Publications by authors named "Hengyi Cao"

27 Publications

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Childhood trauma is linked to decreased temporal stability of functional brain networks in young adults.

J Affect Disord 2021 Jul 2;290:23-30. Epub 2021 May 2.

Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, Changsha, Hunan, China; China National Clinical Research Center on Mental Disorders, Changsha, Hunan, China. Electronic address:

Background: Both childhood trauma and disruptions in brain functional networks are implicated in the development of psychiatric disorders in early adulthood. However, the relationships between these two factors remain unclear. This study aimed to investigate whether and how childhood trauma would relate to changes of functional network dynamics in young adults.

Methods: Resting-state functional magnetic resonance imaging data were collected from 53 young healthy adults, whose childhood trauma histories were assessed by the Childhood Trauma Questionnaire (CTQ). Network switching rate, a measure of stability of dynamic brain networks over time, was calculated at both global and local levels for each participant. Switching rates at both levels were compared between participants with and without childhood trauma, and further correlated with CTQ total score.

Results: In the current sample, 19 (35.8%) participants reported a history of childhood trauma. At the global level, participants with childhood trauma showed significantly higher network switching rates than those without trauma (F = 10.021, p = 0.003). A significant positive correlation was found between network switching rates and CTQ scores in the entire sample (r = 0.378, p = 0.007). At the local level, these effects were mainly observed in the default-mode, fronto-parietal, cingulo-opercular, and occipital subnetworks.

Conclusions: Our study provides preliminary evidence for a possible long-term effect of childhood trauma on brain functional dynamism. These findings may have potential contributions to psychiatric disorders during adulthood.
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http://dx.doi.org/10.1016/j.jad.2021.04.061DOI Listing
July 2021

Distinct and temporally associated neural mechanisms underlying concurrent, postsuccess, and posterror cognitive controls: Evidence from a stop-signal task.

Hum Brain Mapp 2021 Jun 2;42(9):2677-2690. Epub 2021 Apr 2.

Department of Psychology, Yale University, New Haven, Connecticut, USA.

Cognitive control is built upon the interactions of multiple brain regions. It is currently unclear whether the involved regions are temporally separable in relation to different cognitive processes and how these regions are temporally associated in relation to different task performances. Here, using stop-signal task data acquired from 119 healthy participants, we showed that concurrent and poststop cognitive controls were associated with temporally distinct but interrelated neural mechanisms. Specifically, concurrent cognitive control activated regions in the cingulo-opercular network (including the dorsal anterior cingulate cortex [dACC], insula, and thalamus), together with superior temporal gyrus, secondary motor areas, and visual cortex; while regions in the fronto-parietal network (including the lateral prefrontal cortex [lPFC] and inferior parietal lobule) and cerebellum were only activated during poststop cognitive control. The associations of activities between concurrent and poststop regions were dependent on task performance, with the most notable difference in the cerebellum. Importantly, while concurrent and poststop signals were significantly correlated during successful cognitive control, concurrent activations during erroneous trials were only correlated with posterror activations in the fronto-parietal network but not cerebellum. Instead, the cerebellar activation during posterror cognitive control was likely to be driven secondarily by posterror activation in the lPFC. Further, a dynamic causal modeling analysis demonstrated that postsuccess cognitive control was associated with inhibitory connectivity from the lPFC to cerebellum, while excitatory connectivity from the lPFC to cerebellum was present during posterror cognitive control. Overall, these findings suggest dissociable but temporally related neural mechanisms underlying concurrent, postsuccess, and posterror cognitive control processes in healthy individuals.
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http://dx.doi.org/10.1002/hbm.25347DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8127156PMC
June 2021

Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis.

Neuroimage 2021 02 4;226:117508. Epub 2020 Nov 4.

Faculty of Engineering Science, KU Leuven, Leuven 3001, Belgium; Faculty of Medicine, KU Leuven, Leuven 3001, Belgium; KU Leuven Institute for Artificial Intelligence, Leuven B-3000, Belgium.

Along the pathway from behavioral symptoms to the development of psychotic disorders sits the multivariate mediating brain. The functional organization and structural topography of large-scale multivariate neural mediators among patients with brain disorders, however, are not well understood. Here, we design a high-dimensional brain-wide functional mediation framework to investigate brain regions that intermediate between baseline behavioral symptoms and future conversion to full psychosis among individuals at clinical high risk (CHR). Using resting-state functional magnetic resonance imaging (fMRI) data from 263 CHR subjects, we extract an α brain atlas and a β brain atlas: the former underlines brain areas associated with prodromal symptoms and the latter highlights brain areas associated with disease onset. In parallel, we identify and separate mediators that potentially positively and negatively mediate symptoms and psychosis, respectively, and quantify the effect of each neural mediator on disease development. Taken together, these results paint a brain-wide picture of neural markers that are potentially mediating behavioral symptoms and the development of psychotic disorders; additionally, they underscore a statistical framework that is useful to uncover large-scale intermediating variables in a regulatory biological system.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117508DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836235PMC
February 2021

Cross-paradigm connectivity: reliability, stability, and utility.

