Risk prediction of late-onset Alzheimer's disease implies an oligogenic architecture

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement

BACKGROUND

Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets.

METHODS

We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer's disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups.

RESULTS

Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations.

CONCLUSIONS

This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.

Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.

Integration of polygenic and gut metagenomic risk prediction for common diseases

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.

The advent of Alzheimer treatments will change the trajectory of human aging

Slowing neurodegenerative disorders of late life has lagged behind progress on other chronic diseases. But advances in two areas, biochemical pathology and human genetics, have now identified early pathogenic events, enabling molecular hypotheses and disease-modifying treatments. A salient example is the discovery that antibodies to amyloid ß-protein, long debated as a causative factor in Alzheimer's disease (AD), clear amyloid plaques, decrease levels of abnormal tau proteins and slow cognitive decline. Approval of amyloid antibodies as the first disease-modifying treatments means a gradually rising fraction of the world's estimated 60 million people with symptomatic disease may decline less or even stabilize. Society is entering an era in which the unchecked devastation of AD is no longer inevitable. This Perspective considers the impact of slowing AD and other neurodegenerative disorders on the trajectory of aging, allowing people to survive into late life with less functional decline. The implications of this moment for medicine and society are profound.

AI-enabled evaluation of genome-wide association relevance and polygenic risk score prediction in Alzheimer's disease

GWAS focuses on significance loosing false positives; machine learning probes sub-significant features relying on predictivity. Yet, these are far from orthogonal. We sought to explore how these inform each other in sub-genome-wide significant situations to define relevance for predictive features. We introduce the SVM-based RubricOE that selects heavily cross-validated feature sets, and LDpred2 PRS as a strong contrast to SVM, to explore significance and predictivity. Our Alzheimer's test case notoriously lacks strong genetic signals except for few very strong phenotype-SNP associations, which suits the problem we are exploring. We found that the most significant SNPs among ML and PRS-selected SNPs captured most of the predictivity, while weaker associations tend also to contribute weakly to predictivity. SNPs with weak associations tend not to contribute to predictivity, but deletion of these features does not injure it. Significance provides a ranking that helps identify weakly predictive features.

Polygenic effects on the risk of Alzheimer's disease in the Japanese population

BACKGROUND

Polygenic effects have been proposed to account for some disease phenotypes; these effects are calculated as a polygenic risk score (PRS). This score is correlated with Alzheimer's disease (AD)-related phenotypes, such as biomarker abnormalities and brain atrophy, and is associated with conversion from mild cognitive impairment (MCI) to AD. However, the AD PRS has been examined mainly in Europeans, and owing to differences in genetic structure and lifestyle, it is unclear whether the same relationships between the PRS and AD-related phenotypes exist in non-European populations. In this study, we calculated and evaluated the AD PRS in Japanese individuals using genome-wide association study (GWAS) statistics from Europeans.

METHODS

In this study, we calculated the AD PRS in 504 Japanese participants (145 cognitively unimpaired (CU) participants, 220 participants with late mild cognitive impairment (MCI), and 139 patients with mild AD dementia) enrolled in the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) project. In order to evaluate the clinical value of this score, we (1) determined the polygenic effects on AD in the J-ADNI and validated it using two independent cohorts (a Japanese neuropathology (NP) cohort (n = 565) and the North American ADNI (NA-ADNI) cohort (n = 617)), (2) examined the AD-related phenotypes associated with the PRS, and (3) tested whether the PRS helps predict the conversion of MCI to AD.

RESULTS

The PRS using 131 SNPs had an effect independent of APOE. The PRS differentiated between CU participants and AD patients with an area under the curve (AUC) of 0.755 when combined with the APOE variants. Similar AUC was obtained when PRS calculated by the NP and NA-ADNI cohorts was applied. In MCI patients, the PRS was associated with cerebrospinal fluid phosphorylated-tau levels (β estimate = 0.235, p value = 0.026). MCI with a high PRS showed a significantly increased conversion to AD in APOE ε4 noncarriers with a hazard rate of 2.22. In addition, we also developed a PRS model adjusted for LD and observed similar results.

CONCLUSIONS

We showed that the AD PRS is useful in the Japanese population, whose genetic structure is different from that of the European population. These findings suggest that the polygenicity of AD is partially common across ethnic differences.

Inherited polygenic effects on common hematological traits influence clonal selection on JAK2V617F and the development of myeloproliferative neoplasms

Myeloproliferative neoplasms (MPNs) are chronic cancers characterized by overproduction of mature blood cells. Their causative somatic mutations, for example, JAK2V617F, are common in the population, yet only a minority of carriers develop MPN. Here we show that the inherited polygenic loci that underlie common hematological traits influence JAK2V617F clonal expansion. We identify polygenic risk scores (PGSs) for monocyte count and plateletcrit as new risk factors for JAK2V617F positivity. PGSs for several hematological traits influenced the risk of different MPN subtypes, with low PGSs for two platelet traits also showing protective effects in JAK2V617F carriers, making them two to three times less likely to have essential thrombocythemia than carriers with high PGSs. We observed that extreme hematological PGSs may contribute to an MPN diagnosis in the absence of somatic driver mutations. Our study showcases how polygenic backgrounds underlying common hematological traits influence both clonal selection on somatic mutations and the subsequent phenotype of cancer.

Vitamin D, Cognition, and Alzheimer's Disease: Observational and Two-Sample Mendelian Randomization Studies

Background

Observational studies have found that vitamin D supplementation is associated with improved cognition. Further, recent Mendelian randomization (MR) studies have shown that higher vitamin D levels, 25(OH)D, may protect against Alzheimer's disease. Thus, it is possible that 25(OH)D may protect against Alzheimer's disease by improving cognition.

Objective

We assessed this hypothesis, by examining the relationship between 25(OH)D levels and seven cognitive measurements.

Methods

To mitigate bias from confounding, we performed two-sample MR analyses. We used instruments from three publications: Manousaki et al. (2020), Sutherland et al. (2022), and the Emerging Risk Factors Collaboration/EPIC-CVD/Vitamin D Studies Collaboration (2021).

Results

Our observational studies suggested a protective association between 25(OH)D levels and cognitive measures. An increase in the natural log of 25(OH)D by 1 SD was associated with a higher PACC score (BetaPACC score = 0.06, 95% CI = (0.04-0.08); p = 1.8×10-10). However, in the MR analyses, the estimated effect of 25(OH)D on cognitive measures was null. Specifically, per 1 SD increase in genetically estimated natural log of 25(OH)D, the PACC scores remained unchanged in the overall population, (BetaPACC score = -0.01, 95% CI (-0.06 to 0.03); p = 0.53), and amongst individuals aged over 60 (BetaPACC score = 0.03, 95% CI (-0.028 to 0.08); p = 0.35).

Conclusions

In conclusion, our MR study found no clear evidence to support a protective role of increased 25(OH)D concentrations on cognitive performance in European ancestry individuals. However, our study cannot entirely dismiss the potential beneficial effect on PACC for individuals over the age of 60.

Digital Clock Drawing as an Alzheimer's Disease Susceptibility Biomarker: Associations with Genetic Risk Score and APOE in Older Adults

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until significant neuronal loss has likely occurred along with a decline in cognition. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection.

OBJECTIVE

We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker.

DESIGN

We used two primary independent variables, Apolipoprotein E (APOE) ε4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures.

