Establishing normative data for the evaluation of cognitive performance in Huntington's disease considering the impact of gender, age, language, and education

. 2023 Oct ; 270 (10) : 4903-4913. [epub] 20230622

Jazyk angličtina Země Německo Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid37347292

Grantová podpora
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

Odkazy

PubMed 37347292
PubMed Central PMC10511566
DOI 10.1007/s00415-023-11823-x
PII: 10.1007/s00415-023-11823-x
Knihovny.cz E-zdroje

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.

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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

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