1
|
Chybowska AD, Bernabeu E, Yousefi P, Suderman M, Hillary RF, Clark R, MacGillivray L, Murphy L, Harris SE, Corley J, Campbell A, Spires-Jones TL, McCartney DL, Cox SR, Price JF, Evans KL, Marioni RE. A blood- and brain-based EWAS of smoking. Nat Commun 2025; 16:3210. [PMID: 40180905 PMCID: PMC11968855 DOI: 10.1038/s41467-025-58357-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 03/18/2025] [Indexed: 04/05/2025] Open
Abstract
DNA methylation offers an objective method to assess the impact of smoking. In this work, we conduct a Bayesian EWAS of smoking pack years (n = 17,865, ~850k sites, Illumina EPIC array) and extend it by analysing whole genome data of smokers and non-smokers from Generation Scotland (n = 46, ~4-21 million sites via TWIST and Oxford Nanopore sequencing). We develop mCigarette, an epigenetic biomarker of smoking, and test it in two British cohorts. Results of brain- and blood-based EWAS (nbrain=14, nblood = 882, >450k sites, Illumina arrays) reveal several loci with near-perfect discrimination of smoking status, but which do not overlap across tissues. Furthermore, we perform a GWAS of epigenetic smoking, identifying several smoking-related loci. Overall, we improve smoking-related biomarker accuracy and enhance the understanding of the effects of smoking by integrating DNA methylation data from multiple tissues and cohorts.
Collapse
Affiliation(s)
- Aleksandra D Chybowska
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Paul Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, BS8 2BN, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, BS8 2BN, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Richard Clark
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Louise MacGillivray
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Usher Institute, University of Edinburgh, 5-7 Little France Road, Edinburgh, EH16 4UX, UK
| | - Tara L Spires-Jones
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Jackie F Price
- Usher Institute, University of Edinburgh, 5-7 Little France Road, Edinburgh, EH16 4UX, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| |
Collapse
|
2
|
Wang R, Zhu XY, Wang Y. Knowledge graph and frontier trends in melanoma-associated ncRNAs: a bibliometric analysis from 2006 to 2023. Front Oncol 2024; 14:1439324. [PMID: 39659781 PMCID: PMC11628868 DOI: 10.3389/fonc.2024.1439324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 09/24/2024] [Indexed: 12/12/2024] Open
Abstract
Objectives Malignant melanoma (MM) is a highly malignant skin tumor. Although research on non-coding RNAs (ncRNAs) of MM has advanced swiftly in recent years, no specific bibliometric analyses have been conducted on this topic. The present study aims to summarize the knowledge graphs and frontier trends and to provide new perspectives and direction of collaboration for researchers. Method Research data on melanoma and ncRNA published from January 1, 2006 to October 9, 2023 were retrieved and extracted from Web of Science. R Studio (Version 4.3.1), Scimago Graphica (Version 1.0.36), VOSviewer version (1.6.19), and Citespace (6.2.4R) were used to analyze the publications, countries, journals, institutions, authors, keywords, references, and other relevant data and to build collaboration network graphs and co-occurrence network graphs accordingly. Results A total of 1,222 articles were retrieved, involving 4,894 authors, 385 journals, 43,220 references, 2413 keywords, and 1,651 institutions in 47 countries. The average annual growth rate in the number of articles was 25.02% from 2006 to 2023; among all the journals, Plos One had the highest number of publications and citations, which are 42 publications and 2,228 citations, respectively. Chinese researchers were the most prolific publishers in this field, having published a total of 657 articles, among which 42 were published by Shanghai Jiao Tong University, which was the most productive institution. In recent years, the most explored keywords included long non-coding RNAs, immunotherapy, and exosm. According to the timeline chart of reference co-citation, "functional role" has been the most explored hotspot since 2015, and human cancer is a newly emerged hotspot after 2021. Conclusion Through a bibliometric analysis, this study included all publications on ncRNAs and melanoma that were published in English from 2006 to 2023 in Web of Science to analyze the trends in the number of publications, international research focuses, and the direction of collaboration. The results of this study may provide information on knowledge graph, frontier trends and identify research topics in melanoma. More current research proved that ncRNA plays a crucial role in the biological behavior of melanoma including proliferation, invasion, metastasis, drug resistance, etc. With the development of research on ncRNA and melanoma, ncRNA may great potential in development of early diagnosis, targeted therapy and efficacy evaluation in the future. The results of this study also provide new perspectives and research partners for researchers in this field.
Collapse
Affiliation(s)
- Ru Wang
- Department of Pediatrics, Xinzhou District People’s Hospital, Wuhan, Hubei, China
| | - Xiao-yan Zhu
- Sanquan College of Xinxiang Medical University, Xinxiang, Henan, China
| | - Yi Wang
- The Fifth People’s Hospital of Hainan Province, Affiliated Dermatology Hospital of Hainan Medical University, Haikou, Hainan, China
- The Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| |
Collapse
|
3
|
Thakur R, Xu M, Sowards H, Yon J, Jessop L, Myers T, Zhang T, Chari R, Long E, Rehling T, Hennessey R, Funderburk K, Yin J, Machiela MJ, Johnson ME, Wells AD, Chesi A, Grant SF, Iles MM, Landi MT, Law MH, Choi J, Brown KM. Mapping chromatin interactions at melanoma susceptibility loci and cell-type specific dataset integration uncovers distant gene targets of cis-regulation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.11.14.24317204. [PMID: 39802764 PMCID: PMC11722502 DOI: 10.1101/2024.11.14.24317204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/31/2025]
Abstract
Genome-wide association studies (GWAS) of melanoma risk have identified 68 independent signals at 54 loci. For most loci, specific functional variants and their respective target genes remain to be established. Capture-HiC is an assay that links fine-mapped risk variants to candidate target genes by comprehensively mapping cell-type specific chromatin interactions. We performed a melanoma GWAS region-focused capture-HiC assay in human primary melanocytes to identify physical interactions between fine-mapped risk variants and potential causal melanoma susceptibility genes. Overall, chromatin interaction data alone nominated potential causal genes for 61 of the 68 melanoma risk signals, identifying many candidates beyond those reported by previous studies. We further integrated these data with cell-type specific epigenomic (chromatin state, accessibility), gene expression (eQTL/TWAS), DNA methylation (meQTL/MWAS), and massively parallel reporter assay (MPRA) data to prioritize potentially cis-regulatory variants and their respective candidate gene targets. From the set of fine-mapped variants across these loci, we identified 140 prioritized candidate causal variants linked to 195 candidate genes at 42 risk signals. In addition, we developed an integrative scoring system to facilitate candidate gene prioritization, integrating melanocyte and melanoma datasets. Notably, at several GWAS risk signals we observed long-range chromatin connections (500 kb to >1 Mb) with distant candidate target genes. We validated several such cis-regulatory interactions using CRISPR inhibition, providing evidence for known cancer driver genes MDM4 and CBL, as well as the SRY-box transcription factor SOX4, as likely melanoma risk genes.
Collapse
Affiliation(s)
- Rohit Thakur
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Mai Xu
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Hayley Sowards
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Joshuah Yon
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Lea Jessop
- Laboratory of Genomic Susceptibility, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Timothy Myers
- Laboratory of Genomic Susceptibility, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Tongwu Zhang
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Raj Chari
- Genome Modification Core, Frederick National Lab for Cancer Research, Frederick, MD, USA
| | - Erping Long
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China
| | - Thomas Rehling
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Rebecca Hennessey
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Karen Funderburk
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jinhu Yin
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Mitchell J. Machiela
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Matthew E. Johnson
- Division of Human Genetics, Children’s Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Mark M. Iles
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Maria Teresa Landi
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Matthew H. Law
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
- School of Biomedical Sciences, University fo Queensland, Brisbane, QLD, Australia
| | | | - Jiyeon Choi
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kevin M. Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| |
Collapse
|
4
|
Lin S, Shen R, Huang J, Liu Y, Li H, Xu Q. Identification of genomic-wide genetic links between cutaneous melanoma and obesity-related physical traits via cFDR. Genes Genomics 2023; 45:1549-1562. [PMID: 37768517 DOI: 10.1007/s13258-023-01446-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023]
Abstract
BACKGROUND Both epidemiological and clinical studies have suggested the comorbidity between cutaneous melanoma (CM) and obesity-related physical traits. However, it remains unclear about their shared genetic architecture. OBJECTIVE To determine the shared genetic architecture between CM and obesity-related physical traits through conditional false discovery rate (cFDR) analysis. METHOD Quantile-quantile plots were firstly built to assess the pleiotropic enrichment of shared single nucleotide polymorphisms between CM and each trait. Then, cFDR and conjunctional cFDR (ccFDR) were used to identify the shared risk loci between CM and each trait. Moreover, the functional evaluation of shared risk genes was carried out through analyses of expression quantitative trait loci (eQTL), Kyoto Encyclopedia of Genes and Genomes and gene ontology, respectively. Finally, single-cell sequence analysis was performed to locate the expression of eQTL-mapped genes in tissues. RESULTS Successive pleiotropic enrichment was found between CM and 5 obesity-related traits or height. 24 shared risk loci were identified between CM and 13 traits except appendicular lean mass using ccFDR analysis, with 17 novel and 4 validated loci. The functions of ccFDR-identified and eQTL-mapped genes were revealed to be mainly involved in cellular senescence, proliferation, meiotic nuclear division, cell cycle, and the metabolism of lipid, cholesterol and glucose. Single-cell sequence analysis showed that keratinocytes contribute to the occurrence and aggressiveness of CM through secreting paracrine cytokines. CONCLUSION Our findings demonstrate the significant genetic correlation between CM and obesity-related physical traits, which may provide a novel genetical basis for the pathogenesis and treatment of CM.
Collapse
Affiliation(s)
- Shen Lin
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Runnan Shen
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Jingqian Huang
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yanhan Liu
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Hongpeng Li
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Qingfang Xu
- Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| |
Collapse
|
5
|
Natarelli N, Boby A, Aflatooni S, Tran JT, Diaz MJ, Taneja K, Forouzandeh M. Regulatory miRNAs and lncRNAs in Skin Cancer: A Narrative Review. Life (Basel) 2023; 13:1696. [PMID: 37629553 PMCID: PMC10455148 DOI: 10.3390/life13081696] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 07/26/2023] [Accepted: 07/28/2023] [Indexed: 08/27/2023] Open
Abstract
Non-coding RNAs (ncRNAs) have a significant regulatory role in the pathogenesis of skin cancer, despite the fact that protein-coding genes have generally been the focus of research efforts in the field. We comment on the actions of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) in the current review with an eye toward potential therapeutic treatments. LncRNAs are remarkably adaptable, acting as scaffolding, guides, or decoys to modify key signaling pathways (i.e., the Wnt/β-catenin pathway) and gene expression. As post-transcriptional gatekeepers, miRNAs control gene expression by attaching to messenger RNAs and causing their degradation or suppression during translation. Cell cycle regulation, cellular differentiation, and immunological responses are all affected by the dysregulation of miRNAs observed in skin cancer. NcRNAs also show promise as diagnostic biomarkers and prognostic indicators. Unraveling the complexity of the regulatory networks governed by ncRNAs in skin cancer offers unprecedented opportunities for groundbreaking targeted therapies, revolutionizing the landscape of dermatologic care.
Collapse
Affiliation(s)
- Nicole Natarelli
- Morsani College of Medicine, University of South Florida, Tampa, FL 33602, USA
| | - Aleena Boby
- Morsani College of Medicine, University of South Florida, Tampa, FL 33602, USA
| | - Shaliz Aflatooni
- Morsani College of Medicine, University of South Florida, Tampa, FL 33602, USA
| | - Jasmine Thuy Tran
- School of Medicine, University of Indiana, Indianapolis, IN 46202, USA;
| | | | - Kamil Taneja
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | - Mahtab Forouzandeh
- Department of Dermatology, University of Florida, Gainesville, FL 32606, USA
| |
Collapse
|
6
|
Mignogna G, Carey CE, Wedow R, Baya N, Cordioli M, Pirastu N, Bellocco R, Malerbi KF, Nivard MG, Neale BM, Walters RK, Ganna A. Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci. Nat Hum Behav 2023; 7:1371-1387. [PMID: 37386106 PMCID: PMC10444625 DOI: 10.1038/s41562-023-01632-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 05/17/2023] [Indexed: 07/01/2023]
Abstract
Response to survey questionnaires is vital for social and behavioural research, and most analyses assume full and accurate response by participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behaviour across 109 questionnaire items in the UK Biobank (N = 360,628). Phenotypic factor scores for two participant-selected nonresponse answers, 'Prefer not to answer' (PNA) and 'I don't know' (IDK), each predicted participant nonresponse in follow-up surveys (incremental pseudo-R2 = 0.056), even when controlling for education and self-reported health (incremental pseudo-R2 = 0.046). After performing genome-wide association studies of our factors, PNA and IDK were highly genetically correlated with one another (rg = 0.73 (s.e. = 0.03)) and with education (rg,PNA = -0.51 (s.e. = 0.03); rg,IDK = -0.38 (s.e. = 0.02)), health (rg,PNA = 0.51 (s.e. = 0.03); rg,IDK = 0.49 (s.e. = 0.02)) and income (rg,PNA = -0.57 (s.e. = 0.04); rg,IDK = -0.46 (s.e. = 0.02)), with additional unique genetic associations observed for both PNA and IDK (P < 5 × 10-8). We discuss how these associations may bias studies of traits correlated with item nonresponse and demonstrate how this bias may substantially affect genome-wide association studies. While the UK Biobank data are deidentified, we further protected participant privacy by avoiding exploring non-response behaviour to single questions, assuring that no information can be used to associate results with any particular respondents.
Collapse
Affiliation(s)
- Gianmarco Mignogna
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Caitlin E Carey
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Robbee Wedow
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Sociology, Purdue University, West Lafayette, IN, USA.
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
- AnalytiXIN (Analytics Indiana), Indianapolis, IN, USA.
- Department of Statistics, Purdue University, West Lafayette, IN, USA.
| | - Nikolas Baya
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mattia Cordioli
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
- Fondazione Human Technopole, Viale Rita Levi-Montalcini, Milan, Italy
| | - Rino Bellocco
- Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Michel G Nivard
- Department of Biological Psychiatry, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
- Methodology Program, Amsterdam Public Health, Amsterdam, the Netherlands
- Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress and Sleep, Amsterdam, the Netherlands
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Novo Nordisk Foundation for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Raymond K Walters
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrea Ganna
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
7
|
Badré A, Pan C. Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis. PLoS Comput Biol 2023; 19:e1011211. [PMID: 37418352 DOI: 10.1371/journal.pcbi.1011211] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 05/23/2023] [Indexed: 07/09/2023] Open
Abstract
Many complex diseases share common genetic determinants and are comorbid in a population. We hypothesized that the co-occurrences of diseases and their overlapping genetic etiology can be exploited to simultaneously improve multiple diseases' polygenic risk scores (PRS). This hypothesis was tested using a multi-task learning (MTL) approach based on an explainable neural network architecture. We found that parallel estimations of the PRS for 17 prevalent cancers in a pan-cancer MTL model were generally more accurate than independent estimations for individual cancers in comparable single-task learning (STL) models. Such performance improvement conferred by positive transfer learning was also observed consistently for 60 prevalent non-cancer diseases in a pan-disease MTL model. Interpretation of the MTL models revealed significant genetic correlations between the important sets of single nucleotide polymorphisms used by the neural network for PRS estimation. This suggested a well-connected network of diseases with shared genetic basis.
