Abstract
Background:
A physical symptom score (PSS) for the mucopolysaccharidosis (MPS) disorders has been developed to quantitate the somatic burden of disease across multiple organ systems. Studies have demonstrated the sensitivity and its relationship to age, IQ and adaptive functioning of the PSS in older children. With the onset of newborn screening, there is an increased need to characterize the somatic symptoms in the earliest stages of life, especially for young children under 36 months of age. Consequently, a new scale, Infant Physical Symptom Score (IPSS), was developed to score physical symptoms in infants and toddlers.
Objective:
Part I.
To create a measure to quantify somatic burden in patients with MPS disorders under 36 months of age. The IPSS assess outcomes and changes in somatic disease in individuals with MPS disorders diagnosed very early in life.
Part II.
To determine the relationship between IPSS and other measures to evaluate its validity and utility, a) we evaluated the relationship between the IPSS and PSS in the same patients with MPS I over time to determine if the two scales are measuring the same concepts, and b) we evaluated the association between IPSS and a functional adaptive measure over time with a focus on the age at first treatment (under 36 months) to determine if the IPSS has predictive value.
Methods:
Part I.
The Infant Physical Symptom Score (IPSS) for the infant population in MPS disorders was established using data from 39 patients enrolled in the Lysosomal Disease Network longitudinal MPS I study (U54NS065768). All of these patients had Hurler syndrome (MPS IH) and underwent hematopoietic stem cell transplant (HSCT) at the University of Minnesota. Items for the IPSS were selected by reviewing CRFs prepared for the MPS I longitudinal study and examining medical records of these patients prior to HSCT based on the knowledge gained from the development of the PSS.
Part II.
Of those 39 patients, a subset of 19 were all seen 9 to 12 years post HSCT. Having retrospectively calculated their IPSS prior to HSCT, we categorized them by age at HSCT, and examined their most recent PSS along with Composite and Daily Living Skills scores on the Vineland Adaptive Behavior Scales – Second Edition (VABS-II).
Results and Conclusion:
The total score on the IPSS collected prior to transplant differed by patient’s age at transplant, as expected in this progressive condition. Those transplanted at ≤12 months of age had a mean score of 7.4, which was significantly lower, suggesting less somatic disease burden, compared to those transplanted at >12 to ≤24 months (mean 11.8) and >24 to ≤36 months (mean 13.6). Higher IPSS reflects more evidence of somatic disease burden and lower IPSS reflects less evidence of disease burden. Nine to 12 years later, the severity level as measured by the PSS was comparable to severity on the IPSS suggesting that the two scales are measuring similar concepts. Retrospectively calculated pre-transplant IPSS were negatively associated with higher VABS-II Composite scores 9–12 years later (p value-0.015) and to a lesser extent Daily Living Skills scores (p value-0.081). We conclude that the IPSS appears to be a useful approach to quantifying the somatic disease burden of MPS IH patients under 36 months of age.
Keywords: Hurler syndrome, Infant Physical Symptom Score, Adaptive behavior, Physical Symptom Score, somatic burden of disease, Hematopoietic stem cell transplant
1. Introduction:
Mucopolysaccharidosis type I, or MPS I, is an autosomal recessive lysosomal disorder resulting from deficiency or absence of alpha-L-iduronidase [1, 2]. MPS I affects almost all organ systems of the body. MPS I has a spectrum of clinical severity and historically was divided into three phenotypes: severe disease; Hurler syndrome or MPS IH, an attenuated phenotype; Scheie syndrome or MPS IS, and intermediate disease; Hurler-Scheie syndrome or MPS IHS [3, 4, 5, 6]. Currently hematopoietic stem cell transplant (HSCT) is the standard of care for MPS IH [7, 8, 9,10, 11]. Research studies have confirmed the benefit of early treatment for MPS IH, and cognitive and somatic outcomes of HSCT are better the earlier the transplant is performed [12, 13, 14,15]. In addition to age at HSCT, cognitive level pre-transplant is also predictive of cognition post-HSCT [16,15]. However, the somatic disease burden prior to transplant and its association with later functional outcomes has not been studied.
Previously an MPS-specific physical symptom scale was developed to measure disease burden in older children and young adults. A quantitative score, the Physical Symptom Score (PSS) [17] was applied to attenuated MPS I, II, and VI, to determine its association with neuropsychological functions [18]. However, the PSS was not designed for MPS IH whose somatic symptoms presented earlier in life and encompassed a larger number of somatic abnormalities.
