Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.Genome-wide association studies (GWAS) have identified hundreds of genomic risk regions for prostate cancer. Here, the authors perform a transcriptome wide association study (TWAS) by incorporating prostate cancer GWAS with gene expression data to identify potential novel prostate cancer risk loci and possible risk mechanisms.

[1]  Matthew D. Young,et al.  Gene ontology analysis for RNA-seq: accounting for selection bias , 2010, Genome Biology.

[2]  Steven J. M. Jones,et al.  The Molecular Taxonomy of Primary Prostate Cancer , 2015, Cell.

[3]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[4]  Ali Amin Al Olama,et al.  Prostate cancer meta-analysis from more than 143,000 men identifies 57 novel prostate cancer susceptibility loci , 2016 .

[5]  Benjamin A. Logsdon,et al.  Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia , 2016, Nature Neuroscience.

[6]  Eleazar Eskin,et al.  Identification of causal genes for complex traits , 2015, Bioinform..

[7]  Charles Y. Chiu,et al.  Erratum to: Clinical metagenomic identification of Balamuthia mandrillaris encephalitis and assembly of the draft genome: the continuing case for reference genome sequencing , 2016, Genome Medicine.

[8]  Sharon R Grossman,et al.  Integrating common and rare genetic variation in diverse human populations , 2010, Nature.

[9]  D. Barlow,et al.  Cloning of the mouse and human solute carrier 22a3 (Slc22a3/SLC22A3) identifies a conserved cluster of three organic cation transporters on mouse chromosome 17 and human 6q26-q27. , 1999, Genomics.

[10]  David A. Knowles,et al.  RNA splicing is a primary link between genetic variation and disease , 2016, Science.

[11]  Ali Amin Al Olama,et al.  Multiple newly identified loci associated with prostate cancer susceptibility , 2008, Nature Genetics.

[12]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[13]  Asha A. Nair,et al.  Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set , 2015, Nature Communications.

[14]  N. Cox,et al.  Trait-Associated SNPs Are More Likely to Be eQTLs: Annotation to Enhance Discovery from GWAS , 2010, PLoS genetics.

[15]  Peter Kraft,et al.  Association of Prostate Cancer Risk Variants with Gene Expression in Normal and Tumor Tissue , 2014, Cancer Epidemiology, Biomarkers & Prevention.

[16]  Alexander Gusev,et al.  Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights , 2016, Nature Genetics.

[17]  Rebecca L. Siegel Mph,et al.  Cancer statistics, 2016 , 2016 .

[18]  Nikolaos A Patsopoulos,et al.  Limited statistical evidence for shared genetic effects of eQTLs and autoimmune disease-associated loci in three major immune cell types , 2017, Nature Genetics.

[19]  P. Sullivan,et al.  Heritability and Genomics of Gene Expression in Peripheral Blood , 2014, Nature Genetics.

[20]  Ali Amin Al Olama,et al.  Multiple loci on 8q24 associated with prostate cancer susceptibility , 2009, Nature Genetics.

[21]  Simon G. Coetzee,et al.  Comprehensive Functional Annotation of 77 Prostate Cancer Risk Loci , 2014, PLoS genetics.

[22]  A. Jemal,et al.  Cancer statistics, 2016 , 2016, CA: a cancer journal for clinicians.

[23]  Jake K. Byrnes,et al.  Bayesian refinement of association signals for 14 loci in 3 common diseases , 2012, Nature Genetics.

[24]  K. D. Sørensen,et al.  Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci , 2018, Nature Genetics.

[25]  Xiang Zhou,et al.  Polygenic Modeling with Bayesian Sparse Linear Mixed Models , 2012, PLoS genetics.

[26]  H. Klocker,et al.  Putative Prostate Cancer Risk SNP in an Androgen Receptor‐Binding Site of the Melanophilin Gene Illustrates Enrichment of Risk SNPs in Androgen Receptor Target Sites , 2015, Human mutation.

[27]  Henry W. Long,et al.  Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation , 2016, Nature Communications.

[28]  C. Fletcher,et al.  Mutations in Mlph, encoding a member of the Rab effector family, cause the melanosome transport defects observed in leaden mice , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[29]  T. Lehtimäki,et al.  Cardiovascular risk factors in 2011 and secular trends since 2007: The Cardiovascular Risk in Young Finns Study , 2014, Scandinavian journal of public health.

