Browsing by Author "Hwu, Wuh-Liang"

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Critical Trio Exome Benefits In-Time Decision-Making for Pediatric Patients With Severe Illnesses*
(2019-11-01)
Wu, En-Ting
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Hwu, Wuh-Liang
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Chien, Yin-Hsiu
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Hsu, Ching
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Chen, Ting-Fu
Objectives: Critical illnesses caused by undiagnosed genetic conditions are challenging in PICUs. Whole-exome sequencing is a powerful diagnostic tool but usually costly and often fail to arrive at a final diagnosis in a short period. We assessed the feasibility of our whole-exome sequencing as a tool to improve the efficacy of rare diseases diagnosis for pediatric patients with severe illness. Design: Observational analysis. Method: We employed a fast but standard whole-exome sequencing platform together with text mining-assisted variant prioritization in PICU setting over a 1-year period. Setting: A tertiary referral Children's Hospital in Taiwan. Patients: Critically ill PICU patients suspected of having a genetic disease and newborns who were suspected of having a serious genetic disease after newborn screening were enrolled. Interventions: None. Measurements and Main Results: Around 50,000 to 100,000 variants were obtained for each of the 40 patients in 5 days after blood sampling. Eleven patients were immediately found be affected by previously reported mutations after searching mutation databases. Another seven patients had a diagnosis among the top five in a list ranked by text mining. As a whole, 21 patients (52.5%) obtained a diagnosis in 6.2 +/- 1.1 working days (range, 4.3-9 d). Most of the diagnoses were first recognized in Taiwan. Specific medications were recommended for 10 patients (10/21, 47.6%), transplantation was advised for five, and hospice care was suggested for two patients. Overall, clinical management was altered in time for 81.0% of patients who had a molecular diagnosis. Conclusions: The current whole-exome sequencing algorithm, balanced in cost and speed, uncovers genetic conditions in infants and children in PICU, which helps their managements in time and promotes better utilization of PICU resources.
Earlier and higher dosing of alglucosidase alfa improve outcomes in patients with infantile -onset Pompe disease: Evidence from real -world experiences
(2020-06-01)
Chien, Yin-Hsiu
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Tsai, Wen-Hui
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Chang, Chaw-Liang
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Chiu, Pao-Chin
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Chou, Yen-Yin
Functional independence of Taiwanese patients with mucopolysaccharidoses
(2019-08-01)
Lee, Chung-Lin
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Lin, Hsiang-Yu
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Chuang, Chih-Kuang
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Chiu, Huei-Ching
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Tu, Ru-Yi
Background Information on functional strengths and weaknesses of mucopolysaccharidosis (MPS) patients is important for early intervention programs and enzyme replacement therapy (ERT). Methods We used the Functional Independence Measure for Children (WeeFIM) questionnaire to assess the functional skills of 63 Taiwanese MPS patients (median age, 13 years 3 months; range, 3-20 years) from January 2012 to December 2018. Results Mean total WeeFIM score was 75.4 of a potential score of 126. Mean total WeeFIM scores of each type (MPS I, MPS II, MPS IIIB, MPS IVA, and MPS VI) were 103.8, 76.2, 41.6, 92.2, and 113.6, respectively. Mean scores for self-care, mobility, and cognition domains were 30 (maximum 56), 23 (maximum 35), and 22 (maximum 35), respectively. MPS type IIIB patients had the lowest scores in self-care, mobility, cognition, and total domains compared to other types of MPS. All patients with ERT in MPS I, II, and IVA had higher scores in self-care and mobility domains than patients without ERT. Most patients required assistance for self-care skills, especially in grooming and bathing. Conclusion MPS patients require support and supervision in self-care tasks. For cognition tasks, MPS IIIB patients also require help. This questionnaire is useful to identify the strengths and limitations of MPS patients.
