UNVEILING MISSED OPPORTUNITIES: EXPLORING THE INTERPLAY OF CLINICAL OBSERVATIONS AND PHARMACOGENOMIC INSIGHTS IN A NON- VERBAL, NEURODEVELOPMENTALLY COMPLEX AUTISTIC ADULT
Notice bibliographique
Résumé
Abstract Background Neurodevelopmental disorders (NDD) are chronic, heterogeneous conditions often coexisting with various psychiatric disorders. It is thought that many individuals in a general outpatient psychiatric department may have undiagnosed NDD.[1] The complexity of NDD arises from intricate interactions between genetic and environmental factors, contributing to a diverse and medically complex population.[2] Managing individuals with NDD presents challenges for medical professionals due to the varied neurophysiological sensitivities to medications, leading physicians to rely on clinical experience and symptom observation. This case report illustrates the condition of a 25-year-old non-verbal male diagnosed with severe Autism Spectrum Disorder (ASD), residing in a specialized group home with 24- hour care. Notably, the patient, identified with a rare GABA-B receptor mutation through whole exome sequence analysis, exhibited daily escalating self-directed and aggressive behaviors, including head- banging, grabbing, hitting, and self-induced vomiting. Aims and Objectives The purpose of the case report is to examine the pharmacogenomic test results in the context of NDD, specifically addressing the barriers that exist in interpreting the test results in this patient population. The second objective of this study is to comment on potentially missed interventions stemming from barriers,[3]and examine whether pharmacogenomic testing should be considered an early investigation in the context of NDD. Methods The patient described in the case report was hospitalized and the Genecept 2.0 assay from Dynacare in Canada was used for the pharmacogenomic testing. Results Polymorphisms in the following genes were identified: SLC6A4 (5-HTTLPR), DRD2 (rs1799732), MTHFR (C677T), CYP1A2 (1F/1F genotype), CYP2B6 (*6/*6 genotype). The patient gradually improved with resolution of infectious processes. A poor response to dopamine antagonists was also observed. Discussion and Conclusion This case report demonstrates that pharmacogenomic testing accurately predicted the lack of response to D2 antagonists observed clinically. Genetic results concerning the serotonin reuptake transporter polymorphism align with current ASD literature. Additionally, it suggests that potential interventions such as supplementing with tryptophan and addressing deficient folate metabolism cascade in childhood or prospectively may have been overlooked, considering their links with ASD. The comprehensive case management underscores the under-utilization of pharmacogenomic testing despite its potential to guide early treatment for neurodevelopmentally complex patients and prevent injurious outcomes. In summary, pharmacogenomics should be considered an early intervention in cases of neurodevelopmental disorders. References [1]Francé s et al. (2022) Current state of knowledge on the prevalence of neurodevelopmental disorders in childhood according to the DSM-5: a systematic review in accordance with the PRISMA criteria. Child Adolesc Psychiatry Ment Health 16:27. [2]Parenti et al. (2022) Neurodevelopmental Disorders: From Genetics to Functional Pathways. Trends in Neurosciences 43:608-621. [3]Jameson et al. (2021). What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings? Frontiers in Genetics 12.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».