The Chinese Version of UHDRS in Huntington’s Disease: Reliability and Validity Assessment

Abstract

Background:

The Unified Huntington’s Disease Rating Scale (UHDRS) is a universal scale assessing disease severity of Huntington’s disease (HD). However, the English version cannot be widely used in China, and the reliability and validity of the Chinese UHDRS have not yet been confirmed.

Objective:

To test the reliability and validity of Chinse UHDRS in patients with HD.

Methods:

Between August 2013 and August 2021, 159 HD patients, 40 premanifest HD, and 64 healthy controls were consecutively recruited from two medical centers in China and assessed by Chinese UHDRS. Internal consistency and interrater reliability of the scale were examined. Intercorrelation was performed to analyze the convergent and divergent validity of the scale. A receiver operating characteristic analysis was conducted to explore the optimal cutoff point of each cognitive test.

Results:

High internal consistency was found in Chinese UHDRS, and its Cronbach’s alpha values of the motor, cognitive, behavioral and functional subscales were 0.954, 0.826, 0.804, and 0.954, respectively. The interrater reliability of the total motor score was 0.960. The convergent and divergent validity revealed that motor, cognitive and functional subscales strongly related to each other except for Problem Behavior Assessment. Furthermore, we not only provided the normal level of each cognitive test in controls, but also gave the optimal cutoff points of cognitive tests between controls and HD patients.

Conclusion:

We demonstrate for the first time that the translated version of UHDRS is reliable for assessing HD patients in China. This can promote the universal use of UHDRS in clinical practice.

Keywords

Huntington’s disease UHDRS Chinese reliability assessment

INTRODUCTION

Huntington’s disease (HD) is an autosomal-dominant inherited neurodegenerative disease caused by the dynamic mutation in CAG triplet repeat in the huntingtin (HTT) gene on chromosome 4. It is characterized by movement disorders (i.e., chorea or jerky movement), cognitive impairment, and neuropsychiatric dysfunctions [1]. It generally begins insidiously between the ages of 30 and 50 years, and inevitably worsens approximately 15–20 years after the onset of motor symptoms [2]. Cognitive and behavioral changes usually occur 15 years before a formal clinical diagnosis of motor symptoms onset [3]. The prevalence of HD varies between different populations, ranging from 0.1–3.7 per 100,000 people in the East Asian [4] and 10–12 per 100,000 people or more in the Caucasian populations [5].

The Unified Huntington’s Disease Rating Scale (UHDRS), comprised of four main domains of clinical performance (motor, behavior, cognitive, and function), was constructed in 1996 to assess the clinical severity of HD and monitor disease progression. Its English version has proven to be a reliable and valid scale [6]. Despite the fact that many biomarkers have been identified to measure the disease severity [7, 8], UHDRS is still indispensable in clinical and scientific research on HD. However, the English version does not apply well in China, thus a translated scale is needed. In recent years, Chinese Huntington’s Disease Network (CHDN) has translated the English version of UHDRS into Chinese and annually trained physicians to use it. But the reliability and validity of Chinese version have not been confirmed. Thus, the aim of this study is to examine whether the Chinese version of UHDRS is suitable for assessing HD patients in China.

Against this background, 159 HD patients, 40 premanifest HD (pre-HD), and 64 healthy controls (HCs) were included and assessed by the Chinese version of UHDRS. The reliability and validity of the scale were examined, and cutoff values of cognitive tests between control and patients were given.

MATERIALS AND METHODS

Design, setting, and participants

A cross-sectional design was used in this study. Between August 2013 and August 2021, 199 HTT mutation carriers (including 159 HD patients and 40 pre-HD) and 64 HCs were consecutively recruited from Huashan Hospital Affiliated to Fudan University and the Second Affiliated Hospital of Zhejiang University School of Medicine in Southeast China. Both hospitals are among the most prestigious hospitals in China and have dedicated movement disorder clinics for genetic diagnosis of HD and the conduct of HD clinical trials. Scale scorers were trained by CHDN to do the UHDRS.

