scholarly journals A transcriptome-wide association study of Alzheimer’s disease using prediction models of relevant tissues identifies novel candidate susceptibility genes

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Yanfa Sun ◽  
Jingjing Zhu ◽  
Dan Zhou ◽  
Saranya Canchi ◽  
Chong Wu ◽  
...  

Abstract Background Genome-wide association studies (GWAS) have identified over 56 susceptibility loci associated with Alzheimer’s disease (AD), but the genes responsible for these associations remain largely unknown. Methods We performed a large transcriptome-wide association study (TWAS) leveraging modified UTMOST (Unified Test for MOlecular SignaTures) prediction models of ten brain tissues that are potentially related to AD to discover novel AD genetic loci and putative target genes in 71,880 (proxy) cases and 383,378 (proxy) controls of European ancestry. Results We identified 53 genes with predicted expression associations with AD risk at Bonferroni correction threshold (P value < 3.38 × 10−6). Based on fine-mapping analyses, 21 genes at nine loci showed strong support for being causal. Conclusions Our study provides new insights into the etiology and underlying genetic architecture of AD.

2021 ◽  
Author(s):  
Bryce Rowland ◽  
Sanan Venkatesh ◽  
Manuel Tardaguila ◽  
Jia Wen ◽  
Jonathan D Rosen ◽  
...  

Previous genome-wide association studies (GWAS) of hematological traits have identified over 10,000 distinct trait-specific risk loci, but the underlying causal mechanisms at these loci remain incompletely characterized. We performed a transcriptome-wide association study (TWAS) of 29 hematological traits in 399,835 UK Biobank (UKB) participants of European ancestry using gene expression prediction models trained from whole blood RNA-seq data in 922 individuals. We discovered 557 TWAS signals associated with hematological traits distinct from previously discovered GWAS variants, including 10 completely novel gene-trait pairs corresponding to 9 unique genes. Among the 557 associations, 301 were available for replication in a cohort of 141,286 participants of European ancestry from the Million Veteran Program (MVP). Of these 301 associations, 199 replicated at a nominal threshold (α = 0.05) and 108 replicated at a strict Bonferroni adjusted threshold (α = 0.05/301). Using our TWAS results, we systematically assigned 4,261 out of 16,900 previously identified hematological trait GWAS variants to putative target genes. Compared to coloc, our TWAS results show reduced specificity and increased sensitivity to assign variants to target genes.


2021 ◽  
Author(s):  
Abbas Dehghan ◽  
Rui Pinto ◽  
Ibrahim Karaman ◽  
Jian Hung ◽  
Brenan Durainayagam ◽  
...  

Genome-wide association studies (GWAS) have identified genetic loci associated with risk of Alzheimer's disease (AD), but underlying mechanisms are largely unknown. Using untargeted mass spectrometry, we conducted a metabolome-wide association study (MWAS) that identified the association of lactosylceramides (LacCer)s with AD-related single nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0x 10-5 to 1.3 x 10-44). Independent support for the association came through the discovery of differences in concentrations of sphingomyelins, ceramides, and hexose-ceramides in brain tissue from ABCA7-null mice compared to wild type (P =0.049 -1.44 x10-5). We showed that plasma LacCer concentrations are associated with cognitive performance in humans. We found evidence for a potentially causal association of LacCer with AD risk using Mendelian randomisation analysis. Our work suggests that AD risks arising from functional variations in ABCA7 expression are mediated at least in part through ceramides, the metabolism or downstream signalling of which offers new therapeutic opportunities.


2011 ◽  
Vol 39 (4) ◽  
pp. 910-916 ◽  
Author(s):  
Rita J. Guerreiro ◽  
John Hardy

In the present review, we look back at the recent history of GWAS (genome-wide association studies) in AD (Alzheimer's disease) and integrate the major findings with current knowledge of biological processes and pathways. These topics are essential for the development of animal models, which will be fundamental to our complete understanding of AD.


2019 ◽  
Author(s):  
Javier de Velasco Oriol ◽  
Edgar E. Vallejo ◽  
Karol Estrada ◽  

AbstractAlzheimer’s disease (AD) is the leading form of dementia. Over 25 million cases have been estimated worldwide and this number is predicted to increase two-fold every 20 years. Even though there is a variety of clinical markers available for the diagnosis of AD, the accurate and timely diagnosis of this disease remains elusive. Recently, over a dozen of genetic variants predisposing to the disease have been identified by genome-wide association studies. However, these genetic variants only explain a small fraction of the estimated genetic component of the disease. Therefore, useful predictions of AD from genetic data could not rely on these markers exclusively as they are not sufficiently informative predictors. In this study, we propose the use of deep neural networks for the prediction of late-onset Alzheimer’s disease from a large number of genetic variants. Experimental results indicate that the proposed model holds promise to produce useful predictions for clinical diagnosis of AD.


2021 ◽  
Vol 12 ◽  
Author(s):  
Peng-Fei Wu ◽  
Xing-Hao Zhang ◽  
Ping Zhou ◽  
Rui Yin ◽  
Xiao-Ting Zhou ◽  
...  

