Associations of the Top 20 Alzheimer Disease Risk Variants With Brain Amyloidosis

Very low levels of ABCA7 in the cerebrum and Alzheimer's disease onset between the ages of 60 and 80 independently of APOE

This cross-sectional study addressed the ABCA7-Alzheimer's disease (AD) association. ABCA7 protein levels were quantified in 3 cerebral regions of brain donors with Braak neurofibrillary tangle (NFT) stages 0-V. Ordinal regression models were implemented to estimate the effect of ABCA7 on stopping in an earlier Braak NFT stage versus progressing to the later stages in 2 prespecified age segments. In the final model, high ABCA7 levels in the parietal cortex increased the odds of remaining cognitively healthy (ie, in stages 0/I) versus experiencing AD onset (ie, progressing to stages II-V) in the 61-80 age segment (OR = 2.87, adj 95% CI = 1.41-7.86, adj P = .007, n = 109), after controlling for APOE and other covariates. No ABCA7-AD association was found in the 81-98 age segment (n = 113). Parietal ABCA7 levels in 61-80-year-old with stages II-V were very low, even significantly lower than in 81-98-year-old with stages II-V. ABCA7 levels in the prefrontal cortex and hippocampus predicted AD onset in the 61-80 age segment after adjustment for APOE. ABCA7 levels were also the lowest in 61-80-year-old with frequent neuritic plaques. Thus, very low ABCA7 levels in the cerebrum are associated with AD onset in the 7th-8th decade of life.

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent form of dementia, affecting millions worldwide with a progressive decline in cognitive abilities. The AD continuum encompasses a prodormal stage known as Mild Cognitive Impairment (MCI), where patients may either progress to AD (MCIc) or remain stable (MCInc). Understanding the underlying mechanisms of AD requires complementary analysis derived from different data sources, leading to the development of multimodal deep learning models. In this study, we leveraged structural and functional Magnetic Resonance Imaging (sMRI/fMRI) to investigate the disease-induced grey matter and functional network connectivity changes. Moreover, considering AD's strong genetic component, we introduce Single Nucleotide Polymorphisms (SNPs) as a third channel. Given such diverse inputs, missing one or more modalities is a typical concern of multimodal methods. We hence propose a novel deep learning based classification framework where generative module employing Cycle Generative Adversarial Networks (cGAN) was adopted to impute missing data within the latent space. Additionally, we adopted an Explainable Artificial Intelligence (XAI) method, Integrated Gradients (IG), to extract input features relevance, enhancing our understanding of the learned representations. Two critical tasks were addressed: AD detection and MCI conversion prediction. Experimental results showed that our framework was able to reach the state-of-the-art in the classification of CN vs AD reaching an average test accuracy of 0.926 ± 0.02. For the MCInc vs MCIc task, we achieved an average prediction accuracy of 0.711 ± 0.01 using the pre-trained model for CN and AD. The interpretability analysis revealed that the classification performance was led by significant grey matter modulations in cortical and subcortical brain areas well known for their association with AD. Moreover, impairments in sensory-motor and visual resting state network connectivity along the disease continuum, as well as mutations in SNPs defining biological processes linked to amyloid-beta and cholesterol formation clearance and regulation, were identified as contributors to the achieved performance. Overall, our integrative deep learning approach shows promise for AD detection and MCI prediction, while shading light on important biological insights.

The Abca7V1613M variant reduces Aβ generation, plaque load, and neuronal damage

BACKGROUND

Variants in ABCA7, a member of the ABC transporter superfamily, have been associated with increased risk for developing late onset Alzheimer's disease (LOAD).

METHODS

CRISPR-Cas9 was used to generate an Abca7V1613M variant in mice, modeling the homologous human ABCA7V1599M variant, and extensive characterization was performed.

RESULTS

Abca7V1613M microglia show differential gene expression profiles upon lipopolysaccharide challenge and increased phagocytic capacity. Homozygous Abca7V1613M mice display elevated circulating cholesterol and altered brain lipid composition. When crossed with 5xFAD mice, homozygous Abca7V1613M mice display fewer Thioflavin S-positive plaques, decreased amyloid beta (Aβ) peptides, and altered amyloid precursor protein processing and trafficking. They also exhibit reduced Aβ-associated inflammation, gliosis, and neuronal damage.

DISCUSSION

Overall, homozygosity for the Abca7V1613M variant influences phagocytosis, response to inflammation, lipid metabolism, Aβ pathology, and neuronal damage in mice. This variant may confer a gain of function and offer a protective effect against Alzheimer's disease-related pathology.

HIGHLIGHTS

ABCA7 recognized as a top 10 risk gene for developing Alzheimer's disease. Loss of function mutations result in increased risk for LOAD. V1613M variant reduces amyloid beta plaque burden in 5xFAD mice. V1613M variant modulates APP processing and trafficking in 5xFAD mice. V1613M variant reduces amyloid beta-associated damage in 5xFAD mice.

Small RNA Changes in Plasma Have Potential for Early Diagnosis of Alzheimer's Disease before Symptom Onset

Alzheimer's disease (AD), due to its multifactorial nature and complex etiology, poses challenges for research, diagnosis, and treatment, and impacts millions worldwide. To address the need for minimally invasive, repeatable measures that aid in AD diagnosis and progression monitoring, studies leveraging RNAs associated with extracellular vesicles (EVs) in human biofluids have revealed AD-associated changes. However, the validation of AD biomarkers has suffered from the collection of samples from differing points in the disease time course or a lack of confirmed AD diagnoses. Here, we integrate clinical diagnosis and postmortem pathology data to form more accurate experimental groups and use small RNA sequencing to show that EVs from plasma can serve as a potential source of RNAs that reflect disease-related changes. Importantly, we demonstrated that these changes are identifiable in the EVs of preclinical patients, years before symptom manifestation, and that machine learning models based on differentially expressed RNAs can help predict disease conversion or progression. This research offers critical insight into early disease biomarkers and underscores the significance of accounting for disease progression and pathology in human AD studies.

Alzheimer's Disease: Models and Molecular Mechanisms Informing Disease and Treatments

Alzheimer's Disease (AD) is a complex neurodegenerative disease resulting in progressive loss of memory, language and motor abilities caused by cortical and hippocampal degeneration. This review captures the landscape of understanding of AD pathology, diagnostics, and current therapies. Two major mechanisms direct AD pathology: (1) accumulation of amyloid β (Aβ) plaque and (2) tau-derived neurofibrillary tangles (NFT). The most common variants in the Aβ pathway in APP, PSEN1, and PSEN2 are largely responsible for early-onset AD (EOAD), while MAPT, APOE, TREM2 and ABCA7 have a modifying effect on late-onset AD (LOAD). More recent studies implicate chaperone proteins and Aβ degrading proteins in AD. Several tests, such as cognitive function, brain imaging, and cerebral spinal fluid (CSF) and blood tests, are used for AD diagnosis. Additionally, several biomarkers seem to have a unique AD specific combination of expression and could potentially be used in improved, less invasive diagnostics. In addition to genetic perturbations, environmental influences, such as altered gut microbiome signatures, affect AD. Effective AD treatments have been challenging to develop. Currently, there are several FDA approved drugs (cholinesterase inhibitors, Aß-targeting antibodies and an NMDA antagonist) that could mitigate AD rate of decline and symptoms of distress.

Identifying the joint signature of brain atrophy and gene variant scores in Alzheimer's Disease

The joint modeling of genetic data and brain imaging information allows for determining the pathophysiological pathways of neurodegenerative diseases such as Alzheimer's disease (AD). This task has typically been approached using mass-univariate methods that rely on a complete set of Single Nucleotide Polymorphisms (SNPs) to assess their association with selected image-derived phenotypes (IDPs). However, such methods are prone to multiple comparisons bias and, most importantly, fail to account for potential cross-feature interactions, resulting in insufficient detection of significant associations. Ways to overcome these limitations while reducing the number of traits aim at conveying genetic information at the gene level and capturing the integrated genetic effects of a set of genetic variants, rather than looking at each SNP individually. Their associations with brain IDPs are still largely unexplored in the current literature, though they can uncover new potential genetic determinants for brain modulations in the AD continuum. In this work, we explored an explainable multivariate model to analyze the genetic basis of the grey matter modulations, relying on the AD Neuroimaging Initiative (ADNI) phase 3 dataset. Cortical thicknesses and subcortical volumes derived from T1-weighted Magnetic Resonance were considered to describe the imaging phenotypes. At the same time the genetic counterpart was represented by gene variant scores extracted by the Sequence Kernel Association Test (SKAT) filtering model. Moreover, transcriptomic analysis was carried on to assess the expression of the resulting genes in the main brain structures as a form of validation. Results highlighted meaningful genotype-phenotype interactionsas defined by three latent components showing a significant difference in the projection scores between patients and controls. Among the significant associations, the model highlighted EPHX1 and BCAS1 gene variant scores involved in neurodegenerative and myelination processes, hence relevant for AD. In particular, the first was associated with decreased subcortical volumes and the second with decreasedtemporal lobe thickness. Noteworthy, BCAS1 is particularly expressed in the dentate gyrus. Overall, the proposed approach allowed capturing genotype-phenotype interactions in a restricted study cohort that was confirmed by transcriptomic analysis, offering insights into the underlying mechanisms of neurodegeneration in AD in line with previous findings and suggesting new potential disease biomarkers.

Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease

Many of the Alzheimer's disease (AD) risk genes are specifically expressed in microglia and astrocytes, but how and when the genetic risk localizing to these cell types contributes to AD pathophysiology remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets and uncover the impact of cell-type-specific genetic risk on AD endophenotypes. In an autopsy dataset spanning all stages of AD (n = 1457), the astrocytic ADPRS affected diffuse and neuritic plaques (amyloid-β), while microglial ADPRS affected neuritic plaques, microglial activation, neurofibrillary tangles (tau), and cognitive decline. In an independent neuroimaging dataset of cognitively unimpaired elderly (n = 2921), astrocytic ADPRS was associated with amyloid-β, and microglial ADPRS was associated with amyloid-β and tau, connecting cell-type-specific genetic risk with AD pathology even before symptom onset. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

Genome-wide association study in Alzheimer's disease: a bibliometric and visualization analysis

BACKGROUND

Thousands of research studies concerning genome-wide association studies (GWAS) in Alzheimer's disease (AD) have been published in the last decades. However, a comprehensive understanding of the current research status and future development trends of GWAS in AD have not been clearly shown. In this study, we tried to gain a systematic overview of GWAS in AD by bibliometric and visualization analysis.

METHODS

The literature search terms are: ("genome-wide analysis" or "genome-wide association study" or "whole-genome analysis") AND ("Alzheimer's Disease" or "Alzheimer Disease"). Relevant publications were extracted from the Web of Science Core Collection (WoSCC) database. Collected data were further analyzed using VOSviewer, CiteSpace and R package Bibliometrix. The countries, institutions, authors and scholar collaborations were investigated. The co-citation analysis of publications was visualized. In addition, research hotspots and fronts were examined.

RESULTS

A total of 1,350 publications with 59,818 citations were identified. The number of publications and citations presented a significant rising trend since 2013. The United States was the leading country with an overwhelming number of publications (775) and citations (42,237). The University of Washington and Harvard University were the most prolific institutions with 101 publications each. Bennett DA was the most influential researcher with the highest local H-index. Neurobiology of Aging was the journal with the highest number of publications. Aβ, tau, immunity, microglia and DNA methylation were research hotspots. Disease and causal variants were research fronts.

CONCLUSION

The most frequently studied AD pathogenesis and research hotspots are (1) Aβ and tau, (2) immunity and microglia, with TREM2 as a potential immunotherapy target, and (3) DNA methylation. The research fronts are (1) looking for genetic similarities between AD and other neurological diseases and syndromes, and (2) searching for causal variants of AD. These hotspots suggest noteworthy directions for future studies on AD pathogenesis and genetics, in which basic research regarding immunity is promising for clinical conversion. The current under-researched directions are (1) GWAS in AD biomarkers based on large sample sizes, (2) studies of causal variants of AD, and (3) GWAS in AD based on non-European populations, which need to be strengthened in the future.

CSF biomarker analysis of ABCA7 mutation carriers suggests altered APP processing and reduced inflammatory response

BACKGROUND

The Alzheimer's disease (AD) risk gene ABCA7 has suggested functions in lipid metabolism and the immune system. Rare premature termination codon (PTC) mutations and an expansion of a variable number of tandem repeats (VNTR) polymorphism in the gene, both likely cause a lower ABCA7 expression and hereby increased risk for AD. However, the exact mechanism of action remains unclear. By studying CSF biomarkers reflecting different types of AD-related pathological processes, we aim to get a better insight in those processes and establish a biomarker profile of mutation carriers.

METHODS

The study population consisted of 229 AD patients for whom CSF was available and ABCA7 sequencing and VNTR genotyping had been performed. This included 28 PTC mutation and 16 pathogenic expansion carriers. CSF levels of Aβ1-42, Aβ1-40, P-tau181, T-tau, sAPPα, sAPPβ, YKL-40, and hFABP were determined using ELISA and Meso Scale Discovery assays. We compared differences in levels of these biomarkers and the Aβ ratio between AD patients with or without an ABCA7 PTC mutation or expansion using linear regression on INT-transformed data with APOE-status, age and sex as covariates.

RESULTS

Carriers of ABCA7 expansion mutations had significantly lower Aβ1-42 levels (P = 0.022) compared with non-carrier patients. The effect of the presence of ABCA7 mutations on CSF levels was especially pronounced in APOE ε4-negative carriers. In addition, VNTR expansion carriers had reduced Aβ1-40 (P = 0.023), sAPPα (P = 0.047), sAPPβ (P = 0.016), and YKL-40 (P = 0.0036) levels.

CONCLUSIONS

Our results are suggestive for an effect on APP processing by repeat expansions given the changes in the amyloid-related CSF biomarkers that were found in carriers. The decrease in YKL-40 levels in expansion carriers moreover suggests that these patients potentially have a reduced inflammatory response to AD damage. Moreover, our findings suggest the existence of a mechanism, independent of lowered expression, affecting neuropathology in expansion carriers.

Relationship Between FERMT2, CELF1, COPI, CHRNA2, and ABCA7 Genetic Polymorphisms and Alzheimer's Disease Risk in the Southern Chinese Population

Background

Alzheimer's disease (AD) is a multi-gene inherited disease, and apolipoprotein E (APOE) ɛ4 is a strong risk factor. Other genetic factors are important but limited.

Objective

This study aimed to investigate the relationship between 17 single-nucleotide polymorphisms (SNPs) and AD in the Southern Chinese populations.

Methods

We recruited 242 AD patients and 208 controls. The SNaPshot technique was used to detect the SNPs.

Results

Adjusted for sex and age, we found rs6572869 (FERMT2), rs11604680 (CELF1), and rs1317149 (CELF1) were associated with AD risk in the dominant (rs6572869: p = 0.022, OR = 1.55; rs11604680: p = 0.007, OR = 1.68; rs1317149: p = 0.033, OR = 1.50) and overdominant models (rs6572869: p = 0.001, OR = 1.96; rs11604680: p = 0.002, OR = 1.82; rs1317149: p = 0.003, OR = 1.80). rs9898218 (COPI) was associated with AD risk in the overdominant model (p = 0.004, OR = 1.81). Further, rs2741342 (CHRNA2) was associated with AD protection in the dominant (p = 0.002, OR = 0.5) and additive models (p = 0.002, OR = 0.64). Mutations in rs10742814 (CELF1), rs11039280 (CELF1), and rs3752242 (ABCA7) contributed to AD protection. Among them, rs10742814 (CELF1), rs3752242 (ABCA7), and rs11039280 (CELF1) were more significantly associated with AD carrying APOE ɛ4, whereas rs1317149 (CELF1) showed an opposite trend. Interestingly, rs4147912 (ABCA7) and rs2516049 (HLA-DRB1) were identified to be relevant with AD carrying APOE ɛ4. Using expression quantitative trait locus analysis, we found polymorphisms in CELF1 (rs10742814 and rs11039280), ABCA7 (rs4147912), HLA-DRB1 (rs2516049), and ADGRF4 (rs1109581) correlated with their corresponding gene expression in the brain.

Conclusions

We identified four risk and four protective SNPs associated with AD in the Southern Chinese population, with different correlations between APOE ɛ4 carriers and non-carriers. rs4147912 (ABCA7) and rs2516049 (HLA-DRB1) were associated with AD carrying APOE ɛ4.

