Physical and Mental Health Interface - MAFIADOC.COM

Physical and Mental Health Interface

Lundbeck Australia has supported this publication through an unrestricted grant

Physical and Mental Health Interface

Edited by: Associate Professor Michael Salzberg Director Consultation-Liaison Psychiatry St Vincent’s Mental Health Service and The University of Melbourne Melbourne, Victoria Professor David Castle Chair of Psychiatry St Vincent’s Health Melbourne and The University of Melbourne Melbourne, Victoria

Physical and Mental Health Interface © 2009 Australian Postgraduate Medicine Publishing and distribution: Australian Postgraduate Medicine c/o Victorian Medical Postgraduate Foundation Level 8, 27 Victoria Parade Fitzroy, Victoria 3065 Australia Phone: +61 3 9415 1177 Fax: + 61 3 9416 2624 Email: [email protected] Website: www.vmpf.org.au This book is copyright. Apart from any fair dealing for the purpose of private study, research, criticism or review, as permitted under the Copyright Act 1968, no part may be reproduced by any process without prior written permission. Enquiries should be made to the publisher. ISBN 978-0-646-47058-0 Cover Art Tulayijier Sidike (used with permission) Project Management Ann Dancer Typesetting and Design Les-Lea Guy Indexing Russell Brooks Printing BPA Print Group, Melbourne

Foreword

Authors Chapter 1 Cameron Lacey Maori/Indigenous Health Institute (MIHI), University of Otago Christchurch, New Zealand Wendyl D’Souza Department of Medicine, St Vincent’s Hospital, Melbourne, Victoria Michael Salzberg St Vincent’s Mental Health Service and The University of Melbourne Melbourne, Victoria Chapter 2 Dennis Velakoulis Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Health and Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria Mark Walterfang Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Health and Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria Ramon Mocellin Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Health and Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria Christos Pantelis Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria Catriona McLean National Neural Tissue Resource Centre, National Neuroscience Facility, and Anatomical Pathology, Alfred Hospital Melbourne, Victoria Chapter 3 Paul B. Fitzgerald Alfred Psychiatry Research Centre, The Alfred and Monash University School of Psychology, Psychiatry and Psychological Medicine Melbourne, Victoria Edited by David Castle St Vincent’s Health Melbourne and The University of Melbourne Melbourne, Victoria

Chapter 4 David Cunnington Melbourne Sleep Disorders Centre, Melbourne, Victoria Chapter 5 Assen Jablensky Centre for Clinical Research in Neuropsychiatry, School of Psychiatry and Clinical Neurosciences, The University of Western Australia Perth, Western Australia Chapter 6 George Kalogerakis St Vincent’s Hospital, Melbourne, Victoria Edited by David Castle St Vincent’s Health Melbourne and The University of Melbourne Melbourne, Victoria Chapter 7 William Connell Department of Gastroenterology, St Vincent’s Hospital Melbourne, Victoria Jarrod Wilson Department of Gastroenterology, St Vincent’s Hospital Melbourne, Victoria Chapter 8 Sally Bell Department of Gastroenterology, St Vincent’s Hospital Melbourne, Victoria Niranjan Arachchi Department of Gastroenterology, St Vincent’s Hospital Melbourne, Victoria Chapter 9 Robyn Langham Department of Nephrology, St Vincent’s Hospital, Melbourne, Victoria Chapter 10 Jeremy Couper St Vincent’s Mental Health Service, Melbourne, Victoria Edited by David Castle St Vincent’s Health Melbourne and The University of Melbourne Melbourne, Victoria

Chapter 11 Elspeth Guthrie School of Medicine, The University of Manchester Manchester, United Kingdom Chapter 12 Michael Salzberg St Vincent’s Mental Health Service and The University of Melbourne Melbourne, Victoria Margaret J. Morris Department of Pharmacology, School of Medical Sciences The University of New South Wales, Sydney, New South Wales Chapter 13 Simon Jones Department of Psychiatry, The University of Melbourne Melbourne, Victoria David Castle St Vincent’s Health Melbourne and The University of Melbourne Melbourne, Victoria Chapter 14 Helen Schultz St Vincent’s Health, Melbourne, Victoria David Castle St Vincent’s Health Melbourne and The University of Melbourne Melbourne, Victoria Chapter 15 Timothy Nguyen Chad Bousman Gursharan Chana Erick Tatro Ian Everall

Contents 1

Epilepsy and Mood Disorders

2

Schizophrenia-like Psychoses in Frontotemporal Dementia

3

Deep Brain Stimulation in Psychiatry

4

Sleep, Medicine and Psychiatry

5

Preventable Mortality in People with Mental Disorders: an overview of Western Australian research

6

Life Threatening Diabetic Ketoacidosis Associated with Atypical Antipsychotic Therapy

7

Psychiatric Aspects of Inflammatory Bowel Disease

8

Psychiatric Aspects of HCV and Interferon Therapy

9

Affective Disorders and Chronic Kidney Disease

10

Prostate Cancer and the Rise of Psycho-Oncology

11

Update on Somatoform Disorders

12

Stress, Obesity and the Metabolic Syndrome

13

Obesity and Psychosis

14

Depression, Anxiety and Substance Use Disorders in People Living with HIV

15

HIV, Methamphetamine, and the Brain in the Era of Antiretroviral Treatment INDEX

1 Epilepsy and Mood Disorders Cameron Lacy, Wendyl D’Souza, and Michael Salzberg

“Melancholics ordinarily become epileptics, and epileptics melancholics” Hippocrates Epilepsy and psychiatric illness have a long association which can be dated back to the time of Hippocrates. This chapter aims to provide an overview of developments in our understanding of this association focusing on mood disorders, its importance for patients and clinicians and treatment implications. However it is likely that many of the findings are not confined to patients with epilepsy (PWE) but may be relevant to depression in the medically ill more broadly which will be covered in other chapters in this book.

Prevalence of psychiatric comorbidity in epilepsy Epilepsy is the most common serious neurological disorder and one of the world’s most prevalent non-communicable diseases, affecting approximately 4% of individuals at some time in their lives. Mental disorders are the most common form of comorbidity associated with epilepsy. Numerous studies have reported an increased rate of psychiatric comorbidity observed in patients with epilepsy compared to the general population (Swinkels et al., 2005). The range of comorbid disorders includes depression, Epilepsy and Mood Disorders

1

psychoses, anxiety disorders, personality disorder and non-epileptic seizures (Table 1.1). The majority of studies have focussed on depression although anxiety disorders have been shown to be as common as depression and contribute equally to impaired quality of life (Johnson et al., 2004). Some of the shared aetiological factors of depression and epilepsy (discussed below) are now being explored in the association between bipolar affective disorder and epilepsy (Mazza et al., 2007). The remainder of this chapter will focus on depression in PWE although it seems likely that many of the findings could apply to the range of psychiatric syndromes seen in PWE. Table 1.1 Prevalence of psychiatric disorders in people with epilepsy and in the general population Psychiatric Disorder

Epilepsy Patients

General Population

Mood Disorders Depression Bipolar Affective Disorder Psychosis Generalised Anxiety Disorder

30-50%

5-17%

12%

0.3-1.5%

2-9%

1%

15-25%

5-7%

Personality Disorder

4-38%

4%

Non-epileptic Seizures

10-20%

102 cm in men or 88 cm in women) (Brunner et al., 2007). This was largely independent of the many covariates measured in the study; the authors concluded: “Employees experiencing chronic work stress have approximately 50 percent higher odds of obesity, after taking into account socioeconomic position and variation in adverse health behaviours.”((Brunner et al., 2007) (p835). In a prospective cohort study of non-obese male Japanese workers (Nishitani and Sakakibara, 2007), associations were found between job demands, adverse eating behaviour, symptoms of tension/anxiety and depression and BMI increase. Further analysis of the Whitehall II study cohort showed that, at 14 year follow-up, there was a pervasive relationship between work stress, measured on 4 occasions, and risk of metabolic syndrome (Chandola et al., 2006). Persons obese at baseline were excluded from this series of analyses, thus countering the possibility that the association stemmed from pre-existing risk. A key feature of the results was a positive dose-response relationship between work stress and metabolic syndrome. As in their study of obesity (Brunner et al., 2007), this association held after adjustment for health behaviours and occupational status. An illuminating prospective study of 71 women examined the effects of a shared stressor, namely a 12 week nurse practitioner course culminating in a written examination (Roberts et al., 2007). Amongst the cohort, the majority gained weight, but some lost weight and others remained stable; this pattern has been observed in other studies of stress, eating behaviour and body weight. There were clear associations between cortisol elevation and BMI rise, mediated by changes in two psychological variables, namely ‘dietary restraint’ and ‘mastery’. ‘Dietary restraint’ refers to a set of Stress, Obesity and the Metabolic Syndrome

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thoughts and behaviours involving ongoing voluntary efforts to restrict food intake in order to control body weight. Usually, those with high restraint scores experience this way of thinking and behaving as itself stressful and have episodes of ‘disinhibited eating’ in various contexts (see further discussion below). ‘Mastery’ refers to perceived control over one’s life in general; high perceived control has been shown in many studies generally to moderate the impact of stressors. Such prospective studies support the idea that in many individuals, stress contributes causally to weight gain and obesity. However, other evidence suggests reverse causation, i.e. that obesity leads to higher levels of stressful life events (Barry and Petry, 2008). Possible mechanisms include the adverse health effects of obesity itself; and the occupational disadvantages of obesity, including higher rates of unemployment and discrimination against overweight job applicants. Life stress of various kinds has also been implicated in the causation of childhood overweight and obesity. Examples include maternal stress and food insecurity (Gundersen et al., 2008); childhood neglect (Whitaker et al., 2007); and stress experienced by parents of young children, including serious life events, parenting stress, and spouse relationship problems (Koch et al., 2008). An important prospective cohort study of female victims of childhood sexual abuse, followed up from ages 6 to 27 years, showed no significant differences in obesity rates at adolescence, but markedly elevated rates of obesity in young adulthood (Noll et al., 2007), highlighting the potential long-term consequences of early stress, a theme considered further below. The aforementioned studies are selected examples of studies in different age groups, using different concepts and measures of life stress and different study designs. Taken together, they constitute a reasonable case linking life stress to obesity and in some instances they provide insights into potential causal pathways.

