Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results : Several ascending and descending monotonic key genes were identi ed by Monotonic Feature Selector. The identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. Additionally, not only can TO-GCN analysis classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation, but it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic pro ling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identi ed and the related biological implications have been discussed. Finally, we further elucidated for the rst time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes existing in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts as MSC differentiate into mesangial cells.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results : Several ascending and descending monotonic key genes were identi ed by Monotonic Feature Selector. The identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. Additionally, not only can TO-GCN analysis classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation, but it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic pro ling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identi ed and the related biological implications have been discussed. Finally, we further elucidated for the rst time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes existing in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts as MSC differentiate into mesangial cells.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Methods: Differentiation of MSC into mesangial cells was induced by co-culturing with injured mesangial cells. RNA from co-cultured MSC was extracted before running RNA sequencing. Generated RNA-seq data was analysed by two methods simultaneously: 1) Monotonic Feature Selector (MFSelector) to identify the key genes with ascending and descending monotonic patterns, and 2) Time-Ordered Gene Coexpression Network (TO-GCN) to construct a TF co-expression network. Results : MFSelector has identi ed several monotonic key genes (either ascending or descending). These identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were
Background: Breast cancer develops as a result of multiple gene mutations in combination with env... more Background: Breast cancer develops as a result of multiple gene mutations in combination with environmental risk factors. Causative variants in genes such as BRCA1 and/or BRCA2 have been shown to account for hereditary nature of certain breast cancers. However,other genes, such as ATM, PALB2, BRIP1, CHEK, BARD1, while lower in frequency, may also increase breast cancer risk. There are few studies examining the role of these causative variants. Our study aimed to examine the clinical and genetic characterization of hereditary breast cancer in a Chinese population. Methods: We tested a panel of 27 genes implicated in breast cancer risk in 240 participants using Next-Generation Sequencing. The prevalence of genetic causative variants was determined and the association between causative variants and clinico-pathological characteristics was analyzed. Results: Causative variant rate was 19.2% in the breast cancer (case) group and 12.5% in the high-risk group. In the case group 2.5% of patients carried BRCA1 causative variant, 7.5% BRCA2 variants, 1.7% patients had MUTYH, CHEK or PALB2 variants, and 0.8% patients carried ATM, BARD1, NBN, RAD51C or TP53 variants. In the high-risk group 5. 8% women carried MUTYH causative variants, 2.5% had causative variants in ATM, 1.7% patients had variants in BRCA2 and 0.8% in BARD1, BRIP1 or CDH1. There was no significant difference in the presence of causative variants among clinical stages of breast cancer, tumor size and lymph nodes status. However, eight of the 12 BRCA1/2 causative variants were found in the TNBC group. Conclusions: We found increased genetic causative variants in the familial breast cancer group and in high-risk women with a family history of breast cancer. However, the variant MUTYH c.892-2A > G may not be directly associated with hereditary breast carcinoma.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) have been reported can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Methods: Differentiation of MSC into mesangial cells was induced by co-culturing with injured mesangial cells. Total RNA from co-cultured MSC were extracted before running RNA sequencing. Generated RNAseq data was analysed by two methods simultaneously: 1) Monotonic Feature Selector (MFSelector) to identify the key genes with ascending and descending monotonic patterns, and 2) Time-Ordered Gene Coexpression Network (TO-GCN) to construct a TF co-expression network. Results: MFSelector has identi ed several monotonic key genes (either ascending or descending). These identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were
Background: Mesangial cells play an important role in the glomerulus to provide mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus to provide mechanical support and maintaine efficient ultrafiltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic profiling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells, to understand the involvement of transcription factor (TF) along the differentiation process, and finally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results: Several ascending and descending monotonic key genes were identified by Monotonic Feature Selector. The identified descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. TO-GCN analysis can classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation. Furthermore, it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic profiling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identified and the related biological implications have been discussed. Finally, we further elucidated for the first time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes involved in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts during the differentiation of MSC into mesangial cells.