Brain Imaging Behav 2021 Apr;15(2):614-629

Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT, USA.

While functional neuroimaging studies typically focus on a particular paradigm to investigate network connectivity, the human brain appears to possess an intrinsic "trait" architecture that is independent of any given paradigm. We have previously proposed the use of "cross-paradigm connectivity (CPC)" to quantify shared connectivity patterns across multiple paradigms and have demonstrated the utility of such measures in clinical studies. Here, using generalizability theory and connectome fingerprinting, we examined the reliability, stability, and individual identifiability of CPC in a group of highly-sampled healthy traveling subjects who received fMRI scans with a battery of five paradigms across multiple sites and days. Compared with single-paradigm connectivity matrices, the CPC matrices showed higher reliability in connectivity diversity, lower reliability in connectivity strength, higher stability, and higher individual identification accuracy. All of these assessments increased as a function of number of paradigms included in the CPC analysis. In comparisons involving different paradigm combinations and different brain atlases, we observed significantly higher reliability, stability, and identifiability for CPC matrices constructed from task-only data (versus those from both task and rest data), and higher identifiability but lower stability for CPC matrices constructed from the Power atlas (versus those from the AAL atlas). Moreover, we showed that multi-paradigm CPC matrices likely reflect the brain's "trait" structure that cannot be fully achieved from single-paradigm data, even with multiple runs. The present results provide evidence for the feasibility and utility of CPC in the study of functional "trait" networks and offer some methodological implications for future CPC studies.
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http://dx.doi.org/10.1007/s11682-020-00272-zDOI Listing
April 2021

Functional connectome-wide associations of schizophrenia polygenic risk.

Mol Psychiatry 2020 Mar 3. Epub 2020 Mar 3.

Department of Psychology, Yale University, New Haven, CT, USA.

Schizophrenia is a highly heritable mental disorder characterized by functional dysconnectivity across the brain. However, the relationships between polygenic risk factors and connectome-wide neural mechanisms are unclear. Here, combining genetic and multiparadigm fMRI data of 623 healthy Caucasian adults drawn from the Human Connectome Project, we found that higher schizophrenia polygenic risk scores were significantly correlated with lower functional connectivity in a large-scale brain network primarily encompassing the visual system, default-mode system, and frontoparietal system. Such correlation was robustly observed across multiple fMRI paradigms, suggesting a brain-state-independent neural phenotype underlying individual genetic liability to schizophrenia. Moreover, using an independent clinical dataset acquired from the Consortium for Neuropsychiatric Phenomics, we further demonstrated that the connectivity of the identified network was reduced in patients with schizophrenia and significantly correlated with general cognitive ability. These findings provide the first evidence for connectome-wide associations of schizophrenia polygenic risk at the systems level and suggest that disrupted integration of sensori-cognitive information may be a hallmark of genetic effects on the brain that contributes to the pathogenesis of schizophrenia.
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http://dx.doi.org/10.1038/s41380-020-0699-3DOI Listing
March 2020

Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

Neuroimage Clin 2020 7;26:102163. Epub 2020 Jan 7.

Faculty of Psychology, Southwest University, Chongqing 400716, China.

Background: Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach.

Methods: Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 473 healthy controls, as a part of the REST-meta-MDD consortium. Resting-state dynamic functional brain networks were constructed for each subject by a sliding-window approach. Multiple spatio-temporal features of dynamic brain networks, including temporal variability, temporal clustering and temporal efficiency, were then compared between patients and healthy subjects at both global and local levels.

Results: The group of MDD patients showed significantly higher temporal variability, lower temporal correlation coefficient (indicating decreased temporal clustering) and shorter characteristic temporal path length (indicating increased temporal efficiency) compared with healthy controls (corrected p < 3.14×10). Corresponding local changes in MDD were mainly found in the default-mode, sensorimotor and subcortical areas. Measures of temporal variability and characteristic temporal path length were significantly correlated with depression severity in patients (corrected p < 0.05). Moreover, the observed between-group differences were robustly present in both first-episode, drug-naïve (FEDN) and non-FEDN patients.