Sex and APOE ε4 carrier effects on atrophy, amyloid PET, and tau PET burden in early-onset Alzheimer's disease

INTRODUCTION

We used sex and apolipoprotein E ε4 (APOE ε4) carrier status as predictors of pathologic burden in early-onset Alzheimer's disease (EOAD).

METHODS

We included baseline data from 77 cognitively normal (CN), 230 EOAD, and 70 EO non-Alzheimer's disease (EOnonAD) participants from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS). We stratified each diagnostic group by males and females, then further subdivided each sex by APOE ε4 carrier status and compared imaging biomarkers in each stratification. Voxel-wise multiple linear regressions yielded statistical brain maps of gray matter density, amyloid, and tau PET burden.

RESULTS

EOAD females had greater amyloid and tau PET burdens than males. EOAD female APOE ε4 non-carriers had greater amyloid PET burdens and greater gray matter atrophy than female ε4 carriers. EOnonAD female ε4 non-carriers also had greater gray matter atrophy than female ε4 carriers.

DISCUSSION

The effects of sex and APOE ε4 must be considered when studying these populations.

HIGHLIGHTS

Novel analysis examining the effects of biological sex and apolipoprotein E ε4 (APOE ε4) carrier status on neuroimaging biomarkers among early-onset Alzheimer's disease (EOAD), early-onset non-AD (EOnonAD), and cognitively normal (CN) participants. Female sex is associated with greater pathology burden in the EOAD cohort compared to male sex. The effect of APOE ε4 carrier status on pathology burden was the most impactful in females across all cohorts.

Coupling of Alzheimer's Disease Genetic Risk Factors with Viral Susceptibility and Inflammation

Alzheimer's disease (AD) is a neurodegenerative disease characterized by persistent cognitive decline. Amyloid plaque deposition and neurofibrillary tangles are the main pathological features of AD brain, though mechanisms leading to the formation of lesions remain to be understood. Genetic efforts through genome-wide association studies (GWAS) have identified dozens of risk genes influencing the pathogenesis and progression of AD, some of which have been revealed in close association with increased viral susceptibilities and abnormal inflammatory responses in AD patients. In the present study, we try to present a list of AD candidate genes that have been shown to affect viral infection and inflammatory responses. Understanding of how AD susceptibility genes interact with the viral life cycle and potential inflammatory pathways would provide possible therapeutic targets for both AD and infectious diseases.

Clinical effects of novel susceptibility genes for beta-amyloid: a gene-based association study in the Korean population

Amyloid-beta (Aβ) is a pathological hallmark of Alzheimer's disease (AD). We aimed to identify genes related to Aβ uptake in the Korean population and investigate the effects of these novel genes on clinical outcomes, including neurodegeneration and cognitive impairments. We recruited a total of 759 Korean participants who underwent neuropsychological tests, brain magnetic resonance imaging, 18F-flutemetamol positron emission tomography, and microarray genotyping data. We performed gene-based association analysis, and also performed expression quantitative trait loci and network analysis. In genome-wide association studies, no single nucleotide polymorphism (SNP) passed the genome-wide significance threshold. In gene-based association analysis, six genes (LCMT1, SCRN2, LRRC46, MRPL10, SP6, and OSBPL7) were significantly associated with Aβ standardised uptake value ratio in the brain. The three most significant SNPs (rs4787307, rs9903904, and rs11079797) on these genes are associated with the regulation of the LCMT1, OSBPL7, and SCRN2 genes, respectively. These SNPs are involved in decreasing hippocampal volume and cognitive scores by mediating Aβ uptake. The 19 enriched gene sets identified by pathway analysis included axon and chemokine activity. Our findings suggest novel susceptibility genes associated with the uptake of Aβ, which in turn leads to worse clinical outcomes. Our findings might lead to the discovery of new AD treatment targets.

ABCA7-Associated Clinical Features and Molecular Mechanisms in Alzheimer's Disease

Alzheimer's disease (AD) is the most common type of neurodegenerative disease and its pathogenesis is still unclear. Genetic factors are thought to account for a large proportion of the overall AD phenotypes. ATP-binding cassette transporter A7 (ABCA7) is one of the most important risk gene for AD. Multiple forms of ABCA7 variants significantly increase the risk of AD, such as single-nucleotide polymorphisms, premature termination codon variants, missense variants, variable number tandem repeat, mutations, and alternative splicing. AD patients with ABCA7 variants usually exhibit typical clinical and pathological features of traditional AD with a wide age of onset range. ABCA7 variants can alter ABCA7 protein expression levels and protein structure to affect protein functions such as abnormal lipid metabolism, amyloid precursor protein (APP) processing, and immune cell function. Specifically, ABCA7 deficiency can cause neuronal apoptosis by inducing endoplasmic reticulum stress through the PERK/eIF2α pathway. Second, ABCA7 deficiency can increase Aβ production by upregulating the SREBP2/BACE1 pathway and promoting APP endocytosis. In addition, the ability of microglia to phagocytose and degrade Aβ is destroyed by ABCA7 deficiency, leading to reduced clearance of Aβ. Finally, disturbance of lipid metabolism may also be an important method by which ABCA7 variants influence the incidence rate of AD. In the future, more attention should be given to different ABCA7 variants and ABCA7 targeted therapies for AD.

Identification of key lipid metabolism-related genes in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) represents profound degenerative conditions of the brain that cause significant deterioration in memory and cognitive function. Despite extensive research on the significant contribution of lipid metabolism to AD progression, the precise mechanisms remain incompletely understood. Hence, this study aimed to identify key differentially expressed lipid metabolism-related genes (DELMRGs) in AD progression.

METHODS

Comprehensive analyses were performed to determine key DELMRGs in AD compared to controls in GSE122063 dataset from Gene Expression Omnibus. Additionally, the ssGSEA algorithm was utilized for estimating immune cell levels. Subsequently, correlations between key DELMRGs and each immune cell were calculated specifically in AD samples. The key DELMRGs expression levels were validated via two external datasets. Furthermore, gene set enrichment analysis (GSEA) was utilized for deriving associated pathways of key DELMRGs. Additionally, miRNA-TF regulatory networks of the key DELMRGs were constructed using the miRDB, NetworkAnalyst 3.0, and Cytoscape software. Finally, based on key DELMRGs, AD samples were further segmented into two subclusters via consensus clustering, and immune cell patterns and pathway differences between the two subclusters were examined.

RESULTS

Seventy up-regulated and 100 down-regulated DELMRGs were identified. Subsequently, three key DELMRGs (DLD, PLPP2, and PLAAT4) were determined utilizing three algorithms [(i) LASSO, (ii) SVM-RFE, and (iii) random forest]. Specifically, PLPP2 and PLAAT4 were up-regulated, while DLD exhibited downregulation in AD cerebral cortex tissue. This was validated in two separate external datasets (GSE132903 and GSE33000). The AD group exhibited significantly altered immune cell composition compared to controls. In addition, GSEA identified various pathways commonly associated with three key DELMRGs. Moreover, the regulatory network of miRNA-TF for key DELMRGs was established. Finally, significant differences in immune cell levels and several pathways were identified between the two subclusters.

CONCLUSION

This study identified DLD, PLPP2, and PLAAT4 as key DELMRGs in AD progression, providing novel insights for AD prevention/treatment.

Down-Regulation of ABCA7 in Human Microglia, Astrocyte and THP-1 Cell Lines by Cholesterol Depletion, IL-1β and TNFα, or PMA

Adenosine triphosphate-binding cassette transporter subfamily A member 7 (ABCA7) is a major risk factor for Alzheimer's disease. Human neural cell lines were used to investigate the regulation of ABCA7 expression by cholesterol and pro-inflammatory cytokines. Cholesterol was depleted by methyl-β-cyclodextrin, followed by treatment with rosuvastatin to suppress de novo synthesis, while the cells underwent adjustment to low cholesterol. Cholesterol depletion by 50-76% decreased ABCA7 expression by ~40% in C20 microglia and ~21% in A172 astrocytes but had no effect on the protein in SK-N-SH neurons. Cholesterol depletion also suppressed ABCA7 in HMC3 microglia. Previously, cholesterol loss was reported to up-regulate ABCA7 in murine macrophages. ABCA7 was down-regulated during PMA-induced differentiation of human THP-1 monocytes to macrophages. But, cholesterol depletion in THP-1 macrophages by ~71% had no effect on ABCA7. IL-1β and TNFα reduced ABCA7 expression in C20 and HMC3 microglia but not in A172 astrocytes or SK-N-SH neurons. IL-6 did not affect ABCA7 in the neural cells. These findings suggest that ABCA7 is active in regular homeostasis in human neural cells, is regulated by cholesterol in a cell type-dependent manner, i.e., cholesterol depletion down-regulates it in human neuroglia but not neurons, and is incompatible with IL-1β and TNFα inflammatory responses in human microglia.

