Biology subjects

Bennett, D.

Publications and source records attributed to Bennett, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Ataxin-7 promotes Drosophila posterior follicle cell maturation by suppressing yorkie function

Ataxin-7 is a key component of the Spt-Ada-Gcn5-acetyltransferase (SAGA) chromatin-modifying complex that anchors Non-stop/USP22, a deubiquitinase, to the complex, thereby helping to coordinate SAGAs different activities. Recently, we found that non-stop is required in the Drosophila ovary for expression of Hippo signalling pathway components ex and mer, and polarisation of the actin cytoskeleton during collective epithelial cell migration. Here we show that in addition to being required for collective migration, Ataxin-7 plays an essential role in posterior follicle cells (PFCs) to control epithelial maturation and architecture, as well as body axis specification which depends on correct PFC differentiation. Loss of both the deubiquitinase and acetyltransferase modules of SAGA phenocopy loss of Ataxin-7 in PFCs, demonstrating a redundant requirement for SAGAs enzymatic modules. Strikingly, loss of yorkie completely suppressed effects of Ataxin-7 loss-of-function in PFCs, indicating that the only essential function of Ataxin-7 in PFCs is to suppress yorkie function. This may have broad relevance to the roles of SAGA and Ataxin-7 in development and disease.

cell biology↗

bioRxiv2022

A 3D bioengineered neural tissue model generated from patient-derived iPSCs develops Alzheimer's disease-related phenotypes

BackgroundCurrent models to study Alzheimers disease (AD) include cell cultures and animal models. Human diseases, however, are often poorly reproduced in animal models. Developing techniques to differentiate human brain cells from induced pluripotent stem cells (iPSCs) provides a novel approach to studying AD. Three-dimensional (3D) cultures to model AD are represented by organoids, neurospheroids, and scaffold-based cultures. Some AD-related phenotypes have been identified across 3D models [1]. However, to our knowledge, none of these studies could recapitulate several AD-related hallmarks in one single model and establish a temporal relation among them. Furthermore, to date, the transcriptomic features of these 3D models have not been compared with those of human AD brains. These data are, in our opinion, key to understanding the pertinency of these models for studying AD-related pathomechanisms over time. MethodsWe developed a 3D bioengineered model of iPSC-derived neural tissue that combines a porous scaffold composed of silk fibroin protein with an intercalated collagen hydrogel to support the growth of neurons and glial cells into complex and functional networks. This biomaterial scaffold, designed to match the mechanical properties of brain tissue, can support 3D neural cultures for an extended time without necrosis, a fundamental requisite for aging studies. We have optimized our protocol by seeding neural precursor cells (NPCs) into these scaffolds. NPC-derived cultures were generated from iPSC lines obtained from two subjects carrying the familial AD (FAD) APP London mutation, two well-studied control lines, and an isogenic control. Cultures were analyzed at 2 and 4.5 months. ResultsAn elevated A{beta}42/40 ratio was detected in conditioned media from FAD cultures at both time points, as previously reported in 2D cultures derived from the same FAD lines. However, extracellular A{beta}42 deposition and enhanced neuronal excitability were observed in FAD culture only at 4.5 months. The increased excitability of FAD cultures correlated with extracellular A{beta}42 deposition but not with soluble A{beta}42/40 ratio levels, as they were similar at both time points. These data suggest that extracellular A{beta} deposition may trigger enhanced network activity. Notably, neuronal hyperexcitability has been described in AD patients early in the disease. Transcriptomic analysis revealed the deregulation of multiple gene sets in FAD samples. Notably, such alterations were similar to those observed in human AD brains in a large study that performed a co-expression meta-analysis of harmonized data from Accelerating Medicines Partnership for Alzheimers Disease (AMP-AD) across three independent cohorts. ConclusionsOur 3D tissue model supports the differentiation of healthy iPSC-derived cultures in a porous silk-collagen composite sponge with an optically clear central region. This design facilitates nutrient delivery to meet the metabolic demand of long-term cultures. These data provide evidence that our bioengineered model from patient-derived FAD iPSCs develops time-dependent AD-related phenotypes and establishes a temporal relation among them. Furthermore, FAD iPSC-derived neuronal tissue recapitulates transcriptomic features of AD patients. Thus, our bioengineered neural tissue represents a unique tool to model AD-related pathomechanisms over time, with several advantages compared to the existing models.

