Genetic variation modifies risk for neurodegeneration based on biomarker status

LncRNA WDR11-AS1 Promotes Extracellular Matrix Synthesis in Osteoarthritis by Directly Interacting with RNA-Binding Protein PABPC1 to Stabilize SOX9 Expression

Osteoarthritis (OA) is a degenerative disease of articular cartilage that is mainly characterized by chronic and mild inflammation of the joints. Recently, many studies have reported the crucial roles of long noncoding RNAs (lncRNAs) in OA as gene transcriptional regulatory factors, diagnostic biomarkers, or therapeutic targets. However, the exact mechanisms of lncRNAs in the regulation of OA progression remain unclear. In the present study, the lncRNA WDR11 divergent transcript (lncRNA WDR11-AS1) was shown to be downregulated in osteoarthritic cartilage tissues from patients, and to promote extracellular matrix (ECM) synthesis in osteoarthritic chondrocytes with knockdown and overexpression experiments. This function of lncRNA WDR11-AS1 was linked to its ability to interact with the polyadenylate-binding protein cytoplasmic 1 (PABPC1), which was screened by RNA pulldown and mass spectrometry analyses. PABPC1 was discovered to bind ECM-related mRNAs such as SOX9, and the inhibition of PABPC1 improved the mRNA stability of SOX9 to mitigate OA progression. Our results suggest that lncRNA WDR11-AS1 has a promising inhibitory effect on inflammation-induced ECM degradation in OA by directly binding PABPC1, thereby establishing lncRNA WDR11-AS1 and PABPC1 as potential therapeutic targets in the treatment of OA.

A novel inflammation-related lncRNAs prognostic signature identifies LINC00346 in promoting proliferation, migration, and immune infiltration of glioma

In this study, a total of 13 inflammation-related lncRNAs with a high prognostic value were identified with univariate, multivariate Cox regression analysis, and LASSO analysis. LINC00346, which is one of the 13 lncRNAs identified, was positively associated with type 2 macrophage activation and the malignant degree of glioma. Fluorescence in situ hybridization (FISH) and immunohistochemical staining showed that LINC00346 was highly expressed in high-grade glioma, while type 2 macrophages key transcription factor STAT3 and surface marker CD204 were also highly expressed simultaneously. LINC00346 high-expression gliomas were more sensitive to the anti–PD-1 and anti-CTLA-4 therapy. LINC00346 was also associated with tumor proliferation and tumor migration validated by EdU, cell colony, formation CCK8, and transwell assays. These findings reveal novel biomarkers for predicting glioma prognosis and outline relationships between lncRNAs inflammation, and glioma, as well as possible immune checkpoint targets for glioma.

A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

Structural Covariance Network as an Endophenotype in Alzheimer's Disease-Susceptible Single-Nucleotide Polymorphisms and the Correlations With Cognitive Outcomes

The cognitive manifestations of Alzheimer’s disease (AD) are related to brain network degeneration, and genetic differences may mediate network degeneration. Several AD-susceptible loci have been reported to involve amyloid or tau cascades; however, their relationships with gray matter (GM) volume and cognitive outcomes have yet to be established. We hypothesized that single-nucleotide polymorphism genotype groups may interact with apolipoprotein E4 (ApoE4) status or independently exert an effect on cognitive outcomes. We also hypothesized that GM structural covariance networks (SCNs) may serve as an endophenotype of the genetic effect, which, in turn, may be related to neurobehavior test scores. Gray matter SCNs were constructed in 324 patients with AD using T1 magnetic resonance imaging with independent component analysis (ICA). We assessed the effects of 15 genetic loci (rs9349407, rs3865444, rs670139, rs744373, rs3851179, rs11136000, rs3764650, rs610932, rs6887649, rs7849530, rs4866650, rs3765728, rs34011, rs6656401, and rs597668) using additive, recessive, and dominant models on cognitive outcomes. Statistical analysis was performed to explore the independent role of each locus, interactions with ApoE4 status, and relationships to GM ICA network intensity score. For outcome measures, we used the Mini-Mental State Examination (MMSE), Cognitive Abilities Screening Instrument (CASI) total score, and short-term memory (STM) subscores, adjusted for the covariates of education, disease duration, and age. Clinically, the CD2AP G allele showed a protective role in MMSE, CASI total, and CASI-STM scores independently or via interactions with non-ApoE4 status, while the CR1 A genotype group was associated with lower STM subscores independent of ApoE4 status. Three loci showed synergic interactions with ApoE4: BIN 1, MS4A6A, and FTMT. Of the 15 meaningful ICA components, 5 SCNs (anterior and posterior hippocampus, right temporal, left thalamus, default mode network) showed relationships with general cognitive performance, in which only the ApoE4 and MS4A6A genotype groups were independently related to the hippocampus network. The genetic loci MS4A6A, BIN1, CLU, CR1, BIN1, PICALM, and FGF1 influenced the networks independently or in synergy. This study suggests that AD-susceptible loci may each exert clinical significance independently through interactions with ApoE4 status or through SCNs as an endophenotype and that this effect is associated with the cognitive outcomes.

