Dementia rates have accelerated in recent decades, yet our ability to screen for and predict who is at risk remains limited. The Montreal Cognitive Assessment (MoCA) and the Alzheimer's Disease Assessment Scale-Cog-13 item (ADAS-Cog-13) are common screeners that provide insight into early dementia progression. However, how these tools relate to biomarkers and psychological predictors before formal diagnosis is unclear.
Objective
This study examines associations between biological and psychological factors with MoCA and ADAS-Cog-13 scores to guide clinicians in selecting the most informative screener for specific dementia risk profiles.
Methods
Zero-order correlations and Classification and Regression Trees were conducted using data from the ADNI-DOD database, comprising high-risk veterans without baseline dementia.
Results
MoCA scores were primarily associated with biomarker predictors and depression, whereas ADAS-Cog-13 scores were primarily associated with post-traumatic stress disorder diagnoses.
Conclusions
Cognitive screeners tailored to brief psychological and medical histories may improve early detection of cognitive decline and Alzheimer's disease.
SatizabalCLBeiserASChourakiV, et al.Incidence of dementia over three decades in the Framingham Heart Study. N Engl J Med2016; 374: 523–532.
2.
NicholsESzoekeCEIVollsetSE, et al.Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol2019; 18: 88–106.
3.
GambergerDLavračNSrivatsaS, et al.Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer’s disease. Sci Rep2017; 7: 1–12.
4.
AndrewsMRossRMalhotraA, et al.Sleep and tau pathology in Vietnam War Veterans with preclinical and prodromal Alzheimer’s disease. J Alzheimers Dis Rep2021; 5: 41–48.
5.
van DyckCHSwansonCJAisenP, et al.Lecanemab in early Alzheimer’s disease. N Engl J Med2023; 388: 9–21.
6.
LuznyJHolmerovaIWijaP, et al.Dementia still diagnosed too late — data from the Czech Republic. Iran J Public Health2014; 43: 1436–1443.
7.
FolsteinMFFolsteinSEMcHughPR. ‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res1975; 12: 189–198.
8.
TsoiKKFChanJYCHiraiHW, et al.Cognitive tests to detect dementia: a systematic review and meta-analysis. JAMA Intern Med2015; 175: 1450–1458.
9.
NasreddineZSPhillipsNABédirianV, et al.The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc2005; 53: 695–699.
10.
RosenWGMohsRCDavisKL. A new rating scale for Alzheimer’s disease. Am J Psychiatry1984; 141: 1356–1364.
11.
SchragASchottJM. What is the clinically relevant change on the ADAS-Cog?J Neurol Neurosurg Psychiatry2012; 83: 171–173.
12.
PodhornaJKrahnkeTShearM, et al.Alzheimer’s Disease Assessment Scale–Cognitive subscale variants in mild cognitive impairment and mild Alzheimer’s disease: change over time and the effect of enrichment strategies. Alzheimers Res Ther2016; 8: 8.
13.
CullenBO’NeillBEvansJJ, et al.A review of screening tests for cognitive impairment. J Neurol Neurosurg Psychiatry2007; 78: 790–799.
14.
RyanJFransquetPWrigglesworthJ, et al.Phenotypic heterogeneity in dementia: a challenge for epidemiology and biomarker studies. Front Public Health2018; 6: 181.
15.
LiangC-SLiD-JYangF-C, et al.Mortality rates in Alzheimer’s disease and non-Alzheimer’s dementias: a systematic review and meta-analysis. Lancet Healthy Longev2021; 2: e479–e488.
16.
AlzheimerA. Uber eine eigenartige Erkrankung der Hirnrinde. Zentralbl Nervenh Psych1907; 18: 177–179.
17.
MastersCLSimmsGWeinmanNA, et al.Amyloid plaque core protein in Alzheimer disease and Down syndrome. Proc Natl Acad Sci U S A1985; 82: 4245–4249.
18.
HardyJSelkoeDJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science2002; 297: 353–356.
19.
