Male-specific epistasis between WWC1 and TLN2 genes is associated with Alzheimer's disease

Talin mechanotransduction in disease

Talin protein (Talin 1/2) is a mechanosensitive cytoskeleton protein. The unique structure of the Talin plays a vital role in transmitting mechanical forces. Talin proteins connect the extracellular matrix to the cytoskeleton by linking to integrins and actin, thereby mediating the conversion of mechanical signals into biochemical signals and influencing disease progression as potential diagnostic indicators, therapeutic targets, and prognostic indicators of various diseases. Most studies in recent years have confirmed that mechanical forces also have a crucial role in the development of disease, and Talin has been found to play a role in several diseases. Still, more studies need to be done on how Talin is involved in mechanical signaling in disease. This review focuses on the mechanical signaling of Talin in disease, aiming to summarize the mechanisms by which Talin plays a role in disease and to provide references for further studies.

Identification of Tau Toxicity Modifiers in the Drosophila Eye

Drosophila is a powerful model to study human diseases thanks to its genetic tools and ease of screening. Human genes can be expressed in targeted organs and their toxicity assessed on easily scorable external phenotypes that can be used as readouts to perform genetic screens of toxicity modifiers. In this chapter, I describe how to express human Tau protein in the Drosophila eye, assess protein expression by Western blot, assess Tau toxicity by quantifying the size of the Tau-induced rough eye, and perform a genetic screen of modifiers of Tau toxicity in the Drosophila eye.

Characterization of genomic regions escaping epigenetic reprogramming in sheep

The mammalian genome undergoes two global epigenetic reprogramming events during the establishment of primordial germ cells and in the pre-implantation embryo after fertilization. These events involve the erasure and re-establishment of DNA methylation marks. However, imprinted genes and transposable elements (TEs) maintain their DNA methylation signatures to ensure normal embryonic development and genome stability. Despite extensive research in mice and humans, there is limited knowledge regarding environmentally induced epigenetic marks that escape epigenetic reprogramming in other species. Therefore, the objective of this study was to examine the characteristics and locations of genomic regions that evade epigenetic reprogramming in sheep, as well as to explore the biological functions of the genes within these regions. In a previous study, we identified 107 transgenerationally inherited differentially methylated cytosines (DMCs) in the F1 and F2 generations in response to a paternal methionine-supplemented diet. These DMCs were found in TEs, non-repetitive regions, and imprinted and non-imprinted genes. Our findings suggest that genomic regions, rather than TEs and imprinted genes, have the propensity to escape reprogramming and serve as potential candidates for transgenerational epigenetic inheritance. Notably, 34 transgenerational methylated genes influenced by paternal nutrition escaped reprogramming, impacting growth, development, male fertility, cardiac disorders, and neurodevelopment. Intriguingly, among these genes, 21 have been associated with neural development and brain disorders, such as autism, schizophrenia, bipolar disease, and intellectual disability. This suggests a potential genetic overlap between brain and infertility disorders. Overall, our study supports the concept of transgenerational epigenetic inheritance of environmentally induced marks in mammals.

Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies

Epistasis, commonly defined as the interaction between genetic loci, is known to play an important role in the phenotypic variation of complex traits. As a result, many statistical methods have been developed to identify genetic variants that are involved in epistasis, and nearly all of these approaches carry out this task by focusing on analyzing one trait at a time. Previous studies have shown that jointly modeling multiple phenotypes can often dramatically increase statistical power for association mapping. In this study, we present the "multivariate MArginal ePIstasis Test" (mvMAPIT)-a multioutcome generalization of a recently proposed epistatic detection method which seeks to detect marginal epistasis or the combined pairwise interaction effects between a given variant and all other variants. By searching for marginal epistatic effects, one can identify genetic variants that are involved in epistasis without the need to identify the exact partners with which the variants interact-thus, potentially alleviating much of the statistical and computational burden associated with conventional explicit search-based methods. Our proposed mvMAPIT builds upon this strategy by taking advantage of correlation structure between traits to improve the identification of variants involved in epistasis. We formulate mvMAPIT as a multivariate linear mixed model and develop a multitrait variance component estimation algorithm for efficient parameter inference and P-value computation. Together with reasonable model approximations, our proposed approach is scalable to moderately sized genome-wide association studies. With simulations, we illustrate the benefits of mvMAPIT over univariate (or single-trait) epistatic mapping strategies. We also apply mvMAPIT framework to protein sequence data from two broadly neutralizing anti-influenza antibodies and approximately 2,000 heterogeneous stock of mice from the Wellcome Trust Centre for Human Genetics. The mvMAPIT R package can be downloaded at https://github.com/lcrawlab/mvMAPIT.

