Refine
Year of publication
Language
- English (15)
Has Fulltext
- yes (15)
Is part of the Bibliography
- no (15)
Keywords
- Clinical genetics (2)
- Psychiatric disorders (2)
- fMRI (2)
- Agoraphobia (1)
- Bipolar disorder (1)
- Connectivity (1)
- Diagnostic markers (1)
- Diffusion MRI (1)
- Human behaviour (1)
- Imaging genetics (1)
- Learning and memory (1)
- Molecular neuroscience (1)
- NPSR1 (1)
- Panic disorder (1)
- Parcellation (1)
- Personalized medicine (1)
- Piriform cortex (1)
- Predictive markers (1)
- Subregions (1)
- Westphal-Paradigm (1)
Institute
- Medizin (15)
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
Introduction: The neurobiological mechanisms behind panic disorder with agoraphobia (PD/AG) are not completely explored. The functional A/T single nucleotide polymorphism (SNP) rs324981 in the neuropeptide S receptor gene (NPSR1) has repeatedly been associated with panic disorder and might partly drive function respectively dysfunction of the neural “fear network”. We aimed to investigate whether the NPSR1 T risk allele was associated with malfunctioning in a fronto-limbic network during the anticipation and perception of agoraphobia-specific stimuli.
Method: 121 patients with PD/AG and 77 healthy controls (HC) underwent functional magnetic resonance imaging (fMRI) using the disorder specific “Westphal-Paradigm”. It consists of neutral and agoraphobia-specific pictures, half of the pictures were cued to induce anticipatory anxiety.
Results: Risk allele carriers showed significantly higher amygdala activation during the perception of agoraphobia-specific stimuli than A/A homozygotes. A linear group x genotype interaction during the perception of agoraphobia-specific stimuli showed a strong trend towards significance. Patients with the one or two T alleles displayed the highest and HC with the A/A genotype the lowest activation in the inferior orbitofrontal cortex (iOFC).
Discussion: The study demonstrates an association of the NPSR1rs324981 genotype and the perception of agoraphobia-specific stimuli. These results support the assumption of a fronto-limbic dysfunction as an intermediate phenotype of PD/AG.
Representing a phylogenetically old and very basic mechanism of inhibitory neurotransmission, glycine receptors have been implicated in the modulation of behavioral components underlying defensive responding toward threat. As one of the first findings being confirmed by genome-wide association studies for the phenotype of panic disorder and agoraphobia, allelic variation in a gene coding for the glycine receptor beta subunit (GLRB) has recently been associated with increased neural fear network activation and enhanced acoustic startle reflexes. On the basis of two independent healthy control samples, we here aimed to further explore the functional significance of the GLRB genotype (rs7688285) by employing an intermediate phenotype approach. We focused on the phenotype of defensive system reactivity across the levels of brain function, structure, and physiology. Converging evidence across both samples was found for increased neurofunctional activation in the (anterior) insular cortex in GLRB risk allele carriers and altered fear conditioning as a function of genotype. The robustness of GLRB effects is demonstrated by consistent findings across different experimental fear conditioning paradigms and recording sites. Altogether, findings provide translational evidence for glycine neurotransmission as a modulator of the brain’s evolutionary old dynamic defensive system and provide further support for a strong, biologically plausible candidate intermediate phenotype of defensive reactivity. As such, glycine-dependent neurotransmission may open up new avenues for mechanistic research on the etiopathogenesis of fear and anxiety disorders.
Neuronal nitric oxide synthase (NOS-I) impacts on fear/anxiety-like behavior in animals. In humans, the short (S) allele of a functional promotor polymorphism of NOS1 (NOS1 ex1f-VNTR) has been shown to be associated with higher anxiety and altered fear conditioning in healthy subjects in the amygdala and hippocampus (AMY/HIPP). Here, we explore the role of NOS1 ex1f-VNTR as a pathophysiological correlate of panic disorder and agoraphobia (PD/AG). In a sub-sample of a multicenter cognitive behavioral therapy (CBT) randomized controlled trial in patients with PD/AG (n = 48: S/S-genotype n=15, S/L-genotype n=21, L/L-genotype n=12) and healthy control subjects, HS (n = 34: S/S-genotype n=7, S/L-genotype n=17, L/L-genotype=10), a differential fear conditioning and extinction fMRI-paradigm was used to investigate how NOS1 ex1f-VNTR genotypes are associated with differential neural activation in AMY/HIPP. Prior to CBT, L/L-allele carriers showed higher activation than S/S-allele carriers in AMY/HIPP. A genotype × diagnosis interaction revealed that the S-allele in HS was associated with a pronounced deactivation in AMY/HIPP, while patients showed contrary effects. The interaction of genotype × stimulus type (CS+, conditioned stimulus associated with an aversive stimulus vs. CS-, unassociated) showed effects on differential learning in AMY/HIPP. All effects were predominately found during extinction. Genotype associated effects in patients were not altered after CBT. Low statistical power due to small sample size in each subgroup is a major limitation. However, our findings provide first preliminary evidence for dysfunctional neural fear conditioning/extinction associated with NOS1 ex1f-VNTR genotype in the context of PD/AG, shedding new light on the complex interaction between genetic risk, current psychopathology and treatment-related effects.
