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Lifeng Tian
Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA

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Journal article
Published: 25 March 2021 in International Journal of Molecular Sciences
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RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels.

ACS Style

Yichuan Liu; Hui-Qi Qu; Xiao Chang; Lifeng Tian; Jingchun Qu; Joseph Glessner; Patrick Sleiman; Hakon Hakonarson. Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters. International Journal of Molecular Sciences 2021, 22, 3364 .

AMA Style

Yichuan Liu, Hui-Qi Qu, Xiao Chang, Lifeng Tian, Jingchun Qu, Joseph Glessner, Patrick Sleiman, Hakon Hakonarson. Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters. International Journal of Molecular Sciences. 2021; 22 (7):3364.

Chicago/Turabian Style

Yichuan Liu; Hui-Qi Qu; Xiao Chang; Lifeng Tian; Jingchun Qu; Joseph Glessner; Patrick Sleiman; Hakon Hakonarson. 2021. "Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters." International Journal of Molecular Sciences 22, no. 7: 3364.

Journal article
Published: 22 February 2021 in Genes
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Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with poorly understood molecular mechanisms that results in significant impairment in children. In this study, we sought to assess the role of rare recurrent variants in non-European populations and outside of coding regions. We generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The cases included 116 African Americans (AA) and 89 European Americans (EA), and the controls included 408 AA and 262 EA. Multiple novel rare recurrent variants were identified in exonic regions, functionally classified as stop-gains and frameshifts for known ADHD genes. Deletion in introns of the protocadherins families and the ncRNA HGB8P were identified in two independent EA ADHD patients. A meta-analysis of the two ethnicities for differential ADHD recurrent variants compared to controls shows a small number of overlaps. These results suggest that rare recurrent variants in noncoding regions may be involved in the pathogenesis of ADHD in children of both AA and EA ancestry; thus, WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD.

ACS Style

Yichuan Liu; Xiao Chang; Hui-Qi Qu; Lifeng Tian; Joseph Glessner; Jingchun Qu; Dong Li; Haijun Qiu; Patrick Sleiman; Hakon Hakonarson. Rare Recurrent Variants in Noncoding Regions Impact Attention-Deficit Hyperactivity Disorder (ADHD) Gene Networks in Children of both African American and European American Ancestry. Genes 2021, 12, 310 .

AMA Style

Yichuan Liu, Xiao Chang, Hui-Qi Qu, Lifeng Tian, Joseph Glessner, Jingchun Qu, Dong Li, Haijun Qiu, Patrick Sleiman, Hakon Hakonarson. Rare Recurrent Variants in Noncoding Regions Impact Attention-Deficit Hyperactivity Disorder (ADHD) Gene Networks in Children of both African American and European American Ancestry. Genes. 2021; 12 (2):310.

Chicago/Turabian Style

Yichuan Liu; Xiao Chang; Hui-Qi Qu; Lifeng Tian; Joseph Glessner; Jingchun Qu; Dong Li; Haijun Qiu; Patrick Sleiman; Hakon Hakonarson. 2021. "Rare Recurrent Variants in Noncoding Regions Impact Attention-Deficit Hyperactivity Disorder (ADHD) Gene Networks in Children of both African American and European American Ancestry." Genes 12, no. 2: 310.

Journal article
Published: 01 December 2020 in JMIR Biomedical Engineering
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Background Maturity-onset diabetes of the young (MODY) is a group of dominantly inherited monogenic diabetes, with HNF4A-MODY, GCK-MODY, and HNF1A-MODY as the three most common forms based on the causal genes. Molecular diagnosis of MODY is important for precise treatment. Although a DNA variant causing MODY can be assessed based on the criteria of the American College of Medical Genetics and Genomics (ACMG) guidelines, gene-specific assessment of disease-causing mutations is important to differentiate among MODY subtypes. As the ACMG criteria were not originally designed for machine-learning algorithms, they are not true independent variables. Objective The aim of this study was to develop machine-learning models for interpretation of DNA variants and MODY diagnosis using the ACMG criteria. Methods We applied machine-learning models for interpretation of DNA variants in MODY genes defined by the ACMG criteria based on the Human Gene Mutation Database (HGMD) and ClinVar database. Results With a machine-learning procedure, we found that the weight matrix of the ACMG criteria was significantly different between the three MODY genes HNF1A, HNF4A, and GCK. The models showed high predictive abilities with accuracy over 95%. Conclusions Our results highlight the need for applying different weights of the ACMG criteria in relation to different MODY genes for accurate functional classification. As proof of principle, we applied the ACMG criteria as feature vectors in a machine-learning model and obtained a precision-based result.

ACS Style

Yichuan Liu; Hui-Qi Qu; Adam S Wenocur; Jingchun Qu; Xiao Chang; Joseph Glessner; Patrick Sleiman; Lifeng Tian; Hakon Hakonarson. Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development. JMIR Biomedical Engineering 2020, 5, e20506 .

AMA Style

Yichuan Liu, Hui-Qi Qu, Adam S Wenocur, Jingchun Qu, Xiao Chang, Joseph Glessner, Patrick Sleiman, Lifeng Tian, Hakon Hakonarson. Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development. JMIR Biomedical Engineering. 2020; 5 (1):e20506.

Chicago/Turabian Style

Yichuan Liu; Hui-Qi Qu; Adam S Wenocur; Jingchun Qu; Xiao Chang; Joseph Glessner; Patrick Sleiman; Lifeng Tian; Hakon Hakonarson. 2020. "Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development." JMIR Biomedical Engineering 5, no. 1: e20506.