Conclusions: Our findings suggest that excessive temporal variations of brain FC, reflecting abnormal communications between large-scale bran networks over time, may underlie the neuropathology of MDD.
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http://dx.doi.org/10.1016/j.nicl.2020.102163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229351PMC
February 2021

New Evidence Supporting a Role of Hippocampus in the Development of Psychosis.

Biol Psychiatry 2020 02;87(3):200-201

Department of Psychology, Yale University, New Haven, Connecticut; Department of Psychiatry, Yale University, New Haven, Connecticut. Electronic address:

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http://dx.doi.org/10.1016/j.biopsych.2019.10.017DOI Listing
February 2020

Discovery and Validation of Prediction Algorithms for Psychosis in Youths at Clinical High Risk.

Biol Psychiatry Cogn Neurosci Neuroimaging 2020 08 4;5(8):738-747. Epub 2019 Nov 4.

Department of Psychology, Yale University, New Haven, Connecticut. Electronic address:

In the past 2 to 3 decades, clinicians have used the clinical high risk for psychosis (CHR-P) paradigm to better understand factors that contribute to the onset of psychotic disorders. While this paradigm is useful to identify individuals at risk, the CHR-P criteria are not sufficient to predict outcomes from the CHR-P population. Because approximately 25% of the CHR-P population will ultimately convert to psychosis, more precise methods of prediction are needed to account for heterogeneity in both risk factors and outcomes in the CHR-P population. To this end, several groups in recent years have used data-driven approaches to refine predictive algorithms to predict both conversion to psychosis and functional outcomes. These models have generally used either clinical and behavioral data, including demographics and measures of symptom severity, neurocognitive functioning, and social functioning, or neuroimaging data, including structural and functional measures, to predict conversion to psychosis in CHR-P samples. This review focuses on the empirical models that have been derived within each of these lines of research and evaluates the performance and methodology of these models. This review also serves to inform best practices for data-driven approaches and directions moving forward to improve our prediction of psychotic disorders and associated outcomes. Because sample size is still the most critical consideration in the current models, we urge that algorithms to predict conversion be conducted using multisite data in order to obtain the power necessary to conclusively determine predictive accuracy without overfitting.
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http://dx.doi.org/10.1016/j.bpsc.2019.10.006DOI Listing
August 2020

Discovery of new small molecule inhibitors targeting isocitrate dehydrogenase 1 (IDH1) with blood-brain barrier penetration.

Eur J Med Chem 2019 Dec 13;183:111694. Epub 2019 Sep 13.

Interdisciplinary Research Center on Biology and Chemistry, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201203, China. Electronic address:

Isocitrate dehydrogenase 1 (IDH1), which catalyzes the conversion of isocitrate to α-ketoglutarate, is one of key enzymes in the tricarboxylic acid cycle (TCA). Hotspot mutation at Arg in IDH1 that alters the function of IDH1 by further converting the α-ketoglutarate(α-KG) to 2-hydroxyglutarate (2-HG) have been identified in a variety of cancers. Because the IDH1 mutations occur in a significant portion of gliomas and glioblastomas, it is important that IDH1 inhibitors have to be brain penetrant to treat IDH1-mutant brain tumors. Here we report the efforts to design and synthesize a novel serial of mutant IDH1 inhibitors with improved activity and the blood-brain barrier (BBB) penetration. We show that compound 5 exhibits good brain exposure and potent 2-HG inhibition in a HT1080-derived mouse xenograft model, which makes it a potential preclinical candidate to treat IDH1-mutant brain tumors.
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http://dx.doi.org/10.1016/j.ejmech.2019.111694DOI Listing
December 2019

Evidence for cerebello-thalamo-cortical hyperconnectivity as a heritable trait for schizophrenia.

Transl Psychiatry 2019 08 20;9(1):192. Epub 2019 Aug 20.

Department of Psychology, Yale University, New Haven, CT, USA.

Our recent study has demonstrated that increased connectivity in the cerebello-thalamo-cortical (CTC) circuitry is a state-independent neural trait that can potentially predict the onset of psychosis. One possible cause of such "trait" abnormality would be genetic predisposition. Here, we tested this hypothesis using multi-paradigm functional magnetic resonance imaging (fMRI) data from two independent twin cohorts. In a sample of 85 monozygotic (MZ) and 52 dizygotic (DZ) healthy twin pairs acquired from the Human Connectome Project, we showed that the connectivity pattern of the identified CTC circuitry was more similar in the MZ twins (r = 0.54) compared with that in the DZ twins (r = 0.22). The structural equation modeling analysis revealed a heritability estimate of 0.52 for the CTC connectivity, suggesting a moderately strong genetic effect. Moreover, using an independent schizophrenia cotwin sample (10 discordant MZ cotwins, 30 discordant DZ cotwins, and 32 control cotwins), we observed a significant linear relationship between genetic distance to schizophrenia and the connectivity strength in the CTC circuitry (i.e., schizophrenia MZ cotwins > schizophrenia DZ cotwins > control twins, P = 0.045). The present data provide converging evidence that increased connectivity in the CTC circuitry is likely to be a heritable trait that is associated with the genetic risk of schizophrenia.
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http://dx.doi.org/10.1038/s41398-019-0531-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702223PMC
August 2019

