Amygdala Abnormalities in Adults With ADHD

Tajima-Pozo, Kazuhiro; Yus, Miguel; Ruiz-Manrique, Gonzalo; Lewczuk, Adrian; Arrazola, Juan; Montañes-Rada, Francisco

doi:10.1177/1087054716629213

Cited by 27 publications

(22 citation statements)

References 42 publications

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“…At another locus, TMEM161B, a transmembrane protein, had the highest posterior inclusion probability of 0.838 in the amygdala. Brain imaging studies have shown that the amygdala has decreased volume in ADHD patients 15 . Genetic variants in the gene have also been previously associated with major depressive disorder (MDD), which is a disorder that is often co-morbid with ADHD 16 .…”

Section: Discussionmentioning

confidence: 99%

Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Liao

Laporte

Spiegelman

et al. 2019

Preprint

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Attention deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental psychiatric disorders. Previous studies have shown that the disorder is highly heritable and associated with several different risk-taking behaviors. Additionally, brain-imaging studies have identified various brain regions such as the cerebellum and frontal cortex to be altered in ADHD.Large genome-wide association studies (GWAS) have identified several loci associated with ADHD. However, understanding the biological relevance of these genetic loci has proven to be difficult. Here, we conducted the largest ADHD transcriptome-wide association study (TWAS) to date consisting of 19,099 cases and 34,194 controls and identified 9 transcriptome-wide significant hits. We successfully demonstrate that several previous GWAS hits can be largely explained by expression. Probabilistic causal fine-mapping of TWAS signals prioritized KAT2B with a posterior probability of 0.467 in the dorsolateral prefrontal cortex and TMEM161B with a posterior probability of 0.838 in the amygdala. Furthermore, pathway enrichments identified dopaminergic and norepinephrine pathways, which are highly relevant for ADHD. Finally, we used the top eQTLs associated with the TWAS genes to identify phenotypes relevant to ADHD and found an inverse genetic correlation with educational attainment and a positive correlation with "ever smoker", maternal smoking at birth, BMI, and schizophrenia. Overall, our findings highlight the power of TWAS to identify novel risk loci and prioritize putatively causal genes.

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Section: Discussionmentioning

confidence: 99%

Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Liao

Laporte

Spiegelman

et al. 2019

Preprint

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“…The amygdala and associated circuitry have been primarily related to avoidance mechanisms, and the striatum and associated circuitry to approach mechanisms (Ernst and Fudge, 2009). Furthermore, amygdala and striatum abnormalities have been associated with different psychiatric problem domains, for example with depression (Stuhrmann et al, 2011), (social) anxiety (Shin and Liberzon, 2009; Freitas-Ferrari et al, 2010), avoidance behavior (Schlund et al, 2013), ADHD (Cubillo et al, 2012; Tajima-Pozo et al, 2016) and antisocial behavior (Glenn and Yang, 2012; Blair, 2013). To further link approach and reward mechanisms to facial emotion processing in the specific psychiatric problem domains, we commend future study of activation and connectivity of the amygdala, striatum and their associated circuits during the processing of conscious as well as subliminally presented facial emotions.…”

Section: Discussionmentioning

confidence: 99%

Lower Sensitivity to Happy and Angry Facial Emotions in Young Adults with Psychiatric Problems

et al. 2016

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Many psychiatric problem domains have been associated with emotion-specific biases or general deficiencies in facial emotion identification. However, both within and between psychiatric problem domains, large variability exists in the types of emotion identification problems that were reported. Moreover, since the domain-specificity of the findings was often not addressed, it remains unclear whether patterns found for specific problem domains can be better explained by co-occurrence of other psychiatric problems or by more generic characteristics of psychopathology, for example, problem severity. In this study, we aimed to investigate associations between emotion identification biases and five psychiatric problem domains, and to determine the domain-specificity of these biases. Data were collected as part of the ‘No Fun No Glory’ study and involved 2,577 young adults. The study participants completed a dynamic facial emotion identification task involving happy, sad, angry, and fearful faces, and filled in the Adult Self-Report Questionnaire, of which we used the scales depressive problems, anxiety problems, avoidance problems, Attention-Deficit Hyperactivity Disorder (ADHD) problems and antisocial problems. Our results suggest that participants with antisocial problems were significantly less sensitive to happy facial emotions, participants with ADHD problems were less sensitive to angry emotions, and participants with avoidance problems were less sensitive to both angry and happy emotions. These effects could not be fully explained by co-occurring psychiatric problems. Whereas this seems to indicate domain-specificity, inspection of the overall pattern of effect sizes regardless of statistical significance reveals generic patterns as well, in that for all psychiatric problem domains the effect sizes for happy and angry emotions were larger than the effect sizes for sad and fearful emotions. As happy and angry emotions are strongly associated with approach and avoidance mechanisms in social interaction, these mechanisms may hold the key to understanding the associations between facial emotion identification and a wide range of psychiatric problems.

