Functional, structural, and molecular imaging of the risk for anxiety and depression S.P.A.Wolfensberger Functional, structural, and molecular imaging of the risk for anxiety and depression S.P.A.Wolfensberger Department of Psychiatry VU University Amsterdam Functional, structural, and molecular imaging of the risk for anxiety and depression S.P.A.Wolfensberger ISBN 978-90-86595-36-5 Cover design/illustration and lay-out: Esther Beekman (www.estherontwerpt.nl/www.ideesther.nl) Printed by: Ipskamp Drukkers BV, Enschede, The Netherlands All rights reserved. No part of this thesis may be reproduced or transmitted in any form or by any means without prior written permission of the copyright holder. © Saskia Wolfensberger, Amsterdam 2011 VRIJE UNIVERSITEIT Functional, structural, and molecular imaging of the risk for anxiety and depression ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. L.M. Bouter, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de faculteit der Geneeskunde op woensdag 11 mei 2011 om 15.45 uur in de aula van de universiteit, De Boelelaan 1105 door Saskia Pauline Anemoon Wolfensberger geboren te Amsterdam Publication of this thesis has been accomplished with gratefully acknowledged financial support provided by: Department of Psychiatry, VU University Medical Centre, Amsterdam, Janssen Research & Development, Neuroscience, Philips Healthcare Benelux, BV Cyclotron VU and Stichting Ina Veenstra-Rademaker. The studies described in this thesis were carried out at the Department of Radiology, Nuclear Medicine and PET research, Psychiatry and Biological Psychology (VU University Medical Centre, Amsterdam). The studies were financially supported by the Netherlands Organization for Scientific Research (NWO) grants 900-562-137, 904-61-090, 98510-002, 904-61-193, 480-04-004, and 575-25-006, the Centre for Neurogenomics and Cognitive Research (CNCR), the Centre for Medical Systems Biology (CMSB), a center of excellence approved by the Netherlands Genomics Initiative/NOW and Janssen Research & Development, Neuroscience. promotoren: prof.dr. W.J.G. Hoogendijk prof.dr. A.A. Lammertsma prof.dr. J.C.N. de Geus copromotor: prof.dr. D.J. Veltman TABLE OF CONTENTS 9 25 49 77 105 119 137 153 163 167 173 INTRODUCTION Chapter 1 General introduction and outline SECTION A FUNCTIONAL NEUROIMAGING Chapter 2 Amygdala responses to emotional faces in twins discordant or concordant for the risk for anxiety and depression Neuroimage. 2008 Jun;41(2):544-52. Epub 2008 Feb 14 Chapter 3 The neural correlates of verbal encoding and retrieval in monozygotic twins at low or high risk for depression and anxiety Biological Psychology. 2008 Sep;79(1):80-90. Epub 2008 Jan 18 SECTION B STRUCTURAL NEUROIMAGING Chapter 4 Intrapair differences in hippocampal volume in monozygotic twins discordant for the risk for anxiety and depression Biological Psychiatry. 2007 May 1;61(9):1062-71. Epub 2006 Nov 29 SECTION C MOLECULAR NEUROIMAGING Chapter 5 First evaluation of [11C]R116301 as an in vivo tracer of NK1 receptors in man Molecular Imaging and Biology. 2009 Jul-Aug;11(4):241-5. Epub 2009 Mar 31 Chapter 6 Quantification of the NK1 receptor ligand [11C]R116301 Submitted DISCUSSION Chapter 7 Summary and concluding remarks Chapter 8 Nederlandse samenvatting APPENDICES Dissertation series Dankwoord About the author 9 General introduction and outline1 Chapter 1 10 General introduction and outline 11 Background Throughout the course of life, from conception to death, the human body in general and the brain in particular are shaped by (interactive) effects of genes and environment. As a consequence, individual differences in complex traits, including behavioural traits, reflect a mix of variation in genetic make-up and each individual’s unique history of exposures to risk and protective environments. This dual contribution of genetic and environmental variance is also prominently visible in psychopathological traits, like anxiety and depressive disorders, which are the focus of the present thesis. Studies in genetically informative samples, many of which have used a twin design, show that about 40% of clinical anxiety and depression is due to heritable factors, whereas the remaining 60% of the risk for anxiety and depressive disorders can be attributed to environmental factors1,2, including those that interact with genetic factors3-7. A core assumption in this thesis is that these genetic and environmental risk factors primarily act through the brain; by changing the brain at a molecular level, they affect structure and functioning of brain modules that are critical to mood/emotion regulation. This assumption is generally