The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Cell type-specific functions of Alzheimer's disease endocytic risk genes

Endocytosis is a key cellular pathway required for the internalization of cellular nutrients, lipids and receptor-bound cargoes. It is also critical for the recycling of cellular components, cellular trafficking and membrane dynamics. The endocytic pathway has been consistently implicated in Alzheimer's disease (AD) through repeated genome-wide association studies and the existence of rare coding mutations in endocytic genes. BIN1 and PICALM are two of the most significant late-onset AD risk genes after APOE and are both key to clathrin-mediated endocytic biology. Pathological studies also demonstrate that endocytic dysfunction is an early characteristic of late-onset AD, being seen in the prodromal phase of the disease. Different cell types of the brain have specific requirements of the endocytic pathway. Neurons require efficient recycling of synaptic vesicles and microglia use the specialized form of endocytosis-phagocytosis-for their normal function. Therefore, disease-associated changes in endocytic genes will have varied impacts across different cell types, which remains to be fully explored. Given the genetic and pathological evidence for endocytic dysfunction in AD, understanding how such changes and the related cell type-specific vulnerabilities impact normal cellular function and contribute to disease is vital and could present novel therapeutic opportunities. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

PICALM and Alzheimer's Disease: An Update and Perspectives

Genome-wide association studies (GWAS) have identified the PICALM (Phosphatidylinositol binding clathrin-assembly protein) gene as the most significant genetic susceptibility locus after APOE and BIN1. PICALM is a clathrin-adaptor protein that plays a critical role in clathrin-mediated endocytosis and autophagy. Since the effects of genetic variants of PICALM as AD-susceptibility loci have been confirmed by independent genetic studies in several distinct cohorts, there has been a number of in vitro and in vivo studies attempting to elucidate the underlying mechanism by which PICALM modulates AD risk. While differential modulation of APP processing and Aβ transcytosis by PICALM has been reported, significant effects of PICALM modulation of tau pathology progression have also been evidenced in Alzheimer's disease models. In this review, we summarize the current knowledge about PICALM, its physiological functions, genetic variants, post-translational modifications and relevance to AD pathogenesis.

The Links between Cardiovascular Diseases and Alzheimer's Disease

The root cause of non-inherited Alzheimer's disease (AD) remains unknown despite hundreds of research studies performed to attempt to solve this problem. Since proper prophylaxis remains the best strategy, many scientists have studied the risk factors that may affect AD development. There is robust evidence supporting the hypothesis that cardiovascular diseases (CVD) may contribute to AD progression, as the diseases often coexist. Therefore, a lack of well-defined diagnostic criteria makes studying the relationship between AD and CVD complicated. Additionally, inflammation accompanies the pathogenesis of AD and CVD, and is not only a consequence but also implicated as a significant contributor to the course of the diseases. Of note, АроЕε4 is found to be one of the major risk factors affecting both the cardiovascular and nervous systems. According to genome wide association and epidemiological studies, numerous common risk factors have been associated with the development of AD-related pathology. Furthermore, the risk of developing AD and CVDs appears to be increased by a wide range of conditions and lifestyle factors: hypertension, dyslipidemia, hypercholesterolemia, hyperhomocysteinemia, gut/oral microbiota, physical activity, and diet. This review summarizes the literature and provides possible mechanistic links between CVDs and AD.

Association of Alzheimer's disease risk variants on the PICALM gene with PICALM expression, core biomarkers, and feature neurodegeneration

It is still unclear how PICALM mutations influence the risk of Alzheimer’s disease (AD). We tested the association of AD risk variants on the PICALM gene with PICALM expression and AD feature endophenotypes. Bioinformatic methods were used to annotate the functionalities and to select the tag single nucleotide polymorphisms (SNPs). Multiple regressions were used to examine the cross-sectional and longitudinal influences of tag SNPs on cerebrospinal fluid (CSF) AD biomarkers and neurodegenerations. A total of 59 SNPs, among which 75% were reported in Caucasians, were associated with AD risk. Of these, 73% were linked to PICALM expression in the whole blood (p < 0.0001) and/or brain regions (p < 0.05). Eleven SNPs were selected as tag SNPs in Caucasians. rs510566 (T allele) was associated with decreased CSF ptau and ptau/abeta42 ratio. The G allele of rs1237999 and rs510566 was linked with greater reserve capacities of the hippocampus, parahippocampus, middle temporal lobe, posterior cingulate, and precuneus. The longitudinal analyses revealed four loci that could predict dynamic changes of CSF ptau and ptau/abeta42 ratio (rs10501610, p = 0.0001) or AD feature neurodegeneration (rs3851179, rs592297, and rs7480193, p < 0.005). Overall, the genetic, bioinformatic, and association studies tagged four SNPs (rs3851179, rs7480193, rs510566, and rs1237999) as the most prominent PICALM loci contributing to AD in Caucasians.

