kg/m² in (C). BMI, body mass index; CAD, coronary artery disease; CALC, calculated; CI, confidence interval; DON, donor; HBV, hepatitis B virus; HCV, hepatitis C virus; MI, myocardial infarction; OR, odds ratio.

Association between donor BMI and post-transplant outcomes

We included the LT recipients in cohort 2 and excluded the donor age <18 years (n=79,968). Kaplan-Meier and pairwise survival analysis, as well as univariable and multivariable Cox model, were used (Figure 4). The Kaplan-Meier survival analysis revealed differences in survival outcomes among BMI groups, with P<0.01 and P=0.03 for patients and grafts, respectively, following more than 25-year follow-up (Figure 4A,4B). Compared with the normal BMI group, both lean (HR 1.15, 95% CI: 1.01–1.30, P=0.02) and obese donors (HR 1.05, 95% CI: 1.02–1.10, P=0.04) exhibited higher risks of graft failure, and similar results were observed for patient survival (HR =1.07, 95% CI: 1.02–1.30, P=0.03 and HR =1.17, 95% CI: 1.02–1.30, P<0.01). Multivariable Cox analysis showed lower donor BMI as an independent risk factor influencing graft survival and patient survival (HR =1.16, 95% CI: 1.02–1.30, P=0.03; and HR =1.17, 95% CI: 1.02–1.30, P=0.02, respectively). Thus, we inferred that BMI significantly influenced post-transplant survival, with both lean and obese groups exhibiting worse survival outcomes and increased mortality risk. Lean donor was an independent risk factor affecting patient and graft survival more than other groups.

Figure 4 Graft and patient survival analysis based on BMI categories. (A,B) Kaplan-Meier curves for graft and patient survival stratified by donor BMI categories (Normal, Lean, Overweight, Obesity). Log-rank test P values are P=0.03 and <0.01, for pairwise comparisons between BMI groups. (C,D) Univariate Cox regression analysis for graft survival and patient survival. (E,F) Multivariate Cox regression model for graft and patients’ survival, adjusted for potential confounders (sex, age, HCC). BMI, body mass index; CI, confidence interval; HCC, hepatocellular carcinoma; HR, hazard ratio.

Subgroup and sensitivity analyses

In subgroup and sensitivity analyses, continuous BMI generally showed a stable effect across most subgroups for macrosteatosis, microsteatosis, and portal inflammatory infiltrate, with significant interactions observed between BMI and certain covariates (Table 2). Specifically, for macrosteatosis, notable interactions were identified with sex (P for interaction <0.01), hypertension (P for interaction =0.03), heavy alcohol consumption (P for interaction <0.001), and HCV (P for interaction =0.03). Similarly, for microsteatosis, significant interactions with sex (P for interaction =0.003), CAD (P for interaction =0.01), and HCV (P for interaction <0.01) were observed. For portal inflammatory infiltrate, age (P for interaction =0.04) and CAD (P for interaction =0.01) showed significant interactions with BMI. For G3–6 fibrosis, significant interactions were found with heavy alcohol consumption (P for interaction =0.047), CAD (P for interaction =0.045), and diabetes (P for interaction =0.01), underscoring the importance of these covariates, suggesting that these factors modify the association between BMI and liver fibrosis.

Discussion

In this comprehensive study, we assessed the association between donor BMI and liver health indicators (steatosis, fibrosis, portal inflammatory infiltrate) and post-transplant outcomes in the largest cohort of liver transplant donors to date, utilizing precise histological assessments and long-term follow-up data. Our findings substantiate the association between BMI and hepatic steatosis, fibrosis, and portal inflammatory infiltrate, corroborating existing literature on the detrimental effects of obesity on donor liver histology and pathology change (27-29). Our findings provide novel insights into specific BMI categories (BMI <30 kg/m²), revealing the distinct impact of lower BMI on fibrosis and post-transplant outcomes.

Our results confirm previous observations that elevated BMI is a risk factor for moderate-to-severe liver steatosis, while extending these findings through detailed analysis of steatosis subtypes. The RCS analysis (Figure 3) revealed differential patterns between macrovesicular and microvesicular steatosis: macrovesicular steatosis exhibited a progressive increase with increasing BMI, whereas microvesicular steatosis plateaued beyond a specific BMI threshold. These findings are relevant in the context of MASLD, associated with both steatosis subtypes in our donor population (30-32).

