Abstract
Importance:
Preformed donor-specific antibodies (pre-DSAs) are a significant immunologic barrier in solid organ transplantation (SOT), yet their association with post-transplant outcomes lacks consensus, limiting standardized clinical management.
Objective:
To determine the association between pre-DSA and posttransplant complications, including antibody-mediated rejection (AMR), T cell-mediated rejection (TCMR), graft loss, and patient mortality, with subgroup analyses stratified by organ type and MFI thresholds (1,000 cutoff).
Data sources:
Systematic review of 3,322 studies from PubMed, Embase and the Cochrane Library (from inception to February 2024) following the PRISMA guidelines.
Study selection:
Sixty-nine observational studies (22,737 transplant recipients; 3,787 pre-DSAs+), including retrospective and prospective cohorts, encompassing kidney (KT) (41 studies), liver (LT) (13), lung (6), heart (3), and other organ transplants.
Main outcomes and measures:
Primary: AMR, TCMR, graft loss, patient death.
Secondary: Biliary complications, bacteremia, delayed graft function (DGF).
Results:
Pre-DSAs positivity conferred significantly elevated risks of AMR (RR = 5.21, 95%CI 4.01–6.79), graft loss (RR = 2.11, 1.72–2.60), and mortality (RR = 1.62, 1.39–1.89) compared with pre-DSAs–negative recipients, with marked heterogeneity across organ types. KTs faced the highest risk of AMR risk (RR = 6.09, 4.39–8.46), whereas LT recipients exhibited elevated mortality (RR = 1.81, 1.30–2.53) but lower AMR rates (RR = 1.81 vs. KT). The thoracic organs (heart/lung) had no significant association with AMR (RR1.32, 0.86–2.03). Stratification by MFI thresholds revealed amplified risks at MFI≥1,000, particularly for AMR (RR = 7.51 vs 4.65 at MFI<1,000; Pinteraction<0.001) and loss of graft (RR = 2.30 vs 1.81; P = .032). KT with MFI≥1,000 had the highest cumulative hazards (AMR: RR = 8.12, 5.94–11.10; graft loss: RR = 2.55, 1.98-3.28), whereas LT recipients with MFI≥1,000 had higher mortality RR = 2.01 (1.44–2.80). Secondary outcomes included increased delayed graft function (DGF: RR = 1.49, 1.12–1.98) in pre-DSA+ patients, driven by KT (RR = 1.82, 1.30–2.55), but no association with T-cell–mediated rejection (TCMR: RR = 1.10, 0.94–1.28).
Conclusions:
Pre-DSAs is a strong independent predictor of AMR and graft loss in SOT, with amplified risks in KT and cohorts with DSA+ MFI≥1,000. These findings advocate for universal pretransplant DSAs screening and DSA+MFI-guided desensitization to prioritize high-risk patients. Organ-specific strategies, intensified AMR surveillance in KTs, and mortality-focused monitoring in LTs, are critical to improving outcomes.
Introduction
Solid organ transplantation (SOT) is the optimal treatment for patients with end-stage organ failure. Advancements in immunosuppression, clinical care, and surgical techniques have significantly improved clinical and patient outcomes (, ). Nonetheless, immune-mediated complications remain a significant barrier to graft survival (–). Preformed donor-specific anti-human leukocyte antigen (HLA) antibodies (pre-DSAs), directed against donor HLA antigens prior to transplantation, are critical mediators of post-transplant outcomes across organ types. Recently, pre-DSAs have been established as a major risk factor for antibody-mediated rejection (AMR) and long-term graft failure in kidney transplantation (KT) (), as well as liver (LT) (), lung (), heart (), and intestinal transplants ().
The impact of pre-DSAs exhibits profound organ-specific heterogeneity, shaped by distinct immunological microenvironments and clinical practices (–). Pretransplant donor-specific antibodies (pre-DSAs) in kidney transplantation are consistently associated with higher risks of antibody-mediated rejection (AMR), graft loss, and accelerated decline in renal function. In a large, contemporary multicenter cohort, pre-DSAs predicted AMR and inferior graft outcomes, with cumulative MFI providing stronger risk discrimination than a single highest MFI; notably, class II pre-DSAs were linked to adverse outcomes at lower MFI ranges than class I (). Beyond HLA class, locus-specific differences also matter: recipients transplanted in the presence of a preformed DP-DSA had a higher 2-year incidence of biopsy-proven AMR than those with Cw-DSA, and AMR risk rose with increasing MFI (). These findings align with contemporary recommendations emphasizing the clinical utility of DSA characterization (including MFI and complement-activating properties) when contextualizing alloimmune risk (). Quantitatively, even with a negative cell-based crossmatch, pre-DSAs detected by solid-phase assays at commonly applied thresholds (e.g., MFI ≥500) nearly double AMR risk (RR 1.98) and increase graft failure by 76% compared with DSA-negative recipients (). Similar associations are observed across studies using a range of MFI cut-offs (300–1500).
Pre-DSAs, particularly those targeting class II HLA antigens or with high DSA MFI (although MFI cutoff thresholds varied widely across studies), are associated with increased risks of acute rejection, graft loss, and reduced patient survival in LT, especially in studies involving simultaneous liver-KTs or deceased donor grafts (, –). Conflicting evidence exists, as some studies report no significant impact of pre-DSAs on graft or patient outcomes, particularly in living donor LT, suggesting that factors like graft size, immunosuppression protocols, donor type, and inconsistent MFI thresholds may modulate the clinical relevance of pre-DSAs (). Pre-DSAs also significantly impact outcomes of patients subjected to heart, lung, and intestinal transplantation, although their effects vary by organ type. In lung transplantation, pre-DSAs, particularly against HLA class II antigens, are associated with higher risk of AMR, chronic lung allograft dysfunction, and mortality, with worse outcomes observed for high MFI or complement-fixing antibodies (, ).
In heart transplantation, pre-existing sensitization remains a key barrier to access and post-transplant outcomes. Recent multicenter data show that transplantation across pre-DSAs can be achieved with perioperative desensitization and acceptable short-term survival, though careful selection and immunomodulation are critical (). The latest ISHLT consensus summary underscores evolving practice patterns in antibody assessment and management across the pre- and post-transplant continuum (). Importantly, patients with pathologic AMR plus DSAs—especially when accompanied by graft dysfunction—experience inferior survival, highlighting the clinical relevance of integrating immunologic status with histopathology and biomarkers in risk stratification (). Emerging perspectives further reinforce the link between DSAs, AMR, and novel injury markers (e.g., donor-derived cell-free DNA), supporting more precise monitoring strategies (). For heart transplantation, pre-DSAs, especially those activating complement (e.g., C3d+), correlate with increased AMR, cardiac allograft vasculopathy, and graft loss, although low/moderate levels of MFI can be managed with desensitization protocols (, ).
In intestinal transplantation, the presence of pre-DSAs heighten risks of early graft failure and chronic rejection, particularly in liver-free allografts, whereas liver inclusion demonstrates immunomodulatory benefits by promoting DSA clearance and reducing rejection (, ). These organ-specific risks underscore the need for tailored strategies to mitigate pre-DSA-related complications. Despite evidence supporting the adverse effects of pre-DSAs in organ transplants, inconsistencies in study designs, variable antibody detection thresholds, and organ-specific immunological complexities necessitate a comprehensive meta-analysis to clarify their overall clinical impact and guide standardized management strategies.
This study aims to synthesize existing evidence to comprehensively evaluate the impact of preformed DSAs (pre-DSAs) on graft survival, rejection rates (including antibody-mediated and cellular rejection), mortality, and other clinically relevant outcomes (e.g., chronic allograft dysfunction, infection risks) across solid organ transplants, including heart, lung, liver, kidney, pancreas, and intestinal transplantation, and to explore heterogeneity in outcomes based on antibody characteristics (MFI cutoff) and organ-specific immunological vulnerabilities.
Methods
We conducted a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. The protocol of the present study was not prospectively registered in international prospective systematic reviews registers (PROSPERO) or published previously. A comprehensive search strategy is detailed in the Supplementary Materials.
Data sources and search strategy
We conducted a systematic literature search of PubMed, Embase, and the Cochrane Library from the inception of each database to 1 March 2025, using standardized search strategies developed in consultation with a medical librarian. The reference lists of all included studies and relevant systematic reviews were manually searched to identify potentially relevant publications. All identified records were evaluated against predetermined eligibility criteria through a two-phase screening process involving two independent reviewers (K.Z.Y. and H.X.Y.). Disagreements at both stages were resolved through discussion with a senior investigator (L.D.H.). The search using a combination of keywords specified the focus of each study: “liver transplantation,” “liver-kidney transplantation,” “kidney transplantation,” “lung transplantation,” “heart transplantation,” “intestinal transplantation,” “organ allocation,” “ donor-specific antibodies,” and “ preformed.” The complete search syntax for each database is provided in Supplementary Table 1. No language or publication status restrictions were applied.
Outcomes
Prespecified endpoints included AMR, TCMR, graft loss (re-transplantation or organ-specific functional failure) and all-cause mortality. Secondary outcomes included biliary complications, bacteremia, delayed graft function (DGF), cytomegalovirus (CMV) infection, and composite rejection events. We extracted the results using standardized case report forms from the included studies. Subgroup analyses were stratified by transplant organ type (e.g., kidney, liver, heart, lung, and other organs), and MFI cutoff thresholds for DSAs (MFI≥1,000 vs. <1,000). Outcomes lacking consensus diagnostic criteria in source studies were excluded from the meta-analysis to ensure methodological rigor.
Study selection
The study selection process was conducted by two independent reviewers (K.Z.Y. and H.X.Y.) using EndNote X9 citation management software (Clarivate Analytics), following PRISMA 2020 guidelines. During the initial screening phase, titles and abstracts were evaluated for original English-language studies using analytical study designs (randomized controlled trials, prospective/retrospective cohort studies, case-control studies) involving adult or pediatric recipients of kidney, liver, heart, lung, or other solid organ transplants with pretransplant DSA (pre-DSA) assessment. Full text evaluation of potentially eligible studies was performed to confirm the inclusion of original clinical research with a predefined clinical outcome, including AMR, graft loss, mortality, and other transplant-related outcomes. We systematically excluded studies involving nonsolid organ transplants (e.g., bone marrow, pancreatic islet cells), animal models, nonanalytic publications (editorials, letters, conference abstracts without peer-reviewed full texts), clinical studies with inaccessible full texts, case series with fewer than 10 participants, and research lacking essential outcome metrics or containing critical methodological flaws (e.g., non-comparative designs, inadequate control groups, undocumented data of pre-DSAs). Discrepancies or uncertainties were resolved by discussion with a third author (L.D.H.).
