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Bioinformatics scientist at Center for Applied Genomics (CAG) Children's Hospital of Philadelphia (CHOP). Focused on NGS translational research and genomics machine learning
Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogenesis of ADHD. For effective modeling, deep learning approaches have become a method of choice, with ability to predict the impact of genetic variations involving complicated mechanisms. In this study, we examined copy number variation in whole genome sequencing from 116 African Americans ADHD children and 408 African American controls. We divided the human genome into 150 regions, and the variation intensity in each region was applied as feature vectors for deep learning modeling to classify ADHD patients. The accuracy of deep learning for predicting ADHD diagnosis is consistently around 78% in a two-fold shuffle test, compared with ∼50% by traditional k-mean clustering methods. Additional whole genome sequencing data from 351 European Americans children, including 89 ADHD cases and 262 controls, were applied as independent validation using feature vectors obtained from the African American ethnicity analysis. The accuracy of ADHD labeling was lower in this setting (∼70–75%) but still above the results from traditional methods. The regions with highest weight overlapped with the previously reported ADHD-associated copy number variation regions, including genes such as GRM1 and GRM8, key drivers of metabotropic glutamate receptor signaling. A notable discovery is that structural variations in non-coding genomic (intronic/intergenic) regions show prediction weights that can be as high as prediction weight from variations in coding regions, results that were unexpected.
Yichuan Liu; Hui-Qi Qu; Xiao Chang; Kenny Nguyen; Jingchun Qu; Lifeng Tian; Joseph Glessner; Patrick Ma Sleiman; Hakon Hakonarson. Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation. Experimental Biology and Medicine 2021, 1 .
AMA StyleYichuan Liu, Hui-Qi Qu, Xiao Chang, Kenny Nguyen, Jingchun Qu, Lifeng Tian, Joseph Glessner, Patrick Ma Sleiman, Hakon Hakonarson. Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation. Experimental Biology and Medicine. 2021; ():1.
Chicago/Turabian StyleYichuan Liu; Hui-Qi Qu; Xiao Chang; Kenny Nguyen; Jingchun Qu; Lifeng Tian; Joseph Glessner; Patrick Ma Sleiman; Hakon Hakonarson. 2021. "Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation." Experimental Biology and Medicine , no. : 1.
We previously observed enhanced immunoglobulin A (IgA) responses in severe COVID‐19, which might confer damaging effects. Given the important role of IgA in immune and inflammatory responses, the aim of this study was to investigate the dynamic response of the IgA isotype switch factor TGF‐β1 in COVID‐19 patients. We observed, in a total of 153 COVID‐19 patients, that the serum levels of TGF‐β1 were increased significantly at the early and middle stages of COVID‐19, and correlated with the levels of SARS‐CoV‐2‐specific IgA, as well as with the APACHE‐II score in patients with severe disease. In view of the genetic association of the TGF‐β1 activator THBS3 with severe COVID‐19 identified by the COVID‐19 Host Genetics Initiative, this study suggests TGF‐β1 may play a key role in COVID‐19.
Er‐Yi Wang; Hao Chen; Bao‐Qing Sun; Hui Wang; Hui‐Qi Qu; Yichuan Liu; Xi‐Zhuo Sun; Jingchun Qu; Zhang‐Fu Fang; Lifeng Tian; Yi‐Feng Zeng; Shau‐Ku Huang; Hakon Hakonarson; Zhi‐Gang Liu. Serum levels of the IgA isotype switch factor TGF‐β1 are elevated in patients with COVID‐19. FEBS Letters 2021, 1 .
AMA StyleEr‐Yi Wang, Hao Chen, Bao‐Qing Sun, Hui Wang, Hui‐Qi Qu, Yichuan Liu, Xi‐Zhuo Sun, Jingchun Qu, Zhang‐Fu Fang, Lifeng Tian, Yi‐Feng Zeng, Shau‐Ku Huang, Hakon Hakonarson, Zhi‐Gang Liu. Serum levels of the IgA isotype switch factor TGF‐β1 are elevated in patients with COVID‐19. FEBS Letters. 2021; ():1.
