Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies

Identification of differentially expressed genes of blood leukocytes for Schizophrenia

Background

Schizophrenia (SCZ) is a severe neurodevelopmental disorder with brain dysfunction. This study aimed to use bioinformatic analysis to identify candidate blood biomarkers for SCZ.

Methods

The study collected peripheral blood leukocyte samples of 9 SCZ patients and 20 healthy controls for RNA sequencing analysis. Bioinformatic analyses included differentially expressed genes (DEGs) analysis, pathway enrichment analysis, and weighted gene co-expression network analysis (WGCNA).

Results

This study identified 1,205 statistically significant DEGs, of which 623 genes were upregulated and 582 genes were downregulated. Functional enrichment analysis showed that DEGs were mainly enriched in cell chemotaxis, cell surface, and serine peptidase activity, as well as involved in Natural killer cell-mediated cytotoxicity. WGCNA identified 16 gene co-expression modules, and five modules were significantly correlated with SCZ (p < 0.05). There were 106 upregulated genes and 90 downregulated genes in the five modules. The top ten genes sorted by the Degree algorithm were RPS28, BRD4, FUS, PABPC1, PCBP1, PCBP2, RPL27A, RPS21, RAG1, and RPL27. RAG1 and the other nine genes belonged to the turquoise and pink module respectively. Pathway enrichment analysis indicated that these 10 genes were mainly involved in processes such as Ribosome, cytoplasmic translation, RNA binding, and protein binding.

Conclusion

This study finds that the gene functions in key modules and related enrichment pathways may help to elucidate the molecular pathogenesis of SCZ, and the potential of key genes to become blood biomarkers for SCZ warrants further validation.

The role of cell adhesion molecule IgSF9b at the inhibitory synapse and psychiatric disease

Understanding perturbations in synaptic function between health and disease states is crucial to the treatment of neuropsychiatric illness. While genome-wide association studies have identified several genetic loci implicated in synaptic dysfunction in disorders such as autism and schizophrenia, many have not been rigorously characterized. Here, we highlight immunoglobulin superfamily member 9b (IgSF9b), a cell adhesion molecule thought to localize exclusively to inhibitory synapses in the brain. While both pre-clinical and clinical studies suggest its association with psychiatric diseases, our understanding of IgSF9b in synaptic maintenance, neural circuits, and behavioral phenotypes remains rudimentary. Moreover, these functions wield undiscovered influences on neurodevelopment. This review evaluates current literature and publicly available gene expression databases to explore the implications of IgSF9b dysfunction in rodents and humans. Through a focused analysis of one high-risk gene locus, we identify areas requiring further investigation and unearth clues related to broader mechanisms contributing to the synaptic etiology of psychiatric disorders.

The genetic basis of major depressive disorder

The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.

Associating broad and clinically defined polygenic scores for depression with depression-related phenotypes

Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGSBD) and clinical- (PGSMDD) depression summary statistics from the UK Biobank in an independent sample of adults (N = 210; 100% European Ancestry) who were extensively phenotyped for depression and related neurocognitive traits (e.g., rumination, emotion regulation, anhedonia, and resting frontal alpha asymmetry). The UK Biobank-derived PGSBD had small associations with MDD, depression severity, anhedonia, cognitive reappraisal, brooding, and suicidal ideation but only the association with suicidal ideation remained statistically significant after correcting for multiple comparisons. Similarly small associations were observed for the PGSMDD but none remained significant after correcting for multiple comparisons. These findings provide important initial guidance about the expected effect sizes between current UKB PGSs for depression and depression-related neurocognitive phenotypes.

Connecting Dots between Mitochondrial Dysfunction and Depression

Mitochondria are the prime source of cellular energy, and are also responsible for important processes such as oxidative stress, apoptosis and Ca2+ homeostasis. Depression is a psychiatric disease characterized by alteration in the metabolism, neurotransmission and neuroplasticity. In this manuscript, we summarize the recent evidence linking mitochondrial dysfunction to the pathophysiology of depression. Impaired expression of mitochondria-related genes, damage to mitochondrial membrane proteins and lipids, disruption of the electron transport chain, higher oxidative stress, neuroinflammation and apoptosis are all observed in preclinical models of depression and most of these parameters can be altered in the brain of patients with depression. A deeper knowledge of the depression pathophysiology and the identification of phenotypes and biomarkers with respect to mitochondrial dysfunction are needed to help early diagnosis and the development of new treatment strategies for this devastating disorder.

GRM7 gene mutations and consequences for neurodevelopment

The metabotropic glutamate receptor 7 (mGlu7), encoded by the GRM7 gene in humans, is a presynaptic, G protein-coupled glutamate receptor that is essential for modulating neurotransmission. Mutations in or reduced expression of GRM7 have been identified in different genetic neurodevelopmental disorders (NDDs), and rare biallelic missense variants have been proposed to underlie a subset of NDDs. Clinical GRM7 variants have been associated with a range of symptoms consistent with neurodevelopmental molecular features, including hypomyelination, brain atrophy and defects in axon outgrowth. Here, we review the newest findings regarding the cellular and molecular defects caused by GRM7 variants in NDD patients.

Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases

Loneliness and social isolation are detrimental to mental health and may lead to cognitive impairment and neurodegeneration. Although several molecular signatures of loneliness have been identified, the molecular mechanisms by which loneliness impacts the brain remain elusive. Here, we performed a bioinformatics approach to untangle the molecular underpinnings associated with loneliness. Co-expression network analysis identified molecular 'switches' responsible for dramatic transcriptional changes in the nucleus accumbens of individuals with known loneliness. Loneliness-related switch genes were enriched in cell cycle, cancer, TGF-β, FOXO, and PI3K-AKT signaling pathways. Analysis stratified by sex identified switch genes in males with chronic loneliness. Male-specific switch genes were enriched in infection, innate immunity, and cancer-related pathways. Correlation analysis revealed that loneliness-related switch genes significantly overlapped with 82% and 68% of human studies on Alzheimer's (AD) and Parkinson's diseases (PD), respectively, in gene expression databases. Loneliness-related switch genes, BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2, have been identified as genetic risk factors for AD. Likewise, switch genes HLA-DRB5, ALDOA, and GPNMB are known genetic loci in PD. Similarly, loneliness-related switch genes overlapped in 70% and 64% of human studies on major depressive disorder and schizophrenia, respectively. Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression. Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia. Collectively, we identified molecular determinants of loneliness and dysregulated pathways in the brain of non-demented adults. The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides a molecular explanation for the observed prevalence of these diseases among lonely individuals.

Persistent challenges in the development of an mGlu7 PAM in vivo tool compound: The discovery of VU6046980

Herein, we report on the further chemical optimization of the first reported mGlu7 positive allosteric modulator (PAM), VU6027459. Replacement of the quinoline core by a cinnoline scaffold increased mGlu7 PAM potency by ∼ 10-fold, and concomitant introduction of a chiral tricyclic motif led to potent mGlu7 PAMs with enantioselective mGlu receptor selectivity profiles. Of these, VU6046980 emerged as a putative in vivo tool compound with excellent CNS penetration (Kp = 4.1; Kp,uu = 0.7) and efficacy in preclinical models. However, either off-target activity at the sigma-1 receptor or activity at a target not elucidated by large ancillary pharmacology panels led to sedation not driven by activation of mGlu7 (validated in Grm7 knockout mice). Thus, despite a significant advance, a viable mGlu7 PAM in vivo tool remains elusive.

GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis

We present the results of the depression Genome-wide association studies study performed on a cohort of Russian-descent individuals, which identified a novel association at chromosome 7q21 locus. Gene prioritization analysis based on already known depression risk genes indicated MAGI2 (S-SCAM) as the most probable gene from the locus and potential susceptibility gene for the disease. Brain and gut expression patterns were the main features highlighting functional relatedness of MAGI2 to the previously known depression risk genes. Local genetic covariance analysis, analysis of gene expression, provided initial suggestive evidence of hospital anxiety and depression scale and diagnostic and statistical manual of mental disorders scales having a different relationship with gut-brain axis disturbance. It should be noted, that while several independent methods successfully in silico validate the role of MAGI2, we were unable to replicate genetic association for the leading variant in the MAGI2 locus, therefore the role of rs521851 in depression should be interpreted with caution.

The association of ARRB1 polymorphisms with response to antidepressant treatment in depressed patients

Introduction: β-arrestin 1, a protein encoded by ARRB1 involved in receptor signaling, is a potential biomarker for the response to antidepressant drug (ATD) treatment in depression. We examined ARRB1 genetic variants for their association with response following ATD treatment in METADAP, a cohort of 6-month ATD-treated depressed patients. Methods: Patients (n = 388) were assessed at baseline (M0) and after 1 (M1), 3 (M3), and 6 months (M6) of treatment for Hamilton Depression Rating Scale (HDRS) changes, response, and remission. Whole-gene ARRB1 variants identified from high-throughput sequencing were separated by a minor allele frequency (MAF)≥5%. Frequent variants (i.e., MAF≥5%) annotated by RegulomeDB as likely affecting transcription factor binding were analyzed using mixed-effects models. Rare variants (i.e., MAF<5%) were analyzed using a variant set analysis. Results: The variant set analysis of rare variants was significant in explaining HDRS score changes (T = 878.9; p = 0.0033) and remission (T = -1974.1; p = 0.034). Rare variant counts were significant in explaining response (p = 0.016), remission (p = 0.022), and HDRS scores at M1 (p = 0.0021) and M3 (p=<0.001). rs553664 and rs536852 were significantly associated with the HDRS score (rs553664: p = 0.0055 | rs536852: p = 0.046) and remission (rs553664: p = 0.026 | rs536852: p = 0.012) through their interactions with time. At M6, significantly higher HDRS scores were observed in rs553664 AA homozygotes (13.98 ± 1.06) compared to AG heterozygotes (10.59 ± 0.86; p = 0.014) and in rs536852 GG homozygotes (14.88 ± 1.10) compared to AG heterozygotes (11.26 ± 0.95; p = 0.0061). Significantly lower remitter rates were observed in rs536852 GG homozygotes (8%, n = 56) compared to AG heterozygotes (42%, n = 105) at M6 (p = 0.0018). Conclusion: Our results suggest ARRB1 variants may influence the response to ATD treatment in depressed patients. Further analysis of functional ARRB1 variants and rare variant burden in other populations would help corroborate our exploratory analysis. β-arrestin 1 and genetic variants of ARRB1 may be useful clinical biomarkers for clinical improvement following ATD treatment in depressed individuals. Clinical Trial Registration: clinicaltrials.gov; identifier NCT00526383.

HTR1A Inhibits the Progression of Triple-Negative Breast Cancer via TGF-β Canonical and Noncanonical Pathways

Triple-negative breast cancer is the most aggressive subtype of breast cancer and the incidence of depression in breast cancer patients is high, which leading to worse survival and increased risk of recurrence. The effect of antidepressants on breast cancer patients remains contradictory, which might be due to variations in antidepression targets. Therefore, there is significant value to explore the antitumor potential of antidepressants and discover new therapeutic targets for breast patients. The authors screen antidepressant-related oncogenes or suppressors by using siRNAs. After combining functional experiments with online database analysis, 5-hydroxytryptamine receptor 1A (HTR1A is selected with antitumor potential in breast cancer cells in vivo and in vitro. RNA-seq analysis and coimmunoprecipitation assays indicate that HTR1A interacts with TRIM21 and PSMD7 to inhibit the degradation of TβRII through the ubiquitin-proteasome pathway, thereby inhibiting the transforming growth factor-β (TGF-β) canonical and noncanonical pathway. In addition, HTR1A is an independent predictive factor for breast cancer patients. The combined treatment of HTR1A agonists with demethylation drugs may significantly improve patient survival. It is of great significance to clarify the function and mechanism of the depression-related gene HTR1A in breast cancer, which might provide a new approach for triple-negative breast cancer patients.

Methylome-wide association study of antidepressant use in Generation Scotland and the Netherlands Twin Register implicates the innate immune system

Antidepressants are an effective treatment for major depressive disorder (MDD), although individual response is unpredictable and highly variable. Whilst the mode of action of antidepressants is incompletely understood, many medications are associated with changes in DNA methylation in genes that are plausibly linked to their mechanisms. Studies of DNA methylation may therefore reveal the biological processes underpinning the efficacy and side effects of antidepressants. We performed a methylome-wide association study (MWAS) of self-reported antidepressant use accounting for lifestyle factors and MDD in Generation Scotland (GS:SFHS, N = 6428, EPIC array) and the Netherlands Twin Register (NTR, N = 2449, 450 K array) and ran a meta-analysis of antidepressant use across these two cohorts. We found ten CpG sites significantly associated with self-reported antidepressant use in GS:SFHS, with the top CpG located within a gene previously associated with mental health disorders, ATP6V1B2 (β = -0.055, pcorrected = 0.005). Other top loci were annotated to genes including CASP10, TMBIM1, MAPKAPK3, and HEBP2, which have previously been implicated in the innate immune response. Next, using penalised regression, we trained a methylation-based score of self-reported antidepressant use in a subset of 3799 GS:SFHS individuals that predicted antidepressant use in a second subset of GS:SFHS (N = 3360, β = 0.377, p = 3.12 × 10-11, R2 = 2.12%). In an MWAS analysis of prescribed selective serotonin reuptake inhibitors, we showed convergent findings with those based on self-report. In NTR, we did not find any CpGs significantly associated with antidepressant use. The meta-analysis identified the two CpGs of the ten above that were common to the two arrays used as being significantly associated with antidepressant use, although the effect was in the opposite direction for one of them. Antidepressants were associated with epigenetic alterations in loci previously associated with mental health disorders and the innate immune system. These changes predicted self-reported antidepressant use in a subset of GS:SFHS and identified processes that may be relevant to our mechanistic understanding of clinically relevant antidepressant drug actions and side effects.

Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals

Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals.

Identification of putative genetic variants in major depressive disorder patients in Pakistan

BACKGROUND

Major depressive disorder (MDD) is a polygenic, and highly prevalent disorder affecting 322 million people globally. It results in several psychological changes which adversely affect different dimensions of life and may lead to suicide.

METHODS

Whole exome sequencing of 15 MDD patients, enrolled at the Dr. A. Q. Khan Institute of Behavioral Sciences, Karachi, was performed using NextSeq500. Different bioinformatics tools and databases like ANNOVAR, ALoFT, and GWAS were used to identify both common and rare variants associated with the pathogenesis of MDD.