Genetic variants and functional pathways associated with resilience to Alzheimer's disease

Approximately 30% of older adults exhibit the neuropathological features of Alzheimer's disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer's disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values < 2.5 × 10-20), and we observed novel correlations with neuropsychiatric conditions (P-values < 7.9 × 10-4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer's disease (P-values > 0.42) nor associated with APOE (P-values > 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer's disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.

Systems modeling of white matter microstructural abnormalities in Alzheimer's disease

INTRODUCTION

Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression.

METHODS

We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD.

RESULTS

We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions.

DISCUSSION

Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD.

From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review

BACKGROUND

Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.

OBJECTIVE

This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.

METHODS

We searched the literature from July 2008-July 2018 following PRISMA guidelines.

RESULTS

57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.

CONCLUSION

PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

Telomere length associations with cognition depend on Alzheimer's disease biomarkers

Introduction

While telomere shortening, a marker of cellular aging, may impact the progression of age-related neurodegenerative diseases, its association with cognition is unclear, particularly in the context of Alzheimer's disease (AD) pathology.

Methods

Telomere, cognitive, and CSF data from 482 participants in the AD Neuroimaging Initiative (148 cognitively normal, 283 mild cognitive impairment, 51 AD) was leveraged to assess telomere length associations with cognition (measured by memory and executive function) and interactions with CSF amyloid-β, tau, and APOE -ε4. Secondary analyses assessed brain volume and thickness outcomes.

Results

Longer telomeres at baseline were associated with faster executive function decline. Amyloid-β and tau interacted with telomere length on cognition, with longer telomeres related to faster decline among biomarker-positive individuals.

Discussion

Telomere associations with cognition shift with AD progression, with longer telomeres related to worse outcomes as pathology increases, highlighting the need for further investigation of telomere length along the AD neuropathological cascade.

The intrinsic and extrinsic factors that contribute to proteostasis decline and pathological protein misfolding

Proteostasis refers to the ability of cells to maintain the health of the proteome. Highly conserved quality control mechanisms exist to maintain proteostasis. These include the heat shock response, the unfolded protein response, and protein clearance/degradation pathways. Together, these mechanisms and others comprise the proteostasis network. This network is under constant assault and is strikingly sensitive to changes in the protein folding environment, resulting in proteostasis collapse under certain conditions. Here, the intrinsic and extrinsic stresses experienced by the proteostasis network are explored. The intrinsic stresses include genetic background as well as transcriptional and translational fidelity. These cause changes in the abundance or amino acid sequence of cellular proteins. Extrinsic stresses refer to environmental perturbation of the proteome, such as those caused by temperature stress, oxidative stress, air pollution and cigarette smoke. As the stress to the proteome exceeds the capacity of the proteostasis network, progressive neurodegenerative diseases of aging, such as Alzheimer's disease and Huntington's disease are more likely to ensue.

Prediction of causal genes and gene expression analysis of attention-deficit hyperactivity disorder in the different brain region, a comprehensive integrative analysis of ADHD

