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Jiang H, Chai ZX, Cao HW, Zhang CF, Zhu Y, Zhang Q, Xin JW. Genome-wide identification of SNPs associated with body weight in yak. BMC Genomics 2022; 23:833. [PMID: 36522700 PMCID: PMC9756674 DOI: 10.1186/s12864-022-09077-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/08/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The yak is the most important livestock in the Qinghai-Tibet Plateau, and body weight directly affects the economic values of yak. Up to date, the genome-wide profiling of single-nucleotide polymorphisms (SNPs) associating with body weight has not been reported in yak. In the present study, the SNPs in 480 yaks from three breeds were analyzed using the commercial high-density (600 K) yak SNP chips. RESULTS The results identified 12 and 4 SNPs potentially associated with body weight in male and female yaks, respectively. Among them, 9 and 2 SNPs showed significant difference in yak body weight between different genotypes at each locus in male and female yaks, respectively. Further exploration found 33 coding genes within the 100 kbp upstream or downstream to the SNP loci, which might be potentially affected by the variation of SNPs. Among them, G protein-coupled receptor kinase 4 (GRK4) might be potentially affected by the SNP AX-174555047, which has been reported to affect the functioning of two body-weight associated hormones (parathyroid hormone, PTH, and adrenomedullin, ADM). Determination of PTH and ADM levels in yak revealed positive relationship between PTH level and body weight, negative relationship between ADM level and body weight along with the variation of AX-174555047 mutation. CONCLUSIONS These results suggested that the SNP AX-174555047 might potentially affect body weight through mediating GRK4 expression and then PTH and ADM functioning. Thus, the SNP AX-174555047 might be used as a biomarker for molecular breeding of yak. More investigations are required to validate this point.
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Affiliation(s)
- Hui Jiang
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, 850000 Tibet China ,grid.464485.f0000 0004 1777 7975Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Institute of Animal Science and Veterinary (TAAAS), Lhasa, 850009 Tibet China
| | - Zhi-Xin Chai
- grid.412723.10000 0004 0604 889XKey Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Southwest Minzu University, Chengdu, 610041 Sichuan China
| | - Han-Wen Cao
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, 850000 Tibet China ,grid.464485.f0000 0004 1777 7975Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Institute of Animal Science and Veterinary (TAAAS), Lhasa, 850009 Tibet China
| | - Cheng-Fu Zhang
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, 850000 Tibet China ,grid.464485.f0000 0004 1777 7975Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Institute of Animal Science and Veterinary (TAAAS), Lhasa, 850009 Tibet China
| | - Yong Zhu
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, 850000 Tibet China ,grid.464485.f0000 0004 1777 7975Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Institute of Animal Science and Veterinary (TAAAS), Lhasa, 850009 Tibet China
| | - Qiang Zhang
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, 850000 Tibet China ,grid.464485.f0000 0004 1777 7975Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Institute of Animal Science and Veterinary (TAAAS), Lhasa, 850009 Tibet China
| | - Jin-Wei Xin
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Lhasa, 850000 Tibet China ,grid.464485.f0000 0004 1777 7975Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Institute of Animal Science and Veterinary (TAAAS), Lhasa, 850009 Tibet China
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Chen HH, Petty LE, Bush W, Naj AC, Below JE. GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations. CURRENT GENETIC MEDICINE REPORTS 2019; 7:30-40. [PMID: 33312764 PMCID: PMC7731888 DOI: 10.1007/s40142-019-0159-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
PURPOSE OF REVIEW Neurodegenerative diseases, neuropsychiatric disorders, and related traits have highly complex etiologies but are also highly heritable and identifying the causal genes and biological pathways underlying these traits may advance the development of treatments and preventive strategies. While many genome-wide association studies (GWAS) have successfully identified variants contributing to polygenic neurodegenerative and neuropsychiatric phenotypes including Alzheimer's disease (AD), schizophrenia (SCZ), and bipolar disorder (BPD) amongst others, interpreting the biological roles of significantly-associated variants in the genetic architecture of these traits remains a significant challenge. Here we review several 'omics' approaches which attempt to bridge the gap from associated genetic variants to phenotype by helping define the functional roles of GWAS loci in the development of neuropsychiatric disorders and traits. RECENT FINDINGS Several common 'omics' approaches have been applied to examine neuropsychiatric traits, such as nearest-gene mapping, trans-ethnic fine mapping, annotation enrichment analysis, transcriptomic analysis, and pathway analysis, and each of these approaches has strengths and limitations in providing insight into biological mechanisms. One popular emerging method is the examination of tissue-specific genetically-regulated gene expression (GReX), which aggregates the genetic variants' effects at the gene-level. Furthermore, proteomic, metabolomic, and microbiomic studies and phenome-wide association studies will further enhance our understanding of neuropsychiatric traits. SUMMARY GWAS has been applied to neuropsychiatric traits for a decade, but our understanding about the biological function of identified variants remains limited. Today, technological advancements have created analytical approaches for integrating transcriptomics, metabolomics, proteomics, pharmacology and toxicology as tools for understanding the functional roles of genetics variants. These data, as well as the broader clinical information provided by electronic health records, can provide additional insight and complement genomic analyses.
