Functional Magnetic Resonance Imaging
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Imaging the Genetics of Brain Structure and Function Biological Psychology
Biological Psychology 79 (2008) 1–8 Contents lists available at ScienceDirect Biological Psychology journal homepage: www.elsevier.com/locate/biopsycho Editorial Imaging the genetics of brain structure and function ARTICLE INFO ABSTRACT Article history: Imaging genetics combines brain imaging and genetics to detect genetic variation in brain structure and Available online 11 April 2008 function related to behavioral traits, including psychiatric endpoints, cognition, and affective regulation. This special issue features extensive reviews of the current state-of-the-art of the field and adds new findings from twin and candidate gene studies on functional MRI. Here we present a brief overview and discuss a number of desirable future developments which include more specific a priori hypotheses, more standardization of MRI measurements within and across laboratories, and larger sample sizes that allows testing of multiple genes and their interactions up to a scale that allows genetic whole genome association studies. Based on the overall tenet of the contributions to this special issue we predict that imaging genetics will increasingly impact on the classification systems for psychiatric disorders and the early detection and treatment of vulnerable individuals. ß 2008 Elsevier B.V. All rights reserved. Biological Psychology, quite literally, deals with the connection 1. Imaging genetics between the body and the mind. In the past two decades two specific instances of body-mind connections have captured the What exactly is imaging genetics? In the -
Sparse Deep Neural Networks on Imaging Genetics for Schizophrenia Case-Control Classification
medRxiv preprint doi: https://doi.org/10.1101/2020.06.11.20128975; this version posted June 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Sparse Deep Neural Networks on Imaging Genetics for Schizophrenia Case-Control Classification Jiayu Chen1,*, Xiang Li2,*, Vince D. Calhoun1,2,3, Jessica A. Turner1,3, Theo G. M. van Erp4,5, Lei Wang6, Ole A. Andreassen7, Ingrid Agartz7,8,9, Lars T. Westlye7,10 , Erik Jönsson7,9, Judith M. Ford11,12, Daniel H. Mathalon11,12, Fabio Macciardi4, Daniel S. O’Leary13, Jingyu Liu1,2, †, Shihao Ji2, † 1Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA; 2Department of Computer Science, Georgia State University, Atlanta, GA, USA; 3Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA; 4Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, Irvine, CA, USA; 5Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA; 6Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, USA; 7Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, University -
Adding Structure to Function
INVITED COMMENTARY Adding Structure to Function and staging of malignant neoplasm by rate results are obtained with attenua w.hen cross-sectional anatomic im FDG PET are technically demanding. tion-correction versus emission-only aging emerged over two decades ago, A large portion of the body must be images is lacking. Centers continue to Henry N. Wagner, Jr., recognized that imaged quickly, small deposits of neo use noncorrected images for whole- the nuclear medicine community should plasm detected accurately, and the PET body oncology FDG PET, and when focus on tissue and organ function findings interpreted in the context of attenuation correction is performed, rather than anatomy (7). The value of the patient's corresponding normal and noncorrected images are often con functional imaging has not only be abnormal anatomy. At present, 2 practi sulted, in addition to corrected images, come clear since that time but is now cal, related considerations drive the before the final interpretation is ren recognized as the future of diagnostic merging of PET and CT: the need for a dered (7). imaging. Structural and functional im rapid, noise-free transmission scan for In response to the above needs, rapid aging are also increasingly understood attenuation correction of the PET emis advances have been made in the past 5 as complementary rather than compet sion data and a need for an anatomic years in the attenuation-correction hard ing imaging modalities. Over the past framework for the physiologic informa ware and software. The capacity to decade, manufacturers have considered tion provided by PET. perform transmission scans after tracer developing combined CT and PET or Without attenuation correction, PET injection has made routine whole-body SPECT imaging devices. -
Imaging Genetics Approach to Parkinson's Disease and Its
