Comparison between DSQIID total / sub-item scores and plasma p- tau elevation in adults with Down’s syndrome

doi:10.21203/rs.3.rs-3566599/v1

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Comparison between DSQIID total / sub-item scores and plasma p- tau elevation in adults with Down’s syndrome

https://doi.org/10.21203/rs.3.rs-3566599/v1

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Dementia screening questionnaire for individuals with intellectual disabilities (DSQIID) has been an appropriate screening tool for detecting dementia in Down’s syndrome. However, whether this questionnaire reflects the neuropsychiatric signs of Alzheimer’s disease in DS (DS-AD) still remains unknown. To address this issue, we compared plasma phosphorylated tau (P181tau: p-tau) of a representative AD biomarker with the total score and each sub-score of the DSQIID. DSQIID was completed in 43 of the 56 individuals with DS enrolled. DSQIID total scores tended to be positively associated with age, and some of the sub-scores were age-dependently elevated. DSQIID total scores and some sub-scores also positively correlated with plasma p-tau, while all those significant correlations disappeared after age-adjustment. Moreover, one sub-score appeared to have a significant negative correlation with plasma p-tau after age adjustment. DSQIID likely reflects age-associated behavioral changes in DS. The fact that their scores did not correlate with plasma p-tau after age-adjustment leads us to infer that there might be room for improvement in the DSQIID for detecting DS-AD.

Down syndrome

Alzheimer’s disease

phosphorylated tau

plasma biomarker

DSQIID

Down syndrome (DS), trisomy of chromosome 21, is the most frequent chromosomal condition. Because of improving the quality of care for children with DS, the average life expectancy of DS has increased dramatically ¹. On the other hand, another medical issue is emerging along with this prolonged longevity of DS. That is Alzheimer’s disease in adults with DS (DS-AD). Pathological brain changes of individuals with DS over the age of 40 are almost identical to those of patients with Alzheimer’s disease (AD), consisting of both senile plaques and neurofibrillary tangles composed of amyloid β (Aβ) and phosphorylated tau (p-tau), respectively ². That is mainly because trisomy 21 leads overproduction of APP (Amyloid β Precursor Protein) on chromosome 21, which is known as one of causative genes for familial AD ³, as well as overexpression of Dyrk1A and RCAN1 also located on chromosome 21, which are both involved in tau hyperphosphorylation ⁴. Actually, DS confers a strongly increased risk of dementia such that approximately 70–80% of the DS population has dementia by the ages of 60 though not all individuals develop dementia even by 70 years old ^5,6. Given those facts, individuals with DS therefore represent a highly enriched population for AD.

Considering recent development of disease modifying therapies for AD, it is logical to intervene AD in DS-AD by the same methods in near future ⁷. Nowadays, DS-AD can be diagnosed even in preclinical period by using positron emission tomography (PET) for amyloid and tau as well as by fluid biomarker changes of decreased Aβ42 and elevated p-tau in cerebrospinal fluid (CSF) at specialized medical institutions ^8–10. Particularly, recent advance of high-sensitive quantification for plasma p-tau elevation is bringing a safe, objective, and arcuate hospital-based diagnosis for DS-AD to us ^11,12. However, because there are large individual differences in baseline cognitive function, language development, and symptoms of dementia in patients with DS ¹³,prehospital screening for DS-AD by caregivers at home has been quite challenging so that early enrollment of patients with DS-AD for prevention trials was difficult.

Dementia Screening Questionnaire for Individuals with Intellectual Disabilities (DSQIID) has been believed to be one of the appropriate screening tools for detecting dementia in DS ¹⁴. This instrument, developed by Deb et al. in 2007, is observer rated questionnaire consisting of 53 questions ¹⁵. This method is characterized by their unique scoring system that overcomes the floor effect (i.e., the difficulty in assessing relative loss of ability in subjects with lower gains of ability) of other existing dementia assessment scores. This questionnaire is divided into the three parts. The first asks about the best ability the person has or has had. In the second part accounting for 43 of the 53 question scores, if the problems exist from before (“always been the case”) or there are no problems (“dose not apply”), the sub-items are scored zero, and only new symptoms (“always but worse”) and worsening problems (“new symptom”) are scored ¹⁵. The third part contains 10 of the 53 questions, all of which are comparative; for example, ‘speak (signs) less” and “seems generally more tired”. If a response is “yes”, one point is scored. In general, Part 1 is not involved in the scoring. As no weighting factor is assigned to each question, the sum of the points added in Parts 2 and 3 is used as the total score for this test. This method is expected to potentially work as a pre-hospital screening tool for DS-AD that is currently sought after as mentioned above, because of the following two points. The first is its unique design to screen dementia regardless of individual developmental varieties. The second is convenience of observer-rated scoring for caregivers where all inquiries can be filled without visiting hospital. However, DSQIID has a shortage. That is a lack of guarantee whether each sub-score of DSQIID genuinely reflect the neuropsychiatric signs of DS-AD. Because DSQIID was developed before the era of biomarker-based diagnosis of AD, the scores have been validated only by clinical diagnosis of DS-AD but not by the AD biomarker changes. Therefore, some of the sub-scores in DSQIID might be simple results of so-called non-AD neuropsychiatric problems in adult DS such as age-dependent personality changes, depression, and adjustment disorders.

