Shared heritability and functional enrichment across six solid cancers
Abstract
Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
Conflict of interest statement
The authors declare no competing interests.
Figures
References
- Lichtenstein P, et al. Environmental and heritable factors in the causation of cancer–analyses of cohorts of twins from Sweden, Denmark, and Finland. N. Engl. J. Med. 2000;343:78–85. doi: 10.1056/NEJM200007133430201.
- Mucci LA, et al. Familial risk and heritability of cancer among twins in nordic countries. JAMA. 2016;315:68. doi: 10.1001/jama.2015.17703.
- Polderman TJC, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 2015;47:702–709. doi: 10.1038/ng.3285.
- Amundadottir LT, et al. Cancer as a complex phenotype: pattern of cancer distribution within and beyond the nuclear family. PLoS Med. 2004;1:e65. doi: 10.1371/journal.pmed.0010065.
- Yu H, Frank C, Sundquist J, Hemminki A, Hemminki K. Common cancers share familial susceptibility: implications for cancer genetics and counselling. J. Med. Genet. 2017;54:248–253. doi: 10.1136/jmedgenet-2016-103932.
- Frank C, Sundquist J, Yu H, Hemminki A, Hemminki K. Concordant and discordant familial cancer: familial risks, proportions and population impact. Int. J. Cancer. 2017;140:1510–1516. doi: 10.1002/ijc.30583.
- Fehringer G, et al. Cross-cancer genome-wide analysis of lung, ovary, breast, prostate, and colorectal cancer reveals novel pleiotropic associations. Cancer Res. 2016;76:5103–5114. doi: 10.1158/0008-5472.CAN-15-2980.
- Kar SP, et al. Genome-wide meta-analyses of breast, ovarian, and prostate cancer association studies identify multiple new susceptibility loci shared by at least two cancer types. Cancer Discov. 2016;6:1052–1067. doi: 10.1158/-15-1227.
- Sampson JN, et al. Analysis of heritability and shared heritability based on genome-wide association studies for thirteen cancer types. J. Natl. Cancer Inst. 2015;107:djv279. doi: 10.1093/jnci/djv279.
- Gusev A, et al. Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation. Nat. Commun. 2016;7:10979. doi: 10.1038/ncomms10979.
- Jiao S, et al. Estimating the heritability of colorectal cancer. Hum. Mol. Genet. 2014;23:3898–3905. doi: 10.1093/hmg/ddu087.
- Lu Y, et al. Most common ‘sporadic’ cancers have a significant germline genetic component. Hum. Mol. Genet. 2014;23:6112–6118. doi: 10.1093/hmg/ddu312.
- Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 2011;88:76–82. doi: 10.1016/j.ajhg.2010.11.011.
- Finucane HK, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 2015;47:1228–1235. doi: 10.1038/ng.3404.
- Bulik-Sullivan BK, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 2015;47:291–295. doi: 10.1038/ng.3211.
- Lindström S, et al. Quantifying the genetic correlation between multiple cancer types. Cancer Epidemiol. Biomark. Prev. 2017;26:1427–1435. doi: 10.1158/1055-9965.EPI-17-0211.
- Yang J, et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 2010;42:565–569. doi: 10.1038/ng.608.
- Amos CI, et al. The OncoArray Consortium: a network for understanding the genetic architecture of common cancers. Cancer Epidemiol. Biomark. Prev. 2017;26:126–135. doi: 10.1158/1055-9965.EPI-16-0106.
- SMOKING and health. Joint report of the Study Group on Smoking and Health. Science. 1957;125:1129–1133. doi: 10.1126/science.125.3258.1129.
- Shaw R, Beasley N. Aetiology and risk factors for head and neck cancer: United Kingdom National Multidisciplinary Guidelines. J. Laryngol. Otol. 2016;130:S9–S12. doi: 10.1017/S0022215116000360.
- Koene RJ, Prizment AE, Blaes A, Konety SH. Shared risk factors in cardiovascular disease and cancer. Circulation. 2016;133:1104–1114. doi: 10.1161/CIRCULATIONAHA.115.020406.
- Thompson CL, et al. Short duration of sleep increases risk of colorectal adenoma. Cancer. 2011;117:841–847. doi: 10.1002/cncr.25507.
- Sigurdardottir LG, et al. Sleep disruption among older men and risk of prostate cancer. Cancer Epidemiol. Prev. Biomark. 2013;22:872–879. doi: 10.1158/1055-9965.EPI-12-1227-T.
- Gazal S, et al. Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nat. Genet. 2017;49:1421–1427. doi: 10.1038/ng.3954.
- Field RW, Withers BL. Occupational and environmental causes of lung cancer. Clin. Chest Med. 2012;33:681–703. doi: 10.1016/j.ccm.2012.07.001.
- Hulka BS. Epidemiologic analysis of breast and gynecologic cancers. Prog. Clin. Biol. Res. 1997;396:17–29.
- Gaudet MM, et al. Pooled analysis of active cigarette smoking and invasive breast cancer risk in 14 cohort studies. Int. J. Epidemiol. 2017;46:881–893.
- Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70. doi: 10.1038/nature11412.
- Maas P, et al. Breast cancer risk from modifiable and nonmodifiable risk factors among white women in the United States. JAMA Oncol. 2016;2:1295–1302. doi: 10.1001/jamaoncol.2016.1025.
