Translational Neuroimaging: Tools for CNS Drug Discovery, Development and Treatment

Translational Neuroimaging: Tools for CNS Drug Discovery, Development and Treatment combines the experience of academic, clinical and industrial neuroimagers in a unique collaborative approach to provide an integrated perspective of the use of small animal and human brain imaging in developing and validating translational models and biomarkers for the study and treatment of neuropsychiatric disorders. Translational Neuroimaging: Tools for CNS Drug Discovery, Development and Treatment examines the translational role of neuroimaging in model development from preclinical animal models, to human experimental medicine, and finally to clinical studies. The focus of this book is to identify and provide common endpoints between species that can serve to inform both the clinic and the bench with the information needed to accelerate clinically-effective CNS drug discovery. This book covers methodical issues in human and animal neuroimaging translational research as well as detailed applied examples of the use of neuroimaging in neuropsychiatric disorders and the development of drugs for their treatment. Translational Neuroimaging: Tools for CNS Drug Discovery, Development and Treatment appeals to non-clinical and clinical neuroscientists working in and studying neuropsychiatric disorders and their treatment as well as providing the novice researcher or researcher outside of his/her expertise the opportunity to understand the background of translational research and the use of imaging in this field.

• Provides a background to translational research and the use of brain imaging in neuropsychiatric disorders
• Critical discussion of the potential and limitations of neuroimaging as a translational tool for identifying and validating biomarkers
• Identifies cross species neurosystems and common endpoints necessary to help accelerate CNS drug discovery and development for the treatment of neuropsychiatric disorders

• Language: English
• Publisher: Academic Press
• Release date: Oct 5, 2012
• ISBN: 9780123869975

Book preview

Table of Contents

Cover image

Title page

Copyright

Dedication

Preface

1.0 Introduction

2.0 Fundamentals of Neuroimaging

3.0 Translational Neuroimaging

Contributors

Acknowledgments

Abbreviation List

Chapter 1. Neuroimaging Modalities: Description, Comparisons, Strengths, and Weaknesses

1.0 Introduction

2.0 Radiotracer Techniques

3.0 Electrophysiological Techniques

4.0 Magnetic Resonance Techniques

5.0 Advantages, Disadvantages, and Practical Considerations

References

Chapter 2. Magnetic Resonance Imaging as a Tool for Modeling Drug Treatment of CNS Disorders: Strengths and Weaknesses

1.0 Introduction

2.0 MRI

3.0 MRS

4.0 Bold fMRI

5.0 Arterial Spin Labeling of Blood Flow

6.0 Conclusions

Acknowledgments

References

Chapter 3. Small Animal Imaging as a Tool for Modeling CNS Disorders: Strengths and Weaknesses

1.0 Introduction

2.0 Setting Up and Imaging Awake Animals

3.0 Typical Study Designs

4.0 Summary

Acknowledgments

References

Chapter 4. Structural Magnetic Resonance Imaging as a Biomarker for the Diagnosis, Progression, and Treatment of Alzheimer Disease

1.0 Introduction

2.0 Functional Readout of Volumetric MRI

3.0 Correlation of Structural MRI with the Neuropathology of Alzheimer Disease

4.0 Prediction of Clinical Progression to Dementia

5.0 Structural MRI in Therapeutic Clinical Trials

6.0 Use of Structural MRI in a Regulatory Setting

7.0 Conclusions

References

Chapter 5. Positron Emission Tomography in Alzheimer Disease: Diagnosis and Use as Biomarker Endpoints

1.0 Introduction

2.0 Historical Perspective

3.0 Pet as a Biomarker for Alzheimer Disease

4.0 FDG-PET

5.0 Amyloid Pet

6.0 Clinical Relevance of Amyloid Pet

7.0 Future Directions

References

Chapter 6. Rethinking the Contribution of Neuroimaging to Translation in Schizophrenia

1.0 Schizophrenia: A Complex Neuropsychiatric Syndrome

2.0 Antipsychotic Treatment and Related Challenges

3.0 Functional Neuroimaging Markers

4.0 Structural Neuroimaging Markers

5.0 Treatment Effects

6.0 Conclusions

References

Chapter 7. Neuroimaging as a Translational Tool in Animal and Human Models of Schizophrenia

1.0 Introduction

2.0 Pharmacological Models

3.0 Neurodevelopmental Factors

4.0 Effects of Antipsychotic Drugs on Brain Function

5.0 Target Validation

6.0 Conclusion

References

Chapter 8. Functional Magnetic Resonance Imaging as a Biomarker for the Diagnosis, Progression, and Treatment of Autistic Spectrum Disorders

1.0 What is fMRI?

2.0 How has fMRI been used as a Tool to Provide Insights and Advancements in the Scientific Understanding of Autistic Spectrum Disorders?

3.0 Biological Motion and Social Perception

4.0 Failing to Read Intentions: Superior Temporal Sulcus Dysfunction in Autism

5.0 Responses to Biologically Meaningful Stimuli Reveal Neuroendophenotypes of Autistic Spectrum Disorders

6.0 What has been the Clinical Value of fMRI for Autistic Spectrum Disorders?

7.0 What is the Diagnostic Utility of fMRI in Autistic Spectrum Disorders?

References

Chapter 9. Translational Neuroimaging for Drug Discovery and Development in Autism Spectrum Disorders: Guidance from Clinical Imaging and Preclinical Research

1.0 Introduction

2.0 Clinical Imaging in Autism Spectrum Disorders

3.0 Preclinical Genetic Modeling of Autism Spectrum Disorders

4.0 Challenges and Approaches in Translating from Bench to Patients

References

Chapter 10. Neuroimaging as a Biomarker for the Diagnosis, Progression, and Treatment of Substance Abuse Disorders

1.0 Introduction

2.0 Neuroimaging Approaches in Addiction

3.0 Imaging Techniques

4.0 PET Studies in Addiction

5.0 Brain Imaging in Addiction

6.0 Conclusions

References

Chapter 11. Translational Neuroimaging: Substance Abuse Disorders

1.0 Introduction

2.0 Preclinical

3.0 Clinical-Experimental Medicine Models and Drug Studies

4.0 Translational Imaging of Substance Abuse Models for Drug Discovery and Development

References

Chapter 12. Neuroimaging Approaches to the Understanding of Depression and the Identification of Novel Antidepressants

1.0 Introduction

2.0 Imaging Techniques

3.0 Characterization of Disease State and Progression

4.0 Characterization of Therapeutic Manipulations

5.0 Use of Neuroimaging in Biomarker Identification and Early Drug Discovery

6.0 Behavioral Correlates and Use of Neuroimaging Biomarkers in Models of Depression

7.0 Reciprocal Nature of Neuroimaging Results in Animal and Human Models of Depression

8.0 Summary and Future Prospects

References

Index

Copyright

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Dedication

This book is dedicated to my friend and wife, Silvia Gatti-McArthur, who has been my constant support and companion throughout this enquiry into the translational relevance of methods, models, and biomarkers for CNS drug discovery and development. It was she who first encouraged me to take my enquiry beyond my area of expertise and to focus on translational neuroimaging. Thanks to her I have spent many an hour learning and debating its pros and cons. Thank you and T. for putting up with me and pointing me in the right direction.