SETTING

We used existing data from the Framingham Heart Study (FHS), a community-based study with the largest dataset of digital clock drawing data to date.

PARTICIPANTS

The sample consisted of 2,398 older adults ages 60-94 with DCTclockTM data (mean age of 72.3, 55% female and 92% White).

MEASUREMENTS

PRS was calculated using 38 variants identified in a recent large genome-wide association study (GWAS) and meta-analysis of late-onset AD (LOAD).

RESULTS

Results showed that DCTclockTM performance decreased with advancing age, lower education, and the presence of one or more copies of APOE ε4. Lower DCTclockTM Total Score as well as lower composite scores for Information Processing Speed (both command and copy conditions) and Drawing Efficiency (command condition) were significantly associated with higher PRS levels and more copies of APOE ε4. APOE and PRS associations displayed similar effect sizes in both men and women.

CONCLUSIONS

Our results indicate that higher AD genetic risk is associated with poorer DCTclockTM performance in older adults without dementia. This is the first study to demonstrate significant differences in clock drawing performance on the basis of APOE status or PRS.

An interpretable Alzheimer's disease oligogenic risk score informed by neuroimaging biomarkers improves risk prediction and stratification

Introduction

Stratification of Alzheimer's disease (AD) patients into risk subgroups using Polygenic Risk Scores (PRS) presents novel opportunities for the development of clinical trials and disease-modifying therapies. However, the heterogeneous nature of AD continues to pose significant challenges for the clinical broadscale use of PRS. PRS remains unfit in demonstrating sufficient accuracy in risk prediction, particularly for individuals with mild cognitive impairment (MCI), and in allowing feasible interpretation of specific genes or SNPs contributing to disease risk. We propose adORS, a novel oligogenic risk score for AD, to better predict risk of disease by using an optimized list of relevant genetic risk factors.

Methods

Using whole genome sequencing data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (n  =  1,545), we selected 20 genes that exhibited the strongest correlations with FDG-PET and AV45-PET, recognized neuroimaging biomarkers that detect functional brain changes in AD. This subset of genes was incorporated into adORS to assess, in comparison to PRS, the prediction accuracy of CN vs. AD classification and MCI conversion prediction, risk stratification of the ADNI cohort, and interpretability of the genetic information included in the scores.

Results

adORS improved AUC scores over PRS in both CN vs. AD classification and MCI conversion prediction. The oligogenic model also refined risk-based stratification, even without the assistance of APOE, thus reflecting the true prevalence rate of the ADNI cohort compared to PRS. Interpretation analysis shows that genes included in adORS, such as ATF6, EFCAB11, ING5, SIK3, and CD46, have been observed in similar neurodegenerative disorders and/or are supported by AD-related literature.

Discussion

Compared to conventional PRS, adORS may prove to be a more appropriate choice of differentiating patients into high or low genetic risk of AD in clinical studies or settings. Additionally, the ability to interpret specific genetic information allows the focus to be shifted from general relative risk based on a given population to the information that adORS can provide for a single individual, thus permitting the possibility of personalized treatments for AD.

Screening of Multitarget-Directed Natural Compounds as Drug Candidates for Alzheimer's Disease Using In Silico Techniques: Their Extraction and In Vitro Validation

Alzheimer's disease (AD) is a neurodegenerative disorder that impairs neurocognitive function. Acetylcholinesterase (AChE) and β-site APP cleaving enzyme 1 (BACE1) are the two main proteins implicated in AD. Indeed, the major available commercial drugs (donepezil, rivastigmine, and galantamine) against Alzheimer's are AChE inhibitors. However, none of these drugs are known to reverse or reduce the pathophysiological condition of the disease since there are multiple contributing factors to AD. Therefore, there is a need to develop a multitarget-directed ligand approach for its treatment. In the present study, plant bioactive compounds were screened for their AChE and BACE1 inhibition potential by conducting molecular docking studies. Considering their docking score and pharmacokinetic properties, limonin, peimisine, serratanine B, and withanolide A were selected as the lead compounds. Molecular dynamics simulations of these protein-ligand complexes confirmed the conformational and energetically stabilized enzyme-inhibitor complexes. The inhibition potential of the lead compounds was validated by in vitro enzyme assay. Withanolide A inhibited AChE (IC50 value of 107 μM) and showed mixed-type inhibition. At this concentration, it inhibited BACE1 activity by 57.10% and was stated as most effective. Both the compounds, as well as their crude extracts, were found to have no cytotoxic effect on the SH-SY5Y cell line.

Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform

Alzheimer's disease (AD) is a complex genetic disease, and variants identified through genome-wide association studies (GWAS) explain only part of its heritability. Epistasis has been proposed as a major contributor to this 'missing heritability', however, many current methods are limited to only modelling additive effects. We use VariantSpark, a machine learning approach to GWAS, and BitEpi, a tool for epistasis detection, to identify AD associated variants and interactions across two independent cohorts, ADNI and UK Biobank. By incorporating significant epistatic interactions, we captured 10.41% more phenotypic variance than logistic regression (LR). We validate the well-established AD loci, APOE, and identify two novel genome-wide significant AD associated loci in both cohorts, SH3BP4 and SASH1, which are also in significant epistatic interactions with APOE. We show that the SH3BP4 SNP has a modulating effect on the known pathogenic APOE SNP, demonstrating a possible protective mechanism against AD. SASH1 is involved in a triplet interaction with pathogenic APOE SNP and ACOT11, where the SASH1 SNP lowered the pathogenic interaction effect between ACOT11 and APOE. Finally, we demonstrate that VariantSpark detects disease associations with 80% fewer controls than LR, unlocking discoveries in well annotated but smaller cohorts.

Evaluation of the Polygenic Risk Score for Alzheimer's Disease in Russian Patients with Dementia Using a Low-Density Hydrogel Oligonucleotide Microarray

The polygenic risk score (PRS), together with the ɛ4 allele of the APOE gene (APOE-ɛ4), has shown high potential for Alzheimer's disease (AD) risk prediction. The aim of this study was to validate the model of polygenic risk in Russian patients with dementia. A microarray-based assay was developed to identify 21 markers of polygenic risk and ɛ alleles of the APOE gene. This case-control study included 348 dementia patients and 519 cognitively normal volunteers. Cerebrospinal fluid (CSF) amyloid-β (Aβ) and tau protein levels were assessed in 57 dementia patients. PRS and APOE-ɛ4 were significant genetic risk factors for dementia. Adjusted for APOE-ɛ4, individuals with PRS corresponding to the fourth quartile had an increased risk of dementia compared to the first quartile (OR 1.85; p-value 0.002). The area under the curve (AUC) was 0.559 for the PRS model only, and the inclusion of APOE-ɛ4 improved the AUC to 0.604. PRS was positively correlated with tTau and pTau181 and inversely correlated with Aβ42/Aβ40 ratio. Carriers of APOE-ɛ4 had higher levels of tTau and pTau181 and lower levels of Aβ42 and Aβ42/Aβ40. The developed assay can be part of a strategy for assessing individuals for AD risk, with the purpose of assisting primary preventive interventions.

