Fei Wang
Associate Professor Adjunct, Psychiatry
Research & Publications
Biography
News
Research Summary
Converging evidence implicates abnormalities of white matter connections and function within specific neural circuitry in schizophrenia, bipolar disorder and major depressive disorder. New brain scanning techniques (diffusion tensor imaging which provides measures of structural connectivity and functional connectivity which is a new way to analyze functional magnetic resonance image data and provides measures of functional connectivity) are used to investigate neural circuitry abnormalities in these disorders. Recently, findings suggest genetic variations influence neural circuitry to produce the clinical phenotypes of mental disorders. We aim to investigate neural circuitry abnormalities using multiple brain scanning techniques with a combined molecular genetic study to determine which genes might contribute to these abnormalities. Our work will enhance our understanding of the causes of these disorders, our ability to detect the disorders early and to develop novel and more effective treatments.
Extensive Research Description
My longstanding interest is identification of neural circuitry abnormalities using multimodal neuroimaging techniques and investigation of how genetic variations influence neural circuitry to produce the clinical phenotypes of mental disorders, such as schizophrenia, bipolar disorder and major depressive disorder. My primary research interests lie in developing novel multimodal magnetic resonance imaging techniques to characterize the critical neural circuitry abnormalities underlying these disorders and identifying the specific genetic variations that contribute to them. Our work in translational research will contribute to elucidating the neuropathophysiological mechanisms underlying the disorders, aid in the development of new methods for early detection, and importantly, improve treatment of debilitating psychiatric illnesses.
1. Methods of multimodal neuroimaging:
This project aims to use multimodal neuroimaging techniques to identify abnormalities of important neural circuitry in mental disorders. I developed diffusion tensor imaging (DTI) methods to study the cingulum, a white matter structure important in cortico-limbic circuitry. My work demonstrated abnormalities in the anterior cingulum in schizophrenia and bipolar disorder; however, findings demonstrate a different distribution of white matter abnormalities in the two disorders. I have also developed functional magnetic resonance imaging methods to study cortico-limbic functional connectivity to be integrated with DTI methods. Using these methodologies, I have obtained exciting findings that demonstrate altered structural and functional connectivity in cortico-limbic neural circuitry in mood disorders. Moreover, I have identified an association between structural and functional connectivity within this circuitry in bipolar disorder, providing some of the first evidence that these structural abnormalities may contribute to disruptions in the ability of the cortical region to modulate the functioning of limbic structure in mood disorders.
2. Integration of multimodal neuroimaging and molecular genetics:
This project aims to develop translational research approaches of integrating molecular genetics with multimodal neuroimaging to identify novel effects of genetic variations on cortico-limbic circuitry in mental disorders. I have reported an important finding of the influence of genetic variation in neuregulin 1 on dorsal frontotemporal white matter connection abnormalities in schizophrenia. I have also recently authored psychiatric genetic papers in mood disorders including a paper that reports a novel finding of an association between variation in the vascular endothelial growth factor gene and cortico-limbic structure and on two papers on the association between the brain-derived neurotrophic growth factor gene/serotonin transporter protein gene and cortico-limbic structure/function in bipolar disorder.
1. Methods of multimodal neuroimaging:
This project aims to use multimodal neuroimaging techniques to identify abnormalities of important neural circuitry in mental disorders. I developed diffusion tensor imaging (DTI) methods to study the cingulum, a white matter structure important in cortico-limbic circuitry. My work demonstrated abnormalities in the anterior cingulum in schizophrenia and bipolar disorder; however, findings demonstrate a different distribution of white matter abnormalities in the two disorders. I have also developed functional magnetic resonance imaging methods to study cortico-limbic functional connectivity to be integrated with DTI methods. Using these methodologies, I have obtained exciting findings that demonstrate altered structural and functional connectivity in cortico-limbic neural circuitry in mood disorders. Moreover, I have identified an association between structural and functional connectivity within this circuitry in bipolar disorder, providing some of the first evidence that these structural abnormalities may contribute to disruptions in the ability of the cortical region to modulate the functioning of limbic structure in mood disorders.