Collapse
Affiliation(s)
- Adrien Badré
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Chongle Pan
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, United States of America
| |
Collapse
|
8
|
Sun F, Liu J, Wang Y, Yang H, Song D, Fu H, Feng X. BASP1 promotes high glucose-induced endothelial apoptosis in diabetes via activation of EGFR signaling. J Diabetes Investig 2023; 14:535-547. [PMID: 36756695 PMCID: PMC10034959 DOI: 10.1111/jdi.13920] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/08/2022] [Accepted: 09/19/2022] [Indexed: 02/10/2023] Open
Abstract
AIMS Diabetes mellitus is a common chronic disease of glucose metabolism. Endothelial dysfunction is an early event in diabetes complicated by cardiovascular disease. This study aimed to reveal the expression of BASP1 and its biological roles in endothelial cell dysfunction in diabetes complicated by cardiovascular disease. MATERIALS AND METHODS By analyzing the databases related to diabetes complicated with coronary heart disease, BASP1 was screened out as an upregulated gene. Human umbilical vein endothelial cells (HUVECs) and primary mouse aortic endothelial cells were treated with high glucose to establish cell models of diabetes-related endothelial dysfunction, and the expression changes of BASP1 were verified by RT-qPCR, western blot, and immunofluorescence. BASP1 was silenced or overexpressed by siRNA or overexpression plasmid, and its effects on cell migration, apoptosis, tube formation, inflammatory response, and ROS were detected. The possible signaling pathway of BASP1 was found and the mechanism of BASP1 on promoting the progression of endothelial dysfunction was explored using the EGFR inhibitor, gefitinib. RESULTS Bioinformatics analysis indicated that the expression of BASP1 in patients with diabetes mellitus and concomitant coronary heart disease was increased. High glucose induced the upregulation of BASP1 expression in endothelial cells, and showed a time-dependent relationship. Silencing of BASP1 alleviated the damage of high glucose to endothelial cells. BASP1 regulated EGFR positively. The promoting effect of BASP1 on endothelial cell apoptosis may be achieved by regulating the EGFR pathway. CONCLUSION BASP1 promotes endothelial cell injury induced by high glucose in patients with diabetes, which may be activated by activating the EGFR pathway.
Collapse
Affiliation(s)
- Fengnan Sun
- Department of Laboratory Medicine, Yantaishan Hospital, Yantai, China
| | - Junwei Liu
- Department of Laboratory Medicine, Qishan Hospital, Yantai, China
| | - Yanzheng Wang
- Department of Laboratory Medicine, Yantaishan Hospital, Yantai, China
| | - Hongmei Yang
- Department of Laboratory Medicine, Yantaishan Hospital, Yantai, China
| | - Danfeng Song
- Department of Laboratory Medicine, Yantaishan Hospital, Yantai, China
| | - Haiyan Fu
- Department of Laboratory Medicine, Yantaishan Hospital, Yantai, China
| | - Xingxing Feng
- Kunming Key Laboratory of Children Infection and Immunity, Yunnan Key Laboratory of Children's Major Disease Research, Yunnan Institute of Pediatrics, Kunming Children's Hospital, Kunming, China
| |
Collapse
|
9
|
Chat V, Dagayev S, Moran U, Snuderl M, Weber J, Ferguson R, Osman I, Kirchhoff T. A genome-wide association study of germline variation and melanoma prognosis. Front Oncol 2023; 12:1050741. [PMID: 36741706 PMCID: PMC9894711 DOI: 10.3389/fonc.2022.1050741] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 12/23/2022] [Indexed: 01/20/2023] Open
Abstract
Background The high mortality of cutaneous melanoma (CM) is partly due to unpredictable patterns of disease progression in patients with early-stage lesions. The reliable prediction of advanced disease risk from early-stage CM, is an urgent clinical need, especially given the recent expansion of immune checkpoint inhibitor therapy to the adjuvant setting. In our study, we comprehensively investigated the role of germline variants as CM prognostic markers. Methods We performed a genome-wide association analysis in two independent cohorts of N=551 (discovery), and N=550 (validation) early-stage immunotherapy-naïve melanoma patients. A multivariable Cox proportional hazard regression model was used to identify associations with overall survival in the discovery group, followed by a validation analysis. Transcriptomic profiling and survival analysis were used to elucidate the biological relevance of candidate genes associated with CM progression. Results We found two independent associations of germline variants with melanoma prognosis. The alternate alleles of these two SNPs were both associated with an increased risk of death [rs60970102 in MELK: HR=3.14 (2.05-4.81), p=1.48×10-7; and rs77480547 in SH3BP4: HR=3.02 (2.02-4.52), p=7.58×10-8, both in the pooled cohort]. The addition of the combined risk alleles (CRA) of the identified variants into the prognostic model improved the predictive power, as opposed to a model of clinical covariates alone. Conclusions Our study provides suggestive evidence of novel melanoma germline prognostic markers, implicating two candidate genes: an oncogene MELK and a tumor suppressor SH3BP4, both previously suggested to affect CM progression. Pending further validation, these findings suggest that the genetic factors may improve the prognostic stratification of high-risk early-stage CM patients, and propose putative biological insights for potential therapeutic investigation of these targets to prevent aggressive outcome from early-stage melanoma.
Collapse
Affiliation(s)
- Vylyny Chat
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- Department of Population Health and Environmental Medicine, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
| | - Sasha Dagayev
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- Department of Population Health and Environmental Medicine, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
| | - Una Moran
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
| | - Matija Snuderl
- Department of Pathology, New York University School of Medicine, New York, NY, United States
| | - Jeffrey Weber
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
| | - Robert Ferguson
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- Department of Population Health and Environmental Medicine, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
| | - Iman Osman
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
- Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, United States
| | - Tomas Kirchhoff
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, United States
- Department of Population Health and Environmental Medicine, New York University School of Medicine, New York, NY, United States
- The Interdisciplinary Melanoma Cooperative Group, New York University School of Medicine, New York, NY, United States
| |
Collapse
|
10
|
Nunziato M, Scaglione GL, Di Maggio F, Nardelli C, Capoluongo E, Salvatore F. The performance of multi-gene panels for breast/ovarian cancer predisposition. Clin Chim Acta 2023; 539:151-161. [PMID: 36521553 DOI: 10.1016/j.cca.2022.12.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 12/05/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022]
Abstract
BRCA1 and BRCA2 are the most mutated genes in breast cancer. We analyzed 48 breast cancer subjects using two methods that differ in terms of number of genes investigated and strategy used (primers: Panel A - 12 genes - vs probes: Panel B - 48 genes). Both the panels and procedures identified "pathogenic" or "likely pathogenic" variants in TP53, ATM, CHEK2 and BARD1 besides BRCA1 and BRCA2. Panel B identified two other putatively pathogenic variants in RNASEL and in RAD50. Identification of variants other than the BRCA genes can be useful in patient management. A total of 121 variants were distributed within the 12 genes and were correctly detected by both panels. However, the number of calls without divergence, namely ± 0.10 difference of allelic frequency, was 78.3%, while calls with a divergence below 0.10 was 16.7%, thus indicating that only 5% (n = 275) of 5,412 calls had a divergence above 0.10. Although these panels differ from each other, both are useful in different situations, particularly when patients should be tested for genes other than BRCA1/2 (as occurs in patients affected by a so called hereditary syndrome) or for therapeutic purposes.
Collapse
Affiliation(s)
- Marcella Nunziato
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy
| | - Giovanni Luca Scaglione
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy; Istituto Dermopatico dell'Immacolata IDI-IRCCS, Via dei Monti di Creta, 104, 00167 Rome, Italy
| | - Federica Di Maggio
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy
| | - Carmela Nardelli
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy
| | - Ettore Capoluongo
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy; Department of Clinical Pathology and Genomics, Ospedale Cannizzaro, Via Messina, 829, 95126 Catania, Italy.
| | - Francesco Salvatore
- CEINGE - Biotecnologie Avanzate Franco Salvatore, Via Gaetano Salvatore, 486, 80145 Naples, Italy; Department of Molecular Medicine and Medical Biotechnologies, University of Naples Federico II, Via Pansini, 5, 80131 Naples, Italy.
| |
Collapse
|
11
|
Seviiri M, Law MH, Ong JS, Gharahkhani P, Fontanillas P, Olsen CM, Whiteman DC, MacGregor S. A multi-phenotype analysis reveals 19 susceptibility loci for basal cell carcinoma and 15 for squamous cell carcinoma. Nat Commun 2022; 13:7650. [PMID: 36496446 PMCID: PMC9741635 DOI: 10.1038/s41467-022-35345-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
Basal cell carcinoma and squamous cell carcinoma are the most common skin cancers, and have genetic overlap with melanoma, pigmentation traits, autoimmune diseases, and blood biochemistry biomarkers. In this multi-trait genetic analysis of over 300,000 participants from Europe, Australia and the United States, we reveal 78 risk loci for basal cell carcinoma (19 previously unknown and replicated) and 69 for squamous cell carcinoma (15 previously unknown and replicated). The previously unknown risk loci are implicated in cancer development and progression (e.g. CDKL1), pigmentation (e.g. TPCN2), cardiometabolic (e.g. FADS2), and immune-regulatory pathways for innate immunity (e.g. IFIH1), and HIV-1 viral load modulation (e.g. CCR5). We also report an optimised polygenic risk score for effective risk stratification for keratinocyte cancer in the Canadian Longitudinal Study of Aging (794 cases and 18139 controls), which could facilitate skin cancer surveillance e.g. in high risk subpopulations such as transplantees.
Collapse
Affiliation(s)
- Mathias Seviiri
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.
- Center for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia.
| | - Matthew H Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Jue-Sheng Ong
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Puya Gharahkhani
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Catherine M Olsen
- Cancer Control Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - David C Whiteman
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Stuart MacGregor
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| |
Collapse
|
12
|
Corpas M, Megy K, Metastasio A, Lehmann E. Implementation of individualised polygenic risk score analysis: a test case of a family of four. BMC Med Genomics 2022; 15:207. [PMID: 36192731 PMCID: PMC9531350 DOI: 10.1186/s12920-022-01331-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 08/05/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demonstrating their implementation at an individual level. CASE PRESENTATION We performed a systematic curation of PRS sources from established data repositories, selecting 15 phenotypes, comprising an excess of 37 million SNPs related to cancer, cardiovascular, metabolic and autoimmune diseases. We tested selected phenotypes using whole genome sequencing data for a family of four related individuals. Individual risk scores were given percentile values based upon reference distributions among 1000 Genomes Iberians, Europeans, or all samples. Over 96 billion allele effects were calculated in order to obtain the PRS for each of the individuals analysed here. CONCLUSIONS Our results highlight the need for further standardisation in the way PRS are developed and shared, the importance of individual risk assessment rather than the assumption of inherited averages, and the challenges currently posed when translating PRS into risk metrics.
Collapse
Affiliation(s)
- Manuel Corpas
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, UK.
- Institute of Continuing Education, University of Cambridge, Cambridge, UK.
- Facultad de Ciencias de La Salud, Universidad Internacional de La Rioja, Madrid, Spain.
| | - Karyn Megy
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, UK
- Department of Haematology, University of Cambridge & NHS Blood and Transplant, Cambridge, UK
| | - Antonio Metastasio
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, UK
- Camden and Islington NHS Foundation Trust, London, UK
| | - Edmund Lehmann
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, UK
| |
Collapse
|
13
|
Rashid S, Gupta S, McCormick SR, Tsao H. New Insights into Melanoma Tumor Syndromes. JID INNOVATIONS 2022; 2:100152. [DOI: 10.1016/j.xjidi.2022.100152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 06/08/2022] [Accepted: 06/13/2022] [Indexed: 10/14/2022] Open
|
14
|
Pflugfelder A, Yong XLH, Jagirdar K, Eigentler TK, Soyer HP, Sturm RA, Flatz L, Duffy DL. Genome-Wide Association Study Suggests the Variant rs7551288*A within the DHCR24 Gene Is Associated with Poor Overall Survival in Melanoma Patients. Cancers (Basel) 2022; 14:cancers14102410. [PMID: 35626014 PMCID: PMC9139953 DOI: 10.3390/cancers14102410] [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: 02/28/2022] [Revised: 04/27/2022] [Accepted: 05/10/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary The aim of this work was to investigate prognostic genetic factors in melanoma patients. Phenotypic and disease data as well as biomaterial were collected after informed consent from patients followed up in a Skin Cancer Center of a University clinic. Genome-wide analysis (GWAS) was performed with survival data of 556 melanoma patients and genetic data including more than 300,000 common polymorphisms. The SNP rs7551288 reached suggestive genome-wide significance (p = 2 × 10−6). This intronic variant of the DHCR24 gene is involved in the cholesterol synthesis pathway. Further analyses and a literature review suggest an important role of this locus for the clinical course of disease in melanoma patients. Abstract Melanoma incidence rates are high among individuals with fair skin and multiple naevi. Established prognostic factors are tumour specific, and less is known about prognostic host factors. A total of 556 stage I to stage IV melanoma patients from Germany with phenotypic and disease-specific data were analysed; 64 of these patients died of melanoma after a median follow-up time of 8 years. Germline DNA was assessed by the HumanCoreExome BeadChip and data of 356,384 common polymorphisms distributed over all 23 chromosomes were used for a genome-wide analysis. A suggestive genome-wide significant association of the intronic allele rs7551288*A with diminished melanoma-specific survival was detected (p = 2 × 10−6). The frequency of rs7551288*A was 0.43 and was not associated with melanoma risk, hair and eye colour, tanning and total naevus count. Cox regression multivariate analyses revealed a 5.31-fold increased risk of melanoma-specific death for patients with the rs7551288 A/A genotype, independent of tumour thickness, ulceration and stage of disease at diagnoses. The variant rs7551288 belongs to the DHCR24 gene, which encodes Seladin-1, an enzyme involved in the biosynthesis of cholesterol. Further investigations are needed to confirm this genetic variant as a novel prognostic biomarker and to explore whether specific treatment strategies for melanoma patients might be derived from it.
Collapse
Affiliation(s)
- Annette Pflugfelder
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD 4102, Australia; (X.L.H.Y.); (K.J.); (H.P.S.); (R.A.S.); (D.L.D.)
- Center of Dermatooncology, Department of Dermatology, University of Tübingen, 72076 Tübingen, Germany;
- Correspondence:
| | - Xuan Ling Hilary Yong
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD 4102, Australia; (X.L.H.Y.); (K.J.); (H.P.S.); (R.A.S.); (D.L.D.)
- Clem Jones Centre for Ageing Dementia Research, The University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Kasturee Jagirdar
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD 4102, Australia; (X.L.H.Y.); (K.J.); (H.P.S.); (R.A.S.); (D.L.D.)
- Biochemistry and Molecular Biology Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Thomas K. Eigentler
- Department of Dermatology, Venereology and Allergology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10177 Berlin, Germany;
| | - H. Peter Soyer
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD 4102, Australia; (X.L.H.Y.); (K.J.); (H.P.S.); (R.A.S.); (D.L.D.)
- Department of Dermatology, Princess Alexandra Hospital, Brisbane, QLD 4102, Australia
| | - Richard A. Sturm
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD 4102, Australia; (X.L.H.Y.); (K.J.); (H.P.S.); (R.A.S.); (D.L.D.)
| | - Lukas Flatz
- Center of Dermatooncology, Department of Dermatology, University of Tübingen, 72076 Tübingen, Germany;
| | - David L. Duffy
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD 4102, Australia; (X.L.H.Y.); (K.J.); (H.P.S.); (R.A.S.); (D.L.D.)