Background/purpose: Hereditary spastic paraplegia (HSP) is a heterogeneous group of inherited neu... more Background/purpose: Hereditary spastic paraplegia (HSP) is a heterogeneous group of inherited neurodegenerative disorders characterized by slowly progressive lower limbs spasticity and weakness. HSP type 15 (SPG15) is an autosomal recessive subtype caused by ZFYVE26 mutations. The aim of this study was to investigate the frequency and clinical and genetic features of ZFYVE26 mutations in a Taiwanese HSP cohort. Methods: Mutational analysis of the coding regions of ZFYVE26 was performed by targeted resequencing in the 195 unrelated Taiwanese patients with HSP. All of the patients were of Han Chinese ethnicity. Clinical, neuropsychological, electrophysiological evaluations and imaging studies were collected. Results: Among the 195 patients, only one SPG15 patient was identified. The patient had a novel recessive ZFYVE26 frameshift truncating mutation, p.R1806Gfs * 36 (c.5415delC), and presented with insidious onset spastic weakness of lower-extremities and cognitive impairment. Neuropsychological assessment revealed deficits in executive function, visual naming, category verbal fluency, and manual dexterity. Brain MRI showed thin corpus callosum and the "ears of lynx" sign. Conclusion: SPG15 accounts for approximately 0.5% (1/195) of the Taiwanese HSP cohort. This study identified the first Taiwanese SPG15 case and delineated the clinical, genetic,
BACKGROUND Adrenoleukodystrophy (ALD) is an X-linked peroxisomal disorder caused by mutations in ... more BACKGROUND Adrenoleukodystrophy (ALD) is an X-linked peroxisomal disorder caused by mutations in the ABCD1 gene. The clinical manifestations of ALD vary widely with some patients presenting with adrenomyeloneuropathy (AMN) that resembles the phenotype of hereditary spastic paraplegia (HSP). The aim of this study is to investigate the frequency, spectrum, and clinical features of ABCD1 mutations in Taiwanese patients with HSP phenotype. METHODS Mutational analysis of the ABCD1 gene was performed in 230 unrelated Taiwanese patients with clinically suspected HSP by targeted resequencing. Clinical, electrophysiological, and neuroimaging features of the patients carrying an ABCD1 pathogenic mutation were characterized. RESULTS Ten different ABCD1 mutations were identified in eleven patients, including two novel mutations (p.Q177Pfs*17 and p.Y357*) and eight ever reported in ALD cases of other ethnicities. All patients were male and exhibited slowly progressive spastic paraparesis with onset ages ranging from 21 to 50 years. Most of them had additional non-motor symptoms, including autonomic dysfunction in nine patients, sensory deficits in seven, premature baldness in seven, skin hyperpigmentation in five, psychiatric symptoms in one and cerebellar ataxia in one. Seven of the ten patients who ever received nerve conduction studies showed axonal polyneuropathy. Magnetic resonance imaging (MRI) revealed diffuse spinal cord atrophy in seven patients, cerebral white matter hyperintensity in one patient, and cerebellar involvement in one patient. CONCLUSIONS ABCD1 mutations account for 4.8% (11/230) of the cases with HSP phenotype in Taiwan. This study highlights the importance to consider ABCD1 mutations in patients with clinically suspected HSP of unknown genetic causes.
Annals of clinical and translational neurology, Jul 7, 2023
ObjectiveHereditary spastic paraplegias (HSPs) are a group of inherited neurodegenerative disorde... more ObjectiveHereditary spastic paraplegias (HSPs) are a group of inherited neurodegenerative disorders characterized by slowly progressive lower limb spasticity and weakness. HSP type 54 (SPG54) is autosomal recessively inherited and caused by mutations in the DDHD2 gene. This study investigated the clinical characteristics and molecular features of DDHD2 mutations in a cohort of Taiwanese patients with HSP.MethodsMutational analysis of DDHD2 was performed for 242 unrelated Taiwanese patients with HSP. The clinical, neuroimaging, and genetic features of the patients with biallelic DDHD2 mutations were characterized. A cell‐based study was performed to assess the effects of the DDHD2 mutations on protein expression.ResultsSPG54 was diagnosed in three patients. Among them, two patients carried compound heterozygous DDHD2 mutations, p.[R112Q];[Y606*] and p.[R112Q];[p.D660H], and the other one was homozygous for the DDHD2 p.R112Q mutation. DDHD2 p.Y606* is a novel mutation, whereas DDHD2 p.D660H and p.R112Q have been reported in the literature. All three patients manifested adult onset complex HSP with additional cerebellar ataxia, polyneuropathy, or cognitive impairment. Brain proton magnetic resonance spectroscopy revealed an abnormal lipid peak in thalamus of all three patients. In vitro studies demonstrated that all the three DDHD2 mutations were associated with a considerably lower DDHD2 protein level.InterpretationSPG54 was detected in approximately 1.2% (3 of 242) of the Taiwanese HSP cohort. This study expands the known mutational spectrum of DDHD2, provides molecular evidence of the pathogenicity of the DDHD2 mutations, and underlines the importance of considering SPG54 as a potential diagnosis of adult‐onset HSP.
