Kraemmer Julia, Smith Kara, Weintraub Daniel, Guillemot Vincent, Nalls Mike A, Cormier-Dequaire Florence, Moszer Ivan, Brice Alexis, Singleton Andrew B, Corvol Jean-Christophe
Sorbonne Universités, UPMC Univ Paris 06, and INSERM UMRS_1127 and CIC_1422, and CNRS UMR_7225, and AP-HP, and ICM, Département des maladies du système nerveux and Département de Génétique, Hôpital Pitié-Salpêtrière, Paris, France Medical University of Vienna, Vienna, Austria.
Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
J Neurol Neurosurg Psychiatry. 2016 Oct;87(10):1106-11. doi: 10.1136/jnnp-2015-312848. Epub 2016 Apr 13.
Impulse control disorders (ICD) are commonly associated with dopamine replacement therapy (DRT) in patients with Parkinson's disease (PD). Our aims were to estimate ICD heritability and to predict ICD by a candidate genetic multivariable panel in patients with PD.
Data from de novo patients with PD, drug-naïve and free of ICD behaviour at baseline, were obtained from the Parkinson's Progression Markers Initiative cohort. Incident ICD behaviour was defined as positive score on the Questionnaire for Impulsive-Compulsive Disorders in PD. ICD heritability was estimated by restricted maximum likelihood analysis on whole exome sequencing data. 13 candidate variants were selected from the DRD2, DRD3, DAT1, COMT, DDC, GRIN2B, ADRA2C, SERT, TPH2, HTR2A, OPRK1 and OPRM1 genes. ICD prediction was evaluated by the area under the curve (AUC) of receiver operating characteristic (ROC) curves.
Among 276 patients with PD included in the analysis, 86% started DRT, 40% were on dopamine agonists (DA), 19% reported incident ICD behaviour during follow-up. We found heritability of this symptom to be 57%. Adding genotypes from the 13 candidate variants significantly increased ICD predictability (AUC=76%, 95% CI (70% to 83%)) compared to prediction based on clinical variables only (AUC=65%, 95% CI (58% to 73%), p=0.002). The clinical-genetic prediction model reached highest accuracy in patients initiating DA therapy (AUC=87%, 95% CI (80% to 93%)). OPRK1, HTR2A and DDC genotypes were the strongest genetic predictive factors.
Our results show that adding a candidate genetic panel increases ICD predictability, suggesting potential for developing clinical-genetic models to identify patients with PD at increased risk of ICD development and guide DRT management.
冲动控制障碍（ICD）通常与帕金森病（PD）患者的多巴胺替代疗法（DRT）相关。我们的目的是估计ICD的遗传性，并通过候选基因多变量面板预测PD患者的ICD。
从帕金森病进展标志物倡议队列中获取初发PD患者的数据，这些患者在基线时未服用药物且无ICD行为。将发作性ICD行为定义为PD冲动控制障碍问卷中的阳性评分。通过对全外显子测序数据进行限制最大似然分析来估计ICD的遗传性。从DRD2、DRD3、DAT1、COMT、DDC、GRIN2B、ADRA2C、SERT、TPH2、HTR2A、OPRK1和OPRM1基因中选择13个候选变体。通过受试者操作特征（ROC）曲线的曲线下面积（AUC）评估ICD预测。
在纳入分析的276例PD患者中，86%开始接受DRT，40%使用多巴胺激动剂（DA），19%在随访期间报告有发作性ICD行为。我们发现该症状的遗传性为57%。与仅基于临床变量的预测（AUC=65%，95%CI（58%至73%），p=0.002）相比，添加13个候选变体的基因型显著提高了ICD的预测性（AUC=76%，95%CI（70%至83%））。临床遗传预测模型在开始DA治疗的患者中达到最高准确性（AUC=87%，95%CI（80%至93%））。OPRK1、HTR2A和DDC基因型是最强的遗传预测因素。
我们的结果表明，添加候选基因面板可提高ICD的预测性，提示开发临床遗传模型以识别有ICD发生风险增加的PD患者并指导DRT管理具有潜力。