Somatic disease is not clearly evident at birth, as affected infants appear healthy initially, until disease processes trigger clinical complications. Presently the evolution of somatic disease in very young children is incompletely described but the characterization is necessary in light of opportunities for treatment from birth afforded by newborn screening. To quantify the somatic disease burden for children under 36 months with MPS IH, we developed the Infant Physical Symptom Score (IPSS) to offer as a scaling tool and outcome measure for existing treatments and future clinical trials. A second goal was to determine the association between very early somatic disease burden and long-term disease-related functional outcomes as a check on the validity of the IPSS. We hypothesize that this infant somatic disease burden measure, the IPSS, will be associated with PSS scores later in life and be predictive of long-term adaptive functioning.
2. Methods:
2.1. Patients:
Part I.
39 patients with MPS IH prior to receiving transplant were sampled from a multi-site ongoing study, “Longitudinal Studies of Brain Structure and Functions in MPS Disorders” (NIH-U54NS065768), a study of the Lysosomal Disease Network (LDN). All 39 patients were part of this LDN study. They were selected if medical records were available for their pre- and peri- transplant diagnostic workup. Medical record data and LDN Case Report Forms (CRFs) from these patients contributed to the items that were selected for the IPSS.
Part II.
All of the 39 patients had a post-HSCT PSS and among them, 19 patients had a completed Vineland Adaptive Behavior Scale-II (VABS-II) scores [19] between 9 to 12 years post HSCT. Both of these tools, the PSS and VABS-II, were selected to assess the validity of the IPSS.
2.2. Procedure:
Part I.
The design approach for the PSS [16] was used for the development of IPSS to increase compatibility. For development of the IPSS scale, items were chosen using three sources; data gathered via retrospective medical record review on the 39 patients, a literature review, and consultation with the larger MPS team at the University of Minnesota.
For the medical record review, the 39 MPS IH patients were divided into 3 groups according to their age of HSCT:
≤12 months of age (N=14 patients)
>12 and ≤24 months of age (N=17 patients) and
>24 and ≤ 36 months of age (N=8 patients)
In the medical records and CRFs of these patients, medical events, symptoms, and signs were abstracted and quantified in a similar manner to the original physical symptom scale [17] to obtain a summative score of medical problems in multiple organ systems. In the PSS, these sorted into the domains of skeletal/orthopedic, vision, hearing, and cardiorespiratory problems, as well as the number of surgeries and the presence of hydrocephalus.
For the literature review, items were gathered from the literature that cited the most commonly found medical problems in MPS IH [20, 21, 22, 23, 24, 25, 26, 27]. Finally, consultation with MPS experts suggested no additional symptoms were noted beyond those found in the combination of the medical record and CRF review as well as the literature review.
Table 1 includes the components of the IPSS scale. The IPSS scoring system differed from the PSS [16] in that most items had dichotomous values as either present or absent in the IPSS. Because children were younger and did not have as many cumulative symptoms, qualifying the severity of symptoms as was done in the PSS was not indicated for the IPSS. Based on the above-described method, abnormalities during the earliest stages of life in twenty relevant medical domains were identified, including the number of surgeries that the participants underwent. These were given a score of either ‘0’ or ‘1’ to reflect the absence/presence or normality/abnormality of signs and symptoms in each domain at any point in the medical history (either corrected or treated). To apply the IPSS to a patient and score it, the patient’s status is considered at a selected time point, and medical record or other data (e.g., CRFs) are reviewed to complete the IPSS. Once all items are scored, an overall summary score can be calculated by totaling each item score; the higher the total IPSS score the greater the disease burden.
