Effect of Vascular Risk Factors on the Progression of Mild Alzheimer’s Disease and Lewy Body Dementia

Abstract

Background: Vascular risk factors (VRF) are associated with an increased risk of neurodegenerative disease.

Objective: To examine the association between VRF and cognitive decline in patients with Alzheimer’s disease (AD) and Lewy body dementia (LBD).

Methods: We included consecutive referrals with mild AD or LBD to dementia clinics in western Norway from 2005 to 2013. The Mini-Mental Status Exam (MMSE) and Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) were administered at baseline and then annually for up to five years. The VRF include diabetes mellitus, hypertension, hypercholesterolemia, overweight and smoking. Generalized Estimating Equations (GEE) were used to examine the potential association between VRF scores and the change in MMSE and CDR-SB scores, adjusting for age, sex, and the apolipoprotein ɛ4 allele (APOE4).

Results: A total of 200 patients were included (113 AD, 87 LBD) (mean age 76 years, mean baseline MMSE 24.0, mean follow-up time 3.5 years). Smoking was the only VRF significantly associated with a more rapid cognitive decline, however only in the AD group. Being overweight at baseline was associated with a slower cognitive decline. Moreover, hypertension at baseline predicted a slower decline in MMSE scores. In the LBD group diabetes mellitus was found to be associated with a slower increase in CDR-SB scores.

Conclusion: With the exception of smoking, VRF at time of dementia diagnosis were not associated with a more rapid cognitive decline.

Keywords

Alzheimer’s disease dementia Lewy body dementia progression vascular risk factors

INTRODUCTION

Dementia is defined as an acquired impairment in cognitive functioning with reduced ability to perform activities of daily living [1]. The most common causes of dementia are Alzheimer’s disease (AD) (50–75%), followed by vascular dementia (VaD) and Lewy body dementia (LBD) [2]. Dementia with Lewy bodies (DLB) and Parkinson disease dementia (PDD), which have a number of clinical and pathological similarities [3] are combined in one LBD group in the present paper. The apolipoprotein E ɛ4 allele (APOE4) has been shown to increase the risk of AD [4], as well as being associated with a more rapid cognitive decline [5] and with cardiovascular disease [6]. Modifiable risk factors for vascular pathology are risk factors not only for VaD but also for AD [7, 8]. In addition, several studies have shown that vascular risk factors (VRF), such as midlife obesity, hypercholesterolemia (HC), and hypertension increase the risk of developing AD [9, 10]. Of note, white matter hyperintensities (WMH) found on brain magnetic resonance imaging (MRI) scans have been associated with cardiovascular risk factors [11], and have also been shown to predict an increased risk of stroke and dementia [12].

Whether or not VRF also affect the progression of AD is unclear [13]. Even less is known regarding the role of VRF in LBD progression, so further exploration of this is also important, given the wide variation in the rate of cognitive and functional decline in AD and LBD [14]. Investigating this may increase our understanding of pathophysiology, provide prognostic information, and most importantly identify novel intervention and treatment targets.

We therefore aimed to examine the association between VRF and the annual rate of decline in cognition measured by change in the Mini-Mental Status Exam (MMSE) [15] score, and in general and cognitive functioning as measured by the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) [16] score in patients with AD and LBD. We hypothesized that having a higher VRF load at baseline would be associated with a more rapid disease progression.

METHODS

Patients

Participants were selected from the Dementia Study of western Norway (the DemVest study) [17], an ongoing prospective cohort study of patients with mild dementia led from the Centre for Age-Related Medicine at Stavanger University Hospital, Stavanger, Norway. All referrals to the outpatient clinics in old age psychiatry and geriatric medicine in the region were screened for a first time diagnosis of mild dementia during the main inclusion period from March 2005 to March 2007. Prior to study start, a letter was sent to all general practitioners in the area, inviting them to refer all patients with suspected dementia to the study. Moreover, all neurology clinics in the region were asked to refer new cases with mild dementia to the study. From April 2007 patients with DLB and PDD were selectively recruited, in order to increase the number of LBD cases.