Cerebellar Dysfunction and Schizophrenia: From "Cognitive Dysmetria" to a Potential Therapeutic Target.

Am J Psychiatry 2019 07;176(7):498-500

The Department of Psychology, Yale University, New Haven, Conn. (Cao, Cannon); and the Department of Psychiatry, Yale University, New Haven, Conn. (Cannon).

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http://dx.doi.org/10.1176/appi.ajp.2019.19050480DOI Listing
July 2019

Resting-state brain information flow predicts cognitive flexibility in humans.

Sci Rep 2019 03 7;9(1):3879. Epub 2019 Mar 7.

Department of Psychology, Yale University, New Haven, CT, USA.

The human brain is a dynamic system, where communication between spatially distinct areas facilitates complex cognitive functions and behaviors. How information transfers between brain regions and how it gives rise to human cognition, however, are unclear. In this article, using resting-state functional magnetic resonance imaging (fMRI) data from 783 healthy adults in the Human Connectome Project (HCP) dataset, we map the brain's directed information flow architecture through a Granger-Geweke causality prism. We demonstrate that the information flow profiles in the general population primarily involve local exchanges within specialized functional systems, long-distance exchanges from the dorsal brain to the ventral brain, and top-down exchanges from the higher-order systems to the primary systems. Using an information flow map discovered from 550 subjects, the individual directed information flow profiles can significantly predict cognitive flexibility scores in 233 novel individuals. Our results provide evidence for directed information network architecture in the cerebral cortex, and suggest that features of the information flow configuration during rest underpin cognitive ability in humans.
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http://dx.doi.org/10.1038/s41598-019-40345-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6406001PMC
March 2019

Novel Triapine Derivative Induces Copper-Dependent Cell Death in Hematopoietic Cancers.

J Med Chem 2019 03 18;62(6):3107-3121. Epub 2019 Mar 18.

Shanghai Advanced Research Institute , Chinese Academy of Sciences , Shanghai 201210 , China.

Triapine, an iron chelator that inhibits ribonucleotide reductase, has been evaluated in clinical trials for cancer treatment. Triapine in combination with other chemotherapeutic agents shows promising efficacy in certain hematologic malignancies; however, it is less effective against many advanced solid tumors, probably due to the unsatisfactory potency and pharmacokinetic properties. In this report, we developed a triapine derivative IC25 (10) with potent antitumor activity. 10 Preferentially inhibited the proliferation of hematopoietic cancers by inducing mitochondria reactive oxygen species production and mitochondrial dysfunction. Unlike triapine, 10 executed cytotoxic action in a copper-dependent manner. 10-Induced up-expression of thioredoxin-interacting protein resulted in decreased thioredoxin activity to permit c-Jun N-terminal kinase and p38 activation and ultimately led to the execution of the cell death program. Remarkedly, 10 showed good bioavailability and inhibited tumor growth in mouse xenograft models. Taken together, our study identifies compound 10 as a copper-dependent antitumor agent, which may be applied to the treatment of hematopoietic cancers.
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http://dx.doi.org/10.1021/acs.jmedchem.8b01996DOI Listing
March 2019

Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium.

Schizophr Res 2020 12 28;226:30-37. Epub 2019 Jan 28.

Department of Psychology, Yale University, New Haven, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA. Electronic address:

Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, may be implicated in the progression to full psychosis.
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http://dx.doi.org/10.1016/j.schres.2019.01.017DOI Listing
December 2020

Resting-state brain network features associated with short-term skill learning ability in humans and the influence of -methyl-d-aspartate receptor antagonism.

Netw Neurosci 2018 1;2(4):464-480. Epub 2018 Oct 1.

Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.

Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( = 26) and potential effects of the -methyl-d-aspartate (NMDA) antagonist ketamine ( = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( = 0.032) and global efficiency ( = 0.025), whereas negatively correlated with characteristic path length ( = 0.014) and transitivity ( = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability-associated ( = 0.037) and ketamine-susceptible ( = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks.
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http://dx.doi.org/10.1162/netn_a_00045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175691PMC
October 2018

Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization.