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Affiliation(s)
- Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lauren E. Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - William Bush
- Institute for Computational Biology, Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Adam C. Naj
- Department of Biostatistics, Epidemiology, and Informatics; Department of Pathology and Laboratory Medicine; Center for Clinical Epidemiology and Biostatistics; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer E. Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
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Ferguson B, Handoko HY, Mukhopadhyay P, Chitsazan A, Balmer L, Morahan G, Walker GJ. Different genetic mechanisms mediate spontaneous versus UVR-induced malignant melanoma. eLife 2019; 8:e42424. [PMID: 30681412 PMCID: PMC6428585 DOI: 10.7554/elife.42424] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 01/25/2019] [Indexed: 12/23/2022] Open
Abstract
Genetic variation conferring resistance and susceptibility to carcinogen-induced tumorigenesis is frequently studied in mice. We have now turned this idea to melanoma using the collaborative cross (CC), a resource of mouse strains designed to discover genes for complex diseases. We studied melanoma-prone transgenic progeny across seventy CC genetic backgrounds. We mapped a strong quantitative trait locus for rapid onset spontaneous melanoma onset to Prkdc, a gene involved in detection and repair of DNA damage. In contrast, rapid onset UVR-induced melanoma was linked to the ribosomal subunit gene Rrp15. Ribosome biogenesis was upregulated in skin shortly after UVR exposure. Mechanistically, variation in the 'usual suspects' by which UVR may exacerbate melanoma, defective DNA repair, melanocyte proliferation, or inflammatory cell infiltration, did not explain melanoma susceptibility or resistance across the CC. Instead, events occurring soon after exposure, such as dysregulation of ribosome function, which alters many aspects of cellular metabolism, may be important.
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Affiliation(s)
- Blake Ferguson
- Drug Discovery GroupQIMR Berghofer Medical Research InstituteHerstonAustralia
| | - Herlina Y Handoko
- Drug Discovery GroupQIMR Berghofer Medical Research InstituteHerstonAustralia
| | - Pamela Mukhopadhyay
- Drug Discovery GroupQIMR Berghofer Medical Research InstituteHerstonAustralia
| | - Arash Chitsazan
- Drug Discovery GroupQIMR Berghofer Medical Research InstituteHerstonAustralia
| | - Lois Balmer
- Centre for Diabetes ResearchHarry Perkins Institute of Medical ResearchPerthAustralia
- School of Medical and Health SciencesEdith Cowan UniversityJoondalupAustralia
| | - Grant Morahan
- Centre for Diabetes ResearchHarry Perkins Institute of Medical ResearchPerthAustralia
| | - Graeme J Walker
- Drug Discovery GroupQIMR Berghofer Medical Research InstituteHerstonAustralia
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Duffy DL, Zhu G, Li X, Sanna M, Iles MM, Jacobs LC, Evans DM, Yazar S, Beesley J, Law MH, Kraft P, Visconti A, Taylor JC, Liu F, Wright MJ, Henders AK, Bowdler L, Glass D, Ikram MA, Uitterlinden AG, Madden PA, Heath AC, Nelson EC, Green AC, Chanock S, Barrett JH, Brown MA, Hayward NK, MacGregor S, Sturm RA, Hewitt AW, Kayser M, Hunter DJ, Newton Bishop JA, Spector TD, Montgomery GW, Mackey DA, Smith GD, Nijsten TE, Bishop DT, Bataille V, Falchi M, Han J, Martin NG. Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways. Nat Commun 2018; 9:4774. [PMID: 30429480 PMCID: PMC6235897 DOI: 10.1038/s41467-018-06649-5] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 09/13/2018] [Indexed: 11/09/2022] Open
Abstract
The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, UK, and USA comprising 52,506 individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs in KITLG and a region of 9q32. In a bivariate analysis combining the nevus results with a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B, DOCK8, and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis.