Preface

Brain Imaging

Translational Tools for CNS Drug Discovery, Development, and Treatment

Robert A. McArthur

McArthur and Associates GmbH, Ramsteinerstrasse 28, CH-4052 Basel, Switzerland

1.0. Introduction

1.1. Biomarker Identification and Validation

2.0. Fundamentals of Neuroimaging

3.0. Translational Neuroimaging

3.1. Alzheimer Disease

3.2. Schizophrenia

3.2.1. Preclinical and Experimental Neuroimaging

3.2.2. Clinical Translational Neuroimaging

3.3. Autism Spectrum Disorders

3.3.1. Preclinical and Experimental Neuroimaging

3.3.2. Clinical Translational Neuroimaging

3.4. Substance Abuse Disorders

3.4.1. Preclinical and Experimental Neuroimaging

3.4.2. Clinical Translational Neuroimaging

3.5. Major Depressive Disorder

1.0 Introduction

There has been an evolving crisis in the discovery and development of new drugs for the treatment of neuropsychiatric or central nervous system (CNS) disorders. Although therapeutic advancements in the treatment of some neurological disorders, for example multiple sclerosis, have been made,¹,² no major drug for the treatment of psychiatric disorders with a truly novel mechanism of action has been registered since the middle decades of the 20th century.³–⁶ This is despite the great and significant inroads that have been made in our understanding of the molecular and genetic basis of these disorders and technological advancements available to study the brain and its biology, as well as an ever-increasing number of potential therapeutic drug targets.⁷,⁸ Major initiatives have been proposed and implemented to address this issue⁹ but, even so, costly Phase III failures are forcing major drug companies to abandon further CNS research.¹⁰,¹¹ There is an urgent need to realign preclinical drug discovery and development with clinical studies, particularly at the experimental medicine interface, to improve the chances of novel drug candidates being registered as effective treatments for neuropsychiatric disorders.

Translational research is one of the initiatives proposed to improve the registration rate of CNS therapeutic drugs.¹²–¹⁴ There are many definitions of translational research.¹⁵,¹⁶ In terms of CNS drug discovery and development, we have pragmatically defined it as the reciprocal partnership between preclinical and clinical research to further new molecular entities or compounds identified through the application of basic scientific discoveries, optimized into potential drug candidates, and eventually developed into clinically effective medications.¹⁷

Brain imaging has evolved into one of the main translational tools for the study of CNS function and its various psychiatric and neurological pathologies, and for the discovery and development of novel drugs that can be used for the treatment of CNS disorders,.¹⁸–²⁰ Neuroimaging fulfills many roles in the CNS drug discovery, development, registration, and treatment process, which include techniques by which the neurobiology of neuropsychiatric disorders can be studied and understood—especially in terms of systems biology and monitoring the interactions of novel molecules with neurobiological structures and systems. The fundamental role of neuroimaging has been the identification and validation of biological markers that can detect and differentiate neuropsychiatric disorders, monitor the rate of deterioration and impairment as the disorder progresses, and determine how this deterioration can be modified through therapeutic intervention.²¹–²⁹

1.1 Biomarker Identification and Validation

Many putative biomarkers of neuropsychiatric disorders have been identified and proposed.³⁰ However, it is not sufficient simply to observe that a given biological phenomenon is associated with a particular neuropsychiatric disorder, or indeed that the phenomenon occurs reliably with the disorder, to qualify it as a biomarker.²¹,²⁶,³¹ Biomarkers, like animal models of the neuropsychiatric disorders, must undergo rigorous tests of validity³²–³⁴ before being accepted as such.

Model development in animals and humans, including the identification and validation of biomarkers, is crucial for translational CNS drug discovery and development. Though no one animal model can fully recapitulate a neuropsychiatric disorder, the aspects of the disorder being modeled help us not only to understand the neurobiology of CNS disorders but also to identify and validate molecular targets that can be manipulated pharmacologically and through which the responses to these manipulations can be monitored.³⁵–³⁸ Cross-species and homologous comparisons of these responses are fundamental for translational models.

Traditionally, animal models of CNS disorders have relied upon experimental manipulations that produce behavioral anomalies similar to the abnormal behaviors of humans, i.e. models endowed with great face validity. This modeling approach by analogy has been successfully exploited to produce more specific drugs with arguably less harmful side effects than the first drugs discovered serendipitously during the middle decades of the last century. However, they have not been so successful in predicting the eventual clinical efficacy of compounds based upon new molecular targets and mechanisms of action. The predictive validity of traditional models has thus been questioned³⁹ and defended.³⁵,⁴⁰

The identification (and validation) of reliable biological markers of status, progression, and amelioration of CNS disorders that are homologous in animal and humans would contribute greatly to the construct and predictive validity of models, acquire regulatory body recognition and approval, and improve the probability of an innovative investigational compound with a novel mechanism of action achieving registration. The construct validity of animal and human models of neuropsychiatric disorders is based upon our knowledge and understanding of their biological underpinnings.³²,³⁷ Notwithstanding the limitations of small animal neuroimaging discussed throughout this volume, this technique is being used extensively to characterize drug action in the brain and to provide construct validity not only to numerous animal models of abnormal behavior but also to putative biomarkers of the progression of behavioral disorders and their pharmacological amelioration.

Human and small animal neuroimaging is limited by methodological and standardization problems.²³,²⁵,⁴¹,⁴² Nevertheless these techniques are capable of tracking the course of a disorder in humans and model systems, as well as tracking the effects of a potential therapeutic intervention with a known mechanism of action.²⁹ For example, changes in glucose metabolism, amyloid deposition, and altered brain structure can be reliably identified, tracked, and used to define stages of the disorder and differentiate Alzheimer disease (AD)²³,²⁵ from other dementing disorders. The value of these biomarkers cannot be underestimated, particularly to help select subjects with a high probability of developing AD for clinical trials. Amyloid positron emission tomography (PET) can even track the changes in amyloid deposition induced by drugs targeting amyloid. However, an AD biomarker capable of substituting for a clinically meaningful endpoint, such as extended survival with improved cognition and function, and predicting the outcome of the therapeutic intervention²⁸ is still to be achieved.