accepted in psychiatry, where depression and anxiety are now regarded to be brain diseases. The present thesis, however, deviates from the ‘common view in the field with regard to another implicit assumption, namely that environmental risk factors have the same pathogenic effects as genetic risk factors. Instead, it is hypothesized that these two types of risk may have an impact on different brain structures, or that they may affect the same brain structures, but in entirely different, if not opposite, ways. Approach To test this hypothesis, structural and functional brain imaging techniques were used in a unique design involving monozygotic (MZ) discordant/concordant twins, which allowed for separation of the effects of genetic and environmental risk factors. In this design, brain imaging was first compared in MZ twin pairs that were strongly discordant for the risk of, for example, generalized anxiety, obsessive compulsive behaviour, or major depression. In these pairs, one twin scored very high on symptoms of these disorders, whereas the co- twin scored very low. As monozygotic twins always are (nearly) 100% identical at the DNA sequence level8, any discordance at the phenotype level should be the result of differential exposure to environmental influences, such as the lack of social support (environmental deprivation) and life events. Therefore, in these twins, differences in brain activation linked to these behavioural traits also reflect environmental effects on the brain, including epigenetic effects, rather than effects of variation in DNA sequence. Next, MZ twin pairs were selected that were highly concordant for the risk of these traits. In one group the risk was very high in both twins, whilst in the other group it was very low. Chapter 1 12 General introduction and outline 13 Aims The aims of this thesis are twofold. Firstly, using the discordant/concordant twin design, the hypothesis will be tested that genetic and environmental risk factors impact on partly different brain structures or, when they converge on the same brain structures, that they may do so in entirely different, perhaps even opposite, ways. Secondly, a new PET ligand, [11C]R116301, for in vivo investigation of NK1 receptors will be evaluated, as it is suspected that this receptor is involved in anxiety and depression. Molecular imaging studies using PET could be the basis of future (genetic) imaging studies focused on pathways involved in anxiety and depression. Together, functional, structural and molecular approaches promise to advance understanding of neuropsychiatric disorders, in particular anxiety and depression. This is an important mission, because depression and anxiety disorders have high lifetime prevalence (16 and 10%, respectively) and are associated with substantial morbidity and mortality. Unravelling the effects of genetic and environmental risk factors on brain structure and function may be the key to better understanding of the neurobiology of neuropsychiatric disorders. Ultimately, this may lead towards possibilities for early identification of individuals at risk, thereby creating a window for developing preventive strategies, based on individual risk profiles. Brain imaging techniques in this thesis Imaging techniques such as fMRI and structural MRI, magnetic resonance spectroscopy (MRS), PET, single photon emission computed tomography (SPECT), provide useful methods to obtain insight in the living brain. With these imaging methods, information can be obtained on neurobiological parameters such as neuronal activation in time and place, volumetry of brain structures, receptor density and affinity, and neurotransmitter concentration. This thesis focuses on structural MRI, fMRI and PET methods, each of which will be briefly introduced below. Structural MRI MRI is a relatively new technology, which has been in use for a little more than 30 years. It is a non-invasive imaging technique that is used in clinical practice to acquire high-resolution digital images of water-containing human tissues. It provides detailed and high contrast images everywhere in the body, providing clear distinction between different soft tissues, thereby making it especially useful for brain imaging. MRI uses a powerful magnetic field to align the nuclear magnetization vectors of atomic nuclei (of hydrogen atoms) in water in the body. Absorption and emission of radiofrequency radiation of hydrogen nuclei are detectable by the scanner. This signal can be manipulated by additional magnetic fields MZ twins can be regarded as repeated sampling of the same genotype that is exposed to partly different environments. If