Polymorphisms within the metabotropic glutamate receptor 1 gene are associated with depression phenotypes

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• 作者：Andreas Menke ; ^{menke@mpipsykl.mpg.de} ; Philipp Sä ; mann ; Stefan Kloiber ; Darina Czamara ; Susanne Lucae ; Johannes Hennings ; Angela Heck ; Martin A. Kohli ; Michael Czisch ; Bertram M&#252 ; ller-Myhsok ; Florian Holsboer ; Elisabeth B. Binder
• 关键词：Unipolar depression ; Glutamate ; SNP ; Dex/CRH test ; MRI ; HPA-axis
• 刊名：Psychoneuroendocrinology
• 出版年：2012
• 期刊代码：228_03064530
• 类别：med
• 出版时间：April, 2012
• 卷：37
• 期：4
• 页码：565-575
• 文件大小：428 K

摘要

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Summary

Objectives

Glutamate has been implicated in the pathophysiology and treatment of mood disorders possibly by affecting the regulation of the hypothalamus-pituitary-adrenocortical (HPA) axis. Growing evidence suggests an important role of the metabotropic glutamate receptor 1 (mGlu1) in depression-related phenotypes. To test whether these findings can also be supported by human genetics data, we explored polymorphisms within the metabotropic glutamate receptor 1 gene (GRM1) for their association with unipolar depression (UPD) as well as with biological phenotypes of this disorder.

Methods

We first tested the association of 43 tag-SNPs covering the GRM1 locus with UPD in 350 patients and 370 matched controls. We then investigated the effects of the associated SNPs on hippocampal glutamate levels estimated using ¹H-MR-spectroscopy (¹H-MRS) and on endocrine measures from the combined dexamethasone-suppression/CRH stimulation (dex/CRH) test.

Results

Within the GRM1 locus, 22 SNPs showed nominally significant association with UPD, of which 6 withstood corrections for multiple testing (rs2268666 with best allelic p = 7.0 脳 10^鈭?). Supportive evidence for an association with UPD was gained from a second independent sample with 904 patients and 1012 controls. Furthermore, patients homozygous for the non-risk genotypes showed reduced hippocampal glutamate levels as measured by ¹H-MRS, a more pronounced normalization of HPA-axis hyperactivity as well as a better antidepressant treatment outcome.

Conclusions

These results suggest that the combination of genetic and biological markers may allow to subgroup patients into etiopathogenetically more relevant subcategories which could guide clinicians in their antidepressant treatment choices.