The Brain Health Platform: Combining Resilience,Vulnerability,and Performance to Assess Brain Health and Risk of Alzheimer’s Disease and Related Disorders
Restricted accessResearch articleFirst published online December 6, 2022
The Brain Health Platform: Combining Resilience,Vulnerability,and Performance to Assess Brain Health and Risk of Alzheimer’s Disease and Related Disorders
It is difficult to assess brain health status and risk of cognitive impairment, particularly at the initial evaluation. To address this, we developed the Brain Health Platform to quantify brain health and identify Alzheimer’s disease and related disorders (ADRD) risk factors by combining a measure of brain health: the Resilience Index (RI), a measure of risk of ADRD; the Vulnerability Index (VI); and the Number-Symbol Coding Task (NSCT), a measure of brain performance.
Objective:
The Brain Health Platform is intended to be easily and quickly administered, providing an overview of a patient’s risk of developing future impairment based on modifiable and non-modifiable factors as well as current cognitive performance.
Methods:
This cross-sectional study comprehensively evaluated 230 participants (71 controls, 71 mild cognitive impairment, 88 ADRD). VI and RI scores were derived from physical assessments, lifestyle questionnaires, demographics, medical history, and neuropsychological examination including the NSCT.
Results:
Individuals with abnormal scores were 95.7% likely to be impaired, with a misclassification rate of 9.7%. The combined model had excellent discrimination (AUC:0.923±0.053; p < 0.001), performing better than the Montreal Cognitive Assessment.
Conclusion:
The Brain Health Platform combines measures of resilience, vulnerability, and performance to provide a cross-sectional snapshot of overall brain health. The Brain Health Platform can effectively and accurately identify even the very mildest impairments due to ADRD, leveraging brief yet powerful and actionable indices of brain health and risk that could be used to develop personalized, precision medicine-like interventions.
GalvinJE, ChrisphonteS, ChangL-C (2021) Medical and social determinants of brain health and dementia in a multicultural community cohort of older adults. J Alzheimers Dis84, 1563–1576.
6.
ToleaMI, MorrisJC, GalvinJE (2015) Longitudinal associations between physical and cognitive performance among community-dwelling older adults. PLoS One10, e0122878.
7.
ToleaMI, GalvinJE (2016) Relationship between mobility dysfunction staging and global cognitive performance. Alzheimer Dis Assoc Disord30, 230–236.
8.
ToleaMI, ChrisphonteS, GalvinJE (2020) The effect of sociodemographics, physical function, and mood on dementia screening in a multicultural cohort. Clin Interv Aging15, 2249–2263.
9.
GalvinJE, PowlishtaKK, WilkinsK, McKeelDW, XiongC, GrantE, StorandtM, MorrisJC (2005) Predictors of preclinical Alzheimer disease and dementia: A clinicopathologic study. Arch Neurol62, 758.
10.
ToleaMI, HeoJ, ChrisphonteS, GalvinJE (2021) A modified CAIDE risk score as a screening tool for cognitive impairment in older adults. J Alzheimers Dis82, 1755–1768.
11.
GalvinJE, ToleaMI, MooreC, ChrisphonteS (2020) The Number Symbol Coding Task: A brief measure of executive function to detect dementia and cognitive impairment. PLoS One15, e0242233.
12.
GalvinJE, ToleaMI, RosenfeldA, ChrisphonteS (2020) The Quick Physical Activity Rating (QPAR) scale: A brief assessment of physical activity in older adults with and without cognitive impairment. PLoS One15, e0241641.
13.
GalvinJE, ToleaMI, ChrisphonteS (2021) The Cognitive & Leisure Activity Scale (CLAS): A new measure to quantify cognitive activities in older adults with and without cognitive impairment. Alzheimers Dement7, e12134.
14.
InnisAD, ToleaMI, GalvinJE (2021) The effect of baseline patient and caregiver mindfulness on dementia outcomes. J Alzheimers Dis79, 1345–1367.
15.
JoshiMS, GalvinJE (2022) Cognitive resilience in brain health and dementia research. J Alzheimers Dis90, 461–473.
16.
GalvinJE, KleimanMJ, ChrisphonteS, CohenI, DislaS, GalvinCB, GreenfieldKK, MooreC, RawnS, RiccioML, RosenfeldA, SimonJ, WalkerM, ToleaMI (2021) The Resilience Index: A quantifiable measure of brain health and risk of cognitive impairment and dementia. J Alzheimers Dis84, 1729–1746.
17.
KleimanMJ, GalvinJE (2021) The Vulnerability Index: A weighted measure of dementia and cognitive impairment risk. Alzheimers Dement (Amst)13, e12249.
18.
KivipeltoM, NganduT, LaatikainenT, WinbladB, SoininenH, TuomilehtoJ (2006) Risk score for the prediction of dementia risk in 20 years among middle aged people: A longitudinal, population-based study. Lancet Neurol5, 735–741.
19.
