444. POLYGENIC RISK ANALYSES OF VENLAFAXINE-RELATED SIDE EFFECTS IN OLDER ADULTS WITH DEPRESSION
Notice bibliographique
Résumé
Abstract Background Older adults are more susceptible to antidepressant-induced side effects due to higher comorbidity, cognitive decline, and polypharmacy. Onset of side effects is also associated with antidepressant discontinuation, which might increase the risk of relapse or recurrence of depression. Therefore, it is important to investigate genomic factors underlying antidepressant-induced side effects. Aims & Objectives We performed polygenic risk score (PRS) analyses to evaluate the shared genetic architecture between venlafaxine-induced side effects and various disorders of potentially related to a higher risk for specific side effects. Method We analyzed genetic and clinical data from participants enrolled in the Incomplete Response in Late-Life Depression: Getting to Remission study (IRL-GRey, NCT00892047) phase 1, where participants received venlafaxine for 12 weeks, with dosage up to 300mg/day (Lenze et al., 2015). Side effects were assessed at the end of phase 1 using the 46-item Udvalg for Kliniske Undersøgelser (UKU) rating scale. The presence of side effects was identified by a two-point increase in UKU scores compared to baseline measurements. Additionally, according to UKU categorization, adverse effects were categorized as psychic (10 items), neurological (9 items), autonomic (11 items), and other (16 items). PRSice-2 was utilized to construct the PRSs on our target sample (IRL-GRey) using 14 summary statistics from the PGC, UK Biobank, IGAP, and MEGASTROKE consortium. We tested the association between the total 14 PRSs and the presence of at least one adverse effect. Furthermore, the presence of any psychic side effects was tested for their associations with six PRSs for psychiatric disorders (i.e., depression, bipolar disorder, schizophrenia, and antidepressant treatment response), while the presence of neurological side effects was analyzed with three PRSs for Alzheimer’s disease. Logistic regression was utilized to test for these associations adjusting for age, sex, and first three ancestry principal components. Due to the limited sample size in other populations, our PRS analyses were restricted to the European-ancestry subsample, and only discovery cohorts with predominantly European ancestry were included. The results were corrected for multiple testing using a stringent Bonferroni correction with adjusted α = 0.05/(14+6+3) = 0.0022. Results A total of 297 individuals were included in the analyses. Overall, higher PRSs for all stroke (OR = 1.43 [1.11, 1.85], p = 0.006, empirical-p = 0.03), ischemic stroke (OR = 1.44 [1.10, 1.88], p = 0.008, empirical-p = 0.04), and small vessel stroke (OR = 1.41 [1.10, 1.82], p = 0.007, empirical-p = 0.03), were nominally associated with a higher likelihood of experiencing at least one side effect after venlafaxine treatment in the IRL-GRey sample. However, none of these nominally significant associations survived multiple testing corrections before or after permutation. Discussion & Conclusions Our findings indicate nominal genetic associations between venlafaxine-related side effects and PRSs for stroke in older adults. Notably, our previous analyses indicated PRS for stroke also to be associated with non-remission in the same sample (Marshe et al., 2021). By identifying individuals at higher risk of side effects based on their genetic profile, treatment plans could be tailored to minimize side effects and optimize treatment.
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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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) | 0,005 | 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 ».