Mucopolysaccharidosis III in Taiwan: Natural history, clinical and molecular characteristics of 28 patients diagnosed during a 21-year period
(2018-09-01)
Lin, Hsiang-Yu
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Chuang, Chih-Kuang
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Lee, Chung-Lin
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Tu, Ru-Yi
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Lo, Yun-Ting
Mucopolysaccharidosis type III (MPS III, Sanfilippo syndrome) has a variable age of onset and variable rate of progression. However, information regarding the natural history of this disorder in Asian populations is limited. A retrospective analysis was carried out for 28 patients with MPS III (types IIIA [n=3], IIIB [n=23], and IIIC [n=2]; 15 males and 13 females; median age, 8.2 years; age range, 2.7-26.5 years) seen in six medical centers in Taiwan from January 1996 through October 2017. The median age at confirmed diagnosis was 4.6 years. The most common initial symptom was speech delay (75%), followed by hirsutism (64%) and hyperactivity (54%). Both z scores for height and weight were negatively correlated with age (r=-.693 and -0.718, respectively; p<.01). The most prevalent clinical manifestations were speech delay (100%) and intellectual disability (100%), followed by hirsutism (93%), hyperactivity (79%), coarse facial features (68%), sleep disorders (61%), and hepatosplenomegaly (61%). Ten patients (36%) had epilepsy, and the median age at the first seizure was 11 years. Thirteen patients (46%) experienced at least one surgical procedure. At the time of the present study, 7 of the 28 patients had passed away at the median age of 13.0 years. Molecular studies showed an allelic heterogeneity without clear genotype and phenotype correlations. MPS IIIB is the most frequent subtype among MPS III in the Taiwanese population. An understanding of the natural history of MPS III may allow early diagnosis and timely management of the disease facilitating better treatment outcomes.
Newborn Screening for Phenylketonuria: Machine Learning vs Clinicians
(2012)
Chen, Wei-Hsin
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Chen, Han-Ping
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Tseng, Yi-Ju
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Hsu, Kai-Ping
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Hsieh, Sheau-Ling
The metabolic disorders may hinder an infant\'s normal physical or mental development during the neonatal period. The metabolic diseases can be treated by effective therapies if the diseases are discovered in the early stages. Therefore, newborn screening program is essential to prevent neonatal from these damages. In the paper, a support vector machine (SVM) based algorithm is introduced in place of cut-off value decision to evaluate the analyte elevation raw data associated with Phenylketonuria. The data were obtained from tandem mass spectrometry (MS/MS) for newborns. In addition, a combined feature selection mechanism is proposed to compare with the cut-off scheme. By adapting the mechanism, the number of suspected cases is reduced substantially; it also handles the medical resources effectively and efficiently.
Presymptomatic Diagnosis of Spinal Muscular Atrophy Through Newborn Screening
(2017-11-01)
Chien, Yin-Hsiu
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Chiang, Shu-Chuan
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Weng, Wen-Chin
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Lee, Ni-Chung
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Lin, Ching-Jie
Objective To demonstrate the feasibility of presymptomatic diagnosis of spinal muscular atrophy (SMA) through newborn screening (NBS). Study design We performed a screening trial to assess all newborns who underwent routine newborn metabolic screening at the National Taiwan University Hospital newborn screening center between November 2014 and September 2016. A real-time polymerase chain reaction (RT-PCR) genotyping assay for the SMN1/SMN2 intron 7 c. 888+100A/G polymorphism was performed to detect homozygous SMN1 deletion using dried blood spot (DBS) samples. Then the exon 7 c. 840C>T mutation and SMN2 copy number were determined by both droplet digital PCR (ddPCR) using the original screening DBS and multiplex ligation-dependent probe amplification (MLPA) using a whole blood sample. Results Of the 120 267 newborns, 15 tested positive according to the RT-PCR assay. The DBS ddPCR assay excluded 8 false-positives, and the other 7 patients were confirmed by the MLPA assay. Inclusion of the second-tier DBS ddPCR screening assay resulted in a positive prediction value of 100%. The incidence of SMA was 1 in 17 181 (95% CI, 1 in 8323 to 1 in 35 468). Two of the 3 patients with 2 copies of SMN2 and all 4 patients with 3 or 4 copies of SMN2 were asymptomatic at the time of diagnosis. Five of the 8 false-positives were caused by intragenic recombination between SMN1 and SMN2. Conclusion Newborn screening can detect patients affected by SMA before symptom onset and enable early therapeutic intervention. A combination of a RT-PCR and a second-tier ddPCR can accurately diagnose SMA from DBS samples with no false-positives.
