Alzheimer’s Disease Progression: Factors Influencing Cognitive Decline

Abstract

Background:

Alzheimer’s disease (AD) patients present high variability in the rate of cognitive decline. Despite the wide knowledge on factors influencing dementia risk, little is known on what accounts for AD progression. Previous studies on this topic have mainly analyzed each factor separately without taking into account the interaction between genetic and non-genetic factors.

Objective:

The aim of the present study is to evaluate the role of demographic, clinical, therapeutic, and genetic factors and their interaction on cognitive decline among newly diagnosed AD patients.

Methods:

We retrospectively selected 160 AD patients diagnosed at the Neurology Unit of Careggi University Hospital of Florence. We evaluated the occurrence of rapid cognitive changes defined as the worsening of more than four points at the Mini-Mental State Examination after 2-year follow up period.

Results:

Among the 160 AD patients, 50% presented rapid disease progression. Extrapyramidal signs at disease onset were predictors of worse outcome (OR 2.2), especially among Apolipoprotein E (APOE) ɛ4 allele carriers, while the presence of family history for dementia decreased the risk of rapid progression by about 50%. Higher educated ɛ4-carriers showed a slower AD progression. We identified the chronic use of aspirin as potential secondary preventative strategy for the non ɛ4-carriers.

Conclusion:

At dementia onset, some clinical and demographic data can be predictors of future progression. The outcomes of the present study support the already hypothesized interaction between genetic and non-genetic factors during disease course and suggest genetic-based approaches.

Keywords

Alzheimer’s disease APOE aspirin decline dementia progression risk factors

INTRODUCTION

Alzheimer’s disease (AD) has an insidious onset and gets worse overtime. As the disease progresses, the individual requires increasing assistance, until a complete dependency for feeding, hygiene, and mobility [1]. To plan for the future management of a person with AD, it would be important for patients and their families to know the duration of the disease and the estimated time left until the severe stage. Studies evaluating the natural history of AD described significant variability in the rate of cognitive and functional decline among patients. Studies reported an annual Mini-Mental State Examination (MMSE) decline ranging from 0.8 to 4.4 points [2, 3], with a mean of 1.5 during the first year and 2.5 after the second year [4].

Identifying what accounts for variation in AD progression has been the aim of research in the last decades. The predictors of cognitive decline that have been investigated the most are demographic factors, such as age at disease onset [5], sex [2], and education [6]; clinical features as extrapyramidal signs [7 –9], behavioral disorders [10, 11]; APOE genotype [12, 13]; and vascular diseases and their therapies [14 –18]. However, studies are heterogeneous for duration, outcomes, and variables, and therefore produce inconsistent results.

In the present 2-year follow-up study on newly diagnosed AD patients, we retrospectively analyzed the impact of demographic, genetic, clinical, and therapeutic factors on the rate of cognitive decline.

MATERIALS AND METHODS

We selected patients from the outpatient database of the Neurology Unit of Careggi University Hospital of Florence, Italy. All patients with a diagnosis of Probable AD and Probable and Possible AD with evidence of AD pathophysiological process [19] were selected if they were first evaluated in the period between January 2009 and June 2012, and if they had been followed-up for at least 24 months. At the first assessment, patients underwent a comprehensive neurological and neuropsychological examination. During the visit information was collected regarding demographics, family history, personal medical history, and current treatment. All patients underwent brain computed tomography (CT) scans or magnetic resonance imaging (MRI). Genetic tests were carried out to describe APOE genotype in the entire population and to exclude dominantly inherited AD forms in case of young- onset dementia and in subjects with positive family history for dementia. AD-biomarkers were assessed, such as cerebral ¹⁸fluorodeoxyglucose positron emission tomography (FDG-PET) and cerebrospinal fluid (CSF) amyloid and protein tau dosage among the younger group (<65 years) and in case of clinical diagnosis of possible AD (81 subjects). Patients were then followed up regularly every six months. Each follow-up visit included neurological examination, MMSE, and assessment of daily activities, behavioral disorders, and medical history and treatment. Education was measured as the maximum years of formal schooling and it was analyzed as a continuous variable and then as a dichotomized variable, <8 years and ≥8 years, based on results of previous studies [20] and on the mean of the years of schooling in the present population. Family history of dementia was considered positive when one or more first-degree family members had a diagnosis of dementia ofany type.

