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Functional variation of the transthyretin gene among human populations and its correlation with amyloidosis phenotypes

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AMYLOID-JOURNAL OF PROTEIN FOLDING DISORDERS 2013年第4期20卷 256-262页

作者： Polimanti, Renato Di Girolamo, Marco Manfellotto, Dario Fuciarelli, Maria Univ Roma Tor Vergata Dept Biol I-00133 Rome Italy Fatebenefratelli Hosp Clin Pathophysiol Ctr AFaR San Giovanni Calibita Rome Italy

Introduction: Heterogeneity in the genotype-phenotype correlation of transthyretin (TTR)-related amyloidosis has been reported, suggesting that other factors may interact with disease-causing mutations. Additional genetic variants in the TTR gene and its surrounding regions may influence disease phenotype. To explore this hypothesis, we analyzed the TTR variation among human populations to identify functional inter-ethnic differences that could influence the TTR-related amyloidosis. Methods: Using the 1000 Genomes Project database, we analyzed a 20 kb region in 1092 apparently healthy individuals who belonged to 14 human populations. In silico analyses were performed to determine the functional impact of genetic variants. Results: These analyses showed that significant ethnic differences are present in the TTR gene, and some differences may affect TTR gene function. Specifically, the non-coding variants potentially associated with regulatory function showed a significant diversity between African and non-African individuals. Discussion and conclusions: Our results highlighted that cis-regulatory variants may contribute to the cardiac TTR-related amyloidosis observed in patients carrier of Val122Ile mutation, the most common in population with African origin. Indeed, non-coding variants differentiated in Africans are, in some cases, located in binding sites of transcription factors involved in cardiac development and function (i.e. E2F3_2, REST, and TEAD).

关键词： African ancestry ethnicity functional prediction analysis non-coding variants transthyretin-related amyloidosis

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Genome analysis and knowledge-driven variant interpretation with TGex

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BMC MEDICAL GENOMICS 2019年第1期12卷 1-17页

作者： Dahary, Dvir Golan, Yaron Mazor, Yaron Zelig, Ofer Barshir, Ruth Twik, Michal Stein, Tsippi Iny Rosner, Guy Kariv, Revital Chen, Fei Zhang, Qiang Shen, Yiping Safran, Marilyn Lancet, Doron Fishilevich, Simon LifeMap Sci Inc Clin Genet Marshfield MA 02050 USA Weizmann Inst Sci Dept Mol Genet Rehovot Israel Tel Aviv Sourasky Med Ctr Dept Gastroenterol Tel Aviv Israel Tel Aviv Univ Fac Med Tel Aviv Israel Childrens Hosp Guangxi Zhuang Autonomous Reg Genet & Metab Cent Lab Birth Defect Prevent Res Inst Maternal & Child Hlth Hosp Nanning 530002 Peoples R China Shanghai Jiao Tong Univ Dept Med Genet & Mol Diagnost Lab Shanghai Childrens Med Ctr Sch Med Shanghai 200127 Peoples R China Harvard Med Sch Dept Neurol Div Genet & Genom Boston Childrens Hosp Boston MA 02115 USA

Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient's phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex's main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex's broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards' recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. Examining use-cases from a variety of TGex users world-wide, we demonstrate its high diagnostic yields (42% for single exome and 50% for trios in 1500 rare genetic disease cases) and critical actionable genetic findings. The platform's support for integration with EHR and LIMS through dedicated APIs facilitates automated retrieval of patient data for TGex's customizable reporting engine, establishing a rapid

关键词： Next generation sequencing analysis Clinical variant interpretation and classification Exome sequencing Whole genome sequencing non-coding variants Biomedical knowledgebase Rare genetic diseases Hamartomatous polyposis

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Novel disease syndromes unveiled by integrative multiscale network analysis of diseases sharing molecular effectors and comorbidities

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BMC MEDICAL GENOMICS 2018年第6期11卷 1-15页