HD patients were diagnosed by at least two senior neurologists (Professors Zhi-Ying Wu and Yi Dong) based on patients’ clinical manifestations and positive HTT genetic tests. Pre-HD individuals refer to those with a UHDRS-Total Motor Score (TMS) of 5 or less and positive HTT genetic tests [9]. HCs were enrolled from community residents or patients’ companions without neuropsychiatric diseases. At enrollment, comprehensive demographic and medical data, including current medications, disease history and family history, were collected from the participants. Participants with other severe diseases that interfere the results of UHDRS were excluded. All participants were assessed by the Chinese version of UHDRS. Twenty-four patients were assessed twice by two different well-trained raters independently to exam the interrater reliability of the scales. The Ethics Committees of both hospitals have approved the study and the informed consent forms were signed by patients or their authorized representatives.

Genetic testing of HTT gene

Genomic DNA was extracted from peripheral blood by a DNA extraction kit (Qiagen Inc, Valecia, CA). Genetic testing of HTT gene used the method described previously [10]. The forward primer was 5^′-CAGAGCCCCATTCATTGCC-3^′ and the reverse one was 5^′-TGAGGAAGCTGAGGAGGC-3^′. Sanger sequencing was conducted to determine the sizes of CAG triplet repeat.

Clinical measures

The Chinese version of UHDRS was performed in all participants. The scale includes four subscales to assess the motor, cognitive, behavioral and functional performance, respectively [6]. The TMS is used to assess the motor function. It has 15 items with a maximum total motor score of 124 points. Higher scores indicate greater impairment. Scores from items 6 (finger taps), 7 (pronate/supinate-hands), and 10 (bradykinesia-body) are added for the bradykinesia score. Scores from items 1 (ocular pursuit), 2 (saccade initiation), and 3 (saccade velocity) are added for oculomotor symptoms. Scores from item 11 represent dyskinesia and scores from item 12 represent chorea.

Cognitive assessment consisted of a battery of cognitive tests, including Animal Fluency Test (AFT) [11], Symbol Digit Modalities Test (SDMT) [12], Stroop Word Reading test, Stroop Color Naming test, Stroop Color-Word test [13], and Trail Making Test (TMT, including TMT-A and TMT-B) [14]. They are used to measure executive performance. In the AFT, participants are asked to provide as many animal names as possible in 60 s. SDMT is scored by the correct response in 90 s, with lower scores indicating greater impairment. Stroop tests are scored by the total correct number in 45 s. TMT-A and B are scored by the total time of finishing the task. The Chinese version of TMT and Stroop Color-Word test were proved to have good reliability previously [15].

The Problem Behavior Assessment (PBA) was performed to evaluate 11 neuropsychiatric symptoms by the frequency and severity. Multiplying frequency by severity of each item (range 0–16 points) constitutes the total PBA score of 176 points. Higher scores indicate worse behavioral problems.

The functional scales consisted of the Total Functional Capacity (TFC) scale (range 0–13 points), Functional Checklist (0–25 points) and Independence Scale (10–100 points). TFC is widely used in HD studies with a lower score indicating worse daily functioning.

Statistical analysis

The analysis was performed using SPSS 20.0 (IBM Corporation, Armonk, NY). Cronbach’s alpha analysis was used to exam the internal consistency of the scale, and Spearman’s rank order correlation coefficients were used to measure the inter-correlations for each subscale and the interrater reliability of TMS. Comparisons were made using two sample T test or nonparametric Mann-Whitney U test when appropriate on the premise of continuous data. χ² test was used if variables were categorical data. Age and education years were included as covariates in group comparison between HC and pre-HD or between pre-HD and HD groups. Bonferroni correction was used for multiple group comparisons. A receiver operating characteristic (ROC) analysis was used to examine the test’s ability to correctly identify HD patients from controls. Youden index was used to determine the optimal point. Areas under the curve (AUC) represents the overall sensitivity and specificity.

RESULTS

General information of participants

In this cohort, there were 64 HCs, 40 pre-HD, and 159 HD participants. The mean age (SD) of three groups were 39.7 (13.1), 30.4 (6.7), and 45.6 (12.1) years, respectively. There were significant differences in age and education years between HC and pre-HD group, and between pre-HD and HD groups (both p < 0.001, Bonferroni-corrected threshold p = 0.017), while there were no differences in sex ratio. As shown in Table 1, after correcting for age and education years, there was no difference in clinical symptoms between pre-HD and HC group. SDMT was significantly lower in HC than in pre-HD group, but it did not survive after Bonferroni correction. Remarkable decreased scores in all subscales, including AFT, Stroop tests, SDMT, and TMT, were observed in the HD group compared with pre-HD group (p < 0.001) after adjusting for age and education years. The detailed demographic information and clinical symptoms of participants are shown in Table 1.

