Associations Between Variants Near a Monoaminergic Pathways Gene (PHOX2B) and Amygdala Reactivity: A Genome-Wide Functional Imaging Study

The Deep Breath Before the Plunge: Ictal Apnea and the Amygdala

A Human Amygdala Site That Inhibits Respiration and Elicits Apnea in Pediatric Epilepsy

Rhone AE, Kovach CK, Harmata GIS, et al. JCI Insight. 2020;5(6):e134852. doi:10.1172/jci.insight.134852

Background:

Seizure-induced inhibition of respiration plays a critical role in sudden unexpected death in epilepsy (SUDEP). However, the mechanisms underlying seizure-induced central apnea in pediatric epilepsy are unknown.

Methods:

We studied 8 pediatric patients with intractable epilepsy undergoing intracranial electroencephalography. We recorded respiration during seizures and during electrical stimulation mapping of 174 forebrain sites. A machine learning algorithm was used to delineate brain regions that inhibit respiration.

Results:

In 2 patients, apnea coincided with seizure spread to the amygdala. Supporting a role for the amygdala in breathing inhibition in children, electrically stimulating the amygdala produced apnea in all 8 patients (3-17 years old). These effects did not depend on epilepsy type and were relatively specific to the amygdala, as no other site affected breathing. Remarkably, patients were unaware that they had stopped breathing, and none reported dyspnea or arousal, findings critical for SUDEP. Finally, a machine learning algorithm based on 45 stimulation sites and 210 stimulation trials identified a focal subregion in the human amygdala that consistently produced apnea. This site, which we refer to as the amygdala inhibition of respiration (AIR) site, includes the medial subregion of the basal nuclei, cortical and medial nuclei, amygdala transition areas, and intercalated neurons.

Conclusions:

A focal site in the amygdala inhibits respiration and induces apnea (AIR site) when electrically stimulated and during seizures in children with epilepsy. This site may prove valuable for determining those at greatest risk for SUDEP and as a therapeutic target.

Seizure-Related Apneas Have an Inconsistent Linkage to Amygdala Seizure Spread

Park K, Kanth K, Bajwa S, et al. Epilepsia. 2020;61(6):1253-1260.

Objective:

Sudden unexpected death in epilepsy (SUDEP) is a frequent cause of death in epilepsy. Respiratory dysfunction is implicated as a critical factor in SUDEP pathophysiology. Human studies have shown that electrical stimulation of the amygdala resulted in apnea, indicating that the amygdala has a role in respiration control. Unilateral amygdala stimulation resulted in immediate onset of respiratory dysfunction occurring only during nose breathing. In small numbers of patients, some but not all spontaneous seizures resulted in apnea occurring shortly after seizure spread to the amygdala. With this study, we aimed to determine whether seizure onset or spread to the amygdala was necessary and sufficient to cause apnea.

Methods:

We investigated the temporal relationship between apnea/hypopnea (AH) onset and initial seizure involvement within the amygdala in patients with implanted depth electrodes.

Results:

Data from 17 patients (11 female) with 47 seizures were analyzed. With 7 seizures (3 patients), AH preceded amygdala seizure involvement by 2 to 55 seconds. There was no AH with 4 seizures (3 patients) that involved the amygdala. With 8 seizures (4 patients), AH occurred within 2 seconds following amygdala seizure onset. With 28 seizures, AH started >2 seconds after amygdala seizure onset (range: 3-158 seconds). Following seizure onset, there was a significant difference between AH onset time and amygdala seizure onset (P < .001). The mean ± standard deviation AH onset was 27.8 ± 41.06 seconds, and the mean time to amygdala involvement was 8.83 ± 20.19 seconds.

Significance:

There is a wide range of AH onset times relative to amygdala seizure involvement. With some seizures, amygdala seizure involvement occurs without AH. With other seizures, AH precedes amygdala seizures, suggesting that, with spontaneous seizures, involvement of the amygdala may not be crucial to induction of AH with all seizures. Other pathophysiology impacting brain stem respiratory networks may be of greater relevance to seizure-triggered apneas.