Transfer Learning for Classification of Alzheimer's Disease Based on Genome Wide Data

Alzheimer's disease (AD) is a type of brain disorder that is regarded as a degenerative disease because the corresponding symptoms aggravate with the time progression. Single nucleotide polymorphisms (SNPs) have been identified as relevant biomarkers for this condition. This study aims to identify SNPs biomarkers associated with the AD in order to perform a reliable classification of AD. In contrast to existing related works, we utilize deep transfer learning with varying experimental analysis for reliable classification of AD. For this purpose, the convolutional neural networks (CNN) are firstly trained over the genome-wide association studies (GWAS) dataset requested from the AD neuroimaging initiative. We then employ the deep transfer learning for further training of our CNN (as base model) over a different AD GWAS dataset, to extract the final set of features. The extracted features are then fed into Support Vector Machine for classification of AD. Detailed experiments are performed using multiple datasets and varying experimental configurations. The statistical outcomes indicate an accuracy of 89% which is a significant improvement when benchmarked with existing related works.

Can Genetic Markers Predict the Sporadic Form of Alzheimer's Disease? An Updated Review on Genetic Peripheral Markers

Alzheimer's disease (AD) is the most common form of dementia that affects millions of individuals worldwide. Although the research over the last decades has provided new insight into AD pathophysiology, there is currently no cure for the disease. AD is often only diagnosed once the symptoms have become prominent, particularly in the late-onset (sporadic) form of AD. Consequently, it is essential to further new avenues for early diagnosis. With recent advances in genomic analysis and a lower cost of use, the exploration of genetic markers alongside RNA molecules can offer a key avenue for early diagnosis. We have here provided a brief overview of potential genetic markers differentially expressed in peripheral tissues in AD cases compared to controls, as well as considering the changes to the dynamics of RNA molecules. By integrating both genotype and RNA changes reported in AD, biomarker profiling can be key for developing reliable AD diagnostic tools.

Pathway-specific polygenic scores for Alzheimer's disease are associated with changes in brain structure in younger and older adults

Genome-wide association studies have identified multiple Alzheimer's disease risk loci with small effect sizes. Polygenic risk scores, which aggregate these variants, are associated with grey matter structural changes. However, genome-wide scores do not allow mechanistic interpretations. The present study explored associations between disease pathway-specific scores and grey matter structure in younger and older adults. Data from two separate population cohorts were used as follows: the Avon Longitudinal Study of Parents and Children, mean age 19.8, and UK Biobank, mean age 64.4 (combined n = 18 689). Alzheimer's polygenic risk scores were computed using the largest genome-wide association study of clinically assessed Alzheimer's to date. Relationships between subcortical volumes and cortical thickness, pathway-specific scores and genome-wide scores were examined. Increased pathway-specific scores were associated with reduced cortical thickness in both the younger and older cohorts. For example, the reverse cholesterol transport pathway score showed evidence of association with lower left middle temporal cortex thickness in the younger Avon participants (P = 0.034; beta = -0.013, CI -0.025, -0.001) and in the older UK Biobank participants (P = 0.019; beta = -0.003, CI -0.005, -4.56 × 10-4). Pathway scores were associated with smaller subcortical volumes, such as smaller hippocampal volume, in UK Biobank older adults. There was also evidence of positive association between subcortical volumes in Avon younger adults. For example, the tau protein-binding pathway score was negatively associated with left hippocampal volume in UK Biobank (P = 8.35 × 10-05; beta = -11.392, CI -17.066, -5.718) and positively associated with hippocampal volume in the Avon study (P = 0.040; beta = 51.952, CI 2.445, 101.460). The immune response score had a distinct pattern of association, being only associated with reduced thickness in the right posterior cingulate in older and younger adults (P = 0.011; beta = -0.003, CI -0.005, -0.001 in UK Biobank; P = 0.034; beta = -0.016, CI -0.031, -0.001 in the Avon study). The immune response score was associated with smaller subcortical volumes in the older adults, but not younger adults. The disease pathway scores showed greater evidence of association with imaging phenotypes than the genome-wide score. This suggests that pathway-specific polygenic methods may allow progress towards a mechanistic understanding of structural changes linked to polygenic risk in pre-clinical Alzheimer's disease. Pathway-specific profiling could further define pathophysiology in individuals, moving towards precision medicine in Alzheimer's disease.

Intervention of next-generation sequencing in diagnosis of Alzheimer's disease: challenges and future prospects

Clinical diagnosis of several neurodegenerative disorders based on clinical phenotype is challenging due to its heterogeneous nature and overlapping disease manifestations. Therefore, the identification of underlying genetic mechanisms is of paramount importance for better diagnosis and therapeutic regimens. With the emergence of next-generation sequencing, it becomes easier to identify all gene variants in the genome simultaneously, with a system-wide and unbiased approach. Presently various bioinformatics databases are maintained on discovered gene variants and phenotypic indications are available online. Since individuals are unique in their genome, evaluation based on their genetic makeup helps evolve the diagnosis, counselling, and treatment process at the personal level. This article aims to briefly summarize the utilization of next-generation sequencing in deciphering the genetic causes of Alzheimer's disease and address the limitations of whole genome and exome sequencing.

Alzheimer's polygenic risk scores, APOE, Alzheimer's disease risk, and dementia-related blood biomarker levels in a population-based cohort study followed over 17 years

BACKGROUND

In order to utilize polygenic risk scores (PRSs) for Alzheimer's disease (AD) in a meaningful way, influential factors (i.e. training set) and prediction across groups such as APOE e4 (APOE4) genotype as well as associations to dementia-related biomarkers should be explored. Therefore, we examined the association of APOE4 and various PRSs, based on training sets that utilized differing AD definitions, with incident AD and all-cause dementia (ACD) within 17 years, and with levels of phosphorylated tau181 (P-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) in blood. Secondarily, effect modification by APOE4 status and sex was examined.

METHODS

In this prospective, population-based cohort study and nested case-control study, 9,940 participants in Germany were enrolled between 2000 and 2002 by their general practitioners and followed for up to 17 years. Participants were included in this study if dementia status and genetic data were available. A subsample of participants additionally had measurements of P-tau181, NfL, and GFAP obtained from blood samples. Cox and logistic regression analyses were used to assess the association of genetic risk (APOE genotype and PRSnoAPOE) with incident ACD/AD and log-transformed blood levels of P-tau181, NfL, and GFAP.

RESULTS

Five thousand seven hundred sixty-five participants (54% female, aged 50-75years at baseline) were included in this study, of whom 464 received an all-cause dementia diagnosis within 17 years. The PRSs were not more predictive of dementia than APOE4. An APOE4 specific relationship was apparent with PRSs only exhibiting associations to dementia among APOE4 carriers. In the nested case-control study including biomarkers (n = 712), APOE4 status and polygenic risk were significantly associated to levels of GFAP in blood.

CONCLUSIONS

The use of PRSs may be beneficial for increased precision in risk estimates among APOE4 carriers. While APOE4 may play a crucial etiological role in initial disease processes such as Aβ deposition, the PRS may be an indicator of further disease drivers as well as astrocyte activation. Further research is necessary to confirm these findings, especially the association to GFAP.