2. Integration of multimodal neuroimaging and molecular genetics:
This project aims to develop translational research approaches of integrating molecular genetics with multimodal neuroimaging to identify novel effects of genetic variations on cortico-limbic circuitry in mental disorders. I have reported an important finding of the influence of genetic variation in neuregulin 1 on dorsal frontotemporal white matter connection abnormalities in schizophrenia. I have also recently authored psychiatric genetic papers in mood disorders including a paper that reports a novel finding of an association between variation in the vascular endothelial growth factor gene and cortico-limbic structure and on two papers on the association between the brain-derived neurotrophic growth factor gene/serotonin transporter protein gene and cortico-limbic structure/function in bipolar disorder.
- Frontotemporal Neural Systems in Bipolar Disorder and Schizophrenia: This project aims to investigate differences in the distribution of brain abnormalities in bipolar disorder and schizophrenia and to determine which genes may contribute to the distinct distributions.
- Structural and Functional Connectivity of the Perigenual Anterior Cingulate in Adolescents with Bipolar Disorder: This project proposes to integrate multimodal magnetic resonance imaging techniques in order to investigate the different developmental trajectories of structural and functional connections between the amygdala and anterior cingulate cortex in adolescents with and without bipolar disorder.
- The Neural Circuitry of Adolescent Major Depressive Disorder: A Multi-modality Magnetic Resonance Imaging Study: This project proposes to integrate multimodal magnetic resonance imaging techniques in order to investigate the structural and functional connections between the ventral prefrontal cortex and the amygdala in adolescents with and without major depressive disorder.
Coauthors
Research Interests
Bipolar Disorder; Depressive Disorder; Schizophrenia
Selected Publications
- Module control of network analysis in psychopathologyPan C, Zhang Q, Zhu Y, Kong S, Liu J, Zhang C, Wang F, Zhang X. Module control of network analysis in psychopathology. IScience 2024, 27: 110302. DOI: 10.1016/j.isci.2024.110302.
- Exploring the relationship between response time sequence in scale answering process and severity of insomnia: A machine learning approachSu Z, Liu R, Zhou K, Wei X, Wang N, Lin Z, Xie Y, Wang J, Wang F, Zhang S, Zhang X. Exploring the relationship between response time sequence in scale answering process and severity of insomnia: A machine learning approach. Heliyon 2024, 10: e33485. DOI: 10.1016/j.heliyon.2024.e33485.
- Examining the association of family environment and children emotional/behavioral difficulties in the relationship between parental anxiety and internet addiction in youthWang Y, Zhou K, Wang Y, Zhang J, Xie Y, Wang X, Yang W, Zhang X, Yang J, Wang F. Examining the association of family environment and children emotional/behavioral difficulties in the relationship between parental anxiety and internet addiction in youth. Frontiers In Psychiatry 2024, 15: 1341556. PMID: 38895031, PMCID: PMC11184946, DOI: 10.3389/fpsyt.2024.1341556.
- Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders.Zheng J, Zong X, Tang L, Guo H, Zhao P, Womer F, Zhang X, Tang Y, Wang F. Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders. Psychological Medicine 2024, 1-11. PMID: 38804091, DOI: 10.1017/s0033291724000886.
- Repetitive Transcranial Magnetic Stimulation Reversing Abnormal Brain Function in Mood Disorders with Early Life Stress: from preclinical models to clinical applicationsZhao T, Guo H, Yang J, Cai A, Liu J, Zheng J, Xiao Y, Zhao P, Li Y, Luo X, Zhang X, Zhu R, Wang J, Wang F. Repetitive Transcranial Magnetic Stimulation Reversing Abnormal Brain Function in Mood Disorders with Early Life Stress: from preclinical models to clinical applications. Asian Journal Of Psychiatry 2024, 97: 104092. PMID: 38823081, DOI: 10.1016/j.ajp.2024.104092.
