Pathway analysis of genetic markers associated with a functional MRI faces paradigm implicates polymorphisms in calcium responsive pathways

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• 作者：Morten Mattingsdal^a ; ^b ; ^{morten.mattingsdal@medisin.uio.no} ; Andrew Anand Brown^b ; ^c ; Srdjan Djurovic^b ; ^c ; Ida Elken S&#248 ; nderby^d ; Andres Server^e ; Ingrid Melle^b ; ^f ; Ingrid Agartz^b ; ^g ; Eivind Hovig^h ; ⁱ ; Jimmy Jensen^b ; ^j ; Ole A. Andreassen^b ; ^f
• 关键词：fMRI ; Negative faces ; PCA ; Pathway analysis ; Calcium/calmodulin
• 刊名：NeuroImage
• 出版年：2013
• 出版时间：15 April, 2013
• 年：2013
• 卷：70
• 期：Complete
• 页码：143-149
• 全文大小：680 K

文摘

Several lines of evidence suggest that common polygenic variation influences brain function in humans. Combining high-density genetic markers with brain imaging techniques is constricted by the practicalities of collecting sufficiently large brain imaging samples. Pathway analysis promises to leverage knowledge on function of genes to detect recurring signals of moderate effect. We adapt this approach, exploiting the deep information collected on brain function by fMRI methods, to identify molecular pathways containing genetic variants which influence brain activation during a commonly applied experiment based on a face matching task (n = 246) which was developed to study neural processing of faces displaying negative emotions. Genetic markers moderately associated (p < 10^? 4) with whole brain activation phenotypes constructed by applying principal components to contrast maps, were tested for pathway enrichment using permutation based methods. The most significant pathways are related to post NMDA receptor activation events, driven by genetic variants in calcium/calmodulin-dependent protein kinase II (CAMK2G, CAMK2D) and a calcium-regulated nucleotide exchange factor (RASGRF2) in which all are activated by intracellular calcium/calmodulin. The most significant effect of the combined polygenic model were localized to the left inferior frontal gyrus (p = 1.03 ¡Á 10^? 9), a region primarily involved in semantic processing but also involved in processing negative emotions. These findings suggest that pathway analysis of GWAS results derived from principal component analysis of fMRI data is a promising method, to our knowledge, not previously described.