Evidence of associations: nonhuman primate studies Studies in nonhuman primates are particularly persuasive, given the close correspondences in physiology to humans and the salience of complex social stressors in the lives of these animals. A study of 120 Physical and Mental Health Interface

psychosocial stress in adult male cynomolgus monkeys showed a greater amount of abdominal fat as measured by CT scanning in those who exhibited a ‘defeated’, ‘depressed’ response to stress (Jayo et al., 1993); there was also an excess of other features of metabolic syndrome and early signs of coronary atherosclerosis. A potent long-term effect of early life stress was shown in a study of bonnet macaques (Kaufman et al., 2007). The mother-infant dyads were subjected to variable foraging demand (VFD) stress when the infants were ∼4-8 months old (i.e. 16 weeks of stress). VFD is known from previous work to activate stress systems and to cause enduring neuroendocrine, behavioural and brain structural effects, but with no effects on overall physical growth. At 3-4 years of age (the time of puberty onset in this species), these offspring showed various features of the metabolic syndrome, including greater BMI and abdominal girth, and greater levels of blood VLDL and GLP-1 (glucagon-like peptide-1). In a euglycaemichyperinsulinaemic insulin clamp sub-study, they showed reduced glucose clearance rates. Primate studies have many advantages in exploring these complex pathophysiological processes that commence in early life and develop over the lifespan. However, most animal studies exploring the psychobiology of obesity, in particular probing intervening mechanisms, have been carried out in rodents.

Intervening mechanisms connecting stress, obesity & metabolic syndrome – selected themes The physiological control of overall energy balance, of intake and expenditure, are extraordinarily complex – as is the causation of obesity – and the range of plausible mechanisms by which stress could affect these systems is also extensive. The following comments are highly selective (the role of the HPA axis in energy regulation and obesity has been reviewed in detail in recent times, e.g., (Nieuwenhuizen and Rutters, 2008, Bornstein et al., 2006, Adam and Epel, 2007, Warne, 2009, Lo Sauro et al., 2008, MietusSnyder and Lustig, 2008, Dallman et al., 2006, Peters et al., 2007, Torres and Nowson, 2007).) In general, in animal studies experimental stressors lead to decreased food intake, in fact showing a dose-response relationship in this regard. However, there is much variation between species, Stress, Obesity and the Metabolic Syndrome

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including with the type of stressor and its chronicity, and with social factors. For example, in one study, whereas both dominant and subordinate rats ate less and lost weight in the face of stress, subsequently the subordinate animals regained weight mostly as adipose tissue (Tamashiro et al., 2004). Evidence for a role of corticotropin releasing factor (CRF) and of glucocorticoids in these phenomena derives from several sources. CRF inhibits feeding in rats when administered by icv (intracerebroventricular) injection, and may mediate the appetitesuppressing action of leptin. Importantly, interactions have been described between CRF and the potent appetite stimulating peptide, neuropeptide Y (NPY). Removal of glucocorticoids (corticosterone in rats, cortisol in humans and nonhuman primates) by adrenalectomy reduces appetite and body weight and these effects are reversed by glucocorticoid replacement; and glucocorticoids potentiate the appetite stimulating action of NPY. Nieuwenhuizen and Rutters (2008) suggest that the appetite reducing CRF action may characterise the first phase of the stress response, and the opposite action of glucocorticoids may have a role in the succeeding recovery phase, replenishing energy consumed during the first, ‘fight-or-flight’ phase. In humans, stressors generally lead to reduced food intake in some people (∼30%), and increased intake in a majority (see above, discussion of Roberts et al (Roberts et al., 2007)). Predictors of increased eating during stress are female sex, being overweight and high scores on measures of ‘dietary restraint’. Notably, several studies have shown that those high on ‘restraint’ consume more food when subjected to naturalistic or experimental stressors, whereas typically those low on restraint reduce consumption. ‘Emotional eating’, a different construct, refers to overeating in response to negative emotions, such as depression, and compared to dietary restraint has been found to have different causes and consequences (see discussion in (Adam and Epel, 2007), p453). One simple theory posits that the cognitive load of a life stressor competes with – and interferes with – the cognitive load of successful dietary restraint, leading to ‘disinhibition’. However, the connections between stress, dietary restraint and overeating are likely to be more complex than this cognitive model suggests. In several (but not all) studies, higher dietary restraint has 122 Physical and Mental Health Interface

been found to be associated with higher plasma cortisol levels. Glucocorticoids, in both human and animal studies, have been shown to modulate neural systems involved in both the hedonic and motivational aspects of behaviour (‘liking’ and ‘wanting’), including eating behaviour. Thus, glucocorticoids modulate both mu-opioid and dopaminergic systems in the nucleus accumbens in ways likely to augment food intake, particularly of palatable foods – although again the pattern of results is complex and more research is required. A further argument against the simple cognitive approach to understanding the links between ‘restraint’ and stress-induced overeating is suggested by Adam and Epel ((Adam and Epel, 2007), p453). They point to animal models of ‘restrained eating’ involving successive food restriction and stress, and to the observation that, under stressful conditions, these animals do not differ in total food intake, but rather make a relative shift to highly palatable, calorie-dense foods (Boggiano et al., 2005). Other evidence suggests two features of such foods drive this shift: their reward value (as opposed to their metabolic value) and their capacity to attenuate physiological stress responses. The former is suggested by the observation that treatment with the mu-opioid antagonist naloxone markedly reduces the stress-induced increase in palatable food intake (Boggiano et al., 2005). Evidence for the latter proposition derives from several animal studies reporting that high-calorie (fat and/or sugar) diets reduce HPA axis responses to stressors (see discussions in (Warne, 2009, Dallman et al., 2006)). An intriguing aspect of this phenomenon is that it is observable only when the animals are provided with choice of diet (la Fleur et al., 2005). Animals offered highly palatable food alone (e.g., lard) show little or no diminution of ACTH and corticosterone responses to a stressor (such as physical restraint), as is the case for those offered regular chow alone, or a chow/lard mix; but animals offered a choice of regular chow or lard do show a very significant attenuation in the stress response. These findings are very reminiscent of the longstanding evidence from a range of experimental paradigms, human and animal, showing that perceived control typically moderates stress responses. As La Fleur et al point out ((la Fleur et al., 2005), p2197-8) this may be highly relevant to human eating behaviour and obesity in populations that


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are experiencing chronic stress combined with constant availability of highly palatable, calorie-dense foods. Compared to energy intake, the role of the HPA axis and of CRF in energy expenditure has been less studied (see discussions in (Nieuwenhuizen and Rutters, 2008), (Torres and Nowson, 2007) p892, and (Peters et al., 2007)). In general, elevated CRH levels lead to increased resting energy expenditure, perhaps mediated in part via the sympathetic nervous system. Glucocorticoid elevation leads to complex, sometimes opposing effects, although with chronic stress states this tends to be in the direction of diminishing energy expenditure, thus contributing to weight gain and risk of obesity. This net longer-term glucocorticoid effect may be mediated by several mechanisms: feedback inhibition of CRF release; diminished muscle mass; inhibition of thyroid hormone production; and reduction in physical activity levels. A key feature of the obesity induced by glucocorticoid elevation is its central, abdominal distribution (‘visceral obesity’), the form of obesity that is a hallmark of the metabolic syndrome and associated with a range of adverse health outcomes. However, the distribution of body fat is regulated by diverse factors including growth hormone, sex hormones, insulin and NPY (for detailed discussions see (Bjorntorp, 2001, Rosmond, 2005, Dallman et al., 2004, Dallman et al., 2005)) and the centralised obesity in chronic stress states involves factors acting in concert with glucocorticoids, notably insulin and NPY (Kuo et al., 2007). Interestingly, in the latter study (Kuo et al., 2007), chronically stressed mice fed a high fat and sugar diet did not show elevated plasma corticosterone levels, but corticosterone was elevated in abdominal white adipose tissue, probably due to stress-induced upregulation of 11-betahydroxysteroid dehydrogenase-1 (11β-HSD1), the enzyme which converts inactive cortisone to cortisol. Studies also show associations between weight gain and/or obesity and polymorphisms in molecular components of the HPA axis (reviewed in (Nieuwenhuizen and Rutters, 2008, Bornstein et al., 2006)). Complementing these findings are studies in animal models involving over- or under-expression of key genes in this system. Nieuwenhuizen and Rutters (2008) have reviewed evidence implicating polymorphisms of the genes for POMC (pro-opiomelanocortin, the ACTH precursor molecule), corticosteroid 124 Physical and Mental Health Interface

binding globulin (CBG), 11β-HSD1, 11β-HSD2, and GR (glucocorticoid receptor), whilst Bornstein et al (2006) have reviewed evidence from mouse models with genetic manipulations of CRF, the CRF R1 receptor, POMC, 11β-HSD1, and 11β-HSD2. In summary, stressors and stress physiological processes have been implicated in eating behaviour, in the genesis of visceral (or central) obesity, and to a lesser extent in energy expenditure. In addition, in several studies so called ‘palatable’ food (calorically dense food, high in fat and/or sugar), has been shown to attenuate physiological stress responses. The idea that the HPA axis has a role in the genesis of obesity is supported by studies showing that genetic polymorphisms in various components of the HPA axis are associated with greater body weight and obesity, and by studies of animals with the under- or over-expression of key genes in the HPA axis.

