Whole-Exome Sequencing Analysis of Alzheimer's Disease in Non-APOE*4 Carriers

Integrative single-cell RNA sequencing and mendelian randomization analysis reveal the potential role of synaptic vesicle cycling-related genes in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) involves alterations in synaptic vesicle cycling (SVC), which significantly affect neuronal communication and function. Therefore, a thorough investigation into the potential roles of SVC-related genes (SVCRGs) in AD can enhance the identification of critical biomarkers that may influence disease progression and treatment responses.

METHODS

The datasets used in this study were sourced exclusively from public databases. By integrating differential expression analysis with Mendelian randomization (MR), we identified SVCRGs as biomarkers for AD. Functional characterization of these biomarkers was performed, followed by integration into a nomogram. Further investigation of immune infiltration in AD patients and healthy individuals was carried out. Ultimately, the potential cellular mechanisms of AD were explored through single-cell RNA sequencing (scRNA-seq) analysis.

RESULTS

ATP6V1D, ATP6V1G2, CLTB, and NSF were identified as biomarkers, exhibiting a positive correlation with each other and a downregulated expression in AD. These markers were pinpointed as protective factors for AD [odds ratio (OR) < 1, P < 0.05], with potential to reduce the risk of the disease. Integrated into a nomogram, they demonstrated satisfactory diagnostic performance and clinical utility, surpassing the use of single gene. They were collectively enriched in pathways related to "interferon gamma response", "inflammatory response", and "TNFα signaling via NFκB". Additionally, an increase in infiltration of 17 immune cell types in AD was noted, particularly cells associated with neuroinflammation such as activated CD8 T cells and various dendritic cells (DCs), suggesting an inflammatory milieu in AD while also displaying a negative correlation with the biomarkers. The cell types were further annotated, revealing specific expressions of biomarkers and uncovering the heterogeneity of excitatory neurons. A significant reduction in the overall number of excitatory neurons under AD conditions was observed, alongside consistent expression of biomarkers during the developmental stages of excitatory neurons.

CONCLUSION

By using MR, we firstly identified four SVCRGs as protective factors for AD, functioning through pathways associated with mitochondrial dysfunction, chronic inflammation, immune dysregulation, and neuronal damage. These genes had the potential to modulate immune cell infiltration activated in AD patients and exhibited cell-type-specific expression profiles within AD-related cellular contexts. Their findings provide novel insights and valuable references for future research on AD pathogenesis and therapeutic strategies.

Integrated analyses of 5 mC, 5hmC methylation and gene expression reveal pathology-associated AKT3 gene and potential biomarkers for Alzheimer's disease

AIMS

5 mC methylation and hydroxymethylation (5hmC) are associated with Alzheimer's disease (AD). However, previous studies were limited by the absence of a 5hmC calculation. This study aims to find AD associated predictors and potential therapeutic chemicals using bioinformatics approach integrating 5 mC, 5hmC, and expression changes, and an AD mouse model.

METHODS

Gene expression microarray and 5 mC and 5hmC sequencing datasets were downloaded from GEO repository. 142 AD and 52 normal entorhinal cortex specimens were enrolled. Data from oxidative bisulfite sequencing (oxBS)-treated samples, which represent only 5 mC, were used to calculate 5hmC level. Functional analyses, random forest supervised classification and methylation validation were applied. Potential chemicals were predicted by CMap. Morris water maze, Y maze and novel object recognition behavior tests were performed using FAD4T AD mice model. Cortex and hippocampus tissues were isolated for immunohistochemical staining.

RESULTS

C1QTNF5, UBD, ZFP106, NEDD1, AKT3, and MBP genes involving 13 promoter CpG sites with 5mc, 5hmC methylation and expression difference were identified. AKT3 and MBP were down-regulated in both patients and mouse model. Three CpG sites in AKT3 and MBP showed significant methylation difference on validation. FAD4T AD mice showed recession in brain functions and lower AKT3 expression in both cortex and hippocampus. Ten chemicals were predicted as potential treatments for AD.

CONCLUSIONS

AKT3 and MBP may be associated with AD pathology and could serve as biomarkers. The ten predicted chemicals might offer new therapeutic approaches. Our findings could contribute to identifying novel markers and advancing the understanding of AD mechanisms.

Ethnoracial Identity and Cognitive Impairment: A Community Study

BACKGROUND

Identifying potentially modifiable risk factors associated with MCI in different ethnoracial groups could reduce MCI burden and health inequity in the population.

