Non-invasive Functional Assessment and Pathogenesis of Morquio A (NIFAMA)
Conditions: Mucopolysaccharidosis IV Type A, Morquio A Syndrome, MPS IVA
Sponsor: Nemours Children's Clinic

 
    
 
Grant Number: 1R01HD102545-01A4 
ID: 750932-25 
NCT05284006 
Principal Investigator(s): 
Shunji Tomatsu, MD, PhD 
Project Title: Non-invasive functional assessment and pathogenesis of Morquio A  
 
Date of Document: March 11, 2025 
 
Accomplishments 
 
The long-term goal of this research proposal is to better understand the natural history of MPS IVA in terms of 
clinical progression and objective outcome measures. The unique aspect of our research is the establishment 
of innovative non-invasive assessments to evaluate the clinical severity, disease stage, and therapeutic efficacy 
of skeletal dysplasia. Our central hypothesis is that these assessments, when combined into a disease severity 
scoring system, can effectively characterize MPS IVA and assess the benefits of therapeutic interventions. 
 
Aim 1. Conduct multidisciplinary and detailed non-invasive assessments in Morquio A patients. Our 
working hypothesis is that longitudinal non-invasive tests demonstrate accurate prognostic and predictive 
evaluation of skeletal dysplasia and can be carried out across a broad patient group, including patients who are 
young, wheelchair-bound, and post-surgical.  
 
Aim 2. Identify potential surrogate biomarkers of skeletal dysplasia. Our working hypothesis is that 
biochemical biomarkers correlate with disease stage, clinical severity, and non-invasive clinical assessments. 
These biomarkers should, therefore, serve as prognostic and/or predictive biomarkers of therapeutic response. 
 
 
 
 
 

1. Major activities 
Aims 1 and 2. 
a. Team structure: 
As outlined in the grant proposal, we assembled a dedicated and expert study team on May 1, 2021 (Fig. 1), 
demonstrating our unwavering commitment to the project. 
 
-Monthly-based videoconferences between PI and investigators or board members from 6 Morquio A families 
have been set up since May 2021 to discuss the recruitment process, research plan, summary, and report 
on the project. 
 
         
 
Figure 1. Structure of Study Team of Natural History 
b. Recruitment: During the COVID-19 pandemic, the recruitment process was significantly impacted, leading 
to delays due to limited access to the families and the hospital, and the requirement of vaccines to visit the 
hospital. Despite these challenges, sixty-two patients have consented to the study (Figures 2 and 3). Sixty 
patients have completed first visits, and thirty-eight have completed second visits. Twenty-one surgical 
specimens have been collected from participants. See the table below. 
c. Data Collection: This study includes 15 major assessments: clinical assessment procedures; 
anthropometric measurements; activity of daily living and quality-of-life questionnaires; gait kinematics and 
kinetics analysis; pulmonary function tests (PFT); skeletal radiographs and dual-energy x-ray absorptiometry 
(DXA); MRI in cervical spine, temporal bones, and hip; computed tomography angiography (CTA) for tracheal 
obstruction; CT for temporal bones; anesthetic encounters; joint mobility; hearing function; biochemical 
analyses; and pathological analyses.  
In Aim 1, we have conducted all tests except for biochemical analysis. In Aim 2, we have analyzed some 
portions of data and will submit it to the articles, 
 
 
 
 
 
NIH
Funding
Nemours/AIDHC Administration Office (P.I. Shunji Tomatsu)
Non-invasive functional assessment and pathogenesis of Morquio A
REDCap and Statistical 
analyses; Hossain, site 
coordinator
End users; 
physicians, Morquio 
families and society, 
pharmaceutical 
companies
Recruitment and informed 
consent; Klipner, Tomatsu, 
Foundations
BMD; Kecskemethy
IRB; review 
protocol and 
study
DATA AND SAFETY 
MONITORING; Klipner, Tomatsu
Joint Mobility; Rahman
Pulmonary function; Shaffer
Anthropometric assessment; 
Kecskemethy, Bober, Tomatsu
Report
Assessment Tests
Hearing function; Nagao
Gait analysis; Shrader, Church
ADL, QOL; Alderfer, Tomtasu
Skeletal X-rays, MRI, CT; 
Theroux, Averill, Kecskemethy, 
S. Mackenzie
Anesthetic encounters; Theroux
Biomarkers; Mason, Khan, 
Tomatsu
Pathology; W. Mackenzie, 
Tomatsu
Information
Data
Analysis
Morquio 
Foundations 
Family 
members
Report
Support 
Review
Report
Bi-monthly meetings
Results of data
Monitoring
Review and evolve 
protocols
Data sharing; protocols, 
publications, presentations, 
clinical endpoints, disease 
severity score
Report
Approval 
Review
Report
Report
Facilities 
Resources
Biobank
specimens
Surgical specimens; 
W. Mackenzie, S. 
Mackenzie, Pizarro, 

Planned 
Ethnic Categories 
  
  
Not Hispanic or 
Latino 
Hispanic or Latino 
Total 
Racial Categories 
Female 
Male 
Female 
Male 
  
American Indian/Alaska 
Native 
0 
0 
0 
0 
0 
Asian 
3 
3 
0 
0 
6 
Native Hawaiian or Other 
Pacific Islander 
0 
0 
0 
0 
0 
Black or African American 
4 
4 
0 
0 
8 
White 
20 
20 
0 
0 
40 
More than One Race 
0 
0 
3 
3 
6 
Total 
27 
27 
3 
3 
60 
Cumulative (Actual) 
 
 
 
 
d. Summary of Demographics 
Total
Racial Categories
Female
Male
Unknown/
Not 
Reported
Female
Male
Unknown/
Not 
Reported
Female
Male
Unknown/
Not 
Reported
American Indian/Alaska Native
1
1
0
0
0
0
0
0
2
Asian
3
1
0
0
1
0
0
0
0
5
Native Hawaiian or Other Pacific Islander
0
0
0
0
0
0
0
0
0
Black or African American
1
2
0
0
0
0
0
0
3
White
26
14
4
2
46
More than One Race
1
1
0
1
1
0
0
0
0
4
Unknown or Not Reported
2
1
1
1
1
6
Total
29
18
0
6
4
0
0
1
0
66
Ethnic Categories
Not Hispanic or Latino
Hispanic or Latino
Unknown/Not Reported 
Age Enrollment Report
Age Categories
0-1
2--5
6--12
13--17
18--25
26--45
46--64
65-75
76+
Unknown/ 
Not 
Reported
Total
Total
2
13
19
5
12
14
1
*
*
*
66

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2. Geographic maps (Global and US only) 
 
 

 
 
 
 
 
 
 
 
 
 
 
Figure 3. Gender and Age  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 4. Racial Background 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 5. Race: Morquio Study vs. US Population 
 

 
Figure 6. Ethnic Demographics 
 
 
 
Figure 7. Ethnicity: Morquio A Study vs. US Population 
 
2. Specific objectives 
Establishment of innovative non-invasive assessments to evaluate the clinical severity, disease stage, and 
therapeutic efficacy of skeletal dysplasia. 
Aim 1. Conduct multidisciplinary and detailed non-invasive assessments in Morquio A patients. Our 
working hypothesis is that longitudinal non-invasive tests demonstrate accurate prognostic and predictive 
assessment of skeletal dysplasia and can be carried out across a broad patient group, including patients who 
are young, wheelchair-bound, and post-surgical.  
 
Aim 2. Identify potential surrogate biomarkers of skeletal dysplasia. Our working hypothesis is that 
biochemical biomarkers correlate with disease stage, clinical severity, and non-invasive clinical assessments. 
These biomarkers should, therefore, serve as prognostic and/or predictive biomarkers of therapeutic response. 
 
 
3. Significant results (including) major findings, developments, or conclusions (both positive and 
negative) 
 
Aims 1 and 2. 

