The prevalence of obesity among solid organ transplant recipients has risen steadily over recent decades in parallel to global population trends [1, 2]. Registry analyses indicate higher mean BMI at the time of listing and transplantation nowadays when compared with historical cohorts [3–5]. This epidemiological shift has major clinical implications, as obesity is associated with increased perioperative risk, altered pharmacokinetics of immunosuppressive agents, and long-term metabolic complications that can compromise graft function [6–8]. Obesity has therefore transitioned from a secondary comorbidity to a primary determinant of transplant outcomes, underscoring the need for risk-adapted recipient selection, perioperative management, and individualized immunosuppressive strategies [9, 10]. This narrative review aims to provide an integrated overview of obesity-related immunological and pharmacokinetic alterations in transplantation, and to define a framework for individualized immunosuppressive strategies in obese recipients.

Obesity has profound impact on the pharmacokinetics and pharmacodynamics of immunosuppressive drugs. Here, alterations may occur at virtually every step of drug disposition: absorption, distribution, metabolism, and clearance [45, 46]. Increased adipose mass and lean body mass expand the volume of distribution for lipophilic agents, while hepatic steatosis and comorbid metabolic syndrome may impair drug metabolism [47]. Moreover, renal hyperfiltration in obesity alters the clearance of renally excreted metabolites [48]. These metabolic-driven changes translate into significant variability in drug exposure, complicating therapeutic drug monitoring and raising the risk of both rejection and toxicity [49, 50] (see Figure 2).

As already discussed for the individual immunosuppressive agents, therapeutic drug monitoring (TDM) is indispensable in obese transplant recipients, but conventional trough-level monitoring may be unreliable due to obesity-related changes and disturbances. In detail, trough concentrations of tacrolimus do not consistently predict overall exposure [51, 54], and similar limitations have been reported for cyclosporine [46]. This mismatch thus raises the risk of relevant therapeutic misclassification in patients with obesity. Here, limited-sampling approaches and Bayesian AUC estimation may pave the way towards more accurate dosing strategies by providing better correlation with exposure. However, these techniques remain underutilized in current routine care [80]. Along the same lines, AUC-based monitoring correlates more closely with outcomes than fixed dosing for MMF, as shown in a multicenter trial where individualized exposure significantly improved patient outcomes [68]. Another important aspect of tailoring is the choice between weight-based and fixed-dose regimens. Weight-based dosing often leads to overexposure in obese patients, particularly for CNIs and mTOR inhibitors [49, 51]. Therefore, fixed dosing with close monitoring appears safer but is still associated with the potential risk of impaired efficacy. Although desperately needed, no consensus guidelines currently exist [45]. When striving out for concepts beyond pharmacokinetics, biomarker-based strategies may further help to refine immunosuppression intensity. Here, donor-specific antibody monitoring, immune cell functional assays (such as IFN-γ ELISPOT), and transcriptomic signatures have demonstrated additional prognostic value [81]. Therefore, integration of TDM with biomarker-based tools might represent the next level in precision transplant pharmacology [82].

When comparing drug classes, the individual profile of each immunosuppressive agent reveals both obesity-specific strengths and limitations. While still representing the gold standard of immunosuppression in the global population, CNIs remain highly effective in obese transplant recipients, but their use in this particular patient subgroup is complicated by pharmacokinetic variability, nephrotoxicity, and the limited reliability of trough levels; moreover, tacrolimus in particular confers a substantially increased risk of post-transplant diabetes, a complication of major concern in this population [45, 46]. Here, mTOR inhibitors provide an alternative to CNIs and allow for minimization strategies but frequently exacerbate dyslipidemia and insulin resistance, thereby worsening metabolic syndrome in obese recipients [60, 61, 83]. Mycophenolate mofetil is generally well tolerated but may exhibit exposure variability that may be even altered by obesity [50, 64]. Glucocorticoids remain the most problematic class, as their adverse metabolic effects directly overlap with the obesity phenotype, although systematic obesity-specific pharmacokinetic data are lacking [70, 71]. Of note, belatacept has emerged as an attractive therapeutic option because of its nephroprotective properties, fixed intravenous dosing, and absence of metabolic toxicity [77, 78, 84]. However, recent evidence indicates that obese recipients treated with belatacept may experience a higher incidence of acute rejection, highlighting the need for careful patient selection and close immunological monitoring [79].

