Effects of telmisartan on cognition and regional cerebral blood flow in hypertensive patients with Alzheimer's disease
ABSTRACT Recent studies have shown that some antihypertensive medications are associated with a significant reduction in the incidence of Alzheimer's disease (AD). However, it remains uncertain whether antihypertensive drugs may have a preventive effect on cognitive decline in patients with AD. We investigated the effects of telmisartan, an angiotensin II type 1 receptor blocker with peroxisome proliferator-activated receptor γ-stimulating activity, on cognition and regional cerebral blood flow (rCBF) in elderly hypertensive patients with AD.
A total of 20 patients with probable AD and essential hypertension were randomly assigned to the telmisartan group (n = 10, 40-80 mg daily) or the amlodipine group (n = 10, 5-10 mg daily) for 6 months.
The groups had a similar significant reduction in systolic and diastolic blood pressure after treatment. The telmisartan group did not show any changes in cognitive function test scores, while the amlodipine group showed significantly higher scores on the AD Assessment Scale-Cognitive Subscale (Japanese version). Analysis of covariance to analyze treatment effect revealed that the telmisartan group showed increased rCBF in the right supramarginal gyrus, superior parietal lobule, cuneus, and lingual gyrus compared with the amlodipine group, while the amlodipine group showed increased rCBF only in the right cingulate gyrus compared with the telmisartan group at 6 months.
These findings suggest that telmisartan may have additional benefits and be useful for the treatment of elderly hypertensive patients with AD.
SourceAvailable from: Raffaella Valenti[Show abstract] [Hide abstract]
ABSTRACT: Increasing evidence suggests vascular risk factors (VRF) play a role in the pathogenesis of Alzheimer's disease (AD). Epidemiological studies have found associations between VRF and risk of AD. Treating VRF in patients with AD offers a potential treatment option but ineffective treatments should be avoided in this group who are frequently on multiple medications and in whom compliance may be challenging.BMC Medicine 12/2014; 12(1):160. DOI:10.1186/s12916-014-0160-z · 7.28 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: The etiology of Alzheimer's disease (AD) remains unclear. Epidemiologic studies suggest hypertension plays a contributing role to AD. Recently, several experimental and observational studies showed interaction between the renin-angiotensin system and amyloid-b, a key pathologic feature of AD, with diverse results. This article reviews molecular, genetic, experimental and clinical data to clarify the impact on an AD patient with angiotensin converting enzyme inhibitor and angiotensin II receptor blocker therapy, with some guidance for the direction of possible future research.Acta Cardiologica Sinica 03/2014; 30(2):114-118. · 0.85 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: The growing number and variety of genetic network datasets increases the feasibility of understanding how drugs and diseases are associated at the molecular level. Properly selected features of the network representations of existing drug-disease associations can be used to infer novel indications of existing drugs. To find new drug-disease associations, we generated an integrative genetic network using combinations of interactions, including protein-protein interactions and gene regulatory network datasets. Within this network, network adjacencies of drug-drug and disease-disease were quantified using a scored path between target sets of them. Furthermore, the common topological module of drugs or diseases was extracted, and thereby the distance between topological drug-module and disease (or disease-module and drug) was quantified. These quantified scores were used as features for the prediction of novel drug-disease associations. Our classifiers using Random Forest, Multilayer Perceptron and C4.5 showed a high specificity and sensitivity (AUC score of 0.855, 0.828 and 0.797 respectively) in predicting novel drug indications, and displayed a better performance than other methods with limited drug and disease properties. Our predictions and current clinical trials overlap significantly across the different phases of drug development. We also identified and visualized the topological modules of predicted drug indications for certain types of cancers, and for Alzheimer's disease. Within the network, those modules show potential pathways that illustrate the mechanisms of new drug indications, including propranolol as a potential anticancer agent and telmisartan as treatment for Alzheimer's disease.PLoS ONE 10/2014; 9(10):e111668. DOI:10.1371/journal.pone.0111668 · 3.53 Impact Factor