HLA-DQB1*02:272 differs from HLA-DQB1*02:01:01:01 by one nucleotide substitution in codon 48 in exon 2.

HLA-B*27:301 differs from HLA-B*27:05:02:01 by one nucleotide substitution in codon 333 in exon 7.

Background: In lung transplantation, de novo immunodominant donor-specific anti-HLA antibodies recognizing HLA-DQ antigens (dn-iDSA-DQ) are predominant and can induce chronic lung allograft dysfunction (CLAD). We previously developed a method to measure the active concentration of dn-iDSA-DQ. We aimed to determine whether this new quantitative biomarker is associated with transplantation outcomes. Methods: This retrospective multicentre cohort study included 90 lung transplant recipients (LTRs) developing dn-iDSA-DQ, evidenced through single antigen flow beads (SAFB) follow-up. We measured the active concentration of dn-iDSA-DQ at the time of their first detection (T0) for all LTRs, and within the 2 years after DSA detection, whenever possible. SAFB dn-iDSA-DQ characteristics and clinical data were retrieved up to 5 years after DSA detection. Results: We tested 184 sera with SPR (n=90 at T0, n=94 within the 2 years after DSA detection), among which 63 (34.4%) had a quantifiable concentration of the dn-iDSA-DQ (≥0.3 nM). The median SAFB mean fluorescence intensity (MFI) of the dn-iDSA-DQ with a concentration ≥0.3 nM was higher (p<0.0001), yet the correlation between SAFB MFI and active concentration was low (r=0.758, p<0.0001). In multivariate analysis, a concentration of the dn-iDSA-DQ ≥0.3 nM at T0 was independently associated with a lower 2-year CLAD-free survival (HR 2.06, p=0.02). A concentration of the dn-iDSA-DQ ≥0.3 nM within the 2 years from DSA detection was associated with a lower graft survival in univariate analysis. Conclusions: Active concentration of dn-iDSA-DQ appears as a valuable biomarker to identify pathogenic DSA at their first detection because of its association with CLAD. ### Competing Interest Statement The University of Bordeaux, the Bordeaux University Hospital, the CNRS and the INSERM have filed a patent application for measuring the active concentration of anti-HLA antibodies by SPR. J. Visentin, JL. Taupin and C. Di Primo are listed as inventors on this patent. ### Clinical Trial NCT03474536 ### Funding Statement This work has benefited from grants given by Agence de la Biomedecine (AOR 2017 and 2022), Agence Nationale de la Recherche (EPIHLA, AAP 2022), Vaincre la Mucoviscidose, Association Gregory Lemarchal, La Fondation du Souffle, Societe Francophone d Histocompatibilite et Immunogenetique, and European Union Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie grant agreement 888743. The funders had no role in work design and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of Amiens University Hospital (CPP Nord Ouest 2) gave ethical approval for this work. This study was registered on clinicaltrials.gov under the number [NCT03474536][1]. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT03474536&atom=%2Fmedrxiv%2Fearly%2F2026%2F02%2F14%2F2026.02.11.26344836.atom

HLA-B*47:01:07 differs from HLA-B*47:01:01:03 by one nucleotide substitution in codon 284 in exon 5.

HLA-DRB3*02:240 differs from HLA-DRB3*02:20 by one nucleotide substitution in codon 74 in exon 2.

HLA-B*35:02:25 differs from HLA-B*35:02:01:02 by one nucleotide substitution in codon 227 in exon 4.

HLA molecules play a central role in the adaptive immune response. Their high polymorphism influences individual susceptibility to various autoimmune diseases and certain drug-induced hypersensitivities. In France, HLA genotyping is classified as a medical genetics procedure and is strictly regulated. The Société Francophone d'Histocompatibilité et d'Immunogénétique (SFHI) has established national guidelines outlining clinically validated indications, required resolution levels and interpretation criteria based on robust data. These guidelines are particularly relevant for common clinical contexts, including autoimmune diseases and pharmacogenetic testing. Well-established associations include HLA-DQB1*02/DQA1*05 (DQ2) and HLA-DQB1*03:02/DQA1*05 (DQ8) with celiac disease, HLA-B*27 with spondyloarthritis, HLA-DQB1*06:02 with type 1 narcolepsy, HLA-A*29 with Birdshot chorioretinopathy and several pharmacogenetic risk alleles such as HLA-B*57:01 (abacavir), HLA-B*15:02 and HLA-A*31:01 (carbamazepine) and HLA-B*58:01 (allopurinol). In immunotherapy, the efficacy of tebentafusp has been shown to depend on HLA-A*02:01 positivity. HLA alleles must be interpreted as relative risk factors, not absolute predictors. Critical analysis of HLA-related scientific literature requires consideration of the genotyping technique, typing resolution, allele frequencies within the studied population and environmental factors. High-resolution typing is essential in pharmacogenetics and recommended in selected autoimmune disorders. Interpretation should be conducted by qualified medical biologists, integrating clinical context, allelic diversity and recent technological advances, particularly next-generation sequencing. HLA genotyping represents a valuable tool in diagnosis and risk assessment, with increasing importance in the era of personalised medicine.