Chicago/Turabian StyleEr‐Yi Wang; Hao Chen; Bao‐Qing Sun; Hui Wang; Hui‐Qi Qu; Yichuan Liu; Xi‐Zhuo Sun; Jingchun Qu; Zhang‐Fu Fang; Lifeng Tian; Yi‐Feng Zeng; Shau‐Ku Huang; Hakon Hakonarson; Zhi‐Gang Liu. 2021. "Serum levels of the IgA isotype switch factor TGF‐β1 are elevated in patients with COVID‐19." FEBS Letters , no. : 1.
Xiao Chang; Yun Li; Kenny Nguyen; Huiqi Qu; Yichuan Liu; Joseph Glessner; Patrick M.A. Sleiman; Hakon Hakonarson. Genetic correlations between COVID-19 and a variety of traits and diseases. The Innovation 2021, 2, 100112 .
AMA StyleXiao Chang, Yun Li, Kenny Nguyen, Huiqi Qu, Yichuan Liu, Joseph Glessner, Patrick M.A. Sleiman, Hakon Hakonarson. Genetic correlations between COVID-19 and a variety of traits and diseases. The Innovation. 2021; 2 (2):100112.
Chicago/Turabian StyleXiao Chang; Yun Li; Kenny Nguyen; Huiqi Qu; Yichuan Liu; Joseph Glessner; Patrick M.A. Sleiman; Hakon Hakonarson. 2021. "Genetic correlations between COVID-19 and a variety of traits and diseases." The Innovation 2, no. 2: 100112.
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.
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 StyleYichuan 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 StyleYichuan 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.
Background Not all cells in a given individual are identical in their genomic makeup. Mosaicism describes such a phenomenon where a mixture of genotypic states in certain genomic segments exists within the same individual. Mosaicism is a prevalent and impactful class of non-integer state copy number variation (CNV). Mosaicism implies that certain cell types or subset of cells contain a CNV in a segment of the genome while other cells in the same individual do not. Several studies have investigated the impact of mosaicism in single patients or small cohorts but no comprehensive scan of mosaic CNVs has been undertaken to accurately detect such variants and interpret their impact on human health and disease. Results We developed a tool called Montage to improve the accuracy of detection of mosaic copy number variants in a high throughput fashion. Montage directly interfaces with ParseCNV2 algorithm to establish disease phenotype genome-wide association and determine which genomic ranges had more or less than expected frequency of mosaic events. We screened for mosaic events in over 350,000 samples using 1% allele frequency as the detection limit. Additionally, we uncovered disease associations of multiple phenotypes with mosaic CNVs at several genomic loci. We additionally investigated the allele imbalance observations genome-wide to define non-diploid and non-integer copy number states. Conclusions Our novel algorithm presents an efficient tool with fast computational runtime and high levels of accuracy of mosaic CNV detection. A curated mosaic CNV callset of 3716 events in 2269 samples is presented with comparability to previous reports and disease phenotype associations. The new algorithm can be freely accessed via: https://github.com/CAG-CNV/MONTAGE.
Joseph T. Glessner; Xiao Chang; Yichuan Liu; Jin Li; Munir Khan; Zhi Wei; Patrick M. A. Sleiman; Hakon Hakonarson. MONTAGE: a new tool for high-throughput detection of mosaic copy number variation. BMC Genomics 2021, 22, 1 -10.
AMA StyleJoseph T. Glessner, Xiao Chang, Yichuan Liu, Jin Li, Munir Khan, Zhi Wei, Patrick M. A. Sleiman, Hakon Hakonarson. MONTAGE: a new tool for high-throughput detection of mosaic copy number variation. BMC Genomics. 2021; 22 (1):1-10.
Chicago/Turabian StyleJoseph T. Glessner; Xiao Chang; Yichuan Liu; Jin Li; Munir Khan; Zhi Wei; Patrick M. A. Sleiman; Hakon Hakonarson. 2021. "MONTAGE: a new tool for high-throughput detection of mosaic copy number variation." BMC Genomics 22, no. 1: 1-10.