作者： Li, Haiquan Fan, Jungwei Vitali, Francesca Berghout, Joanne Aberasturi, Dillon Li, Jianrong Wilson, Liam Chiu, Wesley Pumarejo, Minsu Han, Jiali Kenost, Colleen Koripella, Pradeep C. Pouladi, Nima Billheimer, Dean Bedrick, Edward J. Lussier, Yves A. Univ Arizona Ctr Biomed Informat & Biostat Tucson AZ 85721 USA Univ Arizona Coll Med Tucson Dept Med Tucson AZ 85721 USA Univ Arizona Grad Interdisciplinary Program Stat Tucson AZ 85721 USA Univ Arizona Ctr Appl Genet & Genom Med Tucson AZ 85721 USA Univ Arizona Ctr Innovat Brain Sci Tucson AZ 85721 USA Univ Arizona UA Canc Ctr Tucson AZ 85721 USA Univ Arizona Univ Arizona Hlth Sci Tucson AZ 85721 USA Univ Arizona Coll Publ Hlth Epidemiol & Biostat Dept Tucson AZ 85721 USA Univ Arizona Dept Biosyst Engn Tucson AZ 85721 USA Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA

BackgroundForty-two percent of patients experience disease comorbidity, contributing substantially to mortality rates and increased healthcare costs. Yet, the possibility of underlying shared mechanisms for diseases remains not well established, and few studies have confirmed their molecular predictions with clinical *** this work, we integrated genome-wide association study (GWAS) associating diseases and single nucleotide polymorphisms (SNPs) with transcript regulatory activity from expression quantitative trait loci (eQTL). This allowed novel mechanistic insights for noncoding and intergenic regions. We then analyzed pairs of SNPs across diseases to identify shared molecular effectors robust to multiple test correction (False Discovery Rate FDReRNA<0.05). We hypothesized that disease pairs found to be molecularly convergent would also be significantly overrepresented among comorbidities in clinical datasets. To assess our hypothesis, we used clinical claims datasets from the Healthcare Cost and Utilization Project (HCUP) and calculated significant disease comorbidities (FDRcomorbidity<0.05). We finally verified if disease pairs resulting molecularly convergent were also statistically comorbid more than by chance using the Fisher's Exact *** approach integrates: (i) 6175 SNPs associated with 238 diseases from similar to 1000 GWAS, (ii) eQTL associations from 19 tissues, and (iii) claims data for 35 million patients from HCUP. Logistic regression (controlled for age, gender, and race) identified comorbidities in HCUP, while enrichment analyses identified cis- and trans-eQTL downstream effectors of GWAS-identified variants. Among similar to 16,000 combinations of diseases, 398 disease-pairs were prioritized by both convergent eQTL-genetics (RNA overlap enrichment, FDReRNA<0.05) and clinical comorbidities (OR>1.5, FDRcomorbidity<0.05). Case studies of comorbidities illustrate specific convergent noncoding regulatory elements. An intergenic

关键词： Disease comorbidities GWAS studies eQTL Genetic network non-coding variants RNA SNP Diseases Complex diseases Intergenic Common diseases

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Enhancer variants associated with Alzheimer's disease affect gene expression via chromatin looping

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BMC MEDICAL GENOMICS 2019年第1期12卷 1-16页

作者： Kikuchi, Masataka Hara, Norikazu Hasegawa, Mai Miyashita, Akinori Kuwano, Ryozo Ikeuchi, Takeshi Nakaya, Akihiro Osaka Univ Grad Sch Med Dept Genome Informat 2-2 Yamadaoka Suita Osaka 5650871 Japan Niigata Univ Brain Res Inst Dept Mol Genet Niigata Japan Asahigawaso Res Inst Asahigawaso Med Welf Ctr Okayama Japan

