Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

ANU-ADRI and not Genetic Risk score predicts MCI in a cohort of older adults followed for 12 years

Shea J. Andrews, Ranmalee Eramudugolla, Jorge I. Velez, Nicolas Cherbuin, Simon Easteal, Kaarin J. Anstey
doi: https://doi.org/10.1101/070516
Shea J. Andrews
aJohn Curtin School of Medical Research, Australian National University, Canberra, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ranmalee Eramudugolla
bCentre for Research on Ageing, Health and Wellbeing, Research School of Population Health Australian National University, Canberra, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jorge I. Velez
cNeuroscience Research Group, University of Antioquia, Medellin, Colombia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicolas Cherbuin
cNeuroscience Research Group, University of Antioquia, Medellin, Colombia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Simon Easteal
aJohn Curtin School of Medical Research, Australian National University, Canberra, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kaarin J. Anstey
cNeuroscience Research Group, University of Antioquia, Medellin, Colombia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

INTRODUCTION We evaluated a risk score comprising lifestyle, medical and demographic factors (ANU-ADRI), and a genetic risk score (GRS) as predictors of Mild Cognitive Impairment (MCI).

METHODS ANU-ADRI risk scores were computed for the baseline assessment of 2,078 participants from the PATH project. Participants were assessed for clinically diagnosed MCI/Dementia and psychometric test-based MCI (MCI-TB) at 12 years of follow-up. Multi-state models estimated the odds of transitioning from cognitively normal (CN) to MCI/Dementia and MCI-TB over 12 years according to baseline ANU-ADRI and GRS.

RESULTS Higher ANU-ADRI score predicted transitioning from CN to either MCI/Dementia and MCI-TB (Hazard ratio [HR] = 1.06, 95% CI:1.04-1.09; HR = 1.06, 95% CI: 1.03-1.09), and a reduced likelihood of cognitive recovery from MCITB to CN (HR = 0.69, 95% CI: 0.49-0.98). GRS was not associated with transition to MCI/Dementia, or MCI-TB.

DISCUSSION The ANU-ADRI may be used for population-level risk assessment and screening.

Systematic Review The authors reviewed the literature using online databases e.g. (PubMed). We consulted mild cognitive impairment (MCI) and Alzheimer’s disease (AD) research detailing the use of risk factors for predicting progression from MCI and AD; and the appropriate statistical models for modelling transitions between cognitive states. These publications are appropriately cited.

Interpretation In the general population, the ANU-ADRI comprising lifestyle, medical and demographic factors is predictive of progression from normal cognition to MCI/Dementia whereas a Genetic Risk Score comprising the main Alzheimer’s risk genes is not predictive.

Future Directions Further evaluation of the ANU-ADRI as a predictor of specific MCI and dementia subtypes is required. The ANU-ADRI may be used to identify individuals indicated for risk reduction intervention and to assist clinical management and cognitive health promotion. Genetic risk scores contribute to understanding dementia etiology but apart from APOE are unlikely to be useful in screening or prevention trials.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted August 19, 2016.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
ANU-ADRI and not Genetic Risk score predicts MCI in a cohort of older adults followed for 12 years
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
ANU-ADRI and not Genetic Risk score predicts MCI in a cohort of older adults followed for 12 years
Shea J. Andrews, Ranmalee Eramudugolla, Jorge I. Velez, Nicolas Cherbuin, Simon Easteal, Kaarin J. Anstey
bioRxiv 070516; doi: https://doi.org/10.1101/070516
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
ANU-ADRI and not Genetic Risk score predicts MCI in a cohort of older adults followed for 12 years
Shea J. Andrews, Ranmalee Eramudugolla, Jorge I. Velez, Nicolas Cherbuin, Simon Easteal, Kaarin J. Anstey
bioRxiv 070516; doi: https://doi.org/10.1101/070516

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genetics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4381)
  • Biochemistry (9581)
  • Bioengineering (7087)
  • Bioinformatics (24845)
  • Biophysics (12598)
  • Cancer Biology (9952)
  • Cell Biology (14348)
  • Clinical Trials (138)
  • Developmental Biology (7945)
  • Ecology (12103)
  • Epidemiology (2067)
  • Evolutionary Biology (15985)
  • Genetics (10921)
  • Genomics (14736)
  • Immunology (9869)
  • Microbiology (23647)
  • Molecular Biology (9477)
  • Neuroscience (50839)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2681)
  • Physiology (4013)
  • Plant Biology (8655)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2391)
  • Systems Biology (6427)
  • Zoology (1346)