The AFG3L2 gene encodes AFG3-like protein 2, which is a subunit of human mitochondrial ATPases as... more The AFG3L2 gene encodes AFG3-like protein 2, which is a subunit of human mitochondrial ATPases associated with various cellular protease activities (m-AAA). The clinical spectrum of AFG3L2 mutations is broad. Dominant AFG3L2 mutations can cause autosomal dominant spinocerebellar ataxia type 28 (SCA28), whereas biallelic AFG3L2 mutations may lead to spastic ataxia 5 (SPAX5). However, the role of AFG3L2 mutations in autosomal recessive spinocerebellar ataxia (SCAR) remains elusive. The aim of this study is to delineate the clinical features and spectrum of AFG3L2 mutations in a Taiwanese cohort with cerebellar ataxia. Mutational analyses of AFG3L2 were carried out by targeted resequencing in a cohort of 133 unrelated patients with molecularly undetermined cerebellar ataxia. We identified one single patient carrying compound heterozygous mutations in AFG3L2, p.[R632*];[V723M] (c.[1894C > T];[2167G > A]). The patient has suffered from apparently sporadic and slowly progressive cerebellar ataxia, ptosis, and ophthalmoparesis since age 55 years. These findings expand the clinical spectrum of AFG3L2 mutations and suggest a new subtype of late-onset SCAR caused by biallelic AFG3L2 mutations.
Recently, DNAJC7 was found to be associated with amyotrophic lateral sclerosis (ALS) in a single ... more Recently, DNAJC7 was found to be associated with amyotrophic lateral sclerosis (ALS) in a single large-scale exome sequencing study. 1 Multiple protein-truncating variants were detected in individuals with ALS that were absent in control subjects. 1 DNAJC7 encodes a member of the DnaJ heat-shock protein family (HspP40), which functions in protein homeostasis, including protein folding and degradation. 2 To validate the pathogenic role of DNAJC7 in ALS and further understand the relevant clinical features, we screened a Taiwanese ALS cohort for DNAJC7 mutations.
Background: The Signal-to-Noise-Ratio (SNR) is often used for identification of biomarkers for tw... more Background: The Signal-to-Noise-Ratio (SNR) is often used for identification of biomarkers for two-class problems and no formal and useful generalization of SNR is available for multiclass problems. We propose innovative generalizations of SNR for multiclass cancer discrimination through introduction of two indices, Gene Dominant Index and Gene Dormant Index (GDIs). These two indices lead to the concepts of dominant and dormant genes with biological significance. We use these indices to develop methodologies for discovery of dominant and dormant biomarkers with interesting biological significance. The dominancy and dormancy of the identified biomarkers and their excellent discriminating power are also demonstrated pictorially using the scatterplot of individual gene and 2-D Sammon's projection of the selected set of genes. Using information from the literature we have shown that the GDI based method can identify dominant and dormant genes that play significant roles in cancer biology. These biomarkers are also used to design diagnostic prediction systems. Results and discussion: To evaluate the effectiveness of the GDIs, we have used four multiclass cancer data sets (Small Round Blue Cell Tumors, Leukemia, Central Nervous System Tumors, and Lung Cancer). For each data set we demonstrate that the new indices can find biologically meaningful genes that can act as biomarkers. We then use six machine learning tools, Nearest Neighbor Classifier (NNC), Nearest Mean Classifier (NMC), Support Vector Machine (SVM) classifier with linear kernel, and SVM classifier with Gaussian kernel, where both SVMs are used in conjunction with one-vs-all (OVA) and one-vs-one (OVO) strategies. We found GDIs to be very effective in identifying biomarkers with strong class specific signatures. With all six tools and for all data sets we could achieve better or comparable prediction accuracies usually with fewer marker genes than results reported in the literature using the same computational protocols. The dominant genes are usually easy to find while good dormant genes may not always be available as dormant genes require stronger constraints to be satisfied; but when they are available, they can be used for authentication of diagnosis. Conclusion: Since GDI based schemes can find a small set of dominant/dormant biomarkers that is adequate to design diagnostic prediction systems, it opens up the possibility of using real-time qPCR assays or antibody based methods such as ELISA for an easy and low cost diagnosis of diseases. The dominant and dormant genes found by GDIs can be used in different ways to design more reliable diagnostic prediction systems.