RESULTS

A total of 1985 variations were identified in 479 MDD-related genes. Several SNPs including rs1079610, rs11750538, rs1799913, rs1801131, rs2230267, rs2231187, rs3819976, rs4314963, rs56265970, rs587780434, rs6330, rs75111588, rs7596487, and rs9624909 were prioritized due to their deleteriousness and frequency difference between the patients and the South Asian population. A non-synonymous variation rs56265970 (BCR) had 26% frequency in patients and was not found in the South Asian population; a multiallelic UTR-5' insertion rs587780434 (RELN) was present with an allelic frequency of 70% in patients whereas 22% in the SAS population. Genetic alterations in PABPC1 genes, a stress-associated gene also had higher allele frequency in the cases than in the normal population.

CONCLUSION

This present study identifies both common and rare variants in the genes associated with the pathogenesis of MDD in Pakistani patients. Genetic variations in BCR, RELN, and stress-associated PABPC1 suggest potential roles in the pathogenesis of MDD.

GABAA subunit single nucleotide polymorphisms show sex-specific association to alcohol consumption and mental distress in a Norwegian population-based sample

Little is known about genetic influences on the relationship between alcohol consumption and mental distress in the general population, where the majority report consumption and distress far below diagnostic thresholds. This study investigated single nucleotide polymorphisms (SNPs) from candidate gene studies on alcohol use disorder and depressive disorders, for association with alcohol consumption and with mental distress in a population-based sample from the Cohort of Norway (n = 1978, 49% women). The relationship between alcohol consumption and mental distress was further examined for genotype modification. There was a positive correlation between mental distress and alcohol consumption in men, as well as an association between SNPs and mental distress in men (GABRG1, GABRA2, DRD2, ANKK1, MTHFR) and women (CHRM2, MTHFR) and between SNPs and alcohol consumption in women (GABRA2, MTHFR). No modification by SNP genotype was found on the relationship between alcohol consumption and mental distress. The association between mental distress and GABRG1 in men remained significant after correcting for multiple comparisons. The results indicate that alcohol consumption and mental distress are associated in the general population even at levels below clinical thresholds and point to SNPs in genes related to GABAergic signalling for level of mental distress in men.

Corrigendum: Potential genetic overlap between insomnia and sleep symptoms in major depressive disorder: A polygenic risk score analysis

[This corrects the article DOI: 10.3389/fpsyt.2021.734077.].

OGDHL Variant rs2293239: A Potential Genetic Driver of Chinese Familial Depressive Disorder

Depressive disorders are a severe psychiatric and social problem that affect more than 4% of the global population. Depressive disorders have explicit hereditary characteristics; however, the precise driving genetic force behind these disorders has not yet been clearly illustrated. In the present study, we recruited a three-generation Chinese pedigree in which 5 of 17 members had long-term depression. We conducted whole-exome sequencing to identify the genetic mutation profiles of the family, and a list of susceptible genetic variations that were highly associated with depression onset was revealed via multiple omics analysis. In particular, a non-synonymous single nucleotide variation in the oxoglutarate dehydrogenase-like (OGDHL) gene, rs2293239 (p.Asn725Ser), was identified as one of the major driving genetic forces for depression onset in the family. This variant causes an important conformational change in the transketolase domain of OGDHL, thus reducing its binding affinity with the cofactor thiamine pyrophosphate and eventually resulting in the abnormal accumulation of glutamate in the brain. Brain imaging analysis further linked the rs2293239 variant with an enlarged amygdala and cerebellum in depressive family members. In summary, the present study enhances the current genetic understanding of depressive disorders. It also provides new options for prioritizing better clinical therapeutic regimens, as well as identifying a new protein target for the design of highly specific drugs to treat depressive disorders.

Prioritization of human well-being spectrum related GWAS-SNVs using ENCODE-based web-tools predict interplay between PSMC3, ITIH4, and SERPINC1 genes in modulating well-being

Several traits related to positive and negative affect show a high genetic as well as phenotypic correlation with well-being in humans, and are therefore collectively termed as "Well-being spectrum". Genome-Wide Association studies (GWA studies) on "well-being measurement" have led to identification of several genomic variants (Single Nucleotide Variants - SNVs), but very little has been explained with respect to their functionality and mode of alteration of well-being. Utilizing a pool of 1258 GWA studies based SNVs on "well-being measurement", we prioritized the SNVs and tried to annotate well-being related functionality through several bioinformatic tools to predict whether a protein sequence variation affects protein function, as well as experimentally validated datasets available in ENCODE based web-tools namely rSNPBase, RegulomeDB, Haploreg, along with GTEx Portal and STRING based protein interaction networks. Prioritization yielded three key SNVs; rs3781627-A, rs13072536-T and 5877-C potentially regulating three genes, PSMC3, ITIH4 and SERPINC1, respectively. Interestingly, the genes showed well clustered protein-protein interaction (maximum combined confidence score >0.4) with other well-being candidate genes, namely TNF and CRP genes suggesting their important role in modulation of well-being. PSMC3 and ITIH4 genes are also involved in driving acute phase responses signifying a probable cross-talk between well-being and psychoneuroimmunological system. To best of our knowledge this study is the first of its kind where the well-being associated GWA studies-SNVs were prioritized and functionally annotated, majorly based on functional data available in public domain, which revealed PSMC3, ITIH4 and SERPINC1 genes as probable candidates in regulation of well-being spectrum.

The genetic basis of major depression

Major depressive disorder (MDD) is a common, debilitating, phenotypically heterogeneous disorder with heritability ranges from 30% to 50%. Compared to other psychiatric disorders, its high prevalence, moderate heritability, and strong polygenicity have posed major challenges for gene-mapping in MDD. Studies of common genetic variation in MDD, driven by large international collaborations such as the Psychiatric Genomics Consortium, have confirmed the highly polygenic nature of the disorder and implicated over 100 genetic risk loci to date. Rare copy number variants associated with MDD risk were also recently identified. The goal of this review is to present a broad picture of our current understanding of the epidemiology, genetic epidemiology, molecular genetics, and gene-environment interplay in MDD. Insights into the impact of genetic factors on the aetiology of this complex disorder hold great promise for improving clinical care.

Lack of association of FKBP5 SNPs and haplotypes with susceptibility and treatment response phenotypes in Han Chinese with major depressive disorder: A pilot case-control study (STROBE)

The identification of single-nucleotide polymorphisms (SNPs) in genes putatively related to pathophysiological processes in major depressive disorder (MDD) might improve both diagnosis and personalized treatment strategies eventually leading to more effective interventions. Considering the important role of the glucocorticoid receptor and the related FK506 binding protein 51 (FKBP51) in the pathophysiology of MDD, we aimed to investigate putative associations between variants of FKBP5, the coding gene of FKBP51, with antidepressant treatment resistance and MDD susceptibility.Nine common SNPs of the FKBP5 gene prioritized based on location and, putative or known functions were genotyped in Han Chinese population, including MDD patients with or without antidepressant-treatment resistance and healthy controls. Associations of FKBP5 SNPs with MDD susceptibility and treatment response were examined in the whole group of MDD patients, as well as in subgroups stratified by antidepressant treatment resistance, compared with healthy controls.In total, 181 Han Chinese patients with MDD and 80 healthy controls were recruited. No significant SNP or haplotype associations were observed in the whole patient group. There were nominal significant differences both for the haplotype block with SNPs in strong LD (r2 > 0.8, P = .040) and haplotype block with SNPs in moderate LD (r2 > 0.1, P = .017) between the haplotype distributions of patients with antidepressant treatment resistance (n = 81) and healthy controls, but both significances did not survive multiple testing correction. Furthermore, no specific haplotype could be observed causing a significant difference in any combination between all comparisons.No associations were observed of FKBP5 variants with MDD or antidepressant treatment response. The lack of associations might be due to the relatively small sample size of this study (power ranged from 0.100 to 0.752). A follow-up study will need larger, better phenotyped, and more homogeneous samples to draw a definitive conclusion regarding the involvement of this gene in MDD.