neuroscience↗

bioRxiv2022

Architecture and dynamics of a novel desmosome-endoplasmic reticulum organelle

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signaling, and lipid transfer. Using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometer proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization and mobility. These findings indicate that desmosomes and the keratin cytoskeleton pattern the distribution of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction. One-Sentence SummaryThe desmosome adhesive junction regulates the organization and dynamics of the endoplasmic reticulum network.

cell biology↗

bioRxiv2021

Genotype-Phenotype Correlation of T Cell Subtypes Reveals Senescent and Cytotoxic Genes in Alzheimer's Disease

Recent studies identifying expression quantitative trait loci (eQTL) in immune cells have uncovered important links between disease risk alleles and gene expression trends in monocytes, T cells, and other cell types. However, these studies are generally done with young, healthy subjects, limiting the utility of their findings for age-related conditions such as Alzheimers disease (AD). We have performed RNA sequencing on four T cell subsets in genome-wide genotyped and well-characterized AD subjects and age- and sex-matched healthy controls from the Religious Orders Study/Memory and Aging Project. Correlating gene expression data with AD neuropathological traits, and with single nucleotide polymorphisms (SNPs) to detect eQTLs, we identified several significant genes involved in T cell senescence and cytotoxicity, consistent with T cell RNA sequencing studies in aged/AD cohorts. We identified unexpected eQTLs previously associated with neuropsychiatric disease traits. Finally, we discovered that pathways related to axon guidance and synaptic function were enriched among trans-eQTLs in coding regions of the genome. Overall, our data sheds more light on the genetic basis behind phenotypic changes in T cells during aging and AD.

immunology↗

bioRxiv2021

The effect of climate change on the distribution of Canidae

Land use by humans and climate change have been seriously affecting the distribution of species resulting in a quarter of all known mammals currently threatened with extinction. Here, we modeled the present and future potential distributions of all 36 extant Canidae species to evaluate their response to future climate scenarios. In addition, we tested if canids were likely to experience evolutionary rescue, which could allow some species to adapt to climate change. Our results suggest that global warming will cause most species to lose or maintain their ranges, while a few will have the potential to benefit from future conditions and considerably expand their geographic distributions. Some canids have the potential to experience evolutionary rescue, but Atelocynus microtis and Chrysocyon brachyurus are two concerning cases that do not show this capacity to adapt given the current pace of climate change. We also reveal that most Canidae hotspot regions are outside protected areas, which may be useful for the identification of key areas for conservation.

ecology↗

bioRxiv2021

Single-cell deconvolution of 3,000 post-mortem brain samples for eQTL and GWAS dissection in mental disorders

Thousands of genetic variants acting in multiple cell types underlie complex disorders, yet most gene expression studies profile only bulk tissues, making it hard to resolve where genetic and non-genetic contributors act. This is particularly important for psychiatric and neurodegenerative disorders that impact multiple brain cell types with highly-distinct gene expression patterns and proportions. To address this challenge, we develop a new framework, SPLITR, that integrates single-nucleus and bulk RNA-seq data, enabling phenotype-aware deconvolution and correcting for systematic discrepancies between bulk and single-cell data. We deconvolved 3,387 post-mortem brain samples across 1,127 individuals and in multiple brain regions. We find that cell proportion varies across brain regions, individuals, disease status, and genotype, including genetic variants in TMEM106B that impact inhibitory neuron fraction and 4,757 cell-type-specific eQTLs. Our results demonstrate the power of jointly analyzing bulk and single-cell RNA-seq to provide insights into cell-type-specific mechanisms for complex brain disorders.

genomics↗

bioRxiv2020

Automatic whole cell organelle segmentation in volumetric electron microscopy

Cells contain hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demands. Obtaining a complete understanding of their organization is challenging and requires nanometer-level, threedimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To meet this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing the cellular organelles in entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from endoplasmic reticulum to microtubules to ribosomes - from multiple cell types. Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures, including their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. We created an open data and open source web repository, OpenOrganelle, to share the data, computer code, and trained models, enabling scientists everywhere to query and further reconstruct the datasets.

cell biology↗

bioRxiv2020

Isotropic 3D electron microscopy reference library of whole cells and tissues

Understanding cellular architecture is essential for understanding biology. Electron microscopy (EM) uniquely visualizes cellular structures with nanometer resolution. However, traditional methods, such as thin-section EM or EM tomography, have limitations inasmuch as they only visualize a single slice or a relatively small volume of the cell, respectively. Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) demonstrated the ability to image cellular samples at 4-nm isotropic voxels with rather limited imageable volume. Here, we present 3D EM images of whole cells and tissues with two orders of magnitude increases in imageable volume at 4-nm voxels. Such data with a combined fine resolution scale and large sample size do not currently exist, and are enabled by the advances in higher precision and stability of FIB milling, together with enhanced signal detection and faster SEM scanning. More importantly, we have generated a volume EM atlas encompassing ten diverse datasets of whole cells and tissues, from cancer cells to immune cells, and from mouse pancreatic islets to Drosophila neural tissues. These open-access data (via OpenOrganelle) represent a foundation to nucleate a new field of high-resolution whole-cell volume EM and subsequent analyses, and invite biologists to explore this new paradigm and pose fundamentally new questions.