[30]  W. Hahn,et al.  Genetic and functional analyses implicate the NUDT11, HNF1B, and SLC22A3 genes in prostate cancer pathogenesis , 2012, Proceedings of the National Academy of Sciences.

[31]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[32]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[33]  K. Czene,et al.  The Heritability of Prostate Cancer in the Nordic Twin Study of Cancer , 2014, Cancer Epidemiology, Biomarkers & Prevention.

[34]  Shane J. Neph,et al.  Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.

[35]  J. Lindberg,et al.  Gene regulatory mechanisms underpinning prostate cancer susceptibility , 2016, Nature Genetics.

[36]  Kaanan P. Shah,et al.  A gene-based association method for mapping traits using reference transcriptome data , 2015, Nature Genetics.

[37]  Dennis J. Hazelett,et al.  Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans , 2015, Human molecular genetics.

[38]  Gregory A. Poland,et al.  Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics , 2015, Genetics.

[39]  Jian Yang,et al.  Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits , 2016, Genome Medicine.

[40]  Jussi Paananen,et al.  Hyperglycemia and a Common Variant of GCKR Are Associated With the Levels of Eight Amino Acids in 9,369 Finnish Men , 2012, Diabetes.

[41]  Zhimin Chen,et al.  Altered DNA Polymerase ι Expression in Breast Cancer Cells Leads to a Reduction in DNA Replication Fidelity and a Higher Rate of Mutagenesis , 2004, Cancer Research.

[42]  T. Lehtimäki,et al.  Integrative approaches for large-scale transcriptome-wide association studies , 2015, Nature Genetics.

[43]  R. Fernando,et al.  Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor , 2013, PLoS genetics.

[44]  Alan M. Kwong,et al.  A reference panel of 64,976 haplotypes for genotype imputation , 2015, Nature Genetics.

[45]  Jin Yang,et al.  Overexpressed DNA Polymerase Iota Regulated by JNK/c-Jun Contributes to Hypermutagenesis in Bladder Cancer , 2013, PloS one.

[46]  P. Visscher,et al.  Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets , 2016, Nature Genetics.

[47]  E. Dermitzakis,et al.  Tissue-Specific Effects of Genetic and Epigenetic Variation on Gene Regulation and Splicing , 2015, PLoS genetics.

[48]  Matthew L. Freedman,et al.  Analysis of the 10q11 Cancer Risk Locus Implicates MSMB and NCOA4 in Human Prostate Tumorigenesis , 2010, PLoS genetics.

[49]  Kai Zhang,et al.  A prostate cancer susceptibility allele at 6q22 increases RFX6 expression by modulating HOXB13 chromatin binding , 2014, Nature Genetics.

[50]  P. Pandolfi,et al.  Targeting of the tumor suppressor GRHL3 by a miR-21-dependent proto-oncogenic network results in PTEN loss and tumorigenesis. , 2011, Cancer cell.

[51]  Benjamin Neale,et al.  Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights , 2016 .

[52]  Johanna Kuusisto,et al.  Changes in Insulin Sensitivity and Insulin Release in Relation to Glycemia and Glucose Tolerance in 6,414 Finnish Men , 2009, Diabetes.

[53]  Peter Kraft,et al.  A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer , 2014, Nature Genetics.

[54]  G. Parmigiani,et al.  Familial Risk and Heritability of Cancer Among Twins in Nordic Countries. , 2016, JAMA.

[55]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.

[56]  Peter Kraft,et al.  Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array , 2013, Nature Genetics.

[57]  Alexander Gusev,et al.  Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits. , 2017, American journal of human genetics.

[58]  Risto Telama,et al.  Cohort profile: the cardiovascular risk in Young Finns Study. , 2008, International journal of epidemiology.

[59]  A. D. De Marzo,et al.  MSMB variation and prostate cancer risk: Clues towards a possible fungal etiology , 2014, The Prostate.

[60]  B. Stranger,et al.  Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types. , 2014, Human molecular genetics.

[61]  M. Rubin,et al.  Variants at IRX4 as prostate cancer expression quantitative trait loci , 2013, European Journal of Human Genetics.

[62]  Z. Szallasi,et al.  CAUSEL: An epigenome and genome editing pipeline for establishing function of non-coding GWAS variants , 2015, Nature Medicine.