Lack of meta-analytic evidence for an impact of COMT Val158Met genotype on brain activation during working memory tasks

Impact of ZNF804A rs1344706 or CACNA1C rs1006737 polymorphisms on cognition in patients with severe mental disorders: A systematic review and meta-analysis

OBJECTIVES

This systematic review and meta-analysis focussed on insights into the relationship between CACNA1C-rs1006737 and ZNF804A-rs1344706 polymorphisms and cognitive performance in schizophrenia (SCZ) spectrum and bipolar disorder (BD) and provide some contributions for clinical practice.

METHODS

We searched the websites databases (PubMED, PsycINFO, Web of Science, EMBASE and Cochrane Library) using eligibility and exclusion criteria to capture all potential studies, based on PICO model and according to the PRISMA.

RESULTS

Eight articles were included in this systematic review (five referring to CACNA1C-rs1006737 and three related to ZNF804A-rs1344706 polymorphisms), with a total of 5759 participants (1751 SCZ patients, 348 BD patients, 3626 controls and 34 first-degree relatives). The results demonstrated that the pooled effect of CACNA1C-rs1006737 (risk difference RD = 0.08; 95% CI 0.02-0.15) was associated with altered cognitive function in patients with severe mental disorders, but not ZNF804A-rs1344706 polymorphism (RD = 0.19; 95% CI 0.09-0.48.

CONCLUSION

The present meta-analysis provides evidence regarding slight association between CACNA1C-rs1006737 polymorphisms and cognitive performance in severe mental disorders, indicating that cognitive impairment in severe mental disorders associated with the CACNA1C rs1006737 risk variants could only be expressed when interacting with environmental exposures. This study is registered with PROSPERO, number CRD42021246726.

The medial temporal lobe structure and function support positive affect

Positive affect (PA) is not only associated with individuals' psychological and physical health, but also their cognitive processes. However, whether medial temporal lobe (MTL) and its subfields' volume/functional connectivity can explain individual variability in PA remains understudied. We investigated the morphological (i.e., grey matter volume; GMV) and functional characteristics (i.e., resting-state functional connectivity; rsFC) of PA with a combination of univariate and multivariate pattern analyses (MVPA) using a large sample of participants (n = 321). We simultaneously collected the T1-weighted (n = 321), high-resolution MTL T2-weighted, and resting-state functional imaging data (n = 209). The MTL and its subfields' volumes, including the CA1, CA2+3, DG, and subiculum (SUB), perirhinal cortex (PRC), and parahippocampus (PHC), were extracted using an automatic segmentation of hippocampal subfields (ASHS) software. The morphological results revealed that GMVs in the prefrontal-occipital and limbic (i.e., hippocampus, amygdala, and PHC) systems were associated with variability in PA at the whole-brain level using MVPA but not univariate analysis. Linear regression results further revealed a positive association between the MTL subfields' GMV, especially for the right PRC, and PA after controlling for several covariates. PRC-seed-based rsFC analyses further revealed that its couplings with the fronto-parietal-occipital system predicted PA in both univariate and MVPA. These findings provide novel insights into the neuroanatomical and functional substrates underlying human PA trait. Findings also suggest critical contributions of the MTL and its subfield of the perirhinal cortex, but not hippocampal subfields, as well as its functional coupling with the fronto-parietal control-system on the formation of PA.

