Petrovska Jana, Coynel David, Fastenrath Matthias, Milnik Annette, Auschra Bianca, Egli Tobias, Gschwind Leo, Hartmann Francina, Loos Eva, Sifalakis Klara, Vogler Christian, de Quervain Dominique J-F, Papassotiropoulos Andreas, Heck Angela
University of Basel, Department of Psychology, Division of Molecular Neuroscience, Birmannsgasse 8, CH-4055 Basel, Switzerland; University of Basel, Transfaculty Research Platform Molecular and Cognitive Neurosciences, Birmannsgasse 8, CH-4055 Basel, Switzerland.
University of Basel, Department of Psychology, Division of Cognitive Neuroscience, Birmannsgasse 8, CH-4055 Basel, Switzerland; University of Basel, Transfaculty Research Platform Molecular and Cognitive Neurosciences, Birmannsgasse 8, CH-4055 Basel, Switzerland.
J Psychiatr Res. 2017 Aug;91:116-123. doi: 10.1016/j.jpsychires.2017.03.007. Epub 2017 Mar 6.
Depressive symptoms exist on a continuum, the far end of which is found in depressive disorders. Utilizing the continuous spectrum of depressive symptoms may therefore contribute to the understanding of the biological underpinnings of depression. Gene set enrichment analysis (GSEA) is an important tool for the identification of gene groups linked to complex traits, and was applied in the present study on genome-wide association study (GWAS) data of depression scores and their brain-level structural correlates in healthy young individuals. On symptom level (i.e. depression scores), robust enrichment was identified for two gene sets: NCAM1 Interactions and Collagen Formation. Depression scores were also associated with decreased fractional anisotropy (FA) - a brain white matter property - within the forceps minor and the left superior temporal longitudinal fasciculus. Within each of these tracts, mean FA value of depression score-associated voxels was used as a phenotype in a subsequent GSEA. The NCAM1 Interactions gene set was significantly enriched in these tracts. By linking the NCAM1 Interactions gene set to depression scores and their structural brain correlates in healthy participants, the current study contributes to the understanding of the molecular underpinnings of depressive symptomatology.
抑郁症状存在于一个连续体上，其远端表现为抑郁障碍。因此，利用抑郁症状的连续谱可能有助于理解抑郁症的生物学基础。基因集富集分析（GSEA）是识别与复杂性状相关的基因组的重要工具，本研究将其应用于健康年轻个体抑郁评分及其脑水平结构相关性的全基因组关联研究（GWAS）数据。在症状水平（即抑郁评分）上，发现两个基因集有显著富集：NCAM1相互作用和胶原形成。抑郁评分还与小钳和左侧颞上纵束内的分数各向异性（FA）降低有关，FA是一种脑白质属性。在这些纤维束中的每一个中，将与抑郁评分相关的体素的平均FA值用作后续GSEA中的一个表型。NCAM1相互作用基因集在这些纤维束中显著富集。通过将NCAM1相互作用基因集与健康参与者的抑郁评分及其脑结构相关性联系起来，本研究有助于理解抑郁症状学的分子基础。