Interaction Analysis Reveals Complex Genetic Associations with Alzheimer's Disease in the CLU and ABCA7 Gene Regions

Sporadic Alzheimer's disease (AD) is a polygenic neurodegenerative disorder. Single-nucleotide polymorphisms (SNPs) in multiple genes (e.g., CLU and ABCA7) have been associated with AD. However, none of them were characterized as causal variants that indicate the complex genetic architecture of AD, which is likely affected by individual variants and their interactions. We performed a meta-analysis of four independent cohorts to examine associations of 32 CLU and 50 ABCA7 polymorphisms as well as their 496 and 1225 pair-wise interactions with AD. The single SNP analyses revealed that six CLU and five ABCA7 SNPs were associated with AD. Ten of them were previously not reported. The interaction analyses identified AD-associated compound genotypes for 25 CLU and 24 ABCA7 SNP pairs, whose comprising SNPs were not associated with AD individually. Three and one additional CLU and ABCA7 pairs composed of the AD-associated SNPs showed partial interactions as the minor allele effect of one SNP in each pair was intensified in the absence of the minor allele of the other SNP. The interactions identified here may modulate associations of the CLU and ABCA7 variants with AD. Our analyses highlight the importance of the roles of combinations of genetic variants in AD risk assessment.

Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease

Alzheimer's disease (AD) heritability is enriched in glial genes, but how and when cell-type-specific genetic risk contributes to AD remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets. In an autopsy dataset spanning all stages of AD (n=1,457), astrocytic (Ast) ADPRS was associated with both diffuse and neuritic Aβ plaques, while microglial (Mic) ADPRS was associated with neuritic Aβ plaques, microglial activation, tau, and cognitive decline. Causal modeling analyses further clarified these relationships. In an independent neuroimaging dataset of cognitively unimpaired elderly (n=2,921), Ast-ADPRS were associated with Aβ, and Mic-ADPRS was associated with Aβ and tau, showing a consistent pattern with the autopsy dataset. Oligodendrocytic and excitatory neuronal ADPRSs were associated with tau, but only in the autopsy dataset including symptomatic AD cases. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

A global view of the genetic basis of Alzheimer disease

The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.

ABC transporters: human disease and pharmacotherapeutic potential

Adenosine triphosphate (ATP)-binding cassette (ABC) transporters are a 48-member superfamily of membrane proteins that actively transport a variety of biological substrates across lipid membranes. Their functional diversity defines an expansive involvement in myriad aspects of human biology. At least 21 ABC transporters underlie rare monogenic disorders, with even more implicated in the predisposition to and symptomology of common and complex diseases. Such broad (patho)physiological relevance places this class of proteins at the intersection of disease causation and therapeutic potential, underlining them as promising targets for drug discovery, as exemplified by the transformative CFTR (ABCC7) modulator therapies for cystic fibrosis. This review will explore the growing relevance of ABC transporters to human disease and their potential as small-molecule drug targets.

The role of ApoE-mediated microglial lipid metabolism in brain aging and disease

Microglia are a unique population of immune cells resident in the brain that integrate complex signals and dynamically change phenotypes in response to the brain microenvironment. In recent years, single-cell sequencing analyses have revealed profound cellular heterogeneity and context-specific transcriptional plasticity of microglia during brain development, aging, and disease. Emerging evidence suggests that microglia adapt phenotypic plasticity by flexibly reprogramming cellular metabolism to fulfill distinct immune functions. The control of lipid metabolism is central to the appropriate function and homeostasis of the brain. Microglial lipid metabolism regulated by apolipoprotein E (ApoE), a crucial lipid transporter in the brain, has emerged as a critical player in regulating neuroinflammation. The ApoE gene allelic variant, ε4, is associated with a greater risk for neurodegenerative diseases. In this review, we explore novel discoveries in microglial lipid metabolism mediated by ApoE. We elaborate on the functional impact of perturbed microglial lipid metabolism on the underlying pathogenesis of brain aging and disease.

Alzheimer's risk factor FERMT2 promotes the progression of colorectal carcinoma via Wnt/β-catenin signaling pathway and contributes to the negative correlation between Alzheimer and cancer

Increasing evidence from epidemiological studies indicate that Alzheimer's disease (AD) has a negative relationship with the incidence of cancers. Whether the Alzheimer's genetic risk factor, named as fermitin family homolog-2 (FERMT2), plays a pivotal part in the progressive process of colorectal carcinoma (CRC) yet remains unclear. This study revealed that FERMT2 was upregulated in CRC tissues which predicted an unfavorable outcome of CRC using the PrognoScan web tool. FERMT2 was co-expressed with a variety of genes have been linked with CRC occurrence and implicated in the infiltration of immune cell in CRC tissues. Overexpressing FERMT2 promoted CRC progression with upregulation of Wnt/β-catenin signaling. Knockdown of FERMT2 suppressed the cell multiplication, colony formation rate, migration and invasion, along with the epithelial to mesenchymal transition (EMT) with downregulation Wnt/β-catenin proteins in cells of CRC, while overexpressing β-catenin reversed the inhibitory effects of silencing FERMT2 on the migration or invasion of CRC cells. Furthermore, Aβ1-42 treated HT22 cells induced downregulation of FERMT2 and inhibited the migration, invasion and EMT in co-cultured CT26 cells through Wnt/β-catenin signaling. Our results revealed that the downregulated FERMT2 gene during AD is prominently activated in CRC, which promotes its progression via Wnt/β-catenin pathway.

SNP-by-CpG Site Interactions in ABCA7 Are Associated with Cognition in Older African Americans

SNPs in ABCA7 confer the largest genetic risk for Alzheimer's Disease (AD) in African Americans (AA) after APOE ε4. However, the relationship between ABCA7 and cognitive function has not been thoroughly examined. We investigated the effects of five known AD risk SNPs and 72 CpGs in ABCA7, as well as their interactions, on general cognitive function (cognition) in 634 older AA without dementia from Genetic Epidemiology Network of Arteriopathy (GENOA). Using linear mixed models, no SNP or CpG was associated with cognition after multiple testing correction, but five CpGs were nominally associated (p < 0.05). Four SNP-by-CpG interactions were associated with cognition (FDR q < 0.1). Contrast tests show that methylation is associated with cognition in some genotype groups (p < 0.05): a 1% increase at cg00135882 and cg22271697 is associated with a 0.68 SD decrease and 0.14 SD increase in cognition for those with the rs3764647 GG/AG (p = 0.004) and AA (p = 2 × 10-4) genotypes, respectively. In addition, a 1% increase at cg06169110 and cg17316918 is associated with a 0.37 SD decrease (p = 2 × 10-4) and 0.33 SD increase (p = 0.004), respectively, in cognition for those with the rs115550680 GG/AG genotype. While AD risk SNPs in ABCA7 were not associated with cognition in this sample, some have interactions with proximal methylation on cognition.

27-Hydroxycholesterol-Induced Dysregulation of Cholesterol Metabolism Impairs Learning and Memory Ability in ApoE ε4 Transgenic Mice

Dysregulated brain cholesterol metabolism is one of the characteristics of Alzheimer’s disease (AD). 27-Hydroxycholesterol (27-OHC) is a cholesterol metabolite that plays an essential role in regulating cholesterol metabolism and it is suggested that it contributes to AD-related cognitive deficits. However, the link between 27-OHC and cholesterol homeostasis, and how this relationship relates to AD pathogenesis, remain elusive. Here, 12-month-old ApoE ε4 transgenic mice were injected with saline, 27-OHC, 27-OHC synthetase inhibitor (anastrozole, ANS), and 27-OHC+ANS for 21 consecutive days. C57BL/6J mice injected with saline were used as wild-type controls. The indicators of cholesterol metabolism, synaptic structure, amyloid β 1-42 (Aβ1-42), and learning and memory abilities were measured. Compared with the wild-type mice, ApoE ε4 mice had poor memory and dysregulated cholesterol metabolism. Additionally, damaged brain tissue and synaptic structure, cognitive decline, and higher Aβ1-42 levels were observed in the 27-OHC group. Moreover, cholesterol transport proteins such as ATP-binding cassette transporter A1 (ABCA1), apolipoprotein E (ApoE), low-density lipoprotein receptor (LDLR), and low-density lipoprotein receptor-related protein1 (LRP1) were up-regulated in the cortex after the 27-OHC treatment. The levels of cholesterol metabolism-related indicators in the hippocampus were not consistent with those in the cortex. Additionally, higher serum apolipoprotein A1 (ApoA1) levels and lower serum ApoE levels were observed in the 27-OHC group. Notably, ANS partially reversed the effects of 27-OHC. In conclusion, the altered cholesterol metabolism induced by 27-OHC was involved in Aβ1-42 deposition and abnormalities in both the brain tissue and synaptic structure, ultimately leading to memory loss in the ApoE ε4 transgenic mice.