METHODS

Among 2845 adults aged 65+ years, we investigated potential risk exposures including education, physical and mental health, lifestyle, and sensory function, and their cross-sectional associations with MCI. We compared proportions of exposures between Black and White participants and explored relationships among race, MCI, and exposures. Logistic regression modeled MCI as a function of each exposure in the overall sample adjusting for age, sex, educational level, and race, and investigating race*exposure interactions.

RESULTS

Compared with White participants, Black participants had greater odds of MCI (OR 1.53; 95% CI, 1.13 to 2.06) and were more likely to report depressive symptoms, diabetes, and stroke, to have high blood pressure and BMI, and to be APOE - 4 carriers. Exposures associated with higher odds of MCI were diabetes, stroke, lifetime smoking, sleep disturbances, social isolation, loneliness, depression and anxiety symptoms, and vision and hearing loss. There were no significant interactions between race and any exposure.

CONCLUSIONS

Black participants had 53% higher odds of MCI adjusting for age, sex, and education. The same exposures were associated with MCI in Black and White participants.

Association of NOTCH4 and ACHE gene polymorphism in Alzheimer's disease of Gujarat cohort

BACKGROUND

Alzheimer's Disease (AD) is the most common form of dementia, affecting cognitive and behavioral functions. AD is a complex disease resulting from the modest effect of gene interaction and environmental factors, as a result of which the exact pathogenesis is still unknown.

AIM

The aim of the present study was to investigate the association between variants of 98 targeted genes with Alzheimer's disease phenotype.

METHOD

A total of 98 genes from 32 AD cases and 11 controls were genotyped using the Haloplex target enrichment method and the PCR-RFLP approach.Association analysis was performed using the PLINK tool to identify the variant significantly associated with AD. Functional enrichment analysis and network analysis was performed using ClueGo and String database respectively. The Expression Quantitative Trait Loci (eQTL) analysis using the Genotype Tissue Expression (GTEx) dataset to explore the possible implication of the variant on the expression of one or more genes in different brain regions and whole blood.

RESULT

Association analysis showed significant association of 19 variant assigned to 16 genes with Alzheimer's with p-value < 0.05 with rs367398/NOTCH4 only variant that passed multiple test corrections. Functional enrichment analysis showed association of these genes with AD. ClueGo and network analysis utilizing the String database suggested that genes are directly and indirectly linked to the AD pathogenesis. eQTL analysis revealed that the rs367398/NOTCH4 and rs1799806/ACHE variant showed significant eQTL for the neighbouring genes.

CONCLUSION

The present study showed the possible role of 16 genes in AD pathogenesis, especially highlighting the role of rs367398/NOTCH4 and rs1799806/ACHE. However further investigation with large cohort is required to study and validate the implication of these variants in the AD pathogenesis.

Microglia in Alzheimer's disease: pathogenesis, mechanisms, and therapeutic potentials

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by protein aggregation in the brain. Recent studies have revealed the critical role of microglia in AD pathogenesis. This review provides a comprehensive summary of the current understanding of microglial involvement in AD, focusing on genetic determinants, phenotypic state, phagocytic capacity, neuroinflammatory response, and impact on synaptic plasticity and neuronal regulation. Furthermore, recent developments in drug discovery targeting microglia in AD are reviewed, highlighting potential avenues for therapeutic intervention. This review emphasizes the essential role of microglia in AD and provides insights into potential treatments.

Genetic overlap between cortical brain morphometry and frontotemporal dementia risk

Frontotemporal dementia (FTD) has a complex genetic etiology, where the precise mechanisms underlying the selective vulnerability of brain regions remain unknown. We leveraged summary-based data from genome-wide association studies (GWAS) and performed LD score regression to estimate pairwise genetic correlations between FTD risk and cortical brain imaging. Then, we isolated specific genomic loci with a shared etiology between FTD and brain structure. We also performed functional annotation, summary-data-based Mendelian randomization for eQTL using human peripheral blood and brain tissue data, and evaluated the gene expression in mice targeted brain regions to better understand the dynamics of the FTD candidate genes. Pairwise genetic correlation estimates between FTD and brain morphology measures were high but not statistically significant. We identified 5 brain regions with a strong genetic correlation (rg > 0.45) with FTD risk. Functional annotation identified 8 protein-coding genes. Building upon these findings, we show in a mouse model of FTD that cortical N-ethylmaleimide sensitive factor (NSF) expression decreases with age. Our results highlight the molecular and genetic overlap between brain morphology and higher risk for FTD, specifically for the right inferior parietal surface area and right medial orbitofrontal cortical thickness. In addition, our findings implicate NSF gene expression in the etiology of FTD.

Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia

Proxy phenotypes allow for the utilization of genetic data from large population cohorts to analyze late-onset diseases by using parental diagnoses as a proxy for genetic disease risk. Proxy phenotypes based on parental diagnosis status have been used in previous studies to identify common variants associated with Alzheimer's disease. As of yet, proxy phenotypes have not been used to identify genes associated with Alzheimer's disease through rare variants. Here we show that a proxy Alzheimer's disease/dementia phenotype can capture known Alzheimer's disease risk genes through rare variant aggregation. We generated a proxy Alzheimer's disease/dementia phenotype for 148,508 unrelated individuals of European ancestry in the UK biobank in order to perform exome-wide rare variant aggregation analyses to identify genes associated with proxy Alzheimer's disease/dementia. We identified four genes significantly associated with the proxy phenotype, three of which were significantly associated with proxy Alzheimer's disease/dementia in an independent replication cohort consisting of 197,506 unrelated individuals of European ancestry in the UK biobank. All three of the replicated genes have been previously associated with clinically diagnosed Alzheimer's disease (SORL1, TREM2, and TOMM40/APOE). We show that proxy Alzheimer's disease/dementia can be used to identify genes associated with Alzheimer's disease through rare variant aggregation.

Investigation of the independent role of a rare APOE variant (L28P; APOE*4Pittsburgh) in late-onset Alzheimer disease

A rare missense APOE variant (L28P; APOE*4Pittsburgh), which is present only in populations with European ancestry, has been reported to be a risk factor for late-onset Alzheimer's disease (LOAD). However, due to the complete linkage disequilibrium of L28P with APOE*4 (C112R), its independent genetic association is uncertain. The original association study implicating L28P with LOAD risk was carried out in a relatively small sample size. In the current study, we have re-evaluated this association in a large case-control sample of 15,762 White U.S. subjects and investigated its independent effect in APOE 3/4 subjects, as L28P has been observed only in the heterozygous state of APOE*4 carriers and 3/4 is the most common genotype containing the APOE*4 allele. The heterozygous carrier frequency of L28P, all with APOE*4, was about 3-fold higher in AD cases than in cognitively intact controls (0.845% vs. 0.277%). The age- and sex-adjusted meta-analysis odds ratio (OR) was 2.87 (95% CI: 1.34 - 6.13; = 0.0066). Among APOE 3/4 subjects, age- and sex-adjusted meta-analysis OR was 1.53 (95% CI: 0.70 - 3.36; p = 0.28), indicating its effect was independent of APOE*4. The lack of statistical significance appears mainly due to the low power of 4138 subjects with the 3/4 genotype (12% power at α= 0.05) compared to the required sample of 139,088 subjects with the 3/4 genotype to detect an OR of 1.5 at α= 0.05 and 80% power. Our data suggesting that L28P has an independent genetic effect on AD risk is reinforced by earlier experimental findings showing that this mutation leads to significant structural and conformational changes in the ApoE4 molecule and can induce functional defects associated with neuronal Aβ42 accumulation and oxidative stress. Additional functional studies in cell-based systems and animal models will help to delineate its functional significance in the etiology of AD.

Novel Genetic Variants in TP37, PIK3R1, CALM1, and PLCG2 of the Neurotrophin Signaling Pathway Are Associated with the Progression from Mild Cognitive Impairment to Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a common neurodegenerative disease and mild cognitive impairment (MCI) is considered as the prodromal stage of AD. Previous studies showed that changes in the neurotrophin signaling pathway could lead to cognitive decline in AD. However, the association of single nucleotide polymorphisms (SNPs) in genes that are involved in this pathway with AD progression from MCI remains unclear.

OBJECTIVE

We investigated the associations between SNPs involved in the neurotrophin signaling pathway with AD progression.

METHODS

We performed single-locus analysis to identify neurotrophin-signaling-related SNPs associated with the AD progression using 767 patients from the Alzheimer's Disease Neuroimaging Initiative study and 1,373 patients from the National Alzheimer's Coordinating Center study. We constructed polygenic risk scores (PRSs) using the identified independent non-APOE SNPs and evaluated its prediction performance on AD progression.