Vascular diseases included hypertension, previous stroke, diabetes, hypercholesterolemia, and heart diseases. Hypertension was defined as a documented history of high blood pressure or use of antihypertensive drugs. Previous stroke and heart diseases, such as atrial fibrillation, myocardial infarction, and heart failure, were diagnosed from medical documentation. Diabetes and hypercholesterolemia were identified by clinical interview and from the results of blood tests performed during the dementia diagnostic procedure [21]. For each subject, the number of vascular diseases was calculated, and then a dichotomized variable was created: 0-1 versus more than 1 disease [21].

Comorbidity was defined as the presence of two chronic pathologies other than vascular disorders (hypothyroidism, hyperthyroidism, pulmonary diseases, hepatic or kidney impairment, chronic infective disease, arthritis), or one severe past or current disease, such as cancer.

Extrapyramidal signs were defined as the presence of two or more of the following symptoms: resting tremor, neck rigidity, arms rigidity, legs rigidity, parkinsonian gait, and body bradykinesia [9]. Behavioral disorders were classified as absent/not severe or present when a patient scored ≥6 (3 frequent x 2 moderate severity) in at least one item among the Neuropsychiatric Inventory Scale (NPI) [22] psychotic core (delusion and hallucination) and agitation, or when the patient was currently using antipsychotic drugs.

Concurrent cerebrovascular pathology was defined as mild/moderate or severe, based on the visual Fazekas scale for leukoaraiosis applied to CT scan or MRI findings (3 = severe leukoaraiosis, 1 or 2 = mild/moderate) [23]. Information on medication included: antihypertensive therapy, statins, hypoglycemic therapy, antidepressant, antipsychotic drugs, aspirin or other antiplatelet therapies, dementia specific treatment.

Diagnosis of Alzheimer’s disease

Before 2011, clinical diagnosis of Probable AD was made according to the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer’s Disease and Related Disorders Association (NINCS-ADRDA) criteria [24]. After 2011, diagnosis was made following the new criteria of the National Institute on Aging (NIA) and the Alzheimer’s Association [19]. In the present study, possible AD cases were included only when presenting with positive ADbiomarkers [19].

APOE genotyping

Genomic DNA was extracted from peripheral blood samples obtained during the baseline survey. APOE was genotyped using a standard polymerase chain reaction technique [25].

Measurement of AD progression

The MMSE score was used to measure cognitive changes. Progression was classified in two categories, slow and rapid progression, based on MMSE score changes over years. A decrease of more than two points after the first year and more than four points after the second year on MMSE indicated fast progression. These values were derived from the mean of MMSE decline in our population and were similar to the mean values reported by the European ICTUS study [4] and the cut-off identified in other population-based studies [26].

Statistical analysis

Univariate analyses were performed with Chi-square test for categorical data and Student’s t-test or analysis of variance for continuous data. Logistic regression analysis was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of rapid AD progression in relation to age, sex, APOE status, clinical features, vascular diseases, comorbidities, medications. First, each factor was separately entered into the model, and then the analysis was repeated adjusting for socio-demographic, clinical, vascular, and genetic factors. We examined potential interactions between APOE genotype and non-genetic features, including the independent variables and their cross- product terms in the same model.

Analyses were performed using IBM SPSS Statistics 20.0 (IBM Corp, New York, NY, USA) and Stata SE 12 for Windows (StataCorp, College Station, TX, USA).

RESULTS

The demographic and clinical characteristics of the patients are presented in Table 1 and Table 2. In particular, during the first year, 61.9% of patients had a benign disease course with a MMSE decrease of less than one point, and 80 out of 99 continued to progress slowly during the second year. Similarly, most of the individuals that presented an aggressive disease course since the start of evaluation continued worsening faster during the second year (Table 1).