Grundke-IqbalIIqbalKTungYC, et al.Abnormal phosphorylation of the microtubule-associated protein tau (tau) in Alzheimer cytoskeletal pathology. Proc Natl Acad Sci U S A1986; 83: 4913–4917.
20.
KaurPKheraAAlajangiHK, et al.Role of tau in various tauopathies, treatment approaches, and emerging role of nanotechnology in neurodegenerative disorders. Mol Neurobiol2023; 60: 1690–1720.
21.
BrierMRGordonBFriedrichsenK, et al.Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease. Sci Transl Med2016; 8: 338–366.
22.
Morishima-KawashimaMIharaY. Alzheimer’s disease: beta-Amyloid protein and tau. J Neurosci Res2002; 70: 392–401.
23.
FarrerLACupplesLAHainesJL, et al.Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA1997; 278: 1349–1356.
24.
FlavinWPHosseiniHRubertiJW, et al.Traumatic brain injury and the pathways to cerebral tau accumulation. Front Neurol2023; 14: 1239653.
25.
SobczakSOlffMRuttenB, et al.Comorbidity rates of posttraumatic stress disorder in dementia: a systematic literature review. Eur J Psychotraumatology2021; 12: 1883923.
26.
WeinerMHarveyDHayesJ, et al.Effects of traumatic brain injury and posttraumatic stress disorder on development of Alzheimer’s disease in Vietnam Veterans using the Alzheimer’s Disease Neuroimaging Initiative: preliminary report. Alzheimers Dement (N Y)2017; 3: 177–188.
27.
BittarABhattNHasanTF, et al.Neurotoxic tau oligomers after single versus repetitive mild traumatic brain injury. Brain Commun2019; 1: fcz004.
28.
DaughertyJDePadillaLSarmientoK, et al.Self-reported lifetime concussion among adults: comparison of 3 different survey questions. J Head Trauma Rehabil2020; 35: E136–E143.
29.
CloustonSADeriYDiminichE, et al.Posttraumatic stress disorder and total amyloid burden and amyloid-β 42/40 ratios in plasma: results from a pilot study of World Trade Center responders. Alzheimers Dement (Amst)2019; 11: 216.
30.
ScheinJHouleCUrganusA, et al.Prevalence of post-traumatic stress disorder in the United States: a systematic literature review. Curr Med Res Opin2021; 37: 2151–2161.
31.
MoulinetITouronEMézengeF, et al.Depressive symptoms have distinct relationships with neuroimaging biomarkers across the Alzheimer’s clinical continuum. Front Aging Neurosci2022; 14: 899158.
32.
LeeB. National, state-level, and county-level prevalence estimates of adults aged ≥18 years self-reporting a lifetime diagnosis of depression — United States, 2020. MMWR Morb Mortal Wkly Rep2023; 72: 644–650.
33.
BarthélemyNRSalvadóGSchindlerSE, et al.Highly accurate blood test for Alzheimer’s disease is similar or superior to clinical cerebrospinal fluid tests. Nat Med2024; 30: 1085–1095.
34.
HorieKSalvadóGKoppisettiRK, et al.Plasma MTBR-tau243 biomarker identifies tau tangle pathology in Alzheimer’s disease. Nat Med2025; 31: 2044–2053.
35.
LandauSMHarveyDMadisonCM, et al.Comparing predictors of conversion and decline in mild cognitive impairment. Neurology2010; 75: 230–238.
36.
MohamedAZCummingPSrourH, et al.Amyloid pathology fingerprint differentiates post-traumatic stress disorder and traumatic brain injury. Neuroimage Clin2018; 19: 716–726.
37.
MohamedAZCummingPGötzJ, et al.Tauopathy in veterans with long-term posttraumatic stress disorder and traumatic brain injury. Eur J Nucl Med Mol Imaging2019; 46: 1139–1151.
38.
LlanoDALaforetGDevanarayanV, et al.Derivation of a new ADAS-cog composite using tree-based multivariate analysis: prediction of conversion from mild cognitive impairment to Alzheimer disease. Alzheimer Dis Assoc Disord2011; 25: 73–84.