It is very important to select a small set of relevant features from a high dimensional data set ... more It is very important to select a small set of relevant features from a high dimensional data set and useful to design either an effective classification or prediction model. This procedure involves a series of estimations of the relationship between each pair of variables and between each variable and class labels. Mutual information is widely used to estimate these relationships. However, alternative strategies may be useful to estimate the mutual information with continuous or hybrid data. In this study, we attempt to evaluate the difference between the selection strategies involved with mutual information and fuzzy mutual information. The results indicate that using fuzzy mutual information is more helpful to obtain more stable feature sets and more accurate estimations of the relationship between two variables.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results : Several ascending and descending monotonic key genes were identi ed by Monotonic Feature Selector. The identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. Additionally, not only can TO-GCN analysis classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation, but it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic pro ling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identi ed and the related biological implications have been discussed. Finally, we further elucidated for the rst time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes existing in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts as MSC differentiate into mesangial cells.
Annals of clinical and translational neurology, Oct 15, 2021
ObjectiveMutations in the colony‐stimulating factor 1 receptor gene (CSF1R) were identified as a ... more ObjectiveMutations in the colony‐stimulating factor 1 receptor gene (CSF1R) were identified as a cause of adult‐onset inherited leukoencephalopathy. The present study aims at investigating the frequency, clinical characteristics, and functional effects of CSF1R mutations in Taiwanese patients with adult‐onset leukoencephalopathy.MethodsMutational analysis of CSF1R was performed in 149 unrelated individuals with leukoencephalopathy by a targeted resequencing panel covering the entire coding regions of CSF1R. In vitro analysis of the CSF1‐induced autophosphorylation activities of mutant CSF1R proteins was conducted to assess the pathogenicity of the CSF1R mutations.ResultsAmong the eight CSF1R variants identified in this study, five mutations led to a loss of CSF1‐induced autophosphorylation of CSF1R proteins. Four mutations (p.K586*, p.G589R, p.R777Q, and p.R782C) located within the tyrosine kinase domain of CSF1R, whereas the p.T79M mutation resided in the immunoglobulin‐like domain. The five patients carrying the CSF1R mutations developed cognitive decline at age 41, 43, 50, 79, and 86 years, respectively. Psychiatric symptoms and behavior changes were observed in four of the five patients. The executive function and processing speed were severely impaired at an early stage, and their cognitive function deteriorated rapidly within 3–4 years. Diffusion‐restricted lesions at the subcortical regions and bilateral corticospinal tracts were found in three patients.Interpretation CSF1R mutations account for 3.5% (5/149) of the adult‐onset leukoencephalopathy in Taiwan. CSF1R mutations outside the tyrosine kinase domain may also disturb the CSF1R function and lead to the clinical phenotype. Molecular functional validation is important to determine the pathogenicity of novel CSF1R variants.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results : Several ascending and descending monotonic key genes were identi ed by Monotonic Feature Selector. The identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. Additionally, not only can TO-GCN analysis classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation, but it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic pro ling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identi ed and the related biological implications have been discussed. Finally, we further elucidated for the rst time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes existing in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts as MSC differentiate into mesangial cells.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results : Several ascending and descending monotonic key genes were identi ed by Monotonic Feature Selector. The identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. Additionally, not only can TO-GCN analysis classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation, but it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic pro ling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identi ed and the related biological implications have been discussed. Finally, we further elucidated for the rst time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes existing in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts as MSC differentiate into mesangial cells.