Pharmacogenetic studies in Alzheimer disease

Advanced patient-specific microglia cell models for pre-clinical studies in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is an incurable neurodegenerative disorder with a rapidly increasing prevalence worldwide. Current approaches targeting hallmark pathological features of AD have had no consistent clinical benefit. Neuroinflammation is a major contributor to neurodegeneration and hence, microglia, the brain's resident immune cells, are an attractive target for potentially more effective therapeutic strategies. However, there is no current in vitro model system that captures AD patient-specific microglial characteristics using physiologically relevant and experimentally flexible culture conditions.

METHODS

To address this shortcoming, we developed novel 3D Matrigel-based monocyte-derived microglia-like cell (MDMi) mono-cultures and co-cultures with neuro-glial cells (ReNcell VM). We used single-cell RNA sequencing (scRNAseq) analysis to compare the transcriptomic signatures of MDMi between model systems (2D, 3D and 3D co-culture) and against published human microglia datasets. To demonstrate the potential of MDMi for use in personalized pre-clinical strategies, we generated and characterized MDMi models from sixteen AD patients and matched healthy controls, and profiled cytokine responses upon treatment with anti-inflammatory drugs (dasatinib and spiperone).

RESULTS

MDMi in 3D exhibited a more branched morphology and longer survival in culture compared to 2D. scRNAseq uncovered distinct MDMi subpopulations that exhibit higher functional heterogeneity and best resemble human microglia in 3D co-culture. AD MDMi in 3D co-culture showed altered cell-to-cell interactions, growth factor and cytokine secretion profiles and responses to amyloid-β. Drug testing assays revealed patient- and model-specific cytokine responses.

CONCLUSION

Our study presents a novel, physiologically relevant and AD patient-specific 3D microglia cell model that opens avenues towards improving personalized drug development strategies in AD.

Brain Age Is Associated with Cognitive Outcomes of Cholinesterase Inhibitor Treatment in Patients with Mild Cognitive Impairment

Background

The effect of cholinesterase inhibitor (ChEI) on mild cognitive impairment (MCI) is controversial. Brain age has been shown to predict Alzheimer's disease conversion from MCI.

Objective

The study aimed to show that brain age is related to cognitive outcomes of ChEI treatment in MCI.

Methods

Brain MRI, the Clinical Dementia Rating (CDR) and Mini-Mental State Exam (MMSE) scores were retrospectively retrieved from a ChEI treatment database. Patients who presented baseline CDR of 0.5 and received ChEI treatment for at least 2 years were selected. Patients with stationary or improved cognition as verified by the CDR and MMSE were categorized to the ChEI-responsive group, and those with worsened cognition were assigned to the ChEI-unresponsive group. A gray matter brain age model was built with a machine learning algorithm by training T1-weighted MRI data of 362 healthy participants. The model was applied to each patient to compute predicted age difference (PAD), i.e. the difference between brain age and chronological age. The PADs were compared between the two groups.

Results

58 patients were found to fit the ChEI-responsive criteria in the patient data, and 58 matched patients that fit the ChEI-unresponsive criteria were compared. ChEI-unresponsive patients showed significantly larger PAD than ChEI-responsive patients (8.44±8.78 years versus 3.87±9.02 years, p = 0.0067).

Conclusions

Gray matter brain age is associated with cognitive outcomes after 2 years of ChEI treatment in patients with the CDR of 0.5. It might facilitate the clinical trials of novel therapeutics for MCI.

Pharmacogenetics of Donepezil and Memantine in Healthy Subjects

Donepezil and memantine are the most common drugs used for Alzheimer's disease. Their low effectiveness could partly be explained by genetic factors. Thus, we aim to identify Single Nucleotide Polymorphisms (SNPs) associated with pharmacokinetics, pharmacodynamics, and the safety of donepezil and memantine. For this regard, 25 volunteers enrolled in a bioequivalence clinical trial were genotyped for 67 SNPs in 21 genes with a ThermoFisher QuantStudio 12K Flex OpenArray. The statistical strategy included a univariate analysis that analyzed the association of these SNPs with pharmacokinetic parameters or the development of adverse drug reactions (ADRs) followed by a Bonferroni-corrected multivariate regression. Statistical analyses were performed with SPSS software v.21 and R commander (version v3.6.3). In the univariate analysis, fourteen and sixteen SNPs showed a significant association with memantine's and donepezil's pharmacokinetic parameters, respectively. Rs20417 (PTGS2) was associated with the development of at least one ADR. However, none of these associations reached the significance threshold in the Bonferroni-corrected multivariate analysis. In conclusion, we did not observe any significant association of the SNPs analyzed with memantine and donepezil pharmacokinetics or ADRs. Current evidence on memantine and donepezil pharmacogenetics does not justify their inclusion in pharmacogenetic guidelines.