- Genetic Epidemiology, QIMR Berghofer Institute of Medical Research, Herston, QLD 4006, Australia
| |
Collapse
|
15
|
Emilsson V, Gudmundsdottir V, Gudjonsson A, Jonmundsson T, Jonsson BG, Karim MA, Ilkov M, Staley JR, Gudmundsson EF, Launer LJ, Lindeman JH, Morton NM, Aspelund T, Lamb JR, Jennings LL, Gudnason V. Coding and regulatory variants are associated with serum protein levels and disease. Nat Commun 2022; 13:481. [PMID: 35079000 PMCID: PMC8789809 DOI: 10.1038/s41467-022-28081-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 01/07/2022] [Indexed: 12/20/2022] Open
Abstract
Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases.
Collapse
Affiliation(s)
- Valur Emilsson
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland.
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Reykjavík, Iceland.
| | | | | | | | | | - Mohd A Karim
- Wellcome Trust Sanger Institute, Welcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Marjan Ilkov
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland
| | - James R Staley
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Elias F Gudmundsson
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, 20892-9205, USA
| | - Jan H Lindeman
- Department of Surgery, Leiden University Medical Center, Leiden, Netherlands
| | - Nicholas M Morton
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Thor Aspelund
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland
| | - John R Lamb
- GNF Novartis, 10675 John Jay Hopkins Drive, San Diego, CA, 92121, USA
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, 22 Windsor Street, Cambridge, MA, 02139, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Kopavogur, Iceland.
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Reykjavík, Iceland.
| |
Collapse
|
16
|
Truderung OAH, Sagi JC, Semsei AF, Szalai C. Melanoma susceptibility: an update on genetic and epigenetic findings. INTERNATIONAL JOURNAL OF MOLECULAR EPIDEMIOLOGY AND GENETICS 2021; 12:71-89. [PMID: 34853632 PMCID: PMC8611230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 09/14/2021] [Indexed: 06/13/2023]
Abstract
Malignant melanoma is one of the most highly ranked cancers in terms of years of life lost. Hereditary melanoma with its increased familial susceptibility is thought to affect up to 12% of all melanoma patients. In the past, only a few high-penetrance genes associated with familial melanoma, such as CDKN2A and CDK4, have been clinically tested. However, findings now indicate that melanoma is a cancer most likely to develop not only due to high-penetrance variants but also due to polygenic inheritance patterns, leaving no clear division between the hereditary and sporadic development of malignant melanoma. Various pathogenic low-penetrance variants were recently discovered through genome-wide association studies, and are now translated into polygenic risk scores. These can show superior sensitivity rates for the prediction of melanoma susceptibility and related mixed cancer syndromes than risk scores based on phenotypic traits of the patients, with odds ratios of up to 5.7 for patients in risk groups. In addition to describing genetic findings, we also review the first results of epigenetic research showing constitutional methylation changes that alter the susceptibility to cutaneous melanoma and its risk factors.
Collapse
Affiliation(s)
- Ole AH Truderung
- Department of Genetics, Cell- and Immunobiology, Semmelweis UniversityH-1089 Budapest, Hungary
| | - Judit C Sagi
- Department of Genetics, Cell- and Immunobiology, Semmelweis UniversityH-1089 Budapest, Hungary
| | - Agnes F Semsei
- Department of Genetics, Cell- and Immunobiology, Semmelweis UniversityH-1089 Budapest, Hungary
| | - Csaba Szalai
- Department of Genetics, Cell- and Immunobiology, Semmelweis UniversityH-1089 Budapest, Hungary
- Heim Pal Children’s HospitalH-1089 Budapest, Hungary
| |
Collapse
|
17
|
Bakshi A, Yan M, Riaz M, Polekhina G, Orchard SG, Tiller J, Wolfe R, Joshi A, Cao Y, McInerney-Leo AM, Yanes T, Janda M, Soyer HP, Cust AE, Law MH, Gibbs P, McLean C, Chan AT, McNeil JJ, Mar VJ, Lacaze P. Genomic Risk Score for Melanoma in a Prospective Study of Older Individuals. J Natl Cancer Inst 2021; 113:1379-1385. [PMID: 33837773 PMCID: PMC8921762 DOI: 10.1093/jnci/djab076] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 02/16/2021] [Accepted: 03/30/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Recent genome-wide association meta-analysis for melanoma doubled the number of previously identified variants. We assessed the performance of an updated polygenic risk score (PRS) in a population of older individuals, where melanoma incidence and cumulative ultraviolet radiation exposure is greatest. METHODS We assessed a PRS for cutaneous melanoma comprising 55 variants in a prospective study of 12 712 individuals in the ASPirin in Reducing Events in the Elderly Trial. We evaluated incident melanomas diagnosed during the trial and prevalent melanomas diagnosed preenrolment (self-reported). Multivariable models examined associations between PRS as a continuous variable (per SD) and categorical (low-risk [0%-20%], medium-risk [21%-80%], high-risk [81%-100%] groups) with incident melanoma. Logistic regression examined the association between PRS and prevalent melanoma. RESULTS At baseline, mean participant age was 75 years; 55.0% were female, and 528 (4.2%) had prevalent melanomas. During follow-up (median = 4.7 years), 120 (1.0%) incident cutaneous melanomas occurred, 98 of which were in participants with no history. PRS was associated with incident melanoma (hazard ratio = 1.46 per SD, 95% confidence interval [CI] = 1.20 to 1.77) and prevalent melanoma (odds ratio [OR] = 1.55 per SD, 95% CI = 1.42 to 1.69). Participants in the highest-risk PRS group had increased risk compared with the low-risk group for incident melanoma (OR = 2.51, 95% CI = 1.28 to 4.92) and prevalent melanoma (OR = 3.66, 95% CI = 2.69 to 5.05). When stratifying by sex, only males had an association between the PRS and incident melanoma, whereas both sexes had an association between the PRS and prevalent melanoma. CONCLUSIONS A genomic risk score is associated with melanoma risk in older individuals and may contribute to targeted surveillance.
Collapse
Affiliation(s)
- Andrew Bakshi
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Mabel Yan
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Moeen Riaz
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Galina Polekhina
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Suzanne G Orchard
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Jane Tiller
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rory Wolfe
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Amit Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; MGH Cancer Center, Boston, MA, USA
| | - Yin Cao
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO, USA; Alvin J. Siteman Cancer Center, Washington University School of Medicine, St Louis, MO, USA
| | - Aideen M McInerney-Leo
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD, USA
| | - Tatiane Yanes
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD, USA
| | - Monika Janda
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD, USA
- Centre of Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - H Peter Soyer
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, QLD, USA
| | - Anne E Cust
- Sydney School of Public Health and Melanoma Institute Australia, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Matthew H Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- School of Biomedical Sciences, Faculty of Health, and Institute of health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Queensland, Australia, Personalised Oncology Division, Walter and Eliza Hall Institute Medical Research and Faculty of Medicine University of Melbourne, Australia
| | - Peter Gibbs
- Department of Anatomical Pathology, Alfred Hospital, Melbourne, Victoria, Australia
| | - Catriona McLean
- Department of Anatomical Pathology, Alfred Hospital, Melbourne, Victoria, Australia
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; MGH Cancer Center, Boston, MA, USA
| | - John J McNeil
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Victoria J Mar
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Victorian Melanoma Service, Alfred Health, Melbourne, Australia
| | - Paul Lacaze
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| |
Collapse
|
18
|
Xu M, Mehl L, Zhang T, Thakur R, Sowards H, Myers T, Jessop L, Chesi A, Johnson ME, Wells AD, Michael HT, Bunda P, Jones K, Higson H, Hennessey RC, Jermusyk A, Kovacs MA, Landi MT, Iles MM, Goldstein AM, Choi J, Chanock SJ, Grant SF, Chari R, Merlino G, Law MH, Brown KM, Brown KM. A UVB-responsive common variant at chromosome band 7p21.1 confers tanning response and melanoma risk via regulation of the aryl hydrocarbon receptor, AHR. Am J Hum Genet 2021; 108:1611-1630. [PMID: 34343493 DOI: 10.1016/j.ajhg.2021.07.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/07/2021] [Indexed: 10/20/2022] Open
Abstract
Genome-wide association studies (GWASs) have identified a melanoma-associated locus on chromosome band 7p21.1 with rs117132860 as the lead SNP and a secondary independent signal marked by rs73069846. rs117132860 is also associated with tanning ability and cutaneous squamous cell carcinoma (cSCC). Because ultraviolet radiation (UVR) is a key environmental exposure for all three traits, we investigated the mechanisms by which this locus contributes to melanoma risk, focusing on cellular response to UVR. Fine-mapping of melanoma GWASs identified four independent sets of candidate causal variants. A GWAS region-focused Capture-C study of primary melanocytes identified physical interactions between two causal sets and the promoter of the aryl hydrocarbon receptor (AHR). Subsequent chromatin state annotation, eQTL, and luciferase assays identified rs117132860 as a functional variant and reinforced AHR as a likely causal gene. Because AHR plays critical roles in cellular response to dioxin and UVR, we explored links between this SNP and AHR expression after both 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and ultraviolet B (UVB) exposure. Allele-specific AHR binding to rs117132860-G was enhanced following both, consistent with predicted weakened AHR binding to the risk/poor-tanning rs117132860-A allele, and allele-preferential AHR expression driven from the protective rs117132860-G allele was observed following UVB exposure. Small deletions surrounding rs117132860 introduced via CRISPR abrogates AHR binding, reduces melanocyte cell growth, and prolongs growth arrest following UVB exposure. These data suggest AHR is a melanoma susceptibility gene at the 7p21.1 risk locus and rs117132860 is a functional variant within a UVB-responsive element, leading to allelic AHR expression and altering melanocyte growth phenotypes upon exposure.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Kevin M Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
| |
Collapse
|
19
|
Marley AR, Li M, Champion VL, Song Y, Han J, Li X. The association between citrus consumption and melanoma risk in the UK Biobank. Br J Dermatol 2021; 185:353-362. [PMID: 33782946 PMCID: PMC8373643 DOI: 10.1111/bjd.19896] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Melanoma incidence has been dramatically increasing worldwide. Psoralen, a known photocarcinogen, is naturally abundant in citrus products, leading to the hypothesis that high citrus consumption may increase melanoma risk. OBJECTIVES To investigate the association between total citrus consumption and melanoma risk, and the association between individual citrus products and melanoma risk, and to test for interactions between total citrus intake and established melanoma risk factors. METHODS Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between citrus consumption and melanoma risk among 1592 cases and 197 372 controls from the UK Biobank cohort. Citrus consumption data were collected via five rounds of 24-h recall questionnaires. International Classification of Diseases codes were used to determine melanoma outcome. RESULTS After adjusting for potential confounders, participants in the highest category of total citrus intake (> 2 servings per day) had a significantly increased risk of melanoma (OR 1·63, 95% CI 1·24-2·12) relative to those with no consumption. For individual citrus products, participants with the most orange and orange juice consumption (> 1 serving per day) had a significantly increased melanoma risk relative to those with no consumption (OR 1·79, 95% CI 1·07-2·78 and OR 1·54, 95% CI 1·10-2·10, respectively). Fair- or very fair-skinned participants with high citrus consumption had an even greater melanoma risk (OR 1·75, 95% CI 1·31-2·29). CONCLUSIONS High citrus consumption was associated with an increased risk of melanoma in a large, prospective, population-based cohort. Further validation of these findings could lead to improved melanoma prevention strategies.
Collapse
Affiliation(s)
- A R Marley
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, USA
| | - M Li
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | - V L Champion
- Department of Community Health Systems, Indiana University School of Nursing, Indianapolis, IN, USA
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Y Song
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, USA
| | - J Han
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, USA
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - X Li
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, USA
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| |
Collapse
|
20
|
Loftus SK, Lundh L, Watkins-Chow DE, Baxter LL, Pairo-Castineira E, Nisc Comparative Sequencing Program, Jackson IJ, Oetting WS, Pavan WJ, Adams DR. A custom capture sequence approach for oculocutaneous albinism identifies structural variant alleles at the OCA2 locus. Hum Mutat 2021; 42:1239-1253. [PMID: 34246199 DOI: 10.1002/humu.24257] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/02/2021] [Accepted: 06/24/2021] [Indexed: 11/09/2022]
Abstract
Oculocutaneous albinism (OCA) is a heritable disorder of pigment production that manifests as hypopigmentation and altered eye development. Exon sequencing of known OCA genes is unsuccessful in producing a complete molecular diagnosis for a significant number of affected individuals. We sequenced the DNA of individuals with OCA using short-read custom capture sequencing that targeted coding, intronic, and noncoding regulatory regions of known OCA genes, and genome-wide association study-associated pigmentation loci. We identified an OCA2 complex structural variant (CxSV), defined by a 143 kb inverted segment reintroduced in intron 1, upstream of the native location. The corresponding CxSV junctions were observed in 11/390 probands screened. The 143 kb CxSV presents in one family as a copy number variant duplication for the 143 kb region. In the remaining 10/11 families, the 143 kb CxSV acquired an additional 184 kb deletion across the same region, restoring exons 3-19 of OCA2 to a copy-number neutral state. Allele-associated haplotype analysis found rare SNVs rs374519281 and rs139696407 are linked with the 143 kb CxSV in both OCA2 alleles. For individuals in which customary molecular evaluation does not reveal a biallelic OCA diagnosis, we recommend preliminary screening for these haplotype-associated rare variants, followed by junction-specific validation for the OCA2 143 kb CxSV.
Collapse
Affiliation(s)
- Stacie K Loftus
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Linnea Lundh
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Dawn E Watkins-Chow
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Laura L Baxter
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Erola Pairo-Castineira
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, UK.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | | | - Ian J Jackson
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, UK.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - William S Oetting
- Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, Minnesota, USA
| | - William J Pavan
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - David R Adams
- Office of the Clinical Director, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| |
Collapse
|
21
|
Heilbron K, Mozaffari SV, Vacic V, Yue P, Wang W, Shi J, Jubb AM, Pitts SJ, Wang X. Advancing drug discovery using the power of the human genome. J Pathol 2021; 254:418-429. [PMID: 33748968 PMCID: PMC8251523 DOI: 10.1002/path.5664] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 03/11/2021] [Accepted: 03/16/2021] [Indexed: 12/31/2022]
Abstract
Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.
Collapse
|
22
|
Chen Y, André M, Adhikari K, Blin M, Bonfante B, Mendoza-Revilla J, Fuentes-Guajardo M, Palmal S, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Lozano RB, Everardo-Martínez P, Gómez-Valdés J, Villamil-Ramírez H, de Cerqueira CCS, Hünemeier T, Ramallo V, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Balding D, Tobin DJ, Wang S, Faux P, Ruiz-Linares A. A genome-wide association study identifies novel gene associations with facial skin wrinkling and mole count in Latin Americans. Br J Dermatol 2021; 185:988-998. [PMID: 33959940 DOI: 10.1111/bjd.20436] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified genes influencing skin ageing and mole count in Europeans, but little is known about the relevance of these (or other genes) in non-Europeans. OBJECTIVES To conduct a GWAS for facial skin ageing and mole count in adults < 40 years old, of mixed European, Native American and African ancestry, recruited in Latin America. METHODS Skin ageing and mole count scores were obtained from facial photographs of over 6000 individuals. After quality control checks, three wrinkling traits and mole count were retained for genetic analyses. DNA samples were genotyped with Illumina's HumanOmniExpress chip. Association testing was performed on around 8 703 729 single-nucleotide polymorphisms (SNPs) across the autosomal genome. RESULTS Genome-wide significant association was observed at four genome regions: two were associated with wrinkling (in 1p13·3 and 21q21·2), one with mole count (in 1q32·3) and one with both wrinkling and mole count (in 5p13·2). Associated SNPs in 5p13·2 and in 1p13·3 are intronic within SLC45A2 and VAV3, respectively, while SNPs in 1q32·3 are near the SLC30A1 gene, and those in 21q21·2 occur in a gene desert. Analyses of SNPs in IRF4 and MC1R are consistent with a role of these genes in skin ageing. CONCLUSIONS We replicate the association of wrinkling with variants in SLC45A2, IRF4 and MC1R reported in Europeans. We identify VAV3 and SLC30A1 as two novel candidate genes impacting on wrinkling and mole count, respectively. We provide the first evidence that SLC45A2 influences mole count, in addition to variants in this gene affecting melanoma risk in Europeans.
