Nectin-2 in general and in the brain

Comparative analysis of machine learning algorithms for Alzheimer's disease classification using EEG signals and genetic information

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairments, and behavioral changes. The presence of abnormal beta-amyloid plaques and tau protein tangles in the brain is known to be associated with AD. However, current limitations of imaging technology hinder the direct detection of these substances. Consequently, researchers are exploring alternative approaches, such as indirect assessments involving monitoring brain signals, cognitive decline levels, and blood biomarkers. Recent studies have highlighted the potential of integrating genetic information into these approaches to enhance early detection and diagnosis, offering a more comprehensive understanding of AD pathology beyond the constraints of existing imaging methods. Our study utilized electroencephalography (EEG) signals, genotypes, and polygenic risk scores (PRSs) as features for machine learning models. We compared the performance of gradient boosting (XGB), random forest (RF), and support vector machine (SVM) to determine the optimal model. Statistical analysis revealed significant correlations between EEG signals and clinical manifestations, demonstrating the ability to distinguish the complexity of AD from other diseases by using genetic information. By integrating EEG with genetic data in an SVM model, we achieved exceptional classification performance, with an accuracy of 0.920 and an area under the curve of 0.916. This study presents a novel approach of utilizing real-time EEG data and genetic background information for multimodal machine learning. The experimental results validate the effectiveness of this concept, providing deeper insights into the actual condition of patients with AD and overcoming the limitations associated with single-oriented data.

N6-methyladenosine-associated genetic variants in NECTIN2 and HPCAL1 are risk factors for abdominal aortic aneurysm

Although N6-methyladenosine (m6A) modification has been implicated in the pathogenesis of abdominal aortic aneurysm (AAA), the relationship between m6A-associated single nucleotide polymorphisms (m6A-SNPs) and AAA remains unknown. This study used integrative multi-omics analysis and clinical validation approaches to systematically identify potential m6A-SNPs connected with AAA risk. We found that rs6859 and rs10198139 could modulate the expression of local genes, NECTIN2 and HPCAL1, respectively, which exhibited upregulation in AAA tissues, and their risk variants were significantly correlated with an increased susceptibility to AAA. Incorporating rs6859 and rs10198139 improved the efficiency of AAA risk prediction compared to the model considering only conventional risk factors. Additionally, these two SNPs were predicted to be located within the regulatory sequences, and rs6859 showed a substantial impact on m6A modification levels. Our findings suggest that m6A-SNPs rs6859 and rs10198139 confer an elevated risk of AAA, possibly by promoting local gene expression through an m6A-mediated manner.

The SNP rs6859 in NECTIN2 gene is associated with underlying heterogeneous trajectories of cognitive changes in older adults

BACKGROUND

Functional decline associated with dementia, including in Alzheimer's disease (AD), is not uniform across individuals, and respective heterogeneity is not yet fully explained. Such heterogeneity may in part be related to genetic variability among individuals. In this study, we investigated whether the SNP rs6859 in nectin cell adhesion molecule 2 (NECTIN2) gene (a major risk factor for AD) influences trajectories of cognitive decline in older participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

METHODS

We retrospectively analyzed records on 1310 participants from the ADNI database for the multivariate analysis. We used longitudinal measures of Mini-Mental State Examination (MMSE) scores in participants, who were cognitively normal, or having AD, or other cognitive deficits to investigate the trajectories of cognitive changes. Multiple linear regression, linear mixed models and latent class analyses were conducted to investigate the association of the SNP rs6859 with MMSE.

RESULTS

The regression coefficient per one allele dose of the SNP rs6859 was independently associated with MMSE in both cross-sectional (-2.23, p < 0.01) and linear mixed models (-2.26, p < 0.01) analyses. The latent class model with three distinct subgroups (class 1: stable and gradual decline, class 2: intermediate and late decline, and class 3: lowest and irregular) performed best in the posterior classification, 42.67% (n = 559), 21.45% (n = 281), 35.88% (n = 470) were classified as class 1, class 2, and class 3. In the heterogeneous linear mixed model, the regression coefficient per one allele dose of rs6859 - A risk allele was significantly associated with MMSE class 1 and class 2 memberships and related decline; Class 1 (-2.28, 95% CI: -4.05, -0.50, p < 0.05), Class 2 (-5.56, 95% CI: -9.61, -1.51, p < 0.01) and Class 3 (-0.37, 95% CI: -1.62, 0.87, p = 0.55).

CONCLUSIONS

This study found statistical evidence supporting the classification of three latent subclass groups representing complex MMSE trajectories in the ADNI cohort. The SNP rs6859 can be suggested as a candidate genetic predictor of variation in modeling MMSE trajectory, as well as for identifying latent classes with higher baseline MMSE. Functional studies may help further elucidate this relationship.

