Imaging genetics: Progressing by leaps and bounds

Association between the expression of lncRNA BASP-AS1 and volume of right hippocampal tail moderated by episode duration in major depressive disorder: a CAN-BIND 1 report

The pathophysiology of major depressive disorder (MDD) encompasses an array of changes at molecular and neurobiological levels. As chronic stress promotes neurotoxicity there are alterations in the expression of genes and gene-regulatory molecules. The hippocampus is particularly sensitive to the effects of stress and its posterior volumes can deliver clinically valuable information about the outcomes of antidepressant treatment. In the present work, we analyzed individuals with MDD (N = 201) and healthy controls (HC = 104), as part of the CAN-BIND-1 study. We used magnetic resonance imaging (MRI) to measure hippocampal volumes, evaluated gene expression with RNA sequencing, and assessed DNA methylation with the (Infinium MethylationEpic Beadchip), in order to investigate the association between hippocampal volume and both RNA expression and DNA methylation. We identified 60 RNAs which were differentially expressed between groups. Of these, 21 displayed differential methylation, and seven displayed a correlation between methylation and expression. We found a negative association between expression of Brain Abundant Membrane Attached Signal Protein 1 antisense 1 RNA (BASP1-AS1) and right hippocampal tail volume in the MDD group (β = -0.218, p = 0.021). There was a moderating effect of the duration of the current episode on the association between the expression of BASP1-AS1 and right hippocampal tail volume in the MDD group (β = -0.48, 95% C.I. [-0.80, -0.16]. t = -2.95 p = 0.004). In conclusion, we found that overexpression of BASP1-AS1 was correlated with DNA methylation, and was negatively associated with right tail hippocampal volume in MDD.

A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis

With advances in neuroimaging and genetics, imaging genetics is a naturally emerging field that combines genetic and neuroimaging data with behavioral or cognitive outcomes to examine genetic influence on altered brain functions associated with behavioral or cognitive variation. We propose a statistical approach, termed imaging genetics generalized structured component analysis (IG-GSCA), which allows researchers to investigate such gene-brain-behavior/cognitive associations, taking into account well-documented biological characteristics (e.g., genetic pathways, gene-environment interactions, etc.) and methodological complexities (e.g., multicollinearity) in imaging genetic studies. We begin by describing the conceptual and technical underpinnings of IG-GSCA. We then apply the approach for investigating how nine depression-related genes and their interactions with an environmental variable (experience of potentially traumatic events) influence the thickness variations of 53 brain regions, which in turn affect depression severity in a sample of Korean participants. Our analysis shows that a dopamine receptor gene and an interaction between a serotonin transporter gene and the environment variable have statistically significant effects on a few brain regions' variations that have statistically significant negative impacts on depression severity. These relationships are largely supported by previous studies. We also conduct a simulation study to safeguard whether IG-GSCA can recover parameters as expected in a similar situation.

A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder

Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks.

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.

FGWAS: Functional genome wide association analysis

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs.

Brain-derived neurotrophic factor Val66Met genotype modulates amygdala habituation

A deficit in amygdala habituation to repeated emotional stimuli may be an endophenotype of disorders characterized by emotion dysregulation, such as borderline personality disorder (BPD). Amygdala reactivity to emotional stimuli is genetically modulated by brain-derived neurotrophic factor (BDNF) variants. Whether amygdala habituation itself is also modulated by BDNF genotypes remains unknown. We used imaging-genetics to examine the effect of BDNF Val66Met genotypes on amygdala habituation to repeated emotional stimuli. We used functional magnetic resonance imaging (fMRI) in 57 subjects (19 BPD patients, 18 patients with schizotypal personality disorder [SPD] and 20 healthy controls [HC]) during a task involving viewing of unpleasant, neutral, and pleasant pictures, each presented twice to measure habituation. Amygdala responses across genotypes (Val66Met SNP Met allele-carriers vs. Non-Met carriers) and diagnoses (HC, BPD, SPD) were examined with ANOVA. The BDNF 66Met allele was significantly associated with a deficit in amygdala habituation, particularly for emotional pictures. The association of the 66Met allele with a deficit in habituation to unpleasant emotional pictures remained significant in the subsample of BPD patients. Using imaging-genetics, we found preliminary evidence that deficient amygdala habituation may be modulated by BDNF genotype.

Influence of BclI C/G (rs41423247) on hippocampal shape and white matter integrity of the parahippocampal cingulum in major depressive disorder

We investigated the interactive effects of BclI C/G (rs41423247) allelic variants and the diagnosis of major depressive disorder (MDD) on hippocampal shape and integrity of the left parahippocampal subdivision of the cingulum. Fifty-two patients with MDD and 52 healthy controls (HCs) underwent T1-weighted structural magnetic resonance imaging and BclI C/G (rs41423247) genotyping. We analyzed hippocampal shape using the FIRST module of FSL and analyzed white matter (WM) integrity using diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS). Significant alterations in left hippocampal shape and decreased fractional anisotropy (FA) values of the left parahippocampal cingulum were observed in MDD patients, compared to HCs. In addition, MDD patients of the BclI minor (G-) allele carrier group showed significant alterations in left hippocampal shape and decreased FA values of the left parahippocampal cingulum compared to BclI minor (G-) allele carrier HCs. No significant differences between diagnostic subgroups of the C/C homozygotes were observed. Our study provides evidence for alterations in hippocampal shape and decreased integrity of the WM region associated with the hippocampus in MDD, and for the possible influence of BclI C/G polymorphism (rs41423247) on hippocampal shape and integrity of the parahippocampal subdivision of the cingulum in depression.