- Nakaya N, et al. Personality traits and cancer risk and survival based on finnish and swedish registry data. Am. J. Epidemiol. 2010;172:377–385. doi: 10.1093/aje/kwq046.
- Oksbjerg Dalton S, Munk Laursen T, Mellemkjaer L, Johansen C, Mortensen PB. Schizophrenia and the risk for breast cancer. Schizophr. Res. 2003;62:89–92. doi: 10.1016/S0920-9964(02)00430-9.
- Hung RJ, et al. A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25. Nature. 2008;452:633–637. doi: 10.1038/nature06885.
- Amos CI, et al. Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat. Genet. 2008;40:616–622. doi: 10.1038/ng.109.
- Gao C, et al. Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer. Int. J. Epidemiol. 2016;45:896–908. doi: 10.1093/ije/dyw129.
- Collaborative Group on Hormonal Factors in Breast Cancer. Menarche, menopause, and breast cancer risk: individual participant meta-analysis, including 118 964 women with breast cancer from 117 epidemiological studies. Lancet Oncol. 2012;13:1141–1151. doi: 10.1016/S1470-2045(12)70425-4.
- Day FR, et al. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. Nat. Genet. 2015;47:1294–1303. doi: 10.1038/ng.3412.
- Day FR, et al. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat. Genet. 2017;49:834–841. doi: 10.1038/ng.3841.
- Zack TI, et al. Pan-cancer patterns of somatic copy number alteration. Nat. Genet. 2013;45:1134–1140. doi: 10.1038/ng.2760.
- Ciriello G, et al. Emerging landscape of oncogenic signatures across human cancers. Nat. Genet. 2013;45:1127–1133. doi: 10.1038/ng.2762.
- Lindblad-Toh K, et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature. 2011;478:476–482. doi: 10.1038/nature10530.
- Calin GA, et al. Ultraconserved regions encoding ncRNAs are altered in human leukemias and carcinomas. Cancer Cell. 2007;12:215–229. doi: 10.1016/j.ccr.2007.07.027.
- Peng JC, Shen J, Ran ZH. Transcribed ultraconserved region in human cancers. RNA Biol. 2013;10:1771–1777. doi: 10.4161/rna.26995.
- Michailidou K, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551:92–94. doi: 10.1038/nature24284.
- Milne RL, et al. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer. Nat. Genet. 2017;49:1767–1778. doi: 10.1038/ng.3785.
- McKay JD, et al. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nat. Genet. 2017;49:1126–1132. doi: 10.1038/ng.3892.
- Schmit, S. L. et al. Novel Common Genetic Susceptibility Loci for Colorectal Cancer. J. Natl. Cancer Inst. 111, djy099 (2019).
- Phelan CM, et al. Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer. Nat. Genet. 2017;49:680–691. doi: 10.1038/ng.3826.
- Lesseur C, et al. Genome-wide association analyses identify new susceptibility loci for oral cavity and pharyngeal cancer. Nat. Genet. 2016;48:1544–1550. doi: 10.1038/ng.3685.
- Schumacher FR, et al. Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci. Nat. Genet. 2018;50:928–936. doi: 10.1038/s41588-018-0142-8.
- Shi H, Mancuso N, Spendlove S, Pasaniuc B. Local genetic correlation gives insights into the shared genetic architecture of complex traits. Am. J. Hum. Genet. 2017;101:737–751. doi: 10.1016/j.ajhg.2017.09.022.
- Sakoda LC, Jorgenson E, Witte JS. Turning of COGS moves forward findings for hormonally mediated cancers. Nat. Genet. 2013;45:345–348. doi: 10.1038/ng.2587.
- Pickrell JK, et al. Detection and interpretation of shared genetic influences on 42 human traits. Nat. Genet. 2016;48:709–717. doi: 10.1038/ng.3570.
- Pickrell JK. Joint analysis of functional genomic data and genome-wide association studies of 18 human traits. Am. J. Hum. Genet. 2014;94:559–573. doi: 10.1016/j.ajhg.2014.03.004.
- Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 2015;44:512–525. doi: 10.1093/ije/dyv080.
- Gusev A, et al. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. Am. J. Hum. Genet. 2014;95:535–552. doi: 10.1016/j.ajhg.2014.10.004.
- Roadmap Epigenomics Consortium. et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317–330. doi: 10.1038/nature14248.
- ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74. doi: 10.1038/nature11247.
- Trynka G, et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat. Genet. 2013;45:124–130. doi: 10.1038/ng.2504.
- Hnisz D, et al. Super-enhancers in the control of cell identity and disease. Cell. 2013;155:934–947. doi: 10.1016/j.cell.2013.09.053.
- Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–427. doi: 10.1038/nature13595.
- Hoffman MM, et al. Integrative annotation of chromatin elements from ENCODE data. Nucleic Acids Res. 2013;41:827–841. doi: 10.1093/nar/gks1284.
- Ward LD, Kellis M. Evidence of abundant purifying selection in humans for recently acquired regulatory functions. Science. 2012;337:1675–1678. doi: 10.1126/science.1225057.
- Andersson R, et al. An atlas of active enhancers across human cell types and tissues. Nature. 2014;507:455–461. doi: 10.1038/nature12787.
Source: PubMed