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This study examined the interactive effects of cerebrovascular risks, advancing age, and HIV infection on neurocognition, and explored whether pharmacological treatment of cerebrovascular risk factors attenuated neurocognitive dysfunction. Participants included 98 HIV-seropositive adults (cerebrovascular risk: 23.5%; age >50: 27.6%). Cerebrovascular risk was associated with slower processing speed even after controlling for age effects (b = −2.071; p = .04), and the interaction of age and cerebrovascular risk was associated with poorer verbal fluency (b = 1.276, p = .002). Participants with pharmacologically untreated cerebrovascular risk demonstrated reduced processing speed, learning/memory, and executive functioning relative to those on medication. Poor cerebrovascular health confers significant risk for HIV+ individuals, and this effect may be of greater consequence than advancing age. The cognitive impact of risk appears to be more pronounced in the absence of adequate pharmacological treatment.
Approximately 50% of HIV-infected individuals will experience some form of neurocognitive decline during the course of their illness (Bloom & Rausch, 1997), including impaired motor skills, executive systems inefficiencies, and slowed information processing as well as decrements in daily living skills (Albert et al., 1995; Heaton et al., 2004; Hinkin et al., 2002; Marcotte et al., 1999). The profile of neurocognitive impairment in HIV has most commonly been interpreted as reflecting a frontal-subcortical pathogenesis (Heaton et al., 1995; Woods, Carey, Troster, Grant, & HNRC Group, 2005), although abnormalities in memory function may be secondary to medial temporal disruption (Castelo, Sherman, Courtney, Melrose, & Stern, 2006; Moore et al., 2006). HIV-associated neurocognitive decline has also been associated with diffuse white matter pathology (Hawkins, McLaughlin, Kendall, & McDonald, 1993; McArthur et al., 1990; Navia, 1997).
Older HIV-infected individuals may be particularly at risk for cognitive compromise (Goodkin et al., 2001; Hinkin et al., 2004; Valcour, Shikuma, Watters, & Sacktor, 2004b), as they show poorer cognitive performance than their younger counterparts, including reduced executive functioning, verbal and visual memory, and motor speed (Sacktor et al., 2007). Clinical outcome appears to be worse in older HIV+ adults relative to younger patients, in that older HIV+ patients demonstrate a shortened time between HIV infection and AIDS diagnosis, a higher mortality rate following an AIDS diagnosis, and a briefer latency between AIDS diagnosis and onset of dementia (Butt et al., 2001; McArthur et al., 1993). HIV-related neurocognitive deficits closely resemble normal aging processes as well as the neurocognitive sequelae of other subcortical dementias, a factor that complicates differential diagnosis (Van Gorp, Mitrushina, Cummings, Satz, & Modesitt, 1989). Results from our laboratory have demonstrated that aging exacerbates the neurocognitive effects of HIV infection, particularly among patients who have progressed to AIDS (Hardy et al., 1999), and that the combined effects of older age and neurocognitive decline are associated with poorer medication adherence (Hinkin et al., 2004).
HIV-infected individuals also show a higher prevalence of cerebrovascular risk factors (including myocardial infarction, coronary heart disease, diabetes, hypertension, obesity, and atherosclerosis) than their seronegative counterparts (Adeyemi, 2007; Hsue et al., 2004; Lebech et al., 2007; Magalhães, Greenberg, Hansen, Odont, & Glick, 2007; Tipping, Villiers, Wainwright, Candy, & Bryer, 2007; Triant, Lee, Hadigan, & Grinspoon, 2007). Studies have demonstrated that acute myocardial infarction rates are higher in HIV+ participants when compared to age-matched seronegative controls (11.13% vs 6.98%; Triant et al., 2007). Other work (Magalhães et al., 2007) has shown hypertension to be the second most common comorbidity (after hepatitis C virus) in HIV infection, with a prevalence rate of 41.4%. Finally, Hsue and colleagues (2004) documented increased markers of coronary artery disease (intima-media thickness; IMT) among HIV-infected adults compared to controls. Taken together, these studies suggest that cerebrovascular risks among HIV-seropositive individuals are highly prevalent. A variety of factors have been postulated to contribute to the increased prevalence of cerebrovascular disease in HIV. These include the adverse effects of antiretroviral therapy (Adeyemi, 2007; Bergersen, 2006; Lorenz et al., 2008), advancing age (Goodkin et al., 2001; Mary-Krause et al., 2003; Valcour et al., 2004b), and the direct impact of HIV infection (Adeyemi, 2007; Hsue et al., 2004; Lorenz et al., 2008; Magalhães et al., 2007; Triant et al., 2007).