Table 1:
Infant Physical Symptom Scale Components and Scoring
| Feature | Score | Description | |
|---|---|---|---|
| Head circumference | Normal | 0 | |
| Abnormal | 1 | > 98th percentile for age and sex | |
| Course facial features including mouth | Normal | 0 | |
| Abnormal | 1 | Presence of any one of the following: enlarged tongue, bulging forehead, broad and depressed nasal root, thick lips, enlarged gingiva, delayed or abnormal dentation | |
| Skeletal dysplasia | Normal | 0 | |
| Abnormal | 1 | Characteristically abnormal X-ray findings of either skull, chest, spine, long bones | |
| Vision | Normal | 0 | |
| Abnormal | 1 | Presence of corneal opacity or clouding | |
| Ear infections | Absent | 0 | |
| Present | 1 | Presence of multiple (>2) ear infections | |
| Hearing loss | Absent | 0 | |
| Present | 1 | Presence of hearing loss; either conductive or sensorineural | |
| Enlarged glands | Absent | 0 | |
| Present | 1 | Presence of enlarged tonsils or adenoids | |
| Noisy breathing/snoring | Absent | 0 | |
| Present | 1 | Presence of noisy breathing or snoring | |
| Upper/lower respiratory infection | Absent | 0 | |
| Present | 1 | Presence of any one of the following: rhinitis, sinusitis, pharyngitis, pneumonia, bronchitis, bronchiolitis | |
| Obstructive/restrictive lung disease | Absent | 0 | |
| Present | 1 | Presence of obstructive/restrictive lung disease | |
| Heart valves | Normal | 0 | |
| Abnormal | 1 | Presence of any valvular disease | |
| Other heart problems | Absent | 0 | |
| Present | 1 | Presence of any abnormal cardiac function or surgery | |
| Limited range of motion (ROM) | Absent | 0 | |
| Present | 1 | Presence of any limited range of motion in joints | |
| Kyphosis/scoliosis | Absent | 0 | |
| Present | 1 | Presence of kyphosis or scoliosis | |
| Genu valgum | Absent | 0 | |
| Present | 1 | Presence of genu valgum | |
| Hernia | Absent | 0 | |
| Present | 1 | Presence of umbilical or inguinal hernia | |
| Organomegaly | Absent | 0 | |
| Present | 1 | Presence of enlarged liver or spleen | |
| Carpal tunnel syndrome (CTS) or claw hand | Absent | 0 | |
| Present | 1 | Presence of CTS or claw hand | |
| Hydrocephalus | Absent | 0 | |
| Present | 1 | Presence of hydrocephalus by imaging or elevated pressure measurement | |
| Number of surgeries (pre and peri HSCT) | 0 | No surgery | |
| (Heart surgery will not be counted here) | 1 | Less than 3 surgeries | |
| 2 | 3 to 6 surgeries | ||
| 3 | 7 to 10 surgeries | ||
| 4 | >10 surgeries | ||
| Total Score = 0 – 23 | |||
Part II.
19 patients from the above-mentioned sample were 9–12 years post-transplant and had available VABS-II scores as well as complete medical data to calculate a post-transplant PSS. The VABS-II is an observer-rated measure of adaptive behavior, i.e., the personal and social skills needed for everyday living for individuals from birth to 90 years old. The VABS-II measures four broad domains (communication, daily living skills [DLS], socialization, and motor skills) and offers an overall Composite score. We used the caregiver-reported Vineland Composite standard score and the DLS standard score (where M = 100 and SD = 15) for comparison with the retrospectively calculated IPSS. Lower VABS-II scores indicate greater impairment in functioning. This measure was chosen because it has been recommended by an international consensus on methods for assessment of MPS, and further, it has been used extensively with MPS disorders in the literature and clinical trials to quantify the impact of disease burden on the day-to-day functioning of the patient [28, 29, 30, 31].
2.3. Ethical considerations
All patients and/or their legal guardians provided written informed consent and/or assent to participate in the Lysosomal Disease Network longitudinal MPS I study (U54NS065768). This study was approved by the University of Minnesota Institutional Review Board: Human Subjects Committee. The protocol was approved by institutional review board or independent research ethics committee.
2.4. Statistical analysis:
Descriptive statistics of mean and SD for continuous variables or frequency and percentage for categorical variables overall and by treatment age groups. Within group means and confidence intervals were constructed using the t-test. Associations were estimated using linear regression and robust variance estimation for confidence intervals and P-values. Differential associations by treatment age groups were evaluated by additionally including an interaction term in regression models. All analyses were conducted using R v3.6.2 [32]
3. Results:
3.1. Part I.
The relationship of age to IPSS, categorized according to when the patients underwent transplant for the 39 patients who were selected to develop this measure. These scores were obtained from pre-transplant medical records and case report forms. Age at treatment was positively associated with IPSS with mean and 95% confidence intervals for each age group. Figure 1 illustrates the increasing somatic effects of disease, reflected by increasing IPSS scores for the groups who are older.