Considering those background above, we herein conducted this cross-sectional observation study comparing the AD biomarker changes to total score of the DSQIID and each sub-item score of the questionnaire to validate genuine usefulness of DSQIID for detection of DS-AD. As mentioned above, a major purpose of early detection of DS-AD is to introduce early intervention by anti-amyloid therapy (such as lecanemab and donanemab) for a population of DS at this moment ^16,17. In light of such rapid changes in the clinical circumstances surrounding DS and AD, we defined DS-AD as DS individuals with biomarker changes that support the presence of amyloid and tau pathology based on the NIA-AA research framework ¹⁸, not as individuals with DS who simply show a decline in social life capacities. As the biomarker change is most appropriately representative of DS-AD defined this way, we chose levels of p-tau phosphorylated at threonine-181 residue as the representative AD biomarker change because elevation of p-tau181 in CSF and plasma occurs solely in AD and not in other neurodegenerative disorders ^19,20. Since it is not feasible to collect CSF from all DS patients, we used plasma p-tau 181 levels as a surrogate marker for DS-AD in this study. Elevation of plasma p-tau 181is also a specific phenomenon reflecting brain AD pathology ²¹, correlates linearly correlated with those levels in CSF, and has been repeatedly reported in DS-AD ^11,12. Note: though various p-tau molecular species have been proposed as the AD biomarker, “p-tau” means p-181 tau in the following description in this study unless otherwise mentioned.

Age dependent elevation of plasma p-tau in DS with and without Apolipoprotein E allele

As summarized in the upper part of Table 1 and Supplementary Table 1, no age and sex difference was observed in the DS and Control groups. No participant had chronic kidney disease or previous history of stroke/myocardial infarction, which are major confounding factors for plasma p-tau measurement ²². Apolipoprotein E (ApoE) genotypes or phenotypes were determined in 54 individuals among 56 enrolled participants with DS, where were 3 with ApoE2/3, 40 with ApoE3/3, and 11 with ApoE3/4. There was no individual with ApoE2/2, ApoE2/4 or ApoE4/4. Allele frequency for ApoE2, ApoE3, and ApoE4 were 2.8%, 87%, and 10.2% respectively. Plasma p-tau levels were significantly higher in the DS group compared to those in the Control groups. When the participants were categorized by age into young (aged 14–25 years), middle-aged (aged 26–42 years), and old cases (over 43 years), the difference of plasma p-tau between the groups was negligible in the young (P = 0.1355), became significant in the middle-aged (P = 0.0011), and was clearly observed with little overlap in the old cases (P = 0.0001) (Fig. 1A). As expected, plasma p-tau levels were strongly correlated to ages in the DS group, while no significant relationship between those was observed in the Control group in Spearman’s test (rs = 0.6725, P < 0.0001 for the DS group and rs= -0.08301, P = 0.6460 for the Control group).