Since the advent of Highly Active Antiretroviral Therapy (HAART) in the late 1990s, the prevalence of cerebrovascular risks among the HIV-infected population has steadily increased due in part to the dyslipidemic effects of protease inhibitors (PI; Bergersen, 2006; Data collection on adverse events of anti-HIV drugs [DAD], 2003; Mary-Krause et al., 2003). Recent investigations have indicated a 26% rise in myocardial infarction (MI) per year during antiretroviral treatment (DAD, 2003), and a twofold increase of MI among PI-treated patients. The increased risk for cerebrovascular disease in PI-treated patients may be attributable to lipid abnormalities and increased IMT. These metabolic changes subsequently lead to atherosclerosis and myocardial infarctions among other risk factors for cerebrovascular compromise (Mary-Krause et al., 2003).
Advancing age also confers increased risk for cerebrovascular disease in HIV and is associated with high rates of hypertension (Bergersen, 2006; Magalhães et al., 2007) and myocardial infarction (MI; Mary-Krause et al., 2003; DAD, 2003; Triant et al., 2007). One study demonstrated a 42% increased risk of MI risk for each 10-year incremental increase in age (Mary-Krause et al., 2003). Older HIV-infected patients may also be particularly vulnerable to cerebrovascular disease (Triant et al., 2007), and when considering the rapidly advancing age of the HIV-infected populace due to longer survival (Goodkin et al., 2001; Mary-Krause et al., 2003; Valcour et al., 2004b) it is reasonable to anticipate that prevalence of cerebrovascular compromise will continue to rise.
Finally, many studies have attributed the high prevalence of cerebrovascular disease to the primary effects of HIV infection. In particular, HIV may directly give rise to conditions including hypertension (Magalhães et al., 2007; Mu, Chai, Lin, Yao, & Chen, 2007), atherosclerosis (Lorenz et al., 2008; Mu et al., 2007), diabetes, dyslipidemia, acute MI (Triant et al., 2007), and increased IMT (Hsue et al., 2004).
It is well established that cerebrovascular risk factors and disease in non-infected adults contribute to cognitive impairment and dementia (Erkinjuntti, 2005; Gregg et al., 2000; Gunstad et al., 2007) and tend to produce deficits in executive function, processing speed, motor function, and memory (Sacktor et al., 2007). Magnetic resonance imaging (MRI) and computerized axial tomography (CT) of patients with vascular illness indicate extensive white matter lesions (Erkinjuntti, 2005). However, the neurocognitive consequences of cerebrovascular risks among aging HIV-infected individuals are less well established. In the post-HAART era, vascular effects of medication and advancing age may serve to explain the rising prevalence of cerebrovascular disease among HIV-infected individuals (Bergersen, 2006; Mary-Krause et al., 2003), thus supporting a likely continued rise in the future. Therefore investigation of the neurocognitive consequences of this evolving illness is highly pertinent.
The differential impact of age and cerebrovascular risk in HIV-positive individuals remains unknown. The primary aim of the present study was therefore to examine the effects of cerebrovascular disease and age as predictors of cognitive functioning in an HIV cohort. Since these factors have generally been associated with similar patterns of fronto-subcortical dysfunction, we expect both of these contributions to predict greater cognitive dysfunction. In contrast, we expect language function to be preserved. A secondary aim was to examine whether pharmacological treatment of cerebrovascular risk factors influences differences between at-risk seropositive participants and seropositive controls across cognitive domains.
Participants included 98 HIV-seropositive (HIV+) adults who were recruited from community agencies and medical centers within the Los Angeles area. We excluded people presenting with a history of a psychiatric episode (mania, depression, psychosis, delirium) within the past year or alcohol/illicit substance abuse or dependence within the last month, based on results of neuropsychiatric data collected using the Structured Clinical Interview for DSM-IV, Axis I Disorders (SCID; First, Spitzer, Gibbon, & Williams, 1995) and the Beck Depression Inventory, second edition (BDI-II; Beck, Steer, & Brown, 1996). Participants were also excluded if they presented with history of CNS opportunistic infection, traumatic brain injury with loss of consciousness greater than 30 minutes, or with medical comorbidities apart from HIV, which are believed to affect cognitive function (e.g., anoxia, kidney dysfunction, seizures, or hepatitis C virus). Individuals presenting with known cerebrovascular events, such as transient ischemic attacks and cerebrovascular accidents, were also excluded.