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Affiliation(s)
- David L Duffy
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Xin Li
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, 63110, USA
| | - Marianna Sanna
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital Campus, Kings College, London, UK
| | - Mark M Iles
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Leonie C Jacobs
- Department of Dermatology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - David M Evans
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | - Seyhan Yazar
- Centre for Ophthalmology and Vision Science, University of Western Australia and the Lions Eye Institute, Perth, Australia
| | | | - Matthew H Law
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | - Alessia Visconti
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital Campus, Kings College, London, UK
| | - John C Taylor
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Fan Liu
- Department of Genetic Identification, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | | | - Anjali K Henders
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Lisa Bowdler
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Dan Glass
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital Campus, Kings College, London, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, Netherlands
| | - Pamela A Madden
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Elliot C Nelson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Adele C Green
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Molecular Oncology Group, CRUK Manchester Institute, University of Manchester, Manchester, UK
| | - Stephen Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jennifer H Barrett
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Matthew A Brown
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | | | | | - Richard A Sturm
- Dermatology Research Centre, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | - Alex W Hewitt
- Centre for Ophthalmology and Vision Science, University of Western Australia and the Lions Eye Institute, Perth, Australia
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - David J Hunter
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | - Julia A Newton Bishop
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Timothy D Spector
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital Campus, Kings College, London, UK
| | - Grant W Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - David A Mackey
- Centre for Ophthalmology and Vision Science, University of Western Australia and the Lions Eye Institute, Perth, Australia
| | | | - Tamar E Nijsten
- Department of Dermatology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - D Timothy Bishop
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Veronique Bataille
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital Campus, Kings College, London, UK
| | - Mario Falchi
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital Campus, Kings College, London, UK
| | - Jiali Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, 63110, USA
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Thyagarajan A, Sahu RP. Potential Contributions of Antioxidants to Cancer Therapy: Immunomodulation and Radiosensitization. Integr Cancer Ther 2017. [PMID: 28627256 PMCID: PMC6041931 DOI: 10.1177/1534735416681639] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Antioxidants play important roles in the maintenance of cellular integrity and thus are critical in maintaining the homeostasis of the host immune system. A balance between the levels of pro-oxidants and antioxidants defines the cellular fate of genomic integrity via maintaining the redox status of the cells. An aberration in this balance modulates host immunity that affects normal cellular signaling pathways resulting in uncontrolled proliferation of cells leading to neocarcinogenesis. For decades, there have been scientific debates on the use of antioxidants for the treatment of human cancers. This review is focused on current updates on the implications of antioxidant use as adjuncts in cancer therapy with an emphasis on immunomodulation and radiosensitization.
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Affiliation(s)
| | - Ravi P. Sahu
- Wright State University, Dayton, OH, USA
- Ravi P. Sahu, Department of Pharmacology and Toxicology, Boonshoft School of Medicine, Wright State University, 230 Health Sciences Building, 3640 Colonel Glenn Highway, Dayton, OH 45435-0001, USA.