- From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive DisorderPan C, Ma Y, Wang L, Zhang Y, Wang F, Zhang X. From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder. Brain Sciences 2024, 14: 509. PMID: 38790487, PMCID: PMC11119370, DOI: 10.3390/brainsci14050509.
- Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral ObservationZhu Y, Zhang R, Yin S, Sun Y, Womer F, Liu R, Zeng S, Zhang X, Wang F. Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation. JMIR Public Health And Surveillance 2024, 10: e47428. PMID: 38648087, PMCID: PMC11074900, DOI: 10.2196/47428.
- Prediction of the efficacy of group cognitive behavioral therapy using heart rate variability based smart wearable devices: a randomized controlled studyLin Z, Zheng J, Wang Y, Su Z, Zhu R, Liu R, Wei Y, Zhang X, Wang F. Prediction of the efficacy of group cognitive behavioral therapy using heart rate variability based smart wearable devices: a randomized controlled study. BMC Psychiatry 2024, 24: 187. PMID: 38448895, PMCID: PMC10916138, DOI: 10.1186/s12888-024-05638-x.
- Dysregulated cerebral blood flow, rather than gray matter Volume, exhibits stronger correlations with blood inflammatory and lipid markers in depressionKang L, Wang W, Nie Z, Gong Q, Yao L, Xiang D, Zhang N, Tu N, Feng H, Zong X, Bai H, Wang G, Wang F, Bu L, Liu Z. Dysregulated cerebral blood flow, rather than gray matter Volume, exhibits stronger correlations with blood inflammatory and lipid markers in depression. NeuroImage Clinical 2024, 41: 103581. PMID: 38430800, PMCID: PMC10944186, DOI: 10.1016/j.nicl.2024.103581.
- A role for the cerebellum in motor-triggered alleviation of anxietyZhang X, Wu W, Shen L, Ji M, Zhao P, Yu L, Yin J, Xie S, Xie Y, Zhang Y, Li H, Zhang Q, Yan C, Wang F, De Zeeuw C, Wang J, Zhu J. A role for the cerebellum in motor-triggered alleviation of anxiety. Neuron 2024, 112: 1165-1181.e8. PMID: 38301648, DOI: 10.1016/j.neuron.2024.01.007.
- State- and trait-related dysfunctions in bipolar disorder across different mood states: a graph theory studyChen Y, Zhao P, Pan C, Chang M, Zhang X, Duan J, Wei Y, Tang Y, Wang F. State- and trait-related dysfunctions in bipolar disorder across different mood states: a graph theory study. Journal Of Psychiatry And Neuroscience 2024, 49: e11-e22. PMID: 38238036, PMCID: PMC10803102, DOI: 10.1503/jpn.230069.
- Integrative omics analysis reveals epigenomic and transcriptomic signatures underlying brain structural deficits in major depressive disorderZheng J, Womer F, Tang L, Guo H, Zhang X, Tang Y, Wang F. Integrative omics analysis reveals epigenomic and transcriptomic signatures underlying brain structural deficits in major depressive disorder. Translational Psychiatry 2024, 14: 17. PMID: 38195555, PMCID: PMC10776753, DOI: 10.1038/s41398-023-02724-8.
- Effectiveness of a Biofeedback Intervention Targeting Mental and Physical Health Among College Students Through Speech and Physiology as Biomarkers Using Machine Learning: A Randomized Controlled TrialWang L, Liu R, Wang Y, Xu X, Zhang R, Wei Y, Zhu R, Zhang X, Wang F. Effectiveness of a Biofeedback Intervention Targeting Mental and Physical Health Among College Students Through Speech and Physiology as Biomarkers Using Machine Learning: A Randomized Controlled Trial. Applied Psychophysiology And Biofeedback 2024, 49: 71-83. PMID: 38165498, DOI: 10.1007/s10484-023-09612-3.