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.
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 StyleYichuan 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 StyleYichuan 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.
Mutations in the sarcomeric protein filamin C (FLNC) gene have been linked to hypertrophic cardiomyopathy (HCM), as they have been determined to increase the risk of ventricular arrhythmia and sudden death. Thus, 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 was discobered in one family member with different phenotype. We performed whole-exome sequencing in a Chinese family with HCM of unknown cause. To determine and confirm the function of a novel mutation of FLNC, we introduced the mutant and wild-type gene into AC16 cells (human cardiomyocytes): we then used western blotting to analyze the expression of FLNC in subcellular fractions, and confocal microscope to observe the subcellular distribution of the protein. As per our findings, we were able to identify a novel missense single nucleotide variant (FLNC c.G5935A [p.A1979T]) in the family, which segregates with the disease. FLNC expression levels were observed to be equivalent in both wild-type and p.A1979T cardiomyocytes. However, the expression of the mutant protein has resulted in cytoplasmic protein aggregations, in contrast to wild-type FLNC, which was distributed in the cytoplasm and did not form aggregates. Unexpectedly, 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, which was not found in other subjects. We then 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 that there is more than one causal mutation in cardiomyopathy warrants clinical attention, especially for patients with atypical clinical features.
Xianyu Qin; Ping Li; Hui-Qi 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. International Heart Journal 2021, 62, 127 -134.
AMA StyleXianyu Qin, Ping Li, Hui-Qi 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. International Heart Journal. 2021; 62 (1):127-134.
Chicago/Turabian StyleXianyu Qin; Ping Li; Hui-Qi 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. 2021. "FLNC and MYLK2 Gene Mutations in a Chinese Family with Different Phenotypes of Cardiomyopathy." International Heart Journal 62, no. 1: 127-134.
Objective Juvenile idiopathic arthritis (JIA) is the most common type of arthritis among children, but a few studies have investigated the contribution of rare variants to JIA. In this study, we aimed to identify rare coding variants associated with JIA for the genome-wide landscape. Methods We established a rare variant calling and filtering pipeline and performed rare coding variant and gene-based association analyses on three RNA-seq datasets composed of 228 JIA patients in the Gene Expression Omnibus against different sets of controls, and further conducted replication in our whole-exome sequencing (WES) data of 56 JIA patients. Then we conducted differential gene expression analysis and assessed the impact of recurrent functional coding variants on gene expression and signalling pathway. Results By the RNA-seq data, we identified variants in two genes reported in literature as JIA causal variants, as well as additional 63 recurrent rare coding variants seen only in JIA patients. Among the 44 recurrent rare variants found in polyarticular patients, 10 were replicated by our WES of patients with the same JIA subtype. Several genes with recurrent functional rare coding variants have also common variants associated with autoimmune diseases. We observed immune pathways enriched for the genes with rare coding variants and differentially expressed genes. Conclusion This study elucidated a novel landscape of recurrent rare coding variants in JIA patients and uncovered significant associations with JIA at the gene pathway level. The convergence of common variants and rare variants for autoimmune diseases is also highlighted in this study.
Xinyi Meng; Xiaoyuan Hou; Ping Wang; Joseph T Glessner; Hui-Qi Qu; Michael E March; Sipeng Zhang; Xiaohui Qi; Chonggui Zhu; Kenny Nguyen; Xinyi Gao; Xiaoge Li; Yichuan Liu; Wentao Zhou; Shuyue Zhang; Junyi Li; Yan Sun; Jie Yang; Patrick M A Sleiman; Qianghua Xia; Hakon Hakonarson; Jin Li. Association of novel rare coding variants with juvenile idiopathic arthritis. Annals of the Rheumatic Diseases 2021, 80, 626 -631.