Translational Neuroimaging: Tools for CNS Drug Discovery, Development, and Treatment is part of a series examining the translational value of animal models and other tools to further neuropsychiatric drug discovery and development.⁴³–⁴⁵ In order to do so, contributors have been carefully selected from the foremost academic and industrial clinical and preclinical researchers involved in the process of drug discovery and development, as well as the treatment of neuropsychiatric patients. Translational neuroscience is a team effort, from the original synthesis of a compound, its testing and optimization, and clinical testing to its ultimate registration and prescription. In this spirit, therefore, the authors have been asked to collaborate as coauthors to examine the translational value of neuroimaging not only from their individual perspectives, but to then present a consensual view of their topic of enquiry.

Translational Neuroimaging: Tools for CNS Drug Discovery, Development, and Treatment is structured into two sections. The first section introduces the fundamental concepts of neuroimaging, the various neuroimaging modalities being used, how neuroimaging is used to study CNS disorders in general, and specifically how neuroimaging is being used for CNS drug discovery and development. It focuses on the translational value of neuroimaging by discussing its unique contribution to neuroscience, but also the methodological issues that limit its use in humans and animals. Three introductory chapters are presented in the first section of the book.

2.0 Fundamentals of Neuroimaging

In Chapter 1, Wise⁴⁶ presents a general overview of neuroimaging modalities and the physiological, metabolic, and functional measurements that are possible. Similar overviews also form part of the introductory material presented by the authors of several other chapters. Neuroimaging is characterized by an array of various modalities from X-rays, electroencephalography (EEG), PET, magnetic resonance imaging (MRI), and magnetic resonance spectroscopy (MRS), for example, each accompanied by their acronyms. This array can be so bewildering to the nonspecialist that a roadmap is considered appropriate. Each neuroimaging modality has its strengths and weaknesses. No one modality is sufficient to give a complete view of the brain or the effects of drugs on the brain and, indeed, various neuroimaging modalities can and are used in combination to give a more complete view. Neuroimaging provides a window into the brain, its structure, activation, and metabolic patterns under default or resting conditions, as well as in response to challenges such as disease, drugs, environment, or genetics. With appropriate radiolabeled tracers, PET can be used to quantify physiological processes and to map the brain, measure cerebral metabolism and blood flow, aid in differential diagnosis, and study receptor systems. PET is used, for example, to determine the engagement of a novel molecule with receptors, which is an essential step for CNS drug discovery and development. One drawback of neuroimaging techniques such as X-rays or PET imaging is the need to subject the body to various forms of radiation: thus, these techniques are limited by exposure levels.

There are a number of noninvasive techniques, of which EEG or magnetoencephalography (MEG) are well known and have been in practice for decades. EEG recordings in response to evoked potentials have long being used in the study of CNS disorders such as schizophrenia, depression, and AD. Magnetic resonance techniques such as MRI make use of physiological responses to magnetic fields without having to rely on radiolabeled isotopes. Changes in the structure of the brain in response to disease, as well as changes in function, can be studied with MR techniques. MRS, on the other hand, can be combined with imaging to detect and quantify changes in metabolites such as N-acetylaspartate, creatine, and choline by tapping into naturally occurring isotopes, which are indicative of neuronal health. Functional MRI (fMRI) is used to study changes in neural activity from changes in cerebral blood flow, volume, and oxygenation. Protocols include blood oxygenation level dependent (BOLD) contrast, which provides good temporal and spatial resolution, especially when examining the brain’s response to specific tasks or demands. Arterial spin labeling (ASL) is another protocol used in functional neuroimaging. Functional neuroimaging can be performed under resting or default conditions, where the brain is assumed not to be responding to overt external stimulation, or in response to an externally applied task or condition such as the administration of a drug (as in pharmacological MRI; phMRI). fMRI techniques have become essential for the study of brain in terms of integrated systems of functional connectivity and how these systems are altered under states of disease or disorder. phMRI, on the other hand, has been important for the development and use of drugs as pharmacological tools to probe brain function and as a method to characterize the distribution and interaction of novel drugs with brain systems in studies of mechanism of action and proof of concept.

In Chapter 2, Brown⁴¹ presents a detailed explanation of the principles and the physics behind MRI modalities, and considers the strengths and weaknesses of each. The main advantage of MRI modalities is the ability to conduct repeated imaging without the need for contrast agents and multimodal imaging, where multiple readouts are possible from the same subject in a single session. An additional advantage of MRS, for example, is that it enables the assessment of metabolic changes in response to disease or drug exposure. Weaknesses of magnetic resonance modalities include a lack of standardization, which can affect the reliability and reproducibility of the method and intrinsic signal strength or spatial resolution and limit the types of observable nuclei, neurotransmitters, and metabolites, as well as leading to the ambiguous interpretation of some metabolites. Brown discusses the differences between BOLD fMRI and ASL. Both are noninvasive multimodal neuroimaging techniques that provide information about distributed brain function, and protocols exist for deriving BOLD and ASL signals from the same session. Weaknesses of using a BOLD protocol include derived rather than physiological readouts, blood-vein contrast differences, signal drop out due to magnetic field gradients, and image distortion. ASL protocols, on the other hand, are capable of deriving cerebral blood flow readouts in physiological units, minimize the blood-vein contrast limitation of BOLD, and are not as prone to signal dropout. However, ASL protocols have modest temporal resolution and poor signal-to-noise and contrast-to-noise ratios, which contrast with the better spatial and temporal resolution of BOLD protocols.

Small animal imaging is a valuable translational tool not only to study and characterize basic neurobiology in animals but also to help develop and validate models of CNS disorders, and ultimately progress a novel compound from discovery through to early clinical development. However, small animal imaging is restricted by a number of limitations, some of which are shared with human neuroimaging, particularly motion artifacts. In Chapter 3, Ferris and his colleagues⁴² address these limitations by modifying the design of the apparatus, improving signal resolution, introducing image analysis software, and habituating animals to the procedure before performing an imaging experiment. For example, anesthesia is generally used to place an animal in a restrainer before being scanned and keep it from moving throughout the experiment. This is a major limitation of small animal neuroimaging because the introduction of an anesthetic is a confounding factor in these experiments, not least because of resulting changes in cerebral blood flow and drug–drug interactions on brain systems of interest.⁴¹,⁴⁷ Ferris and colleagues have overcome this limitation by habituating animals to the restraint and scanning procedure and independently monitoring the effects using physiological and neuroendocrinological markers of stress. This procedure is repeated over a period of weeks until there is a return to baseline responses.