Replication in Imaging Genetics: The Case of Threat-Related Amygdala Reactivity

BACKGROUND

Low replication rates are a concern in most, if not all, scientific disciplines. In psychiatric genetics specifically, targeting intermediate brain phenotypes, which are more closely associated with putative genetic effects, was touted as a strategy leading to increased power and replicability. In the current study, we attempted to replicate previously published associations between single nucleotide polymorphisms and threat-related amygdala reactivity, which represents a robust brain phenotype not only implicated in the pathophysiology of multiple disorders, but also used as a biomarker of future risk.

METHODS

We conducted a literature search for published associations between single nucleotide polymorphisms and threat-related amygdala reactivity and found 37 unique findings. Our replication sample consisted of 1117 young adult volunteers (629 women, mean age 19.72 ± 1.25 years) for whom both genetic and functional magnetic resonance imaging data were available.

RESULTS

Of the 37 unique associations identified, only three replicated as previously reported. When exploratory analyses were conducted with different model parameters compared to the original findings, significant associations were identified for 28 additional studies: eight of these were for a different contrast/laterality; five for a different gender and/or race/ethnicity; and 15 in the opposite direction and for a different contrast, laterality, gender, and/or race/ethnicity. No significant associations, regardless of model parameters, were detected for six studies. Notably, none of the significant associations survived correction for multiple comparisons.

CONCLUSIONS

We discuss these patterns of poor replication with regard to the general strategy of targeting intermediate brain phenotypes in genetic association studies and the growing importance of advancing the replicability of imaging genetics findings.

Genomics studies on musical aptitude, music perception, and practice

When searching for genetic markers inherited together with musical aptitude, genes affecting inner ear development and brain function were identified. The alpha-synuclein gene (SNCA), located in the most significant linkage region of musical aptitude, was overexpressed when listening and performing music. The GATA-binding protein 2 gene (GATA2) was located in the best associated region of musical aptitude and regulates SNCA in dopaminergic neurons, thus linking DNA- and RNA-based studies of music-related traits together. In addition to SNCA, several other genes were linked to dopamine metabolism. Mutations in SNCA predispose to Lewy-body dementia and cause Parkinson disease in humans and affect song production in songbirds. Several other birdsong genes were found in transcriptome analysis, suggesting a common evolutionary background of sound perception and production in humans and songbirds. Regions of positive selection with musical aptitude contained genes affecting auditory perception, cognitive performance, memory, human language development, and song perception and production of songbirds. The data support the role of dopaminergic pathway and their link to the reward mechanism as a molecular determinant in positive selection of music. Integration of gene-level data from the literature across multiple species prioritized activity-dependent immediate early genes as candidate genes in musical aptitude and listening to and performing music.

Opportunities for an enhanced integration of neuroscience and genomics

Neuroimaging and genetics are two rapidly expanding fields of research. Thoughtful integration of these areas is critical for ongoing large-scale research into the genetic mechanisms underlying brain structure, function, and development. Neuroimaging genetics has been slow to evolve relative to psychiatric genetics research, and some may be unaware that new statistical methods allow for the genomic analysis of more modestly-sized imaging samples. We present a broad overview of the extant imaging genetics literature, provide an interpretation of the major problems surrounding the integration of neuroimaging and genetics, discuss the influence and impact of genetics consortia, and suggest statistical genetic analyses that expand the repertoire of imaging researchers amassing rich behavioral data in modestly-sized samples. Specific attention is paid to the creative use of polygenic risk scoring in imaging genetic analyses, with primers on the most current risk scoring applications.

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology.

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.

Childhood trauma is associated with increased brain responses to emotionally negative as compared with positive faces in patients with psychotic disorders

BACKGROUND

Childhood trauma increases risk of a range of mental disorders including psychosis. Whereas the mechanisms are unclear, previous evidence has implicated atypical processing of emotions among the core cognitive models, in particular suggesting altered attentional allocation towards negative stimuli and increased negativity bias. Here, we tested the association between childhood trauma and brain activation during emotional face processing in patients diagnosed with psychosis continuum disorders. In particular, we tested if childhood trauma was associated with the differentiation in brain responses between negative and positive face stimuli. We also tested if trauma was associated with emotional ratings of negative and positive faces.

