CYP46A1 T/C polymorphism associated with the APOEε4 allele increases the risk of Alzheimer’s disease

Preclinical characterization of [18F]T-008, a novel PET imaging radioligand for cholesterol 24-hydroxylase

PURPOSE

Cholesterol 24-hydroxylase (CH24H) is a brain-specific enzyme that plays a major role in brain cholesterol homeostasis by converting cholesterol into 24S-hydroxycholesterol. The selective CH24H inhibitor soticlestat (TAK-935) is being pursued as a drug for treatment of seizures in developmental and epileptic encephalopathies. Herein, we describe the successful discovery and the preclinical validation of the novel radiolabeled CH24H ligand (3-[¹⁸F]fluoroazetidin-1-yl){1-[4-(4-fluorophenyl)pyrimidin-5-yl]piperidin-4-yl}methanone ([¹⁸F]T-008) and its tritiated analog, [³H]T-008.

METHODS

In vitro autoradiography (ARG) studies in the CH24H wild-type (WT) and knockout (KO) mouse brain sections were conducted using [³H]T-008. PET imaging was conducted in two adult rhesus macaques using [¹⁸F]T-008. Each macaque received two test-retest baseline scans and a series of two blocking doses of soticlestat administered prior to [¹⁸F]T-008 to determine the CH24H enzyme occupancy. PET data were analyzed with Logan graphical analysis using plasma input. A Lassen plot was applied to estimate CH24H enzyme occupancy by soticlestat.

RESULTS

In ARG studies, binding of [³H]T-008 was specific to CH24H in the mouse brain sections, which was not observed in CH24H KO or in wild-type mice after pretreatment with soticlestat. In rhesus PET studies, the rank order of [¹⁸F]T-008 uptake was striatum > cortical regions > cerebellum, which was consistent with CH24H distribution in the brain. Pre-blocking with soticlestat reduced the maximum uptake and increased the washout in all brain regions in a dose-dependent manner. Calculated global occupancy values for soticlestat at a dose of 0.89 mg/kg were 97-98%, indicating maximum occupancy.

CONCLUSION

The preclinical in vitro and in vivo evaluation of labeled T-008 demonstrates that [¹⁸F]T-008 is suitable for imaging CH24H in the brain and warrants further studies in humans.

Discovery of Soticlestat, a Potent and Selective Inhibitor for Cholesterol 24-Hydroxylase (CH24H)

Cholesterol 24-hydroxylase (CH24H, CYP46A1), a brain-specific cytochrome P450 (CYP) family enzyme, plays a role in the homeostasis of brain cholesterol by converting cholesterol to 24S-hydroxycholesterol (24HC). Despite a wide range of potential of CH24H as a drug target, no potent and selective inhibitors have been identified. Here, we report on the structure-based drug design (SBDD) of novel 4-arylpyridine derivatives based on the X-ray co-crystal structure of hit derivative 1b. Optimization of 4-arylpyridine derivatives led us to identify 3v ((4-benzyl-4-hydroxypiperidin-1-yl)(2,4'-bipyridin-3-yl)methanone, IC50 = 7.4 nM) as a highly potent, selective, and brain-penetrant CH24H inhibitor. Following oral administration to mice, 3v resulted in a dose-dependent reduction of 24HC levels in the brain (1, 3, and 10 mg/kg). Compound 3v (soticlestat, also known as TAK-935) is currently under clinical investigation for the treatment of Dravet syndrome and Lennox-Gastaut syndrome as a novel drug class for epilepsies.

Increased Plasma Level of 24S-Hydroxycholesterol and Polymorphism of CYP46A1 SNP (rs754203) Are Associated With Mild Cognitive Impairment in Patients With Type 2 Diabetes

Background

Abnormal cholesterol metabolism is common in type 2 diabetes mellitus (T2DM) and causes dementia. Cholesterol 24S-hydroxylase (CYP46A1) converts cholesterol into 24S-hydroxycholesterol (24-OHC) and maintains cholesterol homeostasis in the brain.

Objective

This study aimed to investigate the roles of 24-OHC and the CYP46A1 (rs754203) polymorphism in patients with T2DM and mild cognitive impairment (MCI).

Methods

A total of 193 Chinese patients with T2DM were recruited into two groups according to the Montreal Cognitive Assessment (MoCA). Demographic and clinical data were collected, and neuropsychological tests were conducted. Enzyme-linked immunosorbent assay (ELISA) and Seqnome method were used to detect the concentration of plasma 24-OHC and the CYP46A1 rs754203 genotype, respectively.

Results

Compared with 118 healthy cognition participants, patients with MCI (n = 75) displayed a higher plasma level of 24-OHC and total cholesterol concentration (all p = 0.031), while no correlation was found between them. In the overall diabetes population, the plasma level of 24-OHC was negatively correlated with MoCA (r = −0.150, p = 0.039), and it was further proved to be an independent risk factor of diabetic MCI (OR = 1.848, p = 0.001). Additionally, patients with MCI and the CC genotype of CYP46A1 rs754203 showed the highest plasma level of 24-OHC even though the difference was not statistically significant, and they obtained low scores in both the verbal fluency test and Stroop color and word test A (p = 0.008 and p = 0.029, respectively).

