Renée Baelde
5661145
Masterscriptie
Programmagroep Brein en Cognitie
Begeleiders
extern: Tanja Su
intern: Ben Schmand
E
XPLORING THE DIAGNOSTIC
VALUE OF SCREENING TESTS AND
DTI IN HIV PATIENTS WITH MILD
ABSTRACT
The purpose of present study was to gain more insight in different methods for detecting milder forms of HIV-associated neurocognitive disorders (HAND), which need to be quicker and more reliable tools, so they can help detect HAND. As part of the AgeIV cohort study, 18 participants, who were referred to the memory clinic by one or two screening tests, were subjected to an NPA and a DTI examination. After classification of the screening tests, diagnosis of HAND or non-HAND was made using NPA. Only 61% of the participants that the screening tests referred as having HAND, actually had HAND. Making screening tests only moderately effective for detecting HAND. Furtermore, white matter integrity in two tracts within the brain (a fronto-striatal tract and a striatal-motoric tract), was explored for a possible biomarker to detect early forms of HAND. Results show that patients with HAND have systematically lower white matter integrity than patients without HAND, but no predictive value was found. Future research should further investigate the found relation between HAND and white matter integrity.
TABLE OF CONTENTS
Abstract 2
Abbreviations 4
Introduction
Background on HIV and the AIDS-dementia complex 5
Combination Antiretroviral Therapy 5
HIV-Associated Neurocognitive Disorders 6
Problems in Diagnosing HAND 7
Neuropathology of HAND 9
DTI in HIV research 10
Present study 11 Methods Participants 12 Procedure 13 Screening Tests 14 Neuropsychological Measurements 15 Motor skills 15
Speed of information processing 16
Attention/working memory 16
Executive functioning 17
Memory 17
Language fluency 18
Neuropsychological Examination 18
DTI Data Acquisition 19
Image Processing 20 Statistical Analysis 21 Results 22 Participants 22 Screening Tests 23 Neuropsychological Examination 24
Diffusion Tensor Imaging 27
Explorative 29
Conclusion 30
Discussion 30
Screening Tests 30
Neuropsychological Examination 31
White Matter Indicators 32
Explorative 33 Limitations 34 Further Research 35 References 35 Appendices A NPA measurements 40 B interview 42
ABBREVIATIONS
ADC: AIDS-Dementia Complex AIDS: Acquired Immune Deficiency Syndrome
AMC: Academic Medical Centre in Amsterdam
ANI: Asymptomatic Neurocognitive Impairment
BBB: Blood-Brain Barrier
cART: combined AntiRetroviral Therapy CSF: CerebroSpinal Fluid
CNS: Central Nervous System DTI: Diffusion Tensor Imaging FA: Fractional Anisotropy
FSTC: Fronto-Striatal-Thalamo-Cortical FT: Finger Tapping task
FT animals: Fluency Test animals
FT occupations: Fluency Test occupations FT letter: Fluency Test letter
GP: Grooved Pegboard task HAD: HIV Associated Dementia
HAND: HIV Associated Neurocognitive Disorders
HDS: HIV Dementia Scale
HIV: Human Immunodeficiency Virus
MC: (pre-) Motor Cortex
MMSE: Mini-Mental-State-Examination MND: Mild Neurocognitive Disorder MRI: Magnetic Resonance Imaging NPA: Neuropsychological Assessment PASAT: Paced Auditory Serial Addition Test PFC: PreFrontal Cortex
RAVL: Rey’s Auditory Verbal Learning test Stroop CN: Stroop test, Colour-Naming Stroop CW: Stroop test, Colour-Word SVD: Small Vessel Disease
TMT A: Trail Making Test part A TMT B: Trail Making Test part B
WAIS-DS: Wechsler Adult Intelligence Scale Digit Symbol test
WAIS-LN: Wechsler Adult Intelligence Scale Letter-Number sequencing
WAIS-SS: Wechsler Adult Intelligence Scale Symbol Search test
WCST cat: Wisconsin Card Sorting Task measurement categories
WCST errors: Wisconsin Card Sorting Task measurement errors
WCST pers: Wisconsin Card Sorting Task measurement perseverations
Exploring the diagnostic value of screening tests and DTI in HIV patients with mild
forms of HAND
Background on HIV and AIDS-Dementia Complex
The Human Immunodeficiency Virus (HIV) is truly a global epidemic, affecting roughly 33 million people all over the world. (WHO, UNAIDS & UNICEF 2010). The HIV-1 virus causes AIDS. Shortly after infection, HIV-1 enters the central nervous system (CNS) in mononuclear cells (Davis et al., 1992), destructing CD4 T-cells and causing decline of the functional immune system. This progressive disorder of the immune system is called AIDS, which eventually leads to death through an increased risk of opportunistic infection (Orenstein, Fox, & Wahl, 1997).
Several years after the start of the HIV epidemic, it became clear that more than 50% of all HIV-1-infected patients developed some form of neurological disorder (Ances & Ellis, 2007), eventually leading to AIDS-Dementia Complex (ADC) during the more advanced stage of the disease. ADC is characterized by changes in behaviour and severe progressive decline in cognition and motor functioning (Navia, Jordan & Price, 1986). Typically, cognitive impairment manifests itself in some of the following symptoms: mental slowing, attention, memory and executive functioning deficits. Motor symptoms predominantly consist of slowness and loss of balance. Symptomatic behaviour is characterized by apathy, social withdrawal, and mood disturbances (Antinori et al., 2007).
Combination Antiretroviral Therapy
Presently no effective vaccine is developed, although a variety of drugs have been introduced, each acting on different stages of the infection cycle. Combined antiretroviral therapy (cART), combines different drugs into regimens that attack viral replication at multiple targets in the viral cycle (Koczor & Lewis, 2010). Since the introduction of cART, morbidity and mortality rates among HIV-patients have been substantially lower and the
incidence of ADC decreased remarkably (Cysique & Brew, 2009). Today, accounts of ADC in clinical practice are generally limited to patients who are either treatment naïve, who have never received their present cART treatment before, who are failing therapy due to viral drug resistance, or who have problems with medication adherence (Robertson, Liner, & Heaton, 2009). However, the prevalence of milder neurocognitive impairment remains high (15-50%) (Cysique & Brew, 2009; Valcour, Sithinamsuwan, Letendre, & Ances, 2011). Milder
neurocognitive impairment is even prevalent in patients with well-controlled infection using cART (Simioni et al., 2010). Mild impairment in memory, slowness, difficulty in
concentration, planning, and multitasking (Schouten et al., 2011) is generally reported in these patients.