In search of convergent regional brain abnormality in cognitive emotion regulation: A transdiagnostic neuroimaging meta-analysis

Ineffective use of adaptive cognitive strategies (e.g., reappraisal) to regulate emotional states is often reported in a wide variety of psychiatric disorders, suggesting a common characteristic across different diagnostic categories. However, the extent of shared neurobiological impairments is incompletely understood. This study, therefore, aimed to identify the transdiagnostic neural signature of disturbed reappraisal using the coordinate‐based meta‐analysis (CBMA) approach. Following the best‐practice guidelines for conducting neuroimaging meta‐analyses, we systematically searched PubMed, ScienceDirect, and Web of Science databases and tracked the references. Out of 1,608 identified publications, 32 whole‐brain neuroimaging studies were retrieved that compared brain activation in patients with psychiatric disorders and healthy controls during a reappraisal task. Then, the reported peak coordinates of group comparisons were extracted and several activation likelihood estimation (ALE) analyses were performed at three hierarchical levels to identify the potential spatial convergence: the global level (i.e., the pooled analysis and the analyses of increased/decreased activations), the experimental‐contrast level (i.e., the analyses of grouped data based on the regulation goal, stimulus valence, and instruction rule) and the disorder‐group level (i.e., the analyses across the experimental‐contrast level focused on increasing homogeneity of disorders). Surprisingly, none of our analyses provided significant convergent findings. This CBMA indicates a lack of transdiagnostic convergent regional abnormality related to reappraisal task, probably due to the complex nature of cognitive emotion regulation, heterogeneity of clinical populations, and/or experimental and statistical flexibility of individual studies.

Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion

Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.

Structural and functional neuroimaging of late-life depression: a coordinate-based meta-analysis

Several neuroimaging studies have investigated localized aberrations in brain structure, function or connectivity in late-life depression, but the ensuing results are equivocal and often conflicting. Here, we provide a quantitative consolidation of neuroimaging in late-life depression using coordinate-based meta-analysis by searching multiple databases up to March 2020. Our search revealed 3252 unique records, among which we identified 32 eligible whole-brain neuroimaging publications comparing 674 patients with 568 controls. The peak coordinates of group comparisons between the patients and the controls were extracted and then analyzed using activation likelihood estimation method. Our sufficiently powered analysis on all the experiments, and more homogenous subsections of the data (patients > controls, controls > patients, and functional imaging experiments) revealed no significant convergent regional abnormality in late-life depression. This inconsistency might be due to clinical and biological heterogeneity of LLD, as well as experimental (e.g., choice of tasks, image modalities) and analytic flexibility (e.g., preprocessing and analytic parameters), and distributed patterns of neural abnormalities. Our findings highlight the importance of clinical/biological heterogeneity of late-life depression, in addition to the need for more reproducible research by using pre-registered and standardized protocols on more homogenous populations to identify potential consistent brain abnormalities in late-life depression.

Balance between Transmitter Availability and Dopamine D2 Receptors in Prefrontal Cortex Influences Memory Functioning

Insufficient or excessive dopaminergic tone impairs cognitive performance. We examine whether the balance between transmitter availability and dopamine (DA) D2 receptors (D2DRs) is important for successful memory performance in a large sample of adults (n = 175, 64-68 years). The Catechol-O-Methyltransferase polymorphism served as genetic proxy for endogenous prefrontal DA availability, and D2DRs in dorsolateral prefrontal cortex (dlPFC) were measured with [11C]raclopride-PET. Individuals for whom D2DR status matched DA availability showed higher levels of episodic and working-memory performance than individuals with insufficient or excessive DA availability relative to the number of receptors. A similar pattern restricted to episodic memory was observed for D2DRs in caudate. Functional magnetic resonance imaging data acquired during working-memory performance confirmed the importance of a balanced DA system for load-dependent brain activity in dlPFC. Our data suggest that the inverted-U-shaped function relating DA signaling to cognition is modulated by a dynamic association between DA availability and receptor status.