Figure 1. Association of age at treatment and IPSS.
IPSS- Infant Physical Symptom Score, mo- month
Figure 1 shows average IPSS scores by age at transplant. In line with the progressive nature of MPS IH, the youngest group of patients, ≤12 months, had the lowest average IPSS score (Total average IPSS = 7.4), reflecting the lowest number of somatic findings in the medical record and/or case report form. Similarly, the oldest group of patients, between >24 to ≤36 months, had the highest average IPSS score (Total average IPSS = 13.6). Those transplanted in middle age-range, between >12 to ≥24 months, had an average IPSS in the middle (Total average IPSS = 11.8). The overlap in some total IPSS scores between the age groups shows the individual variability in disease effects and presentation.
Part II
Table 2 provides the demographics of the sample used for follow-up, their age group at transplant (Tx), and their IPSS score. For the follow-up, the PSS, the Vineland Composite standard score and Vineland DLS scores are shown. To examine the association between IPSS and follow up scores, we divided the 19 patients into two groups (≤12 months and >12 months) depending on their age at HSCT: Because only 2 patients were transplanted past the age of >24 to ≤36 months, we combined them with the >12 to ≥24 months group.
Table 2.
Participant characteristics: values presented are mean (SD) or N (%) where indicated
| Covariate | Overall | Tx ≤12mo | Tx >12mo to ≤24mo | Tx >24mo |
|---|---|---|---|---|
| (N=19) | (N=8) | (N=9) | (N=2) | |
| Male | 9 (47.4%) | 3 (37.5%) | 4 (44.4%) | 2 (100.0%) |
| Tx ≤12mo | 8 (42.1%) | 8 (100.0%) | 0 (0.0%) | 0 (0.0%) |
| Tx >12mo to ≤24mo | 9 (47.4%) | 0 (0.0%) | 9 (100.0%) | 0 (0.0%) |
| Tx >24mo | 2 (10.5%) | 0 (0.0%) | 0 (0.0%) | 2 (100.0%) |
| Age at follow-up (years) | 12.3 (0.97) | 11.4 (0.81) | 12.8 (0.62) | 12.9 (0.25) |
| IPSS | 10.4 (3.4) | 7.62 (2.39) | 11.7 (1.87) | 16.0 (1.41) |
| PSS at follow-up | 10.5 (1.8) | 9.73 (1.11) | 11.4 (2.07) | 9.5 (0.71) |
| Vineland Composite at follow-up | 86.2 (11.7) | 91.8 (7.52) | 82.7 (13.2) | 79.7 (14.6) |
| Vineland Daily Living Skills at follow-up | 85.3 (15.8) | 95.0 (10.9) | 78.0 (16.2) | 79.7 (16.0) |
Tx- transplant, IPSS- Infant Physical Symptom Score, PSS- Physical Symptom Score
3.2.
The IPSS and the PSS were examined for each patient. Results indicated that for those patients who had a low IPSS score (generally patients transplanted early, ≤12mo), their PSS was low at follow-up. If their IPSS score was high, for the patients who were transplanted after 12 months, the distribution of their follow up PSS scores was not predictable and the PSS scores spread from low to high. Figure 2 shows the relationship in the pre transplant IPSS and the later PSS scores derived 9 to 12 years post-transplant for each individual patient. The younger group (shown in blue) at transplant had lower IPSS than the older group (shown in red) and the older group at transplant had higher scores on average. Based on our sample, the long-term PSS tends to be lower in those that had a lower initial pre-transplant IPSS, which were often the patients younger at initial treatment. This is in line with previous research indicating better long-term outcomes for patients treated at younger ages. Among patients with higher IPSS, the distribution of their later PSS spreads from low to high which may be due to the impact of age at initial treatment and the other undefined factors.
Figure 2. Relationship of the pre transplant IPSS with PSS score from 9–12 years post-transplant.
PSS- Physical Symptom Score, IPSS- Infant Physical Symptom Score
Figure 2 shows the relationship of the pre transplant IPSS with 9–12 years later PSS score. The younger group at transplant (≤12 months) is shown in blue, and the older group at transplant (>12 months) is shown in red. The blue line represents the mean for the younger group on the PSS and the red line represents the mean for the older group. The blue line is lower, reflecting far fewer somatic findings contributing to a lower total score for the younger transplanted group.