Taken together, these cross-class comparisons underscore that none of the presented immunosuppressive agents provides an ideal single solution for obese graft recipients. Yet, a rational, tailored combination—balancing efficacy, nephroprotection, and metabolic safety—may offer the opportunity to optimize clinical outcomes. Framing immunosuppression within an individualized, obesity-aware therapeutic strategy may thus transform the apparent challenge into an opportunity for precision medicine in transplantation.

Since no single immunosuppressive agent provides an ideal solution for obese transplant recipients, this obvious limitation should rather serve as the starting point for future precision approaches.

In detail, pharmacogenomic testing, most notably CYP3A5 genotyping for tacrolimus, may represent another tangible strategy for individualized dosing. Growing evidence supports its value in optimizing initial dosing, although robust outcome data in obese patient cohorts remain scarce [85–87]. In addition, advances in biomarker-based monitoring—including donor-derived cell-free DNA, microRNAs, chemokine panels, and gene expression profiling—offer further noninvasive tools for dynamic immunological risk assessment [88, 89]. The Barcelona Consensus already recommended integrating biomarkers into clinical immunosuppressive drug management, while acknowledging that most assays still remain under evaluation and are not yet ready for broad implementation [90].

Beyond pharmacogenomic profiling and pharmacokinetic monitoring, biomarker-based approaches are increasingly being explored to refine immunological risk assessment. Here, donor-derived cell-free DNA (dd-cfDNA) is currently the most advanced tool in this context and has already shown good performance for the detection of allograft injury, particularly antibody-mediated rejection, although its specificity remains limited, as elevated levels may also occur in the setting of infection or non-immune injury [89, 91].

Other platforms, including circulating microRNAs, chemokine panels, and gene expression profiling, provide complementary insights into immune activation and graft injury. Among these approaches, dd-cfDNA is currently the most clinically advanced and widely implemented one, whereas transcriptomic platforms are gaining increasing traction in selected settings. In contrast, microRNAs and chemokine-based assays remain largely investigational, with limited availability in routine clinical practice. While these approaches have shown promising diagnostic accuracy in selected settings, their clinical implementation is still limited by the lack of standardized assays and consistent validation across centers [88, 89]. Transcriptomic strategies, in particular, are increasingly incorporated into clinical algorithms, especially in heart and kidney transplantation, but their broader applicability remains under evaluation [82, 89].

Despite these advances, several barriers continue to limit the routine use of biomarker-based monitoring, including costs, limited availability outside specialized centers, and inter-variability between platforms with respect to thresholds and analytical performance [89]. Of critical relevance, prospective data demonstrating a clear impact on clinical outcomes are still scarce.

Importantly, data on biomarker performance in obese transplant recipients are largely lacking. Given that obesity is associated with chronic low-grade inflammation, altered immune cell function, and a high burden of metabolic comorbidities, biomarker readouts may be more difficult to interpret in this population [92]. This represents a relevant knowledge gap and highlights the need for further studies specifically addressing biomarker-guided immunosuppression across different metabolic phenotypes. In this context, obesity may represent a clinically relevant stress model to test and refine biomarker-driven precision immunosuppression strategies.

Of note, real-world analyses have already begun to address obese populations specifically: a propensity-matched study in kidney transplantation demonstrated that immunosuppressive protocol choice significantly influences outcomes in obese recipients, supporting the concept of tailored immunsuppressive approaches [61].

From this perspective, obesity should not only be regarded as a potentially deleterious patient´s variable but rather as an ideal clinical scenario for the implementation of precision medicine in clinical transplantation. Here, integrating TDM, pharmacogenomics, and validated biomarkers with detailed phenotyping and computational modeling may truly enable individualized immunosuppressive regimens although further prospective validation will be crucial (see Figure 3).

Building on these concepts, a pragmatic framework for individualized immunosuppressive management in obese transplant recipients can be proposed. While high-quality prospective data are lacking, several principles emerge from available pharmacokinetic and clinical evidence. A concise overview of key drug-specific considerations is summarized in Table 1. In general, fixed or capped dosing strategies may be preferable to total body weight-based approaches for lipophilic agents such as calcineurin inhibitors, in order to reduce the risk of overexposure and toxicity. Early and repeated therapeutic drug monitoring, ideally incorporating AUC-based approaches where feasible, appears particularly important in this population, especially for agents such as tacrolimus and mycophenolate.