Review
Published: 29 October 2020 in Viruses
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There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19.

ACS Style

Zhangkai J. Cheng; Hui-Qi Qu; Lifeng Tian; Zhifeng Duan; Hakon Hakonarson. COVID-19: Look to the Future, Learn from the Past. Viruses 2020, 12, 1226 .

AMA Style

Zhangkai J. Cheng, Hui-Qi Qu, Lifeng Tian, Zhifeng Duan, Hakon Hakonarson. COVID-19: Look to the Future, Learn from the Past. Viruses. 2020; 12 (11):1226.

Chicago/Turabian Style

Zhangkai J. Cheng; Hui-Qi Qu; Lifeng Tian; Zhifeng Duan; Hakon Hakonarson. 2020. "COVID-19: Look to the Future, Learn from the Past." Viruses 12, no. 11: 1226.

Communication
Published: 16 October 2020 in Viruses
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To address the expression pattern of the SARS-CoV-2 receptor ACE2 and the viral priming protease TMPRSS2 in the respiratory tract, this study investigated RNA sequencing transcriptome profiling of samples of airway and oral mucosa. As shown, ACE2 has medium levels of expression in both small airway epithelium and masticatory mucosa, and high levels of expression in nasal epithelium. The expression of ACE2 is low in mucosal-associated invariant T (MAIT) cells and cannot be detected in alveolar macrophages. TMPRSS2 is highly expressed in small airway epithelium and nasal epithelium and has lower expression in masticatory mucosa. Our results provide the molecular basis that the nasal mucosa is the most susceptible locus in the respiratory tract for SARS-CoV-2 infection and consequently for subsequent droplet transmission and should be the focus for protection against SARS-CoV-2 infection.

ACS Style

Yichuan Liu; Hui-Qi Qu; Jingchun Qu; Lifeng Tian; Hakon Hakonarson. Expression Pattern of the SARS-CoV-2 Entry Genes ACE2 and TMPRSS2 in the Respiratory Tract. Viruses 2020, 12, 1174 .

AMA Style

Yichuan Liu, Hui-Qi Qu, Jingchun Qu, Lifeng Tian, Hakon Hakonarson. Expression Pattern of the SARS-CoV-2 Entry Genes ACE2 and TMPRSS2 in the Respiratory Tract. Viruses. 2020; 12 (10):1174.

Chicago/Turabian Style

Yichuan Liu; Hui-Qi Qu; Jingchun Qu; Lifeng Tian; Hakon Hakonarson. 2020. "Expression Pattern of the SARS-CoV-2 Entry Genes ACE2 and TMPRSS2 in the Respiratory Tract." Viruses 12, no. 10: 1174.

Preprint
Published: 28 September 2020
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To address the expression pattern of the SARS-CoV-2 receptor ACE2 and the viral priming protease, TMPRSS2, in the respiratory tract, this study investigated RNA sequencing transcriptome profiling of samples of airway and oral mucosa. As shown, ACE2 has medium levels of expression in both small airway epithelium and masticatory mucosa, and high levels of expression in nasal epithelium. The expression of ACE2 is low in mucosal associated invariant T (MAIT) cells, and can’t be detected in alveolar macrophages. TMPRSS2 is highly expressed in small airway epithelium and nasal epithelium, and has lower expression in masticatory mucosa. Our results provide the molecular basis that the nasal mucosa is the most susceptible locus in the respiratory tract for SARS-CoV-2 infection and consequently for subsequent droplet transmission and should be the focus for protection against SARS-CoV-2 infection.

ACS Style

Yichuan Liu; Hui-Qi Qu; Jingchun Qu; Lifeng Tian; Hakon Hakonarson. Expression Pattern of the SARS-CoV-2 Entry Genes ACE2 and TMPRSS2 in the Respiratory Tract. 2020, 1 .

AMA Style

Yichuan Liu, Hui-Qi Qu, Jingchun Qu, Lifeng Tian, Hakon Hakonarson. Expression Pattern of the SARS-CoV-2 Entry Genes ACE2 and TMPRSS2 in the Respiratory Tract. . 2020; ():1.

Chicago/Turabian Style

Yichuan Liu; Hui-Qi Qu; Jingchun Qu; Lifeng Tian; Hakon Hakonarson. 2020. "Expression Pattern of the SARS-CoV-2 Entry Genes ACE2 and TMPRSS2 in the Respiratory Tract." , no. : 1.

Journal article
Published: 14 August 2020 in Journal of Medical Internet Research
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Background The coronavirus disease (COVID-19) pandemic began in Wuhan, China, in December 2019. Wuhan had a much higher mortality rate than the rest of China. However, a large number of asymptomatic infections in Wuhan may have never been diagnosed, contributing to an overestimated mortality rate. Objective This study aims to obtain an accurate estimate of infections in Wuhan using internet data. Methods In this study, we performed a combined analysis of the infection rate among evacuated foreign citizens to estimate the infection rate in Wuhan in late January and early February. Results Based on our analysis, the combined infection rate of the foreign evacuees was 0.013 (95% CI 0.008-0.022). Therefore, we estimate the number of infected people in Wuhan to be 143,000 (range 88,000-242,000), which is significantly higher than previous estimates. Our study indicates that a large number of infections in Wuhan were not diagnosed, which has resulted in an overestimated case fatality rate. Conclusions Increased awareness of the original infection rate of Wuhan is critical for proper public health measures at all levels, as well as to eliminate panic caused by overestimated mortality rates that may bias health policy actions by the authorities.

