Abstract
Objectives
Neuropsychiatric symptoms have been reported in people living with HIV (PLWH) on integrase strand transfer inhibitors (INSTIs) in post marketing analysis. Limited data exists regarding brain integrity (function and structure) in PLWH prescribed INSTIs compared to other HIV treatment regimens.
Design
A cross-sectional analysis of PLWH on combined antiretroviral therapy (cART) aged >18 years at a single institution.
Methods
Neuropsychological tests were administered to calculate domain deficit scores (DDS) in learning/memory, executive function, and motor/psychomotor domains. Cortical and subcortical volumes from magnetic resonance imaging were obtained using the FreeSurfer software suite (v5.3) (Harvard University, Boston, MA).
Results
Of 202 participants, median age 55 (48, 60) years old, 49% were on INSTI-based cART. PLWH on INSTIs were similar to individuals on non-INSTIs in terms of age, sex, race, education years, smoking history, depression scores, psychiatric medication use, presence of hepatitis C infection, history of substance use, HIV infection duration and recent or nadir CD4+ T cell count. Participants in the INSTI group performed worse than non-INSTI users in the verbal learning and memory domain (1.5 (interquartile range; 0.25, 2.5) versus (1 (0, 2); p=0.016). The INSTI and non-INSTI groups were similar for other cognitive domains. Frontal, brain stem, and cerebellar volumes were reduced in INSTI compared to non-INSTI users (all p=<0.05).
Conclusion
We demonstrated modest differences in learning/memory performance and smaller brain volumes in PLWH on INSTI-based regimens compared to non-INSTI users. Prospective studies are needed to define mechanisms and the clinical significance of reduced brain integrity in PLWH on INSTIs.
Keywords: Neuropsychological performance, HIV, Antiretroviral therapy, Integrase Strand Transfer Inhibitors, Neuroimaging, Brain volumetrics
Introduction
HIV-associated neurocognitive disorder (HAND) continues to occur in people living with HIV (PLWH), even in the era of combination antiretroviral therapy (cART) [1–3]. The prevalence of HAND is less common among virally suppressed PLWH when compared to demographically similar individuals with detectable viral load [4]. Similarly, studies report lower frequencies of progressive neuropsychological decline [5, 6] and/or structural brain changes in virally suppressed PLWH [7]. However, concerns remain about iatrogenic effects of cART on brain integrity (function and structure), which may contribute to HAND. The non-nuclease reverse transcriptase inhibitors (NNRTI), especially efavirenz (EFV), have been linked to incident neuropsychiatric adverse events and worsening cognition [8, 9]. NNRTIs have been replaced as first line therapy by integrase strand transfer inhibitors (INSTIs).
Although INSTIs were well tolerated in clinical trials, concerns have emerged regarding the risk of neuropsychiatric symptoms. Several post-marketing studies have reported insomnia and depressive symptoms among PLWH who initiated dolutegravir (DTG)-based [10–12] or raltegravir (RAL)-based regimens [13–15]. However, studies of the effects of INSTIs on brain function and structure are lacking. To address this gap in knowledge, we examined neuropsychological performance and brain volumetrics in a cohort of PLWH on INSTI-based regimens compared to a well-matched group of PLWH receiving non-INSTI-based regimens.
Methods
Patient population and study design
We performed a cross-sectional analysis of eligible PLWH enrolled in ongoing research studies conducted at our institution between February 2012 and June 2017, who were 18 years or older, on stable cART and who had neuropsychological performance assessment and neuroimaging results. Participants were excluded if they had less than seven years of education; a history of confounding neurological disorders including epilepsy, dementia or stroke; current or past opportunistic central nervous system infection; a history of brain injury with loss of consciousness for greater than thirty minutes; or evidence of intoxication on the day of assessment. All participants provided informed written consent approved by the institutional review board at Washington University in Saint Louis (WUSTL). Participants in this analysis were representative of PLWH followed at the WUSTL Infectious Diseases clinic (Clinic population 70% male, 70 % African American, median age 45 years old).