All patients have signed an informed consent form and the study has been approved by the Regional Ethics Committee (Approval 2010/633). The dementia diagnoses at baseline were made by two of the study clinicians, according to the Diagnostic and Statistical Manual for Mental Disorders, 4th edition (DSM-IV), based on all available information.A diagnosis of AD was made according to the criteria of the National Institute of Neurological and Communicative Disorders and the Stroke-Alzheimer’s Disease and related Disorders Association [18], a DLB diagnosis according to the revised consensus criteria [19] and a PDD diagnosis according to the recommendations from the Movement Disorder Society Task Force [20].

Design and assessments

Patients are being followed annually, or until withdrawal, death, or loss to follow-up for other reasons. After 5 years, diagnoses were reevaluated by three of the study clinicians (including two of the authors; DA and HS), based on all available data. So far46 brain autopsies have been performed, supporting the clinical diagnosis of LBD and AD in approximately 85% (unpublished data).

Patients eligible for the present study were those diagnosed with AD or LBD. In order to select patients with mild dementia only, an MMSE score of at least 20 was required for inclusion. Patients without dementia or with acute delirium, terminal illness, previous bipolar disorder or psychotic disorder, or those recently diagnosed with a major somatic illness which according to the clinician would have a significant impact on cognition, function or study participation were excluded. Of the 266 patients included in the DemVest study, a total of 200 patients were selected for this study.

At baseline, the patients underwent a comprehensive evaluation including a complete physical examination, electrocardiogram, and blood tests as described in detail elsewhere [17]. Subgroups of patients had brain MRI scans (n = 104) (see [21] for details) analyzed for WMH load using the Scheltens method [22]. Tau, p-tau, and Aβ₄₂ levels in cerebrospinal fluid (CSF) (n = 38) were analyzed as previously described [23]. In a total of 121 subjects apolipoprotein E (APOE) genotype, as previously described [24] was available for analysis.

Other data collected included age, sex, weight, height, smoking status, and medical history. Furthermore, a number of standardized clinical rating scales were performed, including the Montgomery and Aasberg Depression Rating Scale (MADRS) [25], with clinically significant depression defined as a score ≥15 [26]. Patients received symptomatic anti-dementia drug therapy (donepezil, rivastigmine, galantamine, or memantine) when clinicallyindicated.

Assessment of VRF at baseline

Subjects were classified as having or not having the following VRF: overweight, hypertension, HC, diabetes mellitus, and smoking. Overweight was defined as a BMI≥25 kg/m² [27]. Hypertension was defined as having a diagnosis of hypertension or being treated with antihypertensive drugs, i.e., beta-blockers, diuretics, ACE-inhibitors, calcium-antagonists or angiotensin receptor antagonists. Hypercholesterolemia (HC) was defined as having hypercholesterolemia reported in the medical history, or using statins. Diabetes mellitus (DM) was defined as having DM reported in the medical history or usage of insulin or oral antidiabetic drugs (i.e., sulfonylureas, biguanides, glinides, alpha-glucosidase inhibitors, thiazolidinediones, DPP-4 inhibitors and GLP-1 analogues). Patients were defined as smokers if they reported smoking and as nonsmokers if they had never smoked or had quit smoking.

A total VRF summation score was created by adding the scores of the different VRF, giving a score from 0 (no VRF) to 5 (having all the VRF).

Outcome measures

The outcome measures used were the longitudinal assessments of MMSE scores [15] and CDR-SB scores [16]. The MMSE is a test which includes 11 questions subdivided into 2 sections, giving a total score of 0–30 points. In the first part orientation, memory, and attention are tested, while the second part tests the ability to name, follow verbal and written commands, write a sentence, and copy a polygon figure.

The CDR scale, giving an additional assessment of cognitive and daily functioning, was obtained through interviews of both patients and a next of kin. The areas examined in this test are memory, orientation, judgment and problem solving, community affairs, home and hobbies, and personal care. The CDR-SB score is obtained by summing each of the domain area (box) scores, giving a total score of 0–18, where lower scores indicate higher functioning.