BackgroundPrevious observational studies have suggested that associations exist between growth differentiation factor 15 (GDF-15) and neurodegenerative diseases. We aimed to investigate the causal relationships between GDF-15 and Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS).MethodsUsing summary-level datasets from genome-wide association studies of European ancestry, we performed a two-sample Mendelian randomization (MR) study. Genetic variants significantly associated (p &lt; 5 × 10–8) with GDF-15 were selected as instrumental variables (n = 5). An inverse-variance weighted method was implemented as the primary MR approach, while weighted median, MR–Egger, leave-one-out analysis, and Cochran’s Q-test were conducted as sensitivity analyses. All analyses were performed using R 3.6.1 with relevant packages.ResultsMR provided evidence for the association of elevated GDF-15 levels with a higher risk of AD (odds ratio = 1.14; 95% confidence interval, 1.04–1.24; p = 0.004). In the reverse direction, Mendelian randomization suggested no causal effect of genetically proxied risk of AD on circulating GDF-15 (p = 0.450). The causal effects of GDF-15 on PD (p = 0.597) or ALS (p = 0.120) were not identified, and the MR results likewise did not support the association of genetic liability to PD or ALS with genetically predicted levels of GDF-15. No evident heterogeneity or horizontal pleiotropy was revealed by multiple sensitivity analyses.ConclusionWe highlighted the role of GDF-15 in AD as altogether a promising diagnostic marker and a therapeutic target.


2021 ◽  
Author(s):  
Adam C. Naj ◽  
Ganna Leonenko ◽  
Xueqiu Jian ◽  
Benjamin Grenier-Boley ◽  
Maria Carolina Dalmasso ◽  
...  

Risk for late-onset Alzheimer's disease (LOAD) is driven by multiple loci primarily identified by genome-wide association studies, many of which are common variants with minor allele frequencies (MAF)>0.01. To identify additional common and rare LOAD risk variants, we performed a GWAS on 25,170 LOAD subjects and 41,052 cognitively normal controls in 44 datasets from the International Genomics of Alzheimer's Project (IGAP). Existing genotype data were imputed using the dense, high-resolution Haplotype Reference Consortium (HRC) r1.1 reference panel. Stage 1 associations of P<10-5 were meta-analyzed with the European Alzheimer's Disease Biobank (EADB) (n=20,301 cases; 21,839 controls) (stage 2 combined IGAP and EADB). An expanded meta-analysis was performed using a GWAS of parental AD/dementia history in the UK Biobank (UKBB) (n=35,214 cases; 180,791 controls) (stage 3 combined IGAP, EADB, and UKBB). Common variant (MAF≥0.01) associations were identified for 29 loci in stage 2, including novel genome-wide significant associations at TSPAN14 (P=2.33×10-12), SHARPIN (P=1.56×10-9), and ATF5/SIGLEC11 (P=1.03[mult]10-8), and newly significant associations without using AD proxy cases in MTSS1L/IL34 (P=1.80×10-8), APH1B (P=2.10×10-13), and CLNK (P=2.24×10-10). Rare variant (MAF<0.01) associations with genome-wide significance in stage 2 included multiple variants in APOE and TREM2, and a novel association of a rare variant (rs143080277; MAF=0.0054; P=2.69×10-9) in NCK2, further strengthened with the inclusion of UKBB data in stage 3 (P=7.17×10-13). Single-nucleus sequence data shows that NCK2 is highly expressed in amyloid-responsive microglial cells, suggesting a role in LOAD pathology.


2017 ◽  
Author(s):  
Sourena Soheili-Nezhad

All drug trials of the Alzheimer's disease (AD) have failed to slow the progression of dementia in phase III studies, and the most effective therapeutic strategy remains controversial due to the poorly understood disease mechanisms. For AD drug design, amyloid beta (Aβ) and its cascade have been the primary focus since decades ago, but mounting evidence indicates that the underpinning molecular pathways of AD are more complex than the classical reductionist models. Several genome-wide association studies (GWAS) have recently shed light on dark aspects of AD from a hypothesis-free perspective. Here, I use this novel insight to suggest that the amyloid cascade hypothesis may be a wrong model for AD therapeutic design. I review 23 novel genetic risk loci and show that, as a common theme, they code for receptor proteins and signal transducers of cell adhesion pathways, with clear implications in synaptic development, maintenance, and function. Contrary to the Aβ-based interpretation, but further reinforcing the unbiased genome-wide insight, the classical hallmark genes of AD including the amyloid precursor protein (APP), presenilins (PSEN), and APOE also take part in similar pathways of growth cone adhesion and contact-guidance during brain development. On this basis, I propose that a disrupted synaptic adhesion signaling nexus, rather than a protein aggregation process, may be the central point of convergence in AD mechanisms. By an exploratory bioinformatics analysis, I show that synaptic adhesion proteins are encoded by largest known human genes, and these extremely large genes may be vulnerable to DNA damage accumulation in aging due to their mutational fragility. As a prototypic example and an immediately testable hypothesis based on this argument, I suggest that mutational instability of the large Lrp1b tumor suppressor gene may be the primary etiological trigger for APOE-dab1 signaling disruption in late-onset AD. In conclusion, the large gene instability hypothesis suggests that evolutionary forces of brain complexity have led to emergence of large and fragile synaptic genes, and these unstable genes are the bottleneck etiology of aging disorders including senile dementias. A paradigm shift is warranted in AD prevention and therapeutic design.


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