Increased sympathetic noradrenergic signaling is crucially involved in fear and anxiety as defensive states. MicroRNAs regulate dynamic gene expression during synaptic plasticity and genetic variation of microRNAs modulating noradrenaline transporter gene (SLC6A2) expression may thus lead to altered central and peripheral processing of fear and anxiety. In silico prediction of microRNA regulation of SLC6A2 was confirmed by luciferase reporter assays and identified hsa-miR-579-3p as a regulating microRNA. The minor (T)-allele of rs2910931 (MAFcases = 0.431, MAFcontrols = 0.368) upstream of MIR579 was associated with panic disorder in patients (pallelic = 0.004, ncases = 506, ncontrols = 506) and with higher trait anxiety in healthy individuals (pASI = 0.029, pACQ = 0.047, n = 3112). Compared to the major (A)-allele, increased promoter activity was observed in luciferase reporter assays in vitro suggesting more effective MIR579 expression and SLC6A2 repression in vivo (p = 0.041). Healthy individuals carrying at least one (T)-allele showed a brain activation pattern suggesting increased defensive responding and sympathetic noradrenergic activation in midbrain and limbic areas during the extinction of conditioned fear. Panic disorder patients carrying two (T)-alleles showed elevated heart rates in an anxiety-provoking behavioral avoidance test (F(2, 270) = 5.47, p = 0.005). Fine-tuning of noradrenaline homeostasis by a MIR579 genetic variation modulated central and peripheral sympathetic noradrenergic activation during fear processing and anxiety. This study opens new perspectives on the role of microRNAs in the etiopathogenesis of anxiety disorders, particularly their cardiovascular symptoms and comorbidities.
Epigenetic signatures such as methylation of the monoamine oxidase A (MAOA) gene have been found to be altered in panic disorder (PD). Hypothesizing temporal plasticity of epigenetic processes as a mechanism of successful fear extinction, the present psychotherapy-epigenetic study for we believe the first time investigated MAOA methylation changes during the course of exposure-based cognitive behavioral therapy (CBT) in PD. MAOA methylation was compared between N=28 female Caucasian PD patients (discovery sample) and N=28 age- and sex-matched healthy controls via direct sequencing of sodium bisulfite-treated DNA extracted from blood cells. MAOA methylation was furthermore analyzed at baseline (T0) and after a 6-week CBT (T1) in the discovery sample parallelized by a waiting time in healthy controls, as well as in an independent sample of female PD patients (N=20). Patients exhibited lower MAOA methylation than healthy controls (P<0.001), and baseline PD severity correlated negatively with MAOA methylation (P=0.01). In the discovery sample, MAOA methylation increased up to the level of healthy controls along with CBT response (number of panic attacks; T0–T1: +3.37±2.17%), while non-responders further decreased in methylation (−2.00±1.28%; P=0.001). In the replication sample, increases in MAOA methylation correlated with agoraphobic symptom reduction after CBT (P=0.02–0.03). The present results support previous evidence for MAOA hypomethylation as a PD risk marker and suggest reversibility of MAOA hypomethylation as a potential epigenetic correlate of response to CBT. The emerging notion of epigenetic signatures as a mechanism of action of psychotherapeutic interventions may promote epigenetic patterns as biomarkers of lasting extinction effects.