Statistical analyses

Statistical analyses were performed using the IBM SPSS statistical package, version 23 for Windows^®.

In order to take into account the correlation between scores at multiple visits per subject, the Generalized Estimating Equations (GEE) method was used to explore the potential associations between each VRF and the MMSE and CDR-SB scores, adjusting for age, sex, all other VRF, and time since baseline, which was calculated from the actual visit dates. The effect of any VRF on the change in cognitive scores was assessed by including in the models an interaction term between the VRF and time. The VRF summation score was analyzed as a categorical variable, comparing patients with 0, 1, 2, and 3 or more VRF. Analyses were performed both in the total group and in AD patients and LBD patients separately. Supplementary analyses were performed including APOE4 either as a confounder or as a stratifying variable.

The associations of the different baseline VRF scores and the Scheltens total score and CSF Aβ₄₂ were assessed using the Spearman rho correlation.

RESULTS

Among the 214 patients in the DemVest study diagnosed with probable AD or LBD, a total of 200 had an MMSE score at baseline of at least 20 and were included in this study (AD n = 113, LBD n = 87 (DLB n = 69, PDD n = 18)). There was at least one follow-up assessment for 187 patients (107 AD and 80 LBD (64 DLB, 16 PDD)), and mean follow-up time was 3.5 years. A total of 93 died during follow-up, and 10 withdrew from the study (Fig. 1). The baseline characteristics are presented in Table 1. Among the 200 patients, 53% had hypertension, 9% DM, 25% HC, 40% overweight (mean BMI for those with BMI≥25 being 28.4), and 19% were smokers. When comparing demographical data between the AD and LBD groups, the only significant difference found was with regard to sex distribution. In the serological data, small but statistically significant differences were found between the groups for hemoglobin, cholesterol, and triglycerides.

The mean annual decline in MMSE scores was 2.6 (95% CI 2.3 to 2.8) for all patients, 2.7 (2.4 to 3.0) among AD patients and 2.3 (1.8 to 2.8) among LBD patients. The mean annual increase in CDR-SB scores was 1.7 (1.6 to 1.8) in all patients, 1.8 (1.7 to 2.0) among AD patients, and 1.4 (1.2 to 1.7) among LBD patients.

This group of patients had a relatively low burden of established ischemic cardiovascular disease. We found that in their medical history, a total of 15 had stroke, 16 had transitoric ischemic attack, and 15 had myocardial infarction. All patients defined as having HC were using statins.

The individual VRF (See Table 2 for the development in MMSE scores and in Table 3 for CDR-SB. Supplementary Material) were adjusted for other VRF in addition to age and sex. Hypertension at baseline predicted a slower decline in MMSE scores (p = 0.033), but was not associated with the progression of CDR-SB scores (p = 0.43). In addition, being overweight at baseline was associated with a slower decline in MMSE scores (p < 0.001) and a slower increase in CDR-SB scores (p < 0.001).

The apparent protective effect of overweight was present in both dementia groups and for both MMSE and CDR-SB, however with stronger effect estimates in the LBD group. Smoking was associated with a more rapid increase in CDR-SB scores in the AD group (p = 0.045), and with a slower decline in MMSE in the LBD group (p = 0.045). In the LBD group, DM was found to be associated with a slower increase in CDR-SB scores (p = 0.047), and hypertension with a slower decline in MMSE (p = 0.043).

In the subgroup of patients with APOE-genotyping (n = 75; 52 AD, 23 LBD), adjustment for APOE4 had no noticeable effect on the results. VRF summation score was significantly associated with a slower decline in cognitive function as measured by MMSE (Fig. 2A), however the results for CDR-SB were inconsistent (Fig. 2B).

WMH were associated with hypertension (r = 0.27, p = 0.007), but there were no significant associations with other VRF, and no significant associations were found between CSF Aβ₄₂ and any of the VRF.