ACS Style

Hui-Qi Qu; Zhangkai Jason Cheng; Zhifeng Duan; Lifeng Tian; Hakon Hakonarson. The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples. Journal of Medical Internet Research 2020, 22, e20914 .

AMA Style

Hui-Qi Qu, Zhangkai Jason Cheng, Zhifeng Duan, Lifeng Tian, Hakon Hakonarson. The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples. Journal of Medical Internet Research. 2020; 22 (8):e20914.

Chicago/Turabian Style

Hui-Qi Qu; Zhangkai Jason Cheng; Zhifeng Duan; Lifeng Tian; Hakon Hakonarson. 2020. "The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples." Journal of Medical Internet Research 22, no. 8: e20914.

Other
Published: 12 June 2020
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Schizophrenia (SCZ) is a chronic and severely disabling neurodevelopmental disorder that affects people worldwide. RNA-seq has been a powerful method to detect the differentially expressed genes/non-coding RNAs in patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. In this study, dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals’ was obtained from the CommonMind consortium and analyzed with machine learning methods, including random forest, forward feature selection (ffs), and factor analysis, to reduce the numbers of gene/non-coding RNA feature vectors to overcome overfitting problem and explore involved functional clusters. In 2-fold shuffle testing, the average predictive accuracy for SCZ patients was 67% based on coding genes, and the 96% based on long non-coding RNAs (lncRNAs). Coding genes were further clustered into 14 factors and lncRNAs were clustered into 45 factors to represent the underlying features. The largest contribution factor for coding genes contains number of genes critical in neurodevelopment and previously reported in relation with various brain disorders. Genomic loci of lncRNAs were more insightful, enriched for genes critical in synapse function (p=7.3E-3), cell junction (p=0.017), neuron differentiation (p=8.3E-3), phosphorylation (8.2E-4), and involving the Wnt signaling pathway (p=0.029). Taken together, machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the formers regulate every level of gene expression, not limited to mRNA levels.

ACS Style

Yichuan Liu; Hui-Qi Qu; Xiao Chang; Lifeng Tian; Joseph Glessner; Patrick A. M. Sleiman; Hakon Hakonarson. Machine learning reduced gene/non-coding RNA features that classify Schizophrenia patients accurately and highlight insightful gene clusters. 2020, 1 .

AMA Style

Yichuan Liu, Hui-Qi Qu, Xiao Chang, Lifeng Tian, Joseph Glessner, Patrick A. M. Sleiman, Hakon Hakonarson. Machine learning reduced gene/non-coding RNA features that classify Schizophrenia patients accurately and highlight insightful gene clusters. . 2020; ():1.

Chicago/Turabian Style

Yichuan Liu; Hui-Qi Qu; Xiao Chang; Lifeng Tian; Joseph Glessner; Patrick A. M. Sleiman; Hakon Hakonarson. 2020. "Machine learning reduced gene/non-coding RNA features that classify Schizophrenia patients accurately and highlight insightful gene clusters." , no. : 1.

Preprint content
Published: 04 June 2020
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BACKGROUND The coronavirus disease (COVID-19) pandemic began in Wuhan, China, in December 2019. Wuhan had a much higher mortality rate than the rest of China. However, a large number of asymptomatic infections in Wuhan may have never been diagnosed, contributing to an overestimated mortality rate. OBJECTIVE This study aims to obtain an accurate estimate of infections in Wuhan using internet data. METHODS In this study, we performed a combined analysis of the infection rate among evacuated foreign citizens to estimate the infection rate in Wuhan in late January and early February. RESULTS Based on our analysis, the combined infection rate of the foreign evacuees was 0.013 (95% CI 0.008-0.022). Therefore, we estimate the number of infected people in Wuhan to be 143,000 (range 88,000-242,000), which is significantly higher than previous estimates. Our study indicates that a large number of infections in Wuhan were not diagnosed, which has resulted in an overestimated case fatality rate. CONCLUSIONS Increased awareness of the original infection rate of Wuhan is critical for proper public health measures at all levels, as well as to eliminate panic caused by overestimated mortality rates that may bias health policy actions by the authorities.

ACS Style

Hui-Qi Qu; Zhangkai Jason Cheng; Zhifeng Duan; Lifeng Tian; Hakon Hakonarson. The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples (Preprint). 2020, 1 .

AMA Style

Hui-Qi Qu, Zhangkai Jason Cheng, Zhifeng Duan, Lifeng Tian, Hakon Hakonarson. The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples (Preprint). . 2020; ():1.

Chicago/Turabian Style

Hui-Qi Qu; Zhangkai Jason Cheng; Zhifeng Duan; Lifeng Tian; Hakon Hakonarson. 2020. "The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples (Preprint)." , no. : 1.

Preprint content
Published: 30 May 2020
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BACKGROUND Maturity-onset diabetes of the young (MODY) is a group of dominantly inherited monogenic diabetes, with HNF4A-MODY, GCK-MODY, and HNF1A-MODY as the three most common forms based on the causal genes. Molecular diagnosis of MODY is important for precise treatment. Although a DNA variant causing MODY can be assessed based on the criteria of the American College of Medical Genetics and Genomics (ACMG) guidelines, gene-specific assessment of disease-causing mutations is important to differentiate among MODY subtypes. As the ACMG criteria were not originally designed for machine-learning algorithms, they are not true independent variables. OBJECTIVE The aim of this study was to develop machine-learning models for interpretation of DNA variants and MODY diagnosis using the ACMG criteria. METHODS We applied machine-learning models for interpretation of DNA variants in MODY genes defined by the ACMG criteria based on the Human Gene Mutation Database (HGMD) and ClinVar database. RESULTS With a machine-learning procedure, we found that the weight matrix of the ACMG criteria was significantly different between the three MODY genes HNF1A, HNF4A, and GCK. The models showed high predictive abilities with accuracy over 95%. CONCLUSIONS Our results highlight the need for applying different weights of the ACMG criteria in relation to different MODY genes for accurate functional classification. As proof of principle, we applied the ACMG criteria as feature vectors in a machine-learning model and obtained a precision-based result.