Clinical and radiological assessments
Demographic data, HIV parameters including cART history, plasma CD4+T cell counts and HIV RNA, medications (including psychiatric medications) and history of recent substance use (self-reported and urine drug screen verified) were collected. Date of HIV diagnosis was verified using medical records.
Neuropsychological assessment
Neuropsychological performance was evaluated to identify potentially clinically relevant differences between the two groups [16, 17]. Neuropsychological tests were divided into three domains: executive function, learning/memory and motor/psychomotor speed. Executive function was assessed using Letter Number Sequencing (LNS)[18], Trail Making Test B (Trail B)[19], Letter fluency (FAS)[20] and Verb fluency[21]. Learning/memory was assessed by Hopkins Verbal Learning Test-Revised (HVLT-R)[22] total score across three learning trials and total score on the delayed trial[22]. Motor/psychomotor speed was assessed by the Trail Making Test A (Trail A)[19], Grooved Pegboard dominant and non-dominant hands[23], and Digit- Symbol[18]. Each raw score was converted to a standardized score using demographically corrected norms [18, 24–28]. T scores were then converted to a deficit score by assigning a value from 0 (normal) to 5 (severe impairment) for each test[29]. Within each domain, tests were averaged to form a domain deficit score (DDS). DDS scores were averaged to form the total deficit score (TDS). Scores ≥0.5 were considered abnormal.
Mood and sleep assessment
Depressive symptoms were assessed using the Beck Depression Inventory II®[30]. Pittsburgh sleep quality index (PSQI)[31], Epworth Sleepiness Scale[32] and Stanford Sleepiness Scale[33] were used to assess daytime somnolence and sleep quality.
Imaging Acquisition
Neuroimaging was performed using a 3T Siemens Tim Trio MR scanner (Siemens AG, Erlangen, Germany) with a 12-channel head coil. A high-resolution, 3-dimensional, sagittal, magnetization-prepared rapid gradient echo scan (MPRAGE) T1 scan was acquired [repetition time (TR) = 2400 ms, echo time (TE) = 3.16 ms, flip angle = 8, inversion time = 1000 ms, voxel size = 1 × 1 × 1 mm3 voxels, 256 × 256 × 256 acquisition matrix, 162 slices].
Volumetrics
All cortical and subcortical volumes were obtained using the FreeSurfer software suite (v5.3) (Martinos Center, Harvard University, Boston, MA). Each individual’s FreeSurfer segmentation was rigorously inspected and corrected when necessary by a trained research technician. Frontal (frontal pole, precentral gyrus, inferior frontal gyrus (parsopercularis, pars orbitalis, par triangularis)), parietal (superior and inferior regions), temporal (tranverse, inferior and superior temporal regions), occipital (lateral occipital, lingual and cuneus), cerebellar and brain stem regions were examined. Each volume was adjusted for intracranial volume to correct for head size.
Statistical analysis
Continuous variables were expressed as median and interquartile range (IQR) or mean and standard deviation according to distribution. Categorical variables were expressed in percentages. Between-group differences were compared using Mann-Whitney U tests or Students t-tests depending on the distribution of the variable being examined. A binary logistic regression model was used to assess the association between clinical parameters and neuropsychological performance. Variables that were significantly different between the two groups (p values <0.05) were included in the multivariate model. In addition, some variables that were considered clinically relevant, but did not differ between the groups, were also included. P values <0.05 were considered statistically significant. Analyses were performed using IBM SPSS Statistics for Window, version 24 (IBM SPSS Corp., New York, USA) and GraphPad Prism version 7.0 (GraphPad Software Inc, San Diego, USA).