Dopaminergic modulation of regional cerebral blood flow: An arterial spin labelling study of genetic and pharmacological manipulation of COMT activity

Dopamine has direct and complex vasoactive effects on cerebral circulation. Catechol-O-methyltransferase (COMT) regulates cortical dopamine, and its activity can be influenced both genetically and pharmacologically. COMT activity influences the functional connectivity of the PFC at rest, as well as its activity during task performance, determined using blood oxygen level-dependent (BOLD) fMRI. However, its effects on cerebral perfusion have been relatively unexplored. Here, 76 healthy males, homozygous for the functional COMT Val¹⁵⁸Met polymorphism, were administered either the COMT inhibitor tolcapone or placebo in a double-blind, randomised design. We then assessed regional cerebral blood flow at rest using pulsed arterial spin labelling. Perfusion was affected by both genotype and drug. COMT genotype affected frontal regions (Val¹⁵⁸ > Met¹⁵⁸), whilst tolcapone influenced parietal and temporal regions (placebo > tolcapone). There was no genotype by drug interaction. Our data demonstrate that lower COMT activity is associated with lower cerebral blood flow, although the regions affected differ between those affected by genotype compared with those altered by acute pharmacological inhibition. The results extend the evidence for dopaminergic modulation of cerebral blood flow. Our findings also highlight the importance of considering vascular effects in functional neuroimaging studies, and of exercising caution in ascribing group differences in BOLD signal solely to altered neuronal activity if information about regional perfusion is not available.

Platelet MAO activity and COMT Val158Met genotype interaction predicts visual working memory updating efficiency

The exact mechanism how serotonergic and dopaminergic systems relate to one another in working memory (WM) updating is unknown. Platelet monoamine oxidase (MAO) has been used as a marker for central serotonergic capacity, and catechol-O-methyltransferase (COMT) as a marker for central dopaminergic capacity. This study aimed to describe the interaction of platelet MAO activity and COMT Val158Met genotype in visual working memory updating: the ability to replace old information with new within hundreds of milliseconds. Previous studies suggest that platelet MAO activity and COMT Val158Met genotype could have an interaction effect on working memory. However, there are no studies that have directly examined the interaction of these biomarkers in WM updating. We used a 2-back updating task with facial expressions and defined updating efficiency as response times for correct responses. 455 subjects from a population representative sample were included. Mixed models were used for data analysis with an aim to study the interaction of COMT Val158Met genotype (Val/Val, Val/Met and Met/Met) and the level of MAO activity (high vs low). Education, IQ, sex, simple reaction times, and overall updating accuracy were included as covariates. We found that the effect of COMT Val158Met on updating efficiency depends on the level of platelet MAO activity. Low MAO in contrast to high MAO was associated with an increase in updating efficiency in Val/Met but a decrease in Met/Met. The results are discussed in the context of serotonin and dopamine functions in brain regions related to WM. The findings support the view that serotonin modulates dopaminergic activation in updating and contribute to understanding the role of serotonin in PFC, top-down inhibitory signals, and its interactions with dopamine in WM processes.

Brain structure changes associated with sexual orientation

Biological sex differences in brain function and structure are reliably associated with several cortico-subcortical brain regions. While sexual orientation (hetero- versus homosexuality) has been similarly linked to functional differences in several phylogenetically-old brain areas, the research on morphological brain phenotypes associated with sexual orientation is far from conclusive. We examined potential cerebral structural differences linked to sexual orientation in a group of 74 participants, including 37 men (21 homosexual) and 37 women (19 homosexual) using voxel-based morphometry (VBM). Gray matter volumes (GMV) were compared with respect to sexual orientation and biological sex across the entire sample using full factorial designs controlling for total intracranial volume, age, handedness, and education. We observed a significant effect of sexual orientation for the thalamus and precentral gyrus, with more GMV in heterosexual versus homosexual individuals, and for the putamen, with more GMV in homosexual + than heterosexual individuals. We found significant interactions between biological sex and sexual orientation, indicating that the significant effect for the putamen cluster was driven by homosexual women, whereas heterosexual women had increased precentral gyrus GMV. Heterosexual men exhibited more GMV in the thalamus than homosexual men. This study shows that sexual orientation is reflected in brain structure characteristics and that these differ between the sexes. The results emphasize the need to include or control for potential effects of participants' sexual orientation in neuroimaging studies. Furthermore, our findings provide important new insights into the brain morphology underlying sexual orientation and likely have important implications for understanding brain functions and behavior.