Preclinical studies point to a pivotal role of the orexin 1 (OX1) receptor in arousal and fear learning and therefore suggest the HCRTR1 gene as a prime candidate in panic disorder (PD) with/without agoraphobia (AG), PD/AG treatment response, and PD/AG-related intermediate phenotypes. Here, a multilevel approach was applied to test the non-synonymous HCRTR1 C/T Ile408Val gene variant (rs2271933) for association with PD/AG in two independent case-control samples (total n = 613 cases, 1839 healthy subjects), as an outcome predictor of a six-weeks exposure-based cognitive behavioral therapy (CBT) in PD/AG patients (n = 189), as well as with respect to agoraphobic cognitions (ACQ) (n = 483 patients, n = 2382 healthy subjects), fMRI alerting network activation in healthy subjects (n = 94), and a behavioral avoidance task in PD/AG pre- and post-CBT (n = 271). The HCRTR1 rs2271933 T allele was associated with PD/AG in both samples independently, and in their meta-analysis (p = 4.2 × 10−7), particularly in the female subsample (p = 9.8 × 10−9). T allele carriers displayed a significantly poorer CBT outcome (e.g., Hamilton anxiety rating scale: p = 7.5 × 10−4). The T allele count was linked to higher ACQ sores in PD/AG and healthy subjects, decreased inferior frontal gyrus and increased locus coeruleus activation in the alerting network. Finally, the T allele count was associated with increased pre-CBT exposure avoidance and autonomic arousal as well as decreased post-CBT improvement. In sum, the present results provide converging evidence for an involvement of HCRTR1 gene variation in the etiology of PD/AG and PD/AG-related traits as well as treatment response to CBT, supporting future therapeutic approaches targeting the orexin-related arousal system.
Background: Panic disorder is common (5% prevalence) and females are twice as likely to be affected as males. The heritable component of panic disorder is estimated at 48%. Glutamic acid dehydrogenase GAD1, the key enzyme for the synthesis of the inhibitory and anxiolytic neurotransmitter GABA, is supposed to influence various mental disorders, including mood and anxiety disorders. In a recent association study in depression, which is highly comorbid with panic disorder, GAD1 risk allele associations were restricted to females.
Methodology/Principal Findings: Nineteen single nucleotide polymorphisms (SNPs) tagging the common variation in GAD1 were genotyped in two independent gender and age matched case-control samples (discovery sample n = 478; replication sample n = 584). Thirteen SNPs passed quality control and were examined for gender-specific enrichment of risk alleles associated with panic disorder by using logistic regression including a genotype×gender interaction term. The latter was found to be nominally significant for four SNPs (rs1978340, rs3762555, rs3749034, rs2241165) in the discovery sample; of note, the respective minor/risk alleles were associated with panic disorder only in females. These findings were not confirmed in the replication sample; however, the genotype×gender interaction of rs3749034 remained significant in the combined sample. Furthermore, this polymorphism showed a nominally significant association with the Agoraphobic Cognitions Questionnaire sum score.
Conclusions/Significance: The present study represents the first systematic evaluation of gender-specific enrichment of risk alleles of the common SNP variation in the panic disorder candidate gene GAD1. Our tentative results provide a possible explanation for the higher susceptibility of females to panic disorder.
Background: It has been demonstrated that cognitive behavioural therapy (CBT) has a moderate effect on symptom reduction and on general well being of patients suffering from psychosis. However, questions regarding the specific efficacy of CBT, the treatment safety, the cost-effectiveness, and the moderators and mediators of treatment effects are still a major issue. The major objective of this trial is to investigate whether CBT is specifically efficacious in reducing positive symptoms when compared with non-specific supportive therapy (ST) which does not implement CBT-techniques but provides comparable therapeutic attention. Methods: The POSITIVE study is a multicenter, prospective, single-blind, parallel group, randomised clinical trial, comparing CBT and ST with respect to the efficacy in reducing positive symptoms in psychotic disorders. CBT as well as ST consist of 20 sessions altogether, 165 participants receiving CBT and 165 participants receiving ST. Major methodological aspects of the study are systematic recruitment, explicit inclusion criteria, reliability checks of assessments with control for rater shift, analysis by intention to treat, data management using remote data entry, measures of quality assurance (e.g. on-site monitoring with source data verification, regular query process), advanced statistical analysis, manualized treatment, checks of adherence and competence of therapists. Research relating the psychotherapy process with outcome, neurobiological research addressing basic questions of delusion formation using fMRI and neuropsychological assessment and treatment research investigating adaptations of CBT for adolescents is combined in this network. Problems of transfer into routine clinical care will be identified and addressed by a project focusing on cost efficiency. Discussion: This clinical trial is part of efforts to intensify psychotherapy research in the field of psychosis in Germany, to contribute to the international discussion on psychotherapy in psychotic disorders, and to help implement psychotherapy in routine care. Furthermore, the study will allow drawing conclusions about the mediators of treatment effects of CBT of psychotic disorders. Trial Registration Current Controlled Trials ISRCTN29242879