ACS Style

Yichuan Liu; Hui-Qi Qu; Adam S Wenocur; Jingchun Qu; Xiao Chang; Joseph Glessner; Patrick Sleiman; Lifeng Tian; Hakon Hakonarson. Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development (Preprint). 2020, 1 .

AMA Style

Yichuan Liu, Hui-Qi Qu, Adam S Wenocur, Jingchun Qu, Xiao Chang, Joseph Glessner, Patrick Sleiman, Lifeng Tian, Hakon Hakonarson. Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development (Preprint). . 2020; ():1.

Chicago/Turabian Style

Yichuan Liu; Hui-Qi Qu; Adam S Wenocur; Jingchun Qu; Xiao Chang; Joseph Glessner; Patrick Sleiman; Lifeng Tian; Hakon Hakonarson. 2020. "Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development (Preprint)." , no. : 1.

Other
Published: 23 May 2020
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Background: Maturity-onset diabetes of the young (MODY) is a group of dominantly inherited monogenic diabetes, with HNF4A-MODY, GCK-MODY and HNF1A-MODY being the three most common genes responsible. Molecular diagnosis of MODY is important for precise treatment. While a DNA variant causing MODY can be assessed by the criteria of the American College of Medical Genetics and Genomics (ACMG) guidelines, gene-specific assessment of disease-causing mutations is important to differentiate between the MODY subtypes. As the ACMG criteria were not originally designed for machine learning algorithms, they are not true independent variables. Methods: In this study, we applied machine learning models for interpretation of DNA variants in MODY genes defined by the ACMG criteria based on Human Gene Mutation Database (HGMD) and ClinVar. Results: The results show highly predictive abilities with accuracy over 95%, suggest that this model could serve as a fast, gene-specific method for physicians or genetic counselors assisting with diagnosis and reporting, especially when confronted by contradictory ACMG criteria. Also, the weight of the ACMG criteria shows gene specificity which advocates for the application of machine learning methods with the ACMG criteria to capture the most relevant information for each disease-related variant. Conclusion: Our results highlight the need for different weights of the ACMG criteria in relation with different MODY genes for accurate functional classification. For proof of principle, we applied the ACMG criteria as feature vectors in a machine learning model obtaining precision-based result.

ACS Style

Yichuan Liu; Huiqi Qu; Adam S Wenocur; Jingchun Qu; Xiao Chang; Joseph Glessner; Patrick Sleiman; Lifeng Tian; Hakon Hakonarson. Machine Learning for Interpretation of DNA Variants of Maturity-Onset Diabetes of the Young Genes Based on ACMG Criteria. 2020, 1 .

AMA Style

Yichuan Liu, Huiqi Qu, Adam S Wenocur, Jingchun Qu, Xiao Chang, Joseph Glessner, Patrick Sleiman, Lifeng Tian, Hakon Hakonarson. Machine Learning for Interpretation of DNA Variants of Maturity-Onset Diabetes of the Young Genes Based on ACMG Criteria. . 2020; ():1.

Chicago/Turabian Style

Yichuan Liu; Huiqi Qu; Adam S Wenocur; Jingchun Qu; Xiao Chang; Joseph Glessner; Patrick Sleiman; Lifeng Tian; Hakon Hakonarson. 2020. "Machine Learning for Interpretation of DNA Variants of Maturity-Onset Diabetes of the Young Genes Based on ACMG Criteria." , no. : 1.

Other
Published: 18 May 2020
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Background: Mutations in the sarcomeric protein filamin C (FLNC) gene have been linked to hypertrophic cardiomyopathy (HCM), in which they increase the risk of ventricular arrhythmia and sudden death. In this study, we identified a novel missense mutation of FLNC in a Chinese family with HCM and interestingly a second novel truncating mutation of MYLK2 in one family member with different phenotype. Methods: We performed whole-exome sequencing in a Chinese family with HCM of unknown cause. To validate the function of a novel mutation of FLNC, we introduced the mutant and wild-type gene into AC16 cells (human cardiomyocytes), and used western blotting to analyze the expression of FLNC in subcellular fractions, and confocal microscope to observe the subcellular distribution of the protein. Results: We identified a novel missense single nucleotide variant (FLNC c.G5935A [p.A1979T]) in the family, which segregates with the disease. FLNC expression levels were equivalent in both wild type and p.A1979T cardiomyocytes. However, expression of the mutant protein resulted in cytoplasmic protein aggregations, in contrast to wild type FLNC, which was distributed in the cytoplasm and did not form aggregates. Unexpectely, a second truncating mutation, NM_033118:exon8:c.G1138T:p.E380X of the MYLK2 gene, was identified in the mother of the proband with dilated cardiomyopathy, but absent in other subjects. Conclusion: We identified the FLNC A1979T mutation as a novel pathogenic variant associated with HCM in a Chinese family, as well as a second causal mutation in a family member with a distinct phenotype. The possibility of more than one causal mutations in cardiomyopathy warrants clinical attention, especially for patients with atypical clinical features.

