Distribution of samples across different demographic groups
Demographic
Total
Cognitively normal
Cognitively impaired
P-value
Total
Control (Tested as normal)
Normal cognition (Not tested, deemed normal)
Total
MCI
Mild dementia
Moderate dementia
Size, n
127
72
60
13
55
12
26
17
NA
Education group (Mode)
College graduate (35%)
College graduate (38%)
College graduate (47%)
Some college (61%)
High school graduate (35%)
College graduate (58%)
High school graduate (46%)
High school graduate (35%)
< 0.001
Sex (M/F)
67/60
41/32
36/24
5/8
27/28
8/4
11/15
8/9
0.005
Age (SD)
80.5 ± 1.6
72.2 ± 2.3
77.8 ± 2.6
80.0 ± 4.9
83.4 ± 1.9
81.1 ± 5.3
83.8 ± 2.5
84.6 ± 3.5
< 0.001
SD: standard deviation
Declarations
Acknowledgements
We acknowledge the dedication of the Framingham Heart Study participants without whom this research would not be possible. We also thank the FHS study staff for their many years of hard work in the examination of subjects and acquisition of data.
Author contributions
LZ, AN, and RHG contributed to the conception and design of the study. CMP, JAT, and HB contributed to refinement of the design of the study. AN performed the statistical analysis. LZ, AN, and RHG drafted the manuscript. CMP, JAT, HB, and RA critically reviewed the manuscript. All authors approved the final version of the manuscript.
Conflicts of interest
RA has received grant funding support from Biogen. She serves on the scientific advisory boards of Signant Health and Novo Nordisk, and is a scientific consultant to Biogen; none of which have any conflict of interest with the contents of this project. RHG reports personal fees from BrainCheck outside the submitted work and reports receiving stock options from BrainCheck.
Ethical approval
The Framingham Heart Study was approved by the Institutional Review Boards of Boston University Medical Center.
Consent to participate
All participants provided written consent to the study.
Consent to publication
Not applicable.
Availability of data and materials
Given that the text transcripts, demographic, and neuropsychological test data contain personal information, the dataset used in the current study is not publicly available. However, the scripts and tools are available upon request.
Funding
This work was partially supported by the National Library of Medicine Training Grant (T15LM007442; Authors JAT and HAB), National Science Foundation NRT Grant (1735095; Author LZ), Framingham Heart Study’s National Heart, Lung, and Blood Institute contract (N01-HC-25195; HHSN268201500001I), and NIH grants from the National Institute on Aging (AG008122, AG016495, AG033040, AG049810, AG054156, AG062109, AG068753) and Defense Advanced Research Projects Agency FA8750-16-C-0299. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Institutes of Health or the US Department of Health and Human Services. The funding agencies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Arrighi HM, Neumann PJ, Lieberburg IM, Townsend RJ.Lethality of Alzheimer disease and its impact on nursing home placement. Alzheimer Dis Assoc Disord.2010;24:90–5. [DOI] [PubMed]
Robin J, Harrison JE, Kaufman LD, Rudzicz F, Simpson W, Yancheva M.Evaluation of speech-based digital biomarkers: review and recommendations. Digit Biomark.2020;4:99–108. [DOI] [PubMed] [PMC]
Yancheva M, Fraser K, Rudzicz F.Using linguistic features longitudinally to predict clinical scores for Alzheimer’s disease and related dementias. Proceedings of SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies; 2015 Sep 11; Dresden, Germany: ACL Anthol; 2015.