3.3.
Examination of adaptive behavior scores indicated there was a statistically significant relationship in the younger patients (≤12 months at transplant) between age group at transplant and their IPSS and Vineland Composite standard score (P=0.015). There also was a trend in the younger patients toward a relationship between age group at transplant and their IPSS and daily living skills (P=0.081) but the magnitude of the relationship was similar to the Composite standard score (see Table 3 and Figure 3 and 4).
Table 3.
shows a statistically significant relationship between IPSS and Vineland composite standard score in the younger (group (≤12 months) and the older group (>12 months).
| Outcome | Age at Tx Group | IPSS Association with Outcome (95% CI) | P-value |
|---|---|---|---|
| PSS | Age at Tx ≤12mo | 0.00 (−0.44, 0.45) | 0.984 |
| Age at Tx > 12mo | 0.01 (−0.50, 0.52) | 0.972 | |
| Vineland Composite | Age at Tx ≤12mo | 2.03 (0.40, 3.66) | 0.015 |
| Age at Tx > 12mo | 0.01 (−3.11, 3.14) | 0.993 | |
| Vineland Daily Living Skills | Age at Tx ≤12mo | 2.28 (−0.28, 4.84) | 0.081 |
| Age at Tx > 12mo | 0.69 (−2.77, 4.14) | 0.698 |
Tx- transplant, IPSS- Infant Physical Symptom Score, PSS- Physical Symptom Score
Figure 3: Association between Vineland composite standard score and IPSS for younger group.
IPSS- Infant Physical Symptom Score, Vineland composite: Vineland Adaptive Behavior Scale-II (VABS-II) measures four broad domains (communication, daily living skills [DLS], socialization, and motor skills) and offers an overall Composite score.
Figure 4: Association between Vineland daily living skills and IPSS for younger group.
IPSS- Infant Physical Symptom Score, Vineland DLS: Vineland Adaptive Behavior Scale-II (VABS-II) measures four broad domains (communication, daily living skills [DLS], socialization, and motor skills)
Figure 3 shows statistically significant association between Vineland composite standard score and IPSS for younger group. In figure 3 blue colors are the younger group (≤12 months) and red are the older group (>12 months) at transplant.
Figure 4 shows the association between Vineland daily living skills and IPSS in younger patients is not statistically significant although the magnitude of the association is similar to Figure 3. In figure 4 blue colors are the younger group (≤12 months) and red are the older group (>12 months) at transplant.
4. Discussion:
4.1.
The infant physical symptom score (IPSS) was developed to quantify somatic disease in individuals with MPS disorders diagnosed very early in life. While babies with MPS disorders are born appearing healthy, they develop disease signs early in the first year of life. Patients with MPS IH have historically been diagnosed in infancy and toddlerhood early due to the presence of somatic disease. These early symptoms more commonly occurring in those with MPS, and the chances of it happening increase with time/disease progression. Many children with MPS don’t have many signs/symptoms at birth but then develop them in subsequent years. The IPSS reflects how somatic symptoms are accrued and may be irreversible after the physical symptoms emerge. As such, it is necessary to include items on the IPSS that may not be present at birth but added in order to quantify disease emergence across time and ideally demonstrate whether novel therapies and/or early standard treatment prevent emergence of some symptoms. The relationships of IPSS with PSS and Vineland are seen specifically for patients transplanted <12 months. Patients transplanted <12 months had a narrower range of symptoms at diagnosis. Post-transplant young patients continued to have a narrow range thus having less variability and a greater association between the IPSS and PSS. It is possible that these young patients had a single severe symptom that brought them to attention and had not yet accrued many symptoms seen in the older patients. Some may have been diagnosed due to an older sibling. The older patients accrued more symptoms, were more variable in their phenotype, and thus may have had a variable response to treatment.
Now is a critical time to gain better understanding of the accumulating disease burden in the youngest stages of life. With the addition of MPS I to the Recommended Uniform Screening Panel for newborn screening in 2016, there is increasing opportunity to do so. The IPSS is a timely measure directed to quantify the very earliest somatic features of this condition. Early assessment with the IPSS is critical to be able to determine whether early treatment options may significantly lower the initial disease burden. The IPSS may also provide a predictor of later outcomes, especially adaptive function. The IPSS is significantly more predictive in children who were treated under 12 months of age.