Results
Of the 202 participants included in the study, the median (IQR) age was 55 (48, 59) years old, 152 (75%) were male and 136 (67%) were African American. A total of 99 (49%) were on INSTI-based ART regimens, and 103 (51%) were taking non-INSTI based regimens. Baseline demographics are shown in Table 1.
Table 1.
Baseline characteristics
| Characteristics | Non-INSTI n=103 | INSTI n=99 | p-value |
|---|---|---|---|
| Age in years (median, IQR) | 55 (45, 60) | 54 (50, 58) | 0.91 |
| Males (N, %) | 78 (76) | 74 (75) | 0.87 |
| Black (N, %) | 69 (67) | 67 (68) | 0.92 |
| Education in years (mean, SD) | 13 (3) | 13 (2.7) | 0.58 |
| Right handedness (N, %) | 88 (86) | 84 (85) | 0.77 |
| Beck Depression Inventory-II (median, IQR) | 10 (2, 17) | 7 (4, 16) | 0.99 |
| Psychiatric medications (N, %) | 38 (37) | 46 (47) | 0.17 |
| Body mass index (median, IQR) | 26.5 (23.5, 31) | 26.2 (22.7, 29.4) | 0.27 |
|
Substance Use | |||
| Positive urine drug screen (N, %) | 67 (65) | 59 (60) | 0.42 |
| Cannabis | 53 (52) | 44 (44) | |
| Cocaine | 11 (11) | 14 (14) | |
| Opioids | 5 (5) | 6 (6) | |
| Methamphetamine | 2 (2) | 8 (8) | |
| Benzodiazepines | 19 (18) | 15 (15) | |
| Self-reported Illicit drug use (N, %) | 56 (54) | 42 (42) | 0.09 |
| Cannabis | 40 (39) | 33 (33) | |
| Cocaine | 8 (8) | 11 (11) | |
| Opioids | 8 (8) | 3 (3) | |
| Methamphetamine | 1 (1) | 1 (1) | |
| Benzodiazepines | 9 (9) | 8 (8) | |
| Prescribed opiate therapy | 11 (11%) | 7 (7%) | 0.38 |
| Alcohol use (self-reported) (N, %) | 60 (58) | 60 (61) | 0.73 |
| Current smoker (N, %) | 53 (52) | 46 (47) | 0.48 |
| Hepatitis C (N, %) | 8(8) | 10 (10) | 0.56 |
| Testosterone replacement therapy | 4 (4) | 6 (6) | 0.48 |
|
HIV parameters | |||
| Duration of HIV infection (median, IQR) | 185 (89, 263) | 200 (109, 264) | 0.76 |
| Duration of current regimen (months; median, IQR) | 60 (24, 89) | 18 (6, 35) | <0.001 |
| Nadir CD4 (median, IQR) | 185 (35, 302) | 128 (22, 274) | 0.42 |
| Recent CD4 (median, IQR) | 604 (446, 834) | 548 (321, 782) | 0.10 |
| HIV RNA < 20 copies/ml (N, %) | 85 (83) | 79 (80) | 0.33 |
| HIV RNA <200 copies/ml (N, %) | 95 (97) | 91 (95) | 0.50 |
INSTI, integrase strand transfer inhibitor; IQR, interquartile range; SD, standard deviation
The two cART groups did not differ in rates of current substance use, and rates of smoking and alcohol consumption were similar for both groups. There were no difference in depressive symptoms as measured by the Beck Depression Inventory II or the proportion of participants on medication(s) to treat psychiatric conditions overall or by class (supplementary table 2). The median (IQR) number of psychiatric medications was 0 (0, 1) for both groups. There was no difference in the proportion of participant that were prescribed more than one psychiatric medication (non-INSTI 19 (18%) compared to the INSTI group (24 (24%); p=0.31).