TDP-43 chronic deficiency leads to dysregulation of transposable elements and gene expression by affecting R-loop and 5hmC crosstalk

TDP-43 is an RNA/DNA-binding protein that forms aggregates in various brain disorders. TDP-43 engages in many aspects of RNA metabolism, but its molecular roles in regulating genes and transposable elements (TEs) have not been extensively explored. Chronic TDP-43 knockdown impairs cell proliferation and cellular responses to DNA damage. At the molecular level, TDP-43 chronic deficiency affects gene expression either locally or distally by concomitantly altering the crosstalk between R-loops and 5-hydroxymethylcytosine (5hmC) in gene bodies and long-range enhancer/promoter interactions. Furthermore, TDP-43 knockdown induces substantial disease-relevant TE activation by influencing their R-loop and 5hmC homeostasis in a locus-specific manner. Together, our findings highlight the genomic roles of TDP-43 in modulating R-loop-5hmC coordination in coding genes, distal regulatory elements, and TEs, presenting a general and broad molecular mechanism underlying the contributions of proteinopathies to the etiology of neurodegenerative disorders.

Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer's disease

Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer's disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3,350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16×10-19; rs142232675 p.D87N, P=2.71×10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86×10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we demonstrate that overexpression and knock-down of TGFBR2, but not RBMS3, leads to significant changes of sTREM2. The last novel locus is located on the APOE region (rs11666329, P=2.52×10-8), but we demonstrated that this signal was independent of APOE genotype. This signal colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. Overexpression of NECTIN2 led to an increase of sTREM2 supporting the genetic findings. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.

Identification of circulating proteins associated with general cognitive function among middle-aged and older adults

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer's disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets.

Cell adhesion molecules in the pathogenesis of the schizophrenia

The causes of schizophrenia remain obscure and complex to identify. Alterations in dopaminergic and serotonergic neurotransmission are, to date, the primary pharmacological targets in treatment. Underlying abnormalities in neural networks have been identified as cell adhesion molecules (CAMs) involved in synaptic remodeling and interplay between neurons-neurons and neurons-glial cells. Among the CAMs, several families have been identified, such as integrins, selectins, cadherins, immunoglobulins, nectins, and the neuroligin-neurexin complex. In this paper, cell adhesion molecules involved in the pathogenesis of schizophrenia will be described.

Heterogeneity of perivascular astrocyte endfeet depending on vascular regions in the mouse brain

Astrocytes interact with not only synapses but also brain blood vessels through perivascular astrocyte endfeet (PV-AEF) to form the neurovascular unit (NVU). However, PV-AEF components have not been fully identified. Here, we biochemically isolated blood vessels from mouse brain homogenates and purified PV-AEF. The purified PV-AEF were observed in different sizes, similar to PV-AEF on brain blood vessels. Mass spectrometry analysis identified 9,762 proteins in the purified PV-AEF, including cell adhesion molecules, nectin-2δ, Kirrel2, and podoplanin. Immunofluorescence microscopic analysis revealed that nectin-2δ and podoplanin were concentrated mainly in arteries/arterioles and veins/venules of the mouse brain, whereas Kirrel2 was mainly in arteries/arterioles. Nectin-2α/δ, Kirrel2, and podoplanin were preferentially observed in large sizes of the purified PV-AEF. Furthermore, Kirrel2 potentially has cell adhesion activity of cultured astrocytes. Collectively, these results indicate that PV-AEF have heterogeneity in sizes and molecular components, implying different roles of PV-AEF in NVU function depending on vascular regions.

Amyloid-Beta Peptides Trigger Premature Functional and Gene Expression Alterations in Human-Induced Neurons

Alzheimer's disease (AD) is the most prevalent cause of dementia in the elderly, characterized by the presence of amyloid-beta (Aβ) plaques, neurofibrillary tangles, neuroinflammation, synapse loss and neurodegeneration in the brain. The amyloid cascade hypothesis postulates that deposition of Aβ peptides is the causative agent of AD pathology, but we still lack comprehensive understanding of the molecular mechanisms connecting Aβ peptides to neuronal dysfunctions in AD. In this work, we investigate the early effects of Aβ peptide accumulation on the functional properties and gene expression profiles of human-induced neurons (hiNs). We show that hiNs acutely exposed to low concentrations of both cell-secreted Aβ peptides or synthetic Aβ1-42 exhibit alterations in the frequency of calcium transients suggestive of increased neuronal excitability. Using single-cell RNA sequencing, we also show that cell-secreted Aβ up-regulates the expression of several synapse-related genes and down-regulates the expression of genes associated with metabolic stress mainly in glutamatergic neurons and, to a lesser degree, in GABAergic neurons and astrocytes. These neuronal alterations correlate with activation of the SEMA5, EPHA and NECTIN signaling pathways, which are important regulators of synaptic plasticity. Altogether, our findings indicate that slight elevations in Aβ concentrations are sufficient to elicit transcriptional changes in human neurons, which can contribute to early alterations in neural network activity.

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) depends on environmental and heritable factors, with remarkable differences evident between individuals at the molecular level. Here we present a transcriptomic survey of AD using spatial transcriptomics (ST) and single-nucleus RNA-seq in cortical samples from early-stage AD, late-stage AD, and AD in Down Syndrome (AD in DS) donors. Studying AD in DS provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. Our analysis revealed spatial and cell-type specific changes in disease, with broad similarities in these changes between sAD and AD in DS. We performed additional ST experiments in a disease timecourse of 5xFAD and wildtype mice to facilitate cross-species comparisons. Finally, amyloid plaque and fibril imaging in the same tissue samples used for ST enabled us to directly link changes in gene expression with accumulation and spread of pathology.