scholarly journals Are developmental learning disorders risk factors for late‐onset Alzheimer's disease?

2021 ◽  
Vol 17 (S6) ◽  
Author(s):  
Marina Leiman ◽  
Salvador Martín Guinjoan ◽  
Luis Ignacio Brusco ◽  
Mirta Fabiana Villarreal ◽  
Leticia Fiorentini
2013 ◽  
Vol 9 ◽  
pp. P551-P552
Author(s):  
Ardeshir Omoumi ◽  
Alice Fok ◽  
Talitha Greenwood ◽  
Dessa Sadovnick ◽  
Howard Feldman ◽  
...  

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Meredith N. Braskie ◽  
John M. Ringman ◽  
Paul M. Thompson

Late onset Alzheimer's disease (AD) is moderately to highly heritable. Apolipoprotein E alleleε4 (APOE4) has been replicated consistently as an AD risk factor over many studies, and recently confirmed variants in other genes such asCLU, CR1, andPICALMeach increase the lifetime risk of AD. However, much of the heritability of AD remains unexplained. AD is a complex disease that is diagnosed largely through neuropsychological testing, though neuroimaging measures may be more sensitive for detecting the incipient disease stages. Difficulties in early diagnosis and variable environmental contributions to the disease can obscure genetic relationships in traditional case-control genetic studies. Neuroimaging measures may be used as endophenotypes for AD, offering a reliable, objective tool to search for possible genetic risk factors. Imaging measures might also clarify the specific mechanisms by which proposed risk factors influence the brain.


2004 ◽  
Vol 25 ◽  
pp. S25-S26
Author(s):  
Alison M. Goate ◽  
Petra Nowotny ◽  
Tony Hinrichs ◽  
Scott Smemo ◽  
Keoni Kawe ◽  
...  

2020 ◽  
Author(s):  
Neha Raghavan ◽  
Sanjeev Sariya ◽  
Annie Lee ◽  
Yizhe Gao ◽  
Dolly Reyes-Dumeyer ◽  
...  

INTRODUCTION: Late-onset Alzheimer's disease (AD) frequently co-occurs with cerebrovascular disease. We hypothesized that interactions between genes and cerebrovascular risk factors (CVRFs) contribute to AD risk. METHODS: Participants age 65 years or older from five multi-ethnic cohorts (N=14,669) were included in genome-wide association meta-analyses for AD including an interaction factor for a CVRF score created from body mass index, hypertension, heart disease, and diabetes. Significant gene level results were substantiated using neuropathological and gene expression data. RESULTS: At the gene-level, FMNL2 interacted with the CVRF score to significantly modify AD risk (p= 7.7x10-7). A SNP within FRMD4B, rs1498837, was nominally significant (p=7.95x10-7). Increased FMNL2 expression was significantly associated with brain infarcts and AD. DISCUSSION: FMNL2 is highly expressed in the brain and has been associated with ischemic stroke and failures in endosomal trafficking, a major pathway in AD pathology. The results highlight an interaction between FMNL2 and CVRFs on AD susceptibility.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 641-642
Author(s):  
Adrienne Wang ◽  
Ming Yang ◽  
Cecilia Fitzgerald-Cook ◽  
Ben Harrison ◽  
Akimi Green ◽  
...  

Abstract Despite significant progress in identifying risk factors for late-onset Alzheimer’s Disease (LOAD), much of the variance in disease pathogenesis remains unexplained, likely due to the contribution of many genes of small effect size. Model organisms such as Drosophila Melanogaster exhibit conservation in both disease-causing genes and cellular processes implicated in Alzheimer’s Disease (AD), offering a genetically tractable model that can be statistically leveraged to identify causal variants. Here, we combine a Drosophila model of AD with the Drosophila Genetic Reference Panel (DGRP), a model of natural variation consisting of over 200 fully sequenced, isogenic lines derived from a wild-caught population. Expression of two proteins closely associated with AD pathogenesis, A□42 and Tau, in the Drosophila eye results in a “rough eye” phenotype, an easily quantifiable phenotype caused by degeneration of the ommatidial array. By quantifying the degree of A□42- and Tau-mediated degeneration across 164 lines of the DGRP and using a gene-based approach to map associations, we have identified and validated a subset of naturally occurring modifiers of degeneration in Drosophila. Enrichment analysis reveals that the set of genes identified in our screen show significant enrichment for genes identified as significant or suggestive (4x10-6>p>2x10-11) in human GWAS studies. The results presented here provide proof-of-principal for an approach that combines the strengths of forward genetic screens in model organisms with the power of human GWAS studies to identify and validate potential risk factors that have been difficult to detect in human studies alone.


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