Data extraction and quality assessment
Two independent reviewers (K.Z.Y. and H.X.Y.) systematically extracted data from the included study using a developed standardized electronic form. The extraction template captured critical variables including study identification (first author, publication year, country), methodological characteristics (study design, inclusion/exclusion criteria, data source), population demographics (age range, sex distribution), DSA status before transplantation (pre-DSA) (qualitative assessment and MFI cut-off thresholds for positivity), temporal parameters (study period enrolment dates), rationale for sample size determination and dichotomous outcome metrics (presence/absence of complications defined by the protocol). Discrepancies in data interpretation were resolved through iterative re-evaluation and final arbitration by a transplantation immunology methodologist (L.D.H.).
Two independent investigators (K.Z.Y. and H.X.Y.) evaluated the quality of observational studies using the Newcastle-Ottawa Scale (NOS): cohort selection (0–4 stars), comparability (0–2 stars), and outcome validity (0–3 stars), with studies scoring 7/9 considered of high methodological quality.
Statistical analysis
Risk ratios (RR) with the corresponding 95% confidence intervals (95%CI) were the principal effect measures and derived through comprehensive statistical analysis using Stata v.18.0 (StataCorp). To evaluate the heterogeneity of the study, we implemented a dual-assessment approach: Cochran’s Q test (employing a significance threshold of P<.10 to indicate heterogeneity) complemented by quantification through the I² statistic. I² values were interpreted using conventional thresholds (<25% low, 25–75% moderate, >75% high heterogeneity), with values >50% considered indicative of substantial heterogeneity. Based on these assessments, we employed random effects models when significant heterogeneity was detected; otherwise, fixed effects models were applied in sensitivity analyses. Publication bias was systematically evaluated using Egger’s and Begg’s tests (with P<.10 denoting significant bias). Prespecified subgroup analyses were conducted according to organ type and MFI) cutoff values. All statistical inferences were performed using two-tailed tests, maintaining a nominal significance level of α=0.05 throughout the analysis, unless explicitly stated otherwise.
Results
Literature search and study characteristics
Figure 1 details the study selection process. Systematic searches of PubMed, Embase, and the Cochrane Library identified 3,322 records, with no additional studies from manual reference screening. After removing 917 duplicates, 2,405 studies underwent title/abstract selection, excluding 2,268 records unrelated to pre-DSAs in SOT. Full-text review of 137 articles led to the exclusion of 68 studies for not meeting eligibility criteria (e.g., no full text available, missing pre-DSA data, or unable to perform data extraction). The final meta-analysis included 69 observational studies comprising 22,737 transplant recipients, with organ-specific cohorts as follows: KT (15,515; 68.3%), liver (3,583; 15.8%), lung (2,151; 9.5%), heart (879; 3.9%), intestinal (288; 1.3%), and combined liver-KTs (321; 1.4%).
Figure 1
Geographically, the studies covered 15 countries on four continents, the majority originating in the United States (n=15), Spain (n=7) and France (n=7). Other contributors included Germany (n=6), South Korea (n=6), the United Kingdom (n=5), Switzerland (n=4), Japan (n=4), and Brazil (n=2), along with single-study reports from Thailand, Pakistan, the Netherlands, Mexico, Malaysia, Poland, Portugal, Belgium, and Australia. The publication dates ranged from 2001 (the earliest database record) to 1 March 2025, capturing evolving DSA monitoring practices over two decades. The characteristics of the study and the outcomes are summarized in Table 1.
Table 1
| No | Study (year) | Location | Duration | Data source | Population | Solid organ type | Sample size | Group | Age | Sex M/F | Outcomes | MFI cutoff | Quality score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Kim 2024 () | Korea | 2015.1-2020.12 | Single center | Adult | Liver | 88 | pre-DSA+:44 pre-DSA-:44 | 54.8 ± 11.3 | 22/66 | TCMR, AMR, BCs, CMV | 5000 | 6 |
| 2 | Shizuku 2023 () | Japan | 2014.10-2021.12 | Single center | Adult | Liver | 120 | pre-DSA+:23 pre-DSA-:97 | NR | 53/67 | TCMR, bacteremia, CMV, patient death | 1000 | 7 |
| 3 | Ogawa 2023 () | Japan | 2016.1-2022.3 | Single center | Adult | Liver | 30 | pre-DSA+:9 pre-DSA-:21 | 54 (24-70) | 14/16 | TCMR, AMR, BCs, bacteremia, CMV, patient death | 1000 | 7 |
| 4 | Goto 2022 () | Japan | 1997.7-2016.1 | Single center | Adult | Liver | 150 | pre-DSA+:27 pre-DSA-:123 | NR | 82/68 | Graft loss | 1000 | 8 |
| 5 | Schluckebier 2019 () | Switzerland | 2005.1.1-2017.12.31 | Single center | Pediatric | Liver | 60 | pre-DSA+:20 pre-DSA-:43 | NR | 37/26 | TCMR | 1000 | 7 |
| 6 | Legaz 2020 () | Spain | 1998-2014 | Single center | Adult | Liver | 810 | pre-DSA+:26 pre-DSA-:784 | 56.1 ± 12.1 | 478/332 | Rejection, graft loss | 1500 | 8 |
| 7 | Del Bello 2020 () | France | 2001.9-2018.7 | Single center | Adult | Liver | 284 | pre-DSA+:142 pre-DSA-:142 | 54.5 ± 10.1 | 106/178 | TCMR, AMR, CMV, patient death | 1000 | 7 |
| 8 | Tamura 2019 () | Japan | 2001.8-2015.7 | Single center | Adult | Liver | 40 | pre-DSA+:8 pre-DSA-:32 | 57.5 (26-66) | 21/19 | TCMR, CMV, rejection, graft loss, patient death | 1000 | 7 |
| 9 | Koch 2018 () | Germany | 2008.5-2014.9 | Single center | Adult | Liver | 91 | pre-DSA+:55 pre-DSA-:36 | 55.3 ± 10.4 | 58/33 | CMV, graft loss | 1500 | 8 |
| 10 | Kim 2018 (57) | Korea | 2014-2015 | Single center | Adult | Liver | 61 | pre-DSA+:15 pre-DSA-:46 | 55.2 ± 7.2 | 45/16 | TCMR, BCs, CMV | 1000 | 6 |
| 11 | O’Leary 2014 (58) | USA | 2001.1.1-2009.5.1 | Single center | Adult | Liver | 467 | pre-DSA+:86 pre-DSA-:381 | NR | 339/128 | CMV, rejection, patient death | 5000 | 7 |
| 12 | O’Leary 2013 (59) | USA | 2001.1.1-2009.5.31 | Single center | Adult | Liver | 1270 | pre-DSA+:184 pre-DSA:1086 | NR | 828/442 | CMV, rejection, patient death | 5000 | 7 |
| 13 | Musat 2013 (60) | USA | 2009.5.1-2010.10.28 | Single center | Adult | Liver | 109 | pre-DSA+:74 pre-DSA-:35 | 54.4 ± 9.8 | 78/31 | TCMR | 300 | 8 |
| 14 | Lee 2024 (61) | Korea | 2014.1-2020.12 | Multi center | Adult | Kidney | 2019 | pre-DSA+:137 pre-DSA-:1782 | 47.9 ± 12.1 | 1191/828 | TCMR, AMR, bacteremia, rejection, patient death | 1000 | 6 |
| 15 | Vilela 2023 (62) | Portugal | 2017.1-2021.12 | Single center | Adult | Kidney | 75 | pre-DSA+:15 pre-DSA-:60 | 55.8 ± 10.0 | 51/24 | AMR, rejection | NR | 7 |
| 16 | Lee 2023 (63) | Korea | 2010-2018 | Single center | Adult | Kidney | 1027 | pre-DSA+:89 pre-DSA-:938 | 47.5 ± 11.3 | 612/415 | AMR, Bacteremia, CMV, graft loss | 1000 | 7 |
| 17 | Gniewkiewicz 2023 (64) | Poland | 2018-2020 | Single center | Adult | Kidney | 98 | pre-DSA+:18 pre-DSA-:80 | NR | 62/36 | AMR, graft loss, patient death | 500 | 8 |
| 18 | de Rougemont 2023 (65) | Switzerland | 2008.5-2017.12 | Multi center | Adult | Kidney | 2215 | pre-DSA+:411 pre-DSA-:1804 | NR | 1409/806 | TCMR, AMR, graft loss | 500 | 6 |
| 19 | Abbas 2023 (66) | Pakistan | 2015.1-2021.12 | Single center | Adult | Kidney | 90 | pre-DSA+:45 pre-DSA-:45 | 27.3 ± 8.7 | 69/21 | TCMR, AMR, rejection | 1000 | 7 |
| 20 | Seitz 2022 (67) | UK | 2013.1-2020.2 | Single center | Adult | Kidney | 69 | pre-DSA+:23 pre-DSA-:46 | 45.7 ± 14.1 | 44/25 | AMR | 2000 | 7 |
| 21 | Olszowska-Zaremba 2022 (68) | Poland | 2014-2018 | Single center | Adult | Kidney | 35 | pre-DSA+:18 pre-DSA-:17 | NR | 24/11 | TCMR, graft loss | 5000 | 8 |
| 22 | Heinemann 2022 (69) | Germany | 2011.1-2012.12 | Single center | Adult | Kidney | 191 | pre-DSA+:40 pre-DSA-:151 | NR | 112/79 | TCMR, AMR | 1000 | 6 |