The mean age for the total sample was 44.2 (7.6) years and the mean education level was 13.1 (1.9) years. For the total sample, 80.6% were male and most (70.4%) participants were African American. History of opportunistic infection was present in 42.9% of the sample, and 62.5% were diagnosed with AIDS based on history of an opportunistic infection or CD4 count less than 200. The mean natural log (Ln) nadir CD4 count was 4.6 (1.4) and the mean Ln highest viral load was 11.1 (2.2). The mean Ln current CD4 count was 5.8 (0.8) and the mean Ln current viral load was 8.1 (2.4). See Table 1 for demographic descriptive statistics within cerebrovascular (risk/no risk) and age (younger/older) groups.
There were significant gender differences for the cerebrovascular risk groups, and notably there was only one female in this at-risk subgroup. No significant differences (p= .06) were found in level of self-reported depression based on BDI-II total scores, with individuals without risk demonstrating trend increases in depression (12.4[9.6]) when compared to individuals with risk (8.3[7.6]). There were no differences (p > .05) between individuals with and without risk factors on age, education, ethnicity, CD4 count, or viral load. Furthermore, chi-square tests indicated no differences in the proportion of prior history of substance abuse or dependence or prior history of psychiatric illness for the cerebrovascular risk groups, or for cerebrovascular-risk pharmacological treatment groups. Age was coded dichotomously (younger < age 50, older ≥ age 50) for ANOVA tests only, resulting in 71 individuals in the younger group and 27 individuals in the older group. In contrast, we used a continuous age variable for all other analyses. Chi-square tests indicated no differences in the proportion of prior history of substance abuse or dependence for the age groups. However, the younger participants had higher rates of past psychiatric disorder (74% younger, 26% older; chi-square: 5.32; p= .02). Despite this, there were no age group differences in current depressive symptomatology based on the BDI-II.
Individuals were classified as having cerebrovascular risk based on self-report of one or more of the following medical conditions: diabetes, hypertension, myocardial infarction, or congestive heart failure. In the present sample only hypertension and diabetes were present; 6 participants presented with diabetes, and 17 presented with hypertension, totaling 23 participants with risk factors for cerebrovascular disease. These conditions are strongly associated with cerebrovascular disease, with hypertension acting as a major risk factor for a variety of cerebrovascular conditions including stroke, vascular dementia, and Alzheimer’s disease (Elias, D’Agostino, Elias, & Wolf, 1995; Meyer, Rauch, Rauch, Anwarul, & Crawford, 2000; Waldstein, Giggey, Thayer, & Zonderman, 2005), and with diabetes often precipitating both vascular dementia and Alzheimer’s disease (Schnaider Beeri et al., 2004; Xu, Qiu, Wahlin, Winblad, & Fratiglioni, 2004). Of the total sample, 25.9% of the older participants and 22.5% of the younger participants presented with cerebrovascular risk factors.
Pharmacological treatment of cerebrovascular risks was assessed. At-risk participants taking any of the following medication classes were considered to be pharmacologically treated: for hypertension, treatment agents included diuretics, vasodilators, cardioinhibitory medications, centrally acting sympatholytics; for diabetes, treatment agents included insulin, sufonylureas, alpha-glucosidase inhibitors, biguanides, meglitinides, and thiazolidinediones. A total of 10 at-risk individuals were pharmacologically untreated, and 13 were pharmacologically untreated. There were no significant differences between pharmacologically treated and untreated at-risk participants on any demographic or HIV immunological variable.
All participants completed a comprehensive neuropsychological test battery; the battery was administered by trained psychometrists and supervised by a board-certified neuropsychologist (CHH).
We assessed six domains of cognitive function. Verbal fluency was assessed with the Controlled Oral Word Association Test (including FAS and Animal Naming; Benton & Hamsher, 1983). Executive functioning was assessed with the Trail Making Test, Part B (Reitan & Wolfson, 1993), the Booklet Category Test, number of errors (DeFilippis & Campbell, 1997), and the Stroop Color and Word Test, Interference (Stroop, 1935). Processing speed was assessed with the Trail Making Test, A (Reitan & Wolfson, 1993), the Stroop Color and Word Test, Word, and the Stroop and Word Test, Color (Stroop, 1935), and the Digit Symbol Modalities Test (Smith, 1991). Attention and working memory was assessed with the Paced Auditory Serial Addition Test (PASAT) Total (Gronwall, 1977), and the WAIS-III Digit Span Total Score (Wechsler, 1997). Learning and memory were assessed with the California Verbal Learning Test (CVLT) List A Trial 1, CVLT Trials 1–5 Total, CVLT Short Delay Free Recall, and CVLT Long Delay Free Recall (Delis, Kramer, Kaplan, & Ober, 1987). Motor functions were assessed with the Grooved Pegboard dominant and nondominant hands (Matthews & Klöve, 1964).