We dichotomized individuals with DS into ApoE4(+) and the ApoE4(-) groups according to the presence of at least one ApoE4 allele. No age and sex difference was found between these groups (P = 0.182 for age, P = 0.594 for sex). As shown in Fig. 1B, the both groups showed significant age dependent elevation of plasma p-tau levels in Spearman’s rank correlation coefficient test (rs = 0.8153, P = 0.0015 for the ApoE4(+) group and rs = 0.6263, P < 0.0001 for the ApoE4(-) group). We expediently set the cut off level for plasma p-tau at 1.52 pg/ml based on the calculation: the average value (0.72 pg/ml) + 2 x standard deviation (0.40 pg/ml) in the Control group. Based on this cut-off, twelve participants with DS aged more than 30, the youngest age at which amyloid pathology can be pathologically detected in DS ², were identified to have abnormally elevated plasma p-tau. When focusing on the impact of presence of ApoE4 allele in such p-tau elevation in relatively younger ages of 40 to 50 years old, four of the eight belonged to the ApoE4(+) group, while all four cases with abnormal p-tau value aged over 50 were the ApoE4(-) group. Such promotive effect of age-dependent elevation of p-tau by carrying ApoE4 alle in DS was also suggested by the fact that the slope of regression line between age and normalized (log-transformed) p-tau was significantly steeper in the ApoE4(+) group compared to in the ApoE4(-) group (the interaction term between the age and group was significant: P < 0.001 by ANCOVA).

Correlation analysis between DSQIID total / sub-item scores and plasma p-tau

We obtained valid responses to the DSQIID questionnaire from 43 individuals with DS among the 56 enrolled participants. The age, sex, total score of DSQIID part 2 and part3 (DSQIID total score) and levels of plasma p-tau of participants are summarized in the lower part of Table 1 (and Supplementary Table 1). Age dependent elevation of p-tau remained statistically significant in these 43 individuals (rs = 0.7230, P < 0.0001 by Spearman’s test). DSQIID total scores tended to be positively associated with ages, but this association did not reach to statistical significance (rs = 0.2652, P = 0.0857 by Spearman’s test).

We summarized relationship between scores (zero or one) of each sub-item of DSQIID and age as well as plasma p-tau levels (Table 2). The univariate analysis by Spearman’s test revealed 8 sub-items of DSQIID were significantly correlated with age. All of these significant correlations were positive, i.e., scoring on the sub-items was related to older ages. Regarding p-tau, 14 sub-items of DSQIID were significantly correlated with plasma p-tau levels. All of these significant correlations were also positive, i.e., scoring on the sub-items was related to higher p-tau. As expected from the strong positive correlation between age and p-tau level in the DS group, seven of the 14 questions positively correlated with p-tau level showed a significant correlation between score and age. However, these significant correlations between p-tau and the sub-items scores disappeared after age adjustment in multiple regression analysis. Similarly, as shown at the bottom of the table, there was a significant positive correlation between DSQIID total scores and plasma p-tau levels in the univariate analysis by Spearman’s test, while this significant association was disappeared after age-adjustment. Interestingly, one sub-items, "Generally, appears more forgetful”, appeared significant negative correlations with plasma p-tau after age adjustment (P = 0.020, β=-0.224), i.e., scoring on this sub-item was related to lower p-tau suggesting absence of AD pathology.

According to the original DSQIID paper, Deb et al. conducted a forced four factor analysis on the questions in Part 2 of this questionnaire and extracted the following four characteristics; 1. Memory / confusion, 2. Feelings of insecurity, 3. Sleep problems, 4. Behaviour problems ¹⁵. Then, we sub-totaled the items scored in the questionnaire with respect to these four components and conducted univariate and multivariate analyses with age and p-tau as above in the same manner as above (Table 3). In this analysis, scores of sub-components 1 (Memory / confusion) and 2 (Feelings of insecurity) were correlated to plasma p-tau levels while these correlations were disappeared after age-adjustment.

The study enrolled 30 (54%) individuals of relatively young adult Down syndrome younger than 30 years of age ², who are generally assumed to have no amyloid pathology. Therefore, the same analyses as in Tables 2 and 3 was conducted on DS participants over 30 years of age. Although the number of question items and sub-components for which significant differences were detected was reduced due to the smaller number of subjects in the analysis, similar results were observed as in the analysis that included all subjects. There was no positive significant correlation between sub-items / sub-components scores and plasma p-tau in multivariate analysis after age-adjustment, while two sub-items,” Talks to self" and "Generally, appears more forgetful”, appeared significant negative correlations with plasma p-tau after age-adjustment with reproducibility in participants aged 30 years and older. (P = 0.023, β=-0.339 and P = 0.047, β=-0.302, respectively) (Supplementary Tables 2 and 3)

The major findings of this research are the following two points.