Relationships among Height, Weight, Body Mass Index, and Age in Taiwanese Children with Different Types of Mucopolysaccharidoses
(2019-12-01)
Lin, Hsiang-Yu
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Lee, Chung-Lin
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Chiu, Pao Chin
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Niu, Dau-Ming
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Tsai, Fuu-Jen
Background: Children with mucopolysaccharidosis (MPS) generally appear unaffected at birth but may develop multiple clinical manifestations including profound growth impairment as they grow older. Each type of MPS has a variable age at onset and variable rate of progression, however, information regarding growth in Asian children is limited. Methods: This retrospective analysis included 129 Taiwanese patients with MPS (age range, 0.7 to 19.5 years, median age, 7.9 years) from eight medical centers in Taiwan from January 1996 through December 2018. Results: The mean z scores for the first recorded values of height, weight, and body mass index in the patients' medical records were -4.25, -1.04, and 0.41 for MPS I (n = 9), -2.31, 0.19, and 0.84 for MPS II (n = 49), -0.42, 0.08, and -0.12 for MPS III (n = 27), -6.02, -2.04, and 0.12 for MPS IVA (n = 30), and -4.46, -1.52, and 0.19 for MPS VI (n = 14), respectively. MPS IVA had the lowest mean z scores for both height and weight among all types of MPS, followed by MPS VI, MPS I, MPS II, and MPS III, which showed the mildest growth retardation. Both z scores for height and weight were negatively correlated with increasing age for all types of MPS (p < 0.01). Of 32 patients younger than 5 years of age, 16 (50%), and 23 (72%) had positive z scores of height and weight, respectively. A substantial number of younger patients with MPS I, II, III, and IVA had a positive height z score. The median age at diagnosis was 3.9 years (n = 115). Conclusions: The patients with MPS IVA had the most significant growth retardation among all types of MPS, followed by MPS VI, MPS I, MPS II, and MPS III. The height and weight of the MPS patients younger than 2-5 years of age were higher than those of healthy individuals, however, their growth significantly decelerated in subsequent years. Understanding the growth curve and potential involved in each type of MPS may allow for early diagnosis and timely management of the disease, which may improve the quality of life.
Web-Based Newborn Screening System for Metabolic Diseases: Machine Learning Versus Clinicians
(2013-05-01)
Chen, Wei-Hsin
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Hsieh, Sheau-Ling
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Hsu, Kai-Ping
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Chen, Han-Ping
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Su, Xing-Yu
Background: A hospital information system (HIS) that integrates screening data and interpretation of the data is routinely requested by hospitals and parents. However, the accuracy of disease classification may be low because of the disease characteristics and the analytes used for classification. Objective: The objective of this study is to describe a system that enhanced the neonatal screening system of the Newborn Screening Center at the National Taiwan University Hospital. The system was designed and deployed according to a service-oriented architecture (SOA) framework under the Web services. NET environment. The system consists of sample collection, testing, diagnosis, evaluation, treatment, and follow-up services among collaborating hospitals. To improve the accuracy of newborn screening, machine learning and optimal feature selection mechanisms were investigated for screening newborns for inborn errors of metabolism. Methods: The framework of the Newborn Screening Hospital Information System (NSHIS) used the embedded Health Level Seven (HL7) standards for data exchanges among heterogeneous platforms integrated by Web services in the C# language. In this study, machine learning classification was used to predict phenylketonuria (PKU), hypermethioninemia, and 3-methylcrotonyl-CoA-carboxylase (3-MCC) deficiency. The classification methods used 347,312 newborn dried blood samples collected at the Center between 2006 and 2011. Of these, 220 newborns had values over the diagnostic cutoffs (positive cases) and 1557 had values that were over the screening cutoffs but did not meet the diagnostic cutoffs (suspected cases). The original 35 analytes and the manifested features were ranked based on F score, then combinations of the top 20 ranked features were selected as input features to support vector machine (SVM) classifiers to obtain optimal feature sets. These feature sets were tested using 5-fold cross-validation and optimal models were generated. The datasets collected in year 2011 were used as predicting cases. Results: The feature selection strategies were implemented and the optimal markers for PKU, hypermethioninemia, and 3-MCC deficiency were obtained. The results of the machine learning approach were compared with the cutoff scheme. The number of the false positive cases were reduced from 21 to 2 for PKU, from 30 to 10 for hypermethioninemia, and 209 to 46 for 3-MCC deficiency. Conclusions: This SOA Web service-based newborn screening system can accelerate screening procedures effectively and efficiently. An SVM learning methodology for PKU, hypermethioninemia, and 3-MCC deficiency metabolic diseases classification, including optimal feature selection strategies, is presented. By adopting the results of this study, the number of suspected cases could be reduced dramatically.