Maternal smoking during pregnancy and risks to depression and anxiety in offspring: An observational study and genome-wide gene-environment interaction analysis in UK biobank cohort

BACKGROUND

Maternal smoking during pregnancy (MSDP) has been reported to be associated with increased anxiety and depression behaviors in offspring. However, there is still scant evidence to support the link between MSDP and anxiety/depression.

METHODS

Using the subjects from the UK Biobank cohort (n = 371,903-432,881). Logistic regression analyses were first conducted to test the correlation between MSDP and anxiety/depression in offspring. Second, genome-wide gene-environment interaction study (GWGEIS) analyses were conducted by PLINK, using MSDP as environmental factor. Genetic correlation analysis of anxiety/depression and smoking was conducted by the LDSC software using the published genome-wide association study (GWAS) summary data of four smoking traits (n = 337,334-1,232,091), anxiety (n = 31,880) and depression (n = 490,359). Finally, pathway enrichment analysis was carried out to detect the pathway involved in the development of offspring anxiety caused by the interaction of MSDP × SNPs.

RESULTS

Observational analyses showed that anxiety and depression status in offspring were significantly associated with MSDP (all p < 0.0001). Further GWEGI analyses observed significant MSDP-gene interaction effects at UNC80 gene for anxiety (p = 9.09 × 10^-9). LDSC did not detect significant genetic correlation between anxiety and smoking traits. Pathway analysis identified 19 significant pathways for anxiety, such as MANALO_HYPOXIA_UP (FDR = 5.50 × 10^-4), REACTOME_ADHERENS_JUNCTIONS_INTERACTIONS (FDR = 0.0304) and ONDER_CDH1_TARGETS_2_UP (FDR = 0.0371).

CONCLUSION

Our study results suggested the important impact of MDSP on the risk of anxiety in offspring, partly attributing to environment-gene interactions effects.

The role of rs242941, rs1876828, rs242939 and rs110402 polymorphisms of CRHR1 gene and the depression: systematic review and meta-analysis

BACKGROUND

Several studies have evaluated the possible association between polymorphisms or variants in Corticotropin-releasing hormone 1 receptor gene (CRHR1) with depression; however, results remain contradictory and heterogeneous.

OBJECTIVE

To our knowledge, we conducted the first comprehensive systematic review and meta-analysis evaluating the association of the CRHR1 gene and the risk of depression.

METHODS

A search online was conducted in databases for any CRHR1 genetic association studies in depression. Data were extracted for evaluation of pooled estimates using meta-analytic techniques. Statistical analyses were performed using the Comprehensive Meta-analysis, v2.0 software.

RESULT

A total of 1403 cases and 2353 mentally healthy controls were included in this study. We found a significant association of rs242941, rs1876828 and rs242939 variants of the CRHR1 gene with depression. No association of CRHR1 rs110402 and depression was observed.

CONCLUSION

Our meta-analysis shows that some variants of the CRHR1 gene (rs242941, rs1876828 and rs242939) might confer susceptibility to depression. Further studies with larger sample sizes need to be conducted.

Genetic markers for depressive disorders with earlier age at onset

Age at onset has been considered a potential indicator of underlying genetic risk in depression research. However, the variants associated with earlier age at onset of depressive disorder have not been elucidated. To evaluate the genetic architecture of depression onset, whole-exome sequencing of samples from 1000 patients with depressive disorder was performed. Cox proportional hazard models with false discovery rate-adjusted P-values were used to estimate the hazard ratios; carriers and non-carriers of individual coding variants were compared in terms of age at onset of depression with adjustment for sociodemographic and clinical characteristics. The clinical relevance of the candidate variants was also examined. Whole-exome sequencing revealed four variants in the CCL14, FYB, GPRASP1, and CTNND2 genes associated with an increased risk of depressive disorder with earlier age at onset. Although no individual variant was associated with any clinical characteristic except AAO, together they were associated with younger AAO, younger age at visit for treatment, and recurrent and atypical depression. Our data suggest novel candidate genes for depressive disorder with earlier age at onset. These genes could serve as markers allowing early identification of patients at risk of depression, and thus earlier intervention.

Transcription Factor Motifs Associated with Anterior Insula Gene Expression Underlying Mood Disorder Phenotypes

Mood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined. Because the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from the anterior insula postmortem anterior insula of mood disorder samples and compared with unaffected controls for RNA-sequencing identification of differentially expressed genes (DEGs) in (a) bipolar disorder (BD; n = 37) versus (vs.) controls (n = 33), and (b) major depressive disorder (MDD n = 30) vs. controls, and (c) low vs. high axis I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs. We found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low axis I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ, and brain development. Robust imaging-guided transcriptomics by using meta-analytic imaging results to guide independent postmortem dissection for RNA-sequencing was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. Our findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provide novel information about the hierarchical relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders.

Inclusion of genetic variants in an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response

Identifying in advance who is unlikely to respond to a specific antidepressant treatment is crucial to precision medicine efforts. The current work leverages genome-wide genetic variation and machine learning to predict response to the antidepressant citalopram using data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial (n = 1257 with both valid genomic and outcome data). A confirmatory approach selected 11 SNPs previously reported to predict response to escitalopram in a sample different from the current study. A novel exploratory approach selected SNPs from across the genome using nested cross-validation with elastic net logistic regression with a predominantly lasso penalty (alpha = 0.99). SNPs from each approach were combined with baseline clinical predictors and treatment response outcomes were predicted using a stacked ensemble of gradient boosting decision trees. Using pre-treatment clinical and symptom predictors only, out-of-fold prediction of a novel treatment response definition based on STAR*D treatment guidelines was acceptable, AUC = .659, 95% CI [0.629, 0.689]. The inclusion of SNPs using confirmatory or exploratory selection methods did not improve the out-of-fold prediction of treatment response (AUCs were .662, 95% CI [0.632, 0.692] and .655, 95% CI [0.625, 0.685], respectively). A similar pattern of results were observed for the secondary outcomes of the presence or absence of distressing side effects regardless of treatment response and achieving remission or satisfactory partial response, assuming medication tolerance. In the current study, incorporating SNP variation into prognostic models did not enhance the prediction of citalopram response in the STAR*D sample.

