Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Autosomal dominant Alzheimer's Disease (ADAD) represents around 0.5% of all AD cases, and is caused by mutations in PSEN1, PSEN2 and APP genes. Gene expression studies can be useful for unravelling the physiopathology of AD and identifying potential biomarkers. However, most studies are focused on late-onset AD (LOAD), and mainly on brain tissue or immune cells. Preliminary data from our group showed 9 common differentially expressed genes (DEGs) both in brain tissue and lymphoblastoid cell lines in ADAD versus healthy controls (AMMERCR1L, FMR1, FXYD5, PRR3, RNU2.1, SCARNA2, SLC35A1, TCEAL8, TMEM184B). We aim to investigate these DEGs along with 3 AD relevant genes (APP, PSEN1 and MAPT) in whole blood of ADAD with the goal to explore new potential biomarkers.
Method: Our cohort (N = 69) consisted of ADAD symptomatic mutation carriers (SMC; N = 19), asymptomatic mutation carriers (AMC; N = 18) and healthy non carriers (CTRL; N = 32). RNA was extracted from whole blood and relative gene expression was determined by RT-qPCR and ΔΔCt method. Permutation tests were used to determine the differential gene expression between groups. Additionally, a correlation analysis was performed between estimated years of onset (for AMC) or years since onset (for SMC) and relative expression.
Result: DEGs were mainly down-regulated in ADAD with respect to CTRL, except for FXYD5 and MAPT, which were up-regulated. When comparing ADAD mutation carriers versus CTRL the significant genes were APP (p = 0.045), FXYD5 (p = 0.018), MAPT (p = 0.041), PSEN1 (p = 5e-4), SCARNA2 (p = 0.042) and TMEM184B (p = 0.0042) (Fig. 1). Then, we compared AMC versus CTRL and SMC versus CTRL and found two DEGs in both comparisons: FXYD5 (p = 0.015; p = 0.033) and MAPT (p = 0.015; p = 0.034). In AMC group we also found these DEGs: FMR1 (p = 0.011), PRR3 (0.029), PSEN1 (p = 2e-4), SCARNA2 (p = 0.027) and TMEM184B (p = 5e-4) (Fig. 2). Results showed a significant negative correlation for RNU2.1 (p = 0.016) and PRR3 (p = 0.029) between relative expression and years since onset in SMC (Fig. 3).
Conclusion: Mutation carriers show some DEGs in whole blood, even in the asymptomatic stage. FXYD5 and MAPT genes show a consistent up-regulation in both SMC and AMC, suggesting it could be further validated as a possible genetic biomarker in whole blood of ADAD.
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Source |
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http://dx.doi.org/10.1002/alz.089842 | DOI Listing |
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