Identification of novel  FBN1  variations implicated in congenital scoliosis

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Abstract

Congenital scoliosis (CS) is a form of scoliosis caused by congenital vertebral malformations. Genetic predisposition has been demonstrated in CS. We previously reported that TBX6 loss-of-function causes CS in a compound heterozygous model; however, this model can explain only 10% of CS. Many monogenic and polygenic CS genes remain to be elucidated. In this study, we analyzed exome sequencing (ES) data of 615 Chinese CS from the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) project. Cosegregation studies for 103 familial CS identified a novel heterozygous nonsense variant, c.2649G>A (p.Trp883Ter) in FBN1. The association between FBN1 and CS was then analyzed by extracting FBN1 variants from ES data of 574 sporadic CS and 828 controls; 30 novel variants were identified and prioritized for further analyses. A mutational burden test showed that the deleterious FBN1 variants were significantly enriched in CS subjects (OR = 3.9, P = 0.03 by Fisher’s exact test). One missense variant, c.2613A>C (p.Leu871Phe) was recurrent in two unrelated CS subjects, and in vitro functional experiments for the variant suggest that FBN1 may contribute to CS by upregulating the transforming growth factor beta (TGF-β) signaling. Our study expanded the phenotypic spectrum of FBN1, and provided nove insights into the genetic etiology of CS.

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Vertebrate segmentation: from cyclic gene networks to scoliosis.

Olivier Pourquié (2011)

One of the most striking features of the human vertebral column is its periodic organization along the anterior-posterior axis. This pattern is established when segments of vertebrates, called somites, bud off at a defined pace from the anterior tip of the embryo's presomitic mesoderm (PSM). To trigger this rhythmic production of somites, three major signaling pathways--Notch, Wnt/β-catenin, and fibroblast growth factor (FGF)--integrate into a molecular network that generates a traveling wave of gene expression along the embryonic axis, called the "segmentation clock." Recent systems approaches have begun identifying specific signaling circuits within the network that set the pace of the oscillations, synchronize gene expression cycles in neighboring cells, and contribute to the robustness and bilateral symmetry of somite formation. These findings establish a new model for vertebrate segmentation and provide a conceptual framework to explain human diseases of the spine, such as congenital scoliosis. Copyright © 2011 Elsevier Inc. All rights reserved.

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TGF-beta-dependent pathogenesis of mitral valve prolapse in a mouse model of Marfan syndrome.

Francisco Martinez-Murillo, Loretha Myers, Alan Cheng … (2004)

Mitral valve prolapse (MVP) is a common human phenotype, yet little is known about the pathogenesis of this condition. MVP can occur in the context of genetic syndromes, including Marfan syndrome (MFS), an autosomal-dominant connective tissue disorder caused by mutations in fibrillin-1. Fibrillin-1 contributes to the regulated activation of the cytokine TGF-beta, and enhanced signaling is a consequence of fibrillin-1 deficiency. We thus hypothesized that increased TGF-beta signaling may contribute to the multisystem pathogenesis of MFS, including the development of myxomatous changes of the atrioventricular valves. Mitral valves from fibrillin-1-deficient mice exhibited postnatally acquired alterations in architecture that correlated both temporally and spatially with increased cell proliferation, decreased apoptosis, and excess TGF-beta activation and signaling. In addition, TGF-beta antagonism in vivo rescued the valve phenotype, suggesting a cause and effect relationship. Expression analyses identified increased expression of numerous TGF-beta-related genes that regulate cell proliferation and survival and plausibly contribute to myxomatous valve disease. These studies validate a novel, genetically engineered murine model of myxomatous changes of the mitral valve and provide critical insight into the pathogenetic mechanism of such changes in MFS and perhaps more common nonsyndromic variants of mitral valve disease.

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Effective filtering strategies to improve data quality from population-based whole exome sequencing studies

Andrew Carson, Erin N Smith, Hiroko Matsui … (2014)

Background Genotypes generated in next generation sequencing studies contain errors which can significantly impact the power to detect signals in common and rare variant association tests. These genotyping errors are not explicitly filtered by the standard GATK Variant Quality Score Recalibration (VQSR) tool and thus remain a source of errors in whole exome sequencing (WES) projects that follow GATK’s recommended best practices. Therefore, additional data filtering methods are required to effectively remove these errors before performing association analyses with complex phenotypes. Here we empirically derive thresholds for genotype and variant filters that, when used in conjunction with the VQSR tool, achieve higher data quality than when using VQSR alone. Results The detailed filtering strategies improve the concordance of sequenced genotypes with array genotypes from 99.33% to 99.77%; improve the percent of discordant genotypes removed from 10.5% to 69.5%; and improve the Ti/Tv ratio from 2.63 to 2.75. We also demonstrate that managing batch effects by separating samples based on different target capture and sequencing chemistry protocols results in a final data set containing 40.9% more high-quality variants. In addition, imputation is an important component of WES studies and is used to estimate common variant genotypes to generate additional markers for association analyses. As such, we demonstrate filtering methods for imputed data that improve genotype concordance from 79.3% to 99.8% while removing 99.5% of discordant genotypes. Conclusions The described filtering methods are advantageous for large population-based WES studies designed to identify common and rare variation associated with complex diseases. Compared to data processed through standard practices, these strategies result in substantially higher quality data for common and rare association analyses.