A quantifiable measure of disease burden prior to treatment appears to have value in predicting outcome, as demonstrated by the finding of increased somatic burden (i.e., higher IPSS scores) in children who had HSCT after 12 months of age as well as increased challenges with adaptive functions. Children with later HSCT have been shown to have both greater somatic disability as well as difficulties carrying out activities of daily living at age-expected levels.
4.2.
Limitations of this study include the small sample size, which is a common challenge in rare disease research. Additionally, the PSS used to determine the symptom burden for these patients at follow-up was originally developed in attenuated MPS I, II, and VI patients from age 5 to 18. It is assumed that as the types of somatic burden are similar, that the PSS could be applicable to late outcomes in transplanted MPS IH patients. Whether the patients were fully engrafted, whether they were transplanted once or needed a second transplant, and the type of preparative regimen were also not factored in the current analyses. We attempted to demonstrate convergent validity by showing that the IPSS correlated with the PSS, which is the only currently available measure of physical symptoms of MPS in this rare disease population. It is important to note that the symptoms of most treated MPS conditions (except cognitively for MPS III and neuronopathic MPS II) do not drastically change across life, they reliably worsen with time. Finally, because of the rarity of these conditions, including their unique presentation and complex disease mechanisms, cross validation with another sample is challenging.
4.3.
The IPSS may also be a tool to investigate the relationship of genotype to the early somatic phenotype, possibly rendering the genotype an important predictor for post-transplant outcomes. An additional investigation to examine what proportion of the affected patients had two null mutations versus one null and one missense or other mutations in our prospective study in MPS I by newborn screening is a future direction, to investigate the correlation of genotype with early somatic phenotype by implementing IPSS. Another question would be whether newborns with an abnormal screen but with unusual mutations could be categorized with this tool, predicting a future phenotype and possibly influencing treatment decisions. A future paper will address some of these issues along with genotype.
5. Conclusion:
The IPSS was developed to quantify and characterize the physical symptom onset, assign a prognostic score, and improve our understanding of somatic disease progression and long-term outcomes in MPS IH patients. It has the potential to measure the benefits of very early treatment enabled by newborn screening; this is a research question that should be pursued. This measure may provide quantification of disease severity, important in the era of newborn screening in the care and treatment of MPS patients.
Future directions:
Because of the similarity of MPS IH patients to severe MPS II, VI, and VII patients, the IPSS could be applied to both natural history studies and clinical trials in such patients. The IPSS can also facilitate examining the association of somatic disease burden to other factors such as genotype, neurocognition, neuroimaging, psychosocial functioning, and quality of life outcomes in all early diagnosed children with MPS.
Acknowledgements:
We are grateful to all the research participants and their families. We thank Brenda Diethelm-Okita, David Erickson in the Lysosomal Disease Network office at the University of Minnesota for administrative assistance. We are very thankful for the support provided by the National MPS Society, Ryan Foundation for Orphan Disease Research and Center for Neurobehavioral Development (CNBD).
Funding sources:
The Lysosomal Disease Network (LDN) U54-NS065768 is a part of the National Institute of Health (NIH) Rare Diseases Clinical Research Network, supported through collaboration between the NIH Office of Rare Diseases Research at the National Center for Advancing Translational Science, the National Institute of Neurological Disorders and Stroke (NINDS), and National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). This project was supported in part (Dr. Rudser) by the National Center for Advancing Translational Sciences, National Institutes of Health, through University of Minnesota CTSI Grant Number NCATS UL1TR000114. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or CTSI.