GalvinJE (2018) Using informant and performance screening methods to detect mild cognitive impairment and dementia. Curr Geriatr Rep7, 19–25.
20.
GalvinJE, AisenP, LangbaumJB, RodriguezE, SabbaghM, StefanacciR, SternRA, VasseyEA, de WildeA, WestN, RubinoI (2020) Early stages of Alzheimer’s disease: Evolving the care team for optimal patient management. Front Neurol11, 592302.
21.
PorsteinssonAP, IsaacsonRS, KnoxS, SabbaghMN, RubinoI (2021) Diagnosis of early Alzheimer’s disease: Clinical practice in 2021. J Prev Alzheimers Dis8, 371–386.
22.
SabbaghMN, BoadaM, BorsonS, ChilukuriM, DuboisB, IngramJ, IwataA, PorsteinssonAP, PossinKL, RabinoviciGD, VellasB, ChaoS, VergalloA, HampelH (2020) Early detection of mild cognitive impairment (MCI) in primary care. J Prev Alzheimers Dis7, 165–170.
23.
JohnsonDK, StorandtM, MorrisJC, GalvinJE (2009) Longitudinal study of the transition from healthy aging to Alzheimer disease. Arch Neurol66, 1254–1259.
24.
AbulafiaC, FiorentiniL, LoewensteinDA, Curiel-CidR, SevleverG, NemeroffCB, VillarrealMF, VigoDE, GuinjoanSM (2019) Executive functioning in cognitively normal middle-aged offspring of late-onset Alzheimer’s disease patients. J Psychiatr Res112, 23–29.
25.
JenkinsLM, KoganA, MalinabM, IngoC, SedaghatS, BryanNR, YaffeK, ParrishTB, NemethAJ, Lloyd-JonesDM, LaunerLJ, WangL, SorondF (2021) Blood pressure, executive function, and network connectivity in middle-aged adults at risk of dementia in late life. Proc Natl Acad Sci U S A118, e2024265118.
26.
JacobsDM, ThomasRG, SalmonDP, JinS, FeldmanHH, CotmanCW, BakerLD, Alzheimer’s Disease Cooperative Study EXERT Study Group, Alzheimer’s Disease Neuroimaging Initiative (2020) Development of a novel cognitive composite outcome to assess therapeutic effects of exercise in the EXERT trial for adults with MCI: The ADAS-Cog-Exec. Alzheimers Dement (N Y)6, e12059.
27.
AliDG, BahraniAA, BarberJM, El KhouliRH, GoldBT, HarpJP, JiangY, WilcockDM, JichaGA (2022) Amyloid-PET levels in the precuneus and posterior cingulate cortices are associated with executive function scores in preclinical Alzheimer’s disease prior to overt global amyloid positivity. J Alzheimers Dis88, 1127–1135.
28.
WangY-L, ChenJ, DuZ-L, WengH, ZhangY, LiR, JiaZ, SunM, JiangJ, WangF-Z, XuJ, Alzheimer’s Disease Neuroimaging Initiative (2021) Plasma p-tau181 level predicts neurodegeneration and progression to Alzheimer’s dementia: A longitudinal study. Front Neurol12, 695696.
29.
AlbertMS, DeKoskyST, DicksonD, DuboisB, FeldmanHH, FoxNC, GamstA, HoltzmanDM, JagustWJ, PetersenRC, SnyderPJ, CarrilloMC, ThiesB, PhelpsCH, TheisB, PhelpsCH (2011) The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on. Alzheimers Dement7, 270–279.
30.
McKhannGM, KnopmanDS, ChertkowH, HymanBT, JackCR, KawasCH, KlunkWE, KoroshetzWJ, ManlyJJ, MayeuxR, MohsRC, MorrisJC, RossorMN, ScheltensP, CarrilloMC, ThiesB, WeintraubS, PhelpsCH (2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement7, 263–269.
31.
MorrisJC (1993) The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology43, 2412–2412.
32.
GalvinJE (2015) The Quick Dementia Rating System (QDRS): A rapid dementia stagingtool. Alzheimers Dement (Amst)1, 249–259.
33.
BeeklyDL, RamosEM, LeeWW, DeitrichWD, JackaME, WuJ, HubbardJL, KoepsellTD, MorrisJC, KukullWA, CentersTNAD (2007) The National Alzheimer’s Coordinating Center (NACC) Database: The Uniform Data Set. Alzheimer Dis Assoc Disord21, 249–258.
34.
WeintraubS, BesserL, DodgeHH, TeylanM, FerrisS, GoldsteinFC, GiordaniB, KramerJ, LoewensteinD, MarsonD, MungasD, SalmonD, Welsh-BohmerK, ZhouXH, ShirkSD, AtriA, KukullWA, PhelpsC, MorrisJC (2018) Version 3 of the Alzheimer Disease Centers’ Neuropsychological Test Battery in the Uniform Data Set (UDS). Alzheimer Dis Assoc Disord32, 10–17.
35.
