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Larson NB, McDonnell SK, Fogarty Z, Larson MC, Cheville J, Riska S, Baheti S, Weber AM, Nair AA, Wang L, O’Brien D, Davila J, Schaid DJ, Thibodeau SN. Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci. Oncotarget 2017; 8:85896-85908. [PMID: 29156765 PMCID: PMC5689655 DOI: 10.18632/oncotarget.20717] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 07/29/2017] [Indexed: 12/19/2022] Open
Abstract
Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.
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Affiliation(s)
- Nicholas B. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Shannon K. McDonnell
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Zach Fogarty
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Melissa C. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - John Cheville
- Division of Anatomic Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Shaun Riska
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Saurabh Baheti
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Alexandra M. Weber
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Asha A. Nair
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Liang Wang
- Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Daniel O’Brien
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jaime Davila
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Daniel J. Schaid
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Stephen N. Thibodeau
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
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Lin X, Chen Z, Gao P, Gao Z, Chen H, Qi J, Liu F, Ye D, Jiang H, Na R, Yu H, Shi R, Lu D, Zheng SL, Mo Z, Sun Y, Ding Q, Xu J. TEX15: A DNA repair gene associated with prostate cancer risk in Han Chinese. Prostate 2017; 77:1271-1278. [PMID: 28730685 DOI: 10.1002/pros.23387] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 06/22/2017] [Indexed: 11/12/2022]
Abstract
BACKGROUND Both common and rare genetic variants may contribute to risk of developing prostate cancer. Genome-wide association studies (GWASs) have identified ∼100 independent, common variants associated with prostate cancer risk. However, little is known about the association of rare variants (minor allele frequency [MAF] <1%) in the genome with prostate cancer risk. METHODS A two-stage study was used to test the association of rare, deleterious coding variants, annotated using predictive algorithms, with prostate cancer risk in Chinese men. Predicted rare, deleterious coding variants in the Illumina HumanExome-12 v1.1 beadchip were first evaluated in 1343 prostate cancer patients and 1008 controls. Significant variants were then validated in an additional 1816 prostate cancer patients and 1549 controls. RESULTS In the discovery stage, 14 predicted rare, deleterious coding variants were significantly associated with prostate cancer risk (P < 0.01). In the confirmation stage, Q1631H in TEX15 (rs142485241), a DNA repair gene, was significantly associated with prostate cancer risk (P = 0.0069). The estimated odds ratio (OR) of the variant in the combined analysis was 3.24 (95% Confidence Interval 1.85-6.06), P = 8.81 × 10-5 . Additionally, rs28756990 (V741F) at MLH3 (P = 0.06) and rs2961144 (I126V) at OR2A5 (P = 0.065) were marginally associated with prostate cancer risk in the replication stage. CONCLUSIONS Our study provided preliminary evidence that the rare variant Q1631H in DNA repair gene TEX15 is associated with prostate cancer risk. This finding complements known common prostate cancer risk-associated variants and suggests the possible role of DNA repair genes in prostate cancer development.
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Affiliation(s)
- Xiaoling Lin
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Zhongzhong Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Peng Gao
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhimei Gao
- Central Laboratory, Shanghai Children's Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Haitao Chen
- Center for Genomic Translational Medicine and Prevention, School of Public Health, Fudan University, Shanghai, China
| | - Jun Qi
- Department of Urology, Xinhua Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Fang Liu
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Dingwei Ye
- Department of Urology, Fudan University Shanghai Cancer Center and Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Haowen Jiang
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Rong Na
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongjie Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Rong Shi
- School of Public Health, Shanghai Jiaotong University, Shanghai, China
| | - Daru Lu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Siqun Lilly Zheng
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
- Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Yinghao Sun
- Department of Urology, Shanghai Changhai Hospital, The Second Military Medical University, Shanghai, China
| | - Qiang Ding
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianfeng Xu
- Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
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Murthy MN, Blauwendraat C, Guelfi S, Hardy J, Lewis PA, Trabzuni D. Increased brain expression of GPNMB is associated with genome wide significant risk for Parkinson's disease on chromosome 7p15.3. Neurogenetics 2017; 18:121-133. [PMID: 28391543 PMCID: PMC5522530 DOI: 10.1007/s10048-017-0514-8] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Accepted: 03/20/2017] [Indexed: 12/14/2022]
Abstract
Genome wide association studies (GWAS) for Parkinson’s disease (PD) have previously revealed a significant association with a locus on chromosome 7p15.3, initially designated as the glycoprotein non-metastatic melanoma protein B (GPNMB) locus. In this study, the functional consequences of this association on expression were explored in depth by integrating different expression quantitative trait locus (eQTL) datasets (Braineac, CAGEseq, GTEx, and Phenotype-Genotype Integrator (PheGenI)). Top risk SNP rs199347 eQTLs demonstrated increased expressions of GPNMB, KLHL7, and NUPL2 with the major allele (AA) in brain, with most significant eQTLs in cortical regions, followed by putamen. In addition, decreased expression of the antisense RNA KLHL7-AS1 was observed in GTEx. Furthermore, rs199347 is an eQTL with long non-coding RNA (AC005082.12) in human tissues other than brain. Interestingly, transcript-specific eQTLs in immune-related tissues (spleen and lymphoblastoid cells) for NUPL2 and KLHL7-AS1 were observed, which suggests a complex functional role of this eQTL in specific tissues, cell types at specific time points. Significantly increased expression of GPNMB linked to rs199347 was consistent across all datasets, and taken in combination with the risk SNP being located within the GPNMB gene, these results suggest that increased expression of GPNMB is the causative link explaining the association of this locus with PD. However, other transcript eQTLs and subsequent functional roles cannot be excluded. This highlights the importance of further investigations to understand the functional interactions between the coding genes, antisense, and non-coding RNA species considering the tissue and cell-type specificity to understand the underlying biological mechanisms in PD.