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6
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Brodie A, Azaria JR, Ofran Y. How far from the SNP may the causative genes be? Nucleic Acids Res 2016; 44:6046-54. [PMID: 27269582 PMCID: PMC5291268 DOI: 10.1093/nar/gkw500] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Revised: 05/20/2016] [Accepted: 05/22/2016] [Indexed: 02/03/2023] Open
Abstract
While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions.
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Affiliation(s)
- Aharon Brodie
- The Goodman faculty of life sciences, Nanotechnology building, Bar Ilan University, Ramat Gan 52900, Israel
| | - Johnathan Roy Azaria
- The Goodman faculty of life sciences, Nanotechnology building, Bar Ilan University, Ramat Gan 52900, Israel
| | - Yanay Ofran
- The Goodman faculty of life sciences, Nanotechnology building, Bar Ilan University, Ramat Gan 52900, Israel
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Schummer P, Kuphal S, Vardimon L, Bosserhoff AK, Kappelmann M. Specific c-Jun target genes in malignant melanoma. Cancer Biol Ther 2016; 17:486-97. [PMID: 27050748 DOI: 10.1080/15384047.2016.1156264] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
A fundamental event in the development and progression of malignant melanoma is the de-regulation of cancer-relevant transcription factors. We recently showed that c-Jun is a main regulator of melanoma progression and, thus, is the most important member of the AP-1 transcription factor family in this disease. Surprisingly, no cancer-related specific c-Jun target genes in melanoma were described in the literature, so far. Therefore, we focused on pre-existing ChIP-Seq data (Encyclopedia of DNA Elements) of 3 different non-melanoma cell lines to screen direct c-Jun target genes. Here, a specific c-Jun antibody to immunoprecipitate the associated promoter DNA was used. Consequently, we identified 44 direct c-Jun targets and a detailed analysis of 6 selected genes confirmed their deregulation in malignant melanoma. The identified genes were differentially regulated comparing 4 melanoma cell lines and normal human melanocytes and we confirmed their c-Jun dependency. Direct interaction between c-Jun and the promoter/enhancer regions of the identified genes was confirmed by us via ChIP experiments. Interestingly, we revealed that the direct regulation of target gene expression via c-Jun can be independent of the existence of the classical AP-1 (5´-TGA(C/G)TCA-3´) consensus sequence allowing for the subsequent down- or up-regulation of the expression of these cancer-relevant genes. In summary, the results of this study indicate that c-Jun plays a crucial role in the development and progression of malignant melanoma via direct regulation of cancer-relevant target genes and that inhibition of direct c-Jun targets through inhibition of c-Jun is a potential novel therapeutic option for treatment of malignant melanoma.
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Affiliation(s)
- Patrick Schummer
- a Institute of Biochemistry (Emil-Fischer Center), Friedrich-Alexander University Erlangen-Nürnberg , Erlangen , Germany
| | - Silke Kuphal
- a Institute of Biochemistry (Emil-Fischer Center), Friedrich-Alexander University Erlangen-Nürnberg , Erlangen , Germany
| | - Lily Vardimon
- b Department of Biochemistry and Molecular Biology , Tel Aviv University , Israel
| | - Anja K Bosserhoff
- a Institute of Biochemistry (Emil-Fischer Center), Friedrich-Alexander University Erlangen-Nürnberg , Erlangen , Germany
| | - Melanie Kappelmann
- a Institute of Biochemistry (Emil-Fischer Center), Friedrich-Alexander University Erlangen-Nürnberg , Erlangen , Germany
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8
