All patients underwent a detailed neuropsychological assessment, covering fluency, attention, processing speed, memory, executive function and fine motor function. Using normative standards, test scores were converted to age and education corrected scores. Multivariate normative comparison (MNC) was performed to detect cognitive impairment . Our previous work demonstrated that the MNC method can detect cognitive impairment more reliably as compared with the Frascati criteria for HIV-associated neurocognitive disorders (HAND) .
MRI data acquisition
All patients underwent a MRI examination at the AMC and scanning was performed on a 3T Intera and continued on a 3T Ingenia system (Philips Healthcare, Best, the Netherlands) due to a scanner upgrade. This upgrade was statistically accounted for in all analyses and the distribution of patients according to HIV serostatus per scanner system is provided in Table 1. The diffusion weighted MRI scanning parameters were as follows: echo time/repetition time (TE)/(TR) = 92/7081–9665 ms; 55 to 64 continuous slices depending on head size; data matrix 112 × 112; voxel size = 2 × 2 × 2 mm3; diffusion weighting of b = 1000 s/mm2 along 64 directions and four averages with b = 0 s/mm2. For volumetric analyses a sagittal magnetization prepared rapid gradient echo (MPRAGE) scan was acquired (TE/TR = 3.1/6.6 ms; 270 × 270 mm2 field-of-view (FOV), 170 sagittal slices of 1.2 mm thickness, 1.1 × 1.1 mm2 in-plane resolution) and to define white matter lesions of presumed vascular origin a three-dimensional fluid attenuated inversion recovery (3D-FLAIR) scan was performed (TE/TR = 355/4800 ms; inversion time = 1650 ms; FOV 250 × 250 mm2; 321 sagittal slices of 0.56 mm thickness; 1.1 × 1.1 mm2 in-plane resolution).
All data were anonymized prior to analysis. Preprocessing of DTI data was performed with software developed in-house (Matlab; Math Works, Natick, Massachusetts, USA, using the HPCN-UvA Neuroscience Gateway and using resources of the Dutch e-Science Grid . Head motion and deformations induced by eddy currents were corrected for by an affine registration of the diffusion weighted images (DWI) to the nondiffusion weighted image. The gradient directions were corrected by the rotation component of the transformation . Rician noise in the DWI was reduced by an adaptive noise filtering method . Diffusion tensors were calculated using a nonlinear least squares estimation. Subsequently, fractional anisotropy and mean diffusion maps were computed for each patient. All patients-data were then aligned into a common space using the nonlinear registration tool FNIRT .
To reduce the risk of partial volume effects, we focused our analysis on the central parts of the white matter tracts, for which a population-based fractional anisotropy-map was created and skeletonized (fractional anisotropy was thresholded at 0.2) . The resulting fractional anisotropy-based skeleton represents the centre of all major tracts in the population-based template. For each individual patient, its aligned fractional anisotropy and mean diffusion maps were projected onto this fractional anisotropy skeleton (Fig. 1) . Subsequently, each fractional anisotropy and mean diffusion maps were averaged to a white matter summary statistic or used for tract-based spatial statistics (TBSS) in the functional software library (FSL) [47,48].
Anatomical images were used for grey matter, white matter and CSF segmentation by SPM8 . The intracranial volume (ICV) was computed by summing the grey matter, white matter and CSF volumes. The relative total brain volume was defined as the ratio of total brain volume (summing the grey matter and white matter) over ICV.
In addition to white matter summary statistics for each individual DTI metric, normal appearing white matter (NAWM) DTI metrics were derived in which white matter lesion areas (hyperintense on 3D-FLAIR) were masked out (Fig. 1) . This involved training a ‘random-forest’ classification algorithm on a manual annotation set of 20 individuals with varying lesion load, to detect the presence of lesions . This was then applied in the current dataset to identify regions of white matter lesions in HIV+ patients and controls.
Group comparisons of patient characteristics between HIV+ patients and controls were performed (Tables 1 and 2).
Across all patients, the effect of HIV serostatus on white matter fractional anisotropy (WMFA) and white matter mean diffusion (WMMD) measures were examined by linear regression analyses, while adjusting for age, relative brain volume and scanner system. To examine possible accelerated aging effects in HIV+ patients, interaction effects between age and HIV serostatus on WMFA and WMMD measures were assessed.
