Cognitive decline and depressive symptoms in late-life are associated ...

Original Research Paper

Cognitive decline and depressive symptoms in late-life are associated with statin use: evidence from a population-based study of Sardinian old people living in their own home Antonella Mandas1, Maria G. Congiu1, Claudia Abete1, Sandra DessÌ1, Paolo E. Manconi1, Monica Musio2, Silvia Columbu2, Walter Racugno2 1

Department of Internal Medical Science, University of Cagliari, Italy, 2Department of Mathematics and Computer Science, University of Cagliari, Italy

Objectives: This study was designed to provide further insights into the effects of dyslipidemia (Dys-y) and use of statins (St-y) on cognitive functions and mood in older people. Methods: Three hundred and twenty-nine subjects aged § 65 years were screened for cognitive dysfunction using mini mental state examination (MMSE). The geriatric depression scale (GDS) was used to detect depression. Interview questionnaires surveyed activities of daily living (ADL) and instrumental ADL (IADL), as well as other functional disabilities. The presence of neutral lipids (NLs) in cytoplasm of peripheral blood mononuclear cells (PBMCs) was determined with the Oil red O (ORO) staining. Results: There was no significant difference in MMSE and GDS scores between normal (Dys-n) and Dys-y. However, when Dys-y subjects were divided into St-y and non-statin users (St-n), significant differences emerged in the scores of MMSE and GDS: St-y had lower MMSE and higher GDS than St-n. Multiple correspondence analysis and logistic regression provided further evidence that elderly St-y were much more likely to suffer of cognitive impairment and depression than St-n. Another interesting finding was that the intensity of NL-PBMCs measured by ORO staining was greater in subjects with altered MMSE compared with cognitively normal subjects. In addition St-y had higher ORO score than St-n. Discussion: This is an observational study and cannot, therefore, prove a causal relationship between St-y in the elderly and a higher cognitive decline, nevertheless it provides substantial indications that caution should be exercised in the provision of statins in elderly subjects to avoid accelerated memory loss. Keywords: Elderly, Cholesterol, Cognitive impairment, Depression, Statins

Introduction Accumulating evidence suggests that neurodegenerative disorders such as Alzheimer’s disease (AD) and vascular dementia (VD) are associated with changes in lipid metabolism in the brain. Individuals with high cholesterol diets have been observed to have increased risk of AD1 and it has been also reported that dyslipidemia (Dys-y), which is an elevation of plasma cholesterol, triglycerides (TGs), or both, accelerates the development of AD in transgenic animal models.2,3 Further, performance in cognitive tests was inversely associated with plasma concentrations of low-density lipoprotein (LDL)-cholesterol and positively associated with high density lipoprotein (HDL)cholesterol levels.4–8 These studies have led to believe Correspondence to: Antonella Mandas, Department of Medical Sciences, University of Cagliari, SS 554 Bivio Sestu, 09042 Monserrato, Cagliari, Italy. Email: [email protected]

ß W. S. Maney & Son Ltd 2014 DOI 10.1179/1743132813Y.0000000287

that individuals with Dys-y were more susceptible to develop a number of neurodegenerative disorders and that statins, by reducing plasma cholesterol levels, could offer a valuable contribution to maintain and/or improve cognitive performance.9,10 In contrast to general belief, however, randomized, controlled trials and some longitudinal observational studies failed to show any positive effect of statins on the risk of dementia particularly if prescribed in late-life.11,12 Consistently, it has been also reported that Dys-y in midlife is associated with increased risk of late-life cognitive impairment and that statin therapy is likely to have a benefit on cognitive function.13 An analysis of data from the cardiovascular health cognition study, which examined 2798 patients, showed that the use of statins was associated with an 8% increase of risk of all-cause dementia, and a 21% increase in risk of AD alone.14 In addition,

