The genetic blueprint of major depressive disorder: contributions of imaging genetics studies

Multimodal integration of neuroimaging and genetic data for the diagnosis of mood disorders based on computer vision models

Mood disorders, particularly major depressive disorder (MDD) and bipolar disorder (BD), are often underdiagnosed, leading to substantial morbidity. Harnessing the potential of emerging methodologies, we propose a novel multimodal fusion approach that integrates patient-oriented brain structural magnetic resonance imaging (sMRI) scans with DNA whole-exome sequencing (WES) data. Multimodal data fusion aims to improve the detection of mood disorders by employing established deep-learning architectures for computer vision and machine-learning strategies. We analyzed brain imaging genetic data of 321 East Asian individuals, including 147 patients with MDD, 78 patients with BD, and 96 healthy controls. We developed and evaluated six fusion models by leveraging common computer vision models in image classification: Vision Transformer (ViT), Inception-V3, and ResNet50, in conjunction with advanced machine-learning techniques (XGBoost and LightGBM) known for high-dimensional data analysis. Model validation was performed using a 10-fold cross-validation. Our ViT ⊕ XGBoost fusion model with MRI scans, genomic Single Nucleotide polymorphism (SNP) data, and unweighted polygenic risk score (PRS) outperformed baseline models, achieving an incremental area under the curve (AUC) of 0.2162 (32.03% increase) and 0.0675 (+8.19%) and incremental accuracy of 0.1455 (+25.14%) and 0.0849 (+13.28%) compared to SNP-only and image-only baseline models, respectively. Our findings highlight the opportunity to refine mood disorder diagnostics by demonstrating the transformative potential of integrating diverse, yet complementary, data modalities and methodologies.

Gene Expression has Distinct Associations with Brain Structure and Function in Major Depressive Disorder

Major depressive disorder (MDD) is associated with structural and functional brain abnormalities. MDD as well as brain anatomy and function are influenced by genetic factors, but the role of gene expression remains unclear. Here, this work investigates how cortical gene expression contributes to structural and functional brain abnormalities in MDD. This work compares the gray matter volume and resting-state functional measures in a Chinese sample of 848 MDD patients and 749 healthy controls, and these case-control differences are then associated with cortical variation of gene expression. While whole gene expression is positively associated with structural abnormalities, it is negatively associated with functional abnormalities. This work observes the relationships of expression levels with brain abnormalities for individual genes, and found that transcriptional correlates of brain structure and function show opposite relations with gene dysregulation in postmortem cortical tissue from MDD patients. This work further identifies genes that are positively or negatively related to structural abnormalities as well as functional abnormalities. The MDD-related genes are enriched for brain tissue, cortical cells, and biological pathways. These findings suggest that distinct genetic mechanisms underlie structural and functional brain abnormalities in MDD, and highlight the importance of cortical gene expression for the development of cortical abnormalities.

A neural mechanism for affective well-being: Subgenual cingulate cortex mediates real-life effects of nonexercise activity on energy

Physical activity substantially improves well-being and mental health, but the underlying brain processes remain unclear. Most research concerns exercise, although the majority of everyday human behaviors, such as walking or stair climbing, are nonexercise activities. Combining neuroimaging with ecological assessment of activity and GPS-triggered smartphone diaries, we show a specific association of nonexercise activity with energy in two independent samples mediated by the subgenual part of the anterior cingulate cortex (sgACC), a key emotion regulatory site. Furthermore, energy predicted a range of mental health metrics. sgACC volume moderated humans' emotional gain from nonexercise activity in real life: Individuals with low sgACC volume, a risk factor for depression, felt less energized when inactive but benefited more from periods of high nonexercise activity. This suggests an everyday life mechanism affecting affective well-being in the general population and, if substantiated in patient samples, a risk and resilience process for mood disorders.

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.

Neuroimaging genomic studies in major depressive disorder: A systematic review

Genetic-neuroimaging studies could identify new potential endophenotypes of major depressive disorder (MDD). Morphological and functional alterations may be attributable to genetic factors that regulate neurogenesis and neurodegeneration. Given that the association between gene polymorphisms and brain morphology or function has varied across studies, this systematic review aims at evaluating and summarizing all available genetic-neuroimaging studies. Twenty-eight gene variants were evaluated in 64 studies by structural or functional magnetic resonance imaging. Significant genetic-neuroimaging associations were found in monoaminergic genes, BDNF genes, glutamatergic genes, HPA axis genes, and the other common genes, which were consistent with common hypotheses of the pathogenesis of MDD.