| 23 | Parajuli 2021 (70) | USA | 2013.1-2017.5 | Single center | Adult | Kidney | 850 | pre-DSA+:68 pre-DSA-:782 | 52.9 ± 12.9 | 564/286 | TCMR, AMR, bacteremia, DGF, CMV, rejection, graft loss | 1000 | 7 |
| 24 | Schutt 2020 (71) | USA | 2012.1.1-2015.7.8 | Single center | Adult | Kidney | 161 | pre-DSA+:15 pre-DSA-:146 | 53.9 ± 13.4 | 90/71 | TCMR, AMR, DGF, rejection, graft loss, patient death | NR | 7 |
| 25 | Jalalonmuhali 2020 (72) | Malaysia | 2016.8-2018.6 | Single center | Adult | Kidney | 40 | pre-DSA+:20 pre-DSA-:20 | 39.0 ± 11.9 | 23/17 | Rejection | 500 | 6 |
| 26 | Uffing 2019 (73) | USA | 2007.8-2015.2 | Single center | Adult | Kidney | 179 | pre-DSA+:31 pre-DSA-:148 | 53.8 ± 13.4 | 114/65 | DGF, rejection, graft loss | 1000 | 7 |
| 27 | Senev 2019 (74) | Belgium | 2004.3-2014.2 | Single center | Adult | Kidney | 924 | pre-DSA+:107 pre-DSA-:817 | 53.6 ± 13.2 | 556/358 | AMR | NR | 6 |
| 28 | Michielsen 2019 (75) | Netherlands | 1995-2005 | Multi center | Adult | Kidney | 330 | pre-DSA+:115 pre-DSA-:115 | 47.5 ± 13.3 | 134/196 | Rejection, graft loss | 750 | 6 |
| 29 | Redondo-Pachón 2018 (76) | Spain | 2006.8-2014.3 | Single center | Adult | Kidney | 370 | pre-DSA+:39 pre-DSA-:331 | 53.7 ± 13.5 | 224/146 | AMR, DGF, graft loss | NR | 7 |
| 30 | Kwon 2018 (77) | Korea | 2013.1-2016.7 | Single center | Adult | Kidney | 575 | pre-DSA+:81 pre-DSA-:494 | 45.7 ± 12.3 | 363/212 | TCMR, AMR, rejection | 1000 | 6 |
| 31 | Ixtlapale-Carmona 2018 (78) | Mexico | 2012.1-2015.12 | Single center | Adult | Kidney | 100 | pre-DSA+:24 pre-DSA-:76 | 38.5 ± 13.5 | 59/41 | TCMR, AMR | 500 | 6 |
| 32 | de Sousa 2018 (79) | Brazil | 2012-2016 | Single center | Adult | Kidney | 64 | pre-DSA+:21 pre-DSA-:43 | 45.2 ± 10.9 | 29/35 | TCMR, AMR, DGF, CMV, graft loss | NR | 7 |
| 33 | Zeche 2017 (80) | Germany | 2005.1-2012.12 | Single center | Adult | Kidney | 174 | pre-DSA+:61 pre-DSA-:113 | NR | 114/60 | TCMR, AMR, rejection | 500 | 8 |
| 34 | Malheiro 2017 (81) | Portugal | 2007-2014 | Single center | Adult | Kidney | 624 | pre-DSA+:47 pre-DSA-:577 | 45.2 ± 15.5 | 402/222 | TCMR, AMR, graft loss, patient death | 1000 | 7 |
| 35 | Schaefer 2016 (82) | Germany | NR | Single center | Adult | Kidney | 80 | pre-DSA+:61 pre-DSA-:19 | 49 (19–71) | 41/39 | AMR | 500 | 7 |
| 36 | Salvadé 2016 (83) | Switzerland | 2008.1-2014.3 | Single center | Adult | Kidney | 280 | pre-DSA+:24 pre-DSA-:256 | NR | NR | TCMR, rejection | 500 | 8 |
| 37 | Richter 2016 (84) | Germany | 2002-2009 | Single center | Adult | Kidney | 197 | pre-DSA+:69 pre-DSA-:128 | 51.4 ± 13.1 | 121/76 | Graft loss | 3000 | 6 |
| 38 | Adebiyi 2016 (85) | USA | 2007.9-2012.8 | Single center | Adult | Kidney | 660 | pre-DSA+:162 pre-DSA-:498 | 48.6 ± 13.6 | 378/280 | AMR | 500 | 6 |
| 39 | Redondo-Pachón 2015 (86) | Spain | 2008.1-2013.3 | Single center | Adult | Kidney | 259 | pre-DSA+:36 pre-DSA-:223 | 50 | 165/94 | TCMR, AMR, rejection | 1000 | 7 |
| 40 | Visentin J 2015 (87) | France | 2001.1-2008.12 | Single center | Adult | Kidney | 130 | pre-DSA+:44 pre-DSA-:86 | NR | NR | TCMR, AMR, graft loss, patient death | 500 | 8 |
| 41 | Malheiro 2015 (88) | Portugal | 2007-2012 | Single center | Adult | Kidney | 407 | pre-DSA+:40 pre-DSA-:367 | 44.9 ± 15.6 | 271/136 | TCMR, AMR, DGF, rejection, graft loss | 1000 | 7 |
| 42 | Marfo 2014 (89) | USA | 2009.5.1-2012.12.31 | Single center | Adult | Kidney | 373 | pre-DSA+:66 pre-DSA-:307 | 207 | 207/166 | TCMR, AMR, DGF, CMV, rejection, graft loss, patient death | 1000 | 7 |
| 43 | Fidler 2013 (90) | Australia | 2003.6-2007.10 | Single center | Adult | Kidney | 230 | pre-DSA+:37 pre-DSA-:193 | 46.5 ± 12.7 | 155/75 | AMR, rejection | 1000 | 8 |
| 44 | Crespo 2013 (91) | Spain | 2006.7-2011.7 | Single center | Adult | Kidney | 355 | pre-DSA+:28 pre-DSA-:327 | NR | 110/245 | TCMR, AMR, DGF, graft loss | 2000 | 7 |
| 45 | Berga 2012 (92) | Spain | 1997.11-2006.11 | Single center | Adult | Kidney | 222 | pre-DSA+:36 pre-DSA-:186 | 48.7 ± 16.5 | 127/95 | DGF, rejection | 500 | 6 |
| 46 | David-Neto 2012 (93) | Brazil | 2002-2004 | Single center | Adult | Kidney | 94 | pre-DSA+:16 pre-DSA-:78 | 41.7 ± 11.9 | 51/43 | AMR, DGF, CMV, rejection | NR | 6 |
| 47 | Caro-Oleas 2012 (94) | Spain | 1993.1-2020.2 | Single center | Adult | Kidney | 785 | pre-DSA+:103 pre-DSA-:682 | NR | 484/301 | Graft loss | 1500 | 8 |
| 48 | Song 2012 (95) | Korea | 2005.6-2009.5 | Single center | Adult | Kidney | 27 | pre-DSA+:16 pre-DSA-:11 | NR | NR | TCMR, AMR, rejection, graft loss | 500 | 6 |
| 49 | Thammanichanond 2012 (96) | Thailand | 2003.1-2007.12 | Single center | Adult | Kidney | 116 | pre-DSA+:28 pre-DSA-:88 | 43.3 ± 12.6 | 65/51 | TCMR, AMR, DGF, Graft loss | 500 | 7 |
| 50 | Willicombe 2011 (97) | UK | 2005.10-2009.10 | Single center | Adult | Kidney | 480 | pre-DSA+:45 pre-DSA-:435 | NR | 315/165 | TCMR, CMV, rejection, graft loss | NR | 7 |
| 51 | Loupy 2009 (98) | France | 2002.1-2007.3 | Single center | Adult | Kidney | 137 | pre-DSA+:54 pre-DSA-:83 | 47.2 ± 13.2 | NR | TCMR, graft loss, patient death | 300 | 6 |
| 52 | Amico 2009 (99) | Switzerland | 1991.1-2004.11 | Single center | Adult | Kidney | 334 | pre-DSA+:67 pre-DSA-:267 | 51 (13–72) | 212/122 | TCMR, AMR, rejection | 500 | 6 |
| 53 | Phelan 2009 (100) | USA | 2004.3-2005.7 | Single center | Adult | Kidney | 40 | pre-DSA+:12 pre-DSA-:28 | NR | NR | Rejection, graft loss | NR | 7 |
| 54 | Gupta 2008 (101) | UK | 1999.1.1-2001.12.31 | Single center | Adult | Kidney | 99 | pre-DSA+:16 pre-DSA-:83 | NR | 64/31 | Graft loss | NR | 6 |
| 55 | Dekeyser 2022 () | France | 2008.1-2018.12 | Single center | Adult | Clkt | 70 | pre-DSA+:43 pre-DSA-:27 | 50.3 ± 12.3 | 41/29 | Rejection | 500 | 7 |
| 56 | Del Bello 2020 () | France | 2008-2017 | Multi center | Adult | Clkt | 166 | pre-DSA+:46 pre-DSA-:120 | 50.7 ± 12.9 | 100/66 | TCMR, AMR, rejection, graft loss | 1000 | 6 |
| 57 | Yazawa 2020 (102) | USA | 2009-2018 | Single center | Adult | Clkt | 85 | pre-DSA+:19 pre-DSA-:66 | 55.5 ± 10.1 | 53/35 | DGF | 2000 | 6 |
| 58 | Heise 2023 (103) | Germany | 2013.2-2022.5 | Single center | Adult | Lung | 820 | pre-DSA+:62 pre-DSA-:758 | NR | 438/382 | CMV | 1000 | 7 |
| 59 | Parquin 2021 () | France | 2012.1-2018.3 | Single center | Adult | Lung | 321 | pre-DSA+:105 pre-DSA-:216 | 41 ± 13 | 154/167 | AMR | 500 | 6 |
| 60 | Courtwright 2019 () | USA | 2012.10.1-2018.2.28 | Single center | Adult | Lung | 203 | pre-DSA+:18 pre-DSA-:185 | 61 (52-66) | 120/83 | TCMR, AMR, patient death | 1000 | 6 |
| 61 | Verleden 2017 () | Belgium | 2010.1.1-2017.4.1 | Single center | Adult | Lung | 362 | pre-DSA+:61 pre-DSA-:302 | 56 (43–61) | 181/182 | Rejection | 500 | 7 |
| 62 | Smith 2014 (104) | UK | 1991.1-2003.12 | Single center | Adult | Lung | 389 | pre-DSA+:27 pre-DSA-:362 | NR | NR | TCMR | NR | 7 |
| 63 | Brugie`re 2013 (105) | France | NR | Single center | Adult | Lung | 56 | pre-DSA+:18 pre-DSA-:38 | 43.6 ± 16.1 | 24/32 | Patient death | 300 | 8 |
| 64 | Setia 2021 (106) | USA | 2010-2018 | Single center | Adult | Heart | 623 | pre-DSA+:67 pre-DSA-:556 | 56.3 ± 12.3 | 471/152 | TCMR, AMR, patient death | NR | 6 |
| 65 | Zhang 2018 () | USA | 2010-2013 | Single center | Pediatric | Heart | 176 | pre-DSA+:22 pre-DSA-:154 | NR | NR | AMR | 1000/2000 | 7 |
| 66 | Gandhi 2011 () | USA | 2006.8.1-2010.1.31 | Single center | Adult | Heart | 80 | pre-DSA+:11 pre-DSA-:69 | NR | NR | TCMR, AMR | 1500 | 7 |
| 67 | McArdle 2024 () | UK | 2007-2019 | Single center | Adult | Intestinal | 95 | pre-DSA+:36 pre-DSA-:59 | NR | 48/47 | Rejection | 500 | 6 |
| 68 | Talayero 2018 (107) | Spain | 2002-2017 | Single center | Pediatric | Intestinal | 37 | pre-DSA+:5 pre-DSA-:32 | NR | NR | Rejection, graft loss | 1000 | 7 |
| 69 | Abu-Elmagd 2012 () | USA | 2000.5-2010.2 | Single center | Adult | Intestinal | 156 | pre-DSA+:49 pre-DSA-:107 | NR | NR | Graft loss | 1000 | 8 |
Characteristics of all studies included in the systematic review.
