The current state of play on the molecular genetics of depression

2012 ◽  
Vol 43 (4) ◽  
pp. 673-687 ◽  
Author(s):  
S. Cohen-Woods ◽  
I. W. Craig ◽  
P. McGuffin
Keyword(s):  
Major Depressive Disorder ◽  
High Risk ◽  
Depressive Disorder ◽  
Association Studies ◽  
Genetic Research ◽  
Small Samples ◽  
Shared Environment ◽  
Genome Wide Association Studies ◽  
Major Depressive ◽  
Comprehensive Overview

BackgroundIt has been well established that both genes and non-shared environment contribute substantially to the underlying aetiology of major depressive disorder (MDD). A comprehensive overview of genetic research in MDD is presented.MethodPapers were retrieved from PubMed up to December 2011, using many keywords including: depression, major depressive disorder, genetics, rare variants, gene–environment, whole genome, epigenetics, and specific candidate genes and variants. These were combined in a variety of permutations.ResultsLinkage studies have yielded some promising chromosomal regions in MDD. However, there is a continued lack of consistency in association studies, in both candidate gene and genome-wide association studies (GWAS). Numerous factors may account for variable results including the use of different diagnostic approaches, small samples in early studies, population stratification, epigenetic phenomena, copy number variation (CNV), rare variation, and phenotypic and allelic heterogeneity. The conflicting results are also probably, in part, a consequence of environmental factors not being considered or controlled for.ConclusionsEach research group has to identify what issues their sample may best address. We suggest that, where possible, more emphasis should be placed on the environment in molecular behavioural genetics to identify individuals at environmental high risk in addition to genetic high risk. Sequencing should be used to identify rare and alternative variation that may act as a risk factor, and a systems biology approach including gene–gene interactions and pathway analyses would be advantageous. GWAS may require even larger samples with reliably defined (sub)phenotypes.

scholarly journals Relationship between the LHPP Gene Polymorphism and Resting-State Brain Activity in Major Depressive Disorder

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Lingling Cui ◽  
Xiaohong Gong ◽  
Yanqing Tang ◽  
Lingtao Kong ◽  
Miao Chang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Prefrontal Cortex ◽  
Depressive Disorder ◽  
Resting State ◽  
Brain Activity ◽  
Association Studies ◽  
Neural System ◽  
Middle Temporal Gyrus ◽  
Genome Wide Association Studies ◽  
Major Depressive

A single-nucleotide polymorphism at the LHPP gene (rs35936514) has been reported in genome-wide association studies to be associated with major depressive disorder (MDD). However, the neural system effects of rs35936514 that mediate the association are unknown. The present work explores whether the LHPP rs35936514 polymorphism moderates brain regional activity in MDD. A total of 160 subjects were studied: a CC group homozygous for the C allele (23 individuals with MDD and 57 controls) and a T-carrier group carrying the high risk T allele (CT/TT genotypes; 22 MDD and 58 controls). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Brain activity was assessed using the amplitudes of low-frequency fluctuations (ALFF). MDD patients showed a significant increased ALFF in the left middle temporal gyrus and occipital cortex. The T-carrier group showed increased ALFF in the left superior temporal gyrus. Significant diagnosis × genotype interaction was noted in the bilateral lingual gyri, bilateral dorsal lateral prefrontal cortex (dlPFC), and left medial prefrontal cortex (mPFC) (P<0.05, corrected). Results demonstrated that MDD patients with LHPP rs35936514 CT/TT genotype may influence the regional brain activity. These findings implicate the effects of the rs35936514 variation on the neural system in MDD.

scholarly journals Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder

2015 ◽  
Vol 72 (7) ◽  
pp. 642 ◽  
Author(s):  
Marleen H. M. de Moor ◽  
Stéphanie M. van den Berg ◽  
Karin J. H. Verweij ◽  
Robert F. Krueger ◽  
Michelle Luciano ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Major Depressive ◽  
Genome Wide

Genome-wide association studies of placebo and duloxetine response in major depressive disorder

2017 ◽  
Vol 18 (3) ◽  
pp. 406-412 ◽  
Author(s):  
M Maciukiewicz ◽  
V S Marshe ◽  
A K Tiwari ◽  
T M Fonseka ◽  
N Freeman ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Major Depressive ◽  
Genome Wide

scholarly journals Sleep, major depressive disorder, and Alzheimer disease

Neurology ◽  
2020 ◽  
Vol 95 (14) ◽  
pp. e1963-e1970 ◽  
Author(s):  
Jian Huang ◽  
Verena Zuber ◽  
Paul M. Matthews ◽  
Paul Elliott ◽  
Joanna Tzoulaki ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Alzheimer Disease ◽  
Depressive Disorder ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Sleep Patterns ◽  
Major Depressive

