Individualized resting-state functional connectivity abnormalities unveil two major depressive disorder subtypes with contrasting abnormal patterns of abnormality DOI Creative Commons

Keke Fang,

Lianjie Niu, Baohong Wen

et al.

Translational Psychiatry, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 6, 2025

Modern neuroimaging research has recognized that major depressive disorder (MDD) is a connectome disorder, characterized by altered functional connectivity across large-scale brain networks. However, the clinical heterogeneity, likely stemming from diverse neurobiological disturbances, complicates findings standard group comparison methods. This variability driven search for MDD subtypes using objective markers. In this study, we sought to identify potential subject-level abnormalities in connectivity, leveraging large multi-site dataset of resting-state MRI 1276 patients and 1104 matched healthy controls. Subject-level extreme connections, determined comparing against normative ranges derived controls tolerance intervals, were used biological MDD. We identified set connections predominantly between visual network frontoparietal network, default mode ventral attention with key regions anterior cingulate cortex, bilateral orbitofrontal supramarginal gyrus. patients, these linked age onset reward-related processes. Using features, two distinct patterns compared (p < 0.05, Bonferroni correction). When considering all together, no significant differences found. These significantly enhanced case-control discriminability showed strong internal subtypes. Furthermore, reproducible varying parameters, study sites, untreated patients. Our provide new insights into taxonomy have implications both diagnosis treatment

Language: Английский

One-shot normative modelling of whole-brain functional connectivity DOI Creative Commons
Janus RL Kobbersmed, Chetan Gohil, André F. Marquand

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Abstract Many brain diseases and disorders lack objective measures of function as indicators pathology, which has recently spurred the use normative modelling in neuroimaging. Normative models characterize normal variation measurements given sex age, thereby allowing identification abnormalities deviations from normal. is typically based on predicting functional connectivity (FC) between each pair regions. But human an extremely integrated organ, disease often widespread effects that are not well captured by piecemeal analyses, i.e. connection connection. We propose Functional Connectivity Integrative Modelling (FUNCOIN), developing a whole-brain model FC large resting-state fMRI data set captures whole-network-level changes associated with age. This can significantly, substantially, uncover abnormal patterns Parkinson’s patients even scans up to 5.5 years before diagnosis.

Language: Английский

Citations

0
Individualized resting-state functional connectivity abnormalities unveil two major depressive disorder subtypes with contrasting abnormal patterns of abnormality DOI Creative Commons

Keke Fang,

Lianjie Niu, Baohong Wen

et al.

Translational Psychiatry, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 6, 2025

Modern neuroimaging research has recognized that major depressive disorder (MDD) is a connectome disorder, characterized by altered functional connectivity across large-scale brain networks. However, the clinical heterogeneity, likely stemming from diverse neurobiological disturbances, complicates findings standard group comparison methods. This variability driven search for MDD subtypes using objective markers. In this study, we sought to identify potential subject-level abnormalities in connectivity, leveraging large multi-site dataset of resting-state MRI 1276 patients and 1104 matched healthy controls. Subject-level extreme connections, determined comparing against normative ranges derived controls tolerance intervals, were used biological MDD. We identified set connections predominantly between visual network frontoparietal network, default mode ventral attention with key regions anterior cingulate cortex, bilateral orbitofrontal supramarginal gyrus. patients, these linked age onset reward-related processes. Using features, two distinct patterns compared (p < 0.05, Bonferroni correction). When considering all together, no significant differences found. These significantly enhanced case-control discriminability showed strong internal subtypes. Furthermore, reproducible varying parameters, study sites, untreated patients. Our provide new insights into taxonomy have implications both diagnosis treatment

Language: Английский

Citations

0