Background Genome-wide association studies (GWASs) have identified single-nucleotide polymorphisms (SNPs) that may be genetic factors underlying Alzheimer's disease (AD). However, how these AD-associated SNPs (AD SNPs) contribute to the pathogenesis of this disease is poorly understood because most of them are located in non-coding regions, such as introns and intergenic regions. Previous studies reported that some disease-associated SNPs affect regulatory elements including enhancers. We hypothesized that non-coding AD SNPs are located in enhancers and affect gene expression levels via chromatin loops. Methods To characterize AD SNPs within non-coding regions, we extracted 406 AD SNPs with GWAS p-values of less than 1.00 x 10(- 6) from the GWAS catalog database. Of these, we selected 392 SNPs within non-coding regions. Next, we checked whether those non-coding AD SNPs were located in enhancers that typically regulate gene expression levels using publicly available data for enhancers that were predicted in 127 human tissues or cell types. We sought expression quantitative trait locus (eQTL) genes affected by non-coding AD SNPs within enhancers because enhancers are regulatory elements that influence the gene expression levels. To elucidate how the non-coding AD SNPs within enhancers affect the gene expression levels, we identified chromatin-chromatin interactions by Hi-C experiments. Results We report the following findings: (1) nearly 30% of non-coding AD SNPs are located in enhancers;(2) eQTL genes affected by non-coding AD SNPs within enhancers are associated with amyloid beta clearance, synaptic transmission, and immune responses;(3) 95% of the AD SNPs located in enhancers co-localize with their eQTL genes in topologically associating domains suggesting that regulation may occur through chromatin higher-order structures;(4) rs1476679 spatially contacts the promoters of eQTL genes via CTCF-CTCF interactions;(5) the effect of other AD SNPs such as rs7364180 is lik

关键词： Alzheimer's disease Genome-wide association study non-coding variants Chromatin higher-order structure

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Data integration for functional annotation of regulatory single nucleotide polymorphisms associated with Alzheimer's disease susceptibility

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GENE 2018年 672卷 115-125页

作者： Amber, Sanila Zahid, Saadia Natl Univ Sci & Technol Atta ur Rahman Sch Appl Biosci Dept Healthcare Biotechnol Neurobiol Res Lab Islamabad Pakistan

Background. Alzheimer's disease (AD), the most common form of dementia affects 24.3 million people worldwide. More than twenty genetic loci have been associated with AD and a significant number of genetic variants were mapped within these loci. A large proportion of genome wide significant variants lie outside the coding region. However, the plausible function of these variants is still unexplored. Objective: The present study aimed to unravel the regulatory role of proxy single nucleotide polymorphisms (SNPs), to determine their risk of developing AD. Methods: The RegulomeDB was employed to predict the regulatory role of proxy SNPs. Protein association network and functional enrichment analysis was performed using String10.5 and gene ontology, respectively. Results: A total of 451 SNPs were examined through SNAP web portal (r(2) <= 0.80) which returned 2186 proxy SNPs in linkage disequilibrium (LD) with genome wide significant SNPs for AD. Out of 2186 SNPs analyzed in RegulomeDB, 151 had the scores < 3 that indicates the high degree of their potential regulatory function. Further analysis revealed that out of these 151 SNPs, 37 were genome wide significant for AD, 17 were significantly associated with diseases other than AD, 89 were proxy SNPs (not genome wide significant) for various diseases including AD while 8 SNPs were novel proxy SNPs for AD. Conclusion: These findings support the notion that the non-coding variants can be strongly associated with disease risk. Further validation through genome wide association studies will be helpful for the elucidation of their regulatory potential.\

关键词： Alzheimer's disease Genome wide association studies RegulomeDB Single nucleotide polymorphisms non-coding variants Linkage disequilibrium

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SOX9 chromatin folding domains correlate with its real and putative distant cis-regulatory elements

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NUCLEUS 2017年第2期8卷 182-187页

作者： Smyk, Marta Akdemir, Kadir Caner Stankiewicz, Pawel Inst Mother & Child Hlth Dept Med Genet Warsaw Poland Univ Texas MD Anderson Canc Ctr Genom Med Dept Houston TX 77030 USA Baylor Coll Med Dept Mol & Human Genet One Baylor PlazaRm R809 Houston TX 77030 USA

Evolutionary conserved transcription factor SOX9, encoded by the dosage sensitive SOX9 gene on chromosome 17q24.3, plays an important role in development of multiple organs, including bones and testes. Heterozygous point mutations and genomic copy-number variant (CNV) deletions involving SOX9 have been reported in patients with campomelic dysplasia (CD), a skeletal malformation syndrome often associated with male-to-female sex reversal. Balanced and unbalanced structural genomic variants with breakpoints mapping up to 1.3 Mb up- and downstream to SOX9 have been described in patients with milder phenotypes, including acampomelic campomelic dysplasia, sex reversal, and Pierre Robin sequence. Based on the localization of breakpoints of genomic rearrangements causing different phenotypes, 5 genomic intervals mapping upstream to SOX9 have been defined. We have analyzed the publically available database of high-throughput chromosome conformation capture (Hi-C) in multiple cell lines in the genomic regions flanking SOX9. Consistent with the literature data, chromatin domain boundaries in the SOX9 locus exhibit conservation across species and remain largely constant across multiple cell types. Interestingly, we have found that chromatin folding domains in the SOX9 locus associate with the genomic intervals harboring real and putative regulatory elements of SOX9, implicating that variation in intra-domain interactions may be critical for dynamic regulation of SOX9 expression in a cell type-specific fashion. We propose that tissue-specific enhancers for other transcription factor genes may similarly utilize chromatin folding sub-domains in gene regulation.