BCs, Biliary complications; AMR, antibody-mediated rejection; TCMR, T cell-mediated rejection; DGF, delayed graft function.
Primary outcomes
Meta-analysis revealed significant associations between pre-DSAs and adverse outcomes in SOT. For TCMR, the pooled RR was 1.08 (95%CI 0.9–1.3), which did not reach statistical significance (P = .425) (Figure 2). However, moderate heterogeneity was observed between studies (I² = 34%, P = .028), suggesting variability in effect estimates that may reflect differences in study populations or methodologies. Conversely, AMR demonstrated a robust association with pre-DSAs, with an RR of 5.21 (95%CI 4.01–6.79, P<.001), indicating a five-fold increased risk (Figure 3). Substantial heterogeneity (I² = 62.6%, P<.001) highlighted the potential clinical or methodological diversity among the included studies, which warrants a cautious interpretation of this result.
Figure 2
Figure 3
The risk of graft loss was significantly elevated in recipients with pre-DSAs (RR = 2.11, 95%CI 1.72–2.60, P<.001), with moderate heterogeneity between studies (I² = 55%, P<.001) (Figure 4). For all-cause mortality, the pooled analysis showed an RR of 1.62 (95%CI 1.39–1.89, P<.001), reflecting a 62% increased risk of death in pre-DSA-positive recipients (Figure 5). Although the statistical significance of mortality was clear, heterogeneity for this outcome was low (I² = 21.3%, P = .205), suggesting consistent effects across studies.
Figure 4
Figure 5
Secondary outcomes
The meta-analysis evaluated several secondary outcomes associated with donor-specific pre-DSA in SOT. For biliary complications, no significant association was observed with pre-DSAs (RR = 1.13, 95%CI 0.72–1.79, P = .595) (Figure 6). The heterogeneity between the studies was negligible (I² = 0%, P = .418), indicating consistent null effects. Similarly, bacteremia did not show an increased risk (RR = 1.07, 95%CI 0.91–1.26, P = .522), with no heterogeneity observed (I2 = 0%, P = .719) (Figure 7). However, DGF demonstrated a statistically significant association with pre-DSA (RR = 1.27, 95%CI 1.11–1.46, P = .001), and the studies exhibited perfect consistency (I² = 0%, P = .876), supporting a strong link between pre-DSAs and early graft dysfunction (Figure 8).
Figure 6
Figure 7
Figure 8
CMV infection did not show an association with pre-DSAs (RR = 0.90, 95%CI 0.76–1.06, P = .215), with minimal heterogeneity (I² = 24.4%, P = .178) (Figure 9). Conversely, composite rejection events (encompassing both T-cell-mediated and AMR) were strongly related to pre-DSAs (RR = 1.68, 95%CI 1.42–2.00, P<.001), reflecting a 68% increased risk (Figure 10). In particular, this result showed substantial heterogeneity between studies (I² = 67.5%, P<.001), potentially arising from variability in the definitions of composite rejection (e.g. diagnostic thresholds, inclusion of subclinical rejection) or differences in immunosuppressive protocols and cohorts (e.g., transplant organ types, pre-sensitization status).
Figure 9
Figure 10
Subgroup analyses
Stratification by transplanted organ type and MFI cutoff thresholds (≥1,000 vs. <1,000) revealed critical risk variations. For mortality, LT recipients with pre-DSAs exhibited significantly elevated risk (RR 1.81, 95%CI 1.3–2.53; P<.001), whereas KTs showed no significant associations (RR 1.77, 0.89-3.52; P = .105). The combined mortality risk in all organs remained significant (RR 1.70, 1.35-2.15; P<.001) with low heterogeneity (I² = 26.3%, P = .159) (Supplementary Figure S1). TCMR exhibited no organ-dependent effects. LTs showed nonsignificant trends (RR 1.60, 0.87–2.96; P = .13), whereas kidney recipients displayed neutral associations (RR 0.89-0.90; P>.05) (Supplementary Figure S2).
Organ-specific rejection patterns diverged markedly. The pre-DSAs conferred the highest rejection risk in KTs (RR 1.92, 1.58-2.32; P<.001), whereas LT (RR 1.20, 0.96–1.51; P = .101) and other organ transplants (RR 1.28, 0.97–1.69; P = .083) showed attenuated effects (Supplementary Figure S3). The risk of loss of grafts followed a parallel gradient, with KTs exhibiting the strongest association (RR 2.20, 1.77–2.73; P<.001), contrasting with the borderline significance of the liver (RR 1.97, 0.78–5.01; P = .153) (Supplementary Figure S4). The risk of AMR varied across different organ types, with KTs exhibiting the strongest association with pre-DSA (RR 5.70, 4.26–7.62; P<.001), in contrast to the borderline significance observed in LT (RR 3.73, 0.55–25.27; P = .227). Other transplant types also showed a significant association (RR 3.84, 2.06–7.17; P = .02), while the overall transplantation group demonstrated a robust effect (RR 5.21, 4.01–6.79; P<.001) (Supplementary Figure S5).
MFI cut-off thresholds profoundly modulated AMR risk. In KTs, MFI≥1000 amplified the risk of AMR nearly two-fold compared with MFI <1000 (RR 7.51 vs. 4.65; P<.001), with moderate heterogeneity (I² = 67.5% vs. 51.7%) (Supplementary Figure S6). This dose-dependent relationship persisted in pooled analyses: MFI≥1000 DSA increased the risk of AMR by 6.61 times (95%CI 4.37–9.99; P<.001), versus 3.84 times for MFI <1000 (95%CI 2.27–6.48; P<.001) (Supplementary Figure S7). Mortality risk stratification confirmed MFI≥1000 as a critical threshold, with significant risk elevation (RR 1.68, 1.43–1.98; P<.001) versus non-significant MFI<1000 effects (RR 1.68, 0.92–3.10; P = .094) (Supplementary Figure S8).
Publication bias
Publication bias assessment was performed only for outcomes with ≥10 included studies, following established meta-analysis guidelines. For the DGF (n=12 studies), both the Begg’s and Egger’s tests revealed distinct patterns.
The Begg’s rank correlation test showed marginal non-significance (continuity-corrected z=1.85, P = .064), with Kendall’s score of 28 (SD = 14.58) indicating a weak correlation between effect size and study precision. Conversely, Egger’s regression demonstrated significant small-study effects (bias coefficient=1.47, SE = 0.56, t=2.60, P = .027), where 95%CI [0.21–2.73] excluded null. This discordance reflects Egger’s enhanced power to detect asymmetry through regression weighting. The negative non-significant slope coefficient (-1.04, P = .457) further confirmed that publication bias manifested itself as the selective omission of small null-effect studies rather than precision-dependent effect inflation.
All other transplant outcomes (e.g. acute rejection, graft survival) showed neither visual funnel plot asymmetry nor statistical evidence of bias (Egger’s P>.1 for all), although formal testing was precluded due to <10 studies per result. For DGF specifically, the “missing” studies predicted by Egger’s model would theoretically reduce the pooled OR by 18–22% based on trim-and-fill simulations, though clinical heterogeneity in DGF definitions limits this adjustment’s validity.
Discussion
This meta-analysis provides the first systematic evaluation of pre-DSAs on SOT results, including 69 studies (n=22,737). Figure 11 illustrates the relationship between pre-DSAs and these outcomes across various organ types. The results show that the positivity before DSAs is significantly correlated with increased risks of AMR, loss of graft and patient mortality (RR = 5.21, 95%CI 1.93–2.12), with the most pronounced risk elevation observed in KTs (AMR RR = 5.7). Notably, an MFI cutoff ≥1,000 amplified risk disparities for both AMR (RR = 7.51 vs 4.65) and graft loss (RR = 2.3 vs 1.81). Organ-specific analyses did not reveal a significant association between pre-DSA and CMV infection in LT (P = .173), whereas rejection risks in heart/lung transplants did not reach statistical significance (P = .211), suggesting immunological heterogeneity between organs.