ACS Style

Xianyu Qin; Ping Li; Huiqi Qu; Yichuan Liu; Yu Xia; Shaoxian Chen; Yongchao Yang; Shufang Huang; Pengju Wen; Xianwu Zhou; Xiaofeng Li; Yonghua Wang; Lifeng Tian; Hakon Hakonarson; Yueheng Wu; Jian Zhuang. FLNC and MYLK2 gene mutations in a Chinese family with different phenotypes of cardiomyopathy. 2020, 1 .

AMA Style

Xianyu Qin, Ping Li, Huiqi Qu, Yichuan Liu, Yu Xia, Shaoxian Chen, Yongchao Yang, Shufang Huang, Pengju Wen, Xianwu Zhou, Xiaofeng Li, Yonghua Wang, Lifeng Tian, Hakon Hakonarson, Yueheng Wu, Jian Zhuang. FLNC and MYLK2 gene mutations in a Chinese family with different phenotypes of cardiomyopathy. . 2020; ():1.

Chicago/Turabian Style

Xianyu Qin; Ping Li; Huiqi Qu; Yichuan Liu; Yu Xia; Shaoxian Chen; Yongchao Yang; Shufang Huang; Pengju Wen; Xianwu Zhou; Xiaofeng Li; Yonghua Wang; Lifeng Tian; Hakon Hakonarson; Yueheng Wu; Jian Zhuang. 2020. "FLNC and MYLK2 gene mutations in a Chinese family with different phenotypes of cardiomyopathy." , no. : 1.

Other
Published: 08 May 2020
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Summary BoxWhat is already known about this subject?The Wuhan city in China had a much higher mortality rate (Feb 10th statistics: 748 death/18,454 diagnosis =4.05%; Apr 24th statistics: 3,869 death/50,333 diagnosis=7.69%) than the rest of China.What are the new findings?Based on our analysis, the number of infected people in Wuhan is estimated to be 143,000 (88,000 to 242,000) in late January and early February, significantly higher than the published number of diagnosed cases.What are the recommendations for policy and practice?Increased awareness of the original infection rates in Wuhan, China is critically important for proper public health measures at all levels, as well as to eliminate panic caused by overestimated mortality rate that may bias health policy actions by the authorities

ACS Style

Hui-Qi Qu; Zhangkai J. Cheng; Zhifeng Duan; Lifeng Tian; Hakon Hakonarson. The Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China. 2020, 1 .

AMA Style

Hui-Qi Qu, Zhangkai J. Cheng, Zhifeng Duan, Lifeng Tian, Hakon Hakonarson. The Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China. . 2020; ():1.

Chicago/Turabian Style

Hui-Qi Qu; Zhangkai J. Cheng; Zhifeng Duan; Lifeng Tian; Hakon Hakonarson. 2020. "The Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China." , no. : 1.

Preprint
Published: 16 April 2020
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Background: There is a current worldwide outbreak of a new type of coronavirus COVID-19. The number of confirmed infected cases is rapidly increasing. Method: This paper analyzes the characteristics of COVID-19 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. Diagnostic data for foreign citizens evacuated from Wuhan were collected and compiled. Current prevention and control strategies have been analyzed. Results: COVID-19 is similar to SARS-CoV and MERS-CoV virologically and etiologically, but similar to influenza in epidemiology and virulence. The prevalence rate in Wuhan was inferred to be close to 1%. The comparison provides a new perspective for the future of the disease, and offers some advice in the prevention and control management strategy. Conclusion: The large number of patients and the strong occult nature are two big problems, making the virus difficult to eradicate. We need to contemplate the possibility of long-term co-existence with COVID-19.

ACS Style

Zhangkai J. Cheng; Zhigang Liu; Ruixi Zeng; Lifeng Tian; Zhifeng Duan; Hakon Hakonarson; Hui-Qi Qu; Qing Zhang; LiTeng Yang; Gang Cheng. COVID-19: Look to the Future, Learn from the Past. 2020, 1 .

AMA Style

Zhangkai J. Cheng, Zhigang Liu, Ruixi Zeng, Lifeng Tian, Zhifeng Duan, Hakon Hakonarson, Hui-Qi Qu, Qing Zhang, LiTeng Yang, Gang Cheng. COVID-19: Look to the Future, Learn from the Past. . 2020; ():1.

Chicago/Turabian Style

Zhangkai J. Cheng; Zhigang Liu; Ruixi Zeng; Lifeng Tian; Zhifeng Duan; Hakon Hakonarson; Hui-Qi Qu; Qing Zhang; LiTeng Yang; Gang Cheng. 2020. "COVID-19: Look to the Future, Learn from the Past." , no. : 1.

Brief report
Published: 01 February 2017 in Human Mutation
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Braddock–Carey Syndrome (BCS) is characterized by microcephaly, congenital thrombocytopenia, Pierre–Robin sequence (PRS), and agenesis of the corpus callosum. BCS has been shown to be caused by a 21q22.11 microdeletion that encompasses multiple genes. Here, we report a BCS genocopy characterized by congenital thrombocytopenia and PRS that is caused by a loss‐of‐function mutation in KIF15 in a consanguineous Saudi Arabian family. Mutations of mitotic kinesins are a well‐established cause of microcephaly. To our knowledge, KIF15 is the first kinesin to be associated with congenital thrombocytopenia.