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Methods: Differentiation of MSC into mesangial cells was induced by co-culturing with injured mesangial cells. RNA from co-cultured MSC was extracted before running RNA sequencing. Generated RNA-seq data was analysed by two methods simultaneously: 1) Monotonic Feature Selector (MFSelector) to identify the key genes with ascending and descending monotonic patterns, and 2) Time-Ordered Gene Coexpression Network (TO-GCN) to construct a TF co-expression network. Results : MFSelector has identi ed several monotonic key genes (either ascending or descending). These identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were
Background: Breast cancer develops as a result of multiple gene mutations in combination with env... more Background: Breast cancer develops as a result of multiple gene mutations in combination with environmental risk factors. Causative variants in genes such as BRCA1 and/or BRCA2 have been shown to account for hereditary nature of certain breast cancers. However,other genes, such as ATM, PALB2, BRIP1, CHEK, BARD1, while lower in frequency, may also increase breast cancer risk. There are few studies examining the role of these causative variants. Our study aimed to examine the clinical and genetic characterization of hereditary breast cancer in a Chinese population. Methods: We tested a panel of 27 genes implicated in breast cancer risk in 240 participants using Next-Generation Sequencing. The prevalence of genetic causative variants was determined and the association between causative variants and clinico-pathological characteristics was analyzed. Results: Causative variant rate was 19.2% in the breast cancer (case) group and 12.5% in the high-risk group. In the case group 2.5% of patients carried BRCA1 causative variant, 7.5% BRCA2 variants, 1.7% patients had MUTYH, CHEK or PALB2 variants, and 0.8% patients carried ATM, BARD1, NBN, RAD51C or TP53 variants. In the high-risk group 5. 8% women carried MUTYH causative variants, 2.5% had causative variants in ATM, 1.7% patients had variants in BRCA2 and 0.8% in BARD1, BRIP1 or CDH1. There was no significant difference in the presence of causative variants among clinical stages of breast cancer, tumor size and lymph nodes status. However, eight of the 12 BRCA1/2 causative variants were found in the TNBC group. Conclusions: We found increased genetic causative variants in the familial breast cancer group and in high-risk women with a family history of breast cancer. However, the variant MUTYH c.892-2A > G may not be directly associated with hereditary breast carcinoma.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) have been reported can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Methods: Differentiation of MSC into mesangial cells was induced by co-culturing with injured mesangial cells. Total RNA from co-cultured MSC were extracted before running RNA sequencing. Generated RNAseq data was analysed by two methods simultaneously: 1) Monotonic Feature Selector (MFSelector) to identify the key genes with ascending and descending monotonic patterns, and 2) Time-Ordered Gene Coexpression Network (TO-GCN) to construct a TF co-expression network. Results: MFSelector has identi ed several monotonic key genes (either ascending or descending). These identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were
Background: Mesangial cells play an important role in the glomerulus to provide mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus to provide mechanical support and maintaine efficient ultrafiltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic profiling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells, to understand the involvement of transcription factor (TF) along the differentiation process, and finally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results: Several ascending and descending monotonic key genes were identified by Monotonic Feature Selector. The identified descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. TO-GCN analysis can classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation. Furthermore, it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic profiling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identified and the related biological implications have been discussed. Finally, we further elucidated for the first time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes involved in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts during the differentiation of MSC into mesangial cells.