Nat Commun 2018 09 21;9(1):3836. Epub 2018 Sep 21.

Department of Psychology, Yale University, New Haven, CT, 06511, USA.

Understanding the fundamental alterations in brain functioning that lead to psychotic disorders remains a major challenge in clinical neuroscience. In particular, it is unknown whether any state-independent biomarkers can potentially predict the onset of psychosis and distinguish patients from healthy controls, regardless of paradigm. Here, using multi-paradigm fMRI data from the North American Prodrome Longitudinal Study consortium, we show that individuals at clinical high risk for psychosis display an intrinsic "trait-like" abnormality in brain architecture characterized as increased connectivity in the cerebello-thalamo-cortical circuitry, a pattern that is significantly more pronounced among converters compared with non-converters. This alteration is significantly correlated with disorganization symptoms and predictive of time to conversion to psychosis. Moreover, using an independent clinical sample, we demonstrate that this hyperconnectivity pattern is reliably detected and specifically present in patients with schizophrenia. These findings implicate cerebello-thalamo-cortical hyperconnectivity as a robust state-independent neural signature for psychosis prediction and characterization.
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http://dx.doi.org/10.1038/s41467-018-06350-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155100PMC
September 2018

Altered Brain Activation During Memory Retrieval Precedes and Predicts Conversion to Psychosis in Individuals at Clinical High Risk.

Schizophr Bull 2019 06;45(4):924-933

Department of Psychology, Yale University, New Haven, CT.

Memory deficits are a hallmark of psychotic disorders such as schizophrenia. However, whether the neural dysfunction underlying these deficits is present before the onset of illness and potentially predicts conversion to psychosis is unclear. In this study, we investigated brain functional alterations during memory processing in a sample of 155 individuals at clinical high risk (including 18 subjects who later converted to full psychosis) and 108 healthy controls drawn from the second phase of the North American Prodrome Longitudinal Study (NAPLS-2). All participants underwent functional magnetic resonance imaging with a paired-associate memory paradigm at the point of recruitment and were clinically followed up for approximately 2 years. We found that at baseline, subjects at high risk showed significantly higher activation during memory retrieval in the prefrontal, parietal, and bilateral temporal cortices (PFWE < .035). This effect was more pronounced in converters than nonconverters and was particularly manifested in unmedicated subjects (P < .001). The hyperactivation was significantly correlated with retrieval reaction time during scan in converters (P = .009) but not in nonconverters and controls, suggesting an exaggerated retrieval effort. These findings suggest that hyperactivation during memory retrieval may mark processes associated with conversion to psychosis, and such measures have potential as biomarkers for psychosis prediction.
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http://dx.doi.org/10.1093/schbul/sby122DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6581134PMC
June 2019

Inhibition of cIAP1 as a strategy for targeting c-MYC-driven oncogenic activity.

Proc Natl Acad Sci U S A 2018 10 4;115(40):E9317-E9324. Epub 2018 Sep 4.

Interdisciplinary Research Center on Biology and Chemistry, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 201203 Shanghai, China;

Protooncogene , a master transcription factor, is a major driver of human tumorigenesis. Development of pharmacological agents for inhibiting c-MYC as an anticancer therapy has been a longstanding but elusive goal in the cancer field. E3 ubiquitin ligase cIAP1 has been shown to mediate the activation of c-MYC by destabilizing MAD1, a key antagonist of c-MYC. Here we developed a high-throughput assay for cIAP1 ubiquitination and identified D19, a small-molecule inhibitor of E3 ligase activity of cIAP1. We show that D19 binds to the RING domain of cIAP1 and inhibits the E3 ligase activity of cIAP1 by interfering with the dynamics of its interaction with E2. Blocking cIAP1 with D19 antagonizes c-MYC by stabilizing MAD1 protein in cells. Furthermore, we show that D19 and an improved analog (D19-14) promote c-MYC degradation and inhibit the oncogenic function of c-MYC in cells and xenograft animal models. In contrast, we show that activating E3 ubiquitin ligase activity of cIAP1 by Smac mimetics destabilizes MAD1, the antagonist of MYC, and increases the protein levels of c-MYC. Our study provides an interesting example using chemical biological approaches for determining distinct biological consequences from inhibiting vs. activating an E3 ubiquitin ligase and suggests a potential broad therapeutic strategy for targeting c-MYC in cancer treatment by pharmacologically modulating cIAP1 E3 ligase activity.
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http://dx.doi.org/10.1073/pnas.1807711115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176641PMC
October 2018

Novelty modulates human striatal activation and prefrontal-striatal effective connectivity during working memory encoding.