Table 1

Demographic and clinical characteristics of participants

Characteristics	HC	Pre-HD	HD	p1/p2
Number	64	40	159	/
AAO, years	/	/	40.4 (11.7)	/
Age, years	39.7 (13.1)	30.4 (6.7)	45.6 (12.1)	Both<0.001
Male/Female	26/38	24/16	80/79	0.162/0.819
Education, years	11.9 (4.7)	14.8 (2.9)	9.9 (4.2)	Both<0.001
Duration of disease, years	/	/	5.3 (5.2)
Expanded CAG length	/	43.2 (2.8)	45.5 (6.4)	NA/0.02
Total motor score (0–124 points)	0.0 (0.0)	0.2 (0.5)	38.6 (21.9)	0.004/<0.001
Oculomotor symptoms (30 points)	0.0 (0.0)	0.0 (0.0)	7.6 (6.7)	NA/<0.001
Bradykinesia (20 points)	0.0 (0.0)	0.1 (0.3)	7.6 (4.2)	0.080/<0.001
Dystonia (20 points)	0.0 (0.0)	0.0 (0.0)	4.5 (4.5)	NA/<0.001
Chorea (28 points)	0.0 (0.0)	0.0 (0.0)	9.7 (5.5)	NA/<0.001
Global cognition
AFT	18.8 (5.7)	19.4 (5.4)	11.1 (6.0)	0.257/<0.001
Stroop Word Reading test-right	90.8 (23.7)	97.0 (17.6)	48.2 (20.7)	0.179/<0.001
Stroop Color Naming test-right	64.2 (14.0)	69.5 (16.7)	32.4 (17.9)	0.252/<0.001
Stroop Color-Word test-right	37.0 (10.9)	42.7 (9.6)	17.0 (13.3)	0.855/<0.001
SDMT-right	52.7 (18.0)	56.4 (9.9)	20.9 (12.6)	0.021/<0.001
Trail Making Test A, seconds	38.9 (20.0)	35.0 (15.6)	104.3 (62.5)	0.221/<0.001
Trail Making Test B, seconds	67.0 (34.9)	61.0 (6.9)	165.8 (69.1)	0.190/<0.001
PBA (0–176 points)	4.7 (11.8)	4.0 (12.1)	15.7 (19.5)	0.860/<0.001
TFC (0–13 points)	13.0 (0.0)	12.9 (0.3)	8.3 (3.7)	0.567/<0.001
Functional Checklist (0–25 points)	25.0 (0.0)	25.0 (0.0)	18.8 (5.9)	0.142/<0.001
Independence Scale (10–100 points)	100.0 (0.0)	100.0 (0.0)	82.2 (18.5)	NA/<0.001

Date was presented with mean (SD). HC, healthy control; HD, Huntington’s disease; Pre-HD, premanifest HD; AAO, age at onset; AFT, Animal Fluency Test; SDMT, Symbol Digit Modalities Test; PBA, Problem Behavior Assessment; TFC, Total Functional Capacity; NA, not available. p values were adjusted for age and education years. p1 means pre-HD vs. HC. p2 means pre-HD vs. HD. Bonferroni-corrected threshold p = 0.017.

Reliability of Chinese version of UHDRS

Totally 159 baseline data of Chinese version of UHDRS were collected from HD patients. Analyzing the scale by Cronbach’s alpha analysis, the internal consistency values for the motor, cognitive, behavioral and functional scales (standardized Cronbach’s alpha values) were 0.954, 0.826, 0.804, and 0.954, respectively. As shown in Table 2, the intercorrelation analysis showed that motor, cognitive and function domains were closely related to each other except for behavioral performance.