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Hyland PL, Zhang H, Yang Q, Yang HH, Hu N, Lin SW, Su H, Wang L, Wang C, Ding T, Fan JH, Qiao YL, Sung H, Wheeler W, Giffen C, Burdett L, Wang Z, Lee MP, Chanock SJ, Dawsey SM, Freedman ND, Abnet CC, Goldstein AM, Yu K, Taylor PR. Pathway, in silico and tissue-specific expression quantitative analyses of oesophageal squamous cell carcinoma genome-wide association studies data. Int J Epidemiol 2016; 45:206-20. [PMID: 26635288 PMCID: PMC4881832 DOI: 10.1093/ije/dyv294] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2015] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Oesophageal cancer is the fourth leading cause of cancer death in China where essentially all cases are histologically oesophageal squamous cell carcinoma (ESCC). Agnostic pathway-based analyses of genome-wide association study (GWAS) data combined with tissue-specific expression quantitative trait loci (eQTL) analysis and publicly available functional data can identify biological pathways and/or genes enriched with functionally-relevant disease-associated variants. METHOD We used the adaptive multilocus joint test to analyse 1827 pathways containing 6060 genes using GWAS data from 1942 ESCC cases and 2111 controls with Chinese ancestry. We examined the function of risk alleles using in silico and eQTL analyses in oesophageal tissues. RESULTS Associations with ESCC risk were observed for 36 pathways predominantly involved in apoptosis, cell cycle regulation and DNA repair and containing known GWAS-associated genes. After excluding genes with previous GWAS signals, candidate pathways (and genes) for ESCC risk included taste transduction (KEGG_hsa04742; TAS2R13, TAS2R42, TAS2R14, TAS2R46,TAS2R50), long-patch base excision repair (Reactome_pid; POLD2) and the metabolics pathway (KEGG_hsa01100; MTAP, GAPDH, DCTD, POLD2, AMDHD1). We identified and validated CASP8 rs13016963 and IDH2 rs11630814 as eQTLs, and CASP8 rs3769823 and IDH2 rs4561444 as the potential functional variants in high-linkage disequilibrium with these single nucleotide polymorphisms (SNPs), respectively. Further, IDH2 mRNA levels were down-regulated in ESCC (tumour:normal-fold change = 0.69, P = .75E-14). CONCLUSION Agnostic pathway-based analyses and integration of multiple types of functional data provide new evidence for the contribution of genes in taste transduction and metabolism to ESCC susceptibility, and for the functionality of both established and new ESCC risk-related SNPs.
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Affiliation(s)
| | - Han Zhang
- Division of Cancer Epidemiology and Genetics, and
| | - Qi Yang
- Division of Cancer Epidemiology and Genetics, and
| | | | - Nan Hu
- Division of Cancer Epidemiology and Genetics, and
| | - Shih-Wen Lin
- Division of Cancer Epidemiology and Genetics, and
| | - Hua Su
- Division of Cancer Epidemiology and Genetics, and
| | - Lemin Wang
- Division of Cancer Epidemiology and Genetics, and
| | - Chaoyu Wang
- Division of Cancer Epidemiology and Genetics, and
| | - Ti Ding
- Division of Cancer Epidemiology and Genetics, and
| | - Jin-Hu Fan
- Division of Cancer Epidemiology and Genetics, and
| | - You-Lin Qiao
- Division of Cancer Epidemiology and Genetics, and
| | - Hyuna Sung
- Division of Cancer Epidemiology and Genetics, and
| | | | - Carol Giffen
- Division of Cancer Epidemiology and Genetics, and
| | | | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, and Division of Cancer Epidemiology and Genetics, and
| | | | | | | | | | | | | | - Kai Yu
- Division of Cancer Epidemiology and Genetics, and
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9
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Koster R, Chanock SJ. Hard Work Ahead: Fine Mapping and Functional Follow-up of Susceptibility Alleles in Cancer GWAS. CURR EPIDEMIOL REP 2015. [DOI: 10.1007/s40471-015-0049-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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10
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Brossard M, Fang S, Vaysse A, Wei Q, Chen WV, Mohamdi H, Maubec E, Lavielle N, Galan P, Lathrop M, Avril MF, Lee JE, Amos CI, Demenais F. Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk. Int J Cancer 2015; 137:1901-1909. [PMID: 25892537 DOI: 10.1002/ijc.29570] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Revised: 03/12/2015] [Accepted: 03/30/2015] [Indexed: 12/18/2022]
Abstract
Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.