Potential Genetic Overlap Between Insomnia and Sleep Symptoms in Major Depressive Disorder: A Polygenic Risk Score Analysis

Background: The prevalence of insomnia and hypersomnia in depressed individuals is substantially higher than that found in the general population. Unfortunately, these concurrent sleep problems can have profound effects on the disease course. Although the full biology of sleep remains to be elucidated, a recent genome-wide association (GWAS) of insomnia, and other sleep traits in over 1 million individuals was recently published and provides many promising hits for genetics of insomnia in a population-based sample. Methods: Using data from the largest available GWAS of insomnia and other sleep traits, we sought to test if sleep variable PRS scores derived from population-based studies predicted sleep variables in samples of depressed cases [Psychiatric Genomics Consortium - Major Depressive Disorder subjects (PGC MDD)]. A leave-one-out analysis was performed to determine the effects that each individual study had on our results. Results: The only significant finding was for insomnia, where p-value threshold, p = 0.05 was associated with insomnia in our PGC MDD sample (R ² = 1.75^-3, p = 0.006). Conclusion: Our results reveal that <1% of variance is explained by the variants that cover the two significant p-value thresholds, which is in line with the fact that depression and insomnia are both polygenic disorders. To the best of our knowledge, this is the first study to investigate genetic overlap between the general population and a depression sample for insomnia, which has important treatment implications, such as leading to novel drug targets in future research efforts.

An endocannabinoid-regulated basolateral amygdala-nucleus accumbens circuit modulates sociability

Deficits in social interaction (SI) are a core symptom of autism spectrum disorders (ASDs); however, treatments for social deficits are notably lacking. Elucidating brain circuits and neuromodulatory signaling systems that regulate sociability could facilitate a deeper understanding of ASD pathophysiology and reveal novel treatments for ASDs. Here we found that in vivo optogenetic activation of the basolateral amygdala-nucleus accumbens (BLA-NAc) glutamatergic circuit reduced SI and increased social avoidance in mice. Furthermore, we found that 2-arachidonoylglycerol (2-AG) endocannabinoid signaling reduced BLA-NAc glutamatergic activity and that pharmacological 2-AG augmentation via administration of JZL184, a monoacylglycerol lipase inhibitor, blocked SI deficits associated with in vivo BLA-NAc stimulation. Additionally, optogenetic inhibition of the BLA-NAc circuit markedly increased SI in the Shank3B-/- mouse, an ASD model with substantial SI impairment, without affecting SI in WT mice. Finally, we demonstrated that JZL184 delivered systemically or directly to the NAc also normalized SI deficits in Shank3B-/- mice, while ex vivo JZL184 application corrected aberrant NAc excitatory and inhibitory neurotransmission and reduced BLA-NAc-elicited feed-forward inhibition of NAc neurons in Shank3B-/- mice. These data reveal circuit-level and neuromodulatory mechanisms regulating social function relevant to ASDs and suggest 2-AG augmentation could reduce social deficits via modulation of excitatory and inhibitory neurotransmission in the NAc.

Neuroligin-2 as a central organizer of inhibitory synapses in health and disease

Postsynaptic organizational protein complexes play central roles both in orchestrating synapse formation and in defining the functional properties of synaptic transmission that together shape the flow of information through neuronal networks. A key component of these organizational protein complexes is the family of synaptic adhesion proteins called neuroligins. Neuroligins form transsynaptic bridges with presynaptic neurexins to regulate various aspects of excitatory and inhibitory synaptic transmission. Neuroligin-2 (NLGN2) is the only member that acts exclusively at GABAergic inhibitory synapses. Altered expression and mutations in NLGN2 and several of its interacting partners are linked to cognitive and psychiatric disorders, including schizophrenia, autism, and anxiety. Research on NLGN2 has fundamentally shaped our understanding of the molecular architecture of inhibitory synapses. Here, we discuss the current knowledge on the molecular and cellular functions of mammalian NLGN2 and its role in the neuronal circuitry that regulates behavior in rodents and humans.

Discovery of VU6027459: A First-in-Class Selective and CNS Penetrant mGlu7 Positive Allosteric Modulator Tool Compound

Herein, we report the discovery of the first selective and CNS penetrant mGlu₇ PAM (VU6027459) derived from a "molecular switch" within a selective mGlu₇ NAM chemotype. VU6027459 displayed CNS penetration in both mice (K_p = 2.74) and rats (K_p= 4.78), it was orally bioavailable in rats (%F = 69.5), and undesired activity at DAT was ablated.

Prickle2 and Igsf9b Coordinately Regulate the Cytoarchitecture of the Axon Initial Segment

Prickle2 has been identified in genetic studies of subjects with autism spectrum disorder (ASD) and epilepsy, but the pathological mechanism of Prickle2 remains to be fully understood. Proteomic analysis of Prickle2 with mass spectrometry revealed twenty-eight Prickle2 interactors, including immunoglobulin superfamily member 9b (Igsf9b), in the brain. Here, because Igsf9 family proteins are associated with psychiatric diseases and seizures, we studied the physiological interaction between Prickle2 and Igsf9b. Prickle2 colocalized with Igsf9b in cultured hippocampal neurons. Knockdown of Prickle2 affected the subcellular localization of Igsf9b. Interestingly, Igsf9b localized along axonal processes in a pattern opposite to the ASD-related molecule ANK3/AnkG. AnkG is a major component of the axon initial segment (AIS), where a variety of ASD and epilepsy susceptibility proteins accumulate. Igsf9b-knockdown neurons displayed altered AnkG localization. Prickle2 depletion caused defects in AnkG and voltage-gated Na+ channel localization, resulting in altered network activity. These results support the idea that Prickle2 regulates AnkG distribution by controlling the proper localization of Igsf9b. The novel function of Prickle2 in AIS cytoarchitecture provides new insights into the shared pathology of ASD and epilepsy.Key words: Prickle2, Igsf9b, axon initial segment, neuronal excitability, ASD.

Polygenic modelling of treatment effect heterogeneity

Mendelian randomization is the use of genetic variants to assess the effect of intervening on a risk factor using observational data. We consider the scenario in which there is a pharmacomimetic (i.e., treatment-mimicking) genetic variant that can be used as a proxy for a particular pharmacological treatment that changes the level of the risk factor. If the association of the pharmacomimetic genetic variant with the risk factor is stronger in one subgroup of the population, then we may expect the effect of the treatment to be stronger in that subgroup. We test for gene-gene interactions in the associations of variants with a modifiable risk factor, where one genetic variant is treated as pharmacomimetic and the other as an effect modifier, to find genetic subgroups of the population with different predicted response to treatment. If individual genetic variants that are strong effect modifiers cannot be found, moderating variants can be combined using a random forest of interaction trees method into a polygenic response score, analogous to a polygenic risk score for risk prediction. We illustrate the application of the method to investigate effect heterogeneity in the effect of statins on low-density lipoprotein cholesterol.