Identification of Common Neural Circuit Disruptions in Emotional Processing Across Psychiatric Disorders

OBJECTIVE

Disrupted emotional processing is a common feature of many psychiatric disorders. The authors investigated functional disruptions in neural circuitry underlying emotional processing across a range of tasks and across psychiatric disorders through a transdiagnostic quantitative meta-analysis of published neuroimaging data.

METHODS

A PubMed search was conducted for whole-brain functional neuroimaging findings published through May 2018 that compared activation during emotional processing tasks in patients with psychiatric disorders (including schizophrenia, bipolar or unipolar depression, anxiety, and substance use) to matched healthy control participants. Activation likelihood estimation (ALE) meta-analyses were conducted on peak voxel coordinates to identify spatial convergence.

RESULTS

The 298 experiments submitted to meta-analysis included 5,427 patients and 5,491 control participants. ALE across diagnoses and patterns of patient hyper- and hyporeactivity demonstrated abnormal activation in the amygdala, the hippocampal/parahippocampal gyri, the dorsomedial/pulvinar nuclei of the thalamus, and the fusiform gyri, as well as the medial and lateral dorsal and ventral prefrontal regions. ALE across disorders but considering directionality demonstrated patient hyperactivation in the amygdala and the hippocampal/parahippocampal gyri. Hypoactivation was found in the medial and lateral prefrontal regions, most pronounced during processing of unpleasant stimuli. More refined disorder-specific analyses suggested that these overall patterns were shared to varying degrees, with notable differences in patterns of hyper- and hypoactivation.

CONCLUSIONS

These findings demonstrate a pattern of neurocircuit disruption across major psychiatric disorders in regions and networks key to adaptive emotional reactivity and regulation. More specifically, disruption corresponded prominently to the "salience" network, the ventral striatal/ventromedial prefrontal "reward" network, and the lateral orbitofrontal "nonreward" network. Consistent with the Research Domain Criteria initiative, these findings suggest that psychiatric illness may be productively formulated as dysfunction in transdiagnostic neurobehavioral phenotypes such as neurocircuit activation.

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity

BACKGROUND

Genetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.

METHODS

In this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.

RESULTS

In the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).

CONCLUSIONS

This study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training.

Practical recommendations to conduct a neuroimaging meta-analysis for neuropsychiatric disorders

Over the past decades, neuroimaging has become widely used to investigate structural and functional brain abnormality in neuropsychiatric disorders. The results of individual neuroimaging studies, however, are frequently inconsistent due to small and heterogeneous samples, analytical flexibility, and publication bias toward positive findings. To consolidate the emergent findings toward clinically useful insight, meta-analyses have been developed to integrate the results of studies and identify areas that are consistently involved in pathophysiology of particular neuropsychiatric disorders. However, it should be considered that the results of meta-analyses could also be divergent due to heterogeneity in search strategy, selection criteria, imaging modalities, behavioral tasks, number of experiments, data organization methods, and statistical analysis with different multiple comparison thresholds. Following an introduction to the problem and the concepts of quantitative summaries of neuroimaging findings, we propose practical recommendations for clinicians and researchers for conducting transparent and methodologically sound neuroimaging meta-analyses. This should help to consolidate the search for convergent regional brain abnormality in neuropsychiatric disorders.