Raw scores from all measures were standardized using the mean and standard deviation from the total sample for each cognitive test using ([raw score − M/SD] * 15+100). This approach was selected rather than employing age-adjusted norms in order to examine the effects of age in the regression model. We also report the results of follow-up tests using demographically adjusted normative data. Domain scores were then calculated using the mean of the computed standardized scores for cognitive tests within each domain.
Analyses for the present study were conducted utilizing SPSS v15.0. Expectation maximization (EM) was used to impute missing data (1.2% of total data points). Domain variables were centered to a mean score of zero for regression analyses.
We report results using sample-standardized scores rather than demographically corrected T scores, given several factors that are described in detail below which serve to circumvent concerning challenges. First, the demographic standardization of measures across cognitive domains diverges in important ways in terms of (a) the characteristics of their respective normative samples, and (b) the extent of demographic corrections made (i.e., some age only, some age, gender, ethnicity, and education), which could confound results of the domain comparisons. Furthermore, since age is included within our model, we believe that employing additional age corrections would potentially mask important age findings, since this would entail a double correction for age. Although our results did not yield significant age effects over those attributable to cerebrovascular risk, employing age corrections in this manner may create the appearance that our lack of age findings could be related to our overcorrection for this phenomenon of interest. As it stands currently, we have greater confidence that the cerebrovascular effects are above those attributable to age. Recent work has also argued against employing demographic corrections in neuropsychological research altogether, since they may bias results and reduce sensitivity to biological differences in both brain structure and function (Brandt, 2007), and age adjustments in particular may have negative effects on diagnostic validity (Mungas, Reed, Farias, & DeCarli, 2009). It has also been argued that diagnostic accuracy may be improved with unadjusted raw test scores (Kraemer, Moritz, & Yesavage, 1998). Finally, since some investigators have proposed that “normal” age-related effects may actually be highly dependent on microvascular change (Raz & Rodrique, 2006), controlling for age in this manner might have the unintended effect of controlling for cerebrovascular problems (Erkinjuntti, 2005). Since our study was not designed to compare synergistic effects of age and risk factors with those found in the general population (as we did not use a control group), but rather to characterize the effects of these factors within an HIV+ subpopulation, we believe that an examination of absolute differences in function would be most appropriate. For these reasons, we elected to retain the sample-standardized demographically uncorrected scores in our analyses.
A multiple regression method was selected in order to determine whether age (a continuous variable) versus risk significantly contributed to the model independently of the second variable, and this procedure was carried out for each cognitive domain. Hierarchical multiple regression analyses (entering age and presence of risks in the first step and the age*risk composite score in the second step) were then conducted for all cognitive domains. All analyses were re-run after controlling for prior history of stimulant use or psychiatric diagnosis, immunological status, duration of HAART treatment, and gender in order to evaluate the influence of these potential confounds.
Separate hierarchical multiple regression analyses (simultaneously entering age, cerebrovascular risk, and the interaction term) were conducted for each of the six cognitive domains to examine the independent effects of age and cerebrovascular risk factors on neurocognitive functioning (see Table 2). Of the predictor variables, cerebrovascular risk was significantly correlated with age, although the level of correlation was minimal (r= .20; p= .04). For the processing-speed domain, the regression model was significant when age and risk factors were entered into the first step (R Square= .81; p= .02). When these predictor variables were considered simultaneously, only presence of cerebrovascular risk was a significant predictor of processing speed (B= −0.21, p= .04). In the second step of the analysis, the age*risk interaction term failed to reach significance. For the verbal fluency domain, while we did not find significant main effects for age or cerebrovascular risk, the interaction term was significant (R Square= .11, p= .01; age*risk interaction: B= 1.28, p= .002). We did not achieve statistical significance in conducting the follow-up simple effects tests for the domain of verbal fluency due to a reduction in power that resulted when the groups were split. It has been reported that testing for simple effects is not always necessary for understanding interactions, since the interaction is interpretable in its own right. A simple main effect rather considers one single level of the moderator variable and examines the effect of the independent variable at that level (Jaccard & Turrisi, 2003). Although non-significant, the results of the follow-up tests demonstrated that older HIV-positive adults (96.36[13.52]) performed more poorly than younger HIV-positive adults (101.47[12.66]), and that HIV+ individuals with cerebrovascular risks (98.52[13.74]) performed more poorly than HIV+ individuals without cerebrovascular risks (100.54[12.89]) on verbal fluency. There was greater impact of cerebrovascular risks for the younger group with non-significant trend findings (p > .05) indicating higher verbal fluency performance for younger HIV+ adults without cerebrovascular risk factors (102.50[13.06]) than for younger HIV+ individuals with cerebrovascular risk factors (97.92[10.80]). Such a pattern of poorer verbal fluency performance among those with cerebrovascular risks was not evident for the older group. Notably, as noted above, we did not achieve significant main effect results for either age group.