1. We have completed the first visits for 64 patients, the second for 49 patients, and the third for four patients, 
17 scheduling in the problematic situation of COVID-19 after confirming the safety and feasibility of the 
families. 25 Surgical Samples were Collected. 
We recruited the patients, including 5 international patients. We assume 15 % of the MPS IVA patients 
in the USA participated in this program if around 400 MPS IVA patients are present. This is very significant 
in terms of the number of patients. Also, the demographics of the participants are similar to the USA 
ethnic population pattern, which MPS IVA incidence happens in diverse populations. 
2. Until now, no patient has had any discomfort or incapability with the proposed tests, which matches our 
hypothesis that all non-invasive tests are feasible for patients without age or physical handicap. 
Our non-invasive tests are feasible and acceptable to the majority of patients compared to endurance 
tests, which include a 6 min walk test and a 3 min climb-up test. This is one of our major goals and a 
significant result. 
3. We found that NTproCNP is currently the most promising biomarker during the study. We plan to measure 
this biomarker continuously in human blood and urine to identify the correlation between skeletal 
dysplasia and NTproCNP level. In addition, we are exploring the potential of CNP as a therapeutic agent 
on the MPS IVA animal models. The discovery of NTproCNP is significant as a potential surrogate 
biomarker and can be used for the future clinical trial. 
4. Based on the natural history program activity and data, our project is selected for the clinical trial the 
Foundation for the National Institutes of Health (FINH) Accelerating Medicines Partnership® Bespoke 
Gene Therapy Consortium (AMP® BGTC), which is public-private partnership between the NIH, U.S. 
Food and Drug Administration (FDA), biopharmaceutical and life sciences companies, and non-profit and 
other organizations to develop and deliver bespoke (i.e., customized) gene therapies to treat patients 
with rare diseases. AMP® BGTC aims to accelerate the development and approval of gene therapies for 
eight rare diseases, including Morquio A Syndrome.  This is a very significant result for the entire Morquio 
Community, Researchers, and  
We have a schedule of the clinical trial for Morquio A in 2027 using AAV gene therapy. The current data 
will be used for the baseline data of the clinical trial. 
5. Because of COVID-19, we have delayed collecting data, which is a serious issue to have longitudinal 
data (4 visits). 
 
4. Key outcomes or other achievements 
 
Aims 1 and 2.  
Identify potential surrogate biomarkers of skeletal dysplasia. Our working hypothesis is that biochemical 
biomarkers correlate with disease stage, clinical severity, and non-invasive clinical assessments. These 
biomarkers should, therefore, serve as prognostic and/or predictive biomarkers of therapeutic response. 
We collected urine and blood samples from patients who visited the hospital on the first, second, and third 
visits.  
 
Materials and methods 
Subjects 
MPS IVA patients 
MPS IVA patients commuting to Nemours Children’s Hospital in Delaware have participated. Written informed 
consent was obtained before any study procedures were conducted. 
 
Controls 
Residual serum from various patients without skeletal dysplasia at Shimane University Hospital was frozen 
after biochemical analysis and then sent to our laboratory as control samples for this research. The patients 
ranged in age from 0 day to 16 years. Blood samples were also collected from 7 healthy adults working in this 
laboratory, and both plasma and serum were stored. Written informed consent was obtained from them.  
 
a. Collagen type I 
Human Collagen Type I (COL1) ELISA Kit (Cat# EKU03297-96T, BIOMATIK, Kitchener, Canada) was used to 
measure the concentration of collagen type I in patient plasma and control serum and control plasma 
according to the manufacturer's instructions. 
b. Collagen type II 

Human Collagen Type Ⅱ, Col Ⅱ ELISA Kit (Cat# EKC40379, BIOMATIK, Kitchener, Canada) was used to 
measure the concentration of collagen type II in patient plasma and control serum and control plasma 
according to the manufacturer's instructions. 
c. Collagen type X 
Human Collagen X ELISA Kit (Colorimetric) (Cat# NBP2-75826, Novus Biologicals, Centennial, Colorado, 
USA) was used to measure the concentration of collagen type X in patient plasma and control serum and 
control plasma according to the manufacturer's instructions. 
d. NT-proCNP 
NT-proCNP ELISA kit (Cat# BI-20812, BIOMEDICA, Vienna, Austria) was used to measure the concentration 
of amino-terminal pro C type natriuretic peptide (NT-proCNP) in patient plasma and control serum and control 
plasma according to the manufacturer's instructions. 
e. Anti-rhGALNS IgG 
Enzyme-Linked Immunosorbent Assay (ELISA) was used to measure the concentration of anti-rhGALNS IgG 
in each sample. 
f. Anti-AAV8 IgG and Anti-AAV9 IgG 
The ELISA method [1] was used with modifications to detect these antibodies. 
 
g. Genotype 
The genomic DNA of each patient was extracted from frozen WBC, and then all 14 exons in the GALNS gene 
were PCR-amplified and sequenced by the Sanger method to detect pathogenic mutations. 
  
h. Glycosaminoglycans (GAG) analysis by LC-MS/MS 
Control serum and urine: We obtained serum and urine from various patients without skeletal dysplasia at 
Shimane University Hospital. Control serum ages 5-18 years and urine 5-33 years 
 
Results (outcomes) 
Collagen type I and II 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 1. Collagen type I (A) and II (B) levels in patients and controls. 
Both vertical axes are presented on a base-2 logarithmic scale.  
 
a. Collagen type I 
16
32
64
128
256
512
1024
2048
4096
8192
0
20
40
60
Age (years)
(A) Collagen type I (ng/mL)
4
8
16
32
64
128
256
512
1024
0
10
20
30
40
50
60
ERT
Untreated
HSCT
Control
Age
(B) Collagen type II (ng/mL)

We found a statistically significant increase in collagen type I in patients older than 20 (Table 1, Figure 1 (A)). 
Table 1. Comparison of collagen type I levels in 5 age groups. 
Age 
No. 
Mean 
SD 
Maximum 
Minimum 
Mean 
age 
p-value 
Control 
 
 
 
 
 
 
 
≤ 1 y 
1 
2803.4 
0 
2803.4 
2803.4 
0.25 
 
>1, ≤ 5 y 
4 
2715.5 
2400.5 
6397.5 
329.6 
2.51 
 
>5, ≤ 10 y 
6 
1019.0 
481.2 
2039.0 
566.0 
7.19 
 
>10, ≤ 15 y 
5 
1572.0 
2123.6 
5734.8 
32.9 
11.98 
 
> 15, ≤ 20 
y 
1 
996.1 
0 
996.1 
996.1 
15.99 
 
>20 y 
7 
76.6 
18.6 
106.3 
49.3 
39.57 
  
MPS IVA 
 
 
 
 
 
 
 
>1, ≤ 5 y 
8 
1022.4 
681.8 
2654.1 
490.7 
3.05 
0.31 
>5, ≤ 10 y 
24 
679.4 
469.3 
1630.2 
50.3 
7.38 
0.19 
>10, ≤ 15 y 
14 
752.4 
398.1 
1722.0 
381.2 
12.52 
0.48 
> 15, ≤ 20 
y 
11 
323.9 
314.8 
1161.6 
67.0 
17.70 
N/A 
>20 y 
41 
125.7 
92.1 
383.0 
24.5 
33.35 
0.0046 
 
b. Collagen type II 
We found a statistically significant increase in collagen type II in patients in two age groups, between 5 and 10 
years and over 20 years (Table 2, Figure 1 (B)). We calculated the partial correlation coefficient between 
collagen type II and NT-proCNP, controlling for age using the entire age group. There was almost no 
correlation (r = 0.042, p = 0.69).  
Table 2. Comparison of collagen type II levels in 5 age groups. 
 
Age 
No. 
Mean 
SD 
Maximum 
Minimum 
Mean age 
p-value 
Control 
>1, ≤ 5 y 
18 
129.03 
92.41 
324.99 
11.70 
2.68 
>5, ≤ 10 y 
12 
113.70 
53.62 
231.40 
36.66 
6.97 
>10, ≤ 15 y 
7 
85.64 
78.26 
253.57 
16.66 
12.21 
> 15, ≤ 20 y 
2 
43.85 
30.83 
74.68 
13.02 
16.50 
>20 y 
7 
35.72 
22.85 
76.23 
10.51 
39.57 
MPS IVA 
>1, ≤ 5 y 
7 
105.80 
74.15 
240.58 
29.44 
3.23 
0.55 
>5, ≤ 10 y 
21 
234.54 
233.64 
885.55 
15.93 
7.30 
0.037 
>10, ≤ 15 y 
14 
70.07 
59.39 
208.32 
17.03 
12.52 
0.67 
> 15, ≤ 20 y 
11 
131.71 
181.03 
534.18 
12.77 
17.70 
0.21 
>20 y 
40 
90.71 
105.27 
438.58 
6.10 
33.54 
0.0097 
 
c. Collagen type X 

 
Figure 2. Collagen type X levels in blood 
We did not find any significant difference or trend. 
 