AMA StyleXinyi Meng, Xiaoyuan Hou, Ping Wang, Joseph T Glessner, Hui-Qi Qu, Michael E March, Sipeng Zhang, Xiaohui Qi, Chonggui Zhu, Kenny Nguyen, Xinyi Gao, Xiaoge Li, Yichuan Liu, Wentao Zhou, Shuyue Zhang, Junyi Li, Yan Sun, Jie Yang, Patrick M A Sleiman, Qianghua Xia, Hakon Hakonarson, Jin Li. Association of novel rare coding variants with juvenile idiopathic arthritis. Annals of the Rheumatic Diseases. 2021; 80 (5):626-631.
Chicago/Turabian StyleXinyi Meng; Xiaoyuan Hou; Ping Wang; Joseph T Glessner; Hui-Qi Qu; Michael E March; Sipeng Zhang; Xiaohui Qi; Chonggui Zhu; Kenny Nguyen; Xinyi Gao; Xiaoge Li; Yichuan Liu; Wentao Zhou; Shuyue Zhang; Junyi Li; Yan Sun; Jie Yang; Patrick M A Sleiman; Qianghua Xia; Hakon Hakonarson; Jin Li. 2021. "Association of novel rare coding variants with juvenile idiopathic arthritis." Annals of the Rheumatic Diseases 80, no. 5: 626-631.
We analyzed GWAS results released by COVID-19 Host Genetics Initiative, UK biobank and GWAS Catalog to explore the genetic overlap between COVID-19 and a broad spectrum of traits and diseases. We validate previously reported medical conditions and risk factors based on epidemiological studies, including but not limited to hypertension, type 2 diabetes and obesity. We also report novel traits associated with COVID-19, which have not been previously reported from epidemiological data, such as opioid use and educational attainment. Taken together, this study extends our understanding of the genetic basis of COVID-19, and provides target traits for further epidemiological studies.
Xiao Chang; Yun Li; Kenny Nguyen; Huiqi Qu; Yichuan Liu; Joseph Glessner; Patrick Sleiman; Hakon Hakonarson. Genetic correlations between COVID-19 and a variety of diseases and other medically relevant traits. 2020, 1 .
AMA StyleXiao Chang, Yun Li, Kenny Nguyen, Huiqi Qu, Yichuan Liu, Joseph Glessner, Patrick Sleiman, Hakon Hakonarson. Genetic correlations between COVID-19 and a variety of diseases and other medically relevant traits. . 2020; ():1.
Chicago/Turabian StyleXiao Chang; Yun Li; Kenny Nguyen; Huiqi Qu; Yichuan Liu; Joseph Glessner; Patrick Sleiman; Hakon Hakonarson. 2020. "Genetic correlations between COVID-19 and a variety of diseases and other medically relevant traits." , no. : 1.
Although mitochondrial dysfunction has been implicated in the pathophysiology of attention deficit and hyperactivity disorder ADHD, the role of mitochondrial DNA (mtDNA) has not been extensively investigated. To determine whether mtDNA haplogroups influence risk of ADHD, we performed a case-control study comprising 2076 ADHD cases and 5078 healthy controls, all of whom were European decedents recruited from The Children’s Hospital of Philadelphia (CHOP). Associations between eight major European mtDNA Haplogroups and ADHD risk were assessed in three independent European cohorts. Meta-analysis of the three studies indicated that mtDNA haplogroups K (odds ratio = 0.69, P = 2.24 × 10−4, Pcorrected = 1.79 × 10−3) and U (odds ratio = 0.77, P = 8.88 × 10−4, Pcorrected = 7.11 × 10−3) were significantly associated with reduced risk of ADHD. In contrast, haplogroup HHV* (odds ratio = 1.18, P = 2.32 × 10−3, Pcorrected = 0.019) was significantly associated with increased risk of ADHD. Our results provide novel insight into the genetic basis of ADHD, implicating mitochondrial mechanisms in the pathophysiology of this relatively common psychiatric disorder.