Development of dopaminergic genetic associations with visuospatial, verbal and social working memory

Dopamine transmission in the prefrontal cortex (PFC) supports working memory (WM), the temporary holding, processing and manipulation of information in one's mind. The gene coding the catechol-O-methyltransferase (COMT) enzyme, which degrades dopamine, in particular in the PFC, has a common single nucleotide polymorphism leading to two versions of the COMT enzyme which vary in their enzymatic activity. The methionine (Met) allele has been associated with higher WM performance and lower activation of the PFC in executive function tasks than the valine (Val) allele. In a previous study, COMT genotype was associated with performance on verbal and visuospatial WM tasks in adults, as well as with performance on a novel social WM paradigm that requires participants to maintain and manipulate information about the traits of their friends or family over a delay. Here, data collected in children and adolescents (N = 202) were compared to data from the adult sample (N = 131) to investigate possible age differences in genetic associations. Our results replicate and extend previous work showing that the pattern of superior WM performance observed in Met/Met adults emerges during development. These findings are consistent with a decrease in prefrontal dopamine levels during adolescence. Developmentally moderated genetic effects were observed for both visuospatial and social WM, even when controlling for non-social WM performance, suggesting that the maintenance and manipulation of social information may also recruit the dopamine neurotransmitter system. These findings show that development should be considered when trying to understand the impact of genetic polymorphisms on cognitive function.

Strategies for integrated analysis in imaging genetics studies

Imaging Genetics (IG) integrates neuroimaging and genomic data from the same individual, deepening our knowledge of the biological mechanisms behind neurodevelopmental domains and neurological disorders. Although the literature on IG has exponentially grown over the past years, the majority of studies have mainly analyzed associations between candidate brain regions and individual genetic variants. However, this strategy is not designed to deal with the complexity of neurobiological mechanisms underlying behavioral and neurodevelopmental domains. Moreover, larger sample sizes and increased multidimensionality of this type of data represents a challenge for standardizing modeling procedures in IG research. This review provides a systematic update of the methods and strategies currently used in IG studies, and serves as an analytical framework for researchers working in this field. To complement the functionalities of the Neuroconductor framework, we also describe existing R packages that implement these methodologies. In addition, we present an overview of how these methodological approaches are applied in integrating neuroimaging and genetic data.

Using coordinate-based meta-analyses to explore structural imaging genetics

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Maternal deprivation induces alterations in cognitive and cortical function in adulthood

Early life trauma is a risk factor for a number of neuropsychiatric disorders, including schizophrenia (SZ). The current study assessed how an early life traumatic event, maternal deprivation (MD), alters cognition and brain function in rodents. Rats were maternally deprived in the early postnatal period and then recognition memory (RM) was tested in adulthood using the novel object recognition task. The expression of catechol-o-methyl transferase (COMT) and glutamic acid decarboxylase (GAD67) were quantified in the medial prefrontal cortex (mPFC), ventral striatum, and temporal cortex (TC). In addition, depth EEG recordings were obtained from the mPFC, vertex, and TC during a paired-click paradigm to assess the effects of MD on sensory gating. MD animals exhibited impaired RM, lower expression of COMT in the mPFC and TC, and lower expression of GAD67 in the TC. Increased bioelectric noise was observed at each recording site of MD animals. MD animals also exhibited altered information theoretic measures of stimulus encoding. These data indicate that a neurodevelopmental perturbation yields persistent alterations in cognition and brain function, and are consistent with human studies that identified relationships between allelic differences in COMT and GAD67 and bioelectric noise. These changes evoked by MD also lead to alterations in shared information between cognitive and primary sensory processing areas, which provides insight into how early life trauma confers a risk for neurodevelopmental disorders, such as SZ, later in life.

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.

Sex-specific effects of COMT Val158Met polymorphism on corpus callosum structure: A whole-brain diffusion-weighted imaging study

BACKGROUND

Genetic polymorphisms play a significant role in determining brain morphology, including white matter structure and may thus influence the development of brain functions. The main objective of this study was to examine the effect of Val158Met (rs4680) polymorphism of Catechol-O-Methyltransferase (COMT) gene on white matter connectivity in healthy adults.

METHODS

We used a whole-brain diffusion-weighted imaging method with Tract-Based Spatial Statistics (TBSS) analysis to examine white matter structural integrity in intrinsic brain networks on a sample of healthy subjects (N = 82).

