Abstract

Background:

Xenotransfusion using genetically engineered (GE) pig red blood cells (RBCs) offers a promising solution to blood shortages, particularly in emergency settings. Although nonhuman primates (NHPs) have been widely used in preclinical studies, their translational relevance is limited by species-specific immune responses and logistical challenges. This study aimed to evaluate whether brain-dead humans could serve as a human translational reference model by characterizing and comparing their hematologic, biochemical, and immunologic profiles with those of patients with acute blood loss (ABL). The goal was to generate baseline data to inform the design and interpretation of future in vivo studies involving the transfusion of GE pig RBCs.

Materials and methods:

Comprehensive clinical and immunological analyses were performed on donation after brain death (DBD) subjects (n=179) and patients with ABL requiring transfusion (n=104). The parameters included hematological indices, electrolytes, coagulation factors, inflammatory biomarkers, and arterial blood gases. Immune assays were conducted on sera from DBD subjects (n=31) and patients with ABL (n=102) to examine IgM/IgG binding and complement-dependent cytotoxicity (CDC) against triple-knockout (TKO) pig RBCs lacking Gal, Neu5Gc, and Sda antigens.

Results:

Across most measured parameters, overlapping ranges in hematologic and biochemical indices were observed between DBD subjects and patients with ABL. Anti-TKO IgM/IgG binding and CDC were not detectably different between the two groups under the conditions tested. However, differences were observed in several other immune parameters, including hemagglutination, cytokine profiles, total immunoglobulin levels, and complement components.

Conclusion:

Brain-dead humans may represent an ethically feasible human translational reference model for xenotransfusion research. While DBD subjects do not fully reproduce the physiologic and inflammatory milieu of patients with ABL, they provide useful baseline human data for assessing selected early xenoreactive responses to GE pig RBCs and may help bridge the translational gap between NHP studies and future clinical application.

Introduction

The global shortage of human red blood cells (RBCs) poses a critical challenge in transfusion medicine (Ellingson et al., 2017; Jones et al., 2021; World Health Organization, 2022), particularly in acute blood loss (ABL) scenarios such as trauma, surgery, and postpartum hemorrhage. This issue is further compounded for patients with rare blood types (Reid and Mohandas, 2004; Reid et al., 2012), individuals sensitized to human RBCs (Win et al., 2001; Schonewille et al., 2006; Wahl and Quirolo, 2009; Natukunda et al., 2010; Yazdanbakhsh et al., 2012; Vidler et al., 2015; Chonat et al., 2018; Yamamoto et al., 2021; Viayna et al., 2022; Arthur and Stowell, 2023), or those in regions with high prevalence of bloodborne pathogens such as human immunodeficiency virus, hepatitis viruses, or malaria (Bloch et al., 2012; Kanagasabai et al., 2021). Alternative and sustainable sources of RBCs are urgently needed to ensure adequate supply and compatibility. One promising solution is xenotransfusion using genetically engineered (GE) pig RBCs (Roux et al., 2007; Cooper et al., 2010; Wang et al., 2014; Smood et al., 2019; Yamamoto et al., 2021; Chornenkyy et al., 2023; Fang et al., 2024; Roh et al., 2024).

Recent advances in gene-editing technologies have enabled the production of pig RBCs lacking major xenoantigens (Cooper et al., 2010; Wang et al., 2014; Estrada et al., 2015; Hara et al., 2023; Fang et al., 2024; Roh et al., 2024), such as galactose-α1,3-galactose (Gal), N-glycolylneuraminic acid (Neu5Gc), and Sda, and incorporated with human transgenes, including CD55 to reduce immune reactivity (Fang et al., 2024). These triple-knockout (TKO) modifications significantly minimize human antibody binding and complement-dependent cytotoxicity (CDC) compared with wild-type (WT) or α1,3-galactosyltransferase-knockout (GTKO) pigs (Pan et al., 2019; Yamamoto et al., 2021; Chornenkyy et al., 2023; Park et al., 2023; Fang et al., 2024).