HLA-A*01:470 differs from HLA-A*01:01:01:01 by one nucleotide substitution in codon 119 in exon 3.

The systematic use of Single Antigen Flow Beads assays and the implementation of high-resolution HLA typing for donors and kidney transplant recipients allow a precise identification of anti-HLA donor-specific antibodies. In France, the availability of detailed molecular biology HLA typing for deceased donors in the national organ allocation software enables anticipation of wet crossmatch results and estimation of the immunological risk for a recipient/donor pair. This key process, named virtual crossmatching, involves a thorough analysis of the recipient's anti-HLA sensitisation records. Its main goal is to reduce cold ischaemia time in order to extend graft survival. In this article, we present the guidelines for virtual crossmatching developed by a working group from the French-speaking Society of Histocompatibility and Immunogenetics. The guidelines address several considerations regarding HLA typing, anti-HLA antibody testing, and sensitisation event history, which are required to perform virtual crossmatching. We also propose a decision-making process, which situates prospective or retrospective wet crossmatch depending on virtual crossmatch results. The guidelines specifically emphasise the need for a strong clinical-biological agreement to standardise practices and provide a framework for omission of wet crossmatch for both non-sensitised and sensitised recipients.

HLA-DPA1*01:03:61 differs from HLA-DPA1*01:03:01:02 by one nucleotide substitution in codon 81 in exon 2.

In organ transplantation, immunological risk assessment uses cell crossmatch (XM) results, which can be altered by several drugs. We observed two recipients awaiting kidney and liver transplantation with positive flow cytometry XM (FCXM) on T-cells in the absence of Donor Specific Antibodies (DSA). Both were treated with vedolizumab (VDZ) for an inflammatory bowel disease (IBD). VDZ is an IgG1 directed against integrin α4β7, expressed on T and B cell subsets, we therefore suspected that VDZ interfered with XM. We tested with Luminex screening and single antigen assays and with auto- and allo-FCXM on different HLA-typed cells several sera from the two recipients, collected before and during treatment with VDZ. To assess the intensity and the kinetics of the interference, the sera collected during VDZ treatment were from the induction and the maintenance phases at different times post-injection. All sera were DSA-negative with Luminex assays, indicating the absence of interference of VDZ with virtual XM. IgG allo-FCXM on T cells was positive during the maintenance phase while it was randomly positive on B cells. On T cells, the ratio was between 1.6 and 4.4 times the negative control (positivity threshold of 1.5) for the two recipients, and did not depend on the time between collection and injection. Unique T cell populations express Integrin α4β7, then we did not observe a global shift for T cells in the presence of VDZ but a shift for a small subset which was sufficient to induce a positive FCXM. VDZ treatment did not interfere with complement-dependent cytotoxicity XM or with IgM FCXM. Pronase treatment abrogated VDZ interference. In the event of unexpected positive FCXM on T cells in a recipient with IBD, the transplant team should seek VDZ treatment and interference.

HLA-C*07:1173 differs from HLA-C*07:02:01:03 by one nucleotide substitution in codon 96 in exon 3.

HLA-DQA1*01:169 differs from HLA-DQA1*01:01:01:09 by one nucleotide substitution in codon 175 in exon 3.

HLA-DPB1*1784:01 differs from HLA-DPB1*514:01 by one nucleotide substitution in codon 57 in exon 2.

HLA-C*07:1187 differs from HLA-C*07:02:01:01 by one nucleotide substitution in codon 304 in exon 5.

HLA-B*44:357:02 differs from HLA-B*44:357:01 by one nucleotide substitution in codon 160 in exon 3.