HIV-Associated Neurocognitive Disorders
In the light of these developments, the terminology of the HIV-associated cognitive diagnoses has been revised and updated to classify a broadening clinical spectrum of neurocognitive impairment, including the milder abnormalities (Antinori et al., 2007; American Academy of Neurology, 1996). This classification system, HIV-Associated Neurocognitive Disorders (HAND) and the criteria of Antinori et al. (2007) are now commonly used for research and epidemiological purposes. HAND terminology was operationalised by the American Academy of Neurology in 1996, which created three subcategories (Table 1), based on results of an elaborate neuropsychological assessment (NPA). HIV-Associated Dementia (HAD) is the most severe form of injury and is comparable to ADC, mild Neurocognitive Disorder (MND) represents a milder form of impairment, although it still impacts the activities of daily living. Asymptomatic Neurocognitive Impairment (ANI) is the mildest form which is based on the observation that some individuals have demonstrable, usually mild, cognitive impairment, without any apparent abnormality in everyday functioning (Antinori et al., 2007). This last subcategory is the most notable
addition, because its impairment is so mild, criteria lie below normal criteria for clinically impaired cognitive abilities (2 SD below mean).
Since the severe forms of HAND have become less common, this classification system has been geared towards mild impairment (Robertson et al., 2009). These milder forms of HAND are still of substantial concern as they may contribute to a decreased quality of life, diminished work capacity, and poor medication adherence, thereby potentially jeopardizing the long-term sustained suppression and control of infection (Woods, Moore, Weber, & Grant, 2009) .Therefore, the milder HAND syndromes may be a precursor to HAD (Cysique & Brew, 2009) and should be the focus of current research.
Table 1
Terminology of HAND
Asymptomatic Neurocognitive Impairment (ANI)
Impairment in cognitive functioning,
involving at least two cognitive domains, of which performance is at least 1 standard deviation below the mean. The cognitive impairment does not interfere with everyday functioning.
Mild Neurocognitive Disorder (MND) Impairment in cognitive functioning,
involving at least two cognitive domains, of which performance is at least 1 standard deviation below the mean. The cognitive impairment produces at least mild interference in daily functioning. HIV-Associated Dementia (HAD) Impairment in cognitive functioning,
involving at least two cognitive domains, of which performance is at least 2 standard deviation below the mean. The cognitive impairment produces marked interference with day-to-day functioning.
Problems diagnosing HAND
With HAND classification gearing towards mild impairment, it might be questioned whether this classification is too mild. MND and ANI are both defined by performance at
1SD below mean on normative scores in at least two out of five cognitive domains (ANI is even defined without notable impairment in everyday living). Using present criteria 16%-21% of the population is classified as abnormal. When two tests per domain are required, this percentage is 8%-13% (Gisslén, Price, & Nilsson, 2011). Furthermore, considering HAND has a widespread profile of cognitive disorders, comorbidities within roughly the same neuropsychological profile can occur. Hypertension is suggested to be associated with HAND (Valcour et al., 2011) and might amplify the effects of neurocognitive impairment in people with HIV (Ramos-Estebanez et al., 2011) by causing small vessel disease (SVD). SVD is a type of vascular cognitive impairment which manifests itself through white matter hypertensities and lacunar infarcts inducing cognitive impairment (Selnes & Vinters, 2006). This is frequently the cause of impairment in gait, the domains of information processing speed and executive functioning. This neuropsychological profile could easily be mistaken for ANI.
Criteria of mild cognitive impairment (MCI), which is common in elderly participants, might be mistaken for ANI. MCI is a development of cognitive impairments beyond what is expected, based on the age and education of the individual, where the impairments are not significant enough to interfere with daily activities (Albert et al., 2011). Diagnostic criteria entails impairment in one or more cognitive domains, most frequently seen is impairment in episodic memory (the ability to learn and retain new information).
Another difficulty when diagnosing HAND is related to age. Ageing is associated with an increased risk of cognitive impairment, probably due to one of the above inflictions. Yet, higher HIV-1 viral loads are seen in older HIV patients using effective cART regimens (Goodkin et al., 2004), meaning that HIV might become active when people get older, subsequently resulting in more HIV associated cognitive impairment. It is unknown what causes the association with age and higher viral loads. It might be the result of a long-term
process that has been going on for years or there could be an acute unknown increase in viral load in the CNS (Schouten et al., 2011).
So, the criteria of the milder forms of HAND may cause problems. Also the diagnosis tool for HAND, NPA, is expensive, time consuming, exhaustive for patients and it is sensitive to errors (false positives), for it cannot distinguish between HAND and, for instance, comorbidities with roughly the same cognitive manifestations or patients who malinger or do not understand the tasks. A few of these limitations can be remedied by rapid screening tools, developed to detect the presence of HAND. The HIV Dementia Scale (HDS) is currently the most commonly used HAND screening tool in clinical practice (Morgan et al., 2008). Still, it is suggested that the HDS is only able to detect severe forms of neurocognitive impairment, which results in high rates of false negatives when testing for ANI (Carey et al., 2004; Smith, van Gorp, Ryan, Ferrando, & Rabkin, 2003). In conclusion, more reliable detection of HAND at an early stage is necessary. Therefore, more information is needed to differentiate HIV patients in an early stage of HAND and those who are without cognitive impairment. This information might lead to discovering measurable indicators, biomarkers, that will help detect milder forms of HAND.
Neuropathology of HAND
Previous research aimed at finding indicators of HAND did not succeed in revealing the exact mechanism underlying HAND. Post-mortem studies of HAND show a loss of neurons in the brain is found post mortem in patients with HAND. This is likely to be caused by viral and inflammatory protein production, or indirectly by an elevated production of neurotoxic molecules. This is congruent with some suggestions about the mechanism underlying HAND. It is known that HIV enters the CNS using a “Trojan horse” mechanism; infected macrophage-monocyte cells help the virus cross the Blood-Brain Barrier (BBB) (Ances & Ellis, 2007). However, entry to the CNS is (to some extent) restricted for antiretroviral drugs by the BBB and the blood-cerebrospinal fluid barrier (Edén et al., 2010),
resulting in ongoing viral replication within this compartment. This unparalleled course between systematic and CNS-infection in HIV-patients is called ‘viral escape’ (Garvey, Everitt, Winston, Mackie, & Benzie, 2009) and has been held responsible for HIV associated cognitive impairment.