The Radiogenomics of Late-onset Alzheimer Disease

Radiogenomics, defined as the integrated analysis of radiologic imaging and genetic data, is a well-established tool shown to augment neuroimaging in the clinical diagnosis, prognostication, and scientific study of late-onset Alzheimer disease (LOAD). Early work using candidate single nucleotide polymorphisms (SNPs) identified genetic variation in APOE, BIN1, CLU, and CR1 as key modifiers of brain structure and function using magnetic resonance imaging (MRI). More recently, polygenic risk scores used in conjunction with MRI and positron emission tomography have shown great promise as a risk-stratification tool for clinical trials and care-management decisions. In addition, recent work using multimodal MRI and positron emission tomography as proxies of LOAD progression has identified novel risk variants that are enhancing our understanding of LOAD pathophysiology and progression. Herein, we highlight key studies and trends in the radiogenomics of LOAD over the past two decades and their implications for clinical practice and scientific research.

Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative

INTRODUCTION

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials.

METHODS

We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/).

RESULTS

(1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies.

DISCUSSION

ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

Impact of late-onset Alzheimer's genetic risk factors on beta-amyloid endocytic production

The increased production of the 42 aminoacids long beta-amyloid (Aβ42) peptide has been established as a causal mechanism of the familial early onset Alzheimer's disease (AD). In contrast, the causal mechanisms of the late-onset AD (LOAD), that affects most AD patients, remain to be established. Indeed, Aβ42 accumulation has been detected more than 30 years before diagnosis. Thus, the mechanisms that control Aβ accumulation in LOAD likely go awry long before pathogenesis becomes detectable. Early on, APOE4 was identified as the biggest genetic risk factor for LOAD. However, since APOE4 is not present in all LOAD patients, genome-wide association studies of thousands of LOAD patients were undertaken to identify other genetic variants that could explain the development of LOAD. PICALM, BIN1, CD2AP, SORL1, and PLD3 are now with APOE4 among the identified genes at highest risk in LOAD that have been implicated in Aβ42 production. Recent evidence indicates that the regulation of the endocytic trafficking of the amyloid precursor protein (APP) and/or its secretases to and from sorting endosomes is determinant for Aβ42 production. Thus, here, we will review the described mechanisms, whereby these genetic risk factors can contribute to the enhanced endocytic production of Aβ42. Dissecting causal LOAD mechanisms of Aβ42 accumulation, underlying the contribution of each genetic risk factor, will be required to identify therapeutic targets for novel personalized preventive strategies.

Genetic interaction is associated with lower metabolic connectivity and memory impairment in clinically mild Alzheimer's disease

Metabolic connectivity as showed by [18F] fluorodeoxyglucose (FDG) positron emission tomography (FDG-PET) reflects neuronal connectivity. The aim of this study was to investigate the genetic impact on metabolic connectivity in default mode subnetworks and its clinical-pathological relationships in patients with Alzheimer's disease (AD). We separately investigated the modulation of 2 default mode subnetworks, as identified with independent component analysis, by comparing APOE-ε4 carriers to noncarriers with AD. We further analyzed the interaction effects of APOE (APOE-ε4 carriers vs noncarriers) with PICALM (rs3851179-GG vs rs3851179-A-allele carriers) on episodic memory (EM) deficits, reduction in cerebral metabolic rate for glucose (CMRgl) and decreased metabolic connectivity in default mode subnetworks. The metabolic connectivity in the ventral default mode network (vDMN) was positively correlated with EM scores (β =0.441, P < .001). The APOE-ε4 carriers had significantly lower metabolic connectivity in the vDMN than the APOE-ε4 carriers (t(96) = -2.233, P = .028). There was an effect of the APOE-PICALM (rs3851179) interactions on reduced CMRgl in regions of vDMN (P < .001), and on memory deficits (F_3,93 =5.568, P = .020). This study identified that PICALM may modulates memory deficits, reduced CMRgl and decreased metabolic connectivity in the vDMN in APOE-ε4 carriers. [18F] FDG-PET-based metabolic connectivity may serve a useful tool to elucidate the neural networks underlying clinical-pathological relationships in AD.

Data integration for functional annotation of regulatory single nucleotide polymorphisms associated with Alzheimer's disease susceptibility

BACKGROUND

Alzheimer's disease (AD), the most common form of dementia affects 24.3 million people worldwide. More than twenty genetic loci have been associated with AD and a significant number of genetic variants were mapped within these loci. A large proportion of genome wide significant variants lie outside the coding region. However, the plausible function of these variants is still unexplored.

OBJECTIVE

The present study aimed to unravel the regulatory role of proxy single nucleotide polymorphisms (SNPs), to determine their risk of developing AD.

METHODS

The RegulomeDB was employed to predict the regulatory role of proxy SNPs. Protein association network and functional enrichment analysis was performed using String10.5 and gene ontology, respectively.

RESULTS

A total of 451 SNPs were examined through SNAP web portal (r² ≤ 0.80) which returned 2186 proxy SNPs in linkage disequilibrium (LD) with genome wide significant SNPs for AD. Out of 2186 SNPs analyzed in RegulomeDB, 151 had the scores < 3 that indicates the high degree of their potential regulatory function. Further analysis revealed that out of these 151 SNPs, 37 were genome wide significant for AD, 17 were significantly associated with diseases other than AD, 89 were proxy SNPs (not genome wide significant) for various diseases including AD while 8 SNPs were novel proxy SNPs for AD.

CONCLUSION

These findings support the notion that the non-coding variants can be strongly associated with disease risk. Further validation through genome wide association studies will be helpful for the elucidation of their regulatory potential.