{"doi":"10.1111/pcn.13662","title":"Bridging gaps in brain disconnection in childhood <scp>ADHD</scp>: From macroscale connectomes to microscale biological architectures","abstract":null,"journal":"Psychiatry and Clinical Neurosciences","year":2024,"id":626710,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":460786,"name":"Shaozheng Qin","orcid":"0000-0002-1859-2150","position":1,"is_corresponding":false},{"id":1621250,"name":"Boxuan Chen","orcid":"0000-0003-4931-1849","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Bridging gaps in brain disconnection in childhood <scp>ADHD</scp>: From macroscale connectomes to microscale biological architectures","abstract":"The global prevalence of ADHD in children and adolescents was 8.0%. ADHD not only affects the normal life of individuals, but also brings a huge burden to society. As a complex neurodevelopmental disorder, ADHD is influenced by multiple genetic and environmental factors. However, no specific marker has yet been identified as a clear indicator of ADHD nowadays, and our understanding of the neuropathological mechanisms is still in its infancy. In the study of this issue by Chen et al.1 they attempted to address an important question on the intricate neuropathological landscape of ADHD through a comprehensive macro–micro-molecular perspective. Leveraging human neuroimaging data from the ADHD-200 initiative repository, they examined resting-state functional connectivity in ADHD children and matched typically developing cohorts. Their innovative approach involved employing a diffusion mapping embedding model to unveil functional connectome gradients, and then using multivariate partial least squares to uncover co-varied enrichments in neurotransmitter levels, cellular compositions, and chromosomal transcriptional signatures. The major findings uncover cortical gradient perturbations in functional brain networks among ADHD children compared to typically developing peers. Such neuroimaging-derived gradient perturbations were further covaried with spatial enrichment observed in key neurotransmitter receptors (i.e., GABAA/BZ, 5-HT2A) and genetic transcriptional expressions (i.e., DYDC2) linked to episodic memory and emotional regulation. Additionally, further enrichment analyses shed light on the potential genetic and molecular underpinnings of ADHD, implicating specific cellular and chromosomal dysfunctions. The results reported in this study provide important insights into a comprehensive understanding of the neuropathological mechanisms underlying childhood ADHD, elucidating the complex interplay between macroscopic brain connectome aberrations and microscopic biological architectures. One key domain that the current results suggest should be studied further is to delve into the neuropathological mechanisms underlying brain connectome aberrations in ADHD linked to microscale neurotransmitter and genetic transcriptomic profiles derived from independent populations.2 One novel aspect of the Chen et al.1 study design attempts to bridge a gap between macroscale brain connectome aberrations and far-reaching microscale/cellular biological architectures. Given there are many factors and sources that could account for the associations of connectome gradient changes with neurotransmitter and transcriptomic profiles, it would be wise to disentangle the specificity of neurotransmitomic, type-specific and chromosome-level signatures in relation to ADHD rather than other disorders in future studies. As the brain networks undergo protracted development into highly specialized yet interacting neural modules, with dramatic changes in cognitive abilities including attention.3 This raises the question on whether and how the observed associations in this study change over the course of development. Mapping developmental trajectories of ADHD-related brain connectome abnormalities is of great interest for two reasons: first, early onset of ADHD urges the importance of delineating developmental changes in the neuropathological profiles from childhood to adulthood. Thus, it is crucial to identify the developmental neuropathology at early onset of childhood ADHD. Second, the origins of psychopathology are complex and multifaceted, involving the complex interplay of genetic, biological, and environmental factors. It is critical to investigate the neuropathological mechanisms of how risk genes and environmental factors underlie the development of ADHD from childhood to adulthood, and further trace their underlying micro-scale and cellular biological architectures as well as their links to core symptoms. While the search for neuropathological mechanisms from a multiscale perspective are critical, their specific associations to ADHD symptomatology remain critical to translate these findings into feasible detection and interventions. As such, early detection and timely interventions can remedy the incidence and severity of ADHD and alleviate personal and social burden to some extent. This work was supported by the National Natural Science Foundation of China (Grants 32130045 and 82021004) and the Fundamental Research Funds for the Central Universities.","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"38699989","pmcid":null,"openalex_id":"https://openalex.org/W4396615147","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"32130045","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"82021004","title":null},{"funder_name":"Fundamental Research Funds for Central Universities of the Central South University","grant_id":"","title":null},{"funder_name":"Fundamental Research Funds for Central Universities of the Central South University","grant_id":"","title":null}],"total_grants":4,"fwci":0.0,"citation_percentile":0.05642812,"influential_citations":0,"citation_trend":[],"oa_status":"bronze","license":"http://onlinelibrary.wiley.com/termsAndConditions#vor","oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/pcn.13662","host_type":"journal"},{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/pcn.13662","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1111/pcn.13662","host_type":"publisher"},{"url":"http://dx.doi.org/10.1111/pcn.13662","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/38699989","host_type":"repository"}],"fields_of_study":["Functional Brain Connectivity Studies","Attention Deficit Hyperactivity Disorder","Neural dynamics and brain function","Humans","Attention Deficit Disorder with Hyperactivity","Connectome","Child","Brain","Nerve Net"],"mesh_terms":["Attention Deficit Disorder with Hyperactivity","Brain","Child","Humans","Nerve Net","Connectome"],"keywords":["Disconnection","Connectome","Microscale chemistry","Bridging (networking)","Neuroscience","Psychology","Functional connectivity","Computer science","Philosophy","Computer network"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-04T14:55:33.280548Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}