To identify confounders and determinants (intoxicants, comorbidities and risk factors, biomarkers of immune activation and HIV/ART-related factors) of WMFA and WMMD measures, stepwise linear regression analyses were performed (P < 0.05 probability to enter and P > 0.1 probability to remove), while adjusting for age, brain volume and scanner system.
To examine associations of WMFA and WMMD measures with cognition, HIV+ patients were classified as either cognitively impaired or unimpaired by MNC. Group comparison on cognitive status was performed on the WMFA and WMMD measures, adjusted for age, brain volume and scanner system. The test statistic of the MNC method was Hotelling's T2. To create a continuous measure of cognitive function and prevent a bimodal distribution, each Hotelling's T2 statistic was subtracted from the lowest Hotelling's T2 statistic and multiplied by the direction of deviation (i.e. positive or negative deviation reflecting better or poorer cognition as compared with the control group). Associations of this transformed statistic with WMFA and WMMD, were examined by linear regression, adjusting for age, brain volume and scanner system.
To provide spatial information on significant findings of white matter DTI metrics, TBSS group comparison and correlational analyses were performed, while adjusting for age, brain volume and scanner system. Multiple comparisons were corrected for by using permutation tests. This was implemented using the Randomise software within FSL, employing the threshold-free cluster enhancement (TFCE), in which P-values <0.05 were considered significant. All analyses were subsequently repeated with NAWM DTI metrics.
MNC was performed using R statistical software , whereas remaining analyses were done in SPSS (version 20.0; IBM, Armonk, New York, USA).
Demographic and clinical characteristics
Participants were enrolled to the neuroimaging study between December 2011 and August 2013. Neuroimaging data were available from 100 HIV+ patients and 70 controls. An overview of the demographics, neuroimaging and HIV/ART-related factors are shown in Table 1, whereas Table 2 provides an overview of intoxicants, comorbidities and risk factors and biomarkers of immune activation. The HIV+ patients [median age: 54 (interquartile, IQR 49–61) years] were highly comparable to the controls [median age: 53 (IQR 49–59) years]. Both groups were also similar in their substance use behaviour, except for ecstasy use, which was more common in the controls (11 vs. 2%, P = 0.02). Controls also had higher plasma concentrations of glycated haemoglobin (HbA1c, 37 vs. 35, P = 0.01) and BMI (26 vs. 24, P = 0.002). HIV+ patients fulfilled more often the criteria for central obesity (i.e. waist/hip ratio>0.9) and had greater lifetime tobacco exposure as measured by pack-years of smoking (P = 0.03, P = 0.01). Levels of soluble CD14 were higher in HIV+ patients, whereas CD4+/CD8+ ratios were lower as compared with controls (P < 0.001, P < 0.001). No group differences were found for the remaining factors.
HIV+ patients had been treated with antiretroviral therapy for a median duration of 11.4 (IQR 4.9–14.9) years and showed substantial immune recovery. Their median nadir CD4+ cell count was 170 (IQR 60–248), with a current CD4+ cell count of 620 (IQR 475–787) cells/μl.
Group comparisons on white matter diffusion properties
Across the white matter there were significant differences between the HIV+ patients and controls. HIV+ patients showed significantly lower WMFA (P = 0.03) and significantly higher WMMD (P = 0.02). See Table 1 for further details. Interaction effects were assessed and no interaction effect of age and HIV serostatus was found for these white matter DTI-metrics (fractional anisotropy: P = 0.59, mean diffusion: P = 0.58).
Voxel-wise comparison by TBSS showed a widespread pattern of lower fractional anisotropy and higher mean diffusion in HIV+ patients compared with controls (Fig. 2). Patterns of reduced fractional anisotropy were seen in projection- and thalamic fibres (i.e. cortical spinal tract and anterior thalamic radiation), all major association fibres (i.e. superior longitudinal fasciculus, inferior longitudinal fasciculus, inferior-fronto-occipital fasciculus and uncinated fasciculus), limbic system fibres (i.e. cingulum) and callosal fibres (i.e. forceps minor and forceps major). Differences in mean diffusion were less pronounced and mainly localized in the left hemisphere, although lowering the statistical threshold also showed contralateral effects (data not shown).