0
2
4
6
8
10
12
14
16
18
0
2
4
6
8
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64
Col X (ng/mL)
ERT
no ERT
HSCT
controls

d. NT-proCNP 
We revealed a significant increase of NT-proCNP in patients under 20 years (Welch's t-test, p = 2.67 x 10-12). 
The increase was particularly evident just before the age of pubertal growth spurt in healthy subjects (Fig. 3). If 
we focus only on patients who have two data points at different ages before the age of pubertal growth spurt (all 
had received ERT during these two periods), 5 out of 10 boys and 2 out of 3 girls showed the increase in NT-
proCNP level. This suggests that plasma NT-proCNP would not be a pharmacodynamic biomarker differing from 
urinary KS [10] before the age of pubertal growth spurt. 
Figure 3: Correlation between age, NT-proCNP level in plasma, and height of patients with MPS IVA. Males and females are shown in the 
left and right figures, respectively. Round dots represent patients treated with enzyme replacement therapy (ERT). Triangle markers represent 
patients who were never treated with ERT. Square markers represent patients treated with hematopoietic stem cell transplantation (HSCT). 
Filled markers represent patients for whom height at blood sample collection was recorded. The color of each marker represents the z-score of 
each patient's height calculated based on the 2022 CDC growth chart. Black dotted lines show median, 5th and 95th percentiles for healthy 
controls [30]. When a patient has two data points, each data point is connected by a green dotted line. 
Figure 4: The relationship between each patient's plasma NT-proCNP level, age, and subsequent height growth rate (height velocity): 
Height velocity was calculated from two sets of height data measured at different times, 7-20 months apart. Each dot represents the age of 
each patient at which the first height was measured (horizontal axis) and the corresponding later height velocity (vertical axis). Round dots 
represent patients who received ERT continuously until the second height data was obtained. The square dot represents a patient who had 
received HSCT. The triangular dot indicates a patient who never received ERT until his second height data was obtained. Larger round dots 
represent the attenuated phenotype, while smaller round dots represent the severe phenotype. Each dot is filled with a color corresponding to 
the plasma NT-proCNP level at the first height measurement. The light blue and pink lines show the 50th percentile for height velocity for 
male and female MPS IVA patients, respectively [29]. The gray dotted line shows the 50th percentile for height velocity for healthy males 
and females. 

The concentration of NT-proCNP in plasma from patients under 20 years showed a negative correlation with 
age, and the correlation coefficient (r) was -0.612 (p = 7.44 x 10-11). The Z-score of each patient’s height 
showed a significant negative correlation with age, as current therapy is ineffective to prevent growth failure in 
MPS IVA (r = -0.703, p < 1.21 x 10-6). We then calculated the partial correlation coefficient between NT-
proCNP and z-score of height controlling for age, which is summarized in Table 3 (below, partial correlation 
coefficient between NT-proCNP and z-score of height, controlling for age). We found a negative 
correlation after the age of 8 years. 
 
In addition, for patients with more than two visits, 
height velocity was calculated from two sets of height 
data measured at different times, 7-20 months apart, 
as summarized in Fig. 4. These findings are 
consistent with the hypothesis in achondroplasia that 
elevated levels of CNP-related peptides are natural 
responses to disturbed bone growth [11, 12]. Further 
accumulation of data from MPS patients is essential 
and urgent to determine the accurate correlation between NT-proCNP and skeletal symptoms, including 
height. 
e. Anti-rhGALNS IgG 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 5. Anti-GALNS antibody levels in blood 
ERT is strongly associated with the elevation of anti-rhGALNS antibodies. One patient who received HSCT at 
8 years had received ERT until HSCT. 
 
f. Anti-AAV8 IgG and Anti-AAV9 IgG 
Under investigation. 
 
 
 
 
 
 
Age group 
number 
of 
subjects 
Partial 
correlation 
coefficient 
p-value 
≤ 8 y 
20 
0.19 
0.4355 
>8, ≤ 13 y 
17 
-0.568 
0.0217 
>13, ≤ 20 y 
15 
-0.837 
1.865 × 10-4 
0
5
10
15
20
25
30
35
40
45
0
2
4
6
8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64
Anti-GALNS IgG (mg/L)
ERT
no ERT
HSCT

g. Genotype: we have identified the following genotypes from participants. 
 
 
 
Patient
Height
Age
ID
Sex
Race
(Z-score)
(year)
Allele 1
Allele 2
Treatment
M01
F
White or Caucasian
-6.34
17.16
c.740G>A (G247D)
c.901G>T (G301C)
ERT
-6.73
18.70
M02
F
Chinese
38.57
c.953T>G (M318R)
c.1567T>G (X523EextX93)
ERT
40.00
M03
F
White or Caucasian
24.62
c.448delC (H150Tfs*3)
c.651_652insG (K218Efs*45)
ERT
M04
F
White or Caucasian
42.12
c.675dupC (F226Lfs*37)
unknown
ERT
43.51
M05
F
White or Caucasian
-9.93
18.35
c.346G>A (G116S)
c.1156C>T (R386C)
ERT
-9.76
19.78
M06
F
White or Caucasian
-8.52
19.89
c.346G>A (G116S)
c.1156C>T (R386C)
ERT
21.29
M07
M
White or Caucasian
32.25
c.337A>T (I113F)
c.1171A>G (M391V)
No ERT for 2 years and 8 months
M08
M
White or Caucasian
no record
8.00
c.122T>A (M41K)
c.122T>A (M41K)
ERT
-6.09
9.03
Received HSCT 1 year ago
M10
M
White or Caucasian
1.22
10.82
c.338T>C (I113T)
c.1219A>C (N407H)
ERT
1.01
12.37
M11
F
White or Caucasian
-5.36
15.11
c.421T>A (W141R)
unknown
ERT
-5.53
16.55
M12
F
White or Caucasian
26.65
c.697G>A (D233N)
c.1034T>C (L345P)
No ERT for 4 years and 4 months
28.15
M13
M
Black or African American
-7.52
13.13
c.251C>A (A84E)
c.319G>A (A107T)
ERT
-6.75
14.84
M14
F
White or Caucasian
-5.7
16.29
c.740G>A (G247D)
unknown
ERT
-5.7
17.83
M15
M
White or Caucasian
-2.39
5.32
 c.498delC (F167Lfs*32)
c.901G>T (G301C)
ERT
-3.84
6.81
M16
M
Filipino
-5.09
5.21
c.228C>A (N76K)
c.1480A>G (p.M494V)
ERT
no record
6.77
M19
F
Black or African American
-6.49
9.44
c.245C>T (S82L)
unknown
ERT
-5.64
10.96
M20
F
White or Caucasian
-4.09
9.49
c.498delC (F167Lfs*32)
c.1474G>A (A492T)
ERT
-3.53
10.06
M21
M
White or Caucasian
-4.08
6.12
c.651_652insG (K218Efs*45)
c.1159G>A (G387S)
ERT
-5.22
7.55
M22
M
White or Caucasian
-5.45
8.34
c.651_652insG (K218Efs*45)
c.1159G>A (G387S)
ERT
-7.24
9.78
M25
M
White or Caucasian
41.34
c.155C>T (P52L)
c.337A>T (I113F)
Never received ERT
43.28
M26
M
Filipino
-7.03
12.39
c.93delC (N32Tfs*97)
c.946G>A (G316R)
ERT
no record
13.89
M28
F
Mixed
31.20
c.868G>A (G290S)
c.868G>A (G290S)
Never received ERT
Japanese and Caucasian
32.75
M30
F
White or Caucasian
43.52
c.121-12T>C
c.121-12T>C
ERT
M31
M
Black or African American
-1.29
9.86
c.935C>G (T312S)
c.1520G>T (C507F)
ERT
-1.11
11.44
M32
F
White or Caucasian
45.50
c.121-12T>C
c.121-12T>C
Never received ERT
47.03
M33
F
White or Caucasian
29.94
c.1012C>T (Q338X)
c.1171A>G (M391V)
Never received ERT
31.48
M34
M
White or Caucasian
28.17
c.121A>T (M41L)
c.121A>T (M41L)
ERT
29.69
M35
M
White or Caucasian
-6.86
11.23
c.139G>A (G47R)
c.1156C>T (R386C)
No ERT for 4 years
-7.69
12.64
M36
F
Asian Indian
25.72
c.346G>A (G116S)
c.346G>A (G116S)
ERT
27.27
M37
M
Asian Indian
-10.12
19.01
c.346G>A (G116S)
c.346G>A (G116S)
ERT
20.56
M38
F
White or Caucasian
-5.63
16.04
c.1559G>A (W520X)
unknown
ERT
M39
F
White or Caucasian
-3.54
12.08
c.1559G>A (W520X)
unknown
ERT
M41
M
White or Caucasian
35.29
c.121A>T (M41L)
c.498delC (F167Lfs*32)
ERT
36.86
M42
F
White or Caucasian
28.24
c.860C>T (S287L)
c.1055T>C (L352P)
ERT
29.95
M43
M
White or Caucasian
29.04
c.121A>T (M41L)
c.901G>T (G301C)
ERT
30.52
M44
F
White or Caucasian
24.28
c.1171A>G (p.M391V)
c.502G>A (p.G168R)
ERT
25.85
M45
F
White or Caucasian
61.08
c.740G>A (G247D)
c.761A>G (Y254C)
Never received ERT
62.66
M46
F
White or Caucasian
no record
6.92
c.167C>A (T56N)
c.502G>A (G168R)
ERT
-5.54
8.40
M47
F
Some other race
24.33
c.139G>A (G47R)
c.466T>C (F156L)
ERT
25.78
M48
F
White or Caucasian
-7.11
13.23
c.139G>A (G47R)
c.466T>C (F156L)
ERT
-7.66
14.68
M49
M
White or Caucasian
-6.44
7.68
c.1156C>T (R386C)
c.1156C>T (R386C)
ERT
M50
F
White or Caucasian
-3.33
5.65
c.451C>A (P151T)
c.477G>A (W159X)
ERT
-4.81
7.26
M51
M
White or Caucasian
-0.9
2.89
c.451C>A (P151T)
c.477G>A (W159X)
ERT
-0.52
4.50
M52
F
Multiple Races
no record
2.50
c.651_652insG (K218Efs*45)
unknown
Received HSCT 11 months ago
no record
4.60
-2.54
6.21
M53
F
Chinese
23.20
c.1482+5G>C
c.1498G>T (G500C)
No ERT for 13 months
24.37
ERT
M54
F
White or Caucasian
36.26
not tested
not tested
No ERT for 5 years and 9 months
M55
F
White or Caucasian
-3.04
5.39
c.1339G>C (D447H)
unknown
ERT
-4.2
6.80
M56
F
White or Caucasian
-1.44
3.79
c.740G>A (G247D)
c.1451C>A (P484H)
Never received ERT
M57
M
White or Caucasian
0.41
1.13
c.740G>A(G247D)
c.1451C>A (P484H)
Never received ERT
M58
M
White or Caucasian
-4.38
6.78
c.1012C>T (Q338X)
c.181C>G (R61G)
ERT
M59
M
White or Caucasian
-4.14
6.26
c.337A>T (p.I113F)
c.901G>T (p.G301C)
ERT
M60
F
Some other race
26.58
c.901G>T (G301C)
c.1156C>T (R386C)
Never received ERT
M63
F
White or Caucasian
22.72
c.331C>T (Q111X)
c.1365-2A>G
ERT
M64
M
Black or African American
-3.74
5.64
c.633+1G>C
c.1558T>C (W520R)
ERT
M65
M
Black or African American
-2.9
6.50
c.633+1G>C
c.1558T>C (W520R)
ERT
M66
F
White or Caucasian
-2.1
3.34
c.1156C>T (R386C)
unknown
ERT
M67
M
White or Caucasian
-1.55
11.58
c.1171 A>G (M391V)
c.331C>T (Q111X)
ERT
M68
M
White or Caucasian
45.78
c.1156C>T (R386C)
c.181C>T (R61W)
ERT
M69
M
Asian
-3.03
2.33
c.106_111del (p.L36_L37del)
c.1201C>T (H401Y)
ERT
M71
M
White or Caucasian
-3
9.12
c.1219A>C (N407H)
5.81 kb large deletion
ERT
Genotype