Xiao Chang; Yichuan Liu; Frank Mentch; Joseph Glessner; Huiqi Qu; Kenny Nguyen; Patrick M. A. Sleiman; Hakon Hakonarson. Mitochondrial DNA haplogroups and risk of attention deficit and hyperactivity disorder in European Americans. Translational Psychiatry 2020, 10, 1 -6.
AMA StyleXiao Chang, Yichuan Liu, Frank Mentch, Joseph Glessner, Huiqi Qu, Kenny Nguyen, Patrick M. A. Sleiman, Hakon Hakonarson. Mitochondrial DNA haplogroups and risk of attention deficit and hyperactivity disorder in European Americans. Translational Psychiatry. 2020; 10 (1):1-6.
Chicago/Turabian StyleXiao Chang; Yichuan Liu; Frank Mentch; Joseph Glessner; Huiqi Qu; Kenny Nguyen; Patrick M. A. Sleiman; Hakon Hakonarson. 2020. "Mitochondrial DNA haplogroups and risk of attention deficit and hyperactivity disorder in European Americans." Translational Psychiatry 10, no. 1: 1-6.
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.
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 StyleYichuan 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 StyleYichuan 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.
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.
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 StyleYichuan 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 StyleYichuan 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.
Previous studies of attention-deficit hyperactivity disorder (ADHD) have suggested that structural variants (SVs) play an important role but these were mainly studied in subjects of European ancestry and focused on coding regions. In this study, we sought to address the role of SVs in non-European populations and outside of coding regions. To that end, we generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The ADHD cases included 116 African Americans (AA) and 89 of European Ancestry (EA) with SVs in comparison with 408 AA and 262 controls, respectively. Multiple SVs and target genes that associated with ADHD from previous studies were identified or replicated, and novel recurrent ADHD-associated SV loci were discovered. We identified clustering of non-coding SVs around neuroactive ligand-receptor interaction pathways, which are involved in neuronal brain function, and highly relevant to ADHD pathogenesis and regulation of gene expression related to specific ADHD phenotypes. There was little overlap (around 6%) in the genes impacted by SVs between AA and EA. These results suggest that SVs within non-coding regions may play an important role in ADHD development and that WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD
Yichuan Liu; Xiao Chang; Huiqi Qu; Joseph Glessner; Lifeng Tian; Dong Li; Haijun Qiu; Patrick M. A. Sleiman; Hakon Hakonarson. Non-coding structural variation differentially impacts attention-deficit hyperactivity disorder (ADHD) gene networks in African American vs Caucasian children. Scientific Reports 2020, 10, 1 -8.
AMA StyleYichuan Liu, Xiao Chang, Huiqi Qu, Joseph Glessner, Lifeng Tian, Dong Li, Haijun Qiu, Patrick M. A. Sleiman, Hakon Hakonarson. Non-coding structural variation differentially impacts attention-deficit hyperactivity disorder (ADHD) gene networks in African American vs Caucasian children. Scientific Reports. 2020; 10 (1):1-8.
Chicago/Turabian StyleYichuan Liu; Xiao Chang; Huiqi Qu; Joseph Glessner; Lifeng Tian; Dong Li; Haijun Qiu; Patrick M. A. Sleiman; Hakon Hakonarson. 2020. "Non-coding structural variation differentially impacts attention-deficit hyperactivity disorder (ADHD) gene networks in African American vs Caucasian children." Scientific Reports 10, no. 1: 1-8.
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.
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 StyleYichuan 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 StyleYichuan 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.
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.
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 StyleYichuan 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 StyleYichuan 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.
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.
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 StyleXianyu 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 StyleXianyu 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.