cell biology↗

bioRxiv2020

Drosophila USP22/non-stop regulates the Hippo pathway to polarise the actin cytoskeleton during collective border cell migration

Polarisation of the actin cytoskeleton is vital for the collective migration of cells in vivo. During invasive border cell migration in Drosophila, actin polarisation is directly controlled by Hippo pathway components, which reside at contacts between border cells in the cluster. Here we identify, in a genetic screen for deubiquitinating enzymes involved in border cell migration, an essential role for non-stop/USP22 in the expression of Hippo pathway components expanded and merlin; loss of non-stop function consequently leads to a redistribution of F-actin and the polarity determinant Crumbs, loss of polarised actin protrusions and premature tumbling of the border cell cluster. Non-stop is a component of the Spt-Ada-Gcn5-acetyltransferase (SAGA) transcriptional coactivator complex, but SAGA’s histone acetyltransferase module, which does not bind to expanded or merlin, is dispensable for migration. Taken together, our results uncover novel roles for SAGA-independent non-stop/USP22 in Hippo-mediated collective cell migration, which may help guide studies in other systems where USP22 is necessary for cell motility and invasion.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cell biology↗

bioRxiv2020

Powerful Variance-Component TWAS method identifies novel and known risk genes for clinical and pathologic Alzheimer's dementia phenotypes

Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, existing TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Existing TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTLs estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N=[~]3.4K) and summary-level (N=[~]54K) GWAS data to study Alzheimers dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by existing TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs; these findings also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use. Author SummaryExisting Transcriptome-wide association studies (TWAS) tools make strong assumptions about the relationships among genetic variants, transcriptome, and phenotype that may be violated in practice, thereby substantially reducing the power. Here, we propose a novel variance-component TWAS method (VC-TWAS) that relaxes these assumptions and can be implemented with both individual-level and summary-level GWAS data. Our simulation studies showed that VC-TWAS achieved higher power compared to existing TWAS methods when the underlying assumptions required by existing TWAS tools were violated. We further applied VC-TWAS to both individual-level (N=[~]3.4K) and summary-level (N=[~]54K) GWAS data to study Alzheimers dementia (AD). With individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by existing TWAS methods. Interestingly, 5 of these genes were shown to possess significant pleiotropic effects on AD pathology phenotypes, revealing possible biological mechanisms. With summary-level data of a larger sample size, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs, which also validated our findings with the individual-level GWAS data. In conclusion, VC-TWAS provides an important analytic tool for identifying risk genes whose effects on phenotypes might be mediated through transcriptomes.

genetics↗

bioRxiv2020

Controlling for off-target genetic effects using polygenic scores improves the power of genome-wide association studies

Ongoing increases in the size of human genotype and phenotype collections offer the promise of improved understanding of the genetics of complex diseases. In addition to the biological insights that can be gained from the nature of the variants that contribute to the genetic component of complex trait variability, these data bring forward the prospect of predicting complex traits and the risk of complex genetic diseases from genotype data. Here we show that advances in phenotype prediction can be applied to improve the power of genome-wide association studies. We demonstrate a simple and efficient method to model genetic background effects using polygenic scores derived from SNPs that are not on the same chromosome as the target SNP. Using simulated and real data we found that this can result in a substantial increase in the number of variants passing genome-wide significance thresholds. This increase in power to detect trait-associated variants also translates into an increase in the accuracy with which the resulting polygenic score predicts the phenotype from genotype data. Our results suggest that advances in methods for phenotype prediction can be exploited to improve the control of background genetic effects, leading to more accurate GWAS results and further improvements in phenotype prediction.