Brain Struct Funct 2018 Sep 11;223(7):3121-3132. Epub 2018 May 11.

Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.

The functional role of the basal ganglia (BG) in the gating of suitable motor responses to the cortex is well established. Growing evidence supports an analogous role of the BG during working memory encoding, a task phase in which the "input-gating" of relevant materials (or filtering of irrelevant information) is an important mechanism supporting cognitive capacity and the updating of working memory buffers. One important aspect of stimulus relevance is the novelty of working memory items, a quality that is understudied with respect to its effects on corticostriatal function and connectivity. To this end, we used functional magnetic resonance imaging (fMRI) in 74 healthy volunteers performing an established Sternberg working memory task with different task phases (encoding vs. retrieval) and degrees of stimulus familiarity (novel vs. previously trained). Activation analyses demonstrated a highly significant engagement of the anterior striatum, in particular during the encoding of novel working memory items. Dynamic causal modeling (DCM) of corticostriatal circuit connectivity identified a selective positive modulatory influence of novelty encoding on the connection from the dorsolateral prefrontal cortex (DLPFC) to the anterior striatum. These data extend prior research by further underscoring the relevance of the BG for human cognitive function and provide a mechanistic account of the DLPFC as a plausible top-down regulatory element of striatal function that may facilitate the "input-gating" of novel working memory materials.
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http://dx.doi.org/10.1007/s00429-018-1679-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132644PMC
September 2018

Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms.

Cereb Cortex 2019 03;29(3):1263-1279

Department of Psychology, Yale University, New Haven, CT, USA.

While graph theoretical modeling has dramatically advanced our understanding of complex brain systems, the feasibility of aggregating connectomic data in large imaging consortia remains unclear. Here, using a battery of cognitive, emotional and resting fMRI paradigms, we investigated the generalizability of functional connectomic measures across sites and sessions. Our results revealed overall fair to excellent reliability for a majority of measures during both rest and tasks, in particular for those quantifying connectivity strength, network segregation and network integration. Processing schemes such as node definition and global signal regression (GSR) significantly affected resulting reliability, with higher reliability detected for the Power atlas (vs. AAL atlas) and data without GSR. While network diagnostics for default-mode and sensori-motor systems were consistently reliable independently of paradigm, those for higher-order cognitive systems were reliable predominantly when challenged by task. In addition, based on our present sample and after accounting for observed reliability, satisfactory statistical power can be achieved in multisite research with sample size of approximately 250 when the effect size is moderate or larger. Our findings provide empirical evidence for the generalizability of brain functional graphs in large consortia, and encourage the aggregation of connectomic measures using multisite and multisession data.
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http://dx.doi.org/10.1093/cercor/bhy032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676966PMC
March 2019

Reliability of functional magnetic resonance imaging activation during working memory in a multisite study: Clarification and implications for statistical power.

Neuroimage 2017 12 4;163:456-458. Epub 2017 Nov 4.

Department of Psychiatry and Biobehavioral Sciences, UCLA, United States.

In this technical note, we clarify the meaning of the generalizability-theory based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during working memory processing (Forsyth et al., Neuroimage 2014;97:51-52). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i.e., analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single site study design for statistical power, including a figure that shows sample size requirements to detect activation in two key nodes of the working memory circuitry given observed differences in reliability of measurement between single and multisite designs.
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http://dx.doi.org/10.1016/j.neuroimage.2017.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716858PMC
December 2017

Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study: Clarification and implications for statistical power.

Hum Brain Mapp 2018 01 31;39(1):599-601. Epub 2017 Oct 31.

Department of Psychology, Yale University, New Haven, Connecticut, 06520.

In this commentary, we clarify the meaning of the generalizability-theory-based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during an emotion processing task (Gee et al., Human Brain Mapping 2015;36:2558-2579). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study, in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i.e., analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single-site study design for statistical power, including Figure 1 that shows sample size requirements to detect activation in two key nodes of the emotion processing circuitry given observed differences in reliability of measurement between single-site and multisite designs.
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http://dx.doi.org/10.1002/hbm.23875DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5718980PMC
January 2018

The 5-HTTLPR Polymorphism Affects Network-Based Functional Connectivity in the Visual-Limbic System in Healthy Adults.

Neuropsychopharmacology 2018 Jan 7;43(2):406-414. Epub 2017 Jun 7.

Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.

