Pathways from Normal and Disordered Personality to Substance Use Disorders

描述（由申请人提供）：慢性物质使用（SU）和合法和非法物质使用障碍（sud）使人衰弱，并在很大程度上导致全球发病率和死亡率。人格和人格障碍强烈影响SU和sud的风险，但我们对其中的病因途径知之甚少。该项目利用一个独特的资源来解决一些关于SU和sud的新研究问题。我们将使用最先进的遗传流行病学方法，通过纵向、表型丰富、遗传信息丰富的基于人群的挪威双胞胎登记处（NTR），确定从正常、异常和病理人格到合法和非法SU和sud的因果和非因果途径。我们将利用挪威独特的个人识别号码，将NTR数据与国家、以人口为基础的临床登记处联系起来，研究风险因素、原因和疾病机制以及合法和非法SU和sud的后果。这将有助于确认和识别未报告的SUD病例。登记数据还将提供客观的人口统计、社会经济地位和社会心理功能障碍的信息，通过病假、残疾和疾病来衡量，从而使我们能够确定从SU和SUD到社会心理功能障碍的因果和非因果途径。我们的项目有六个科学目标和一个操作目标。我们将使用横断面和纵向数据来估计去抑制正常、异常和病理人格类型、SU和SUD以及相关的I轴疾病之间的表型关联的性质，然后将这些关联分解为遗传和环境途径。使用互补方法，我们将对关键变量之间的因果关系方向进行建模，同时测试冥想模型，以阐明SU作为sud和相关外化谱系障碍的门户的作用。使用遗传信息纵向模型，我们将探索酒精使用障碍和重度抑郁症之间的因果关系。我们还将合并NTR双胞胎数据与挪威统计局的数据，以检查从SU和sud到客观社会心理功能障碍的表型和遗传途径，并以全国病假、残疾和疾病为索引。我们的操作目标是确定新的第四波关于NTR双胞胎终生SU和sud的问卷数据。这将为测试相互竞争的纵向模型提供统计能力。协作小组的建模专业知识将确保这些资源的最佳利用。本申请是在由美国国立卫生研究院和挪威研究理事会共同建立的“挪威与美国研究小组合作项目”特别资助机制下提交的。我们建议通过将NTR的新数据和现有数据与国家、基于人群的人口统计和临床登记处联系起来，研究正常、异常和病理人格中的遗传和环境风险因素如何影响和预测SU和sud的风险。同样的数据将提供客观资料，说明社会福利津贴和社会福利津贴如何与病假、疾病和残疾有关。

DESCRIPTION (provided by applicant): Chronic substance use (SU) and licit and illicit substance use disorders (SUDs) are debilitating and contribute substantially to global morbidity and mortality. Personality and personality disorders strongly influence risk of SU and SUDs, but we know little about the etiologic pathways involved. This project utilizes a unique resource to address a number of novel research questions concerning SU and SUDs. We will use state-of-the-art genetic epidemiological methods to identify causal and non-causal pathways from normal, abnormal and pathological personality to licit and illicit SU and SUDs using the longitudinal, phenotypically rich, and genetically informative population-based Norwegian Twin Registry (NTR). We will link the NTR data to national, population-based and clinical registries, using Norway's unique personal identification number to study the risk factors, causes and disease mechanism as well as consequences of licit and illicit SU and SUDs. This will enable validation and identification of unreported SUD cases. The registry data will also provide objective information on demographics, socioeconomic status and psychosocial dysfunction as measured by sick leave, disability, and illness thereby enabling us to determine the causal and non-causal pathways from SU and SUD to psychosocial dysfunction. Our project has 6 scientific and one operational aim. We will use cross-sectional and longitudinal data to estimate the nature of the phenotypic associations between disinhibitory normal, abnormal and pathological personality types, SU and SUD, and correlated Axis I disorders before decomposing the associations into genetic and environmental pathways. Using complementary approaches we will model direction of causation between our key variables, while testing meditational models to clarify the role of SU as a gateway to SUDs and correlated externalizing spectrum disorders. Using genetically informative longitudinal models we will explore the causal relationship between alcohol use disorders and major depression. We will also merge NTR twin data with data from Statistics Norway to examine the phenotypic and genetic pathways from SU and SUDs to objective psychosocial dysfunction as indexed by nationwide sick leave, disability and illness. Our operational aim is to ascertain a new, fourth wave of questionnaire data on lifetime SU and SUDs from the NTR twins. This will provide statistical power to test competing longitudinal models. The modelling expertise of the collaborative group will ensure optimal exploitation of these resources. This application is submitted under a special funding mechanism "Norwegian Collaborative Projects with Research Groups in the United States" established and cofounded by the NIH and the Research Council of Norway. We propose to study how genetic and environmental risk factors in normal, abnormal and pathological personality impact and predict the risk of SU and SUDs by linking new and existing data from the NTR to national, population-based demographic and clinical registries. The same data will provide objective information on how SU and SUDs are related to sick leave, illness and disability.