The first is that plasma p-tau was age dependently elevated and reached to the abnormal cut-off over 40’s in the DS group ^11,12. This finding is corresponding to the recent biomarker researches including ours as well as is in line with the previous pathological and clinical observation that DS-AD become evident from 40’s ^2,5,6. The result that the slope of regression line between age and p-tau was steeper in the ApoE4 group is also in line with the recent reports that DS individuals with ApoE4 allele presented AD in younger ages compared to those without ApoE4 allele ²³. When we consider the fact which plasma p181-tau elevation is specifically observed in MCI due to AD and early phase of AD, not in other type of neurodegenerative disease i.e. vascular dementia or frontotemporal dementia ^{21 24}, these results validate our assumption that plasma p-tau concentrations can be used as a marker to detect development of AD-DS.

The second is that the DSQIID total scores and the scores on 14 of 53 sub-items were positively correlated to plasma levels of p-tau, while none of these correlations remained significant after age-adjustment. Considering the following two facts: seven of these 14 sub-items’ scores presenting correlation with p-tau levels were also positively correlated with age; DSQIID total scores tended to be positively associated with ages, the total scores and some sub-scores in DSQIID certainly reflects to some extent age-related behavioral changes in individual with DS. However, the fact that there was no correlation to plasma p-tau neither in the DSQIID total scores nor in any sub-items of that after age-adjustment may cast doubt on the previous assumption that the DSQIID can screen for DS-AD. Moreover, one sub-item, "Generally, appears more forgetful”, showed significant negative correlations with plasma p-tau after age-adjustment in this study, suggesting that there is a room for improvement in the DSQIID for the purpose of detecting DS-AD. Although we cannot deny the potential confounding effect from the substantial number of young DS individuals enrolled in this study, results similar to those obtained from the participants of all ages were confirmed in the sub-analyses where DS participants < 30 years of age were excluded. In the present study, we calculated scores of the four sub-components in DSQIID part 2 and examined age-adjusted correlations between these sub-component scores and p-tau, but could not identify any sub-components associated with elevated p-tau. Therefore, in order to improve DSQIID to effectively detect development of DS-AD, any strategies of weighting specific sub-components cannot be proposed from the results of this study. In a future, when revising this questionnaire to be more effective, elimination of questions less relevant to DS-AD and adoption of symptoms more specifically appearing in DS-AD, for example myoclonus ²⁵ etc., may be considered.

We acknowledge that the small sample size was a major limitation of this study, which may have weakened the statistical power to detect an association between the sub-scores of DSQIIS and the p-tau levels. Moreover, although plasma p-tau is the most reliable blood-based marker for detection of DS-AD, lack of imaging biomarkers like amyloid and tau PET was another limitation in this study. In the future, it will be necessary to conduct large-scale case-control studies with fluid and imaging biomarkers in order to validate the relationship between DSQIID total/sub items scores and DS-AD.

We conducted comparisons between plasma p-tau of the blood-based biomarker for DS-AD and DSQIID total/sub-items scores that is one of structured care-giver interview asking specifically about functional and behavioral changes and has been believed to one of the appropriate screening tools for detecting dementia in DS. DSQIID total scores tended to be positively associated with age and some of the sub-scores age-dependently elevated significantly, suggesting DSQIID scores likely reflect behavioral changes associated with aging in DS individuals. DSQIID total scores and some sub-items scores were positively correlated with plasma p-tau elevation, while all those significant correlations were disappeared after age-adjustment. Moreover, one sub-items, "Generally, appears more forgetful”, appeared significant negative correlations with plasma p-tau after age-adjustment. This lack of positive correlation and even negative correlation between DSQIID sub-scores and p-tau after age-adjustment lead us to infer that there is a room for improvement in the DSQIID for the purpose of detecting DS-AD.

Study design, ethics statement, and subject recruitment

Written informed consent was obtained before participation from the nearest caregiver or if possible, from subject with DS. The study was approved by the University Ethics Committee of Kyoto Prefectural University of Medicine (KPUM), Kyoto, Japan (RBMR-C-1226) and also approved by research ethics committee by Tokyo Metropolitan Kita Medical and Rehabilitation Center for the Disabled (number: 2019-22). Informed assent and informed consent from patients in the DS group was obtained when possible and from the nearest relative, respectively. Study procedures were designed and performed in accordance with the Declaration of Helsinki. We enrolled 56 patients with DS (DS group) from the registration for DS in KPUM, Hananoki Medical Welfare Center, and Tokyo Metropolitan Kita Medical and Rehabilitation Center for the Disabled from February 2013 to December 2020. To set a reference value of p-tau, we also enrolled 33 healthy controls (Control group) from another registry of KPUM. The participants of the control groups also provided written informed consent before participation. The registry protocols were approved by the medical ethics committees at KPUM (approval number: ERB-G-12). The control participants were not selected from family members of the DS group.