DISCUSSION

The main findings of the current study are that among the VRF, only smoking was significantly associated with a more rapid cognitive decline in patients with AD, and that being overweight was associated with a slower cognitive decline in both AD and LBD. Moreover, in the LBD group slower cognitive decline was associated with DM (CDR-SB) in addition to smoking and hypertension (MMSE).

Our finding of an association between smoking and a more rapid cognitive decline in AD patients is consistent with some, but not all studies [13, 28], and is of particular clinical interest as smoking is a potentially modifiable risk factor. The association between smoking and a more rapid decline could be mediated through brain small vessel disease burden in smokers [29], progression of WMH [30], or through adverse effects on the cholinergic system [31]. In our study, we found an association between smoking and a slower decrease in MMSE scores in the LBD group, somewhat consistent with previous studies suggesting an inverse association between smoking and the risk of PD. Possible mechanisms include reduction of the enzyme monoamine B oxidase, interaction with glutathione S-transferases, or induction of cytochrome P-450, with a potentially increased detoxification of environmental toxins [32, 33]. Thus smoking might appear to have opposite effects in AD and PD. However, a recent meta-analysis found that smoking increases the risk of PDD [34]. Also, Alves et al. found that once patients had been diagnosed with PD, smoking had no major protective effect [35]. Notably, smoking has not been found to be a risk factor for DLB [36], the risk factors for which appear to be a composite of those for AD and PD. Finally, the relationship between smoking exposure and the development and course of LBD might, at least to some extent, be a matter of timing, i.e., time of onset and duration of smoking.

Obesity in midlife has been associated with an increased risk of dementia [9], and has also been associated with increased cortical amyloid accumulation in women [37], whereas it was associated with a lower risk of cognitive decline in a middle aged and older cohort in another study [38]. Furthermore, it has been found that weight loss over a period of one year in patients with amnestic MCI (aMCI) and AD was associated with faster clinical progression in aMCI, but not in AD [39]. In this study, we found that overweight at time of dementia diagnosis was associated with a slower rate of cognitive decline, suggesting that overweight might be a marker of better health in old age and at time of dementia diagnosis. Also, it is possible that there is a perception among clinicians that patients with overweight tolerate acetylcholinesterase inhibitors better, and therefore are started on such medications more often than those with lower BMI. As shown in a recent review, treatment with acetylcholinesterase inhibitors is associated with a significant risk of weight loss in older patients with dementia [40]. Our finding also could be considered as an illustration of the “obesity paradox” [41]; that is, in contrast to the general population, in the geriatric patient groups, overweight and even obesity is considered as a protective factor. Coin et al. found BMI not only to be a good nutritional parameter and an indicator of global health in older people with dementia, but also that a BMI of 25 could be a cut-off value below which cognitive status deteriorates [42]. Also, in the Cardiovascular Health Study, where BMI was calculated at two age points, it was found that whereas mid-life high BMI was related to higher dementia risk, there was an inverse relation with BMI after 65 years [43]. On the other hand, Strandberg et al. argue that in cross-sectional or short–term studies a link could be observed between greater body weight and better prognosis simply through selection due to chronic diseases gradually leading to weight loss [44].

Paradoxical associations also exist between HC and cognitive function, as results from the CAIDE study have shown that high midlife serum total cholesterol is a risk factor for dementia and AD, while a decrease in serum total cholesterol after midlife was associated with increased risk of late-life cognitive impairment [45]. Still, Helzner et al. found that higher prediagnostic total cholesterol and low-density lipoprotein cholesterol (LDL-C) concentrations were associated with accelerated post diagnostic cognitive decline [28]. Unfortunately, we did not have complete LDL-C measurements available in this study.

A previous study has found an association between increasing systolic blood pressure and a higher rate of cognitive decline in AD [46]. In our study, we found hypertension to be associated with a slower decline in MMSE scores. However, as extensive WMH have been related to dementia [47], we also analyzed the association between VRF and WMH. As hypothesized, we found a significant relationship between hypertension and WMH, consistent with findings in previous studies [30]. The lack of an association between hypertension and cognitive decline might suggest that cerebrovascular pathology, as reflected in WMH load is not an important contributor to cognitive decline after onset of dementia inAD and LBD.