Collapse
Affiliation(s)
- Y Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China
| | - M André
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France.,Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - K Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, UK.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK
| | - M Blin
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - B Bonfante
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - J Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú.,Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - M Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - S Palmal
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - J C Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - M Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - V Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - V Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - C Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - W Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - R B Lozano
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico.,Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - P Everardo-Martínez
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - J Gómez-Valdés
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - H Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, MC, 4510, Mexico
| | | | - T Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - V Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil.,Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - R Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - L Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil
| | - M-C Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil
| | - V Acuña-Alonzo
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - S Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, MC, 4510, Mexico
| | - C Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - G Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - G Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - F Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, 1000000, Chile
| | - D Balding
- Melbourne Integrative Genomics, Schools of BioSciences and Mathematics & Statistics, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - D J Tobin
- The Charles Institute of Dermatology, University College Dublin, Dublin, Ireland
| | - S Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Shanghai, 200031, China
| | - P Faux
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - A Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China.,UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK
| |
Collapse
|
23
|
Cai M, Yuan T, Huang H, Gui L, Zhang L, Meng Z, Wu W, Sheng Y, Zhang X. Integrative Analysis of Omics Data Reveals Regulatory Network of CDK10 in Vitiligo Risk. Front Genet 2021; 12:634553. [PMID: 33679896 PMCID: PMC7925885 DOI: 10.3389/fgene.2021.634553] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 01/25/2021] [Indexed: 12/20/2022] Open
Abstract
Vitiligo is a multifactorial polygenic disorder, characterized by acquired depigmented skin and overlying hair resulting from the destruction of melanocytes. Genome-wide association studies (GWASs) of vitiligo have identified approximately 100 genetic variants. However, the identification of functional genes and their regulatory elements remains a challenge. To prioritize putative functional genes and DNAm sites, we performed a Summary data-based Mendelian Randomization (SMR) and heterogeneity in dependent instruments (HEIDI) test to integrate omics summary statistics from GWAS, expression quantitative trait locus (eQTL), and methylation quantitative trait loci (meQTL) analysis of large sample size. By integrating omics data, we identified two newly putative functional genes (SPATA2L and CDK10) associated with vitiligo and further validated CDK10 by qRT-PCR in independent samples. We also identified 17 vitiligo-associated DNA methylation (DNAm) sites in Chr16, of which cg05175606 was significantly associated with the expression of CDK10 and vitiligo. Colocalization analyses detected transcript of CDK10 in the blood and skin colocalizing with cg05175606 at single nucleotide polymorphism (SNP) rs77651727. Our findings revealed that a shared genetic variant rs77651727 alters the cg05175606 as well as up-regulates gene expression of CDK10 and further decreases the risk of vitiligo.
Collapse
Affiliation(s)
- Minglong Cai
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Tao Yuan
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - He Huang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Lan Gui
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Li Zhang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Ziyuan Meng
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Wenjuan Wu
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Yujun Sheng
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| | - Xuejun Zhang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Institute of Dermatology, Anhui Medical University, Hefei, China
| |
Collapse
|
24
|
Fritsche LG, Patil S, Beesley LJ, VandeHaar P, Salvatore M, Ma Y, Peng RB, Taliun D, Zhou X, Mukherjee B. Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks. Am J Hum Genet 2020; 107:815-836. [PMID: 32991828 PMCID: PMC7675001 DOI: 10.1016/j.ajhg.2020.08.025] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 08/28/2020] [Indexed: 02/06/2023] Open
Abstract
To facilitate scientific collaboration on polygenic risk scores (PRSs) research, we created an extensive PRS online repository for 35 common cancer traits integrating freely available genome-wide association studies (GWASs) summary statistics from three sources: published GWASs, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWASs. Our framework condenses these summary statistics into PRSs using various approaches such as linkage disequilibrium pruning/p value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRSs in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRSs. We expect this integrated platform to accelerate PRS-related cancer research.
Collapse
Affiliation(s)
- Lars G Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Snehal Patil
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Lauren J Beesley
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Peter VandeHaar
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Maxwell Salvatore
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Ying Ma
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Robert B Peng
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Department of Statistics, Northwestern University, Evanston, IL 60208, USA
| | - Daniel Taliun
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
| |
Collapse
|
25
|
Jaikumarr Ram A, Girija As S, Jayaseelan VP, Arumugam P. Overexpression of BASP1 Indicates a Poor Prognosis in Head and Neck Squamous Cell Carcinoma. Asian Pac J Cancer Prev 2020; 21:3435-3439. [PMID: 33247706 PMCID: PMC8033119 DOI: 10.31557/apjcp.2020.21.11.3435] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Indexed: 01/04/2023] Open
Abstract
Objective: Brain abundant membrane attached signal protein 1 (BASP1) was originally identified as a membrane and cytoplasmic protein. Recent studies have shown that BASP1 highly expressed in cancer and promoted the proliferation of cancer. However, the role of BASP1 in head and neck squamous cell carcinoma (HNSCC) is largely unknown. Here, we performed a systematic data analysis to examine whether BASP1 can function as prognostic marker in HNSCC. Methods: In this study, we used Oncomine, and UALCAN, databases to analyze the expression of BASP1 in HNSCC. We used Kaplan-Meier plotter to evaluate the effect of BASP1 on clinical prognosis. In addition, we also analyzed genetic alterations, interaction network, and functional enrichment of BASP1. Results: BASP1 mRNA expression level was remarkably increased in HNSCC than in normal tissues (P=1.624e-12). Moreover, high BASP1 expression was significantly related to poor survival (p=0.00056) in HNSCC patients. In addition, BASP1 gene amplified in 5% of HNSCC patients which contributes to the overexpression of BASP1. Conclusions: These findings suggest that BASP1 was frequently amplified which contributes to the overexpression of BASP1, thereby promoting HNSCC progression. Thus, these results indicate that BASP1 might serve as a biomarker to predict the progression and prognosis of HNSCC patients.
Collapse
Affiliation(s)
- Ashwin Jaikumarr Ram
- Department of Microbiology, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
| | - Smiline Girija As
- Department of Microbiology, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
| | | | - Paramasivam Arumugam
- BRULAC-DRC, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
| |
Collapse
|
26
|
Law MH, Aoude LG, Duffy DL, Long GV, Johansson PA, Pritchard AL, Khosrotehrani K, Mann GJ, Montgomery GW, Iles MM, Cust AE, Palmer JM, Shannon KF, Spillane AJ, Stretch JR, Thompson JF, Saw RPM, Scolyer RA, Martin NG, Hayward NK, MacGregor S. Multiplex melanoma families are enriched for polygenic risk. Hum Mol Genet 2020; 29:2976-2985. [PMID: 32716505 PMCID: PMC7566496 DOI: 10.1093/hmg/ddaa156] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 07/10/2020] [Accepted: 07/14/2020] [Indexed: 01/04/2023] Open
Abstract
Cancers, including cutaneous melanoma, can cluster in families. In addition to environmental etiological factors such as ultraviolet radiation, cutaneous melanoma has a strong genetic component. Genetic risks for cutaneous melanoma range from rare, high-penetrance mutations to common, low-penetrance variants. Known high-penetrance mutations account for only about half of all densely affected cutaneous melanoma families, and the causes of familial clustering in the remainder are unknown. We hypothesize that some clustering is due to the cumulative effect of a large number of variants of individually small effect. Common, low-penetrance genetic risk variants can be combined into polygenic risk scores. We used a polygenic risk score for cutaneous melanoma to compare families without known high-penetrance mutations with unrelated melanoma cases and melanoma-free controls. Family members had significantly higher mean polygenic load for cutaneous melanoma than unrelated cases or melanoma-free healthy controls (Bonferroni-corrected t-test P = 1.5 × 10-5 and 6.3 × 10-45, respectively). Whole genome sequencing of germline DNA from 51 members of 21 families with low polygenic risk for melanoma identified a CDKN2A p.G101W mutation in a single family but no other candidate high-penetrance melanoma susceptibility genes. This work provides further evidence that melanoma, like many other common complex disorders, can arise from the joint action of multiple predisposing factors, including rare high-penetrance mutations, as well as via a combination of large numbers of alleles of small effect.
Collapse
Affiliation(s)
- Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Lauren G Aoude
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
- Surgical Oncology Group, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD 4102, Australia
| | - David L Duffy
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Georgina V Long
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
- Department of Medical Oncology, Mater Hospital, North Sydney, NSW 2060, Australia
- Department of Medical Oncology, Royal North Shore Hospital, St Leonards, NSW 2065, Australia
| | - Peter A Johansson
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Antonia L Pritchard
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
- Genetics and Immunology, University of the Highlands and Islands, Inverness IV2 5NA, UK
| | - Kiarash Khosrotehrani
- Experimental Dermatology Group, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD 4102, Australia
- Department of Dermatology, Princess Alexandra Hospital, Brisbane, QLD 4102, Australia
| | - Graham J Mann
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
| | - Grant W Montgomery
- Molecular Biology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Mark M Iles
- Leeds Institute for Medical Research, University of Leeds, Leeds LS2 9JT, UK
| | - Anne E Cust
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
- School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia
| | - Jane M Palmer
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Kerwin F Shannon
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Andrew J Spillane
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Jonathan R Stretch
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - John F Thompson
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Robyn P M Saw
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
- Department of Tissue Oncology and Diagnostic Pathology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, NSW 2050, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Nicholas K Hayward
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| |
Collapse
|
27
|
Lourenço GJ, Oliveira C, Carvalho BS, Torricelli C, Silva JK, Gomez GVB, Rinck-Junior JA, Oliveira WL, Vazquez VL, Serrano SV, Moraes AM, Lima CSP. Inherited variations in human pigmentation-related genes modulate cutaneous melanoma risk and clinicopathological features in Brazilian population. Sci Rep 2020; 10:12129. [PMID: 32699307 PMCID: PMC7376158 DOI: 10.1038/s41598-020-68945-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 05/04/2020] [Indexed: 01/29/2023] Open
Abstract
Ultraviolet light exposure and cutaneous pigmentation are important host risk factors for cutaneous melanoma (CM), and it is well known that inherited ability to produce melanin varies in humans. The study aimed to identify single-nucleotide variants (SNVs) on pigmentation-related genes with importance in risk and clinicopathological aspects of CM. The study was conducted in two stages. In stage 1, 103 CM patients and 103 controls were analyzed using Genome-Wide Human SNV Arrays in order to identify SNVs in pigmentation-related genes, and the most important SNVs were selected for data validation in stage 2 by real-time polymerase-chain reaction in 247 CM patients and 280 controls. ADCY3 c.675+9196T>G, CREB1 c.303+373G>A, and MITF c.938-325G>A were selected for data validation among 74 SNVs. Individuals with CREB1 GA or AA genotype and allele "A" were under 1.79 and 1.47-fold increased risks of CM than others, respectively. Excesses of CREB1 AA and MITF AA genotype were seen in patients with tumors at Clark levels III to V (27.8% versus 13.7%) and at III or IV stages (46.1% versus 24.9%) compared to others, respectively. When compared to others, patients with ADCY3 TT had 1.89 more chances of presenting CM progression, and those with MITF GA or AA had 2.20 more chances of evolving to death by CM. Our data provide, for the first time, preliminary evidence that inherited abnormalities in ADCY3, CREB1, and MITF pigmentation-related genes, not only can increase the risk to CM, but also influence CM patients' clinicopathological features.
Collapse
Affiliation(s)
- Gustavo Jacob Lourenço
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Cristiane Oliveira
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Benilton Sá Carvalho
- Department of Statistics, Institute of Mathematics, Statistic, and Computer Science, University of Campinas, Campinas, São Paulo, Brazil
| | - Caroline Torricelli
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Janet Keller Silva
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Gabriela Vilas Bôas Gomez
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - José Augusto Rinck-Junior
- Clinical Oncology Service, Department of Internal Medicine, Faculty of Medical Sciences, University of Campinas, Rua Alexander Fleming, 181, Cidade Universitária "Zeferino Vaz", Barão Geraldo, Campinas, São Paulo, Brazil
- A.C. Camargo Cancer Center, São Paulo, São Paulo, Brazil
| | - Wesley Lima Oliveira
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Vinicius Lima Vazquez
- Melanoma and Sarcoma Surgery Department, Barretos Cancer Hospital, Barretos, São Paulo, Brazil
| | | | - Aparecida Machado Moraes
- Clinical Oncology Service, Department of Internal Medicine, Faculty of Medical Sciences, University of Campinas, Rua Alexander Fleming, 181, Cidade Universitária "Zeferino Vaz", Barão Geraldo, Campinas, São Paulo, Brazil
| | - Carmen Silvia Passos Lima
- Laboratory of Cancer Genetics, Faculty of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil.
- Clinical Oncology Service, Department of Internal Medicine, Faculty of Medical Sciences, University of Campinas, Rua Alexander Fleming, 181, Cidade Universitária "Zeferino Vaz", Barão Geraldo, Campinas, São Paulo, Brazil.
| |
Collapse
|
28
|
Choi J, Zhang T, Vu A, Ablain J, Makowski MM, Colli LM, Xu M, Hennessey RC, Yin J, Rothschild H, Gräwe C, Kovacs MA, Funderburk KM, Brossard M, Taylor J, Pasaniuc B, Chari R, Chanock SJ, Hoggart CJ, Demenais F, Barrett JH, Law MH, Iles MM, Yu K, Vermeulen M, Zon LI, Brown KM. Massively parallel reporter assays of melanoma risk variants identify MX2 as a gene promoting melanoma. Nat Commun 2020; 11:2718. [PMID: 32483191 PMCID: PMC7264232 DOI: 10.1038/s41467-020-16590-1] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 05/12/2020] [Indexed: 02/07/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified ~20 melanoma susceptibility loci, most of which are not functionally characterized. Here we report an approach integrating massively-parallel reporter assays (MPRA) with cell-type-specific epigenome and expression quantitative trait loci (eQTL) to identify susceptibility genes/variants from multiple GWAS loci. From 832 high-LD variants, we identify 39 candidate functional variants from 14 loci displaying allelic transcriptional activity, a subset of which corroborates four colocalizing melanocyte cis-eQTL genes. Among these, we further characterize the locus encompassing the HIV-1 restriction gene, MX2 (Chr21q22.3), and validate a functional intronic variant, rs398206. rs398206 mediates the binding of the transcription factor, YY1, to increase MX2 levels, consistent with the cis-eQTL of MX2 in primary human melanocytes. Melanocyte-specific expression of human MX2 in a zebrafish model demonstrates accelerated melanoma formation in a BRAFV600E background. Our integrative approach streamlines GWAS follow-up studies and highlights a pleiotropic function of MX2 in melanoma susceptibility. There are more than 20 known melanoma susceptibility genes. Here, using a massively parallel reporter assay, the authors identify risk-associated variants that alter gene transcription, and demonstrate that expression of one such gene, MX2, leads to the promotion of melanoma in a zebrafish model.