Table 2

The inter-correlation analysis of the Chinese version of UHDRS

	TMS	AFT	SWR	SCN	SCW	SDMT	TMT-A	TMT-B	PBA	TFC	FC	IS
TMS	–1.000**
AFT	–0.475**	–1.000**
SWR	–0.495**	–0.441**	–1.000**
SCN	–0.537**	–0.412**	–0.643**	–1.000**
SCW	–0.536**	–0.476**	–0.460**	–0.730**	–1.000**
SDMT	–0.511**	–0.500**	–0.592**	–0.596**	–0.480**	–1.000**
TMT-A	–0.355**	–0.367**	–0.400**	–0.459**	–0.359**	–0.621**	–1.000**
TMT-B	–0.433**	–0.247**	–0.335**	–0.454**	–0.387**	–0.647**	–0.650**	1.000
PBA	–0.314**	–0.193**	–0.147**	–0.101**	–0.109**	–0.211**	0.200*	–0.252**	–1.000**
TFC	–0.658**	–0.494**	–0.330**	–0.466**	–0.434**	–0.435**	–0.318**	–0.357**	–0.458**	1.000**
FC	–0.641**	–0.522**	–0.458**	–0.450**	–0.457**	–0.565**	–0.374**	–0.411**	–0.456**	0.868**	1.000**
IS	–0.627**	–0.427**	–0.372**	–0.442**	–0.403**	–0.480**	–0.351**	–0.372**	–0.429**	0.852**	0.857**	1.000

*p < 0.05; **p < 0.01. UHDRS, Unified Huntington’s Disease Rating Scale; TMS, Total Motor Score; AFT, Animal Fluency Test; SWR, Stroop Word Reading test; SCN, Stroop Color Naming test; SCW, Stroop Color-Word test; SDMT, Symbol Digit Modalities Test; TMT, Trail Making Test; PBA, Problem Behavior Assessment; TFC, Total Functional Capacity; FC, Functional Checklist; IS, Independence Scale.

In addition, 40 Chinese version of UHDRS were collected from pre-HD individuals to exam the consistency of UHDRS scales in pre-HD stage. As we expected, the internal consistency values were acceptable with the standardized Cronbach’s alpha values of 0.737 for cognitive scales and 0.778 for PBA. However, the consistency values were not good for TMS and functional subscales (Cronbach’s alpha values = 0.085 and < 0.001, respectively). The reason may be due to the ceiling effects of these scales, as TMS and functional performances were usually intact in pre-HD stage.

As the assessment of TMS is relatively subjective and varied according to different examiners, we then explored the interrater reliability of TMS. A total of 24 patients were assessed by two well-trained raters (Xiao-Yan Li and Yu-Feng Bao) and evaluations were performed independently. The intraclass correlation coefficients of the scales were 0.960 for the TMS, 0.810 for the oculomotor score, 0.776 for the bradykinesia score, 0.860 for the chorea score, and 0.836 for the dystoniascore.

Convergent and divergent validity of Chinese version of UHDRS

Convergent validity was explored by correlating the TMS with the behavioral, cognitive, and functional subscales. As show in Table 2, TMS correlated significantly with other three subscales (p < 0.01), most with functional subscales (TFC, Functional Checklist and Independence Scale) (r = –0.627∼–0.658), followed by cognitive subscales (r = –0.537 ∼ 0.433) and PBA (r = 0.314).

Divergent validity was further explored by correlating PBA with other three subscales. As shown in Table 2, PBA showed moderate correlations with TMS (r = 0.314) and functional subscales (r = –0.429∼–0.458), but mild or little correlations with cognitive subscales (r = –0.211∼0.252).

Sensitivity and specificity of Chinese version of UHDRS

A battery of cognitive tests was performed in HD and pre-HD groups as well as the control group. The mean scores of cognitive tests in Chinese controls are given in Table 3. To determine the best cutoff values of each cognitive subscale between HD and control groups, ROC analysis was made. As show in Table 4 and Supplementary Figure 1, Stroop tests, SDMT, TMT-A, and TMT-B all showed excellent accuracy (AUC = 0.869–0.922) in distinguishing HD from controls, except for AFT (AUC = 0.825). And their cutoff values were 79 for Stroop Word Reading test, 50 for Stroop Color Naming test, 23 for Stroop Color-Word test, and 35 for SDMT. Using the cutoff values, we could conveniently identify HD patients from controls.