In addition to ‘viral escape’, and the inability of some cART to pass the BBB and to suppress viral replication in the CNS (Cysique & Brew, 2009), indirect neuronal intoxication may contribute to the cognitive impairment in patients with HIV. Some cART regimens are thought to cause production of neurotoxic molecules (Koczor & Lewis, 2010), which affect the CNS in a way that results in neuronal damage and subsequent cognitive deficits. Additionally, cART consists of a cocktail of drugs, which can cause CNS toxicity due to complex drug interactions (Nachega, Mugavero, Zeier, Vitória, & Gallant, 2011). This is especially the case with Efavirenz, a type of cART drug suggested to be related to neurotoxicity (Ciccarelli et al., 2011). Besides examining the relation between HAND and viral escape and neurotoxicity, present study also examines white matter integrity as HIV patients typically show widespread neuronal loss, white matter abnormalities (Masliah et al., 1997) and thinning of the prefrontal cortex (PFC) (Thompson et al., 2005), which is associated with the cognitive impairment seen in patients with HAND.
DTI Findings
Recent Diffusion Tensor Imaging (DTI) studies have proven helpful in gaining more insight into the mechanism underlying HAND and detecting neurological biomarkers. DTI is able to reveal abnormalities in white matter fibre structures, which provides insight in brain connectivity. DTI studies measuring whole brain white matter integrity have demonstrated widespread white matter abnormalities in multiple white matter regions (Tucker et al., 2004). These abnormalities occur in both patients with HAD and a HIV patients without HAD, but more severe abnormalities were found in patients with HAD. Present study will try to find abnormalities in patients with less severe forms of HAND. The focus will lie on the
fronto-striatal-thalamo-cortical circuit (FSTC) and a motor tract. The FSTC consists of reciprocal tracts that link the prefrontal cortex (PFC) subsequently to the striatum, basal ganglia structures (e.g. caudate nucleus, putamen & globus pallidus), thalamus and back to the cortex (Draganski et al., 2008). Although neuropathology of HAND is evident in a wide array of brain regions, the FSTC is examined, as the highest HIV-1 viral loads are found in some of these structures (Kumar, Borodowsky, Fernandez, Gonzalez, & Kumar, 2007). Furthermore, white matter integrity between the structures in the FSTC circuit is also affected (Melrose, Tinaz, Castelo, Courtney, & Stern, 2008) It seems likely that the FSTC circuit mediates HIV-associated cognitive decline, as this circuit regulates executive functioning, which is one of the main domains in which patients with HAND may be impaired. Furthermore, changes in PFC regions correlate with failure on memory and attention tasks, which are often affected in patients with HAND (Melrose et al., 2008; Thompson et al., 2005). However, deficits in the FSTC cannot explain all HAND symptoms or all neurological findings. Present study therefore examines another region, the motoric tract (MC), which initiates in the capsula interna and extends into the motor cortex. Decline in motor functioning is another main symptom of HAND, notably in HAD (Dawes et al., 2008). Previous research has not examined the white matter integrity of this specific tract.
Present Study
Currently, frequently seen forms of HAND in clinical practice are the milder forms, ANI and MND. Commonly, these patients are treated with effective cART. Still, little research examines the detection of these milder forms, or their relation to neuropathology. Diagnostic tools used for HAND have shown marked limitations. Therefore this study
examines the currently used tools, but also tries to find new possibilities for detecting HAND. The aim of this study is to acquire more insight in detecting HAND. First, present study examines the known diagnostic tools for detecting HAND. Expected is that the HDS and MMSE can effectively identify most patients with HAND. Furthermore, we hypothesize
that patients without HAND show better performance on all neuropsychological domains than patients with a HAND diagnosis. Furthermore, white matter integrity in both groups is
examined, and we expect to find marked differences, where patients without HAND show higher white matter integrity than patients diagnosed with HAND. Also, present study aims to relate functional and structural impairment and explores a possible biomarker. Expected is that the FSTC will account for differences in executive functioning and the MC tract will account for differences in motor ability. Lastly, we will explore the role of MCI and SVD, two previously not excludable comorbidities, the role of age and of medication that is suggested to be related to toxicity.
Methods Participants
Participants were recruited at the HIV outpatient clinic of the Academic Medical Centre of Amsterdam (AMC), as part of the AgeIV Cohort Study. This is a multidisciplinary prospective study on comorbidity and aging in HIV, which assesses the incidence and prevalence of a broad range of (age-related) co-morbidities and risk factors among HIV-infected patients. Some data of this cohort study, were available for present explorative study. At the start of to the cohort study, participants were screened for HAND with the HDS and MMSE, a off score of respectively 10 and 24 was applied. All who performed below cut-off were referred to the AMC memory clinic, for the screening tests suggest that these patients could have HAND.
Present study uses a subgroup of the patients who were referred to the memory clinic, this sample was comprised of 33 HIV-positive participants. Participants of the AgeIV Cohort Study with an HDS or MMSE score below cut off, were assessed for inclusion in the analysis of present study. Exclusion criteria were current or past opportunistic infections or tumours of the CNS, non-HIV-related major neurological or psychiatric disorders, current use of illicit drugs or sedative-hypnotics, because these can interfere with DTI images and performance on
the NPA. Leaving 29 participants eligible. However after acquisition, five more participants were excluded for not having received a DTI-scan and six were excluded for their NPA results were evaluated as unreliable, on account of an insufficient knowledge of the English or Dutch language, not enough motivation or too little education. After inclusion 18 participants were eligible. Figure 1. shows the flowchart of participants in present study. All included participants were older than 45 years and the majority was male. Three participants were not undergoing anti-retroviral treatment at the time of the study. These participants were after examination referred to a specialist to prescribe such treatment.
