MTHFR: Genetic variants, expression analysis and COMT interaction in major depressive disorder

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers

BACKGROUND

The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation.

METHODS

We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values.

RESULTS

A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response.

CONCLUSIONS

The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

A Systematic Review of Candidate Genes for Major Depression

Background and Objectives: The aim of this systematic review was to analyse which candidate genes were examined in genetic association studies and their association with major depressive disorder (MDD). Materials and Methods: We searched PUBMED for relevant studies published between 1 July 2012 and 31 March 2019, using combinations of keywords: “major depressive disorder” OR “major depression” AND “gene candidate”, “major depressive disorder” OR “major depression” AND “polymorphism”. Synthesis focused on assessing the likelihood of bias and investigating factors that may explain differences between the results of studies. For selected gene list after literature overview, functional enrichment analysis and gene ontology term enrichment analysis were conducted. Results: 141 studies were included in the qualitative review of gene association studies focusing on MDD. 86 studies declared significant results (p < 0.05) for 172 SNPs in 85 genes. The 13 SNPs associations were confirmed by at least two studies. The 18 genetic polymorphism associations were confirmed in both the previous and this systematic analysis by at least one study. The majority of the studies (68.79 %) did not use or describe power analysis, which may have had an impact over the significance of their results. Almost a third of studies (N = 54) were conducted in Chinese Han population. Conclusion: Unfortunately, there is still insufficient data on the links between genes and depression. Despite the reported genetic associations, most studies were lacking in statistical power analysis, research samples were small, and most gene polymorphisms have been confirmed in only one study. Further genetic research with larger research samples is needed to discern whether the relationship is random or causal. Summations: This systematic review had summarized all reported genetic associations and has highlighted the genetic associations that have been replicated. Limitations: Unfortunately, most gene polymorphisms have been confirmed only once, so further studies are warranted for replicating these genetic associations. In addition, most studies included a small number of MDD cases that could be indicative for false positive. Considering that polymorphism loci and associations with MDD is also vastly dependent on interpersonal variation, extensive studies of gene interaction pathways could provide more answers to the complexity of MDD.

Human Dermal Fibroblast: A Promising Cellular Model to Study Biological Mechanisms of Major Depression and Antidepressant Drug Response

BACKGROUND

Human dermal fibroblasts (HDF) can be used as a cellular model relatively easily and without genetic engineering. Therefore, HDF represent an interesting tool to study several human diseases including psychiatric disorders. Despite major depressive disorder (MDD) being the second cause of disability in the world, the efficacy of antidepressant drug (AD) treatment is not sufficient and the underlying mechanisms of MDD and the mechanisms of action of AD are poorly understood.

OBJECTIVE

The aim of this review is to highlight the potential of HDF in the study of cellular mechanisms involved in MDD pathophysiology and in the action of AD response.

METHODS

The first part is a systematic review following PRISMA guidelines on the use of HDF in MDD research. The second part reports the mechanisms and molecules both present in HDF and relevant regarding MDD pathophysiology and AD mechanisms of action.

RESULTS

HDFs from MDD patients have been investigated in a relatively small number of works and most of them focused on the adrenergic pathway and metabolism-related gene expression as compared to HDF from healthy controls. The second part listed an important number of papers demonstrating the presence of many molecular processes in HDF, involved in MDD and AD mechanisms of action.

CONCLUSION

The imbalance in the number of papers between the two parts highlights the great and still underused potential of HDF, which stands out as a very promising tool in our understanding of MDD and AD mechanisms of action.

Genetic Markers in Psychiatry

Psychiatric disorders such as addiction (substance use and addictive disorders), depression, eating disorders, schizophrenia, and post-traumatic stress disorder (PTSD) are severe, complex, multifactorial mental disorders that carry a high social impact, enormous public health costs, and various comorbidities as well as premature morbidity. Their neurobiological foundation is still not clear. Therefore, it is difficult to uncover new set of genes and possible genetic markers of these disorders since the understanding of the molecular imbalance leading to these disorders is not complete. The integrative approach is needed which will combine genomics and epigenomics; evaluate epigenetic influence on genes and their influence on neuropeptides, neurotransmitters, and hormones; examine gene × gene and gene × environment interplay; and identify abnormalities contributing to development of these disorders. Therefore, novel genetic approaches based on systems biology focused on improvement of the identification of the biological underpinnings might offer genetic markers of addiction, depression, eating disorders, schizophrenia, and PTSD. These markers might be used for early prediction, detection of the risk to develop these disorders, novel subtypes of the diseases and tailored, personalized approach to therapy.

