Literature DB >> 36213312

Improving risk indexes for Alzheimer's disease and related dementias for use in midlife.

Aaron Reuben1, Terrie E Moffitt1,2,3,4,5, Wickliffe C Abraham6, Antony Ambler4, Maxwell L Elliott1, Ahmad R Hariri1, Honalee Harrington1, Sean Hogan7, Renate M Houts1, David Ireland7, Annchen R Knodt1, Joan Leung8, Amber Pearson9,10, Richie Poulton7, Suzanne C Purdy11, Sandhya Ramrakha7, Line J H Rasmussen12, Karen Sugden1, Peter R Thorne11,13,14, Benjamin Williams1, Graham Wilson7,15, Avshalom Caspi1,2,3,4,5.   

Abstract

Knowledge of a person's risk for Alzheimer's disease and related dementias (ADRDs) is required to triage candidates for preventive interventions, surveillance, and treatment trials. ADRD risk indexes exist for this purpose, but each includes only a subset of known risk factors. Information missing from published indexes could improve risk prediction. In the Dunedin Study of a population-representative New Zealand-based birth cohort followed to midlife (N = 938, 49.5% female), we compared associations of four leading risk indexes with midlife antecedents of ADRD against a novel benchmark index comprised of nearly all known ADRD risk factors, the Dunedin ADRD Risk Benchmark (DunedinARB). Existing indexes included the Cardiovascular Risk Factors, Aging, and Dementia index (CAIDE), LIfestyle for BRAin health index (LIBRA), Australian National University Alzheimer's Disease Risk Index (ANU-ADRI), and risks selected by the Lancet Commission on Dementia. The Dunedin benchmark was comprised of 48 separate indicators of risk organized into 10 conceptually distinct risk domains. Midlife antecedents of ADRD treated as outcome measures included age-45 measures of brain structural integrity [magnetic resonance imaging-assessed: (i) machine-learning-algorithm-estimated brain age, (ii) log-transformed volume of white matter hyperintensities, and (iii) mean grey matter volume of the hippocampus] and measures of brain functional integrity [(i) objective cognitive function assessed via the Wechsler Adult Intelligence Scale-IV, (ii) subjective problems in everyday cognitive function, and (iii) objective cognitive decline measured as residualized change in cognitive scores from childhood to midlife on matched Weschler Intelligence scales]. All indexes were quantitatively distributed and proved informative about midlife antecedents of ADRD, including algorithm-estimated brain age (β's from 0.16 to 0.22), white matter hyperintensities volume (β's from 0.16 to 0.19), hippocampal volume (β's from -0.08 to -0.11), tested cognitive deficits (β's from -0.36 to -0.49), everyday cognitive problems (β's from 0.14 to 0.38), and longitudinal cognitive decline (β's from -0.18 to -0.26). Existing indexes compared favourably to the comprehensive benchmark in their association with the brain structural integrity measures but were outperformed in their association with the functional integrity measures, particularly subjective cognitive problems and tested cognitive decline. Results indicated that existing indexes could be improved with targeted additions, particularly of measures assessing socioeconomic status, physical and sensory function, epigenetic aging, and subjective overall health. Existing premorbid ADRD risk indexes perform well in identifying linear gradients of risk among members of the general population at midlife, even when they include only a small subset of potential risk factors. They could be improved, however, with targeted additions to more holistically capture the different facets of risk for this multiply determined, age-related disease.
© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.