Procedure
For the cohort study participants underwent a personal interview, 100 min of eye examinations, 60 min MRI-examinations (plus preparations), Lumbar puncture and blood examination, 120 min of NPA. detailed blood-, CSF-, MRI- and neuropsychological examination as part of their clinical management. For the cohort study this procedure was expanded with a personal interview, 100 min of eye examinations, lumbar puncture and blood examination. All participants were informed of the AgeIV Cohort Study protocol and prior to enrolment, had given written informed consent. Present study uses a subgroup of the participants who were referred to the memory clinic, who are thus possibly eligible for HAND. An exhaustive NPA is decisive on whether a participants has HAND and which class. Present study examines only the data of the NPA, DTI components of the MRI examination and components of the personal interview (approved by the Medical Ethics Committee). All the components used in present study were conducted on the same day, by a trained neuropsychologist (or psychologist in training). The interview took place in the AMC, participants were asked questions about their socio-demografical characteristics, medication and habits, activities and daily living. Next, they underwent an NPA (specified below) and after an MRI examination. Before MRI examinations participants were not allowed to consume any caffeine, alcohol or drugs, for it could influence MRI images. Usually the
participants first completed the NPA and then the MRI examination, yet due to planning issues some participants finished MRI examination first or after only one hour of NPA examination.
Figure 1. Flow chart of participants.
Screening Tests
In present study, participants were tested using three different screening tools: the HIV dementia scale (HDS), Montreal cognitive assessment (MoCA), and the mini-mental state examination (MMSE). These tools can rapidly screen participants for cognitive impairment.
Participants were referred to the AMC memory clinic when they scored below cut-off score on either the HDS or MMSE. The HDS, is currently most used for detecting HAND. In four short items it screens for deficits in attention, memory, motor abilities, and information processing speed. Maximum score is 16. HDS has its limitations in detecting milder forms of HAND, present study also utilizes the MMSE (Folstein, Folstein, & McHugh, 1975), which is the most commonly used standardized screening tool for detecting dementia. This test consists of 11 questions that are associated with a wide array of cognitive abilities as orientation, registration, estimation, attention, memory and language. After inclusion, a third screening test was added to the NPA. The MoCA is deemed to measure the existence of both cortical and subcortical functions. This test consists of 13 items, that screen for memory, visuospatial abilities, attention, executive functioning, language and orientation. The maximum score of MMSE and MoCA is 30. Present study will try to examine if MoCA is useful as screening test for HAND. Due to lack of time, not all participants executed all the screening tests, all did complete the HDS, but only 12 performed the MMSE and 10 the MoCA.
Neuropsychological Measures
To classify HAND in ANI, MND, or HAD results of an exhaustive NPA are utilized, which should ideally include six domains of cognitive abilities, each domain measured by at least two tests. This study assessed a battery of 16 standardized tests, administered by a trained neuropsychologist. The tests were selected on previous research supporting their sensitivity to early HIV-related neurocognitive changes. They are needed to form six different cognitive domains, containing at least two tests per domain. The domains examined are language, executive functioning, speed of information processing, attention/working memory, visual and verbal memory, and motor skills. (Antinori et al., 2007; Woods et al., 2004). The domains were considered impaired when test scores of at least two different tests within a domain were below 1 SD of the normative mean. The whole test battery is shown in Appendix A.
Motor skills. The Finger Tapping Test (Halstead, 1947) and the Grooved Pegboard Test
(Kløve, 1963) were selected as a measure of motor functioning with relatively minimal loading on components of complex cognitive processing. The Finger Tapper is an instrument which requires participants to tap as fast as possible on a tapping device and measures the number of taps made within a limited time. Both hands were measured (FT dominant and FT non-dominant). The Grooved Pegboard requires participants to place small metal key-shaped pegs into a metal board with key-shaped slots. Measured is the time acquired to put all pegs in their slots, also both hands are measured separately (GP dominant and GP non-dominant).
Speed of information processing. Speed of information processing is assessed through the
use of relatively simple timed motor tasks, which solely require basic cognitive processing. The Trail Making Test (Part A; Reitan, 1958) is a timed paper and pencil procedure, upon which participants need to connect numbers in ascending order. Scored is the time participants needed to complete the test (TMT A). The Digit Symbol Test (WAIS-III; Smith, 1982) requires participants to draw corresponding symbols below random ordered digits as fast as possible. The number of correct symbols within the allowed time is measured (WAIS-DS). Another WAIS-III test, the Symbol Search Test (Schmidt, 1996), requires quick visual scanning. Participants have to match symbols appearing in different groups. The number of correct responses within the allowed time is measured (WAIS-SS). Also the Stroop Colour-Naming (Card II; Stroop, 1935) test is used to assess this domain. A timed task demanding no motor skills. The test consists of rectangular colour patches in yellow, red, blue and green printed in random order. The time it takes to name these colour patches as quickly as possible is measured (Stroop CN).
Attention/working memory. The attention domain comprises more complex cognitive
processing, which is operationalized using several simple cognitive tasks which must be performed simultaneously. The Letter-Number Sequencing Subtest of the WAIS III (Schmidt, 1996) involves ordering numbers and letters which are verbally presented in an unordered
sequence. The number of correct responses is measured (WAIS-LN). The Paced Auditory Serial Addition Test (Gronwall, 1977) generates one number every 3.2 seconds (or every 2.8 seconds on trial 2). Participants must add each new digit to the one immediately prior to it, and answer the calculations out loud. Measured are all the correct responses in one trial (these scores are respectively referred to as PASAT 3.2 and PASAT 2.8).
Executive functioning. ‘Executive functions’ is an umbrella term for cognitive processes that
regulate, control, and manage other cognitive processes. Examples of executive functions are planning, working memory, problem solving, verbal reasoning, inhibition, mental flexibility, task switching, initiation and monitoring of actions. This was measured using the suppression of an overlearned simple tendency over the performance of a task of greater difficulty (e.g. Stroop Colour and Word Test), and task switching (e.g. Trailmaking Part B) or problem solving (e.g Wisconsin Card Sorting Test).