The serotonin transporter-linked polymorphic region 5-HTTLPR is a key genetic regulator of 5-HTT expression in the human brain where the short allele S has been implicated in emotion dysregulation. However, the neural mechanism underlying the association between this variant and emotion processing is still unclear. Earlier studies suggested an effect of 5-HTTLPR on amygdala activation during emotional face processing. However, this association has been questioned in recent studies employing larger sample sizes and meta-analyses. Here, we examined a sample of 223 healthy subjects with a well-established fMRI emotional face processing task to (1) re-evaluate the association between 5-HTTLPR and amygdala activation, (2) explore potential network-based functional connectivity phenotypes for associations with 5-HTTLPR, and (3) probe the reliability, behavioral significance and potential structural confounds of the identified network phenotype. Our results revealed no significant effect of 5-HTTLPR on amygdala activation (P>0.79). However, the number of S alleles was significantly correlated with functional connectivity of a visual-limbic subnetwork (P=0.03). The subnetwork cluster included brain regions that are pivotal to emotion regulation such as the hippocampus, orbitofrontal cortex, anterior cingulate gyrus, fusiform gyrus, and subcortex. Notably, individuals with lower subnetwork connectivity had significantly higher emotion suppression scores (P=0.01). Further, the connectivity metrics were test-retest reliable and independent from subnetwork gray matter volume and white matter anisotropy. Our data provide evidence for a functional network-based phenotype linking genetic variation in 5-HTTLPR to emotion regulation, and suggest that further critical evaluations of the association between 5-HTTLPR and amygdala activation are warranted.
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http://dx.doi.org/10.1038/npp.2017.121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729553PMC
January 2018

Increased thalamic centrality and putamen-thalamic connectivity in patients with parkinsonian resting tremor.

Brain Behav 2017 01 23;7(1):e00601. Epub 2016 Nov 23.

Department of Radiology The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China.

Introduction: Evidence has indicated a strong association between hyperactivity in the cerebello-thalamo-motor cortical loop and resting tremor in Parkinson's disease (PD). Within this loop, the thalamus serves as a central hub based on its structural centrality in the generation of resting tremor. To study whether this thalamic abnormality leads to an alteration at the whole-brain level, our study investigated the role of the thalamus in patients with parkinsonian resting tremor in a large-scale brain network context.

Methods: Forty-one patients with PD (22 with resting tremor, TP and 19 without resting tremor, NTP) and 45 healthy controls (HC) were included in this resting-state functional MRI study. Graph theory-based network analysis was performed to examine the centrality measures of bilateral thalami across the three groups. To further provide evidence to the central role of the thalamus in parkinsonian resting tremor, the seed-based functional connectivity analysis was then used to quantify the functional interactions between the basal ganglia and the thalamus.

Results: Compared with the HC group, patients with the TP group exhibited increased degree centrality (< .04), betweenness centrality (< .01), and participation coefficient (< .01) in the bilateral thalami. Two of these alterations (degree centrality and participation coefficient) were significantly correlated with tremor severity, especially in the left hemisphere (< .02). The modular analysis showed that the TP group had more intermodular connections between the thalamus and the regions within the cerebello-thalamo-motor cortical loop. Furthermore, the data revealed significantly enhanced functional connectivity between the putamen and the thalamus in the TP group (= .027 corrected for family-wise error).

Conclusions: These findings suggest increased thalamic centrality as a potential tremor-specific imaging measure for PD, and provide evidence for the altered putamen-thalamic interaction in patients with resting tremor.
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http://dx.doi.org/10.1002/brb3.601DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5256184PMC
January 2017

Altered Functional Subnetwork During Emotional Face Processing: A Potential Intermediate Phenotype for Schizophrenia.

JAMA Psychiatry 2016 06;73(6):598-605

Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.

Importance: Although deficits in emotional processing are prominent in schizophrenia, it has been difficult to identify neural mechanisms related to the genetic risk for this highly heritable illness. Prior studies have not found consistent regional activation or connectivity alterations in first-degree relatives compared with healthy controls, suggesting that a more comprehensive search for connectomic biomarkers is warranted.

Objectives: To identify a potential systems-level intermediate phenotype linked to emotion processing in schizophrenia and to examine the psychological association, task specificity, test-retest reliability, and clinical validity of the identified phenotype.

Design, Setting, And Participations: The study was performed in university research hospitals from June 1, 2008, through December 31, 2013. We examined 58 unaffected first-degree relatives of patients with schizophrenia and 94 healthy controls with an emotional face-matching functional magnetic resonance imaging paradigm. Test-retest reliability was analyzed with an independent sample of 26 healthy participants. A clinical association study was performed in 31 patients with schizophrenia and 45 healthy controls. Data analysis was performed from January 1 to September 30, 2014.