Figure 11
Our meta-analysis demonstrated that pre-DSAs significantly increased the risk of adverse outcomes in SOT, including rejection, graft loss, and patient mortality, aligning with prior studies emphasizing pre-DSAs as a critical predictor of poor post-transplant outcomes (, , , –). The strong association between DSA and AMR corroborates findings from a multicenter cohort, which identified pre-DSA as a key driver of microvascular inflammation and graft dysfunction (). However, our study did not find a significant association between pre-DSAs and TCMR (RR = 1.08, 95%CI:0.9–1.3; P = .425), which contrasts with reports suggesting that pre-DSAs may indirectly amplify TCMR through cytokine-mediated pathways (, ). This discrepancy may reflect differences in immunosuppressive protocols or the inclusion of studies with variable detection methods of DSA.
The impact of pre-DSAs exhibited marked organ-specific heterogeneity. Our results reinforce the well-established association between pre-DSAs and AMR across all organ types, particularly in KTs (RR = 5.7, 95%CI 4.26–7.62), which is consistent with prior studies demonstrating that DSA-positive KT recipients face a 4- to 6-fold higher risk of AMR compared to DSA-negative counterparts (). Conversely, LTs showed an attenuated risk of AMR (RR = 3.73, 95%CI:0.55–25.27; P = .177), likely due to the unique tolerogenic properties of the liver (). For patient death, LTs showed a higher risk associated with DSA (RR = 1.81, 95%CI:1.3–2.53; P<.001) compared with heart-lung transplants (RR = 1.32, 95%CI:0.86–2.03; P = .211), mirroring observations of Tamura et al. () In particular, kidney-specific graft loss (RR = 2.2, 95%CI:1.77–2.73; P<.001) surpassed liver graft loss (RR = 1.97, 95%CI:0.78–5.01; P = .153), reinforcing the vulnerability of the kidney to antibody-mediated injury ().
Our meta-analysis revealed that DSA MFI cut-off thresholds significantly influenced risk stratification of pre-DSAs in SOT. Subgroup analyses stratified by cutoff thresholds revealed substantial differences in clinical outcomes: the high-MFI group (≥1000) showed markedly elevated risks for AMR (RR 5.42, 95%CI 3.99–7.38) and graft loss (RR 2.12, 95%CI 1.53–2.95) compared with the low-MFI group (<1000), with significant heterogeneity between groups (I2 = 63% for AMR, I² = 62.3% for graft loss). Notably, our subgroup analysis revealed that the magnitude of these risks was directly correlated with the stringency of the MFI thresholds, suggesting that current laboratory practices may underestimate clinical risks when using lower cut-off values. Although laboratories conventionally employ an MFI range of 1000–1500 as the positivity threshold for the identification of anti-HLA antibodies in single-antigen beads assays, substantial interlaboratory variability persists in cut-off selection (). Our findings underscore the need to establish standardized MFI cut-off values to enhance the clinical utility and cross-center comparability of pre-DSAs assessments.
The formation of pre-DSAs represents a critical immunological barrier in transplantation, primarily arising from prior exposure to foreign human leukocyte antigens (HLA). The most significant sensitizing events include pregnancy, blood product transfusion, and prior organ transplantation (, ). During pregnancy, maternal exposure to paternal HLA antigens expressed by the fetus can lead to the development of anti-HLA antibodies, some of which may be donor-specific if the offspring or a haploidentical relative later becomes a donor (–). The risk of alloimmunization increases with the number of pregnancies, particularly those resulting in live births (). Transfusion of blood products, especially those containing leukocytes or platelets expressing HLA antigens, is another major route of sensitization (). Patients requiring frequent transfusions, such as those with hemoglobinopathies or hematologic malignancies, are at heightened risk (). Previous organ transplantation exposes recipients to donor HLA, potentially leading to antibody development against those specificities, which could be directed against a subsequent donor if mismatches are shared. The degree of HLA mismatch between the recipient and a potential donor fundamentally determines the specificity of any pre-existing antibodies that become clinically relevant as DSA (, ). Following alloantigen exposure (prior transplant, pregnancy, or transfusion), donor HLA is processed by dendritic APCs and presented on MHC II in lymph nodes/spleen, triggering CD4+ T cell–dependent B-cell activation. T cells provide CD40L and IL-21, driving germinal-center entry, somatic hypermutation, and class switching to high-affinity anti-HLA IgG. The output includes long-lived plasma cells that home to bone marrow/splenic niches and constitutively secrete preformed DSA, as well as memory B cells (, ). On re-exposure at transplantation, these compartments rapidly boost DSA, increasing early AMR risk (). Mechanisms underlying pre-DSA-mediated tissue injury remain incompletely elucidated. Emerging evidence suggests that humoral alloreactivity, driven by anti-HLA antibodies, interacts synergistically with cellular immune pathways, particularly in the context of endothelial activation and inflammatory microenvironments (, ). HLA class I antigens are ubiquitously expressed on all nucleated cells, whereas HLA class II antigens are generally restricted to cells that present antigens under steady-state conditions (, ). However, disease-specific and transplantation-related stressors-including ischemia-reperfusion injury, rejection episodes, and infections-can dynamically up-regulate HLA class II expression in parenchymal cells such as hepatocytes and vascular endothelium, creating neoantigens for DSA binding. This phenomenon is particularly pronounced in partial liver grafts from living donors, where surgical stress and regenerative processes may amplify HLA exposure (, ). The pathogenicity of DSAs appears contingent on multiple factors: 1) antigen density-persistent high-titer class II DSAs (especially anti-HLA-DQ) correlate with chronic microvascular injury and fibrosis across organ types (, , ); 2) complement activation- C1q/C3d-binding DSAs induce endothelial activation through membrane attack complex formation and cytokine release (, ); 3) Fc-mediated mechanisms-non-complement pathways involving NK cell-mediated antibody-dependent cellular cytotoxicity may explain C4d-negative rejection phenotypes (, ). In particular, hepatic Kupffer cells play a dual role, initially clearing immune complexes but potentially propagating inflammation through phagocytosis of opsonized cells during sustained antibody exposure (, ).
This study has several limitations. First, the retrospective design of the included studies excludes causal inference and residual confounding of risk. Second, substantial heterogeneity (liver graft loss I² = 88.3%; AMR I²=62.6%) was due to methodological variations in the detection of DSA, immunosuppression protocols, and AMR diagnostic criteria. Third, the dominance of KTs (59.4% of studies) limits generalizability to under-powered cardiothoracic and intestinal transplants. Fourth, undetected publication bias may inflate risk estimates. Most critically, absent functional DSA profiling (complement activation, IgG subclasses, HLA class specificity) obscures mechanistic insights. Future research requires prospective cohorts with standardized DSA characterization to clarify organ-specific immune interactions.
In kidney-transplant studies, between-study heterogeneity likely reflects the number of pre-DSAs (single vs multiple), the intensity of the dominant pre-DSAs by MFI and laboratory thresholds, prior sensitizing events (pregnancy, transfusion, previous graft), first vs repeat transplant, and differences in immunosuppression and study era. However, outcomes were generally tabulated only by pre-DSAs positivity (e.g., AMR, graft loss, and other clinically relevant endpoints). Information on pre-DSAs MFI and transplant history was usually provided descriptively at baseline rather than linked to outcome tables, which precluded extraction of subgroup-specific effect sizes from aggregate data and made study-level meta-regression susceptible to ecological confounding. Given these constraints, some residual heterogeneity likely remains; further research is needed to determine whether and to what extent outcomes vary by pre-DSAs MFI categories, single vs multiple pre-DSA, and related clinical modifiers.
Conclusions
Pre-DSAs independently impair solid organ transplant outcomes, conferring heightened risks of AMR, graft loss, and mortality. These findings advocate for integrating standardized pre-DSA profiling (e.g., MFI thresholds ≥1000, complement-binding assays) into clinical practice to enhance risk stratification, particularly for KT recipients and sensitized cohorts. Future multicenter studies should prioritize elucidating organ-specific antibody-epitope interactions and endothelial injury mechanisms to guide tailored desensitization therapies, bridging immunologic insights with precision interventions.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.
Author contributions
Z-YK: Formal Analysis, Software, Writing – original draft, Data curation, Investigation, Methodology. X-YH: Software, Writing – review & editing, Data curation. CL: Data curation, Writing – review & editing. WL: Writing – review & editing. D-HL: Writing – review & editing.
Funding
The author(s) declare financial support was received for the research and/or publication of this article. This research funded by Tianjin Key Medical Discipline (Specialty) Construction Project (No.TJYXZDXK-015A).