Determinants and confounders of altered white matter diffusion properties
Joint analysis of HIV+ patients and controls showed that HIV serostatus, age, lower brain volume and the number of antihypertensive medications used were significantly associated with lower WMFA and higher WMMD (Table 3: Model 1). Remaining possible confounding variables examined (see Tables 1 and 2 for a complete overview) did not contribute sufficiently to the white matter DTI-metrics and were therefore not selected for the final model.
When restricting the analysis to the HIV+ group, the number of antihypertensive medications used remained significantly associated. Additionally, higher LDL-cholesterol and duration spent with CD4+ cell count below 500 cells/μl, were significantly associated with higher WMMD (Table 3: Model 2). Patients who had been treated with mono- or dual therapy with nucleoside reverse transcriptase inhibitors before the start of cART showed significantly higher WMMD (P = 0.04). However, this effect was confounded by duration spent with CD4+ cell count below 500 cells/μl and did not remain significant. No collinearity was found between age or volume and the determinants.
Voxel-wise correlation analyses by TBSS showed a diffuse pattern of significantly increased mean diffusion with longer duration spent with a CD4+ cell count below 500 cells/μl (Fig. 2). This relation was found in projection and thalamic fibres, all major association fibres, limbic system fibres and callosal fibres.
Altered white matter diffusion properties and its association with cognitive performance
Sixteen percentage of the HIV+ patients were classified as cognitively impaired by MNC (alpha was 5%, one-tailed, assuming a specificity of 95%, which was previously verified) . Comparing cognitively impaired and cognitively unimpaired HIV+ patients, no significant differences in WMFA (P = 0.82) or WMMD (P = 0.91) were found. Overall poorer cognitive performance was not associated with WMFA (ß = 0.007, P = 0.82, η2 < 0.001) or WMMD (ß = –0.051, P = 0.61, η2 = 0.003).
Repeating the analyses on the normal appearing white matter
All findings on WMFA and WMMD alterations persisted after excluding white matter lesion areas from the analyses (including effects of HIV serostatus, the number of antihypertensive medications used, LDL-cholesterol and duration spent with CD4+ cell count below 500 cells/μl). See supplementary Results and Tables 1 and 2, http://links.lww.com/QAD/A820.
In this study, cerebral white matter structure was assessed in 100 middle-aged HIV+ men with well suppressed viral load on cART and compared with 70 HIV-uninfected, but otherwise highly comparable, controls. We found significant white matter structure alterations in HIV+ patients, which consisted of lower fractional anisotropy and higher mean diffusion, as assessed by DTI. TBSS showed that these effects were widespread throughout the brain. Additionally, deleterious effects of hypertension, dyslipidaemia and duration of past immune deficiency were found. HIV-associated cognitive deficits were not found to be associated with white matter structure alterations.
Interpretation of findings
The diffuse pattern of altered diffusion properties found in HIV+ patients relative to highly comparable HIV-uninfected controls may indicate subtle but widespread white matter injury. Consistent findings of alterations in fractional anisotropy and mean diffusion have been reported previously in middle-aged and older HIV+ patients compared with healthy controls [14,16,19,22,23,26,27,29,30,33,34,36]. The origin of the subtlety of our findings compared with previous studies may be two-fold. First, all HIV-patients in our cohort were adequately treated on cART. Second, healthy controls were carefully matched on lifestyle and comorbid disease. Comparing to previous work, one might infer that improved treatment diminishes HIV-induced white matter structure alterations. The fact that two comparable studies which exclusively included aviraemic HIV+ patients did not report white matter structure alterations might be due to smaller sample sizes as compared with our study [35,39]. Furthermore, one of the studies also excluded all possible comorbidities  and therefore may have excluded HIV effects, as HIV itself has been reported to be independently associated with cardiovascular disease and many other comorbidities .
In addition to the effects of HIV serostatus and ageing, we found independent associations of hypertension and dyslipidemia with white matter structure alterations. Effects of hypertension were particularly consistent, which might be partly HIV-mediated, as increased cardiovascular risk has been frequently reported in HIV . Evidence for possible accelerated CNS ageing could not be derived from this cross-sectional analysis. Follow-up measurements are currently underway and may provide more insight into a possible interaction effect of age and HIV serostatus on white matter structure alterations in adequately treated HIV+ patients.
