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- The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders (2017)
- Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.
- Genome-wide analysis of rare copy number variations reveals PARK2 as a candidate gene for attention-deficit/hyperactivity disorder (2012)
- Attention-deficit/hyperactivity disorder (ADHD) is a common, highly heritable neurodevelopmental disorder. Genetic loci have not yet been identified by genome-wide association studies. Rare copy number variations (CNVs), such as chromosomal deletions or duplications, have been implicated in ADHD and other neurodevelopmental disorders. To identify rare (frequency ≤1%) CNVs that increase the risk of ADHD, we performed a whole-genome CNV analysis based on 489 young ADHD patients and 1285 adult population-based controls and identified one significantly associated CNV region. In tests for a global burden of large (>500 kb) rare CNVs, we observed a nonsignificant (P=0.271) 1.126-fold enriched rate of subjects carrying at least one such CNV in the group of ADHD cases. Locus-specific tests of association were used to assess if there were more rare CNVs in cases compared with controls. Detected CNVs, which were significantly enriched in the ADHD group, were validated by quantitative (q)PCR. Findings were replicated in an independent sample of 386 young patients with ADHD and 781 young population-based healthy controls. We identified rare CNVs within the parkinson protein 2 gene (PARK2) with a significantly higher prevalence in ADHD patients than in controls (P=2.8 × 10(-4) after empirical correction for genome-wide testing). In total, the PARK2 locus (chr 6: 162 659 756-162 767 019) harboured three deletions and nine duplications in the ADHD patients and two deletions and two duplications in the controls. By qPCR analysis, we validated 11 of the 12 CNVs in ADHD patients (P=1.2 × 10(-3) after empirical correction for genome-wide testing). In the replication sample, CNVs at the PARK2 locus were found in four additional ADHD patients and one additional control (P=4.3 × 10(-2)). Our results suggest that copy number variants at the PARK2 locus contribute to the genetic susceptibility of ADHD. Mutations and CNVs in PARK2 are known to be associated with Parkinson disease.
- Identification of shared risk loci and pathways for bipolar disorder and schizophrenia (2017)
- Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. BD shows substantial clinical and genetic overlap with other psychiatric disorders, in particular schizophrenia (SCZ). The genes underlying this etiological overlap remain largely unknown. A recent SCZ genome wide association study (GWAS) by the Psychiatric Genomics Consortium identified 128 independent genome-wide significant single nucleotide polymorphisms (SNPs). The present study investigated whether these SCZ-associated SNPs also contribute to BD development through the performance of association testing in a large BD GWAS dataset (9747 patients, 14278 controls). After re-imputation and correction for sample overlap, 22 of 107 investigated SCZ SNPs showed nominal association with BD. The number of shared SCZ-BD SNPs was significantly higher than expected (p = 1.46x10-8). This provides further evidence that SCZ-associated loci contribute to the development of BD. Two SNPs remained significant after Bonferroni correction. The most strongly associated SNP was located near TRANK1, which is a reported genome-wide significant risk gene for BD. Pathway analyses for all shared SCZ-BD SNPs revealed 25 nominally enriched gene-sets, which showed partial overlap in terms of the underlying genes. The enriched gene-sets included calcium- and glutamate signaling, neuropathic pain signaling in dorsal horn neurons, and calmodulin binding. The present data provide further insights into shared risk loci and disease-associated pathways for BD and SCZ. This may suggest new research directions for the treatment and prevention of these two major psychiatric disorders.