Stress in early life: a shared causal factor leading to psychopathology and energy dysregulation in later life? A psychiatrist reading the literature on the causation of obesity and the metabolic syndrome will find striking correspondences between that field and current research on the causation of most mental disorders. Similarly, researchers on obesity and metabolic syndrome are likely to feel at home reading up-to-date accounts of the causation of, say, schizophrenia or major depression. Both kinds of disorder are seen as the end-product of multi-stage psychobiological processes commencing very early in life, although manifesting clinically years or decades later; both involve complex forms of gene-environment interaction; and in both, there is increasing evidence for epigenetic modulation by experience (psychological, metabolic etc) of key physiological processes involved in pathogenesis. Apart from this general framework of thinking, there are specific substantive areas of research that overlap between the two fields. The HPA axis has already been discussed above. A key component of the HPA axis, the GR receptor, has been shown in rats to be epigenetically modified by maternal behaviour: the pups of rat dams that exhibit low levels of mothering behaviour (such as licking, grooming and arched-back nursing) grow up to show more Stress, Obesity and the Metabolic Syndrome

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anxious behaviour and augmented HPA axis responses to stress (Szyf et al., 2007), effects created in the pups by epigenetic modification of the promoter region of the GR gene. The metabolic consequences of this effect are as yet unknown, but given the pivotal role of the HPA axis and GR in energy regulation, they may well be considerable. Another example is serotonergic neurotransmission. A polymorphism in the 5HT transporter gene, termed the ‘short’ allele, has been shown to act as a vulnerability factor for major depression, i.e. the ‘short allele’ has no significant univariate association with depression, but does confer risk in the presence of life stress (Caspi et al., 2003). More recently, the same ‘short’ polymorphism has been reported to be a risk factor for overweight in adolescents (Sookoian et al., 2007) and in adult males (Sookoian et al., 2008). One of the most important areas of correspondence concerns the critical role of early life experience. This has implications both for understanding pathogenesis and ultimately for prevention strategies. In psychiatry, there is abundant evidence for many disorders of the role of early life experience in creating vulnerability or resilience to mental disorder (e.g., for schizophrenia (see Keshavan et al. (2004)). Similarly, there is now abundant evidence that the origins of metabolic syndrome and obesity lie in prenatal and early postnatal life (Cottrell and Ozanne, 2008, Gluckman and Hanson, 2008, Gluckman et al., 2008b, Pankevich et al., 2009) and that, indeed, there may be epigenetically mediated transgenerational effects on metabolism and body weight (Gluckman et al., 2008a).

Conclusion The interface between physical and mental health is nowhere better shown than in the evolving field of research concerning the connections between the psychobiology of stress and the causation of the metabolic syndrome and obesity. This brief overview has omitted many interesting and relevant areas. For example, the serious problem of metabolic syndrome and premature death in schizophrenia and the severe mood disorders has been highlighted by the role of some second-generation antipsychotic medications, such as olanzapine and clozapine (discussed in Chapter ** in this 126 Physical and Mental Health Interface

volume). But adverse effects of these medications are only one amongst many factors leading to these adverse health outcomes in the mentally ill (McElroy et al., 2006). For these populations too, the kinds of stress effects discussed here, operating at multiple points in development, are likely to be relevant and deserve consideration in future research.

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13 Obesity and Psychosis Simon Jones and David Castle

Introduction It is now well established that people with mental illness die prematurely and have significantly higher medical comorbidity and mortality compared to the general population (Brown 1997; Harris and Barraclough 1998). In people with psychotic illnesses such as schizophrenia, schizoaffective disorder and bipolar affective disorder (hereafter referred to as severe mental illness – SMI), cardiovascular disease is the most common cause of premature mortality (Lawrence, Holman et al. 2003). Of the cardiovascular risk factors, the increasing prevalence of weight increase and obesity is one of the most concerning. The prevalence of obesity in this group has exceeded the increases seen in the general population (Dickerson, Brown et al. 2006; Barnes, Paton et al. 2007). This has been shown in prevalence studies in different high-income settings. For example, a U.S. study of people with SMI treated in the community found that 50% of women and 41% of men were obese (compared to 27% and 20% respectively in a matched community sample without psychotic disorders) (Dickerson, Brown et al. 2006); an Australian study of people with psychotic disorders in a residential psychiatric rehabilitation setting found that 59% were obese (Tirupati and Chua 2007), compared to approximately 18% in the general population (2004-5 National Health Survey, www.abs.gov.au/ausstats); and, a UK multi-centre community Obesity and Psychosis

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prevalence study found that 35% of people with SMI were obese compared to 19% in the corresponding 2006 national sample (Filik, Sipos et al. 2006).

Causes for higher prevalence of obesity in people with SMI There are many potential causes for greater weight-gain in this population. People with chronic psychotic disorders are often less physically active than the general population – reasons might include illness factors (e.g. negative symptoms), psychiatric comorbidity (e.g. depression), medication side-effects (e.g. oversedation) or socio-environmental factors (e.g. social isolation or lack of access to exercise equipment) (Brown, Birtwistle et al. 1999; Daumit, Goldberg et al. 2005). People with SMI tend to have increased caloric intake, including higher fat content and reduced fibre and vitamin intake (McCreadie, Macdonald et al. 1998; McCreadie and Scottish Schizophrenia Lifestyle 2003; Daumit, Goldberg et al. 2005). This can be due to many causes, including alterations in satiety regulation associated with the illness, direct appetite stimulation by some medications or other side-effects such as a dry mouth, which may increase intake of high caloric drinks (Strassnig, Brar et al. 2003; Werneke, Taylor et al. 2003). In addition, cognitive deficits associated with chronic psychotic illness (e.g. organisation and planning skills) or economic disadvantage may negatively impact on diet. The widespread use of atypical anti-psychotic medication has also been a significant contributing factor for the high prevalence of obesity in people with SMI (Allison, Mentore et al. 1999). Olanzapine and clozapine have been shown to cause the greatest weight increase. Studies of people with a first episode of psychosis have shown that a majority will experience significant weight gain on these medications. For example, a recent study found that 91% of drug-naïve first episode patients who took olanzapine had an increase in weight of at least 7% during the first year of treatment, compared to 23% of controls matched for age, gender and socioeconomic status (Strassnig, Miewald et al. 2007). Most other atypical anti-psychotic medications have also been found to be associated with a significantly greater increase in weight than older ‘typical’ anti-psychotic medications (Zipursky, Gu et al. 2005). The risk of obesity is even higher when people take multiple anti132 Physical and Mental Health Interface

psychotics or additional medications such as some mood stabilisers (e.g. sodium valproate) or anti-depressants (e.g. mirtazapine) (Correll, Frederickson et al. 2007). Likely mechanisms of antipsychotic-induced weight gain include effects on dopaminergic, serotoninergic and histaminergic neurotransmission, changes in neuroendocrine systems (e.g. hypothalamic-pituitary axis), and changes in neuropeptides (e.g. leptin, tumour necrosis factor: TNF-α) (Zimmermann, Kraus et al. 2003). To date, attempts to find specific genetic variations which lead to increased susceptibility to anti-psychotic induced weight gain have not yielded any conclusive results. Proposed candidate genes have included the leptin and leptin receptor gene, the serotonin transporter (SERT) gene or linked promoter region, the promelanin concentrating hormone (PMCH) gene, the guanine nucleotide binding protein (GNB3) gene, the synaptomal associated protein (SNAP25) gene and the adrenergic alpha2a receptor gene which has been linked to eating behaviours and lipolytic activity (Muller and Kennedy 2006; Bozina, Medved et al. 2007; Ellingrod, Bishop et al. 2007). Association studies which have examined allelic variants of these genes and differences in anti-psychotic weight gain have been limited by small sample sizes and inconsistencies across different populations. The 5HT2C receptor is also thought to modulate feeding behaviour and anti-psychotic medications such as olanzapine and clozapine have potent 5HT2C blockade. Knock-out mouse models suggest a potential role of such blockade in the development of obesity, but its significance in anti-psychotic weight gain in humans remains unclear (De Luca, Muller et al. 2007). Anti-psychotic medications such as olanzapine may also effect leptin regulation and brain derived neurotrophic factor (BDNF), which are thought to modulate food intake, lipid metabolism and changes in weight (Zhang, Tan et al. 2007). Although the mechanisms of individual susceptibility remain unclear, the potential benefit of a more tailored approach to treatment informed by such genetic variants and mediators of weight control is an important goal of ongoing research (de Leon and Diaz 2007).

Impact of obesity on people with SMI Obesity and associated cardiovascular risk factors can negatively impact on the lives of people with SMI in several ways. Obesity Obesity and Psychosis

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alone (without other cardiovascular risk factors) has been shown to increase hospitalisation and mortality risk from coronary heart disease, other cardiovascular disease and diabetes (Yan, Daviglus et al. 2006). Central or visceral adiposity (particularly common in anti-psychotic induced weight gain), associated with at least two of either hypertension, lipid abnormalities, and insulin resistance (hyperglycemia) constitutes the ‘metabolic syndrome’ (Alberti, Zimmet et al. 2005). This has been found to be two to four times more common in people with SMI compared to the general population (Ellingrod, Miller et al. 2008) and is associated with particularly high cardiovascular risk (Henderson, Cagliero et al. 2000; Bermudes, Keck et al. 2006). People with SMI often gain weight from a young age (Strassnig, Miewald et al. 2007) and this can further increase later cardiovascular risk (Weiss, Dziura et al. 2004). Relatively small decreases in weight have been shown to be worthwhile in terms of decreased cardiovascular risk. As little as 5% increase in weight in early adulthood may lead to a doubling of the risk of developing insulin resistance or metabolic syndrome by middle age (Weber and Wyne 2006) – making early preventative strategies worthwhile. Interventions to reduce weight or prevent initial weight gain can have additional benefits on other risk factors such as blood pressure and lipid profile – aside from the other benefits that activities such as exercise can have on mental health. Even if exercise does not lead to weight loss or prevention of weight gain, it can decrease the accumulation of visceral fat, which is associated with a high risk of cardiovascular disease and diabetes (Pascot, Despres et al. 2000; Melanson, McInnis et al. 2001; Tracy 2001). Obesity can cause a range of other medical problems including an increase in some cancers, respiratory insufficiency (e.g. obstructive sleep apnoea) and musculoskeletal problems (Lean, Han et al. 1998). Some of the consequences of these such as shortness of breath with exertion or lower back pain may further impede activity and attempts to lose weight. In addition, the high prevalence of smoking in people with SMI can further exacerbate many of these conditions. There is good evidence that people with SMI frequently stop taking medication due to concerns about weight gain (Pierson 2006; Haupt 134 Physical and Mental Health Interface

2007; Tham, Jones et al. 2007). In one study, obese patients were found to be two times more likely than people with normal BMI to report non-adherence to medication due to concerns about weight, after adjusting for possible confounding factors (Weiden, Mackell et al. 2004). In addition to the risk of psychotic relapse with medication non-adherence, the inactivity and lethargy associated with being overweight can also worsen ‘negative symptoms’. Inactivity and social exclusion can be further exacerbated by other known sequelae of weight gain. Several studies, using different measures (e.g. SF-12, SF-36, B-WISE, IWQoL-Lite), have shown that weight increase in people with SMI contributes to reduced quality of life, lowered self-esteem, and role limitation due to worse physical and emotional functioning (Allison, Mackell et al. 2003; Strassnig, Brar et al. 2003; De Hert, Peuskens et al. 2006; Tham, Jones et al. 2007).