No significant results were obtained in the regression models (main effects or age*risk interactions) for the domains of attention, learning and memory, executive functioning, or motor functioning. Regression findings described above remained consistent when controlling for the effects of psychiatric or stimulant use history, gender, immunological variables, and duration of HAART treatment.
Follow-up ANOVA analyses (see Table 3) were conducted within the cerebrovascular risk group to determine whether participants with diabetes or hypertension performed better when these illnesses were treated than pharmacologically untreated participants across cognitive tasks. There were no differences between pharmacologically treated versus untreated HIV+ participants on past history of psychiatric illness or substance abuse, immunological status (opportunistic infections, recent/highest viral load, recent/nadir CD4 count, AIDS status), or demographic variables including age and education. Results were significant for processing speed and learning/memory. For the processing-speed domain, the treated participants performed better than the untreated participants (F= 7.78; p= .01; partial η2= 0.27). For the learning/memory domain, again the untreated participants performed better than the untreated participants (F= 4.66; p= .04; partial η2= 0.18). For the executive functioning domain, a trend was shown with the untreated participants performing better than untreated led participants (F= 3.16; p= .09; partial η2= 0.13). ANCOVA analyses (controlling for stimulant use) again indicated processing-speed differences between treated and untreated cerebrovascular-at-risk participants (F= 4.74; p= .04; partial η2= 0.19). Due to issues related to reduced power, findings no longer reached significance for the learning/memory domain, despite apparent differences in mean values on visual inspection (untreated mean= 90[12.5], treated mean= 103[15.4]).
Given these findings, we then sought to establish whether more robust cognitive differences would be found when comparing pharmacologically untreated at-risk participants to seropositive controls (see Table 4). Significant differences were found on processing speed (F= 16.02; p < .001; partial η2= 0.15), learning/memory (F= 7.49; p= .008; partial η2= 0.08), and executive functioning (F= 5.15; p= .03; partial η2= 0.05). For the processing-speed domain, HIV-infected participants with untreated risk factors performed less well than infected participants without risk factors (F= 16.021; p < .001; partial η2= 0.15). For the learning/memory domain, HIV-infected participants without untreated risk factors performed less well than infected participants without risk factors (F= 7.488; p= .008; partial η2= 0.08). Finally, for the executive functioning domain, HIV-infected participants with untreated risk factors performed less well than infected participants without risk factors (F= 5.147; p= .03; partial η2= 0.05). Follow-up ANCOVA analyses (controlling for history of stimulant abuse or dependence) again demonstrated these findings, with reduced processing speed (F= 14.97; p < .001; partial η2= 0.17), learning/memory (F= 8.31; p < .01; partial η2= 0.10), and executive functioning (F= 4.80; p= .03; partial η2= 0.06) among untreated cerebrovascular-at-risk participants when compared to at-risk participants with adequate pharmacological treatment.
The present study sought to investigate the differential impact of age and cerebrovascular risk factors on neurocognitive function in HIV-infected individuals. A secondary but related aim was to determine whether pharmacological treatment of cerebrovascular risks mitigated cognitive dysfunction. To our knowledge the present study is the first to address whether cerebrovascular risks are particularly deleterious to neurocognitive function in an HIV-infected sample, although this is well established in the aging and dementia literature. We hypothesized that increased age and the presence of cerebrovascular risks in HIV-positive individuals would be associated with greater fronto-subcortical dysfunction.
Results indicated that cerebrovascular risk factors are predictive of processing-speed declines in HIV+ participants, above and beyond the effects of age. Our findings therefore suggest that the relative contribution of cerebrovascular illness to processing-speed reduction may be greater than that of age alone within HIV-positive populations. These results are consistent with previous literature, which has documented the effects of cerebrovascular risk factors and disease on frontal-subcortical cognitive functioning in healthy older adults and in dementing populations (Erkinjuntti, 2005; Gregg et al., 2000; Gunstad et al., 2007; Sacktor et al., 2007). Neuroimaging of patients with vascular illness frequently reveals subcortical lesions, even in the absence of clinically documented cerebrovascular insults (Erkinjuntti, 2005), which may have the effect of slowing speed of neuronal transmission thus precipitating slowing of information processing speed. Furthermore, compared to reports in the general population, white matter lesions are more common among HIV-seropositive individuals, and are suggested to increase with age but not with higher levels of HIV-related CNS pathology. Based on these considerations, it has been posited that cerebrovascular disease plays an even greater role in the cognitive compromise of aging HIV-infected individuals when compared to the normal aging population (McMurtray et al., 2007). Moreover, a recent study demonstrated that white matter hyperintensities generally caused by small-vessel ischemic disease were more prevalent in HIV-seropositive individuals with greater mean systolic blood pressure (mm Hg). The frontal lobes were most significantly affected, with reduced cortical volume in those with moderate white matter hyperintensities (McMurtray et al., 2008).