In the development of animal models for CNS disorders, abnormal behaviors are induced by various manipulations such as acute or chronic drug administration, lesions, and genetic or environmental manipulations. The effects of these manipulations are then assessed using different endpoints such as behavior, biochemistry, or neuroimaging, which help provide the construct validity of the model.³² Throughout this book, there are numerous examples of how the construct validity of animal and human models of CNS disorders is assessed. Ferris and colleagues describe the development of a model of anxiety through predatory fear, whose effects are assessed in the conscious animal by neuroimaging. Following the habituation procedure described above, the animal is replaced in the scanning apparatus and subjected to the novel taste of sucrose in the presence of a predator. This presence of a predator elicits a biological fear response conditioned to the taste of sucrose such that physiological responses will be elicited in the absence of the predator during subsequent scanning. This procedure has revealed an integrated neural pathway in the circuit of Papez, on which the effects of therapeutic drug treatment on the behavioral and neuro-activation patterns can be assessed.

3.0 Translational Neuroimaging

The second section of the book is subdivided into specific neuropsychiatric therapeutic areas, which are primarily psychiatric: autism spectrum disorders (ASDs), major depressive disorders, schizophrenia, and substance abuse disorders. These therapeutic areas were chosen on the basis of the extensive use of neuroimaging in their diagnosis and in monitoring the progression of the disorders and the effect of therapeutic intervention. These areas were also chosen to show how neuroimaging contributes to the discovery of novel compounds being developed to treat these disorders. Each therapeutic area in the second section is further subdivided into two chapters. The first focuses on the clinical aspects of neuroimaging techniques, that is, their use as diagnostic criteria and for monitoring disease progression. The second concentrates on the use of neuroimaging as a tool for drug development and validation of human and animal models of the CNS disorder being considered. Throughout the second section of Translational Neuroimaging: Tools for CNS Drug Discovery, Development and Treatment the following themes are explored: construct validity of animal and human experimental medicine models through neuroimaging, endophenotypes, imaging biomarkers, imaging genetics, and systems biology.

3.1 Alzheimer Disease

Although this volume concentrates on psychiatric rather than neurological disorders, it should not be inferred that neuroimaging has not had a major impact on basic neurological disorder research, drug discovery and development, and treatment.⁴⁸ Psychiatric disorders are defined primarily by clinical behavioral manifestations⁴⁹ as opposed to the physical, usually neurodegenerative, phenomena that characterize neurological disorders.⁵⁰ AD, however, is a neurological disorder that is characterized both behaviorally and physically. Two chapters examine the role of neuroimaging in the study of this disorder and on differential diagnosis and monitoring the effects of therapeutic interventions.

In Chapter 5, Schmidt and his colleagues²⁵ present a detailed discussion on PET imaging and its use as a diagnostic tool, a tool to identify and validate biomarkers of AD, and in clinical trials of novel therapeutic agents for its treatment. Neuropsychiatric clinical trials can be particularly problematic, not only because of the lack of neuroimaging standardization leading to poor reproducibility, as discussed by Brown in this volume,⁴¹ but also owing to the globalization and multiplicity of clinical trial centers, all of which can impact upon the reliability of the measures.⁵¹,⁵²

Therapeutic effectiveness in psychiatric clinical trials,⁵¹,⁵³ as well as in clinical trials of prospective drugs for some neurological disorders with a strong behavioral component such as AD,⁵² is assessed through the use of psychometric rating scales, scales of quality of daily living, and self- or carer assessments. These scales, though validated and used extensively over the years, are beset by many problems, including susceptibility to placebo responses,⁵⁴ lack of standardization of training of raters,⁵⁵ and cultural differences, especially in multicenter studies done in many countries.⁵¹ Functional endpoints, including neuroimaging, can be measured with great accuracy and precision in both animals and humans and are used throughout the late discovery and early development stage of a potential drug candidate;³⁵ however, they do not necessarily correlate with subjective rating scale measures of clinical efficacy. The identification, development, and validation of neuropsychiatric biomarkers and their integration into clinical trials is being encouraged by regulatory bodies.²⁸,⁵⁶–⁶¹

Some sources of variability in PET imaging identified by Schmidt and his colleagues include: differences in data acquisition protocols; different scanner models; motion artifacts; comparison of several images taken over time and averaged across subjects; spatial mapping of a subject’s PET or MRI image to a reference brain space; different software for normalizing images; and the analysis of image data. A number of government–academic–industrial initiatives and consortia have been established over the past decade in order to help standardize the use of neuroimaging in the study and treatment of AD, including the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Australian Imaging Biomarkers and Lifestyle (AIBL) initiative, and the European Collaboration for the Discovery of Novel Biomarkers for Alzheimer’s Disease (AddNeuroMed).

AD is a disorder whose final diagnosis has typically been dependent upon postmortem pathological evidence of neurodegeneration, neuritic plaques, and neurofibrillary tangles,⁶² while diagnosis of probable AD has been made on the basis of progressive dementia and other cognitive deterioration in the absence of other neurologic, psychiatric, or systemic disorders.⁶³ These criteria have been reviewed over the years in order to define and monitor the progression of AD dementia from benign forgetfulness to mild cognitive impairment (MCI) and finally to Alzheimer dementia.⁶⁴ The recognition of a prodromal state of AD (amnestic MCI) has stimulated the search for biomarkers that can diagnose and monitor the progression of AD and differentiate AD from other forms of dementia. These biomarkers help to identify subjects who can be used in proactive clinical trials of AD therapeutic agents that may help treat patients before frank dementia occurs.

The amyloid hypothesis of AD ⁶⁵ has been one of the dominant drivers of research into the causes of AD and its potential treatment. A number of radiolabeled amyloid tracers have been developed, such as ¹¹C-PiB, which have been used at multiple sites and for serial testing. ¹⁸F-AV-45 has also been approved by the US Food and Drug Administration as an amyloid tracer. These tracers are being used to monitor the progression of dementia in the elderly from MCI to probable AD. Between 89% and 98% of probable AD subjects are PiB positive and a significant proportion of elderly subjects who go on to develop this disorder are also PiB positive. Notwithstanding the importance of the amyloid hypothesis to guide AD therapeutics, this disorder is also associated with reduced cerebral glucose metabolism. Changes in brain glucose metabolism have been imaged using tracers such as ¹⁸F-fluorodeoxyglucose. Studies using this tracer indicate that a pattern of cerebral hypometabolism related to progressive Alzheimer dementia can be differentiated from other types of dementia such as frontotemporal dementia.