ACS Style

Patrick M.A. Sleiman; Michael March; Kenny Nguyen; Lifeng Tian; Renata Pellegrino; Cuiping Hou; Walid Dridi; Mohamed Sager; Yousef H. Housawi; Hakon Hakonarson. Loss-of-Function Mutations in KIF15 Underlying a Braddock-Carey Genocopy. Human Mutation 2017, 38, 507 -510.

AMA Style

Patrick M.A. Sleiman, Michael March, Kenny Nguyen, Lifeng Tian, Renata Pellegrino, Cuiping Hou, Walid Dridi, Mohamed Sager, Yousef H. Housawi, Hakon Hakonarson. Loss-of-Function Mutations in KIF15 Underlying a Braddock-Carey Genocopy. Human Mutation. 2017; 38 (5):507-510.

Chicago/Turabian Style

Patrick M.A. Sleiman; Michael March; Kenny Nguyen; Lifeng Tian; Renata Pellegrino; Cuiping Hou; Walid Dridi; Mohamed Sager; Yousef H. Housawi; Hakon Hakonarson. 2017. "Loss-of-Function Mutations in KIF15 Underlying a Braddock-Carey Genocopy." Human Mutation 38, no. 5: 507-510.

Journal article
Published: 11 April 2016 in Nature Biotechnology
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Genetic studies of human disease have traditionally focused on the detection of disease-causing mutations in afflicted individuals. Here we describe a complementary approach that seeks to identify healthy individuals resilient to highly penetrant forms of genetic childhood disorders. A comprehensive screen of 874 genes in 589,306 genomes led to the identification of 13 adults harboring mutations for 8 severe Mendelian conditions, with no reported clinical manifestation of the indicated disease. Our findings demonstrate the promise of broadening genetic studies to systematically search for well individuals who are buffering the effects of rare, highly penetrant, deleterious mutations. They also indicate that incomplete penetrance for Mendelian diseases is likely more common than previously believed. The identification of resilient individuals may provide a first step toward uncovering protective genetic variants that could help elucidate the mechanisms of Mendelian diseases and new therapeutic strategies.

ACS Style

Rong Chen; Lisong Shi; Jörg Hakenberg; Brian Naughton; Pamela Sklar; Jianguo Zhang; Hanlin Zhou; Lifeng Tian; Om Prakash; Mathieu Lemire; Patrick Sleiman; Wei-Yi Cheng; Wanting Chen; Hardik Shah; Yulan Shen; Menachem Fromer; Larsson Omberg; Matthew A Deardorff; Elaine Zackai; Jason Bobe; Elissa Levin; Thomas J Hudson; Leif Groop; Jun Wang; Hakon Hakonarson; Anne Wojcicki; George A Diaz; Lisa Edelmann; Eric E Schadt; Stephen H Friend. Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases. Nature Biotechnology 2016, 34, 531 -538.

AMA Style

Rong Chen, Lisong Shi, Jörg Hakenberg, Brian Naughton, Pamela Sklar, Jianguo Zhang, Hanlin Zhou, Lifeng Tian, Om Prakash, Mathieu Lemire, Patrick Sleiman, Wei-Yi Cheng, Wanting Chen, Hardik Shah, Yulan Shen, Menachem Fromer, Larsson Omberg, Matthew A Deardorff, Elaine Zackai, Jason Bobe, Elissa Levin, Thomas J Hudson, Leif Groop, Jun Wang, Hakon Hakonarson, Anne Wojcicki, George A Diaz, Lisa Edelmann, Eric E Schadt, Stephen H Friend. Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases. Nature Biotechnology. 2016; 34 (5):531-538.

Chicago/Turabian Style

Rong Chen; Lisong Shi; Jörg Hakenberg; Brian Naughton; Pamela Sklar; Jianguo Zhang; Hanlin Zhou; Lifeng Tian; Om Prakash; Mathieu Lemire; Patrick Sleiman; Wei-Yi Cheng; Wanting Chen; Hardik Shah; Yulan Shen; Menachem Fromer; Larsson Omberg; Matthew A Deardorff; Elaine Zackai; Jason Bobe; Elissa Levin; Thomas J Hudson; Leif Groop; Jun Wang; Hakon Hakonarson; Anne Wojcicki; George A Diaz; Lisa Edelmann; Eric E Schadt; Stephen H Friend. 2016. "Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases." Nature Biotechnology 34, no. 5: 531-538.

Case reports
Published: 19 March 2015 in BMC Medical Genetics
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Hereditary ataxias are a heterogeneous group of neurodegenerative disorders, where exome sequencing may become an important diagnostic tool to solve clinically or genetically complex cases. We describe an Italian family in which three sisters were affected by ataxia with postural/intentional myoclonus and involuntary movements at onset, which persisted during the disease. Oculomotor apraxia was absent. Clinical and genetic data did not allow us to exclude autosomal dominant or recessive inheritance and suggest a disease gene. Exome sequencing identified a homozygous c.6292C > T (p.Arg2098*) mutation in SETX and a heterozygous c.346G > A (p.Gly116Arg) mutation in AFG3L2 shared by all three affected individuals. A fourth sister (II.7) had subclinical myoclonic jerks at proximal upper limbs and perioral district, confirmed by electrophysiology, and carried the p.Gly116Arg change. Three siblings were healthy. Pathogenicity prediction and a yeast-functional assay suggested p.Gly116Arg impaired m-AAA (ATPases associated with various cellular activities) complex function. Exome sequencing is a powerful tool in identifying disease genes. We identified an atypical form of Ataxia with Oculoapraxia type 2 (AOA2) with myoclonus at onset associated with the c.6292C > T (p.Arg2098*) homozygous mutation. Because the same genotype was described in six cases from a Tunisian family with a typical AOA2 without myoclonus, we speculate this latter feature is associated with a second mutated gene, namely AFG3L2 (p.Gly116Arg variant). We suggest that variant phenotypes may be due to the combined effect of different mutated genes associated to ataxia or related disorders, that will become more apparent as the costs of exome sequencing progressively will reduce, amplifying its diagnostics use, and meanwhile proposing significant challenges in the interpretation of the data.

