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

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.

Social isolation from childhood to mid-adulthood: is there an association with older brain age?

“…For example, it has been found that gray matter volume, a specific measure of brain health, partly mediates the longitudinal association between social isolation and cognitive function (Shen et al, 2022). Finally, we may speculate that there are implications for understanding dementia, a pathological form of cognitive dysfunction, given that a lack of social contact has been associated with elevated dementia risk (see reviews by: Desai, John, Stott, & Charlesworth, 2020; Kuiper et al, 2015; Penninkilampi, Casey, Singh, & Brodaty, 2018; Ren et al, 2023; and Sommerlad, Ruegger, Singh-Manoux, Lewis, & Livingston, 2018), and that older brain age has been considered to be a biomarker for (Gaser, Franke, Klöppel, Koutsouleris, & Sauer, 2013; Wang et al, 2019) and midlife antecedent of (Reuben et al, 2022) dementia.…”

Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth‐cohort geographic analyses

“…Outcome Set 1: Dementia risk‐factor index included five indexes which are suitable for use in midlife (Supplementary Table S3): 3 The Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) index 28 ; The LIfestyle for BRAin health (LIBRA) index 29 ; The Australian National University Alzheimer's Disease Risk Index (ANU‐ADRI) 30 ; and Modifiable risk factors selected by the Lancet Commission on Dementia (Lancet) 31 ; and A comprehensive midlife index, the Dunedin ADRD Risk Benchmark (DunedinARB), comprised of 48 putative ADRD risk indicators organized into 10 conceptually distinct risk domains (Figure 1; Supplementary Table S4). 3 …”

“…Subjective Overall Health risk includes self, informant, and research‐worker ratings of Study member overall health. Figure from Reuben et al 3 . Details on the individual risk factors and indicators are provided in Supplementary Table 4.…”

“…Assessments were carried out at birth and ages 3, 5, 7, 9, 11, 13, 15, 18, 21, 26, 32, 38, and, most Outcome Set 1: Dementia risk-factor index included five indexes which are suitable for use in midlife (Supplementary Table S3): S4). 3 These indexes are checklists that aggregate risk factors known to increase dementia risk because they are either robustly predictive of dementia (e.g., hearing impairment, a history of depression) or are believed to mechanistically precipitate or enhance disease processes (e.g., apolipoprotein E [APOE] genotype status, heart disease). Figure 1 and Supplementary Figure S1 present the risk factors captured in the DunedinARB and the four other indexes, respectively.…”

“…After accumulating evidence that individual behaviors antedate lower ADRD risk (e.g., eating a Mediterranean diet, pursuing daily physical activity), 3 attention has shifted to the spaces in which individual behaviors occur 4–6 . The neighborhoods in which older adults live constrain and influence the social, recreational, and dietary choices they make on a daily basis, as well as determine the physical/chemical stressors to which they are exposed, including air and water pollutants, noise, heat, and environmental disasters 4–6 …”