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Affiliation(s)
- Megha N Murthy
- Genetics and Genomics Laboratory, DOS in Genetics and Genomics, University of Mysore, Mysore, Karnataka, 570006, India
- School of Pharmacy, University of Reading, Whiteknights, Reading, RG6 6AP, UK
| | - Cornelis Blauwendraat
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Sebastian Guelfi
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - John Hardy
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Patrick A Lewis
- School of Pharmacy, University of Reading, Whiteknights, Reading, RG6 6AP, UK
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Daniah Trabzuni
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.
- Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh, 11211, Saudi Arabia.
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Winter JM, Gildea DE, Andreas JP, Gatti DM, Williams KA, Lee M, Hu Y, Zhang S, Mullikin JC, Wolfsberg TG, McDonnell SK, Fogarty ZC, Larson MC, French AJ, Schaid DJ, Thibodeau SN, Churchill GA, Crawford NPS. Mapping Complex Traits in a Diversity Outbred F1 Mouse Population Identifies Germline Modifiers of Metastasis in Human Prostate Cancer. Cell Syst 2016; 4:31-45.e6. [PMID: 27916600 DOI: 10.1016/j.cels.2016.10.018] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 09/08/2016] [Accepted: 10/20/2016] [Indexed: 01/02/2023]
Abstract
It is unclear how standing genetic variation affects the prognosis of prostate cancer patients. To provide one controlled answer to this problem, we crossed a dominant, penetrant mouse model of prostate cancer to Diversity Outbred mice, a collection of animals that carries over 40 million SNPs. Integration of disease phenotype and SNP variation data in 493 F1 males identified a metastasis modifier locus on Chromosome 8 (LOD = 8.42); further analysis identified the genes Rwdd4, Cenpu, and Casp3 as functional effectors of this locus. Accordingly, analysis of over 5,300 prostate cancer patient samples revealed correlations between the presence of genetic variants at these loci, their expression levels, cancer aggressiveness, and patient survival. We also observed that ectopic overexpression of RWDD4 and CENPU increased the aggressiveness of two human prostate cancer cell lines. In aggregate, our approach demonstrates how well-characterized genetic variation in mice can be harnessed in conjunction with systems genetics approaches to identify and characterize germline modifiers of human disease processes.
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Affiliation(s)
- Jean M Winter
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Derek E Gildea
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Jonathan P Andreas
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | | | - Kendra A Williams
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Minnkyong Lee
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Ying Hu
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, Rockville, MD 20892, USA
| | - Suiyuan Zhang
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
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- NIH Intramural Sequencing Center, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - James C Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Tyra G Wolfsberg
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Shannon K McDonnell
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Zachary C Fogarty
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Melissa C Larson
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Amy J French
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Stephen N Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | | | - Nigel P S Crawford
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
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Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics. Genetics 2016; 204:933-958. [PMID: 27655946 DOI: 10.1534/genetics.116.188953] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2016] [Accepted: 09/07/2016] [Indexed: 12/21/2022] Open
Abstract
Functional annotations have been shown to improve both the discovery power and fine-mapping accuracy in genome-wide association studies. However, the optimal strategy to incorporate the large number of existing annotations is still not clear. In this study, we propose a Bayesian framework to incorporate functional annotations in a systematic manner. We compute the maximum a posteriori solution and use cross validation to find the optimal penalty parameters. By extending our previous fine-mapping method CAVIARBF into this framework, we require only summary statistics as input. We also derived an exact calculation of Bayes factors using summary statistics for quantitative traits, which is necessary when a large proportion of trait variance is explained by the variants of interest, such as in fine mapping expression quantitative trait loci (eQTL). We compared the proposed method with PAINTOR using different strategies to combine annotations. Simulation results show that the proposed method achieves the best accuracy in identifying causal variants among the different strategies and methods compared. We also find that for annotations with moderate effects from a large annotation pool, screening annotations individually and then combining the top annotations can produce overly optimistic results. We applied these methods on two real data sets: a meta-analysis result of lipid traits and a cis-eQTL study of normal prostate tissues. For the eQTL data, incorporating annotations significantly increased the number of potential causal variants with high probabilities.
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Abstract
Prostate cancer is a leading cause of cancer-related death in Western men. Our understanding of the genetic alterations associated with disease predisposition, development, progression, and therapy response is rapidly improving, at least in part, owing to the development of next-generation sequencing technologies. Large advances have been made in our understanding of the genetics of prostate cancer through the application of whole-exome sequencing, and this review summarises recent advances in this field and discusses how exome sequencing could be used clinically to promote personalised medicine for prostate cancer patients.
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Affiliation(s)
- Angela C Pine
- Molecular Oncology, School of Biological Sciences, University of Essex, Colchester, Essex, UK
| | - Flavia F Fioretti
- Androgen Signalling Laboratory, Division of Cancer, Department of Surgery and Cancer, Imperial Centre for Translational & Experimental Medicine, Imperial College London, London, UK
| | - Greg N Brooke
- Molecular Oncology, School of Biological Sciences, University of Essex, Colchester, Essex, UK; Androgen Signalling Laboratory, Division of Cancer, Department of Surgery and Cancer, Imperial Centre for Translational & Experimental Medicine, Imperial College London, London, UK
| | - Charlotte L Bevan
- Androgen Signalling Laboratory, Division of Cancer, Department of Surgery and Cancer, Imperial Centre for Translational & Experimental Medicine, Imperial College London, London, UK
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