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Affiliation(s)
- Myriam Brossard
- INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France
| | - Shenying Fang
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Amaury Vaysse
- INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France
| | - Qingyi Wei
- Duke Cancer Institute, Duke University Medical center and Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Wei V Chen
- Laboratory Informatics System, Department of Clinical Applications & Support, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Hamida Mohamdi
- INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France
| | - Eve Maubec
- INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France.,AP-HP (Assistance Publique-Hôpitaux de Paris), Hôpital Bichat, Service de Dermatologie, Université Paris Diderot, Paris, France
| | - Nolwenn Lavielle
- INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France
| | - Pilar Galan
- INSERM, UMR U557; Institut national de la Recherche Agronomique,U1125; Conservatoire national des arts et métiers, Centre de Recherche en Nutrition Humaine, Ile de France, Bobigny, France
| | - Mark Lathrop
- McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada
| | | | - Jeffrey E Lee
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Christopher I Amos
- Department of Community and Family Medicine, Geisel College of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Florence Demenais
- INSERM, Genetic Variation and Human Diseases Unit, UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, Paris, France
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11
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Koster R, Mitra N, D'Andrea K, Vardhanabhuti S, Chung CC, Wang Z, Loren Erickson R, Vaughn DJ, Litchfield K, Rahman N, Greene MH, McGlynn KA, Turnbull C, Chanock SJ, Nathanson KL, Kanetsky PA. Pathway-based analysis of GWAs data identifies association of sex determination genes with susceptibility to testicular germ cell tumors. Hum Mol Genet 2014; 23:6061-8. [PMID: 24943593 PMCID: PMC4204765 DOI: 10.1093/hmg/ddu305] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2013] [Revised: 05/28/2014] [Accepted: 06/12/2014] [Indexed: 02/06/2023] Open
Abstract
Genome-wide association (GWA) studies of testicular germ cell tumor (TGCT) have identified 18 susceptibility loci, some containing genes encoding proteins important in male germ cell development. Deletions of one of these genes, DMRT1, lead to male-to-female sex reversal and are associated with development of gonadoblastoma. To further explore genetic association with TGCT, we undertook a pathway-based analysis of SNP marker associations in the Penn GWAs (349 TGCT cases and 919 controls). We analyzed a custom-built sex determination gene set consisting of 32 genes using three different methods of pathway-based analysis. The sex determination gene set ranked highly compared with canonical gene sets, and it was associated with TGCT (FDRG = 2.28 × 10(-5), FDRM = 0.014 and FDRI = 0.008 for Gene Set Analysis-SNP (GSA-SNP), Meta-Analysis Gene Set Enrichment of Variant Associations (MAGENTA) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (i-GSEA4GWAS) analysis, respectively). The association remained after removal of DMRT1 from the gene set (FDRG = 0.0002, FDRM = 0.055 and FDRI = 0.009). Using data from the NCI GWA scan (582 TGCT cases and 1056 controls) and UK scan (986 TGCT cases and 4946 controls), we replicated these findings (NCI: FDRG = 0.006, FDRM = 0.014, FDRI = 0.033, and UK: FDRG = 1.04 × 10(-6), FDRM = 0.016, FDRI = 0.025). After removal of DMRT1 from the gene set, the sex determination gene set remains associated with TGCT in the NCI (FDRG = 0.039, FDRM = 0.050 and FDRI = 0.055) and UK scans (FDRG = 3.00 × 10(-5), FDRM = 0.056 and FDRI = 0.044). With the exception of DMRT1, genes in the sex determination gene set have not previously been identified as TGCT susceptibility loci in these GWA scans, demonstrating the complementary nature of a pathway-based approach for genome-wide analysis of TGCT.