There was no difference in daytime somnolence, sleep quality or sleep disturbance between the two groups (global PSQI score (non-INSTI 7 (4, 10) versus INSTI (7 (4, 11); p=0.79); Epworth Sleepiness Scale (non-INSTI 8 (5, 12) versus INSTI (7 (4, 9); p=0.09) and Stanford Sleepiness Scale (non-INSTI 2 (1, 3) versus INSTI (2 (1, 3); p=0.79). There was no difference in the self-reported or confirmed length of time since HIV diagnosis between the groups. Nadir and recent CD4+ T cell counts were similar in both groups as were the proportion of participants with HIV RNA <200 copies per/ml or <20 copies/ml. For the participants on an INSTI-based regimen, 40 (40%) were on RAL, 29 (29%) on ETG, and 30 (30%) on DTG.
Although there were no differences between the groups in the proportion of participants on protease inhibitors (PIs), a higher proportion of participants in the non-INSTI group were on NNRTIs compared to those in the INSTI group (67 (65%) versus 19 (19%); p<0.001)). The most commonly used NNRTI was EFV with 43 (42%) individuals prescribed this medication in the non-INSTI group compared to 6 (6%) in the INSTI group, p<0.001)). Interestingly, the proportion of participants who had received EFV as part of a previous regimen was similar for both groups ((non-INSTI 34 (33%) compared to INSTI 39 (39%); p=0.35).
The most common prescribed ART regimens for the INSTI group were tenofovir, emtricitabine (FTC), cobicistat, ETG (25%); abacavir (ABC) or tenofovir, lamivudine (3TC), DTG (16%) and ABC or tenofovir, FTC, RAL (14%). In the non-INSTI group, the most common regimens were tenofovir, FTC, EFV (38%); tenofovir, FTC, darunavir, ritonavir (12%) and tenofovir, FTC, atazanavir, ritonavir (11%). Within the INSTI group 10% of participants were receiving nucleoside reverse transcriptase inhibitor (NRTI)-sparing regimens compared to 3% in the non-INSTI group. Reflecting the more recent approval of INSTIs, participants in the non-INSTI group had been on their current regimens for longer period compared to the INSTI group (60 versus 18 months; p<0.001).
The learning/ memory DDS was higher (worse) in the INSTI group compared to the non-INSTI group (1.5 (0, 2.5) versus 1 (0, 2); p=0.016) (Table 2). This remained significant after correction for nadir CD4+ T cell count, duration of current cART regimen, current NNRTI or PI use, current psychiatric medication use, or having previously received another cART regimen (OR 3.9 (CI 1.4, 11.8); p=0.012). When INSTI’s were included in the model as DTG or non-DTG INSTI, both DTG and non-DTG remained significant (Table 3). The proportion of PLWH with abnormal learning/memory domain scores (primarily within learning and retention) was significantly higher in the INSTI group compared to the non-INSTI group (73 (74%) versus 61 (59%), p=0.029). There was no difference in executive function or motor/psychomotor DDS. Participants in the INSTI group had worse TDS than those in the non-INSTI group (0.75 (0.33, 1.25) versus 0.5 (0.25, 1); p=0.049) that primarily reflects deficits in the learning/memory domain score. The proportion of PLWH with abnormal TDS was also significantly higher in the INSTI group compared to the non-INSTI group (70 (71%) versus 57 (55%), p=0.024).
Table 2.
Between group domain and total deficit scores
| Deficit scores | Non-INSTI n=103 | INSTI n=99 | p-value | ||
|---|---|---|---|---|---|
| Learning/ memory | 1 | (0, 2) | 1.5 | (0, 2.5) | 0.016 |
| Executive function | 0.25 | (0, 0.75) | 0.5 | (0, 1) | 0.85 |
| Psychomotor/processing speed | 0 | (0, 0.5) | 0 | (0.5) | 0.98 |
| Total deficit | 0.5 | (0.25, 1) | 0.75 | (0.33, 1.25) | 0.049 |
INSTI, integrase strand transfer inhibitors. Data presented are median (IQR)
Table 3.