Role of neuroinflammation in neurodegeneration development

Studies in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease and Amyotrophic lateral sclerosis, Huntington's disease, and so on, have suggested that inflammation is not only a result of neurodegeneration but also a crucial player in this process. Protein aggregates which are very common pathological phenomenon in neurodegeneration can induce neuroinflammation which further aggravates protein aggregation and neurodegeneration. Actually, inflammation even happens earlier than protein aggregation. Neuroinflammation induced by genetic variations in CNS cells or by peripheral immune cells may induce protein deposition in some susceptible population. Numerous signaling pathways and a range of CNS cells have been suggested to be involved in the pathogenesis of neurodegeneration, although they are still far from being completely understood. Due to the limited success of traditional treatment methods, blocking or enhancing inflammatory signaling pathways involved in neurodegeneration are considered to be promising strategies for the therapy of neurodegenerative diseases, and many of them have got exciting results in animal models or clinical trials. Some of them, although very few, have been approved by FDA for clinical usage. Here we comprehensively review the factors affecting neuroinflammation and the major inflammatory signaling pathways involved in the pathogenicity of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and Amyotrophic lateral sclerosis. We also summarize the current strategies, both in animal models and in the clinic, for the treatment of neurodegenerative diseases.

Cholesterol Metabolism in Aging and Age-Related Disorders

All mammalian cell membranes contain cholesterol to maintain membrane integrity. The transport of this hydrophobic lipid is mediated by lipoproteins. Cholesterol is especially enriched in the brain, particularly in synaptic and myelin membranes. Aging involves changes in sterol metabolism in peripheral organs and also in the brain. Some of those alterations have the potential to promote or to counteract the development of neurodegenerative diseases during aging. Here, we summarize the current knowledge of general principles of sterol metabolism in humans and mice, the most widely used model organism in biomedical research. We discuss changes in sterol metabolism that occur in the aged brain and highlight recent developments in cell type-specific cholesterol metabolism in the fast-growing research field of aging and age-related diseases, focusing on Alzheimer's disease. We propose that cell type-specific cholesterol handling and the interplay between cell types critically influence age-related disease processes.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

Identification of novel genes for age-at-onset of Alzheimer's disease by combining quantitative and survival trait analyses

INTRODUCTION

Our understanding of the genetic predisposition for age-at-onset (AAO) of Alzheimer's disease (AD) is limited. Here, we sought to identify genes modifying AAO and examined whether any have sex-specific effects.

METHODS

Genome-wide association analysis were performed on imputed genetic data of 9219 AD cases and 10,345 controls from 20 cohorts of the Alzheimer's Disease Genetics Consortium. AAO was modeled from cases directly and as a survival outcome.

RESULTS

We identified 11 genome-wide significant loci (P < 5 × 10-8 ), including six known AD-risk genes and five novel loci, UMAD1, LUZP2, ARFGEF2, DSCAM, and 4q25, affecting AAO of AD. Additionally, 39 suggestive loci showed strong association. Twelve loci showed sex-specific effects on AAO including CD300LG and MLX/TUBG2 for females and MIR4445 for males.

DISCUSSION

Genes that influence AAO of AD are excellent therapeutic targets for delaying onset of AD. Several loci identified include genes with promising functional implications for AD.

Step by step: towards a better understanding of the genetic architecture of Alzheimer's disease

Alzheimer's disease (AD) is considered to have a large genetic component. Our knowledge of this component has progressed over the last 10 years, thanks notably to the advent of genome-wide association studies and the establishment of large consortia that make it possible to analyze hundreds of thousands of cases and controls. The characterization of dozens of chromosomal regions associated with the risk of developing AD and (in some loci) the causal genes responsible for the observed disease signal has confirmed the involvement of major pathophysiological pathways (such as amyloid precursor protein metabolism) and opened up new perspectives (such as the central role of microglia and inflammation). Furthermore, large-scale sequencing projects are starting to reveal the major impact of rare variants - even in genes like APOE - on the AD risk. This increasingly comprehensive knowledge is now being disseminated through translational research; in particular, the development of genetic risk/polygenic risk scores is helping to identify the subpopulations more at risk or less at risk of developing AD. Although it is difficult to assess the efforts still needed to comprehensively characterize the genetic component of AD, several lines of research can be improved or initiated. Ultimately, genetics (in combination with other biomarkers) might help to redefine the boundaries and relationships between various neurodegenerative diseases.

Comprehensive genetic screening of early-onset dementia patients in an Austrian cohort-suggesting new disease-contributing genes

Early-onset dementia (EOD), with symptom onset before age 65, has a strong genetic burden. Due to genetic and clinical overlaps between different types of dementia, whole-exome sequencing (WES) has emerged as an appropriate screening method for diagnostic testing and novel gene-finding approaches. We performed WES and C9orf72 repeat testing in 60 well-defined Austrian EOD patients. Seven patients (12%) carried likely disease-causing variants in monogenic genes, PSEN1, MAPT, APP, and GRN. Five patients (8%) were APOE4 homozygote carriers. Definite and possible risk variants were detected in the genes TREM2, SORL1, ABCA7 and TBK1. In an explorative approach, we cross-checked rare gene variants in our cohort with a curated neurodegeneration candidate gene list and identified DCTN1, MAPK8IP3, LRRK2, VPS13C and BACE1 as promising candidate genes. Conclusively, 12 cases (20%) carried variants relevant to patient counseling, comparable to previously reported studies, and can thus be considered genetically resolved. Reduced penetrance, oligogenic inheritance and not yet identified high-risk genes might explain the high number of unresolved cases. To address this issue, we provide complete genetic and phenotypic information (uploaded to the European Genome-phenome Archive), enabling other researchers to cross-check variants. Thereby, we hope to increase the chance of independently finding the same gene/variant-hit in other well-defined EOD patient cohorts, thus confirming new genetic risk variants or variant combinations.

Alzheimer's Disease: Significant Benefit from the Yeast-Based Models

Alzheimer's disease (AD) is an age-related, multifaceted neurological disorder associated with accumulation of aggregated proteins (amyloid Aβ and hyperphosphorylated tau), loss of synapses and neurons, and alterations in microglia. AD was recognized by the World Health Organization as a global public health priority. The pursuit of a better understanding of AD forced researchers to pay attention to well-defined single-celled yeasts. Yeasts, despite obvious limitations in application to neuroscience, show high preservation of basic biological processes with all eukaryotic organisms and offer great advantages over other disease models due to the simplicity, high growth rates on low-cost substrates, relatively simple genetic manipulations, the large knowledge base and data collections, and availability of an unprecedented amount of genomic and proteomic toolboxes and high-throughput screening techniques, inaccessible to higher organisms. Research reviewed above clearly indicates that yeast models, together with other, more simple eukaryotic models including animal models, C. elegans and Drosophila, significantly contributed to understanding Aβ and tau biology. These models allowed high throughput screening of factors and drugs that interfere with Aβ oligomerization, aggregation and toxicity, and tau hyperphosphorylation. In the future, yeast models will remain relevant, with a focus on creating novel high throughput systems to facilitate the identification of the earliest AD biomarkers among different cellular networks in order to achieve the main goal-to develop new promising therapeutic strategies to treat or prevent the disease.

Alzheimer's disease and related dementias among aging veterans: Examining gene-by-environment interactions with post-traumatic stress disorder and traumatic brain injury

INTRODUCTION

Post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) confer risk for Alzheimer's disease and related dementias (ADRD).

METHODS

This study from the Million Veteran Program (MVP) evaluated the impact of apolipoprotein E (APOE) ε4, PTSD, and TBI on ADRD prevalence in veteran cohorts of European ancestry (EA; n = 11,112 ADRD cases, 170,361 controls) and African ancestry (AA; n = 1443 ADRD cases, 16,191 controls). Additive-scale interactions were estimated using the relative excess risk due to interaction (RERI) statistic.