关键词： chromatin looping long distance gene regulation non-coding variants structural variants tissue-specific enhancers

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Using DIVAN to assess disease/trait-associated single nucleotide variants in genome-wide scale

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BMC Research Notes 2017年第1期10卷 1-7页

作者： Chen, Li Qin, Zhaohui S. Department of Health Outcomes Research and Policy Harrison School of Pharmacy Auburn University Auburn 36849 AL United States Department of Biostatistics and Bioinformatics Rollins School of Public Health Emory University Atlanta 30322 GA United States Department of Biomedical Informatics Emory University School of Medicine Atlanta 30322 GA United States

Objective: The majority of sequence variants identified by Genome-wide association studies (GWASs) fall outside of the protein-coding regions. Unlike coding variants, it is challenging to connect these noncoding variants to the pathophysiology of complex diseases/traits due to the lack of functional annotations in the non-coding regions. To overcome this, by leveraging the rich collection of genomic and epigenomic profiles, we have developed DIVAN, or Disease/trait-specific Variant ANnotation, which enables the assignment of a measurement (D-score) for each base of the human genome in a disease/trait-specific manner. To facilitate the utilization of DIVAN, we pre-computed D-scores for every base of the human genome (hg19) for 45 different diseases/traits. Results: In this work, we present a detailed protocol on how to utilize DIVAN software toolkit to retrieve D-scores either by variant identifiers or by genomic regions for a disease/trait of interest. We also demonstrate the utilities of the D-scores using real data examples. We believe that the pre-computed D-scores for 45 diseases/traits is a useful resource to follow up on the discoveries made by GWASs, and the DIVAN software toolkit provides a convenient way to access this resource. DIVAN is freely available at https://***/site/emorydivan/software. © 2017 The Author(s).

关键词： D-score DIVAN non-coding variants Software

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Deciphering the Quantitative Effects of Cooperativity and Mutations on Transcription Factor Binding

Deciphering the Quantitative Effects of Cooperativity and Mu...

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作者： Martin, Vincentius Duke University

学位级别：Ph.D., Doctor of Philosophy

Transcription factor (TF) proteins bind to DNA in a sequence specific manner to regulate gene expression. The binding affinity of TFs for individual sites is well characterized and can be represented using DNA motif models such as position weight matrices. However, there are many factors influencing TF-DNA recognition in the cell, leading to complexities than cannot be captured by motif models alone. Here, we present our studies on two factors: cooperative TF binding and alterations in TF binding due to DNA mutations. Both factors require quantitative and rigorous approaches to distinguish real effects from random noise. First, we present a new method for characterizing cooperative binding of TFs to DNA. This method addresses the issue that TF binding sites located in close proximity, which occurs frequently across the human genome, are not necessarily bound cooperatively. To distinguish between cooperative and independent binding, we developed a high-throughput on-chip binding assay designed specifically to measure TF binding to neighboring sites. Using the experimental data from our assay, we trained machine learning models to differentiate between cooperative and independent binding of TFs. This method enabled us to reveal molecular mechanisms used by TFs to bind DNA cooperatively. Second, we introduce QBiC-Pred (Quantitative Predictions of TF Binding Changes Due to Sequence variants), an ordinary least squares based method to predict the magnitude of the effect of DNA mutations on TF-DNA recognition. We implemented QBiC-Pred as a web service: ***, which allows users to run our models through a user-friendly web interface. We used this method to identify non-recurring putative regulatory driver mutations in cancer. Our approach is novel because we prioritize mutations based on their effects on transcription factor (TF) binding, instead of relying on the recurrence of the mutations among tumor samples---which is often difficult to perform as indiv