METHOD

We included 101 patients with a Diagnostic and Statistical Manual of Mental Disorders (DSM) schizophrenia spectrum or bipolar spectrum diagnosis. History of childhood trauma was obtained using the Childhood Trauma Questionnaire. Brain activation was measured with functional magnetic resonance imaging during presentation of faces with negative or positive emotional expressions. After the scanner session, patients performed emotional ratings of the same faces.

RESULTS

Higher levels of total childhood trauma were associated with stronger differentiation in brain responses to negative compared with positive faces in clusters comprising the right angular gyrus, supramarginal gyrus, middle temporal gyrus and the lateral occipital cortex (Cohen's d = 0.72-0.77). In patients with schizophrenia, childhood trauma was associated with reporting negative faces as more negative, and positive faces as less positive (Cohen's d > 0.8).

CONCLUSIONS

Along with the observed negativity bias in the assessment of emotional valence of faces, our data suggest stronger differentiation in brain responses between negative and positive faces with higher levels of trauma.

Contribution of oxytocin receptor polymorphisms to amygdala activation in schizophrenia spectrum disorders

BACKGROUND

Oxytocin has been proposed to mediate amygdala dysfunction associated with altered emotion processing in schizophrenia, but the contribution of oxytocin pathway genes is yet to be investigated.

AIMS

To identify potential different contributions of three oxytocin receptor polymorphisms (rs53576, rs237902 and rs2254298) between patients with schizophrenia spectrum disorders (SCZ), affective spectrum disorders (AD) and healthy controls (HC).

METHOD

In a total of 346 participants (104 with SCZ, 100 with AD, and 142 HC) underwent genotyping and functional magnetic resonance imaging (fMRI) during an emotional faces matching paradigm. Genetic association analyses were performed to test the possible effects on task-induced BOLD amygdala response to fearful/angry faces.

RESULTS

In participants with SCZ, the rs237902 G allele was associated with low amygdala activation (left hemisphere: b=-4.99, Bonferroni corrected P=0.04) and interaction analyses showed that this association was disorder specific (left hemisphere: Bonferroni corrected P=0.003; right hemisphere: Bonferroni corrected P=0.03). There were no associations between oxytocin polymorphisms and amygdala activation in the total sample, among AD patients or HC.

CONCLUSIONS

Rs237902 was associated with amygdala activation in response to fearful/angry faces only in patients with SCZ. Our findings indicate that the endogenous oxytocin system could serve as a contributing factor in biological underpinnings of emotion processing and that this contribution is disorder specific.

DECLARATION OF INTEREST

O.A.A. received speaker's honoraria from GSK, Otsuka, Lundbeck.

COPYRIGHT AND USAGE

© The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

Random Projection for Fast and Efficient Multivariate Correlation Analysis of High-Dimensional Data: A New Approach

In recent years, the advent of great technological advances has produced a wealth of very high-dimensional data, and combining high-dimensional information from multiple sources is becoming increasingly important in an extending range of scientific disciplines. Partial Least Squares Correlation (PLSC) is a frequently used method for multivariate multimodal data integration. It is, however, computationally expensive in applications involving large numbers of variables, as required, for example, in genetic neuroimaging. To handle high-dimensional problems, dimension reduction might be implemented as pre-processing step. We propose a new approach that incorporates Random Projection (RP) for dimensionality reduction into PLSC to efficiently solve high-dimensional multimodal problems like genotype-phenotype associations. We name our new method PLSC-RP. Using simulated and experimental data sets containing whole genome SNP measures as genotypes and whole brain neuroimaging measures as phenotypes, we demonstrate that PLSC-RP is drastically faster than traditional PLSC while providing statistically equivalent results. We also provide evidence that dimensionality reduction using RP is data type independent. Therefore, PLSC-RP opens up a wide range of possible applications. It can be used for any integrative analysis that combines information from multiple sources.