Despite these advances, the preclinical evaluation of GE pig RBCs in vivo remains limited largely because of the difficulty in establishing reliable animal models that can accurately reflect human immune responses and support reproducible measurement of RBC survival. Early studies using baboons demonstrated that unmodified pig RBCs were rapidly cleared within 5 minutes (Eckermann et al., 2004). However, the enzymatic removal of αGal antigens with α-galactosidase significantly extended RBC survival to approximately 2 hours. Combining this procedure with complement depletion using cobra venom factor increased the survival to 24 hours. Additional interventions, including the co-administration of bovine serum albumin–Gal conjugates and phagocytosis inhibitors such as medronate liposomes, further prolonged survival beyond 72 hours. Transfusion of large volumes also achieved modest prolongation of RBC survival, though the effect was associated with adverse effects such as splenic congestion and follicular hyperplasia (Dor et al., 2004).

Approaches to camouflaging non-Gal antigens using succinimid propionate-linked methoxypolyethyleneglycol have been explored. This strategy extended RBC survival in rhesus monkeys up to 12 hours without immunosuppression when combined with α-galactosidase treatment and up to 40 hours when immunosuppressive therapy was added (Tan et al., 2006).

Another strategy involved expressing human complement-regulatory and antiphagocytic proteins, such as CD55 and CD47, on pig RBCs (Fang et al., 2024). However, in vivo studies showed that TKO/CD55/CD47 pig RBCs transfused into cynomolgus monkeys survived less than 2 hours, which was only a modest improvement over WT controls (Fang et al., 2024). Promising results were obtained when TKO pig RBCs were transfused into New World (NW) nonhuman primates (NHPs), specifically capuchin monkeys, without immunosuppression. In this setting, RBC survival reached 5–7 days (Yamamoto et al., 2021). The low levels of anti-TKO IgM antibodies in the recipient monkeys did not hinder their short-term survival. This finding suggests that extended survival is achievable in recipients with minimal or absent anti-TKO antibodies, particularly when combined with further pharmacologic modulation of complement or phagocytosis pathways.

The above incremental advances underscore the limitations of NHP models for xenotransfusion. All NHP species tested to date, especially Old World (OW) NHPs such as baboons and rhesus or cynomolgus monkeys, are crossmatch-positive to TKO pig RBCs due to species-specific immunologic backgrounds. This intrinsic incompatibility limits their utility for evaluating the safety and efficacy of GE pig RBCs in a clinically relevant setting.

Brain-dead humans have recently emerged as a novel preclinical model to address the abovementioned research gap. These subjects provide an ethically feasible and clinically relevant platform for evaluating immune responses to xenogeneic cells under controlled conditions (Montgomery et al., 2022; Porrett et al., 2022; Locke et al., 2023; Moazami et al., 2023; Cheung et al., 2024; Jones-Carr et al., 2024; Ma et al., 2024; Mallapaty, 2024; Wang et al., 2024). Although their use has been successfully demonstrated in solid organ xenotransplantation studies (Montgomery et al., 2024), their potential as a model for xenotransfusion remains underexplored. In particular, the resemblance of their pathophysiological and immunological characteristics to those of patients with ABL, which is a critical consideration for validating their use as reference models, remains unclear.

This study aimed to evaluate the suitability of brain-dead humans as a human translational reference model for xenotransfusion. We compared hematological, biochemical, and immunological characteristics between brain-dead humans and patients with ABL using standardized protocols within a single institutional and laboratory framework. The resulting dataset provides a foundational human reference for the design and interpretation of future in vivo studies involving GE pig RBCs.

MethodsStudy design and ethical approval

This study was conducted under the approval of the Institutional Review Board (IRB) of the Second Affiliated Hospital of Hainan Medical University (IRB- LW2022901 and IRB- LW2022231). Serum, plasma, and blood samples were collected from donation after brain death (DBD) subjects through an organ procurement organization in Hainan Province and from patients with ABL through the Department of Emergency at the Second Affiliated Hospital. Healthy adult volunteers provided informed consent for their participation. For the DBDs, written informed consent was obtained from their next of kin at the time of organ donation. The consent process included explicit approval for the collection and use of biological samples such as blood (including serum and plasma) and tissues in the clinical evaluation of organ function and safety, and future research purposes. All procedures complied with applicable institutional, national, and international ethical guidelines, including IRB oversight.