The genetics of anxiety-related negative valence system traits

NIMH's Research Domain Criteria (RDoC) domain of negative valence systems (NVS) captures constructs of negative affect such as fear and distress traditionally subsumed under the various internalizing disorders. Through its aims to capture dimensional measures that cut across diagnostic categories and are linked to underlying neurobiological systems, a large number of phenotypic constructs have been proposed as potential research targets. Since "genes" represent a central "unit of analysis" in the RDoC matrix, it is important for studies going forward to apply what is known about the genetics of these phenotypes as well as fill in the gaps of existing knowledge. This article reviews the extant genetic epidemiological data (twin studies, heritability) and molecular genetic association findings for a broad range of putative NVS phenotypic measures. We find that scant genetic epidemiological data is available for experimentally derived measures such as attentional bias, peripheral physiology, or brain-based measures of threat response. The molecular genetic basis of NVS phenotypes is in its infancy, since most studies have focused on a small number of candidate genes selected for putative association to anxiety disorders (ADs). Thus, more research is required to provide a firm understanding of the genetic aspects of anxiety-related NVS constructs. © 2016 Wiley Periodicals, Inc.

Imaging genetics studies on monoaminergic genes in major depressive disorder

Although depression is the leading cause of disability worldwide, current understanding of the neurobiology of depression has failed to be translated into clinical practice. Major depressive disorder (MDD) pathogenesis is considered to be significantly influenced by multiple risk genes, however genetic effects are not simply expressed at a behavioral level. Therefore the concept of endophenotype has been applied in psychiatric genetics. Imaging genetics applies anatomical or functional imaging technologies as phenotypic assays to evaluate genetic variation and their impact on behavior. This paper attempts to provide a comprehensive review of available imaging genetics studies, including reports on genetic variants that have most frequently been linked to MDD, such as the monoaminergic genes (serotonin transporter gene, monoamine oxidase A gene, tryptophan hydroxylase-2 gene, serotonin receptor 1A gene and catechol-O-methyl transferase gene), with regard to key structures involved in emotion processing, such as the hippocampus, amygdala, anterior cingulate cortex and orbitofrontal cortex.

Impact of monoamine-related gene polymorphisms on hippocampal volume in treatment-resistant depression

OBJECTIVE

In major depressive disorder (MDD), single nucleotide polymorphisms (SNPs) in monoaminergic genes may impact disease susceptibility, treatment response, and brain volume. The objective of this study was to examine the effect of such polymorphisms on hippocampal volume in patients with treatment-resistant MDD and healthy controls. Candidate gene risk alleles were hypothesised to be associated with reductions in hippocampal volume.

METHODS

A total of 26 outpatients with treatment-resistant MDD and 27 matched healthy controls underwent magnetic resonance imaging and genotyping for six SNPs in monoaminergic genes [serotonin transporter (SLC6A4), norepinephrine transporter (SLC6A2), serotonin 1A and 2A receptors (HTR1A and HTR2A), catechol-O-methyltransferase (COMT), and brain-derived neurotrophic factor (BDNF)]. Hippocampal volume was estimated using an automated segmentation algorithm (FreeSurfer).

RESULTS

Hippocampal volume did not differ between patients and controls. Within the entire study sample irrespective of diagnosis, C allele-carriers for both the NET-182 T/C [rs2242446] and 5-HT1A-1019C/G [rs6295] polymorphisms had smaller hippocampal volumes relative to other genotypes. For the 5-HTTLPR (rs25531) polymorphism, there was a significant diagnosis by genotype interaction effect on hippocampal volume. Among patients only, homozygosity for the 5-HTTLPR short (S) allele was associated with smaller hippocampal volume. There was no association between the 5-HT2A, COMT, and BDNF SNPs and hippocampal volume.