Negative symptoms in schizophrenia show association with amygdala volumes and neural activation during affective processing

OBJECTIVES

Negative symptoms in schizophrenia have been associated with structural and functional alterations of the amygdala. We hypothesised that there would be between-group differences in amygdala volume and neural activation patterns during processing of affective stimuli among patients with schizophrenia and healthy controls. We further hypothesised correlations between neuroimaging metrics and clinical ratings of negative symptoms in patients with schizophrenia.

METHODS

We used structural and functional magnetic resonance imaging to assess volume and neural activation of the amygdala in 28 patients with schizophrenia and 28 healthy controls.

RESULTS

We found no between-group differences in amygdala volume or neural activation. However, we found a significant negative correlation between emotional blunting and neural activation in the left amygdala during processing of positive affect. We also found a significant negative correlation between stereotyped thinking and the volume of right amygdala.

CONCLUSION

Our findings implicate the amygdala in a subgroup of negative symptoms in schizophrenia that are characterised by reduced expression with blunted affect and stereotyped thinking.

Altered Brain Activation during Emotional Face Processing in Relation to Both Diagnosis and Polygenic Risk of Bipolar Disorder

Objectives

Bipolar disorder (BD) is a highly heritable disorder with polygenic inheritance. Among the most consistent findings from functional magnetic imaging (fMRI) studies are limbic hyperactivation and dorsal hypoactivation. However, the relation between reported brain functional abnormalities and underlying genetic risk remains elusive. This is the first cross-sectional study applying a whole-brain explorative approach to investigate potential influence of BD case-control status and polygenic risk on brain activation.

Methods

A BD polygenic risk score (PGRS) was estimated from the Psychiatric Genomics Consortium BD case-control study, and assigned to each individual in our independent sample (N=85 BD cases and 121 healthy controls (HC)), all of whom participated in an fMRI emotional faces matching paradigm. Potential differences in BOLD response across diagnostic groups were explored at whole-brain level in addition to amygdala as a region of interest. Putative effects of BD PGRS on brain activation were also investigated.

Results

At whole-brain level, BD cases presented with significantly lower cuneus/precuneus activation than HC during negative face processing (Z-threshold=2.3 as cluster-level correction). The PGRS was associated positively with increased right inferior frontal gyrus (rIFG) activation during negative face processing. For amygdala activation, there were no correlations with diagnostic status or PGRS.

Conclusions

These findings are in line with previous reports of reduced precuneus and altered rIFG activation in BD. While these results demonstrate the ability of PGRS to reveal underlying genetic risk of altered brain activation in BD, the lack of convergence of effects at diagnostic and PGRS level suggests that this relation is a complex one.

A genome-wide linkage and association study of musical aptitude identifies loci containing genes related to inner ear development and neurocognitive functions

Humans have developed the perception, production and processing of sounds into the art of music. A genetic contribution to these skills of musical aptitude has long been suggested. We performed a genome-wide scan in 76 pedigrees (767 individuals) characterized for the ability to discriminate pitch (SP), duration (ST) and sound patterns (KMT), which are primary capacities for music perception. Using the Bayesian linkage and association approach implemented in program package KELVIN, especially designed for complex pedigrees, several single nucleotide polymorphisms (SNPs) near genes affecting the functions of the auditory pathway and neurocognitive processes were identified. The strongest association was found at 3q21.3 (rs9854612) with combined SP, ST and KMT test scores (COMB). This region is located a few dozen kilobases upstream of the GATA binding protein 2 (GATA2) gene. GATA2 regulates the development of cochlear hair cells and the inferior colliculus (IC), which are important in tonotopic mapping. The highest probability of linkage was obtained for phenotype SP at 4p14, located next to the region harboring the protocadherin 7 gene, PCDH7. Two SNPs rs13146789 and rs13109270 of PCDH7 showed strong association. PCDH7 has been suggested to play a role in cochlear and amygdaloid complexes. Functional class analysis showed that inner ear and schizophrenia-related genes were enriched inside the linked regions. This study is the first to show the importance of auditory pathway genes in musical aptitude.