The interaction between age and risk did not significantly contribute to processing-speed reductions. Our inability to document an age-risk interaction effect for this variable could reflect the fact that cerebrovascular risks are of greater importance than age, and/or account for a portion of the age effects. There is, however, mounting evidence for age-related (Hartley, Speer, Jonides, Reuter-Lorenz, & Smith, 2001; Petersen, Smith, Kokmen, Ivnik, & Tangalos, 1992; West, Ergis, Winocur, & Saint-Cyr, 1998; Willis, 1996; Winocur, Moscovitch, & Stuss, 1996), cerebrovascular-related (Gregg et al., 2000; Gunstad et al., 2007; Sacktor et al., 2007), and HIV-related changes in fronto-subcortical neurocognitive functioning (Levine, Stuss, & Milberg, 1997; Sacktor et al., 2007; Stuss, Craik, Sayer, Franchi, & Alexander, 1996), alongside evidence of subcortical pathology and inefficient frontal lobe functioning in older adults (Boone et al., 1992; Schacter, Savage, Alpert, Rauch, & Albert, 1996), individuals with cerebrovascular risks (Erkinjuntti, 2005; Gregg et al., 2000; Gunstad et al., 2007), and HIV-positive people (Hinkin et al., 1995; McArthur et al., 1990; Navia, 1997; Navia, Jordan, & Price, 1986). Therefore a shared neuroanatomical substrate has been identified which could be particularly vulnerable to the combined effects of these factors. Previous research has also shown that older adults with medical problems are at greater risk for cognitive dysfunction (Uchiyama, Mitrushina, Satz, & Schall, 1996), and thus older individuals with HIV/AIDS and cerebrovascular risks might be anticipated to be at even greater risk for neurocognitive impairment. Despite these observations, the literature has yet to establish a synergistic effect of age and cerebrovascular risks on processing speed, and our lack of an interaction finding may reflect the relatively greater importance of risk for cerebrovascular compromise to neurodegeneration.
It is also possible that the unequal sample sizes in older and younger groups (n= 71 in the younger group and n= 27 in the older group) may have contributed to the absence of an age–risk interaction for the processing-speed domain in this study. The lack of effect may also be explained by the greater number of younger than older individuals presenting with cerebrovascular risk, which could dilute any potential interaction. It should also be noted that the age range of our sample was somewhat truncated (from 32 to 69 years of age), particularly for the older participants (from 50 to 69 years of age). Therefore, the effect of age on processing speed in this study may have been underpowered, as it is well accepted that significant cognitive deterioration becomes more apparent in later decades. Larger samples with broader representation of the age spectrum will be necessary to determine whether the combined effects of HIV infection, risk factors, and older age contribute to cognitive decline.