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.

The Construction of a Multidomain Risk Model of Alzheimer's Disease and Related Dementias

BACKGROUND

Alzheimer's disease (AD) and related dementia (ADRD) risk is affected by multiple dependent risk factors; however, there is no consensus about their relative impact in the development of these disorders.

OBJECTIVE

To rank the effects of potentially dependent risk factors and identify an optimal parsimonious set of measures for predicting AD/ADRD risk from a larger pool of potentially correlated predictors.

METHODS

We used diagnosis record, survey, and genetic data from the Health and Retirement Study to assess the relative predictive strength of AD/ADRD risk factors spanning several domains: comorbidities, demographics/socioeconomics, health-related behavior, genetics, and environmental exposure. A modified stepwise-AIC-best-subset blanket algorithm was then used to select an optimal set of predictors.

RESULTS

The final predictive model was reduced to 10 features for AD and 19 for ADRD; concordance statistics were about 0.85 for one-year and 0.70 for ten-year follow-up. Depression, arterial hypertension, traumatic brain injury, cerebrovascular diseases, and the APOE4 proxy SNP rs769449 had the strongest individual associations with AD/ADRD risk. AD/ADRD risk-related co-morbidities provide predictive power on par with key genetic vulnerabilities.

CONCLUSION

Results confirm the consensus that circulatory diseases are the main comorbidities associated with AD/ADRD risk and show that clinical diagnosis records outperform comparable self-reported measures in predicting AD/ADRD risk. Model construction algorithms combined with modern data allows researchers to conserve power (especially in the study of disparities where disadvantaged groups are often grossly underrepresented) while accounting for a high proportion of AD/ADRD-risk-related population heterogeneity stemming from multiple domains.

Genome-Wide Association Study of Parasite Resistance to Gastrointestinal Nematodes in Corriedale Sheep

Selection of genetically resistant animals is one alternative to reduce the negative impact of gastrointestinal nematodes (GIN) on sheep production. The aim of this study was to identify genomic regions associated with GIN resistance in Corriedale sheep by single-step genome-wide association studies (ssGWAS) using 170, 507 and 50K single nucleotide polymorphisms (SNPs). Analysis included 19,547 lambs with faecal egg counts (FEC) records, a pedigree file of 40,056 animals and 454, 711 and 383 genotypes from 170, 507 and 50K SNPs, respectively. Genomic estimated breeding values (GEBV) were obtained with single-step genomic BLUP methodology (ssGBLUP), using a univariate animal model, which included contemporary group, type of birth and age of dam as class fixed effects and age at FEC recording as covariate. The SNP effects as wells as p-values were estimated with POSTGSF90 program. Significance level was defined by a chromosome-wise False Discovery Rate of 5%. Significant genomic regions were identified in chromosomes 1, 3, 12 and 19 with the 170 SNP set, in chromosomes 7, 12 and 24 using the 507 SNP chip and only in chromosome 7 with the 50K SNP chip. Candidate genes located in these regions, using Oar_v4.0 as reference genome, were TIMP3, TLR5, LEPR and TLR9 (170 SNPs), SYNDIG1L and MGRN1 (507 SNP chip) and INO80, TLN2, TSHR and EIF2AK4 (50K SNP chip). These results validate genomic regions associated with FEC previously identified in Corriedale and other breeds and report new candidate regions for further investigation.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Exploring Sex-Related Differences in Microglia May Be a Game-Changer in Precision Medicine