Demographic and clinical characteristics of participants

A total of 179 DBDs and 104 patients with ABL were included in this study. Their demographic and clinical characteristics, including age, gender, and cause of brain death or ABL, are summarized in Table 1.

CharacteristicBrain-dead donors (DBD)Acute blood loss (ABL) patientsP valueTotal number 179104–Age, mean (± SD), years46.4 (± 25.3)47.3 (± 14.0)0.43Gender- Male151 (84%)74 (71.2%)0.34- Female28 (16%)30 (28.8%)0.58Cause of condition- Spontaneous cerebral hemorrhage103 (58%)––- Traumatic cerebral hemorrhage58 (32%)––- Cerebral infarction5 (3%)––- Organ injury–31 (30%)–- Bone fracture–42 (40%)–- Craniocerebral injury–19 (18%)–- Other13 (7%)12 (12%)–Injury details (ABL)- Traffic–90 (87%)–- Fallen–14 (13%)–

Demographic and clinical characteristics of research subjects.

The patients with ABL were categorized into four groups according to their injury severity score (ISS) (Stevenson et al., 2001) for the subsequent analysis of immune responses to TKO pig RBCs (see Results for details).

Sample collection and processing

Blood samples were analyzed as whole blood or processed into serum and plasma fractions. Serum samples from 37 DBD subjects and 102 patients with ABL were available for immunological analyses; however, the number of samples differed by assay because of sample availability and volume constraints, as shown in Table 2. In particular, anti-TKO pig RBC response assays were performed in a subset of 31 DBD samples. All the samples were processed and stored under standardized conditions to maintain their integrity.

Mean (± SD), NumberDBDABL patientsP valueHematological parametersRBC (1×106/μL)3.61 (0.98), n=1793.42 (0.8), n=1040.222Hb (mg/mL)107.9 (27.66), n=17999.9 (20.6), n=1040.0357HCT (%)32 (8), n=17930 (6), n=1040.12WBC (1×106/μL)12.82 (6.35), n=17913.29 (5.17), n=1040.5824Platelet (1×103/μL)185.3 (116.10), n=179185.7 (75.79), n=1040.323Neutrophil number (1×106/μL)11.23 (5.42), n=17911.62 (5.22), n=1040.3146Lymphocyte number (1×106/μL)1.08 (0.69), n=1791.09 (0.56), n=1040.5954Monocyte number (1×106/μL)0.82 (0.94), n=1790.73 (0.35), n=1040.2381Neutrophil (%)83.73 (7.30), n=17984.81 (6.79), n=1040.1673Lymphocytes (%)9.80 (7.31), n=1799.08 (5.83), n=1040.3577Monocytes (%)5.64 (3.31), n=1795.63 (2.19), n=1040.4267Biochemical parametersAST (U/L)89.62 (157.01), n=179118.3 (239.5), n=1010.9914ALT (U/L)72.95 (115.01), n=17973.47 (143.0), n=1010.1791Total bilirubin (TB, mg/dL)1.31 (1.35), n=1790.94 (0.76), n=1010.0101Creatinine (Cr, mg/dL)1.04 (0.69), n=1790.78 (0.72), n=101<0.0001Creatine kinase-muscle/brain (CK-MB, (U/L)52.88 (59.06), n=16065.06 (81.28), n=550.2168Myoglobin (Mb, ng/mL)545.90 (450.2), n=104679.5 (464.3), n=450.0683Albumin (g/L)38.25 (8.10), n=17933.3 (7.3), n=101<0.0001Globulin (g/L)23.59 (6.27), n=17917.76 (5.44), n=101<0.0001Albumin/globulin1.76 (0.68), n=1791.99 (0.54), n=101<0.0001LDH (U/L)444 (500.60), n=125448 (415), n=870.3226ElectrolytesSodium (Na, mmol/L)147.90 (10.79), n=179142.2 (4.39), n=104<0.0001Chlorine (Cl, mmol/L)111.20 (10.18), n=179106.8 (6.33), n=1040.0017Potassium (K, mmol/L)4.04 (0.86), n=1793.99 (0.61), n=1040.5829Calcium (Ca, mmol/L)2.24 (0.27), n=1721.74 (0.45), n=81<0.0001Magnesium (Mg, mmol/L)0.90 (0.16), n=1460.69 (0.10), n=11<0.0001Phosphorus (P, mmol/L)0.95 (0.68), n=1271.17 (0.82), n=470.0243Coagulation and inflammatory markersAntithrombin III (AT-III, %)65.90 (32.30), n=15265.78 (24.88), n=110.8096D-dimer (mg/L)14.19 (25.75), n=14525.84 (31.77), n=74<0.0001Fibrinogen (FIB, g/L)4.85 (2.44), n=1742.76 (1.97), n=100<0.0001C-reactive protein (CRP, mg/L)127.8 (99.70), n=17842.6 (59.7), n=99<0.0001Arterial blood gas testPH7.39 (0.12), n=1727.36 (0.09), n=750.0017HCO3− (mmol/L)23.96 (4.71), n=17622.59 (4.22), n=760.046PaO2 (mmHg)114.20 (62.57), n=176139.7 (57.31), n=750.0062PaCO2 (mmHg)47.19 (17.08), n=17937.32 (10.75), n=75<0.0001Lactic acid (mmol/L)2.36 (2.18), n=1733.2 (2.9), n=600.0097Immunological parametersTotal IgM (g/L)1.38 (1.08), n=450.65 (0.21), n=130.026Total IgG (g/L)9.04 (3.41), n=456.21 (3.26), n=130.0193Total IgA (g/L)3.03 (1.81), n=451.26 (0.51), n=13<0.0001C3 (g/L)1.02 (0.38), n=450.65 (0.32), n=130.0005C4 (g/L)0.30 (1.14), n=450.13 (0.05), n=13<0.0001IL-2 (pg/mL)1.36 (1.30), n=370.8 (0.95), n=101<0.0001IL-4 (pg/mL)3.08 (2.04), n=379.27 (9.56), n=101<0.0001IL-6 (pg/mL)599.90 (840.20), n=37878 (2684), n=1010.9457IL-10 (pg/mL)20.49 (62.81), n=3799.09 (167.3), n=101<0.0001IFN-γ (pg/mL)0.96 (2.10), n=3731.16 (24.8), n=101<0.0001TNF-α (pg/mL)1.58 (0), n=3725.33 (21.02), n=101<0.0001Anti-TKO pig RBC response:IgM binding (rGM)3.61 (4.84), n=313.31 (2.98), n=1020.6142IgG binding (rGM)14.59 (51.40), n=311.48 (0.43), n=1020.1483CDC (cytotoxicity%)13.43 (6.21), n=3116.67 (11.44), n=1020.9206Hemagglutination1.55 (1.15), n=312.85 (1.56), n=102<0.0001