RESULTS

PTSD, TBI, and APOE ε4 showed strong main-effect associations with ADRD. RERI analysis revealed significant additive APOE ε4 interactions with PTSD and TBI in the EA cohort and TBI in the AA cohort. These additive interactions indicate that ADRD prevalence associated with PTSD and TBI increased with the number of inherited APOE ε4 alleles.

DISCUSSION

PTSD and TBI history will be an important part of interpreting the results of ADRD genetic testing and doing accurate ADRD risk assessment.

APOE ɛ4, but not polygenic Alzheimer's disease risk, is related to longitudinal decrease in hippocampal brain activity in non-demented individuals

The hippocampus is affected early in Alzheimer's disease (AD) and altered hippocampal functioning influences normal cognitive aging. Here, we used task-based functional MRI to assess if the APOE ɛ4 allele or a polygenic risk score (PRS) for AD was linked to longitudinal changes in memory-related hippocampal activation in normal aging (baseline age 50-95, n = 292; n = 182 at 4 years follow-up, subsequently non-demented for at least 2 years). Mixed-models were used to predict level and change in hippocampal activation by APOE ɛ4 status and PRS based on gene variants previously linked to AD at p ≤ 1, p < 0.05, or p < 5e-8 (excluding APOE). APOE ɛ4 and PRS_p<5e-8 significantly predicted AD risk in a larger sample from the same study population (n = 1542), while PRS_p≤1 predicted memory decline. APOE ɛ4 was linked to decreased hippocampal activation over time, with the most prominent effect in the posterior hippocampi, while PRS was unrelated to hippocampal activation at all p-thresholds. These results suggests a link for APOE ɛ4, but not for AD genetics in general, on functional changes of the hippocampi in normal aging.

Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies

The increasing incidence of Alzheimer's disease (AD) has been leading towards a significant growth in socioeconomic challenges. A reliable prediction of AD might be useful to mitigate or at-least slow down its progression for which, identification of the factors affecting the AD and its accurate diagnoses, are vital. In this study, we use Genome-Wide Association Studies (GWAS) dataset which comprises significant genetic markers of complex diseases. The original dataset contains large number of attributes (620901) for which we propose a hybrid feature selection approach based on association test, principal component analysis, and the Boruta algorithm, to identify the most promising predictors of AD. The selected features are then forwarded to a wide and deep neural network models to classify the AD cases and healthy controls. The experimental outcomes indicate that our approach outperformed the existing methods when evaluated on standard dataset, producing an accuracy and f1-score of 99%. The outcomes from this study are impactful particularly, the identified features comprising AD-associated genes and a reliable classification model that might be useful for other chronic diseases.

Molecular insights into the pathogenic impact of vitamin D deficiency in neurological disorders

Neurological disorders are the major cause of disability, leading to a decrease in quality of life by impairing cognitive, sensorimotor, and motor functioning. Several factors have been proposed in the pathogenesis of neurobehavioral changes, including nutritional, environmental, and genetic predisposition. Vitamin D (VD) is an environmental and nutritional factor that is widely distributed in the central nervous system's subcortical grey matter, neurons of the substantia nigra, hippocampus, thalamus, and hypothalamus. It is implicated in the regulation of several brain functions by preserving neuronal structures. It is a hormone rather than a nutritional vitamin that exerts a regulatory role in the pathophysiology of several neurological disorders, including Alzheimer's disease, Parkinson's disease, epilepsy, and multiple sclerosis. A growing body of epidemiological evidence suggests that VD is critical in neuronal development and shows neuroprotective effects by influencing the production and release of neurotrophins, antioxidants, immunomodulatory, regulation of intracellular calcium balance, and direct effect on the growth and differentiation of nerve cells. This review provides up-to-date and comprehensive information on vitamin D deficiency, risk factors, and clinical and preclinical evidence on its relationship with neurological disorders. Furthermore, this review provides mechanistic insight into the implications of vitamin D and its deficiency on the pathogenesis of neurological disorders. Thus, an understanding of the crucial role of vitamin D in the neurobiology of neurodegenerative disorders can assist in the better management of vitamin D-deficient individuals.

Recent Advances in Water-Splitting Electrocatalysts Based on Electrodeposition

Green hydrogen is being considered as a next-generation sustainable energy source. It is created electrochemically by water splitting with renewable electricity such as wind, geothermal, solar, and hydropower. The development of electrocatalysts is crucial for the practical production of green hydrogen in order to achieve highly efficient water-splitting systems. Due to its advantages of being environmentally friendly, economically advantageous, and scalable for practical application, electrodeposition is widely used to prepare electrocatalysts. There are still some restrictions on the ability to create highly effective electrocatalysts using electrodeposition owing to the extremely complicated variables required to deposit uniform and large numbers of catalytic active sites. In this review article, we focus on recent advancements in the field of electrodeposition for water splitting, as well as a number of strategies to address current issues. The highly catalytic electrodeposited catalyst systems, including nanostructured layered double hydroxides (LDHs), single-atom catalysts (SACs), high-entropy alloys (HEAs), and core-shell structures, are intensively discussed. Lastly, we offer solutions to current problems and the potential of electrodeposition in upcoming water-splitting electrocatalysts.

Modern Approaches to the Diagnosis of Cognitive Impairment and Alzheimer's Disease: A Narrative Literature Review

BACKGROUND

The aging of the worlds population leads to an increase in the prevalence of age-related diseases, including cognitive impairment. At the stage of dementia, therapeutic interventions become usually ineffective. Therefore, researchers and clinical practitioners today are looking for methods that allow for early diagnosis of cognitive impairment, including techniques that are based on the use of biological markers.

AIM

The aim of this literature review is to delve into scientific papers that are centered on modern laboratory tests for Alzheimers disease, including tests for biological markers at the early stages of cognitive impairment.

METHODS

The authors have carried out a descriptive review of scientific papers published from 2015 to 2023. Studies that are included in the PubMed and Web of Science electronic databases were analyzed. A descriptive analysis was used to summarized the gleaned information.

RESULTS

Blood and cerebrospinal fluid (CSF) biomarkers, as well as the advantages and disadvantages of their use, are reviewed. The most promising neurotrophic, neuroinflammatory, and genetic markers, including polygenic risk models, are also discussed.

CONCLUSION

The use of biomarkers in clinical practice will contribute to the early diagnosis of cognitive impairment associated with Alzheimers disease. Genetic screening tests can improve the detection threshold of preclinical abnormalities in the absence of obvious symptoms of cognitive decline. The active use of biomarkers in clinical practice, in combination with genetic screening for the early diagnosis of cognitive impairment in Alzheimers disease, can improve the timeliness and effectiveness of medical interventions.