Table 1

Demographic and clinical characteristics of the study population (n = 160)

Baseline Characteristics	No. subjects	Percentages
Sex, female	94	58.7%
Age at baseline, mean (SD)	75.6 (7.9)
Age group ≤65 y	60	37.5%
> 65 and < 75 y	23	14.4%
≥75 y	77	48.1%
Time to first visit, years, mean (SD)	1.7 (1)
Schooling, y, mean (SD)	7.7 (4)
Education > 8 y	69	43.1%
MMSE score at baseline, mean (SD)	22 (4.1)
APOE ɛ4 carriers (n = 110)	66, 7 ɛ4/ɛ4	57%, 4.4%
Family history for dementia	75	49%
1 family member affected	50	31.2%
≥2 family members affected	25	15.6%
Vascular diseases (more than 1)	70	43%
Hypertension	93	58%
Diabetes	21	13%
Heart disease	18	11.2%
History of Stroke or TIA	5	3%
Hypercholesterolemia	53	33%
Comorbidities	51	31.8%
Concurrent cerebrovascular pathology	49	30.6%
Extrapyramidal signs
At baseline	42; 10 iatrogenic	26,2%; 6% iatrogenic
during follow-up time (24 months)	11; 5 iatrogenic	6.9%; 3% iatrogenic
Behavioral disorders (BPSD)
At baseline	39	24%
during follow-up time (24 months)	17	10.6%
Follow-up
MMSE decreasing after 12 months, mean (SD)	–2.1 (1.8)
Slow progression	99	61.9%
MMSE decreasing after 24 months, mean (SD)	–4.2 (2.8)
Slow progression	80	50%

Table 2

Frequency of medications in the study population (n = 160)

Medications	No. subjects	Percentages
Aspirin	I	45.6%
Statins	43	26.9%
SSRI	102	63.7%
Antipsychotic	36	22.5%
Dementia therapy
None	25	15.6%
Acetylcholinesterase inhibitors	71	44.4%
Memantine	47	29.4%
Both	17	10.6%

SSRI, selective serotonin reuptake inhibitors.

There were no differences between patients with slow and rapid AD progression related to the MMSE value at baseline, sex, educational level, APOE genotype, or vascular diseases (Supplementary Table 1). Age at onset presented a bimodal distribution, with younger and older age groups more likely to have a faster cognitive decline, however, the result did not reach statistical significance. Among all the evaluated factors, extrapyramidal signs at disease onset increased the probability to have a rapid cognitive decline, while positive family history for dementia and aspirin therapy were statistically associated with a slower AD progression, even after the adjustment for possible confounders (Table 3). Details on confounders and non-significant results related to drugs are shown in Supplementary Table 2 and the Supplementary Material.

Table 3

Adjusted OR and 95% confidence interval of AD rapid progression associated with demographic factors, clinical features, vascular diseases, and aspirin therapy

	Rapid progression OR (95% CI)^*	Rapid Progression OR (95% CI)^§
Age compared with 65–75 y
≤65 y	2.5 (0.90–6.99)	1.89 (0.45–8.01)
≥75 y	2.16 (1.02–4.69)	1.85 (0.57–6.03)
Sex, female	1.83 (0.91–3.65)	1.25 (0.45–3.51)
Education >8 y	1.16 (0.57–2.35)	0.65 (0.21–2.02)
APOEɛ4-carriers	0.56 (0.27–1.33)	0.88 (0.31–2.54)
Positive Family history of dementia	0.52 (0.26–1.00)	0.39 (0.15–0.97)
Extrapyramidal signs	2.2 (1.04–4.69)	3.38 (1.15–9.9)
Behavioral disorders	1.04 (0.52–2.11)	0.73 (0.37–1.42)
Mixed AD	1.15 (0.55–2.41)	0.89 (0.3–3.24)
Vascular diseases >1	0.87 (0.6–1.2)	1.37 (0.48–2.54)
Comorbidity	1.12 (0.63–1.99)	1.09 (0.41–2.93)
Aspirin therapy	0.44 (0.22–0.88)	0.34 (0.11–0.88)

^*Basic adjusted: age, gender, education, MMSE at baseline. ^§Full adjusted: age, gender, education, MMSE at baseline, cerebrovascular pathology, vascular disease, APOE, family history, extrapyramidal signs, aspirin.

APOE genotype-stratified analysis (n = 110)

APOE ɛ4 and non-ɛ4 carriers were similar in terms of age, sex, educational level, vascular diseases, and clinical features at disease onset, while pure neurodegenerative brain pathology and family history of dementia were statistically more frequent among ɛ4-carriers (Supplementary Table 3). Significant two-way interactions between APOE and education (p-value = 0.038), extrapyramidal signs (p-value = 0.021), and aspirin therapy (p-value = 0.013) were detected.