A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

Apolipoprotein E in Cardiometabolic and Neurological Health and Diseases

A preponderance of evidence obtained from genetically modified mice and human population studies reveals the association of apolipoprotein E (apoE) deficiency and polymorphisms with pathogenesis of numerous chronic diseases, including atherosclerosis, obesity/diabetes, and Alzheimer’s disease. The human APOE gene is polymorphic with three major alleles, ε2, ε3 and ε4, encoding apoE2, apoE3, and apoE4, respectively. The APOE gene is expressed in many cell types, including hepatocytes, adipocytes, immune cells of the myeloid lineage, vascular smooth muscle cells, and in the brain. ApoE is present in subclasses of plasma lipoproteins, and it mediates the clearance of atherogenic lipoproteins from plasma circulation via its interaction with LDL receptor family proteins and heparan sulfate proteoglycans. Extracellular apoE also interacts with cell surface receptors and confers signaling events for cell regulation, while apoE expressed endogenously in various cell types regulates cell functions via autocrine and paracrine mechanisms. This review article focuses on lipoprotein transport-dependent and -independent mechanisms by which apoE deficiency or polymorphisms contribute to cardiovascular disease, metabolic disease, and neurological disorders.

Contribution of Alzheimer's biomarkers and risk factors to cognitive impairment and decline across the Alzheimer's disease continuum

INTRODUCTION

Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression.

METHODS

Within 248 Aβ-positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ-positron emission tomography [PET] uptake, regional tau-PET uptake, and regional magnetic resonance imaging-based atrophy) and risk-factors (age, sex, education, apolipoprotein E [APOE], and white-matter lesions) on cross-sectional cognitive impairment and longitudinal cognitive decline.

RESULTS

Sixteen percent of variance in cross-sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ-tau-atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively.

DISCUSSION

These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.

Predicting Amyloid Positivity in Cognitively Unimpaired Older Adults: A Machine Learning Approach Using A4 Data

BACKGROUND AND OBJECTIVES

To develop and test the performance of the Positive Aβ Risk Score (PARS) for prediction of β-amyloid (Aβ) positivity in cognitively unimpaired individuals for use in clinical research. Detecting Aβ positivity is essential for identifying at-risk individuals who are candidates for early intervention with amyloid targeted treatments.

METHODS

We used data from 4,134 cognitively normal individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study. The sample was divided into training and test sets. A modified version of AutoScore, a machine learning-based software tool, was used to develop a scoring system using the training set. Three risk scores were developed using candidate predictors in various combinations from the following categories: demographics (age, sex, education, race, family history, body mass index, marital status, and ethnicity), subjective measures (Alzheimer's Disease Cooperative Study Activities of Daily Living-Prevention Instrument, Geriatric Depression Scale, and Memory Complaint Questionnaire), objective measures (free recall, Mini-Mental State Examination, immediate recall, digit symbol substitution, and delayed logical memory scores), and APOE4 status. Performance of the risk scores was evaluated in the independent test set.

RESULTS

PARS model 1 included age, body mass index (BMI), and family history and had an area under the curve (AUC) of 0.60 (95% CI 0.57-0.64). PARS model 2 included free recall in addition to the PARS model 1 variables and had an AUC of 0.61 (0.58-0.64). PARS model 3, which consisted of age, BMI, and APOE4 information, had an AUC of 0.73 (0.70-0.76). PARS model 3 showed the highest, but still moderate, performance metrics in comparison with other models with sensitivity of 72.0% (67.6%-76.4%), specificity of 62.1% (58.8%-65.4%), accuracy of 65.3% (62.7%-68.0%), and positive predictive value of 48.1% (44.1%-52.1%).

DISCUSSION

PARS models are a set of simple and practical risk scores that may improve our ability to identify individuals more likely to be amyloid positive. The models can potentially be used to enrich trials and serve as a screening step in research settings. This approach can be followed by the use of additional variables for the development of improved risk scores.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that in cognitively unimpaired individuals PARS models predict Aβ positivity with moderate accuracy.

Association of the top 20 Alzheimer's disease risk genes with [18F]flortaucipir PET

Introduction

We previously reported genetic associations of the top Alzheimer's disease (AD) risk alleles with amyloid deposition and neurodegeneration. Here, we report the association of these variants with [18F]flortaucipir standardized uptake value ratio (SUVR).

Methods

We analyzed the [18F]flortaucipir scans of 352 cognitively normal (CN), 160 mild cognitive impairment (MCI), and 54 dementia (DEM) participants from Alzheimer's Disease Neuroimaging Initiative (ADNI)2 and 3. We ran step-wise regression with log-transformed [18F]flortaucipir meta-region of interest SUVR as the outcome measure and genetic variants, age, sex, and apolipoprotein E (APOE) ε4 as predictors. The results were visualized using parametric mapping at familywise error cluster-level-corrected P < .05.

Results

APOE ε4 showed significant (P < .05) associations with tau deposition across all disease stages. Other significantly associated genes include variants in ABCA7 in CN, CR1 in MCI, BIN1 and CASS4 in MCI and dementia participants.

Discussion

We found significant associations to tau deposition for ABCA7, BIN1, CASS4, and CR1, in addition to APOE ε4. These four variants have been previously associated with tau metabolism through model systems.

Sex-specific lipid dysregulation in the Abca7 knockout mouse brain

Alzheimer’s disease is a devastating neurodegenerative disease that affects more women than men. The pathomechanism underlying the sex disparity, especially in the brain, is unclear. ABCA7 is one of the strongest susceptibility genes for Alzheimer’s disease. It mediates the transport of lipids across membranes and is associated with pathways related to amyloid-β neuropathology. However, the role of ABCA7 in the regulation of brain lipids is largely unknown. Sex-specific differences in the pathological link between brain lipid dysregulation and amyloid-β are also unknown. Here, we undertook quantitative discovery lipidomics of male and female Abca7 knockout (n = 52) and wild type (n = 35) mouse brain using sophisticated liquid chromatography/mass spectrometry. We identified 61 lipid subclasses in the mouse brain and found sex-specific differences in lipids that were altered with Abca7 deletion. The altered lipids belong to cellular pathways that control cell signalling, sterol metabolism, mitochondrial function and neuroprotection. We also investigated the relationship between lipids and amyloid-β levels in the Abca7 knockout mice and found elevated free cholesterol only in female mice that was significantly correlated with amyloid-β42 levels. In male Abca7 knockout mice, the neuroprotective ganglioside GD1a levels were elevated and inversely correlated with amyloid-β42 levels. Collectively, these results demonstrate that Abca7 deletion leads to sex-specific lipid dysregulation in the brain, providing insight into the underlying sex disparity in the aetiology of Alzheimer’s disease.

Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.

METHODS

We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.

RESULTS

Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.

DISCUSSION

ADNI has had a profound impact in improving clinical trials for AD.