Potential interventions for weight gain and obesity in people with SMI Despite the high prevalence of obesity and the significant impact it has on people with SMI, there have been surprisingly few well designed studies that have examined ways of trying to prevent or reduce obesity in this group. Four systematic reviews of this topic were published between 2002 and 2006. Two of these focused on behavioural interventions (Werneke, Taylor et al. 2003; Loh, Meyer et al. 2006), one on pharmacological management (Werneke, Taylor et al. 2002) and one covered both categories of interventions (Faulkner, Soundy et al. 2003). Most of the studies in these reviews had significant limitations. Some studies were case reviews or medical chart reviews, from which no firm conclusions can be drawn. Others were described as intervention studies but most were not of a randomised control design. There was significant variation in the types of behavioural interventions, very few used any form of standardised or manualised treatment that could be transferred to other settings, none of them had any form of quality control, and most were of short duration (median 8 weeks) so any medium or longer-term benefits of the interventions were unclear. There were also numerous weaknesses in studies of the pharmacological interventions. Although four of the eight studies reviewed were randomised control trials (Werneke, Taylor et al. 2002; Faulkner, Obesity and Psychosis

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Soundy et al. 2003), these were also of short duration (mean 14 weeks) and shared many of the methodological problems of the behavioural studies. The many different types of medications investigated and the small number of studies for each medication also made it difficult to draw any definite conclusions about efficacy. A systematic review in 2007 examined randomised control trials (RCTs) of ‘behavioural’ (5 studies) and pharmacological interventions (18 studies) undertaken prior to April 2006 (Faulkner, Cohn et al. 2007). Only one of the studies from the previous systematic reviews was included in this review. Although all studies were classified as ‘randomised’, the specific method of randomisation was not given in 19 of the studies and there was no evidence of allocation concealment in most studies leading to the possibility of selection bias. As with earlier studies, there was a high loss to follow-up in many trials. Most studies were small (underpowered) and had short follow-up. It is difficult to make any conclusions from this review due to the potential for bias in many of the individual studies and the fact that meta-analysis was not possible due to the heterogeneity of many aspects of the studies – different populations (e.g. inpatient versus outpatient), different psychiatric conditions, and variation in ‘behavioural’ interventions (e.g. group versus individual, dietary modification versus exercise program). Table 13.1 shows the randomised control trials published since the 2007 Cochrane Review [literature search (to week 1, July 2008) using Medline and PsycINFO]. Compared with earlier studies, these trials had a broader range of outcome measures including multiple anthropometric measures, different metabolic measures and standardised quality of life measures in addition to more commonly used psychiatric rating scales. Follow-up rates were better than many earlier studies and most used an intention-to-treat analysis. However, some of the methodological deficiencies of earlier studies were repeated. For example, only two studies followed-up participants beyond the completion of the intervention (Jean-Baptiste, Tek et al. 2007; Khazaal, Fresard et al. 2007), so there is still very little evidence of any persistent benefits from either the behavioural interventions or medications.


Numerous medications have been tested for weight loss or prevention in the general population. Orlistat (an inhibitor of fat absorption) and sibutramine (a centrally acting appetite suppressant) have been shown to be most effective for weight reduction and are licensed specifically for long-term management of weight loss. They have also been shown to improve lipid profile and glycemic control (Werneke, Taylor et al. 2002; Faulkner, Cohn et al. 2007). Both these medications have potential problems for people with SMI. Sibutramine has been associated with panic symptoms and exacerbation of psychotic symptoms. In one study of people with bipolar affective disorder and obesity, almost 80% of subjects taking sibutramine did not complete the 24 week trial (McElroy, Frye et al. 2007). Taking orlistat without dietary change can lead to unpleasant side effects such as flatulence or faecal incontinence – potentially more of a problem in people with SMI who tend to have a higher fat content in their diet (Werneke, Taylor et al. 2002; McCreadie and Scottish Schizophrenia Lifestyle 2003). Such side effects also make blinding in trials impossible. A recent study of orlistat in people with clozapine or olanzapine-induced weight gain had inconclusive results (Joffe, Takala et al. 2008). Of other medications that have been trialled, metformin has shown some promise for prevention of weight gain and treatment of obesity and is generally well tolerated and is safe provided precautions are taken (i.e. check of liver function prior to commencement due to the risk of lactic acidosis if a person has hepatic failure). It has minimal side effects and has also shown benefits in terms of improvements in insulin resistance and lipid profile (Knowler, Barrett-Connor et al. 2002). We are aware of five trials of metformin in people with SMI (Morrison, Cottingham et al. 2002; Baptista, Martinez et al. 2006; Klein, Cottingham et al. 2006; Baptista, Rangel et al. 2007; Wu, Zhao et al. 2008). Although some of these studies have concluded that metformin may have a role in abrogating weight gain or assisting weight loss, some have had similar methodological weaknesses to those outlined above; further, larger, more rigorous longer-term studies are needed. The potential advantage of comprehensive lifestyle interventions over medication in reducing risk factors has been highlighted in other settings. The Diabetes Prevention Program found that a ‘lifestyle modification program’ reduced the incidence of diabetes in people at high risk and was superior to metformin (Knowler, Obesity and Psychosis

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Barrett-Connor et al. 2002). Given the above limitations with many of the studies of behavioural type interventions, there is a need for larger and better designed studies of interventions designed to reduce multiple cardiovascular risk factors including weight gain and obesity in psychiatric populations. A recent pilot study assessed the feasibility of conducting a multicomponent risk factor intervention to promote smoking cessation and a change in body mass index among people with psychosis in community settings in Melbourne, Newcastle, and Sydney (Baker, Richmond et al., in press). It also examined whether reduction in smoking and weight was associated with improved body image, decreased depression and improved quality and enjoyment of life. Over a 3 month period there was excellent follow-up (100%) with good evidence of reduced smoking and improvement in quality of life related to weight reduction. The sample size (n=43) meant the study had low power, but there was still some evidence of improvement in physical activity, weight decrease and decrease in overall coronary risk percentile. There is a need for further well designed randomised control trials with sufficient power to determine if such interventions could be effective in community mental health settings. Other priorities of future research include studies with longer follow-up times (including outcome measurements beyond the cessation of the intervention), and trials which examine the effect of an intervention on overall cardiovascular risk rather than single outcome measures such as weight or insulin resistance. Table 13.1 Randomised control trials for weight loss in people with SMI, since Cochrane review* (Faulkner, Cohn et al. 2007)

INSERT TABLE


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JEAN-BAPTISTE, M., C. TEK, et al. (2007). "A pilot study of a weight management program with food provision in schizophrenia." Schizophrenia Research 96(13): 198-205. JOFFE, G., P. TAKALA, et al. (2008). "Orlistat in clozapine- or olanzapine-treated patients with overweight or obesity: a 16-week randomized, double-blind, placebo-controlled trial." Journal of Clinical Psychiatry 69(5): 706-11. KHAZAAL, Y., E. FRESARD, et al. (2007). "Cognitive behavioural therapy for weight gain associated with antipsychotic drugs." Schizophrenia Research 91(1-3): 169-77. KLEIN, D. J., E. M. COTTINGHAM, et al. (2006). "A randomized, double-blind, placebo-controlled trial of metformin treatment of weight gain associated with initiation of atypical antipsychotic therapy in children and adolescents.[see comment]." American Journal of Psychiatry 163(12): 20729. KNOWLER, W. C., E. BARRETT-CONNOR, et al. (2002). "Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.[see comment]." New England Journal of Medicine 346(6): 393-403. LAWRENCE, D. M., C. D. a. J. HOLMAN, et al. (2003). "Death rate from ischaemic heart disease in Western Australian psychiatric patients 1980-1998." British Journal of Psychiatry 182: 31-6. LEAN, M. E., T. S. HAN, et al. (1998). "Impairment of health and quality of life in people with large waist circumference." Lancet 351(9106): 853-6. LOH, C., J. M. MEYER, et al. (2006). "A comprehensive review of behavioral interventions for weight management in schizophrenia." Annals of Clinical Psychiatry 18(1): 23-31. McCREADIE, R., E. MacDONALD, et al. (1998). "Dietary intake of schizophrenic patients in Nithsdale, Scotland: case-control study." BMJ 317(7161): 784-5. McCREADIE, R. G. and G. Scottish Schizophrenia Lifestyle (2003). "Diet, smoking and cardiovascular risk in people with schizophrenia: descriptive study.[see comment]." British Journal of Psychiatry 183: 534-9. McELROY, S. L., M. A. FRYE, et al. (2007). "A 24-week, randomized, controlled trial of adjunctive sibutramine versus topiramate in the treatment of weight gain in overweight or obese patients with bipolar disorders." Bipolar Disorders 9(4): 426-34. McKIBBIN, C. L., T. L. PATTERSON, et al. (2006). "A lifestyle intervention for older schizophrenia patients with diabetes mellitus: a randomized controlled trial." Schizophrenia Research 86(1-3): 36-44. MELANSON, K. J., K. J. McINNIS, et al. (2001). "Obesity and cardiovascular disease risk: research update.[see comment]." Cardiology in Review 9(4): 202-7. MORRISON, J. A., E. M. COTTINGHAM, et al. (2002). "Metformin for weight loss in pediatric patients taking psychotropic drugs." American Journal of Psychiatry 159(4): 655-7. MULLER, D. J. and J. L. KENNEDY (2006). "Genetics of antipsychotic treatment emergent weight gain in schizophrenia." Pharmacogenomics 7(6): 863-87.