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“…The findings of amygdala anatomical abnormities in children with ADHD were supported by many previous studies. Amygdala played as a critically important role in emotion regulation (Banks et al, 2007; Davidson et al, 2000; Domes et al, 2010) and thus structural anomalies associated amygdala have been widely observed in children (Van Dessel et al, 2019) and adults with ADHD (Tajima-Pozo et al, 2018), which suggested that the aberrant structure of amygdala may be associated with less control of impulsivity and delay aversion (Van Dessel et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Multimodal Neuroimaging-based Prediction of Adult Outcomes in Childhood-onset ADHD using Ensemble Learning Techniques

Luo

Alvarez

Halperin

et al. 2019

Preprint

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Attention deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous neurodevelopmental disorder, currently relaying on subjective symptom observations for diagnosis.Machine learning classifiers have been utilized to assist the development of neuroimaging-based biomarkers for objective diagnosis of ADHD. However, the existing basic model-based studies in ADHD reported suboptimal classification performances and inconclusive results, mainly due to the limited flexibility for each type of basic classifiers to appropriately handle multi-dimensional source features with various properties. In this study, we proposed to apply ensemble learning techniques (ELTs) in multimodal neuroimaging data collected from 72 young adults, including 36 probands (18 remitters and 18 persisters of childhood ADHD) and 36 group-matched controls. All the currently available optimization strategies for ELTs (i.e., voting, bagging, boosting and stacking techniques) were tested in a pool of semi-final classification results generated by seven basic classifiers. The highdimensional neuroimaging features for classification included regional cortical gray matter (GM) thickness and surface area, GM volume of subcortical structures, volume and fractional anisotropy of major white matter fiber tracts, pair-wise regional connectivity and global/nodal topological properties of the functional brain network for cue-evoked attention process. As a result, the bagging-based ELT with the base model of support vector machine achieved the best results, with the most significant improvement of the area under the receiver of operating characteristic curve (0.89 for ADHD vs. controls, and 0.9 for ADHD persisters vs. remitters). We found that features of nodal efficiency in right inferior frontal gyrus, right middle frontal (MFG)-inferior parietal (IPL) functional connectivity, and right amygdala volume significantly contributed to accurate discrimination between ADHD probands and controls; higher nodal efficiency of right MFG greatly contributed to inattentive and hyperactive/impulsive symptom remission, while higher right MFG-IPL functional connectivity strongly linked to symptom persistence in adults with childhood ADHD. Our study also suggested that considering their solidly improved robustness than the commonly implemented basic classifiers, ELTs may have the potential to identify more reliable neurobiological markers for severe brain disorders.structures estimated from structural MRI data, volume and FA of major WM fiber tracts derived from DTI data, the pair-wise regional connectivity and global/nodal topological properties (i.e., global-, local-, and nodal-efficiency, etc.) of the cue-evoked attention processing network computed from task-based fMRI data. Based on findings from existing studies from our group and other teams, we hypothesized that structural and functional alterations in frontal, parietal, and subcortical areas and their interactions would significantly contribute to accurate discrimination of ADHD probands (adults diag...

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Amygdala Abnormalities in Adults With ADHD

Cited by 27 publications

References 42 publications

Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Transcriptome-wide association study of attention deficit hyperactivity disorder identifies associated genes and phenotypes

Lower Sensitivity to Happy and Angry Facial Emotions in Young Adults with Psychiatric Problems

Multimodal Neuroimaging-based Prediction of Adult Outcomes in Childhood-onset ADHD using Ensemble Learning Techniques

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