Alzheimer’s Disease: An Update and Insights Into Pathophysiology

Alzheimer’s disease (AD) is an irreversible brain disorder associated with slow, progressive loss of brain functions mostly in older people. The disease processes start years before the symptoms are manifested at which point most therapies may not be as effective. In the hippocampus, the key proteins involved in the JAK2/STAT3 signaling pathway, such as p-JAK2-Tyr1007 and p-STAT3-Tyr705 were found to be elevated in various models of AD. In addition to neurons, glial cells such as astrocytes also play a crucial role in the progression of AD. Without having a significant effect on tau and amyloid pathologies, the JAK2/STAT3 pathway in reactive astrocytes exhibits a behavioral impact in the experimental models of AD. Cholinergic atrophy in AD has been traced to a trophic failure in the NGF metabolic pathway, which is essential for the survival and maintenance of basal forebrain cholinergic neurons (BFCN). In AD, there is an alteration in the conversion of the proNGF to mature NGF (mNGF), in addition to an increase in degradation of the biologically active mNGF. Thus, the application of exogenous mNGF in experimental studies was shown to improve the recovery of atrophic BFCN. Furthermore, it is now coming to light that the FGF7/FGFR2/PI3K/Akt signaling pathway mediated by microRNA-107 is also involved in AD pathogenesis. Vascular dysfunction has long been associated with cognitive decline and increased risk of AD. Vascular risk factors are associated with higher tau and cerebral beta-amyloid (Aβ) burden, while synergistically acting with Aβ to induce cognitive decline. The apolipoprotein E4 polymorphism is not just one of the vascular risk factors, but also the most prevalent genetic risk factor of AD. More recently, the research focus on AD shifted toward metabolisms of various neurotransmitters, major and minor nutrients, thus giving rise to metabolomics, the most important “omics” tool for the diagnosis and prognosis of neurodegenerative diseases based on an individual’s metabolome. This review will therefore proffer a better understanding of novel signaling pathways associated with neural and glial mechanisms involved in AD, elaborate potential links between vascular dysfunction and AD, and recent developments in “omics”-based biomarkers in AD.

Impact of sex and APOE ε4 on the association of cognition and hippocampal volume in clinically normal, amyloid positive adults

INTRODUCTION

Cognitive decline follows pathological changes including neurodegeneration on the Alzheimer's disease continuum. However, it is unclear which cognitive domains first become affected by neurodegeneration in amyloid-positive individuals and if sex or apolipoprotein (APOE) ε4 status differences affect this relationship.

METHODS

Data from 1233 cognitively unimpaired, amyloid-positive individuals 65 to 85 years of age were studied to assess the effect of hippocampal volume (HV) on cognition and to evaluate differences due to sex and APOE ε4 status.

RESULTS

Lower HV was linked with worse performance on measures of memory (free recall, total recall, logical memory delayed recall, Mini-Mental State Examination [MMSE]), executive functioning (digit symbol substitution, DSS), and the Preclinical Alzheimer's Cognitive Composite (PACC). Among both women and APOE ε4+ individuals, all cognitive measures, except MMSE, were associated with HV. DSS and PACC had the largest effect sizes in differentiating early and intermediate stage neurodegeneration.

DISCUSSION

Despite all cognitive measures being associated with HV, cognitive tests show differences in detecting early or late signs of neurodegeneration. Differences exist in association between cognition and neurodegeneration based on sex and APOE ε4 status.

Polygenic Scores of Alzheimer's Disease Risk Genes Add Only Modestly to APOE in Explaining Variation in Amyloid PET Burden

BACKGROUND

Brain accumulation of amyloid-β is a hallmark event in Alzheimer's disease (AD) whose underlying mechanisms are incompletely understood. Case-control genome-wide association studies have implicated numerous genetic variants in risk of clinically diagnosed AD dementia.

OBJECTIVE

To test for associations between case-control AD risk variants and amyloid PET burden in older adults, and to assess whether a polygenic measure encompassing these factors would account for a large proportion of the unexplained variance in amyloid PET levels in the wider population.

METHODS

We analyzed data from the Mayo Clinic Study of Aging (MCSA) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Global cortical amyloid PET burden was the primary outcome. The 38 gene variants from Wightman et al. (2021) were analyzed as predictors, with PRSice-2 used to assess the collective phenotypic variance explained.

RESULTS

Known AD risk variants in APOE, PICALM, CR1, and CLU were associated with amyloid PET levels. In aggregate, the AD risk variants were strongly associated with amyloid PET levels in the MCSA (p = 1.51×10-50) and ADNI (p = 3.21×10-64). However, in both cohorts the non-APOE variants uniquely contributed only modestly (MCSA = 2.1%, ADNI = 4.4%) to explaining variation in amyloid PET levels.

CONCLUSION

Additional case-control AD risk variants added only modestly to APOE in accounting for individual variation in amyloid PET burden, results which were consistent across independent cohorts with distinct recruitment strategies and subject characteristics. Our findings suggest that advancing precision medicine for dementia may require integration of strategies complementing case-control approaches, including biomarker-specific genetic associations, gene-by-environment interactions, and markers of disease progression and heterogeneity.

Shared genetic architecture between the two neurodegenerative diseases: Alzheimer's disease and glaucoma

BACKGROUND

Considered as the representatives of neurodegenerative diseases, Alzheimer's disease (AD) and glaucoma are complex progressive neuropathies affected by both genetic and environmental risk factors and cause irreversible damages. Current research indicates that there are common features between AD and glaucoma in terms of epidemiology and pathophysiology. However, the understandings and explanations of their comorbidity and potential genetic overlaps are still limited and insufficient.

METHOD

Genetic pleiotropy analysis was performed using large genome-wide association studies summary statistics of AD and glaucoma, with an independent cohort of glaucoma for replication. Conditional and conjunctional false discovery rate methods were applied to identify the shared loci. Biological function and network analysis, as well as the expression level analysis were performed to investigate the significance of the shared genes.

RESULTS

A significant positive genetic correlation between AD and glaucoma was identified, indicating that there were significant polygenetic overlaps. Forty-nine shared loci were identified and mapped to 11 shared protein-coding genes. Functional genomic analyses of the shared genes indicate their modulation of critical physiological processes in human cells, including those occurring in the mitochondria, nucleus, and cellular membranes. Most of the shared genes indicated a potential modulation of metabolic processes in human cells and tissues. Furthermore, human protein-protein interaction network analyses revealed that some of the shared genes, especially MTCH2, NDUFS3, and PTPMT1, as well as SPI1 and MYBPC3, may function concordantly. The modulation of their expressions may be related to metabolic dysfunction and pathogenic processes.

CONCLUSION

Our study identified a shared genetic architecture between AD and glaucoma, which may explain their shared features in epidemiology and pathophysiology. The potential involvement of these shared genes in molecular and cellular processes reflects the "inter-organ crosstalk" between AD and glaucoma. These results may serve as a genetic basis for the development of innovative and effective therapeutics for AD, glaucoma, and other neurodegenerative diseases.

ABCA7, a Genetic Risk Factor Associated with Alzheimer's Disease Risk in African Americans

African American/Black adults are twice as likely to have Alzheimer's disease (AD) compared to non-Hispanic White adults. Genetics partially contributes to this disparity in AD risk, among other factors, as there are several genetic variants associated with AD that are more prevalent in individuals of African or European ancestry. The phospholipid-transporting ATPase ABCA7 (ABCA7) gene has stronger associations with AD risk in individuals with African ancestry than in individuals with European ancestry. In fact, ABCA7 has been shown to have a stronger effect size than the apolipoprotein E (APOE) ɛ4 allele in African American/Black adults. ABCA7 is a transmembrane protein involved in lipid homeostasis and phagocytosis. ABCA7 dysfunction is associated with increased amyloid-beta production, reduced amyloid-beta clearance, impaired microglial response to inflammation, and endoplasmic reticulum stress. This review explores the impact of ABCA7 mutations that increase AD risk in African American/Black adults on ABCA7 structure and function and their contributions to AD pathogenesis. The combination of biochemical/biophysical and 'omics-based studies of these variants needed to elucidate their downstream impact and molecular contributions to AD pathogenesis is highlighted.

The Worldwide Alzheimer's Disease Neuroimaging Initiative: ADNI-3 updates and global perspectives

The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW-ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public-private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI-1, ADNI-GO, ADNI-2, and ADNI-3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW-ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW-ADNI researchers who shared updates from ADNI-3 and their vision for ADNI-4.

MINCR: A long non-coding RNA shared between cancer and neurodegeneration

The multitasking nature of lncRNAs allows them to play a central role in both physiological and pathological conditions. Often the same lncRNA can participate in different diseases. Specifically, the MYC-induced Long non-Coding RNA MINCR is upregulated in various cancer types, while downregulated in Amyotrophic Lateral Sclerosis patients. Therefore, this work aims to investigate MINCR potential mechanisms of action and its implications in cancer and neurodegeneration in relation to its expression levels in SH-SY5Y cells through RNA-sequencing approach. Our results show that MINCR overexpression causes massive alterations in cancer-related genes, leading to disruption in many fundamental processes, such as cell cycle and growth factor signaling. On the contrary, MINCR downregulation influences a small number of genes involved in different neurodegenerative disorders, mostly concerning RNA metabolism and inflammation. Thus, understanding the cause and functional consequences of MINCR deregulation gives important insights on potential pathogenetic mechanisms both in cancer and in neurodegeneration.