h. GAGs 
The results of mono-sulfated KS, di-sulfated KS, KS ratio (the rate of di-sulfated KS among total KS), and C6S 
in urine and blood from patients are summarized in Table 4 and Figure 6. For C6S, the number of available 
control samples was less than for KS, so the "number of samples" and "mean age" differed from KS in Table 
4. Partial correlation coefficients controlling for age between z-score of height and each significant GAG 
(mono-sulfated and di-sulfated KS and urinary C6S) were calculated and summarized in Table 5. 
 
Table 4. Summary of GAG levels in 5 age groups 
Age group 
Number 
of 
samples 
Mean 
age 
Mono-
sulfated KS 
Di-sulfated KS 
KS ratio (%) 
C6S 
Number 
of 
sample
s 
Mean 
age 
Control (urine) 
 
 
 
 
  
 
 
>1, ≤ 5 y 
18 
3.47 
2128 ± 618 
663 ± 263 
23.4 ± 4.6 
N/A 
0 
N/A 
>5, ≤ 10 y 
14 
6.48 
1380 ± 833 
768 ± 439 
36.8 ± 5.6 
164.7 ± 
129.7 
14 
6.48 
>10, ≤ 15 y 
15 
12.75 
971 ± 574 
802 ± 413 
46.5 ± 9.4 
178.1 ± 
104.1 
15 
12.75 
> 15, ≤ 20 
y 
3 
17 
215 ± 96 
271 ± 69 
57.2 ± 4.9 
83.3 ± 17.2 
3 
17 
>20 y 
6 
37.92 
157 ± 45 
255 ± 283 
48.7 ± 18.6 
88.0 ± 19.8 
3 
31.03 
MPS IVA (urine) 
 
 
 
 
 
 
 
>1, ≤ 5 y 
3 
3.73 
9202 ± 1563* 
20081 ± 2603** 
68.6 ± 3.6*** 
727 ± 282 
 
 
>5, ≤ 10 y 
23 
7.24 
9904 ± 
5024*** 
18225 ± 
9116*** 
63.9 ± 8.3*** 
633 ± 398*** 
 
 
>10, ≤ 15 y 
15 
12.36 
8143 ± 
10725* 
12343 ± 
11876** 
65.1 ± 11.1*** 
465 ± 247*** 
 
 
> 15, ≤ 20 
y 
11 
17.7 
2340 ± 
1178*** 
3091 ± 1509*** 
56.7 ± 8.0 
289 ± 189** 
 
 
>20 y 
39 
33.56 
2267 ± 
1391*** 
4033 ± 2286*** 
64.4 ± 7.7 
245 ± 131*** 
  
 
 
 
 
 
 
 
 
 
 
Age group 
Number 
of 
samples 
Mean 
age 
Mono-
sulfated KS 
Di-sulfated KS 
KS ratio (%) 
C6S 
Number 
of 
sample
s 
Mean 
age 
Control (serum) 
 
 
 
 
  
 
 
>1, ≤ 5 y 
4 
2 
1095 ± 223 
229 ± 40 
17.4 ± 1.3 
5.15 ± 2.67 
4 
2 
>5, ≤ 10 y 
17 
7.18 
660 ± 220 
197 ± 59 
23.3 ± 3.6 
2.34 ± 2.01 
17 
7.18 
>10, ≤ 15 y 
10 
12.35 
545 ± 235 
248 ± 88 
32.3 ± 5.0 
2.81 ± 2.29 
10 
12.35 
> 15, ≤ 20 
y 
10 
15.9 
322 ± 123 
118 ± 73 
27.8 ± 14.7 
0.49 ± 0.06 
2 
17 
>20 y 
15 
42.2 
314 ± 109 
86 ± 43 
21.4 ± 7.8 
N/A 
0 
N/A 
MPS IVA (plasma) 
 
 
 
 
 
 
 
>1, ≤ 5 y 
8 
3.13 
1805 ± 514* 
910 ± 229*** 
33.7 ± 4.1*** 
1.97 ± 2.53 
 
 
>5, ≤ 10 y 
22 
7.33 
1556 ± 363*** 
639 ± 227*** 
28.7 ± 6.0** 
1.97 ± 3.88 
 
 
>10, ≤ 15 y 
14 
12.52 
1257 ± 306*** 
509 ± 181*** 
28.4 ± 4.3 
1.12 ± 0.41 
 
 
> 15, ≤ 20 
y 
11 
17.7 
482 ± 90** 
166 ± 45 
25.5 ± 4.6 
1.65 ± 1.04 
 
 
>20 y 
40 
33.54 
493 ± 132*** 
238 ± 76*** 
32.6 ± 6.3 
0.85 ± 0.43 
 
 
*p < 0.05, **p < 0.01, ***p < 0.001 
 
 

 
 
100
1000
10000
100000
0
10
20
30
40
50
60
Urine monosulfated KS
(ng/mg creatinine)
0
500
1000
1500
2000
2500
3000
0
10
20
30
40
50
60
Monosulfated KS in blood
(ng/mL)
ERT
Untreated
HSCT
Control
10
100
1000
10000
100000
0
10
20
30
40
50
60
Urine di-sulfated KS
(ng/mg creatinine)
0
200
400
600
800
1000
1200
1400
0
10
20
30
40
50
60
Di-sulfated KS in blood
(ng/mL)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0
10
20
30
40
50
60
Urine KS ratio
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0
10
20
30
40
50
60
KS ratio in blood
0
200
400
600
800
1000
1200
1400
1600
1800
0
10
20
30
40
50
60
Age
(years)
Urine C6S (ng/mg creatinine) 
0
4
8
12
16
20
0
10
20
30
40
50
60
C6S in blood (ng/mL)