Reference:
- [1].Neufeld E, Muenzer J. The mucopolysaccharidoses. The metabolic and molecular bases of inherited disease. 2001;8:3421–3452. [Google Scholar]
- [2].Hopwood JJ, Morris CP (1990) The mucopolysaccharidosis: Diagnosis, molecular genetics and treatment. Mol Biol Med 7(5), 381–404 [PubMed] [Google Scholar]
- [3].Whitley CB. The Mucopolysaccharidoses. In: Beighton P, ed. McKusick’s Heritable Disorders of Connective Tissue. 5 ed. Mosby, Inc.; 1992:367–500 [Google Scholar]
- [4].Muenzer J, Wraith JE, Clarke LA. Mucopolysaccharidosis I: Management and Treatment Guidelines. Pediatrics. 2009-01-01 2009;123(1):19–29. doi: 10.1542/peds.2008-0416 [DOI] [PubMed] [Google Scholar]
- [5].Clarke LA, Heppner J (2002) Mucopolyschharidosis Type I, (Updated 2011 Jul 21). In: Pagon RA: Adam MP; Bird TD, et al. , editors. Gene Reviews™ [Internet]. Seattle (WA): University of Washington, Seattle; 1993–2013. Available from: http://www.ncbi.nlm.nih.gov/books/NBK1162/. [Google Scholar]
- [6].Pastores GM, Arn P, Beck M et al. (2007) The MPS I registry: Design, methodology, and early findings of a global disease registry for monitoring patients with Mucopolysaccharidosis Type I. Mol Genet and Metab 91:37–47. [DOI] [PubMed] [Google Scholar]
- [7].Whitley CB, Ramsay NK, Kersey JH, Krivit W. Bone marrow transplantation for Hurler syndrome: assessment of metabolic correction. Birth Defects: Original Article Series. 1986. 22(1):7–24. [PubMed] [Google Scholar]
- [8].Peters C, Balthazor M, Shapiro E et al. (1996) Outcome of unrelated donor bone marrow transplantation in 40 children with Hurler syndrome. Blood 87: 4894–4902 [PubMed] [Google Scholar]
- [9].Peters C, Shapiro E, Anderson J et al. (1998) Hurler syndrome: II. Outcome of HLA-genotypically identical sibling and HLA-haploidentical related donor bone marrow transplantation in Wfty-four children. The Storage Disease Collaborative Study Group,Blood 91: 2601–2608 [PubMed] [Google Scholar]
- [10].Souillet G, GuVon N, Maire I et al. (2003) Outcome of 27 patients with Hurler’s syndrome transplanted from either related or unrelated haematopoietic stem cell sources, Bone Marrow Transplant. 31: 1105–1117 [DOI] [PubMed] [Google Scholar]
- [11].Staba SL, Escolar ML, Poe M et al. (2004) Cord-blood transplants from unrelated donors in patients with Hurler’s syndrome. N. Engl. J. Med 350:1960–1969 [DOI] [PubMed] [Google Scholar]
- [12].Grosse SD, Lam WK, Wiggins LD, Kemper AR. Cognitive outcomes and age of detection of severe mucopolysaccharidosis type 1. Genetics in Medicine. 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Lum SH, Miller WP, Jones S, et al. The Changing Patterns of Graft Failure in MPS1H, Hurler Syndrome: A Review of 30-Years Experience. Blood. 2016;128(22):4700–4700 [Google Scholar]
- [14].Shapiro EG, Nestrasil I, Rudser K, et al. Neurocognition across the spectrum of mucopolysaccharidosis type I: age, severity, and treatment. Molecular genetics and metabolism. 2015;116(1):61–68 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Aldenhoven M, Wynn RF, Orchard PJ, et al. Long-term outcome of Hurler syndrome patients after hematopoietic cell transplantation: an international multicenter study. Blood. 2015;125(13):2164–2172 [DOI] [PubMed] [Google Scholar]
- [16].Shapiro E, Lockman L, Balthazor M, Krivit W. Neuropsychological outcomes of several storage diseases with and without bone marrow transplantation. Journal of inherited metabolic disease. 1995;18(4):413–429 [DOI] [PubMed] [Google Scholar]
- [17].Ahmed A, Rudser K, Kunin-Batson A, Delaney K, Whitley C, Shapiro E. Mucopolysaccharidosis (MPS) physical symptom score: development, reliability, and validity. JIMD Reports, Volume 26. Springer; 2015:61–68 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].Ahmed A, Shapiro E, Rudser K, King K, Whitley CB. Association of physical symptom score (PSS) with age and cognitive measures in attenuated mucopolysaccharidosis types I, II and VI. Molecular Genetics and Metabolism. 2016;117(2):S16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [19].Sparrow SS, Cicchetti DV, Balla DA. Vineland adaptive behavior scales: Second edition (Vineland II), The expanded interview form. Pearson Assessments; 2008 [Google Scholar]