Genetics of Alzheimer's disease: an East Asian perspective

Alzheimer's disease (AD) is an age-related multifactorial neurodegenerative disorder. Advances in genome technology, including next generation sequencing have uncovered complex genetic effects in AD by analyzing both common and rare functional variants. Multiple lines of evidence suggest that the pathogenesis of AD is influenced by multiple genetic components rather than single genetic factor. Previous genetic studies on AD have predominantly included European ancestry cohorts; hence, the non-European population may be underrepresented, potentially leading to reduced diversity in AD genetic research. Additionally, ethnic diversity may result in dissimilar effects of genetic determinants in AD. APOE genotypes are a well-established genetic risk factor in AD, with the East Asian population having a higher risk of AD associated with the APOE ε4 allele. To date, seven genome-wide association studies (GWAS) have been conducted in East Asians, which report a total of 26 AD-associated loci. Several rare variants, including the p.H157Y variant in TREM2, and the p.G186R and p.R274W variants in SHARPIN are associated with risk of AD in East Asians. Extending genetic studies to diverse populations, including East Asians is necessary, which could yield more comprehensive insights into AD, and here we review the recent findings regarding the genetic determinants of AD from an East Asian perspective.

Alzheimer's Disease Genetic Risk, Cognition, and Brain Aging in Midlife

We examined associations of an Alzheimer's disease (AD) Genetic Risk Score (AD-GRS) and midlife cognitive and neuroimaging outcomes in 1,252 middle-aged participants (311 with brain MRI). A higher AD-GRS based on 25 previously identified loci (excluding apolipoprotein E [APOE]) was associated with worse Montreal Cognitive Assessment (-0.14 standard deviation [SD] [95% confidence interval {CI}: -0.26, -0.02]), older machine learning predicted brain age (2.35 years[95%CI: 0.01, 4.69]), and white matter hyperintensity volume (0.35 SD [95% CI: 0.00, 0.71]), but not with a composite cognitive outcome, total brain, or hippocampal volume. APOE ε4 allele was not associated with any outcomes. AD risk genes beyond APOE may contribute to subclinical differences in cognition and brain health in midlife. ANN NEUROL 2023;93:629-634.

Alzheimer's Disease Polygenic Scores Predict Changes in Episodic Memory and Executive Function Across 12 Years in Late Middle Age

OBJECTIVE

Alzheimer's disease (AD) is highly heritable, and AD polygenic risk scores (AD-PRSs) have been derived from genome-wide association studies. However, the nature of genetic influences very early in the disease process is still not well known. Here we tested the hypothesis that an AD-PRSs would be associated with changes in episodic memory and executive function across late midlife in men who were cognitively unimpaired at their baseline midlife assessment..

METHOD

We examined 1168 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively normal (CN) at their first of up to three assessments across 12 years (mean ages 56, 62, and 68). Latent growth models of episodic memory and executive function were based on 6-7 tests/subtests. AD-PRSs were based on Kunkle et al. (Nature Genetics, 51, 414-430, 2019), p < 5×10^-8 threshold.

RESULTS

AD-PRSs were correlated with linear slopes of change for both cognitive abilities. Men with higher AD-PRSs had steeper declines in both memory (r = -.19, 95% CI [-.35, -.03]) and executive functioning (r = -.27, 95% CI [-.49, -.05]). Associations appeared driven by a combination of APOE and non-APOE genetic influences.

CONCLUSIONS

Memory is most characteristically impaired in AD, but executive functions are one of the first cognitive abilities to decline in midlife in normal aging. This study is among the first to demonstrate that this early decline also relates to AD genetic influences, even in men CN at baseline.

Genetic Risk for Alzheimer Disease and Plasma Tau Are Associated With Accelerated Parietal Cortex Thickness Change in Middle-Aged Adults

Background and Objectives

Neuroimaging and biomarker studies in Alzheimer disease (AD) have shown well-characterized patterns of cortical thinning and altered biomarker concentrations of tau and β-amyloid (Aβ). However, earlier identification of AD has great potential to advance clinical care and determine candidates for drug trials. The extent to which AD risk markers relate to cortical thinning patterns in midlife is unknown. The first objective of this study was to examine cortical thickness change associated with genetic risk for AD among middle-aged military veterans. The second objective was to determine the relationship between plasma tau and Aβ and change in brain cortical thickness among veterans stratified by genetic risk for AD.

Methods

Participants consisted of post-9/11 veterans (N = 155) who were consecutively enrolled in the Translational Research Center for TBI and Stress Disorders prospective longitudinal cohort and were assessed for mild traumatic brain injury (TBI) and posttraumatic disorder (PTSD). Genome-wide polygenic risk scores (PRSs) for AD were calculated using summary results from the International Genomics of Alzheimer's Disease Project. T-tau and Aβ40 and Aβ42 plasma assays were run using Simoa technology. Whole-brain MRI cortical thickness change estimates were obtained using the longitudinal stream of FreeSurfer. Follow-up moderation analyses examined the AD PRS × plasma interaction on change in cortical thickness in AD-vulnerable regions.

Results

Higher AD PRS, signifying greater genetic risk for AD, was associated with accelerated cortical thickness change in a right hemisphere inferior parietal cortex cluster that included the supramarginal gyrus, angular gyrus, and intraparietal sulcus. Higher tau, but not Aβ42/40 ratio, was associated with greater cortical thickness change among those with higher AD PRS. Mild TBI and PTSD were not associated with cortical thickness change.

Discussion

Plasma tau, particularly when combined with genetic stratification for AD risk, can be a useful indicator of brain change in midlife. Accelerated inferior parietal cortex changes in midlife may be an important factor to consider as a marker of AD-related brain alterations.

Single-cell-led drug repurposing for Alzheimer's disease

Alzheimer's disease is the most common form of dementia. Notwithstanding the huge investments in drug development, only one disease-modifying treatment has been recently approved. Here we present a single-cell-led systems biology pipeline for the identification of drug repurposing candidates. Using single-cell RNA sequencing data of brain tissues from patients with Alzheimer's disease, genome-wide association study results, and multiple gene annotation resources, we built a multi-cellular Alzheimer's disease molecular network that we leveraged for gaining cell-specific insights into Alzheimer's disease pathophysiology and for the identification of drug repurposing candidates. Our computational approach pointed out 54 candidate drugs, mainly targeting MAPK and IGF1R signaling pathways, which could be further evaluated for their potential as Alzheimer's disease therapy.

PICALM Variation Moderates the Relationships of APOE ɛ4 with Alzheimer's Disease Cerebrospinal Biomarkers and Memory Function Among Non-Demented Population

BACKGROUND

APOE ɛ4 and PICALM are established genes associated with risk of late-onset Alzheimer's disease (AD). Previous study indicated interaction of PICALM with APOE ɛ4 in AD patients.

OBJECTIVE

To explore whether PICALM variation could moderate the influences of APOE ɛ4 on AD pathology biomarkers and cognition in pre-dementia stage.

METHODS

A total of 1,034 non-demented participants (mean age 74 years, 56% females, 40% APOE ɛ4 carriers) were genotyped for PICALM rs3851179 and APOE ɛ4 at baseline and were followed for influences on changes of cognition and cerebrospinal fluid (CSF) AD markers in six years. The interaction effects were examined via regression models adjusting for age, gender, education, and cognitive diagnosis.

RESULTS

The interaction term of rs3851179×APOE ɛ4 accounted for a significant amount of variance in baseline general cognition (p = 0.039) and memory function (p = 0.002). The relationships of APOE ɛ4 with trajectory of CSF Aβ42 (p = 0.007), CSF P-tau181 (p = 0.003), CSF T-tau (p = 0.001), and memory function (p = 0.017) were also moderated by rs3851179 variation.