 
Table 5. The partial correlation coefficient (r) between each GAG and the z-score of height of patients 
under 20 years old, controlling for age 
  
Number of subjects to 
calculate the r value 
r 
p 
Urine di-sulfated KS 
49 
-0.484 
0.00049 
Urine mono-sulfated KS 
49 
-0.42 
0.00293 
Plasma di-sulfated KS 
50 
-0.041 
0.777 
Plasma mono-sulfated KS 
50 
-0.181 
0.213 
Urine C6S 
49 
-0.282 
0.0517 
 
 
Conclusions and plan 
 
Collagen type I: This is not a significant biomarker for pediatric patients. Several papers reported that the 
expression level of mRNA encoding collagen type I increased in chondrocytes from human MPS IVA patients 
[13, 14]. Comprehensive proteomic analysis of 6-week-old mouse femurs also showed that collagen alpha-1 
and 2 (Uniprot IDs: P11087 and Q01149) increased in MPS IVA [15]. Therefore, we predicted that patients 
would present with higher concentration levels than the control group. However, only adult patients showed 
such differences. On the contrary, other age groups showed lower concentration in patients, even though it 
was not statistically significant. Because human collagen type I has a molecular weight of approximately 300 
kDa, much larger than NT-proCNP, and is surrounded by hydroxyapatite in bone [16–18]It could be pretty 
difficult for collagen type I to escape from bone and cartilage and enter the bloodstream compared to NT-
proCNP, thereby preventing higher concentrations in the blood of patients. We should measure smaller 
peptides related to collagen type I. 
 
Collagen type II: This is not a significant biomarker for pediatric patients. Blood procollagen II C-terminal 
propeptide (CPII) and/or urinary C-terminal telopeptide of type II collagen (CTX-II) are currently the two primary 
markers of type II collagen metabolism in osteoarthritis [19–21], joint injuries [22], and Kashin-Beck disease 
(KBD) [23]. CPII reflects the synthesis of type II collagen during cartilage repair and remodeling [24–26], while 
CTX-II is a marker of type II collagen breakdown, reflecting cartilage catabolism [21, 27]. We will consider 
focusing on these peptides related to collagen type II. 
 
Collagen type X: No significant findings were obtained. Also, the kit I used 
(https://www.novusbio.com/products/collagen-x-elisa-kit_nbp2-75826) is no longer manufactured. We will have 
to purchase other kits if we continue to measure this biomarker. 
 
NTproCNP in humans 
This is currently the most promising biomarker. We will measure this biomarker in human urine and a novel 
MPS IVA rat model. In addition, to increase specificity, we are collaborating with a mass spectrometer 
manufacturer (SCIEX, Framingham, MA) to establish a method to measure this biomarker by mass 
spectrometry. 
 
GAGs 
Urinary di-sulfated KS may not be a pharmacodynamic biomarker. Complete data analysis is ongoing. 
 
Other biomarkers: 
Figure 6: Glycosaminoglycan levels in urine and blood. Mono-sulfated KS, di-sulfated KS, KS ratio (di-sulfated KS to total KS), 
and C6S levels in urine and blood are summarized in scatter plots. The horizontal axes indicate the age (years) of each patient or 
control. For urinary mono-sulfated and di-sulfated KS levels, the vertical axes are shown on a base-10 logarithmic scale. Round red 
dots indicate patients who ever received ERT. Purple squares are indicated for patients who received HSCT. Gray triangles 
represent patients who never received ERT or HSCT. Green x marks represent controls. For blood samples, plasma samples were 
used for patients and serum for controls. 

As I showed in the previous review [28], IL-1β, IL-6, IL-18, TNF-α, MMPs may be among the other candidates 
to measure. We are measuring these biomarkers with the Luminex™ xMAP™ INTELLIFLEX system by 
technicians at our institute. The results will be available shortly.  
 
References 
 
1. Martino, A. T.; Herzog, R. W.; Anegon, I.; Adjali, O. Adeno-Associated Virus, Methods and Protocols. 
Methods Mol Biology, 2011, 807, 259–272. https://doi.org/10.1007/978-1-61779-370-7_11. 
2. Khan, S. A.; Mason, R. W.; Giugliani, R.; Orii, K.; Fukao, T.; Suzuki, Y.; Yamaguchi, S.; Kobayashi, H.; Orii, 
T.; Tomatsu, S. Glycosaminoglycans Analysis in Blood and Urine of Patients with Mucopolysaccharidosis. 
Molecular genetics and metabolism, 2018, 125 (1–2), 44–52. https://doi.org/10.1016/j.ymgme.2018.04.011. 
3. Khan, S. A.; Mason, R. W.; Kobayashi, H.; Yamaguchi, S.; Tomatsu, S. Advances in Glycosaminoglycan 
Detection. Molecular genetics and metabolism, 2020, 130 (2), 101–109. 
https://doi.org/10.1016/j.ymgme.2020.03.004. 
4. Kubaski, F.; Mason, R. W.; Nakatomi, A.; Shintaku, H.; Xie, L.; Vlies, N. N. van; Church, H.; Giugliani, R.; 
Kobayashi, H.; Yamaguchi, S.; et al. Newborn Screening for Mucopolysaccharidoses: A Pilot Study of 
Measurement of Glycosaminoglycans by Tandem Mass Spectrometry. Journal of inherited metabolic disease, 
2017, 40 (1), 151–158. https://doi.org/10.1007/s10545-016-9981-6. 
5. Kubaski, F.; Suzuki, Y.; Orii, K.; Giugliani, R.; Church, H. J.; Mason, R. W.; Dung, V. C.; Ngoc, C. T.; 
Yamaguchi, S.; Kobayashi, H.; et al. Glycosaminoglycan Levels in Dried Blood Spots of Patients with 
Mucopolysaccharidoses and Mucolipidoses. Molecular genetics and metabolism, 2017, 120 (3), 247–254. 
https://doi.org/10.1016/j.ymgme.2016.12.010. 
6. Tomatsu, S.; Shimada, T.; Mason, R. W.; Montano, A. M.; Kelly, J.; LaMarr, W. A.; Kubaski, F.; Giugliani, R.; 
Guha, A.; Yasuda, E.; et al. Establishment of Glycosaminoglycan Assays for Mucopolysaccharidoses. 
Metabolites, 2014, 4 (3), 655–679. https://doi.org/10.3390/metabo4030655. 
7. Hintze, J. P.; Tomatsu, S.; Fujii, T.; Montano, A. M.; Yamaguchi, S.; Suzuki, Y.; Fukushi, M.; Ishimaru, T.; 
Orii, T. Comparison of Liquid Chromatography-Tandem Mass Spectrometry and Sandwich ELISA for 
Determination of Keratan Sulfate in Plasma and Urine. Biomarker insights, 2011, 6, 69–78. 
https://doi.org/10.4137/bmi.s7451. 
8. Shimada, T.; Tomatsu, S.; Mason, R. W.; Yasuda, E.; Mackenzie, W. G.; Hossain, J.; Shibata, Y.; Montano, 
A. M.; Kubaski, F.; Giugliani, R.; et al. Di-Sulfated Keratan Sulfate as a Novel Biomarker for 
Mucopolysaccharidosis II, IVA, and IVB. JIMD reports, 2015, 21, 1–13. 
https://doi.org/10.1007/8904_2014_330. 
9. Tomatsu, S.; Kubaski, F.; Sawamoto, K.; Mason, R. W.; Yasuda, E.; Shimada, T.; Montano, A. M.; 
Yamaguchi, S.; Suzuki, Y.; Orii, T. Newborn Screening and Diagnosis of Mucopolysaccharidoses: Application 
of Tandem Mass Spectrometry. Nihon Masu Sukuriningu Gakkai Shi, 2014, 24, 19–37. 
10. Hendriksz, C. J.; Burton, B.; Fleming, T. R.; Harmatz, P.; Hughes, D.; Jones, S. A.; Lin, S.; Mengel, E.; 
Scarpa, M.; Valayannopoulos, V.; et al. Efficacy and Safety of Enzyme Replacement Therapy with BMN 110 
(Elosulfase Alfa) for Morquio A Syndrome (Mucopolysaccharidosis IVA): A Phase 3 Randomised Placebo‐
controlled Study. J. Inherit. Metab. Dis., 2014, 37 (6), 979–990. https://doi.org/10.1007/s10545-014-9715-6. 
11. Olney, R. C.; Prickett, T. C. R.; Espiner, E. A.; Mackenzie, W. G.; Duker, A. L.; Ditro, C.; Zabel, B.; 
Hasegawa, T.; Kitoh, H.; Aylsworth, A. S.; et al. C-Type Natriuretic Peptide Plasma Levels Are Elevated in 
Subjects With Achondroplasia, Hypochondroplasia, and Thanatophoric Dysplasia. J Clin Endocrinol 
Metabolism, 2015, 100 (2), E355–E359. https://doi.org/10.1210/jc.2014-2814. 