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Author and article information

Contributors

Zhihong Wu: wuzh3000@126.com

Nan Wu:

ORCID: http://orcid.org/0000-0002-9429-2889

dr.wunan@pumch.cn

Journal

Journal ID (nlm-ta): J Hum Genet

Journal ID (iso-abbrev): J. Hum. Genet

Title: Journal of Human Genetics

Publisher: Springer Singapore (Singapore )

ISSN (Print): 1434-5161

ISSN (Electronic): 1435-232X

Publication date (Electronic): 11 December 2019

Publication date PMC-release: 11 December 2019

Publication date (Print): 2020

Volume: 65

Issue: 3

Pages: 221-230

Affiliations

[1 ]ISNI 0000 0001 0662 3178, GRID grid.12527.33, Department of Orthopedic Surgery, Peking Union Medical College Hospital, , Peking Union Medical College and Chinese Academy of Medical Sciences, ; Beijing, 100730 China

[2 ]ISNI 0000 0001 0662 3178, GRID grid.12527.33, Graduate School of Peking Union Medical College, , Chinese Academy of Medical Sciences, ; Beijing, 100005 China

[3 ]Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo, 108-8639 Japan

[4 ]Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Beijing, 100730 China

[5 ]ISNI 0000 0000 9889 6335, GRID grid.413106.1, Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, , Chinese Academy of Medical Sciences and Peking Union Medical College, ; Beijing, 100021 China

[6 ]GRID grid.412615.5, Department of Joint Surgery, , First Affiliated Hospital of Sun Yat-sen University, ; #58 Zhongshan 2nd Road, Guangzhou, 510080 China

[7 ]ISNI 0000 0000 9889 6335, GRID grid.413106.1, Department of Medical Genetics, Institute of Basic Medical Sciences, , Chinese Academy of Medical Sciences and Peking Union Medical College, ; Beijing, 100005 China

[8 ]ISNI 0000 0000 9889 6335, GRID grid.413106.1, Medical Research Center & Department of Central Laboratory, , Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, ; Beijing, 100730 China

[9 ]ISNI 0000 0001 0662 3178, GRID grid.12527.33, Medical Research Center of Orthopedics, , Chinese Academy of Medical Sciences, ; Beijing, 100730 China

[10 ]ISNI 0000 0001 0348 3990, GRID grid.268099.c, School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Institute of Biomedical Big Data, , Wenzhou Medical University, ; 325027 Wenzhou, China

[11 ]ISNI 0000 0001 0662 3178, GRID grid.12527.33, Department of Cardiology, Peking Union Medical College Hospital, , Peking Union Medical College and Chinese Academy of Medical Sciences, ; No. 1 Shuaifuyuan, Beijing, 100730 China

Author information

Nan Wu http://orcid.org/0000-0002-9429-2889

Article

Publisher ID: 698

DOI: 10.1038/s10038-019-0698-x

PMC ID: 6983459

PubMed ID: 31827250

SO-VID: cbd36f17-855c-4d3f-84d9-73c281e0f0ba

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 30 July 2019

Date revision received : 23 October 2019

Date accepted : 8 November 2019

Funding

Funded by: the National Natural Science Foundation of China 81822030 Beijing Natural Science Foundation 7172175 CAMS Initiative Fund for Medical Sciences 2016-I2M-3-003 the Central Level Public Interest Program for Scientific Research Institute 2018RC31003 the National Key Research and Development Program of China 2018YFC0910506

Funded by: the Central Level Public Interest Program for Scientific Research Institute 2018RC31003 the International Program Associate grant from RIKEN of Japan 190038

Funded by: Beijing Natural Science Foundation 7184232

Funded by: CAMS Initiative Fund for Medical Sciences 2016-I2M-3-003 the National Key Research and Development Program of RIKEN & Ministry of Science and Technology of China (RIKEN-MOST) 2016YFE0128400 RIKEN Incentive Research Projects 201801062228

Funded by: the National Natural Science Foundation of China 81572097 and 81871746

Funded by: the National Key Research and Development Program of China 2016YFC0901501

Funded by: the National Natural Science Foundation of China 81772301 CAMS Initiative Fund for Medical Sciences 2016-I2M-3-003

Funded by: grants from Japan Agency For Medical Research and Development (AMED) 18ek0109280, 18ek0109212 the National Key Research and Development Program of RIKEN & Ministry of Science and Technology of China (RIKEN-MOST) 2016YFE0128400

Funded by: the National Natural Science Foundation of China 81672123

Funded by: the National Natural Science Foundation of China 81772299 CAMS Initiative Fund for Medical Sciences 2016-I2M-3-003,2016-I2M-2-006 and 2017-I2M-2-001 the National Key Research and Development Program of China 2018YFC0910506

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Keywords: medical genomics,genetics research

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ScienceOpen disciplines: Genetics

Keywords: medical genomics, genetics research

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Identification of novel FBN1 variations implicated in congenital scoliosis

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Most cited references 32

Vertebrate segmentation: from cyclic gene networks to scoliosis.

TGF-beta-dependent pathogenesis of mitral valve prolapse in a mouse model of Marfan syndrome.

Effective filtering strategies to improve data quality from population-based whole exome sequencing studies

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Cited by 9

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