- Aberrant Hippocampal Development in Early-onset Mental Disorders and Promising Interventions: Evidence from a Translational StudyYang J, Guo H, Cai A, Zheng J, Liu J, Xiao Y, Ren S, Sun D, Duan J, Zhao T, Tang J, Zhang X, Zhu R, Wang J, Wang F. Aberrant Hippocampal Development in Early-onset Mental Disorders and Promising Interventions: Evidence from a Translational Study. Neuroscience Bulletin 2023, 40: 683-694. PMID: 38141109, PMCID: PMC11178726, DOI: 10.1007/s12264-023-01162-2.
- Prediction of anxious depression using multimodal neuroimaging and machine learningZhou E, Wang W, Ma S, Xie X, Kang L, Xu S, Deng Z, Gong Q, Nie Z, Yao L, Bu L, Wang F, Liu Z. Prediction of anxious depression using multimodal neuroimaging and machine learning. NeuroImage 2023, 285: 120499. PMID: 38097055, DOI: 10.1016/j.neuroimage.2023.120499.
- Functional and Structural Connectivity Between the Perigenual Anterior Cingulate and Amygdala in Bipolar DisorderWang F, Kalmar JH, He Y, Jackowski M, Chepenik LG, Edmiston E, Tie K, Gong G, Shah MP, Jones M, Uderman J, Constable RT, Blumberg HP. Functional and Structural Connectivity Between the Perigenual Anterior Cingulate and Amygdala in Bipolar Disorder. Biological Psychiatry 2009, 66: 516-521. PMID: 19427632, PMCID: PMC2830492, DOI: 10.1016/j.biopsych.2009.03.023.
- Neuregulin 1 genetic variation and anterior cingulum integrity in patients with schizophrenia and healthy controls.Wang F, Jiang T, Sun Z, Teng SL, Luo X, Zhu Z, Zang Y, Zhang H, Yue W, Qu M, Lu T, Hong N, Huang H, Blumberg HP, Zhang D. Neuregulin 1 genetic variation and anterior cingulum integrity in patients with schizophrenia and healthy controls. Journal Of Psychiatry And Neuroscience 2009, 34: 181-6. PMID: 19448847, PMCID: PMC2674970.
- Influence of Vascular Endothelial Growth Factor Variation on Human Hippocampus MorphologyBlumberg HP, Wang F, Chepenik LG, Kalmar JH, Edmiston E, Duman RS, Gelernter J. Influence of Vascular Endothelial Growth Factor Variation on Human Hippocampus Morphology. Biological Psychiatry 2008, 64: 901-903. PMID: 18707678, PMCID: PMC2649728, DOI: 10.1016/j.biopsych.2008.07.003.
- Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imagingWang F, Jackowski M, Kalmar JH, Chepenik LG, Tie K, Qiu M, Gong G, Pittman BP, Jones MM, Shah MP, Spencer L, Papademetris X, Constable RT, Blumberg HP. Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imaging. The British Journal Of Psychiatry 2008, 193: 126-129. PMID: 18669996, PMCID: PMC2732002, DOI: 10.1192/bjp.bp.107.048793.
- Abnormal Corpus Callosum Integrity in Bipolar Disorder: A Diffusion Tensor Imaging StudyWang F, Kalmar JH, Edmiston E, Chepenik LG, Bhagwagar Z, Spencer L, Pittman B, Jackowski M, Papademetris X, Constable RT, Blumberg HP. Abnormal Corpus Callosum Integrity in Bipolar Disorder: A Diffusion Tensor Imaging Study. Biological Psychiatry 2008, 64: 730-733. PMID: 18620337, PMCID: PMC2586998, DOI: 10.1016/j.biopsych.2008.06.001.
- Anterior cingulum abnormalities in male patients with schizophrenia determined through diffusion tensor imaging.Wang F, Sun Z, Cui L, Du X, Wang X, Zhang H, Cong Z, Hong N, Zhang D. Anterior cingulum abnormalities in male patients with schizophrenia determined through diffusion tensor imaging. The American Journal Of Psychiatry 2004, 161: 573-5. PMID: 14992988, DOI: 10.1176/appi.ajp.161.3.573.