Mack WJ, Freed DM, Williams BW, Henderson VW.Boston naming test: shortened versions for use in Alzheimer’s disease. J Gerontol.1992;47:P154–8. [DOI] [PubMed]
Fraser KC, Meltzer JA, Rudzicz F.Linguistic features identify Alzheimer’s disease in narrative speech. J Alzheimers Dis.2016;49:407–22. [DOI] [PubMed]
Alhanai T, Au R, Glass J.Spoken language biomarkers for detecting cognitive impairment. arXiv:1710.07551v1 [Preprint]. 2017 [cited 2020 June 15]:[8 p.]. Available from https://arxiv.org/abs/1710.07551. [DOI]
Thomas JA, Burkhardt HA, Chaudhry S, Ngo AD, Sharma S, Zhang L, et al. Assessing the utility of language and voice biomarkers to predict cognitive impairment in the Framingham Heart Study cognitive aging cohort data. J Alzheimers Dis.2020;76:905–22. [DOI] [PubMed]
Uhlmann RF, Larson EB.Effect of education on the Mini-Mental State Examination as a screening test for dementia. J Am Geriatr Soc.1991;39:876–80. [DOI] [PubMed]
Matthews F, Marioni R, Brayne C; Medical Research Council Cognitive Function and Ageing Study. Examining the influence of gender, education, social class and birth cohort on MMSE tracking over time: a population-based prospective cohort study. BMC Geriatr.2012;12:45. [DOI] [PubMed] [PMC]
Orrell M, Sahakian B.Education and dementia. BMJ.1995;310:951–2. [DOI] [PubMed] [PMC]
Buckwalter JG, Sobel E, Dunn ME, Diz MM, Henderson VW.Gender differences on a brief measure of cognitive functioning in Alzheimer’s disease. Arch Neurol.1993;50:757–60. [DOI] [PubMed]
Coravos A, Goldsack JC, Karlin DR, Nebeker C, Perakslis E, Zimmerman N, et al. Digital medicine: a primer on measurement. Digit Biomark.2019;3:31–71. [DOI] [PubMed] [PMC]
Andersson C, Johnson AD, Benjamin EJ, Levy D, Vasan RS.70-year legacy of the Framingham Heart Study. Nat Rev Cardiol.2019;16:687–98. [DOI] [PubMed]
Ash S, Moore P, Antani S, McCawley G, Work M, Grossman M.Trying to tell a tale: discourse impairments in progressive aphasia and frontotemporal dementia. Neurology.2006;66:1405–13. [DOI] [PubMed]
Lobur M, Romanyuk A, Romanyshyn M.Using NLTK for educational and scientific purposes. 2011 11th Int. Conf. Exp. Des. Appl. CAD Syst. Microelectron. CADSM, 2011, p. 426–8.
Honnibal M, Montani I.SpaCy: industrial-strength natural language processing (NLP) with Python and Cython. Explosion; 2019.
Boschi V, Catricalà E, Consonni M, Chesi C, Moro A, Cappa SF.Connected speech in neurodegenerative language disorders: a review. Front Psychol.2017;8. [DOI] [PubMed] [PMC]
Kempler D, Goral M.Language and dementia: neuropsychological aspects. Annu Rev Appl Linguist.2008;28:73–90. [DOI] [PubMed] [PMC]
A speech recognition-based solution for the automatic detection of mild cognitive impairment from spontaneous speech. Curr Alzheimer Res; c2021 (cited 2020 February 6). Available from http://www.eurekaselect.com/157444/article [DOI]
Association AP.Diagnostic and statistical manual of mental disorders (DSM-5®). American Psychiatric Assoc; 2013.
Bachman DL, Wolf PA, Linn R, Knoefel JE, Cobb J, Belanger A, et al. Prevalence of dementia and probable senile dementia of the Alzheimer type in the Framingham Study. Neurology1992;42:115–9. [DOI] [PubMed]
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM.Clinical diagnosis of Alzheimer’s disease. Neurology1984;34:939. [DOI] [PubMed]
Satizabal CL, Beiser AS, Chouraki V, Chêne G, Dufouil C, Seshadri S.Incidence of dementia over three decades in the Framingham Heart Study. N Engl J Med2016;374:523–32. [DOI] [PubMed] [PMC]
Orimaye SO, Wong JS-M, Golden KJ.Learning predictive linguistic features for Alzheimer’s disease and related dementias using verbal utterances. Proc. Workshop Comput. Linguist. Clin. Psychol. Linguist. Signal Clin. Real., Baltimore, Maryland, USA: Association for Computational Linguistics; 2014, p. 78–87.