This might also be the explanation to why we found a relationship between DM and a slower increase in CDR-SB scores in LBD patients. That is, once a patient is diagnosed with a neurodegenerative disease, the disease will progress independently of VRF such as DM. In a study including patients with PD, cerebrovascular risk factors were not associated with incident dementia, indicating that disease-related degenerative brain changes are the main causes of dementia in PD [48]. Moreover, an autopsy study found an inverse correlation between severity of Lewy body pathology and major cerebrovascular lesions, suggesting that patients with a higher Lewy body burden are less likely to have severe cerebrovascular pathology or a history of stroke, and viceversa [49].

The effect of the combination of different VRF on cognitive decline has not been much studied. Blom et al., in contrast to our study, found no significant associations neither when dichotomized as VRF≥2 yes/no nor as VRF≥3 yes/no [46]. Viticchi et al. found that an increased burden of vascular risk, as measured with the Framingham cardiovascular risk profile, can be considered as a predictive tool for cognitive worsening in AD [50]. Also, one study has suggested that in AD patients without cardiovascular disease, treatment of VRF is associated with a slower decline in MMSE scores [51].

The present study has some limitations. Blood pressure measurements were not standardized, that is, calculating the average of at least two independent measurements on at least three different occasions [52]. We have taken this into account by using a history of hypertension rather than blood pressure measurements taken at baseline as the definition of hypertension. There were some missing values in the blood tests, possibly introducing some bias. Although there were statistically significant differences between the groups in our serum analyses, these differences were rather small and of uncertain clinical relevance. Our definition of HC employing use of statins, or a history of HC, may have led to an overestimation of HC frequency as some patients could be using statins as secondary prophylaxis after cerebrovascular or cardiovascular events rather than for HC. Also, in our study all patients given a HC diagnosis were receiving statins. Thus, the potential effect of “HC” in our analyses in practice might be an effect of taking statins. Of note, some studies have suggested that use of statins may be a protective factor with respect to cognitive decline [53]. In addition, missing analyses of glycosylated hemoglobin may have led to an underestimation of the number of patients with DM as patients with type 2 DM not receiving drug treatment would not to be detected in this study. Furthermore, only a subgroup of patients had Scheltens WMH scores and CSF Aβ₄₂ measurements, thereby reducing the statistical power of these analyses. Due to the relatively moderate study size, we were not able to account for all possible heterogeneity in the sample, thus some subgroup effects of VRF on progression of dementia may have been missed. Finally, since we included patients at time of dementia diagnosis, information regarding previous diseases is retrospective and subject to recall bias by the caregiver, thus detailed information regarding the duration of the risk factors was not available.

The strengths of this study include the longitudinal multicenter design, with a relatively homogenous group of patients with newly diagnosed AD and LBD. The diagnoses were reevaluated after 5 years based on an extensive and standardized clinical assessment program, and verification by means of postmortem brain autopsies has been performed in a sizeable subgroup. The patients were followed for a mean of3.5 years, thus this is one of the longest prospectively studied LBD cohorts. Moreover, this study included patients from several centers in the western region of Norway, and included referrals both from memory and neurology outpatient clinics, as well as from GPs. Therefore, our findings probably are representative of the general geriatric population with mild AD and LBD in Norway.

In conclusion, we found a significant association between being overweight at baseline and a slower progression of cognitive decline both in AD and LBD patients. Smoking at baseline was the only VRF associated with a more rapid cognitive decline, and only in the AD group. Smoking cessation might therefore potentially slow down the cognitive decline in AD, in addition to other benefits.

DISCLOSURE STATEMENT

Authors’ disclosures available online (http://j-alz.com/manuscript-disclosures/160847r1).

Footnotes

Appendix

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