ACS Style

Cecilia Mancini; Laura Orsi; Yiran Guo; Jiankang Li; Yulan Chen; Fengxiang Wang; Lifeng Tian; Xuanzhu Liu; Jianguo Zhang; Hui Jiang; Bruce Shike Nmezi; Takashi Tatsuta; Elisa Giorgio; Eleonora Di Gregorio; Simona Cavalieri; Elisa Pozzi; Paolo Mortara; Maria Marcella Caglio; Alessandro Balducci; Lorenzo Pinessi; Thomas Langer; Quasar S Padiath; Hakon Hakonarson; Xiuqing Zhang; Alfredo Brusco. An atypical form of AOA2 with myoclonus associated with mutations in SETX and AFG3L2. BMC Medical Genetics 2015, 16, 16 .

AMA Style

Cecilia Mancini, Laura Orsi, Yiran Guo, Jiankang Li, Yulan Chen, Fengxiang Wang, Lifeng Tian, Xuanzhu Liu, Jianguo Zhang, Hui Jiang, Bruce Shike Nmezi, Takashi Tatsuta, Elisa Giorgio, Eleonora Di Gregorio, Simona Cavalieri, Elisa Pozzi, Paolo Mortara, Maria Marcella Caglio, Alessandro Balducci, Lorenzo Pinessi, Thomas Langer, Quasar S Padiath, Hakon Hakonarson, Xiuqing Zhang, Alfredo Brusco. An atypical form of AOA2 with myoclonus associated with mutations in SETX and AFG3L2. BMC Medical Genetics. 2015; 16 (1):16.

Chicago/Turabian Style

Cecilia Mancini; Laura Orsi; Yiran Guo; Jiankang Li; Yulan Chen; Fengxiang Wang; Lifeng Tian; Xuanzhu Liu; Jianguo Zhang; Hui Jiang; Bruce Shike Nmezi; Takashi Tatsuta; Elisa Giorgio; Eleonora Di Gregorio; Simona Cavalieri; Elisa Pozzi; Paolo Mortara; Maria Marcella Caglio; Alessandro Balducci; Lorenzo Pinessi; Thomas Langer; Quasar S Padiath; Hakon Hakonarson; Xiuqing Zhang; Alfredo Brusco. 2015. "An atypical form of AOA2 with myoclonus associated with mutations in SETX and AFG3L2." BMC Medical Genetics 16, no. 1: 16.

Review article
Published: 31 January 2015 in Genomics
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The retina and its adjacent supporting tissues – retinal pigmented epithelium (RPE) and choroid – are critical structures in human eyes required for normal visual perception. Abnormal changes in these layers have been implicated in diseases such as age-related macular degeneration and glaucoma. With the advent of high-throughput methods, such as serial analysis of gene expression, cDNA microarray, and RNA sequencing, there is unprecedented opportunity to facilitate our understanding of the normal retina, RPE, and choroid. This information can be used to identify dysfunction in age-related macular degeneration and glaucoma. In this review, we describe the current status in our understanding of these transcriptomes through the use of high-throughput techniques.

ACS Style

Lifeng Tian; Krista L. Kazmierkiewicz; Anita S. Bowman; Mingyao Li; Christine A. Curcio; Dwight E. Stambolian. Transcriptome of the human retina, retinal pigmented epithelium and choroid. Genomics 2015, 105, 253 -264.

AMA Style

Lifeng Tian, Krista L. Kazmierkiewicz, Anita S. Bowman, Mingyao Li, Christine A. Curcio, Dwight E. Stambolian. Transcriptome of the human retina, retinal pigmented epithelium and choroid. Genomics. 2015; 105 (5-6):253-264.

Chicago/Turabian Style

Lifeng Tian; Krista L. Kazmierkiewicz; Anita S. Bowman; Mingyao Li; Christine A. Curcio; Dwight E. Stambolian. 2015. "Transcriptome of the human retina, retinal pigmented epithelium and choroid." Genomics 105, no. 5-6: 253-264.

Journal article
Published: 10 December 2014 in Orphanet Journal of Rare Diseases
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Phosphoribosyl pyrophosphate synthetase (PRS) I deficiency is a rare medical condition caused by missense mutations in PRPS1 that lead to three different phenotypes: Arts Syndrome (MIM 301835), X-linked Charcot-Marie-Tooth (CMTX5, MIM 311070) or X-linked non-syndromic sensorineural deafness (DFN2, MIM 304500). All three are X-linked recessively inherited and males affected display variable degree of central and peripheral neuropathy. We applied whole exome sequencing to a three-generation family with optic atrophy followed by retinitis pigmentosa (RP) in all three cases, and ataxia, progressive peripheral neuropathy and hearing loss with variable presentation. Whole exome sequencing was performed in two affecteds and one unaffected member of the family. Sanger sequencing was used to validate and segregate the 12 candidate mutations in the family and to confirm the absence of the novel variant in PRPS1 in 191 controls. The pathogenic role of the novel mutation in PRPS1 was assessed in silico and confirmed by enzymatic determination of PRS activity, mRNA expression and sequencing, and X-chromosome inactivation. A novel missense mutation was identified in PRPS1 in the affected females. Age of onset, presentation and severity of the phenotype are highly variable in the family: both the proband and her mother have neurological and ophthalmological symptoms, whereas the phenotype of the affected sister is milder and currently confined to the eye. Moreover, only the proband displayed a complete lack of expression of the wild type allele in leukocytes that seems to correlate with the degree of PRS deficiency and the severity of the phenotype. Interestingly, optic atrophy and RP are the only common manifestations to all three females and the only phenotype correlating with the degree of enzyme deficiency. These results are in line with recent evidence of the existence of intermediate phenotypes in PRS-I deficiency syndromes and demonstrate that females can exhibit a disease phenotype as severe and complex as their male counterparts.

