Zang YF papers

Phys Life Rev. 2025 Aug 25;55:58-60. doi: 10.1016/j.plrev.2025.08.011. Online ahead of print.

NO ABSTRACT

PMID:40884981 | DOI:10.1016/j.plrev.2025.08.011

CNS Neurosci Ther. 2025 Aug;31(8):e70533. doi: 10.1111/cns.70533.

ABSTRACT

AIMS: Major depressive disorder (MDD) is a common psychiatric disorder whose causes and manifestations are diverse and numerous. To facilitate targeted therapeutic interventions, we characterized the abnormalities in effective connectivity within the cognitive-affective (CCN-AN) circuits to identify predictive biomarkers of TMS efficacy based on a large multicenter dataset and an independent dataset from patients receiving TMS.

METHODS: Both functional and effective connectivity (FC, EC) were analyzed. As there was only one significant connection observed in FC, classification based on the differences in EC was performed using REST-meta-MDD. Furthermore, correlations between these abnormal connectivity and depression severity, as well as depression and suicidality alleviation, were calculated to determine their predictive implications for TMS efficacy using an independent dataset.

RESULTS: Overall increased connectivity from the AN to the CCN and decreased connectivity from the CCN to the AN in MDD were observed using EC. These disruptions drove the classification accuracy up to 79.1%. Furthermore, the connection from the right inferior parietal lobule (IPL. R) to the right amygdala (AMYG.R) was negatively correlated with depression scores. Notably, the IPL connectivity to the anterior cingulate cortex (ACC) and the AMYG.R were closely correlated with depression and suicidal ideation alleviation following TMS treatment.

CONCLUSIONS: These findings suggest that MDD is characterized by disruptions in both top-down and bottom-up emotion regulation systems. Notably, the key abnormal connectivities, particularly those from the IPL to ACC and AMYG, could predict the efficacy of TMS treatment. This insight refines MDD diagnosis and paves the way for more precise targeted interventions in the future.

PMID:40755356 | PMC:PMC12319422 | DOI:10.1111/cns.70533

Sci Bull (Beijing). 2025 Aug 30;70(16):2676-2690. doi: 10.1016/j.scib.2025.05.042. Epub 2025 Jun 4.

ABSTRACT

The subgenual anterior cingulate cortex (sgACC) plays a central role in the pathophysiology of major depressive disorder (MDD). Its functional interactive profile with the left dorsal lateral prefrontal cortex (DLPFC) is associated with transcranial magnetic stimulation (TMS) treatment outcomes. Previous research on sgACC functional connectivity (FC) in MDD has yielded inconsistent results, partly due to small sample sizes and limited statistical power. Furthermore, calculating sgACC-FC to target TMS individually is challenging. We used a large multi-site cross-sectional sample (1660 patients with MDD vs. 1341 healthy controls) from Phase II of the Depression Imaging REsearch ConsorTium (DIRECT) to systematically delineate case-control difference maps of sgACC-FC. We explored the potential impact of group-level abnormality profiles on TMS target localization and clinical efficacy. Next, we developed an MDD big data-guided, individualized TMS targeting algorithm to integrate group-level statistical maps with individual-level brain activity to individually localize TMS targets. We found enhanced sgACC-DLPFC FC in patients with MDD compared with healthy controls (HC). These group differences altered the position of the sgACC anti-correlation peak in the left DLPFC. We showed that the magnitude of case-control differences in the sgACC-FC was related to clinical improvement in two independent clinical samples. This targeting algorithm may generate targets demonstrating stronger associations with clinical efficiency than group-level targets. We reliably delineated MDD-related abnormalities of sgACC-FC profiles in a large, independently ascertained sample and demonstrated the potential impact of such case-control differences on FC-guided localization of TMS targets.

PMID:40628558 | DOI:10.1016/j.scib.2025.05.042

Mov Disord Clin Pract. 2025 Jun 28. doi: 10.1002/mdc3.70203. Online ahead of print.

NO ABSTRACT

PMID:40579937 | DOI:10.1002/mdc3.70203