Collapse
Affiliation(s)
- Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Andrew Vu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Julien Ablain
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Matthew M Makowski
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 XZ, Nijmegen, The Netherlands
| | - Leandro M Colli
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Mai Xu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Rebecca C Hennessey
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Harriet Rothschild
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Cathrin Gräwe
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 XZ, Nijmegen, The Netherlands
| | - Michael A Kovacs
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Karen M Funderburk
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Myriam Brossard
- Université de Paris, UMRS-1124, Institut National de la Santé et de la Recherche Médicale (INSERM), F-75006, Paris, France
| | - John Taylor
- Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Bogdan Pasaniuc
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Raj Chari
- Genome Modification Core, Frederick National Lab for Cancer Research, National Cancer Institute, Frederick, MD, 21701, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Clive J Hoggart
- Department of Medicine, Imperial College London, London, SW7 2BU, UK
| | - Florence Demenais
- Université de Paris, UMRS-1124, Institut National de la Santé et de la Recherche Médicale (INSERM), F-75006, Paris, France
| | - Jennifer H Barrett
- Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia
| | - Mark M Iles
- Leeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Michiel Vermeulen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 XZ, Nijmegen, The Netherlands
| | - Leonard I Zon
- Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Kevin M Brown
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA.
| |
Collapse
|
29
|
Landi MT, Bishop DT, MacGregor S, Machiela MJ, Stratigos AJ, Ghiorzo P, Brossard M, Calista D, Choi J, Fargnoli MC, Zhang T, Rodolfo M, Trower AJ, Menin C, Martinez J, Hadjisavvas A, Song L, Stefanaki I, Scolyer R, Yang R, Goldstein AM, Potrony M, Kypreou KP, Pastorino L, Queirolo P, Pellegrini C, Cattaneo L, Zawistowski M, Gimenez-Xavier P, Rodriguez A, Elefanti L, Manoukian S, Rivoltini L, Smith BH, Loizidou MA, Del Regno L, Massi D, Mandala M, Khosrotehrani K, Akslen LA, Amos CI, Andresen PA, Avril MF, Azizi E, Soyer HP, Bataille V, Dalmasso B, Bowdler LM, Burdon KP, Chen WV, Codd V, Craig JE, Dębniak T, Falchi M, Fang S, Friedman E, Simi S, Galan P, Garcia-Casado Z, Gillanders EM, Gordon S, Green A, Gruis NA, Hansson J, Harland M, Harris J, Helsing P, Henders A, Hočevar M, Höiom V, Hunter D, Ingvar C, Kumar R, Lang J, Lathrop GM, Lee JE, Li X, Lubiński J, Mackie RM, Malt M, Malvehy J, McAloney K, Mohamdi H, Molven A, Moses EK, Neale RE, Novaković S, Nyholt DR, Olsson H, Orr N, Fritsche LG, Puig-Butille JA, Qureshi AA, Radford-Smith GL, Randerson-Moor J, Requena C, Rowe C, Samani NJ, Sanna M, Schadendorf D, et alLandi MT, Bishop DT, MacGregor S, Machiela MJ, Stratigos AJ, Ghiorzo P, Brossard M, Calista D, Choi J, Fargnoli MC, Zhang T, Rodolfo M, Trower AJ, Menin C, Martinez J, Hadjisavvas A, Song L, Stefanaki I, Scolyer R, Yang R, Goldstein AM, Potrony M, Kypreou KP, Pastorino L, Queirolo P, Pellegrini C, Cattaneo L, Zawistowski M, Gimenez-Xavier P, Rodriguez A, Elefanti L, Manoukian S, Rivoltini L, Smith BH, Loizidou MA, Del Regno L, Massi D, Mandala M, Khosrotehrani K, Akslen LA, Amos CI, Andresen PA, Avril MF, Azizi E, Soyer HP, Bataille V, Dalmasso B, Bowdler LM, Burdon KP, Chen WV, Codd V, Craig JE, Dębniak T, Falchi M, Fang S, Friedman E, Simi S, Galan P, Garcia-Casado Z, Gillanders EM, Gordon S, Green A, Gruis NA, Hansson J, Harland M, Harris J, Helsing P, Henders A, Hočevar M, Höiom V, Hunter D, Ingvar C, Kumar R, Lang J, Lathrop GM, Lee JE, Li X, Lubiński J, Mackie RM, Malt M, Malvehy J, McAloney K, Mohamdi H, Molven A, Moses EK, Neale RE, Novaković S, Nyholt DR, Olsson H, Orr N, Fritsche LG, Puig-Butille JA, Qureshi AA, Radford-Smith GL, Randerson-Moor J, Requena C, Rowe C, Samani NJ, Sanna M, Schadendorf D, Schulze HJ, Simms LA, Smithers M, Song F, Swerdlow AJ, van der Stoep N, Kukutsch NA, Visconti A, Wallace L, Ward SV, Wheeler L, Sturm RA, Hutchinson A, Jones K, Malasky M, Vogt A, Zhou W, Pooley KA, Elder DE, Han J, Hicks B, Hayward NK, Kanetsky PA, Brummett C, Montgomery GW, Olsen CM, Hayward C, Dunning AM, Martin NG, Evangelou E, Mann GJ, Long G, Pharoah PDP, Easton DF, Barrett JH, Cust AE, Abecasis G, Duffy DL, Whiteman DC, Gogas H, De Nicolo A, Tucker MA, Newton-Bishop JA, Peris K, Chanock SJ, Demenais F, Brown KM, Puig S, Nagore E, Shi J, Iles MM, Law MH. Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility. Nat Genet 2020; 52:494-504. [PMID: 32341527 PMCID: PMC7255059 DOI: 10.1038/s41588-020-0611-8] [Show More Authors] [Citation(s) in RCA: 147] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 03/09/2020] [Indexed: 12/17/2022]
Abstract
Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 cases of melanoma (67% newly genotyped) and 375,188 controls identified 54 significant (P < 5 × 10-8) loci with 68 independent single nucleotide polymorphisms. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with GWAS of nevus count and hair color, and transcriptome association approaches, uncovered 31 potential secondary loci for a total of 85 cutaneous melanoma susceptibility loci. These findings provide insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation and telomere maintenance, together with identifying potential new pathways for cutaneous melanoma pathogenesis.
Collapse
Affiliation(s)
- Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - D Timothy Bishop
- Leeds Institute of Medical Research at St James's, Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alexander J Stratigos
- Department of Dermatology, Andreas Syggros Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Paola Ghiorzo
- Genetics of Rare Cancers, Ospedale Policlinico San Martino, Genoa, Italy
- Department of Internal Medicine and Medical Specialties (DIMI), University of Genoa, Genoa, Italy
| | - Myriam Brossard
- Genetic Epidemiology and Functional Genomics of Multifactorial Diseases Team, Institut National de la Santé et de la Recherche Médicale (INSERM), UMRS-1124, Université Paris Descartes, Paris, France
| | - Donato Calista
- Department of Dermatology, Maurizio Bufalini Hospital, Cesena, Italy
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maria Concetta Fargnoli
- Department of Dermatology & Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Monica Rodolfo
- Unit of Immunotherapy of Human Tumors, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Adam J Trower
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
| | - Chiara Menin
- Immunology and Molecular Oncology Unit, Venito Institute of Oncology IOV-IRCCS, Padua, Italy
| | | | - Andreas Hadjisavvas
- Department of EM/Molecular Pathology & The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Lei Song
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Irene Stefanaki
- Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
| | - Richard Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
- Central Clinical School, The University of Sydney, Sydney, New South Wales, Australia
- New South Wales Health Pathology, Sydney, New South Wales, Australia
| | - Rose Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alisa M Goldstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Miriam Potrony
- Dermatology Department, Melanoma Unit, Hospital Clínic de Barcelona, IDIBAPS, Universitat de Barcelona, CIBERER, Barcelona, Spain
| | - Katerina P Kypreou
- Department of Dermatology, University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
| | - Lorenza Pastorino
- Genetics of Rare Cancers, Ospedale Policlinico San Martino, Genoa, Italy
- Department of Internal Medicine and Medical Specialties (DIMI), University of Genoa, Genoa, Italy
| | - Paola Queirolo
- Medical Oncology Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Cristina Pellegrini
- Department of Dermatology & Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Laura Cattaneo
- Pathology Unit, Azienda Socio-Sanitaria Territoriale Papa Giovanni XXIII, Bergamo, Italy
| | - Matthew Zawistowski
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Pol Gimenez-Xavier
- Dermatology Department, Melanoma Unit, Hospital Clínic de Barcelona, IDIBAPS, Universitat de Barcelona, CIBERER, Barcelona, Spain
| | - Arantxa Rodriguez
- Department of Dermatology, Instituto Valenciano de Oncología, Valencia, Spain
| | - Lisa Elefanti
- Immunology and Molecular Oncology Unit, Venito Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Licia Rivoltini
- Unit of Immunotherapy of Human Tumors, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Maria A Loizidou
- Department of EM/Molecular Pathology & The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Laura Del Regno
- Institute of Dermatology, Catholic University, Rome, Italy
- Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
| | - Daniela Massi
- Section of Anatomic Pathology, Department of Health Sciences, University of Florence, Florence, Italy
| | - Mario Mandala
- Department of Oncology, Giovanni XXIII Hospital, Bergamo, Italy
| | - Kiarash Khosrotehrani
- UQ Diamantina Institute, The University of Queensland, Brisbane, Queensland, Australia
- Department of Dermatology, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Lars A Akslen
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Christopher I Amos
- Department of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Per A Andresen
- Department of Pathology, Molecular Pathology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Marie-Françoise Avril
- Assistance Publique-Hôpitaux de Paris, Hôpital Cochin, Service de Dermatologie, Université Paris Descartes, Paris, France
| | - Esther Azizi
- Department of Dermatology, Sheba Medical Center, Tel Hashomer, Sackler Faculty of Medicine, Tel Aviv, Israel
- Oncogenetics Unit, Sheba Medical Center, Tel Hashomer, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - H Peter Soyer
- Department of Dermatology, Princess Alexandra Hospital, Brisbane, Queensland, Australia
- Dermatology Research Centre, The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Veronique Bataille
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Dermatology, West Herts NHS Trust, Herts, UK
| | - Bruna Dalmasso
- Genetics of Rare Cancers, Ospedale Policlinico San Martino, Genoa, Italy
- Department of Internal Medicine and Medical Specialties (DIMI), University of Genoa, Genoa, Italy
| | - Lisa M Bowdler
- Sample Processing, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Kathryn P Burdon
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Wei V Chen
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jamie E Craig
- Department of Ophthalmology, Flinders University, Adelaide, South Australia, Australia
| | - Tadeusz Dębniak
- Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, Szczecin, Poland
| | - Mario Falchi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Dermatology, West Herts NHS Trust, Herts, UK
| | - Shenying Fang
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Eitan Friedman
- Oncogenetics Unit, Sheba Medical Center, Tel Hashomer, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Sarah Simi
- Section of Anatomic Pathology, Department of Health Sciences, University of Florence, Florence, Italy
| | - Pilar Galan
- Université Paris 13, Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Institut National de la Santé et de la Recherche Médicale (INSERM U1153), Institut National de la Recherche Agronomique (INRA U1125), Conservatoire National des Arts et Métiers, Communauté d'Université Sorbonne Paris Cité, Bobigny, France
| | - Zaida Garcia-Casado
- Department of Dermatology, Instituto Valenciano de Oncología, Valencia, Spain
| | - Elizabeth M Gillanders
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Adele Green
- Cancer and Population Studies, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- CRUK Manchester Institute, Institute of Inflammation and Repair, University of Manchester, Manchester, UK
| | - Nelleke A Gruis
- Department of Dermatology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Johan Hansson
- Department of Oncology-Pathology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Mark Harland
- Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - Jessica Harris
- Translational Research Institute, Institute of Health and Biomedical Innovation, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Per Helsing
- Department of Dermatology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Anjali Henders
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Marko Hočevar
- Department of Surgical Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Veronica Höiom
- Department of Oncology-Pathology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - David Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Christian Ingvar
- Department of Surgery, Clinical Sciences, Lund University, Lund, Sweden
| | - Rajiv Kumar
- Division of Molecular Genetic Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Julie Lang
- Department of Medical Genetics, University of Glasgow, Glasgow, UK
| | - G Mark Lathrop
- McGill University and Genome Quebec Innovation Centre, Montreal, Canada
| | - Jeffrey E Lee
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xin Li
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, USA
| | - Jan Lubiński
- International Hereditary Cancer Center, Pomeranian Medical University, Szczecin, Poland
| | - Rona M Mackie
- Department of Medical Genetics, University of Glasgow, Glasgow, UK
- Department of Public Health, University of Glasgow, Glasgow, UK
| | - Maryrose Malt
- Cancer and Population Studies, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Josep Malvehy
- Dermatology Department, Melanoma Unit, Hospital Clínic de Barcelona, IDIBAPS, Universitat de Barcelona, CIBERER, Barcelona, Spain
| | - Kerrie McAloney
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Hamida Mohamdi
- Genetic Epidemiology and Functional Genomics of Multifactorial Diseases Team, Institut National de la Santé et de la Recherche Médicale (INSERM), UMRS-1124, Université Paris Descartes, Paris, France
| | - Anders Molven
- Department of Pathology, Haukeland University Hospital, Bergen, Norway
- Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Eric K Moses
- Centre for Genetic Origins of Health and Disease, Faculty of Medicine, Dentistry and Health Sciences, The University of Western Australia, Crawley, Western Australia, Australia
| | - Rachel E Neale
- Cancer Aetiology & Prevention, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Srdjan Novaković
- Department of Molecular Diagnostics, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Dale R Nyholt
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Håkan Olsson
- Department of Oncology/Pathology, Clinical Sciences, Lund University, Lund, Sweden
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Nicholas Orr
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Lars G Fritsche
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Joan Anton Puig-Butille
- Biochemistry and Molecular Genetics Department, Melanoma Unit, Hospital Clínic de Barcelona, IDIBAPS, Universitat de Barcelona,CIBERER, Barcelona, Spain
| | - Abrar A Qureshi
- Department of Dermatology, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Graham L Radford-Smith
- Inflammatory Bowel Diseases, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Department of Gastroenterology and Hepatology, Royal Brisbane & Women's Hospital, Brisbane, Queensland, Australia
- University of Queensland School of Medicine, Herston Campus, Brisbane, Queensland, Australia
| | | | - Celia Requena
- Department of Dermatology, Instituto Valenciano de Oncología, Valencia, Spain
| | - Casey Rowe
- UQ Diamantina Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Marianna Sanna
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Dermatology, West Herts NHS Trust, Herts, UK
| | - Dirk Schadendorf
- Department of Dermatology, University Hospital Essen, Essen, Germany
- German Consortium Translational Cancer Research (DKTK), Heidelberg, Germany
| | - Hans-Joachim Schulze
- Department of Dermatology, Fachklinik Hornheide, Institute for Tumors of the Skin, University of Münster, Münster, Germany
| | - Lisa A Simms
- Inflammatory Bowel Diseases, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Mark Smithers
- Queensland Melanoma Project, Princess Alexandra Hospital, The University of Queensland, St Lucia, Queensland, Australia
- Mater Research Institute, The University of Queensland, St Lucia, Queensland, Australia
| | - Fengju Song
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, P. R. China
| | - Anthony J Swerdlow
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | - Nienke van der Stoep
- Department of Clinical Genetics, Center of Human and Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Nicole A Kukutsch
- Department of Dermatology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Alessia Visconti
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Dermatology, West Herts NHS Trust, Herts, UK
| | - Leanne Wallace
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Sarah V Ward
- Centre for Genetic Origins of Health and Disease, School of Biomedical Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Lawrie Wheeler
- Translational Research Institute, Institute of Health and Biomedical Innovation, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Richard A Sturm
- Dermatology Research Centre, The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Amy Hutchinson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genome Research Laboratory, Leidos Biomedical Research, Bethesda, MD, USA
| | - Kristine Jones
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genome Research Laboratory, Leidos Biomedical Research, Bethesda, MD, USA
| | - Michael Malasky
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genome Research Laboratory, Leidos Biomedical Research, Bethesda, MD, USA
| | - Aurelie Vogt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genome Research Laboratory, Leidos Biomedical Research, Bethesda, MD, USA
| | - Weiyin Zhou
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genome Research Laboratory, Leidos Biomedical Research, Bethesda, MD, USA
| | - Karen A Pooley
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - David E Elder
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiali Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, USA
| | - Belynda Hicks
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Genome Research Laboratory, Leidos Biomedical Research, Bethesda, MD, USA
| | - Nicholas K Hayward
- Oncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Peter A Kanetsky
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Chad Brummett
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Catherine M Olsen
- Cancer Control Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Evangelos Evangelou
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Graham J Mann
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Centre for Cancer Research, Westmead Institute for Medical Research, Sydney, Australia
- John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Georgina Long
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Royal North Shore Hospital, Sydney, Australia
| | - Paul D P Pharoah
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | | | - Anne E Cust
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, Sydney, Australia
| | - Goncalo Abecasis
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - David L Duffy
- Dermatology Research Centre, The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - David C Whiteman
- Cancer Control Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Helen Gogas
- First Department of Internal Medicine, Laikon General Hospital Greece, National and Kapodistrian University of Athens, Athens, Greece
| | - Arcangela De Nicolo
- Cancer Genomics Program, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Margaret A Tucker
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Ketty Peris
- Institute of Dermatology, Catholic University, Rome, Italy
- Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Florence Demenais
- Genetic Epidemiology and Functional Genomics of Multifactorial Diseases Team, Institut National de la Santé et de la Recherche Médicale (INSERM), UMRS-1124, Université Paris Descartes, Paris, France
| | - Kevin M Brown
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Susana Puig
- Dermatology Department, Melanoma Unit, Hospital Clínic de Barcelona, IDIBAPS, Universitat de Barcelona, CIBERER, Barcelona, Spain
| | - Eduardo Nagore
- Department of Dermatology, Instituto Valenciano de Oncología, Valencia, Spain
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mark M Iles
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
| |
Collapse
|
30
|
Dalmasso B, Ghiorzo P. Evolution of approaches to identify melanoma missing heritability. Expert Rev Mol Diagn 2020; 20:523-531. [PMID: 32124637 DOI: 10.1080/14737159.2020.1738221] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 03/02/2020] [Indexed: 02/08/2023]
Abstract
Introduction: Around 10% of melanoma patients have a positive family history of melanoma and/or related cancers. Although a germline pathogenic variant in a high-risk gene can be identified in up to 40% of these patients, the remaining part of melanoma heritability remains largely unexplained.Areas covered: The aim of this review is to provide an overview of the impact that new technologies and new research approaches had and are having on finding more efficient ways to unravel the missing heritability in melanoma.Expert opinion: High-throughput sequencing technologies have been crucial in increasing the number of genes/loci that might be implicated in melanoma predisposition. However, results from these approaches may have been inferior to the expectations, due to an increase in quantitative information which hasn't been followed at the same speed by an improvement of the methods to correctly interpret these data. Optimal approaches for improving our knowledge on melanoma heritability are currently based on segregation analysis coupled with functional assessment of candidate genes. An improvement of computational methods to infer genotype-phenotype correlations could help address the issue of missing heritability.
Collapse
Affiliation(s)
- Bruna Dalmasso
- Department of Internal Medicine and Medical Specialties, University of Genoa, Genova, Italy
- IRCCS Ospedale Policlinico San Martino, Genetics of Rare Cancers, Genoa, Italy
| | - Paola Ghiorzo
- Department of Internal Medicine and Medical Specialties, University of Genoa, Genova, Italy
- IRCCS Ospedale Policlinico San Martino, Genetics of Rare Cancers, Genoa, Italy
| |
Collapse
|
31
|
van der Spek A, Warner SC, Broer L, Nelson CP, Vojinovic D, Ahmad S, Arp PP, Brouwer RWW, Denniff M, van den Hout MCGN, van Rooij JGJ, Kraaij R, van IJcken WFJ, Samani NJ, Ikram MA, Uitterlinden AG, Codd V, Amin N, van Duijn CM. Exome Sequencing Analysis Identifies Rare Variants in ATM and RPL8 That Are Associated With Shorter Telomere Length. Front Genet 2020; 11:337. [PMID: 32425970 PMCID: PMC7204400 DOI: 10.3389/fgene.2020.00337] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 03/20/2020] [Indexed: 01/04/2023] Open
Abstract
Telomeres are important for maintaining genomic stability. Telomere length has been associated with aging, disease, and mortality and is highly heritable (∼82%). In this study, we aimed to identify rare genetic variants associated with telomere length using whole-exome sequence data. We studied 1,303 participants of the Erasmus Rucphen Family (ERF) study, 1,259 of the Rotterdam Study (RS), and 674 of the British Heart Foundation Family Heart Study (BHF-FHS). We conducted two analyses, first we analyzed the family-based ERF study and used the RS and BHF-FHS for replication. Second, we combined the summary data of the three studies in a meta-analysis. Telomere length was measured by quantitative polymerase chain reaction in blood. We identified nine rare variants significantly associated with telomere length (p-value < 1.42 × 10–7, minor allele frequency of 0.2–0.5%) in the ERF study. Eight of these variants (in C11orf65, ACAT1, NPAT, ATM, KDELC2, and EXPH5) were located on chromosome 11q22.3 that contains ATM, a gene involved in telomere maintenance. Although we were unable to replicate the variants in the RS and BHF-FHS (p-value ≥ 0.21), segregation analysis showed that all variants segregate with shorter telomere length in a family. In the meta-analysis of all studies, a nominally significant association with LTL was observed with a rare variant in RPL8 (p-value = 1.48 × 10−6), which has previously been associated with age. Additionally, a novel rare variant in the known RTEL1 locus showed suggestive evidence for association (p-value = 1.18 × 10–4) with LTL. To conclude, we identified novel rare variants associated with telomere length. Larger samples size are needed to confirm these findings and to identify additional variants.
Collapse
Affiliation(s)
- Ashley van der Spek
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,SkylineDx B.V., Rotterdam, Netherlands
| | - Sophie C Warner
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | - Linda Broer
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.,NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Pascal P Arp
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Rutger W W Brouwer
- Center for Biomics, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | | | - Jeroen G J van Rooij
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Neurology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Wilfred F J van IJcken
- Center for Biomics, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.,NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.,NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
32
|
Identification of a Gene-Related Risk Signature in Melanoma Patients Using Bioinformatic Profiling. JOURNAL OF ONCOLOGY 2020; 2020:7526204. [PMID: 32411243 PMCID: PMC7206882 DOI: 10.1155/2020/7526204] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 01/21/2020] [Indexed: 01/15/2023]
Abstract
Introduction Gene signature has been used to predict prognosis in melanoma patients. Meanwhile, the efficacy of immunotherapy was correlated with particular genes expression or mutation. In this study, we systematically explored the gene expression pattern in the melanoma-immune microenvironment and its relationship with prognosis. Methods A cohort of 122 melanoma cases with whole-genome microarray expression data were enrolled from the Gene Expression Omnibus (GEO) database. The findings were validated using The Cancer Genome Atlas (TCGA) database. A principal component analysis (PCA), gene set enrichment analysis (GSEA), and gene oncology (GO) analysis were performed to explore the bioinformatic implications. Results Different gene expression patterns were identified according to the clinical stage. All eligible gene sets were analyzed, and the 8 genes (GPR87, KIT, SH3GL3, PVRL1, ATP1B1, CDAN1, FAU, and TNFSF14) with the greatest prognostic impact on melanoma. A gene-related risk signature was developed to distinguish patients with a high or low risk of an unfavorable outcome, and this signature was validated using the TCGA database. Furthermore, the prognostic significance of the signature between the classified subgroups was verified as an independent prognostic predictor of melanoma. Additionally, the low-risk melanoma patients presented an enhanced immune phenotype compared to that of the high-risk gene signature patients. Conclusions The gene pattern differences in melanoma were profiled, and a gene signature that could independently predict melanoma patients with a high risk of poor survival was established, highlighting the relationship between prognosis and the local immune response.
Collapse
|
33
|
Hartl M, Puglisi K, Nist A, Raffeiner P, Bister K. The brain acid-soluble protein 1 (BASP1) interferes with the oncogenic capacity of MYC and its binding to calmodulin. Mol Oncol 2020; 14:625-644. [PMID: 31944520 PMCID: PMC7053243 DOI: 10.1002/1878-0261.12636] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Revised: 12/16/2019] [Accepted: 01/09/2020] [Indexed: 12/13/2022] Open
Abstract
The MYC protein is a transcription factor with oncogenic potential controlling fundamental cellular processes such as cell proliferation, metabolism, differentiation, and apoptosis. The MYC gene is a major cancer driver, and elevated MYC protein levels are a hallmark of most human cancers. We have previously shown that the brain acid-soluble protein 1 gene (BASP1) is specifically downregulated by the v-myc oncogene and that ectopic BASP1 expression inhibits v-myc-induced cell transformation. The 11-amino acid effector domain of the BASP1 protein interacts with the calcium sensor calmodulin (CaM) and is mainly responsible for this inhibitory function. We also reported recently that CaM interacts with all MYC variant proteins and that ectopic CaM increases the transactivation and transformation potential of the v-Myc protein. Here, we show that the presence of excess BASP1 or of a synthetic BASP1 effector domain peptide leads to displacement of v-Myc from CaM. The protein stability of v-Myc is decreased in cells co-expressing v-Myc and BASP1, which may account for the inhibition of v-Myc. Furthermore, suppression of v-Myc-triggered transcriptional activation and cell transformation is compensated by ectopic CaM, suggesting that BASP1-mediated withdrawal of CaM from v-Myc is a crucial event in the inhibition. In view of the tumor-suppressive role of BASP1 which was recently also reported for human cancer, small compounds or peptides based on the BASP1 effector domain could be used in drug development strategies aimed at tumors with high MYC expression.
Collapse
Affiliation(s)
- Markus Hartl
- Institute of Biochemistry and Center for Molecular Biosciences (CMBI)University of InnsbruckAustria
| | - Kane Puglisi
- Institute of Biochemistry and Center for Molecular Biosciences (CMBI)University of InnsbruckAustria
| | - Andrea Nist
- Institute of Biochemistry and Center for Molecular Biosciences (CMBI)University of InnsbruckAustria
- Present address:
Genomics Core FacilityPhilipps University of MarburgGermany
| | - Philipp Raffeiner
- Institute of Biochemistry and Center for Molecular Biosciences (CMBI)University of InnsbruckAustria
- Present address:
Department of Molecular MedicineScripps ResearchLa JollaCAUSA
| | - Klaus Bister
- Institute of Biochemistry and Center for Molecular Biosciences (CMBI)University of InnsbruckAustria
| |
Collapse
|
34
|
Liyanage UE, Law MH, Han X, An J, Ong JS, Gharahkhani P, Gordon S, Neale RE, Olsen CM, MacGregor S, Whiteman DC. Combined analysis of keratinocyte cancers identifies novel genome-wide loci. Hum Mol Genet 2019; 28:3148-3160. [PMID: 31174203 PMCID: PMC6737293 DOI: 10.1093/hmg/ddz121] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 05/30/2019] [Accepted: 06/03/2019] [Indexed: 12/12/2022] Open
Abstract
The keratinocyte cancers (KC), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common cancers in fair-skinned people. KC treatment represents the second highest cancer healthcare expenditure in Australia. Increasing our understanding of the genetic architecture of KC may provide new avenues for prevention and treatment. We first conducted a series of genome-wide association studies (GWAS) of KC across three European ancestry datasets from Australia, Europe and USA, and used linkage disequilibrium (LD) Score regression (LDSC) to estimate their pairwise genetic correlations. We employed a multiple-trait approach to map genes across the combined set of KC GWAS (total N = 47 742 cases, 634 413 controls). We also performed meta-analyses of BCC and SCC separately to identify trait specific loci. We found substantial genetic correlations (generally 0.5-1) between BCC and SCC suggesting overlapping genetic risk variants. The multiple trait combined KC GWAS identified 63 independent genome-wide significant loci, 29 of which were novel. Individual separate meta-analyses of BCC and SCC identified an additional 13 novel loci not found in the combined KC analysis. Three new loci were implicated using gene-based tests. New loci included common variants in BRCA2 (distinct to known rare high penetrance cancer risk variants), and in CTLA4, a target of immunotherapy in melanoma. We found shared and trait specific genetic contributions to BCC and SCC. Considering both, we identified a total of 79 independent risk loci, 45 of which are novel.
Collapse
Affiliation(s)
- Upekha E Liyanage
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Matthew H Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Xikun Han
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Jiyuan An
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Jue-Sheng Ong
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Puya Gharahkhani
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Rachel E Neale
- Cancer Aetiology and Prevention, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - Catherine M Olsen
- Cancer Control Group, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD 4006, Australia
| | | | - Stuart MacGregor
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| | - David C Whiteman
- Cancer Control Group, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia
| |
Collapse
|
35
|
Roberts MR, Asgari MM, Toland AE. Genome-wide association studies and polygenic risk scores for skin cancer: clinically useful yet? Br J Dermatol 2019; 181:1146-1155. [PMID: 30908599 DOI: 10.1111/bjd.17917] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2019] [Indexed: 12/27/2022]
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified thousands of susceptibility variants, although most have been associated with small individual risk estimates that offer little predictive value. However, combining multiple variants into polygenic risk scores (PRS) may be more informative. Multiple studies have developed PRS composed of GWAS-identified variants for cutaneous cancers. This review highlights data from these studies. OBJECTIVES To review published GWAS and PRS studies for melanoma, cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC), and discuss their potential clinical utility. METHODS We searched PubMed and the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue to identify relevant studies. RESULTS Results from 21 GWAS (11 melanoma, 3 cSCC, 7 BCC) and 11 PRS studies are summarized. Six loci in pigmentation genes overlap between these three cancers (ASIP/RALY, IRF4, MC1R, OCA2, SLC45A2 and TYR). Additional loci overlap for cSCC/BCC and BCC/melanoma, but no other loci are shared between cSCC and melanoma. PRS for melanoma show roughly two-to-threefold increases in risk and modest improvements in risk prediction (2-7% increases). PRS are associated with twofold and threefold increases in risk of cSCC and BCC, respectively, with small improvements (2% increase) in predictive ability. CONCLUSIONS Existing data indicate that PRS may offer small, but potentially meaningful, improvements to risk prediction. Additional research is needed to clarify the potential utility of PRS in cutaneous carcinomas. Clinical translation will require well-powered validation studies incorporating known risk factors to evaluate PRS as tools for screening. What's already known about this topic? Over 50 susceptibility loci for melanoma, basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) have been identified in genome-wide association studies (GWAS). Polygenic risk scores (PRS) using variants identified from GWAS have also been developed for melanoma, BCC and cSCC, and investigated with respect to clinical risk prediction. What does this study add? This review provides an overview of GWAS findings and the potential clinical utility of PRS for melanoma, BCC and cSCC.
Collapse
Affiliation(s)
- M R Roberts
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, U.S.A.,Department of Population Medicine, Harvard Pilgrim Healthcare Institute, Boston, MA, U.S.A
| | - M M Asgari
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, U.S.A.,Department of Population Medicine, Harvard Pilgrim Healthcare Institute, Boston, MA, U.S.A
| | - A E Toland
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, Ohio State University, 998 Biomedical Research Tower, 460 W 12th Ave, Columbus, OH, 43210, U.S.A
| |
Collapse
|
36
|
Edwards TL, Giri A, Hellwege JN, Hartmann KE, Stewart EA, Jeff JM, Bray MJ, Pendergrass SA, Torstenson ES, Keaton JM, Jones SH, Gogoi RP, Kuivaniemi H, Jackson KL, Kho AN, Kullo IJ, McCarty CA, Im HK, Pacheco JA, Pathak J, Williams MS, Tromp G, Kenny EE, Peissig PL, Denny JC, Roden DM, Velez Edwards DR. A Trans-Ethnic Genome-Wide Association Study of Uterine Fibroids. Front Genet 2019; 10:511. [PMID: 31249589 PMCID: PMC6582231 DOI: 10.3389/fgene.2019.00511] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 05/10/2019] [Indexed: 01/02/2023] Open
Abstract
Uterine fibroids affect up to 77% of women by menopause and account for up to $34 billion in healthcare costs each year. Although fibroid risk is heritable, genetic risk for fibroids is not well understood. We conducted a two-stage case-control meta-analysis of genetic variants in European and African ancestry women with and without fibroids classified by a previously published algorithm requiring pelvic imaging or confirmed diagnosis. Women from seven electronic Medical Records and Genomics (eMERGE) network sites (3,704 imaging-confirmed cases and 5,591 imaging-confirmed controls) and women of African and European ancestry from UK Biobank (UKB, 5,772 cases and 61,457 controls) were included in the discovery genome-wide association study (GWAS) meta-analysis. Variants showing evidence of association in Stage I GWAS (P < 1 × 10-5) were targeted in an independent replication sample of African and European ancestry individuals from the UKB (Stage II) (12,358 cases and 138,477 controls). Logistic regression models were fit with genetic markers imputed to a 1000 Genomes reference and adjusted for principal components for each race- and site-specific dataset, followed by fixed-effects meta-analysis. Final analysis with 21,804 cases and 205,525 controls identified 326 genome-wide significant variants in 11 loci, with three novel loci at chromosome 1q24 (sentinel-SNP rs14361789; P = 4.7 × 10-8), chromosome 16q12.1 (sentinel-SNP rs4785384; P = 1.5 × 10-9) and chromosome 20q13.1 (sentinel-SNP rs6094982; P = 2.6 × 10-8). Our statistically significant findings further support previously reported loci including SNPs near WT1, TNRC6B, SYNE1, BET1L, and CDC42/WNT4. We report evidence of ancestry-specific findings for sentinel-SNP rs10917151 in the CDC42/WNT4 locus (P = 1.76 × 10-24). Ancestry-specific effect-estimates for rs10917151 were in opposite directions (P-Het-between-groups = 0.04) for predominantly African (OR = 0.84) and predominantly European women (OR = 1.16). Genetically-predicted gene expression of several genes including LUZP1 in vagina (P = 4.6 × 10-8), OBFC1 in esophageal mucosa (P = 8.7 × 10-8), NUDT13 in multiple tissues including subcutaneous adipose tissue (P = 3.3 × 10-6), and HEATR3 in skeletal muscle tissue (P = 5.8 × 10-6) were associated with fibroids. The finding for HEATR3 was supported by SNP-based summary Mendelian randomization analysis. Our study suggests that fibroid risk variants act through regulatory mechanisms affecting gene expression and are comprised of alleles that are both ancestry-specific and shared across continental ancestries.
Collapse
Affiliation(s)
- Todd L. Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Ayush Giri
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Jacklyn N. Hellwege
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Katherine E. Hartmann
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Elizabeth A. Stewart
- Division of Reproductive Endocrinology and Infertility, Departments of Obstetrics and Gynecology and Surgery, Mayo Clinic, Rochester, MN, United States
| | - Janina M. Jeff
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Michael J. Bray
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Sarah A. Pendergrass
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA, United States
| | - Eric S. Torstenson
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jacob M. Keaton
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Sarah H. Jones
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Radhika P. Gogoi
- Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, United States
| | - Helena Kuivaniemi
- Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, United States
- SAMRC-SHIP South African Tuberculosis Bioinformatics Initiative, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Kathryn L. Jackson
- Center for Health Information Partnerships, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Abel N. Kho
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Iftikhar J. Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, United States
| | - Catherine A. McCarty
- Department of Family Medicine and Behavioral Health, University of Minnesota Medical School, Duluth, MN, United States
| | - Hae Kyung Im
- Department of Medicine, University of Chicago, Chicago, IL, United States
| | - Jennifer A. Pacheco
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Jyotishman Pathak
- Division of Health Informatics, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY, United States
| | - Marc S. Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Gerard Tromp
- Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, United States
- SAMRC-SHIP South African Tuberculosis Bioinformatics Initiative, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Eimear E. Kenny
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Center for Statistical Genetics, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Peggy L. Peissig
- Biomedical Informatics Research Center, Marshfield Clinic Research Institute, Marshfield, WI, United States
| | - Joshua C. Denny
- Department of Biomedical Informatics and Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Dan M. Roden
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Digna R. Velez Edwards
- Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University School of Medicine, Nashville, TN, United States
| |
Collapse
|
37
|
Fritsche LG, Beesley LJ, VandeHaar P, Peng RB, Salvatore M, Zawistowski M, Gagliano Taliun SA, Das S, LeFaive J, Kaleba EO, Klumpner TT, Moser SE, Blanc VM, Brummett CM, Kheterpal S, Abecasis GR, Gruber SB, Mukherjee B. Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb. PLoS Genet 2019; 15:e1008202. [PMID: 31194742 PMCID: PMC6592565 DOI: 10.1371/journal.pgen.1008202] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 06/25/2019] [Accepted: 05/17/2019] [Indexed: 01/08/2023] Open
Abstract
Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods.
Collapse
Affiliation(s)
- Lars G. Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Lauren J. Beesley
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Peter VandeHaar
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Robert B. Peng
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Maxwell Salvatore
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Matthew Zawistowski
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Sarah A. Gagliano Taliun
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Sayantan Das
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Jonathon LeFaive
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Erin O. Kaleba
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Thomas T. Klumpner
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Stephanie E. Moser
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Victoria M. Blanc
- Central Biorepository, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Chad M. Brummett
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sachin Kheterpal
- Division of Pain Medicine, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Gonçalo R. Abecasis
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
| | - Stephen B. Gruber
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- Michigan Institute for Data Science, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America
- University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America
| |
Collapse
|
38
|
Hartl M, Schneider R. A Unique Family of Neuronal Signaling Proteins Implicated in Oncogenesis and Tumor Suppression. Front Oncol 2019; 9:289. [PMID: 31058089 PMCID: PMC6478813 DOI: 10.3389/fonc.2019.00289] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 03/29/2019] [Indexed: 12/20/2022] Open
Abstract
The neuronal proteins GAP43 (neuromodulin), MARCKS, and BASP1 are highly expressed in the growth cones of nerve cells where they are involved in signal transmission and cytoskeleton organization. Although their primary structures are unrelated, these signaling proteins share several structural properties like fatty acid modification, and the presence of cationic effector domains. GAP43, MARCKS, and BASP1 bind to cell membrane phospholipids, a process reversibly regulated by protein kinase C-phosphorylation or by binding to the calcium sensor calmodulin (CaM). GAP43, MARCKS, and BASP1 are also expressed in non-neuronal cells, where they may have important functions to manage cytoskeleton architecture, and in case of MARCKS and BASP1 to act as cofactors in transcriptional regulation. During neoplastic cell transformation, the proteins reveal differential expression in normal vs. tumor cells, and display intrinsic tumor promoting or tumor suppressive activities. Whereas GAP43 and MARCKS are oncogenic, tumor suppressive functions have been ascribed to BASP1 and in part to MARCKS depending on the cell type. Like MARCKS, the myristoylated BASP1 protein is localized both in the cytoplasm and in the cell nucleus. Nuclear BASP1 participates in gene regulation converting the Wilms tumor transcription factor WT1 from an oncoprotein into a tumor suppressor. The BASP1 gene is downregulated in many human tumor cell lines particularly in those derived from leukemias, which display elevated levels of WT1 and of the major cancer driver MYC. BASP1 specifically inhibits MYC-induced cell transformation in cultured cells. The tumor suppressive functions of BASP1 and MARCKS could be exploited to expand the spectrum of future innovative therapeutic approaches to inhibit growth and viability of susceptible human tumors.
Collapse
Affiliation(s)
- Markus Hartl
- Center of Molecular Biosciences (CMBI), Institute of Biochemistry, University of Innsbruck, Innsbruck, Austria
| | - Rainer Schneider
- Center of Molecular Biosciences (CMBI), Institute of Biochemistry, University of Innsbruck, Innsbruck, Austria
| |
Collapse
|
39
|
Shi Z, Yu H, Wu Y, Lin X, Bao Q, Jia H, Perschon C, Duggan D, Helfand BT, Zheng SL, Xu J. Systematic evaluation of cancer-specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts. Cancer Med 2019; 8:3196-3205. [PMID: 30968590 PMCID: PMC6558466 DOI: 10.1002/cam4.2143] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 03/01/2019] [Accepted: 03/18/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Genetic risk score (GRS) is an odds ratio (OR)-weighted and population-standardized method for measuring cumulative effect of multiple risk-associated single nucleotide polymorphisms (SNPs). We hypothesize that GRS is a valid tool for risk assessment of most common cancers. METHODS Utilizing genotype and phenotype data from The Cancer Genome Atlas (TCGA) and Electronic Medical Records and Genomics (eMERGE), we tested 11 cancer-specific GRSs (bladder, breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, prostate, renal, and thyroid cancer) for association with the respective cancer type. Cancer-specific GRSs were calculated, for the first time in these cohorts, based on previously published risk-associated SNPs using the Caucasian subjects in these two cohorts. RESULTS Mean cancer-specific GRS in the population controls of eMERGE approximated the expected value of 1.00 (between 0.98 and 1.02) for all 11 types of cancer. Mean cancer-specific GRS was consistently higher in respective cancer patients than controls for all 11 types of cancer (P < 0.05). When subjects were categorized into low-, average-, and high-risk groups based on cancer-specific GRS (<0.5, 0.5-1.5, and >1.5, respectively), significant dose-response associations of higher cancer-specific GRS with higher OR of respective type of cancer were found for nine types of cancer (P-trend < 0.05). More than 64% subjects in the population controls of eMERGE can be classified as high risk for at least one type of these cancers. CONCLUSION Validity of GRS for predicting cancer risk is demonstrated for most types of cancer. If confirmed in larger studies, cancer-specific GRS may have the potential for developing personalized cancer screening strategy.
Collapse
Affiliation(s)
- Zhuqing Shi
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.,State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, China
| | - Hongjie Yu
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois
| | - Yishuo Wu
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoling Lin
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, China.,Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Quanwa Bao
- State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, China
| | - Haifei Jia
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Chelsea Perschon
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois
| | - David Duggan
- Translational Genomics Research Institute, Phoenix, Arizona
| | - Brian T Helfand
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois
| | - Siqun L Zheng
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois
| | - Jianfeng Xu
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.,State Key Laboratory of Genetic Engineering, School of Life Science, Fudan University, Shanghai, China.,Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
| |
Collapse
|
40
|
Chattopadhyay S, Hemminki A, Försti A, Sundquist K, Sundquist J, Hemminki K. Familial Risks and Mortality in Second Primary Cancers in Melanoma. JNCI Cancer Spectr 2019; 2:pky068. [PMID: 31360883 PMCID: PMC6649697 DOI: 10.1093/jncics/pky068] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 10/09/2018] [Accepted: 10/19/2018] [Indexed: 12/11/2022] Open
Abstract
Background Malignant melanoma (MM) patients are at increasing risk of developing second primary cancers (SPCs). We assessed mortality and risk of SPCs in MM patients with siblings or parents affected with same cancer compared with that of the general population. Methods We used the Swedish Family-Cancer Database to assess relative risks (RRs) and causes of death in SPCs until 2015 in patients with a MM diagnosis between 1958 and 2015. We identified 35 451patients with MM among whom 3212 received a subsequent diagnosis of SPC. RRs of SPCs after MM diagnosis were calculated stratifying over concordant family history of cancer in first-degree relatives. Results Familial RRs were increased for second melanoma (RR = 19.28, 95% CI = 16.71 to 22.25), squamous cell skin cancer (RR = 7.58, 95% CI = 5.57 to 10.29), leukemia (RR = 5.69, 95% CI = 2.96 to 10.94), bladder (RR = 4.15, 95% CI = 2.50 to 6.89), ovarian (RR = 3.89, 95% CI = 1.46 to 10.37), kidney cancer (RR = 3.77, 95% CI = 1.57 to 9.06), cancer of unknown primary (RR = 3.67, 95% CI = 1.65 to 8.16), nervous system (RR = 2.88, 95% CI = 1.20 to 6.93), breast (RR = 2.34, 95% CI = 1.92 to 2.84), lung (RR = 2.24, 95% CI = 1.50 to 3.35), and prostate cancer (RR = 2.22, 95% CI = 1.89 to 2.61) with statistical significance. For all cancers, familial RR was in excess (2.09, 95% CI = 2.02 to 2.16 vs 1.78, 95% CI = 1.69 to 1.87; Ptrend < .0001). Cause of death in MM patients with SPC is shown to be dependent on the cancer site though SPCs contributed to majority of deaths. Conclusions SPCs appear higher with prior family history of cancer and contribute to mortality. SPC was the most common cause of death in patients with SPC and is almost uniformly the major contributing cause of death for all cancer sites. For improved survival in MM patients, prevention and early detection of SPCs would be important.
Collapse
Affiliation(s)
- Subhayan Chattopadhyay
- Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany
| | - Akseli Hemminki
- Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland.,Cancer Gene Therapy Group, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Asta Försti
- Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany.,Cancer Gene Therapy Group, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kristina Sundquist
- Cancer Gene Therapy Group, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY.,Center for Community-based Healthcare Research and Education (CoHRE) Department of Functional Pathology, School of Medicine, Shimane University, Matsue, Japan
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden.,Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY.,Center for Community-based Healthcare Research and Education (CoHRE) Department of Functional Pathology, School of Medicine, Shimane University, Matsue, Japan
| | - Kari Hemminki
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| |
Collapse
|
41
|
Ostrom QT, Coleman W, Huang W, Rubin JB, Lathia JD, Berens ME, Speyer G, Liao P, Wrensch MR, Eckel-Passow JE, Armstrong G, Rice T, Wiencke JK, McCoy LS, Hansen HM, Amos CI, Bernstein JL, Claus EB, Houlston RS, Il’yasova D, Jenkins RB, Johansen C, Lachance DH, Lai RK, Merrell RT, Olson SH, Sadetzki S, Schildkraut JM, Shete S, Andersson U, Rajaraman P, Chanock SJ, Linet MS, Wang Z, Yeager M, Melin B, Bondy ML, Barnholtz-Sloan JS. Sex-specific gene and pathway modeling of inherited glioma risk. Neuro Oncol 2019; 21:71-82. [PMID: 30124908 PMCID: PMC6303471 DOI: 10.1093/neuonc/noy135] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Background To date, genome-wide association studies (GWAS) have identified 25 risk variants for glioma, explaining 30% of heritable risk. Most histologies occur with significantly higher incidence in males, and this difference is not explained by currently known risk factors. A previous GWAS identified sex-specific glioma risk variants, and this analysis aims to further elucidate risk variation by sex using gene- and pathway-based approaches. Methods Results from the Glioma International Case-Control Study were used as a testing set, and results from 3 GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for nominally significant autosomal SNPs (P < 0.01 in a previous meta-analysis) and nominally significant X-chromosome SNPs (P < 0.01), 3 algorithms (Pascal, BimBam, and GATES) were used to generate gene scores, and Pascal was used to generate pathway scores. Results were considered statistically significant in the discovery set when P < 3.3 × 10-6 and in the validation set when P < 0.001 in 2 of 3 algorithms. Results Twenty-five genes within 5 regions and 19 genes within 6 regions reached statistical significance in at least 2 of 3 algorithms in males and females, respectively. EGFR was significantly associated with all glioma and glioblastoma in males only and a female-specific association in TERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the BioCarta telomeres pathway in both males and females. Conclusions These results provide additional evidence that there may be differences by sex in genetic risk for glioma. Additional analyses may further elucidate the biological processes through which this risk is conferred.
Collapse
Affiliation(s)
- Quinn T Ostrom
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | | | - William Huang
- Case Western Reserve University, Cleveland, Ohio, USA
| | - Joshua B Rubin
- Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, USA; Department of Neuroscience, Washington University School of Medicine, St Louis, Missouri, USA
| | - Justin D Lathia
- Department of Stem Cell Biology and Regenerative Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Michael E Berens
- Cancer and Cell Biology Division, The Translational Genomics Research Institute, Phoenix, Arizona, USA
| | - Gil Speyer
- Cancer and Cell Biology Division, The Translational Genomics Research Institute, Phoenix, Arizona, USA
| | - Peter Liao
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Margaret R Wrensch
- Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Jeanette E Eckel-Passow
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Georgina Armstrong
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Terri Rice
- Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - John K Wiencke
- Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Lucie S McCoy
- Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Helen M Hansen
- Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Jonine L Bernstein
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Elizabeth B Claus
- School of Public Health, Yale University, New Haven, Connecticut, USA
- Department of Neurosurgery, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom
| | - Dora Il’yasova
- Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia, USA
- Cancer Control and Prevention Program, Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina, USA
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Robert B Jenkins
- Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Christoffer Johansen
- Oncology Clinic, Finsen Center, Rigshospitalet and Survivorship Research Unit, The Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Daniel H Lachance
- Department of Neurology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Rose K Lai
- Departments of Neurology and Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Ryan T Merrell
- Department of Neurology, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Sara H Olson
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Siegal Sadetzki
- Cancer and Radiation Epidemiology Unit, Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Joellen M Schildkraut
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | | | - Ulrika Andersson
- Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Preetha Rajaraman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, USA
| | - Martha S Linet
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, USA
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
- Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, USA
| | - Beatrice Melin
- Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden
| | - Melissa L Bondy
- Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Jill S Barnholtz-Sloan
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| |
Collapse
|
42
|
Ozola A, Ruklisa D, Pjanova D. Association of the 16q24.3 region gene variants rs1805007 and rs4785763 with heightened risk of melanoma in Latvian population. Meta Gene 2018. [DOI: 10.1016/j.mgene.2018.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
|
43
|
An atlas of genetic associations in UK Biobank. Nat Genet 2018; 50:1593-1599. [PMID: 30349118 DOI: 10.1038/s41588-018-0248-z] [Citation(s) in RCA: 408] [Impact Index Per Article: 58.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 08/29/2018] [Indexed: 12/20/2022]
Abstract
Genome-wide association studies (GWAS) have identified many loci contributing to variation in complex traits, yet the majority of loci that contribute to the heritability of complex traits remain elusive. Large study populations with sufficient statistical power are required to detect the small effect sizes of the yet unidentified genetic variants. However, the analysis of huge cohorts, like UK Biobank, is challenging. Here, we present an atlas of genetic associations for 118 non-binary and 660 binary traits of 452,264 UK Biobank participants of European ancestry. Results are compiled in a publicly accessible database that allows querying genome-wide association results for 9,113,133 genetic variants, as well as downloading GWAS summary statistics for over 30 million imputed genetic variants (>23 billion phenotype-genotype pairs). Our atlas of associations (GeneATLAS, http://geneatlas.roslin.ed.ac.uk ) will help researchers to query UK Biobank results in an easy and uniform way without the need to incur high computational costs.
Collapse
|
44
|
Bradbury C, Köttgen A, Staubach F. Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource. Forensic Sci Int Genet 2018; 38:93-104. [PMID: 30391626 DOI: 10.1016/j.fsigen.2018.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 08/27/2018] [Accepted: 10/13/2018] [Indexed: 01/04/2023]
Abstract
With recent advances in DNA sequencing technologies it has become feasible and cost effective to genotype larger marker sets for forensic purposes. Two technologies that make use of the larger marker sets have come into focus in forensic research and applications; inference of biogeographic ancestry (BGA) and forensic DNA phenotyping (FDP). These methods hold the promise to reveal information about a yet unknown perpetrator from a DNA sample. In contrast, DNA-profiling, that is a standard practice in case work, relies on matching DNA-profiles between crime scene material and suspects on a database of DNA-profiles. Markers for DNA-profiling were developed under the premise to reveal as little additional information about the human source of the profile as possible, the rationale being that personal privacy rights have to be balanced against the public interest in solving a crime. The same argument holds for markers used in BGA and FDP; these markers might also reveal information on off-target phenotypes (OTPs), that go beyond BGA and the phenotypes targeted in FDP. In particular, health related OTPs might shift the balance between privacy protection and public interest. However, to our knowledge, there is currently no convenient resource available to incorporate knowledge on OTPs in BGA and FDP assay design and application. In order to provide such a resource, we performed a systematic search for OTPs associated with a comprehensive set of markers (1766 SNPs) used or suggested to be used for BGA inference and FDP. In this set, we identified a relatively small number of 27 SNPs (1.53%) that convey information on diverse health related OTPs such as cancer risk, induced asthma, or risk of alcoholism. Some of these SNPs are commonly used for FDP and BGA across different marker sets. We conclude that the effects of SNP markers used in FDP and BGA on OTPs are currently limited, with few exceptions that should be considered in a balanced decision on assay design and application.
Collapse
Affiliation(s)
- Cedric Bradbury
- University College Freiburg, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Dept. of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Fabian Staubach
- Institute of Biology I, Dept. of Evolutionary Biology and Ecology, Albert-Ludwigs-University Freiburg, Freiburg, Germany.
| |
Collapse
|
45
|
Sikora M, Rudnicka L, Borkowska B, Kardynał A, Słowińska M, Rakowska A, Warszawik-Hendzel O, Wiergowska A, Ługowska I, Rutkowski P, Dębniak T, Lubiński J, Olszewska M. Genetic polymorphisms may influence the vertical growth rate of melanoma. J Cancer 2018; 9:3078-3083. [PMID: 30210630 PMCID: PMC6134810 DOI: 10.7150/jca.26404] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Accepted: 07/09/2018] [Indexed: 01/10/2023] Open
Abstract
Background: Identification of new predictive markers in melanoma is of great clinical importance. This study was aimed to analyze association between selected common variants in the cancer susceptibility genes and melanoma progression at the time of diagnosis. Material and Method: The study included 243 consecutive patients with melanoma. Genotyping was performed using real-time PCR. Results: Our data revealed modest association between xeroderma pigmentosum complementation group D (XPD) codon 312 polymorphism and tumor thickness (as defined by Breslow score; XPD D312N CC: 3.00 ± 3.78mm, CT: 1.71 ± 2.48mm, TT: 2,53 ± 3,24mm, P=0.023). The CT genotype in XPD D312N polymorphism was more frequently represented in non-invasive melanomas compared to deeply penetrating tumors. None of the common SNPs in cyclin dependent kinase inhibitor 2A (CDKN2A), vitamin D receptor (VDR), melanocortin 1 receptor (MC1R) were associated with Breslow depth. Conclusion: These findings suggest that genetic alteration in XPD contributes to melanoma progression and may be a potential diagnostic and molecular prognostic marker.
Collapse
Affiliation(s)
- Mariusz Sikora
- Department of Dermatology, Medical University of Warsaw, 02-008 Warsaw, Poland
| | - Lidia Rudnicka
- Department of Dermatology, Medical University of Warsaw, 02-008 Warsaw, Poland
| | - Barbara Borkowska
- Department of Dermatology, Medical University of Warsaw, 02-008 Warsaw, Poland
| | - Agnieszka Kardynał
- Department of Dermatology, Central Clinical Hospital MSWiA, 02-507 Warsaw, Poland
| | - Monika Słowińska
- Department of Dermatology, Military Institute of Medicine, 04-141 Warsaw, Poland
| | - Adriana Rakowska
- Department of Dermatology, Medical University of Warsaw, 02-008 Warsaw, Poland
| | | | - Anna Wiergowska
- Department of Dermatology, Central Clinical Hospital MSWiA, 02-507 Warsaw, Poland
| | - Iwona Ługowska
- Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, 02-781 Warsaw, Poland
| | - Piotr Rutkowski
- Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, 02-781 Warsaw, Poland
| | - Tadeusz Dębniak
- Department of Genetics and Pathomorphology, Pomeranian Medical University, 70-111 Szczecin, Poland
| | - Jan Lubiński
- Department of Genetics and Pathomorphology, Pomeranian Medical University, 70-111 Szczecin, Poland
| | | |
Collapse
|
46
|
Perovic V, Sumonja N, Marsh LA, Radovanovic S, Vukicevic M, Roberts SGE, Veljkovic N. IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. Sci Rep 2018; 8:10563. [PMID: 30002402 PMCID: PMC6043496 DOI: 10.1038/s41598-018-28815-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Accepted: 06/28/2018] [Indexed: 01/04/2023] Open
Abstract
Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency.
Collapse
Affiliation(s)
- Vladimir Perovic
- Centre for Multidisciplinary Research and Engineering, Vinca Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia
| | - Neven Sumonja
- Centre for Multidisciplinary Research and Engineering, Vinca Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia
| | - Lindsey A Marsh
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Sandro Radovanovic
- Centre for business decision making, Faculty of organizational Sciences, University of Belgrade, Belgrade, Serbia
| | - Milan Vukicevic
- Centre for business decision making, Faculty of organizational Sciences, University of Belgrade, Belgrade, Serbia
| | - Stefan G E Roberts
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Nevena Veljkovic
- Centre for Multidisciplinary Research and Engineering, Vinca Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia.
| |
Collapse
|
47
|
Visconti A, Duffy DL, Liu F, Zhu G, Wu W, Chen Y, Hysi PG, Zeng C, Sanna M, Iles MM, Kanetsky PA, Demenais F, Hamer MA, Uitterlinden AG, Ikram MA, Nijsten T, Martin NG, Kayser M, Spector TD, Han J, Bataille V, Falchi M. Genome-wide association study in 176,678 Europeans reveals genetic loci for tanning response to sun exposure. Nat Commun 2018; 9:1684. [PMID: 29739929 PMCID: PMC5940788 DOI: 10.1038/s41467-018-04086-y] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 04/03/2018] [Indexed: 12/03/2022] Open
Abstract
The skin’s tendency to sunburn rather than tan is a major risk factor for skin cancer. Here we report a large genome-wide association study of ease of skin tanning in 176,678 subjects of European ancestry. We identify significant association with tanning ability at 20 loci. We confirm previously identified associations at six of these loci, and report 14 novel loci, of which ten have never been associated with pigmentation-related phenotypes. Our results also suggest that variants at the AHR/AGR3 locus, previously associated with cutaneous malignant melanoma the underlying mechanism of which is poorly understood, might act on disease risk through modulation of tanning ability. The skin’s tanning response to sun exposure shows great interindividual variability. Here, Visconti et al. perform a genome-wide association study for ease of skin tanning and identify 20 genetic loci, ten of which had not previously been associated with pigmentation-related traits.
Collapse
Affiliation(s)
- Alessia Visconti
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - David L Duffy
- QIMR Berghofer Medical Research Institute, Brisbane, 4029, Australia
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,University of Chinese Academy of Sciences, Beijing, 100049, China.,Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, 4029, Australia
| | - Wenting Wu
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis, 46202, IN, USA
| | - Yan Chen
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Pirro G Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Changqing Zeng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Marianna Sanna
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Mark M Iles
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK
| | - Peter A Kanetsky
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, 33612, FL, USA
| | - Florence Demenais
- INSERM, UMR 946, Genetic Variation and Human Diseases Unit, Paris, 75010, France.,Institut Universitaire d'Hématologie, Université Paris Diderot, Sorbonne Paris Cité, Paris, 75010, France
| | - Merel A Hamer
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, 4029, Australia
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3000 CA, The Netherlands
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Jiali Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis, 46202, IN, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, 02115, MA, USA
| | - Veronique Bataille
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK.,Department of Dermatology, West Herts NHS Trust, Herts, HP2 4AD, UK
| | - Mario Falchi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK.
| |
Collapse
|
48
|
Methylation-associated silencing of BASP1 contributes to leukemogenesis in t(8;21) acute myeloid leukemia. Exp Mol Med 2018; 50:1-8. [PMID: 29674693 PMCID: PMC5938046 DOI: 10.1038/s12276-018-0067-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 12/06/2017] [Accepted: 01/02/2018] [Indexed: 12/20/2022] Open
Abstract
The AML1-ETO fusion protein (A/E), which results from the t(8;21) translocation, is considered to be a leukemia-initiating event. Identifying the mechanisms underlying the oncogenic activity of A/E remains a major challenge. In this study, we identified a specific down-regulation of brain acid-soluble protein 1 (BASP1) in t(8;21) acute myeloid leukemia (AML). A/E recognized AML1-binding sites and recruited DNA methyltransferase 3a (DNMT3a) to the BASP1 promoter sequence, which triggered DNA methylation-mediated silencing of BASP1. Ectopic expression of BASP1 inhibited proliferation and the colony-forming ability of A/E-positive AML cell lines and led to apoptosis and cell cycle arrest. The DNMT inhibitor decitabine up-regulated the expression of BASP1 in A/E-positive AML cell lines. In conclusion, our data suggest that BASP1 silencing via promoter methylation may be involved in A/E-mediated leukemogenesis and that BASP1 targeting may be an actionable therapeutic strategy in t(8;21) AML. A chromosomal rearrangement commonly observed in certain leukemias selectively inactivates a gene that otherwise thwarts cancerous growth. Between 7 and 12% of acute myeloid leukemia cases exhibit a dramatic alteration in chromosomal structure that results in the production of an abnormal fusion protein. Researchers led by Li Yu at the General Hospital of Shenzen University in China have learned that this protein promotes disease progression by switching off an important tumor suppressor. Yu and colleagues showed that it binds a genomic sequence that regulates the gene encoding a second protein called BASP1, dramatically reducing its production. This gene silencing facilitates tumor growth. Chemicals that reactivated BASP1 production slowed proliferation and initiated ‘self-destruct’ mechanisms in leukemia cells. These findings suggest that BASP1-oriented therapies could offer a fruitful avenue of treatment for some patients.
Collapse
|
49
|
Wu W, Amos CI, Lee JE, Wei Q, Sarin KY, Han J. Inverse Relationship between Vitiligo-Related Genes and Skin Cancer Risk. J Invest Dermatol 2018; 138:2072-2075. [PMID: 29580869 DOI: 10.1016/j.jid.2018.03.1511] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 03/11/2018] [Accepted: 03/13/2018] [Indexed: 12/19/2022]
Affiliation(s)
- Wenting Wu
- Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA; Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana, USA
| | -
- 23andMe Inc., Mountain View, California, USA
| | - Christopher I Amos
- Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Jeffrey E Lee
- Department of Surgical Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | - Qingyi Wei
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina, USA; Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Kavita Y Sarin
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
| | - Jiali Han
- Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA; Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana, USA.
| |
Collapse
|