Background/purpose: Hereditary spastic paraplegia (HSP) is a heterogeneous group of inherited neu... more Background/purpose: Hereditary spastic paraplegia (HSP) is a heterogeneous group of inherited neurodegenerative disorders characterized by slowly progressive lower limbs spasticity and weakness. HSP type 15 (SPG15) is an autosomal recessive subtype caused by ZFYVE26 mutations. The aim of this study was to investigate the frequency and clinical and genetic features of ZFYVE26 mutations in a Taiwanese HSP cohort. Methods: Mutational analysis of the coding regions of ZFYVE26 was performed by targeted resequencing in the 195 unrelated Taiwanese patients with HSP. All of the patients were of Han Chinese ethnicity. Clinical, neuropsychological, electrophysiological evaluations and imaging studies were collected. Results: Among the 195 patients, only one SPG15 patient was identified. The patient had a novel recessive ZFYVE26 frameshift truncating mutation, p.R1806Gfs * 36 (c.5415delC), and presented with insidious onset spastic weakness of lower-extremities and cognitive impairment. Neuropsychological assessment revealed deficits in executive function, visual naming, category verbal fluency, and manual dexterity. Brain MRI showed thin corpus callosum and the "ears of lynx" sign. Conclusion: SPG15 accounts for approximately 0.5% (1/195) of the Taiwanese HSP cohort. This study identified the first Taiwanese SPG15 case and delineated the clinical, genetic,
BACKGROUND Adrenoleukodystrophy (ALD) is an X-linked peroxisomal disorder caused by mutations in ... more BACKGROUND Adrenoleukodystrophy (ALD) is an X-linked peroxisomal disorder caused by mutations in the ABCD1 gene. The clinical manifestations of ALD vary widely with some patients presenting with adrenomyeloneuropathy (AMN) that resembles the phenotype of hereditary spastic paraplegia (HSP). The aim of this study is to investigate the frequency, spectrum, and clinical features of ABCD1 mutations in Taiwanese patients with HSP phenotype. METHODS Mutational analysis of the ABCD1 gene was performed in 230 unrelated Taiwanese patients with clinically suspected HSP by targeted resequencing. Clinical, electrophysiological, and neuroimaging features of the patients carrying an ABCD1 pathogenic mutation were characterized. RESULTS Ten different ABCD1 mutations were identified in eleven patients, including two novel mutations (p.Q177Pfs*17 and p.Y357*) and eight ever reported in ALD cases of other ethnicities. All patients were male and exhibited slowly progressive spastic paraparesis with onset ages ranging from 21 to 50 years. Most of them had additional non-motor symptoms, including autonomic dysfunction in nine patients, sensory deficits in seven, premature baldness in seven, skin hyperpigmentation in five, psychiatric symptoms in one and cerebellar ataxia in one. Seven of the ten patients who ever received nerve conduction studies showed axonal polyneuropathy. Magnetic resonance imaging (MRI) revealed diffuse spinal cord atrophy in seven patients, cerebral white matter hyperintensity in one patient, and cerebellar involvement in one patient. CONCLUSIONS ABCD1 mutations account for 4.8% (11/230) of the cases with HSP phenotype in Taiwan. This study highlights the importance to consider ABCD1 mutations in patients with clinically suspected HSP of unknown genetic causes.
Annals of clinical and translational neurology, Jul 7, 2023
ObjectiveHereditary spastic paraplegias (HSPs) are a group of inherited neurodegenerative disorde... more ObjectiveHereditary spastic paraplegias (HSPs) are a group of inherited neurodegenerative disorders characterized by slowly progressive lower limb spasticity and weakness. HSP type 54 (SPG54) is autosomal recessively inherited and caused by mutations in the DDHD2 gene. This study investigated the clinical characteristics and molecular features of DDHD2 mutations in a cohort of Taiwanese patients with HSP.MethodsMutational analysis of DDHD2 was performed for 242 unrelated Taiwanese patients with HSP. The clinical, neuroimaging, and genetic features of the patients with biallelic DDHD2 mutations were characterized. A cell‐based study was performed to assess the effects of the DDHD2 mutations on protein expression.ResultsSPG54 was diagnosed in three patients. Among them, two patients carried compound heterozygous DDHD2 mutations, p.[R112Q];[Y606*] and p.[R112Q];[p.D660H], and the other one was homozygous for the DDHD2 p.R112Q mutation. DDHD2 p.Y606* is a novel mutation, whereas DDHD2 p.D660H and p.R112Q have been reported in the literature. All three patients manifested adult onset complex HSP with additional cerebellar ataxia, polyneuropathy, or cognitive impairment. Brain proton magnetic resonance spectroscopy revealed an abnormal lipid peak in thalamus of all three patients. In vitro studies demonstrated that all the three DDHD2 mutations were associated with a considerably lower DDHD2 protein level.InterpretationSPG54 was detected in approximately 1.2% (3 of 242) of the Taiwanese HSP cohort. This study expands the known mutational spectrum of DDHD2, provides molecular evidence of the pathogenicity of the DDHD2 mutations, and underlines the importance of considering SPG54 as a potential diagnosis of adult‐onset HSP.