Conclusion

In patients with T2DM, high plasma level of 24-OHC and the CC genotype carrier of CYP46A1 rs754203 may portend a high risk of developing early cognitive impairment, including attention and executive deficits.

Advanced stratification analyses in molecular association meta-analysis: methodology and application

Background

Stratification analyses have been widely utilized in molecular association meta-analyses to estimate the interaction between genetic and environmental factors or to control for the confounding variables linked to a disease. Two calculation methods utilized in practical research, which are known as the variants of factorial stratification analysis and confounder-controlling stratification analysis in our nomenclature, have been applied in previous studies, but none of which have presented a methodology and application for these analyses.

Methods

In this paper, these two approaches are integrated and further developed into a standard procedure for stratification analysis. We first propose the advanced statistical methodology and theoretical algorithm of these three types of stratification analysis and then provide two example applications in meta-analyses of molecular association to illustrate the computing processes and interpretation of the results.

Results

The standard stratification analysis synthesizes the advantages of the first two practical methods, including identifying and controlling confounding moderators or revealing and calculating gene-environment interactions, to efficiently classify the real influence of various investigated factors on a disease in the general population. Additional challenges concerning this method and their potential solutions are also discussed, such as the approach to utilizing only the partially stratified data available in meta-research practice.

Conclusions

The standard stratification method will be extensively applicable to rapidly expanding future research on the complex relationships among genetics, environment, disease, and other variables.

Controlling for confounding factors and revealing their interactions in genetic association meta-analyses: a computing method and application for stratification analyses

Subgroup and stratification analyses have been widely applied in genetic association studies to compare the effects of different factors or control for the effects of the confounding variables associated with a disease. However, studies have not systematically provided application standards and computing methods for stratification analyses. Based on the Mantel-Haenszel and Inverse-Variant approaches and two practical computing methods described in previous studies, we propose a standard stratification method for meta-analyses that contains two sequential steps: factorial stratification analysis and confounder-controlling stratification analysis. Examples of genetic association meta-analyses are used to illustrate these points. The standard stratification analysis method identifies interacting effects on investigated factors and controls for confounding variables, and this method effectively reveals the real effects of these factors and confounding variables on a disease in an overall study population. We also discuss important issues concerning stratification for meta-analyses, such as conceptual confusion between subgroup and stratification analyses, and incorrect calculations previously used for factorial stratification analyses. This standard stratification method will have extensive applications in future research for increasing studies on the complicated relationships between genetics and disease.

Multiplex Single Nucleotide Polymorphism Analyses

Quantitative polymerase chain reaction (qPCR) is a routinely used method for detection and quantitation of gene expression in real time. This is achieved through the incorporation and measurement of fluorescent reporter probes in the amplified cDNA strands, since the fluorescent signals increase as the reaction progresses. The availability of multiple probes that fluoresce at different wavelengths allows for multiplexing as this gives rise to amplicons with unique fluorescent signatures. Here, we describe a method using the SensiFAST and SensiFAST One-Step probe kits which allows simultaneous real-time quantitation of up to 5 amplicons.

ABCA1-Mediated Cholesterol Efflux Capacity to Cerebrospinal Fluid Is Reduced in Patients With Mild Cognitive Impairment and Alzheimer's Disease

Background

Animal and human studies indicate that ABCA1‐mediated cholesterol transport is important in Alzheimer's disease (AD). We hypothesized that the efficiency of cerebrospinal fluid (CSF) to facilitate ABCA1‐mediated cholesterol efflux would be reduced in participants with mild cognitive impairment (MCI) or AD compared with cognitively healthy participants.

Methods and Results

CSF was collected from a cross‐sectional study of cognitively healthy participants (n=47) and participants with MCI (n=35) or probable AD (n=26).The capacity of CSF to mediate cholesterol transport was assessed using a BHK cell line that can be induced to express the ABCA1 transporter. ABCA1‐mediated cholesterol efflux capacity was 30% less in participants with MCI or AD compared with cognitively healthy participants (P<0.001 for both). Cholesterol efflux capacity correlated with CSF cholesterol content (r=0.37, P<0.001). CSF phosphatidylcholine decreased in participants with MCI and AD compared with cognitively healthy participants (9% less in MCI and 27% less in AD compared with cognitively healthy participants, P=0.01) and correlated with CSF efflux capacity (r=0.3, P=0.001). CSF sphingomyelin also correlated with the efflux capacity (r=0.24, P=0.02). Concentrations of CSF apoA‐I and apoE did not significantly correlate with measures of efflux capacity.

Conclusions

In people with MCI and AD, the capacity of CSF to facilitate ABCA1‐mediated cholesterol efflux is impaired. This lesser cholesterol efflux in MCI supports a pathophysiological role for ABCA1‐mediated cholesterol transport in early neurodegeneration.