The total duration of immune deficiency (i.e. the number of years spent with CD4+ cell count lower than 500 cells/μl) was also strongly associated with white matter structure alterations. This may reflect irreversible damage that has occurred during immune deficiency by both direct viral and host-derived proinflammatory factors. Previously reported persistent white matter injury in HIV+ patients with partial immune reconstitution, provides evidence that such damage could be permanent in nature . Moreover, the use of cART and higher current CD4+ cell counts have been associated with higher fractional anisotropy values , suggesting that prevention of immune deficiency may avert irreversible white matter structure damage.
Among HIV+ patients in the cART-era, effects of cumulative exposure to immune deficiency are possibly insufficiently captured by the nadir CD4+ cell count [33–35,39,40]. Subtle white matter structure alterations may be better captured by a measure of cumulative exposure to immune deficiency, as used in this study. These findings provide additional support for the current HIV treatment guidelines that stress the importance of preventing immune deficiency and initiating antiretroviral therapy in all patients irrespective of CD4+ cell count .
Pretreatment with nucleoside-analogue reverse transcriptase inhibitors before the start of cART was associated with white matter structure injury, but this relationship seemed to be driven by the duration of past immune deficiency. This is compatible with HIV+ patients diagnosed in the pre cART era to have been more likely to have experienced more prolonged periods of advanced immune deficiency.
Although associations between systemic markers of immune activation and inflammation (i.e. sCD14 and sCD16) with white matter structure alterations were not observed, ongoing proinflammatory reactions within the CNS affecting white matter structure cannot be ruled out. Postmortem studies have reported persistent levels of elevated markers of microglia/macrophage activation in cART treated HIV cases , suggesting proinflammatory reactions may not be normalized in the context of cART and that the continued presence of neuro- and myelinotoxic cytokines may induce subtle white matter alterations, such as those observed in the current study.
Although several studies have previously reported white matter structure alterations to be related to HIV-associated cognitive impairment [24,27,28,31,34,37], others did not report such an relationship [26,30,35,39]. An association between white matter structure alterations and cognitive deficits was not observed in the current study. The magnitude of the effect of HIV-serostatus on cognition and white matter structure alterations in the current study was small; hence a possible relationship between the two would likely be subtle. Note that in absolute numbers, our group of 16 cognitively impaired patients is of comparable size to the CHARTER cohort, reporting 10 impaired patients . The successful treatment of HIV+ patients and exclusion of otherwise confounding factors are in our opinion key to the subtlety of effects we report. If white matter structure is to be used as a biomarker to predict cognitive impairment and subsequent deterioration in ageing HIV+ patients, then larger, multicentre cohorts with hundreds of patients are needed. Also, sufficient time between follow-up measurements is required in future studies, as cognitive decline was not related to a significant increase of mean diffusion in HIV+ patients after one year of follow-up .
The presence of white matter lesions of presumed vascular origin is associated with findings of white matter structure alterations . Greater microstructural alterations have been reported in HIV+ patients with white matter lesions, compared with HIV+ patients with no lesions . Although some studies have carefully reviewed the analysed regions for white matter lesions [15,26], we studied the NAWM separately by patient-wise excluding lesion areas. All effects persisted in whole brain measures.
Although controls enrolled in this study had very similar demographics and lifestyle, HIV+ patients reported more lifetime tobacco exposure and controls more ecstasy use. Moreover, although HIV+ patients had lower BMI, they fulfilled more often the criteria for central obesity, and showed increased monocyte activation (i.e. higher levels of soluble CD14) and lower CD4+/CD8+ ratio. Such vascular risk factors and increased immune activation are known complications of HIV-infection or its treatment. However, none of these parameters were related to white matter structure alterations in the current study. About one-third of HIV+ patients and controls were scanned on a different scanning system due to a scanner replacement. We have adjusted for the scanner effects by factoring its effects in the statistical model. When analysing the subset of patients on a single machine, the effects within HIV+ patients are persistent, the relation between CD4+ cell count less than 500 cells/μl and mean diffusion remains significant (beta = 0.26, P = 0.005). When comparing groups, effects sizes are of equal sign but slightly smaller, and P-values thus higher (fractional anisotropy: beta = –0.010, P = 0.19; mean diffusion: beta = 0.11, P = 0.09).
In this 3T DTI study, middle-aged HIV+ men with suppressed viraemia on cART showed pronounced white matter structure alterations as compared with highly comparable HIV-uninfected controls. The association with duration of exposure to immune deficiency suggests irreversible damage from previous periods of immune deficiency when host-inflammatory and virus toxicity were at their peak. In addition, independent associations between vascular risk factors and white matter structure abnormalities were found. Longitudinal follow-up studies are needed to determine the progression and synergistic effects of these risk factors.
