Dissecting the neurobiology of anxiety across diagnostic categories – the extension of the Marburg/Münster affective disorders cohort study (MACS) regarding anxiety disorders

焦虑症（AXD）病因学研究的进展往往受到样本量小，研究之间高度异质性和缺乏独立样本重复的阻碍。此外，只有少数纵向MRI研究和transdiagnosis方法完全缺失。然而，考虑到AXD和情感障碍（AD，即重度抑郁症（MDD）和双相情感障碍（BD））之间约40- 70%的高共病率，转诊断方法对AXD尤其重要，这至少可以部分地由遗传和环境风险因素的高度交叉来解释。因此，出现了对新一代研究的需求，所述新一代研究采用a）大规模样品，B）纵向设计，c）结构和功能成像方法，d）明确定义的、深度表型化的患者和携带遗传、环境和这两种风险因素的对照样品，e）用最新的遗传和表观遗传方法分析，f）创新的多组学分子方法。为了真正推进该领域，g）基于h）来自这些患者组的多模态数据的多变量分析和i）在其他样本中的复制的几个患者组的transdiagnosis方法将是必要的下一步。（惊恐障碍、广场恐怖症、社交恐怖症、多重恐怖症、广泛性焦虑症）。数据收集、质量控制和分析程序对应于DFG FOR 2107“神经生物学情感障碍”（www.FOR2107.de）的程序。表型分析包括多模式MRI成像、GWAS、细胞因子、微生物组、环境和终身风险、神经心理学、人格特质和临床参数。截至2019年5月，在第一次测量时间在FOR 2107中检查了2577例受试者（健康、MDD、BD），在第二次测量时间检查了1262例受试者。在AD患者中，42%的患者合并有AXD。本申请包括两年后在第一测量点招募和分析300名AXD患者和在第二测量点招募和分析225名患者。这种方法以可管理的成本以多种方式扩展了FOR 2107的现有独特数据。数据分析将包括单变量、假设驱动的方法，但特别是多维分析与机器学习技术的多组学方法。拟议的项目将开放一个大型的、独特的AXD患者队列，使其有可能首次分析基因-环境相互作用的基础上，多个（表）遗传和（内）表型数据在transdiagnosis和纵向设计。这使得新的病理生理学实体被定义在神经生物学的基础上。这些将从根本上拓宽对AXD病因的理解，并有助于预防、预测个体疾病进展和开发新疗法。

Advances in etiology research in anxiety disorders (AXD) are often hampered by small sample sizes, high heterogeneity between studies, and lack of replication in independent samples. Furthermore, there are only few longitudinal MRI studies and transdiagnostic approaches are completely missing. However, transdiagnostic approaches are particularly important for AXD, considering the high comorbidity of about 40-70 % between AXD and affect disorders (AD, ie, major depressive disorder (MDD) and bipolar disorder (BD)), which can be explained at least in part by a high intersection of genetic and environmental risk factors. Thus, there is an emerging need for a novel generation of studies employing a) large-scale samples, b) longitudinal designs, c) structural and functional imaging approaches in d) well-defined, deeply phenotyped patients and control samples carrying genetic, environmental, and both risk factors, which are e) analysed with latest genetic and epigenetic methods and f) innovative multi-omics molecular approaches. To truly advance the field, g) a transdiagnostic approach with several patient groups based on h) multivariate analyses of multimodal data from these patient groups and i) replication in other samples will be a necessary next step.The aim of the proposed project is the investigation of a total of 300 patients with AXD (panic disorder, agoraphobia, social phobia, multiple phobias, generalized anxiety disorder) at two time points, two years apart. Data collection, quality control and analysis procedures correspond to those of the DFG FOR2107 "Neurobiology Affective Disorders" (www.FOR2107.de). Phenotyping includes multimodal MRI imaging, GWAS, cytokines, microbiome, environmental and lifetime risks, neuropsychology, personality traits and clinical parameters. As of May 2019, 2577 subjects (healthy, MDD, BD) were examined in the FOR2107 for the first and 1262 for the second measurement time. Of the patients with AD, 42% have a comorbid AXD. The present application comprises the recruitment and analysis of 300 patients with AXD at the first and 225 patients at the second measurement point after two years. This approach extends the existing, unique data of the FOR2107 in manifold ways at manageable costs. The data analyzes will include both univariate, hypothesis-driven approaches, but especially multi-dimensional analyzes with machine learning techniques for the multi-omics approaches.The proposed project will open up a large, unique cohort of patients with AXD, making it possible for the first time to analyze gene-environment interactions based on multiple (epi-) genetic and (endo) phenotypic data in a transdiagnostic and longitudinal design. This allows new pathophysiological entities to be defined on a neurobiological basis. These will fundamentally broaden the understanding of the etiology of AXD and contribute to the prevention, prediction of individual disease progression, and the development of new therapies.