Results did reveal an interaction effect between age and cerebrovascular risk factors on the verbal fluency domain, although a greater impact of cerebrovascular risks on verbal fluency function was demonstrated for the younger (rather than older) HIV-infected group. The inability to document greater deficits among HIV-infected individuals affected by the combined impacts of cerebrovascular risk and older age is surprising, given that both factors in isolation have been shown to reduce frontal-striatal cognitive function (as described in further detail above). It is possible that the additive effects of these conditions are obscured due to the overlapping nature of these two processes. Nevertheless, it is believed that deficits in working memory and processing speed underlie age-related decline on measures of verbal fluency (Borstein et al., 1992; Bryan & Luszcz, 2000; Sacktor et al., 2007; Sheline et al., 2006), and current findings may therefore be related to the processing-speed main effect described above. Previous investigation of verbal fluency within the broader HIV-infected population is well in line with our current results, and has demonstrated deficits in verbal fluency among individuals with HIV when compared to controls (HIV+ < HIV−; Bornstein et al., 1992; Iudicello et al., 2007, 2008; Levine, Berger, Didona, & Duncan, 1992; Marsh & McCall, 1994). Moreover, various cerebrovascular risk factors, including diabetes mellitus, HTN, and cardiac disease, have been shown to affect verbal fluency (Backman et al., 2004; Brady, Spiro, & Gaxiano, 2005; Brady, Spiro, McGlinchey-Berroth, Milberg, & Gaziano, 2001; Verhaeghen, Borchelt, & Smith, 2003; Wahlin, Nilsson, & Fastborn, 2002) and, in one study in particular, the strongest relationship of risk to cognitive outcomes in general was demonstrated for verbal fluency performance (Brady et al., 2001). It also appears that higher number of cardiovascular risk factors (including age, blood pressure, diabetes mellitus, current cigarette smoking, and cardiovascular disease) is related to greater decline in verbal fluency performance (Brady et al., 2001). Moreover, both phonemic and semantic components of verbal fluency have been associated with cerebrovascular risk factors. In particular, several studies of diabetes mellitus (Vanhanen et al., 1997; Verhaeghen et al., 2003; Wahlin et al., 2002) have shown impairment in phonemic fluency to be more pronounced than impairment in semantic fluency, even after accounting for preclinical dementia and impending death (Wahlin et al., 2002). However, in the case of older untreated hypertensive participants, impairment in semantic fluency in the absence of phonemic fluency has also been implicated (Brady et al., 2005). Our results suggest that among younger HIV-specific participants, cerebrovascular risks are associated with combined semantic and phonemic verbal fluency decrements, and this finding is consistent with prior studies of seronegative participants. Given that this represents the first study to address the effects of aging and cerebrovascular risk within an HIV-infected sample, these results should be interpreted with caution and further evidence will be necessary to provide support for the findings reported here.
While we did not specifically examine the independent cognitive effects of cerebrovascular conditions of interest (e.g., diabetes versus hypertension) due to our sample size limitations, it should be noted that diabetes mellitus in particular has been implicated in studies of cognitive function among seropositive individuals. Even after adjusting for age and other vascular factors, research has revealed that diabetes is significantly associated with HIV-associated dementia (HAD), particularly in HIV patients over 60 years of age. Valcour and colleagues (Valcour et al., 2004a) have reported that fasting glucose levels were positively correlated with increasing neurocognitive impairment. Additionally, insulin resistance is a common complication in HIV and was found to be associated with neurocognitive impairment among older seropositive and seronegative patients. Strikingly, the level of neurocognitive impairment was similar to that of HAD (Valcour et al., 2006).
When we examined subgroup differences between pharmacologically treated versus untreated at-risk HIV-seropositive participants, we found significant differences in processing speed and learning/memory, and trend differences in executive functioning, with untreated HIV participants performing more poorly than untreated HIV participants. As a result we elected to investigate whether differences between participants with and without cerebrovascular risk would be more pronounced when including only untreated participants. Results of this follow-up analysis indicated significant group differences in processing speed, learning/memory, and executive functioning, with untreated at-risk individuals performing less well than seropositive controls in all cases. Effect sizes were more robust when pharmacological treatment of cerebrovascular risk was considered, in contrast to analyses comparing at-risk individuals to seropositive controls. See Figure 1 for an illustration of these results. Even when covarying for the effects of prior history of stimulant abuse or dependence, these results continued to remain significant. These results are particularly noteworthy, and suggest the important role of pharmacological intervention in preventing more severe frontal-subcortical cognitive dysfunction.