- [20].Whitley CB. The mucopolysaccharidoses In: Beighton P (ed), McKusick’s Heritable Diseases of Connective Tissue, 1993, 5th ed, 367–499 [Google Scholar]
- [21].Beck M, Arn P, Giugliani R, Muenzer J, Okuyama T, Taylor J, Fallet S The natural history of MPS I: Global perspectives from the MPS I Registry. Genet. Med 2014; 16:759–765. doi: 10.1038/gim.2014.25 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [22].Chen SJ, Li YW, Wang TR, Hsu JC Bony changes in common mucopolysaccharidoses. [(accessed on 21 October 2019)]; Acta Paediatr. Sin 1996. 37:178–184. Available online: http://www-ncbi-nlm-nih-gov.ezp2.lib.umn.edu/pubmed/8755171 [PubMed] [Google Scholar]
- [23].Rasalkar DD, Chu WCW, Hui J, Chu CM, Paunipagar BK, Li CK Pictorial review of mucopolysaccharidosis with emphasis on MRI features of brain and spine. Br. J. Radiol 2011; 84:469–477. doi: 10.1259/bjr/59197814 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24].Leighton SE, Papsin B, Vellodi A, Dinwiddie R, Lane R Disordered breathing during sleep in patients with mucopolysaccharidoses. [(accessed on 12 April 2018)]; Int. J. Pediatr. Otorhinolaryngol 2001. 58:127–138. doi: 10.1016/S0165-5876(01)00417-7. Available online: http://www-ncbi-nlm-nih-gov.ezp2.lib.umn.edu/pubmed/11278021 [DOI] [PubMed] [Google Scholar]
- [25].Lin HY, Shih SC, Chuang CK, Lee KS, Chen MR, Lin HC, Chiu PC, Niu DM, Lin SP Assessment of hearing loss by pure-tone audiometry in patients with mucopolysaccharidoses. Mol. Genet. Metab 2014; 111:533–538. doi: 10.1016/j.ymgme.2014.02.003 [DOI] [PubMed] [Google Scholar]
- [26].Braunlin EA, Harmatz PR, Scarpa M, Furlanetto B, Kampmann C, Loehr JP, Ponder KP, Roberts WC, Rosenfeld HM, Giugliani R Cardiac disease in patients with mucopolysaccharidosis: Presentation, diagnosis and management. [(accessed on 12 April 2018)]; J. Inherit. Metab. Dis 2011. 34:1183–1197. doi: 10.1007/s10545-011-9359-8. Available online: http://www-ncbi-nlm-nih-gov.ezp2.lib.umn.edu/pubmed/21744090 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Braunlin E, Wang R Cardiac issues in adults with the mucopolysaccharidoses: Current knowledge and emerging needs. Heart. 2016; 102:1257–1262. doi: 10.1136/heartjnl-2015-309258 [DOI] [PubMed] [Google Scholar]
- [28].Van der Lee JH, Morton J, Adams HR, Clarke L, Eisengart JB, Escolar M, Giugliani R, Harmatz P, Hogan M, Kearney S, Muenzer J, Muschol N, Rust S, Saville BR, Semrud-Clikeman M, Wang R, Shapiro E. (2020). Therapy development for the mucopolysaccharidoses: updated consensus recommendations for neuropsychological endpoints. Molecular Genetics and Metabolism, 131(1–2), 181–196 [DOI] [PubMed] [Google Scholar]
- [29].Van der Lee JH, Morton J, Adams HR, Clarke L, Ebbink BJ, Escolar M, Giugliani R, Harmatz P, Hogan M, Jones S, Kearney S, Muenzer J, Rust S, Semrud-Clikeman M, Wijburg F, Yu Z-f, Janzen D, Shapiro E (2017). Cognitive endpoints for therapy development for neuronopathic mucopolysaccharidoses: Results of a consensus procedure. Molecular Genetics and Metabolism, 121:70–79 [DOI] [PubMed] [Google Scholar]
- [30].Janzen D, Delaney K, Shapiro E. (2017). Cognitive and adaptive measurement endpoints for clinical trials in mucopolysaccharidoses types I, II, and III: A review of the literature. Molecular Genetics and Metabolism, 121:57–69 [DOI] [PubMed] [Google Scholar]
- [31].Bjoraker K, Delaney K, Peters C, Krivit W, Shapiro E (2006). Long Term Outcomes of Adaptive Functions for Children with MPS I. Journal of Behavioral and Developmental Pediatrics, 27, 290–296 [DOI] [PubMed] [Google Scholar]
- [32].R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ [Google Scholar]