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a study published in the Cochrane Library which reviews drug trials, pointed out that some patients taking statins have suffered from short-term memory loss, depression, and mood swings. It has been also reported that the risk of developing AD is in no way related to plasma cholesterol levels and that persons having naturally low cholesterol levels demonstrate poorer performance on a variety of cognitive tests.11 All these data seem to support the idea that statins, even if undoubtedly useful in preventing heart attacks and strokes,12 should not be routinely prescribed to subjects over 65 years that are more susceptible to memory loss and depression.15,16 In an attempt to add another small piece to understand the very large and complex puzzle that is ‘statins and cognitive impairment in the elderly’, in this study we further explored the associations of depression and cognitive impairment with dyslipidemia (Dys-y) and statin use (St-y), in a population of subjects aged 65 years and more, living in the privacy and comfort of their own homes.17 We chose to enroll old subjects living in their own homes since they generally have less comorbidity than those hospitalized and consequently less clinical-diagnostic confounding factors. Furthermore, since a previous investigation by our group found an unbalance between cholesterol pools (free and esterified cholesterol, FC and CE) in peripheral blood mononuclear cells (PBMC) of AD patients and their first degree relatives,18 we also evaluated the effect of statins on lipid accumulation in PBMCs by utilizing 60 blood samples from 65 years or older subjects who gave ‘informed consent’ to their participation.

Methods Participants To examine the relationship between Dys-y and cognitive performance and depression in the elderly, in this study we analyzed data from a population of 329 subjects 65 years or older (137 men (M) and 192 female (F)). All participants lived in Assemini, a little Sardinian village with about 24 000 inhabitants (about 3850 § 65 years). Detailed subject history was recorded with the use of a questionnaire focusing on medical history. Age, gender, number of years of school completed, smoking habits, alcohol consumption, hypertension, type 2 diabetes, and cardiovascular diseases were established by reading clinical documentation and by examining medical records. Dys-y included participants that have or have had a LDL-cholesterol . 4.1 mmol/l during the last four years. St-y was defined as use of any drug in the class of HMG-CoA reductase inhibitors including more lipophilic statins such as simvastatin and less lipophilic, atorvastatin, rosuvastatin, and pravastatin for at least three years.

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Comprehensive geriatric assessment (CGA) All subjects underwent a comprehensive geriatric assessment (CGA) consisting of: 1. Activities of daily living (ADL) index,19 which measures functional status by quantifying patient performance in 10 activities of daily life. These activities are grouped according to self-care (feeding, grooming, bathing, dressing, bowel and bladder care, and toilet use) and mobility (ambulation, transfers, and stair climbing). A maximal score of 20 indicates that a patient is fully independent in physical functioning, and a lowest score of 0 represents a totally dependent bed-ridden state. 2. Instrumental activities of daily living (IADL) scale20 which assesses independence in eight activities that are more cognitively and physically demanding than ADL, including managing finances, taking medications, using telephone, shopping, using transportation, preparing meals, doing housework, and washing. A score of 8 indicating total autonomy, and 0, total dependence. 3. Mini mental state examination (MMSE) which assesses cognitive status, corrected for age and education, 30 correct-answer points indicating cognitive deficit absence, and 0, maximum cognitive deficit. Subjects with a MMSE score , 24 were considered cognitively impaired.21 4. Geriatric depression scale (GDS, 30 items) which assesses depressive symptoms. The grid sets a range of 0–9 is considered as ‘normal’, 10–19 as "mildly depressed", and 20–30 as "severely depressed".22 5. Performance-oriented mobility assessment (POMA) designed to assess balance and gait during position changes and gait maneuvers used during normal activities. The balance portion has nine maneuvers which are graded on an ordinal scale as either normal adaptive or abnormal. The maximum total score is 16 points. The gait portion has seven gait characteristics which are graded as normal or abnormal. The maximum total score is 12 points. The total mobility score for balance and gait is thencalculated. The maximum possible score is 28 points.23 6. Physical performance test (PPT) which assesses multiple domains of physical function using observed performance of tasks that simulate activities of daily living of various degrees of difficulty. This test measures performance on seven tasks, including writing a sentence, simulated eating, lifting a book and putting it on a shelf, putting on and removing a jacket, bending over and picking up a penny, circling, and walking for 25 feet. For each task, participants receive a score based on time to completion. The maximum possible score for the seven tasks is 28 points.24 7. Mini nutritional assessment (MNA) designed and validated to provide a single, rapid assessment to early identify malnutrition risk in elderly subjects. The total MNA score is calculated as the sum of the scores assigned to the replies to each of the 18 questions, and is subdivided thus: anthropometric assessment, 8 points; global assessment, 9 points; dietary assessment, 9 points; and self-assessment, 4 points. The maximum score of 30 indicates an optimal nutritional condition. This assessment included body mass index (BMI) determination.25