One area of microglial biology that has been relatively neglected until recently is sex differences and this is in spite of the fact that sex is a risk factor in several diseases that are characterized by neuroinflammation and, by extension, microglial activation. Why these sex differences exist is not known but the panoply of differences extend to microglial number, genotype and phenotype. Significantly, several of these sex-related differences are also evident in health and change during life emphasizing the dynamic and plastic nature of microglia. This review will consider how age impacts on sex-related differences in microglia and ask whether the advancement of personalized medicine demands that a greater focus is placed on studying sex-related differences in microglia in Alzheimer's disease, Parkinson's disease and models of inflammatory stress and trauma in order to make true progress in dealing with these conditions.

Interplay between stress-related genes may influence Alzheimer's disease development: The results of genetic interaction analyses of human data

Emerging evidence from experimental and clinical research suggests that stress-related genes may play key roles in AD development. The fact that genome-wide association studies were not able to detect a contribution of such genes to AD indicates the possibility that these genes may influence AD non-linearly, through interactions of their products. In this paper, we selected two stress-related genes (GCN2/EIF2AK4 and APP) based on recent findings from experimental studies which suggest that the interplay between these genes might influence AD in humans. To test this hypothesis, we evaluated the effects of interactions between SNPs in these two genes on AD occurrence, using the Health and Retirement Study data on white indidividuals. We found several interacting SNP-pairs whose associations with AD remained statistically significant after correction for multiple testing. These findings emphasize the importance of nonlinear mechanisms of polygenic AD regulation that cannot be detected in traditional association studies. To estimate collective effects of multiple interacting SNP-pairs on AD, we constructed a new composite index, called Interaction Polygenic Risk Score, and showed that its association with AD is highly statistically significant. These results open a new avenue in the analyses of mechanisms of complex multigenic AD regulation.

The phenotypic and transcriptomic effects of developmental exposure to nanomolar levels of estrone and bisphenol A in zebrafish

Estrone and BPA are two endocrine disrupting chemicals (EDCs) that are predicted to be less potent than estrogens such as 17β-estradiol and 17α-ethinylestradiol. Human exposure concentrations to estrone and BPA can be as low as nanomolar levels. However, very few toxicological studies have focused on the nanomolar-dose effects. Low level of EDCs can potentially cause non-monotonic responses. In addition, exposures at different developmental stages can lead to different health outcomes. To identify the nanomolar-dose effects of estrone and BPA, we used zebrafish modeling to study the phenotypic and transcriptomic responses after extended duration exposure from 0 to 5 days post-fertilization (dpf) and short-term exposure at days 4-5 post fertilization. We found that non-monotonic transcriptomic responses occurred after extended duration exposures at 1 nM of estrone or BPA. At this level, estrone also caused hypoactivity locomotive behavior in zebrafish. After both extended duration and short-term exposures, BPA led to more apparent phenotypic responses, i.e. skeletal abnormalities and locomotion changes, and more significant transcriptomic responses than estrone exposure. After short-term exposure, BPA at concentrations equal or above 100 nM affected locomotive behavior and changed the expression of both estrogenic and non-estrogenic genes that are linked to neurological diseases. These data provide gaps of mechanisms between neurological genes expression and associated phenotypic response due to estrone or BPA exposures. This study also provides insights for assessing the acceptable concentration of BPA and estrone in aquatic environments.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.