39.
WeinerMWVeitchDPHayesJ, et al.Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer’s disease in veterans, using the Alzheimer’s Disease Neuroimaging Initiative. Alzheimers Dement2014; 10: S226–S235.
40.
BamfordARAdamsJNKimS, et al.The amyloid beta 42/38 ratio as a plasma biomarker of early memory deficits in cognitively unimpaired older adults. Neurobiol Aging2024; 144: 12–18.
41.
ReinertJMartensHHuettenrauchM, et al.Aβ38 in the brains of patients with sporadic and familial Alzheimer’s disease and transgenic mouse models. J Alzheimers Dis2014; 39: 871–881.
42.
BraunGADearAJSanagavarapuK, et al.Amyloid-β peptide 37, 38 and 40 individually and cooperatively inhibit amyloid-β 42 aggregation. Chem Sci2022; 13: 2423–2439.
43.
QuarteyMONyarkoJNKMaleyJM, et al.The Aβ(1-38) peptide is a negative regulator of the Aβ(1-42) peptide implicated in Alzheimer disease progression. Sci Rep2021; 11: 431.
44.
ThabtahFOngSPeeblesD. Examining cognitive factors for Alzheimer’s disease progression using computational intelligence. Healthc Basel Switz2022; 10: 2045.
45.
GreenbergSA. The geriatric depression scale (GDS). Best Pract Nurs Care Older Adults2012; 4: 1–2.
46.
BlakeDDWeathersFWNagyLM, et al.The development of a Clinician-Administered PTSD Scale. J Trauma Stress1995; 8: 75–90.
47.
HanssonOSeibylJStomrudE, et al.CSF Biomarkers of Alzheimer’s disease concord with amyloid-β PET and predict clinical progression: a study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement2018; 14: 1470–1481.
48.
ShawLMKoreckaMLeeEB, et al.ADNI Biomarker Core: a review of progress since 2004 and future challenges. Alzheimers Dement2025; 21: e14264.
49.
ShawLMHanssonOManuilovaE, et al.Method comparison study of the Elecsys® β-Amyloid (1–42) CSF assay versus comparator assays and LC-MS/MS. Clin Biochem2019; 72: 7–14.
50.
BlennowKShawLMStomrudE, et al.Predicting clinical decline and conversion to Alzheimer’s disease or dementia using novel Elecsys Aβ(1-42), pTau and tTau CSF immunoassays. Sci Rep2019; 9: 19024.
51.
van HartenACWisteHJWeigandSD, et al.Detection of Alzheimer’s disease amyloid beta 1-42, p-tau, and t-tau assays. Alzheimers Dement2022; 18: 635–644.
52.
YamazakiYZhaoNCaulfieldTR, et al.Apolipoprotein E and Alzheimer disease: pathobiology and targeting strategies. Nat Rev Neurol2019; 15: 501–518.
53.
WhitwellJLTosakulwongNWeigandSD, et al.Relationship of APOE, age at onset, amyloid and clinical phenotype in Alzheimer disease. Neurobiol Aging2021; 108: 90–98.
54.
SaykinAJShenLYaoX, et al.Genetic studies of quantitative MCI and AD phenotypes in ADNI: progress, opportunities, and plans. Alzheimers Dement2015; 11: 792–814.
55.
TongTGrayKGaoQ, et al.Multi-modal classification of Alzheimer’s disease using nonlinear graph fusion. Pattern Recognit2017; 63: 171–181.
CummingG. The new statistics: why and how. Psychol Sci2014; 25: 7–29.
58.
JackCRKnopmanDSJagustWJ, et al.Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol2013; 12: 207–216.
59.
OssenkoppeleRJansenWJRabinoviciGD, et al.Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA2015; 313: 1939–1949.
60.
AzargoonjahromiANasiriH. CSF Amyloid-β42 associates with neuropsychiatric and cognitive outcomes via cerebral glucose metabolism. Mol Brain2025; 18: 55.