RESULTS

We identified 25 SNPs significantly associated with AD progression with Bayesian false-discovery probability ≤0.8. Based on the linkage disequilibrium clumping and expression quantitative trait loci analysis, we found 6 potentially functional SNPs that were associated with AD progression independently. The PRS analysis quantified the combined effects of these SNPs on longitudinal cognitive assessments and biomarkers from cerebrospinal fluid and neuroimaging. The addition of PRSs to the prediction model for 3-year progression to AD from MCI significantly increased the predictive accuracy.

CONCLUSION

Genetic variants in the specific genes of the neurotrophin signaling pathway are predictors of AD progression. eQTL analysis supports that these SNPs regulate expression of key genes involved in the neurotrophin signaling pathway.

Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through  GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.

Genomics and Functional Genomics of Alzheimer's Disease

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.

Genomics of Alzheimer's disease implicates the innate and adaptive immune systems

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterised by cognitive impairment, behavioural alteration, and functional decline. Over 130 AD-associated susceptibility loci have been identified by genome-wide association studies (GWAS), while whole genome sequencing (WGS) and whole exome sequencing (WES) studies have identified AD-associated rare variants. These variants are enriched in APOE, TREM2, CR1, CD33, CLU, BIN1, CD2AP, PILRA, SCIMP, PICALM, SORL1, SPI1, RIN3, and more genes. Given that aging is the single largest risk factor for late-onset AD (LOAD), the accumulation of somatic mutations in the brain and blood of AD patients have also been explored. Collectively, these genetic findings implicate the role of innate and adaptive immunity in LOAD pathogenesis and suggest that a systemic failure of cell-mediated amyloid-β (Aβ) clearance contributes to AD onset and progression. AD-associated variants are particularly enriched in myeloid-specific regulatory regions, implying that AD risk variants are likely to perturbate the expression of myeloid-specific AD-associated genes to interfere Aβ clearance. Defective phagocytosis, endocytosis, and autophagy may drive Aβ accumulation, which may be related to naturally-occurring antibodies to Aβ (Nabs-Aβ) produced by adaptive responses. Passive immunisation is providing efficiency in clearing Aβ and slowing cognitive decline, such as aducanumab, donanemab, and lecanemab (ban2401). Causation of AD by impairment of the innate immunity and treatment using the tools of adaptive immunity is emerging as a new paradigm for AD, but immunotherapy that boosts the innate immune functions of myeloid cells is highly expected to modulate disease progression at asymptomatic stage.

Reassessment of Pioglitazone for Alzheimer's Disease

Alzheimer's disease is a quintessential 'unmet medical need', accounting for ∼65% of progressive cognitive impairment among the elderly, and 700,000 deaths in the United States in 2020. In 2019, the cost of caring for Alzheimer's sufferers was $244B, not including the emotional and physical toll on caregivers. In spite of this dismal reality, no treatments are available that reduce the risk of developing AD or that offer prolonged mitiagation of its most devestating symptoms. This review summarizes key aspects of the biology and genetics of Alzheimer's disease, and we describe how pioglitazone improves many of the patholophysiological determinants of AD. We also summarize the results of pre-clinical experiments, longitudinal observational studies, and clinical trials. The results of animal testing suggest that pioglitazone can be corrective as well as protective, and that its efficacy is enhanced in a time- and dose-dependent manner, but the dose-effect relations are not monotonic or sigmoid. Longitudinal cohort studies suggests that it delays the onset of dementia in individuals with pre-existing type 2 diabetes mellitus, which small scale, unblinded pilot studies seem to confirm. However, the results of placebo-controlled, blinded clinical trials have not borne this out, and we discuss possible explanations for these discrepancies.

Searching the Dark Genome for Alzheimer's Disease Risk Variants

Sporadic Alzheimer's disease (AD) is a complex genetic disease, and the leading cause of dementia worldwide. Over the past 3 decades, extensive pioneering research has discovered more than 70 common and rare genetic risk variants. These discoveries have contributed massively to our understanding of the pathogenesis of AD but approximately half of the heritability for AD remains unaccounted for. There are regions of the genome that are not assayed by mainstream genotype and sequencing technology. These regions, known as the Dark Genome, often harbour large structural DNA variants that are likely relevant to disease risk. Here, we describe the dark genome and review current technological and bioinformatics advances that will enable researchers to shed light on these hidden regions of the genome. We highlight the potential importance of the hidden genome in complex disease and how these strategies will assist in identifying the missing heritability of AD. Identification of novel protein-coding structural variation that increases risk of AD will open new avenues for translational research and new drug targets that have the potential for clinical benefit to delay or even prevent clinical symptoms of disease.