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Attention-Deficit/Hyperactivity Disorder (ADHD) is frequently comorbid with other psychiatric disorders and also with somatic conditions, such as obesity. In addition to the clinical overlap, significant genetic correlations have been found between ADHD and obesity as well as body mass index (BMI). The biological mechanisms driving this association are largely unknown, but some candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the link between ADHD and obesity measures. Using the largest GWAS summary statistics currently available for ADHD (N=53,293), BMI (N=681,275), and obesity (N=98,697), we first tested the association of dopaminergic and circadian rhythm gene sets with each phenotype. This hypothesis-driven approach showed that the dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), while the circadian rhythm gene set was associated with BMI only (P=1.28×10−3). We then took a data-driven approach by conducting genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. This approach further supported the implication of dopaminergic signaling in the link between ADHD and obesity measures, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was significantly enriched in both the ADHD-BMI and ADHD-obesity gene-based meta-analysis results. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering the shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of preventive interventions and/or efficient treatment of these conditions.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720–10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), the circadian rhythm was associated with BMI (P=1.28×10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7×10−3; replication data P=3.9×10−2) – a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
The precise understanding of the dopaminergic (DA) system and its pharmacological modifications is crucial for diagnosis and treatment of neuropsychiatric disorders, as well as for understanding basic processes, such as motivation and reward. We probed the functional connectivity (FC) of subcortical nuclei related to the DA system according to seed regions defined according to an atlas of subcortical nuclei. We conducted a large pharmaco-fMRI study using a double-blind, placebo-controlled design, where we examined the effect of l -DOPA, a dopamine precursor, and amisulpride, a D2/D3-receptor antagonist on resting-state FC in 45 healthy young adults using a cross-over design. We examined the FC of subcortical nuclei with connection to the reward system and their reaction to opposing pharmacological probing. Amisulpride increased FC from the putamen to the precuneus and from ventral striatum to precentral gyrus. l -DOPA increased FC from the ventral tegmental area (VTA) to the insula/operculum and between ventral striatum and ventrolateral prefrontal cortex and it disrupted ventral striatal and dorsal caudate FC with the medial prefrontal cortex. In an exploratory analysis, we demonstrated that higher self-rated impulsivity goes together with a significant increase in VTA-mid-cingulate gyrus FC during l -DOPA-challenge. Therefore, our DA challenge modulated distinct large-scale subcortical connectivity networks. A dopamine-boost can increase midbrain DA nuclei connectivity to the cortex. The involvement of the VTA-cingulum connectivity in dependence of impulsivity has implications for diagnosis and therapy in disorders like ADHD.
Objective: The DIRAS2 gene is associated with ADHD, but its function is largely unknown. Thus, we aimed to explore the genes and molecular pathways affected by DIRAS2. Method: Using short hairpin RNAs, we downregulated Diras2 in murine hippocampal primary cells. Gene expression was analyzed by microarray and affected pathways were identified. We used quantitative real-time polymerase chain reaction (qPCR) to confirm expression changes and analyzed enrichment of differentially expressed genes in an ADHD GWAS (genome-wide association studies) sample. Results: Diras2 knockdown altered expression of 1,612 genes, which were enriched for biological processes involved in neurodevelopment. Expression changes were confirmed for 33 out of 88 selected genes. These 33 genes showed significant enrichment in ADHD patients in a gene-set-based analysis. Conclusion: Our findings show that Diras2 affects numerous genes and thus molecular pathways that are relevant for neurodevelopmental processes. These findings may further support the hypothesis that DIRAS2 is linked to etiological processes underlying ADHD. (J. of Att. Dis. 2021; 25(4) 572-583).