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WU, R.-R., J.-P. ZHAO, et al. (2008). "Lifestyle intervention and metformin for treatment of antipsychotic-induced weight gain: a randomized controlled trial." JAMA 299(2): 185-93. YAN, L. L., M. L. DAVIGLUS, et al. (2006). "Midlife body mass index and hospitalization and mortality in older age.[see comment]." JAMA 295(2): 1908. ZHANG, X. Y., Y. L. TAN, et al. (2007). "Serum BDNF levels and weight gain in schizophrenic patients on long-term treatment with antipsychotics." Journal of Psychiatric Research 41(12): 997-1004. ZIMMERMANN, U., T. KRAUS, et al. (2003). "Epidemiology, implications and mechanisms underlying drug-induced weight gain in psychiatric patients." Journal of Psychiatric Research 37(3): 193-220. ZIPURSKY, R. B., H. GU, et al. (2005). "Course and predictors of weight gain in people with first-episode psychosis treated with olanzapine or haloperidol.[see comment]." British Journal of Psychiatry 187: 537-43.


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14 Depression, Anxiety and Substance Use Disorders in People Living with HIV Helen Schultz and David Castle

Introduction Since the introduction of highly active anti-retroviral therapy (HAART) in 1996, the mortality and morbidity of people living with HIV has significantly decreased. Despite this, the number of people becoming infected continues to grow. HIV infection combined with substance use and mental illness represents a major challenge to health care providers. If substance use and depression are not adequately managed the ability to treat HIV infection is compromised. On a larger scale, the comorbid presence of these conditions represents a risk to infection rates in the wider population. This chapter outlines the epidemiology, clinical presentation and treatment approaches to assist people living with HIV who have comorbid depression and/or anxiety.

Epidemiology Depression The number of cases of HIV infection worldwide has grown to over 30 million, and 50% of these cases are women. (UNAIDS, 2008). Depression, Anxiety and Substance Use Disorders in People Living with HIV

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In Australia, the number of people living with HIV was estimated at over 20,000 (National Centre in HIV Epidemiology and Clinical Research, 2008). In contrast to many other less developed parts of the world, the primary means of transmission in Australia is sexual contact between men. Therefore, gay men make up the majority of those living with HIV (National Centre in HIV Epidemiology and Clinical Research, 2008). As gay men, both HIV-positive and -negative, have a higher incidence of mental health problems than heterosexual men (Rogers et al, 2003), it becomes obvious that the ability to treat HIV infection along with mental health and substance use disorders is critical to improve quality of life for individuals, as well as reducing the likelihood of a rise in infection rates through high-risk behaviour. It is well documented that women tend to have a higher incidence of depressive episodes compared to men, due to the effects of oestrogen at life stages such as menopause and post partum. As the number of women with HIV increases and a greater number of women with HIV live until menopause, there may be a concurrent rise in mood disorders such as depression amongst this cohort. Estimates of the incidence of depression in people living with HIV vary from less than 5% to 48% (for review see Hartzell et al, 2008). The variation is dependant upon the population studied, the size of the cohort and the use of different diagnostic instruments for depression. Nonetheless, the general consensus is that the level of depression is higher in those living with HIV. Various factors contribute to depression in people living with HIV. These include: stigma, loss of employment, isolation, debility, the stress of living with an illness and change of body image. In gay men, there might also be a greater chance of isolation from family caused by a lack of acceptance of their homosexuality.

Anxiety Like depression, the prevalence of anxiety in people living with HIV was found to be varying from 5% up to 38% (for review see Hartzell et al, 2008). This variation is due to differing patient groups, sample sizes and diagnosis methodologies. Nonetheless, it is generally considered that many HIV-infected patients have 146 Physical and Mental Health Interface

anxiety and/or experience panic attacks. Anxiety disorders increase the likelihood of poor adherence to HAART. When patients present with comorbid symptoms of anxiety, PSTD and/or depression, they are also more likely to engage in high-risk behaviour that is associated with a higher risk of infection in the community.

Clinical presentation Depression Depression can develop in patients before or after infection with HIV. This condition might be caused by a pre-existing mood disorder, the effects of substance use or medications (such as antiretroviral drugs) or underlying medical conditions such as HIV viral load in the central nervous system or other opportunistic infections. Studies of gay men living with HIV suggest that depression is predominantly due to psychosocial concerns rather than physical or medical illness (Komiti et al, 2002). The clinical presentation of people living with HIV is problematic as many of the clinical and life situations faced by patients can give similar symptoms without being caused by major depression. It is important that depression is not considered a normal or natural response for a patient who has learnt of their HIV diagnosis, as failure to diagnose and treat mental health problems results in poorer outcomes. (Obviously, depressed HIV-positive patients are also at higher risk of suicide attempts, especially if there is a history of such attempts.) While diagnosis with a serious medical condition is cause for a normal stress response, the persistent presence of depressive symptoms (for longer than two weeks), should be considered as possibly representing a major depressive episode. The differential diagnosis is that of an adjustment disorder, which occurs after a defined stressor, and resolves within a period of six months. Both diagnoses warrant careful assessment and management. However, these disorders can be difficult to define in HIV-infected patients, as several of the symptoms could be due to treatment. For instance, fatigue and weight loss could be the result of depression or the physical conditions caused by HIV infection or HIV treatment. Symptoms of depression that people living with HIV have in common with HIV-negative patients include changes in appetite, Depression, Anxiety and Substance Use Disorders in People Living with HIV

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sleep, sexual function, energy as well as cognitive symptoms like feeling hopeless, helpless, guilty, anhedonic, suicidal and negative about one’s self and others. While a depressed mood is often present, depressive symptoms may involve a variety of other symptoms such as apathy or feeling “stressed”. In Australia, a survey found that general practitioners (GPs) understood that gay men living with HIV were more likely to present in the clinic with sexual dysfunction as the major symptom associated with their depression (Newman et al, 2008). This was thought to represent the high value placed on physical fitness and sexual activity in the gay male community. A differential diagnosis of bipolar disorder should always be considered, especially before commencing treatment with antidepressants, some of which exacerbate manic symptoms. HIV and other infections of the brain along with medications such as corticosteroids, androgens, didanosine, zidovudine and efavirnez have all been associated with the induction of mania. Symptoms that could suggest bipolar disorder include, a decreased need or ability to sleep, excessive energy and overactivity, increased impulsive and/or sexual behaviours, increased spending, excessive irritability, overactive thoughts, increased talking, elation and grandiosity. An increase in substance use after commencing antidepressant medication can also indicate emerging manic symptoms. If depressive symptoms seem to be independent of the results of a psychological assessment, neurocognitive testing and neurological examination should be performed to exclude the possibility of neurodegenerative changes. For instance apathy, a common symptom of depression, may be indicative of subcortical neurocortical degeneration.

Anxiety It is rare for patients to exhibit symptoms of anxiety without also exhibiting symptoms of depression. Therefore, the clinical evaluation for anxiety is similar to that already described for depression. However, for anxiety disorders, careful exploration of past and family history of anxiety disorders, as well as elucidation of somatic symptoms such as headaches, excessive sweating, palpitations and muscle spasms is warranted. 148 Physical and Mental Health Interface

Anxiety may be profound at the time of diagnosis and at other important stages during the clinical course, such as the development of opportunistic infections. In some cases the level of anxiety may reach the level require for a diagnosis of an adjustment disorder.

Risk issues and assessment The combination of mental health problems (such as major depressive, anxiety and substance use disorders) and HIV infection can have a major impact on the patient. •

In the first instance, such people are less likely to access medical treatment, including HAART. If they do, the timing of treatment can be significantly delayed compared with patients who do not have a mental illness. In contrast, GPs in Australia felt that gay men were more likely to access medical care than heterosexual men (Newman et al, 2008).

•

Once they have accessed medical support, these patients are less likely to adhere to medical treatment, such as HAART, thus reducing the immunological and virological outcomes of the medication.

•

Some patients with a triple diagnosis are more likely to engage in high-risk sexual and substance-use behaviours. These might also increase the likelihood of co-infection with other sexuallytransmitted or blood-borne diseases such as herpes, hepatitis B, and hepatitis C. There is also potential for infection with a number of different strains of HIV. Sexually transmitted diseases (STDs) also increase the risk of HIV transmission.

The combination of these three issues is more likely to result in a poor outcome for the patient and increases the risk of transmission of HIV. The literature outlines a complex picture of the cause of high-risk behaviour in people living with HIV (see Horberg et al, 2008; Parry et al, 2007; Walkup et al, 2008). Given the high likelihood of poor outcomes, screening and assessment combined with regular rescreening are valuable tools that can reduce under-diagnosis of depression and substance use. The ability to find those who are more likely to engage in high-risk sexual and/or needle-use


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behaviours enables targeted interventions and strategies to improve outcomes for individuals.