Table 3

The normal range of cognitive tests in Chinese healthy controls

Characteristics	Mean (SD)
Animal Fluency Test	18.8 (5.7)
Stroop Word Reading test-right number	90.8 (23.7)
Stroop Color Naming test-right number	64.2 (14.0)
Stroop Color-Word test-right number	37.0 (10.9)
Symbol Digit Modalities Test-right number	52.7 (18.0)
Trail Making Test A(s)	38.9 (20.0)
Trail Making Test B(s)	67.0 (34.9)

Table 4

The sensitivity and specificity of cognitive tests between HD and controls

Cognitive tests	Sensitivity	Specificity	AUC	Cutoff
Animal Fluency Test-number	0.911	0.628	0.825	13
Stroop Word Reading test-right number	0.817	0.928	0.909	79
Stroop Color Naming test-right number	0.885	0.824	0.922	50
Stroop Color-Word test-right number	0.933	0.691	0.869	23
Symbol Digit Modalities Test-number	0.867	0.853	0.923	35
Trail Making Test A(s)	0.814	0.853	0.903	55
Trail Making Test B(s)	0.865	0.847	0.902	96

AUC, area under the curve.

In addition, we also performed ROC analysis for TMS, PBA, TFC, Functional Checklist and Independence Scale. Except for PBA with AUC = 0.773, other subscales all showed high discriminative capacities (AUC = 0.846–0.997) for distinguishing HD from controls (Supplementary Figure 1).

DISCUSSION

In our study, we proved that the Chinese version of UHDRS had high internal consistency, with good standardized Cronbach’s alpha values of UHDRS-motor, cognitive, behavioral and functional subscales, similar to the original English version (0.95, 0.90, 0.83, 0.95, respectively) [6]. In addition, the inter-rater reliability of TMS was also acceptable and as good as the English version (interclass correlation coefficients was 0.94 for the TMS) [6]. Moreover, UHDRS had good convergent and divergent validity. In conclusion, this study demonstrates for the first time the reliability and validity of Chinese version of UHDRS in assessing Chinese HDpatients.

The PBA score of Chinse UHDRS was significantly related to the TMS and functional scores, but it was lowly related to the cognitive scores. In a previous study on an English version of UHDRS [6], the PBA score was not related to any other subscales. The different results may be caused by different disease stages of HD patients recruited. Our HD patients had a short disease duration than those in the previous study (mean 5.3 years vs. 8.9 years) [6]. This meant they had different profiles of behavioral problems, which may insert different effects on motor and function performances [6]. Furthermore, some types of behavior problems, like psychosis and apathy, were reported to contribute to worse motor and functional performances [16 –18].

Cognitive impairments emerge at least 10–15 years prior to predicted time of motor symptom onset [3, 7]. In our cohort, there was no difference in cognitive performance between pre-HD and HC individuals after Bonferroni correction. This may be caused by the fact that pre-HD individuals in our cohort were too young to exhibit any functional decline. Since the mean age of pre-HD was 30.4 years old and the mean age at onset of HD patients was 40.4 years old, pre-HD individuals had approximately 10 years before the expected motor symptoms onset. In additions, as HD patients’ cognition was badly impaired, cognitive tests had good sensitivity and specificity to distinguish HD patients from controls. This may help Chinese physicians to early identify HD patients and assess the severity of cognitive level of them.

There are some limitations in this study. Firstly, the participants in this study were limited to two hospitals in Southeast China. As China is a large country with considerable regional variability in language, education level, and economy, which may cause some bias to the results. Secondly, the simple size of controls was relatively small, larger samples are needed to give the reference performance on each cognitive test in general population. Thirdly, we only tested the interrater reliability of TMS, and the reliability of cognitive and functional assessments was not proved. Lastly, the findings were drawn from a cross-sectional study, and the ability of Chinese UHDRS to detect disease progression in the longitudinal observation will need to be explored in future studies.

In summary, we have confirmed for the first time that the translated version of UHDRS was accessible to Chinese HD patients. Using the Chinese UHDRS, we can depict a comprehensive clinical profile of Chinese HD patients in the future. Moreover, the scale assessment also helps physicians quickly understand the disease severity of the patients, contributing to a more appropriate management.

Footnotes

ACKNOWLEDGMENTS

Our work is guided by Chinese Huntington’s Disease Network. And Chinese Huntington’s Disease Network is supported by CHDI foundation. We would like to thank all individuals for their supports and willingness to participate in this study.

This study was supported by the Key Research and Development project of Zhejiang Province to Zhi-Ying Wu (2019C03039) and the research foundation for distinguished scholar of Zhejiang University to Zhi-Ying Wu (188020-193810101 /089).