CONCLUSIONS

APOE ɛ4 carriers experienced slower clinical and pathological progression when they had more protective A alleles of PICALM rs3851179. These findings firstly revealed the gene-gene interactive effects of PICALM with APOE ɛ4 in pre-dementia stage.

Genotypic Effects of the TOMM40'523 Variant and APOE on Longitudinal Cognitive Change over 4 Years: The TOMMORROW Study

BACKGROUND

The 523 poly-T length polymorphism (rs10524523) in TOMM40 has been reported to influence longitudinal cognitive test performance within APOE ε3/3 carriers. The results from prior studies are inconsistent. It is also unclear whether specific APOE and TOMM40 genotypes contribute to heterogeneity in longitudinal cognitive performance during the preclinical stages of AD.

OBJECTIVES

To determine the effects of these genes on longitudinal cognitive change in early preclinical stages of AD, we used the clinical trial data from the recently concluded TOMMORROW study to examine the effects of APOE and TOMM40 genotypes on neuropsychological test performance.

DESIGN

A phase 3, double-blind, placebo-controlled, randomized clinical trial.

SETTING

Academic affiliated and private research clinics in Australia, Germany, Switzerland, the UK, and the USA.

PARTICIPANTS

Cognitively normal older adults aged 65 to 83.

INTERVENTION

Pioglitazone tablet.

MEASUREMENTS

Participants from the TOMMORROW trial were stratified based on APOE genotype (APOE ε3/3, APOE ε3/4, APOE ε4/4). APOE ε3/3 carriers were further stratified by TOMM40'523 genotype. The final analysis dataset consists of 1,330 APOE ε3/3 carriers and 7,001 visits. Linear mixed models were used to compare the rates of decline in cognition across APOE groups and the APOE ε3/3 carriers with different TOMM40'523 genotypes.

RESULTS

APOE ε3/4 and APOE ε4/4 genotypes compared with the APOE ε3/3 genotype were associated with worse performance on measures of global cognition, episodic memory, and expressive language. Further, over the four years of observation, the APOE ε3/3 carriers with the TOMM40'523-S/S genotype showed better global cognition and accelerated rates of cognitive decline on tests of global cognition, executive function, and attentional processing compared to APOE ε3/3 carriers with TOMM40'523-S/VL and VL/VL genotypes and compared to the APOE ε3/4 and APOE ε4/4 carriers.

CONCLUSIONS

We suggest that both APOE and TOMM40 genotypes may independently contribute to cognitive heterogeneity in the pre-MCI stages of AD. Controlling for this genetic variability will be important in clinical trials designed to slow the rate of cognitive decline and/or prevent symptom onset in preclinical AD.

Insights from multi-omics integration in complex disease primary tissues

Genome-wide association studies (GWAS) have provided insights into the genetic basis of complex diseases. In the next step, integrative multi-omics approaches can characterize molecular profiles in relevant primary tissues to reveal the mechanisms that underlie disease development. Here, we highlight recent progress in four examples of complex diseases generated by integrative studies: type 2 diabetes (T2D), osteoarthritis, Alzheimer's disease (AD), and systemic lupus erythematosus (SLE). High-resolution methodologies such as single-cell and spatial omics techniques will become even more important in the future. Furthermore, we emphasize the urgent need to include as yet understudied cell types and increase the diversity of studied populations.

Inflammation context in Alzheimer's disease, a relationship intricate to define

Alzheimer's disease (AD), the most common form of dementia, is characterized by the accumulation of amyloid β (Aβ) and hyperphosphorylated tau protein aggregates. Importantly, Aβ and tau species are able to activate astrocytes and microglia, which release several proinflammatory cytokines, such as tumor necrosis factor α (TNF-α) and interleukin 1β (IL-1β), together with reactive oxygen (ROS) and nitrogen species (RNS), triggering neuroinflammation. However, this inflammatory response has a dual function: it can play a protective role by increasing Aβ degradation and clearance, but it can also contribute to Aβ and tau overproduction and induce neurodegeneration and synaptic loss. Due to the significant role of inflammation in the pathogenesis of AD, several inflammatory mediators have been proposed as AD markers, such as TNF-α, IL-1β, Iba-1, GFAP, NF-κB, TLR2, and MHCII. Importantly, the use of anti-inflammatory drugs such as NSAIDs has emerged as a potential treatment against AD. Moreover, diseases related to systemic or local inflammation, including infections, cerebrovascular accidents, and obesity, have been proposed as risk factors for the development of AD. In the following review, we focus on key inflammatory processes associated with AD pathogenesis.

Mitochondrial Ca2+ Signaling and Bioenergetics in Alzheimer's Disease

Alzheimer's disease (AD) is a hereditary and sporadic neurodegenerative illness defined by the gradual and cumulative loss of neurons in specific brain areas. The processes that cause AD are still under investigation and there are no available therapies to halt it. Current progress puts at the forefront the "calcium (Ca2+) hypothesis" as a key AD pathogenic pathway, impacting neuronal, astrocyte and microglial function. In this review, we focused on mitochondrial Ca2+ alterations in AD, their causes and bioenergetic consequences in neuronal and glial cells, summarizing the possible mechanisms linking detrimental mitochondrial Ca2+ signals to neuronal death in different experimental AD models.

Sticker-and-spacer model for amyloid beta condensation and fibrillation

A major pathogenic hallmark of Alzheimer's disease is the presence of neurotoxic plaques composed of amyloid beta (Aβ) peptides in patients' brains. The pathway of plaque formation remains elusive, though some clues appear to lie in the dominant presence of Aβ_{1 − 42} in these plaques despite Aβ₁₋₄₀ making up approximately 90% of the Aβ pool. We hypothesize that this asymmetry is driven by the hydrophobicity of the two extra amino acids that are incorporated in Aβ₁₋₄₂. To investigate this hypothesis at the level of single molecules, we have developed a molecular “sticker-and-spacer lattice model” of unfolded Aβ. The model protein has a single sticker that may reversibly dimerise and elongate into semi-flexible linear chains. The growth is hampered by excluded-volume interactions that are encoded by the hydrophilic spacers but are rendered cooperative by the attractive interactions of hydrophobic spacers. For sufficiently strong hydrophobicity, the chains undergo liquid-liquid phase-separation (LLPS) into condensates that facilitate the nucleation of fibers. We find that a small fraction of Aβ₁₋₄₀ in a mixture of Aβ₁₋₄₀ and Aβ₁₋₄₂ shifts the critical concentration for LLPS to lower values. This study provides theoretical support for the hypothesis that LLPS condensates act as a precursor for aggregation and provides an explanation for the Aβ₁₋₄₂-enrichment of aggregates in terms of hydrophobic interactions.