RESULTS

Results revealed a sex-specific effect of COMT on corpus callosum (CC): in males only, Val homozygotes had significantly higher fractional anisotropy (FA) compared to Met-carriers. Volume-of-interest analysis showed a genotype by sex interaction on FA in genu and rostral midbody of CC, whereby Val males demonstrated higher FA than Met females.

CONCLUSIONS

These results demonstrate the key effect of genes by sex interaction, rather than their individual contribution, on the corpus callosum anatomy.

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.

COMT Val(158) Met genotype is associated with reward learning: a replication study and meta-analysis

Identifying mechanisms through which individual differences in reward learning emerge offers an opportunity to understand both a fundamental form of adaptive responding as well as etiological pathways through which aberrant reward learning may contribute to maladaptive behaviors and psychopathology. One candidate mechanism through which individual differences in reward learning may emerge is variability in dopaminergic reinforcement signaling. A common functional polymorphism within the catechol-O-methyl transferase gene (COMT; rs4680, Val(158) Met) has been linked to reward learning, where homozygosity for the Met allele (linked to heightened prefrontal dopamine function and decreased dopamine synthesis in the midbrain) has been associated with relatively increased reward learning. Here, we used a probabilistic reward learning task to asses response bias, a behavioral form of reward learning, across three separate samples that were combined for analyses (age: 21.80 ± 3.95; n = 392; 268 female; European-American: n = 208). We replicate prior reports that COMT rs4680 Met allele homozygosity is associated with increased reward learning in European-American participants (β = 0.20, t = 2.75, P < 0.01; ΔR(2) = 0.04). Moreover, a meta-analysis of 4 studies, including the current one, confirmed the association between COMT rs4680 genotype and reward learning (95% CI -0.11 to -0.03; z = 3.2; P < 0.01). These results suggest that variability in dopamine signaling associated with COMT rs4680 influences individual differences in reward which may potentially contribute to psychopathology characterized by reward dysfunction.

COMT Val(158)Met Polymorphism Is Associated with Verbal Working Memory in Neurofibromatosis Type 1

Neurofibromatosis type I (NF1) is a neurogenetic disease marked by multiple cognitive and learning problems. Genetic variants may account for phenotypic variance in NF1. Here, we investigated the association between the catechol-O-methyltransferase (COMT) Val(158)Met polymorphism and working memory and arithmetic performance in 50 NF1 individuals. A significant association of the COMT polymorphism was observed only with verbal working memory, as measured by the backward digit-span task with an advantageous performance for Met/Met carriers. To study how genetic modifiers influence NF1 cognitive performance might be of importance to decrease the unpredictability of the cognitive profile among NF1 patients.

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis.

Genetics of cognitive control: Implications for Nimh's research domain criteria initiative

Cognitive control refers to a set of mental processes that modulate other cognitive and emotional systems in service of goal-directed adaptive behavior. There is growing support for the notion that cognitive control abnormalities are a central component of many of the neuropsychological deficits observed in individuals with mental illnesses, particularly those with psychotic disorders. NIMH's research domain criteria (RDoC) initiative, which is designed to develop biologically informed constructs to better understand psychopathology, designated cognitive control a construct within the cognitive systems domain. Identification of genes that influence cognitive control or its supportive brain systems will improve our understating of the RDoC construct and provide candidate genes for psychotic disorders. We examine evidence for cognitive control deficits in psychosis, determine if these measures could be useful endophenotypes, and explore work linking genetic variation to cognitive control performance. While there is a wealth of evidence to support the notion the cognitive control is a valid endophenotype for psychosis, its genetic underpinning remains ill characterized. However, existing work provides a promising foundation on which future endeavors might build. Confirming existing individual gene associations will go some way to expanding our understanding of the genetics of cognitive control, and by extension, psychotic disorders. Yet, to truly understand the molecular underpinnings of such complex traits, it may be necessary to evaluate genes in tandem, focusing not on single genes but rather on empirically derived gene sets or on functionally defined networks of genes.