Comparison of hematological, biochemical, electrolyte, coagulation, inflammatory, and immunological parameters between brain-dead donors (DBD) and acute blood loss (ABL) patients.

rGM, relative geometric mean; DBD, brain-dead donor; ABL, acute blood loss.

Laboratory analysis

Comprehensive evaluations were conducted to analyze hematological, biochemical, electrolyte, coagulation, inflammatory marker, and arterial blood gas parameters (Table 2). All routine analyses were performed at the Central Laboratory of the Second Affiliated Hospital of Hainan Medical University using automated and standardized systems. Complement activity was evaluated using the Zybio platform (Zybio, Chongqing, China), and cytokine profiles were quantified using the Agilent system (Agilent, USA, SK00024AAJ). Flow cytometric analyses were performed using the NoVoCyte D3000 flow cytometer (Agilent Technologies, Beijing, China).

In vitro assessments of anti-triple-knockout (TKO, lacking Gal/Neu5Gc/Sda expression) pig RBC responses were also conducted (Table 2). These assays included IgM and IgG antibody binding, complement-dependent cytotoxicity (CDC), and hemagglutination as described in detail in the In vitro assays section below.

Preparation of RBCs

Blood from TKO pigs (blood type O [non-A]) (Feng et al., 2022; He et al., 2024; Wang et al., 2024) was provided by Chengdu Clonorgan Biotechnology Co., Ltd. under Institutional Animal Care and Use Committee approval (IACUC#ZK09-24-01A). RBCs were isolated from the heparinized blood through three wash cycles with 1× phosphate-buffered saline (PBS; Gibco, Shanghai, China) at 700g for 5 min at 4 °C (Long et al., 2009; Gao et al., 2017).