Drug class selection should be primarily considered based on the metabolic and clinical profile of the individual patient. In detail, calcineurin inhibitor minimization strategies may be considered in individuals at high risk of nephrotoxicity, whereas mTOR inhibitors require caution in patients with pre-existing dyslipidemia or impaired wound healing. Mycophenolate exposure may be reduced in obese recipients, supporting the use of exposure-guided dosing strategies. In selected cases, belatacept-based regimens may offer a metabolically favorable alternative, although data in obese populations remain limited.

Importantly, these considerations should not be interpreted as prescriptive recommendations but rather as a conceptual framework to support individualized decision-making. Integration of pharmacokinetic monitoring, emerging biomarkers, and clinical phenotyping is likely essential to optimize the balance between rejection and toxicity in this complex patient population.

In addition to immunosuppressive tailoring, adjunctive management of obesity-related metabolic risk is becoming increasingly relevant in transplant recipients. Emerging evidence suggests that glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium–glucose cotransporter-2 inhibitors (SGLT2 inhibitors) may improve body weight, glycemic control, and cardiovascular risk profiles in selected transplant populations, particularly after kidney transplantation [93, 94]. Available studies further indicate an overall favorable safety profile, with no consistent evidence for clinically relevant interactions with standard immunosuppressive agents, although gastrointestinal intolerance with GLP-1RAs and genitourinary infections with SGLT2 inhibitors remain important considerations [93, 94].

Yet, the underlying evidence is still largely observational, and transplant-specific prospective data remain limited [93–95]. These agents should therefore be viewed as promising adjuncts within a multidisciplinary metabolic strategy rather than as established components of immunosuppressive management.

Despite a growing body of evidence, important gaps of knowledge continue to limit the development of evidence-based strategies for obese transplant recipients. Most pharmacokinetic studies remain small and retrospective [47, 49, 51], and only few trials prespecify obesity as a stratification variable, thus leaving uncertainty about optimal dosing [5, 11]. Especially steroids are understudied in this vulnerable population [69, 70], and current data rarely integrate obesity-driven inflammation, pharmacokinetic variability, and clinical outcomes within the same cohorts [82]. Large datasets seldom include detailed body composition or metabolic phenotyping [43], and mechanistic insights such as histopathological correlates are only rarely linked with pharmacological and clinical data [15].

A major limitation in current practice is the reliance on body mass index as the primary measure of obesity. Additional metrics such as waist-to-hip ratio, visceral fat quantification, and CT-based skeletal muscle index provide a more refined assessment of metabolic and immunological risk and may better identify high-risk phenotypes such as sarcopenic obesity. BMI does not reflect body composition or fat distribution and therefore provides only a limited estimate of metabolic risk. In this context, visceral adiposity and ectopic fat appear to be more closely linked to metabolic and inflammatory complications than overall body weight. Similarly, sarcopenic obesity—defined by the coexistence of excess adiposity and reduced muscle mass—has been associated with frailty and poorer post-transplant outcomes [96].

Imaging-based approaches, particularly computed tomography-based assessment of skeletal muscle mass, as well as functional measures of body composition, may allow for a more accurate characterization of metabolic risk. Integrating these parameters into clinical studies and transplant registries could improve risk stratification and help refining immunosuppressive strategies according to individual metabolic risk profiles [96].

Nevertheless, these challenges outline a clear roadmap for future research. Obesity-stratified randomized controlled trials, adequately powered pharmacokinetic/pharmacodynamic studies, and systematic evaluation of AUC-based monitoring will be essential [68, 80]. Advances in model-informed precision dosing, pharmacogenomics, and biomarker-guided immunomonitoring offer unprecedented opportunities towards individualized immunosuppressive therapy [82, 97]. Integrating these tools with detailed phenotyping and computational prediction models may help to transform the current limitations into actionable strategies [97].

In summary, obesity consistently emerges as a risk factor for inferior graft outcomes, higher perioperative morbidity, and increased metabolic complications across solid organ transplantation [7, 8]. By understanding the complex interplay of obesity-induced inflammation, pharmacokinetic variability, and immunological risk [33, 38], clinicians will have to move beyond “one-size-fits-all” approaches. Here, tailoring immunosuppression through therapeutic drug monitoring, biomarker-guided adjustments, and precision dosing algorithms holds the promise of improving long-term graft survival and patient wellbeing in this high-risk population [66, 68, 82, 97]. From this perspective, obesity should not only be regarded as a clinical challenge but as an ideal context for precision medicine, where individualized strategies can turn risk into opportunity.