genomics↗

bioRxiv2020

WEGE: A NEW METRIC FOR RANKING LOCATIONS FOR BIODIVERSITY CONSERVATION

AimIn order to implement effective conservation policies, it is crucial to know how biodiversity is distributed and one of the most widely used systems is the Key Biodiversity Areas (hereafter KBA) criteria, developed by the International Union for Conservation of Nature (IUCN). Here we develop a tool to rank Key Biodiversity Areas in a continuous scale to allow the ranking between KBAs and test this tool on a simulated dataset of 10 000 scenarios of species compositions of reptiles and mammals in eight locations in Mozambique. LocationMozambique, Africa MethodsWe compare the KBA criteria with four priorisation metrics (weighted endemism, extinction risk, evolutionary distinctiveness and EDGE score) to rank the biodiversity importance of eight sites with a randomly generated species composition of reptiles and mammals in Mozambique. ResultsWe find that none of these metrics is able to provide a suitable ranking of the sites surveyed that would ultimately allow prioritization. We therefore develop and validate the "WEGE index" (Weighted Endemism including Global Endangerment index), which is an adaptation of the EDGE score (Evolutionarily Distinct and Globally Endangered) and allows the ranking of sites according to the KBA criteria but on a continuous scale. Main conclusionsFor our study system, the WEGE index scores areas that trigger KBA status higher and is able to rank their importance in terms of biodiversity by using the range and threat status of species present at the site. Prioritization may be crucial for policy making and real-life conservation, allowing the choice between otherwise equally qualified sites according to the KBA categories. WEGE is intended to support a transparent decision-making process in conservation.

ecology↗

bioRxiv2019

Anxious and obsessive-compulsive traits are independently associated with valuation of non-instrumental information

Aversion to uncertainty about the future has been proposed as a transdiagnostic trait underlying psychiatric diagnoses including obsessive-compulsive disorder and generalised anxiety. This association might explain the frequency of pathological information-seeking behaviours such as compulsive checking and reassurance-seeking in these disorders. Here we tested the behavioural predictions of this model using a non-instrumental information-seeking task that measured preferences for unusable information about future outcomes in different payout domains (gain, loss, and mixed gain/loss). We administered this task, along with a targeted battery of self-report questionnaires, to a general-population sample of 146 adult participants. Using computational cognitive modelling of choices to test competing theories of information valuation, we found evidence for a model in which preferences for costless and costly information about future outcomes were independent, and in which information preference was modulated by both outcome mean and outcome variance. Critically, we also found positive associations between a model parameter controlling preference for costly information and individual differences in latent traits of both anxiety and obsessive-compulsion. These associations were invariant across different payout domains, providing evidence that individuals high in obsessive-compulsive and anxious traits show a generalised increase in willingness-to-pay for unusable information about uncertain future outcomes, even though this behaviour reduces their expected future reward.

animal behavior and cognition↗

bioRxiv2019

A Multidimensional Systems Biology Analysis of Cellular Senescence in Ageing and Disease

Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of ageing and has been linked to ageing-related diseases like cancer. Senescent cells have been shown to accumulate in tissues of aged organisms which in turn can lead to chronic inflammation. Many genes have been associated with cell senescence, yet a comprehensive understanding of cell senescence pathways is still lacking. To this end, we created CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes associated with cellular senescence, and performed various integrative and functional analyses. We observed that genes promoting cell senescence tend to be overexpressed with age in human tissues and are also significantly overrepresented in anti-longevity and tumour-suppressor gene databases. By contrast, genes inhibiting cell senescence overlapped with pro-longevity genes and oncogenes. Furthermore, an evolutionary analysis revealed a strong conservation of senescence-associated genes in mammals, but not in invertebrates. Using the CellAge genes as seed nodes, we also built protein-protein interaction and co-expression networks. Clusters in the networks were enriched for cell cycle and immunological processes. Network topological parameters also revealed novel potential senescence-associated regulators. We then used siRNAs and observed that of 26 candidates tested, 19 induced markers of senescence. Overall, our work provides a new resource for researchers to study cell senescence and our systems biology analyses provide new insights and novel genes regarding cell senescence.

systems biology↗

bioRxiv2019

Brain microRNAs associated with late-life depressive symptoms are also associated with cognitive trajectory and dementia