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Figure 1 Representative set of images for each score number (from 0 to 5) of PBMCs stained with ORO. Freshly isolated PBMCs were stained with ORO to evidence NLs and counterstained with hematoxylin for nuclei. Cells were then examined by light microscopy and imaged (see Methods section).

Oil Red O staining Cytoplasmic neutral lipids (NLs) were determined in PBMCs from 60 subjects randomly selected from the population described above by staining cells with Oil Red O (ORO). Collected PBMCs were washed three times with PBS, and fixed by soaking in 10% formalin. Cells were then treated with isopropyl alcohol (60%), washed, and stained with ORO (a lipid-soluble dye which stains NLs, including CE but not FC), that appear as bright red spots in the cytoplasm. After staining, cells were imaged using a Leitz invertedphase microscope fitted with a digital camera. At least two different fields per sample were imaged and analyzed. The red intensity was scored on a semi-quantitative scale (from 0 to 5) by two blinded observers: 0–1, indicated no staining or rare positive cells; 2, staining barely visible at low power (6200); 3, focal staining or faint diffuse staining clearly visible at low power; 4, multifocal staining or moderate diffuse staining; and 5, intense diffuse staining. Representative photos for each score are shown in Fig. 1.

Statistical analysis Quantitative variables were shown as mean¡standard deviation (M¡SD). Comparisons among these variables were made by Student’s t test, the Wilcoxon test (when the t-test was not allowed), and the Pearson correlation coefficient, when applicable. Multiple correspondence analysis (MCA)26 was used to simultaneously analyze the associations between

different dichotomous variables: sex (M and F), presence of dyslipidemia (Dys-y and Dys-n), and statin use (St-y and St-n). CGA parameters and age were examined as both a quantitative and dichotomous variables (categories used are indicated in Results section). An odds ratio (OD), chi-square (x2) test was performed to identify statistically significant associations. Finally, we have also considered a logistic regression model27 to study the relationship between some variables (i.e. statin use) and specific indicators, MMSE and GDS in particular. Logistic regression is especially useful for analysis of observational data when adjustment is needed to reduce the potential bias resulting from differences in the groups being compared. All statistical tests were made using Excel’s data analysis tool. For MCA analysis we used XLSTAT 2013. A P-value of 0.05 was considered for statistical significance.

Results The current analyses focus on 329 individuals aged 65 years and older. Table 1 shows the comparison between characteristics of Dys-n and Dys-y participants. There were no significant differences between Dys-n and Dys-y in age, sex, education (number of years), and smoking and alcohol habits. Quite obviously the percentage of hypertensive and diabetic subjects was significantly higher in Dys-y group compared to Dys-n. Analyses of relationships between the different CGA parameters revealed no statistically significant


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Table 1 Characteristics of participants (comparison between Dys-n and Dys-y) Characteristics

Dys-n (222)

Dys-y (107)

P values

Age (mean years¡SD) Age range Sex: male/female Education (years) Current smokers no.(%) Current alcohol drinkers no.(%) Hypertension no.(%) Type 2 diabetes no.(%)

74.2¡7.1 65–99 100/122 (45/55%) 4.6¡3.1 13 (5.8) 95 (43) 129 (58.1) 23 (10.4)

73.1¡6.9 65–92 37/70 (35/65%) 4.2¡2.9 8 (7.5) 38 (35.5) 86 (80.4) 32 (29.9)