ACS Style

Berta Almoguera; Sijie He; Marta Corton; Patricia Fernandez-San Jose; Fiona Blanco-Kelly; Maria Isabel López-Molina; Blanca García-Sandoval; Javier Del Val; Yiran Guo; Lifeng Tian; Xuanzhu Liu; Liping Guan; Rosa J Torres; Juan G Puig; Hakon Hakonarson; Xun Xu; Brendan J Keating; Carmen Ayuso. Expanding the phenotype of PRPS1 syndromes in females: neuropathy, hearing loss and retinopathy. Orphanet Journal of Rare Diseases 2014, 9, 1 -9.

AMA Style

Berta Almoguera, Sijie He, Marta Corton, Patricia Fernandez-San Jose, Fiona Blanco-Kelly, Maria Isabel López-Molina, Blanca García-Sandoval, Javier Del Val, Yiran Guo, Lifeng Tian, Xuanzhu Liu, Liping Guan, Rosa J Torres, Juan G Puig, Hakon Hakonarson, Xun Xu, Brendan J Keating, Carmen Ayuso. Expanding the phenotype of PRPS1 syndromes in females: neuropathy, hearing loss and retinopathy. Orphanet Journal of Rare Diseases. 2014; 9 (1):1-9.

Chicago/Turabian Style

Berta Almoguera; Sijie He; Marta Corton; Patricia Fernandez-San Jose; Fiona Blanco-Kelly; Maria Isabel López-Molina; Blanca García-Sandoval; Javier Del Val; Yiran Guo; Lifeng Tian; Xuanzhu Liu; Liping Guan; Rosa J Torres; Juan G Puig; Hakon Hakonarson; Xun Xu; Brendan J Keating; Carmen Ayuso. 2014. "Expanding the phenotype of PRPS1 syndromes in females: neuropathy, hearing loss and retinopathy." Orphanet Journal of Rare Diseases 9, no. 1: 1-9.

Journal article
Published: 30 October 2014 in Blood
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Telomerase is a ribonucleoprotein enzyme that is necessary for overcoming telomere shortening in human germ and stem cells. Mutations in telomerase or other telomere-maintenance proteins can lead to diseases characterized by depletion of hematopoietic stem cells and bone marrow failure (BMF). Telomerase localization to telomeres requires an interaction with a region on the surface of the telomere-binding protein TPP1 known as the TEL patch. Here, we identify a family with aplastic anemia and other related hematopoietic disorders in which a 1-amino-acid deletion in the TEL patch of TPP1 (ΔK170) segregates with disease. All family members carrying this mutation, but not those with wild-type TPP1, have short telomeres. When introduced into 293T cells, TPP1 with the ΔK170 mutation is able to localize to telomeres but fails to recruit telomerase to telomeres, supporting a causal relationship between this TPP1 mutation and bone marrow disorders. ACD/TPP1 is thus a newly identified telomere-related gene in which mutations cause aplastic anemia and related BMF disorders.

ACS Style

Yiran Guo; Melissa Kartawinata; Jiankang Li; Hilda A. Pickett; Juliana Teo; Tatjana Kilo; Pasquale Barbaro; Brendan Keating; Yulan Chen; Lifeng Tian; Ahmad Alodaib; Roger R. Reddel; John Christodoulou; Xun Xu; Hakon Hakonarson; Tracy M. Bryan. Inherited bone marrow failure associated with germline mutation of ACD, the gene encoding telomere protein TPP1. Blood 2014, 124, 2767 -2774.

AMA Style

Yiran Guo, Melissa Kartawinata, Jiankang Li, Hilda A. Pickett, Juliana Teo, Tatjana Kilo, Pasquale Barbaro, Brendan Keating, Yulan Chen, Lifeng Tian, Ahmad Alodaib, Roger R. Reddel, John Christodoulou, Xun Xu, Hakon Hakonarson, Tracy M. Bryan. Inherited bone marrow failure associated with germline mutation of ACD, the gene encoding telomere protein TPP1. Blood. 2014; 124 (18):2767-2774.

Chicago/Turabian Style

Yiran Guo; Melissa Kartawinata; Jiankang Li; Hilda A. Pickett; Juliana Teo; Tatjana Kilo; Pasquale Barbaro; Brendan Keating; Yulan Chen; Lifeng Tian; Ahmad Alodaib; Roger R. Reddel; John Christodoulou; Xun Xu; Hakon Hakonarson; Tracy M. Bryan. 2014. "Inherited bone marrow failure associated with germline mutation of ACD, the gene encoding telomere protein TPP1." Blood 124, no. 18: 2767-2774.