The AFG3L2 gene encodes AFG3-like protein 2, which is a subunit of human mitochondrial ATPases as... more The AFG3L2 gene encodes AFG3-like protein 2, which is a subunit of human mitochondrial ATPases associated with various cellular protease activities (m-AAA). The clinical spectrum of AFG3L2 mutations is broad. Dominant AFG3L2 mutations can cause autosomal dominant spinocerebellar ataxia type 28 (SCA28), whereas biallelic AFG3L2 mutations may lead to spastic ataxia 5 (SPAX5). However, the role of AFG3L2 mutations in autosomal recessive spinocerebellar ataxia (SCAR) remains elusive. The aim of this study is to delineate the clinical features and spectrum of AFG3L2 mutations in a Taiwanese cohort with cerebellar ataxia. Mutational analyses of AFG3L2 were carried out by targeted resequencing in a cohort of 133 unrelated patients with molecularly undetermined cerebellar ataxia. We identified one single patient carrying compound heterozygous mutations in AFG3L2, p.[R632*];[V723M] (c.[1894C > T];[2167G > A]). The patient has suffered from apparently sporadic and slowly progressive cerebellar ataxia, ptosis, and ophthalmoparesis since age 55 years. These findings expand the clinical spectrum of AFG3L2 mutations and suggest a new subtype of late-onset SCAR caused by biallelic AFG3L2 mutations.
Recently, DNAJC7 was found to be associated with amyotrophic lateral sclerosis (ALS) in a single ... more Recently, DNAJC7 was found to be associated with amyotrophic lateral sclerosis (ALS) in a single large-scale exome sequencing study. 1 Multiple protein-truncating variants were detected in individuals with ALS that were absent in control subjects. 1 DNAJC7 encodes a member of the DnaJ heat-shock protein family (HspP40), which functions in protein homeostasis, including protein folding and degradation. 2 To validate the pathogenic role of DNAJC7 in ALS and further understand the relevant clinical features, we screened a Taiwanese ALS cohort for DNAJC7 mutations.
Background: The Signal-to-Noise-Ratio (SNR) is often used for identification of biomarkers for tw... more Background: The Signal-to-Noise-Ratio (SNR) is often used for identification of biomarkers for two-class problems and no formal and useful generalization of SNR is available for multiclass problems. We propose innovative generalizations of SNR for multiclass cancer discrimination through introduction of two indices, Gene Dominant Index and Gene Dormant Index (GDIs). These two indices lead to the concepts of dominant and dormant genes with biological significance. We use these indices to develop methodologies for discovery of dominant and dormant biomarkers with interesting biological significance. The dominancy and dormancy of the identified biomarkers and their excellent discriminating power are also demonstrated pictorially using the scatterplot of individual gene and 2-D Sammon's projection of the selected set of genes. Using information from the literature we have shown that the GDI based method can identify dominant and dormant genes that play significant roles in cancer biology. These biomarkers are also used to design diagnostic prediction systems. Results and discussion: To evaluate the effectiveness of the GDIs, we have used four multiclass cancer data sets (Small Round Blue Cell Tumors, Leukemia, Central Nervous System Tumors, and Lung Cancer). For each data set we demonstrate that the new indices can find biologically meaningful genes that can act as biomarkers. We then use six machine learning tools, Nearest Neighbor Classifier (NNC), Nearest Mean Classifier (NMC), Support Vector Machine (SVM) classifier with linear kernel, and SVM classifier with Gaussian kernel, where both SVMs are used in conjunction with one-vs-all (OVA) and one-vs-one (OVO) strategies. We found GDIs to be very effective in identifying biomarkers with strong class specific signatures. With all six tools and for all data sets we could achieve better or comparable prediction accuracies usually with fewer marker genes than results reported in the literature using the same computational protocols. The dominant genes are usually easy to find while good dormant genes may not always be available as dormant genes require stronger constraints to be satisfied; but when they are available, they can be used for authentication of diagnosis. Conclusion: Since GDI based schemes can find a small set of dominant/dormant biomarkers that is adequate to design diagnostic prediction systems, it opens up the possibility of using real-time qPCR assays or antibody based methods such as ELISA for an easy and low cost diagnosis of diseases. The dominant and dormant genes found by GDIs can be used in different ways to design more reliable diagnostic prediction systems.