The expression of Gal, Neu5Gc, and Sda on pig RBCs was evaluated by CytoFLEX flow cytometry (Beckman Coulter, Brea, CA, USA) using the following antibodies: FITC-conjugated BSI-B4 lectin (Sigma, L2895, Shanghai, China) for Gal, FITC-conjugated Dolichos biflorus agglutinin (Vector Laboratories, FL-1031, Shanghai, China) for Sda, and a primary chicken anti-Neu5Gc antibody (BioLegend, #146901, Beijing, China) with an Alexa Fluor488 goat anti-chicken secondary antibody (Abcam, ab96947, Shanghai, China) (Li et al., 2021; Li et al., 2022). A chicken IgY isotype control (BioLegend, #402101) was employed as the negative control. The TKO RBCs were confirmed to lack Gal, Neu5Gc, and Sda expression. Meanwhile, wild-type pig RBCs and human RBCs (blood type O) served as the positive and negative controls, respectively (data not shown).

Detection of CD45 and SLA class I antigens

The surface expression of CD45 (mouse anti-pig CD45 antibody [FITC, Clone: K252.1E4, Bio-Rad, MCA1222A647, USA]) and SLA class I antigen (mouse anti-pig SLA class I antibody [FITC or Alexa Fluor® 647, Clone: JM1E3, Bio-Rad, MCA2261A647, USA]) on pig RBCs was analyzed by CytoFLEX flow cytometry. The purity of the isolated RBCs was confirmed to exceed 99% (data not shown). Platelet depletion was not separately quantified.

IgM and IgG antibody binding to TKO pig RBCs

Serum samples were decomplemented by heat inactivation at 56 °C for 30 min and stored at −80 °C until further use. The binding of IgM and IgG antibodies to TKO pig RBCs was assessed following established protocols (Li et al., 2022).

TKO pig RBCs or human RBCs (blood group O, negative control; 1×106 cells/150 µL of PBS) were incubated with 50 µL of serum for 30 min at 4 °C. After incubation, the RBCs were washed and suspended in 100 µL of PBS containing 10% goat serum for blocking (20 min at 4 °C). Afterward, the RBCs were incubated with Alexa Fluor® 647 AffiniPure™ goat anti-human IgM, Fc5μ fragment specific, and Alexa Fluor® 488 AffiniPure™ goat anti-human IgG (H+L; Jackson ImmunoResearch, USA; 1:1000) antibodies for 30 min in the dark at 4 °C. Following antibody labeling, the RBCs were washed and resuspended in 200 µL of PBS. Flow cytometry was performed to measure antibody binding. Data were analyzed with FlowJo V10 (Tree Star, Ashland, OR, USA). Antibody binding was expressed as a relative geometric mean, calculated by dividing the geometric mean of each sample by that of the negative control (secondary antibody without serum) (Li et al., 2019; Li et al., 2020; Li et al., 2021; Li et al., 2022; Oscherwitz et al., 2022). Human O RBCs served as the negative control.

Serum CDC assay: hemolytic assay

The CDC of serum (at a final concentration of 25%) against TKO pig RBCs was assessed by hemolytic assay (Yamamoto et al., 2021). In brief, 100 µL of 50% heat-inactivated serum, 100 µL of PBS buffer (blank/serum-free control), or 0.1% Triton X-100 buffer (positive control; Sigma) was incubated with 100 µL of pig RBCs (5×107 cells/mL) at 4 °C for 30 min, resulting in a final serum concentration of 25%. Following incubation, the mixture was washed with PBS and centrifuged at 500g for 5 min. The supernatant was carefully aspirated, and 400 µL of 30% rabbit complement (Cedarlane, CL3441, Canada) or 400 µL of PBS (blank control) was added to the RBC pellet. The mixture was incubated at 37 °C for 30 min. After incubation, the samples were centrifuged at 500g for 5 min, and 100 µL of the supernatant was carefully collected in triplicate (a total of 300 µL) to avoid disturbing the RBC pellet. The supernatant was transferred to UV-transparent 96-well microplates (Corning, #3635, Shanghai, China), and absorbance was measured at 560 nm using a spectrophotometer (Thermo Fisher Scientific, Multiskan™ FC, Shanghai, China). Each sample was analyzed in triplicate.