12. Klag, K. A.; Horton, W. A. Advances in Treatment of Achondroplasia and Osteoarthritis. Hum. Mol. Genet., 
2016, 25 (R1), R2–R8. https://doi.org/10.1093/hmg/ddv419. 
13. Franceschi, L. D.; Roseti, L.; Desando, G.; Facchini, A.; Grigolo, B. A Molecular and Histological 
Characterization of Cartilage from Patients with Morquio Syndrome. Osteoarthr Cartilage, 2007, 15 (11), 1311–
1317. https://doi.org/10.1016/j.joca.2007.04.008. 
14. Dvorak-Ewell, M.; Wendt, D.; Hague, C.; Christianson, T.; Koppaka, V.; Crippen, D.; Kakkis, E.; Vellard, M. 
Enzyme Replacement in a Human Model of Mucopolysaccharidosis IVA In Vitro and Its Biodistribution in the 
Cartilage of Wild Type Mice. PLoS ONE, 2010, 5 (8), e12194. https://doi.org/10.1371/journal.pone.0012194. 
15. Álvarez, J. Victor.; Bravo, S. B.; Chantada-Vázquez, M. P.; Pena, C.; Colón, C.; Tomatsu, S.; Otero-
Espinar, F. J.; Couce, M. L. Morquio A Syndrome: Identification of Differential Patterns of Molecular Pathway 
Interactions in Bone Lesions. Int. J. Mol. Sci., 2024, 25 (6), 3232. https://doi.org/10.3390/ijms25063232. 
16. Sorokina, L. V.; Shahbazian-Yassar, R.; Shokuhfar, T. Collagen Biomineralization: Pathways, Mechanisms, 
and Thermodynamics. Emergent Mater., 2021, 4 (5), 1205–1224. https://doi.org/10.1007/s42247-021-00226-1. 
17. Bakkalci, D.; Micalet, A.; Hosni, R. A.; Moeendarbary, E.; Cheema, U. Associated Changes in Stiffness of 
Collagen Scaffolds during Osteoblast Mineralisation and Bone Formation. BMC Res. Notes, 2022, 15 (1), 310. 
https://doi.org/10.1186/s13104-022-06203-z. 
18. Garnero, P. The Role of Collagen Organization on the Properties of Bone. Calcif. Tissue Int., 2015, 97 (3), 
229–240. https://doi.org/10.1007/s00223-015-9996-2. 
19. Conrozier, T.; Ferrand, F.; Poole, A. R.; Verret, C.; Mathieu, P.; Ionescu, M.; Vincent, F.; Piperno, M.; 
Spiegel, A.; Vignon, E. Differences in Biomarkers of Type II Collagen in Atrophic and Hypertrophic 
Osteoarthritis of the Hip: Implications for the Differing Pathobiologies. Osteoarthr. Cartil., 2007, 15 (4), 462–
467. https://doi.org/10.1016/j.joca.2006.09.002. 
20. Arunrukthavon, P.; Heebthamai, D.; Benchasiriluck, P.; Chaluay, S.; Chotanaphuti, T.; Khuangsirikul, S. 
Can Urinary CTX-II Be a Biomarker for Knee Osteoarthritis? Arthroplasty, 2020, 2 (1), 6. 
https://doi.org/10.1186/s42836-020-0024-2. 
21. Cheng, H.; Hao, B.; Sun, J.; Yin, M. C-Terminal Cross-Linked Telopeptides of Type II Collagen as 
Biomarker for Radiological Knee Osteoarthritis: A Meta-Analysis. CARTILAGE, 2020, 11 (4), 512–520. 
https://doi.org/10.1177/1947603518798884. 
22. Nicolini, A.; Mansur, N.; Dreyfuss, J.; Ejnisman, B.; Cohen, M.; Astur, D. Avaliação Do Biomarcador CTX-II 
Em Pacientes Com Ruptura Do Ligamento Cruzado Anterior: Estudo Piloto*. Rev. Bras. Ortop., 2020, 56 (03), 
326–332. https://doi.org/10.1055/s-0040-1712139. 
23. Song, Q. Q.; Sun, L. Y.; Li, C. H.; Liu, Y. J.; Cui, S. L.; Liu, Y. Q.; Cao, Y. H.; Pei, J. R.; Wang, Y.; Lian, W.; 
et al. The Urinary Levels of CTX-II, C2C, PYD, and Helix-II Increased among Adults with KBD: A Cross-
Sectional Study. J. Orthop. Surg. Res., 2019, 14 (1), 328. https://doi.org/10.1186/s13018-019-1392-6. 
24. Cahue, S.; Sharma, L.; Dunlop, D.; Ionescu, M.; Song, J.; Lobanok, T.; King, L.; Poole, A. R. The Ratio of 
Type II Collagen Breakdown to Synthesis and Its Relationship with the Progression of Knee Osteoarthritis. 
Osteoarthr. Cartil., 2007, 15 (7), 819–823. https://doi.org/10.1016/j.joca.2007.01.016. 
25. Conrozier, T.; Poole, A. R.; Ferrand, F.; Mathieu, P.; Vincent, F.; Piperno, M.; Verret, C.; Ionescu, M.; 
Vignon, E. Serum Concentrations of Type II Collagen Biomarkers (C2C, C1, 2C and CPII) Suggest Different 
Pathophysiologies in Patients with Hip Osteoarthritis. Clin. Exp. Rheumatol., 2008, 26 (3), 430–435. 

26. Mullan, R. H.; Matthews, C.; Bresnihan, B.; FitzGerald, O.; King, L.; Poole, A. R.; Fearon, U.; Veale, D. J. 
Early Changes in Serum Type Ii Collagen Biomarkers Predict Radiographic Progression at One Year in 
Inflammatory Arthritis Patients after Biologic Therapy. Arthritis Rheum., 2007, 56 (9), 2919–2928. 
https://doi.org/10.1002/art.22843. 
27. Bay-Jensen, A.-C.; Tabassi, N. C.; Sondergaard, L. V.; Andersen, T. L.; Dagnaes-Hansen, F.; Garnero, P.; 
Kassem, M.; Delaissé, J.-M. The Response to Oestrogen Deprivation of the Cartilage Collagen Degradation 
Marker, CTX-II, Is Unique Compared with Other Markers of Collagen Turnover. Arthritis Res. Ther., 2009, 11 
(1), R9. https://doi.org/10.1186/ar2596. 
28. Ago, Y.; Rintz, E.; Musini, K. S.; Ma, Z.; Tomatsu, S. Molecular Mechanisms in Pathophysiology of 
Mucopolysaccharidosis and Prospects for Innovative Therapy. Int. J. Mol. Sci., 2024, 25 (2), 1113. 
https://doi.org/10.3390/ijms25021113. 
29. Doherty, C.; Stapleton, M.; Piechnik, M.; Mason, R. W.; Mackenzie, W. G.; Yamaguchi, S.; Kobayashi, H.; 
Suzuki, Y.; Tomatsu, S. Effect of Enzyme Replacement Therapy on the Growth of Patients with Morquio A. J. 
Hum. Genet., 2019, 64 (7), 625–635. https://doi.org/10.1038/s10038-019-0604-6. 
30. Olney, R. C.; Permuy, J. W.; Prickett, T. C. R.; Han, J. C.; Espiner, E. A. Amino‐terminal Propeptide of C‐
type Natriuretic Peptide (NTproCNP) Predicts Height Velocity in Healthy Children. Clin. Endocrinol., 2012, 77 
(3), 416–422. https://doi.org/10.1111/j.1365-2265.2012.04392.x. 
  
Discussion 
Unmet goals 
Aim 1.  
We have reached our goal of over 60 actively enrolled participants and will continue to have follow-up visits as 
they are interested.  
1. We will not have enough to achieve 4 visits; therefore, we will resubmit the grant based on the 
achievements. 
2. We will summarize the data and will publish each test data. 
 
