Molecular Assessment of Heart Transplant Biopsies
Notice bibliographique
Résumé
INTERHEART (ClinicalTrails.gov NCT02670408). Introduction We previously developed a molecular diagnostic system for assessment of rejection phenotypes in endomyocardial biopsies (EMB) based on expression of rejection-associated transcripts (RAT) derived in kidney (JHLT 36:1192, 2017). This system used archetypal analysis to identify 3 rejection-related molecular phenotypes among the biopsies (A1NoRejection, A2TCMR, A3ABMR), with each biopsy assigned scores relating them to the molecular phenotypes. We now explored whether there was another dimension beyond rejection that reflected acute parenchymal injury. Materials & Methods 889 single-piece EMBs from 462 heart transplant recipients at 8 centres in North America, Europe, and Australia were analyzed on Affymetrix microarrays. We used 2 methods to assess injury: archetypal analysis to assign groups, and expression of previously defined injury-repair transcripts (IRRAT). EMBs with A2TCMR scores ≥ 0.3 and A3ABMR scores ≥ 0.5 in the previously published 3 archetype model were designated “molecular rejection.” EMBs with A4 scores ≥ 0.4 in a new 4 archetype model were designated “molecular injury.” The rejection and injury designations were not mutually exclusive. Results EMBs characterized by archetypal analysis using 4 rather than 3 archetypes were distributed by principal component analysis based on RAT expression (Figure 1). PC1 reflected rejection, and PC2 reflected ABMR vs. TCMR (Figure 1A). The new group (A4) had an “acute injury” phenotype that was most apparent in PC3 (Figure 1B).A4 had high expression of macrophage transcripts and IRRAT. The median IRRAT score in EMBs with high injury and low rejection scores was high compared to relatively normal biopsies (0.79 vs. -0.19) (Table 1). Median IRRAT scores in EMBs with high rejection and low injury were also elevated, albeit to a lesser extent (0.21 vs. -0.19). The expression of rejection transcripts was somewhat elevated in acute injury without rejection, reflecting overlap between inflammatory processes activated in rejection and non- rejection-related injury.Many A4 EMBs were taken very early post-transplant (median time 30 days), probably reflecting injury induced in donation/implantation. Histology sometimes misdiagnosed rejection in A4 EMBs because of the macrophage infiltration: of 17 EMBs with high molecular injury and no molecular rejection, 9 were called rejection by histology. Conclusion Unsupervised analysis with 4 archetypes discovered a new group, acute injury, with high expression of macrophage and injury transcripts and early time post-transplant. Thus hearts often have an early acute injury phenotype that is inflamed, more so than in kidney transplants. Some of these biopsies have molecular rejection but some do not. Some with no molecular rejection are called rejection by histology, apparently reflecting injury-induced inflammation. We conclude that a molecular approach that independently assesses rejection and injury is needed for EMBs. Transcriptome Sciences, Inc.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,004 |
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 ».