In Chapter 4, Novak and Einstein²³ focus on the use of structural MRI (sMRI) as a tool to establish biomarkers for the study of AD. Similar to the discussion of PET by Schmidt and colleagues, they discuss the limitations and methodological problems arising from the use of MRI. The importance of MRI and its use in therapeutic clinical trials, as well as the position of regulatory authorities on the use of neuroimaging in clinical development, are also discussed. sMRI has been used to identify and follow the course of the key neuropathological changes in AD, that is, neuritic amyloid plaques, diffuse β-amyloid protein deposits, and neurofibrillary tangles, neurodegeneration, and gliosis. sMRI has also been used to relate neuroanatomical changes to neurocognitive tests and tests of functional ability. For example, it has been observed that cognitive impairments and loss of brain volume on MRI are more closely related to neurofibrillary tangles and neuron loss on post-mortem examination than to amyloid burden, particularly for medial temporal structures such as the entorhinal cortex and hippocampus. On the other hand, increased amyloid deposition occurs early in AD, perhaps initiating the pathological cascade of atrophy and cognitive deterioration. Regional patterns of atrophy described by sMRI have been used for differential diagnosis of AD from other dementing pathologies, such as frontotemporal dementia, to differentiate the pathological changes due to AD from those observed in healthy elderly subjects, and to map the modulatory effects of genetic polymorphisms such as the Apolipoprotein E ε4 (APOE ε4) allele on the rates of neurodegeneration and cognitive deterioration.

Both Schmidt and colleagues and Novak and Einstein review the use of neuroimaging during clinical trials of clinically active and potential therapeutic agents for the treatment of AD. The effects of clinically active and registered drugs such as donepezil (Aricept), memantine (Namenda), galantamine (Razadyne) have been examined by PET neuroimaging in clinical studies.²⁵ Aricept, Namenda, and Razadyne tend to maintain improved glucose metabolism in frontal and temporal cortices and these changes can be related to maintenance in cognitive scores. Aricept and Exelon (rivastigmine) have been studied in MCI subjects.²³ While Aricept failed to alter hippocampal or entorhinal volumes, it did lower the rate of brain atrophy and the effects correlated with cognitive scores. Exelon also induced a slower rate of ventricular volume change during the first two years of the study.

Neuroimaging has also been used to examine the effects of experimental drugs in AD patients and MCI subjects. Phenserine, intravenous immune globulin, intranasal insulin, and rosiglitazone all preserved or increased glucose metabolism associated with generally positive though varying effects on cognitive ability.²⁵ Novak and Einstein report on the use of MRI on clinical studies using vitamins in MCI and AD subjects.⁶⁶ Vitamin E had no effect, but the combination of vitamins B6 and B12, and folic acid reduced homocysteine values, reduced whole brain atrophy, and had positive effects on cognitive ability. The effects of the muscarinic M1 receptor functional agonist, milameline, were also assessed by MRI. Though the trial was stopped for apparent lack of clinical efficacy,⁶⁷ changes in temporal horn volume that correlated significantly with cognitive changes were observed.²³ Since, 2000, there has been a concerted effort to develop anti-amyloid treatment for AD through the use of antibodies ⁶⁸,⁶⁹ such as bapineuzumab and gantenerumab. Amyloid PET scanning has described reduced amyloid burden, as measured by ¹¹C-PiB-PET.²⁵ MRI assessment of the effects of bapineuzumab failed to show significant changes in brain or ventricular volume, but a reduction in volume loss, associated with clinical efficacy was seen in a subgroup of subjects who were APOE ε4 noncarriers. Nonetheless, reduced brain volume was noted in some AD patients treated with AN-1792, compared to placebo.²³

3.2 Schizophrenia

3.2.1 Preclinical and Experimental Neuroimaging

Aspects of schizophrenia have been traditionally modeled pharmacologically using drugs like amphetamine that produce psychotic-like behavior in humans and animals.⁷⁰,⁷¹ It was later observed that NMDA (N-methyl-D-aspartate) receptor antagonists like phencyclidine and ketamine also produce psychotomimetic symptoms both in humans⁷² and animals.⁷³ This work and others implicated two major neurotransmitters with schizophrenia and psychosis, and have given rise to the dopaminergic⁷⁴ and glutamatergic⁷⁵ hypotheses of this disorder. Steckler and Salvadore⁷⁶ discuss the use of neuroimaging following acute or repeated administration of these drugs, the effects of which are generally mirrored in animal and human experimental studies. The effects of amphetamine are related to the magnitude of dopamine release and can be blocked by dopamine receptor blockers. The effects of ketamine, however, are not generally altered by dopamine receptor blockers, but rather by drugs that enhance glutamatergic activity. Ketamine is being used in human experimental medicine as a model biological vulnerability to psychosis that is related to changes in prefrontal cortical activity and subsequent perceptual illusions and delusional ideations. The induction of positive symptoms by ketamine is related to increased glutamate in the anterior cingulate cortex (ACC). These results are also reflected in animal studies, providing cross-species consistency, and are of translational value.

Other models of schizophrenia in animals include genetic⁷⁷ and neurodevelopmental⁷⁸ models. Neuroimaging plays a major role in describing the effects of genetic variations on brain function and structure, and on the establishment of intermediate phenotypes or endophenotypes to study psychiatric disorders.⁷⁹ Imaging genetics is a rapidly expanding field that combines investigations of risk genes identified through genome-wide association studies, for example. This work could provide novel drug targets to be validated and taken beyond the limitations of traditional animal and human experimental models. Steckler and Salvadore focus on polymorphisms in the ZNF804A and DISC1 genes to illustrate the methods and applications of imaging genetics and the translational potential of this approach. Genetic animal models reviewed by Steckler and Salvadore in Chapter 7 include transgenic mice expressing a dominant-negative form of the DISC1 (disrupted-in-schizophrenia 1) gene; mice lacking the stable tubule-only polypeptide (STOP); NCAM-180 knockout mice; mice lacking the complexin-2 (Cplx2) gene; mice overexpressing the G-protein coupled receptor SREB2/GPR85; and transgenic chakragati (ckr) mice. These murine models display enlarged ventricles reminiscent of those reported in schizophrenic patients.