APOE in the bullseye of neurodegenerative diseases: impact of the APOE genotype in Alzheimer’s disease pathology and brain diseases

ApoE is the major lipid and cholesterol carrier in the CNS. There are three major human polymorphisms, apoE2, apoE3, and apoE4, and the genetic expression of APOE4 is one of the most influential risk factors for the development of late-onset Alzheimer's disease (AD). Neuroinflammation has become the third hallmark of AD, together with Amyloid-β plaques and neurofibrillary tangles of hyperphosphorylated aggregated tau protein. This review aims to broadly and extensively describe the differential aspects concerning apoE. Starting from the evolution of apoE to how APOE's single-nucleotide polymorphisms affect its structure, function, and involvement during health and disease. This review reflects on how APOE's polymorphisms impact critical aspects of AD pathology, such as the neuroinflammatory response, particularly the effect of APOE on astrocytic and microglial function and microglial dynamics, synaptic function, amyloid-β load, tau pathology, autophagy, and cell–cell communication. We discuss influential factors affecting AD pathology combined with the APOE genotype, such as sex, age, diet, physical exercise, current therapies and clinical trials in the AD field. The impact of the APOE genotype in other neurodegenerative diseases characterized by overt inflammation, e.g., alpha- synucleinopathies and Parkinson's disease, traumatic brain injury, stroke, amyotrophic lateral sclerosis, and multiple sclerosis, is also addressed. Therefore, this review gathers the most relevant findings related to the APOE genotype up to date and its implications on AD and CNS pathologies to provide a deeper understanding of the knowledge in the APOE field.

Modified Taq polymerase for allele-specific ultra-sensitive detection of genetic variants

Allele-specific polymerase chain reaction (AS-PCR) has been used as a simple, cost-effective method for genotyping and gene mapping in research and clinical settings. AS-PCR permits the detection of single nucleotide variants (SNVs) and indels owing to the selective extension of a perfectly matched primer (to the template DNA) over a mismatched primer. Thus, the mismatch discrimination power of the DNA polymerase is critical. Unfortunately, currently available polymerases often amplify some mismatched primer-template complexes as well as matched ones, obscuring allele-specific detection. To increase mismatch discrimination, we have generated mutations in the Thermus aquaticus (Taq) DNA polymerase, selected the most efficient variant, and evaluated its performance in SNP and cancer mutation genotyping. In addition, the primer design and reaction buffer conditions were optimized for allele-specific amplification. Our highly selective AS-PCR, which is based on an allele-discriminating priming system (ADPS) that leverages a Taq polymerase variant with optimized primers and reaction buffer, can detect mutations with mutant allele frequency as low as 0.01% in genomic DNA and 0.0001% in plasmid DNA. This method serves as a simple, fast, cost-effective, and ultra-sensitive way to detect SNVs and indels with low abundance.

Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders

To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders.

Polygenic resilience scores capture protective genetic effects for Alzheimer's disease

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Genetic Risk, Midlife Life's Simple 7, and Incident Dementia in the Atherosclerosis Risk in Communities Study

BACKGROUND AND OBJECTIVES

Higher scores in Life's Simple 7 (LS7), a metric for cardiovascular and brain health, have been associated with lower risk of dementia. It is uncertain whether this association holds among those with high genetic risk of dementia. Our objective is to evaluate the extent that LS7 may offset dementia risk across the range of genetic risk.

METHODS

Participants in the Atherosclerosis Risk in Communities (ARIC) Study were followed from 1987-1989 to 2019. We derived midlife LS7 scores and generated genetic risk scores (GRS) using genome-wide summary statistics of Alzheimer disease, which have been used to study the genetic risk for dementia. Incident dementia was ascertained based on the criteria of the National Institute on Aging-Alzheimer's Association workgroups and Diagnostic and Statistical Manual of Mental Disorders. The associations of the GRS and LS7 with incident dementia were evaluated using Cox regression.

RESULTS

This study included 8,823 European American (EA) and 2,738 African American (AA) participants (mean age at baseline 54 years). We observed 1,603 cases of dementia among EA participants and 631 among AA participants (median follow-up 26.2 years). Higher GRS were associated with higher risk of dementia (EA, hazard ratio [HR] per SD 1.44, 95% CI 1.37, 1.51; AA, HR 1.26, 95% CI 1.16, 1.36). Among EA participants, higher LS7 scores were consistently associated with lower risk of dementia across quintiles of GRS, including the highest quintile (HR per point 0.91, 95% CI 0.87, 0.96). Among AA participants, the associations between LS7 and incident dementia within stratum of GRS had the same direction as among EA participants, although wide CIs and smaller sample sizes limited reliable inferences.

DISCUSSION

Across strata of GRS, higher midlife LS7 scores were associated with lower risk of dementia. Larger sample sizes from diverse populations are needed to obtain more reliable estimates of the effects of modifiable health factors on dementia risk within genetic risk strata in each ancestry group.

Assessment of a polygenic hazard score for the onset of pre-clinical Alzheimer's disease

Abstract

Background

With a growing number of loci associated with late-onset (sporadic) Alzheimer’s disease (AD), the polygenic contribution to AD is now well established. The development of polygenic risk score approaches have shown promising results for identifying individuals at higher risk of developing AD, thereby facilitating the development of preventative and therapeutic strategies. A polygenic hazard score (PHS) has been proposed to quantify age-specific genetic risk for AD. In this study, we assessed the predictive power and transferability of this PHS in an independent cohort, to support its clinical utility.

Results

Using genotype and imaging data from 780 individuals enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, we investigated associations between the PHS and several AD-related traits, including 1) cross-sectional Aβ-amyloid (Aβ) deposition, 2) longitudinal brain atrophy, 3) longitudinal cognitive decline, 4) age of onset. Except in the cognitive domain, we obtained results that were consistent with previously published findings. The PHS was associated with increased Aβ burden, faster regional brain atrophy and an earlier age of onset.

Conclusion

Overall, the results support the predictive power of a PHS, however, with only marginal improvement compared to apolipoprotein E alone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08617-2.

Polygenic risk of Alzheimer's disease in the Faroe Islands

INTRODUCTION

The Faroe Islands are a geographically isolated population in the North Atlantic with a similar prevalence Alzheimer's disease (AD) and all cause dementia as other European nations. However, the genetic risk underlying Alzheimer's disease and other dementia susceptibility has yet to be elucidated.

METHODS

Forty-nine single nucleotide polymorphisms (SNPs) were genotyped in 174 patients with AD and other dementias and 159 healthy controls. Single variant and polygenic risk score (PRS) associations, with/without APOE variability, were assessed by logistic regression. Performance was examined using receiver operating characteristics 'area under the curve' analysis (ROC AUC).

RESULTS

APOE rs429358 was associated with AD in the Faroese cohort after correction for multiple testing (OR=6.32, CI[3.98-10.05], p=6.31e^-15 ), with suggestive evidence for three other variants: NECTIN2 rs41289512 (OR 2.05, CI[1.20-3.51], p=0.01), HLA-DRB1 rs6931277 (OR 0.67, CI[0.48-0.94], p=0.02), and APOE rs7412 [ε2] (OR 0.28, CI[0.11-0.73], p=0.01). PRS were associated with AD with or without the inclusion of APOE (PRS^+APOE OR=4.5. CI[2.90-5.85, p=4.56e-¹⁵ and PRS^-APOE OR=1.53, CI[1.21-1.98], p=6.82e^-4 ). AD ROC AUC analyses demonstrated a PRS^+APOE AUC=80.3% and PRS^-APOE AUC=63.4%. However, PRS^+APOE was also significantly associated with all cause dementia (OR=3.39, CI[2.51-4.71], p= 2.50e^-14 ) with an AUC=76.9%, i.e. all cause dementia did show similar results albeit less significant.

DISCUSSION

In the Faroe Islands, SNP analyses highlighted APOE and immunogenomic variability in AD and dementia risk. PRS^+APOE , based on 25 SNPs/loci, had excellent sensitivity and specificity for Alzheimer's disease with AUC of 80.3%. High PRS were also associated with an earlier onset of late-onset AD.