关键词： Cooperative binding DNA-binding specificity Machine learning models non-coding variants Regulatory drivers Transcription factors

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A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations

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BMC BIOINFORMATICS 2021年第SUPPL 6期22卷 128-128页

作者： Jia, Hao Park, Sung-Joon Nakai, Kenta Univ Tokyo Dept Comp Sci Bunkyo Ku 7-3-1 Hongo Tokyo 1138656 Japan Univ Tokyo Human Genome Ctr Inst Med Sci Minato Ku 4-6-1 Shirokanedai Tokyo 1088639 Japan

Background Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed to predict their functional impact. However, the intrinsic difficulty in dealing with the scarcity of data leads to the necessity to further improve the algorithms. In this work, we propose a novel method, employing a semi-supervised deep-learning model with pseudo labels, which takes advantage of learning from both experimentally annotated and unannotated data. Results We prepared known functional non-coding variants with histone marks, DNA accessibility, and sequence context in GM12878, HepG2, and K562 cell lines. Applying our method to the dataset demonstrated its outstanding performance, compared with that of existing tools. Our results also indicated that the semi-supervised model with pseudo labels achieves higher predictive performance than the supervised model without pseudo labels. Interestingly, a model trained with the data in a certain cell line is unlikely to succeed in other cell lines, which implies the cell-type-specific nature of the non-coding variants. Remarkably, we found that DNA accessibility significantly contributes to the functional consequence of variants, which suggests the importance of open chromatin conformation prior to establishing the interaction of non-coding variants with gene regulation. Conclusions The semi-supervised deep learning model coupled with pseudo labeling has advantages in studying with limited datasets, which is not unusual in biology. Our study provides an effective approach in finding non-coding mutations potentially associated with various biological phenomena, including human diseases.

关键词： non-coding variants Epigenome Semi-supervised learning Deep learning Pseudo label

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Implementing next-generation sequencing for diagnosis and management of hereditary hearing impairment: a comprehensive review

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Expert review of molecular diagnostics 2024年第9期24卷 753-765页

作者： Cheng-Yu Tsai Jacob Shu-Jui Hsu Pei-Lung Chen Chen-Chi Wu Graduate Institute of Medical Genomics and Proteomics National Taiwan University College of Medicine Taipei Taiwan. Department of Otolaryngology National Taiwan University Hospital Taipei Taiwan. Graduate Institute of Clinical Medicine National Taiwan University College of Medicine Taipei Taiwan. Institute of Molecular Medicine National Taiwan University College of Medicine Taipei Taiwan. Department of Medical Genetics National Taiwan University Hospital Taipei Taiwan. Department of Medical Research National Taiwan University Hospital Hsin-Chu Branch Hsinchu Taiwan. Department of Otolaryngology National Taiwan University Hospital Hsin-Chu Branch Hsinchu Taiwan.

INTRODUCTION:Sensorineural hearing impairment (SNHI), a common childhood disorder with heterogeneous genetic causes, can lead to delayed language development and psychosocial problems. Next-generation sequencing (NGS) offers high-throughput screening and high-sensitivity detection of genetic etiologies of SNHI, enabling clinicians to make informed medical decisions, provide tailored treatments, and improve prognostic outcomes. AREAS COVERED:This review covers the diverse etiologies of HHI and the utility of different NGS modalities (targeted sequencing and whole exome/genome sequencing), and includes HHI-related studies on newborn screening, genetic counseling, prognostic prediction, and personalized treatment. Challenges such as the trade-off between cost and diagnostic yield, detection of structural variants, and exploration of the non-coding genome are also highlighted. EXPERT OPINION:In the current landscape of NGS-based diagnostics for HHI, there are both challenges (e.g. detection of structural variants and non-coding genome variants) and opportunities (e.g. the emergence of medical artificial intelligence tools). The authors advocate the use of technological advances such as long-read sequencing for structural variant detection, multi-omics analysis for non-coding variant exploration, and medical artificial intelligence for pathogenicity assessment and outcome prediction. By integrating these innovations into clinical practice, precision medicine in the diagnosis and management of HHI can be further improved.

关键词： Diagnostics long-read sequencing medical artificial intelligence next-generation sequencing non-coding variants prognostics sensorineural hearing impairment

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