0.1850a,b 0.07124c 0.2551a,b 0.5732c 0.2076c 7.012e-05c 8.541e-06c

Dys-n 5 LDL-cholesterol,4.1 mmol/l, Dys-y5LDL-cholesterol . 4.1 mmol/l. Differences that are statistically significant are indicated in bold. a t-test b Wilcoxon test c 2 x

differences between Dys-y and Dys-n groups (Table 2). When Dys-y was categorized into St-y and St-n, no differences in age, sex, education (number of years), smoking and alcohol habits as wells as in CGA parameters were observed between the two groups (data not shown). However, the St-y had significantly higher scores of GDS and lower scores of MMSE than St-n (Table 3). Noteworthy, with respect to use of water soluble (hydrophylic) or lipid soluble (lipophilic) statins, no significant differences in MMSE and GDS scores were observed. Compared to St-n, subjects receiving the most lipophilic of the statins, simvastatin showed a reduction of 7% in MMSE score and an elevation of 4% in GDS score (P 5 0.033 and P 5 0.031, respectively). In subjects receiving the less lipophilic atorvastatin or the hydrophilic rosuvastatin and pravastatin, MMSE score was reduced by 9% and GDS increased by 5% (P 5 0.005 and 0.009, respectively). In this study LDLcholesterol levels correlated positively with MMSE score (r 5 0.3510, P , 0.05). Although these results appear to be challenging, because of the observational nature of the study and Table 2 CGA and Dys-y)

parameters

(comparison

between

Dys-n Table 3 CGA parameters of Dys-y (comparison between St-n and St-y)

CGA parameters

Dys-n

Dys-y

P values

MMSE mean score¡SD GDS mean score¡SD BMI mean¡SD BMI § 25 no.(%) MNA score mean¡SD MNA score , 24 no.(%) ADL mean score¡SD ADL score , 20 no. (%) IADL mean score¡SD IADL , 6score no. (%) PPT mean score¡SD PPT , 24 score no. (%) POMA mean score¡SD POMA , 24 score no. (%)

25.8¡3.4 10.1¡6.6 28.0¡4.7 163 (73) 24.5¡2.9 69 (31.1) 18.5¡3.4 73 (32.8) 5.8¡2.2 110 (49.5) 14.3¡5.3 212 (95.5) 23.6¡7.3 53 (23.9)

25.6¡3.6 10.5¡6.1 28.1¡4.2 83 (78) 24.1¡3.3 38 (35.5) 18.0¡4.2 39 (55.7) 6.1¡2.3 41 (38.3) 14.9¡5.9 101 (94.4) 24.1¡6.3 25 (23.4)

0.8986a,b 0.4831a,b 0.7873a 0.4172c 0.3780a,b 0.4214c 0.4017a,b 0.5226c 0.0903a,b 0.05547c 0.2652a,b 0.663c 0.9257a,b 0.9189c

Dys-n 5 LDL-cholesterol . 4.1 mmol/l, Dys-y 5 LDL-cholesterol , 4.1 mmol/l. a t-test b Wilcoxon test c 2 x

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the smallness of the sample in some subgroups, no conclusion can be made regarding the existence of a causal relationship between St-y and an increased risk of developing dementia and depression. Therefore to make the overall findings more understandable and expendable and to give a realistic impression of the relation between two or more variables, we dichotomized some variables and determined associations between selected subgroups by using a number of statistical tests such as multiple correspondence analysis (MCA), chi-square (x2) test, and odds ratios (OR) and their confidence intervals (CI). Furthermore, to evaluate the quantitative aspects of the relationships between the MMSE and GDS variables and St-y a logistic regression model was also considered. Observing the MCA plot (Fig. 2), we found that vertical axis clearly separates St-y and Dys-y, (at the bottom) from St-n and Dys-n (at the top). In addition, the categories of abnormal MMSE and GDS scores (MMSE-1 and GDS-2) were located with St-y in the right lower quadrant. By contrast, the normal MMSE-2 and GDS-1 were located with St-n in the left upper quadrant. With the exception for altered MNA-1 and for F which were associated with

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Variables

St-n (44)

St-y (63)