Background Rubinstein–Taybi syndrome (RTS) is a rare, congenital, plurimalformative, and neurodevelopmental disorder. Previous studies have reported that large deletions contribute to more severe RTS phenotypes than those caused by CREBBP point mutations, suggesting a concurrent pathogenetic role of flanking genes, typical of contiguous gene syndromes, but the detailed genetics are unclear. Results This study presented a rare case of Rubinstein-Taybi (RT) syndrome with serious cardiac abnormalities. Based on the clinical and genetic analysis of the patient, the ADCY9 gene deletion was highlighted as a plausible explanation of cardiac abnormalities. In adcy9 morphant zebrafish, cardiac malformation was observed. Immunofluorescence study disclosed increased macrophage migration and cardiac apoptosis. RNA sequencing in zebrafish model highlighted the changes of a number of genes, including increased expression of the mmp9 gene which encodes a matrix metalloproteinase with the main function to degrade and remodel extracellular matrix. Conclusions In this study, we identified a plausible new candidate gene ADCY9 of CHD through the clinical and genetic analysis of a rare case of Rubinstein-Taybi (RT) syndrome with serious cardiac abnormalities. By functional study of zebrafish, we demonstrated that deletion of adcy9 is the causation for the cardiac abnormalities. Cardiac apoptosis and increased expression of the MMP9 gene are involved in the pathogenesis.
Yueheng Wu; Yu Xia; Ping Li; Hui-Qi Qu; Yichuan Liu; Yongchao Yang; Jijin Lin; Meng Zheng; Lifeng Tian; Zhuanbin Wu; Shufang Huang; Xianyu Qin; Xianwu Zhou; Shaoxian Chen; Yanying Liu; Yonghua Wang; Xiaofeng Li; Hanshi Zeng; Hakon Hakonarson; Jian Zhuang. Role of the ADCY9 gene in cardiac abnormalities of the Rubinstein-Taybi syndrome. Orphanet Journal of Rare Diseases 2020, 15, 101 -10.
AMA StyleYueheng Wu, Yu Xia, Ping Li, Hui-Qi Qu, Yichuan Liu, Yongchao Yang, Jijin Lin, Meng Zheng, Lifeng Tian, Zhuanbin Wu, Shufang Huang, Xianyu Qin, Xianwu Zhou, Shaoxian Chen, Yanying Liu, Yonghua Wang, Xiaofeng Li, Hanshi Zeng, Hakon Hakonarson, Jian Zhuang. Role of the ADCY9 gene in cardiac abnormalities of the Rubinstein-Taybi syndrome. Orphanet Journal of Rare Diseases. 2020; 15 (1):101-10.
Chicago/Turabian StyleYueheng Wu; Yu Xia; Ping Li; Hui-Qi Qu; Yichuan Liu; Yongchao Yang; Jijin Lin; Meng Zheng; Lifeng Tian; Zhuanbin Wu; Shufang Huang; Xianyu Qin; Xianwu Zhou; Shaoxian Chen; Yanying Liu; Yonghua Wang; Xiaofeng Li; Hanshi Zeng; Hakon Hakonarson; Jian Zhuang. 2020. "Role of the ADCY9 gene in cardiac abnormalities of the Rubinstein-Taybi syndrome." Orphanet Journal of Rare Diseases 15, no. 1: 101-10.
Background and Aims Among the >240 genetic loci described to date which confer susceptibility to inflammatory bowel disease, a small subset have been fine-mapped to an individual, non-coding single nucleotide polymorphism [SNP]. To illustrate a model mechanism by which a presumed-causal non-coding SNP can function, we analysed rs1887428, located in the promoter region of the Janus kinase 2 [JAK2] gene. Methods We utilized comparative affinity purification-mass spectrometry, DNA–protein binding assays, CRISPR/Cas9 genome editing, transcriptome sequencing and methylome quantitative trait locus methods to characterize the role of this SNP. Results We determined that the risk allele of rs1887428 is bound by the transcription factor [TF] RBPJ, while the protective allele is bound by the homeobox TF CUX1. While rs188748 only has a very modest influence on JAK2 expression, this effect was amplified downstream through the expression of pathway member STAT5B and epigenetic modification of the JAK2 locus. Conclusion Despite the absence of a consensus TF-binding motif or expression quantitative trait locus, we have used improved methods to characterize a putatively causal SNP to yield insight into inflammatory bowel disease mechanisms. Podcast This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast
Christopher Cardinale; Michael E March; Xiang Lin; Yichuan Liu; Lynn A Spruce; Jonathan P Bradfield; Zhi Wei; Steven H Seeholzer; Struan F A Grant; Hakon Hakonarson. Regulation of Janus Kinase 2 by an Inflammatory Bowel Disease Causal Non-coding Single Nucleotide Polymorphism. Journal of Crohn's and Colitis 2020, 14, 646 -653.