the phenotypic resemblance in both twins is very high, genetic factors are a likely cause of this resemblance. This is particularly true in anxiety and depression, where the only alternative source of resemblance between MZ twins - common environmental factors including the sharing of parents - has been shown to have no significant impact2. Comparison of MZ twins that are very high on anxious depressive symptoms with twins that are very low on anxious depressive symptoms, therefore, constitutes a contrast of low versus high genetic risk for anxiety and depressive disorder. Verification of the contribution of genetic factors to the phenotypic contrast between concordant low and concordant high MZ pairs can be done by testing other family members of the twins (e.g. parents or siblings), who are expected to also score very low or very high respectively on anxious depressive symptoms. Differences in brain activation linked to these behavioural traits between twins from the high-risk families and those from the low- risk families should mainly reflect effects of variation in DNA sequences between the two groups. To date, the above type of imaging genetics is increasingly used9-18. In addition, there are many studies that employ a candidate gene approach to specifically look at cerebral effects of potential genetic risk factors. In the latter approach a genetic association is tested between measured variation in a candidate gene, usually obtained by previous association to a psychiatric outcome, and variation in brain structure and function, typically assessed by structural and functional magnetic resonance imaging19-39. This approach allows for mapping of the effects of risk genes on neurobiological parameters using neuroimaging, and has the advantage of measures causally closer to genes and gene expression than behaviour. It also provides a means to uncover the neurobiological mechanisms by which gene variants impact on the brain. It has been predicted that this booming field of imaging genetics will see further growth over the coming decade40-42. Remarkably, to date most imaging genetics studies have employed electroencephalography, magneto-encephalography, structural MRI, or functional magnetic resonance imaging (fMRI). At present, there has not been a single molecular imaging study using positron emission tomography in which such a monozygotic discordant/concordant twin design has been used in the context of anxiety and depressive disorders. This lack of molecular imaging studies is somewhat puzzling, but may in part be due to the paucity of relevant, adequately evaluated and valid radiotracers needed to specifically investigate the molecular basis of anxiety and depression. PET, however, is the most direct and sensitive method to measure receptor function in vivo. Therefore, it should be an ideal method to detect genetic differences in regional density and affinity of receptors for neurotransmitters involved in psychiatric disease. Chapter 1 14 General introduction and outline 15 the effects of noise, enabling the detection of signal changes that correlate significantly with task stimuli. Advantages of fMRI are its good temporal resolution, allowing for event related analyses according to task performance, relatively low costs, possibility of repeated measurements, and flexible scan duration. Possible limitations of fMRI are its low signal to noise ratio, its relative measures (i.e. measuring differences in signal activation: active state compared to baseline), sensitivity to artefacts, and the fact that the BOLD signal is not a direct measure of neural activity. BOLD signal intensity changes may therefore be difficult to interpret in terms of underlying neurodynamics55,56. PET The first commercial PET camera was built in 1978, 2 years before the advent of MRI. During the following decades, it was increasingly used as a research tool to measure physiologically relevant processes at a molecular level in the living human body and, more recently, in animal models of disease. PET scanning is a non-invasive quantitative imaging technique involving the use of positron emitting radionuclides. Scans are acquired following intravenous injection of a tracer labelled with a radionuclide (called a radioligand in case of neuroreceptor studies) that accumulates in the tissue to be studied, and decays by emission of a positron (anti-electron). After travelling at most a few millimetres, a positron will combine with an electron and the two particles will annihilate almost instantly, resulting in the simultaneous release of two gamma rays (photons) with an energy of 511 keV (equivalent to the mass of