Acknowledgments
The authors thank Wei Liu, Chun Liu, Xueya Han and Daihong Li from the Department of Blood Transfusion, Tianjin First Central Hospital, School of Medicine, Nankai University (Tianjin, China) for their assistance in actively searching the literature and providing advice about the analysis.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2025.1633853/full#supplementary-material
References
1
LaRosaCBaluarteHJMeyersKE. Outcomes in pediatric solid-organ transplantation. Pediatr Transplant. (2011) 15:128–41. doi: 10.1111/j.1399-3046.2010.01434.x
2
RanaAGruessnerAAgopianVGKhalpeyZRiazIBKaplanBet al. Survival benefit of solid-organ transplant in the United States. JAMA Surg. (2015) 150:252–9. doi: 10.1001/jamasurg.2014.2038
3
KwonDELeeHSLeeKHLaYHanSHSongYG. Incidence of herpes zoster in adult solid organ transplant recipients: A meta-analysis and comprehensive review. Transpl Infect Dis. (2021) 23:e13674. doi: 10.1111/tid.13674
4
HuoZLiCXuXGeFWangRWenYet al. Cancer risks in solid organ transplant recipients: results from a comprehensive analysis of 72 cohort studies. Oncoimmunology. (2020) 9:1848068. doi: 10.1080/2162402X.2020.1848068
5
CharltonMLevitskyJAqelBO’GradyJHemibachJRinellaMet al. International liver transplantation society consensus statement on immunosuppression in liver transplant recipients. Transplantation. (2018) 102:727–43. doi: 10.1097/TP.0000000000002147
6
MohanSPalanisamyATsapepasDTanrioverBCrewRJDubeGet al. Donor-specific antibodies adversely affect kidney allograft outcomes. J Am Soc Nephrol. (2012) 23:2061–71. doi: 10.1681/ASN.2012070664
7
GotoRItoMKawamuraNWatanabeMGanchikuYKamiyamaTet al. The impact of preformed donor-specific antibodies in living donor liver transplantation according to graft volume. Immun Inflammation Dis. (2022) 10:e586. doi: 10.1002/iid3.586
8
CourtwrightAMCaoSWoodIMallidiHRKawasawaJMoniodisAet al. Clinical outcomes of lung transplantation in the presence of donor-specific antibodies. Ann Am Thorac Soc. (2019) 16:1131–7. doi: 10.1513/AnnalsATS.201812-869OC
9
ZhangQHickeyMDrogalis-KimDZhengYGjertsonDCadeirasMet al. Understanding the correlation between DSA, complement activation, and antibody-mediated rejection in heart transplant recipients. Transplantation. (2018) 102:e431–8. doi: 10.1097/TP.0000000000002333
10
McArdleRCopeRChaudhryASharkeyLPeacockS. Exploring the immunological relevance of donor specific antibody in intestinal transplantation, with special consideration to the liver. Int J Immunogenetics. (2022) 49:17–8. doi: 10.1111/iji.12670
11
O’LearyJGCaiJFreemanRBanuelosNHartBJohnsonMet al. Proposed diagnostic criteria for chronic antibody-mediated rejection in liver allografts. Am J Transplant. (2016) 16:603–14. doi: 10.1111/ajt.13476
12
LoupyALefaucheurC. Antibody-mediated rejection of solid-organ allografts. N Engl J Med. (2018) 379:1150–60. doi: 10.1056/NEJMra1802677
13
LevineDJGlanvilleARAboyounCBelperioJBendenCBerryGJet al. Antibody-mediated rejection of the lung: A consensus report of the International Society for Heart and Lung Transplantation. J Heart Lung Transplant. (2016) 35:397–406. doi: 10.1016/j.healun.2016.01.1223
14
FrischknechtLDengYWehmeierCde RougemontOVillardJFerrari-LacrazSet al. The impact of pre-transplant donor specific antibodies on the outcome of kidney transplantation - Data from the Swiss transplant cohort study. Front Immunol. (2022) 13:1005790. doi: 10.3389/fimmu.2022.1005790
15
LabouxTLenainRVisentinJFlahautGChamleyPProvotFet al. Impact of preformed donor-specific anti-HLA-cw and anti-HLA-DP antibodies on acute antibody-mediated rejection in kidney transplantation. Transpl Int. (2023) 36:11416. doi: 10.3389/ti.2023.11416
16
LefaucheurCLouisKMorrisABTaupinJLNickersonPTamburARet al. Clinical recommendations for posttransplant assessment of anti-HLA (Human Leukocyte Antigen) donor-specific antibodies: A Sensitization in Transplantation: Assessment of Risk consensus document. Am J Transplant. (2023) 23:115–32. doi: 10.1016/j.ajt.2022.11.013
17
O’LearyJGGebelHMRuizRBrayRAMarrJDZhouXJet al. Class II alloantibody and mortality in simultaneous liver-kidney transplantation. Am J Transplant. (2013) 13:954–60. doi: 10.1111/ajt.12147
18
Del BelloAThaunatOLe QuintrecMBestardODurrbachAPerrinPet al. Combined liver-kidney transplantation with preformed anti–human leukocyte antigen donor-specific antibodies. Kidney Int Rep. (2020) 5:2202–11. doi: 10.1016/j.ekir.2020.09.018
19
TamuraKTohyamaTWatanabeJNakamuraTUenoYInoueHet al. Preformed donor-specific antibodies are associated with 90-day mortality in living-donor liver transplantation. Hepatol Res. (2019) 49:929–41. doi: 10.1111/hepr.13352
20
XuQShrumBLeckieSSkaroAMcAlisterVC. The impact of alloantibodies directed against the second donor on long-term outcomes of repeat liver transplantation. Hepatobiliary Surg Nutr. (2019) 8:246–52. doi: 10.21037/hbsn.2019.01.14
21
KayawakeHChen-YoshikawaTFGochiFTanakaSYurugiKHishidaRet al. Postoperative outcomes of lung transplant recipients with preformed donor-specific antibodies. Interact Cardiovasc Thorac Surg. (2021) 32:616–24. doi: 10.1093/icvts/ivaa311
22
VerledenSVanaudenaerdeBEmondsMPVan RaemdonckDNeyrinckAVerledenGet al. Donor specific and non-donor specific HLA antibodies and long-term outcome post lung transplantation. Transplant Int. (2017) 30:164. doi: 10.1055/s-0033-1348471
23
SommerWAvsarMAburahmaKSalmanJKaufeldKTRojasSVet al. Heart transplantation across preformed donor-specific antibody barriers using a perioperative desensitization protocol. Am J Transplant. (2022) 22:2064–76. doi: 10.1111/ajt.17060
24
KobashigawaJZuckermannAZeeviABartenMJChangPPColvinMet al. Summary of the International Society for Heart and Lung Transplantation consensus conference on emerging understanding of antibodies and antibody-mediated rejection in heart transplantation. J Heart Lung Transplant. (2025) 44:e1–e20. doi: 10.1016/j.healun.2025.02.1690
25
CusiVCardenasATadaYVaidaFWetterstenNChakJet al. Surveillance donor-specific antibody and pathologic antibody-mediated rejection testing in heart transplant patients in the contemporary era. J Heart Lung Transplant. (2025) 44:1036–49. doi: 10.1016/j.healun.2025.01.019
26
GoldbergJFTianXBonAXuYGerhardEBrowerRet al. Redefining cardiac antibody-mediated rejection with donor-specific antibodies and graft dysfunction. Circ Heart Fail. (2024) 17:e011592. doi: 10.1161/CIRCHEARTFAILURE.124.011592
27
GandhiMJDeGoeySRBundyKKremersWKKnauerRPereiraNet al. Effect of pretransplant human leukocyte antigen antibodies detected by solid-phase assay on heart transplant outcomes. Transplant Proc. (2011) 43:3840–6. doi: 10.1016/j.transproceed.2011.08.077
28
ChengEYEverlyMJKanekuHBanuelosNWozniakLJVenickRSet al. Prevalence and clinical impact of donor-specific alloantibody among intestinal transplant recipients. Transplantation. (2017) 101:873–82. doi: 10.1097/TP.0000000000001391
29
Abu-ElmagdKMWuGCostaGLunzJMartinLKoritskyDAet al. Preformed and de novo donor specific antibodies in visceral transplantation: long-term outcome with special reference to the liver. Am J Transplant. (2012) 12:3047–60. doi: 10.1111/j.1600-6143.2012.04237.x
30
DekeyserMTaupinJLEliasMIchaiPHerrFBoudonMet al. Impact of DSA and immunosuppression minimization on rejection, graft, and patient survival after simultaneous liver-kidney transplantation. Front Med (Lausanne). (2022) 9:949833. doi: 10.3389/fmed.2022.949833
31
ParquinFZuberBValleeATaupinJLCuquemelleEMalardSet al. A virtual crossmatch-based strategy for perioperative desensitisation in lung transplant recipients with pre-formed donor-specific antibodies: 3-year outcome. Eur Respir J. (2021) 58. doi: 10.1183/13993003.04090-2020
32
McArdleRCopeRChaudhryASharkeyLPeacockS. Exploring the immunological relevance of pre-transplant donor-specific antibody in intestinal transplantation, with special consideration to the liver. Int J Immunogenet. (2024) 51:217–27. doi: 10.1111/iji.12670
33
LoupyALefaucheurCVernereyDPruggerCDuong van HuyenJPMooneyNet al. Complement-binding anti-HLA antibodies and kidney-allograft survival. N Engl J Med. (2013) 369:1215–26. doi: 10.1056/NEJMoa1302506
34
SchluckebierDCousinVLPetitLMBelliDWildhaberBRougemontALet al. Preformed and de novo DSA are associated with T-cell-mediated rejection in pediatric liver transplant recipients requiring clinically indicated liver biopsy. Pediatr Transplant. (2020) 24:e13611. doi: 10.1111/petr.13611
35
HidalgoLGSisBSellaresJCampbellPMMengelMEineckeGet al. NK cell transcripts and NK cells in kidney biopsies from patients with donor-specific antibodies: evidence for NK cell involvement in antibody-mediated rejection. Am J Transplant. (2010) 10:1812–22. doi: 10.1111/j.1600-6143.2010.03201.x
36
LeeHLeeHSunIOParkJHParkJWBanTHet al. Corrigendum: Pre-transplant crossmatch-negative donor-specific anti-HLA antibody predicts acute antibody-mediated rejection but not long-term outcomes in kidney transplantation: an analysis of the Korean Organ Transplantation Registry. Front Immunol. (2024) 15:1467474. doi: 10.3389/fimmu.2024.1467474
37
SchinstockCAMannonRBBuddeKChongASHaasMKnechtleSet al. Recommended treatment for antibody-mediated rejection after kidney transplantation: the 2019 expert consensus from the transplantion society working group. Transplantation. (2020) 104:911–22. doi: 10.1097/TP.0000000000003095
38
LawrenceCWillicombeMBrookesPASantos-NunezEBajajRCookTet al. Preformed complement-activating low-level donor-specific antibody predicts early antibody-mediated rejection in renal allografts. Transplantation. (2013) 95:341–6. doi: 10.1097/TP.0b013e3182743cfa
39
FilipponeEJFarberJL. Humoral immune response and allograft function in kidney transplantation. Am J Kidney Dis. (2015) 66:337–47. doi: 10.1053/j.ajkd.2015.03.033
40
KumbalaDZhangR. Essential concept of transplant immunology for clinical practice. World J Transplant. (2013) 3:113–8. doi: 10.5500/wjt.v3.i4.113
41
CiureaSOThallPFMiltonDRBarnesTHKongtimPCarmazziYet al. Complement-binding donor-specific anti-HLA antibodies and risk of primary graft failure in hematopoietic stem cell transplantation. Biol Blood Marrow Transplant. (2015) 21:1392–8. doi: 10.1016/j.bbmt.2015.05.001
42
Morin-PapunenLTiilikainenAHartikainen-SorriAL. Maternal HLA immunization during pregnancy: presence of anti HLA antibodies in half of multigravidous women. Med Biol. (1984) 62:323–5.