Platelet biomarkers identifying mild cognitive impairment in type 2 diabetes patients

Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer's disease (AD). Therefore, identifying periphery biomarkers correlated with mild cognitive impairment (MCI) is of importance for early diagnosis of AD. Here, we performed platelet proteomics in T2DM patients with MCI (T2DM‐MCI) and without MCI (T2DM‐nMCI). Pearson analysis of the omics data with MMSE (mini‐mental state examination), Aβ1‐42/Aβ1‐40 (β‐amyloid), and rGSK‐3β(T/S9) (total to Serine‐9‐phosphorylated glycogen synthase kinase‐3β) revealed that mitophagy/autophagy‐, insulin signaling‐, and glycolysis/gluconeogenesis pathways‐related proteins were most significantly involved. Among them, only the increase of optineurin, an autophagy‐related protein, was simultaneously correlated with the reduced MMSE score, and the increased Aβ1‐42/Aβ1‐40 and rGSK‐3β(T/S9), and the optineurin alone could discriminate T2DM‐MCI from T2DM‐nMCI. Combination of the elevated platelet optineurin and rGSK‐3β(T/S9) enhanced the MCI‐discriminating efficiency with AUC of 0.927, specificity of 86.7%, sensitivity of 85.3%, and accuracy of 0.859, which is promising for predicting cognitive decline in T2DM patients.

Alzheimer's genetic risk factor FERMT2 (Kindlin-2) controls axonal growth and synaptic plasticity in an APP-dependent manner

Although APP metabolism is being intensively investigated, a large fraction of its modulators is yet to be characterized. In this context, we combined two genome-wide high-content screenings to assess the functional impact of miRNAs and genes on APP metabolism and the signaling pathways involved. This approach highlighted the involvement of FERMT2 (or Kindlin-2), a genetic risk factor of Alzheimer's disease (AD), as a potential key modulator of axon guidance, a neuronal process that depends on the regulation of APP metabolism. We found that FERMT2 directly interacts with APP to modulate its metabolism, and that FERMT2 underexpression impacts axonal growth, synaptic connectivity, and long-term potentiation in an APP-dependent manner. Last, the rs7143400-T allele, which is associated with an increased AD risk and localized within the 3'UTR of FERMT2, induced a downregulation of FERMT2 expression through binding of miR-4504 among others. This miRNA is mainly expressed in neurons and significantly overexpressed in AD brains compared to controls. Altogether, our data provide strong evidence for a detrimental effect of FERMT2 underexpression in neurons and insight into how this may influence AD pathogenesis.

Preventing Alzheimer's disease within reach by 2025: Targeted-risk-AD-prevention (TRAP) strategy

INTRODUCTION

Alzheimer's disease (AD) is a progressive neurodegenerative disease that currently affects 6.2 million people in the United States and is projected to impact 12.7 million worldwide in 2050 with no effective disease-modifying therapeutic or cure. In 2011 as part of the National Alzheimer's Project Act, the National Plan to Address Alzheimer's Disease was signed into law which proposed to effectively prevent AD by 2025, which is rapidly approaching. The preclinical phase of AD can begin 20 years prior to diagnosis, which provides an extended window for preventive measures that would exert a transformative impact on incidence and prevalence of AD.

METHODS

A novel combination of text-mining and natural language processing strategies to identify (1) AD risk factors, (2) therapeutics that can target risk factor pathways, and (3) studies supporting therapeutics in the PubMed database was conducted. To classify the literature relevant to AD preventive strategies, a relevance score (RS) based on STRING (search tool for the retrieval of interacting genes/proteins) score for protein-protein interactions and a confidence score (CS) on Bayesian inference were developed. To address mechanism of action, network analysis of protein targets for effective drugs was conducted. Collectively, the analytic approach, referred to as a targeted-risk-AD-prevention (TRAP) strategy, led to a ranked list of candidate therapeutics to reduce AD risk.

RESULTS

Based on TRAP mining of 9625 publications, 364 AD risk factors were identified. Based on risk factor indications, 629 Food and Drug Administration-approved drugs were identified. Computation of ranking scores enabled identification of 46 relevant high confidence (RS & CS > 0.7) drugs associated with reduced AD risk. Within these candidate therapeutics, 16 had more than one clinical study supporting AD risk reduction. Top-ranked therapeutics with high confidence emerged within lipid-lowering, anti-inflammatory, hormone, and metabolic-related drug classes.

DISCUSSION

Outcomes of our novel bioinformatic strategy support therapeutic targeting of biological mechanisms and pathways underlying relevant AD risk factors with high confidence. Early interventions that target pathways associated with increased risk of AD have the potential to support the goal of effectively preventing AD by 2025.

Region-Specific Differences in the Apoe4-dependent Response to Focal Brain Injury

Apolipoprotein E (apoE) plays a role in various physiological functions including lipid transport, synaptic plasticity, and immune modulation. Epidemiological studies suggest that the apoE4 allele increases the risk of post-traumatic sequelae. This study was performed to investigate regionspecific effects of the apoE4 isoform on post-traumatic neurodegeneration. Two focal brain injuries were introduced separately in the motor cortex and hippocampus of apoE4 knock-in, apoE3 knock-in, apoE knockout, and wild-type (WT) mice. Western blotting showed that the expression levels of pre-synaptic and post-synaptic markers at the recovery stage were lower in the hippocampal injury core in apoE4 mice, compared with apoE3 and WT mice. Fast glial activation (determined by immunohistochemistry with glial fibrillary acidic protein, ionized calcium binding adaptor molecule 1, and cluster of differentiation 45 antibodies) was characteristic of apoE4 mice with hippocampal injury penumbra. apoE4-specific changes were not observed after cortical injury. The intensity of microglial activation in the hippocampus was inversely correlated with the volume of injury reduction on sequential magnetic resonance imaging examinations, when validated using matched samples. These findings indicate that the effects of the interaction between apoE4 and focal brain damage are specific to the hippocampus. Manipulation of inflammatory cell responses could be beneficial for reducing post-traumatic hippocampal neurodegeneration in apoE4 carriers.

Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop

Imaging genomics is a rapidly evolving field that combines state-of-the-art bioimaging with genomic information to resolve phenotypic heterogeneity associated with genomic variation, improve risk prediction, discover prevention approaches, and enable precision diagnosis and treatment. Contemporary bioimaging methods provide exceptional resolution generating discrete and quantitative high-dimensional phenotypes for genomics investigation. Despite substantial progress in combining high-dimensional bioimaging and genomic data, methods for imaging genomics are evolving. Recognizing the potential impact of imaging genomics on the study of heart and lung disease, the National Heart, Lung, and Blood Institute convened a workshop to review cutting-edge approaches and methodologies in imaging genomics studies, and to establish research priorities for future investigation. This report summarizes the presentations and discussions at the workshop. In particular, we highlight the need for increased availability of imaging genomics data in diverse populations, dedicated focus on less common conditions, and centralization of efforts around specific disease areas.

Identifying novel genetic variants for brain amyloid deposition: a genome-wide association study in the Korean population

Background

Genome-wide association studies (GWAS) have identified a number of genetic variants for Alzheimer’s disease (AD). However, most GWAS were conducted in individuals of European ancestry, and non-European populations are still underrepresented in genetic discovery efforts. Here, we performed GWAS to identify single nucleotide polymorphisms (SNPs) associated with amyloid β (Aβ) positivity using a large sample of Korean population.

Methods

One thousand four hundred seventy-four participants of Korean ancestry were recruited from multicenters in South Korea. Discovery dataset consisted of 1190 participants (383 with cognitively unimpaired [CU], 330 with amnestic mild cognitive impairment [aMCI], and 477 with AD dementia [ADD]) and replication dataset consisted of 284 participants (46 with CU, 167 with aMCI, and 71 with ADD). GWAS was conducted to identify SNPs associated with Aβ positivity (measured by amyloid positron emission tomography). Aβ prediction models were developed using the identified SNPs. Furthermore, bioinformatics analysis was conducted for the identified SNPs.