Genome-wide interaction analysis of pathological hallmarks in Alzheimer's disease

Genome-wide association studies have identified many loci associated with Alzheimer's dementia. However, these variants only explain part of the heritability of Alzheimer's disease (AD). As genetic epistasis can be a major contributor to the "missing heritability" of AD, we conducted genome-wide epistasis screening for AD pathologies in 2 independent cohorts. First, we performed a genome-wide epistasis study of AD-related brain pathologies (N_max = 1318) in ROS/MAP. Candidate interactions were validated using cerebrospinal fluid biomarkers of AD in ADNI (N_max = 1128). Further functional analysis tested the association of candidate interactions with neuroimaging phenotypes. For tau and amyloid-β pathology, we identified 2803 and 464 candidate SNP-SNP interactions, respectively. Associations of candidate SNP-SNP interactions with brain volume and white matter changes from neuroimages provides additional insights into their molecular functions. Transcriptional analysis supported possible gene-gene interactions identified by statistical screening through their co-expression in the brain. In summary, we outlined an exhaustive epistasis analysis to identify novel genetic interactions with potential roles in AD pathologies. We further delved into the functional relevance of candidate interactions by association with neuroimaging phenotypes and analysis of co-expression between corresponding gene pairs.

Sex-dependent effect of APOE on Alzheimer's disease and other age-related neurodegenerative disorders

The importance of apolipoprotein E (APOE) in late-onset Alzheimer's disease (LOAD) has been firmly established, but the mechanisms through which it exerts its pathogenic effects remain elusive. In addition, the sex-dependent effects of APOE on LOAD risk and endophenotypes have yet to be explained. In this Review, we revisit the different aspects of APOE involvement in neurodegeneration and neurological diseases, with particular attention to sex differences in the contribution of APOE to LOAD susceptibility. We discuss the role of APOE in a broader range of age-related neurodegenerative diseases, and summarize the biological factors linking APOE to sex hormones, drawing on supportive findings from rodent models to identify major mechanistic themes underlying the exacerbation of LOAD-associated neurodegeneration and pathology in the female brain. Additionally, we list sex-by-genotype interactions identified across neurodegenerative diseases, proposing APOE variants as a shared etiology for sex differences in the manifestation of these diseases. Finally, we present recent advancements in 'omics' technologies, which provide a new platform for more in-depth investigations of how dysregulation of this gene affects the development and progression of neurodegenerative diseases. Collectively, the evidence summarized in this Review highlights the interplay between APOE and sex as a key factor in the etiology of LOAD and other age-related neurodegenerative diseases. We emphasize the importance of careful examination of sex as a contributing factor in studying the underpinning genetics of neurodegenerative diseases in general, but particularly for LOAD.

The multiplex model of the genetics of Alzheimer's disease

Genes play a strong role in Alzheimer's disease (AD), with late-onset AD showing heritability of 58-79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.

Association of childhood traumatization and neuropsychiatric outcomes with altered plasma micro RNA-levels

Childhood traumatization (CT) is associated with the development of several neuropsychiatric disorders in later life. Experimental data in animals and observational data in humans revealed evidence for biological alterations in response to CT that may contribute to its long-term consequences. This includes epigenetic changes in miRNA levels that contribute to complex alterations of gene expression. We investigated the association between CT and 121 miRNAs in a target sample of N = 150 subjects from the general population and patients from the Department of Psychiatry. We hypothesized that CT exhibits a long-term effect on miRNA plasma levels. We supported our findings using bioinformatics tools and databases. Among the 121 miRNAs 22 were nominally significantly associated with CT and four of them (let-7g-5p, miR-103a-3p, miR-107, and miR-142-3p) also after correction for multiple testing; most of them were previously associated with Alzheimer's disease (AD) or depression. Pathway analyses of target genes identified significant pathways involved in neurodevelopment, inflammation and intracellular transduction signaling. In an independent general population sample (N = 587) three of the four miRNAs were replicated. Extended analyses in the general population sample only (N = 687) showed associations of the four miRNAs with gender, memory, and brain volumes. We gained increasing evidence for a link between CT, depression and AD through miRNA alterations. We hypothesize that depression and AD not only share environmental factors like CT but also biological factors like altered miRNA levels. This miRNA pattern could serve as mediating factor on the biological path from CT to adult neuropsychiatric disorders.