Plasma samples and clinical data collection

Plasma samples were obtained via venous puncture: a total of 8 mL of blood was collected in EDTA-containing tubes. After collection, plasma was separated by centrifugation for 10 min at 3,000 rpm and placed in polypropylene vials. Fresh samples obtained from the enrolled subjects were immediately stored at -80 ̊C until analysis. DSQIID of the DS group were completed by their carers ²⁶. If DSQIID was evaluated more than once for the participants, the results of the questionnaire with the smallest lag-time from blood collection were used. Results with DSQIID examined before or after more than 2 years from blood collection were not used for the study. The part 1 of DSQIID questionnaire, which contains answers in writing and a few simple questions aiming to estimates the best abilities of patients, was not included in the analysis. The total score in the part 2 and 3 and its sub-score of each item represented as zero (the problems exist from before or there are no problems) or one (appearing new symptoms or worsening existed problems) were used for the following analysis.

Measurement of p-tau and Apolipoprotein E typing

The plasma p-tau concentration was measured by the single-molecule immunoarray (Simoa) method with reagents from a single lot using the Simoa P-tau181 assay on an HD-1 Simoa analyzer according to the protocol issued by the manufacturer (Quanterix, Lexington, MA, USA). All samples were analyzed in duplicate on one occasion.

Apolipoprotein E (ApoE) haplotype were determined with genotyping by Invader assay or DNA microarray method undertaken by BML Inc (Tokyo, Japan) or PreMedica inc. (Tokyo, Japan) or phenotyping by isoelectricelectrophoresis for plasma ²⁷ undertaken by BML Inc (Tokyo, Japan).

Statistics

A comparison between the two independent groups was performed using Mann-Whitney’s U test. The Chi-square test was used to evaluate the significance of categorical variables. Univariate correlation analysis was conducted using Spearman’s rank correlation coefficient test (Spearman’s test). Difference of slopes of regression lines was determined by significance of interaction term in the analysis of covariance (ANCOVA). (SPSS ver. 23, IBM Japan Ltd, Tokyo, Japan) Multiple regression analysis was performed with plasma phosphorylated tau concentration after log-transformed as the dependent variable and DSQIID sub-items and age as explanatory variables. SPSS ver. 23 (IBM Japan Ltd, Tokyo, Japan), was used for multivariate analyses. The normality test for residuals of multiple regression analysis was performed by the D'Agostino-Pearson omnibus normality test and Shapiro-Wilk normality test. The above analyses were carried out using GraphPad Prism software version 9.0 (San Diego, CA, USA). The level of significance was set at P < 0.05.

Table 1

Demographics of the participants
Participants with blood collection	DS group	Control group	P value
Number of cases	56	33
Age (mean ± SD)	31.66 ± 10.89	34.82 ± 10.82	P = 0.1291
Sex	Female:27, Male:29	Female:14, Male:19	P = 0.6630
plasma p-tau (pg/ml) (mean ± SD)	2.06 ± 2.11	0.72 ± 0.40	P < 0.0001
ApoE type
E2/2	0	N/A
E2/3	3	N/A
E3/3	40	N/A
E3/4	11	N/A
E4/4	0	N/A
N/A	2	N/A
Participants with DSQIID examined within 2 years of blood collection	DS group
Number of cases	43
Age (mean ± SD)	32.21 ± 10.79
Sex	Female:21, Male:22
plasma p-tau (pg/ml) (mean ± SD)	2.022 ± 2.20
DSQIID total score (median (minimum-maximum)	9 (0–38)
E2/2	0
E2/3	1
E3/3	31
E3/4	9
E4/4	0
N/A	2
SD: standard deviation, NA: not available,