The Stroop Colour and Word Test (Stroop, 1935) is a timed task in which participants need to name the colour of the ink of the words (yellow, blue, red, green) as quickly as possible. However, the words are printed in an incongruous colour ink. Recorded variable were the interference score, which is the time spend on the Colour-Word task given the time spend on the Stroop CN task (Stroop CW). The Trailmaking Test (Part B; Reitan, 1958) is a paper and pencil procedure which requires participants to connect alternating letters and numbers in an ascending and alphabetical order. For examining executive functioning, the interference score was used: time spend on Part B given the time spend on Part A (TMT BA). The Wisconsin Card Sorting Test (WCST; Berg, 2010) is a computerized task, that is used to assess problem solving. It presents a number of stimulus cards to the participant, who is told to match the cards to four possible open cards, without knowing on what principle they should match (colour, number, shape). However, participants are told whether a particular match is right or wrong. Recorded variables are the number of categories completed (WCST cat),
number of perseverative responses (WCST pers) and number of perseverative errors (WCST errors).
Memory. Visual memory impairment was measured by the Wechsler Memory Scale
(WMS-IV; Wechsler, 1987). This test was conducted on a computer, it consists of five figures presented in ascending difficulty. The participants need to copy the figures from memory twice, once immediately after presentation (WMS-learn), once after a delay (WMS-recall). Verbal memory is assessed through Rey’s Auditory Verbal Learning Test (Schmidt, 1996), in which participants have to learn a list of 15 unrelated words repeated over five different trials and are asked to repeat the learned words after each trial (these five trails added together make the score referred to as RAVL-learn) and after a 30 min. delay (RAVL-recall).
Language fluency. The fluency of speech is assessed through Letter Fluency and Category
Fluency (GIT; Luteijn & van der Ploeg, 1983). Letter Fluency requires spontaneous production of words beginning with a given letter within a limited amount of time. Measured were the produced words in three trails with a different starting letter (FT Letter). Category Fluency requires spontaneous production of words belonging to a given category within a limited amount of time. This test consist of two trails where participants have to produce animals or occupations. Measured are the number correct words produced in the trails (respectively FT animals and FT occupations).
Neuropsychological Examination
For data analysis, raw test scores were used to compare changes from individual participants’ performances, to see also slight variations. These scores were controlled for demographical features to minimize the influence of age, education, sex, and ethnicity whenever possible and appropriate. Validated normative t-scores were applied for within-group analysis’ and for classifying participants as neurocognitive impaired (ANI, MND, or HAD) or unimpaired.
Besides NPA results, measurements of functional decline, assessed by self-report questionnaires are needed to diagnose HAND. The (IADL) and the interview are used in present study for as a self-report questionnaire. The interview conducted is shown in Appendix B. Mild interference in daily functioning requires at least two of the followings: participants needing assistance with two or more IADL’s, less efficiency/productivity during day-to-day tasks and unable to perform some aspects of previous job. Major functional decline requires at least two of the following: participants needing substantially greater assistance with two or more IADL’s, unable to maintain former employment and self-reports of great difficulty in four of six cognitive domains (Antinori et al., 2007). Using these criteria, the participants were divided into either the group with HAND or in the group without HAND.
The expression of related comorbidities like SVD or MCI can be similar to ANI. Diagnostic criteria of Amnestic MCI entail lower performance (1-1,5 SD below mean) in one or more cognitive domains, most frequently seen is impairment in episodic memory (the ability to learn and retain new information) (Albert et al., 2011). In present research lower performance at least 1 SD below the mean on the suggested domains is examined. Diagnostic neuropsychological criteria of SVD are not fully clear yet. For it is usually diagnosed by the Fazekas scale (Gouw, 2010). Previous research suggest SVD is related to lower performance on EF and motor domains (Prins et al., 2005; Selnes & Vinters, 2006). In present research lower performance will be quantified as at least 1 SD below the mean on suggested domains. The incidence of these comorbidities are examined.
DTI Data Acquisition
All neuroimaging scans were performed on an Intera 3 Tesla imager at the AMC in Amsterdam, with a phased array SENSE 8-channel receiver head coil. DTI data for all included participants were acquired using multi-slice spin echo single-shot echo-planar imaging using the following parameters: TE/TR = 92/7725 ms; flip angle 90˚; diffusion
sensitivities of b=0 and b=1000 s/mm2; field of view = 224x224x120 mm2, 55-60 continuous (no inter-slice gap) slices in saggital direction, slice thickness 2 mm, field of view 224x120x224 mm2; acquisition matrix 112×112 mm; voxel size 2×2×2 mm2. Diffusion-weighted images were acquired in 64 diffusion directions and DTI scan time for a complete brain was approximately 8-9 minutes, depending on the number of slices used. The current study is part of a larger study, therefore subjects underwent the DTI scan additional to other MRI scans. Total scan duration was approximately 60 minutes.
Image Processing
All data was anonymised prior to analysis, and assessed qualitatively to check for radiological abnormalities outside of the normal range. Participants with such abnormalities were excluded from the study, as described above. Data pre-processing was performed using software developed in-house, written in Matlab (The MathWorks, Natick, MA, USA), and conducted on the Dutch Lifescience Grid to transform data to DTI and co-registered T1 scans on which probabilistic tractography could be performed, using the fMRIB software library (http://www.fmrib.ox.ac.uk/fsl/index.html) (Giesbertz, 2012)
After consulting an experienced neurosurgeon, Pepijn van der Munkhof, two tracts were distilled for examination. These tracts were chosen for respectively their association with executive functioning (Tate et al., 2010) and motor ability (Tate et al., 2010; Werring et al., 1998), as well as their association with HIV-1 (Pomara, Crandall, Choi, Johnson, & Lim, 2001). The tract deemed to be associated with executive functioning is part of the FSTC. The PFC-tract that present study researches begins in the caudate nucleus and extends to the PFC. The motor tract, beginning in the posterior part of the capsula interna and extends into the motor cortex (MC).Using Matlab, the mean fractional anisotropy (FA) -values per patient were calculated over each tract and hemisphere, resulting in the tracts shown in figure 2. The FA-value is a measurement of diffusion in fibers. Using a DTI we can measure in which direction diffusion occurs and the degree of diffusion. The FA-values lie between 0 and 1.
Where 0 corresponds to unrestricted diffusion in all directions and 1 corresponds to restricted diffusion in one direction due to barriers (as is expected in white matter fibres). Roughly said, low FA-values correspond with low connectivity between areas, whereas high FA-values leads to good connectivity between areas.
Figure 2. Probabilistic fibretracking. Mean FA of all participants in the selected motor tracts (red-yellow) and the PFC-tracts (blue-purple).