AMA StyleChristopher Cardinale, Michael E March, Xiang Lin, Yichuan Liu, Lynn A Spruce, Jonathan P Bradfield, Zhi Wei, Steven H Seeholzer, Struan F A Grant, Hakon Hakonarson. Regulation of Janus Kinase 2 by an Inflammatory Bowel Disease Causal Non-coding Single Nucleotide Polymorphism. Journal of Crohn's and Colitis. 2020; 14 (5):646-653.
Chicago/Turabian StyleChristopher Cardinale; Michael E March; Xiang Lin; Yichuan Liu; Lynn A Spruce; Jonathan P Bradfield; Zhi Wei; Steven H Seeholzer; Struan F A Grant; Hakon Hakonarson. 2020. "Regulation of Janus Kinase 2 by an Inflammatory Bowel Disease Causal Non-coding Single Nucleotide Polymorphism." Journal of Crohn's and Colitis 14, no. 5: 646-653.
Aortic valve sclerosis is a highly prevalent, poorly characterized asymptomatic manifestation of calcific aortic valve disease and may represent a therapeutic target for disease mitigation. Human aortic valve cusps and blood were obtained from 333 patients undergoing cardiac surgery ( n = 236 for severe aortic stenosis, n = 35 for asymptomatic aortic valve sclerosis, n = 62 for no valvular disease), and a multiplex assay was used to evaluate protein expression across the spectrum of calcific aortic valve disease. A subset of six valvular tissue samples ( n = 3 for asymptomatic aortic valve sclerosis, n = 3 for severe aortic stenosis) was used to create RNA sequencing profiles, which were subsequently organized into clinically relevant gene modules. RNA sequencing identified 182 protein-encoding, differentially expressed genes in aortic valve sclerosis vs. aortic stenosis; 85% and 89% of expressed genes overlapped in aortic stenosis and aortic valve sclerosis, respectively, which decreased to 55% and 84% when we targeted highly expressed genes. Bioinformatic analyses identified six differentially expressed genes encoding key extracellular matrix regulators: TBHS2, SPARC, COL1A2, COL1A1, SPP1, and CTGF. Differential expression of key circulating biomarkers of extracellular matrix reorganization was observed in control vs. aortic valve sclerosis (osteopontin), control vs. aortic stenosis (osteoprotegerin), and aortic valve sclerosis vs. aortic stenosis groups (MMP-2), which corresponded to valvular mRNA expression. We demonstrate distinct mRNA and protein expression underlying aortic valve sclerosis and aortic stenosis. We anticipate that extracellular matrix regulators can serve as circulating biomarkers of early calcific aortic valve disease and as novel targets for early disease mitigation, pending prospective clinical investigations.
Alexander P. Kossar; Wanda Anselmo; Juan B. Grau; Yichuan Liu; Aeron Small; Samuel Carter; Lisa Salvador; Lei Zhao; Mary Ellen Cvijic; Zhuyin Li; Melissa Yarde; Nancy Rioux; Daniel J. Rader; Robert J. Levy; Giovanni Ferrari. Circulating and tissue matricellular RNA and protein expression in calcific aortic valve disease. Physiological Genomics 2020, 52, 191 -199.
AMA StyleAlexander P. Kossar, Wanda Anselmo, Juan B. Grau, Yichuan Liu, Aeron Small, Samuel Carter, Lisa Salvador, Lei Zhao, Mary Ellen Cvijic, Zhuyin Li, Melissa Yarde, Nancy Rioux, Daniel J. Rader, Robert J. Levy, Giovanni Ferrari. Circulating and tissue matricellular RNA and protein expression in calcific aortic valve disease. Physiological Genomics. 2020; 52 (4):191-199.