Molecular linkage between post-traumatic stress disorder and cognitive impairment: a targeted proteomics study of World Trade Center responders

Existing work on proteomics has found common biomarkers that are altered in individuals with post-traumatic stress disorder (PTSD) and mild cognitive impairment (MCI). The current study expands our understanding of these biomarkers by profiling 276 plasma proteins with known involvement in neurobiological processes using the Olink Proseek Multiplex Platform in individuals with both PTSD and MCI compared to either disorder alone and with unaffected controls. Participants were World Trade Center (WTC) responders recruited through the Stony Brook WTC Health Program. PTSD and MCI were measured with the PTSD Checklist (PCL) and the Montreal Cognitive Assessment, respectively. Compared with unaffected controls, we identified 16 proteins associated with comorbid PTSD-MCI at P < 0.05 (six at FDR < 0.1), 20 proteins associated with PTSD only (two at FDR < 0.1), and 24 proteins associated with MCI only (one at FDR < 0.1), for a total of 50 proteins. The multiprotein composite score achieved AUCs of 0.84, 0.77, and 0.83 for PTSD-MCI, PTSD only, and MCI only versus unaffected controls, respectively. To our knowledge, the current study is the largest to profile a large set of proteins involved in neurobiological processes. The significant associations across the three case-group analyses suggest that shared biological mechanisms may be involved in the two disorders. If findings from the multiprotein composite score are replicated in independent samples, it has the potential to add a new tool to help classify both PTSD and MCI.

Sex differences in the genetic architecture of depression

The prevalence and clinical characteristics of depressive disorders differ between women and men; however, the genetic contribution to sex differences in depressive disorders has not been elucidated. To evaluate sex-specific differences in the genetic architecture of depression, whole exome sequencing of samples from 1000 patients (70.7% female) with depressive disorder was conducted. Control data from healthy individuals with no psychiatric disorder (n = 72, 26.4% female) and East-Asian subpopulation 1000 Genome Project data (n = 207, 50.7% female) were included. The genetic variation between men and women was directly compared using both qualitative and quantitative research designs. Qualitative analysis identified five genetic markers potentially associated with increased risk of depressive disorder in females, including three variants (rs201432982 within PDE4A, and rs62640397 and rs79442975 within FDX1L) mapping to chromosome 19p13.2 and two novel variants (rs820182 and rs820148) within MYO15B at the chromosome 17p25.1 locus. Depressed patients homozygous for these variants showed more severe depressive symptoms and higher suicidality than those who were not homozygotes (i.e., heterozygotes and homozygotes for the non-associated allele). Quantitative analysis demonstrated that the genetic burden of protein-truncating and deleterious variants was higher in males than females, even after permutation testing. Our study provides novel genetic evidence that the higher prevalence of depressive disorders in women may be attributable to inherited variants.

Significance of Single-Nucleotide Variants in Long Intergenic Non-protein Coding RNAs

Single-nucleotide variants (SNVs) are the most common genetic variants and universally present in the human genome. Genome-wide association studies (GWASs) have identified a great number of disease or trait-associated variants, many of which are located in non-coding regions. Long intergenic non-protein coding RNAs (lincRNAs) are the major subtype of long non-coding RNAs; lincRNAs play crucial roles in various disorders and cellular models via multiple mechanisms. With rapid growth in the number of the identified lincRNAs and genetic variants, there is great demand for an investigation of SNVs in lincRNAs. Hence, in this article, we mainly summarize the significant role of SNVs within human lincRNA regions. Some pivotal variants may serve as risk factors for the development of various disorders, especially cancer. They may also act as important regulatory signatures involved in the modulation of lincRNAs in a tissue- or disorder-specific manner. An increasing number of researches indicate that lincRNA variants would potentially provide additional options for genetic testing and disease risk assessment in the personalized medicine era.

A logical relationship for schizophrenia, bipolar, and major depressive disorder. Part 1: Evidence from chromosome 1 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was investigated systematically (Aukes et al., Genetics in Medicine, 2012, 14, 338-341) and any two or even three of these disorders could coexist in some families. Furthermore, evidence from symptomatology and psychopharmacology also imply the existence of intrinsic connections between these three major psychiatric disorders. A total of 71,445 SNPs on chromosome 1 were genotyped on 119 SCZ, 253 BPD (type-I), 177 MDD cases and 1000 controls and further validated in 986 SCZ patients in the population of Shandong province of China. Outstanding psychosis genes are systematically revealed( ATP1A4, ELTD1, FAM5C, HHAT, KIF26B, LMX1A, NEGR1, NFIA, NR5A2, NTNG1, PAPPA2, PDE4B, PEX14, RYR2, SYT6, TGFBR3, TTLL7, and USH2A). Unexpectedly, flanking genes for up to 97.09% of the associated SNPs were also replicated in an enlarged cohort of 986 SCZ patients. From the perspective of etiological rather than clinical psychiatry, bipolar, and major depressive disorder could be subtypes of schizophrenia. Meanwhile, the varied clinical feature and prognosis might be the result of interaction of genetics and epigenetics, for example, irreversible or reversible shut down, and over or insufficient expression of certain genes, which may gives other aspects of these severe mental disorders.

Genetics of resilience: Implications from genome-wide association studies and candidate genes of the stress response system in posttraumatic stress disorder and depression

Resilience is the ability to cope with critical situations through the use of personal and socially mediated resources. Since a lack of resilience increases the risk of developing stress-related psychiatric disorders such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD), a better understanding of the biological background is of great value to provide better prevention and treatment options. Resilience is undeniably influenced by genetic factors, but very little is known about the exact underlying mechanisms. A recently published genome-wide association study (GWAS) on resilience has identified three new susceptibility loci, DCLK2, KLHL36, and SLC15A5. Further interesting results can be found in association analyses of gene variants of the stress response system, which is closely related to resilience, and PTSD and MDD. Several promising genes, such as the COMT (catechol-O-methyltransferase) gene, the serotonin transporter gene (SLC6A4), and neuropeptide Y (NPY) suggest gene × environment interaction between genetic variants, childhood adversity, and the occurrence of PTSD and MDD, indicating an impact of these genes on resilience. GWAS on PTSD and MDD provide another approach to identifying new disease-associated loci and, although the functional significance for disease development for most of these risk genes is still unknown, they are potential candidates due to the overlap of stress-related psychiatric disorders and resilience. In the future, it will be important for genetic studies to focus more on resilience than on pathological phenotypes, to develop reasonable concepts for measuring resilience, and to establish international cooperations to generate sufficiently large samples.

Novel association between TGFA, TGFB1, IRF1, PTGS2 and IKBKB single-nucleotide polymorphisms and occurrence, severity and treatment response of major depressive disorder

Background

Activation of the immune system might affect the severity of depressive episodes as well as response to the antidepressant treatment. The purpose of this study was to investigate whether the occurrence of variant alleles of analyzed SNPs are involved in prevalence and progression of depression. Moreover, selected genes and SNPs have not been investigated in context of the disease severity and treatment. Therefore, six polymorphisms were selected: g.41354391A>G-TGFB1 (rs1800469), g.132484229C>A-IRF (rs2070729), g.186643058A>G-PTGS2 (rs5275), g.186640617C>T-PTGS2 (rs4648308), g.70677994G>A-TGFA (rs2166975) and g.42140549G>T-IKBKB (rs5029748).

Methods

A total of 360 (180 patients and 180 controls) DNA samples were genotyped using TaqMan probes.