positron or electron) into opposite directions. PET imaging is based on the assumption that simultaneous detection of a pair of these gamma rays by two opposing detectors of the PET scanner, is the result of an annihilation event along a straight line in space connecting these two detectors (line of response). Following the registration of these events, counts from all lines of response (sinograms) are reconstructed to provide maps of radioactivity distribution. By performing repeated scans over time, kinetic information (rate of uptake, clearance) can be obtained. Using tracer kinetic modelling, this can be translated into quantitative measures of physiological parameters of interest. To perform a scan, a short-lived radioactive ligand or tracer is administered. To this end a positron emitting radionuclide is chemically incorporated into a biologically active molecule. Development of radiotracers has proven to be time and money consuming and can be seen as a limiting factor in PET applications. On the other hand, PET technology can be used to trace the biologic pathway of any compound in living humans and many other species, provided it can be radiolabelled with a PET radionuclide. Several radiotracers have been developed for imaging receptors, neurotransmitter transporters, enzymes and other molecular targets. Due to the short half lives of most (phase and frequency encoding) to build up enough information to construct an image of the body. The advance of volumetric measurements of brain structures using structural MRI has resulted in many studies reporting brain structure abnormalities in a number of neuropsychiatric disorders. The hippocampal region/formation is one of the brain structures that has been a focus of research and this has revealed a number of structural abnormalities in a variety of neurological and psychiatric disorders, such as Alzheimer’s disease43,44, mild cognitive impairment45, schizophrenia46, major depression47 and anxiety 48, 9 and others. MR derived volumetric techniques have demonstrated good validity and reproducibility, and accuracy of the measurements has been shown by MRI volumetric measurement of phantoms with known volumes 50-52. However, studies on brain structures in neuropsychiatric disorders show inconsistencies, both in terms of laterality (left or right), and in direction of volume changes (increase of decrease). Part of these discrepancies may be due to the different methods used for measuring brain structure. Voxel based morphometry (VBM)53 is an automatic whole brain method and is increasingly being used as a tool to examine volume changes at a voxel level, obviating manual volumetry, i.e subjective interpretation of anatomic variations. However, it does not provide absolute volumes of brain structures. Most (pre)processing and analysis is automated in software packages, such as statistical parametric mapping (SPM) (www.fil.ion.ucl.ac.uk/ spm/), although many methodological questions remain, including what template to use for normalisation, what level and type of correction to use, and how best to display results. Functional MRI Functional magnetic resonance imaging (fMRI) is an extension of traditional MRI. It is one of the most recent neuroimaging modalities. Since the early 1990s, fMRI has increasingly been used to study brain function. It uses the varying magnetic properties of the oxygen transporter molecule haemoglobin (the blood oxygen level dependent (BOLD) effect) to examine brain function in human subjects54. Activated nerve cells consume oxygen carried by hemoglobin in red blood cells from local capillaries. The local response to this use of oxygen is an increase in blood flow to regions with increased neural activity (hemodynamic response). The vascular system actually overcompensates for this oxygen need of neurons in an activated state. This leads to a locally increased ratio of oxygenated hemoglobin relative to deoxygenated hemoglobin. Because deoxygenated hemoglobin attenuates the MR signal, the vascular response leads to a signal increase that is related to neural activity. In most fMRI studies, subjects are scanned while performing a certain task (or ‘paradigm’). In such paradigms, conditions of interest alternate with reference conditions to produce differences in BOLD signal intensity. Task conditions have to be repeated in order to reduce Chapter 1 16 General introduction and outline 17 on the same brain structures, this assumption is tested in this chapter, by applying optimized voxel-based morphometry to magnetic resonance images obtained in the same MZ twin pairs as mentioned in chapters 2 and 3. In part 3 of this