P values

MMSE (mean score¡SD) GDS (mean score¡SD) BMI (mean score¡SD) BMI § 25 no.(%) MNA (mean score¡SD) MNA score , 24 no.(%) ADL (mean score¡SD) ADL score , 20 no. (%) IADL (mean score¡SD) IADL , 6score no. (%) PPT (mean score¡SD) PPT , 24 score no. (%) POMA (mean score¡SD) POMA , 24 score no. (%)

26.6¡2.7 8.8¡5.5 27.9¡4.2 34 (77.3) 24.6¡2.8 17 (39.2) 17.4¡5.3 15 (34.1) 5.9¡2.3 19 (43.2) 14.3¡5.8 43 (97.7) 23.7¡7.3 9 (20.4)

24.9¡4.0 11.6¡6.3 28.3¡4.2 49 (77.8) 23.7¡3.6 33 (52.4) 18.4¡3.2 24 (38.1) 6.3¡2.3 22 (34.9) 15.4¡6.0 58 (92.1) 24.5¡5.5 16 (25.4)

0.02077a,b 0.01828a,b 0.9445a,b 0.9509c 0.1827a,b 0.1609c 0.9064a,b 0.6719c 0.3791a,b 0.3871c 0.4560 a,b 0.2102 c 0.8713 a,b 0.5522 c

Statistical differences that are significant are indicated in bold. a t test b Wilcoxon test c 2 x

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Figure 2 Plot of MCA analysis. Axis 1 and 2 explain the 69.69% (F1 zF2) of the variability of the data. Dichotomous variables were coded as follows: MMSE (1 5 score § 24; 2 5 score , 24); GDS (1 5 score ƒ 9, 2 5 score . 9); ADL (1 5 score 20, 2 5 score , 20); IADL (1 5 score § 6; 2 5 score , 6); POMA (1 5 score ƒ 24; 2 5 score § 25); MNA (1 5 score , 24; 2 5 score § 24); BMI (1 5 score , 26, 2 5 score § 26); Dys-n, Dys-y; St-n, St-y; Age (1 5 ƒ 75 years, 2 5 § 76); Sex (M 5 male, F 5 female). The plot represents the projection of the categories of all the variables considered on the plane identified by the two principal axes.

St-y and for the normal MNA-2 and M which were associated with St-n, no other variable was found to be linked with ‘St-y/St-n’ categories. ORs with corresponding 95% CIs and chi-square tests confirmed the presence of a significant association between St-y and MMSE-1 and GDS-2 (Table 4). Once again no statistically significant relationships were observed between Dys-y and MMSE-1 and GDS-2 categories (Table 4).

The logistic regression analysis was carried out with the stepwise backward technique (step by step elimination of non-significant factors from the full model) (data not shown). A first model showed that St-y were 2.4 times more likely to develop an abnormal MMSE score (, 24) than St-n. This model had a good accuracy of prediction (75%). The second model showed that the probability for a female to be depressed (GDS1) is approximately

Table 4 Chi-square and OR with 95% CI analysis Participants All (329) Dys X2 (P) OD (95% CI)

y n

St X2 (P) OD (95% CI)

y n

Sex X2 (P) OD (95% CI)

F M

MMSE-1

MMSE-2

GDS-1

GDS-2

104 (32%) 35 69 0.089(0.766) 1.08 (0.66–1.77) 28 76 5.99 (0.0265) 1.87 (1.07–3.27) 71 33 8.33 (0.0039) 1.85 (1.13–3.02)

225 (68%) 72 153

176 (53%) 55 121

37 188

27 149

121 104

87 89

153 (47%) 52 101 0.279 (0.597) 0.88 (0.56–1.40) 36 117 4.81 (0.0284) 1.70 (0.98–2.96) 105 48 16.83 (0.0000) 2.24 (1.42–3.52)

Statistical differences that are significant are indicated in bold.