Schizophrenia can be regarded as a neurodevelopmental disorder modified by environmental factors.⁸⁰ The time course of ventricle enlargement has been observed in young DISC1 mutant mice and in Cplx2 knockout mice subjected to a perinatal head trauma. The results of the latter study indicate the value of neuroimaging when carrying out genetic × environment studies in animal models. Among the neurodevelopmental animal models of schizophrenia are prenatal infection models of the dam using human influenza virus or agents that cause inflammation. These procedures have shown postnatal brain atrophy and anisotropy in the brains of the offspring, demonstrated by neuroimaging. Further, these prenatal insults are related to abnormal behaviors related to schizophrenia. Lateral structural enlargement appears to be a common sign of rodent models of schizophrenia, including prenatal lesion induction with the mitotoxin methylazoxymethanol acetate. Of note, however, is the specificity of these genetic models, which are also considered as models of autism.¹⁶ This is consistent with the emerging view that many psychiatric disorders are part of spectra rather than categories.⁸¹

3.2.2 Clinical Translational Neuroimaging

Contrary to the neurodegenerative hypothesis of schizophrenia,⁸² in Chapter 6 Tost et al.²⁶ propose that schizophrenia is a genetically predisposed state of maladaptive structural organization of neural circuits that promotes the emergence of clinical symptoms in adulthood. They do so through their examination of the role of neuroimaging in schizophrenia from a systems biology perspective that integrates regulatory neural prefrontal-limbic circuits, including the prefrontal cortex, hippocampus, and striatum. fMRI has contributed to this mapping of the neural systems underlying aspects related to schizophrenia such as impairments in working memory [dorsolateral prefrontal cortex (DLPFC), rostral ACC (rACC), and inferior parietal areas], reward and salience (midbrain and ventral striatum), and regulation of emotions (amygdala and higher-order areas of the prefrontal or cingulate lobe). Imaging genetics is an important tool in this mapping. The ZNF804A genotype and interstitial deletions in chromosome 22q11 are linked to genetic risks in schizophrenia and are implicated in abnormal prefrontal-hippocampal connectivity.i

Consistent reductions in gray matter volume, particularly frontal-temporal cortices, are found by sMRI in healthy but at-high-risk subjects, as well as in first-episode schizophrenics. Similarly, DTI studies indicate impaired axonal integrity, which has also been observed in healthy, but at-risk, relatives. These observations are important, suggesting potential endophenotypes or markers for the prodromal stage of schizophrenia.⁸³

Dopaminergic ligands are used extensively in receptor occupancy studies.⁸⁴ In Chapter 7, Steckler and Salvadore⁷⁶ report a few inconsistent effects of clinically active antipsychotics such as haloperidol (Haldol), clozapine (Clozaril), risperidone (Risperdal), sulpiride (Dolmatil), or amisulpiride (Solian) in healthy subjects and rats. Haldol showed limited effects on cerebral blood flow, BOLD response, and metabolism in healthy human subjects. However, according to the review of Tost et al., describing clinically active antipsychotics in schizophrenic patients,²⁶ Haldol reduces global gray volume in schizophrenics, an effect associated with long-term antipsychotic exposure. These results are discussed in terms of neurotoxic effects of antipsychotics and neuronal remodeling. Tost et al., further report that olanzapine (Zyprexa) and quetiapine (Seroquel) restore task-related activation and connectivity patterns, and disturb neural activation during working memory, emotion processing, and verbal fluency tasks, respectively, in schizophrenic patients.

3.3 Autism Spectrum Disorders

Imaging genetics plays a crucial role in present CNS drug discovery and development for the treatment of ASDs, which have many behavioral characteristics whose pathology is poorly understood and which have a complex environmental and genetic etiology.⁸⁵ Furthermore, there is no drug approved for the treatment of the core symptoms of communication difficulties, social challenges, and repetitive behavior associated with ASD.²⁷ The antipsychotic drugs Risperdal or aripiprazole (Abilify) have been approved to treat autism-related irritability. The off-label use of many classes of drugs [psychostimulants, e.g. amphetamine (Adderall); selective serotonin reuptake inhibitors, e.g. fluoxetine (Prozac); opioid receptor antagonists, e.g. naltrexone (Revia); and antiepileptics, e.g. valproic acid (Depakote)] form part of the polypharmacy used to treat behavioral symptoms.ii

This has prompted a concerted and international effort to pool together the resources of the pharmaceutical industry, academic groups, and patient interest groups to carry out basic research into this disorder, with the intention of discovering effective pharmacological therapy for its treatment.iii

In Chapter 9, Badura and colleagues¹⁶ discuss the role of imaging genetics in the development of animal models of ASD.

sMRI and fMRI have identified abnormalities related to core symptoms of ASD such as emotional and social intelligence. Face and emotion recognition procedures indicate that ASD subjects show hypoactivation in the amygdala or fusiform regions in response to happy and neutral faces. This hypoactivation is also seen in unaffected siblings, suggesting an ASD endophenotype. While ASD subjects do not appear to have trouble recognizing faces, they appear to have difficulty in interpreting emotional cues. This may be due to the degree of familiarity of the face as well as the speed of recognition of the emotion.iv

Similarly, apparent memory difficulties in ASD subjects may be related to strategies for completing a task. One psychological construct tested by neuroimaging is that of the self-versus-other reflection, mediated through activation of the ventromedial prefrontal cortex, in which ASD subjects show reduced activation in this area as well as the ACC. Hypoactivity in the ventromedial prefrontal and cingulate cortices and decreased connectivity between insular cortical regions with somatosensory cortex and amygdala are evident even during resting states and suggest that these networks may underlie self-introspection and emotional regulation.

3.3.1 Preclinical and Experimental Neuroimaging

Badura and colleagues discuss the strengths and weaknesses of neuroimaging techniques as a translational tool for model development and drug discovery and development. For example, fMRI is an effective tool for identifying groups of brain regions or systems under control and experimentally manipulated conditions. This neuroimaging readout helps provide construct validity to the models used to study the neurobiology of ASD and to strengthen their use to test and optimize compounds discovered as potential therapeutic agents. Novel statistical and procedural approaches in neuroimaging are being developed to address the methodological limitations of neuroimaging. The increasing use of machine learning or multivariate pattern recognition techniques are helping to improve the signal-to-noise characteristics of neuroimaging. These techniques are improving identification of the CNS site of action and the time course of novel compound activity, as well as the study of single subjects rather than group classification.