Chicago/Turabian StyleAlexander P. Kossar; Wanda Anselmo; Juan B. Grau; Yichuan Liu; Aeron Small; Samuel Carter; Lisa Salvador; Lei Zhao; Mary Ellen Cvijic; Zhuyin Li; Melissa Yarde; Nancy Rioux; Daniel J. Rader; Robert J. Levy; Giovanni Ferrari. 2020. "Circulating and tissue matricellular RNA and protein expression in calcific aortic valve disease." Physiological Genomics 52, no. 4: 191-199.
Background Neuroblastoma is a childhood malignancy that arises from the developing sympathetic nervous system. Although mitochondrial dysfunctions have been implicated in the pathophysiology of neuroblastoma, the role of mitochondrial DNA (mtDNA) has not been extensively investigated. Methods A total of 2404 Caucasian children diagnosed with neuroblastoma and 9310 ancestry-matched controls were recruited at the Children’s Hospital of Philadelphia. The mtDNA haplogroups were identified from SNP array data of two independent cohorts. We conducted a case-control study to explore potential associations of mtDNA haplogroups with the susceptibility of neuroblastoma. The genetic effect of neuroblastoma was measured by odds ratios (ORs) of mitochondrial haplogroups. All tests were two-sided. Results Haplogroup K was statistically significantly associated with reduced risk of neuroblastoma in the discovery cohort consisting of 1474 cases and 5699 controls (OR = 0.72, 95% confidence interval [CI] = 0.57 to 0.90; P = 4.8 × 10-3). The association was replicated in an independent cohort (OR = 0.69, 95% CI = 0.53 to 0.92; P = .01) of 930 cases and 3611 controls. Pooled analysis was performed by combining the two data sets. The association remained highly statistically significant after correction for multiple testing (OR = 0.71, 95% CI = 0.59 to 0.84, P = 1.96 × 10-4, Pcorrected = .002). Further analysis focusing on neuroblastoma subtypes indicated haplogroup K was more associated with high-risk neuroblastoma (OR = 0.57, 95% CI = 0.43 to 0.76; P = 1.46 × 10–4) than low-risk and intermediate-risk neuroblastoma. Conclusions Haplogroup K is an independent genetic factor associated with reduced risk of developing neuroblastoma in European descents. These findings provide new insights into the genetic basis of neuroblastoma, implicating mitochondrial DNA encoded proteins in the etiology of neuroblastoma.
Xiao Chang; Marina Bakay; Yichuan Liu; Joseph Glessner; Komal Rathi; Cuiping Hou; Huiqi Qu; Zalman Vaksman; Kenny Nguyen; Patrick M A Sleiman; Sharon J Diskin; John M Maris; Hakon Hakonarson. Mitochondrial DNA Haplogroups and Susceptibility to Neuroblastoma. Journal of the National Cancer Institute 2020, 112, 1259 -1266.
AMA StyleXiao Chang, Marina Bakay, Yichuan Liu, Joseph Glessner, Komal Rathi, Cuiping Hou, Huiqi Qu, Zalman Vaksman, Kenny Nguyen, Patrick M A Sleiman, Sharon J Diskin, John M Maris, Hakon Hakonarson. Mitochondrial DNA Haplogroups and Susceptibility to Neuroblastoma. Journal of the National Cancer Institute. 2020; 112 (12):1259-1266.
Chicago/Turabian StyleXiao Chang; Marina Bakay; Yichuan Liu; Joseph Glessner; Komal Rathi; Cuiping Hou; Huiqi Qu; Zalman Vaksman; Kenny Nguyen; Patrick M A Sleiman; Sharon J Diskin; John M Maris; Hakon Hakonarson. 2020. "Mitochondrial DNA Haplogroups and Susceptibility to Neuroblastoma." Journal of the National Cancer Institute 112, no. 12: 1259-1266.