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Swinford CG, Risacher SL, Vosmeier A, Deardorff R, Chumin EJ, Dzemidzic M, Wu YC, Gao S, McDonald BC, Yoder KK, Unverzagt FW, Wang S, Farlow MR, Brosch JR, Clark DG, Apostolova LG, Sims J, Wang DJ, Saykin AJ. Amyloid and tau pathology are associated with cerebral blood flow in a mixed sample of nondemented older adults with and without vascular risk factors for Alzheimer's disease. Neurobiol Aging 2023; 130:103-113. [PMID: 37499587 PMCID: PMC10529454 DOI: 10.1016/j.neurobiolaging.2023.06.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 05/30/2023] [Accepted: 06/21/2023] [Indexed: 07/29/2023]
Abstract
Identification of biomarkers for the early stages of Alzheimer's disease (AD) is an imperative step in developing effective treatments. Cerebral blood flow (CBF) is a potential early biomarker for AD; generally, older adults with AD have decreased CBF compared to normally aging peers. CBF deviates as the disease process and symptoms progress. However, further characterization of the relationships between CBF and AD risk factors and pathologies is still needed. We assessed the relationships between CBF quantified by arterial spin-labeled magnetic resonance imaging, hypertension, APOEε4, and tau and amyloid positron emission tomography in 77 older adults: cognitively normal, subjective cognitive decline, and mild cognitive impairment. Tau and amyloid aggregation were related to altered CBF, and some of these relationships were dependent on hypertension or APOEε4 status. Our findings suggest a complex relationship between risk factors, AD pathologies, and CBF that warrants future studies of CBF as a potential early biomarker for AD.
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Affiliation(s)
- Cecily G Swinford
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA
| | - Aaron Vosmeier
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA
| | - Rachael Deardorff
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA
| | - Evgeny J Chumin
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Mario Dzemidzic
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA
| | - Sujuan Gao
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Biostatistics and Health Data Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Brenna C McDonald
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Karmen K Yoder
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA
| | - Frederick W Unverzagt
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sophia Wang
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin R Farlow
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jared R Brosch
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David G Clark
- Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA
| | - Justin Sims
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Danny J Wang
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer's Disease Research Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
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Cacabelos R. Pharmacogenetic considerations when prescribing cholinesterase inhibitors for the treatment of Alzheimer's disease. Expert Opin Drug Metab Toxicol 2020; 16:673-701. [PMID: 32520597 DOI: 10.1080/17425255.2020.1779700] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
INTRODUCTION Cholinergic dysfunction, demonstrated in the late 1970s and early 1980s, led to the introduction of acetylcholinesterase inhibitors (AChEIs) in 1993 (Tacrine) to enhance cholinergic neurotransmission as the first line of treatment against Alzheimer's disease (AD). The new generation of AChEIs, represented by Donepezil (1996), Galantamine (2001) and Rivastigmine (2002), is the only treatment for AD to date, together with Memantine (2003). AChEIs are not devoid of side-effects and their cost-effectiveness is limited. An option to optimize the correct use of AChEIs is the implementation of pharmacogenetics (PGx) in the clinical practice. AREAS COVERED (i) The cholinergic system in AD, (ii) principles of AD PGx, (iii) PGx of Donepezil, Galantamine, Rivastigmine, Huperzine and other treatments, and (iv) practical recommendations. EXPERT OPINION The most relevant genes influencing AChEI efficacy and safety are APOE and CYPs. APOE-4 carriers are the worst responders to AChEIs. With the exception of Rivastigmine (UGT2B7, BCHE-K), the other AChEIs are primarily metabolized via CYP2D6, CYP3A4, and UGT enzymes, with involvement of ABC transporters and cholinergic genes (CHAT, ACHE, BCHE, SLC5A7, SLC18A3, CHRNA7) in most ethnic groups. Defective variants may affect the clinical response to AChEIs. PGx geno-phenotyping is highly recommended prior to treatment.
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Affiliation(s)
- Ramón Cacabelos
- Department of Genomic Medicine, EuroEspes Biomedical Research Center, International Center of Neuroscience and Genomic Medicine , Bergondo, Corunna, Spain
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Pharmacogenomics of Cognitive Dysfunction and Neuropsychiatric Disorders in Dementia. Int J Mol Sci 2020; 21:ijms21093059. [PMID: 32357528 PMCID: PMC7246738 DOI: 10.3390/ijms21093059] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 04/21/2020] [Accepted: 04/21/2020] [Indexed: 02/07/2023] Open
Abstract
Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6–10 drugs/day with the consequent risk for drug–drug interactions and adverse drug reactions (ADRs >80%) which accelerate cognitive decline. The pharmacoepigenetic machinery is integrated by pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes redundantly and promiscuously regulated by epigenetic mechanisms. CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 geno-phenotypes are involved in the metabolism of over 90% of drugs currently used in patients with dementia, and only 20% of the population is an extensive metabolizer for this tetragenic cluster. ADRs associated with anti-dementia drugs, antipsychotics, antidepressants, anxiolytics, hypnotics, sedatives, and antiepileptic drugs can be minimized by means of pharmacogenetic screening prior to treatment. These drugs are substrates, inhibitors, or inducers of 58, 37, and 42 enzyme/protein gene products, respectively, and are transported by 40 different protein transporters. APOE is the reference gene in most pharmacogenetic studies. APOE-3 carriers are the best responders and APOE-4 carriers are the worst responders; likewise, CYP2D6-normal metabolizers are the best responders and CYP2D6-poor metabolizers are the worst responders. The incorporation of pharmacogenomic strategies for a personalized treatment in dementia is an effective option to optimize limited therapeutic resources and to reduce unwanted side-effects.
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