ObjectiveTo explore the causal relationships between sleep, major depressive disorder (MDD), and Alzheimer disease (AD).MethodsWe conducted bidirectional 2-sample Mendelian randomization analyses. Genetic associations were obtained from the largest genome-wide association studies currently available in UK Biobank (n = 446,118), Psychiatric Genomics Consortium (n = 18,759), and International Genomics of Alzheimer's Project (n = 63,926). We used the inverse variance–weighted Mendelian randomization method to estimate causal effects and weighted median and Mendelian randomization–Egger for sensitivity analyses to test for pleiotropic effects.ResultsWe found that higher risk of AD was significantly associated with being a “morning person” (odds ratio [OR] 1.01, p = 0.001), shorter sleep duration (self-reported: β = −0.006, p = 1.9 × 10−4; accelerometer based: β = −0.015, p = 6.9 × 10−5), less likely to report long sleep (β = −0.003, p = 7.3 × 10−7), earlier timing of the least active 5 hours (β = −0.024, p = 1.7 × 10−13), and a smaller number of sleep episodes (β = −0.025, p = 5.7 × 10−14) after adjustment for multiple comparisons. We also found that higher risk of AD was associated with lower risk of insomnia (OR 0.99, p = 7 × 10−13). However, we did not find evidence that these abnormal sleep patterns were causally related to AD or for a significant causal relationship between MDD and risk of AD.ConclusionWe found that AD may causally influence sleep patterns. However, we did not find evidence supporting a causal role of disturbed sleep patterns for AD or evidence for a causal relationship between MDD and AD.

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

2019 ◽  
Vol 20 (8) ◽  
pp. 1993 ◽  
Author(s):  
Ankit Srivastava ◽  
Priyanka Singh ◽  
Hitesh Gupta ◽  
Harpreet Kaur ◽  
Neha Kanojia ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Association Studies ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Antidepressant Response ◽  
Major Depressive ◽  
Disease Etiology ◽  
Genome Wide

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.

scholarly journals Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies

2019 ◽  
Vol 49 (16) ◽  
pp. 2646-2656 ◽  
Author(s):  
I. Schwabe ◽  
Y. Milaneschi ◽  
Z. Gerring ◽  
P. F. Sullivan ◽  
E. Schulte ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Sample Size ◽  
Study Design ◽  
Genetic Architecture ◽  
Association Studies ◽  
Self Report ◽  
Genome Wide Association Studies ◽  
Major Depressive ◽  
Combining Data

AbstractTo identify genetic risk loci for major depressive disorder (MDD), two broad study design approaches have been applied: (1) to maximize sample size by combining data from different phenotype assessment modalities (e.g. clinical interview, self-report questionnaires) and (2) to reduce phenotypic heterogeneity through selecting more homogenous MDD subtypes. The value of these strategies has been debated. In this review, we summarize the most recent findings of large genomic studies that applied these approaches, and we highlight the merits and pitfalls of both approaches with particular attention to methodological and psychometric issues. We also discuss the results of analyses that investigated the heterogeneity of MDD. We conclude that both study designs are essential for further research. So far, increasing sample size has led to the identification of a relatively high number of genomic loci linked to depression. However, part of the identified variants may be related to a phenotype common to internalizing disorders and related traits. As such, samples containing detailed clinical information are needed to dissect depression heterogeneity and enable the potential identification of variants specific to a more restricted MDD phenotype. A balanced portfolio reconciling both study design approaches is the optimal approach to progress further in unraveling the genetic architecture of depression.

scholarly journals Higher polygenic risk scores for schizophrenia may be suggestive of treatment non-response in major depressive disorder

2020 ◽  
Author(s):  
Giuseppe Fanelli ◽  
Francesco Benedetti ◽  
Siegfried Kasper ◽  
Alexander Kautzky ◽  
Joseph Zohar ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Association Studies ◽  
Poor Response ◽  
Point Of View ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Major Depressive ◽  
Polygenic Risk ◽  
Resistant Depression

AbstractBackgroundUp to 60% of patients with major depressive disorder (MDD) do not respond to the first treatment with antidepressants. Response to antidepressants is a polygenic trait, although its underpinning genetics has not been fully clarified. This study aimed to investigate if Polygenic Risk Scores (PRSs) for major psychiatric disorders and neuroticism were associated with non-response or resistance to antidepressants in MDD.MethodsPRSs for bipolar disorder, MDD, neuroticism, and schizophrenia (SCZ) were computed in 1148 MDD patients recruited by the European Group for the Study of Resistant Depression. Summary statistics from largest meta-analyses of genome-wide association studies were used as base data. Patients were classified as responders, non-responders to one treatment, non-responders to two or more treatments (treatment-resistant depression or TRD). Regression analyses were adjusted for population stratification and recruitment sites.ResultsPRSs did not predict either non-response or TRD after Bonferroni correction. However, SCZ-PRS was nominally associated with non-response (p=0.003). Patients in the highest SCZ-PRS quintile were more likely to be non-responders than those in the lowest quintile (OR=2.23, 95% CI=1.21-4.10, p=0.02). Patients in the lowest SCZ-PRS quintile showed higher response rates when they did not receive augmentation with second-generation antipsychotics (SGAs), while those in the highest SCZ-PRS quintile had a poor response independently from the treatment strategy (p=0.009).ConclusionsA higher genetic liability to SCZ may reduce responsiveness to pharmacological treatment in MDD. From a clinical point of view, our results suggest that MDD patients with low SCZ-PRS do not benefit from augmentation with SGAs.

scholarly journals The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rona J. Strawbridge ◽  
Keira J. A. Johnston ◽  
Mark E. S. Bailey ◽  
Damiano Baldassarre ◽  
Breda Cullen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
European Ancestry ◽  
Cardiometabolic Disease ◽  
Metabolic Profiles ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Increased Risk

AbstractUnderstanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

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