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      Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

      , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , 23andMe Research Team, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

      Nature Neuroscience

      Springer Nature

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          Abstract

          Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.

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          Most cited references 38

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          Identification of 15 genetic loci associated with risk of major depression in individuals of European descent

          Despite strong evidence supporting the heritability of Major Depressive Disorder, previous genome-wide studies were unable to identify risk loci among individuals of European descent. We used self-reported data from 75,607 individuals reporting clinical diagnosis of depression and 231,747 reporting no history of depression through 23andMe, and meta-analyzed these results with published MDD GWAS results. We identified five independent variants from four regions associated with self-report of clinical diagnosis or treatment for depression. Loci with pval<1.0×10−5 in the meta-analysis were further analyzed in a replication dataset (45,773 cases and 106,354 controls) from 23andMe. A total of 17 independent SNPs from 15 regions reached genome-wide significance after joint-analysis over all three datasets. Some of these loci were also implicated in GWAS of related psychiatric traits. These studies provide evidence for large-scale consumer genomic data as a powerful and efficient complement to traditional means of ascertainment for neuropsychiatric disease genomics.
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            Skeletal muscle PGC-1α1 modulates kynurenine metabolism and mediates resilience to stress-induced depression.

            Depression is a debilitating condition with a profound impact on quality of life for millions of people worldwide. Physical exercise is used as a treatment strategy for many patients, but the mechanisms that underlie its beneficial effects remain unknown. Here, we describe a mechanism by which skeletal muscle PGC-1α1 induced by exercise training changes kynurenine metabolism and protects from stress-induced depression. Activation of the PGC-1α1-PPARα/δ pathway increases skeletal muscle expression of kynurenine aminotransferases, thus enhancing the conversion of kynurenine into kynurenic acid, a metabolite unable to cross the blood-brain barrier. Reducing plasma kynurenine protects the brain from stress-induced changes associated with depression and renders skeletal muscle-specific PGC-1α1 transgenic mice resistant to depression induced by chronic mild stress or direct kynurenine administration. This study opens therapeutic avenues for the treatment of depression by targeting the PGC-1α1-PPAR axis in skeletal muscle, without the need to cross the blood-brain barrier. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Genetic identification of brain cell types underlying schizophrenia

              With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. Applying knowledge of the cellular taxonomy of the brain from single-cell RNA-sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common variant genomic results consistently mapped to pyramidal cells, medium spiny neurons, and certain interneurons but far less consistently to embryonic, progenitor, or glial cells. These enrichments were due to sets of genes specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (synaptic genes, FMRP interactors, antipsychotic targets, etc.) generally implicate the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with medium spiny neurons did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.
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                Author and article information

                Journal
                Nature Neuroscience
                Nat Neurosci
                Springer Nature
                1097-6256
                1546-1726
                February 4 2019
                Article
                10.1038/s41593-018-0326-7
                6522363
                30718901
                7565cc6d-a9fe-4024-9930-6a97b86dad65
                © 2019

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