www.nature.com/scientificreports OPEN Imaging genetics approach to Parkinson’s disease and its correlation with clinical score Received: 07 November 2016 Mansu Kim1,2, Jonghoon Kim1,2, Seung-Hak Lee1,2 & Hyunjin Park2,3 Accepted: 24 March 2017 Parkinson’s disease (PD) is a progressive neurodegenerative disorder associated with both underlying Published: 21 April 2017 genetic factors and neuroimaging findings. Existing neuroimaging studies related to the genome in PD have mostly focused on certain candidate genes. The aim of our study was to construct a linear regression model using both genetic and neuroimaging features to better predict clinical scores compared to conventional approaches. We obtained neuroimaging and DNA genotyping data from a research database. Connectivity analysis was applied to identify neuroimaging features that could differentiate between healthy control (HC) and PD groups. A joint analysis of genetic and imaging information known as imaging genetics was applied to investigate genetic variants. We then compared the utility of combining different genetic variants and neuroimaging features for predicting the Movement Disorder Society-sponsored unified Parkinson’s disease rating scale (MDS-UPDRS) in a regression framework. The associative cortex, motor cortex, thalamus, and pallidum showed significantly different connectivity between the HC and PD groups. Imaging genetics analysis identified PARK2, PARK7, HtrA2, GIGYRF2, and SNCA as genetic variants that are significantly associated with imaging phenotypes. A linear regression model combining genetic and neuroimaging features predicted the MDS-UPDRS with lower error and higher correlation with the actual MDS-UPDRS compared to other models using only genetic or neuroimaging information alone. Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by bradykinesia, resting trem- ors, rigidity, and difficulty with voluntary movement1. -
Quantitative Functional Imaging of the Brain: Towards Mapping Neuronal Activity by BOLD Fmri
NMR IN BIOMEDICINE NMR Biomed. 2001;14:413–431 DOI:10.1002/nbm.733 Quantitative functional imaging of the brain: towards mapping neuronal activity by BOLD fMRI Fahmeed Hyder,1,2,5* Ikuhiro Kida,1 Kevin L. Behar,3 Richard P. Kennan,6 Paul K. Maciejewski4 and Douglas L. Rothman1,2,5 1Departments of Diagnostic Radiology, Magnetic Resonance Center for Research in Metabolism and Physiology, Yale University, New Haven, CT, USA 2Department of Biomedical Engineering, Yale University, New Haven, CT, USA 3Department of Psychiatry, Yale University, New Haven, CT, USA 4Department of Internal Medicine, Magnetic Resonance Center for Research in Metabolism and Physiology, Yale University, New Haven, CT, USA 5Section of Bioimaging Sciences, Yale University School of Medicine, New Haven, CT, USA 6Department of Diagnostic Radiology, Albert Einstein College of Medicine, Bronx, NY, USA Received 22 February 2001; Revised 22 August 2001; Accepted 22 August 2001 ABSTRACT: Quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) measurements of energy metabolism (i.e. cerebral metabolic rate of oxygen consumption, CMRO2), blood circulation (i.e. cerebral blood flow, CBF, and volume, CBV), and functional MRI (fMRI) signal over a wide range of neuronal activity and pharmacological treatments are used to interpret the neurophysiologic basis of blood oxygenation level dependent (BOLD) image-contrast at 7 T in glutamatergic neurons of rat cerebral cortex. Multi-modal MRI and MRS measurements of CMRO2, CBF, CBV and BOLD signal (both gradient-echo and spin-echo) are used to interpret the neuroenergetic basis of BOLD image-contrast. Since each parameter that can influence the BOLD image-contrast is measured quantitatively and separately, multi-modal measurements of changes in CMRO2, CBF, CBV, BOLD fMRI signal allow calibration and validation of the BOLD image-contrast. -
The Emerging Spectrum of Allelic Variation in Schizophrenia
Molecular Psychiatry (2013) 18, 38 -- 52 & 2013 Macmillan Publishers Limited All rights reserved 1359-4184/13 www.nature.com/mp EXPERT REVIEW The emerging spectrum of allelic variation in schizophrenia: current evidence and strategies for the identification and functional characterization of common and rare variants BJ Mowry1,2 and J Gratten1 After decades of halting progress, recent large genome-wide association studies (GWAS) are finally shining light on the genetic architecture of schizophrenia. The picture emerging is one of sobering complexity, involving large numbers of risk alleles across the entire allelic spectrum. The aims of this article are to summarize the key genetic findings to date and to compare and contrast methods for identifying additional risk alleles, including GWAS, targeted genotyping and sequencing. A further aim is to consider the challenges and opportunities involved in determining the functional basis of genetic associations, for instance using functional genomics, cellular models, animal models and imaging genetics. We conclude that diverse approaches will be required to identify and functionally characterize the full spectrum of risk variants for schizophrenia. These efforts should adhere to the stringent standards of statistical association developed for GWAS and are likely to entail very large sample sizes. Nonetheless, now more than any previous time, there are reasons for optimism and the ultimate goal of personalized interventions and therapeutics, although still distant, no longer seems unattainable. Molecular Psychiatry (2013) 18, 38--52; doi:10.1038/mp.2012.34; published online 1 May 2012 Keywords: CNV; functional genomics; GWAS; schizophrenia; sequencing; SNP THE NATURE OF THE PROBLEM complications (obesity, nicotine dependence, metabolic syndrome 13 Schizophrenia is a chronic psychiatric disorder characterized by and premature mortality), low employment and substantial 14 delusional beliefs, auditory hallucinations, disorganized thought homelessness. -