An important limitation to the current study concerns the self-reported nature of cerebrovascular risk determination. We recognize the importance of collecting blood sugar and serial blood pressure data for accurately evaluating the presence of cerebrovascular risk, and recommend that future research conduct rigorous medical confirmation of the presence of cerebrovascular risks. Although self-report methods have limitations with respect to validity, previous studies have reported high agreement between self-reported diagnosis and medical records (Azar, Murrell, & Mast, 2005; Bush, Miller, Golden, & Hale, 1989; Simpson et al., 2004). After researchers considered such factors as advanced age and existing cognitive impairment, excellent agreement remained between self-report and medical diagnosis among patients with cancer, stroke, myocardial infarction, and Parkinson’s disease (Simpson et al., 2004). Furthermore, we did not consider whether the duration of the medical condition associated with cerebrovascular risk affects results. Although it is possible that risk duration may influence cognitive outcomes, previous studies of diabetes have failed to reveal cross-sectional durational differences in neurocognitive performance on measures of learning, memory, and problem solving, or differences over 3 years across a variety of cognitive performances (Fischer, de Frias, Yeung, & Dixon, 2009; Ryan, 2005). Moreover, our cerebrovascular risk sample was limited to individuals with hypertension and/or diabetes only; other pertinent risks for cerebrovascular disease, such as obesity and sleep apnea, should be evaluated and the relative contributions of variant risks factors should be addressed. Future research should also employ larger samples with more evenly distributed groups in order to better evaluate the extent to which the effects of these three combined conditions are particularly deleterious. It should also be emphasized that our cerebrovascular risk group included only individuals with diabetes or hypertension, and clearly the scope of risk factors is far more extensive than this study could address. Including individuals with more diverse risk factors and examining differences between subsets of at-risk individuals will likely be revealing in identifying factors of greater or lesser consequence to cognitive compromise. We would also like to acknowledge the limitations associated with not having included a seronegative control group in this study. This investigation remains unequipped to selectively address effects that are specific to HIV, and rather centers on the broader study of cerebrovascular versus aging effects on cognition within the population of HIV+ individuals. Therefore future research should include a seronegative control group in order to better address possible synergistic effects of cerebrovascular risks and HIV illness on cognitive ability. Finally, as described earlier in detail, we elected to utilize sample-standardized raw scores in our analyses rather than demographically corrected standard scores, although we certainly appreciate the limitations associated with use of these unadjusted values. However, we believe that use of uncorrected scores reduces unintended masking of age findings attributable to over-correction for age, and is in line with previous work that has recommended use of unadjusted raw scores to improve diagnostic validity (Kraemer et al., 1998; Mungas et al., 2009), and sensitivity to differences in brain structure and function (Brandt, 2007). Despite these considerations, we appreciate that our study is unable to compare the synergistic effects of age and risk factors with those found in the general population.
The results from this study indicate a significant impact of cerebrovascular risk factors among HIV-infected individuals, and this effect may be of greater importance to processing-speed reductions than advancing age. The impact of cerebrovascular risk on cognitive functioning appears to be more pronounced and more widespread in pharmacologically untreated patients. The increasing presence of vascular risk factors such as hypertension and myocardial infarction among the HIV-infected population is likely to be attributable to treatment with HAART alongside the rising mean age of individuals with HIV (Bergersen, 2006; DAD, 2003; Goodkin et al., 2001; Mary-Krause et al., 2003; Valcour et al., 2004a). As individuals with HIV infection continue to age, the risk for small-vessel ischemic disease is likewise expected to rise, since one recent study demonstrated that, among HIV-seropositive individuals, age was found to be correlated with both decreased white matter lesion volume and leukoaraiosis severity (McMurtray et al., 2007). Given the similarities in symptom presentation, as persons with HIV/AIDS become older, the distinctions among normal age-related cognitive decline, HIV-associated neurocognitive impairment, vascular cognitive impairment, and other age-related dementias will become increasingly difficult to ascertain.
Generating a neuropsychological profile of cerebrovascular risk factors for HIV-positive individuals is especially important for practicing neuropsychologists, as it will facilitate identification of patients requiring additional monitoring. Neuropsychologists should be cognizant of the potential physiological compromises that can arise from the combination of HIV and cerebrovascular risks and should be alert to alterations and/or fluctuations in cognitive status that signal a cerebrovascular process warranting further medical evaluation (Marcotte, Grant, Atkinson, & Heaton, 2001). A clear understanding of the trajectory of neuropsychological compromise associated with HIV illness will allow neuropsychologists to examine whether existing impairments have been further exacerbated by cerebrovascular risk-related illnesses, and to help focus treatment efforts.
Furthermore, recognizing patients who might benefit from pharmacological treatment of cerebrovascular risks will be of vital importance in preventing additional neurocognitive compromise in an already vulnerable population. Clinical treatment of HIV-infected individuals should include a detailed review of vascular risk factors. Neuropsychologists should additionally consider referral to other disciplines specializing in cardiovascular and cerebrovascular illness for evaluation of appropriate pharmacological treatment agents to be administered prophylactically against cognitive deterioration.
It should also be emphasized that cognitive impairment of this nature can lead to substantial difficulty in executing even the most simple functional abilities as well as instrumental activities of daily living (e.g., adhering to medications, preparing meals, managing finances). Therefore, in approaching work with HIV-infected older adults who are at risk for cerebrovascular disease, neuropsychologists should consider incorporating cognitive rehabilitative techniques into treatment to address the multiple cognitive impairments arising from the combined effects of HIV infection and cerebrovascular risk. For example, teaching patients to use such external aids as memory notebooks, alarms, and/or pill counts for remembering and maintaining complex medication regimens can assist with overall quality of living.
Funding was as follows: (1) NIMH R01 MH58522: Cognitive deficits and medication adherence in HIV/AIDS to CHH; (2) 5 T32 MH19535: Neuropsychology of HIV/AIDS to CHH.
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