Table 2

Correlation between sub-items of DSQIID, age, and plasma p-tau levels
Sub-items of DSQIID	Univariate analysis for age		Univariate analysis for p-tau		Multivariate analysis for log p-tau value
	Univariate analysis for age		Univariate analysis for p-tau		each score		age
	rs	P-value	rs	P-value	β	P-value	β	P-value
Part 2
1. Cannot wash and/or bathe without help	0.053	0.735	0.269	0.081	0.120	0.215	0.778	< 0.001
2. Cannot dress without help	0.256	0.098	0.323	0.035	0.017	0.866	0.788	< 0.001
3. Dresses inappropriately (e.g. back to front, incomplete)	0.374	0.014	0.352	0.021	-0.034	0.750	0.807	< 0.001
4. Undresses inappropriately (e.g. in public)	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A
5. Needs help eating	0.303	0.048	0.319	0.037	0.120	0.249	0.747	< 0.001
6. Needs help using the bathroom	0.23	0.138	0.223	0.15	-0.046	0.642	0.805	< 0.001
7. Incontinent (including occasional accidents)	0.103	0.51	0.09	0.565	-0.059	0.541	0.798	< 0.001
8. Does not initiate conversation	0.150	0.336	0.272	0.078	-0.013	0.898	0.796	< 0.001
9. Cannot find words	0.166	0.293	0.398	0.009	0.049	0.623	0.783	< 0.001
10. Cannot follow simple instructions	0.280	0.069	0.351	0.021	0.131	0.196	0.751	< 0.001
11. Cannot follow more than one instruction at a time	0.401	0.008	0.482	0.001	-0.034	0.756	0.809	< 0.001
12. Stops in the middle of a task	0.142	0.364	0.266	0.084	0.036	0.713	0.788	< 0.001
13. Cannot read	0.191	0.221	0.299	0.052	0.048	0.632	0.780	< 0.001
14. Cannot write (including printing own name)	0.17	0.275	0.315	0.04	0.115	0.243	0.769	< 0.001
15. Changed sleep pattern (sleeping more or sleeping less)	-0.077	0.622	-0.013	0.936	0.100	0.298	0.799	< 0.001
16. Wakes frequently at night	0.224	0.148	0.222	0.153	-0.032	0.751	0.802	< 0.001
17. Confused at night	-0.181	0.247	-0.184	0.238	-0.028	0.777	0.789	< 0.001
18. Sleeps during the day	0.035	0.823	-0.076	0.628	-0.109	0.258	0.799	< 0.001
19. Wanders at night	-0.112	0.474	-0.236	0.127	-0.073	0.454	0.786	< 0.001
20. Cannot find way in familiar surroundings	0.213	0.17	0.161	0.302	-0.031	0.753	0.799	< 0.001
21. Wanders	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A
22. Loses track of time (time of day, day of the week, seasons)	0.068	0.666	0.211	0.175	0.091	0.345	0.786	< 0.001
23. Not confident walking over small cracks, lines on the ground or uneven surfaces	0.368	0.015	0.27	0.08	-0.026	0.802	0.804	< 0.001
24. Unsteady walk, loses balance	0.214	0.169	0.251	0.104	0.106	0.290	0.765	< 0.001
25. Cannot walk unaided	0.321	0.036	0.302	0.049	0.008	0.940	0.791	< 0.001
26. Cannot recognize familiar person (staff / relatives)	-0.237	0.127	-0.187	0.231	0.032	0.749	0.800	< 0.001
27. Cannot remember names of familiar persons	0.000	> 0.999	0.228	0.141	0.145	0.128	0.784	< 0.001
28. Cannot remember recent events	0.28	0.069	0.31	0.043	0.035	0.729	0.783	< 0.001
29. Withdraws from social activities	-0.04	0.8	0.071	0.651	-0.025	0.797	0.794	< 0.001
30. Withdraws from other persons	0.000	> 0.9999	0.231	0.137	0.060	0.537	0.792	< 0.001
31. Loss of interest in hobbies and activities	0.098	0.533	0.217	0.162	-0.043	0.659	0.796	< 0.001
32. Seems to go into own world	0.076	0.628	0.115	0.462	-0.025	0.796	0.794	< 0.001
33. Obsessive repetitive behaviour (e.g. empties cupboards repeatedly)	-0.043	0.784	0.09	0.565	-0.056	0.567	0.787	< 0.001
34. Hides or hoards objects	0.162	0.299	0.11	0.481	-0.100	0.301	0.801	< 0.001
35. Loses objects	0.187	0.229	0.14	0.37	-0.026	0.792	0.797	< 0.001
36. Puts familiar things into wrong places	0.413	0.006	0.424	0.005	0.040	0.703	0.779	< 0.001
37. Does not know what to do with familiar objects	0.423	0.005	0.444	0.003	0.186	0.080	0.711	< 0.001
38. Appears insecure	0.139	0.4	0.14	0.37	-0.009	0.926	0.795	< 0.001
39. Appears anxious or nervous	-0.141	0.368	0.06	0.703	0.052	0.594	0.800	< 0.001
40. Appears depressed	0.133	0.397	0.271	0.079	0.072	0.456	0.787	< 0.001
41. Shows aggression (verbal or physical)	-0.06	0.702	0.04	0.799	-0.013	0.897	0.793	< 0.001
42. Fits / epilepsy	0.151	0.334	-0.059	0.708	-0.043	0.655	0.798	< 0.001
43. Talks to self	0.188	0.227	0.159	0.309	-0.175	0.068	0.821	< 0.001
Part 3.
44. Lost some skills (e.g. brushing teeth)	0.178	0.253	0.212	0.172	0.032	0.745	0.788	< 0.001
45. Speaks (or signs) less	-0.044	0.779	0.092	0.557	-0.005	0.960	0.793	< 0.001
46. Seems generally more tired	0.017	0.912	0.1	0.525	-0.013	0.891	0.795	< 0.001
47. Appears tearful, gets more easily upset	0.355	0.02	0.408	0.007	0.036	0.734	0.780	< 0.001
48. Appears generally slower	0.18	0.247	0.42	0.005	0.041	0.679	0.786	< 0.001
49. Slower speech	0.257	0.096	0.33	0.031	-0.054	0.585	0.806	< 0.001
50. Appears more lazy	0.072	0.647	0.196	0.207	-0.016	0.871	0.794	< 0.001
51. Walks slower	0.142	0.365	0.248	0.109	0.122	0.210	0.771	< 0.001
52. Generally, appears more forgetful	0.253	0.101	0.094	0.549	-0.224	0.020	0.847	< 0.001
53. Generally, appears more confused	0.199	0.201	0.263	0.088	-0.016	0.874	0.797	< 0.001
DSQIID total score	0.265	0.086	0.454	0.002	0.180	0.862	0.788	< 0.001

