Symptom-Based Profiling and Multimodal Neuroimaging of a Large Preteenage Population Identifies Distinct Obsessive-Compulsive Disorder–like Subtypes With Neurocognitive Differences

Wu, Xinran; Yu, Gechang; Zhang, Kai; Feng, Jianfeng; Zhang, Jie; Sahakian, Barbara J.; Robbins, Trevor W.

doi:10.1016/j.bpsc.2021.06.011

Cited by 8 publications

(9 citation statements)

References 95 publications

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“…Consistent with habit-based dominance theories in OCD, such alterations may facilitate the emergence of compulsions ( 48 ). This may concur with recent findings reporting that children with compulsive phenotypes showed structural alterations in the motor cortex and increased FC between the sensorimotor and the default mode networks, suggesting that motor/premotor regions may be strongly connected to distant cortical regions ( 49 ). Likewise, these results comply with the well-established efficacy of low-frequency repetitive transcranial magnetic stimulation targeting the SMA on improving OCSs ( 50 ), which may be explained by its inhibitory effects on SMA hyperconnectivity.…”

Section: Discussionsupporting

confidence: 93%

“…Connectivity alterations in this region may result in decreased information exchange across different CSTC loops, whose fiber tracts are progressively compressed within the same striatal nuclei ( 67 ). In this regard, recent research with large youth samples provides an anatomical basis for such decreased connectivity, as compulsivity has been associated with reduced myelin-related growth in the left ventral striatum ( 68 ) and OCSs with decreased fractional anisotropy in the superior corticostriatal tract ( 49 , 69 ).…”

Section: Discussionmentioning

confidence: 99%

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Neurogenetics of Dynamic Connectivity Patterns Associated With Obsessive-Compulsive Symptoms in Healthy Children

Suñol

Alemany

Díez

et al. 2022

Biological Psychiatry Global Open Science

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Neurogenetics of Dynamic Connectivity Patterns Associated With Obsessive-Compulsive Symptoms in Healthy Children

Suñol

Alemany

Díez

et al. 2022

Biological Psychiatry Global Open Science

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“…Our results showed that the main reason for this might be the high heterogeneity of OCD. Especially, Wu et al ( 2021 ) uncovered two subgroups with distinct symptom profiles using a large sample of children with OCD, providing powerful evidence of the high heterogeneity in OCD. In fact, when mixed together, all patients presented no significant differences compared with the HCs in our study.…”

Section: Discussionmentioning

confidence: 99%

Two distinct subtypes of obsessive compulsive disorder revealed by heterogeneity through discriminative analysis

Han

Guo

et al. 2022

Human Brain Mapping

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Neurobiological heterogeneity in obsessive compulsive disorder (OCD) is understudied leading to conflicting neuroimaging findings. Therefore, we investigated objective neuroanatomical subtypes of OCD by adopting a newly proposed method based on gray matter volumes (GMVs). GMVs were derived from T1-weighted anatomical images of patients with OCD (n = 100) and matched healthy controls (HCs; n = 106). We first inquired whether patients with OCD presented higher interindividual variability HCs in terms of GMVs. Then, we identified distinct subtypes of OCD by adopting heterogeneity through discriminative analysis (HYDRA), where regional GMVs were treated as features. Patients with OCD presented higher interindividual variability than HCs, suggesting a high structural heterogeneity of OCD.HYDRA identified two distinct robust subtypes of OCD presenting opposite neuroanatomical aberrances compared with HCs, while sharing indistinguishable clinical and demographic features. Specifically, Subtype 1 exhibited widespread increased GMVs in cortical and subcortical regions, including the orbitofrontal gyrus, right anterior insula, bilateral hippocampus, and bilateral parahippocampus and cerebellum. Subtype 2 demonstrated overall decreased GMVs in regions such as the orbitofrontal gyrus, right anterior insula, and precuneus. When mixed together, none of patients presented significant differences compared with HCs. In addition, the total intracranial

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“…Next, we considered a more exploratory relationship between dimensional psychopathology and cortical volume. Several groups have reported inverse associations between CBCL scales and cortical volume, including using ABCD data 25, 26 . In a recent study focused on genetic and neurodevelopmental underpinnings of psychopathology in ABCD 27 , among the broadband CBCL scales (total, internalizing, externalizing) we identified externalizing symptoms (CBCLext) as most strongly related to cortical volumes at Baseline, after taking into account both MQC ratings and SHN.…”

Section: Resultsmentioning

confidence: 99%

Uncovering and mitigating bias in large, automated MRI analyses of brain development

Elyounssi

Kunitoki

Clauss

et al. 2023

Preprint

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Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk1, 2. However, MRI studies of youth are especially susceptible to motion and other artifacts3, 4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies,5and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohen’s d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.

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Symptom-Based Profiling and Multimodal Neuroimaging of a Large Preteenage Population Identifies Distinct Obsessive-Compulsive Disorder–like Subtypes With Neurocognitive Differences

Cited by 8 publications

References 95 publications

Neurogenetics of Dynamic Connectivity Patterns Associated With Obsessive-Compulsive Symptoms in Healthy Children

Neurogenetics of Dynamic Connectivity Patterns Associated With Obsessive-Compulsive Symptoms in Healthy Children

Two distinct subtypes of obsessive compulsive disorder revealed by heterogeneity through discriminative analysis

Uncovering and mitigating bias in large, automated MRI analyses of brain development

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