Multivariable analysis of learning/memory domain deficit scores
| Variable | Odds ratio | (95% CI) | P value |
|---|---|---|---|
| Current dolutegravir use | 4.7 | 1.2, 18.4 | 0.028 |
| Current non-dolutegravir use | 3.7 | 1.2, 11.7 | 0.026 |
| Current NNRTI use | 1.2 | 0.4, 3.4 | 0.7 |
| Current Protease inhibitor use | 1.2 | 0.4, 3.2 | 0.8 |
| Previous ART | 1.1 | 0.4, 2.8 | 0.8 |
| Current psychiatric medications | 0.7 | 0.3, 1.4 | 0.3 |
| Duration of current ART | 1.0 | 0.9, 1.1 | 0.3 |
| Nadir CD4+T cell count | 1.0 | 0.9, 1.0 | 0.4 |
NNRTI, non-nucleoside reverse transcriptase inhibitors, ART, antiretroviral therapy
Variables that were significantly different between the two groups (p values <0.05) were included in the multivariate model. In addition, some variables that were clinically significant but did not differ between the groups were also included.
As the effects observed could be due to exposure to multiple cART regimens, we performed an additional analysis within a subset of participants (44, 21.7%) who were on their first cART regimen (11 on INSTI based regimens and 33 on non-INSTI based regimens). We observed worse performance in the learning/memory domain in the INSTI group (2.5 (0.5, 3) compared to the non-INSTI group (0.125, 2; p=0.021). No significant differences were seen in the executive function or motor/psychomotor domains when comparing the two subgroups. Participants on their first cART regimen had similar demographics to the overall cohort: median age 54 years old (IQR 40, 63), 73% African American, 68% male, 39% using psychiatric medication(s), and history of substance use (61%). Similarly, for those on first ART regimens there was no difference in age, gender, race, substance use history or use of psychiatric medication between INSTI and non-INSTI based regimens (all p>0.05).
Overall, participants on INSTIs had lower total grey volume and subcortical grey volumes compared to those receiving non-INSTI regimens. Frontal, brain stem and cerebellar volumes were smaller for the INSTI group (all p’s<0.05) (supplementary table 3). There was no significant difference in other regional cortical or subcortical white matter volumes between the groups.
Discussion
Antiretroviral drugs have previously been associated with neuropsychiatric symptoms including dizziness, sleep disturbance, abnormal dreams, anxiety and depression. Despite this, limited data exits in relation to the effect of specific antiretroviral drugs on neuropsychological function [34]. The primary aim of this study was to determine if differences existed in neuropsychological function and brain structure in PLWH on INSTI-based cART compared to a well-matched group on non-INSTI based cART. Here, we demonstrated worse learning/memory performance and smaller regional brain volumes in PLWH on INSTI-based regimens. This could be due to multiple possible etiologies including direct neurotoxicity of the INSTI cART regimens themselves, variation in CSF concentrations of different cART agents, the effect of a recent switch of regimen to an INSTI-based regimen, or different drug interactions between INSTI vs PI or NNRTI based cART.
Although not definitive, direct neurotoxicity has been reported in vitro with ART. cART has been shown to lead to oxidative stress and neuronal damage and may account for some of the observed reductions in brain volumes[35]. A recent autopsy study demonstrated higher likelihood of neuronal phospho-tau lesions in the putamen of patients on darunavir, whilst ritonavir use was associated with marked microgliosis in the putamen, both suggestive of cerebral degenerative changes. However, there was insufficient INSTI use to allow for their assessment[36]. Interestingly, a recent study in primary rat neuroglial cultures demonstrated neurotoxicity of ETG but not RAL or DTG [37]. Clinically, concerns have been raised regarding increased prevalence of neural-tube defects (NTD) in infants born to mothers treated with DTG at the time of conception. In a surveillance study that is currently ongoing in Botswana, the prevalence of NTD in those who received DTG-based therapy was 0.94% compared to 0.12% in those in non-DTG based regimens. Neurotoxicity concerns have resulted in cART guideline changes for women of childbearing age. However, limited data exists on differences in brain volumes according to type of cART in PLWH[38].