Implications for management and outlook of HIV infection Management and risk reduction for HIV-positive patients who also have a mental illness can be challenging. Interventions can be difficult to implement in patients facing many psychological and social problems (see below for discussion of psychosocial issues) but nonetheless, a number of strategies have proved effective. Those that combine treatments and target each of the factors involved in individual patient’s problems appear to give the best outcomes. Providing concomitant mental health and substance use treatments is important to retain patients in medical care for their HIV. By so doing, outcomes for the individual are improved and infection control (both of HIV and opportunistic infections) is greatly improved. Pharmacological and cognitive therapies have been effective in treating depression and anxiety in people living with HIV. Successful outcomes are more likely if depressed patients are treated with both HAART and antidepressants. A recent study has shown that treatment of depressed patients with both HAART and antidepressants improves adherence to HAART and improves virological outcomes to the same level as those shown by nondepressed patients taking HAART alone (Horberg et al, 2008). This type of regimen is also best combined with counselling for highrisk behaviours. GPs in Australia believe that regular and high frequency contact has been a successful method for improving management of depression in HIV-positive gay men (Newman et al, 2009). Where substance use is a concern, interventions are best when they target substance use and risk behaviours. It is well established that HIV transmission is lowered by reducing intravenous drug use with pharmacological treatments such as methadone while at the same time promoting needle exchange and safe disposal of used needles. Means of improving infection control in other settings have included testing for substance use in psychiatric and criminal justice facilities. On the whole, such screening for substance use is


best initiated in primary care rather than waiting for patients to reach specialist care. In fact, being in medical care itself reduces high-risk behaviours in HIV-positive drug users compared with those who are not in care (Walkup et al, 2008). An example of a multidisciplinary treatment protocol based on public-health approaches has been developed (Rosenberg et al, 2004). In this intervention, clients are screened for sexual and needle-use high-risk behaviour, tested for HIV and hepatitis, immunised for hepatitis A and B and provided with risk-reduction counselling. This process (STIRR: screen, test, immunise, reduce risk, refer takes about one hour per patient and a pilot study at a community mental health centre showed that the participation rate was 68%. The patients involved demonstrated improved knowledge of blood-borne infections and an increased motivation for prevention.

Management of mental health issues Biological (psychopharmacology) People living with HIV are at risk of negative complex drug interactions for a number of reasons. •

Patients can be taking a combination of three or more antiretroviral agents.

•

Many of these anti-retroviral agents have a great effect on the cytochrome p450 (CYP450) enzyme system.

•

Patients might be taking one or more drugs for opportunistic infections.

•

Some patients require treatment with psychotropic drugs.

•

With the advent of HAART, patients are living longer and might also be taking drugs for illnesses such as diabetes and coronary artery disease.

For treatment of mental health problems, there is evidence that prescribing anti-retroviral medication alone can improve the quality of life and psychological health of patients, probably by improving overall physical wellbeing. However, as discussed, for many Depression, Anxiety and Substance Use Disorders in People Living with HIV

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patients untreated depression and anxiety can render treatment with anti-retroviral medication less than effective. For this reason, in many cases, concomitant treatment with psychotropic agents is required. Antidepressants and anxiolytics are the most commonly prescribed psychotropic drugs for people living with HIV. The primary goals of treatment with these drugs are to eliminate symptoms of depression and anxiety, minimise drug side effects, and to avoid drug-illness and drug-drug interactions. In general, treatment with antidepressants is best started at lower doses and gradually increased. This should proceed at a slower rate for people living with HIV, especially if their illness is advanced or their treatment regimens are complex. As mentioned, for all patients treated with antidepressants, the clinician should be wary for any signs that symptoms of mania are emerging and, if so, take appropriate action. The need to prescribe antidepressants might also affect the choice of anti-retroviral treatment. For instance, efavirenz has potential neuropsychiatric effects. In addition, psychotropic drugs and antiretrovirals might both be metabolised by CYP450 enzymes and lead to drug-drug interactions (see Colibazzi et al, 2006), although this issue requires further study. It is also unfortunate that the majority of research that specifically studies medical complications arising from antidepressants was performed before the use of HAART. The interaction between anti-retroviral and psychotropic drugs, as we currently understand it, is due to the mode with which these drugs interact with the CYP450 system. Based on the information that follows in this section (see Colibazzi et al, 2006; Olatunji et al, 2006; Repetto & Petitto, 2008; Thompson et al, 2006), Table 14.1 suggests psychotropic drugs that could be considered first-line agents after a pre-treatment risk-benefit analysis has been undertaken for each patient.


Table 14.1 Potential first-line psychotropic drugs for treating depression and anxiety in HIV-positive patients Antidepressants SSRIs Citalopram Escitalopram Sertraline Fluoxetine (some interactions with anit-retrovirals) Paroxetine (some interactions with anit-retrovirals) SNRIs Venlafaxine Duloxetine Novel agents Mirtazapine Anxiolytics Glucuronidated benzodiazepines Lorazepam Temazepam Oxazepam

Anti-retroviral drugs All protease inhibitors (PIs) and nonnucleoside reversetranscriptase inhibitors (NNRIs) are metabolised by isoenzymes of the CYP450 system and can inhibit or induce isoenzymes of CYP450. It is this complex interaction that warrants considerable care when these drugs are combined with antidepressant and anxiolytic drugs, which can also interact with CYP450. Ritonavir is the most likely anti-retroviral drug to have significant interactions as it is metabolised by CYP3A4 and 2D6 and potently inhibits CYP3A, 2D6, 2C9 and 2C19 isoenzymes. On the other hand, the third class of anti-retrovirals, the nucleoside reverse-transcriptase inhibitors do not significantly interact with CYP450 and are therefore less likely to interfere with psychotropic drugs.

Tricyclic antidepressants (TCAs) While a pre-HAART study showed that imipramine effectively treated depression in HIV-positive patients, adverse side effects led Depression, Anxiety and Substance Use Disorders in People Living with HIV

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to high rates of discontinuance of therapy. Although this class of drug might be effective against depressive symptoms, the more modern antidepressants that have fewer side effects are more likely to be used for depressed patients. Therefore the use of TCAs is limited to some patients who do not respond to other medications. In addition to the above concerns, as TCAs are metabolised by the CYP450 enzymes, there is the possibility that combination treatment with anti-retroviral agents that inhibit CYP450 isoenzymes could increase the toxicity of the TCAs.

Selective serotonin reuptake inhibitors (SSRIs) SSRIs are used to treat a number of disorders including depression (fluoxetine, sertraline, paroxetine, citalopram, escitalopram), anxiety (paroxetine and escitalopram), panic disorder (fluoxetine, sertraline, and paroxetine), PTSD (sertraline and paroxetine) and other disorders not considered here. They are preferred over TCAs because of their relatively lower side-effect profile and a reduced toxicity from overdosing. SSRIs do, however, have some side effects including insomnia, anxiety, agitation, irritability, nausea and sexual dysfunction. Many of these side effects subside within a few days of treatment except for sexual dysfunction that is more likely to persist. This could be an issue in the Australian context where many HIV-positive patients are gay men. GPs have reported that their gay male patients are very concerned about sexual function and that it was difficult to treat these patients without affecting their sexual function. The interactions that occur between the older SSRIs and antiretroviral drugs are primarily through their interactions with the CYP 3A4 and 2D6 isoenzymes. In contrast, the newer SSRIs such as citalopram and escitalopram interact with the 2C19 isozyme and are therefore less likely to interact with anti-retroviral drugs. Sertraline interacts with a number of the CYP450 isoenzymes (CYP2D6, CYP2C9, CYP2B6, CYP2C19 and CYP3A4). Thus inhibition of one or two of these isoenzymes (for instance, by an anti-retroviral) is less likely to significantly affect sertraline’s efficacy, as it can still interact with other CYP450 isoenzymes.


Serotonin and noradrenaline reuptake inhibitors (SNRIs) The newer generation SNRIs have proved helpful for treating depression in HIV-positive patients. These agents are also useful for treating anxiety and chronic pain in those patients where these symptoms are an issue. Venlafaxine weakly interacts with CYP2D6 and thus has a much lower possibility of interacting with anti-retroviral drugs. Duloxetine interacts with CYP2D6 and 1A2 and therefore clinicians should monitor for adverse interactions, especially with ritonavir.

Mirtazapine This novel antidepressant interacts with CYP450 isoenzymes 1A2 and 2D6 and might lead to adverse reactions, especially with ritonavir. Clinicians should therefore monitor for adverse reactions as little is known about the drug-drug interactions of this antidepressant. The side-effect profile, including sedation and weight gain, has made it a useful treatment for depression in people living with HIV who are having trouble sleeping and need to gain weight.

Anxiolytics Most anxiolytics are metabolised by CYP3A4. As such, a potent inhibitor of this enzyme such as ritonavir could decrease the clearance of these drugs and potentially lead to overdosing, oversedation and possibly death. However, the glucuronidated benzodiazepines such as lorazepam, temazepam and oxazepam are metabolised by glucuronidation and are therefore a better choice for people living with HIV. It should be noted that ritonavir and nelfinavir increase the rate of glucuronidation and could decrease the levels of these anxiolytics in the blood. This outcome is preferred to the possibility of oversedation. The ongoing use of any members of this class of drugs is not recommended, especially in patients who have problems with substance use. For longer term treament, clinicians could try antidepressants such as venlafaxine that is also useful for reducing anxiety. Depression, Anxiety and Substance Use Disorders in People Living with HIV

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Psychological interventions Psychological and social interventions are important for any patient with depressive, anxiety or substance use disorders. For those who are also living with HIV, common sense suggests that such interventions are even more important to improve health outcomes and to reduce infection rates. In addition, some patients might prefer help from some form of psychosocial therapy rather than medication. Whatever the theoretical orientation of the psychological intervention, for people living with HIV it is particularly important to provide: •

A safe and trusting environment in both primary and secondary care

•

A focus on reducing high-risk sexual and needle-use behaviours

•

Ongoing monitoring of use of drugs and/or alcohol and adoption of relapse prevention strategies

The amount of research available conducted on psychotherapy for HIV-positive patients is limited and much of it was performed in the pre-HAART era. It is therefore difficult to state which of the available strategies is most effective for people living with HIV. However, research suggests that treatment with psychological interventions in people living with HIV appears to give better outcomes than no treatment. The following types of therapies can be used in both an individual, family- or group-based context: •

Supportive psychotherapy

•

Cognitive-behavioural therapy (CBT)

•

Interpersonal therapy.

Although research is limited (see Colibazzi et al, 2006; Ferrando & Freyberg, 2008; Olatunji et al, 2006), it appears that individual and group-based interpersonal and CBT are more effective that supportive psychotherapy. Given the importance of this issue, there is possibly a need for more research into useful psychosocial therapies specifically for people living with HIV to help them find optimal treatments. On the other hand, Australian researchers have 156 Physical and Mental Health Interface

suggested that current psychosocial interventions could be modelled on those for HIV-negative populations as they found that there was not a distinct type of depression in people with HIV compared with those who do not have HIV (Judd et al, 2005).