Results

We observed that A/G of the rs2166975 TGFA, A/C of rs2070729 IRF1 and G/T of rs5029748 IKBKB were associated with an increased risk of depression development while the T/T of rs5029748 IKBKB, T/T of rs4648308 PTGS2 and G/G of rs2166975 TGFA reduced this risk. We also stratified the study group according to gender and found that genotype A/G and allele G of the rs2166975 TGFA, G/T of rs5029748 IKBKB as well as C allele of rs4648308 PTGS2, homozygote A/A and allele A of rs5275 PTGS2 were associated with increased risk of depression development in men while homozygote G/G of rs5275 PTGS2 decreased this risk. Moreover, C/T of rs4648308 PTGS2 and A/G of rs5275 PTGS2 was positively correlated with the risk of the disease occurrence in women. Furthermore, a gene-gene analysis revealed a link between studied polymorphisms and depression. In addition, A/A of rs1800469 TGFB1 was associated with earlier age of onset of the disease while G/G of this SNP increased severity of the depressive episode. Interestingly, A/C of rs2070729 IRF1 and T/T of rs5029748 IKBKB may modulate the effectiveness of selective serotonin reuptake inhibitors therapy. In conclusion, studied SNPs may modulate the risk of occurrence, age of onset, severity of the disease and response to the antidepressant treatment.

Genetic variants associated with psychotic symptoms across psychiatric disorders

BACKGROUND

Recent evidence suggests that psychiatric symptoms share a common genetic liability across diagnostic categories. The present study investigated the effects of variants within previously identified relevant genes on specific symptom clusters, independently from the diagnosis.

METHODS

1550 subjects affected by Schizophrenia (SCZ), Major Depressive Disorder or Bipolar Disorder were included. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale (HDRS). Principal component analysis and a further clinical refinement were used to define symptom clusters. Clusters scores were tested for association with 46 genetic variants within nine genes previously linked to one or more major psychiatric disorders by large genome wide association studies (ANK3, CACNA1C, CACNB2, FKBP5, FZD3, GRM7, ITIH3, SYNE1, TCF4). Exploratory analyses were performed in each disorder separately to further elucidate the SNPs effects.

RESULTS

five PANSS clusters (Negative; Impulsiveness; Cognitive; Psychotic; Depressive) and four HDRS clusters (Core Depressive; Somatic; Psychotic-like; Insomnia) were identified. CACNA1C rs11615998 was associated with HDRS Psychotic cluster in the whole sample. In the SCZ sample, CACNA1C rs11062296 was associated with PANSS Impulsiveness cluster and CACNA1C rs2238062 was associated with PANSS negative cluster.

DISCUSSION

CACNA1C rs11615998 was associated with psychotic symptoms (C-allele carriers have decreased psychotic-risk) independently from the diagnosis, in line with the evidence of a cross disorder effect of many risk variants. This gene was previously associated with SCZ and cross-disorder liability to psychiatric disorders. Our findings confirmed that deep phenotyping is pivotal to clarify the role of genetic variants on symptoms patterns.

Novel susceptibility genes were found in a targeted sequencing of stroke patients with or without depression in the Chinese Han population

BACKGROUND

Both stroke and depression are multi-factorial diseases, with both genetic and environmental factors likely to participate in their pathogenesis. Post stroke depression (PSD) is a common complication after stroke leading to poor functional outcome, increased physical disability and mortality. Although several genes have been associated with PSD, the genetic basis of PSD remains poorly understood.

METHOD

A 2-stage candidate gene study by targeted sequencing was conducted involving stroke patients with or without depression and health controls. In the discovery stage (121 PSD, 131 non-PSD and 639 HC), logistic regression was used to test associations respectively in PSD and non-PSD groups. In the replication stage (200 PSD, 218 non-PSD and 983 HC), 54 selected SNPs were again genotyped in an independent cohort. Fixed-effects inverse variance-weighted meta-analysis was used in the combined samples.

RESULTS

The study identified 2 novel genes associated with PSD [HTR3D (rs55674402, p = 0.002512, odds ratio (OR) = 0.7431); NEUROG3 (rs144643855, p = 0.00325, OR = 0.6523)] and 3 risk SNPs in one risk gene associated with non-PSD [PIK3C2B (rs17406271, p = 0.0006801, OR = 1.446; rs2271419, p = 0.0005836, OR = 1.497; rs2271420, p = 0.001031, OR = 1.431)] in the Chinese sample. NEUROG3 shows highest expression level in hippocampus. Functional enrichment analysis shows that susceptibility genes for PSD are mostly enriched in chemical synaptic transmission and regulation of lipid synthetic process.

LIMITATIONS

The sample size was not sufficient to reach a genome-wide p value level. To overcome this shortage, some unique strategies were applied during the selection of SNPs for replication. Secondly, the age, gender composition and depressive severity between two stages were not well-matched. Different sample sources should be blamed, and to minimizing the influence, gender was corrected as co-variant in logistic regression.

CONCLUSION

This study identified that HTR3D and NEUROG3 were linked with the susceptibility of PSD and PIK3C2B with stroke in the Chinese Han population. Further replication of these findings in a larger and better matched sample is warranted. Functional analysis suggests that the pathogenesis of PSD may be implicated in 5-HT synaptic transmission, neural plasticity and lipid metabolism, and therapeutic interventions targeting these pathways may be effective approaches for PSD treatment.

Differential effects on neurodevelopment of FTO variants in obesity and bipolar disorder suggested by in silico prediction of functional impact: An analysis in Mexican population

INTRODUCTION

Several studies indicate that polygenic obesity is linked to fat-mass and obesity-associated (FTO) genetic variants. Nevertheless, the link between variants in FTO and mental disorders has been barely explored. The present work aims to determine whether FTO genetic variants are associated with bipolar disorder and obesity, and to perform an in silico prediction of variant-dependent functional impact on the developing brain transcriptome.

METHODS

Four hundred and forty-six Mexican mestizos were included in a genetic association analysis. SNP-sequence kernel association test and linear mixed models were implemented for genetic association assessment. For functional impact prediction, we analyzed the mapping of regulatory elements, the modification of binding sites of transcription factors and the expression of transcription factors in the brain developing transcriptome, searching on different databases.

RESULTS

In the set-based analysis, we found different associated regions to BD (bipolar disorder) and obesity. The promoter flanking region of FTO intron 1 was associated with differential effects on BMI, while intron 2 of RPGRIP1L and FTO upstream regions were associated with BD. The prediction analysis showed that FTO BD-associated variants disturb binding sites of SP1 and SP2; obesity-associated variants, on the other hand, disturb binding sites of FOXP1, which are transcription factors highly expressed during prenatal development stages of the brain.

CONCLUSION

Our results suggest a possible effect of FTO variants on neurodevelopment in obesity and bipolar disorder, which gives new insights into the molecular mechanism underlying this association.

GRIK4 and GRM7 gene may be potential indicator of venlafaxine treatment reponses in Chinese of Han ethnicity

Venlafaxine is one of commonly prescribed antidepressants for major depressive disorder (MDD). Accumulated evidence implicates the involvement of glutamatergic receptors in the pathophysiology of MDD and antidepressant treatment.By using 193 MDD patients who have been taking venlafaxine for 6 weeks, we investigated whether single nucleotide polymorphisms (SNPs) in glutamate ionotropic receptor kainate type subunit 4 (GRIK4), glutamate ionotropic receptor AMPA type subunit 1 (GRIA1) and glutamate metabotropic receptor 7 (GRM7) were associated with treatment response. 14 SNPs were selected randomly depended on association studies. Efficacy of treatment was determined by 17-item of Hamilton Rating Scale. Allele and genotype frequencies were compared between responders and non-responders.After adjusting by the false discovery rate (FDR), rs6589847 and rs56275759 in GRIK4 and rs9870680 in GRM7 showed associating with venlafaxine treatment response at week 6. (FDR: P = .018, P = .042, and P = .040, respectively).Our results indicated that genetic variants in the GRIK4 and GRM7 may associate with the treatment response in MDD patients treated by venlafaxine.