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twice that of a male. In this model no statistical difference was observed between abnormal MMSE and St-y. A low percentage (58%) of good accuracy of prediction was also evidenced. As the last point, PBMCs-ORO staining was determined in 60 of the 329 subjects, who successfully re-contacted, gave informed consent for ORO test to be done. Twenty three out of 60 subjects had an abnormal MMSE score and 37 had GDS scoring above the cut-off point (. 9). Thirteen out of 23 subjects with abnormal MMSE were Dys-y, while among 37 with abnormal GDS 22 were Dys-y. Statins were taken by 14/60, all of whom had abnormal GDS, while 9/14 had abnormal MMSE. None of the subjects with normal GDS and only five with normal MMSE score were St-y. Differences in St-y, sex, MMSE and GDS score, and Dys-y between patients with normal ORO (score 5 0–1) and abnormal score (score 5 2–5), were analyzed by chi-square test. Results are reported in Table 5. As expected, the profile of patients with normal and abnormal values for the variable ORO are quite different; in particular, the presence of abnormal values of the MMSE and GDS, as well as St-y seems to characterize patients with abnormal ORO. These considerations have been also supported by a model of logistic regression. The model used is the result of a stepwise variables selection procedure. More precisely, we started with a full model in which we included as potential explanatory variables all those presented in Fig. 2 and finished with a selected model containing only the variables MMSE and St. Data indicated that patients with MMSE , 24 have a significant greater probability of having abnormal ORO score than patients with MMSE § 24. This risk was even greater in St-y compared to St-n.

Discussion Despite the numerous studies on the role of dyslipidemia in etiology of dementia and depression, the results so far reported are contradictory. Similarly, studies on the potential neuroprotective role of statins remain inconclusive.9 Some studies revealed, in fact, that high serum cholesterol levels increased the risk of dementia and depression, others that high cholesterol had no effect and still others that high cholesterol reduced the risk of cognitive impairment

and depressive symptoms.3,4,7,9,11,28,29 Equivalently, some studies indicated that high doses of statins may prevent dementia in older age; others have been unable to find this association and still others that statin use might confer increased risk for dementia. It has been suggested that these inconsistencies could result from heterogeneity in study design, analytic methods, sample size, cognitive evaluation, and statin characteristics (e.g. lipophilic and less-lipophilic statins which may influence the capacity to cross the blood–brain barrier, BBB).30–34 In the present study, analyses performed using different statistical methods did not reveal any significant association between dyslipidemia and the presence of depression and cognitive impairment in old people living in their own homes. Consistent with this results, Pearson’s correlation analysis showed a significant positive correlation between LDL-cholesterol levels and MMSE score (r 5 0.3510, P , 0.05). However, when subjects with dyslipidemia were subdivided into St-y and St-n, St-y had significantly higher scores on the GDS and lower scores on MMSE compared with Stn. No significant differences in age, sex, education (number of years), and smoking and alcohol habits and in CGA parameters were observed between the two groups. These results support the idea that statin therapy may be an independent risk factor for cognitive impairment and depression in dyslipidemic older subjects. The main effect of statins is to lower LDL-cholesterol by blocking cholesterol synthesis in the liver. As a group, statins are thought to prevent cardiovascular disease by improving endothelial function, reducing inflammatory responses, maintaining stability of atherosclerotic plaques, and preventing the formation of thrombi even in subjects with normal cholesterol levels.35 These pleiotropic statins effects have led to consider this class of drugs for treatment of non-cardiovascular conditions including depression and dementia. As already mentioned, several observational studies have, indeed, reported a protective effect of statin therapy on the risk of AD and dementia,31 however, randomized clinical trials failed to find this benefit.31 A recent narrative review by Rojas-Fernandez and Colleagues has explored the potential adverse effect of statins on cognition by performing literature search using MEDLINE (1950– November 2011), EMBASE (1980-November 2011),

Table 5 Differences in ORO scores between St-y and St-n Variables

ORO (0–2 score) (n 5 35)

ORO (3–5 score) (n 5 25)

P values (x2)

Dys-y St-y MMSE (score , 24) GDS (score . 9) Sex (M)

13 (37%) 3 (12%) 5 (20%) 16 (45%) 16 (45%)

15 (60%) 11 (31%) 23 (66%) 21 (60%) 6 (24%)

0.08018 0.00138 2.702 e209 0.002637 0.08529

Statistical differences that are significant are indicated in bold.