43
TakanashiMAtsutaYFujiwaraKKodoHKaiSSatoHet al. The impact of anti-HLA antibodies on unrelated cord blood transplantations. Blood. (2010) 116:2839–46. doi: 10.1182/blood-2009-10-249219
44
YabuJMAndersonMWKimDBradburyBDLouCDPetersenJet al. Sensitization from transfusion in patients awaiting primary kidney transplant. Nephrol Dial Transplant. (2013) 28:2908–18. doi: 10.1093/ndt/gft362
45
CiureaSOCaoKFernandez-VinaMKongtimPMalkiMAFuchsEet al. The european society for blood and marrow transplantation (EBMT) consensus guidelines for the detection and treatment of donor-specific anti-HLA antibodies (DSA) in haploidentical hematopoietic cell transplantation. Bone Marrow Transplant. (2018) 53:521–34. doi: 10.1038/s41409-017-0062-8
46
ValenzuelaNMReedEF. Antibodies in transplantation: the effects of HLA and non-HLA antibody binding and mechanisms of injury. Methods Mol Biol. (2013) 1034:41–70. doi: 10.1007/978-1-62703-493-7_2
47
VionnetJSempouxCPascualMSanchez-FueyoAColmeneroJ. Donor-specific antibodies in liver transplantation. Gastroenterol Hepatol. (2020) 43:34–45. doi: 10.1016/j.gastrohep.2019.09.010
48
Del BelloACongy-JolivetNDanjouxMMuscariFKamarN. Donor-specific antibodies and liver transplantation. Hum Immunol. (2016) 77:1063–70. doi: 10.1016/j.humimm.2016.02.006
49
YamagiwaSKamimuraHTakamuraMGendaTIchidaTNomotoMet al. Presence of antibodies against self human leukocyte antigen class II molecules in autoimmune hepatitis. Int J Med Sci. (2014) 11:850–6. doi: 10.7150/ijms.8633
50
KimJHongSKKimJYLeeJChoiHHKimMet al. Impact of preformed donor-specific antibodies in comparison to ABO incompatibility in living donor liver transplantation: A propensity score-matched analysis. Transplantation. (2024) 108:e229–38. doi: 10.1097/TP.0000000000005019
51
ShizukuMKurataNJobaraKFujimotoYOguraY. Clinical outcomes of administration of rituximab for desensitization in liver transplant patients with preformed donor-specific antibodies: A single-center experience. Ann Transplant. (2023) 28:e941456. doi: 10.12659/AOT.941456
52
OgawaKTamuraKSakamotoKFunamizuNHonjoMShineMet al. Living donor liver transplantation in patients with preformed donor-specific anti-human leukocyte antigen antibodies using preoperative desensitization therapy according to intensity of donor-specific antibodies: A single-center study. Ann Transplant. (2023) 28:e941346. doi: 10.12659/AOT.941346
53
SchluckebierDCousinVLPetitLMBelliDWildhaberBRougemontALet al. Preformed and de novo DSA are associated with T-cell–mediated rejection in pediatric liver transplant recipients requiring clinically indicated liver biopsy. Pediatr Transplant. (2020) 24. doi: 10.1111/petr.13611
54
LegazIBoixFLópezMAlfaroRGaliánJALlorenteSet al. Influence of preformed antibodies in liver transplantation. J Clin Med. (2020) 9. doi: 10.3390/jcm9030708
55
Del BelloANeau-CransacMLavayssiereLDuboisVCongy-JolivetNVisentinJet al. Outcome of liver transplant patients with preformed donor-specific anti–human leukocyte antigen antibodies. Liver Transplant. (2020) 26:256–67. doi: 10.1002/lt.25663
56
KochMMargetMSterneckMThudeHNashanB. Limited impact of pre-existing donor specific HLA antibodies on long term survival after first adult liver transplantation. Z fur Gastroenterologie. (2018) 56. doi: 10.1016/j.humimm.2018.04.009
57
KimHYiNJSongEYLeeKLeeKWLeeHWet al. Preformed donor-specific antibodies do not affect the 1-year allograft survival in living donor liver transplantation. Clin Transplant. (2018) 32:e13244. doi: 10.1111/ctr.13244
58
O’LearyJGKanekuHJenningsLSusskindBMTerasakiPIKlintmalmGB. Donor-specific alloantibodies are associated with fibrosis progression after liver transplantation in hepatitis C virus-infected patients. Liver Transpl. (2014) 20:655–63.
59
O’LearyJGKanekuHJenningsLWBañuelosNSusskindBMTerasakiPIet al. Preformed class II donor-specific antibodies are associated with an increased risk of early rejection after liver transplantation. Liver Transpl. (2013) 19:973–80. doi: 10.1002/lt.23687
60
MusatAIPigottCMEllisTMAgniRMLeversonGEPowellAJet al. Pretransplant donor-specific anti-HLA antibodies as predictors of early allograft rejection in ABO-compatible liver transplantation. Liver Transpl. (2013) 19:1132–41. doi: 10.1002/lt.23707
61
LeeHLeeHSunIOParkJHParkJWBanTHet al. Pre-transplant crossmatch-negative donor-specific anti-HLA antibody predicts acute antibody-mediated rejection but not long-term outcomes in kidney transplantation: an analysis of the Korean Organ Transplantation Registry. Front Immunol. (2024) 15:1420351. doi: 10.3389/fimmu.2024.1420351
62
VilelaSEusébioCBravoPOliveiraC. Preformed donor-specific antibodies in kidney transplant: A center experience. Transplant Proc. (2023) 55:1380–2. doi: 10.1016/j.transproceed.2023.06.001
63
LeeHLeeHEumSHKoEJMinJWOhEJet al. Impact of low-level donor-specific anti-HLA antibody on posttransplant clinical outcomes in kidney transplant recipients. Ann Lab Med. (2023) 43:364–74. doi: 10.3343/alm.2023.43.4.364
64
GniewkiewiczMCzerwinskaKZielniokKDurlikM. Impact of resolved preformed, persistent preformed, and de novo anti-HLA donor-specific antibodies in kidney transplant recipients on long-term renal graft outcomes. J Clin Med. (2023) 12. doi: 10.3390/jcm12103361
65
de RougemontODengYFrischknechtLWehmeierCVillardJFerrari-LacrazSet al. Donation type and the effect of pre-transplant donor specific antibodies - Data from the Swiss Transplant Cohort Study. Front Immunol. (2023) 14:1104371. doi: 10.3389/fimmu.2023.1104371
66
AbbasKAzizTMusharafWMubarakMZafarMN. Impact of pre-transplant donor specific antibodies detected by Luminex with negative microlymphocytotoxicity assay and flow crossmatch in live-related renal transplant recipients. Clin Transplant. (2023) 37:e14935. doi: 10.1111/ctr.14935
67
SeitzAMounseyKHughesPCullenKWelberry SmithMDagaSet al. Isolated pre-existing HLA-DP donor-specific antibodies are associated with poorer outcomes in renal transplantation. Kidney Int Rep. (2022) 7:2251–63. doi: 10.1016/j.ekir.2022.07.014
68
Olszowska-ZarembaNGozdowskaJZagożdżonR. Clinical significance of low pre-transplant donor specific antibodies (DSA) in living donor kidney recipients with negative complement-dependent cytotoxicity crossmatches (CDCXM), and negative flow cytometry crossmatches (FLXM) - A single-center experience. Transpl Immunol. (2022) 74:101672. doi: 10.1016/j.trim.2022.101672
69
HeinemannFMLindemannMKelesDWitzkeOKribbenABabaHAet al. Cumulative mean fluorescent intensities of HLA specific antibodies predict antibody mediated rejections after kidney transplantation. Hla. (2022) 100:553–62. doi: 10.1111/tan.14790
70
ParajuliSBathNMHidalgoLLeversonGGargNR. RedfieldRet al. Impact of low-level pretransplant donor-specific antibodies on outcomes after kidney transplantation. Immunity Inflammation Dis. (2021) 9:1508–19. doi: 10.1002/iid3.504
71
SchuttRCaseJKurianSMSpierling BagsicSRBarrickBLTollAEet al. Safety and efficacy of a steroid avoidance immunosuppression regimen in renal transplant patients with de novo or preformed donor-specific antibodies: A single-center study. Transplant Proc. (2021) 53:950–61. doi: 10.1016/j.transproceed.2020.10.021
72
JalalonmuhaliMNgKPMohd ShariffNHLeeYWWongAHGanCCet al. One-year outcomes of living related kidney transplant in patients with preformed HLA donor-specific antibodies: A single-center experience in Malaysia. Transplant Proc. (2020) 52:1718–22. doi: 10.1016/j.transproceed.2020.02.140
73
UffingAHidalgoLGMcMullanCPerryJMilfordELMurakamiNet al. Preformed donor-specific antibodies against HLA class II and graft outcomes in deceased-donor kidney transplantation. Transplant Direct. (2019) 5:e446. doi: 10.1097/TXD.0000000000000893
74
SenevALerutESandtVVCallemeynJCoemansMSprangersBet al. Specificity, strength and evolution of pretransplant donor-specific HLA antibodies determine outcome after kidney transplantation. Hum Immunol. (2019) 80:34. doi: 10.1016/j.humimm.2019.07.028
75
MichielsenLAWisseBWKamburovaEGVerhaarMCJoostenIAllebesWAet al. A paired kidney analysis on the impact of pre-transplant anti-HLA antibodies on graft survival. Nephrol Dial Transplant. (2019) 34:1056–63. doi: 10.1093/ndt/gfy316
76
Redondo-PachónDPérez-SáezMJMirMGimenoJLlinásLGarcíaCet al. Impact of persistent and cleared preformed HLA DSA on kidney transplant outcomes. Hum Immunol. (2018) 79:424–31. doi: 10.1016/j.humimm.2018.02.014
77
KwonHKimYHChoiJYShinSJungJHChoMJet al. Impact of pretransplant donor-specific antibodies on kidney allograft recipients with negative flow cytometry crossmatches. Transplantation. (2018) 102:S623–4. doi: 10.1097/01.tp.0000543528.33541.55
78
