The impact of population pharmacogenomics and risk allele frequencies on cisplatin-induced peripheral sensory neuropathy (PSN).
Notice bibliographique
Résumé
12092 Background: Taxane-treated breast cancer patients with genetically African ancestry have worse PSN than other groups. However, no study has examined the association between ancestry and PSN after cisplatin-based chemotherapy. Increased risk could be partially explained by differing risk allele frequencies across populations for alleles increasing the general vulnerability to PSN or altering drug metabolism. Methods: The Platinum Study enrolled cisplatin-treated testicular cancer survivors (TCS) who completed clinical exams and surveys. A PSN score was derived from the mean of 8 sensory items (using EORTC-CIPN20), assigning severity on a 0-2 scale. Multidimensional scaling scores for each TCS were calculated, plotted and anchored by data from the 1000 Genomes Reference population to determine genetic ancestry. Multinomial logistic regression assessed the association between genetic ancestry and PSN. To determine risk alleles for PSN and allele frequencies across populations, risk allele panels were created, including ancestry-informative markers (AIMs) determined by the AncestrySNPMiner tool. Allele frequencies were calculated in each group; SNPs with frequency differences > 0.3 in the African (AFRAFR) population vs. others were included. For filtering the AIMs, GTEx data was used to identify expression quantitative trait loci (eQTL) or splicing quantitative trait loci (sQTL) in nerve/brain tissue. Multinomial logistic regression assessed associations between SNP genotype and PSN phenotype for SNPs with differing allele frequencies across populations. Results: Despite small numbers of non-Europeans, TCS with African ancestry had increased incidence and severity of PSN vs. TCS with European ancestry. In a subset analysis of EUR (n = 681) and AFRAFR (n = 13) patients who received 400-450 mg/m2 of cisplatin, the relative risk ratio (RRR) in the AFRAFR vs. EUR TCS of severe neuropathy vs. none was 7.96 (P = 0.074) and the RRR for any neuropathy vs. none was 7.79 (P = 0.049). There were 394 independent AIMs with significant ( > 0.3) allele frequency differences between the AFRAFR and other populations that were eQTLs and/or sQTLs in nerve/brain tissue. Using multinominal logistic regression between genotype and phenotype for all TCS (n = 1513) with covariates for age at survey and 10 genetic principal components: 16 SNPs had P-values < 0.05 for severe PSN vs. none and/or any PSN vs. none. Although not statistically significant with multiple testing corrections, these suggestively significant SNPs could be potentially validated in additional populations. Conclusions: These results are preliminary evidence for the potential importance of differing risk allele frequencies across populations in explaining some disparities in cisplatin-related PSN. If confirmed, genotyping for risk variants could impact treatment decisions and enable monitoring to mitigate PSN.
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 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».