Abnormal Regional Spontaneous Brain Activities in White Matter in Patients with Autism Spectrum Disorder

Ma, Lin; Liu, Mengge; Xue, Kaizhong; Ye, Caihua; Man, Weiqi; Cheng, Meng; Liu, Zhixuan; Zhu, Dan; Liu, Feng; Wang, Junping

doi:10.1016/j.neuroscience.2022.02.022

Cited by 9 publications

(4 citation statements)

References 60 publications

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“…Endophenotypes were first defined as gene variants used to explore behavioral traits or biological markers, but endophenotypes now include using behavioral traits or biological markers to explore possible links between other features of a disorder ( 19 ). An autism biomarker endophenotype, such as abnormal brain white matter ( 20 ), could be used to search for a narrowed set of gene variants, or narrowed set of symptoms and behaviors. And a behavioral endophenotype can also be used to index other behavioral endophenotypes.…”

Section: Transdiagnostic Endophenotypesmentioning

confidence: 99%

“…The Research Domain Criteria (RDoC) project ( 1 ), initiated by the National Institute of Mental Health, is designed to find transdiagnostic pathophysiologies by means of functional behavioral constructs. RDoC is one of two large projects studying transdiagnostic behavioral endophenotypes in adult disorders, the other is the Psychiatric Ratings using Intermediate Stratified Markers (PRISM) project ( 20 , 21 ). Both projects use transdiagnostic endophenotypes as devices for exploring the possible shared biological bases of psychiatric disorders and symptoms.…”

Section: Transdiagnostic Endophenotypesmentioning

confidence: 99%

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Heterogeneity thwarts autism explanatory power: A proposal for endophenotypes

Waterhouse

2022

Front. Psychiatry

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Many researchers now believe that autism heterogeneity is likely to include many disorders, but most research is based on samples defined by the DSM-5 Autism Spectrum Disorder (ASD) criteria. However, individuals diagnosed with autism have complex and varied biological causes for their symptoms. Therefore, autism is not a unitary biological entity. And although autism is significantly different from typical development, autism is not a unitary clinical disorder because diagnosed individuals vary in symptom patterns, comorbidities, biomarkers, and gene variants. The DSM-5 ASD criteria were designed to reduce heterogeneity, and there have been many other efforts to reduce autism heterogeneity including using more stringent clinical criteria, dividing autism into low and high functioning groups, creating subgroups, and by studying larger samples. However, to date these efforts have not been successful. Heterogeneity is extensive and remains unexplained, and no autism pathophysiology has been discovered. Most importantly, heterogeneity has hindered the explanatory power of the autism diagnosis to discover drug regimens and effective behavioral treatments. The paper proposes that possible transdiagnostic endophenotypes may reduce autism heterogeneity. Searching for transdiagnostic endophenotypes requires exploring autism symptoms outside of the framework of the DSM-5 autism diagnosis. This paper proposes that researchers relax diagnostic criteria to increase the range of phenotypes to support the search for transdiagnostic endophenotypes. The paper proposes possible candidates for transdiagnostic endophenotypes. These candidates are taken from DSM-5 ASD criteria, from concepts that have resulted from researched theories, and from symptoms that are the result of subtyping. The paper then sketches a possible basis for a future transdiagnostic endophenotypes screening tool that includes symptoms of autism and other neurodevelopmental disorders.

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Section: Transdiagnostic Endophenotypesmentioning

confidence: 99%

Section: Transdiagnostic Endophenotypesmentioning

confidence: 99%

Heterogeneity thwarts autism explanatory power: A proposal for endophenotypes

Waterhouse

2022

Front. Psychiatry

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“…Resting-state functional magnetic resonance imaging (rs-fMRI) is an effective tool for studying psychiatric disorders, including MDD [ 11 , 12 ], autism [ 13 ], schizophrenia [ 14 ], and bipolar disorder [ 15 ]. Rs-fMRI was also further applied in the study of subtype MDD [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Resting-State Striatal Differences in First-Episode Depression and Recurrent Depression

Sun

et al. 2022

Brain Sciences

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The presence of reward deficits in major depressive disorder is associated with abnormal striatal function. However, differences in striatal whole-brain functional between recurrent depressive episode (RDE) and first-episode depression (FDE) have not been elucidated. Thirty-three patients with RDE, 27 with FDE, and 35 healthy controls (HCs) were recruited for this study. A seed-based functional connectivity (FC) method was used to analyze abnormalities in six predefined striatal subregion circuits among the three groups of subjects and to further explore the correlation between abnormal FC and clinical symptoms. The results revealed that compared with the FDE group, the RDE group showed higher FC of the striatal subregion with the left middle occipital gyrus, left orbital area of the middle frontal gyrus, and bilateral posterior cerebellar gyrus, while showing lower FC of the striatal subregion with the right thalamus, left inferior parietal lobule, left middle cingulate gyrus, right angular gyrus, right cerebellum anterior lobe, and right caudate nucleus. In the RDE group, the HAMD-17 scores were positively correlated with the FC between the left dorsal rostral putamen and the left cerebellum posterior lobe. This study provides new insights into understanding the specificity of striatal circuits in the RDE group.

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“…Li et al further quantified the functional importance of individual WM voxels using engagement ( Li et al, 2020 ). To date, WM functional abnormalities have been demonstrated to characterize the underlying pathological processes of many brain disorders including schizophrenia ( Fan et al, 2020 ), bipolar disorder ( Lu et al, 2021 ), and autism spectrum disorder ( Ma et al, 2022 ). Therefore, it is feasible to characterize the WM dysfunction in VCI using fMRI.…”

Section: Introductionmentioning

confidence: 99%