Genetic variants in major depressive disorder: From pathophysiology to therapy

In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.

MTHFR gene methylation is associated with perceived stress in healthy young adults

BACKGROUND

Epigenetic factors have been identified in the past years as interesting candidates for psychiatric disorders and related endophenotypes. It has been found that the methylenetetrahydrofolate reductase (MTHFR) gene is associated with major depressive disorder, and the aim of the current study was to examine the possible association between perceived stress and MTHFR methylation, taking into account depressive symptoms as a covariate.

PARTICIPANTS AND METHODS

Seventy-eight healthy Colombian participants (mean age=20.9 years; SD=3.0) were evaluated with the Perceived Stress Scale and with the Patient Health Questionnaire-9 for depressive symptomatology. MTHFR methylation levels were measured with a methylation-sensitive high-resolution melting method. A multiple regression analysis (adjusting for age, sex, and depressive symptoms) was carried out to assess the association between MTHFR methylation and perceived stress scores.

RESULTS

We found a significant inverse correlation between MTHFR methylation levels and perceived stress scores (r=-0.502; P=5.9×10(-5)), which remained significant after being adjusted for age, sex, and depressive symptomatology.

CONCLUSION

To our knowledge, this is the first study that reports an association between perceived stress and MTHFR methylation levels. This report adds evidence to the emerging role of epigenetic changes in endophenotypes related to affective disorders.

Methylenetetrahydrofolate Reductase A1298C Polymorphism and Major Depressive Disorder

Major depressive disorder (MDD) is a disorder that carries significant psychosocial and economic implications. Research efforts have focused on identifying biomarkers that can aid in the prediction, diagnosis, and efficacious treatment of MDD. Most of this focus has been placed on a polymorphism of the methylenetetrahydrofolate reductase (MTHFR) gene, C677T. MTHFR C677T is screened during MDD diagnosis in many protocols. However, MTHFR C667T poses conflicting data in various ethnic groups and geographic populations calling into question its utility. Another polymorphism, MTHFR A1298C, has often taken the back-seat to MTHFR C677T in respect to research focus. MTHFR A1298C is implicated in irregular homocysteine metabolism and aberrant folate cycles and, through this, it may play a role as either a driver in the development of MDD or as a predictive or diagnostic marker, possibly in combination with C677T. The number of studies evaluating MTHFR A1298C and the power of those studies is lacking and thus larger studies are required to confirm the association between this polymorphism and MDD.

Interaction of multiple gene variants and their effects on schizophrenia phenotypes

BACKGROUND

Schizophrenia is a clinically heterogeneous disorder and may be explained by its complex genetic architecture. Many schizophrenia susceptibility genes were identified but the picture remains unclear due to inconsistent or contradictory genetic association studies. This confusion may, in part, be because symptoms result from the combined interaction of many genes and these interacting genes are associated with specific sub-phenotypes of schizophrenia rather than schizophrenia as a whole. This study investigates the relationship between schizophrenia susceptibility genes and schizophrenia sub-phenotypes by identifying multiple gene variant interactions.

MATERIALS AND METHODS

Fifty SNPs from 21 genes were genotyped in 235 Australian participants with schizophrenia screened for various phenotypes. Schizophrenia participants were grouped into relevant phenotype clusters using cluster analysis and normalized phenotype cluster scores were calculated for each patient. The relationship between genotypes and normalized phenotype cluster scores were analyzed by linear regression analysis.

RESULTS

Three phenotype clusters were identified. There was some overlap in symptoms between phenotype clusters, particularly for depression. However, cluster 1 appears to be characterized by speech disorder and affective behavior symptoms, cluster 2 has predominantly hallucination symptoms and cluster 3 has mainly delusion symptoms. Interaction of five SNPs was found to have an effect on cluster 1 symptoms; ten SNPs on cluster 2 symptoms; and eight SNPs on cluster 3 symptoms.

CONCLUSION

The interaction of specific susceptibility genes is likely to lead to specific clinical sub-phenotypes of schizophrenia. Larger patient cohorts with more extensive clinical data will improve the detection of gene interactions and the resultant schizophrenia clinical phenotypes.