For that reason, we performed APOE-stratified analysis. We found a significant slower decline associated with the use of aspirin (OR = 0.05; 95% CI: 0.007–0.37) among non-ɛ4 carriers, and with high education (OR = 0.30; 95% CI: 0.08–1.10.) among ɛ4-carriers, and a significant faster decline associated with extrapyramidal signs (OR = 13.3; 95% CI: 1.47–59.40 CI 95%) among ɛ4-subgroup.

Patients with missing APOE genotype information were older and more likely to present concurrent cerebrovascular pathology compared with patients that had genotyping data, but they did not differ in the other characteristics.

DISCUSSION

To our knowledge, only two studies have previously explored the role of family history on progression, and they found no association [27] or a faster decline in the case of affected parents [28]; in both cases the effect of APOE genotype was not evaluated. Our analyses showed a strong association between positive family history for dementia and a slower cognitive decline. It is possible that when genetic determinants lead to disease onset, the progression is more benign than when AD is caused by other factors.

Consistent with previous research [7–9 , 29], we found that extrapyramidal signs predict faster worsening, especially among the ɛ4-carriers. Neuropathological data demonstrated that the severity of motor signs reflects the burden of AD-associated brain lesions [30] in the substantia nigra [31]. Nevertheless, the mechanisms underlying the pathogenesis of behavioral disorders are unclear [32], and their influence on cognitive decline was not confirmed in our and in other studies [7, 11].

Aspirin was associated with a 60% reduced risk of rapid AD progression, similar to another longitudinal observational study [33]. Despite the fact that randomized clinical trials failed to show any effect of aspirin on cognition [17, 34], the Evaluation of Vascular Care in Alzheimer’s Disease (EVA) Study demonstrated slower or no increase of white matter lesions [34] in patients who have been treated for vascular disorders for two years. Differently from observational studies, in randomized clinical trials aspirin is administered to patients that have no potential indication for its use, and for a short period. Experimental data showed that aspirin can directly counteract amyloid-β aggregation [35], but only after long-term use [36]. Thus, aspirin could influence AD risk and progression through three different mechanisms: decreasing vascular burden pathology, reducing chronic neuroinflammation with its anti-inflammatory action [37], and interfering with amyloid-β aggregation.

To our knowledge only two studies have analyzed the interaction between genetic and non-genetic factors [14, 38] on AD progression. Consistent with Oliveira and colleagues [38], we confirmed that high education was associated with slower cognitive decline among ɛ4-carriers. Higher education is a proxy for cognitive reserve [39] and performs a protective role on dementia risk especially among ɛ4-carriers [22]. However, the role of schooling after dementia onset is controversial [6 , 40]. The joint effect of APOE genotype and education could explain the debated results, and therefore requiring further investigation. Similarly, an interaction between APOE genotype and vascular factors has been demonstrated on dementia risk but does not seem to be linear during the course of the disease [14], even showing a protective role of vascular factors on dementia progression in AD ɛ4-patients. Interestingly, in our sample aspirin therapy was beneficial especially among non ɛ4-carriers, in whom probably white matter lesions have more effect onprogression [34].

There are some limitations in our study. First, our sample is relatively small and that can affect statistical power. Secondly, due to the retrospective design, we did not take into account dropouts. Thirdly, being a University Hospital Neurology Unit, we could have a selection bias of patients. However, the characteristics of our population were similar to other clinical samples [13, 27].

The strengths of our study included the extensive clinical examination, the high accuracy of AD diagnosis, the availability of neuroimaging data and the extensive evaluation of risk factors.

In conclusion, our study suggests that some indicators of cognitive decline can be detected at the time of diagnosis and that the long-term use of aspirin may offer a possibility as a secondary preventive strategy.

In our opinion, the genetic-non-genetic factors interaction on AD progression needs to be further investigated since it varies along disease course. Understanding the concurrent role of those factors could clarify the neurodegenerative mechanism and could lead to different therapeutic approaches based on genetic background.

DISCLOSURE STATEMENT

Authors’ disclosures available online (http://j-alz.com/manuscript-disclosures/17-0665r1).

Footnotes

The supplementary material is available in the electronic version of this article: .

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