Establishing normative data for the evaluation of cognitive performance in Huntington's disease considering the impact of gender, age, language, and education
Language English Country Germany Media print-electronic
Document type Journal Article
Grant support
Project Nr. 8F19004
EU Joint Programme - Neurodegenerative Disease Research
Grant PROGRES Q27/LF1
Univerzita Karlova v Praze
Project ID No 739510
Rare Diseases Clinical Research Network
PubMed
37347292
PubMed Central
PMC10511566
DOI
10.1007/s00415-023-11823-x
PII: 10.1007/s00415-023-11823-x
Knihovny.cz E-resources
- Keywords
- Cognition, Cognitive decline, Huntington’s disease, Neuropsychological testing, Normative data, Online calculator,
- MeSH
- Bayes Theorem MeSH
- Huntington Disease * complications diagnosis MeSH
- Language MeSH
- Cognition MeSH
- Middle Aged MeSH
- Humans MeSH
- Neuropsychological Tests MeSH
- Educational Status MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: A declining cognitive performance is a hallmark of Huntington's disease (HD). The neuropsychological battery of the Unified HD Rating Scale (UHDRS'99) is commonly used for assessing cognition. However, there is a need to identify and minimize the impact of confounding factors, such as language, gender, age, and education level on cognitive decline. OBJECTIVES: Aim is to provide appropriate, normative data to allow clinicians to identify disease-associated cognitive decline in diverse HD populations by compensating for the impact of confounding factors METHODS: Sample data, N = 3267 (60.5% females; mean age of 46.9 years (SD = 14.61, range 18-86) of healthy controls were used to create a normative dataset. For each neuropsychological test, a Bayesian generalized additive model with age, education, gender, and language as predictors was constructed to appropriately stratify the normative dataset. RESULTS: With advancing age, there was a non-linear decline in cognitive performance. In addition, performance was dependent on educational levels and language in all tests. Gender had a more limited impact. Standardized scores have been calculated to ease the interpretation of an individual's test outcome. A web-based online tool has been created to provide free access to normative data. CONCLUSION: For defined neuropsychological tests, the impact of gender, age, education, and language as factors confounding disease-associated cognitive decline can be minimized at the level of a single patient examination.
Department of Neurology Ulm University Oberer Eselsberg 45 89081 Ulm Germany
Huntington Center South kbo Isar Amper Klinikum Taufkirchen Germany
See more in PubMed
Huntington’s disease Collaborative Research, G A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. Cell. 1993;72(6):971–983. doi: 10.1016/0092-8674(93)90585-E. PubMed DOI
Roos RAC. Huntington's disease: a clinical review. Orphanet J Rare Dis. 2010;5(1):40–40. doi: 10.1186/1750-1172-5-40. PubMed DOI PMC
Paulsen, et al. Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: a decade of the PREDICT-HD study. Front Aging Neurosci. 2014;6:78. doi: 10.3389/fnagi.2014.00078. PubMed DOI PMC
Tabrizi SJ, et al. Potential endpoints for clinical trials in premanifest and early Huntington's disease in the TRACK-HD study: analysis of 24 month observational data. Lancet Neurol. 2012;11(1):42–53. doi: 10.1016/S1474-4422(11)70263-0. PubMed DOI
Stout JC, et al. Evaluation of longitudinal 12 and 24 month cognitive outcomes in premanifest and early Huntington's disease. J Neurol Neurosurg Psychiatry. 2012;83(7):687–694. doi: 10.1136/jnnp-2011-301940. PubMed DOI PMC
Snowden JS. The neuropsychology of Huntington's disease. Arch Clin Neuropsychol. 2017;32(7):876–887. doi: 10.1093/arclin/acx086. PubMed DOI
Alenius M, et al. Cognitive Performance among Cognitively Healthy Adults Aged 30–100 Years. Dementia Geriatric Cogn Disord Extra. 2019;9(1):11–23. doi: 10.1159/000495657. PubMed DOI PMC
Weber D, et al. The changing face of cognitive gender differences in Europe. Proc Natl Acad Sci. 2014;111(32):11673–11678. doi: 10.1073/pnas.1319538111. PubMed DOI PMC