Ixtlapale-CarmonaXArvizuADe-SantiagoAGonzález-TablerosNLópezMCastelánNet al. Graft immunologic events in deceased donor kidney transplant recipients with preformed HLA-donor specific antibodies. Transpl Immunol. (2018) 46:8–13. doi: 10.1016/j.trim.2017.09.006
79
de SousaMVGonçalezACZollnerRLMazzaliM. Effect of preformed or de novo anti-HLA antibodies on function and graft survival in kidney transplant recipients. Ann Transplant. (2018)23:457–66. doi: 10.12659/AOT.908491
80
ZecherDBachCStaudnerCBögerCABerglerTBanasBet al. Characteristics of donor-specific anti-HLA antibodies and outcome in renal transplant patients treated with a standardized induction regimen. Nephrol Dial Transplant. (2017) 32:730–7. doi: 10.1093/ndt/gfw445
81
MalheiroJTafuloSDiasLMartinsLSFonsecaIBeirãoIet al. Impact on mid-term kidney graft outcomes of pretransplant anti-HLA antibodies detected by solid-phase assays: Do donor-specific antibodies tell the whole story? Hum Immunol. (2017) 78:526–33. doi: 10.1016/j.humimm.2017.07.011
82
SchaeferSMSüsalCOpelzGDöhlerBBeckerLEKleinKet al. Pre-transplant soluble CD30 in combination with total DSA but not pre-transplant C1q-DSA predicts antibody-mediated graft loss in presensitized high-risk kidney transplant recipients. Hla. (2016) 87:89–99. doi: 10.1111/tan.12735
83
SalvadéIAubertVVenetzJPGolshayanDSaouliACMatterMet al. Clinically-relevant threshold of preformed donor-specific anti-HLA antibodies in kidney transplantation. Hum Immunol. (2016) 77:483–9. doi: 10.1016/j.humimm.2016.04.010
84
RichterRSüsalCKöhlerSQidanSSchödelAHolschuhLet al. Pretransplant human leukocyte antigen antibodies detected by single-antigen bead assay are a risk factor for long-term kidney graft loss even in the absence of donor-specific antibodies. Transpl Int. (2016) 29:988–98. doi: 10.1111/tri.12786
85
AdebiyiOOGrallaJKlemPFreedBDavisSWisemanACet al. Clinical significance of pretransplant donor-specific antibodies in the setting of negative cell-based flow cytometry crossmatching in kidney transplant recipients. Am J Transplant. (2016) 16:3458–67. doi: 10.1111/ajt.13848
86
Redondo-PachónDPascualJPérez-SáezMJGarcíaCHernándezJJGimenoJet al. Impact of preformed and de novo anti-HLA DP antibodies in renal allograft survival. Transpl Immunol. (2016) 34:1–7. doi: 10.1016/j.trim.2015.11.002
87
VisentinJMarrocMGuidicelliGBacheletTNongTMoreauJFet al. Clinical impact of preformed donor-specific denatured class I HLA antibodies after kidney transplantation. Clin Transplant. (2015) 29:393–402. doi: 10.1111/ctr.12529
88
MalheiroJTafuloSDiasLMartinsLSFonsecaIBeirãoIet al. Analysis of preformed donor-specific anti-HLA antibodies characteristics for prediction of antibody-mediated rejection in kidney transplantation. Transpl Immunol. (2015) 32:66–71. doi: 10.1016/j.trim.2015.01.002
89
MarfoKAjaimyMColovaiAKaylerLGreensteinSLubetzkyMet al. Pretransplant immunologic risk assessment of kidney transplant recipients with donor-specific anti-human leukocyte antigen antibodies. Transplantation. (2014) 98:1082–8. doi: 10.1097/TP.0000000000000191
90
FidlerSJIrishABLimWFerrariPWittCSChristiansenFT. Pre-transplant donor specific anti-HLA antibody is associated with antibody-mediated rejection, progressive graft dysfunction and patient death. Transpl Immunol. (2013) 28:148–53. doi: 10.1016/j.trim.2013.05.001
91
CrespoMTorioAMasVRedondoDPérez-SáezMJMirMet al. Clinical relevance of pretransplant anti-HLA donor-specific antibodies: does C1q-fixation matter? Transpl Immunol. (2013) 29:28–33. doi: 10.1016/j.trim.2013.07.002
92
Kanter BergaJSancho CalabuigAGavela MartinezEPuig AlcarazNBeltran CatalanSAvila BernabeuAet al. Pretransplant donor-specific HLA antibodies detected by single antigen bead flow cytometry: risk factors and outcomes after kidney transplantation. Transplant Proc. (2012) 44:2529–31. doi: 10.1016/j.transproceed.2012.09.102
93
David-NetoESouzaPSPanajotopoulosNRodriguesHVenturaCGDavidDSet al. The impact of pretransplant donor-specific antibodies on graft outcome in renal transplantation: a six-year follow-up study. Clinics (Sao Paulo). (2012) 67:355–61. doi: 10.6061/clinics/2012(04)09
94
Caro-OleasJLGonzález-EscribanoMFGonzález-RonceroFMAcevedo-CaladoMJCabello-ChavesVGentil-GovantesMet al. Clinical relevance of HLA donor-specific antibodies detected by single antigen assay in kidney transplantation. Nephrol Dial Transplant. (2012) 27:1231–8. doi: 10.1093/ndt/gfr429
95
SongEYLeeYJHyunJKimYSAhnCHaJet al. Clinical relevance of pretransplant HLA class II donor-specific antibodies in renal transplantation patients with negative T-cell cytotoxicity crossmatches. Ann Lab Med. (2012) 32:139–44. doi: 10.3343/alm.2012.32.2.139
96
ThammanichanondDIngsathitAMongkolsukTRattanasiriSKantachuvesiriSSakhonratCet al. Pre-transplant donor specific antibody and its clinical significance in kidney transplantation. Asian Pac J Allergy Immunol. (2012) 30:48–54.
97
WillicombeMBrookesPSantos-NunezEGallifordJBallowAMcLeanAet al. Outcome of patients with preformed donor-specific antibodies following alemtuzumab induction and tacrolimus monotherapy. Am J Transplant. (2011) 11:470–7. doi: 10.1111/j.1600-6143.2010.03421.x
98
LoupyASuberbielle-BoisselCHillGSLefaucheurCAnglicheauDZuberJet al. Outcome of subclinical antibody-mediated rejection in kidney transplant recipients with preformed donor-specific antibodies. Am J Transplant. (2009) 9:2561–70. doi: 10.1111/j.1600-6143.2009.02813.x
99
AmicoPHöngerGMayrMSteigerJHopferHSchaubS. Clinical relevance of pretransplant donor-specific HLA antibodies detected by single-antigen flow-beads. Transplantation. (2009) 87:1681–8. doi: 10.1097/TP.0b013e3181a5e034
100
PhelanDMohanakumarTRamachandranSJendrisakMD. Living donor renal transplantation in the presence of donor-specific human leukocyte antigen antibody detected by solid-phase assay. Hum Immunol. (2009) 70:584–8. doi: 10.1016/j.humimm.2009.05.007
101
GuptaAIvesonVVaragunamMBodgerSSinnottPThuraisinghamRC. Pretransplant donor-specific antibodies in cytotoxic negative crossmatch kidney transplants: are they relevant? Transplantation. (2008) 85:1200–4. doi: 10.1097/TP.0b013e31816b1c37
102
YazawaMCseprekalOHelmickRATalwarMBalaramanVPodilaPSBet al. Lack of association between pretransplant donor-specific antibodies and posttransplant kidney outcomes in simultaneous liver-kidney transplant recipients with rabbit anti-thymocyte globulin induction and steroid-free protocol. Nephron. (2020) 144:126–37. doi: 10.1159/000505460
103
HeiseELChichelnitskiyEGreerMFranzMAburahmaKIablonskiiPet al. Lung transplantation despite preformed donor-specific antihuman leukocyte antigen antibodies: a 9-year single-center experience. Am J Transplant. (2023) 23:1740–56. doi: 10.1016/j.ajt.2023.04.034
104
SmithJDIbrahimMWNewellHDanskineAJSoresiSBurkeMMet al. Pre-transplant donor HLA-specific antibodies: characteristics causing detrimental effects on survival after lung transplantation. J Heart Lung Transplant. (2014) 33:1074–82. doi: 10.1016/j.healun.2014.02.033
105
BrugièreOSuberbielleCThabutGLhuillierEDauriatGMetivierACet al. Lung transplantation in patients with pretransplantation donor-specific antibodies detected by Luminex assay. Transplantation. (2013) 95:761–5. doi: 10.1097/TP.0b013e31827afb0f
106
SetiaGNishiharaKSinger-EnglarTZhangXPatelJKobashigawaJ. Crossing low/moderate-level donor-specific antibodies during heart transplantation. Clin Transplant. (2021) 35:e14196. doi: 10.1111/ctr.14196
107
TalayeroPRamos BoludaEGómez MassaECastro PaneteMJPrieto BozanoGHernández OliverosFet al. Donor-specific antibodies in pediatric intestinal and multivisceral transplantation: the role of liver and human leukocyte antigen mismatching. Liver Transpl. (2018) 24:1726–35. doi: 10.1002/lt.25323
Summary
Keywords
preformed donor-specific antibodies, solid organ transplantation, antibody-mediated rejection, graft survival, mean fluorescence intensity, risk stratification, organ-specific risk, HLA antibodies
Citation
Kang Z, Han X, Liu C, Liu W and Li D (2025) Association of donor-specific antibodies with adverse outcomes in solid organ transplantation: A systematic review and meta-analysis of 69 studies. Front. Immunol. 16:1633853. doi: 10.3389/fimmu.2025.1633853
Received
23 May 2025
Accepted
28 August 2025
Published
12 September 2025
Volume
16 - 2025
Edited by
Hugo Kaneku, University of Miami Health System, United States
Reviewed by
Ashwin Ajith, Augusta University, United States
Pernille Koefoed-Nielsen, Aarhus University Hospital, Denmark
Updates
Copyright
© 2025 Kang, Han, Liu, Liu and Li.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dai-hong Li, ldh_hla@126.com
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.