Statistical Analysis
The data were analysed using SPSS 20.0 for Windows. First, current data-set was tested for normality with the Shapiro-Wilk test, for the current data-set is small (n = 18). The data were not normally distributed and therefore non-parametric tests were used for analysis. The data-set was split into two groups, participants diagnosed with neurocognitive impairment (HAND group) and participants without neurocognitive impairment (non-HAND). The Mann-Whitney test was applied to test for significant difference between the two groups. Significance was accepted at the level of p < 0.05. A dummy-coded summary-score for each domain was obtained. Impaired domains were assessed per participant, when they performed at least 1 SD below mean on at least two different test within that domain, it was given a 1, unimpaired domains were given a 0. This was used to reflect the amount of impairment on each NP domain. The chi squared test was applied to examine which domains
were more impaired. Furthermore, a comparison was made between ANI and the percentage of which can also be accounted for by comorbidities.
To see if FA-values can predict the outcome of NPA-results a linear regression was applied. The motor tests (FT and GP) were per hand correlated with the corresponding, lateral motor-tract and the selected cognitive tests (interference score TMT part B, interference score Stroop CW, and WCST categories scores were used) were related to the mean PFC-track.
Results
Participants
Participants were divided into two groups: HAND and non-HAND. The non-HAND group consisted of 9 participants, and the HAND group consisted of 11 participants, of which 8 (72.7%) were diagnosed with ANI and 3 (27.3%) with MND. Demographic characteristics of the HAND and non-HAND group are given in Table 2; there are no significant differences on demographic characteristics between the two groups, so consequently, the raw scores of the neuropsychological tests could be used for between-group analysis.
Table 2
Demographic characteristics of the group diagnosed with HAND and without HAND
HAND Non-HAND t p N (%) Age [M, SD] Gender, men (%) Education, years [M, SD] Dutch language (%) Handedness, right (%) HIV Medication (%) 11 (61) 51.6, 2.9 9 (82) 12.5, 2.9 6 (55) 9 (82) 3 (27) 7 (39) 57.9, 11,1 7 (100) 13.3, 4.7 5 (71) 6 (86) 0 (0) 1.47 -1.49 0.47 -0.69 -0.20 -1.94 .19 .17 .65 .50 .84 .08
HAND Non-HAND t p Efavirenz (%) Cognitive complaints (%) Psychomedication (%) MMSE [M, SD] HDS [M, SD] MoCa [M, SD] 1 (9) 3 (27) 1 (9) 26.9, 3.0 8.9, 0.8 25.2, 1.8 3 (43) 2 (29) 0 (0) 26.8, 2.8 9.2, 2.1 23.3, 3.8 -1.52 0.06 0.79 -0.03 0.43 -1.09 .16 .96 .44 .97 .67 .31 Screening Tests
The HAND group does not differ from the non-HAND group on MMSE, MoCA or HDS-scores (Table 2). All participants scored below cut-off point of a screening test. Yet, only 11 (61.1%) of these participants were actually diagnosed with HAND. Thus, 39% of participants screened by HDS and MMSE were incorrectly identified as being cognitively impaired.
Table 3 shows the success rate of screening tests when identifying HAND and non-HAND. It shows, both for the HAND and for the non-HAND group, what percentage of the group was previously correctly or incorrectly classified by the screening tests as HAND or as non-HAND. The HDS seemed most accurate at correctly classifying participants in the HAND group, although it also had a high rate of falsely classified participants as having HAND (while they belonged in the non-HAND group). The HDS placed 86 percent of the non-HAND group in the HAND group. The MMSE and the MoCA both seemed inaccurate in correctly classifying HAND, and had an unacceptably high rate of incorrectly diagnosing HAND and incorrectly diagnosing non-HAND (Table 3).
Table 3
Precision of the various screening tests in this sample N (%).
Note: not all participants executed all screening tests. All did complete the HDS, but only 12 performed the MMSE and 10 the MoCA.
Neuropsychological Examination
Raw scores obtained on each task were compared between the HAND and non-HAND group. Table 4 shows a summary of this comparison. As expected, the non-HAND group subsequently better than the HAND-group on 8 out of 23 NPA measurements. Three domains, Language Fluency, Information Processing and Executive Functioning, contain NPA measurements where the non-HAND group performed better than the HAND group, with medium effect sizes between .45 and .69. However, on one measurement, the WCST cat, the HAND group (M = 4.4) performed unexpectedly better than the non-HAND group (M = 2.4), U = 12.50, p < .05, r = -.48.
MoCA MMSE HDS
HAND correctly identified HAND incorrectly identified HAND total 3 (50) 3 (50) 6 (100) 2 (29) 5 (71) 7 (100) 11 (100) 0 (0) 11 (100) Non-HAND incorrectly identified
Non-HAND correctly identified Non-HAND total 3 (75) 1 (25) 4 (100) 2 (40) 3 (60) 5 (100) 6 (86) 1 (14) 7 (100)
Table 4
Mean, SD scores and effect sizes obtained from the HAND and non-HAND group on each neuropsychological test.
Domain Test HAND Non-HAND pa d
Memory Information Processing Attention Language Fluency Executive Functioning Motoric Functioning RAVL-learn RAVL-recall WMS-learn WMS-recall Stroop CN TMT A WAIS-DS WAIS-SS WAIS-LN PASAT 3.2 PASAT 2.8 FT animals FT occupations FT letter Stroop CW TMT BA WCST cat WCST errors WCST pers GP dominant GP non-dominant FT dominant 40.3, 9.6 8.7, 2.9 37.4, 16.2 25.2, 14.2 81.6, 12.2 45.6, 8.7 40.4, 7.4 24.1, 2.9 8.0, 1.9 38.7, 9.4 36.3, 3.6 17.1, 2.4 12.1, 3.3 26.0, 8.9 143.4, 31.6 132.8, 32.5 4.4, 1.4 41.4, 19.3 28.4, 207 90.6, 15.1 96.9, 19.8 37.0, 9.4 39.0, 4.5 7.4, 2.3 30.3, 5.5 20.0, 11.9 58.0, 9.5 37.0, 9.8 58.4, 20.2 29.7, 5.1 9.1, 1.3 40.6, 9.9 39.8, 3.8 19.3, 4.9 16.9, 4.5 35.0, 10.4 105.0, 26.4 96.0, 14.8 2.4, 1.9 50.0, 20.7 25.9, 11.6 77.1, 18.8 85.0, 25.7 43.9, 7.8 .298 .123 .097 .235 .001a .076 .018a .009a .123 .269 .176 .164 .004a .029a .013a .006a .023a .204 .419 .075 .106 .076 .77 1.07 .94 1.13 .57 .55 .52 -1.06
Domain Test HAND Non-HAND pa d
FT non-dominant 35.2, 7.3 41.5, 10.7 .076
ap < .05 (1-tailed). Note: Effect sizes are only given at significant group differences. Cohen’s
d is composed using t-scores. Test names and measurements can be found at methods section: Neuropsychological Measures.