Notwithstanding the complex genetics of ASD, this disorder is associated with a number of neurodevelopmental disorders which share autistic phenotypes. These disorders include 22q13 deletion, Angelman, fragile X, and Rett syndromes. Animal genetic models are providing a method of entry into the study of ASD. Various mutant murine models of syndromic ASD have been developed. The fragile-X syndrome Fmr1 knockout mouse, for example, displays altered sensitivity to sensory stimuli, attention deficits, hyperactivity, impulsivity, increased repetitive behaviors, and resistance to change. This mouse has been used to develop leading glutamatergic⁸⁶ and GABAergic⁸⁷ approaches for the treatment of ASD. The Rett syndrome model is based on the deletion of the X-linked gene MECP2 (methyl CpG binding protein 2). These mice display breathing abnormalities, hind limb clasping, motor dysfunction, seizures, tremors, and/or learning and memory deficits. Conditional deletion of the PTEN (phosphatase and tensin) gene on chromosome 10 can produce decreased social interactions and recognition, hyperactivity, increased anxiety-like behaviors and startle response, learning and memory impairments, prepulse inhibition deficits, and seizures. Neuroligin-4 knockout mice display decreased social interactions and recognition and increased aggression. Neuroligin-3 and neurexin-1α knockout mice display more subtle behavioral abnormalities. Other mutant mouse models discussed by Badura and colleagues include CNTNAP2 (contactin-associated protein-like 2) gene knockouts, SHANK3 gene knockouts, chromosome 15q11–13 duplication, and the BTBR T+tf/J inbred mouse strain. This mouse strain displays impairment in several social behavior tasks, abnormalities in vocalizations in response to social stimuli, repetitive grooming behavior, and aberrant learning and memory, as well as a spontaneous deletions of the DISC1 gene.⁷⁶

3.3.2 Clinical Translational Neuroimaging

In Chapter 8, Westphal et al.²⁷ focus on the social dysfunction characteristic of ASD, which is thought to occur early during development and to precede and have functional consequences on other core symptoms of the disorder. A number of neuroanatomical structures are involved in social perception, including the posterior superior temporal sulcus (STS). The right posterior STS, has been implicated in the interpretation of the actions, intentions, and psychological dispositions of others. Westphal and colleagues have combined virtual reality procedures with neuroimaging to explore the role of the STS in social information processing.

These studies in young and adult participants demonstrate that the STS responds more strongly to walking human figures or a robot simulacrum than to an inanimate object or disjointed mechanical figures. Biological motion selectively activates the posterior STS. Activity in the posterior STS is sensitive to making eye contact with others, that is, the intention of establishing social interaction. Further, activity in the posterior STS is sensitive to actions that are congruent or incongruent with prior emotional context related to understanding another’s preferences. These results support the contention of Westphal et al. that the posterior STS has a role in processing socially relevant stimuli.

ASD individuals avoid eye contact and have trouble connecting the information conveyed during eye gaze with its significance. In studies comparing ASD children with normal children and children with delayed but normal development, ASD children are capable of reporting the direction of a gaze in a cartoon character, but not of reporting the intention of that gaze. This inability is also related to the degree of social impairment.

Comparing children with ASD, unaffected siblings, and typically developing children is an elegant way of determining potential endophenotypes.⁷⁹ Differential activation of brain areas in response to biological motion relative to scrambled motion identifies dysfunctions in brain activity specific to ASD (state regions) and disrupts neural circuitry shared by the ASD children and their unaffected siblings (trait regions), as well as compensatory recruitment of brain areas by the unaffected siblings.

These responses can not only be used to differentiate children with ASD at an early age but also give clues to potential endophenotypes. These results also illustrate the compensatory ability of the brains of individuals to maintain normal social function. The association of neuroimaging results with the Social Responsiveness Scale (SRS) scores used in the clinical definition of efficacy in clinical trials was evaluated. Significant negative correlations were observed between activity in the right posterior STS of ASD subjects and their SRS score (state activity), as well as between STS activity and SRS scores of unaffected siblings (trait activity).

3.4 Substance Abuse Disorders

Clinical studies of substance abuse are complicated by a number of factors. Subjects, for example, typically abuse more than one substance and many substance abusers have comorbid infectious, metabolic, neurologic, or psychiatric problems. Furthermore, there are ethical issues involved with the administration of drugs to drug-naive humans as well as to potential subjects who have managed to cease their drug-taking.⁸⁸ Clinical experimental medicine studies of substance abuse are therefore carried out in current users of the drug who are not seeking treatment. Notwithstanding this limitation, there are a number of methodological similarities in human experimental and animal models that help establish common endpoints in human and animal responses necessary for preclinical and clinical translation of CNS drug development. For example, self-administration procedures in humans are similar to those used in animals, that is, the human or animal subject is required to carry out an action such as a button or lever press in order to get their drug. The amount of work that the subject is willing to expend in order to get a drug or to maintain or vary a dose level can be easily manipulated experimentally and is related to motivational aspects of the procedure. Similarly, while it is difficult to separate genetic from environmental factors in studies of human genetics, these are complemented by studies in genetic animal models where environmental factors can be more carefully controlled. In Chapter 11, Schwarz and colleagues³⁸ present an overview of animal and human experimental medicine models of substance abuse disorders and review the neuroimaging methods used.

3.4.1 Preclinical and Experimental Neuroimaging

Neuroimaging provides a biological readout by which the construct validity of animal models and biomarkers can be established. Aspects of substance abuse disorders can be modeled experimentally through manipulations of the animal’s genetic background, environment, or through pharmacological manipulations.⁸⁹,⁹⁰ These are the inducing manipulations that characterize the individual models, the effects of which are then evaluated behaviorally, biochemically, or electrophysiologically.³²,⁹¹,⁹² Neuroimaging techniques are becoming essential tools to (1) characterize the effects of the inducing conditions (e.g. stress, genetic background, forced or voluntary exposure, and self-administration of drugs of abuse) on the animal; or (2) the effects of drugs of abuse on the drug-naive animal or the model preparation.⁹³ Because of the difficulty in scanning conscious animals, neuroimaging studies characterizing a behavioral model need to be done in parallel, that is, the behavioral characteristics of the model are usually evaluated before scanning the anesthetized animal. Nevertheless, PET and MRI studies in small animals are being done routinely, but one should be aware of the possible confounding effects of anesthesia or stress on the neuroimaging readout.⁴²,⁹³ For example, Schwarz and colleagues describe how 2-deoxyglucose (2-DG) PET and phMRI studies have been used to follow changes in local cerebral glucose utilization (LCGU) in response to changes in blood alcohol levels in drug-naive animals, and how these changes can be modified by drugs. Similar studies have been carried out to characterize the effects of amphetamine, cocaine, and nicotine.

MRS studies have been carried out in rats chronically exposed to alcohol to describe the neurochemical changes associated with this exposure. Similarly, the effects of chronic alcohol exposure on brain structure, function, and metabolism have been carried out. Interestingly, differential effects of anesthesia on 2-DG-imaged LCGU following acute alcohol withdrawal have been described: LCGU was increased in anesthetized animals but reduced in conscious and minimally restrained animals. Chronic alcohol exposure in humans, on the other hand, is linked to reductions in brain volume, disruptions in white matter microstructure, temporal lobe atrophy, and reductions in N-acetyl aspartate (NAA), choline (Cho), and GABA (γ-aminobutyric acid). These effects can be partially reversed through abstinence. Similar effects are reported following chronic nicotine abuse, though temporal lobe atrophy appears more affected by smoking.