CONFLICT OF INTEREST

Authors report no potential conflicts of interest.

The supplementary material is available in the electronic version of this article: .

References

, Zhang

, Wu

. Development of research on Huntington disease in China, Neurosci Bull. 2017;33(3):312–6. doi: 10.1007/s12264-016-0093-y.

Sun

, Zhang

, Wu

Huntington’s disease: relationship between phenotype and genotype, Mol Neurobiol. 2017;54(1):342–8. doi: 10.1007/s12035-015-9662-8.

Bates

, Dorsey

, Gusella

, Hayden

, Kay

, Leavitt

, et al. Huntington disease, Nat Rev Dis Primers.5. 2015;1:342. doi: 10.1038/nrd2015.5.

, Li

, Dong

, Gao

, Cheng

, Ni

, et al. Haplotype analysis, encompassing HTT gene in Chinese patients with Huntington’s disease. Eur J Neurol. 2020;27(2):273–9. doi: 10.1111/ene.14072.

Evans

, Douglas

, Rawlins

, Wexler

, Tabrizi

, Smeeth

Prevalence of adult Huntington’s disease in the UK based on diagnoses recorded in general practice records, J Neurol Neurosurg Psychiatry. 2013;84(10):1156–60. doi: 10.1136/jnnp-2012-304636.

Unified Huntington’s Disease Rating Scale: reliability and consistency. Huntington Study Grou, Mov Disord. 1996;11(2):136–42. doi: 10.1002/mds.870110204.

Scahill

, Zeun

, Osborne-Crowley

, Johnson

, Gregory

, Parker

, 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):502–12. doi: 10.1016/S1474-4422(20)30143-5.

Byrne

, Rodrigues

, Johnson

, Wijeratne

, De Vita

, Alexander

, et al. Evaluation of mutant huntingtin and neurofilament proteins as potential markers in Huntington’s disease, Sci Transl Med2018;10(458). doi: 10.1126/scitranslmed.aat7108.

Tabrizi

, Reilmann

, Roos

, Durr

, Leavitt

, Owen

, 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.

10.

Dong

, Sun

, Liu

, Ni

, Shi

, Wu

Chinese patients with Huntington’s disease initially presenting with spinocerebellar ataxia, Clin Genet. 2013;83(4):380–3. doi: 10.1111/j.1399-0004.2012.01927.x.

11.

Canning

, Leach

, Stuss

, Ngo

, Black

Diagnostic utility of abbreviated fluency measures in Alzheimer disease and vascular dementia, Neurology. 2004;62(4):556–62. doi: 10.1212/wnl.62.4.556.

12.

Fellows

, Schmitter-Edgecombe

Symbol Digit Modalities Test:regression-based normative data and clinical utility, Arch ClinNeuropsychol. 2019;35(1):105–15. doi: 10.1093/arclin/acz020.

13.

Scarpina

, Tagini

The Stroop Color and Word Test, Front Psychol. 2017;8;12557. doi: 10.3389/fpsyg.2017.00557.

14.

Tombaugh

Trail Making Test A and B: normative data stratified by age and education, Arch Clin Neuropsychol. 2004;19(2):203–14. doi: 10.1016/S0887-6177(03)00039-8.

15.

Wang

, Zhou

, Huang

, Yang

Reliability of the Chinese version of the Trail Making Test and Stroop Color and Word Test among older adults, Int J Gerontol. 2018;12;336–9. doi: 10.1016/j.ijge.2018.06.003.

16.

van Duijn

, Reedeker

, Giltay

, Roos

, van der Mast

Correlates of apathy in Huntington’s disease, J Neuropsychiatry Clin Neurosci. 2010;22(3):287–94. doi: 10.1176/jn2010.22.3.287.

17.

, Gao

, Xie

, Bao

, Dong

, Wu

The clinical, imaging and, biological features of psychosis in Han Chinese patients with Huntington’s disease. J Psychiatr Res. 2021;141;333–8. doi: 10.1016/j.jpsychires.2021.07.024.

18.

Oosterloo

, Craufurd

, Nijsten

, van Duijn

Obsessive-compulsive and perseverative behaviors in Huntington’s Disease, J Huntingtons Dis. 2019;8(1):1–7. doi: 10.3233/JHD-180335.