Zang YF papers

Front Psychiatry. 2026 Sep 28;17:1770305. doi: 10.3389/fpsyt.2026.1770305. eCollection 2026.

ABSTRACT

BACKGROUND/OBJECTIVES: Accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) requires multi-informant assessments across different settings, yet consistent agreement between parents and teachers remains challenging. This systematic review and meta-analysis aimed to quantify the level of concordance between parent and teacher ratings of ADHD symptoms in children and adolescents and to examine the moderating effects of child gender and sample settings.

METHODS: We conducted a comprehensive search of Web of Science, Embase, and PubMed from 1994 to May 2026(PROSPERO: CRD42024556281). Inclusion criteria encompassed studies assessing ADHD symptoms in individuals under 18 years using DSM-IV/V criteria and reporting Cohen's Kappa for parent-teacher agreement. A random-effects meta-analysis was performed, with subgroup analyses based on gender and sample settings (clinical, school, community). Heterogeneity was assessed using the I² statistic.

RESULTS: Eleven studies involving 8796 participants were included. The overall parent-teacher agreement was low (Kappa = 0.25, 95% CI: 0.18-0.31), with substantial heterogeneity (I² = 75.8%). Subgroup analyses revealed that gender had a minimal impact on agreement levels (boys: Kappa=0.25; girls: Kappa=0.32). However, sample settings significantly moderated agreement: school-based samples showed the highest concordance (Kappa=0.31), followed by community samples (Kappa=0.27), while clinical samples demonstrated the lowest and non-significant agreement (Kappa=0.07).

CONCLUSIONS: This meta-analysis confirmed low parent-teacher agreement in ADHD assessments, with the lowest agreement observed in clinical samples. Existing studies also suggest moderate agreement between parents themselves, although the limited data precluded a meta-analysis on this specific comparison. Nevertheless, these findings highlight that high levels of discrepancy across informants should be a focus of clinical attention. When integrating multi-informant data, such discrepancies must be explicitly interpreted, and standardized methods are needed to reconcile them in diagnostic decision-making.

SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=4556281, identifier CRD4202455628.

PMID:42865956 | PMC:PMC13655581 | DOI:10.3389/fpsyt.2026.1770305

Biol Psychiatry. 2026 Aug 17:S0006-3223(26)01470-8. doi: 10.1016/j.biopsych.2026.07.025. Online ahead of print.

ABSTRACT

BACKGROUND: Response to repetitive transcranial magnetic stimulation (rTMS) in major depressive disorder (MDD) varies substantially. Normative modeling of functional connectivity can disentangle disease-related pathophysiology from demographic variability, potentially refining personalized targeting.

METHODS: We constructed a normative model of subgenual anterior cingulate cortex (sgACC)-dorsolateral prefrontal cortex (DLPFC) functional connectivity using exclusively healthy controls (HCs; DIRECT dataset, n = 1,313). Individual Z-score maps were generated for 1,583 MDD patients; the DLPFC voxel with the most negative Z-score defined the functional connectivity normative deviation (FCND)-guided target. Clinical utility was tested in two independent rTMS cohorts (active: n=39, sham: n=23; accelerated iTBS: n=15) by correlating Euclidean distance from the stimulation site to the FCND target with improvement. We explored whether Z-score normalization statistically mediated this relationship.

RESULTS: In the DIRECT dataset, patients with MDD showed significantly more negative values for the most negative Z-score (Min Z-score) than HCs, and this Min Z-score correlated negatively with depressive symptom severity, as measured by the 17-item Hamilton Depression Rating Scale. In the YT active group, shorter distance to the FCND-guided target was associated with greater clinical improvement, while no association was observed in the sham group. This association was also significant in the aiTBS dataset. Exploratory mediation analysis revealed an indirect effect statistically consistent with the hypothesis that distance influences improvement through Z-score normalization in the active group, with a directionally consistent trend in the iTBS dataset.

CONCLUSION: The FCND-guided target framework provides a personalized, mechanism-informed strategy for precision neuromodulation in MDD.

PMID:42607914 | DOI:10.1016/j.biopsych.2026.07.025

Neuroimage. 2026 Aug 7:122160. doi: 10.1016/j.neuroimage.2026.122160. Online ahead of print.

ABSTRACT

Functional magnetic resonance imaging (fMRI) is the most commonly used technique for non-invasive exploration of human cognition and neuroscience. Conventional T2*-weighted single-echo resting-state fMRI (SE-rfMRI) is limited by signal loss in regions prone to susceptibility artifacts and inseparable confounding from non-neuronal baseline (i.e., initial signal intensity S0) fluctuations. While multi-echo optimally combined rfMRI (ME-OC) effectively mitigates signal loss, confounding from S0 fluctuations remains unaddressed. Here, we leverage quantitative T2* fluctuation from ME-rfMRI to derive intrinsic functional metrics that are biophysically cleaner and more robust. Across both cortical and subcortical brain regions, we systematically evaluated the test-retest reliability and functional validity of two key local metrics, amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo), derived from our proposed method against those from conventional SE-rfMRI and ME-OC. In subcortical regions, T2*-derived metrics showed the highest mean ICCs among the three signal representations for both ALFF (ICC = 0.67, 0.66, and 0.54) and ReHo (ICC = 0.73, 0.67, and 0.63) for T2* fluctuation, ME-OC, and SE-rfMRI, respectively. A similar regionally selective pattern was observed in cortical areas susceptible to magnetic field inhomogeneities, including the orbitofrontal cortex (ALFF ICC = 0.87, 0.75, and 0.82), insula (0.83, 0.61, and 0.71), and temporal pole (0.80, 0.73, and 0.79) for T2* fluctuation, ME-OC, and SE-rfMRI, respectively. In terms of functional validity, ALFF from T2* fluctuation uniquely revealed significant condition-related differences in the right putamen, inferior frontal gyrus, and suborbital sulcus, which both ME-OC and SE-rfMRI failed to detect. Together, our findings suggest that quantitative T2*-derived metrics may provide a reliable and more biophysically specific characterization of intrinsic fMRI signal fluctuations, particularly in subcortical and susceptibility-prone cortical regions, and may complement conventional approaches in future research applications.

PMID:42567430 | DOI:10.1016/j.neuroimage.2026.122160