3.4.2 Clinical Translational Neuroimaging

Although substance abuse disorders properly refer to the addiction to substances such as alcohol, psychostimulants, and other drugs of abuse, there has been a growing realization that behavioral addictions such as gambling and impulsivity share common neural substrates. A number of motivational theories have been put forward such as reward deficit,⁴⁵,⁹⁴ impulsivity,⁹⁵,⁹⁶ or allostasis.⁹⁷ In Chapter 10, Nutt and Nestor²⁴ discuss neuroimaging clinical studies in the light of these motivational theories.

Notwithstanding the problems inherent in carrying out human clinical studies in substance abusers (discussed above), clinical neuroimaging studies in abstinent or treatment-seeking subjects are identifying and establishing biomarkers of addictive behavior.²⁴ Neuroimaging and other studies have implicated the ACC, amygdala, hippocampus, lateral prefrontal cortex, nucleus accumbens, orbitofrontal cortex, and ventral striatum as key components in addictive behaviors. In terms of neurotransmitters, the dopaminergic, GABA, and opioid systems have been most studied. Neuroimaging has been greatly advanced by the availability of radiolabeled ligands that interact with these systems, such as ¹¹C-raclopride and ¹⁸F-fallypride (dopaminergic system), ¹¹C-carfentanil (opioid system), and ¹¹C-flumazenil and ¹²³I- iomazenil (GABAergic system). Nevertheless, there is a need to develop other radioligands targeting other systems.

PET studies have been used to identify potential biomarkers of the development of substance abuse addiction. For example, subjects addicted to alcohol, cocaine, heroin, and methamphetamine show impaired dopaminergic neurotransmission including reductions in dopamine (DA) release and D2/3 receptor numbers, which is associated with their addiction behaviors. Elevations in μ-type opioid receptors in the striatum, prefrontal cortex, and other cortical areas are observed in early alcohol and drug abstinence. These may underlie symptoms such as craving, distress, and dysphoria. It has been reported that mOR binding can predict treatment outcome better than standard clinical variables. On the other hand, the GABAergic system is characterized by impaired GABA function and downregulated receptors, which may contribute to the seizures and anxiety observed in alcohol withdrawal, for example.

Relapse of drug seeking and abuse is associated with craving or reaction to drug-related stimuli. Pharmacological imaging studies have identified common areas of neural activation for abused substances, and the high temporal resolution of fMRI allows the temporal sequence of brain activity to be correlated with changes in subjective ratings of experiences following drug administration, including feelings associated with craving. Gustatory and olfactory cues related to alcohol, for example, are capable of increasing the BOLD response in the mesocorticolimbic system. Craving and relapse can also be studied without giving drugs to experimental subjects by the use of visually presented stimuli. These direct cues can be conditioned to previously neutral visual cues and elicit activated BOLD responses. Reactivity to smoking-related cues in the insula and dorsal ACC may be a predictive marker of relapse, while reductions in activity in the amygdala, orbitofrontal cortex, thalamus, and ventral striatum may help predict treatment effects. Studies in alcoholics indicate that activation to alcohol-related stimuli in specific cortical and subcortical regions may also serve as predictive biomarkers of relapse and treatment. These studies are helping us to understand the process of relapse and guide drug discovery and the development of treatments for substance abuse.

A number of clinically active and experimental drug studies have been carried out in nontreatment-seeking alcoholics. Abilify, Revia, and the 5-HT3 receptor antagonist ondansetron (Zofran) reduce visual cue-induced activation as well as subjective feelings of craving. The effect of Revia is consistent with the observed effects of this drug on drinking patterns in humans.⁹⁸ Varenicline (Chantix) and bupropion (Zyban) are drugs approved for the treatment of smoking. Both drugs have been shown to reduce regional brain activation and subjective feelings of craving in response to cigarette-related cues.⁹⁹

3.5 Major Depressive Disorder

In Chapter 12, Kumar and colleagues²² present a very comprehensive review of the role of neuroimaging in MDD. Regions such as the DLPFC, amygdala, hippocampus, rACC, and subgenual ACC have been implicated in MDD and this disorder can be related to dysfunction between cortical and limbic connectivity. MDD-related microstructural changes in the white matter of frontal-subcortical circuits, for example, have been observed and may contribute as a risk factor for affective disorders. In general, corticolimbic dysfunction with hypoactive prefrontal and hyperactive limbic regions is associated with MDD and can be normalized by antidepressant therapy.

Abnormal monoaminergic [norepinephrine, DA, and serotonin (5-HT)] function has been traditionally associated with depression and its treatment, although the role of other neurochemical and neuroendocrinological approaches are being actively pursued.¹⁰⁰ Neuroimaging plays a great part in elucidating the role of the monoamines 5-HT and DA in depression. For example, PET studies with appropriate radioligands indicate that reduced 5-HT1A receptor binding is observed in the hippocampus, medial temporal cortex, and midbrain raphe of depressed patients. Increased 5-HT transporter binding has been observed in the insula, periaqueductal gray, striatum, and thalamus of medication-free MDD subjects. Reduced dopamine D1 receptor binding is observed in the caudate, nucleus accumbens, and putamen of depressed patients and is related to disease duration and anhedonia. MRS studies have reported reductions in NAA, increased Cho, reduced cerebrospinal fluid levels of myo-inositol, reduced glutamix (Glx), and reduced GABA levels in MDD. Antidepressant treatments have been shown to restore reduced 5-HT1A binding and NAA and Glx levels in depressed patients.

Depression is related to a negative bias in information processing through which depressed patients display enhanced attention to, and interpretation and memory of, negative emotional material.¹⁰¹ Negative bias is common in mood disorders with different cognitive features. Impaired attention, for example, is more prominent in anxiety disorders, while impaired memory plays a more prominent role in depression. Bias can be evaluated through patient labeling of ambiguous facial expressions presented to them. Depressed subjects typically label these ambiguous facial expressions as negative and undervalue positive cues.¹⁰² fMRI studies associate responses to negative facial expressions with exaggerated activity responses in the amygdala, insula, and ventral striatum and to reduced activity in cortical regions, including the ACC, dorsolateral prefrontal cortex, and rACC. These differences in regional activity can be ameliorated by a variety of antidepressant treatments such as the selective serotonin reuptake inhibitors citalopram (Celexa), Prozac, and sertraline (Zoloft), the noradrenergic and specific serotonergic antidepressants mirtazapine (Remeron), and the noradrenergic and serotonergic reuptake inhibitor venlafaxine (Effexor).

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