It is very important to select a small set of relevant features from a high dimensional data set ... more It is very important to select a small set of relevant features from a high dimensional data set and useful to design either an effective classification or prediction model. This procedure involves a series of estimations of the relationship between each pair of variables and between each variable and class labels. Mutual information is widely used to estimate these relationships. However, alternative strategies may be useful to estimate the mutual information with continuous or hybrid data. In this study, we attempt to evaluate the difference between the selection strategies involved with mutual information and fuzzy mutual information. The results indicate that using fuzzy mutual information is more helpful to obtain more stable feature sets and more accurate estimations of the relationship between two variables.
Background: Mesangial cells play an important role in the glomerulus, providing mechanical suppor... more Background: Mesangial cells play an important role in the glomerulus, providing mechanical support to it, and maintaining e cient ultra ltration of renal plasma. Loss of mesangial cells due to pathologic conditions may lead to impaired renal function. Mesenchymal stem cells (MSC) can differentiate into many cell types, including mesangial cells. However transcriptomic pro ling during MSC differentiation into mesangial cells had not been studied yet. The aim of this study is to examine the pattern of transcriptomic changes during MSC differentiation into mesangial cells as well as to understand the involvement of transcription factor (TF) along the differentiation process, and nally to elucidate the relationship among TF-TF and TF-key gene or biomarkers during the differentiation of MSC into mesangial cells. Results : Several ascending and descending monotonic key genes were identi ed by Monotonic Feature Selector. The identi ed descending monotonic key genes are related to stemness or regulation of cell cycle while ascending monotonic key genes are associated with the functions of mesangial cells. The TFs were arranged in a co-expression network in order of time by Time-Ordered Gene Co-expression Network (TO-GCN) analysis. Additionally, not only can TO-GCN analysis classify the differentiation process into three stages: differentiation preparation, differentiation initiation and maturation, but it can also explore TF-TF-key genes regulatory relationships in the muscle contraction process. Conclusions: A systematic analysis for transcriptomic pro ling of MSC differentiation into mesangial cells has been established. Key genes or biomarkers, TFs and pathways involved in differentiation of MSC-mesangial cells have been identi ed and the related biological implications have been discussed. Finally, we further elucidated for the rst time the three main stages of mesangial cell differentiation, and the regulatory relationships between TF-TF-key genes existing in the muscle contraction process. Through this study, we have increased fundamental understanding of the gene transcripts as MSC differentiate into mesangial cells.
Annals of clinical and translational neurology, Oct 15, 2021
ObjectiveMutations in the colony‐stimulating factor 1 receptor gene (CSF1R) were identified as a ... more ObjectiveMutations in the colony‐stimulating factor 1 receptor gene (CSF1R) were identified as a cause of adult‐onset inherited leukoencephalopathy. The present study aims at investigating the frequency, clinical characteristics, and functional effects of CSF1R mutations in Taiwanese patients with adult‐onset leukoencephalopathy.MethodsMutational analysis of CSF1R was performed in 149 unrelated individuals with leukoencephalopathy by a targeted resequencing panel covering the entire coding regions of CSF1R. In vitro analysis of the CSF1‐induced autophosphorylation activities of mutant CSF1R proteins was conducted to assess the pathogenicity of the CSF1R mutations.ResultsAmong the eight CSF1R variants identified in this study, five mutations led to a loss of CSF1‐induced autophosphorylation of CSF1R proteins. Four mutations (p.K586*, p.G589R, p.R777Q, and p.R782C) located within the tyrosine kinase domain of CSF1R, whereas the p.T79M mutation resided in the immunoglobulin‐like domain. The five patients carrying the CSF1R mutations developed cognitive decline at age 41, 43, 50, 79, and 86 years, respectively. Psychiatric symptoms and behavior changes were observed in four of the five patients. The executive function and processing speed were severely impaired at an early stage, and their cognitive function deteriorated rapidly within 3–4 years. Diffusion‐restricted lesions at the subcortical regions and bilateral corticospinal tracts were found in three patients.Interpretation CSF1R mutations account for 3.5% (5/149) of the adult‐onset leukoencephalopathy in Taiwan. CSF1R mutations outside the tyrosine kinase domain may also disturb the CSF1R function and lead to the clinical phenotype. Molecular functional validation is important to determine the pathogenicity of novel CSF1R variants.
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Papers by Yu-Shuen Tsai