CONCLUSION

The results indicate that the volume of the hippocampus may be influenced by serotonin- and norepinephrine-related gene polymorphisms. The NET and 5-HT1A polymorphisms appear to have similar effects on hippocampal volume in patients and controls while the 5-HTTLPR polymorphism differentially affects hippocampal volume in the presence of depression.

fMRI measurements of amygdala activation are confounded by stimulus correlated signal fluctuation in nearby veins draining distant brain regions

Imaging the amygdala with functional MRI is confounded by multiple averse factors, notably signal dropouts due to magnetic inhomogeneity and low signal-to-noise ratio, making it difficult to obtain consistent activation patterns in this region. However, even when consistent signal changes are identified, they are likely to be due to nearby vessels, most notably the basal vein of rosenthal (BVR). Using an accelerated fMRI sequence with a high temporal resolution (TR = 333 ms) combined with susceptibility-weighted imaging, we show how signal changes in the amygdala region can be related to a venous origin. This finding is confirmed here in both a conventional fMRI dataset (TR = 2000 ms) as well as in information of meta-analyses, implying that “amygdala activations” reported in typical fMRI studies are likely confounded by signals originating in the BVR rather than in the amygdala itself, thus raising concerns about many conclusions on the functioning of the amygdala that rely on fMRI evidence alone.

From psychiatric disorders to animal models: a bidirectional and dimensional approach

Psychiatric genetics research is bidirectional in nature, with human and animal studies becoming more closely integrated as techniques for genetic manipulations allow for more subtle exploration of disease phenotypes. This synergy highlights the importance of considering the way in which we approach the genotype-phenotype relationship. In particular, the nosologic divide of psychiatric illness, although clinically relevant, is not directly translatable in animal models. For instance, mice will never fully recapitulate the broad criteria for many psychiatric disorders; additionally, mice will never have guilty ruminations, suicidal thoughts, or rapid speech. Instead, animal models have been and continue to provide a means to explore dimensions of psychiatric disorders to identify neural circuits and mechanisms underlying disease-relevant phenotypes. The genetic investigation of psychiatric illness can yield the greatest insights if efforts continue to identify and use biologically valid phenotypes across species. This review discusses the progress to date and the future efforts that will enhance translation between human and animal studies, including the identification of intermediate phenotypes that can be studied across species and the importance of refined modeling of human disease-associated genetic variation in mice and other animal models.

Platelet serotonin transporter function predicts default-mode network activity

Background

The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence.

Methods

A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (V_max) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet V_max.

Results

The present study demonstrates that increases in platelet V_max significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet V_max is related to global DMN activation and not intrinsic DMN connectivity.

Conclusion

This study provides evidence that platelet V_max predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal V_max coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.

No influence of brain-derived neurotrophic factor (BDNF) polymorphisms on treatment response in a naturalistic sample of patients with major depression

The role of the brain-derived neurotrophic factor (BDNF) in the pathophysiology of major depressive disorder (MDD) remains to be elucidated. Recent post hoc analyses indicated a potential association of three polymorphisms in the BDNF gene with worse treatment outcome in patients with the subtype of melancholic depression. We aimed at replicating these findings in a German naturalistic multicenter follow-up. Three polymorphisms in the BDNF gene (rs7103411, rs6265 (Val66Met) and rs7124442) were genotyped in 324 patients with MDD and 470 healthy controls. We applied univariate tests and logistic regression models stratifying for depression subtype and gender. The three polymorphisms were not associated with MDD as diagnosis. Further, no associations were found in univariate tests. With logistic regression, we only found a tendency towards an association of the rs6265 (Val66Met) polymorphism with overall response to treatment (response rates: GG (val/val) < GA (val/met) < AA (met/met); p = 0.0129) and some gender differences for the rs6265 (Val66Met) and rs7103411 polymorphisms. Treatment outcome stratified for subtypes of depression did not differ significantly between the investigated polymorphisms or using haplotype analyses. However, results showed a tendency towards significance. At this stage, we cannot support an influence of these three polymorphisms. Further studies in larger patient samples to increase sample sizes of subgroups are warranted.

Regional gray matter reductions are associated with genetic liability for anxiety and depression: an MRI twin study

BACKGROUND

The influence of genetic and/or environmental factors on the volumetric brain changes observed in subjects affected by anxiety and depression disorders remains unclear. The current study aimed to investigate whether genetic and environmental liabilities make different contributions to abnormalities in gray matter volume (GMV) in anxiety and depression using a concordant and discordant MZ twin pairs design.

METHODS

Fifty-three magnetic resonance imaging (3T) brain scans were obtained from monozygotic (MZ) twins concordant (6 pairs) and discordant (10 pairs) for lifetime anxiety and depression disorders and from healthy twins (21 subjects). We applied voxel-based morphometry to analyse GMV differences. Concordant affected twins were compared to healthy twins and within-pairs comparisons were performed in the discordant group.