Social issues An Australian study of people living with HIV showed that psychosocial issues were more likely to be the cause of depression than organic or medical illness related to HIV infection (Komiti et al, 2002). In the HAART era, patients are more likely to live longer and to be medically “well” and therefore, a set of well-recognised psychosocial risk factors predicted depression. These include: •

Substance use

•

Personality style

•

Personal history of depression

•

Family history of psychiatric illness

•

Social isolation

A causal relationship between depression and substance use is not clear, as depression could lead a person to substance use or, just as likely, substance use could ultimately result in depression. Social support was shown to be a protective factor from depressive symptoms and highlights the need for social interventions in people living with HIV who have depression, anxiety or substance use disorders (Judd et al, 2005). A qualitative study of Australian GPs found that high frequency of contact and support for their patients was helpful, especially for those who were socially isolated from their families (Newman et al, 2009). Given that depression in people living with HIV was attributed to psychosocial factors, it has been suggested that interventions can be modelled upon those used for other groups that develop depression (Judd et al, 2005). In general, studies have shown that for patients with combined mental health with substance use diagnoses, integrated treatment


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for both issues is more effective that separate services. For people living with HIV, the same would most likely be true. People living with HIV and who receive a combination of social services in addition to medical and psychological services are more likely to remain in medical care and to adhere to HAART, thus improving outcomes (see Parry et al, 2007). These social services include: •

Housing

•

Financial and legal assistance

•

Food and nutrition

•

Complimentary therapies

•

Spiritual counselling

Ideally, these services would be integrated and tailored for the individual and supply ongoing support. Comorbid features such as alcohol and drug use should also be targeted and patients may be referred to peer-support services. Groups such as Narcotics Anonymous, Alcoholics Anonymous or HIV and substance use support groups can be helpful to minimise high-risk behaviours and to augment social support.

3 ADDITIONAL TABLES TO BE INSERTED HERE? REFERENCES COLIBAZZI T, HSU TT, GILMER WS. 2006. Human immunodeficiency virus and depression in primary care: a clinical review. Prim Care Companion J Clin Psychiatry 8:201-11. FERRANDO SJ, FREYBERG Z. 2008. Treatment of depression in HIV positive individuals: a critical review. Int Rev Psychiatry 20:61-71. HARTZELL JD, JANKE IE, WEINTROB AC. 2008. Impact of depression on HIV outcomes in the HAART era. J Antimicrob Chemother 62:246-55. HORBERG MA, SILVERBERG MJ, HURLEY LB, TOWNER WJ, KLEIN DB, et al. 2008. Effects of depression and selective serotonin reuptake inhibitor use on adherence to highly active antiretroviral therapy and on clinical outcomes in HIV-infected patients. J Acquir Immune Defic Syndr 47:384-90.


JUDD F, KOMITI A, CHUA P, MIJCH A, HOY J, et al. 2005. Nature of depression in patients with HIV/AIDS. Aust and NZ J Psychiatry 39:826-32. KOMITI A, JUDD F, GRECH P, MIJCH A, HOY J, et al. 2002. Depression in people living with HIV/AIDS attending primary care and outpatient clinics. Aust and NZ J Psychiatry 37:70-7. National Centre in HIV Epidemiology and Clinical Research. HIV/AIDS, viral hepatitis and sexually transmissible infections in Australia Annual Surveillance Report 2008. NEWMAN CE, KIPPAX SC, MAO L, ROGERS GD, SALTMAN DC, KIDD MR. 2009. Features of the management of depression in gay men and men with HIV from the perspective of Australian GPs. Fam Pract 26:27-33. NEWMAN CE, KIPPAX SC, MAO L, SALTMAN DC. 2008. GPs understanding of how depression affects gay and HIV positive men. Aust Fam Physician 37:678-80. OLATUNJI BO, MIMIAGA MJ, O'CLEIRIGH C, SAFREN SA. 2006. Review of treatment studies of depression in HIV. Top HIV Med 14:112-24. PARRY CD, BLANK MB, PITHEY AL. 2007. Responding to the threat of HIV among persons with mental illness and substance abuse. Curr Opin Psychiatry 20:235-41. REPETTO MJ, PETITTO JM. 2008. Psychopharmacology in HIV-infected patients. Psychosom Med 70:585-92. ROGERS G, CURRY M, ODDY J, PRATT N, BEILBY J, WILKINSON D. 2003. Depressive disorders and unprotected casual anal sex among Australian homosexually active men in primary care. HIV Med 4:271-5. ROSENBERG S, BRUNETTE M, OXMAN T, MARSH B, DIETRICH A, et al. 2004. The STIRR model of best practices for blood-borne diseases among clients with serious mental illness Psychiatric services 55:660-4. THOMPSON A, SILVERMAN B, DZENG L, TREISMAN G. 2006. Psychotropic medications and HIV. Clin Infect Dis 42:1305-10. UNAIDS. 2008 Report of the global AIDS epidemic. WALKUP J, BLANK MB, GONZALEZ JS, SAFREN S, SCHWARTZ R, et al. 2008. The impact of mental health and substance abuse factors on HIV prevention and treatment. J Acquir Immune Defic Syndrome 47:S15-S9.


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15 HIV, Methamphetamine, and the Brain in the Era of Antiretroviral Treatment Timothy Nguyen, Chad Bousman, Gursharan Chana, Erick Tatro, and Ian Everall

Introduction Human Immunodeficiency Virus (HIV) infection is a global pandemic and methamphetamine (METH) use is a growing public health emergency that is often associated with HIV. In this review, we will discuss the current understanding of HIV infection and its neuropathology together with the evidence of synergistic neuropathological effects of METH, and how they may relate to the clinical development of HIV associated neurocognitive disorder (HAND). In the current era of highly active antiretroviral therapy (HAART), the infected population is growing due to prolonged life expectancy. Between 30.6 and 36.1 million people are living with HIV worldwide and in 2007 it is estimated that 2.7 million people were newly infected while 2.0 million died (Report on the global AIDS epidemic, 2008). The most recent prevalence data in the United States estimates 0.72% of men and 0.20% of women between the ages of 18-49 are living with HIV. More than half (53%) of new HIV infections in the US are among men who have sex with men, and 18% are injection drug users (Report on the global AIDS epidemic, 2008). Although HAART has increased the lifespan of HIV seropositive individuals, up to 30% of the population develops HAND. HAND is characterised by diminished HIV, Methamphetamine, and the Brain in the Era of Antiretroviral Treatment

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psychomotor response, behavioural slowing, and impaired cognitive function that affect daily activities and lowers quality of life (Kaplan, et al., 1995; Tozzi, et al., 2004), particularly, in later stages of infection when viral load and immunosuppression is high (Bhaskaran, et al., 2008). Recent evidence has indicated that methamphetamine (METH) is a significant behavioural and biological comorbidity factor in contracting HIV and developing HAND. HIV infected METH users have significantly elevated rates of dependence (Bing, et al., 2001) and are more likely to participate in high-risk sexual behaviour and subsequently transmit HIV (Bousman, et al., 2009; Rawson, et al., 2008). Interactions between METH use and HIV-infection are a major public health concern for a variety of reasons. METH has been shown to increase blood-brain barrier (BBB) permeability and potentiate viral entry into the central nervous system (CNS) (Mahajan, et al., 2008), enhance HIV infection of macrophages (Liang, et al., 2008), and monocyte derived dendritic cells (Nair, et al., 2009). In addition, METH use has been linked to poor adherence to medication regimen, decreased efficacy of HAART, and increased HIV viral loads (Ellis, et al., 2003). Furthermore, it was suggested that METH is consumed with greater frequency among seropositive individuals to self-manage HIV-related depression, fatigue, and neuropathic pain (Robinson & Rempel, 2006). Thus, it appears that the interaction between METH use and HIV-infection is complex and potentially synergistic in causing neurocognitive decline.

Neuropathology of HIV infection in the central nervous system HIV infection of the central nervous system occurs early after primary systemic exposure. Originating in the peripheral system, binding of the HIV envelope protein gp120 to the primary receptor CD4 and chemokine co-receptors CXCR4 and CCR5 facilitates HIV fusion into lymphocytes and monocytes respectively (Dragic, et al., 1996). Referred to as the 'Trojan Horse' hypothesis, initial viral entry into the CNS is thought to occur by the normal migration of infected peripheral blood monocytes across the BBB (Kim, Corey, Alvarez, & Williams, 2003). Normally, tight junctions formed by specialised microvascular endothelial cells of the BBB prevent the free diffusion of circulating pathogens and 162 Physical and Mental Health Interface

cells into the brain. However, the BBB is selectively permeable to essential ions and peripheral blood monocytes that transform into macrophages and augment normal macrophage turnover in the CNS without altering tight junction integrity. Infected peripheral monocytes migrate across the BBB where, as part of an inflammatory response, they release toxic viral proteins, cytokines, and chemokines which recruit neuroprotective microglia and macrophages to the area (Buckner, Luers, Calderon, Eugenin, & Berman, 2006). Unlike microglia or macrophages, direct infection of neurons and astrocytes appears to be restrictive in that neurons have not been shown to replicate the virus and astrocytes have only been shown to produce early viral regulatory proteins (Gorry, et al., 2003). However, as the primary infected cells, microglia and macrophages replicate the virus, propagate it throughout the CNS, and release neuroinflammatory mediators that disrupt the BBB and astrocyte homeostatic mechanisms to induce neuronal apoptosis (Hult, Chana, Masliah, & Everall, 2008; Kaul & Lipton, 2006). While much has been elucidated regarding neuronal injury and death, the process is not clearly understood. Free-floating HIV and its shed viral proteins gp120, vpr, nef, and tat have been implicated in directly inducing dendritic simplification and neuronal apoptosis on their own (Alirezaei, et al., 2007; Bonavia, et al., 2001; Rom, et al., 2009; Trillo-Pazos, McFarlane-Abdulla, Campbell, Pilkington, & Everall, 2000). However, the predominant causes of neuronal injury seem to be indirect mechanisms of neurodegeneration by chemokine and cytokine dysregulation (Li, Galey, Mattson, & Nath, 2005). Infected macrophages and microglia release proinflammatory chemokines and cytokines such as tumor necrosis factor alpha (TNFα), interleukin 1 beta (IL-1β), interleukin 6 (IL6), platelet activating factor (PAF), arachidonate, and nitric oxide (NO). These pro-inflammatory factors potentiate neuronal injury through N-methyl-D-aspartate receptor (NMDAR) excitotoxicity (Kaul & Lipton, 2004). TNFα and IL-1β release L-cysteine which enhances NMDAR activation by glutamate resulting in excessive Ca2+ influx (Sattler & Tymianski, 2001), free radical production and oxidative stress in neurons which can result in programmed cell death (Reynolds, Laurie, Mosley, & Gendelman, 2007). In a feedforward manner, excessive Ca2+ influx also induces the additional release of glutamate, subsequently overstimulating NMDARs on neighboring neurons (Erdmann, Whitney, & Zheng, 2006). HIV, Methamphetamine, and the Brain in the Era of Antiretroviral Treatment