Identification of age- and gender-associated long noncoding RNAs in the human brain with Alzheimer's disease

Alzheimer's disease (AD) is an age- and gender-associated brain disorder. Long noncoding RNAs (lncRNAs) have emerged as key regulators of brain development, homeostasis, and pathologies. Here, we used gene array data sets and bioinformatics analysis to identify differentially expressed age- and gender-associated lncRNAs in human AD brains. We found that the expressions of 16 age-associated and 13 gender-associated lncRNAs were dysregulated in AD brains. Notably, the expressions of age-associated lncRNAs-SNHG19 and LINC00672-were significantly correlated with Braak stage of AD, positively and negatively, respectively, whereas the expressions of gender-associated lncRNAs-RNF144A-AS1, LY86-AS1, and LINC00639-were negatively correlated with Braak stage of AD. Functional analysis suggests that the pathways involved in neurodegenerative diseases, synaptic vesicle cycle, and endocytosis were overly represented within age- and gender-associated lncRNA-correlating genes. The identification of age- and gender-associated lncRNAs and their differential expressions in the human AD brain provide potential targets for further experimental validation and mechanistic investigation, which could, in turn, pave the way for developing age- and gender-specific prevention and adjunctive therapeutic options for patients with AD.

The new genetic landscape of Alzheimer's disease: from amyloid cascade to genetically driven synaptic failure hypothesis?

A strong genetic predisposition (60–80% of attributable risk) is present in Alzheimer’s disease (AD). In view of this major genetic component, identification of the genetic risk factors has been a major objective in the AD field with the ultimate aim to better understand the pathological processes. In this review, we present how the genetic risk factors are involved in APP metabolism, β-amyloid peptide production, degradation, aggregation and toxicity, innate immunity, and Tau toxicity. In addition, on the basis of the new genetic landscape, resulting from the recent high-throughput genomic approaches and emerging neurobiological information, we propose an over-arching model in which the focal adhesion pathway and the related cell signalling are key elements in AD pathogenesis. The core of the focal adhesion pathway links the physiological functions of amyloid precursor protein and Tau with the pathophysiological processes they are involved in. This model includes several entry points, fitting with the different origins for the disease, and supports the notion that dysregulation of synaptic plasticity is a central node in AD. Notably, our interpretation of the latest data from genome wide association studies complements other hypotheses already developed in the AD field, i.e., amyloid cascade, cellular phase or propagation hypotheses. Genetically driven synaptic failure hypothesis will need to be further tested experimentally within the general AD framework.

How to increase our belief in discovered statistical interactions via large-scale association studies?

The understanding that differences in biological epistasis may impact disease risk, diagnosis, or disease management stands in wide contrast to the unavailability of widely accepted large-scale epistasis analysis protocols. Several choices in the analysis workflow will impact false-positive and false-negative rates. One of these choices relates to the exploitation of particular modelling or testing strategies. The strengths and limitations of these need to be well understood, as well as the contexts in which these hold. This will contribute to determining the potentially complementary value of epistasis detection workflows and is expected to increase replication success with biological relevance. In this contribution, we take a recently introduced regression-based epistasis detection tool as a leading example to review the key elements that need to be considered to fully appreciate the value of analytical epistasis detection performance assessments. We point out unresolved hurdles and give our perspectives towards overcoming these.

Relationship Between Alzheimer's Disease and the Immune System: A Meta-Analysis of Differentially Expressed Genes

Alzheimer's disease (AD), a neurodegenerative diseases (neuro-diseases) which is prevalent in the elderly and seriously affects the lives of individuals. Many studies have discussed the relationship between immune system and AD pathogenesis. Here, the meta-analysis of differentially expressed (DE) genes based on microarray data was conducted to study the association between AD and immune system. 9519 target genes of hippocampus in 146 subjects (73 AD cases and 73 controls) from 4 microarray data sets were compiled and DE genes with p < 1.00E - 04 were selected to conduct the pathway-analysis. The results indicated that the DE genes were significantly enriched in the neuro-diseases as well as the immune system pathways.