Aim 2. 
1. We will continue to assay the biomarkers, including glycosaminoglycans (C6S and KS), Collagen, and 
Inflammatory factors. 
2. We will submit the manuscripts with data of biological biomarkers. 
 
 
PUBLICATIONS (other achievements) 
 
2022  
Poletto E, Colella P, Pimentel Vera LN, Khan S, Tomatsu S, Baldo G, Gomez-Ospina N. Improved engraftment 
and therapeutic efficacy by human genome-edited hematopoietic stem cells with Busulfan-based 
myeloablation. Mol Ther Methods Clin Dev. 2022 Apr 19;25:392-409. doi: 10.1016/j.omtm.2022.04.009. 
PMID: 35573043; PMCID: PMC9065050.  
Rintz E, Węgrzyn G, Fujii T, Tomatsu S. Molecular Mechanism of Induction of Bone Growth by the C-Type 
Natriuretic Peptide. Int J Mol Sci. 2022 May 25;23(11):5916. doi: 10.3390/ijms23115916. PMID: 
35682595; PMCID: PMC9180634.  
Leal AF, Fnu N, Benincore-Flórez E, Herreño-Pachón AM, Echeverri-Peña OY, Alméciga-Díaz CJ, Tomatsu S. 
The landscape of CRISPR/Cas9 for inborn errors of metabolism. Mol Genet Metab. 2023 
Jan;138(1):106968. doi: 10.1016/j.ymgme.2022.106968. Epub 2022 Dec 7. PMID: 36525790; PMCID: 
PMC10199355.  
Jalal K, Carter RL, Barczykowski A, Tomatsu S, Langan TJ. A Roadmap for Potential Improvement of Newborn 
Screening for Inherited Metabolic Diseases Following Recent Developments and Successful Applications 
of Bivariate Normal Limits for Pre-Symptomatic Detection of MPS I, Pompe Disease, and Krabbe Disease. 

Int J Neonatal Screen. 2022 Nov 15;8(4):61. doi: 10.3390/ijns8040061. PMID: 36412587; PMCID: 
PMC9680456.  
Celik B, Cicek K, Leal AF, Tomatsu S. Regulation of Molecular Targets in Osteosarcoma Treatment. Int J Mol 
Sci. 2022 Oct 20;23(20):12583. doi: 10.3390/ijms232012583. PMID: 36293439; PMCID: PMC9604206.  
Piechnik M, Amendum PC, Sawamoto K, Stapleton M, Khan S, Fnu N, Álvarez V, Pachon AMH, Danos O, 
Bruder JT, Karumuthil-Melethil S, Tomatsu S. Sex Difference Leads to Differential Gene Expression 
Patterns and Therapeutic Efficacy in Mucopolysaccharidosis IVA Murine Model Receiving AAV8 Gene 
Therapy. Int J Mol Sci. 2022 Oct 21;23(20):12693. doi: 10.3390/ijms232012693. PMID: 36293546; 
PMCID: PMC9604118.  
Pan X, Taherzadeh M, Bose P, Heon-Roberts R, Nguyen ALA, Xu T, Pará C, Yamanaka Y, Priestman DA, Platt 
FM, Khan S, Fnu N, Tomatsu S, Morales CR, Pshezhetsky AV. Glucosamine amends CNS pathology in 
mucopolysaccharidosis IIIC mouse expressing misfolded HGSNAT. J Exp Med. 2022 Aug 
1;219(8):e20211860. doi: 10.1084/jem.20211860. Epub 2022 Jun 15. PMID: 35704026; PMCID: 
PMC9204472.  
Rintz E, Higuchi T, Kobayashi H, Galileo DS, Wegrzyn G, Tomatsu S. Promoter considerations in the design of 
lentiviral vectors for use in treating lysosomal storage diseases. Mol Ther Methods Clin Dev. 2021 Nov 
24;24:71-87. doi: 10.1016/j.omtm.2021.11.007. PMID: 34977274; PMCID: PMC8688940.  
2023  
Leal AF, Fnu N, Benincore-Flórez E, Herreño-Pachón AM, Echeverri-Peña OY, Alméciga-Díaz CJ, Tomatsu S. 
The landscape of CRISPR/Cas9 for inborn errors of metabolism. Mol Genet Metab. 2023 
Jan;138(1):106968. doi: 10.1016/j.ymgme.2022.106968. Epub 2022 Dec 7. PMID: 36525790; PMCID: 
PMC10199355.  
Khan SA, Nidhi FNU, Amendum PC, Tomatsu S. Detection of Glycosaminoglycans in Biological Specimens. 
Methods Mol Biol. 2023;2619:3-24. doi: 10.1007/978-1-0716-2946-8_1. PMID: 36662458; PMCID: 
PMC10199356.  
Rintz E, Herreño-Pachón AM, Celik B, Nidhi F, Khan S, Benincore-Flórez E, Tomatsu S. Bone Growth Induction 
in Mucopolysaccharidosis IVA Mouse. Int J Mol Sci. 2023 Jun 8;24(12):9890. doi: 10.3390/ijms24129890. 
PMID: 37373036; PMCID: PMC10298227.  
Theroux MC, DiCindio S, Averill LW, Pizarro C, Oommen A, Bober MB, Ditro C, Campbell J, Duker AL, Jones T, 
Passi V, Barth P, Schmidt RJ, Little M, Mackenzie S, Tomatsu S, Mackenzie WG. Tracheal Narrowing 
and Its Impact on Anesthesia Care in Patients With Morquio A (Mucopolysaccharidosis Type IVA): An 
Observational 
Study. 
Anesth 
Analg. 
2023 
Nov 
1;137(5):1075-1083. 
doi: 
10.1213/ANE.0000000000006513. Epub 2023 May 9. PMID: 37862598; PMCID: PMC10634225.  
Leal AF, Celik B, Fnu N, Khan S, Tomatsu S, Alméciga-Díaz CJ. Iron oxide-coupled CRISPR-nCas9-based 
genome editing assessment in mucopolysaccharidosis IVA mice. Mol Ther Methods Clin Dev. 2023 Nov 
7;31:101153. doi: 10.1016/j.omtm.2023.101153. PMID: 38107675; PMCID: PMC10724691.  
Leal AF, Alméciga-Díaz CJ, Tomatsu S. Mucopolysaccharidosis IVA: Current Disease Models and Drawbacks. 
Int J Mol Sci. 2023 Nov 9;24(22):16148. doi: 10.3390/ijms242216148. PMID: 38003337; PMCID: 
PMC10671113.  
2024  
Ago Y, Rintz E, Musini KS, Ma Z, Tomatsu S. Molecular Mechanisms in Pathophysiology of 
Mucopolysaccharidosis and Prospects for Innovative Therapy. Int J Mol Sci. 2024 Jan 17;25(2):1113. 
doi: 10.3390/ijms25021113.PMID: 38256186. 
Khan SA, Nidhi F, Leal AF, Celik B, Herreño-Pachón AM, Saikia S, Benincore-Flórez E, Ago Y, Tomatsu S. 
Glycosaminoglycans in mucopolysaccharidoses and other disorders. Adv Clin Chem.  2024;122:1-52. 
doi: 10.1016/bs.acc.2024.06.011. Epub 2024 Jul 23. PMID: 39111960.  
Leal AF, Herreno-Pachón AM, Benincore-Flórez E, Karunathilaka A, Tomatsu S. Current Strategies for 
Increasing Knock-In Efficiency in CRISPR/Cas9-Based Approaches. Int J Mol Sci. 2024 Feb 
20;25(5):2456. doi: 10.3390/ijms25052456. 
Álvarez JV, Bravo SB, Chantada-Vázquez MP, Pena C, Colón C, Tomatsu S, Otero-Espinar FJ, Couce ML. 
Morquio A Syndrome: Identification of Differential Patterns of Molecular Pathway Interactions in Bone 
Lesions. Int J Mol Sci. 2024 Mar 12;25(6):3232. doi: 10.3390/ijms25063232.PMID: 38542208 
Rintz E, Celik B, Fnu N, Herreño-Pachón AM, Khan S, Benincore-Flórez E, Tomatsu S. Adeno-associated virus-
based gene therapy delivering combinations of two growth-associated genes to MPS IVA mice. Mol Ther 
Nucleic Acids. 2024 May 7;35(2):102211. doi: 10.1016/j.omtn.2024.102211. eCollection 2024 Jun 11. 
PMID: 38831899. 