Previous research indicates that anxiety disorders are characterized by an overgeneralization of conditioned fear as compared with healthy participants. Therefore, fear generalization is considered a key mechanism for the development of anxiety disorders. However, systematic investigations on the variance in fear generalization are lacking. Therefore, the current study aims at identifying distinctive phenotypes of fear generalization among healthy participants. To this end, 1175 participants completed a differential fear conditioning phase followed by a generalization test. To identify patterns of fear generalization, we used a k-means clustering algorithm based on individual arousal generalization gradients. Subsequently, we examined the reliability and validity of the clusters and phenotypical differences between subgroups on the basis of psychometric data and markers of fear expression. Cluster analysis reliably revealed five clusters that systematically differed in mean responses, differentiation between conditioned threat and safety, and linearity of the generalization gradients, though mean response levels accounted for most variance. Remarkably, the patterns of mean responses were already evident during fear acquisition and corresponded most closely to psychometric measures of anxiety traits. The identified clusters reliably described subgroups of healthy individuals with distinct response characteristics in a fear generalization test. Following a dimensional view of psychopathology, these clusters likely delineate risk factors for anxiety disorders. As crucial group characteristics were already evident during fear acquisition, our results emphasize the importance of average fear responses and differentiation between conditioned threat and safety as risk factors for anxiety disorders.
Background: Recent research has shown an increased risk of accidents and injuries in ADHD patients, which could potentially be reduced by stimulant treatment. Therefore, the first aim of our study was to evaluate the prevalence of adult ADHD in a trauma surgery population. The second aim was to investigate accident mechanisms and circumstances which could be specific to ADHD patients, in comparison to the general population.
Methods: We screened 905 accident victims for ADHD using the ASRS 18-item self-report questionnaire. The basic demographic data and circumstances of the accidents were also assessed.
Results: Prevalence of adult ADHD was found to be 6.18% in our trauma surgery patient sample. ADHD accident victims reported significantly higher rates of distraction, stress and overconfidence in comparison to non-ADHD accident victims. Overconfidence and being in thoughts as causal mechanisms for the accidents remained significantly higher in ADHD patients after correction for multiple comparison. ADHD patients additionally reported a history of multiple accidents.
Conclusion: The majority of ADHD patients in our sample had not previously been diagnosed and were therefore not receiving treatment. The results subsequently suggest that general ADHD screening in trauma surgery patients may be useful in preventing further accidents in ADHD patients. Furthermore, psychoeducation regarding specific causal accident mechanisms could be implemented in ADHD therapy to decrease accident incidence rate.
Attention-deficit/hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder. In recent years, genetic studies have revealed several risk gene variants associated with ADHD; however, these variants could only be partly replicated and are responsible for only a fraction of the whole heritability of ADHD estimated from family and twin studies. One factor that could potentially explain the ‘missing heritability’ of ADHD is that childhood and adult or persistent ADHD could be genetically distinct subtypes, which therefore need to be analyzed separately. Another approach to identify this missing heritability could be combining the investigation of both common and rare gene risk variants as well as polygenic risk scores. Finally, environmental factors are also thought to play an important role in the etiology of ADHD, acting either independently of the genetic background or more likely in gene–environment interactions. Environmental factors might additionally convey their influence by epigenetic mechanisms, which are relatively underexplored in ADHD. The aforementioned mechanisms might also influence the response of patients with ADHD to stimulant and other ADHD medication. We conducted a selective review with a focus on risk genes of childhood and adult ADHD, gene–environment interactions, and pharmacogenetics studies on medication response in childhood and adult ADHD.
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.
Introduction: Previous studies have established graph theoretical analysis of functional network connectivity (FNC) as a potential tool to detect neurobiological underpinnings of psychiatric disorders. Despite the promising outcomes in studies that examined FNC aberrancies in bipolar disorder (BD) and major depressive disorder (MDD), there is still a lack of research comparing both mood disorders, especially in a nondepressed state. In this study, we used graph theoretical network analysis to compare brain network properties of euthymic BD, euthymic MDD and healthy controls (HC) to evaluate whether these groups showed distinct features in FNC.
Methods: We collected resting‐state functional magnetic resonance imaging (fMRI) data from 20 BD patients, 15 patients with recurrent MDD as well as 30 age‐ and gender‐matched HC. Graph theoretical analyses were then applied to investigate functional brain networks on a global and regional network level.
Results: Global network analysis revealed a significantly higher mean global clustering coefficient in BD compared to HC. We further detected frontal, temporal and subcortical nodes in emotion regulation areas such as the limbic system and associated regions exhibiting significant differences in network integration and segregation in BD compared to MDD patients and HC. Participants with MDD and HC only differed in frontal and insular network centrality.
Conclusion: In conclusion, our findings indicate that a significantly altered brain network topology in the limbic system might be a trait marker specific to BD. Brain network analysis in these regions may therefore be used to differentiate euthymic BD not only from HC but also from patients with MDD.
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.