CDC (%) was calculated using the following formula:

Hemagglutination assay

Isolated TKO pig RBCs were reconstituted with PBS containing Ca2+/Mg2+ and transferred to each well (20 μL of RBCs at a concentration of 5×108/mL) of a 96-well flat plate (Corning), followed by the addition of 20 μL of 50% heat-inactivated serum (final serum concentration of 25%). The mixture was incubated at room temperature for 60 min. Observations were performed under a microscope (Nikon, TS2-FL, Japan), and images were captured using NIS-Elements software. Agglutination was examined using the modified Marsh scoring method (Marsh, 1972; Long et al., 2009).

To serve as negative controls, human blood type O red blood cells were included in all IgM/IgG binding, hemagglutination, and CDC assays.

Statistical analysis

The normality of data distribution was evaluated using the Shapiro–Wilk test in GraphPad Prism 8 (GraphPad Software, La Jolla, CA, USA). On the basis of the results, nonparametric tests were used for group comparisons when the data did not meet the assumptions of normality. The Mann–Whitney U test was used for comparisons between two groups, and the Kruskal–Wallis test followed by Dunn’s post hoc test was applied for comparisons among three or more groups. All statistical analyses were performed using GraphPad Prism 8. Data were presented as mean ± standard deviation (SD), unless otherwise indicated. A p value of <0.05 was considered statistically significant. Statistical significance was annotated as follows: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***), and p < 0.0001 (****).

Declaration of generative AI and AI-assisted technologies in the writing process

During the early stages of manuscript preparation, the authors used ChatGPT (OpenAI, GPT-4) to assist with language refinement and improving clarity. However, the final version of the manuscript was professionally edited by a language editing company that does not use AI tools. No content generation, data interpretation, or scientific reasoning was delegated to any AI. All scientific content and conclusions were conceived, written, and verified by the authors. This declaration is made in accordance with the TITAN Guidelines 2025 on the use of artificial intelligence in scientific publishing (Agha et al., 2025).

ResultsHematological parameters

No significant differences in RBC count or hematocrit (HCT) were observed between the DBDs and patients with ABL (Figure 1A). However, hemoglobin (Hb) levels were significantly lower in the patients with ABL than in the DBDs (p < 0.05). Similarly, no significant differences in white blood cell (WBC), neutrophil, lymphocyte, platelet, and monocyte counts and their percentages existed between the two groups (Figures 1A, B). These findings show overlapping hematological profiles between DBD subjects and patients with ABL for most measured parameters, with the exception of Hb levels.

(A) Hematological parameters and (B) differential counts and percentages of neutrophils, lymphocytes, and monocytes in DBDs (n = 179) and patients with ABL (n = 104). No significant differences in RBC count, hematocrit (HCT), WBC count, and differential counts and percentages of neutrophils, lymphocytes, monocytes, and platelets were observed between the two groups. Hemoglobin (Hb) levels were significantly lower in the patients with ABL than in the DBDs (*p < 0.05). Data are presented as individual points with mean ± SD. ns, not significant. The dashed lines indicate the clinically accepted normal reference range.

Biochemical parameters

No significant differences in liver function markers including AST and ALT were observed between the two groups (Supplementary Figure 1A). However, total bilirubin (TB) and creatinine (Cr) levels were significantly higher in the DBDs than in the patients with ABL (p < 0.05 and p < 0.0001, respectively). These findings suggest that potential liver dysfunction (possibly due to ischemia, hypoperfusion, or hemolysis) and impaired renal clearance (possibly caused by hypovolemia or ischemic injury) may be associated with brain death. Muscle damage markers, such as creatine kinase myocardial band (CK-MB) and myoglobin (Mb), showed no significant differences between the two groups, indicating their similar levels of muscle injury.

Protein analysis revealed that albumin and globulin levels and their ratio (Supplementary Figure 1B) were significantly lower in the patients with ABL than in the DBDs (p < 0.0001 for all comparisons), reflecting protein loss or dilution due to fluid resuscitation. Meanwhile, their lactate dehydro