We thank Merel Burgering for her assistance in MRI scanning. We thank Sandra van der Berg and Raschel Snoeks for their help considering MRI contraindications. We thank Paul Groot for his support concerning data transport and storage. Above all, we gratefully acknowledge all study participants for their co-operation.
This work was supported by the Nuts-OHRA Foundation (grant no 1003–026), Amsterdam, The Netherlands, as well as by The Netherlands Organisation for Health Research and Development (ZonMW) together with AIDS Fonds (grant nos 300020007 and 2009063, respectively). Additional unrestricted scientific grants were received from Gilead Sciences, ViiV Healthcare, Janssen Pharmaceutica N.V., Bristol-Myers Squibb, Boehringer Ingelheim, and Merck & Co.
None of these funding bodies had a role in the design or conduct of the study, the analysis and interpretation of the results, or the decision to publish.
T.S.: Collected study data, performed statistical analysis and the literature search, and drafted the manuscript.
M.C.: Processed the MRI data, supervised MRI data analysis, contributed to the data interpretation, and contributed to the writing of the manuscript.
F.W.: Contributed to the study design, supervised statistical analysis, contributed to data interpretation, and critically reviewed and revised the manuscript.
J.S.: Contributed to data collection, data interpretation, and critically reviewed and revised the manuscript.
G.G.: Contributed to data interpretation and critically reviewed and revised the manuscript.
J.C.: Contributed to data interpretation and critically reviewed and revised the manuscript.
D.S.: Contributed to data interpretation and critically reviewed and revised the manuscript.
F.V.: Contributed to the study design, data interpretation, and critically reviewed and revised the manuscript.
M.P.: Contributed to the study design, data interpretation, and critically reviewed and revised the manuscript.
P.P.: Contributed to study design, data interpretation, and critically reviewed and revised the manuscript.
P.R. conceived the main cohort study and the sub-study, obtained study funding, contributed to both study designs, to data interpretation, and critically reviewed and revised the manuscript.
C.M.: Conceived the sub-study and obtained study funding, contributed to its design, data interpretation, and critically reviewed and revised the manuscript.
Study funding: This work was supported by the Nuts-OHRA Foundation (grant no 1003-026), Amsterdam, The Netherlands, as well as by The Netherlands Organisation for Health Research and Development (ZonMW) together with AIDS Fonds (grant nos 300020007 and 2009063, respectively). Additional unrestricted scientific grants were received from Gilead Sciences, ViiV Healthcare, Janssen Pharmaceutica N.V., Bristol-Myers Squibb, Boehringer Ingelheim, and Merck&Co.
None of these funding bodies had a role in the design or conduct of the study, the analysis and interpretation of the results, or the decision to publish.
Disclosures: T.S. has received travel grants from Boehringer Ingelheim.
M.C. has received travel grants from Boehringer Ingelheim.
F.W. has received travel grants from Gilead Sciences, ViiV Healthcare, Boehringer Ingelheim, Abbvie, and Bristol-Myers Squibb.
J.S. has received travel grants from Gilead Sciences, ViiV Healthcare, and Boehringer Ingelheim.
D.S. is funded by a National Institute of Health Research Professorship (NIHR-RP-011-048) and has received an investigator-led grant from Pfizer, unrelated to the current work.
P.P. has been an ad hoc advisor to or speaking at various events sponsored by ViiV Healthcare, Gilead Sciences, Abbvie and Bristol-Myers Squibb.
P.R. through his institution has received independent scientific grant support from Gilead Sciences, Janssen Pharmaceuticals Inc., Merck&Co, Bristol-Myers Squibb, Boehringer Ingelheim and ViiV Healthcare, and travel support through his institution from Gilead Sciences and Janssen Pharmaceuticals Inc. In addition he has served on a scientific advisory board for Gilead Sciences and serves on a data safety monitoring committee for Janssen Pharmaceutica N.V., for which his institution has received remuneration.
Conflicts of interest
C.M., G.G., J.C., F.V. and M.P. have no conflicts of interest.
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aging; antiretroviral therapy; cerebral white matter; diffusion tensor imaging (DTI); HIV-1-infection; HIV-associated neurocognitive disorders (HAND); neuropsychological assessment
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