Brain Imaging Technologies
Updated July 2019 By Carolyn H. Asbury, Ph.D., Dana Foundation Senior Consultant, and John A. Detre, M.D., Professor of Neurology and Radiology, University of Pennsylvania With appreciation to Ulrich von Andrian, M.D., Ph.D., and Michael L. Dustin, Ph.D., for their expert guidance on cellular and molecular imaging in the initial version; to Dana Grantee Investigators for their contributions to this update, and to Celina Sooksatan for monograph preparation. Cover image by Tamily Weissman; Livet et al., Nature 2017 . Table of Contents Section I: Introduction to Clinical and Research Uses..............................................................................................1 • Imaging’s Evolution Using Early Structural Imaging Techniques: X-ray, Angiography, Computer Assisted Tomography and Ultrasound..............................................2 • Magnetic Resonance Imaging.............................................................................................................4 • Physiological and Molecular Imaging: Positron Emission Tomography and Single Photon Emission Computed Tomography...................6 • Functional MRI.....................................................................................................................................7 • Resting-State Functional Connectivity MRI.........................................................................................8 • Arterial Spin Labeled Perfusion MRI...................................................................................................8 -
Functional Renal Imaging: New Trends in Radiology and Nuclear Medicine
Functional Renal Imaging: New Trends in Radiology and Nuclear Medicine Emmanuel Durand, MD, PhD,* Philippe Chaumet-Riffaud, MD, PhD,* and Nicolas Grenier, MD† The objective of this work is to compare the characteristics of various techniques for functional renal imaging, with a focus on nuclear medicine and magnetic resonance imaging. Even with low spatial resolution and rather poor signal-to-noise ratio, classical nuclear medicine has the advantage of linearity and good sensitivity. It remains the gold standard technique for renal relative functional assessment. Technetium-99m (99mTc)- labeled diethylenetriamine penta-acetate remains the reference glomerular tracer. Tu- bular tracers have been improved: 123I- or 131I-hippuran, 99mTc-MAG3 and, recently, 99mTc-nitrilotriacetic acid. However, advancement in molecular imaging has not pro- duced a groundbreaking tracer. Renal magnetic resonance imaging with classical gadolinated tracers probably has potential in this domain but has a lack of linearity and, therefore, its value still needs evaluation. Moreover, the advent of nephrogenic sys- temic fibrosis has delayed its expansion. Other developments, such as diffusion or blood oxygen level-dependent imaging, may have a role in the future. The other modalities have a limited role in clinical practice for functional renal imaging. Semin Nucl Med 41:61-72 © 2011 Elsevier Inc. All rights reserved. he main function of the kidneys is to maintain the injection of a diagnostic agent, but physical labeling, such Thomeostasis of extracellular content. Imaging tech- as tagging or arterial spin labeling in magnetic resonance niques can indirectly explore this function by showing imaging (MRI), also may be used. Therefore, when com- processes that are used for this purpose: perfusion, filtra- paring different techniques for functional imaging, 2 as- tion, secretion, concentration, and drainage. -
CHIMGEN: a Chinese Imaging Genetics Cohort to Enhance Cross-Ethnic and Cross-Geographic Brain Research
Molecular Psychiatry (2020) 25:517–529 https://doi.org/10.1038/s41380-019-0627-6 PERSPECTIVE CHIMGEN: a Chinese imaging genetics cohort to enhance cross- ethnic and cross-geographic brain research 1 1 2 3,4 5 6 7 Qiang Xu ● Lining Guo ● Jingliang Cheng ● Meiyun Wang ● Zuojun Geng ● Wenzhen Zhu ● Bing Zhang ● 8,9 10 11 12 13 14 15,16 Weihua Liao ● Shijun Qiu ● Hui Zhang ● Xiaojun Xu ● Yongqiang Yu ● Bo Gao ● Tong Han ● 17 18 1 1 1 19 20 Zhenwei Yao ● Guangbin Cui ● Feng Liu ● Wen Qin ● Quan Zhang ● Mulin Jun Li ● Meng Liang ● 21 22 23 24 25,26 27 28 Feng Chen ● Junfang Xian ● Jiance Li ● Jing Zhang ● Xi-Nian Zuo ● Dawei Wang ● Wen Shen ● 29 30 31,32 33,34 35,36 37 38 Yanwei Miao ● Fei Yuan ● Su Lui ● Xiaochu Zhang ● Kai Xu ● Long Jiang Zhang ● Zhaoxiang Ye ● 1,39 Chunshui Yu ● for the CHIMGEN Consortium Received: 26 September 2018 / Revised: 21 November 2019 / Accepted: 27 November 2019 / Published online: 11 December 2019 © The Author(s) 2019. This article is published with open access Abstract The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral 1234567890();,: 1234567890();,: phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18–30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. -
Introduction to Imaging Genetics Half Day Morning Course / 8:00-12:00
