Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

Qi, Shile; Sui, Jing; Pearlson, Godfrey D.; Bustillo, Juan; Perrone‐Bizzozero, Nora I.; Kochunov, Peter; Turner, Jessica A.; Fu, Zening; Shao, Wei; Jiang, Rongtao; Yang, Xiao; Liu, Jingyu; Du, Yuhui; Chen, Jiayu; Zhang, Daoqiang; Calhoun, Vince D.

doi:10.1038/s41467-022-32513-8

Cited by 30 publications

(10 citation statements)

References 75 publications

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“…In contrast to previous work conducted in patients with SCZ 26,100 , healthy adults [101][102][103] , and a large sample of individuals across the psychosis spectrum from childhood to adulthood 104 , here we did not find associations between SCZ PGS and resting-state FC, nor any other PGS, in participants of EUR ancestry.…”

Section: Discussioncontrasting

confidence: 99%

Attention-mediated genetic influences on psychotic symptomatology in adolescence

Chang,

Hughes,

Zhu

et al. 2024

Preprint

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Attention problems are among the earliest precursors of schizophrenia (SCZ). Here we examine relationships between multi-trait polygenic scores (PGS), psychotic spectrum symptoms, and attention-related phenotypes in an adolescent cohort (ABCD; n=11,855, mean baseline age: 9.93). Across three biennial visits, greater attentional variability and altered functional connectivity were associated with severity of psychotic-like experiences (PLEs). In European ancestry youth, neuropsychiatric and cognitive PGS were associated with greater PLE severity and greater attentional variability; notably, the effect of multi-trait PGS on PLEs weakened over time. Attentional variability partially mediated relationships between multi-trait PGS and PLEs, explaining 4-16% of these associations. Lastly, multi-trait PGS parsed by developmental co-expression patterns were significantly associated with greater PLE severity, though effect sizes were larger for genome-wide PGS. Findings suggest that broad neurodevelopmental liability is implicated in pathophysiology of psychotic spectrum symptomatology in adolescence, and attentional variability may act as an intermediate between risk variants and symptom expression.

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Section: Discussioncontrasting

confidence: 99%

Attention-mediated genetic influences on psychotic symptomatology in adolescence

Chang,

Hughes,

Zhu

et al. 2024

Preprint

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“…1 g). Specifically, patient-wise HDRS/DKVFLFSS scores were used as a reference to jointly decompose the preprocessed fALFF and GMV by "MCCAR+jICA" [43][44][45][46] (multisite canonical correlation analysis with reference + joint independent component analysis) to investigate the antidepressant-response and cognitive-impairment fALFF-GMV covarying multimodal brain networks (Fig. 1 a, b).…”

Section: Analysis Pipelinementioning

confidence: 99%

Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder

Calhoun

Zhang

et al. 2022

BMC Med

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Background Although electroconvulsive therapy (ECT) is an effective treatment for depression, ECT cognitive impairment remains a major concern. The neurobiological underpinnings and mechanisms underlying ECT antidepressant and cognitive impairment effects remain unknown. This investigation aims to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks and assesses whether they are associated with the ECT-induced electric field (E-field) with an optimal pulse amplitude estimation. Methods A single site clinical trial focused on amplitude (600, 700, and 800 mA) included longitudinal multimodal imaging and clinical and cognitive assessments completed before and immediately after the ECT series (n = 54) for late-life depression. Another two independent validation cohorts (n = 84, n = 260) were included. Symptom and cognition were used as references to supervise fMRI and sMRI fusion to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks. Correlations between ECT-induced E-field within these two networks and clinical and cognitive outcomes were calculated. An optimal pulse amplitude was estimated based on E-field within antidepressant-response and cognitive-impairment networks. Results Decreased function in the superior orbitofrontal cortex and caudate accompanied with increased volume in medial temporal cortex showed covarying functional and structural alterations in both antidepressant-response and cognitive-impairment networks. Volume increases in the hippocampal complex and thalamus were antidepressant-response specific, and functional decreases in the amygdala and hippocampal complex were cognitive-impairment specific, which were validated in two independent datasets. The E-field within these two networks showed an inverse relationship with HDRS reduction and cognitive impairment. The optimal E-filed range as [92.7–113.9] V/m was estimated to maximize antidepressant outcomes without compromising cognitive safety. Conclusions The large degree of overlap between antidepressant-response and cognitive-impairment networks challenges parameter development focused on precise E-field dosing with new electrode placements. The determination of the optimal individualized ECT amplitude within the antidepressant and cognitive networks may improve the treatment benefit–risk ratio. Trial registration ClinicalTrials.gov Identifier: NCT02999269.

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“…Due to the abnormal connections among neurons in the brains of patients with schizophrenia [47], [49]- [51], the whole-brain networks of these patients undergo large changes in performance [72]. Regarding structural abnormalities, studies have demonstrated abnormalities in the white and gray matter of the brain in schizophrenia patients, leading to changes in brain activity [73]- [75]. Overall, these changes result in increased complexity and disorder of the entire nervous system in schizophrenia patients, leading to clinical symptoms.…”

Section: Discussionmentioning

confidence: 99%

Network Analysis of Magnetoencephalogram Signals in Schizophrenia Patients When Viewing Emotional Facial Stimuli

Bai

Yao

Yan

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Schizophrenia is a serious mental disorder. Network analysis of magnetoencephalogram signals may help to identify potential biomarkers of schizophrenia. The goal of this investigation was to identify potential biomarkers in the magnetoencephalogram signals of patients with schizophrenia, global brain connectivity measures was used for emotion recognition in discriminating the patients from controls. First, we employed a mutual information method to explore the topological characteristics of the brain network in patients with schizophrenia among different frequency bands in response to four different stimulus conditions. Second, multidimensional cross-recurrence quantification analysis was performed to investigate the differences in dynamic coupling among different frequencies of brain magnetic waves in patients with schizophrenia in response to four different stimulus conditions, as the major novel contribution of our study. We found that the differences in topological features of the brain network appear in different frequency bands under different stimulus conditions. The differences are evident in the alpha 1 (8-10 Hz) and beta (13-30 Hz) frequency bands in response to negative stimuli, in the alpha 1 (8-10 Hz) frequency band in response to positive stimuli, and in the theta (4-8 Hz) and alpha 1 (8-10 Hz) frequency bands in response to neutral and gray-cross stimuli. In addition, differences in dynamic coupling among pairs of frequency bands were the most prominent in response to positive stimuli. The characteristics identified by our methods may be potential markers of schizophrenia present in magnetoencephalogram data, which can facilitate the clinical identification of schizophrenia patients. Our method provides a comprehensive perspective of brain networks in patients with schizophrenia and has practical applications for the clinical diagnosis of this disease.

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Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

Cited by 30 publications

References 75 publications

Attention-mediated genetic influences on psychotic symptomatology in adolescence

Attention-mediated genetic influences on psychotic symptomatology in adolescence

Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder

Network Analysis of Magnetoencephalogram Signals in Schizophrenia Patients When Viewing Emotional Facial Stimuli

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