N/A: Not Applicable because no subjects were scored for the relevant sub-items.

β: standardized partial regression coefficient

Significant correlations between the scores of sub-items and p-tau levels were highlighted in bold.

Note

Age-adjusted multivariate analysis was performed using multiple regression analysis. Significant models were obtained for all analyses. No model was significantly different in the D'Agostino-Pearson omnibus and Shapiro-Wilk normality tests of residuals.

Table 3

Correlation between scores of sub-components of DSQIID part 2, age, and plasma p-tau levels
Sub-components of DSQIID part 2	Univariate analysis for age		Univariate analysis for p-tau		Multivariate analysis for log p-tau value
	Univariate analysis for age		Univariate analysis for p-tau		each score		age
	rs	P-value	rs	P-value	β	P-value	β	P-value
Component 1: Memory / confusion	0.336	0.028	0.521	0.0003	0.085	0.417	0.762	< 0.001
Component 2: Feelings of insecurity	0.248	0.108	0.446	0.003	0.019	0.854	0.788	< 0.001
Component 3: Sleep problems	0.093	0.553	0.074	0.637	-0.025	0.800	0.797	< 0.001
Component 4: Behaviour problems	0.155	0.322	0.282	0.067	-0.041	0.674	0.798	< 0.001

Scores on the 43 questions that comprise Part 2 of the DSQIID score were categorized into the four components shown below. The scores for each component are the unweighted sum of the scores on the questions of the component.

Component 1: 1. Cannot wash and/or bathe without help, 2. Cannot dress without help, 3. Dresses inappropriately (e.g. back to front, incomplete), 9. Cannot find words, 10. Cannot follow simple instructions, 11. Cannot follow more than one instruction at a time, 12. Stops in the middle of a task, 13. Cannot read, 14. Cannot write (including printing own name), 17. Confused at night, 20. Cannot find way in familiar surroundings, 22. Loses track of time (time of day, day of the week, seasons), 23. Not confident walking over small cracks, lines on the ground or uneven surfaces, 26. Cannot recognize familiar person (staff / relatives), 27. Cannot remember names of familiar persons, 28. Cannot remember recent events, 32. Seems to go into own world, 37. Does not know what to do with familiar objects, and 43. Talks to self.

Component 2: 2. Cannot dress without help, 5. Needs help eating, 6. Needs help using the bathroom, 7. Incontinent (including occasional accidents), 8. Does not initiate conversation, 24. Unsteady walk, loses balance, 25. Cannot walk unaided, 29. Withdraws from social activities, 30. Withdraws from other persons, 31. Loss of interest in hobbies and activities, 38. Appears insecure, 39. Appears anxious or nervous, and 40. Appears depressed.