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
A broad range of neuropsychiatric disorders are associated with alterations in macroscale brain circuitry and connectivity. Identifying consistent brain patterns underlying these disorders by means of structural and functional MRI has proven challenging, partly due to the vast number of tests required to examine the entire brain, which can lead to an increase in missed findings. In this study, we propose polyconnectomic score (PCS) as a metric designed to quantify the presence of disease-related brain connectivity signatures in connectomes. PCS summarizes evidence of brain patterns related to a phenotype across the entire landscape of brain connectivity into a subject-level score. We evaluated PCS across four brain disorders (autism spectrum disorder, schizophrenia, attention deficit hyperactivity disorder, and Alzheimer’s disease) and 14 studies encompassing ∼35,000 individuals. Our findings consistently show that patients exhibit significantly higher PCS compared to controls, with effect sizes that go beyond other single MRI metrics ([min, max]: Cohen’s d = [0.30, 0.87], AUC = [0.58, 0.73]). We further demonstrate that PCS serves as a valuable tool for stratifying individuals, for example within the psychosis continuum, distinguishing patients with schizophrenia from their first-degree relatives (d = 0.42, p = 4 x 10−3, FDR-corrected), and first-degree relatives from healthy controls (d = 0.34, p = 0.034, FDR-corrected). We also show that PCS is useful to uncover associations between brain connectivity patterns related to neuropsychiatric disorders and mental health, psychosocial factors, and body measurements.
In psychiatry, there has been a growing focus on identifying at-risk populations. For schizophrenia, these efforts have led to the development of early recognition and intervention measures. Despite a similar disease burden, the populations at risk of bipolar disorder have not been sufficiently characterized. Within the BipoLife consortium, we used magnetic resonance imaging (MRI) data from a multicenter study to assess structural gray matter alterations in N = 263 help-seeking individuals from seven study sites. We defined the risk using the EPIbipolar assessment tool as no-risk, low-risk, and high-risk and used a region-of-interest approach (ROI) based on the results of two large-scale multicenter studies of bipolar disorder by the ENIGMA working group. We detected significant differences in the thickness of the left pars opercularis (Cohen’s d = 0.47, p = 0.024) between groups. The cortex was significantly thinner in high-risk individuals compared to those in the no-risk group (p = 0.011). We detected no differences in the hippocampal volume. Exploratory analyses revealed no significant differences in other cortical or subcortical regions. The thinner cortex in help-seeking individuals at risk of bipolar disorder is in line with previous findings in patients with the established disorder and corresponds to the region of the highest effect size in the ENIGMA study of cortical alterations. Structural alterations in prefrontal cortex might be a trait marker of bipolar risk. This is the largest structural MRI study of help-seeking individuals at increased risk of bipolar disorder.
Highlights
• Piriform cortex and amgydala can be separated based on their distinct structural connectivity.
• Similar to histological findings, the connectivity of the piriform cortex suggests posterior frontal and temporal subregions.
• Subregions of the piriform cortex have distinct connectivity profiles.
• Anterior PC extended into ventrotemporal PC posteriorly, which has not been described before, requiring further investigation.
• All parcellations were made publicly available.
Abstract
The anatomy of the human piriform cortex (PC) is poorly understood. We used a bimodal connectivity-based-parcellation approach to investigate subregions of the PC and its connectional differentiation from the amygdala.
One hundred (55 % female) genetically unrelated subjects from the Human Connectome Project were included. A region of interest (ROI) was delineated bilaterally covering PC and amygdala, and functional and structural connectivity of this ROI with the whole gray matter was computed. Spectral clustering was performed to obtain bilateral parcellations at granularities of k = 2–10 clusters and combined bimodal parcellations were computed. Validity of parcellations was assessed via their mean individual-to-group similarity per adjusted rand index (ARI).
Individual-to-group similarity was higher than chance in both modalities and in all clustering solutions. The amygdala was clearly distinguished from PC in structural parcellations, and olfactory amygdala was connectionally more similar to amygdala than to PC. At higher granularities, an anterior and ventrotemporal and a posterior frontal cluster emerged within PC, as well as an additional temporal cluster at their boundary. Functional parcellations also showed a frontal piriform cluster, and similar temporal clusters were observed with less consistency. Results from bimodal parcellations were similar to the structural parcellations. Consistent results were obtained in a validation cohort.
Distinction of the human PC from the amygdala, including its olfactory subregions, is possible based on its structural connectivity alone. The canonical fronto-temporal boundary within PC was reproduced in both modalities and with consistency. All obtained parcellations are freely available.