Systems Approach to Identify Common Genes and Pathways Associated with Response to Selective Serotonin Reuptake Inhibitors and Major Depression Risk

Despite numerous studies on major depressive disorder (MDD) susceptibility, the precise underlying molecular mechanism has not been elucidated which restricts the development of etiology-based disease-modifying drug. Major depressive disorder treatment is still symptomatic and is the leading cause of (~30%) failure of the current antidepressant therapy. Here we comprehended the probable genes and pathways commonly associated with antidepressant response and MDD. A systematic review was conducted, and candidate genes/pathways associated with antidepressant response and MDD were identified using an integrative genetics approach. Initially, single nucleotide polymorphisms (SNPs)/genes found to be significantly associated with antidepressant response were systematically reviewed and retrieved from the candidate studies and genome-wide association studies (GWAS). Also, significant variations concerning MDD susceptibility were extracted from GWAS only. We found 245 (Set A) and 800 (Set B) significantly associated genes with antidepressant response and MDD, respectively. Further, gene set enrichment analysis revealed the top five co-occurring molecular pathways (p ≤ 0.05) among the two sets of genes: Cushing syndrome, Axon guidance, cAMP signaling pathway, Insulin secretion, and Glutamatergic synapse, wherein all show a very close relation to synaptic plasticity. Integrative analyses of candidate gene and genome-wide association studies would enable us to investigate the putative targets for the development of disease etiology-based antidepressant that might be more promising than current ones.

Network Analysis of Depression-Related Transcriptomic Profiles

Major depressive disorder is a common debilitating disorder that is associated with increased morbidity and mortality. However, the molecular mechanism underlying depression remains largely unknown. The current study investigated the association of depression with blood gene expression using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Depression was measured by the geriatric depression scale, and the blood gene expression was measured by the Affymetrix Human Genome U219 Array. Linear regression was used to test the association between gene expression and depression, and the model was adjusted for age and sex. A total of 671 participants were included in our study (mean age 75 ± 8 years, 43.2% women). We found three genes were associated with depression, including COL1A2 (P = 8.9 × 10^-8), RNF150 (P = 1.4 × 10^-7) and CTGF (P = 8.3 × 10^-7). An interaction network was built, and the pathway analysis indicated that many depression-related genes were involved in the neurotrophin signaling pathway (P = 2.1 × 10^-7). Future studies are necessary to validate our findings and further investigate potential mechanism of depression.

Telomeres in neurological disorders

Ever since their discovery, the telomeres and the telomerase have been topics of intensive research, first as a mechanism of cellular aging and later as an indicator of health and diseases in humans. By protecting the chromosome ends, the telomeres play a vital role in preserving the information in our genome. Telomeres shorten with age and the rate of telomere erosion provides insight into the proliferation history of cells. The pace of telomere attrition is known to increase at the onset of several pathological conditions. Telomere shortening has been emerging as a potential contributor in the pathogenesis of several neurological disorders including autism spectrum disorders (ASD), schizophrenia, Alzheimer's disease (AD), Parkinson's disease (PD) and depression. The rate of telomere attrition in the brain is slower than that of other tissues owing to the low rate of cell proliferation in brain. Telomere maintenance is crucial for the functioning of stem cells in brain. Taking together the studies on telomere attrition in various neurological disorders, an association between telomere shortening and disease status has been demonstrated in schizophrenia, AD and depression, in spite of a few negative reports. But, studies in ASD and PD have failed to produce conclusive results. The cause-effect relationship between TL and neurological disorders is yet to be elucidated. The factors responsible for telomere erosion, which have also been implicated in the pathogenesis of neurological disorders, need to be explored in detail. Telomerase activation is now being considered as a potential therapeutic strategy for neurological disorders.

GWAS of Behavioral Traits

Over the past decade, genome-wide association studies (GWAS) have evolved into a powerful tool to investigate genetic risk factors for human diseases via a hypothesis-free scan of the genome. The success of GWAS for psychiatric disorders and behavioral traits have been somewhat mixed, partly owing to the complexity and heterogeneity of these traits. Significant progress has been made in the last few years in the development and implementation of complex statistical methods and algorithms incorporating GWAS. Such advanced statistical methods applied to GWAS hits in combination with incorporation of different layers of genomics data have catapulted the search for novel genes for behavioral traits and improved our understanding of the complex polygenic architecture of these traits.This chapter will give a brief overview on GWAS and statistical methods currently used in GWAS. The chapter will focus on reviewing the current literature and highlight some of the most important GWAS on psychiatric and other behavioral traits and will conclude with a discussion on future directions.

IgSF9b regulates anxiety behaviors through effects on centromedial amygdala inhibitory synapses

Abnormalities in synaptic inhibition play a critical role in psychiatric disorders, and accordingly, it is essential to understand the molecular mechanisms linking components of the inhibitory postsynapse to psychiatrically relevant neural circuits and behaviors. Here we study the role of IgSF9b, an adhesion protein that has been associated with affective disorders, in the amygdala anxiety circuitry. We show that deletion of IgSF9b normalizes anxiety-related behaviors and neural processing in mice lacking the synapse organizer Neuroligin-2 (Nlgn2), which was proposed to complex with IgSF9b. This normalization occurs through differential effects of Nlgn2 and IgSF9b at inhibitory synapses in the basal and centromedial amygdala (CeM), respectively. Moreover, deletion of IgSF9b in the CeM of adult Nlgn2 knockout mice has a prominent anxiolytic effect. Our data place IgSF9b as a key regulator of inhibition in the amygdala and indicate that IgSF9b-expressing synapses in the CeM may represent a target for anxiolytic therapies.

IgSF9b is a synaptic adhesion protein that has been linked to psychiatric disorders. Here the authors show that deletion of IgSF9b regulates anxiety-like behaviour in mice by increasing inhibitory synaptic transmission in the centromedial amygdala.

WITHDRAWN: Single nucleotide polymorphism, a putative driver for the role of long intergeneric non-coding RNA

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Immunoglobulin-Like Receptors and Their Impact on Wiring of Brain Synapses

Synapse formation is mediated by a surprisingly large number and wide variety of genes encoding many different protein classes. One of the families increasingly implicated in synapse wiring is the immunoglobulin superfamily (IgSF). IgSF molecules are by definition any protein containing at least one Ig-like domain, making this family one of the most common protein classes encoded by the genome. Here, we review the emerging roles for IgSF molecules in synapse formation specifically in the vertebrate brain, focusing on examples from three classes of IgSF members: ( a) cell adhesion molecules, ( b) signaling molecules, and ( c) immune molecules expressed in the brain. The critical roles for IgSF members in regulating synapse formation may explain their extensive involvement in neuropsychiatric and neurodevelopmental disorders. Solving the IgSF code for synapse formation may reveal multiple new targets for rescuing IgSF-mediated deficits in synapse formation and, eventually, new treatments for psychiatric disorders caused by altered IgSF-induced synapse wiring.

Genes associated with anhedonia: a new analysis in a large clinical trial (GENDEP)

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10-9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10-5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson's Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies.