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Discovery of Resistance Genes in Rye by Targeted Long-Read Sequencing and Association Genetics. Cells 2022; 11:cells11081273. [PMID: 35455953 PMCID: PMC9032263 DOI: 10.3390/cells11081273] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/01/2022] [Accepted: 04/06/2022] [Indexed: 02/06/2023] Open
Abstract
The majority of released rye cultivars are susceptible to leaf rust because of a low level of resistance in the predominant hybrid rye-breeding gene pools Petkus and Carsten. To discover new sources of leaf rust resistance, we phenotyped a diverse panel of inbred lines from the less prevalent Gülzow germplasm using six distinct isolates of Puccinia recondita f. sp. secalis and found that 55 out of 92 lines were resistant to all isolates. By performing a genome-wide association study using 261,406 informative SNP markers, we identified five resistance-associated QTLs on chromosome arms 1RS, 1RL, 2RL, 5RL and 7RS. To identify candidate Puccinia recondita (Pr) resistance genes in these QTLs, we sequenced the rye nucleotide-binding leucine-rich repeat (NLR) intracellular immune receptor complement using a Triticeae NLR bait-library and PacBio® long-read single-molecule high-fidelity (HiFi) sequencing. Trait-genotype correlations across 10 resistant and 10 susceptible lines identified four candidate NLR-encoding Pr genes. One of these physically co-localized with molecular markers delimiting Pr3 on chromosome arm 1RS and the top-most resistance-associated QTL in the panel.
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103
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Li S, Li S, Su S, Zhang H, Shen J, Wen Y. Gene Region Association Analysis of Longitudinal Quantitative Traits Based on a Function-On-Function Regression Model. Front Genet 2022; 13:781740. [PMID: 35265102 PMCID: PMC8899465 DOI: 10.3389/fgene.2022.781740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 01/04/2022] [Indexed: 11/13/2022] Open
Abstract
In the process of growth and development in life, gene expressions that control quantitative traits will turn on or off with time. Studies of longitudinal traits are of great significance in revealing the genetic mechanism of biological development. With the development of ultra-high-density sequencing technology, the associated analysis has tremendous challenges to statistical methods. In this paper, a longitudinal functional data association test (LFDAT) method is proposed based on the function-on-function regression model. LFDAT can simultaneously treat phenotypic traits and marker information as continuum variables and analyze the association of longitudinal quantitative traits and gene regions. Simulation studies showed that: 1) LFDAT performs well for both linkage equilibrium simulation and linkage disequilibrium simulation, 2) LFDAT has better performance for gene regions (include common variants, low-frequency variants, rare variants and mixture), and 3) LFDAT can accurately identify gene switching in the growth and development stage. The longitudinal data of the Oryza sativa projected shoot area is analyzed by LFDAT. It showed that there is the advantage of quick calculations. Further, an association analysis was conducted between longitudinal traits and gene regions by integrating the micro effects of multiple related variants and using the information of the entire gene region. LFDAT provides a feasible method for studying the formation and expression of longitudinal traits.
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Affiliation(s)
- Shijing Li
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Shiqin Li
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Shaoqiang Su
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Hui Zhang
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jiayu Shen
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yongxian Wen
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
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104
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Simulation Research on the Methods of Multi-Gene Region Association Analysis Based on a Functional Linear Model. Genes (Basel) 2022; 13:genes13030455. [PMID: 35328009 PMCID: PMC8954869 DOI: 10.3390/genes13030455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 02/26/2022] [Accepted: 02/27/2022] [Indexed: 11/16/2022] Open
Abstract
Genome-wide association analysis is an important approach to identify genetic variants associated with complex traits. Complex traits are not only affected by single gene loci, but also by the interaction of multiple gene loci. Studies of association between gene regions and quantitative traits are of great significance in revealing the genetic mechanism of biological development. There have been a lot of studies on single-gene region association analysis, but the application of functional linear models in multi-gene region association analysis is still less. In this paper, a functional multi-gene region association analysis test method is proposed based on the functional linear model. From the three directions of common multi-gene region method, multi-gene region weighted method and multi-gene region loci weighted method, that test method is studied combined with computer simulation. The following conclusions are obtained through computer simulation: (a) The functional multi-gene region association analysis test method has higher power than the functional single gene region association analysis test method; (b) The functional multi-gene region weighted method performs better than the common functional multi-gene region method; (c) the functional multi-gene region loci weighted method is the best method for association analysis on three directions of the common multi-gene region method; (d) the performance of the Step method and Multi-gene region loci weighted Step for multi-gene regions is the best in general. Functional multi-gene region association analysis test method can theoretically provide a feasible method for the study of complex traits affected by multiple genes.
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105
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Xu J, Li L, Ren J, Zhong X, Xie C, Zheng A, Abudukadier A, Tuerxun M, Zhang S, Tang L, Hairoula D, Zou X. Whole-Exome Sequencing Implicates the USP34 rs777591A > G Intron Variant in Chronic Obstructive Pulmonary Disease in a Kashi Cohort. Front Cell Dev Biol 2022; 9:792027. [PMID: 35198563 PMCID: PMC8859106 DOI: 10.3389/fcell.2021.792027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 12/08/2021] [Indexed: 12/17/2022] Open
Abstract
Genetic factors are important factors in chronic obstructive pulmonary disease (COPD) onset. Plenty of risk and new causative genes for COPD have been identified in patients of the Chinese Han population. In contrast, we know considerably little concerning the genetics in the Kashi COPD population (Uyghur). This study aims at clarifying the genetic maps regarding COPD susceptibility in Kashi (China). Whole-exome sequencing (WES) was used to analyze three Uyghur families with COPD in Kashi (eight patients and one healthy control). Sanger sequencing was also used to verify the WES results in 541 unrelated Uyghur COPD patients and 534 Uyghur healthy controls. WES showed 72 single nucleotide variants (SNVs), two deletions, and small insertions (InDels), 26 copy number variants (CNVs), and 34 structural variants (SVs), including g.71230620T > A (rs12449210T > A, NC_000,016.10) in the HYDIN axonemal central pair apparatus protein (HYDIN) gene and g.61190482A > G (rs777591A > G, NC_000002.12) in the ubiquitin-specific protease 34 (USP34) gene. After Sanger sequencing, we found that rs777591“AA” under different genetic models except for the dominant model (adjusted OR = 0.8559, 95%CI 0.6568–1.115, p > .05), could significantly reduce COPD risk, but rs12449210T > A was not related to COPD. In stratified analysis of smoking status, rs777591“AA” reduced COPD risk significantly among the nonsmoker group. Protein and mRNA expression of USP34 in cigarette smoke extract-treated BEAS-2b cells increased significantly compared with those in the control group. Our findings associate the USP34 rs777591“AA” genotype as a protector factor in COPD.
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Affiliation(s)
- Jingran Xu
- Department of Medical College, Shihezi University, Shihezi, China
| | - Li Li
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Jie Ren
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Xuemei Zhong
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Chengxin Xie
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Aifang Zheng
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Ayiguzali Abudukadier
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Maimaitiaili Tuerxun
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Sujie Zhang
- Department of Medical College, Shihezi University, Shihezi, China
| | - Lifeng Tang
- Department of Medical College, Shihezi University, Shihezi, China
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Dilare Hairoula
- Department of Medical College, Shihezi University, Shihezi, China
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Xiaoguang Zou
- Department of Medical College, Shihezi University, Shihezi, China
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
- *Correspondence: Xiaoguang Zou,
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106
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Kulminski AM, Philipp I, Shu L, Culminskaya I. Definitive roles of TOMM40-APOE-APOC1 variants in the Alzheimer's risk. Neurobiol Aging 2022; 110:122-131. [PMID: 34625307 PMCID: PMC8758518 DOI: 10.1016/j.neurobiolaging.2021.09.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/06/2021] [Accepted: 09/07/2021] [Indexed: 02/03/2023]
Abstract
Despite advances, the roles of genetic variants from the APOE-harboring 19q13.32 region in Alzheimer's disease (AD) remain controversial. We leverage a comprehensive approach to gain insights into a more homogeneous genetic architecture of AD in this region. We use a sample of 2,673 AD-affected and 16,246 unaffected subjects from 4 studies and validate our main findings in the landmark Alzheimer's Disease Genetics Consortium cohort (3,662 AD-cases and 1,541 controls). We report the remarkably high excesses of the AD risk for carriers of the ε4 allele who also carry minor alleles of rs2075650 (TOMM40) and rs12721046 (APOC1) polymorphisms compared to carriers of their major alleles. The exceptionally high 4.37-fold (p=1.34 × 10-3) excess was particularly identified for the minor allele homozygotes. The beneficial and adverse variants were significantly depleted and enriched, respectively, in the AD-affected families. This study provides compelling evidence for the definitive roles of the APOE-TOMM40-APOC1 variants in the AD risk.
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Affiliation(s)
- Alexander M. Kulminski
- Corresponding Author: Alexander M. Kulminski, Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA,
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107
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Grid-based Gaussian process models for longitudinal genetic data. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS 2022. [DOI: 10.29220/csam.2022.29.1.065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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108
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Grid-based Gaussian process models for longitudinal genetic data. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS 2022. [DOI: 10.29220/csam.2022.29.1.745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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109
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Cheng S, Lyu J, Shi X, Wang K, Wang Z, Deng M, Sun B, Wang C. Rare variant association tests for ancestry-matched case-control data based on conditional logistic regression. Brief Bioinform 2022; 23:6502553. [PMID: 35021184 DOI: 10.1093/bib/bbab572] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 11/29/2021] [Accepted: 12/13/2021] [Indexed: 12/13/2022] Open
Abstract
With the increasing volume of human sequencing data available, analysis incorporating external controls becomes a popular and cost-effective approach to boost statistical power in disease association studies. To prevent spurious association due to population stratification, it is important to match the ancestry backgrounds of cases and controls. However, rare variant association tests based on a standard logistic regression model are conservative when all ancestry-matched strata have the same case-control ratio and might become anti-conservative when case-control ratio varies across strata. Under the conditional logistic regression (CLR) model, we propose a weighted burden test (CLR-Burden), a variance component test (CLR-SKAT) and a hybrid test (CLR-MiST). We show that the CLR model coupled with ancestry matching is a general approach to control for population stratification, regardless of the spatial distribution of disease risks. Through extensive simulation studies, we demonstrate that the CLR-based tests robustly control type 1 errors under different matching schemes and are more powerful than the standard Burden, SKAT and MiST tests. Furthermore, because CLR-based tests allow for different case-control ratios across strata, a full-matching scheme can be employed to efficiently utilize all available cases and controls to accelerate the discovery of disease associated genes.
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Affiliation(s)
- Shanshan Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Jingjing Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Xian Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Kai Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Zengmiao Wang
- Center for Quantitative Biology, Peking University, Beijing 100871, P. R. China
| | - Minghua Deng
- Center for Quantitative Biology, Peking University, Beijing 100871, P. R. China.,LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, P. R. China.,Center for Statistical Sciences, Peking University, Beijing 100871, P. R. China
| | - Baoluo Sun
- Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Singapore
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.,Department of Orthopedic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
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110
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Bloom AJ, Mao X, Strickland A, Sasaki Y, Milbrandt J, DiAntonio A. Constitutively active SARM1 variants that induce neuropathy are enriched in ALS patients. Mol Neurodegener 2022; 17:1. [PMID: 34991663 PMCID: PMC8739729 DOI: 10.1186/s13024-021-00511-x] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 12/17/2021] [Indexed: 03/31/2023] Open
Abstract
Background In response to injury, neurons activate a program of organized axon self-destruction initiated by the NAD+ hydrolase, SARM1. In healthy neurons SARM1 is autoinhibited, but single amino acid changes can abolish autoinhibition leading to constitutively active SARM1 enzymes that promote degeneration when expressed in cultured neurons. Methods To investigate whether naturally occurring human variants might disrupt SARM1 autoinhibition and potentially contribute to risk for neurodegenerative disease, we assayed the enzymatic activity of all 42 rare SARM1 alleles identified among 8507 amyotrophic lateral sclerosis (ALS) patients and 9671 controls. We then intrathecally injected mice with virus expressing SARM1 constructs to test the capacity of an ALS-associated constitutively active SARM1 variant to promote neurodegeneration in vivo. Results Twelve out of 42 SARM1 missense variants or small in-frame deletions assayed exhibit constitutive NADase activity, including more than half of those that are unique to the ALS patients or that occur in multiple patients. There is a > 5-fold enrichment of constitutively active variants among patients compared to controls. Expression of constitutively active ALS-associated SARM1 alleles in cultured dorsal root ganglion (DRG) neurons is pro-degenerative and cytotoxic. Intrathecal injection of an AAV expressing the common SARM1 reference allele is innocuous to mice, but a construct harboring SARM1V184G, the constitutively active variant found most frequently among the ALS patients, causes axon loss, motor dysfunction, and sustained neuroinflammation. Conclusions These results implicate rare hypermorphic SARM1 alleles as candidate genetic risk factors for ALS and other neurodegenerative conditions. Supplementary Information The online version contains supplementary material available at 10.1186/s13024-021-00511-x.
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Affiliation(s)
- A Joseph Bloom
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA.
| | - Xianrong Mao
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA
| | - Amy Strickland
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA
| | - Yo Sasaki
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA
| | - Jeffrey Milbrandt
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA.
| | - Aaron DiAntonio
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Developmental Biology, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA.
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111
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Rollar S, Geyer M, Hartl L, Mohler V, Ordon F, Serfling A. Quantitative Trait Loci Mapping of Adult Plant and Seedling Resistance to Stripe Rust ( Puccinia striiformis Westend.) in a Multiparent Advanced Generation Intercross Wheat Population. FRONTIERS IN PLANT SCIENCE 2021; 12:684671. [PMID: 35003147 PMCID: PMC8733622 DOI: 10.3389/fpls.2021.684671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 11/19/2021] [Indexed: 05/20/2023]
Abstract
Stripe rust caused by the biotrophic fungus Puccinia striiformis Westend. is one of the most important diseases of wheat worldwide, causing high yield and quality losses. Growing resistant cultivars is the most efficient way to control stripe rust, both economically and ecologically. Known resistance genes are already present in numerous cultivars worldwide. However, their effectiveness is limited to certain races within a rust population and the emergence of stripe rust races being virulent against common resistance genes forces the demand for new sources of resistance. Multiparent advanced generation intercross (MAGIC) populations have proven to be a powerful tool to carry out genetic studies on economically important traits. In this study, interval mapping was performed to map quantitative trait loci (QTL) for stripe rust resistance in the Bavarian MAGIC wheat population, comprising 394 F6 : 8 recombinant inbred lines (RILs). Phenotypic evaluation of the RILs was carried out for adult plant resistance in field trials at three locations across three years and for seedling resistance in a growth chamber. In total, 21 QTL for stripe rust resistance corresponding to 13 distinct chromosomal regions were detected, of which two may represent putatively new QTL located on wheat chromosomes 3D and 7D.
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Affiliation(s)
- Sandra Rollar
- Julius Kühn Institute (JKI) – Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Quedlinburg, Germany
| | - Manuel Geyer
- Bavarian State Research Center for Agriculture, Institute for Crop Science and Plant Breeding, Freising, Germany
| | - Lorenz Hartl
- Bavarian State Research Center for Agriculture, Institute for Crop Science and Plant Breeding, Freising, Germany
| | - Volker Mohler
- Bavarian State Research Center for Agriculture, Institute for Crop Science and Plant Breeding, Freising, Germany
| | - Frank Ordon
- Julius Kühn Institute (JKI) – Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Quedlinburg, Germany
| | - Albrecht Serfling
- Julius Kühn Institute (JKI) – Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Quedlinburg, Germany
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112
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Samayoa LF, Olukolu BA, Yang CJ, Chen Q, Stetter MG, York AM, Sanchez-Gonzalez JDJ, Glaubitz JC, Bradbury PJ, Romay MC, Sun Q, Yang J, Ross-Ibarra J, Buckler ES, Doebley JF, Holland JB. Domestication reshaped the genetic basis of inbreeding depression in a maize landrace compared to its wild relative, teosinte. PLoS Genet 2021; 17:e1009797. [PMID: 34928949 PMCID: PMC8722731 DOI: 10.1371/journal.pgen.1009797] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/03/2022] [Accepted: 12/03/2021] [Indexed: 12/29/2022] Open
Abstract
Inbreeding depression is the reduction in fitness and vigor resulting from mating of close relatives observed in many plant and animal species. The extent to which the genetic load of mutations contributing to inbreeding depression is due to large-effect mutations versus variants with very small individual effects is unknown and may be affected by population history. We compared the effects of outcrossing and self-fertilization on 18 traits in a landrace population of maize, which underwent a population bottleneck during domestication, and a neighboring population of its wild relative teosinte. Inbreeding depression was greater in maize than teosinte for 15 of 18 traits, congruent with the greater segregating genetic load in the maize population that we predicted from sequence data. Parental breeding values were highly consistent between outcross and selfed offspring, indicating that additive effects determine most of the genetic value even in the presence of strong inbreeding depression. We developed a novel linkage scan to identify quantitative trait loci (QTL) representing large-effect rare variants carried by only a single parent, which were more important in teosinte than maize. Teosinte also carried more putative juvenile-acting lethal variants identified by segregation distortion. These results suggest a mixture of mostly polygenic, small-effect partially recessive effects in linkage disequilibrium underlying inbreeding depression, with an additional contribution from rare larger-effect variants that was more important in teosinte but depleted in maize following the domestication bottleneck. Purging associated with the maize domestication bottleneck may have selected against some large effect variants, but polygenic load is harder to purge and overall segregating mutational burden increased in maize compared to teosinte. Inbreeding depression is the reduction in fitness and vigor resulting from mating of close relatives observed in many plant and animal species. Mating of close relatives increases the probability that an individual inherits two non-functioning mutations at the same gene, resulting in lower fitness of such matings. We do not know the extent to which inbreeding depression is due to mutations with large-effects versus small-effect polygenic variants. We compared the effects of outcrossing and self-fertilization on 18 traits in a landrace population of maize, which underwent a population bottleneck during domestication, and a neighboring population of its wild relative teosinte. Inbreeding depression was greater in maize than teosinte for 15 of 18 traits and we found that this was consistent with higher predicted ‘genetic load’ in maize based solely on the evolutionary conservation of the sequence variants observed in the population. We also mapped genome positions associated with inbreeding depression, identifying more and larger-effect genetic variants in teosinte than maize. These results suggest that during domestication, some of the rare large-effect variants in teosinte were bred out, but many genetic variants of small effects on inbreeding depression increased in frequency maize.
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Affiliation(s)
- Luis Fernando Samayoa
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Bode A. Olukolu
- Department of Entomology and Plant Pathology, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Chin Jian Yang
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Qiuyue Chen
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Markus G. Stetter
- Institute for Plant Sciences and Center of Excellence on Plant Sciences, University of Cologne, Cologne, Germany
| | - Alessandra M. York
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | | | - Jeffrey C. Glaubitz
- Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America
| | - Peter J. Bradbury
- US Department of Agriculture–Agricultural Research Service, Cornell University, Ithaca, New York, United States of America
| | - Maria Cinta Romay
- Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America
| | - Qi Sun
- Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America
| | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, Center for Population Biology, and Genome Center, University of California, Davis, California, United States of America
| | - Edward S. Buckler
- US Department of Agriculture–Agricultural Research Service, Cornell University, Ithaca, New York, United States of America
| | - John F. Doebley
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - James B. Holland
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
- United States Department of Agriculture–Agriculture Research Service, Raleigh, North Carolina, United States of America
- * E-mail:
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113
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Lu H, Qiao J, Shao Z, Wang T, Huang S, Zeng P. A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics. BMC Med 2021; 19:314. [PMID: 34895209 PMCID: PMC8667366 DOI: 10.1186/s12916-021-02186-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 11/10/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear. METHODS We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders. RESULTS We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders. CONCLUSIONS Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.
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Affiliation(s)
- Haojie Lu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Zhonghe Shao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuiping Huang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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114
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Legarra A, Garcia-Baccino CA, Wientjes YCJ, Vitezica ZG. The correlation of substitution effects across populations and generations in the presence of nonadditive functional gene action. Genetics 2021; 219:iyab138. [PMID: 34718531 PMCID: PMC8664574 DOI: 10.1093/genetics/iyab138] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 08/19/2021] [Indexed: 11/14/2022] Open
Abstract
Allele substitution effects at quantitative trait loci (QTL) are part of the basis of quantitative genetics theory and applications such as association analysis and genomic prediction. In the presence of nonadditive functional gene action, substitution effects are not constant across populations. We develop an original approach to model the difference in substitution effects across populations as a first order Taylor series expansion from a "focal" population. This expansion involves the difference in allele frequencies and second-order statistical effects (additive by additive and dominance). The change in allele frequencies is a function of relationships (or genetic distances) across populations. As a result, it is possible to estimate the correlation of substitution effects across two populations using three elements: magnitudes of additive, dominance, and additive by additive variances; relationships (Nei's minimum distances or Fst indexes); and assumed heterozygosities. Similarly, the theory applies as well to distinct generations in a population, in which case the distance across generations is a function of increase of inbreeding. Simulation results confirmed our derivations. Slight biases were observed, depending on the nonadditive mechanism and the reference allele. Our derivations are useful to understand and forecast the possibility of prediction across populations and the similarity of GWAS effects.
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Affiliation(s)
- Andres Legarra
- INRAE/INP, UMR 1388 GenPhySE, Castanet-Tolosan 31326, France
| | - Carolina A. Garcia-Baccino
- INRAE/INP, UMR 1388 GenPhySE, Castanet-Tolosan 31326, France
- Departamento de Producción Animal, Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires C1417DSQ, Argentina
- SAS NUCLEUS, Le Rheu 35650, France
| | - Yvonne C. J. Wientjes
- Wageningen University & Research, Animal Breeding and Genomics, Wageningen 6700 AH, the Netherlands
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115
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Kesavan M, Turner JH. Myeloid Toxicity of Radionuclide Cancer Therapy. Cancer Biother Radiopharm 2021; 37:164-172. [PMID: 34871036 DOI: 10.1089/cbr.2021.0286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Emergent genomic analytic techniques in patients with cancer offer the potential to define the risk of myelo dysplastic syndrome (MDS) and acute leukemia (AL) manifesting following targeted radionuclide therapy of metastatic lymphoma, neuroendocrine tumors (NETs), and prostate cancer. Characterization of the genetic profile will allow risk stratification of patients before theranostic radionuclide management of advanced cancers and offers the opportunity to minimize toxicity while preserving optimal individualized efficacy in the practice of personalized precision nuclear oncology. Our review of a single-center experience of prospective radionuclide theranostic management of metastatic non-Hodgkin lymphoma (NHL), NETs, and castration-resistant prostate cancer (metastatic castrate-resistant prostate cancer [mCRPC]) over the past decade, and comparison with published studies, shows that while the risk of significant myelotoxicity is generally low, at <3%, the consequences in the small minority of patients who develop MDS or AL are substantial, and survival is poor. Timely identification of patients at heightened risk of hematologic toxic complication, using novel genomic technology before institution of radionuclide therapy, will facilitate amelioration of myelotoxicity. In current clinical practice, the minimal hematological toxicity of chemo-free theranostic management of advanced cancer is significantly less compared with newly adopted chemotherapy -immunotherapy regimens, and the financial toxicity associated with these novel agents is avoided.
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Affiliation(s)
- Murali Kesavan
- Department of Hematology, School of Health and Medical Sciences, The University of Western Australia, Perth, Australia
| | - J Harvey Turner
- Department of Hematology, School of Health and Medical Sciences, The University of Western Australia, Perth, Australia
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116
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Ho PJ, Khng AJ, Loh HW, Ho WK, Yip CH, Mohd-Taib NA, Tan VKM, Tan BKT, Tan SM, Tan EY, Lim SH, Jamaris S, Sim Y, Wong FY, Ngeow J, Lim EH, Tai MC, Wijaya EA, Lee SC, Chan CW, Buhari SA, Chan PMY, Chen JJC, Seah JCM, Lee WP, Mok CW, Lim GH, Woo E, Kim SW, Lee JW, Lee MH, Park SK, Dunning AM, Easton DF, Schmidt MK, Teo SH, Li J, Hartman M. Germline breast cancer susceptibility genes, tumor characteristics, and survival. Genome Med 2021; 13:185. [PMID: 34857041 PMCID: PMC8638193 DOI: 10.1186/s13073-021-00978-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 09/24/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Mutations in certain genes are known to increase breast cancer risk. We study the relevance of rare protein-truncating variants (PTVs) that may result in loss-of-function in breast cancer susceptibility genes on tumor characteristics and survival in 8852 breast cancer patients of Asian descent. METHODS Gene panel sequencing was performed for 34 known or suspected breast cancer predisposition genes, of which nine genes (ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, and TP53) were associated with breast cancer risk. Associations between PTV carriership in one or more genes and tumor characteristics were examined using multinomial logistic regression. Ten-year overall survival was estimated using Cox regression models in 6477 breast cancer patients after excluding older patients (≥75years) and stage 0 and IV disease. RESULTS PTV9genes carriership (n = 690) was significantly associated (p < 0.001) with more aggressive tumor characteristics including high grade (poorly vs well-differentiated, odds ratio [95% confidence interval] 3.48 [2.35-5.17], moderately vs well-differentiated 2.33 [1.56-3.49]), as well as luminal B [HER-] and triple-negative subtypes (vs luminal A 2.15 [1.58-2.92] and 2.85 [2.17-3.73], respectively), adjusted for age at diagnosis, study, and ethnicity. Associations with grade and luminal B [HER2-] subtype remained significant after excluding BRCA1/2 carriers. PTV25genes carriership (n = 289, excluding carriers of the nine genes associated with breast cancer) was not associated with tumor characteristics. However, PTV25genes carriership, but not PTV9genes carriership, was suggested to be associated with worse 10-year overall survival (hazard ratio [CI] 1.63 [1.16-2.28]). CONCLUSIONS PTV9genes carriership is associated with more aggressive tumors. Variants in other genes might be associated with the survival of breast cancer patients. The finding that PTV carriership is not just associated with higher breast cancer risk, but also more severe and fatal forms of the disease, suggests that genetic testing has the potential to provide additional health information and help healthy individuals make screening decisions.
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Affiliation(s)
- Peh Joo Ho
- Genome Institute of Singapore, Human Genetics, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Alexis J. Khng
- Genome Institute of Singapore, Human Genetics, Singapore, Singapore
| | - Hui Wen Loh
- Genome Institute of Singapore, Human Genetics, Singapore, Singapore
| | - Weang-Kee Ho
- School of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Malaysia
- Cancer Research Malaysia, 1 Jalan SS12/1A, 47500 Subang Jaya, Selangor Malaysia
| | - Cheng Har Yip
- Subang Jaya Medical Centre, Jalan SS 12/1A, 47500 Subang Jaya, Selangor Malaysia
| | - Nur Aishah Mohd-Taib
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- UM Cancer Research Institute, Kuala Lumpur, Malaysia
| | - Veronique Kiak Mien Tan
- Department of Breast Surgery, Singapore General Hospital, Singapore, Singapore
- Division of Surgical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Benita Kiat-Tee Tan
- Department of Breast Surgery, Singapore General Hospital, Singapore, Singapore
- Division of Surgical Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Department of General Surgery, Sengkang General Hospital, Singapore, Singapore
| | - Su-Ming Tan
- Division of Breast Surgery, Changi General Hospital, Singapore, Singapore
| | - Ern Yu Tan
- Department of General Surgery, Tan Tock Seng Hospital, Singapore, 308433 Singapore
- Lee Kong Chian School of Medicine, Singapore, Singapore
- Institute of Molecular and Cell Biology, Singapore, Singapore
| | - Swee Ho Lim
- KK Breast Department, KK Women’s and Children’s Hospital, Singapore, 229899 Singapore
| | - Suniza Jamaris
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- UM Cancer Research Institute, Kuala Lumpur, Malaysia
| | - Yirong Sim
- Department of Breast Surgery, Singapore General Hospital, Singapore, Singapore
- Division of Surgical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Fuh Yong Wong
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Joanne Ngeow
- Lee Kong Chian School of Medicine, Nanyang Technology University, Singapore, Singapore
- Cancer Genetics Service, National Cancer Centre Singapore, Singapore, Singapore
- Oncology Academic Clinical Program, Duke NUS, Singapore, Singapore
| | - Elaine Hsuen Lim
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Mei Chee Tai
- Cancer Research Malaysia, 1 Jalan SS12/1A, 47500 Subang Jaya, Selangor Malaysia
| | | | - Soo Chin Lee
- Department of Hematology-oncology, National University Cancer Institute, National University Health System, Singapore, 119074 Singapore
| | - Ching Wan Chan
- Department of Surgery, University Surgical Cluster, National University Hospital, Singapore, Singapore
| | - Shaik Ahmad Buhari
- Department of Surgery, University Surgical Cluster, National University Hospital, Singapore, Singapore
| | - Patrick M. Y. Chan
- Department of General Surgery, Tan Tock Seng Hospital, Singapore, 308433 Singapore
| | - Juliana J. C. Chen
- Department of General Surgery, Tan Tock Seng Hospital, Singapore, 308433 Singapore
| | | | - Wai Peng Lee
- Division of Breast Surgery, Changi General Hospital, Singapore, Singapore
| | - Chi Wei Mok
- Division of Breast Surgery, Changi General Hospital, Singapore, Singapore
| | - Geok Hoon Lim
- KK Breast Department, KK Women’s and Children’s Hospital, Singapore, 229899 Singapore
| | - Evan Woo
- KK Breast Department, KK Women’s and Children’s Hospital, Singapore, 229899 Singapore
| | - Sung-Won Kim
- Department of Surgery, Breast Care Center, Daerim St. Mary’s Hospital, Seoul, Korea
| | - Jong Won Lee
- Department of Surgery, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Republic of Korea
| | - Min Hyuk Lee
- Department of Surgery, Soonchunhyang University and Hospital, Seoul, Republic of Korea
| | - Sue K. Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Marjanka K. Schmidt
- Division of Molecular Pathology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Soo-Hwang Teo
- Cancer Research Malaysia, 1 Jalan SS12/1A, 47500 Subang Jaya, Selangor Malaysia
- Department of Surgery, Faculty of Medicine, University of Malaya, Jalan Universiti, 50630 Kuala Lumpur, Malaysia
| | - Jingmei Li
- Genome Institute of Singapore, Human Genetics, Singapore, Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Surgery, University Surgical Cluster, National University Hospital, Singapore, Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
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117
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Kim J, Shen J, Wang A, Mehrotra DV, Ko S, Zhou JJ, Zhou H. VCSEL: Prioritizing SNP-set by penalized variance component selection. Ann Appl Stat 2021; 15:1652-1672. [DOI: 10.1214/21-aoas1491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Juhyun Kim
- Department of Biostatistics, University of California, Los Angeles
| | - Judong Shen
- Biostatistics and Research Decision Sciences, Merck & Co., Inc
| | - Anran Wang
- Biostatistics and Research Decision Sciences, Merck & Co., Inc
| | | | - Seyoon Ko
- Department of Biostatistics, University of California, Los Angeles
| | - Jin J. Zhou
- Department of Medicine, University of California, Los Angeles
| | - Hua Zhou
- Department of Biostatistics, University of California, Los Angeles
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118
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Ben-Yosef N, Frampton M, Schiff ER, Daher S, Abu Baker F, Safadi R, Israeli E, Segal AW, Levine AP. Genetic analysis of four consanguineous multiplex families with inflammatory bowel disease. Gastroenterol Rep (Oxf) 2021; 9:521-532. [PMID: 34925849 PMCID: PMC8677555 DOI: 10.1093/gastro/goab007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 11/03/2020] [Accepted: 11/26/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Family studies support a genetic predisposition to inflammatory bowel diseases (IBD), but known genetic variants only partially explain the disease heritability. Families with multiple affected individuals potentially harbour rare and high-impact causal variants. Long regions of homozygosity due to recent inbreeding may increase the risk of individuals bearing homozygous loss-of-function variants. This study aimed to identify rare and homozygous genetic variants contributing to IBD. METHODS Four families with known consanguinity and multiple cases of IBD were recruited. In a family-specific analysis, we utilised homozygosity mapping complemented by whole-exome sequencing. RESULTS We detected a single region of homozygosity shared by Crohn's disease cases from a family of Druze ancestry, spanning 2.6 Mb containing the NOD2 gene. Whole-exome sequencing did not identify any potentially damaging variants within the region, suggesting that non-coding variation may be involved. In addition, affected individuals in the families harboured several rare and potentially damaging homozygous variants in genes with a role in autophagy and innate immunity including LRRK1, WHAMM, DENND3, and C5. CONCLUSION This study examined the potential contribution of rare, high-impact homozygous variants in consanguineous families with IBD. While the analysis was not designed to achieve statistical significance, our findings highlight genes or loci that warrant further research. Non-coding variants affecting NOD2 may be of importance in Druze patients with Crohn's disease.
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Affiliation(s)
- Noam Ben-Yosef
- Centre for Molecular Medicine, Division of Medicine, University College London, London, UK
- Institute of Gastroenterology and Liver disease, Hadassah Medical Center, Jerusalem, Israel
| | - Matthew Frampton
- Centre for Molecular Medicine, Division of Medicine, University College London, London, UK
| | - Elena R Schiff
- Institute of Ophthalmology, Moorfields Eye Hospital, University College London, London, UK
| | - Saleh Daher
- Institute of Gastroenterology and Liver disease, Hadassah Medical Center, Jerusalem, Israel
| | - Fadi Abu Baker
- Institue of Gastroenterology and Hepatology, Hillel Yaffe Medical Center, Hadera, Israel
| | - Rifaat Safadi
- Institute of Gastroenterology and Liver disease, Hadassah Medical Center, Jerusalem, Israel
| | - Eran Israeli
- Institute of Gastroenterology and Liver disease, E. Wolfson Medical Center, Holon, Israel
| | - Anthony W Segal
- Centre for Molecular Medicine, Division of Medicine, University College London, London, UK
| | - Adam P Levine
- Centre for Molecular Medicine, Division of Medicine, University College London, London, UK
- Department of Pathology, University College London, London, UK
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119
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Abstract
Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.
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120
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Raimondi D, Corso M, Fariselli P, Moreau Y. From genotype to phenotype in Arabidopsis thaliana: in-silico genome interpretation predicts 288 phenotypes from sequencing data. Nucleic Acids Res 2021; 50:e16. [PMID: 34792168 PMCID: PMC8860592 DOI: 10.1093/nar/gkab1099] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 10/06/2021] [Accepted: 10/22/2021] [Indexed: 01/09/2023] Open
Abstract
In many cases, the unprecedented availability of data provided by high-throughput sequencing has shifted the bottleneck from a data availability issue to a data interpretation issue, thus delaying the promised breakthroughs in genetics and precision medicine, for what concerns Human genetics, and phenotype prediction to improve plant adaptation to climate change and resistance to bioagressors, for what concerns plant sciences. In this paper, we propose a novel Genome Interpretation paradigm, which aims at directly modeling the genotype-to-phenotype relationship, and we focus on A. thaliana since it is the best studied model organism in plant genetics. Our model, called Galiana, is the first end-to-end Neural Network (NN) approach following the genomes in/phenotypes out paradigm and it is trained to predict 288 real-valued Arabidopsis thaliana phenotypes from Whole Genome sequencing data. We show that 75 of these phenotypes are predicted with a Pearson correlation ≥0.4, and are mostly related to flowering traits. We show that our end-to-end NN approach achieves better performances and larger phenotype coverage than models predicting single phenotypes from the GWAS-derived known associated genes. Galiana is also fully interpretable, thanks to the Saliency Maps gradient-based approaches. We followed this interpretation approach to identify 36 novel genes that are likely to be associated with flowering traits, finding evidence for 6 of them in the existing literature.
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Affiliation(s)
| | - Massimiliano Corso
- Institut Jean-Pierre Bourgin, Université Paris-Saclay, INRAE, AgroParisTech, 78000 Versailles, France
| | - Piero Fariselli
- Department of Medical Sciences, University of Torino, 10123 Torino, Italy
| | - Yves Moreau
- ESAT-STADIUS, KU Leuven, 3001 Leuven, Belgium
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121
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Kim M, Harmanci AO, Bossuat JP, Carpov S, Cheon JH, Chillotti I, Cho W, Froelicher D, Gama N, Georgieva M, Hong S, Hubaux JP, Kim D, Lauter K, Ma Y, Ohno-Machado L, Sofia H, Son Y, Song Y, Troncoso-Pastoriza J, Jiang X. Ultrafast homomorphic encryption models enable secure outsourcing of genotype imputation. Cell Syst 2021; 12:1108-1120.e4. [PMID: 34464590 PMCID: PMC9898842 DOI: 10.1016/j.cels.2021.07.010] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 04/21/2021] [Accepted: 07/29/2021] [Indexed: 02/06/2023]
Abstract
Genotype imputation is a fundamental step in genomic data analysis, where missing variant genotypes are predicted using the existing genotypes of nearby "tag" variants. Although researchers can outsource genotype imputation, privacy concerns may prohibit genetic data sharing with an untrusted imputation service. Here, we developed secure genotype imputation using efficient homomorphic encryption (HE) techniques. In HE-based methods, the genotype data are secure while it is in transit, at rest, and in analysis. It can only be decrypted by the owner. We compared secure imputation with three state-of-the-art non-secure methods and found that HE-based methods provide genetic data security with comparable accuracy for common variants. HE-based methods have time and memory requirements that are comparable or lower than those for the non-secure methods. Our results provide evidence that HE-based methods can practically perform resource-intensive computations for high-throughput genetic data analysis. The source code is freely available for download at https://github.com/K-miran/secure-imputation.
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Affiliation(s)
- Miran Kim
- Department of Computer Science and Engineering and Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
| | - Arif Ozgun Harmanci
- Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA.,Corresponding authors: ,
| | | | - Sergiu Carpov
- Inpher, EPFL Innovation Park Bàtiment A, 3rd Fl, 1015 Lausanne, Switzerland.,CEA, LIST, 91191 Gif-sur-Yvette Cedex, France
| | - Jung Hee Cheon
- Department of Mathematical Sciences, Seoul National University, Seoul, 08826, Republic of Korea.,Crypto Lab Inc., Seoul, 08826, Republic of Korea
| | | | - Wonhee Cho
- Department of Mathematical Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | | | - Nicolas Gama
- Inpher, EPFL Innovation Park Bàtiment A, 3rd Fl, 1015 Lausanne, Switzerland
| | - Mariya Georgieva
- Inpher, EPFL Innovation Park Bàtiment A, 3rd Fl, 1015 Lausanne, Switzerland
| | - Seungwan Hong
- Department of Mathematical Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | | | - Duhyeong Kim
- Department of Mathematical Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | | | - Yiping Ma
- University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lucila Ohno-Machado
- UCSD Health Department of Biomedical Informatics, University of California, San Diego, CA, 92093, USA
| | - Heidi Sofia
- National Institutes of Health (NIH) - National Human Genome Research Institute, Bethesda, MD, 20892, USA
| | | | - Yongsoo Song
- Department of Computer Science and Engineering, Seoul National University, Seoul, 08826, Republic of Korea
| | | | - Xiaoqian Jiang
- Center for Secure Artificial intelligence For hEalthcare (SAFE), School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, 77030, USA.,Corresponding authors: ,
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Ghosh Dasgupta M, Abdul Bari MP, Shanmugavel S, Dharanishanthi V, Muthupandi M, Kumar N, Chauhan SS, Kalaivanan J, Mohan H, Krutovsky KV, Rajasugunasekar D. Targeted re-sequencing and genome-wide association analysis for wood property traits in breeding population of Eucalyptus tereticornis × E. grandis. Genomics 2021; 113:4276-4292. [PMID: 34785351 DOI: 10.1016/j.ygeno.2021.11.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 06/20/2021] [Accepted: 11/10/2021] [Indexed: 11/16/2022]
Abstract
Globally, Eucalyptus plantations occupy 22 million ha area and is one of the preferred hardwood species due to their short rotation, rapid growth, adaptability and wood properties. In this study, we present results of GWAS in parents and 100 hybrids of Eucalyptus tereticornis × E. grandis using 762 genes presumably involved in wood formation. Comparative analysis between parents predicted 32,202 polymorphic SNPs with high average read depth of 269-562× per individual per nucleotide. Seventeen wood related traits were phenotyped across three diverse environments and GWAS was conducted using 13,610 SNPs. A total of 45 SNP-trait associations were predicted across two locations. Seven large effect markers were identified which explained more than 80% of phenotypic variation for fibre area. This study has provided an array of candidate genes which may govern fibre morphology in this genus and has predicted potential SNPs which can guide future breeding programs in tropical Eucalyptus.
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Affiliation(s)
| | | | | | | | - Muthusamy Muthupandi
- Institute of Forest Genetics and Tree Breeding, R.S. Puram, Coimbatore 641002, India
| | - Naveen Kumar
- Institute of Wood Science and Technology, 18(th) Cross Malleshwaram, Bangalore 560 003, India
| | - Shakti Singh Chauhan
- Institute of Wood Science and Technology, 18(th) Cross Malleshwaram, Bangalore 560 003, India
| | | | - Haritha Mohan
- Institute of Forest Genetics and Tree Breeding, R.S. Puram, Coimbatore 641002, India
| | - Konstantin V Krutovsky
- Department of Forest Genetics and Forest Tree Breeding, Georg-August University of Göttingen, 37077 Göttingen, Germany; Center for Integrated Breeding Research, George-August University of Göttingen, 37075 Göttingen, Germany; Laboratory of Forest Genomics, Genome Research and Education Center, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, 660036 Krasnoyarsk, Russia; Laboratory of Population Genetics, N.I. Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia; Department of Ecosystem Science and Management, Texas A&M University, College Station, TX 77843-2138, USA
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Kolin DA, Kulm S, Elemento O. Prediction of primary venous thromboembolism based on clinical and genetic factors within the U.K. Biobank. Sci Rep 2021; 11:21340. [PMID: 34725413 PMCID: PMC8560817 DOI: 10.1038/s41598-021-00796-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 10/15/2021] [Indexed: 01/18/2023] Open
Abstract
Both clinical and genetic factors drive the risk of venous thromboembolism. However, whether clinically recorded risk factors and genetic variants can be combined into a clinically applicable predictive score remains unknown. Using Cox proportional-hazard models, we analyzed the association of risk factors with the likelihood of venous thromboembolism in U.K. Biobank, a large prospective cohort. We then created a polygenic risk score of 36 single nucleotide polymorphisms and a clinical score determined by age, sex, body mass index, previous cancer diagnosis, smoking status, and fracture in the last 5 years. Participants were at significantly increased risk of venous thromboembolism if they were at high clinical risk (subhazard ratio, 4.37 [95% CI, 3.85-4.97]) or high genetic risk (subhazard ratio, 3.02 [95% CI, 2.63-3.47]) relative to participants at low clinical or genetic risk, respectively. The combined model, consisting of clinical and genetic components, was significantly better than either the clinical or the genetic model alone (P < 0.001). Participants at high risk in the combined score had nearly an eightfold increased risk of venous thromboembolism relative to participants at low risk (subhazard ratio, 7.51 [95% CI, 6.28-8.98]). This risk score can be used to guide decisions regarding venous thromboembolism prophylaxis, although external validation is needed.
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Affiliation(s)
- David A Kolin
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
- Physiology, Biophysics, and Systems Biology, Weill Cornell Medicine, New York, NY, USA.
| | - Scott Kulm
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics, and Systems Biology, Weill Cornell Medicine, New York, NY, USA
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics, and Systems Biology, Weill Cornell Medicine, New York, NY, USA
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124
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Waldmann P. A proximal LAVA method for genome-wide association and prediction of traits with mixed inheritance patterns. BMC Bioinformatics 2021; 22:523. [PMID: 34702175 PMCID: PMC8547073 DOI: 10.1186/s12859-021-04436-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 10/11/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The genetic basis of phenotypic traits is highly variable and usually divided into mono-, oligo- and polygenic inheritance classes. Relatively few traits are known to be monogenic or oligogeneic. The majority of traits are considered to have a polygenic background. To what extent there are mixtures between these classes is unknown. The rapid advancement of genomic techniques makes it possible to directly map large amounts of genomic markers (GWAS) and predict unknown phenotypes (GWP). Most of the multi-marker methods for GWAS and GWP falls into one of two regularization frameworks. The first framework is based on [Formula: see text]-norm regularization (e.g. the LASSO) and is suitable for mono- and oligogenic traits, whereas the second framework regularize with the [Formula: see text]-norm (e.g. ridge regression; RR) and thereby is favourable for polygenic traits. A general framework for mixed inheritance is lacking. RESULTS We have developed a proximal operator algorithm based on the recent LAVA regularization method that jointly performs [Formula: see text]- and [Formula: see text]-norm regularization. The algorithm is built on the alternating direction method of multipliers and proximal translation mapping (LAVA ADMM). When evaluated on the simulated QTLMAS2010 data, it is shown that the LAVA ADMM together with Bayesian optimization of the regularization parameters provides an efficient approach with lower test prediction mean-squared-error (65.89) than the LASSO (66.11), Ridge regression (83.41) and Elastic net (66.11). For the real pig data the test MSE of the LAVA ADMM is 0.850 compared to the LASSO, RR and EN with 0.875, 0.853 and 0.853, respectively. CONCLUSIONS This study presents the LAVA ADMM that is capable of joint modelling of monogenic major genetic effects and polygenic minor genetic effects which can be used for both genome-wide assoiciation and prediction purposes. The statistical evaluations based on both simulated and real pig data set shows that the LAVA ADMM has better prediction properies than the LASSO, RR and EN. Julia code for the LAVA ADMM is available at: https://github.com/patwa67/LAVAADMM .
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Affiliation(s)
- Patrik Waldmann
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland.
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125
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Dunn CD. The population frequency of human mitochondrial DNA variants is highly dependent upon mutational bias. Biol Open 2021; 10:272468. [PMID: 34643212 PMCID: PMC8565468 DOI: 10.1242/bio.059072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 10/07/2021] [Indexed: 12/23/2022] Open
Abstract
Next-generation sequencing can quickly reveal genetic variation potentially linked to heritable disease. As databases encompassing human variation continue to expand, rare variants have been of high interest, since the frequency of a variant is expected to be low if the genetic change leads to a loss of fitness or fecundity. However, the use of variant frequency when seeking genomic changes linked to disease remains very challenging. Here, I explored the role of selection in controlling human variant frequency using the HelixMT database, which encompasses hundreds of thousands of mitochondrial DNA (mtDNA) samples. I found that a substantial number of synonymous substitutions, which have no effect on protein sequence, were never encountered in this large study, while many other synonymous changes are found at very low frequencies. Further analyses of human and mammalian mtDNA datasets indicate that the population frequency of synonymous variants is predominantly determined by mutational biases rather than by strong selection acting upon nucleotide choice. My work has important implications that extend to the interpretation of variant frequency for non-synonymous substitutions.
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Affiliation(s)
- Cory D Dunn
- Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland
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126
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Wang H, Guo Z, Zheng Y, Yu C, Hou H, Chen B. No Casual Relationship Between T2DM and the Risk of Infectious Diseases: A Two-Sample Mendelian Randomization Study. Front Genet 2021; 12:720874. [PMID: 34527023 PMCID: PMC8435717 DOI: 10.3389/fgene.2021.720874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 07/26/2021] [Indexed: 12/29/2022] Open
Abstract
Background In epidemiological studies, it has been proven that the occurrence of type 2 diabetes mellitus (T2DM) is related to an increased risk of infectious diseases. However, it is still unclear whether the relationship is casual. Methods We employed a two-sample Mendelian randomization (MR) to clarify the causal effect of T2DM on high-frequency infectious diseases: sepsis, skin and soft tissue infections (SSTIs), urinary tract infections (UTIs), pneumonia, and genito-urinary infection (GUI) in pregnancy. And then, we analyzed the genome-wide association study (GWAS) meta-analysis of European-descent individuals and conducted T2DM-related single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) that were associated with genome-wide significance (p < 5 × 10–8). MR estimates were obtained using the inverse variance-weighted (IVW), the MR-Egger regression, the simple mode (SM), weighted median, and weighted mode. Results The UK Biobank (UKB) cohort (n > 500,000) provided data for GWASs on infectious diseases. MR analysis showed little evidence of a causal relationship of T2DM with five mentioned infections’ (sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy) susceptibility [odds ratio (OR) = 0.99999, p = 0.916; OR = 0.99986, p = 0.233; OR = 0.99973, p = 0.224; OR = 0.99997, p = 0.686; OR, 1.00002, p = 0.766]. Sensitivity analysis showed similar results, indicating the robustness of causality. There were no heterogeneity and pleiotropic bias. Conclusion T2DM would not be causally associated with high-frequency infectious diseases (including sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy).
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Affiliation(s)
- Huachen Wang
- Intensive Care Unit, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zheng Guo
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Yulu Zheng
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Chunyan Yu
- Medical Imaging Department, Longgang District Central Hospital of Shenzhen, Shenzhen, China
| | - Haifeng Hou
- Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Bing Chen
- Intensive Care Unit, The Second Hospital of Tianjin Medical University, Tianjin, China
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127
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Liu Y, Dougherty JD. utr.annotation: a tool for annotating genomic variants that could influence post-transcriptional regulation. Bioinformatics 2021; 37:3926-3928. [PMID: 34478494 DOI: 10.1093/bioinformatics/btab635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/21/2021] [Accepted: 08/31/2021] [Indexed: 11/12/2022] Open
Abstract
SUMMARY Whole genome sequencing of patient populations is identifying thousands of new variants in UnTranslated Regions(UTRs). While the consequences of UTR mutations are not as easily predicted from primary sequence as coding mutations are, there are some known features of UTRs that modulate their function. utr.annotation is an R package that can be used to annotate potential deleterious variants in the UTR regions for both human and mouse species. Given a CSV or VCF format variant file, utr.annotation provides information of each variant on whether and how it alters known translational regulators including: upstream Open Reading Frames (uORFs), upstream Kozak sequences, polyA signals, Kozak sequences at the annotated translation start site, start codons, and stop codons, conservation scores in the variant position, and whether and how it changes ribosome loading based on a model derived from empirical data. AVAILABILITY utr.annotation is freely available on Bitbucket (https://bitbucket.org/jdlabteam/utr.annotation/src/master/) and CRAN (https://cran.r-project.org/web/packages/utr.annotation/index.html). SUPPLEMENTARY INFORMATION Supplementary data are available at https://wustl.box.com/s/yye99bryfin89nav45gv91l5k35fxo7z.
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Affiliation(s)
- Yating Liu
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
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128
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Figueiredo J, Mercadillo F, Melo S, Barroso A, Gonçalves M, Díaz-Tasende J, Carneiro P, Robles L, Colina F, Ibarrola C, Perea J, Morais-de-Sá E, Seruca R, Urioste M. Germline CDH1 G212E Missense Variant: Combining Clinical, In Vitro and In Vivo Strategies to Unravel Disease Burden. Cancers (Basel) 2021; 13:cancers13174359. [PMID: 34503169 PMCID: PMC8430832 DOI: 10.3390/cancers13174359] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/23/2021] [Accepted: 08/26/2021] [Indexed: 12/20/2022] Open
Abstract
Simple Summary Hereditary diffuse gastric cancer (HDGC) is an inherited cancer syndrome associated with CDH1 germline mutations. The increasing detection of CDH1 genetic variants due to multigene panel testing poses a serious clinical challenge and urges the development of effective classification strategies. In this study, we describe the identification of the novel CDH1 G212E variant in a large family strongly affected by diffuse gastric cancer. Through a comprehensive characterization pipeline, we provide evidence of the damaging nature of this genetic alteration, thus impacting patient management and family screening. Abstract E-cadherin, encoded by CDH1, is an essential molecule for epithelial homeostasis, whose loss or aberrant expression results in disturbed cell–cell adhesion, increased cell invasion and metastasis. Carriers of CDH1 germline mutations have a high risk of developing diffuse gastric cancer and lobular breast cancer, associated with the cancer syndrome Hereditary Diffuse Gastric Cancer (HDGC). The ubiquitous availability of cancer panels has led to the identification of an increasing amount of “incidental” CDH1 genetic variants that pose a serious clinical challenge. This has sparked intensive research aiming at an accurate classification of the variants and consequent validation of their clinical relevance. The present study addressed the significance of a novel CDH1 variant, G212E, identified in an unusually large pedigree displaying strong aggregation of diffuse gastric cancer. We undertook a comprehensive pipeline encompassing family data, in silico predictions, in vitro assays and in vivo strategies, which validated the deleterious phenotype induced by this genetic alteration. In particular, we demonstrated that the G212E variant affects the stability and localization, as well as the adhesive and anti-invasive functions of E-cadherin, triggering epithelial disruption and disorganization. Our findings illustrate the clinical implication of a complementary approach for effective variant categorization and patient management.
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Affiliation(s)
- Joana Figueiredo
- i3S—Instituto de Investigação e Inovação em Saúde, University of Porto, 4200-135 Porto, Portugal; (S.M.); (M.G.); (P.C.); (E.M.-d.-S.); (R.S.)
- Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), 4200-135 Porto, Portugal
- Correspondence: (J.F.); (M.U.)
| | - Fátima Mercadillo
- Familial Cancer Clinical Unit, Spanish National Cancer Research Centre (CNIO), 28029 Madrid, Spain; (F.M.); (A.B.)
| | - Soraia Melo
- i3S—Instituto de Investigação e Inovação em Saúde, University of Porto, 4200-135 Porto, Portugal; (S.M.); (M.G.); (P.C.); (E.M.-d.-S.); (R.S.)
- Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), 4200-135 Porto, Portugal
| | - Alicia Barroso
- Familial Cancer Clinical Unit, Spanish National Cancer Research Centre (CNIO), 28029 Madrid, Spain; (F.M.); (A.B.)
| | - Margarida Gonçalves
- i3S—Instituto de Investigação e Inovação em Saúde, University of Porto, 4200-135 Porto, Portugal; (S.M.); (M.G.); (P.C.); (E.M.-d.-S.); (R.S.)
- Institute for Molecular and Cell Biology (IBMC), University of Porto, 4200-135 Porto, Portugal
- Instituto de Ciências Biomédicas de Abel Salazar (ICBAS), Universidade do Porto, 4050-313 Porto, Portugal
| | - José Díaz-Tasende
- Endoscopy Unit, Gastroenterology Department, 12 de Octubre Universitary Hospital, 28041 Madrid, Spain;
| | - Patrícia Carneiro
- i3S—Instituto de Investigação e Inovação em Saúde, University of Porto, 4200-135 Porto, Portugal; (S.M.); (M.G.); (P.C.); (E.M.-d.-S.); (R.S.)
- Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), 4200-135 Porto, Portugal
| | - Luis Robles
- Familial Cancer Unit, Medical Oncology Service, 12 de Octubre Universitary Hospital, 28041 Madrid, Spain;
| | - Francisco Colina
- Pathology Department, 12 de Octubre Universitary Hospital, 28041 Madrid, Spain or (F.C.); (C.I.)
| | - Carolina Ibarrola
- Pathology Department, 12 de Octubre Universitary Hospital, 28041 Madrid, Spain or (F.C.); (C.I.)
| | - José Perea
- Surgery Department, Fundación Jiménez Díaz University Hospital, 28040 Madrid, Spain;
| | - Eurico Morais-de-Sá
- i3S—Instituto de Investigação e Inovação em Saúde, University of Porto, 4200-135 Porto, Portugal; (S.M.); (M.G.); (P.C.); (E.M.-d.-S.); (R.S.)
- Institute for Molecular and Cell Biology (IBMC), University of Porto, 4200-135 Porto, Portugal
| | - Raquel Seruca
- i3S—Instituto de Investigação e Inovação em Saúde, University of Porto, 4200-135 Porto, Portugal; (S.M.); (M.G.); (P.C.); (E.M.-d.-S.); (R.S.)
- Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), 4200-135 Porto, Portugal
- Medical Faculty, University of Porto, 4200-319 Porto, Portugal
| | - Miguel Urioste
- Familial Cancer Clinical Unit, Spanish National Cancer Research Centre (CNIO), 28029 Madrid, Spain; (F.M.); (A.B.)
- Correspondence: (J.F.); (M.U.)
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129
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Glinge C, Lahrouchi N, Jabbari R, Tfelt-Hansen J, Bezzina CR. Genome-wide association studies of cardiac electrical phenotypes. Cardiovasc Res 2021; 116:1620-1634. [PMID: 32428210 PMCID: PMC7341169 DOI: 10.1093/cvr/cvaa144] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 04/24/2020] [Accepted: 05/14/2020] [Indexed: 12/19/2022] Open
Abstract
The genetic basis of cardiac electrical phenotypes has in the last 25 years been the subject of intense investigation. While in the first years, such efforts were dominated by the study of familial arrhythmia syndromes, in recent years, large consortia of investigators have successfully pursued genome-wide association studies (GWAS) for the identification of single-nucleotide polymorphisms that govern inter-individual variability in electrocardiographic parameters in the general population. We here provide a review of GWAS conducted on cardiac electrical phenotypes in the last 14 years and discuss the implications of these discoveries for our understanding of the genetic basis of disease susceptibility and variability in disease severity. Furthermore, we review functional follow-up studies that have been conducted on GWAS loci associated with cardiac electrical phenotypes and highlight the challenges and opportunities offered by such studies.
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Affiliation(s)
- Charlotte Glinge
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Center, University of Amsterdam, Heart Center, Amsterdam Cardiovascular Sciences, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.,Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Inge Lehmanns Vej 7, 2100 Copenhagen, Denmark
| | - Najim Lahrouchi
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Center, University of Amsterdam, Heart Center, Amsterdam Cardiovascular Sciences, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Reza Jabbari
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Inge Lehmanns Vej 7, 2100 Copenhagen, Denmark
| | - Jacob Tfelt-Hansen
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Inge Lehmanns Vej 7, 2100 Copenhagen, Denmark.,Department of Forensic Medicine, Faculty of Medical Sciences, University of Copenhagen, Frederik V's Vej, 2100 Copenhagen, Denmark
| | - Connie R Bezzina
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Center, University of Amsterdam, Heart Center, Amsterdam Cardiovascular Sciences, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
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130
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Ye T, Shao J, Kang H. Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization. Ann Stat 2021. [DOI: 10.1214/20-aos2027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Ting Ye
- Department of Statistics, University of Pennsylvania
| | - Jun Shao
- School of Statistics, East China Normal University
| | - Hyunseung Kang
- Department of Statistics, University of Wisconsin-Madison
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131
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Spedicati B, Cocca M, Palmisano R, Faletra F, Barbieri C, Francescatto M, Mezzavilla M, Morgan A, Pelliccione G, Gasparini P, Girotto G. Natural human knockouts and Mendelian disorders: deep phenotyping in Italian isolates. Eur J Hum Genet 2021; 29:1272-1281. [PMID: 33727708 PMCID: PMC8384846 DOI: 10.1038/s41431-021-00850-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 12/30/2020] [Accepted: 02/23/2021] [Indexed: 02/02/2023] Open
Abstract
Whole genome sequencing (WGS) allows the identification of human knockouts (HKOs), individuals in whom loss of function (LoF) variants disrupt both alleles of a given gene. HKOs are a valuable model for understanding the consequences of genes function loss. Naturally occurring biallelic LoF variants tend to be significantly enriched in "genetic isolates," making these populations specifically suited for HKO studies. In this work, a meticulous WGS data analysis combined with an in-depth phenotypic assessment of 947 individuals from three Italian genetic isolates led to the identification of ten biallelic LoF variants in ten OMIM genes associated with known autosomal recessive diseases. Notably, only a minority of the identified HKOs (C7, F12, and GPR68 genes) displayed the expected phenotype. For most of the genes, instead, (ACADSB, FANCL, GRK1, LGI4, MPO, PGAM2, and RP1L1), the carriers showed none or few of the signs and symptoms typically associated with the related diseases. Of particular interest is a case presenting with a FANCL biallelic LoF variant and a positive diepoxybutane test but lacking a full Fanconi anemia phenotypic spectrum. Identifying KO subjects displaying expected phenotypes suggests that the lack of correct genetic diagnoses may lead to inappropriate and delayed treatment. In contrast, the presence of HKOs with phenotypes deviating from the expected patterns underlines how LoF variants may be responsible for broader phenotypic spectra. Overall, these results highlight the importance of in-depth phenotypical characterization to understand the role of LoF variants and the advantage of studying these variants in genetic isolates.
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Affiliation(s)
- Beatrice Spedicati
- grid.5133.40000 0001 1941 4308Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Massimiliano Cocca
- grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
| | - Roberto Palmisano
- grid.5133.40000 0001 1941 4308Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Flavio Faletra
- grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
| | - Caterina Barbieri
- grid.18887.3e0000000417581884Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Margherita Francescatto
- grid.5133.40000 0001 1941 4308Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Massimo Mezzavilla
- grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
| | - Anna Morgan
- grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
| | - Giulia Pelliccione
- grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
| | - Paolo Gasparini
- grid.5133.40000 0001 1941 4308Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy ,grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
| | - Giorgia Girotto
- grid.5133.40000 0001 1941 4308Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy ,grid.418712.90000 0004 1760 7415Institute for Maternal and Child Health – I.R.C.C.S. “Burlo Garofolo”, Trieste, Italy
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Lou J, Yu S, Feng L, Guo X, Wang M, Branco AT, Li T, Lemos B. Environmentally induced ribosomal DNA (rDNA) instability in human cells and populations exposed to hexavalent chromium [Cr (VI)]. ENVIRONMENT INTERNATIONAL 2021; 153:106525. [PMID: 33774497 PMCID: PMC8477438 DOI: 10.1016/j.envint.2021.106525] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 03/09/2021] [Accepted: 03/11/2021] [Indexed: 05/12/2023]
Abstract
Hexavalent Chromium [Cr (VI)] is an established toxicant, carcinogen, and a significant source of public health concern. The multicopy ribosomal DNA (rDNA) array is mechanistically linked to aging and cancer, is the most evolutionarily conserved segment of the human genome, and gives origin to nucleolus, a nuclear organelle where ribosomes are assembled. Here we show that exposure to Cr (VI) induces instability in the rDNA, triggering cycles of rapid, specific, and transient amplification and contraction of the array in human cells. The dynamic of environmentally responsive rDNA copy number (CN) amplification and contraction occurs at doses to which millions of individuals are regularly exposed. Finally, analyses of human populations occupationally exposed to Cr (VI) indicate that environmental exposure history and drinking habits but not age shape extensive naturally occurring rDNA copy number variation. Our observations identify a novel pathway of response to hexavalent chromium exposure and raise the prospect that a suite of environmental determinants of rDNA copy number remain to be discovered.
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Affiliation(s)
- Jianlin Lou
- Program in Molecular and Integrative Physiological Sciences & Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA; School of Public Health, Hangzhou Medical College, Hangzhou, People's Republic of China; Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, People's Republic of China
| | - Shoukai Yu
- Program in Molecular and Integrative Physiological Sciences & Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Lingfang Feng
- School of Public Health, Hangzhou Medical College, Hangzhou, People's Republic of China; Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, People's Republic of China
| | - Xinnian Guo
- School of Public Health, Hangzhou Medical College, Hangzhou, People's Republic of China; Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, People's Republic of China
| | - Meng Wang
- Program in Molecular and Integrative Physiological Sciences & Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Alan T Branco
- Program in Molecular and Integrative Physiological Sciences & Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Tao Li
- School of Public Health, Hangzhou Medical College, Hangzhou, People's Republic of China; Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou, People's Republic of China
| | - Bernardo Lemos
- Program in Molecular and Integrative Physiological Sciences & Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
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133
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Otomo N, Lu HF, Koido M, Kou I, Takeda K, Momozawa Y, Kubo M, Kamatani Y, Ogura Y, Takahashi Y, Nakajima M, Minami S, Uno K, Kawakami N, Ito M, Sato T, Watanabe K, Kaito T, Yanagida H, Taneichi H, Harimaya K, Taniguchi Y, Shigematsu H, Iida T, Demura S, Sugawara R, Fujita N, Yagi M, Okada E, Hosogane N, Kono K, Nakamura M, Chiba K, Kotani T, Sakuma T, Akazawa T, Suzuki T, Nishida K, Kakutani K, Tsuji T, Sudo H, Iwata A, Kaneko K, Inami S, Kochi Y, Chang WC, Matsumoto M, Watanabe K, Ikegawa S, Terao C. Polygenic Risk Score of Adolescent Idiopathic Scoliosis for Potential Clinical Use. J Bone Miner Res 2021; 36:1481-1491. [PMID: 34159637 DOI: 10.1002/jbmr.4324] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 04/14/2021] [Accepted: 04/18/2021] [Indexed: 12/12/2022]
Abstract
Adolescent idiopathic scoliosis (AIS) is a common disease causing three-dimensional spinal deformity in as many as 3% of adolescents. Development of a method that can accurately predict the onset and progression of AIS is an immediate need for clinical practice. Because the heritability of AIS is estimated as high as 87.5% in twin studies, prediction of its onset and progression based on genetic data is a promising option. We show the usefulness of polygenic risk score (PRS) for the prediction of onset and progression of AIS. We used AIS genomewide association study (GWAS) data comprising 79,211 subjects in three cohorts and constructed a PRS based on association statistics in a discovery set including 31,999 female subjects. After calibration using a validation data set, we applied the PRS to a test data set. By integrating functional annotations showing heritability enrichment in the selection of variants, the PRS demonstrated an association with AIS susceptibility (p = 3.5 × 10-40 with area under the receiver-operating characteristic [AUROC] = 0.674, sensitivity = 0.644, and specificity = 0.622). The decile with the highest PRS showed an odds ratio of as high as 3.36 (p = 1.4 × 10-10 ) to develop AIS compared with the fifth in decile. The addition of a predictive model with only a single clinical parameter (body mass index) improved predictive ability for development of AIS (AUROC = 0.722, net reclassification improvement [NRI] 0.505 ± 0.054, p = 1.6 × 10-8 ), potentiating clinical use of the prediction model. Furthermore, we found the Cobb angle (CA), the severity measurement of AIS, to be a polygenic trait that showed a significant genetic correlation with AIS susceptibility (rg = 0.6, p = 3.0 × 10-4 ). The AIS PRS demonstrated a significant association with CA. These results indicate a shared polygenic architecture between onset and progression of AIS and the potential usefulness of PRS in clinical settings as a predictor to promote early intervention of AIS and avoid invasive surgery. © 2021 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Nao Otomo
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan.,Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan.,Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Hsing-Fang Lu
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan.,Department of Clinical Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan.,Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Ikuyo Kou
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
| | - Kazuki Takeda
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan.,Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Michiaki Kubo
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan.,Laboratory of Complex Trait Genomics, Graduate School of Frontier Science, The University of Tokyo, Tokyo, Japan
| | - Yoji Ogura
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Yohei Takahashi
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Masahiro Nakajima
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
| | - Shohei Minami
- Department of Orthopedic Surgery, Seirei Sakura Citizen Hospital, Sakura, Japan
| | - Koki Uno
- Department of Orthopedic Surgery, National Hospital Organization, Kobe Medical Center, Kobe, Japan
| | | | - Manabu Ito
- Department of Orthopedic Surgery, National Hospital Organization, Hokkaido Medical Center, Sapporo, Japan
| | - Tatsuya Sato
- Department of Orthopedic Surgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Kei Watanabe
- Department of Orthopedic Surgery, Niigata University Medical and Dental General Hospital, Niigata, Japan
| | - Takashi Kaito
- Department of Orthopedic Surgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Haruhisa Yanagida
- Department of Orthopedic & Spine Surgery, Fukuoka Children's Hospital, Fukuoka, Japan
| | - Hiroshi Taneichi
- Department of Orthopedic Surgery, Dokkyo Medical University School of Medicine, Mibu, Japan
| | - Katsumi Harimaya
- Department of Orthopedic Surgery, Kyushu University Beppu Hospital, Beppu, Japan
| | - Yuki Taniguchi
- Department of Orthopedic Surgery, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hideki Shigematsu
- Department of Orthopedic Surgery, Nara Medical University, Kashihara, Japan
| | - Takahiro Iida
- First Department of Orthopedic Surgery, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Satoru Demura
- Department of Orthopedic Surgery, Graduate School of Medical Science Kanazawa University, Kanazawa, Japan
| | - Ryo Sugawara
- Department of Orthopedic Surgery, Jichi Medical University, Shimotsuke, Japan
| | - Nobuyuki Fujita
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan.,Department of Orthopedic Surgery, Fujita Health University, Toyoake, Japan
| | - Mitsuru Yagi
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Eijiro Okada
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Naobumi Hosogane
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan.,Department of Orthopedic Surgery, National Defense Medical College, Tokorozawa, Japan
| | - Katsuki Kono
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan.,Kono Orthopaedic Clinic, Tokyo, Japan
| | - Masaya Nakamura
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Kazuhiro Chiba
- Department of Orthopedic Surgery, National Defense Medical College, Tokorozawa, Japan
| | - Toshiaki Kotani
- Department of Orthopedic Surgery, Seirei Sakura Citizen Hospital, Sakura, Japan
| | - Tsuyoshi Sakuma
- Department of Orthopedic Surgery, Seirei Sakura Citizen Hospital, Sakura, Japan
| | - Tsutomu Akazawa
- Department of Orthopedic Surgery, Seirei Sakura Citizen Hospital, Sakura, Japan
| | - Teppei Suzuki
- Department of Orthopedic Surgery, National Hospital Organization, Kobe Medical Center, Kobe, Japan
| | - Kotaro Nishida
- Department of Orthopedic Surgery, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Kenichiro Kakutani
- Department of Orthopedic Surgery, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Taichi Tsuji
- Department of Orthopedic Surgery, Meijo Hospital, Nagoya, Japan
| | - Hideki Sudo
- Department of Advanced Medicine for Spine and Spinal Cord Disorders, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan
| | - Akira Iwata
- Department of Preventive and Therapeutic Research for Metastatic Bone Tumor, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan
| | - Kazuo Kaneko
- Department of Orthopedic Surgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Satoshi Inami
- Department of Orthopedic Surgery, Dokkyo Medical University School of Medicine, Mibu, Japan
| | - Yuta Kochi
- Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental and University, Tokyo, Japan
| | - Wei-Chiao Chang
- Department of Clinical Pharmacy, Taipei Medical University, Taipei, Taiwan.,Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.,Department of Pharmacy, Taipei Medical University-Wangfang Hospital, Taipei, Taiwan.,Center for Biomarkers and Biotech Drugs, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Morio Matsumoto
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Kota Watanabe
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan.,Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan.,Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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134
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Kjaersgaard Andersen R, Clemmensen SB, Larsen LA, Hjelmborg JVB, Ødum N, Jemec GBE, Christensen K. Evidence of gene-gene interaction in Hidradenitis suppurativa - A nationwide register study of Danish twins. Br J Dermatol 2021; 186:78-85. [PMID: 34289077 DOI: 10.1111/bjd.20654] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/15/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Hidradenitis suppurativa (HS) is a recurrent inflammatory skin disease that, apart from rare causative loss-of-function mutations, has a widely unknown genetic aetiology. Our objective was to estimate the relative importance of genetic and environmental factors underlying HS susceptibility. METHODS Through the Danish Twin Registry and the Danish National Patient Registry we joined information on zygosity with that of HS status. HS cases were identified by International Code of Diseases 8 (705.91) and 10 (L73.2). Heritability was assessed by the classic biometric model and the possibility of gene-gene interaction through the multi-locus modeling approach. RESULTS Amongst 100,044 registered twins, we found 170 twins (from 163 pairs) diagnosed with HS. The seven concordant pairs were all monozygotic, and monozygotic twins had a casewise concordance rate of 28% (95% CI: 7%; 49%), corresponding to a familial risk of 73 (95% CI 13; 133) times that of the background population. The biometrical modelling suggested a heritability of 0.80 (95% CI 0.67; 0.93), and the multilocus index estimate was 230 (95% CI: 60; 400). This is highly indicative of gene-gene interactions, with the possibility of up to six interacting loci. CONCLUSION This twin study is substantially larger, and employs a more valid phenotype than prior studies. Genetics account for the majority of the HS susceptibility, and HS is most likely caused by gene-gene interactions rather than monogenetic mutations or solely additive genetic factors. New approaches aimed at assessing potential interactions at a SNP-SNP level should be implemented in future HS genome-wide association studies.
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Affiliation(s)
| | - S B Clemmensen
- Danish Twin Registry, Department of Epidemiology, Biostatistics and Biodemography, University of southern Denmark, Odense, Denmark
| | - L A Larsen
- Danish Twin Registry, Department of Epidemiology, Biostatistics and Biodemography, University of southern Denmark, Odense, Denmark
| | - J V B Hjelmborg
- Danish Twin Registry, Department of Epidemiology, Biostatistics and Biodemography, University of southern Denmark, Odense, Denmark
| | - N Ødum
- LEO Foundation Skin Immunology Research Center, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark
| | - G B E Jemec
- Department of Dermatology, Zealand University Hospital, Roskilde
| | - K Christensen
- Danish Twin Registry, Department of Epidemiology, Biostatistics and Biodemography, University of southern Denmark, Odense, Denmark
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135
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Contextualizing genetic risk score for disease screening and rare variant discovery. Nat Commun 2021; 12:4418. [PMID: 34285202 PMCID: PMC8292385 DOI: 10.1038/s41467-021-24387-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 06/07/2021] [Indexed: 11/08/2022] Open
Abstract
Studies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.
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136
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Evans KS, van Wijk MH, McGrath PT, Andersen EC, Sterken MG. From QTL to gene: C. elegans facilitates discoveries of the genetic mechanisms underlying natural variation. Trends Genet 2021; 37:933-947. [PMID: 34229867 DOI: 10.1016/j.tig.2021.06.005] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/01/2021] [Accepted: 06/03/2021] [Indexed: 11/15/2022]
Abstract
Although many studies have examined quantitative trait variation across many species, only a small number of genes and thereby molecular mechanisms have been discovered. Without these data, we can only speculate about evolutionary processes that underlie trait variation. Here, we review how quantitative and molecular genetics in the nematode Caenorhabditis elegans led to the discovery and validation of 37 quantitative trait genes over the past 15 years. Using these data, we can start to make inferences about evolution from these quantitative trait genes, including the roles that coding versus noncoding variation, gene family expansion, common versus rare variants, pleiotropy, and epistasis play in trait variation across this species.
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Affiliation(s)
- Kathryn S Evans
- Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA; Interdisciplinary Biological Sciences Program, Northwestern University, Evanston, IL 60208, USA
| | - Marijke H van Wijk
- Laboratory of Nematology, Wageningen University and Research, 6708 PB, Wageningen, The Netherlands
| | - Patrick T McGrath
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Erik C Andersen
- Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA.
| | - Mark G Sterken
- Laboratory of Nematology, Wageningen University and Research, 6708 PB, Wageningen, The Netherlands.
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137
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Mahmood A, Shah AA, Umair M, Wu Y, Khan A. Recalling the pathology of Parkinson's disease; lacking exact figure of prevalence and genetic evidence in Asia with an alarming outcome: A time to step-up. Clin Genet 2021; 100:659-677. [PMID: 34195994 DOI: 10.1111/cge.14019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 06/14/2021] [Accepted: 06/23/2021] [Indexed: 11/26/2022]
Abstract
Parkinson's disease (PD) is the second most common and progressive neurodegenerative disease globally, with major symptoms like bradykinesia, impaired posture, and tremor. Several genetic and environmental factors have been identified but elucidating the main factors have been challenging due to the disease's complex nature. Diagnosis, prognosis, and management of such diseases are challenging and require effective targeted attention in developing countries. Recently, PD is growing rapidly in many crowded Asian countries as an alarming threat with inadequate knowledge of its prevalence, genetic architecture, and geographic distribution. This study gave an in-depth overview of the prevalence, incidence and genomic/genetics studies published so far in the Asian population. To the best of our knowledge, PD has increased significantly in several Asian countries, including China, South Korea, Japan, Thailand, and Israel over the past few years, requiring a greater level of care and attention. Genetic screening of families with PD at national levels and establishing an official database of PD cases are essential to get a comprehensive and conclusive view of the exact prevalence and genetic diversity of PD in the Asian population to properly manage and treat the disease.
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Affiliation(s)
- Arif Mahmood
- Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.,Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Abid Ali Shah
- Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Muhammad Umair
- Medical Genomics Research Department, King Abdullah International Medical Research Center (KAIMRC), King Saud bin Abdul-Aziz University for Health Sciences, Ministry of National Guard-Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Yiming Wu
- Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Amjad Khan
- Faculty of Science, Department of Biological Sciences, University of Lakki Marwat, Lakki Marwat, Pakistan
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138
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Yang H, Mohd Saad NS, Ibrahim MI, Bayer PE, Neik TX, Severn-Ellis AA, Pradhan A, Tirnaz S, Edwards D, Batley J. Candidate Rlm6 resistance genes against Leptosphaeria. maculans identified through a genome-wide association study in Brassica juncea (L.) Czern. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:2035-2050. [PMID: 33768283 DOI: 10.1007/s00122-021-03803-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 02/23/2021] [Indexed: 06/12/2023]
Abstract
One hundred and sixty-seven B. juncea varieties were genotyped on the 90K Brassica assay (42,914 SNPs), which led to the identification of sixteen candidate genes for Rlm6. Brassica species are at high risk of severe crop loss due to pathogens, especially Leptosphaeria maculans (the causal agent of blackleg). Brassica juncea (L.) Czern is an important germplasm resource for canola improvement, due to its good agronomic traits, such as heat and drought tolerance and high blackleg resistance. The present study is the first using genome-wide association studies to identify candidate genes for blackleg resistance in B. juncea based on genome-wide SNPs obtained from the Illumina Infinium 90 K Brassica SNP array. The verification of Rlm6 in B. juncea was performed through a cotyledon infection test. Genotyping 42,914 single nucleotide polymorphisms (SNPs) in a panel of 167 B. juncea lines revealed a total of seven SNPs significantly associated with Rlm6 on chromosomes A07 and B04 in B. juncea. Furthermore, 16 candidate Rlm6 genes were found in these regions, defined as nucleotide binding site leucine-rich-repeat (NLR), leucine-rich repeat RLK (LRR-RLK) and LRR-RLP genes. This study will give insights into the blackleg resistance in B. juncea and facilitate identification of functional blackleg resistance genes which can be used in Brassica breeding.
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Affiliation(s)
- Hua Yang
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD, Australia
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | | | | | - Philipp E Bayer
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Ting Xiang Neik
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Anita A Severn-Ellis
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Aneeta Pradhan
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Soodeh Tirnaz
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia.
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139
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Genome-wide association studies: assessing trait characteristics in model and crop plants. Cell Mol Life Sci 2021; 78:5743-5754. [PMID: 34196733 PMCID: PMC8316211 DOI: 10.1007/s00018-021-03868-w] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 05/28/2021] [Accepted: 05/29/2021] [Indexed: 01/19/2023]
Abstract
GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.
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140
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Chen C, D'Alessandro E, Murani E, Zheng Y, Giosa D, Yang N, Wang X, Gao B, Li K, Wimmers K, Song C. SINE jumping contributes to large-scale polymorphisms in the pig genomes. Mob DNA 2021; 12:17. [PMID: 34183049 PMCID: PMC8240389 DOI: 10.1186/s13100-021-00246-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 06/09/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Molecular markers based on retrotransposon insertion polymorphisms (RIPs) have been developed and are widely used in plants and animals. Short interspersed nuclear elements (SINEs) exert wide impacts on gene activity and even on phenotypes. However, SINE RIP profiles in livestock remain largely unknown, and not be revealed in pigs. RESULTS Our data revealed that SINEA1 displayed the most polymorphic insertions (22.5 % intragenic and 26.5 % intergenic), followed by SINEA2 (10.5 % intragenic and 9 % intergenic) and SINEA3 (12.5 % intragenic and 5.0 % intergenic). We developed a genome-wide SINE RIP mining protocol and obtained a large number of SINE RIPs (36,284), with over 80 % accuracy and an even distribution in chromosomes (14.5/Mb), and 74.34 % of SINE RIPs generated by SINEA1 element. Over 65 % of pig SINE RIPs overlap with genes, most of them (> 95 %) are in introns. Overall, about one forth (23.09 %) of the total genes contain SINE RIPs. Significant biases of SINE RIPs in the transcripts of protein coding genes were observed. Nearly half of the RIPs are common in these pig breeds. Sixteen SINE RIPs were applied for population genetic analysis in 23 pig breeds, the phylogeny tree and cluster analysis were generally consistent with the geographical distributions of native pig breeds in China. CONCLUSIONS Our analysis revealed that SINEA1-3 elements, particularly SINEA1, are high polymorphic across different pig breeds, and generate large-scale structural variations in the pig genomes. And over 35,000 SINE RIP markers were obtained. These data indicate that young SINE elements play important roles in creating new genetic variations and shaping the evolution of pig genome, and also provide strong evidences to support the great potential of SINE RIPs as genetic markers, which can be used for population genetic analysis and quantitative trait locus (QTL) mapping in pig.
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Affiliation(s)
- Cai Chen
- College of Animal Science & Technology, Yangzhou University, 225009, Yangzhou, Jiangsu, China
| | - Enrico D'Alessandro
- Department of Veterinary Science, University of Messina, 98168, Messina, Italy
| | - Eduard Murani
- Leibniz Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Yao Zheng
- College of Animal Science & Technology, Yangzhou University, 225009, Yangzhou, Jiangsu, China
| | - Domenico Giosa
- Department of Clinical and Experimental Medicine, University Hospital of Messina, 98125, Messina, Italy
| | - Naisu Yang
- College of Animal Science & Technology, Yangzhou University, 225009, Yangzhou, Jiangsu, China
| | - Xiaoyan Wang
- College of Animal Science & Technology, Yangzhou University, 225009, Yangzhou, Jiangsu, China
| | - Bo Gao
- College of Animal Science & Technology, Yangzhou University, 225009, Yangzhou, Jiangsu, China
| | - Kui Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, 100193, Beijing, China
| | - Klaus Wimmers
- Leibniz Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Chengyi Song
- College of Animal Science & Technology, Yangzhou University, 225009, Yangzhou, Jiangsu, China.
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141
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Lam KK, Thean LF, Cheah PY. Advances in colorectal cancer genomics and transcriptomics drive early detection and prevention. Int J Biochem Cell Biol 2021; 137:106032. [PMID: 34182137 DOI: 10.1016/j.biocel.2021.106032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 06/17/2021] [Accepted: 06/23/2021] [Indexed: 12/20/2022]
Abstract
Colorectal carcinoma (CRC) is a high incidence cancer and leading cause of cancer mortality worldwide. The advances in genomics and transcriptomics in the past decades have improved the detection and prevention of CRC in familial CRC syndromes. Nevertheless, the ultimate goal of personalized medicine for sporadic CRC is still not within reach due no less to the difficulty in integrating population disparity and clinical data to combat what essentially is a very heterogenous disease. This minireview highlights the achievement of the past decades and present possible direction in the hope of early detection and metastasis prevention for reducing CRC-associated morbidity and mortality.
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Affiliation(s)
- Kuen Kuen Lam
- Department of Colorectal Surgery, Singapore General Hospital, Singapore, Singapore
| | - Lai Fun Thean
- Department of Colorectal Surgery, Singapore General Hospital, Singapore, Singapore
| | - Peh Yean Cheah
- Department of Colorectal Surgery, Singapore General Hospital, Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore; Duke-NUS Medical School, National University of Singapore, Singapore.
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Waller RG, Klein RJ, Vijai J, McKay JD, Clay-Gilmour A, Wei X, Madsen MJ, Sborov DW, Curtin K, Slager SL, Offit K, Vachon CM, Lipkin SM, Dumontet C, Camp NJ. Sequencing at lymphoid neoplasm susceptibility loci maps six myeloma risk genes. Hum Mol Genet 2021; 30:1142-1153. [PMID: 33751038 PMCID: PMC8188404 DOI: 10.1093/hmg/ddab066] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 11/14/2022] Open
Abstract
Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS single nucleotide polymorphisms in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, seven of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (P = 1.0 × 10-6), EOMES (P = 6.0 × 10-6) and BTNL2 (P = 2.1 × 10-3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.
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MESH Headings
- Acyl-CoA Oxidase/genetics
- Butyrophilins/genetics
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Hodgkin Disease/genetics
- Hodgkin Disease/pathology
- Humans
- Interferon Regulatory Factors/genetics
- Leukemia, Lymphocytic, Chronic, B-Cell/genetics
- Leukemia, Lymphocytic, Chronic, B-Cell/pathology
- Lymphocytes/pathology
- Lymphoma, Follicular/genetics
- Lymphoma, Follicular/pathology
- Lymphoma, Large B-Cell, Diffuse/genetics
- Lymphoma, Large B-Cell, Diffuse/pathology
- Male
- Multiple Myeloma/genetics
- Multiple Myeloma/pathology
- Polymorphism, Single Nucleotide/genetics
- Risk Factors
- T-Box Domain Proteins/genetics
- Tetraspanins/genetics
- Transmembrane Activator and CAML Interactor Protein/genetics
- Exome Sequencing
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Affiliation(s)
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Icahn Institute for Data Science and Genomic Technology, New York, NY 10029-5674, USA
| | - Joseph Vijai
- Department of Medicine, Clinical Genetics Service, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - James D McKay
- Genetic Cancer Susceptibility, International Agency for Research on Cancer, 69372 Lyon Cedex 08, France
| | - Alyssa Clay-Gilmour
- Department of Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Xiaomu Wei
- Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Michael J Madsen
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Douglas W Sborov
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Karen Curtin
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Susan L Slager
- Department of Health Sciences, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
| | - Kenneth Offit
- Department of Medicine, Clinical Genetics Service, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Celine M Vachon
- Department of Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Steven M Lipkin
- Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Charles Dumontet
- INSERM 1052, CNRS 5286, University of Lyon, 69361 Lyon Cedex 07, France
| | - Nicola J Camp
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
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143
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Rare variants regulate expression of nearby individual genes in multiple tissues. PLoS Genet 2021; 17:e1009596. [PMID: 34061836 PMCID: PMC8195400 DOI: 10.1371/journal.pgen.1009596] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 06/11/2021] [Accepted: 05/11/2021] [Indexed: 12/30/2022] Open
Abstract
The rapid decrease in sequencing cost has enabled genetic studies to discover rare variants associated with complex diseases and traits. Once this association is identified, the next step is to understand the genetic mechanism of rare variants on how the variants influence diseases. Similar to the hypothesis of common variants, rare variants may affect diseases by regulating gene expression, and recently, several studies have identified the effects of rare variants on gene expression using heritability and expression outlier analyses. However, identifying individual genes whose expression is regulated by rare variants has been challenging due to the relatively small sample size of expression quantitative trait loci studies and statistical approaches not optimized to detect the effects of rare variants. In this study, we analyze whole-genome sequencing and RNA-seq data of 681 European individuals collected for the Genotype-Tissue Expression (GTEx) project (v8) to identify individual genes in 49 human tissues whose expression is regulated by rare variants. To improve statistical power, we develop an approach based on a likelihood ratio test that combines effects of multiple rare variants in a nonlinear manner and has higher power than previous approaches. Using GTEx data, we identify many genes regulated by rare variants, and some of them are only regulated by rare variants and not by common variants. We also find that genes regulated by rare variants are enriched for expression outliers and disease-causing genes. These results suggest the regulatory effects of rare variants, which would be important in interpreting associations of rare variants with complex traits. It has been shown that rare variants may affect many diseases including both rare and common diseases with the advent of next-generation sequencing technology. An important question is how rare variants affect diseases or traits, especially whether or how they regulate gene expression as they may affect diseases through gene regulation. However, it is challenging to identify the regulatory effects of rare variants because it often requires large sample sizes and the existing statistical approaches are not optimized for it. Here, we develop a novel method, LRT-q, based on a likelihood ratio test that aggregates the effects of multiple rare variants nonlinearly to achieve higher statistical power than previous rare variant association methods. We apply LRT-q to the latest GTEx v8 dataset and identify regulatory effect of rare variants on individual genes. We also observe that genes regulated by rare variants are likely to be disease-causing genes. These results demonstrate the functional effects of rare variants, especially on gene expression, which provides important biological insights in understanding the genetic mechanism of rare variants in complex traits and diseases.
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144
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Childhood risk factors for adulthood chronic kidney disease. Pediatr Nephrol 2021; 36:1387-1396. [PMID: 32500249 DOI: 10.1007/s00467-020-04611-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 04/03/2020] [Accepted: 05/11/2020] [Indexed: 12/25/2022]
Abstract
Chronic kidney disease (CKD) is a major public health challenge, affecting as much as 8 to 18% of the world population. Identifying childhood risk factors for future CKD may help clinicians make early diagnoses and initiation of preventive interventions for CKD and its attendant comorbidities as well as monitoring for complications. The purpose of this review is to describe childhood risk factors that may predict development of overt kidney disease later in life. Currently, there are multiple childhood risk factors associated with future onset and progression of CKD. These risk factors can be grouped into five categories: genetic factors (e.g., monogenic or risk alleles), perinatal factors (e.g., low birth weight and prematurity), childhood kidney diseases (e.g., congenital anomalies, glomerular diseases, and renal cystic ciliopathies), childhood onset of chronic conditions (e.g., cancer, diabetes, hypertension, dyslipidemia, and obesity), and different lifestyle factors (e.g., physical activity, diet, and factors related to socioeconomic status). The available published information suggests that the lifelong risk for CKD can be attributed to multiple factors that appear already during childhood. However, results are conflicting on the effects of childhood physical activity, diet, and dyslipidemia on future renal function. On the other hand, there is consistent evidence to support follow-up of high-risk groups.
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145
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Tang H, He Z. Advances and challenges in quantitative delineation of the genetic architecture of complex traits. QUANTITATIVE BIOLOGY 2021; 9:168-184. [PMID: 35492964 PMCID: PMC9053444 DOI: 10.15302/j-qb-021-0249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Genome-wide association studies (GWAS) have been widely adopted in studies of human complex traits and diseases. Results This review surveys areas of active research: quantifying and partitioning trait heritability, fine mapping functional variants and integrative analysis, genetic risk prediction of phenotypes, and the analysis of sequencing studies that have identified millions of rare variants. Current challenges and opportunities are highlighted. Conclusion GWAS have fundamentally transformed the field of human complex trait genetics. Novel statistical and computational methods have expanded the scope of GWAS and have provided valuable insights on the genetic architecture underlying complex phenotypes.
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Affiliation(s)
- Hua Tang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA 94305, USA
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146
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Zeng P, Shao Z, Zhou X. Statistical methods for mediation analysis in the era of high-throughput genomics: Current successes and future challenges. Comput Struct Biotechnol J 2021; 19:3209-3224. [PMID: 34141140 PMCID: PMC8187160 DOI: 10.1016/j.csbj.2021.05.042] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 05/21/2021] [Accepted: 05/21/2021] [Indexed: 12/12/2022] Open
Abstract
Mediation analysis investigates the intermediate mechanism through which an exposure exerts its influence on the outcome of interest. Mediation analysis is becoming increasingly popular in high-throughput genomics studies where a common goal is to identify molecular-level traits, such as gene expression or methylation, which actively mediate the genetic or environmental effects on the outcome. Mediation analysis in genomics studies is particularly challenging, however, thanks to the large number of potential mediators measured in these studies as well as the composite null nature of the mediation effect hypothesis. Indeed, while the standard univariate and multivariate mediation methods have been well-established for analyzing one or multiple mediators, they are not well-suited for genomics studies with a large number of mediators and often yield conservative p-values and limited power. Consequently, over the past few years many new high-dimensional mediation methods have been developed for analyzing the large number of potential mediators collected in high-throughput genomics studies. In this work, we present a thorough review of these important recent methodological advances in high-dimensional mediation analysis. Specifically, we describe in detail more than ten high-dimensional mediation methods, focusing on their motivations, basic modeling ideas, specific modeling assumptions, practical successes, methodological limitations, as well as future directions. We hope our review will serve as a useful guidance for statisticians and computational biologists who develop methods of high-dimensional mediation analysis as well as for analysts who apply mediation methods to high-throughput genomics studies.