Proteasome system dysregulation and treatment resistance mechanisms in major depressive disorder

Several studies have demonstrated that allelic variants related to inflammation and the immune system may increase the risk for major depressive disorder (MDD) and reduce patient responsiveness to antidepressant treatment. Proteasomes are fundamental complexes that contribute to the regulation of T-cell function. Only one study has shown a putative role of proteasomal PSMA7, PSMD9 and PSMD13 genes in the susceptibility to an antidepressant response, and sparse data are available regarding the potential alterations in proteasome expression in psychiatric disorders such as MDD. The aim of this study was to clarify the role of these genes in the mechanisms underlying the response/resistance to MDD treatment. We performed a case-control association study on 621 MDD patients, of whom 390 were classified as treatment-resistant depression (TRD), and we collected peripheral blood cells and fibroblasts for mRNA expression analyses. The analyses showed that subjects carrying the homozygous GG genotype of PSMD13 rs3817629 had a twofold greater risk of developing TRD and exhibited a lower PSMD13 mRNA level in fibroblasts than subjects carrying the A allele. In addition, we found a positive association between PSMD9 rs1043307 and the presence of anxiety disorders in comorbidity with MDD, although this result was not significant following correction for multiple comparisons. In conclusion, by confirming the involvement of PSMD13 in the MDD treatment response, our data corroborate the hypothesis that the dysregulation of the complex responsible for the degradation of intracellular proteins and potentially controlling autoimmunity- and immune tolerance-related processes may be involved in several phenotypes, including the TRD.

Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders

OBJECTIVES

To provide guidance for the management of mood disorders, based on scientific evidence supplemented by expert clinical consensus and formulate recommendations to maximise clinical salience and utility.

METHODS

Articles and information sourced from search engines including PubMed and EMBASE, MEDLINE, PsycINFO and Google Scholar were supplemented by literature known to the mood disorders committee (MDC) (e.g., books, book chapters and government reports) and from published depression and bipolar disorder guidelines. Information was reviewed and discussed by members of the MDC and findings were then formulated into consensus-based recommendations and clinical guidance. The guidelines were subjected to rigorous successive consultation and external review involving: expert and clinical advisors, the public, key stakeholders, professional bodies and specialist groups with interest in mood disorders.

RESULTS

The Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders (Mood Disorders CPG) provide up-to-date guidance and advice regarding the management of mood disorders that is informed by evidence and clinical experience. The Mood Disorders CPG is intended for clinical use by psychiatrists, psychologists, physicians and others with an interest in mental health care.

CONCLUSIONS

The Mood Disorder CPG is the first Clinical Practice Guideline to address both depressive and bipolar disorders. It provides up-to-date recommendations and guidance within an evidence-based framework, supplemented by expert clinical consensus.

MOOD DISORDERS COMMITTEE

Professor Gin Malhi (Chair), Professor Darryl Bassett, Professor Philip Boyce, Professor Richard Bryant, Professor Paul Fitzgerald, Dr Kristina Fritz, Professor Malcolm Hopwood, Dr Bill Lyndon, Professor Roger Mulder, Professor Greg Murray, Professor Richard Porter and Associate Professor Ajeet Singh.

INTERNATIONAL EXPERT ADVISORS

Professor Carlo Altamura, Dr Francesco Colom, Professor Mark George, Professor Guy Goodwin, Professor Roger McIntyre, Dr Roger Ng, Professor John O'Brien, Professor Harold Sackeim, Professor Jan Scott, Dr Nobuhiro Sugiyama, Professor Eduard Vieta, Professor Lakshmi Yatham.

AUSTRALIAN AND NEW ZEALAND EXPERT ADVISORS

Professor Marie-Paule Austin, Professor Michael Berk, Dr Yulisha Byrow, Professor Helen Christensen, Dr Nick De Felice, A/Professor Seetal Dodd, A/Professor Megan Galbally, Dr Josh Geffen, Professor Philip Hazell, A/Professor David Horgan, A/Professor Felice Jacka, Professor Gordon Johnson, Professor Anthony Jorm, Dr Jon-Paul Khoo, Professor Jayashri Kulkarni, Dr Cameron Lacey, Dr Noeline Latt, Professor Florence Levy, A/Professor Andrew Lewis, Professor Colleen Loo, Dr Thomas Mayze, Dr Linton Meagher, Professor Philip Mitchell, Professor Daniel O'Connor, Dr Nick O'Connor, Dr Tim Outhred, Dr Mark Rowe, Dr Narelle Shadbolt, Dr Martien Snellen, Professor John Tiller, Dr Bill Watkins, Dr Raymond Wu.