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Affiliation(s)
- Roelof Koster
- Translational Medicine and Human Genetics, Department of Medicine
| | | | - Kurt D'Andrea
- Translational Medicine and Human Genetics, Department of Medicine
| | | | - Charles C Chung
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services,National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services,National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Cancer Genome Research Laboratory, Division of Cancer Epidemiology and Genetics, SAIC-Frederick, Inc., NCI-Frederick, Frederick, MD, USA
| | - R Loren Erickson
- Walter Reed Army Institute of Research, Silver Spring, MD, USA and
| | - David J Vaughn
- Division of Hematology-Oncology, Department of Medicine and, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin Litchfield
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, UK
| | - Nazneen Rahman
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, UK
| | - Mark H Greene
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services,National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Katherine A McGlynn
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services,National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, UK
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services,National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Katherine L Nathanson
- Translational Medicine and Human Genetics, Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Peter A Kanetsky
- Department of Biostatistics and Epidemiology, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA,
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12
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Brodie A, Tovia-Brodie O, Ofran Y. Large scale analysis of phenotype-pathway relationships based on GWAS results. PLoS One 2014; 9:e100887. [PMID: 25007247 PMCID: PMC4090199 DOI: 10.1371/journal.pone.0100887] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Accepted: 05/28/2014] [Indexed: 12/13/2022] Open
Abstract
The widely used pathway-based approach for interpreting Genome Wide Association Studies (GWAS), assumes that since function is executed through the interactions of multiple genes, different perturbations of the same pathway would result in a similar phenotype. This assumption, however, was not systemically assessed on a large scale. To determine whether SNPs associated with a given complex phenotype affect the same pathways more than expected by chance, we analyzed 368 phenotypes that were studied in >5000 GWAS. We found 216 significant phenotype-pathway associations between 70 of the phenotypes we analyzed and known pathways. We also report 391 strong phenotype-phenotype associations between phenotypes that are affected by the same pathways. While some of these associations confirm previously reported connections, others are new and could shed light on the molecular basis of these diseases. Our findings confirm that phenotype-associated SNPs cluster into pathways much more than expected by chance. However, this is true for <20% (70/368) of the phenotypes. Different types of phenotypes show markedly different tendencies: Virtually all autoimmune phenotypes show strong clustering of SNPs into pathways, while most cancers and metabolic conditions, and all electrophysiological phenotypes, could not be significantly associated with any pathway despite being significantly associated with a large number of SNPs. While this may be due to missing data, it may also suggest that these phenotypes could result only from perturbations of specific genes and not from other perturbations of the same pathway. Further analysis of pathway-associated versus gene-associated phenotypes is, therefore, needed in order to understand disease etiology and in order to promote better drug target selection.
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Affiliation(s)
- Aharon Brodie
- The Goodman Faculty of Life Sciences, Nanotechnology Building, Bar Ilan University, Ramat Gan, Israel
| | - Oholi Tovia-Brodie
- Department of Cardiology, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
| | - Yanay Ofran
- The Goodman Faculty of Life Sciences, Nanotechnology Building, Bar Ilan University, Ramat Gan, Israel
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13
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Vaithilingam RD, Safii SH, Baharuddin NA, Ng CC, Cheong SC, Bartold PM, Schaefer AS, Loos BG. Moving into a new era of periodontal genetic studies: relevance of large case-control samples using severe phenotypes for genome-wide association studies. J Periodontal Res 2014; 49:683-95. [PMID: 24528298 DOI: 10.1111/jre.12167] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2013] [Indexed: 12/19/2022]
Abstract
Studies to elucidate the role of genetics as a risk factor for periodontal disease have gone through various phases. In the majority of cases, the initial 'hypothesis-dependent' candidate-gene polymorphism studies did not report valid genetic risk loci. Following a large-scale replication study, these initially positive results are believed to be caused by type 1 errors. However, susceptibility genes, such as CDKN2BAS (Cyclin Dependend KiNase 2B AntiSense RNA; alias ANRIL [ANtisense Rna In the Ink locus]), glycosyltransferase 6 domain containing 1 (GLT6D1) and cyclooxygenase 2 (COX2), have been reported as conclusive risk loci of periodontitis. The search for genetic risk factors accelerated with the advent of 'hypothesis-free' genome-wide association studies (GWAS). However, despite many different GWAS being performed for almost all human diseases, only three GWAS on periodontitis have been published - one reported genome-wide association of GLT6D1 with aggressive periodontitis (a severe phenotype of periodontitis), whereas the remaining two, which were performed on patients with chronic periodontitis, were not able to find significant associations. This review discusses the problems faced and the lessons learned from the search for genetic risk variants of periodontitis. Current and future strategies for identifying genetic variance in periodontitis, and the importance of planning a well-designed genetic study with large and sufficiently powered case-control samples of severe phenotypes, are also discussed.