Entities:  

Keywords:  Alzheimer’s disease; dementia; modifiable risk factors; preventive medicine; risk index

Year:  2022        PMID: 36213312      PMCID: PMC9535507          DOI: 10.1093/braincomms/fcac223

Source DB:  PubMed          Journal:  Brain Commun        ISSN: 2632-1297


  46 in total

Review 1.  Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

Authors:  James H Cole; Katja Franke
Journal:  Trends Neurosci       Date:  2017-10-23       Impact factor: 13.837

2.  The 9 year cognitive decline before dementia of the Alzheimer type: a prospective population-based study.

Authors:  Hélène Amieva; Hélène Jacqmin-Gadda; Jean-Marc Orgogozo; Nicolas Le Carret; Catherine Helmer; Luc Letenneur; Pascale Barberger-Gateau; Colette Fabrigoule; Jean-François Dartigues
Journal:  Brain       Date:  2005-03-17       Impact factor: 13.501

3.  Predicting cognitive decline: a dementia risk score vs. the Framingham vascular risk scores.

Authors:  Sara Kaffashian; Aline Dugravot; Alexis Elbaz; Martin J Shipley; Séverine Sabia; Mika Kivimäki; Archana Singh-Manoux
Journal:  Neurology       Date:  2013-04-02       Impact factor: 9.910

4.  Association between midlife dementia risk factors and longitudinal brain atrophy: the PREVENT-Dementia study.

Authors:  John T O'Brien; Michael J Firbank; Karen Ritchie; Katie Wells; Guy B Williams; Craig W Ritchie; Li Su
Journal:  J Neurol Neurosurg Psychiatry       Date:  2019-12-05       Impact factor: 10.154

5.  Why do trials for Alzheimer's disease drugs keep failing? A discontinued drug perspective for 2010-2015.

Authors:  Dev Mehta; Robert Jackson; Gaurav Paul; Jiong Shi; Marwan Sabbagh
Journal:  Expert Opin Investig Drugs       Date:  2017-06       Impact factor: 6.206

6.  A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial.

Authors:  Tiia Ngandu; Jenni Lehtisalo; Alina Solomon; Esko Levälahti; Satu Ahtiluoto; Riitta Antikainen; Lars Bäckman; Tuomo Hänninen; Antti Jula; Tiina Laatikainen; Jaana Lindström; Francesca Mangialasche; Teemu Paajanen; Satu Pajala; Markku Peltonen; Rainer Rauramaa; Anna Stigsdotter-Neely; Timo Strandberg; Jaakko Tuomilehto; Hilkka Soininen; Miia Kivipelto
Journal:  Lancet       Date:  2015-03-12       Impact factor: 79.321

7.  Predictive Value of Odor Identification for Incident Dementia: The Shanghai Aging Study.

Authors:  Ding Ding; Zhenxu Xiao; Xiaoniu Liang; Wanqing Wu; Qianhua Zhao; Yang Cao
Journal:  Front Aging Neurosci       Date:  2020-08-26       Impact factor: 5.750

8.  The Dunedin Multidisciplinary Health and Development Study: overview of the first 40 years, with an eye to the future.

Authors:  Richie Poulton; Terrie E Moffitt; Phil A Silva
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2015-04-03       Impact factor: 4.328

9.  Clustering of health, crime and social-welfare inequality in 4 million citizens from two nations.

Authors:  Avshalom Caspi; Barry J Milne; Terrie E Moffitt; Leah S Richmond-Rakerd; Stephanie D'Souza; Signe Hald Andersen; Sean Hogan; Renate M Houts; Richie Poulton; Sandhya Ramrakha
Journal:  Nat Hum Behav       Date:  2020-01-20

10.  Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy.

Authors:  Maxwell L Elliott; Avshalom Caspi; Renate M Houts; Antony Ambler; Jonathan M Broadbent; Robert J Hancox; HonaLee Harrington; Sean Hogan; Ross Keenan; Annchen Knodt; Joan H Leung; Tracy R Melzer; Suzanne C Purdy; Sandhya Ramrakha; Leah S Richmond-Rakerd; Antoinette Righarts; Karen Sugden; W Murray Thomson; Peter R Thorne; Benjamin S Williams; Graham Wilson; Ahmad R Hariri; Richie Poulton; Terrie E Moffitt
Journal:  Nat Aging       Date:  2021-03-15
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