Recent genome-wide association study (GWAS) identified 12 independent loci for Attention-deficit hyperactivity disorder (ADHD). However, the causal genes expression and pathways of ADHD is still vague. We integrated GWAS, eQTL and genes expression data to find the causal genes, genes expression, and genes prioritization in the different brain tissues and whole blood cells. Overall 47 genes were prioritized, the most promising genes were LSG1, HYAL3, PIDD, PNPLA2, BLOC1S2, PLK1S1, CALN1, KAT2B, CTNNB1 and WDR11. Whereas, the CALN1, KAT2B, and WDR11 were previously associated with schizophrenia (SZ), bipolar (BP) and drug abuse. Gene ontology analysis shows that the glutamate receptor signaling pathway (P = 8.009E-07, with false discovery rate (FDR) < 5%), GRIK5 sub network (P = 2.887E-06, FDR < 5%), abnormal gait (P = 3.657E-06, FDR < 5%), REACTOME_SIGNALING_BY_ERBB2 (P = 5.161E-06, FDR < 5%), and abnormal nervous system physiology (P = 5.239E-06, FDR < 5%) were associated with ADHD. These causal genes were highly expressed in Fetal Astrocytes, Neurons, and Microglia/Macrophage. This study illustrates the comprehensive GWAS integrative approach of ADHD. However, further genetic and functional studies are required to validate the role of these genes in the etiology of ADHD, which should provide novel insights into the understanding of this disease.

Genome-wide association study for variants that modulate relationships between cerebrospinal fluid amyloid-beta 42, tau, and p-tau levels

Background

A relationship quantitative trait locus exists when the correlation between multiple traits varies by genotype for that locus. Relationship quantitative trait loci (rQTL) are often involved in gene-by-gene (G×G) interactions or gene-by-environmental interactions, making them a powerful tool for detecting G×G.

Methods

We performed genome-wide association studies to identify rQTL between tau and Aβ42 and ptau and Aβ42 with over 3000 individuals using age, gender, series, APOE ε2, APOE ε4, and two principal components for population structure as covariates. Each significant rQTL was separately screened for interactions with other loci for each trait in the rQTL model. Parametric bootstrapping was used to assess significance.

Results

We found four significant tau/Aβ42 rQTL from three unique locations and six ptau/Aβ42 rQTL from five unique locations. G×G screens with these rQTL produced four significant G×G interactions (one Aβ42, two ptau, and one tau) with four rQTL where each second locus was from a unique location. On follow-up, rs1036819 and rs74025622 were associated with Alzheimer’s disease (AD) case/control status; rs15205 and rs79099429 were associated with rate of decline.

Conclusions

The two most significant rQTL (rs8027714 and rs1036819) for ptau/Aβ42 are on different chromosomes and both are strong hits for pelvic organ prolapse. While diseases of the nervous system can cause pelvic organ prolapse, it is unlikely related to the ptau/Aβ42 relationship but may suggest that these two loci share a pathway. In addition to a ptau/Aβ42 rQTL and association with AD case/control status, rs1036819 is a strong rQTL for case/control status/Aβ42 and for tau/Aβ42. It resides in the ZFAT gene, which is related to autoimmune thyroid disease. For tau, rs9817620 interacts with the tau/Aβ42 rQTL rs74025622. It is in the CHL1 gene, which is a neural cell adhesion molecule and may be involved in signal transduction pathways. CHL1 is related to BACE1, which is a β-secretase enzyme that initiates production of the β-amyloid peptide involved in AD and is a primary drug target. Overall, there are numerous loci that affect the relationship between these important AD endophenotypes and some are due to interactions with other loci. Some affect the risk of AD and/or rate of progression.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0410-y) contains supplementary material, which is available to authorized users.

State of Play in Alzheimer's Disease Genetics

Alzheimer's disease (AD), the main form of dementia in the elderly, is the most common progressive neurodegenerative disease characterized by rapidly progressive cognitive dysfunction and behavior impairment. AD exhibits a considerable heritability and great advances have been made in approaches to searching the genetic etiology of AD. In AD genetic studies, methods have developed from classic linkage-based and candidate-gene-based association studies to genome-wide association studies (GWAS) and next generation sequencing (NGS). The identification of new susceptibility genes has provided deeper insights to understand the mechanisms underlying AD. In addition to searching novel genes associated with AD in large samples, the NGS technologies can also be used to shed light on the 'black matter' discovery even in smaller samples. The shift in AD genetics between traditional studies and individual sequencing will allow biomaterials of each patient as the central unit of genetic studies. This review will cover genetic findings in AD and consequences of AD genetic findings. Firstly, we will discuss the discovery of mutations in APP, PSEN1, PSEN2, APOE, and ADAM10. Then we will summarize and evaluate the information obtained from GWAS of AD. Finally, we will outline the efforts to identify rare variants associated with AD using NGS.