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Affiliation(s)
- R D Vaithilingam
- Faculty of Dentistry, Department of Restorative Dentistry, University of Malaya, Kuala Lumpur, Malaysia
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14
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Neurobiology meets genomic science: the promise of human-induced pluripotent stem cells. Dev Psychopathol 2013; 24:1443-51. [PMID: 23062309 DOI: 10.1017/s095457941200082x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The recent introduction of the induced pluripotent stem cell technology has made possible the derivation of neuronal cells from somatic cells obtained from human individuals. This in turn has opened new areas of investigation that can potentially bridge the gap between neuroscience and psychopathology. For the first time we can study the cell biology and genetics of neurons derived from any individual. Furthermore, by recapitulating in vitro the developmental steps whereby stem cells give rise to neuronal cells, we can now hope to understand factors that control typical and atypical development. We can begin to explore how human genes and their variants are transcribed into messenger RNAs within developing neurons and how these gene transcripts control the biology of developing cells. Thus, human-induced pluripotent stem cells have the potential to uncover not only what aspects of development are uniquely human but also variations in the series of events necessary for normal human brain development that predispose to psychopathology.
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15
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Wei P, Tang H, Li D. Insights into pancreatic cancer etiology from pathway analysis of genome-wide association study data. PLoS One 2012; 7:e46887. [PMID: 23056513 PMCID: PMC3464266 DOI: 10.1371/journal.pone.0046887] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2012] [Accepted: 09/06/2012] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Pancreatic cancer is the fourth leading cause of cancer death in the U.S. and the etiology of this highly lethal disease has not been well defined. To identify genetic susceptibility factors for pancreatic cancer, we conducted pathway analysis of genome-wide association study (GWAS) data in 3,141 pancreatic cancer patients and 3,367 controls with European ancestry. METHODS Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways identified from the Kyoto Encyclopedia of Genes and Genomes database. We used the logistic kernel machine (LKM) test to identify major contributing genes to each pathway. We conducted functional enrichment analysis of the most significant genes (P<0.01) using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). RESULTS Two pathways were significantly associated with risk of pancreatic cancer after adjusting for multiple comparisons (P<0.00025) and in replication testing: neuroactive ligand-receptor interaction, (Ps<0.00002), and the olfactory transduction pathway (P = 0.0001). LKM test identified four genes that were significantly associated with risk of pancreatic cancer after Bonferroni correction (P<1×10(-5)): ABO, HNF1A, OR13C4, and SHH. Functional enrichment analysis using DAVID consistently found the G protein-coupled receptor signaling pathway (including both neuroactive ligand-receptor interaction and olfactory transduction pathways) to be the most significant pathway for pancreatic cancer risk in this study population. CONCLUSION These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer.
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Affiliation(s)
- Peng Wei
- Division of Biostatistics and Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
| | - Hongwei Tang
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
- * E-mail:
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16
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Lessons from cancer immunoediting in cutaneous melanoma. Clin Dev Immunol 2012; 2012:192719. [PMID: 22924051 PMCID: PMC3424677 DOI: 10.1155/2012/192719] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2012] [Accepted: 04/28/2012] [Indexed: 02/07/2023]
Abstract
We will revisit the dual role of the immune system in controlling and enabling tumor progression, known as cancer immunoediting. We will go through the different phases of this phenomenon, exposing the most relevant evidences obtained from experimental models and human clinical data, with special focus on Cutaneous Melanoma, an immunogenic tumor per excellence. We will describe the different immunotherapeutic strategies employed and consider current models accounting for tumor heterogeneity. And finally, we will propose a rational discussion of the progress made and the future challenges in the therapeutics of Cutaneous Melanoma, taking into consideration that tumor evolution is the resulting from a continuous feedback between tumor cells and their environment, and that different combinatorial therapeutic approaches can be implemented according to the tumor stage.
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