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Affiliation(s)
- Ping Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
- Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Zhonghe Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor 48109, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor 48109, MI, USA
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147
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A genetic polymorphism that is associated with mitochondrial energy metabolism increases risk of fibromyalgia. Pain 2021; 161:2860-2871. [PMID: 32658146 DOI: 10.1097/j.pain.0000000000001996] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Alterations in cellular energy metabolism have been implicated in chronic pain, suggesting a role for mitochondrial DNA. Previous studies reported associations of a limited number of mitochondrial DNA polymorphisms with specific pain conditions. In this study, we examined the full mitochondrial genomes of people with a variety of chronic pain conditions. A discovery cohort consisting of 609 participants either with or without a complex persistent pain conditions (CPPCs) was examined. Mitochondrial DNA was subjected to deep sequencing for identification of rare mutations, common variants, haplogroups, and heteroplasmy associated with 5 CPPCs: episodic migraine, irritable bowel syndrome, fibromyalgia, vulvar vestibulitis, or temporomandibular disorders. The strongest association found was the presence of the C allele at the single nucleotide polymorphism m.2352T>C (rs28358579) that significantly increased the risk for fibromyalgia (odds ratio [OR] = 4.6, P = 4.3 × 10). This relationship was even stronger in women (OR = 5.1, P = 2.8 × 10), and m.2352T>C was associated with all other CPPCs in a consistent risk-increasing fashion. This finding was replicated in another cohort (OR = 4.3, P = 2.6 × 10) of the Orofacial Pain: Prospective Evaluation and Risk Assessment study consisting of 1754 female participants. To gain insight into the cellular consequences of the associated genetic variability, we conducted an assay testing metabolic reprogramming in human cell lines with defined genotypes. The minor allele C was associated with decreased mitochondrial membrane potential under conditions where oxidative phosphorylation is required, indicating a role of oxidative phosphorylation in pathophysiology of chronic pain. Our results suggest that cellular energy metabolism, modulated by m.2352T>C, contributes to fibromyalgia and possibly other chronic pain conditions.
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148
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Yan Y, Martinez R, Rasheed MN, Cahal J, Xu Z, Rui Y, Qualmann KJ, Hagan JP, Kim DH. Germline and somatic mutations in the pathology of pineal cyst: A whole-exome sequencing study of 93 individuals. Mol Genet Genomic Med 2021; 9:e1691. [PMID: 33943042 PMCID: PMC8222845 DOI: 10.1002/mgg3.1691] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 03/29/2021] [Accepted: 04/09/2021] [Indexed: 11/10/2022] Open
Abstract
Background Pineal cyst is a benign lesion commonly occurring in people of any age. Until now, the underlying molecular alterations have not been explored. Methods We performed whole exome sequencing of 93 germline samples and 21 pineal cyst tissue samples to illustrate its genetic architecture and somatic mutations. The dominant and recessive inheritance modes were considered, and a probability was calculated to evaluate the significance of variant overrepresentation. Results By analyzing pineal cyst as a Mendelian disease with a dominant inheritance pattern, we identified 42,325 rare germline variants, and NM_001004711.1:c.476A>G was highly enriched (FDR<0.2). By analyzing it as a recessive disorder, we identified 753 homozygous rare variants detected in at least one pineal cyst sample each. One STIM2 rare variant, NM_001169117.1:c.1652C>T, was overrepresented (FDR<0.05). Analyzing at a gene‐based level, we identified a list of the most commonlymutated germline genes, including POP4, GNGT2 and TMEM254. A somatic mutation analysis of 21 samples identified 16 variants in 15 genes, which mainly participated in the biological processes of gene expression and epigenetic regulation, immune response modulation, and transferase activity. Conclusion These molecular profiles are novel for this condition and provide data for investigators interested in pineal cysts.
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Affiliation(s)
- Yuanqing Yan
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Rebecca Martinez
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Maria N Rasheed
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joshua Cahal
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Zhen Xu
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yanning Rui
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Krista J Qualmann
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - John P Hagan
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dong H Kim
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Memorial Hermann Hospital, Mischer Neuroscience Institute, Houston, TX, USA
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149
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Secolin R, de Araujo TK, Gonsales MC, Rocha CS, Naslavsky M, Marco LD, Bicalho MAC, Vazquez VL, Zatz M, Silva WA, Lopes-Cendes I. Genetic variability in COVID-19-related genes in the Brazilian population. Hum Genome Var 2021; 8:15. [PMID: 33824725 PMCID: PMC8017521 DOI: 10.1038/s41439-021-00146-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 02/15/2021] [Accepted: 02/15/2021] [Indexed: 12/13/2022] Open
Abstract
SARS-CoV-2 utilizes the angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane serine protease (TMPRSS2) to infect human lung cells. Previous studies have suggested that different host ACE2 and TMPRSS2 genetic backgrounds might contribute to differences in the rate of SARS-CoV-2 infection or COVID-19 severity. Recent studies have also shown that variants in 15 genes related to type I interferon immunity to influenza virus might predispose patients toward life-threatening COVID-19 pneumonia. Other genes (SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, IL6, CTSL, ABO, and FURIN) and HLA alleles have also been implicated in the response to infection with SARS-CoV-2. Currently, Brazil has recorded the third-highest number of COVID-19 cases worldwide. We aimed to investigate the genetic variation present in COVID-19-related genes in the Brazilian population. We analyzed 27 candidate genes and HLA alleles in 954 admixed Brazilian exomes. We used the information available in two public databases (http://www.bipmed.org and http://abraom.ib.usp.br/) and additional exomes from individuals born in southeast Brazil, the region of the country with the highest number of COVID-19 patients. Variant allele frequencies were compared with the 1000 Genomes Project phase 3 (1KGP) and gnomAD databases. We detected 395 nonsynonymous variants; of these, 325 were also found in the 1KGP and/or gnomAD. Six of these variants were previously reported to influence the rate of infection or clinical prognosis of COVID-19. The remaining 70 variants were identified exclusively in the Brazilian sample, with a mean allele frequency of 0.0025. In silico analysis revealed that seven of these variants are predicted to affect protein function. Furthermore, we identified HLA alleles previously associated with the COVID-19 response at loci DQB1 and DRB1. Our results showed genetic variability common to other populations and rare and ultrarare variants exclusively found in the Brazilian population. These findings might lead to differences in the rate of infection or response to infection by SARS-CoV-2 and should be further investigated in patients with this disease. Genetic variants in the Brazilian population do not appear to explain the relatively high overall rates of COVID-19 cases compared to other countries, but could be relevant for risk assessment at the individual level. Iscia Lopes-Cendes of the University of Campinas and colleagues in Brazil examined gene sequences for variations in 27 genes reported to influence COVID-19 infection in Brazilians of mixed heritage and of people born in the southeast where case numbers are high. These studies included the ACE2 gene that codes for a receptor allowing SARS-CoV-2 to enter host cells. Genetic variants were also identified in two international genome databases. Seventy variants were unique to Brazilians, but computer modeling predicted only seven variants that could affect protein function. The team also looked for and found variants that could affect individual immunity to COVID-19. Similar genetic studies could help identify at-risk individuals and therapeutic targets.
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Affiliation(s)
- Rodrigo Secolin
- Department of Translational Medicine, University of Campinas (UNICAMP), and The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, SP Brazil
| | - Tânia K de Araujo
- Department of Translational Medicine, University of Campinas (UNICAMP), and The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, SP Brazil
| | - Marina C Gonsales
- Department of Translational Medicine, University of Campinas (UNICAMP), and The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, SP Brazil
| | - Cristiane S Rocha
- Department of Translational Medicine, University of Campinas (UNICAMP), and The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, SP Brazil
| | - Michel Naslavsky
- Departament of Genetics and Evolutive Biology, Institute of Bioscience, University of São Paulo, (USP) and The Human Genome and Stem Cell Research Center, São Paulo, SP Brazil
| | - Luiz De Marco
- Department of Surgery, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG Brazil
| | - Maria A C Bicalho
- Department of Clinical Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG Brazil
| | - Vinicius L Vazquez
- Molecular Oncology Research Center (CPOM), Barretos Cancer Hospital, Barretos, SP Brazil
| | - Mayana Zatz
- Departament of Genetics and Evolutive Biology, Institute of Bioscience, University of São Paulo, (USP) and The Human Genome and Stem Cell Research Center, São Paulo, SP Brazil
| | - Wilson A Silva
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo at Ribeirão Preto (USP), Ribeirão Preto, SP Brazil
| | - Iscia Lopes-Cendes
- Department of Translational Medicine, University of Campinas (UNICAMP), and The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, SP Brazil
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150
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Kristan A, Gašperšič J, Režen T, Kunej T, Količ R, Vuga A, Fink M, Žula Š, Anžej Doma S, Preložnik Zupan I, Pajič T, Podgornik H, Debeljak N. Genetic analysis of 39 erythrocytosis and hereditary hemochromatosis-associated genes in the Slovenian family with idiopathic erythrocytosis. J Clin Lab Anal 2021; 35:e23715. [PMID: 33534944 PMCID: PMC8059723 DOI: 10.1002/jcla.23715] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/10/2020] [Accepted: 01/15/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Erythrocytosis is a condition with an excessive number of erythrocytes, accompanied by an elevated haemoglobin and/or haematocrit value. Congenital erythrocytosis has a diverse genetic background with several genes involved in erythropoiesis. In clinical practice, nine genes are usually examined, but in approximately 70% of patients, no causative mutation can be identified. In this study, we screened 39 genes, aiming to identify potential disease-driving variants in the family with erythrocytosis of unknown cause. PATIENTS AND METHODS Two affected family members with elevated haemoglobin and/or haematocrit and negative for acquired causes and one healthy relative from the same family were selected for molecular-genetic analysis of 24 erythrocytosis and 15 hereditary haemochromatosis-associated genes with targeted NGS. The identified variants were further analysed for pathogenicity using various bioinformatic tools and review of the literature. RESULTS Of the 12 identified variants, two heterozygous variants, the missense variant c.471G>C (NM_022051.2) (p.(Gln157His)) in the EGLN1 gene and the intron variant c.2572-13A>G (NM_004972.3) in the JAK2 gene, were classified as low-frequency variants in European population. None of the two variants were present in a healthy family member. Variant c.2572-13A>G has potential impact on splicing by one prediction tool. CONCLUSION For the first time, we included 39 genes in the erythrocytosis clinical panel and identified two potential disease-driving variants in the Slovene family studied. Based on the reported functional in vitro studies combined with our bioinformatics analysis, we suggest further functional analysis of variant in the JAK2 gene and evaluation of a cumulative effect of both variants.
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Affiliation(s)
- Aleša Kristan
- Medical Centre for Molecular BiologyFaculty of MedicineInstitute of Biochemistry and Molecular GeneticsUniversity of LjubljanaLjubljanaSlovenia
| | - Jernej Gašperšič
- Medical Centre for Molecular BiologyFaculty of MedicineInstitute of Biochemistry and Molecular GeneticsUniversity of LjubljanaLjubljanaSlovenia
| | - Tadeja Režen
- Centre for Functional Genomics and Bio‐ChipsFaculty of MedicineInstitute of Biochemistry and Molecular GeneticsUniversity of LjubljanaLjubljanaSlovenia
| | - Tanja Kunej
- Department of Animal ScienceBiotechnical FacultyUniversity of LjubljanaLjubljanaSlovenia
| | - Rok Količ
- Kemomed Research and DevelopmentKemomed LtdKranjSlovenia
| | - Andrej Vuga
- Kemomed Research and DevelopmentKemomed LtdKranjSlovenia
| | - Martina Fink
- Clinical Department of HaematologyUniversity Medical Centre LjubljanaLjubljanaSlovenia
| | - Špela Žula
- Clinical Department of HaematologyUniversity Medical Centre LjubljanaLjubljanaSlovenia
| | - Saša Anžej Doma
- Clinical Department of HaematologyUniversity Medical Centre LjubljanaLjubljanaSlovenia
| | - Irena Preložnik Zupan
- Clinical Department of HaematologyUniversity Medical Centre LjubljanaLjubljanaSlovenia
- Department of Internal MedicineFaculty of MedicineUniversity of LjubljanaLjubljanaSlovenia
| | - Tadej Pajič
- Clinical Department of HaematologyUniversity Medical Centre LjubljanaLjubljanaSlovenia
- Clinical Institute of Genomic MedicineUniversity Medical Centre LjubljanaLjubljanaSlovenia
| | - Helena Podgornik
- Clinical Department of HaematologyUniversity Medical Centre LjubljanaLjubljanaSlovenia
- Chair of Clinical BiochemistryFaculty of PharmacyUniversity of LjubljanaLjubljanaSlovenia
| | - Nataša Debeljak
- Medical Centre for Molecular BiologyFaculty of MedicineInstitute of Biochemistry and Molecular GeneticsUniversity of LjubljanaLjubljanaSlovenia
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