Results

In addition to APOE, we identified nine SNPs on chromosome 7, which were associated with a decreased risk of Aβ positivity at a genome-wide suggestive level. Of these nine SNPs, four novel SNPs (rs73375428, rs2903923, rs3828947, and rs11983537) were associated with a decreased risk of Aβ positivity (p < 0.05) in the replication dataset. In a meta-analysis, two SNPs (rs7337542 and rs2903923) reached a genome-wide significant level (p < 5.0 × 10⁻⁸). Prediction performance for Aβ positivity increased when rs73375428 were incorporated (area under curve = 0.75; 95% CI = 0.74–0.76) in addition to clinical factors and APOE genotype. Cis-eQTL analysis demonstrated that the rs73375428 was associated with decreased expression levels of FGL2 in the brain.

Conclusion

The novel genetic variants associated with FGL2 decreased risk of Aβ positivity in the Korean population. This finding may provide a candidate therapeutic target for AD, highlighting the importance of genetic studies in diverse populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00854-z.

Atremorine in Parkinson's disease: From dopaminergic neuroprotection to pharmacogenomics

Atremorine is a novel bioproduct obtained by nondenaturing biotechnological processes from a genetic species of Vicia faba. Atremorine is a potent dopamine (DA) enhancer with powerful effects on the neuronal dopaminergic system, acting as a neuroprotective agent in Parkinson's disease (PD). Over 97% of PD patients respond to a single dose of Atremorine (5 g, p.o.) 1 h after administration. This response is gender-, time-, dose-, and genotype-dependent, with optimal doses ranging from 5 to 20 g/day, depending upon disease severity and concomitant medication. Drug-free patients show an increase in DA levels from 12.14 ± 0.34 pg/ml to 6463.21 ± 1306.90 pg/ml; and patients chronically treated with anti-PD drugs show an increase in DA levels from 1321.53 ± 389.94 pg/ml to 16,028.54 ± 4783.98 pg/ml, indicating that Atremorine potentiates the dopaminergic effects of conventional anti-PD drugs. Atremorine also influences the levels of other neurotransmitters (adrenaline, noradrenaline) and hormones which are regulated by DA (e.g., prolactin, PRL), with no effect on serotonin or histamine. The variability in Atremorine-induced DA response is highly attributable to pharmacogenetic factors. Polymorphic variants in pathogenic (SNCA, NUCKS1, ITGA8, GPNMB, GCH1, BCKDK, APOE, LRRK2, ACMSD), mechanistic (DRD2), metabolic (CYP2D6, CYP2C9, CYP2C19, CYP3A4/5, NAT2), transporter (ABCB1, SLC6A2, SLC6A3, SLC6A4) and pleiotropic genes (APOE) influence the DA response to Atremorine and its psychomotor and brain effects. Atremorine enhances DNA methylation and displays epigenetic activity via modulation of the pharmacoepigenetic network. Atremorine is a novel neuroprotective agent for dopaminergic neurons with potential prophylactic and therapeutic activity in PD.

Plasma lipidome is dysregulated in Alzheimer's disease and is associated with disease risk genes

Lipidomics research could provide insights of pathobiological mechanisms in Alzheimer's disease. This study explores a battery of plasma lipids that can differentiate Alzheimer's disease (AD) patients from healthy controls and determines whether lipid profiles correlate with genetic risk for AD. AD plasma samples were collected from the Sydney Memory and Ageing Study (MAS) Sydney, Australia (aged range 75-97 years; 51.2% male). Untargeted lipidomics analysis was performed by liquid chromatography coupled-mass spectrometry (LC-MS/MS). We found that several lipid species from nine lipid classes, particularly sphingomyelins (SMs), cholesterol esters (ChEs), phosphatidylcholines (PCs), phosphatidylethanolamines (PIs), phosphatidylinositols (PIs), and triglycerides (TGs) are dysregulated in AD patients and may help discriminate them from healthy controls. However, when the lipid species were grouped together into lipid subgroups, only the DG group was significantly higher in AD. ChEs, SMs, and TGs resulted in good classification accuracy using the Glmnet algorithm (elastic net penalization for the generalized linear model [glm]) with more than 80% AUC. In general, group lipids and the lipid subclasses LPC and PE had less classification accuracy compared to the other subclasses. We also found significant increases in SMs, PIs, and the LPE/PE ratio in human U251 astroglioma cell lines exposed to pathophysiological concentrations of oligomeric Aβ₄₂. This suggests that oligomeric Aβ₄₂ plays a contributory, if not causal role, in mediating changes in lipid profiles in AD that can be detected in the periphery. In addition, we evaluated the association of plasma lipid profiles with AD-related single nucleotide polymorphisms (SNPs) and polygenic risk scores (PRS) of AD. We found that FERMT2 and MS4A6A showed a significantly differential association with lipids in all lipid classes across disease and control groups. ABCA7 had a differential association with more than half of the DG lipids (52.63%) and PI lipids (57.14%), respectively. Additionally, 43.4% of lipids in the SM class were differentially associated with CLU. More than 30% of lipids in ChE, PE, and TG classes had differential associations with separate genes (ChE-PICALM, SLC24A4, and SORL1; PE-CLU and CR1; TG-BINI) between AD and control group. These data may provide renewed insights into the pathobiology of AD and the feasibility of identifying individuals with greater AD risk.

Role of ABCA7 in Human Health and in Alzheimer's Disease

Several studies, including genome wide association studies (GWAS), have strongly suggested a central role for the ATP-binding cassette transporter subfamily A member 7 (ABCA7) in Alzheimer’s disease (AD). This ABC transporter is now considered as an important genetic determinant for late onset Alzheimer disease (LOAD) by regulating several molecular processes such as cholesterol metabolism and amyloid processing and clearance. In this review we shed light on these new functions and their cross-talk, explaining its implication in brain functioning, and therefore in AD onset and development.

Accelerating Alzheimer's disease drug discovery and development: what's the way forward?

Introduction: As the global burden of Alzheimer's disease (AD) grows, an effective disease-modifying therapy remains a distant prospect following the repeated failure of multiple therapeutics targeting β-amyloid and (it seems) tau over many years of costly effort. The repeated failure of single-target therapies to meaningfully modify disease progression raises major questions about the validity of many aspects of drug development in this area, especially target selection.Area covered: The authors explore the critical questions raised by a review of the collective experience to date, relating to why findings with non-clinical models and clinical biomarkers so frequently fail to translate to positive outcomes in clinical trials, which alternatives should be considered, and how we can design and conduct clinical trials that can successfully identify and quantify meaningful benefits in the future.Expert opinion: It is our opinion that we must recognize and accept the need to consider less specific, more multimodal approaches to addressing neurodegeneration in AD if we are to make progress - and we must avoid repeating the well intentioned, but ultimately erroneous, assumptions of the past.

Associations of Alzheimer's disease risk variants with gene expression, amyloidosis, tauopathy, and neurodegeneration

BACKGROUND

Genome-wide association studies have identified more than 30 Alzheimer's disease (AD) risk genes, although the detailed mechanism through which all these genes are associated with AD pathogenesis remains unknown. We comprehensively evaluate the roles of the variants in top 30 non-APOE AD risk genes, based on whether these variants were associated with altered mRNA transcript levels, as well as brain amyloidosis, tauopathy, and neurodegeneration.

METHODS

Human brain gene expression data were obtained from the UK Brain Expression Consortium (UKBEC), while other data used in our study were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We examined the association of AD risk allele carrier status with the levels of gene expression in blood and brain regions and tested the association with brain amyloidosis, tauopathy, and neurodegeneration at baseline, using a multivariable linear regression model. Next, we analyzed the longitudinal effects of these variants on the change rates of pathology using a mixed effect model.

RESULTS

Altogether, 27 variants were detected to be associated with the altered expression of 21 nearby genes in blood and brain regions. Eleven variants (especially novel variants in ADAM10, IGHV1-68, and SLC24A4/RIN3) were associated with brain amyloidosis, 7 variants (especially in INPP5D, PTK2B) with brain tauopathy, and 8 variants (especially in ECHDC3, HS3ST1) with brain neurodegeneration. Variants in ADAMTS1, BZRAP1-AS1, CELF1, CD2AP, and SLC24A4/RIN3 participated in more than one cerebral pathological process.

CONCLUSIONS

Genetic variants might play functional roles and suggest potential mechanisms in AD pathogenesis, which opens doors to uncover novel targets for AD treatment.