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.

Genetic Testing and Neuroimaging for Youth at Risk for Mental Illness: Trading off Benefit and Risk

BACKGROUND

According to the World Health Organization, mental illness is one of the leading causes of disability worldwide. The first onset of mental illness usually occurs during childhood or adolescence, with nearly 12 million diagnosed cases in the United States alone. Neuroimaging and genetic testing have been invaluable in research on behavioral, affective, and attentional disorders, particularly with their potential predictive capabilities, and ability to improve diagnosis and to decrease the associated burdens of disease. The present study focused specifically the perspectives of mental health providers on the role of neuroimaging and genetic testing in clinical practice with children and adolescents.

METHODS

We interviewed 38 psychiatrists, psychologists, and allied mental health professionals who work primarily with youth about their receptivity toward either the use of neuroimaging or genetic testing. Interviews probed the role they foresee for these modalities for prediction, diagnosis, treatment planning, and the benefits and risks they anticipate.

RESULTS

Practitioners anticipated three major benefits associated with clinical introduction of imaging and genetic testing in the mental health care for youth: (1) improved understanding of the brain and mental illness, (2) more accurate diagnosis than available through conventional clinical examination, and (3) legitimization of treatment plans. They also perceived three major risks: (1) misuse or misinterpretation of the imaging or genetic data, (2) potential adverse impacts on employment and insurance as adolescents reach adulthood, and (3) infringements on self-esteem or self-motivation.

LIMITATIONS

The nature of the interview questions focused on the future of neuroimaging and genetic testing testing research in the context of clinical neuroscience. Therefore, the responses from interview participants are based on anticipated rather than actual experience.

CONCLUSIONS

Continued expansion of brain imaging and genetic testing into clinical care will require a delicate balance of brain biology and respect for autonomy in the still-evolving cognitive and affective world of young individuals.

The functional epistasis of 5-HTTLPR and BDNF Val66Met on emotion processing: a preliminary study

An epistatic interaction of 5-HTTLPR and BDNF Val66Met polymorphisms has been implicated in the structure of rostral anterior cingulate cortex (rACC) and amygdala (AMY): key regions associated with emotion processing. However, a functional epistasis of 5-HTTLPR and BDNF Val66Met on overt emotion processing has yet to be determined. Twenty-eight healthy, Caucasian female participants provided saliva samples for genotyping and underwent functional magnetic resonance imaging (fMRI) during which an emotion processing protocol were presented. Confirming the validity of this protocol, we observed blood oxygen level-dependent (BOLD) activity consistent with fMRI meta-analyses on emotion processing. Region-of-interest analysis of the rACC and AMY revealed main effects of 5-HTTLPR and BDNF Val66Met, and an interaction of 5-HTTLPR and BDNF Val66Met. The effect of the BDNF Met66 allele was dependent on 5-HTTLPR alleles, such that participants with S and Met alleles had the greatest rACC and AMY activation during the presentation of emotional images relative to other genetic groupings. Increased activity in these regions was interpreted as increased reactivity to emotional stimuli, suggesting that those with S and Met alleles are more reactive to emotional stimuli relative to other groups. Although limited by a small sample, this study contributes novel and preliminary findings relating to a functional epistasis of the 5-HTTLPR and BDNF Val66Met genes in emotion processing and provides guidance on appropriate methods to determine genetic epistasis in fMRI.

Neuroimaging and genetics: exploring, searching, and finding

This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.

Brain connectivity in psychiatric imaging genetics

In the past decade, imaging genetics has evolved into a highly successful neuroimaging discipline with a variety of sophisticated research tools. To date, several neural systems mechanisms have been identified that mediate genetic risk for mental disorders linked to common candidate and genome-wide-supported variants. In particular, the examination of intermediate connectivity phenotypes has recently gained increasing popularity. This paper gives an overview of the scientific methods and evidence that link indices of neural network organization to the genetic susceptibility for mental illness with a focus on the effects of candidate genes and genome-wide supported risk variants on brain structure and function.

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

OBJECTIVES

To review neuroimaging intermediate phenotypes of MDD and their relation to genetic risk variants.

METHODS

A systematic literature search of peer-reviewed English language articels using PubMed ( www.pubmed.org ) was performed.

RESULTS

Comprehensive evidence on the influence of serotonergic genes (SLC6A4, HTR1A, MAOA, TPH2) and BDNF on the following neural intermediate phenotypes is displayed: amygdala reactivity, coupling of amygdala-anterior cingulate cortex (ACC) activity, ACC volume, hippocampal volume and serotonin receptor 1A (5-HT1A) binding potential (BP).

CONCLUSIONS

Intermediate phenotypes may bridge the gap between genotype and phenotype by reducing the impreciseness of psychiatric phenotypes and yield more insights into the underlying biology.

Is there a personalized medicine for mood disorders?

Major Depressive Disorder (MDD) and antidepressant therapy response are largely based on behavioral criteria, which are known to correlate at best modestly with biological measures. Therefore, it is not surprising that the search for peripheral biological markers (biomarkers) being assessed in distant biological systems such as body fluids has not yet resulted in clinically convincing measures for MDD diagnostics or treatment evaluation. Imaging genetics studies, however, have been successful in the search for intermediate imaging phenotypes of MDD and treatment response that are directly related to the neurobiological underpinnings of MDD, but are not suitable for a broad clinical use today. Hence, we argue that intermediate phenotypes derived from imaging genetics studies should be utilized as substitutes of behaviorally assessed psychiatric diagnoses or therapy response in the search for easily accessible peripheral biomarkers. This article will further cover the current state of peripheral and neural biomarker research.