title: Validating the role of the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI) and a genetic risk score in progression to cognitive impairment in a population-based cohort of older adults followed for 12 years.
abstract: BACKGROUND
  The number of people living with dementia is expected to exceed 130 million by 2050, which will have serious personal, social and economic implications. Employing successful intervention and treatment strategies focused on disease prevention is currently the only available approach that can have an impact on the projected rates of dementia, with risk assessment being a key component of population-based risk reduction for identification of at-risk individuals. We evaluated a risk index comprising lifestyle, medical and demographic factors (the Australian National University Alzheimer's Disease Risk Index [ANU-ADRI]), as well as a genetic risk score (GRS), for assessment of the risk of progression to mild cognitive impairment (MCI).
  
  
  METHODS
  The ANU-ADRI was computed for the baseline assessment of 2078 participants in the Personality and Total Health (PATH) Through Life project. GRSs were constructed on the basis of 25 single-nucleotide polymorphisms previously associated with Alzheimer's disease (AD). Participants were assessed for clinically diagnosed MCI and dementia as well as psychometric test-based MCI (MCI-TB) at 12 years of follow-up. Multi-state models were used to estimate 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
  A higher ANU-ADRI score was associated with increased risk of progressing from CN to both MCI and MCI-TB (HR 1.07 [95% CI 1.04-1.11]; 1.07 [1.04-1.09]). The GRS was associated with transitions from CN to dementia (HR 4.19 [95% CI 1.72-10.20), but not to MCI or MCI-TB (HR 1.05 [95% CI 0.86-1.29]; 1.03 [0.87-1.21]). Limitations of our study include that the ethnicity of participants in the PATH project is predominately Caucasian, potentially limiting the generalisability of the results of this study to people of other ethnicities. Biomarkers of AD were not available to define MCI attributable to AD. Not all the predictive variables for the ANU-ADRI were available in the PATH project.
  
  
  CONCLUSIONS
  In the general population, the ANU-ADRI, comprising lifestyle, medical and demographic factors, is associated with the risk of progression from CN to MCI, whereas a GRS comprising the main AD risk genes was not associated with this risk. The ANU-ADRI may be used for population-level risk assessment and screening.
authors.affiliation: John Curtin School of Medical Research, Australian National University, Canberra, Australia. shea.andrews@anu.edu.au.|Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health Australian National University, The Australian National University Florey, Building 54, Mills Road, Acton ACT 2601, Canberra, Australia. shea.andrews@anu.edu.au.
authors.forename: Shea J
authors.identifier: http://orcid.org/0000-0002-1921-9470
authors.initials: SJ
authors.lastname: Andrews
authors.affiliation: Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health Australian National University, The Australian National University Florey, Building 54, Mills Road, Acton ACT 2601, Canberra, Australia.
authors.forename: Ranmalee
authors.initials: R
authors.lastname: Eramudugolla
authors.affiliation: John Curtin School of Medical Research, Australian National University, Canberra, Australia.|Universidad del Norte, Barranquilla, Colombia.|Neuroscience Research Group, University of Antioquia, Medellin, Colombia.
authors.forename: Jorge I
authors.initials: JI
authors.lastname: Velez
authors.affiliation: Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health Australian National University, The Australian National University Florey, Building 54, Mills Road, Acton ACT 2601, Canberra, Australia.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Cherbuin
authors.affiliation: John Curtin School of Medical Research, Australian National University, Canberra, Australia.
authors.forename: Simon
authors.initials: S
authors.lastname: Easteal
authors.affiliation: Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health Australian National University, The Australian National University Florey, Building 54, Mills Road, Acton ACT 2601, Canberra, Australia.
authors.forename: Kaarin J
authors.initials: KJ
authors.lastname: Anstey
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics*; D001315:Australia; D020958:Australian Capital Territory / Q000453:epidemiology; D060825:Cognitive Dysfunction / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics*; D015897:Comorbidity; D018450:Disease Progression; D005260:Female; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000453:epidemiology / Q000235:genetics*; D005820:Genetic Testing / Q000379:methods; D006801:Humans; D015994:Incidence; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity
chemical_list: D005819:Genetic Markers
keywords: Alzheimer’s disease; Cognitive aging; Cohort studies; Mild cognitive impairment (MCI); Multi-state models; Risk factors in epidemiology