A dummy-coded summary score was used to reflect cognitive impairment on each domain. For each domain, participants obtained a score: 0 for unimpaired, 1 for impaired. Figure 3 shows each cognitive domain and which percentage of participants scored a deviant summary score on this domain. The HAND group shows impairment on all domains except memory. In the non-HAND group, impaired domains also exist, but on a much lower scale. Three participants (42,9%) in the non-HAND group have one impaired domain, being either Information Processing Speed, Executive Functioning and Motor skills. An analysis of the results of the summary scores with a Chi squared test, showed that the HAND group had higher impairment on the domain Fluency χ2(1) = 5.73, p < .05 on the Information Processing Speed domain χ2(1) = 7.90, p < .05 than the non-HAND group.
Figure 3. Percentages of deviant domain summary scores of the HAND and non-HAND group.
Diffusion Tensor Imaging
Most FA-values were not normally distributed. Therefore, non-parametric tests were used. The right and left hemispherical tracts had the same FA-values for each cluster. Figure 4 shows that overall, the FA-values of each cluster of the MC- and PFC-tract are higher for the non-HAND group than the values for the HAND group. In Table 5, the mean FA-values of each tract are depicted and compared between groups. When taking together the mean FA-values of both hemispheres, the FA-values of the PFC-tract and the MC-tract are higher in the non-HAND group than in the HAND group.
Table 5
The mean FA-values, mean (SD) and effect sizes of the MC and PFC tract of the non-HAND and the HAND group.
Mean FA-value HAND non-HAND p d
PFC right hemisphere PFC left hemisphere MC right hemisphere MC left hemisphere PFC both hemispheres MC both hemispheres .271 (.013) .273 (.015) .395 (.023) .411 (.025) .272 (.014) .403 (.025) .292 (.014) .284 (.029) .423 (.033) .440 (.033) .289 (.029) .435 (.034) 0.014a 0.184 0.072 0.027a 0.035a 0.021a 1.50 0.37 0.85 0.88 0.59 0.94 ap < .05 (1-tailed)
Present study produced a linear regression to find out if there is a direct relation between lower FA-values and poor results on neuropsychological tests. As this is a within-group analysis, T-scores were used instead of raw data. When investigating the relation between the MC tracts and the motor tests no significant regression was found, not even when using the FA-values of both hemispheres together, or when examining the separate hemispheres with corresponding motor tests ( the motor tests performed with the right hand is associated with the lateral MC tract of left hemisphere and vice versa), no significant
regression was found. When examining the relation between the PFC tract and
neuropsychological tests, both PFC tracts (together and separately) were used as independent variables in the regression. The neuropsychological measurements Stroop CW, TMT BA, WCST cat, WCST errors, and WCST pers were utilized as dependent variables.
A direct relation was found in the HAND group between the mean FA-values of the PFC-tract and the results of an EF test (WCST cat). Within the HAND-group, the mean FA-values of the PFC-tract could be predicted by the scores on the WCST cat. Higher mean FA-values of
the PFC-tract were connected to participants producing less categories during the WCST (F=18,5 p< .01). This relation is visualized in figure 4. This strong regression (R2=0.755) is contrary to the expectations. When controlling for outliers or a small number of influential cases, by exploring Cook’s distance and standardized residuals they all appeared to be in the normal range, meaning nothing was found that differed substantially from the main trend of the data. Yet, when taking into account the present sample size, we should be careful interpreting this result
Figure 4. Regression line of the relation between the mean FA over the PFC tract and the WCST categories.
Explorative
Four participants (22%) in this sample had cART-regimen with Efavirenz. No further analysis can be done to examine an increased risk of Efavirenz on having HAND, for the
sample size is too small. Furthermore, the HAND group has a similar age as the non-HAND group, as is shown in Table 2, suggesting age has no influence on the presence of HAND.
In this sample, HAND does not have comorbidities with MCI (the most frequently seen version), although four participants (36,4 %) in the HAND group also meet the criteria for vascular cognitive impairment.
Conclusion
The aim of present study was to acquire more insight in the detection of milder forms of HAND, to find a substitute for NPA as a tool for diagnosis. Current results support previous research on screening tools. The HDS has been proven to be the most useful screening test in detecting HAND. Yet, this instrument often classifies HIV patients without cognitive
impairment falsely as having HAND.
When examining biomarkers in the white matter integrity as a diagnostic tool for HAND, current results show marked differences in white matter integrity between patients with milder forms of HAND and those without a HAND diagnosis. Less white matter integrity in patients with HIV tends to be associated with a higher risk of HAND, yet no predictive relation could be found. This relation should be examined further in future research.
Discussion
As the results presented above are not straightforward, the next paragraphs will discuss them more extensively. First, the results of the commonly used detection methods, screening tests and NPA will be discussed. Next, we will further examine the use of DTI.
Screening Tests
Current results of screening tests show inaccuracy for detecting milder forms of HAND. The examined screening tests together, classified all patients in this sample as
cognitively impaired, when only 61 percent were actually diagnosed with a form of HAND afterwards. Supporting claims of previous research (Carey et al., 2004; Morgan et al., 2008), the HDS was most effective at detecting HIV-patients suffering from HAND, but also produced a high rate of false positives. Results show that both the MMSE and MoCA are inaccurate at correctly detecting HAND in patients with HAND, and have high rates of falsely classifying patients with HAND as free from impairment and falsely classifying patients without HAND as having HAND. Unexpectedly, it classified 71 percent of the patients with HAND as not having HAND, which excludes it from being a useful screening test for milder forms of HAND. Furthermore, the MoCA and HDS were correct at identifying the more severe MND cases as having HAND, whereas the MMSE could not. Thus, it can be concluded that the MoCA and the HDS are more adequate at identifying HAND than common standardized screening tools for dementia (measuring posterior neocortical pathophysiology), such as the MMSE.