RESULTS

GMV reductions in bilateral fusiform gyrus and amygdala were observed in concordant affected twins for anxiety and depression compared to healthy twins. No intrapair differences were found in GMV between discordant affected twins and their healthy co-twins.

LIMITATIONS

The sample size was modest. This might explain why no intrapair differences were found in the discordant MZ twin group.

CONCLUSIONS

As concordant affected MZ twins are believed to have a particularly high genetic liability for the disorder, our findings suggest that fusiform gyrus and amygdala gray matter reductions are related to a genetic risk for anxiety and depression. Discrepancies in regard to brain abnormalities in anxiety and depression may be related to the admixture of patients with GMV abnormalities mainly accounted for by genetic factors with patients presenting GMV mainly accounted for by environmental factors.

Modulatory effects of the piccolo genotype on emotional memory in health and depression

Major depressive disorder (MDD) has been associated with biased memory formation for mood-congruent information, which may be related to altered monoamine levels. The piccolo (PCLO) gene, involved in monoaminergic neurotransmission, has previously been linked to depression in a genome-wide association study. Here, we investigated the role of the PCLO risk allele on functional magnetic resonance imaging (MRI) correlates of emotional memory in a sample of 89 MDD patients (64 PCLO risk allele carriers) and 29 healthy controls (18 PCLO risk allele carriers). During negative word encoding, risk allele carriers showed significant lower activity relative to non-risk allele carriers in the insula, and trend-wise in the anterior cingulate cortex and inferior frontal gyrus. Moreover, depressed risk allele carriers showed significant lower activity relative to non-risk allele carriers in the striatum, an effect which was absent in healthy controls. Finally, amygdalar response during processing new positive words vs. known words was blunted in healthy PCLO+ carriers and in MDD patients irrespective of genotype, which may indicate that signalling of salient novel information does not occur to the same extent in PCLO+ carriers and MDD patients. The PCLO risk allele may increase vulnerability for MDD by modulating local brain function with regard to responsiveness to salient stimuli (i.e. insula) and processing novel negative information. Also, depression-specific effects of PCLO on dorsal striatal activation during negative word encoding and the absence of amygdalar salience signalling for novel positive information further suggest a role of PCLO in symptom maintenance in MDD.

The implications of genomics on the nursing care of adults with neuropsychiatric conditions

PURPOSE

Neuropsychiatric disorders contribute substantially to disease burden and quality of life across the lifespan and the globe. The purpose of this article is to review the state of the science regarding genomic contributions to selected common neuropsychiatric conditions and to examine the consequent immediate and future implications for nursing practice and research.

ORGANIZING CONSTRUCT

Our work is guided by an ecological model that recognizes that common diseases are complex or multifactorial, meaning that multiple genomic and environmental factors contribute to their etiology.

METHODS

A review of the literature was conducted to determine the state of the science in relationship to the genomic contributions to selected neuropsychiatric disorders.

FINDINGS

Neuropsychiatric conditions are genomically heterogeneous, both within a single disorder and across groups of disorders. While recent genomic research yields clinically validated and useful information for a small subset of persons (e.g., predictive genetic testing for Huntington disease and early-onset Alzheimer disease), broad clinical application of genetic information is not yet available. In addition, the implications of genomics for the development and targeting of nonpharmacologic treatment strategies is largely unexplored.

CONCLUSIONS

Further research is needed to expand knowledge beyond genomic risk for the presence of disease to knowledge about the genomic risk for symptoms, symptom burden, and tailored symptom management interventions.

CLINICAL RELEVANCE

Knowledge about the genomic influences on neuropsychiatric conditions suggests important implications for practicing nurses in the identification of persons at risk, provision of follow-up support, and in the administration of medications.

Bridging the gap between neuroscientific and psychodynamic models in child and adolescent psychiatry

This article provides a selective review of the neuroscience and child-psychoanalytic literature, focusing on areas of significant overlap and emphasizing comprehensive theories in developmental neuroscience and child psychoanalysis with testable mechanisms of action. Topics include molecular biology and genetics findings relevant to psychotherapy research, neuroimaging findings relevant to psychotherapy, brain regions of interest for psychotherapy, neurobiologic changes caused by psychotherapy, use of neuroimaging to predict treatment outcome, and schemas as a bridging concept between psychodynamic and cognitive neuroscience models. The combined efforts of neuroscientists and psychodynamic clinicians and theorists are needed to unravel the mechanisms of human mental functioning.