Inter-individual variabilities in cerebrospinal fluid (CSF) penetration of antiretrovirals may contribute to the relative risk of neuropsychiatric side effects. Higher CSF concentrations of certain medications can produce neurotoxicity whereas lower concentrations may increase viral replication and inflammation in the central nervous system [39, 40]. Neuropsychiatric symptoms in PLWH have been associated with inter-individual variability in CSF concentration of RAL[41]. EFV use was associated with improvement in neuropsychological testing, likely due to viral suppression; however, higher blood levels of EFV corresponded with worse neuropsychological performance [42]. The expression of neuropsychiatric symptoms may be due to complex interactions between HIV, cART, and the host.
Previous studies have demonstrated neuropsychological dysfunction in individuals with both sleep disturbances and depression [43, 44]. High prevalence of sleep disturbances have been reported in PLWH and have been associated with a myriad of factors including depression and specific antiretroviral drugs [45]. However, we did not observe differences in subjective sleep measures between the groups. Of note in a recent study that demonstrated increased DTG peak concentration in older (>60 years) PLWH, there was also no differences in sleep quality noted at 3 or 6 months[46].
Empirical data on INSTIs and neuropsychological function is limited. A small prospective study reported decline in neuropsychological function after 24 weeks of RAL in virally suppressed PLWH ≥ 60 years old [47]. Of note, a recent pilot study included comprehensive assessment of cerebral function parameters including cognitive function, cerebrospinal fluid parameters and MRI imaging in 20 patients who switched from a RAL-based regimen to a DTG-based regimen and did not demonstrate changes in any parameters[48]. Here we present data indicating a modest worsening in the learning and memory domain of PLWH on INSTI-based regimens. We also observed significant lower brain volumes, especially within the frontal, brain stem and cerebellar regions. Frontotemporal connections are involved in multiple cognitive functions including learning and memory, and are affected in PLWH[49].
This study has several limitations. Although the groups are well matched for baseline demographics as well as HIV clinical variables, the cross-sectional design means that it is subject to the inherent biases associated with this study design and does not allow examination of causal pathways. As is common in the management of PLWH for several years, the majority of study participants had previous cART treatment but data on the reason for switching regimens were not available. Although many study participants were likely switched to regimens with better safety and tolerability profiles as part of routine standard of care, we cannot rule out potential channeling bias introduced by these switches. To account for this, the use of previous cART was included in our regression model. To address this further, we examined the cohort of participants who were on their first cART regimen. Although the cohort was small, the learning/memory DDS was also worse in the subgroup on INSTI’s in this analysis. This study is also prone to survival bias as some participants may have discontinued non-INSTI drugs prior to the time of analysis because of neuropsychiatric adverse events. Also since the non-INSTI group had been taking their current regimen much longer than the INSTI group, the non-INSTI group may be selected for participants who tolerate NNRTI or PI therapy. Finally, data on the participant’s functional or menopausal status were not available[48].
In conclusion, in this large cohort of PLWH, the use of INSTI-based regimens were associated with modestly reduced neuropsychological performance in the learning and memory domain as well as lower brain volumes when compared to their counterparts on non-INSTI based regimens. These findings emphasize the importance of clinical monitoring of PLWH being switched to INSTI-based regimens. Longitudinal studies with preplanned hypotheses are needed to confirm the observed findings and explore potential underlying mechanisms.
Supplementary Material
Acknowledgments
Conflicts of interest and sources of funding:
The authors do not have any conflicts of interest to report. The study was supported by grants from the National Institute of Nursing Research (NINR) R01-NR015738, R01-NR012657, and R01-NR014449 and the National Institute of Mental Health (NIMH) R01-MH118031
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