thesis, chapter 5 and chapter 6, the ligand [11C]R116301 is evaluated as a putative novel PET tracer for the quantification of NK1 receptors. In chapter 5 the presence of an NK1 related specific signal is evaluated using a blocking study and in chapter 6 the optimal model for quantifying NK1 receptors using [11C]R116301 is derived. In chapter 7 the main findings of this thesis are summarised and discussed and recommendation of future research are given. radionuclides, they must be produced using a cyclotron in close proximity to the PET imaging facility. Two commonly used PET radionuclides are [11C] and [18F] with half-lives of 20 and 110 min, respectively. For example, [18F]MPPF is a ligand of the 5-HT1A receptor, [11C]raclopride a ligand of the D2/D3 receptor, and [18F]flumazenil a ligand of the benzodiazepine recognition site on the GABA/benzodiazepine receptor complex. Most commonly, [18F]FDG (fluoro- deoxyglucose) is used for measuring glucose metabolism and [15O]H2O for measuring rCBF (regional cerebral blood flow). The properties of a PET tracer depend, amongst others, on its metabolism, and its selectivity and affinity for the target to be studied, i.e. in this thesis the NK1 receptor. Another important property of a PET tracer is the level of non-specific binding. A signal due to specific binding might be lost if the level of non-specific binding (background) is too high. At the beginning of the neuroimaging era, more than 30 years ago, the very first activation studies were performed using [18F]FDG, followed by [15O]H2O as the method of choice for measuring neuronal activation. Nowadays, fMRI has gradually replaced [15O]H2O PET for examining the response of the brain to stimuli. Whereas [15O]H2O PET has better signal to noise ratio (S/R) and does not suffer from signal loss near bone-air transitions, this is outweighed by the higher temporal and spatial resolution of fMRI. Another advantage of fMRI is that it does not require administration of radioactive tracers, thereby enabling multiple repeated measurements within one subject and flexible duration of experiments. However, PET has the unique capability to detect molecular events at picomolar concentrations, compared with micromolar concentrations in MRS. 1.1 Outline of this thesis Chapter 2 begins by examining emotion processing in relation to the risk for anxiety and depression. In the literature, functional brain imaging studies have reported deviant amygdala responses to emotional stimuli in subjects suffering from anxiety and depressive disorder, but compared to healthy controls both hyperactivity and hypoactivity have been reported. Using fMRI in extremely discordant (at very low or very high risk for anxiety and depression) MZ twins, in chapter 2 the hypothesis is tested that the basis for these discrepant findings lies in different effects of genetic and environmental risk factors on amygdala functioning . In chapter 3, neuronal correlates of emotional processing are examined during an encoding and recognition paradigm using emotionally salient words in the same design and study sample as used in chapter 2. In chapter 4, the second part of this thesis, volumetric differences in brain structure are examined in relation to the risk for anxiety and depression. As current biological psychiatric models assume that genetic and environmental risk factors for anxiety and depression act References 18 19 References References 1. Kendler KS, Prescott CA. A population-based twin study of lifetime major depression in men and women. Archives of General Psychiatry 1999; 56:39-44. 2. Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: Review and meta-analysis. American Journal of Psychiatry 2000; 157:1552-62. 3. Caspi A, Taylor A, Moffitt TE, Plomin R. Neighborhood deprivation affects children’s mental health: Environmental risks identified in a genetic design. Psychological Science 2000; 11:338-42. 4. Eley TC, Sugden K, Corsico A et al. Gene-environment interaction analysis of serotonin system markers with adolescent depression. Molecular Psychiatry 2004; 9:908-15. 5. Grabe HJ, Lange M, Wolff B et al. Mental and physical distress is modulated by a polymorphism in the 5-HT transporter gene interacting with social stressors and chronic disease burden. Molecular Psychiatry 2005; 10:220-4. 6. Kaufman J, Yang BZ, Douglas-Palumberi H et al. Brain-derived neurotrophic factor- 5-HTTLPR gene interactions and environmental modifiers of depression in children. Biological Psychiatry 2006; 59:673-80. 7. Kendler KS, Heath A, Martin NG, Eaves LJ. Symptoms of Anxiety and Depression in A Volunteer Twin Population - the Etiologic Role of Genetic and Environmental-Factors. Archives of General Psychiatry 1986; 43:213-21. 