Letter to the Editor Re: Letter by Naesens et al. Microvascular inflammation: Gene expression changes do not necessarily reflect pathogenesis
Notice bibliographique
Résumé
We thank the authors for this useful commentary1Naesens M Thaunat O Mengel M Microvascular inflammation: gene expression changes do not necessarily reflect pathogenesis.Am J Transplant. 2022; (doi:10.1111/ajt.17136)Abstract Full Text Full Text PDF Scopus (1) Google Scholar on our paper analyzing DSA-negative molecular ABMR,2Halloran PF, Madill-Thomsen KS, Pon S, et al. Molecular diagnosis of ABMR with or without donor-specific antibody in kidney transplant biopsies: differences in timing and intensity but similar mechanisms and outcomes [published online ahead of print May 16, 2022]. Am J Transplant. doi:10.1111/ajt.17092Google Scholar although we disagree to some extent with the conclusions. Our data found that in the INTERCOMEX population with molecular ABMR, DSA negativity is very common, particularly in early-stage ABMR but also in late-stage ABMR. On average, DSA-negative ABMR was earlier, less intense (i.e. lower ABMR-associated gene expression), and more often C4d-negative, but was virtually identical to DSA-positive ABMR in the top differentially expressed ABMR-associated transcripts. We could not find distinct molecular differences between DSA-negative and DSA-positive ABMR, other than some small increases in injury-related transcript expression, which may be explained by the earlier mean time posttransplant. We have recently confirmed the main points in the new Trifecta-Kidney analysis, where we show that both molecular and histologic ABMR are approximately 50% DSA-negative.3Halloran PF, Reeve J, Madill-Thomsen KS, et al. Antibody-mediated rejection without detectable donor-specific antibody releases donor-derived cell-free DNA: results from the Trifecta study. Transplantation. In press.Google Scholar In Trifecta-Kidney, DSA-negative ABMR is slightly less molecularly active, but still releases donor-derived cell-free DNA at levels similar to that seen in DSA-positive ABMR.3Halloran PF, Reeve J, Madill-Thomsen KS, et al. Antibody-mediated rejection without detectable donor-specific antibody releases donor-derived cell-free DNA: results from the Trifecta study. Transplantation. In press.Google Scholar The main point is that within all ABMR—DSA-negative or DSA-positive—there is extensive heterogeneity in intensity and stage. Type 1 ABMR (in patients with DSA before transplantation) behaves differently from type 2 ABMR with de novo DSA.4Aubert O Loupy A Hidalgo L et al.Antibody-mediated rejection due to preexisting versus de novo donor-specific antibodies in kidney allograft recipients.J Am Soc Nephrol. 2017; 28: 1912-1923Crossref PubMed Scopus (158) Google Scholar In addition, there is a subtle minor ABMR-related process in many biopsies that we have been calling negative for ABMR because they fall below the arbitrary thresholds for ABMR established both in MMDx and histology.5Madill-Thomsen KS Bohmig GA Bromberg J et al.Donor-specific antibody is associated with increased expression of rejection transcripts in renal transplant biopsies classified as no rejection.J Am Soc Nephrol. 2021; 32: 2743-2758Crossref PubMed Scopus (16) Google Scholar We must start thinking of ABMR-related molecular and histologic changes as a broad spectrum. At the moment, it is unlikely that distinct disease mechanisms operate in DSA-negative versus DSA-positive ABMR. These labels can be retained as reminders of one aspect of the heterogeneity within ABMR, as long as the much greater heterogeneity in intensity, stage, and duration is recognized. We are in a new era of appreciating the diversity within the ABMR phenotype and its relationship to pathogenic mechanisms. More importantly, management issues are critical: we do not really know how to manage DSA-positive ABMR or DSA-negative ABMR, or for that matter how to adjust management based on other aspects of heterogeneity in the ABMR spectrum. We should keep an open mind on how we should ultimately classify these common, important, and heterogeneous disease states. The authors of this manuscript have conflicts of interest to disclose as described by the American Journal of Transplantation. P.F. Halloran holds shares in Transcriptome Sciences Inc., a University of Alberta research company dedicated to developing molecular diagnostics, supported in part by a licensing agreement between TSI and Thermo Fisher, and by a research grant from Natera. P.F. Halloran is a consultant to Natera. The other author has declared no conflict of interest exists.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,027 | 0,026 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,010 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».