ObjectiveLate-life depression is associated with an increased risk for dementia, but our knowledge of the molecular mechanisms underlying this association is limited. Hence, the authors investigated whether microRNAs, important post-transcriptional regulators of gene expression, contribute to this association.\n\nMethodLate-life depressive symptoms were assessed annually in 300 non-demented participants of the Religious Orders Study and Rush Memory and Aging Project for a mean of seven years using the Center for Epidemiological Studies Depression scale. Participants underwent annual cognitive testing, clinical assessment of cognitive status, and uniform neuropathologic examination after death. microRNAs were profiled from the prefrontal cortex using Nanostring platform. A global microRNA association study of late-life depressive symptoms was performed using linear mixed model adjusting for sex, age, Alzheimers dementia pathological burden, proportions of brain cell types, post-mortem interval, and RNA integrity.\n\nResultsFour brain microRNAs were associated with late-life depressive symptoms at adjusted p<0.05 (miR-484, miR-26b, miR-30d, and miR-197). Lower expressions of these miRNAs were associated with greater depressive symptoms. Furthermore, lower expressions of miR-484 and miR-197 were associated with faster decline of cognitive performance over time. Additionally, lower miR-484 level was associated with higher probability of having Alzheimers dementia. Lastly, the predicted targets of miR-484 were enriched in a brain protein co-expression module involving synaptic transmission and regulation of long-term neuronal synaptic plasticity.\n\nConclusionsThis is the first study to identify brain microRNAs associated with late-life depressive symptoms assessed longitudinally. Additionally, the authors found a link between late-life depressive symptoms and dementia through miR-484 and miR-197.

genomics↗

bioRxiv2019

Adapting the ELEAT: Early Life Exposure Assessment Tool) to Portugal - a pilot study to tackle gene-environment interactions in Autism Spectrum Disorder

BackgroundAutism Spectrum Disorder (ASD) is a pervasive and clinically heterogeneous neurodevelopmental disorder characterized by deficits in social communication and interaction skills, and repetitive and stereotyped behaviours. It is known that ASD has a strong genetics component, but heritability estimates of 50-80% suggest that modifiable non-genetic factors may play an important role in the onset of the disorder. Recently, pre-, peri and post-natal exposure to a variety of environmental factors has been implicated in ASD. Yet, the comprehensive assessment of environmental exposures in this pathology, using large population datasets, is still lacking. The objective of this study was to pilot an environmental exposure assessment tool in Portugal.\n\nMethodsTo examine environmental exposures in a population of Portuguese children with ASD, we translated, adapted and piloted the Early Life Exposure Assessment Tool (ELEAT). The ELEAT was originally developed to assess environmental factors in studies of neurodevelopmental disorders. It is a questionnaire filled by mothers of children with ASD, enquiring about Demographic Information, Maternal Conditions/Medical Interventions, Breastfeeding and Child Diet, Maternal Diet, Supplements, Lifestyle, Home and Environment, Environment, Occupation and Exposures. The ELEAT gathers information about environmental exposure along key phases for early neurodevelopment, from 3 months prior to conception, pregnancy, labor and delivery to the first year of life of the child. Two focus groups were realized, one with mothers of typically-developing children and another with mothers of children with ASD, in order to discuss the mothers opinion regarding the tool comprehensiveness and relevance.\n\nResultsThe large majority of mothers were sure about their answers for all modules, with a small fraction of the group reporting difficulties for the Occupations/Exposures module. Most mothers considered the ELEAT to be a little too long, but generally found that the instructions were clear and, most importantly, agreed that the questions were important.\n\nConclusionsIntegration of the pilot feedback will allow us to enhance the tool and optimize its usage in Portuguese-speaking communities, improving its capacity to assemble accurate environmental data from diverse cultural settings, and to be extended to larger population datasets. Combined with genetic and clinical data, the ELEAT will contribute to the identification of modifiable lifestyle and environmental risk factors for ASD. Such evidence may eventually provide the opportunity for disease prevention or reduced severity by mitigating exposure when genetic susceptibility is identified early in life.

developmental biology↗

bioRxiv2018

Lipid associated polygenic enrichment in Alzheimer’s disease

Cardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimers disease (AD) pathogenesis. Beyond the [isin]4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimers risk.

genetics↗

bioRxiv2017

A molecular network of the aging brain implicates INPPL1 and PLXNB1 in Alzheimer’s disease

The fact that only symptomatic therapies of small effect are available for Alzheimers disease (AD) today highlights the need for new therapeutic targets with which to prevent a major contributor to aging-related cognitive decline. Here, we report the construction and validation of a molecular network of the aging human frontal cortex. Using RNA sequence data from 478 individuals, we first identify the role of modules of coexpressed genes, and then confirm them in independent AD datasets. Then, we prioritize influential genes in AD-related modules and test our predictions in human model systems. We functionally validate two putative regulator genes in human astrocytes: INPPL1 and PLXNB1, whose activity in AD may be related to semaphorin signalling and type II diabetes, which have both been implicated in AD. This arc of network identification followed by statistical and experimental validation provides specific new targets for therapeutic development and illustrates a network approach to a complex disease.\n\nOne sentence summaryMolecular network analysis of RNA sequencing data from the aging human cortex identifies new Alzheimers and cognitive decline genes.

systems biology↗