Harrison SL, et al. Exploring strategies to operationalize cognitive reserve: a systematic review of reviews. J Clin Exp Neuropsychol. 2015;37(3):253–264. doi: 10.1080/13803395.2014.1002759. PubMed DOI
Boone K, et al. The association between neuropsychological scores and ethnicity, language, and acculturation variables in a large patient population. Arch Clin Neuropsychol. 2007;22(3):355–365. doi: 10.1016/j.acn.2007.01.010. PubMed DOI
Stout J, Glikmann-Johnston Y, Andrews S. Cognitive assessment strategies in Huntington's disease research. J Neurosci Methods. 2015;265:19–24. doi: 10.1016/j.jneumeth.2015.12.007. PubMed DOI
Mestre TA, et al. Rating scales for cognition in Huntington's disease: critique and recommendations. Mov Disord. 2018;33(2):187–195. doi: 10.1002/mds.27227. PubMed DOI PMC
Huntington Study Group Unified Huntington's disease rating scale: reliability and consistency. Mov Disord. 1996;11(2):136–142. doi: 10.1002/mds.870110204. PubMed DOI
Paulsen JS, Smith MM, Long JD. Cognitive decline in prodromal Huntington Disease: Implications for Clinical Trials. J Neurol Neurosurg Psychiatry. 2013;84(11):1233–1239. doi: 10.1136/jnnp-2013-305114. PubMed DOI PMC
Smith A (1982) Symbol digit modalities test (SDMT) manual (revised). Vol. c. 1982: Western Psychological Services. 1–37
Stroop JR. Studies of interference in serial verbal reactions. J Exp Psychol. 1935;18(6):643–662. doi: 10.1037/h0054651. DOI
Golden CJ, editor. Stroop color and word test: a manual for clinical and experimental uses. Chicago: Stoelting Co; 1978.
Staff, Personnel Research Section, Classification and Replacement Branch, AGO. (1944). The new Army individual test of general mental ability. Psychol Bull 41(8):532–538. 10.1037/h0063394
Reitan RM. The relation of the trail making test to organic brain damage. J Consult Psychol. 1955;19(5):393–394. doi: 10.1037/h0044509. PubMed DOI
Benton AL, Hamsher K. Multilingual aphasia examination manual. Iowa City: University of Iowa; 1976.
Scarpina F, Tagini S. The stroop color and word test. Front Psychol. 2017 doi: 10.3389/fpsyg.2017.00557. PubMed DOI PMC
Sathe S, et al. Enroll-HD: an integrated clinical research platform and worldwide observational study for Huntington's disease. Front Neurol. 2021 doi: 10.3389/fneur.2021.667420. PubMed DOI PMC
Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–370. doi: 10.1111/j.1600-0447.1983.tb09716.x. PubMed DOI
Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–198. doi: 10.1016/0022-3956(75)90026-6. PubMed DOI
Landwehrmeyer GB, et al. Data analytics from enroll-HD, a global clinical research platform for Huntington's disease. Movement Disord Clin Pract. 2017;4(2):212–224. doi: 10.1002/mdc3.12388. PubMed DOI PMC
Senft G. Systems of nominal classification. 2. Cambridge: Cambridge University Press; 2008.
Beeri MS, et al. Age, gender, and education norms on the CERAD neuropsychological battery in the oldest old. Neurology. 2006;67(6):1006–1010. doi: 10.1212/01.wnl.0000237548.15734.cd. PubMed DOI PMC
Mills JA, et al. Cognitive and motor norms for Huntington's disease. Arch Clin Neuropsychol. 2020;35(6):671–682. doi: 10.1093/arclin/acaa026. PubMed DOI
Marquand AF, et al. Understanding heterogeneity in clinical cohorts using normative models: beyond case-control studies. Biol Psychiatry. 2016;80(7):552–561. doi: 10.1016/j.biopsych.2015.12.023. PubMed DOI PMC
Wang LAL, et al. Bayesian regression-based developmental norms for the Benton Facial Recognition Test in males and females. Behav Res Methods. 2020 doi: 10.3758/s13428-019-01331-0. PubMed DOI PMC
Ziegler G, et al. Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects. Neuroimage. 2014;97:333–348. doi: 10.1016/j.neuroimage.2014.04.018. PubMed DOI PMC
Wood SN, Scheipl F, Faraway JJ. Straightforward intermediate rank tensor product smoothing in mixed models. Stat Comput. 2012;23(3):341–360. doi: 10.1007/s11222-012-9314-z. DOI
Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput. 2017;27(5):1413–1432. doi: 10.1007/s11222-016-9696-4. DOI
Stan Development Team (2019) Stan User’s Guide