NasreddineZS, PhillipsNA, BédirianV, CharbonneauS, WhiteheadV, CollinI, CummingsJL, ChertkowH (2005) The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. J Am Geriatr Soc53, 695–699.
36.
ShapiroAM, BenedictRHB, SchretlenD, BrandtJ (1999) Construct and concurrent validity of the Hopkins Verbal Learning Test – Revised. Clin Neuropsychol13, 348–358.
37.
SnaithRP (2003) The Hospital Anxiety and Depression Scale. Health Qual Life Outcomes1, 29.
38.
GalvinJE, RoeCM, PowlishtaKK, CoatsMA, MuichSJ, GrantE, MillerJP, StorandtM, MorrisJC (2005) The AD8: A brief informant interview to detect dementia. Neurology65, 559–564.
39.
GalvinJE, ToleaMI, ChrisphonteS (2020) Using a patient-reported outcome to improve detection of cognitive impairment and dementia: The patient version of the Quick Dementia Rating System (QDRS). PLoS One15, e0240422.
40.
WilkinsCH, RoeCM, MorrisJC (2010) A brief clinical tool to assess physical function: The mini physical performance test. Arch Gerontol Geriatr50, 96–100.
41.
FriedLP, TangenCM, WalstonJ, NewmanAB, HirschC, GottdienerJ, SeemanT, TracyR, KopWJ, BurkeG, McBurnieMA (2001) Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci56, M146–M157.
42.
RosenWG, TerryRD, FuldPA, KatzmanR, PeckA (1980) Pathological verification of ischemic score in differentiation of dementias. Ann Neurol7, 486–488.
43.
PfefferRI, KurosakiTT, HarrahCH, ChanceJM, FilosS (1982) Measurement of functional activities in older adults in the community. J Gerontol37, 323–329.
44.
KauferDI, CummingsJL, KetchelP, SmithV, MacMillanA, ShelleyT, LopezOL, DeKoskyST (2000) Validation of the NPI-Q, a brief clinical form of the Neuropsychiatric Inventory. J Neuropsychiatry Clin Neurosci12, 233–239.
45.
McKeithIG, FermanTJ, ThomasAJ, BlancF, BoeveBF, FujishiroH, KantarciK, MuscioC, O’BrienJT, PostumaRB, AarslandD, BallardC, BonanniL, DonaghyP, EmreM, GalvinJE, GalaskoD, GoldmanJG, GompertsSN, HonigLS, IkedaM, LeverenzJB, LewisSJG, MarderKS, MasellisM, SalmonDP, TaylorJP, TsuangDW, WalkerZ, TiraboschiP (2020) Research criteria for the diagnosis of prodromal dementia with Lewy bodies. Neurology94, 743–755.
RossDE, OchsAL, TateDF, TokacU, SeabaughJ, AbildskovTJ, BiglerED (2018) High correlations between MRI brain volume measurements based on NeuroQuant® and FreeSurfer. Psychiatry Res Neuroimaging278, 69–76.
49.
PerssonK, BarcaML, CavallinL, Br{ækhusA, KnapskogA-B, SelbækG, EngedalK (2018) Comparison of automated volumetry of the hippocampus using NeuroQuant® and visual assessment of the medial temporal lobe in Alzheimer’s disease. Acta Radiol59, 997–1001.
50.
HeisterD, BrewerJB, MagdaS, BlennowK, McEvoyLK, Initiative F the ADN (2011) Predicting MCI outcome with clinically available MRI and CSF biomarkers. Neurology77, 1619–1628.
51.
DhanaK, EvansDA, RajanKB, BennettDA, MorrisMC (2020) Healthy lifestyle and the risk of Alzheimer dementia: Findings from 2 longitudinal studies. Neurology95, e374–e383.
52.
LiMJ, BlackDS, GarlandEL (2016) The Applied Mindfulness Process Scale (AMPS): A process measure for evaluating mindfulness-based interventions. Pers Individ Dif93, 6–15.
53.
KleimanMJ, ChangL-C, GalvinJE (2022) The Brain Health Platform. Comprehensive Center for Brain Health. http://vi-ri-nsct.herokuapp.com/.
54.
VallatR (2018) Pingouin: Statistics in Python. J Open Source Softw3, 1026.
KeanyE (2020) BorutaShap: A wrapper feature selection method which combines the Boruta feature selection algorithm with Shapley values. Zenodo. https://doi.org/10.5281/zenodo.4247618
58.
LundbergS, LeeS-I (2017) A Unified Approach to Interpreting Model Predictions. Advances in Neural Information Processing Systems 30 (NIPS 2017)16, 426–430.
59.
KleimanMJ, BarenholtzE, GalvinJE (2021) Screening for early-stage Alzheimer’s disease using optimized feature sets and machine learning. J Alzheimers Dis81, 355–366.
60.
De RoeckEE, De DeynPP, DierckxE, EngelborghsS (2019) Brief cognitive screening instruments for early detection of Alzheimer’s disease: A systematic review. Alzheimers Res Ther11, 1–14.