Epigenetic Modulation of Mood Disorders

BACKGROUND

Mood disorders are expressed in many heterogeneous forms, varying from anxiety to severe major clinical depression. The disorders are expressed in individual variety through manifestations governed by co-morbidities, symptom frequency, severity, and duration, and the effects of genes on phenotypes. The underlying etiologies of mood disorders consist of complex interactive operations of genetic and environmental factors. The notion of endophenotypes, which encompasses the markers of several underlying liabilities to the disorders, may facilitate efforts to detect and define, through staging, the genetic risks inherent to the extreme complexity of disease state.

AIMS

This review evaluates the role of genetic biomarkers in assisting clinical diagnosis, identification of risk factors, and treatment of mood disorders.

METHODS

Through a systematic assessment of studies investigating the epigenetic basis for mood disorders, the present review examines the interaction of genes and environment underlying the pathophysiology of these disorders.

RESULTS

The majority of research findings suggest that the notion of endophenotypes, which encompasses the markers of several underlying liabilities to the disorders, may facilitate efforts to detect and define, through staging, the genetic risks inherent to the extreme complexity of the disease states. Several strategies under development and refinement show the propensity for derivation of essential elements in the etiopathogenesis of the disorders affecting drug-efficacy, drug metabolism, and drug adverse effects, e.g., with regard to selective serotonin reuptake inhibitors. These include: transporter gene expression and genes encoding receptor systems, hypothalamic-pituitary-adrenal axis factors, neurotrophic factors, and inflammatory factors affecting neuroimmune function. Nevertheless, procedural considerations of pharmacogenetics presume the parallel investment of policies and regulations to withstand eventual attempts at misuse, thereby ensuring patient integrity.

CONCLUSIONS

Identification of genetic biomarkers facilitates choice of treatment, prediction of response, and prognosis of outcome over a wide spectrum of symptoms associated with affective states, thereby optimizing clinical practice procedures. Epigenetic regulation of primary brain signaling, e.g., serotonin and hypothalamic-pituitary-adrenal function, and factors governing their metabolism are necessary considerations. The participation of neurotrophic factors remains indispensable for neurogenesis, survival, and functional maintenance of brain systems.

Gene, brains, and environment-genetic neuroimaging of depression

Depression, conceptualized as major depressive disorder (MDD), is a complex psychiatric disorder with multiple behavioral changes and alterations in various brain regions. Biochemically, serotonin and others substances like GABA, glutamate, norepinephrin, adrenaline/noradrenaline play an essential role in the pathogenesis of MDD. The paper reviews recent human neuroimaging findings on how the genes underlying these biochemical substances modulate neural activity, behavior, and ultimately clinical symptoms. Current data provide solid evidence that genes related to serotonin impact emotion-related neural activity in the amygdala and the anterior cingulate cortex. By contrast, evidence is not as strong for genes related to biochemical substances other than serotonin and other regions of the brain. The review concludes with discussing future genetic, neural, and clinical challenges that point out the central role of gene × environment and brain × environment interactions as genetic and neural predispositions of depression.

Imaging-genetics in autism spectrum disorder: advances, translational impact, and future directions

Autism Spectrum Disorder (ASD) refers to a group of heterogeneous neurodevelopmental disorders that are unified by impairments in reciprocal social communication and a pattern of inflexible behaviors. Recent genetic advances have resolved some of the complexity of the genetic architecture underlying ASD by identifying several genetic variants that contribute to the disorder. Different etiological pathways associated with ASD may converge through effects on common molecular mechanisms, such as synaptogenesis, neuronal motility, and axonal guidance. Recently, with more sophisticated techniques, neuroimaging, and neuropathological studies have provided some consistency of evidence that altered structure, activity, and connectivity within complex neural networks is present in ASD, compared to typically developing children. The imaging-genetics approach promises to help bridge the gap between genetic variation, resultant biological effects on the brain, and production of complex neuropsychiatric symptoms. Here, we review recent findings from the developing field of imaging-genetics applied to ASD. Studies to date have indicated that relevant risk genes are associated with alterations in circuits that mediate socio-emotional, visuo-spatial, and language processing. Longitudinal studies ideally focused on early development, in conjunction with investigation for gene-gene, and gene-environment interactions may move the promise of imaging-genetics in ASD closer to the clinical domain.