Bürkner P-C. brms: an R package for bayesian multilevel models using stan. J Stat Soft. 2017 doi: 10.18637/jss.v080.i01. DOI
R Core Team (2019) R: A language and environment for statistical computing. In: R Foundation for Statistical Computing. Vienna, Austria
Muth C, Oravecz Z, Gabry J. User-friendly Bayesian regression modeling: a tutorial with rstanarm and shinystan. Quant Methods Psychol. 2018;14(2):99–119. doi: 10.20982/tqmp.14.2.p099. DOI
Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput. 2016;27(5):1413–1432. doi: 10.1007/s11222-016-9696-4. DOI
Julayanont P, McFarland NR, Heilman KM. Mild cognitive impairment and dementia in motor manifest Huntington's disease: Classification and prevalence. J Neurol Sci. 2020;408:116523. doi: 10.1016/j.jns.2019.116523. PubMed DOI
Tabrizi SJ, et al. Predictors of phenotypic progression and disease onset in premanifest and early-stage Huntington's disease in the TRACK-HD study: analysis of 36-month observational data. Lancet Neurol. 2013;12(7):637–649. doi: 10.1016/S1474-4422(13)70088-7. PubMed DOI
Scahill RI, et al. Biological and clinical characteristics of gene carriers far from predicted onset in the Huntington's disease Young Adult Study (HD-YAS): a cross-sectional analysis. Lancet Neurol. 2020;19(6):502–512. doi: 10.1016/S1474-4422(20)30143-5. PubMed DOI PMC
Strauss E, Sherman EMS, Spreen O, editors. A compendium of neuropsychological tests: Administration, norms, and commentary. 3. New York: Oxford University Press; 2006.
Verhaeghen P, Salthouse TA. Meta-analyses of age-cognition relations in adulthood: estimates of linear and nonlinear age effects and structural models. Psychol Bull. 1997;122(3):231–249. doi: 10.1037/0033-2909.122.3.231. PubMed DOI
Salthouse TA. Trajectories of normal cognitive aging. Psychol Aging. 2019;34(1):17–24. doi: 10.1037/pag0000288. PubMed DOI PMC
Bugaiska A, Thibaut JP. Analogical reasoning and aging: the processing speed and inhibition hypothesis. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2015;22(3):340–356. doi: 10.1080/13825585.2014.947915. PubMed DOI
Tombaugh TN, Kozak J, Rees L. Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Arch Clin Neuropsychol. 1999;14(2):167–177. PubMed
Kavé G, Knafo-Noam A. Lifespan development of phonemic and semantic fluency: universal increase, differential decrease. J Clin Exp Neuropsychol. 2015;37(7):751–763. doi: 10.1080/13803395.2015.1065958. PubMed DOI
Goral M, et al. Change in lexical retrieval skills in adulthood. Mental Lexicon. 2007;2(2):129–181. doi: 10.1075/ml.2.2.05gor. DOI
Craik FI, Bialystok E. Cognition through the lifespan: mechanisms of change. Trends Cogn Sci. 2006;10(3):131–138. doi: 10.1016/j.tics.2006.01.007. PubMed DOI
Wilson RS, et al. Educational attainment and cognitive decline in old age. Neurology. 2009;72(5):460–465. doi: 10.1212/01.wnl.0000341782.71418.6c. PubMed DOI PMC
Lam M, et al. Formulation of the age-education index: measuring age and education effects in neuropsychological performance. Psychol Assess. 2013;25(1):61–70. doi: 10.1037/a0030548. PubMed DOI
Bezdicek O, et al. The Prague Stroop Test: Normative standards in older Czech adults and discriminative validity for mild cognitive impairment in Parkinsons disease. J Clin Exp Neuropsychol. 2015;37:794–807. doi: 10.1080/13803395.2015.1057106. PubMed DOI
Ardila A. A cross-linguistic comparison of category verbal fluency test (ANIMALS): a systematic review. Arch Clin Neuropsychol. 2020;35(2):213–225. doi: 10.1093/arclin/acz060. PubMed DOI
Fernández AL, Marcopulos BA. A comparison of normative data for the Trail Making Test from several countries: equivalence of norms and considerations for interpretation. Scand J Psychol. 2008;49(3):239–246. doi: 10.1111/j.1467-9450.2008.00637.x. PubMed DOI
Statucka M and Cohn M (2019) Origins matter: culture impacts cognitive testing in Parkinson’s disease. Front Hum Neurosci 13:269. 10.3389/fnhum.2019.00269 PubMed PMC
Dickinson MD, Hiscock M. The Flynn effect in neuropsychological assessment. Appl Neuropsychol. 2011;18(2):136–142. doi: 10.1080/09084282.2010.547785. PubMed DOI