Component 3: 4. Undresses inappropriately (e.g. in public), 15. Changed sleep pattern (sleeping more or sleeping less), 16. Wakes frequently at night, 18. Sleeps during the day, 19. Wanders at night, 21. Wanders, and 42. Fits / epilepsy.

Component 4: 33. Obsessive repetitive behaviour (e.g. empties cupboards repeatedly), 34. Hides or hoards objects, 35. Loses objects, 36. Puts familiar things into wrong places, and 41. Shows aggression (verbal or physical) ¹⁵

Acknowledgements

We would like to thank Editage (www.editage.com) for English language editing.

Author Contributions

MS was involved with the conceptualization and design of the study, laboratory work, data analysis, and interpretation of the data, and MS wrote the first manuscript. TK and CT were involved with the conceptualization and design of the study, patient enrollment, data collection, data analysis, interpretation of the data, and review of the manuscript. HT and TT were involved with data collection and data analysis. TO, YF, FKF, KM, MO, and YM assisted with patient enrollment and review of the manuscript. ST was involved in data analysis and interpretation of the data. NT and TM participated in the review and revision of the manuscript. All authors reviewed the drafts and approved the final version of the manuscript.

Data availability statement

The authors are committed to promoting transparency and open science. Reasonable　requests for access to an anonymized version of the dataset can be made by contacting the corresponding author.

Ethics declarations

Study procedures were designed and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained before participation from the nearest caregiver or if possible, from subject with DS. The study was approved by the University Ethics Committee of Kyoto Prefectural University of Medicine (KPUM), Kyoto, Japan (RBMR-C-1226) and also approved by research ethics committee by Tokyo Metropolitan Kita Medical and Rehabilitation Center for the Disabled (number: 2019-22). Informed assent and informed consent from patients in the DS group was obtained when possible and from the nearest relative, respectively.

Conflict of financial interests:

TK received JSPS KAKENHI (grant numbers JP21K07466, JP21K07855). FKM received JSPS KAKENHI (grant number JP19K16924) and a Japan heart foundation research grant. TO received Grants-in-Aid from the Japan Society for the Promotion of Science (JSPS KAKENHI) (grant number JP20K16605) and a grant from the Takeda Science Foundation. MS received JSPS KAKENHI (grant number JP23L12663). TM received JSPS KAKENHI (grant number JP18K07533), a Grant-in-Aid for Research on Intractable Disease (21FC0201, 21FC1002) from the Japanese Ministry of Health, Labor, and Welfare, Japan, and AMED (grant numbers JP21dm0307003s0105, JP21ek0109516s0301, JP21ek0210120s0202). The other authors have no financial disclosure to declare.

Funding declaration

This study was supported by Grants-in-Aid (grant numbers 21K07466 to TK and 23K12663) from the Ministry of Education, Culture, Sports, Science and Technology of Japan; and the grants from Japan Research Society for Adults with Down Syndrome (JRSADS) and from The Kyoto Lifetec Support Center and the grant for Social Welfare Activities of Mitsubishi Foundation. The funding organizations had no involvement in study design, data-collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Additional information: Supplemental Table 1, Supplementary Table 2 and 3

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Competing interest reported. TK received JSPS KAKENHI (grant numbers JP21K07466, JP21K07855). FKM received JSPS KAKENHI (grant number JP19K16924) and a Japan heart foundation research grant. TO received Grants-in-Aid from the Japan Society for the Promotion of Science (JSPS KAKENHI) (grant number JP20K16605) and a grant from the Takeda Science Foundation. MS received JSPS KAKENHI (grant number JP23L12663). TM received JSPS KAKENHI (grant number JP18K07533), a Grant-in-Aid for Research on Intractable Disease (21FC0201, 21FC1002) from the Japanese Ministry of Health, Labor, and Welfare, Japan, and AMED (grant numbers JP21dm0307003s0105, JP21ek0109516s0301, JP21ek0210120s0202). The other authors have no financial disclosure to declare.

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Comparison between DSQIID total / sub-item scores and plasma p- tau elevation in adults with Down’s syndrome

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Introduction

Results

Age dependent elevation of plasma p-tau in DS with and without Apolipoprotein E allele

Correlation analysis between DSQIID total / sub-item scores and plasma p-tau

Discussion

Conclusion

Methods

Study design, ethics statement, and subject recruitment

Plasma samples and clinical data collection

Measurement of p-tau and Apolipoprotein E typing

Statistics

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References

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