Main Outcomes And Measures: Conventional amygdala activity and seeded connectivity measures, graph-based global and local network connectivity measures, Spearman rank correlation, intraclass correlation, and gray matter volumes.

Results: Among the 152 volunteers included in the relative-control sample, 58 were unaffected first-degree relatives of patients with schizophrenia (mean [SD] age, 33.29 [12.56]; 38 were women), and 94 were healthy controls without a first-degree relative with mental illness (mean [SD] age, 32.69 [10.09] years; 55 were women). A graph-theoretical connectivity approach identified significantly decreased connectivity in a subnetwork that primarily included the limbic cortex, visual cortex, and subcortex during emotional face processing (cluster-level P corrected for familywise error = .006) in relatives compared with controls. The connectivity of the same subnetwork was significantly decreased in patients with schizophrenia (F = 6.29, P = .01). Furthermore, we found that this subnetwork connectivity measure was negatively correlated with trait anxiety scores (P = .04), test-retest reliable (intraclass correlation coefficient = 0.57), specific to emotional face processing (F = 17.97, P < .001), and independent of gray matter volumes of the identified brain areas (F = 1.84, P = .18). Replicating previous results, no significant group differences were found in face-related amygdala activation and amygdala-anterior cingulate cortex connectivity (P corrected for familywise error =.37 and .11, respectively).

Conclusions And Relevance: Our results indicate that altered connectivity in a visual-limbic subnetwork during emotional face processing may be a functional connectomic intermediate phenotype for schizophrenia. The phenotype is reliable, task specific, related to trait anxiety, and associated with manifest illness. These data encourage the further investigation of this phenotype in clinical and pharmacologic studies.
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http://dx.doi.org/10.1001/jamapsychiatry.2016.0161DOI Listing
June 2016

Functional connectivity measures as schizophrenia intermediate phenotypes: advances, limitations, and future directions.

Curr Opin Neurobiol 2016 Feb 11;36:7-14. Epub 2015 Aug 11.

Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany. Electronic address:

The search for quantifiable biological mediators of genetic risk or 'intermediate phenotypes' is an essential strategy in psychiatric neuroscience and a useful tool for exploring the complex relationships between genes, neural circuits and behaviors. In recent years, the examination of connectivity-based intermediate phenotypes has gained increasing popularity in the study of schizophrenia, a brain disorder that manifests in early adulthood and disturbs a wide range of neural network functions. To date, several potential connectivity phenotypes have been identified that link neuroimaging measures of neural circuit interaction to genetic susceptibility for schizophrenia. This paper briefly reviews recent advances, current limitations and future directions in the search for functional connectivity intermediate phenotypes for schizophrenia across different cognitive domains.
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http://dx.doi.org/10.1016/j.conb.2015.07.008DOI Listing
February 2016

Test-retest reliability of fMRI-based graph theoretical properties during working memory, emotion processing, and resting state.

Neuroimage 2014 Jan 18;84:888-900. Epub 2013 Sep 18.

Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany.

The investigation of the brain connectome with functional magnetic resonance imaging (fMRI) and graph theory analyses has recently gained much popularity, but little is known about the robustness of these properties, in particular those derived from active fMRI tasks. Here, we studied the test-retest reliability of brain graphs calculated from 26 healthy participants with three established fMRI experiments (n-back working memory, emotional face-matching, resting state) and two parcellation schemes for node definition (AAL atlas, functional atlas proposed by Power et al.). We compared the intra-class correlation coefficients (ICCs) of five different data processing strategies and demonstrated a superior reliability of task-regression methods with condition-specific regressors. The between-task comparison revealed significantly higher ICCs for resting state relative to the active tasks, and a superiority of the n-back task relative to the face-matching task for global and local network properties. While the mean ICCs were typically lower for the active tasks, overall fair to good reliabilities were detected for global and local connectivity properties, and for the n-back task with both atlases, smallworldness. For all three tasks and atlases, low mean ICCs were seen for the local network properties. However, node-specific good reliabilities were detected for node degree in regions known to be critical for the challenged functions (resting-state: default-mode network nodes, n-back: fronto-parietal nodes, face-matching: limbic nodes). Between-atlas comparison demonstrated significantly higher reliabilities for the functional parcellations for global and local network properties. Our findings can inform the choice of processing strategies, brain atlases and outcome properties for fMRI studies using active tasks, graph theory methods, and within-subject designs, in particular future pharmaco-fMRI studies.
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http://dx.doi.org/10.1016/j.neuroimage.2013.09.013DOI Listing
January 2014