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Overactivation of NMDAR is further potentiated by impaired glutamate reuptake by infected astrocytes due to arachidonate released from microglia (Brown, 2007; Genis, et al., 1992). Furthermore, NO has also been implicated in disrupting BBB permeability (de Vries, Kuiper, de Boer, Van Berkel, & Breimer, 1997), further increasing HIV and other pathogenic entry into the CNS. In a clinical study of 975 seropositive individuals at CDC stages A (medically asymptomatic), B (symptomatic), and C (AIDS defining symptoms) and 212 seronegative controls conducted by the HIV Neurobehavioral Research Center (HNRC) in San Diego, California, the number of individuals with HAND directly corresponded with the severity of symptoms (Grant, Sacktor, & McArthur, 2005). This direct correlation suggests that progression of HAND is more rapid in patients with advanced immunosuppresion. Not surprisingly, molecular studies correlated impaired cognitive function and severity of HAND with cerebralspinal fluid (CSF) viral load (von Giesen, Adams, Koller, & Arendt, 2005), increased number of activated microglia, elevated levels of excitotoxins, decreased synaptic density, and selective loss of calbindin-immunoreactive interneurons and pyramidal neurons (Everall, et al., 1999; Masliah, Ge, Achim, & Wiley, 1995; Masliah, et al., 1997).

Methamphetamine as a comorbidity factor for HIV neuropathogenesis Recent evidence has suggested that HAND and HIV neurotoxicity may be exacerbated by METH. METH users have significantly higher rates of cognitive impairment compared to all other groups (Rippeth, et al., 2004). In addition, imaging studies such as proton magnetic resonance spectroscopy has shown that N-acetylaspartate, a marker of neuronal integrity, is significantly diminished among seropositive METH users compared to all other groups including seropositive non-METH users (Chang, Ernst, Speck, & Grob, 2005). Furthermore, it was found that patients with HAND who use METH suffered a 57% loss of calbindin interneurons in the frontal cortex compared to a 36% loss in seropositive non-METH users (Chana, et al., 2006). Calbindin interneurons are inhibitory GABAergic neurons and reductions in their density have a


disinhibitory affect, exacerbating HIV-mediated excitotoxicity of their target pyramidal cells. Gene expression studies from autopsy brain tissue have shown that the interferon-stimulated neuroinflammatory genes STAT-1, IFP35, and ISG15 are further dysregulated by as much as five fold in seropositive METH users as compared to seropositive non-METH users (Everall, et al., 2005). Although not completely understood, it is postulated that ISG15 serves as a molecular marker for protein degradation by the unfolded protein response pathway (Ritchie, et al., 2002). In astroglial-neuronal co-cultures, METH increased ISG15 expression while decreasing the expression of the neuronal dendritic integrity marker microtubule associated protein-2 (Everall, et al., 2005). The growing body of evidence supporting the synergistic neurodegenerative effects of HIV and METH warrant special attention to the clinical presentation of HAND.

Clinical aspects of HIV infection HIV seropositive individuals can suffer an array of neuropsychiatric disorders (Gonzalez et al., 2004; Reger, Welsh, Razani, Martin, & Boone, 2002) with varying severity. A common neuropsychiatric manifestation is cognitive impairment, which most severely manifests as dementia. In the 1980s this dementia was termed AIDS dementia complex, then in 1991 was re-termed HIV associated dementia (AAN AIDS Task Force, 1991), but recently in 2007 a new definition of HIV neurocognitive impairment proposed the term HAND (Antinori, et al., 2007). Under the new criteria of HAND, three defining stages have recently been established to rate severity by comparing the cognitive domains of attention-information processing, language, abstraction-executive, complex perceptual motor skills, memory (including learning and recall), and simple motor skills of seropositive subjects to seronegative persons of similar age, education, and cultural background (Antinori, et al., 2007). The three stages of severity are: asymptomatic neurocognitive impairment (ANI) which documents acquired impairment in at least two cognitive abilities but without decrement to daily functioning; mild neurocognitive disorder (MND), previously referred to as minor cognitive-motor disorder (MCMD) (AAN AIDS Task Force, 1991), which is used when at least two cognitive impairments mildly affect daily functioning; and HIV-associated dementia HIV, Methamphetamine, and the Brain in the Era of Antiretroviral Treatment

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(HAD) which is indicated by cognitive impairment so severe that it markedly interferes with daily functioning. Interestingly, the severity of HAND can fluctuate with some affected individuals being observed to have an improvement in their cognitive function. Strict adherence to HAART has been shown to mitigate severity (Deutsch, et al., 2001). However, a longitudinal study of 120 seropositive individuals by the HNRC showed those who suffer from HAND have an increased risk of mortality after eight years even if the severity symptoms improved (Grant, et al., 2005). The pathology underlying this enhanced mortality is not clear but may indicate persistent inflammatory as well as dendritic and synaptic damage even when severity of symptoms improves.

Screening, diagnosis, and treatment Neurocognitive assessments should be derived both from selfreported patient history and neuropsychiatric examination. Questions about memory, attention, concentration, ability to learn, and work performance should be screened for possible changes. However, self-reporting is prone to subjectivity and some patients may lie, exaggerate, or underreport their circumstances. Therefore, objective neuropsychological testing should also be conducted as outlined by the revised HIV Dementia Rating Scale (Morgan, et al., 2007; Sacktor, et al., 2005). This scale employs appropriate norms and improves screening sensitivity from 17% to 71% compared to the Mini-Mental State Examination. After initial screening, a HAND diagnosis can be made by employing a comprehensive neuropsychological test battery. However, if access to a neuropsychologist is not available the diagnosis may be aided by utilising a brief neurocognitive battery that specifically probes the severity of impairment in key cognitive domains. Four suggested sensitive tests are: (1) The Grooved Pegboard Test which records the time required to place 25 small grooved pegs onto a metal board and monitors psychomotor speed and fine coordination; (2) The Trails Making Test part B which measures psychomotor speed, attention, and information processing by requiring subjects to connect a series of randomly arranged circles in a designated sequential order, based on alternating numbers and letters (i.e., 1 to A to 2 to B, etc.); (3) The WAIS-III Digit Symbol Test which examines psychomotor speed, 166 Physical and Mental Health Interface

concentration, and graphomotor abilities by requiring the respondent to match symbols to numbers as quickly as possible using a visual reference; and (4) A modified version of the Hopkins Verbal Learning Test which assesses language, attention, and the ability to learn and recall by asking subjects to memorise a list of 12 words and to recognise them when listed again after a 20 minute delay. Ideally, diagnostic testing should also include a blood panel, urinalysis, lumbar puncture, and MRI to rule out other causes such as systemic infections, drug complications, and hepatitis C. Once a diagnosis of HAND has been reached the mainstay of treatment should be focused on prescribing anti-retroviral drugs (ARV). There are two scenarios to consider: first, if the patient is ARV treatment-naïve, then there should be a discussion with the HIV physician regarding commencing treatment. Second, if the patient is already on ARVs then the discussion should be around the possibility of including drugs in the ARV regime that have been demonstrated to enter the CNS. The data in this regard has mainly focused on drugs levels in the CSF. Letendre et al. (2008) have published CNS Penetration Effectiveness (CPE) scores derived from molecular and pharmacological properties of various ARVs and showed that drugs with higher penetration ranks correlated with lower CSF viral loads. The concept of CPE scores is currently an evolving issue. Caution should be advised before starting patients with ANI or MND on CPE enhanced regimes since simpler regimes may enhance adherence and protect other organs, which are also vulnerable to HIV related damage. In considering quality of life, physicians should generally consider saving CPE options for later. Additionally, early administration may induce drug-resistant viral mutations and worsen prognosis (Smit, et al., 2004). To date, there is no established protocol for when to initiate ARVs for the specific treatment of HAND, nor are there any guidelines for which ARVs to use (Liner, Hall, & Robertson, 2008). In addition to HAART, there is a growing interest in developing brain directed adjunctive therapies including GSKβ inhibitors such as lithium. GSK3β is a constitutively active kinase that is multifunctional. In neurons it regulates the stability of the cytoskeleton and the formation of synapses while overactivity is associated with apoptosis. In a recent small open label clinical trial Letendre et al. (2006) observed improvement in the cognitive performance of HIV infected individuals with HAND who received HIV, Methamphetamine, and the Brain in the Era of Antiretroviral Treatment

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lithium for 12 weeks. Similarly, memantine, which protects against the effects of gp120, has been investigated (Lipton, 1992; Nath, et al., 2000; Schifitto, et al., 2007). Finally, other researchers are determining if the anti-inflammatory properties of minocycline can confer protection to the HIV infected brain (Follstaedt, Barber, & Zink, 2008; Jenwitheesuk & Samudrala, 2007). In conclusion this review has highlighted the fact that the brain is still vulnerable to damage even in the era of effective ARV and the ensuing cognitive impairment can be exacerbated by comorbid methamphetamine use. Clinicians need to be aware that such impairments can present in people living with HIV and be able to screen and diagnose accordingly so that appropriate treatment can be commenced. Finally, as this population is living longer it will be necessary to find brain directed adjunctive therapies to minimise the burden of HAND.

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Index

Index

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