Also, it should be noted that ANI and MND criteria lie very close to, and even
overlap, with clinically unimpaired patients, as it only requires performing 1 SD below mean on a domain instead of 2SD, which is common in neuropsychological research. This makes it hard or even impossible for screening tests to have both high sensitivity and high specificity for this diagnosis. Consequently, HAND screening tools can be effective in detecting severe forms of HAND, but problems in identifying ANI from non-impaired patients may be expected.
Neuropsychological Examination
Currently, an NPA is the main diagnostic tool for detecting HAND. As expected, certain differences exist between patients diagnosed with HAND and those without HAND diagnosis on NPA test results. Patients without HAND performed mostly better on NPA measurements within the domains of Language Fluency and Information Processing Speed. However, patients without a HAND diagnosis did not perform better on all tests. On one
measurement (the WCST cat), patients without HAND even performed worse than patients with a HAND diagnosis. Also, impaired domains (persistently scoring at least 1 SD below the mean on tests representing the same cognitive ability) are present in 43% of patients without a HAND diagnosis, which is more than is expected in a normal control group. This is not surprising, as the patients without a HAND diagnosis are not part of a normal control group. These patients were referred by screening tests for having cognitive impairment.
White Matter indicators
Present study proposes impairments in white matter integrity as a possible biomarker for HAND. Current results show, as expected, better white matter integrity in patients without HAND than in patients with a HAND diagnosis. This relation had a moderate to high effect size. The white matter integrity of the tracts was the same over each hemisphere, indicating the same connectivity between brain areas over the two hemispheres
Despite the relation between white matter integrity and HAND, unexpectedly no relation between motoric abilities and white matter integrity of the MC-circuit can be found. Likewise, no relation could be found between the white matter integrity in the fronto-striatal circuitry and most of the executive functioning measurements. It is still possible that lessened white matter integrity is responsible for deficits in the corresponding cognitive domains. Yet, due to a small sample size, present study was not able to prove this. Current results however did find an unexpectedly strong relation between the WCST cat (one measurement of an executive functioning test) and the white matter integrity in the fronto-striatal circuitry, where lower white matter integrity leads to higher performance on the task. This result is
unexplainable within the present neuropsychological research. No other executive functioning measurement produces the same result, so it should not be concluded that worse executive functioning relates to lower white matter integrity in the fronto-striatal circuitry. This
in regression analysis, random data may appear to show a strong effect (because R= k/N-1). The rule of thumb is 10 cases per predictor; in current analysis this condition is not met.
However, the found relation between WCST cat and white matter integrity in the fronto-striatal tract appears to be too strong to be dismissed as a statistical default. Another explanation might be the influence of a not presently investigated brain area. Previous
research suggests that the WCST does not only engage the PFC (Nyhus & Barceló, 2009), but also a variety of other brain structures. White matter integrity in the fronto-striatal tract does not solely account for performance on the WCST. Other structures probably facilitated performance on the WCST. Yet, this explanation does not explain why only the WCST cat shows this result and not the rest of the test.
Furthermore, current results show all FA-values to be lower than normal. This is probably caused by the probabilistic way of tracking. The mean FA-value over all voxels of a tract is calculated, including voxels located on the edges of the fibres. These edge-voxels have lower FA-values, which results in generally lower FA-values in the tracts
Explorative
Lastly, present study hoped to explore the effects of age, SVD and MCI comorbidities and the toxic effects of Efavirenz. No relation between age and HAND was found. This might be due to the fact that the study included only HIV patients over 45 years old, resulting in a too small age differences or sample size. Also, no patients showed detectable HIV-1 viral loads in the bloodstream or CSF, which might cause extra cognitive impairment. Furthermore, no effect of medication that prior research thought to have toxic effects (Efavirenz) was found. No conclusion can be drawn from this result, as present study only included 4 patients with Efavirenz in their cART regimen.
Comorbidities related to rapid aging and to hypertension with the same cognitive manifestation were investigated. No patients with HAND were also eligible for the most common form of MCI (amnesic MCI). However, 4 patients with HAND may also be eligible
for a small vascular impairment. Present study however delivers no evidence that these patients do not have HAND. It is possible that SVD comorbidity is present. These patients were not excluded from the analysis. Using NPA as a diagnostic tool, comorbidities could occur in the sample. Further research should be aware of this.
Limitations
As stated earlier, present study uses a small sample size, which limits the robustness of the linear regression results and creates difficulties finding results due to lack of power. Furthermore, the examined sample is a heterogeneous one. A heterogeneous sample is usually preferable, as a way of correctly representing a population. The heterogeneity of present study however, together with a lack of control group and incomplete test results, makes it harder to find robust differences between groups. Furthermore, conclusions about the differences caused by HIV cannot be made, because of the absence of a control group.
Furthermore, present study focuses on ANI and MND, which are not full-blown clinical disorders, but preliminary stages of HAND. Effects of ANI and MND lie between normal functioning and more severe forms of HAND. This entails some difficulties, as some patients diagnosed with ANI could just be in the normal ‘low’ range of functioning. And due to the possible widespread cognitive impairment, some patients who are diagnosed with ANI may suffer from other comorbid disorders with the same manifestation of symptoms, like SVD or MCI. This limits the validity of the HAND sample, and its usefulness when searching for biomarkers.
Finally, present study examined two brain areas associated with HIV. However, previous research on this subject is inconclusive about which structures are affected by HIV and which affected structures have the largest influence on HAND. So other, not presently investigated, brain structures could also have effects on HAND.
Further research
Interesting about current results is that a relation between the occurrence of HAND and white matter integrity is found in two tracts. Also, an obvious relation exists between NPA results and HAND, because NPA results provide the HAND diagnosis. Still, no relation between NPA results and white matter integrity is found. This might be caused by too little power of present study, or might be caused be another unknown factor. Further research should examine these relations more closely, especially the question if the white matter integrity in these tracts may be causally related to HIV. Research into the question if these abnormalities proceed HAND, may lead to the development of a biomarker.Hopefully, the made suggestions for future research will bring us a step further in finding a reliable and quick method for detecting milder forms of HAND.
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