Introduction to Imaging Genetics Half Day Morning Course / 8:00-12:00 Organizers: Jason Stein, PhD, University of North Carolina at Chapel Hill, United States This course will introduce the fundamentals of “Imaging Genetics,” the process of modeling and understanding how genetic variation influences the structure and function of the human brain as measured through brain imaging. The course begins with a brief history of imaging genetics, including discussion on replicability and significance thresholds. Then, we will review recent findings in neuropsychiatric disease risk, what neuroimaging genetics can learn from neuropsychiatric genetics, and how neuroimaging genetics can be used to explain missing mechanisms in neuropsychiatric genetics. We will cover datasets and methods for conducting common and rare variant associations, as well as bioinformatic tools to interpret findings in the context of gene regulation. Overall this course will provide the neuroimager who is not familiar with genetics techniques an understanding of the current state genetics field when exploring neuroimaging phenotypes. Course Schedule: 8:00-8:45 A brief history of imaging genetics Jason Stein, PhD, University of North Carolina at Chapel Hill, United States 8:45-9:30 The genetic influences on neuropsychiatric disease risk Sven Cichon, Dr. rer. nat., Universitat Basel, Switzerland 9:30-10:15 The effect of common genetic variation on human brain structure Paul Thompson, Imaging Genetics Center, Keck School of Medicine of University of Southern California, United States 10:15-10:30 Break 10:30-11:15 The effect of rare variation on human brain structure Carrie Bearden, University of California, Los Angeles, United States 11:15-12:00 Connecting genetic variation to gene regulation Bernard Ng, PhD, University of British Columbia, Canada . -
Measuring Brain Connectivity with Functional Imaging and Transcranial Magnetic Stimulation
30 MEASURING BRAIN CONNECTIVITY WITH FUNCTIONAL IMAGING AND TRANSCRANIAL MAGNETIC STIMULATION MARK S. GEORGE AND DARYL E. BOHNING THE PROBLEM OF ATTRIBUTING tivity and behavior. For example, if a brain region uses more CAUSALITY WITH OBSERVATIONAL glucose (fluorodeoxyglucose PET, or FDG PET) or oxygen FUNCTIONAL BRAIN IMAGING (15O PET or BOLD fMRI) while a subject performs a be- havioral act, one can safely say that this regional activity Developments in functional imaging during the past two correlates with the behavior. Most functional imaging re- decades have allowed for significant advances in understand- searchers have correctly and appropriately used the term ing how the brain functions at a systems, circuit, or organ correlate, rather than cause, knowing well that the exact level. Positron emission tomography (PET), single-photon causal relationship of the regional activity to the behavior emission computed tomography (SPECT), and blood oxy- remains unclear after even the most fastidious study. For gen level-dependent (BOLD) functional magnetic reso- example, is the region producing the behavior? Or is the nance imaging (fMRI) now allow researchers to image brain region trying to inhibit or modulate the behavior? Or is activity (usually related to oxygen or glucose use) with crisp the region only incidentally activated as part of the neural spatial and temporal resolution. For example, fMRI can network? spatially resolve structures as small as 1 to 2 mm and view A recent advance in this field involves combining func- brain activity in time blocks as brief as 2 to 3 seconds. tional imaging with transcranial magnetic stimulation Although this time resolution is crude relative to the speed (TMS), a new technology that noninvasively stimulates the of neuronal activity and information flow between brain cortex. -
[For Consideration As Part of the ENIGMA Special Issue] Ten Years
[For consideration as part of the ENIGMA Special Issue] Ten years of Enhancing Neuro-Imaging Genetics through Meta-Analysis: An overview from the ENIGMA Genetics Working Group Sarah E. Medland1,2,3, Katrina L. Grasby1, Neda Jahanshad4, Jodie N. Painter1, Lucía Colodro- Conde1,2,5,6, Janita Bralten7,8, Derrek P. Hibar4,9, Penelope A. Lind1,5,3, Fabrizio Pizzagalli4, Sophia I. Thomopoulos4, Jason L. Stein10, Barbara Franke7,8, Nicholas G. Martin11, Paul M. Thompson4 on behalf of the ENIGMA Genetics Working Group 1 Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 2 School of Psychology, University of Queensland, Brisbane, Australia. 3 Faculty of Medicine, University of Queensland, Brisbane, Australia. 4 Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA. 5 School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia. 6 Faculty of Psychology, University of Murcia, Murcia, Spain. 7 Department of Human Genetics, Radboud university medical center, Nijmegen, The Netherlands. 8 Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands. 9 Personalized Healthcare, Genentech, Inc., South San Francisco, USA. 10 Department of Genetics & UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, USA. 11 Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. Abstract Here we review the motivation for creating the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings and future directions of the Genetics Working Group.