Comparison of variants of canonical correlation analysis and partial least squares for combined analysis of MRI and genetic data

The standard analysis approach in neuroimaging genetics studies is the mass-univariate linear modeling (MULM) approach. From a statistical view, however, this approach is disadvantageous, as it is computationally intensive, cannot account for complex multivariate relationships, and has to be corrected for multiple testing. In contrast, multivariate methods offer the opportunity to include combined information from multiple variants to discover meaningful associations between genetic and brain imaging data. We assessed three multivariate techniques, partial least squares correlation (PLSC), sparse canonical correlation analysis (sparse CCA) and Bayesian inter-battery factor analysis (Bayesian IBFA), with respect to their ability to detect multivariate genotype-phenotype associations. Our goal was to systematically compare these three approaches with respect to their performance and to assess their suitability for high-dimensional and multi-collinearly dependent data as is the case in neuroimaging genetics studies. In a series of simulations using both linearly independent and multi-collinear data, we show that sparse CCA and PLSC are suitable even for very high-dimensional collinear imaging data sets. Among those two, the predictive power was higher for sparse CCA when voxel numbers were below 400 times sample size and candidate SNPs were considered. Accordingly, we recommend Sparse CCA for candidate phenotype, candidate SNP studies. When voxel numbers exceeded 500 times sample size, the predictive power was the highest for PLSC. Therefore, PLSC can be considered a promising technique for multivariate modeling of high-dimensional brain-SNP-associations. In contrast, Bayesian IBFA cannot be recommended, since additional post-processing steps were necessary to detect causal relations. To verify the applicability of sparse CCA and PLSC, we applied them to an experimental imaging genetics data set provided for us. Most importantly, application of both methods replicated the findings of this data set.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

A translational neuroscience framework for the development of socioemotional functioning in health and psychopathology

The development of socioemotional functioning is a complex process that occurs over a protracted time period and requires coordinating affective, cognitive, and social faculties. At many points in development, the trajectory of socioemotional development can be deleteriously altered due to a combination of environmental insults and individual vulnerabilities. The result can be psychopathology. However, researchers are just beginning to understand the neural and genetic mechanisms involved in the development of healthy and disordered socioemotional functioning. We propose a translational developmental neuroscience framework to understand the transactional process that results in socioemotional functioning in both healthy and disordered populations. We then apply this framework to healthy socioemotional development, pediatric anxiety, pediatric depression, and autism spectrum disorder, selectively reviewing current literature in light of the framework. Finally, we examine ways that the framework can help to frame future directions of research on socioemotional development and translational implications for intervention.

Genetics of the connectome

Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods--such as genome-wide association studies (GWAS), linkage and candidate gene studies--that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity.

Pathway analysis of genetic markers associated with a functional MRI faces paradigm implicates polymorphisms in calcium responsive pathways

Several lines of evidence suggest that common polygenic variation influences brain function in humans. Combining high-density genetic markers with brain imaging techniques is constricted by the practicalities of collecting sufficiently large brain imaging samples. Pathway analysis promises to leverage knowledge on function of genes to detect recurring signals of moderate effect. We adapt this approach, exploiting the deep information collected on brain function by fMRI methods, to identify molecular pathways containing genetic variants which influence brain activation during a commonly applied experiment based on a face matching task (n=246) which was developed to study neural processing of faces displaying negative emotions. Genetic markers moderately associated (p<10(-4)) with whole brain activation phenotypes constructed by applying principal components to contrast maps, were tested for pathway enrichment using permutation based methods. The most significant pathways are related to post NMDA receptor activation events, driven by genetic variants in calcium/calmodulin-dependent protein kinase II (CAMK2G, CAMK2D) and a calcium-regulated nucleotide exchange factor (RASGRF2) in which all are activated by intracellular calcium/calmodulin. The most significant effect of the combined polygenic model were localized to the left inferior frontal gyrus (p=1.03 × 10(-9)), a region primarily involved in semantic processing but also involved in processing negative emotions. These findings suggest that pathway analysis of GWAS results derived from principal component analysis of fMRI data is a promising method, to our knowledge, not previously described.