8. Boomsma DI, Beem AL, van den BM et al. Netherlands twin family study of anxious depression (NETSAD). Twin Research 2000; 3:323-34. 9. Ahveninen J, Jaaskelainen IP, Osipova D et al. Inherited auditory-cortical dysfunction in twin pairs discordant for schizophrenia. Biological Psychiatry 2006; 60:612-20. 10. Brans RG, van Haren NE, van Baal GC, Schnack HG, Kahn RS, Pol HE. Heritability of changes in brain volume over time in twin pairs discordant for schizophrenia. Archives of General Psychiatry 2008; 65:1259-68. 11. den Braber A, van ‘t Ent D, Blokland GAM et al. An fMRI study in monozygotic twins discordant for obsessive-compulsive symptoms. Biological Psychology 2008; 79:91-102. 12. Ettinger U, Picchioni M, Landau S et al. Magnetic resonance imaging of the thalamus and adhesio interthalamica in twins with schizophrenia. Archives of General Psychiatry 2007; 64: 401-9. 13. Posthuma D, Gosso MF, Altink B et al. Imaging genetics & cognition: A pilot study involving the CHRM2 and SNAP-25 genes. Behavior Genetics 2007; 37:787. 14. Rijsdijk FV, van Haren NE, Picchioni MM et al. Brain MRI abnormalities in schizophrenia: same genes or same environment? Psychological Medicin 2005; 35:1399-409. 15. Spaniel F, Tintera J, Hajek T et al. Language lateralization in monozygotic twins discordant and concordant for schizophrenia. A functional MRI pilot study. European Psychiatry 2007; 22:319-22. 16. van ‘t Ent D, Lehn H, Derks E et al. Functional MRI during performance of the stroop task in monozygotic twins concordant or discordant for attention/hyperactivity problems. Psychophysiology 2008; 45:S18. 17. van ‘t Ent D, Lehn H, Derks EM et al. A structural MRI study in monozygotic twins concordant or discordant for attention/hyperactivity problems: evidence for genetic and environmental heterogeneity in the developing brain. Neuroimage 2007 April 15;35: 1004- 20. 18. van der Schol AC, Vonk R, Brans RG er al. Influence of genes and environment on brain voolumes in twin pairs concordant and discordant for bipolar disorder. Archives of General Psychiatry 2009; 66:142-51 19. Fisher PM, Meltzer CC, Ziolko SK, Price JC, Hariri AR. Capacity for 5-HT1A-mediated autoregulation predicts amygdala reactivity. Nature Neuroscience 2006; 9:1362-3. 20. Bertolino A, Taurisano P, Pisciotta NM et al. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance. PLoS One 2010; 5:e9348. 21. Neumann SA, Brown SM, Ferrell RE, Flory JD, Manuck SB, Hariri AR. Human choline transporter gene variation is associated with corticolimbic reactivity and autonomic- cholinergic function. Biological Psychiatry 2006; 60:1155-62. 22. Viding E, Williamson DE, Hariri AR. Developmental imaging genetics: Challenges and promises for translational research. Development and Psychopathology 2006; 18:877-92. 23. Brown SM, Hariri AR. Neuroimaging studies of serotonin gene polymorphisms: Exploring the interplay of genes, brain, and behavior. Cognitive Affective & Behavioral Neuroscience 2006; 6:44-52. 24. Hariri AR, Drabant EM, Weinberger DR. Imaging genetics: Perspectives from studies of genetically driven variation in serotonin function and corticolimbic affective processing. Biological Psychiatry 2006; 59:888-97. 25. Hariri AR, Holmes A. Genetics of emotional regulation: the role of the serotonin transporter in neural function. Trends in Cognitive Sciences 2006; 10:182-91. 26. Meyer-Lindenberg A, Buckholtz JW, Kolachana B et al. Neural mechanisms of genetic risk for impulsivity and violence in humans. Proceedings of the National Academy of Sciences of the United States of America 2006; 103:6269-74. 27. Winterer G, Hariri AR, Goldman D, Weinberger DR. Neuroimaging and human genetics. Neuroimaging, Pt B 2005;67:325-+. 28. Brown SM, Peet E, Manuck SB et al. A regulatory variant of the human tryptophan hydroxylase-2 gene biases amygdala reactivity. Molecular Psychiatry 2005; 10:884-8. References 20 21 References 29. Bertolino A, Arciero G, Rubino V et al. Variation of human amygdala response during threatening stimuli as a function of 5’HTTLPR genotype and personality style. Biological Psychiatry 2005; 57:1517-25. 30. Siegle GJ, Hariri AR, Blumberg HP. Examining genetic influences upon frontal and sensory cortico-limbic connectivity in mood-disordered individuals: Can we determine distinct neuroendophenotypes? Biological Psychiatry 2005; 57:143S-4S. 31. Pezawas L, Meyer-Lindenberg A, Drabant EM et al. 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nature Neuroscience 2005; 8:828-34. 