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and the Cochrane Library (1960–November 2011).32 They found that studies, showing that statin use is associated with cognitive impairment, are principally observational studies (e.g., case reports/series). Conversely, in the majority of randomized controlled trials statins were found to have either a neutral or beneficial effect on cognition. Since statins that are less lipophilic are thought to contribute less to cognitive impairment owing to limited penetration across the BBB,32 the authors suggested, in cases where cognitive impairment secondary to statin is suspected,31 to switch from a highly lipophilic to a less lipophilic statin. In the present study MMSE scores were significantly lower and GDS higher in either, subjects receiving the more lipophilic statins (simvastatin) and those receiving the less lipophilic (atorvastatin, pravastatin, or rosuvastatin) statins compared to untreated subjects. These findings are consistent with interesting results obtained in the short-term treatment comparing the lipophilic simvastatin with the hydrophilic pravastatin in mice. Both, simvastatin and pravastatin, were detected in cerebral cortex of mice administered the drugs in vivo, indicating that also less lipophilic statins cross BBB. It has been suggested that transfer of the lipophilic compounds lovastatin and simvastatin across the BBB occurs via passive diffusion, whereas pravastatin is taken up by an active, low affinity system. Recently, the organic anion-transporting polypeptide 1a4 (Oatp1a4), a member of class of proteins of OATP family (human: OATPs; rodent: Oatps) of transporters which are responsible for both the influx and efflux of compounds across the BBB, has been indicated as the active uptake transporter for pravastatin.36,37 These results suggest that all statins can pass through the BBB and get into brain cells, but the mechanism by which they may impair cognitive functions remain elusive. Another interesting finding of this study was that the intensity of NLs, determined in PBMCs from 60 selected old subjects by ORO staining, was negatively associated with MMSE and positively with GDS scores. ORO score were also positively correlated with St-y. These results are consistent with previous studies showing that NLs, mainly CEs, accumulated in cytoplasm of PBMCs from AD patients and in some of their first degree relatives.18,38,39 It has been suggested that NL-PBMC determination by ORO staining may be useful for identification of a subset of subjects who might run a major risk of developing AD.18 This is an observational study and therefore it can only show an association but cannot prove causation, hence, by comparing the results from the literature with ours, we shall try to outline plausible mechanisms by which statins may impair cognition.


It is well known that BBB prevents the brain uptake of cholesterol-containing lipoprotein particles; therefore neurons receive cholesterol almost entirely from in situ synthesis.36 Since, the brain produces its own cholesterol, compensatory mechanisms may be necessary to allow for elimination; these involve either, cholesterol esterification by acetylCoenzyme A acetyltransferase 1 (ACAT1) and cholesterol conversion into 24S-hydroxycholesterol (24OHC). In contrast to cholesterol, 24OHC crosses the BBB and is delivered into plasma for further elimination.40–42 Significant experimental evidence indicates that cholinergic function, ionotropic and metabotropic receptor machinery, neural oxidative stress reactions, and other features of neurodegeneration are governed by this fine brain cholesterol regulation.41 This means that statins by reducing brain cholesterol synthesis lead to neuronal cholesterol homeostatic imbalance and as a result cause neuronal cell death and myelin breakdown. Myelin degradation causes the liberation of lipids, mainly FC, that may be reutilized for new myelin synthesis or stored in brain cells as CEs40–42 or secreted into the plasma as 24OHC.40–42 In view of the fact, that 24OHC is transported in plasma by the same lipoproteins as cholesterol; it can be internalized by blood mononuclear cells and accumulated in cytoplasm as CEs.40–42 In accordance with this, it has been found that treatment with statins causes a significant increase in the ratio between 24OHC and cholesterol in the circulation.42 These hypothesized mechanisms also provide a rationale for the accumulation of NLs found in this and previous studies in PBMCs from subjects with cognitive impairment.18 In summary, although this study cannot definitively prove the causal nature of the association between Sty in the elderly and a higher cognitive decline, it provides considerable evidence that caution should be exercised in provision of statins in elderly subjects to avoid accelerated memory loss.

Acknowledgements We would like to thank all elderly subjects from Assemini community who volunteered to participate in this study.

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