W5. INVESTIGATING THE GENETIC LINK BETWEEN HEART RATE VARIABILITY (HRV) AND ANXIETY DISORDERS: POLYGENIC RISK SCORE OVERLAP AND ASSOCIATION OF HRV GENOME-WIDE POLYMORPHISMS WITH ANXIETY
Notice bibliographique
Résumé
Background Anxiety disorders are associated with reduced heart rate variability (HRV), a heritable measure of difference in time between heartbeats. Given this link, genetic variants related to HRV may provide insight into the risk for pathological anxiety. This study examined the genetic overlap between anxiety risk and HRV using polygenic risk scores (PRS). In addition, polymorphisms related to HRV were investigated to determine if they influence anxiety disorder risk, potentially mediated by HRV. Methods In 184 European individuals (100 anxiety disorder, 84 controls, age 18-65, 69% female), we measured 5-minute resting HRV via photoplethysmography with the Empatica E4 wristband and genotyped their DNA samples with the Global Screening Array. Blood volume pulse data was processed via Kubios HRV software, and HRV was calculated using the root mean square of successive beat-to-beat interval differences. Anxiety and HRV PRSs were computed using the summary statistics from a meta-analysis of anxiety disorder GWASs and meta-analysis of HRV GWASs, respectively, using a clumping and thresholding approach with standard p-value thresholds (5e-8 to 1) followed by high-resolution analysis (PRSice-2). To test for anxiety disorder PRS association with resting HRV in our sample, and the HRV PRS association with anxiety disorder, we used linear and logistic regression , respectively. Additionally, using the 15 significant SNPs from a pre-existing HRV GWAS, we performed mediation analyses (SPSS macro PROCESS) to study their associations with anxiety disorder status in our sample through resting HRV. Covariates in all analyses included age, sex, and the first three principal components of ancestry. Results For the association of anxiety disorders PRS with resting HRV, none of the standard p-value thresholds explained a significant amount of variance. The high-resolution analysis revealed a p-value threshold of 0.0004 for the maximum variance explained in resting HRV, which was nominally significant (R2=0.023, p=0.029, β=-0.16, 501 SNPs). For the association of HRV PRS with anxiety disorder status, among the standard p-value thresholds, 5e-05 explained the largest amount of variance and was nominally associated with anxiety disorder (R2=0.027, p=0.039, OR=1.43, 55 SNPs). In the high-resolution analysis, we observed a p-value threshold of 3.34e-05 for the maximum variance explained in anxiety disorder status, displaying nominal significance (R2=0.035, p=0.018, OR=1.51, 48 SNPs). When testing whether the HRV GWAS top-hit SNPs are associated with anxiety disorder mediated through resting HRV, NDUFA11 rs12980262 A-carriers and GNG11 rs180238 and rs4262 C-carriers had higher anxiety risk through lower HRV (b=0.35, 95%CI=0.09–0.76; b=0.15, 95%CI=0.01–0.39; b=0.17, 95%CI=0.02–0.42), and LINC00477 rs10842383 T-carriers had lower anxiety risk through higher HRV (b=-0.17, 95%CI=-0.42–-0.004). Discussion This study provides preliminary support for a genetic overlap between anxiety disorders and HRV. We also identified genetic variants from HRV investigations that link to anxiety, with effects influenced by HRV. These variants have not been studied in the context of psychiatry and are therefore novel markers to explore further. Limitations include the modest sample size and restriction to Europeans. The anxiety-HRV association thus supports the potential of HRV genetic variations as novel therapy targets that may alleviate pathological anxiety symptoms.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».