- Associative memory impairments are associated with functional alterations within the memory network in schizophrenia patients and their unaffected first-degree relatives : an fMRI study (2019)
- Memory impairments are a major characteristic of schizophrenia (SZ). In the current study, we used an associative memory task to test the hypothesis that SZ patients and first-degree relatives have altered functional patterns in comparison to healthy controls. We analyzed the fMRI activation pattern during the presentation of a face-name task in 27 SZ patients, 23 first-degree relatives, and 27 healthy controls. In addition, we performed correlation analyses between individual psychopathology, accuracy and reaction time of the task and the beta scores of the functional brain activations. We observed a lower response accuracy and increased reaction time during the retrieval of face-name pairs in SZ patients compared with controls. Deficient performance was accompanied by abnormal functional activation patterns predominantly in DMN regions during encoding and retrieval. No significant correlation between individual psychopathology and neuronal activation during encoding or retrieval of face-name pairs was observed. Findings of first-degree relatives indicated slightly different functional pattern within brain networks in contrast to controls without significant differences in the behavioral task. Both the accuracy of memory performance as well as the functional activation pattern during retrieval revealed alterations in SZ patients, and, to a lesser degree, in relatives. The results are of potential relevance for integration within a comprehensive model of memory function in SZ. The development of a neurophysiological model of cognition in psychosis may help to clarify and improve therapeutic options to improve memory and functioning in the illness.
- A data science-based analysis points at distinct patterns of lipid mediator plasma concentrations in patients with dementia (2019)
- Based on accumulating evidence of a role of lipid signaling in many physiological and pathophysiological processes including psychiatric diseases, the present data driven analysis was designed to gather information needed to develop a prospective biomarker, using a targeted lipidomics approach covering different lipid mediators. Using unsupervised methods of data structure detection, implemented as hierarchal clustering, emergent self-organizing maps of neuronal networks, and principal component analysis, a cluster structure was found in the input data space comprising plasma concentrations of d = 35 different lipid-markers of various classes acquired in n = 94 subjects with the clinical diagnoses depression, bipolar disorder, ADHD, dementia, or in healthy controls. The structure separated patients with dementia from the other clinical groups, indicating that dementia is associated with a distinct lipid mediator plasma concentrations pattern possibly providing a basis for a future biomarker. This hypothesis was subsequently assessed using supervised machine-learning methods, implemented as random forests or principal component analysis followed by computed ABC analysis used for feature selection, and as random forests, k-nearest neighbors, support vector machines, multilayer perceptron, and naïve Bayesian classifiers to estimate whether the selected lipid mediators provide sufficient information that the diagnosis of dementia can be established at a higher accuracy than by guessing. This succeeded using a set of d = 7 markers comprising GluCerC16:0, Cer24:0, Cer20:0, Cer16:0, Cer24:1, C16 sphinganine, and LacCerC16:0, at an accuracy of 77%. By contrast, using random lipid markers reduced the diagnostic accuracy to values of 65% or less, whereas training the algorithms with randomly permuted data was followed by complete failure to diagnose dementia, emphasizing that the selected lipid mediators were display a particular pattern in this disease possibly qualifying as biomarkers.
- Bright light therapy versus physical exercise to prevent co-morbid depression and obesity in adolescents and young adults with attention-deficit / hyperactivity disorder : study protocol for a randomized controlled trial (2018)
- Background: The risk for major depression and obesity is increased in adolescents and adults with attention-deficit / hyperactivity disorder (ADHD) and adolescent ADHD predicts adult depression and obesity. Non-pharmacological interventions to treat and prevent these co-morbidities are urgently needed. Bright light therapy (BLT) improves day–night rhythm and is an emerging therapy for major depression. Exercise intervention (EI) reduces obesity and improves depressive symptoms. To date, no randomized controlled trial (RCT) has been performed to establish feasibility and efficacy of these interventions targeting the prevention of co-morbid depression and obesity in ADHD. We hypothesize that the two manualized interventions in combination with mobile health-based monitoring and reinforcement will result in less depressive symptoms and obesity compared to treatment as usual in adolescents and young adults with ADHD. Methods: This trial is a prospective, pilot phase-IIa, parallel-group RCT with three arms (two add-on treatment groups [BLT, EI] and one treatment as usual [TAU] control group). The primary outcome variable is change in the Inventory of Depressive Symptomatology total score (observer-blinded assessment) between baseline and ten weeks of intervention. This variable is analyzed with a mixed model for repeated measures approach investigating the treatment effect with respect to all three groups. A total of 330 participants with ADHD, aged 14 – < 30 years, will be screened at the four study centers. To establish effect sizes, the sample size was planned at the liberal significance level of α = 0.10 (two-sided) and the power of 1-β = 80% in order to find medium effects. Secondary outcomes measures including change in obesity, ADHD symptoms, general psychopathology, health-related quality of life, neurocognitive function, chronotype, and physical fitness are explored after the end of the intervention and at the 12-week follow-up. Discussion: This is the first pilot RCT on the use of BLT and EI in combination with mobile health-based monitoring and reinforcement targeting the prevention of co-morbid depression and obesity in adolescents and young adults with ADHD. If at least medium effects can be established with regard to the prevention of depressive symptoms and obesity, a larger scale confirmatory phase-III trial may be warranted. Trial registration: German Clinical Trials Register, DRKS00011666. Registered on 9 February 2017. ClinicalTrials.gov, NCT03371810. Registered on 13 December 2017.