32. Hariri AR. Genetic susceptibility factors for intermediate phenotypes of serotonergic neurotransmission, amygdala reactivity, and fearful temperament. Biological Psychiatry 2004; 55:192S. 33. Holmes A, Hariri AR. The serotonin transporter gene-linked polymorphism and negative emotionality: placing single gene effects in the context of genetic background and environment. Genes Brain and Behavior 2003; 2:332-5. 34. Hariri AR, Weinberger DR. Functional neuroimaging of genetic variation in serotonergic neurotransmission. Genes Brain and Behavior 2003; 2:341-9. 35. Hariri AR, Goldberg TE, Mattay VS et al. Brain-derived neurotrophic factor val(66)met polymorphism affects human memory-related hippocampal activity and predicts memory performance. Journal of Neuroscience 2003; 23:6690-4. 36. Hariri AR, Kolachana BS, Goldberg TE et al. BDNF val(66)met genetic variation and the response of the human hippocampus. Biological Psychiatry 2003; 53:113S. 37. Hariri AR, Weinberger DR. Imaging genomics. British Medical Bulletin 2003; 65:259-70. 38. Hariri AR, Mattay VS, Tessitore A et al. Serotonin transporter genetic variation and the response of the human amygdala. Science 2002; 297:400-3. 39. Hirvonen J, Van Erp TG, Huttunen J et al. Brain dopamine D1 receptors in twins discordant for schizophrenia. American Journal of Psychiatry 2006; 1631:1747-53. 40. de GE, Goldberg T, Boomsma DI, Posthuma D. Imaging the genetics of brain structure and function. Biological Psychology 2008; 79:1-8. 41. Hariri AR, Weinberger DR. Functional neuroimaging of genetic variation in serotonergic neurotransmission. Genes Brain Behavior 2003; 2:341-9. 42. Winterer G, Hariri AR, Goldman D, Weinberger DR. Neuroimaging and human genetics. International Review of Neurobiology 2005; 67:325-83. 43. Barnes J, Scahill RI, Frost C, Schott JM, Rossor MN, Fox NC. Increased hippocampal atrophy rates in AD over 6 months using serial MR imaging. Neurobiology of Aging 2008; 29:1199- 203. 44. Toledo-Morrell L, Stoub TR, Wang CS. Hippocampal atrophy and disconnection in incipient and mild Alzheimer’s disease. Dentate Gyrus: A Comphrehensive Guide to Structure, Function, and Clinical Implications 2007;163:741-+. 45. Tapiola T, Pennanen C, Tapiola M et al. MRI of hippocampus and entorhinal cortex in mild cognitive impairment: A follow-up study. Neurobiology of Aging 2008; 29:31-8. 46. Honea RA, Meyer-Lindenberg A, Hobbs KB et al. Is gray matter volume an intermediate phenotype for schizophrenia? A voxel-based morphometry study of patients with schizophrenia and their healthy siblings. Biological Psychiatry 2008; 63:465-74. 47. Konarski JZ, Mcintyre RS, Kennedy SH, Rafi-Tari S, Soczynska JK, Ketter TA. Volumetric neuroimaging investigations in mood disorders: bipolar disorder versus major depressive disorder. Bipolar Disorders 2008; 10:1-37. 48. Letizia B, Maricla T, Sara C et al. Magnetic resonance imaging volumes of the hippocampus in drug-naive patients with post-traumatic stress disorder without comorbidity conditions. Journal of Psychiatric Research 2008; 2:752-62. 49. Yamasue H, Abe O, Suga M et al. Gender-common and -specific neuroanatomical basis of human anxiety-related personality traits. Cerebral Cortex 2008; 8:46-52. 50. Jack CR, Bentley MD, Twomey CK, Zinsmeister AR. Mr Imaging-Based Volume Measurements of the Hippocampal-Formation and Anterior Temporal-Lobe - Validation Studies. Radiology 1990; 176:205-9. 51. Pantel J, O’Leary DS, Cretsinger K et al. A new method for the in vivo volumetric measurement of the human hippocampus with high neuroanatomical accuracy. Hippocampus 2000; 10:752-8. 52. Watson C, Andermann F, Gloor P et al. Anatomic Basis of Amygdaloid and Hippocampal Volume Measurement by Magnetic-Resonance-Imaging. Neurology 1992; 42:1743-50. 53. Ashburner J, Friston KJ. Voxel-based morphometry - The methods. Neuroimage 2000 June; 11:805-21. 54. Jezzard P, Matthews P M, Smith S M. Functional MRI- An introduction to methods, New York: Oxford University Press, 2001. 55. Logothetis NK, Wandell BA. Interpreting the BOLD signal. Annual Review of Physiology 2004; 66:735-69. 56. Logothetis NK. What we can do and what we cannot do with fMRI. Nature 2008; 453:869- 78. 22 23 SECTION A Functional Neuroimaging 25 Amygdala responses to emotional faces in twins discordant or concordant for the risk for anxiety and depression Wolfensberger SP, Veltman DJ, Hoogendijk WJ, Boomsma DI, de Geus EJ Neuroimage. 