Taylor A, Marcus M, Santorini B.The Penn Treebank: an overview. In: Abeillé A, editor. Treebanks, vol. 20, Dordrecht: Springer Netherlands; 2003, pp. 5–22. [DOI]
Hugo J, Ganguli M.Dementia and cognitive impairment: epidemiology, diagnosis, and treatment. Clin Geriatr Med.2014;30:421–42. [DOI] [PubMed] [PMC]
Jarrold W, Peintner B, Wilkins D, Vergryi D, Richey C, Gorno-Tempini ML, et al. Aided diagnosis of dementia type through computer-based analysis of spontaneous speech. Proc. Workshop Comput. Linguist. Clin. Psychol. Linguist. Signal Clin. Real., Baltimore, Maryland, USA: Association for Computational Linguistics; 2014, pp. 27–37.
Tausczik YR, Pennebaker JW.The psychological meaning of words: LIWC and computerized text analysis methods. J Lang Soc Psychol.2010;29:24–54. [DOI]
Weiner J, Schultz T.Automatic screening for transition into dementia using speech. Speech Commun. 13th ITG-Symp. 2018, pp. 1–5.
Croisile B, Ska B, Brabant MJ, Duchene A, Lepage Y, Aimard G, et al. Comparative study of oral and written picture description in patients with Alzheimer’s disease. Brain Lang.1996;53:1–19. [DOI] [PubMed]
Goedert M, Ghetti B, Spillantini MG.Frontotemporal dementia: implications for understanding Alzheimer disease. Cold Spring Harb Perspect Med.2012;2:a006254. [DOI] [PubMed] [PMC]
Dai T, Davey A, Woodard JL, Miller LS, Gondo Y, Kim S-H, et al. Sources of variation on the Mini-Mental State Examination in a population-based sample of centenarians. J Am Geriatr Soc.2013;61:1369–76. [DOI] [PubMed] [PMC]
Tangalos EG, Smith GE, Ivnik RJ, Petersen RC, Kokmen E, Kurland LT, et al. The Mini-Mental State Examination in general medical practice: clinical utility and acceptance. Mayo Clin Proc.1996;71:829–37. [DOI] [PubMed]
Trzepacz PT, Hochstetler H, Wang S, Walker B, Saykin AJ.Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults. BMC Geriatr.2015;15. [DOI] [PubMed] [PMC]
Lesuis SL, Hoeijmakers L, Korosi A, de Rooij SR, Swaab DF, Kessels HW, et al. Vulnerability and resilience to Alzheimer’s disease: early life conditions modulate neuropathology and determine cognitive reserve. Alzheimers Res Ther.2018;10:95. [DOI] [PubMed] [PMC]
Zemla JC, Austerweil JL.Analyzing Knowledge Retrieval Impairments Associated with Alzheimer’s disease using network analyses. Complexity.2019;2019:e4203158. [DOI]
Leveille SG, Guralnik JM, Ferrucci L, Corti MC, Kasper J, Fried LP.Black/white differences in the relationship between MMSE scores and disability: the women’s health and aging study. J Gerontol Ser B.1998;53B:P201–8. [DOI]
Overton M, Pihlsgård M, Elmståhl S.Diagnostic stability of mild cognitive impairment, and predictors of reversion to normal cognitive functioning. Dement Geriatr Cogn Disord.2019;48:317–29. [DOI] [PubMed]
Stegmann GM, Hahn S, Liss J, Shefner J, Rutkove SB, Kawabata K, et al. Repeatability of commonly used speech and language features for clinical applications. Digit Biomark.2020;4:109–22. [DOI] [PubMed] [PMC]
Liu CK, Miller BL, Cummings JL, Mehringer CM, Goldberg MA, Howng SL, et al. A quantitative MRI study of vascular dementia. Neurology.1992;42:138. [DOI] [PubMed]
Lin H, Karjadi C, Ang TFA, Prajakta J, McManus C, Alhanai TW, et al. Identification of digital voice biomarkers for cognitive health. Explor Med.2020;1:406–17. [DOI] [PubMed] [PMC]