Bradford A, Klipner K, Mackenzie WSG, Tomatsu S. Accelerating Medicines Partnership Bespoke Gene 
Therapy Consortium for Rare Disorders. Nippon Rynshou. 2024 May 82;5 769-777.Celik B, Leal AF, 
Tomatsu S. Potential Targeting Mechanisms for Bone-Directed Therapies. Int J Mol Sci. 2024, 25(15), 
8339; https://doi.org/10.3390/ijms25158339. 
Celik B, Rintz E, Sansanwal N, Khan S, Bigger B, Tomatsu S. Lentiviral Vector-Mediated Ex Vivo Hematopoietic 
Stem Cell Gene Therapy for MPS IVA Murine Model. Hum Gene Ther. 2024 Oct 24. doi: 
10.1089/hum.2024.094. 
Herreño-Pachón AM, Sawamoto K, Stapleton M, Khan S, Piechnik M, J. Álvarez V, Tomatsu S. AAV Gene 
Transfer Ameliorates the Progression of Skeletal Lesions in Mucopolysaccharidosis IVA Mice. Hum Gene 
Ther. 2024 Oct 25. doi: 10.1089/hum.2024.096.  
 
2025 
Khan S, Ago Y, Tomatsu S. VIEWPOINT: AAV gene therapy for rare disorders: generate critical data on safety 
and efficacy. Med (accepted). 
Khan SA, Álvarez JA, Nidhi F, Florez EB, Tomatsu S. Evaluation of AAV vectors with tissue-specific or 
ubiquitous promoters in a mouse model of mucopolysaccharidosis type IVA. Mol Ther Methods Clin Dev. 
(accepted). 

Supplementary Table 1 (3/11/2025) 
 
Study 
ID 
Sex 
Age (Years) at 
Enrollment 
Race 
Ethnicity 
M01 
F 
17 
White or Caucasian 
Non-Hispanic or Latino 
M02 
F 
38 
Asian 
Non-Hispanic or Latino 
M03 
F 
24 
White or Caucasian 
Non-Hispanic or Latino 
M04 
F 
42 
White or Caucasian 
Non-Hispanic or Latino 
M05 
F 
18 
White or Caucasian 
Non-Hispanic or Latino 
M06 
F 
19 
White or Caucasian 
Non-Hispanic or Latino 
M07 
M 
32 
White or Caucasian 
Non-Hispanic or Latino 
M08 
M 
8 
White or Caucasian 
Hispanic or Latino 
M10 
M 
10 
White or Caucasian 
Non-Hispanic or Latino 
M11 
F 
14 
White or Caucasian 
Non-Hispanic or Latino 
M12 
F 
26 
White or Caucasian 
Non-Hispanic or Latino 
M13 
M 
12 
Black or African American 
Non-Hispanic or Latino 
M14 
F 
16 
White or Caucasian 
Hispanic or Latino 
M15 
M 
5 
White or Caucasian 
Non-Hispanic or Latino 
M16 
M 
5 
Multiple Races 
Non-Hispanic or Latino 
M19 
F 
9 
Black or African American 
Non-Hispanic or Latino 
M20 
F 
9 
White or Caucasian 
Non-Hispanic or Latino 
M21 
M 
5 
White or Caucasian 
Non-Hispanic or Latino 
M22 
M 
8 
White or Caucasian 
Non-Hispanic or Latino 
M25 
M 
41 
White or Caucasian 
Non-Hispanic or Latino 
M26 
M 
11 
Multiple Races 
Hispanic or Latino 
M27 
M 
9 
White or Caucasian 
Hispanic or Latino 
M28 
F 
30 
Multiple Races 
Non-Hispanic or Latino 
M30 
F 
43 
White or Caucasian 
Non-Hispanic or Latino 
M31 
M 
9 
Black or African American 
Non-Hispanic or Latino 
M32 
F 
45 
White or Caucasian 
Non-Hispanic or Latino 
M33 
F 
29 
White or Caucasian 
Non-Hispanic or Latino 
M34 
M 
27 
White or Caucasian 
Non-Hispanic or Latino 
M35 
M 
11 
Other 
Hispanic or Latino 
M36 
F 
25 
Other 
Non-Hispanic or Latino 
M37 
M 
18 
Other 
Non-Hispanic or Latino 
M41 
M 
35 
White or Caucasian 
Non-Hispanic or Latino 
M42 
F 
27 
White or Caucasian 
Non-Hispanic or Latino 
M43 
M 
28 
White or Caucasian 
Non-Hispanic or Latino 
M44 
F 
23 
White or Caucasian 
Non-Hispanic or Latino 
M45 
F 
60 
White or Caucasian 
Non-Hispanic or Latino 
M46 
F 
6 
White or Caucasian 
Hispanic or Latino 
M47 
F 
23 
White or Caucasian 
Hispanic or Latino 
M48 
F 
12 
White or Caucasian 
Hispanic or Latino 
M49 
M 
6 
White or Caucasian 
Hispanic or Latino 
M50 
F 
4 
White or Caucasian 
Non-Hispanic or Latino 
M51 
M 
2 
White or Caucasian 
Non-Hispanic or Latino 
M52 
F 
3 
Multiple Races 
Hispanic or Latino 
M53 
F 
22 
Asian 
Non-Hispanic or Latino 
M54 
F 
35 
White or Caucasian 
Non-Hispanic or Latino 
M55 
F 
4 
White or Caucasian 
Non-Hispanic or Latino 
M56 
F 
3 
White or Caucasian 
Non-Hispanic or Latino 
M57 
M 
10 months 
White or Caucasian 
Non-Hispanic or Latino 
M58 
M 
6 
White or Caucasian 
Non-Hispanic or Latino 
M59 
M 
5 
White or Caucasian 
Non-Hispanic or Latino 

M60 
F 
25 
Other 
Hispanic or Latino 
M63 
F 
22 
White or Caucasian 
Non-Hispanic or Latino 
M64 
M 
5 
Multiple Races 
Non-Hispanic or Latino 
M65 
M 
6 
Multiple Races 
Non-Hispanic or Latino 
M66 
F 
3 
White or Caucasian 
Hispanic or Latino 
M67 
M 
11 
White or Caucasian 
Non-Hispanic or Latino 
M68 
M 
45 
White or Caucasian 
Hispanic or Latino 
M69 
M 
2 
Asian 
Non-Hispanic or Latino 
M70 
M 
13 
White or Caucasian 
Non-Hispanic or Latino 
M71 
M 
8 
White or Caucasian 
Non-Hispanic or Latino 
M72 
M 
2 
Asian 
Hispanic or Latino 
M73 
F 
3 
White or Caucasian 
Non-Hispanic or Latino 
M74 
F 
37 
White or Caucasian  
Non-Hispanic or Latino 
M76 
F 
10 months 
White or Caucasian 
Non-Hispanic or Latino 
M77 
F 
2 
White or Caucasian 
Non-Hispanic or Latino 
M78 
M 
11 
White or Caucasian 
Non-Hispanic or Latino 
 
 
Supplementary Table 2 (3/11/2025) 
 
Estimated Number of Actively Enrolled Participants to Complete Each Study Visit Before May 2026 
Baseline 
66 
18 months 
62 
36 months 
50 
54 months 
0 
 
 
 
ClinicalTrials.gov Protocol Registration and Results System (PRS) 
 
750932-25 NCT05284006 Non-invasive Functional Assessment and Pathogenesis of Morquio A (NIFAMA) 
 
NIH: Study Record | Beta ClinicalTrials.gov 
Clinicaltrials.gov: Non-invasive Functional Assessment and Pathogenesis of Morquio A - Full Text View - 
ClinicalTrials.gov 
 
 
 
 

Describe briefly what you plan to do during the next reporting period to accomplish the goals and 
objectives. 
We have reached our goal of over 60 actively enrolled participants and will continue to have follow-up visits as 
they are interested.  
1. We will not have enough to achieve 4 visits because of the initial delay due to COVID19 pandemic. We 
will accommodate the patients as much as possible to increase the number of visits in total. We will also 
resubmit the grant to accomplish 4 visits. 
2. We will summarize the data and will publish each test data in the 5th year period. 
 
3. We will continue to assay the biomarkers, including glycosaminoglycans (C6S and KS), Nt-pro-CNP, 
Collagen, and Inflammatory factor and will correlate these biological biomarkers with the clinical 
phenotype, especially skeletal symptoms. We will submit the manuscripts with data of biological 
biomarkers. 
 
 Discuss efforts to ensure that the approach is scientifically rigorous and results are robust and 
unbiased. Remember that significant changes in objectives and scope require prior approval of the 
agency (e.g., NIH Grants Policy Statement, 8.1.2). 
 Include any important modifications to the original plans. Provide a scientific justification for any 
changes involving research with human subjects or vertebrate animals. A detailed description of such 
changes must be provided under Changes.