Targeted neurogenesis pathway-based gene analysis identifies ADORA2A associated with hippocampal volume in mild cognitive impairment and Alzheimer's disease

Alzheimer's disease (AD) patients display hippocampal atrophy, memory impairment, and cognitive decline. New neurons are generated throughout adulthood in 2 regions of the brain implicated in AD, the dentate gyrus of the hippocampus and the subventricular zone of the olfactory bulb. Disruption of this process contributes to neurodegenerative diseases including AD, and many of the molecular players in AD are also modulators of adult neurogenesis. However, the genetic mechanisms underlying adult neurogenesis in AD have been underexplored. To address this gap, we performed a gene-based association analysis in cognitively normal and impaired participants using neurogenesis pathway-related candidate genes curated from existing databases, literature mining, and large-scale genome-wide association study findings. A gene-based association analysis identified adenosine A2a receptor (ADORA2A) as significantly associated with hippocampal volume and the association between rs9608282 within ADORA2A and hippocampal volume was replicated in the meta-analysis after multiple comparison adjustments (p = 7.88 × 10-6). The minor allele of rs9608282 in ADORA2A is associated with larger hippocampal volumes and better memory.

Genetic variation in neurodegenerative diseases and its accessibility in the model organism Caenorhabditis elegans

BACKGROUND

Neurodegenerative diseases (NGDs) such as Alzheimer's and Parkinson's are debilitating and largely untreatable conditions strongly linked to age. The clinical, neuropathological, and genetic components of NGDs indicate that neurodegeneration is a complex trait determined by multiple genes and by the environment.

MAIN BODY

The symptoms of NGDs differ among individuals due to their genetic background, and this variation affects the onset and progression of NGD and NGD-like states. Such genetic variation affects the molecular and cellular processes underlying NGDs, leading to differential clinical phenotypes. So far, we have a limited understanding of the mechanisms of individual background variation. Here, we consider how variation between genetic backgrounds affects the mechanisms of aging and proteostasis in NGD phenotypes. We discuss how the nematode Caenorhabditis elegans can be used to identify the role of variation between genetic backgrounds. Additionally, we review advances in C. elegans methods that can facilitate the identification of NGD regulators and/or networks.

CONCLUSION

Genetic variation both in disease genes and in regulatory factors that modulate onset and progression of NGDs are incompletely understood. The nematode C. elegans represents a valuable system in which to address such questions.

The Vanderbilt Memory & Aging Project: Study Design and Baseline Cohort Overview

BACKGROUND

Vascular health factors frequently co-occur with Alzheimer's disease (AD). A better understanding of how systemic vascular and cerebrovascular health intersects with clinical and pathological AD may inform prevention and treatment opportunities.

OBJECTIVE

To establish the Vanderbilt Memory & Aging Project, a case-control longitudinal study investigating vascular health and brain aging, and describe baseline methodology and participant characteristics.

METHODS

From September 2012 to November 2014, 335 participants age 60- 92 were enrolled, including 168 individuals with mild cognitive impairment (MCI, 73±8 years, 41% female) and 167 age-, sex-, and race-matched cognitively normal controls (NC, 72±7 years, 41% female). At baseline, participants completed a physical and frailty examination, fasting blood draw, neuropsychological assessment, echocardiogram, cardiac MRI, and brain MRI. A subset underwent 24-hour ambulatory blood pressure monitoring and lumbar puncture for cerebrospinal fluid (CSF) collection.

RESULTS

As designed, participant groups were comparable for age (p = 0.31), sex (p = 0.95), and race (p = 0.65). MCI participants had greater Framingham Stroke Risk Profile scores (p = 0.008), systolic blood pressure values (p = 0.008), and history of left ventricular hypertrophy (p = 0.04) than NC participants. As expected, MCI participants performed worse on all neuropsychological measures (p-values < 0.001), were more likely to be APOEɛ4 carriers (p = 0.02), and had enhanced CSF biomarkers, including lower Aβ42 (p = 0.02), higher total tau (p = 0.004), and higher p-tau (p = 0.02) compared to NC participants.

CONCLUSION

Diverse sources of baseline and longitudinal data will provide rich opportunities to investigate pathways linking vascular and cerebrovascular health, clinical and pathological AD, and neurodegeneration contributing to novel strategies to delay or prevent cognitive decline.

Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans

INTRODUCTION

Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans.

METHODS

Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated.

RESULTS

ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD.

DISCUSSION

Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.