2008 Jun;41(2):544-52. Epub 2008 Feb 14 2 Chapter 2 26 Amygdala responses to emotional faces in twins discordant or concordant for the risk for anxiety and depression 27 Introduction Functional imaging studies of brain correlates of anxiety and depression have converged on the amygdala, a structure crucial for emotional processing (Canli et al., 2005; Davidson et al., 2003; Drevets, 2001; Fu et al., 2004; Kumari et al., 2003; Lawrence et al., 2004; Rauch et al., 2000; Shin et al., 2005; Siegle et al., 2001; Stein et al., 2002; Surguladze et al., 2005; Thomas et al., 2001; Wright et al., 2003). A replicated association has been found between amygdala reactivity to emotional stimuli and a polymorphism in the serotonin transporter gene (Hariri et al., 2002, 2005; Pezawas et al., 2005), and other genes in the serotonergic pathway also seem to influence amygdala reactivity (Brown et al., 2005; Buckholtz et al., 2007; Dannlowski et al., 2007; Iidaka et al., 2005). tioning. About 60% of the risk for anxiety and depressive disorders can be attributed to environmental factors (Kendler and Prescott, 1999; Sullivan et al., 2000) and interaction of genetic and environmental factors has also been reported (Caspi et al., 2000; Eley et al., 2004; Grabe et al., 2005; Kaufman et al., 2006; Kendler et al., 1986). It is currently unclear whether environmental risk factors have the same pathogenic effects as genetic risk factors. It is quite possible that these two types of risk impact on the same brain structures but in entirely different perhaps even opposite ways. Indeed, deviant amygdala responses to emotional stimuli in subjects suffering from anxiety and depressive disorder have been observed, but although most studies have found hyperactivity compared to healthy controls (Canli et al., 2005; Fu et al., 2004; Siegle et al., 2001; Surguladze et al., 2005), in others negative findings (Kumari et al., 2003; Lawrence et al., 2004; Davidson et al., 2003), or even amygdala hypoactivity has been reported (Drevets, 2001; Thomas et al., 2001). Such discrepant findings may well arise because genetic and environmental risk factors differently impact amygdala functioning. Here we employ brain imaging of concordant and discordant monozygotic (MZ) twin pairs to test how genetic and environmental risks for anxiety and depression are reflected in the amygdala response to emotionally salient stimuli. Monozygotic twins are (nearly) always 100% identical at the DNA sequence level (Boomsma et al., 2002) and differences in phenotypic status can be expected to reflect discordance for environmental risk factors. Discordant MZ twins were selected to be at low or high risk for anxiety disorder and major depression based on their ratings on neuroticism, anxiety, and depression in longitudinal surveys. A compound risk score for anxiety and depression based on these ratings was shown to have strong predictive validity for clinical anxiety and clinical depression in this population (Middeldorp et al., 2004) as assessed by the Composite International Diagnostic Interview, a well-validated instrument to assess these disorders (Andrews and Peters, 1998). Because MZ twins are genetically identical, discordance in the risk for anxiety and Abstract Background Functional brain imaging studies have shown deviant amygdala responses to emotional stimuli in subjects suffering from anxiety and depressive disorder, but both hyperactivity and hypoactivity compared to healthy controls have been reported. To account for these discrepant findings, we hypothesize that genetic and environmental risk factors differently impact on amygdala functioning. Methods To test this hypothesis, we assessed amygdala responses to an emotional faces paradigm during functional magnetic resonance imaging in monozygotic twin pairs discordant for the risk of anxiety and depression (n =10 pairs) and in monozygotic twin pairs concordant for high (n=7 pairs) or low (n=15 pairs) risk for anxiety and depression. Results Main effects (all faces vs. baseline) revealed robust bilateral amygdala activity across groups. In discordant twins, increased amygdala responses were found for negatively valenced stimuli (angry/anxious faces) in high-risk twins compared to their low-risk co- twins. In contrast, concordant high-risk pairs revealed blunted amygdala reactivity to both positive and negative faces compared with concordant low-risk pairs. Post-hoc analyses showed that these findings were independent of 5-HTTLPR genotype. Conclusions Our findings indicate amygdala hyperactivity in subjects who are at high risk for anxiety and depression through environmental factors and amygdala hypoactivity in those at risk mainly through genetic factors. We suggest that this result reflects a difference in baseline amygdala activation in these groups. Future imaging studies on anxiety and depression should aim to avoid admixture of subjects who are at genetic risk with those at risk due to environmental factors.