The RCS analysis demonstrated a U-shaped relationship between BMI levels and significant fibrosis, indicating elevated risk at both extremes of the BMI spectrum (BMI >29.40 kg/m² and BMI <25.37 kg/m²). This finding partially aligns with the J-shaped correlation reported by Liu et al. (33), who identified an inflection point at 23.05 kg/m² for BMI and liver stiffness. In contrast, our cohort exhibited a more pronounced effect size at lower BMI levels. We observed methodological variations between logistic regression and RCS analyses, which could be attributed to differences in BMI data treatment (categorical vs. continuous variables). Specifically, categorical analysis using a 25 kg/m² cutoff may have contributed to these discrepancies. Nevertheless, both analytical approaches consistently demonstrated the association of both lower and higher BMI levels with increased fibrosis risk, evident in the continuous variable analysis.

While our findings contradict the predominantly reported dose-dependent linear relationship between BMI and fibrosis (34), this discrepancy may be explained by the unique characteristics of our donor population. The higher prevalence of lean donors with underlying conditions, such as HBV, HCV, and alcoholic liver disease in our cohort likely influenced the observed outcomes, providing valuable insights into the complex interplay between BMI and liver health in transplant donors.

Our analysis of BMI and portal inflammatory infiltrate adds a novel dimension to the literature, as few studies have examined this specific feature in donor livers. Portal inflammatory infiltrate, characterized by inflammatory cells in the liver’s portal tracts, is increasingly being recognized as a marker of immune activation and liver injury. Common in alcoholic and metabolic-associated liver diseases, portal inflammatory infiltrate is associated with advanced disease stages (35). This is relevant to transplantation, where inflammation in the donor liver can amplify post-transplant immune responses, further increase the risk of graft rejection or dysfunction and negatively impacting graft survival (36). Our findings underscore the importance of considering BMI as a marker for immune-related alterations affecting liver immune status.

Donor obesity (BMI >30 kg/m²) increases the risk of post-transplant complications and graft failure (37-39). Existing studies might be subject to selection bias as the grafts from obese donors are usually subject to biopsy to exclude steatosis, and the recipients are categorized as low-risk (37-38). Our findings extend this understanding by demonstrating that both low and high BMI donors posed significant risks to graft and patient survival, with lean donors potentially presenting a greater risk than obese donors in our cohort (Figure 4). “Lean donor” was identified as the only independent risk factor in BMI grades for both patient and graft survival through multivariable Cox regression analysis (Figure 4). The association between low BMI and adverse outcomes may be attributed to several underlying factors. From baseline characteristics, lean donors were more frequently associated with HCV, HBV, heavy alcohol consumption, and higher fibrosis risk, all known to compromise transplant success. Importantly, low BMI often reflects the end-stage status of these chronic conditions rather than representing a healthy physiological state. These findings underscore the importance of comprehensive donor evaluation, specifically, BMI as a key clinical parameter in transplant candidate selection.

Our findings highlight the complex, multifaceted relationship between BMI and donor liver histology, affected by several confounding factors. We included various donor-related factors, including age, sex, and metabolic comorbidities, to better understand interactions between BMI and liver outcomes. Male donors, older age groups, and individuals with a history of hypertension or diabetes are particularly vulnerable to the negative impact of elevated BMI on liver quality. These interactions align with previous findings showing that components of metabolic syndrome, such as hypertension and diabetes, exacerbate liver steatosis and fibrosis (40-42). Such donor characteristics should inform LT decision-making.

Strengths and limitations

This study’s strengths include its large sample size and use of the well-established UNOS national database, encompassing comprehensive data on donor characteristics and results of liver biopsy. The application of advanced statistical techniques, such as RCS regression, allowed us to uncover nonlinear relationships between BMI and liver histology, and multivariable regression with strong validation for BMI impact on post-transplant outcome.

However, our study has some limitations that warrant further consideration. First, its observational design limits our ability to establish causation between BMI and liver steatosis, fibrosis, and portal inflammatory infiltrate. Despite adjusting for multiple confounders, residual confounding by unmeasured variables (e.g., diet and physical activity) may be present. Second, variability in liver biopsy interpretation between pathologists and centers could have introduced bias. Third, even though with long-term follow-up, graft survival analysis spanned 30 years; however, chronic rejection or late-onset complications were not enrolled in the study. Lastly, our findings may be limited in generalizability due to the demographic composition of donors in the UNOS database, which may not fully represent donors’ characteristics.

Conclusions

In summary, our study provides valuable insights into the complex association between donor BMI and hepatic macrosteatosis, microsteatosis, fibrosis, portal inflammatory infiltrate, and post-transplant outcome, with significant implications for LT practices. These findings strongly support the use of BMI as a vital screening tool for assessing liver histology and identifying high-risk donors. Future research should focus on BMI-based risk stratification to optimize donor-recipient matching and explore interventions that improve transplant outcomes.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-19/rc

Peer Review File: Available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-19/prf

Funding: This work was supported by Major Science and Technology Projects in Yunnan Province (No. 202302AA310025). The funding source had no role in the design, conduct, or reporting of this study.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tgh.amegroups.com/article/view/10.21037/tgh-25-19/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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