- Defective synaptic transmission causes disease signs in a mouse model of Juvenile Neuronal Ceroid Lipofuscinosis (2017)
- Juvenile neuronal ceroid lipofuscinosis (JNCL or Batten disease) caused by mutations in the CLN3 gene is the most prevalent inherited neurodegenerative disease in childhood resulting in widespread central nervous system dysfunction and premature death. The consequences of CLN3 mutation on the progression of the disease, on neuronal transmission, and on central nervous network dysfunction are poorly understood. We used Cln3 knockout (Cln3Δex1-6) mice and found increased anxiety-related behavior and impaired aversive learning as well as markedly affected motor function including disordered coordination. Patch-clamp and loose-patch recordings revealed severely affected inhibitory and excitatory synaptic transmission in the amygdala, hippocampus, and cerebellar networks. Changes in presynaptic release properties may result from dysfunction of CLN3 protein. Furthermore, loss of calbindin, neuropeptide Y, parvalbumin, and GAD65-positive interneurons in central networks collectively support the hypothesis that degeneration of GABAergic interneurons may be the cause of supraspinal GABAergic disinhibition.
- Orexin in the anxiety spectrum : association of a HCRTR1 polymorphism with panic disorder/agoraphobia, CBT treatment response and fear-related intermediate phenotypes (2019)
- 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.
- Gender differences in associations of glutamate decarboxylase 1 gene (GAD1) variants with panic disorder (2012)
- 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.
- A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy (2012)
- Pattern recognition approaches to the analysis of neuroimaging data have brought new applications such as the classification of patients and healthy controls within reach. In our view, the reliance on expensive neuroimaging techniques which are not well tolerated by many patient groups and the inability of most current biomarker algorithms to accommodate information about prior class frequencies (such as a disorder's prevalence in the general population) are key factors limiting practical application. To overcome both limitations, we propose a probabilistic pattern recognition approach based on cheap and easy-to-use multi-channel near-infrared spectroscopy (fNIRS) measurements. We show the validity of our method by applying it to data from healthy controls (n = 14) enabling differentiation between the conditions of a visual checkerboard task. Second, we show that high-accuracy single subject classification of patients with schizophrenia (n = 40) and healthy controls (n = 40) is possible based on temporal patterns of fNIRS data measured during a working memory task. For classification, we integrate spatial and temporal information at each channel to estimate overall classification accuracy. This yields an overall accuracy of 76% which is comparable to the highest ever achieved in biomarker-based classification of patients with schizophrenia. In summary, the proposed algorithm in combination with fNIRS measurements enables the analysis of sub-second, multivariate temporal patterns of BOLD responses and high-accuracy predictions based on low-cost, easy-to-use fNIRS patterns. In addition, our approach can easily compensate for variable class priors, which is highly advantageous in making predictions in a wide range of clinical neuroimaging applications. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.
