Dataset Information

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 (r_g?=?0.57, p?=?4.6?×?10^-8), breast and ovarian cancer (r_g?=?0.24, p?=?7?×?10^-5), breast and lung cancer (r_g?=?0.18, p =1.5?×?10^-6) and breast and colorectal cancer (r_g?=?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.

SUBMITTER: Jiang X

PROVIDER: S-EPMC6347624 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Shared heritability and functional enrichment across six solid cancers.

Jiang Xia X Finucane Hilary K HK Schumacher Fredrick R FR Schmit Stephanie L SL Tyrer Jonathan P JP Han Younghun Y Michailidou Kyriaki K Lesseur Corina C Kuchenbaecker Karoline B KB Dennis Joe J Conti David V DV Casey Graham G Gaudet Mia M MM Huyghe Jeroen R JR Albanes Demetrius D Aldrich Melinda C MC Andrew Angeline S AS Andrulis Irene L IL Anton-Culver Hoda H Antoniou Antonis C AC Antonenkova Natalia N NN Arnold Susanne M SM Aronson Kristan J KJ Arun Banu K BK Bandera Elisa V EV Barkardottir Rosa B RB Barnes Daniel R DR Batra Jyotsna J Beckmann Matthias W MW Benitez Javier J Benlloch Sara S Berchuck Andrew A Berndt Sonja I SI Bickeböller Heike H Bien Stephanie A SA Blomqvist Carl C Boccia Stefania S Bogdanova Natalia V NV Bojesen Stig E SE Bolla Manjeet K MK Brauch Hiltrud H Brenner Hermann H Brenton James D JD Brook Mark N MN Brunet Joan J Brunnström Hans H Buchanan Daniel D DD Burwinkel Barbara B Butzow Ralf R Cadoni Gabriella G Caldés Trinidad T Caligo Maria A MA Campbell Ian I Campbell Peter T PT Cancel-Tassin Géraldine G Cannon-Albright Lisa L Campa Daniele D Caporaso Neil N Carvalho André L AL Chan Andrew T AT Chang-Claude Jenny J Chanock Stephen J SJ Chen Chu C Christiani David C DC Claes Kathleen B M KBM Claessens Frank F Clements Judith J Collée J Margriet JM Correa Marcia Cruz MC Couch Fergus J FJ Cox Angela A Cunningham Julie M JM Cybulski Cezary C Czene Kamila K Daly Mary B MB deFazio Anna A Devilee Peter P Diez Orland O Gago-Dominguez Manuela M Donovan Jenny L JL Dörk Thilo T Duell Eric J EJ Dunning Alison M AM Dwek Miriam M Eccles Diana M DM Edlund Christopher K CK Edwards Digna R Velez DRV Ellberg Carolina C Evans D Gareth DG Fasching Peter A PA Ferris Robert L RL Liloglou Triantafillos T Figueiredo Jane C JC Fletcher Olivia O Fortner Renée T RT Fostira Florentia F Franceschi Silvia S Friedman Eitan E Gallinger Steven J SJ Ganz Patricia A PA Garber Judy J García-Sáenz José A JA Gayther Simon A SA Giles Graham G GG Godwin Andrew K AK Goldberg Mark S MS Goldgar David E DE Goode Ellen L EL Goodman Marc T MT Goodman Gary G Grankvist Kjell K Greene Mark H MH Gronberg Henrik H Gronwald Jacek J Guénel Pascal P Håkansson Niclas N Hall Per P Hamann Ute U Hamdy Freddie C FC Hamilton Robert J RJ Hampe Jochen J Haugen Aage A Heitz Florian F Herrero Rolando R Hillemanns Peter P Hoffmeister Michael M Høgdall Estrid E Hong Yun-Chul YC Hopper John L JL Houlston Richard R Hulick Peter J PJ Hunter David J DJ Huntsman David G DG Idos Gregory G Imyanitov Evgeny N EN Ingles Sue Ann SA Isaacs Claudine C Jakubowska Anna A James Paul P Jenkins Mark A MA Johansson Mattias M Johansson Mikael M John Esther M EM Joshi Amit D AD Kaneva Radka R Karlan Beth Y BY Kelemen Linda E LE Kühl Tabea T Khaw Kay-Tee KT Khusnutdinova Elza E Kibel Adam S AS Kiemeney Lambertus A LA Kim Jeri J Kjaer Susanne K SK Knight Julia A JA Kogevinas Manolis M Kote-Jarai Zsofia Z Koutros Stella S Kristensen Vessela N VN Kupryjanczyk Jolanta J Lacko Martin M Lam Stephan S Lambrechts Diether D Landi Maria Teresa MT Lazarus Philip P Le Nhu D ND Lee Eunjung E Lejbkowicz Flavio F Lenz Heinz-Josef HJ Leslie Goska G Lessel Davor D Lester Jenny J Levine Douglas A DA Li Li L Li Christopher I CI Lindblom Annika A Lindor Noralane M NM Liu Geoffrey G Loupakis Fotios F Lubiński Jan J Maehle Lovise L Maier Christiane C Mannermaa Arto A Marchand Loic Le LL Margolin Sara S May Taymaa T McGuffog Lesley L Meindl Alfons A Middha Pooja P Miller Austin A Milne Roger L RL MacInnis Robert J RJ Modugno Francesmary F Montagna Marco M Moreno Victor V Moysich Kirsten B KB Mucci Lorelei L Muir Kenneth K Mulligan Anna Marie AM Nathanson Katherine L KL Neal David E DE Ness Andrew R AR Neuhausen Susan L SL Nevanlinna Heli H Newcomb Polly A PA Newcomb Lisa F LF Nielsen Finn Cilius FC Nikitina-Zake Liene L Nordestgaard Børge G BG Nussbaum Robert L RL Offit Kenneth K Olah Edith E Olama Ali Amin Al AAA Olopade Olufunmilayo I OI Olshan Andrew F AF Olsson Håkan H Osorio Ana A Pandha Hardev H Park Jong Y JY Pashayan Nora N Parsons Michael T MT Pejovic Tanja T Penney Kathryn L KL Peters Wilbert H M WHM Phelan Catherine M CM Phipps Amanda I AI Plaseska-Karanfilska Dijana D Pring Miranda M Prokofyeva Darya D Radice Paolo P Stefansson Kari K Ramus Susan J SJ Raskin Leon L Rennert Gad G Rennert Hedy S HS van Rensburg Elizabeth J EJ Riggan Marjorie J MJ Risch Harvey A HA Risch Angela A Roobol Monique J MJ Rosenstein Barry S BS Rossing Mary Anne MA De Ruyck Kim K Saloustros Emmanouil E Sandler Dale P DP Sawyer Elinor J EJ Schabath Matthew B MB Schleutker Johanna J Schmidt Marjanka K MK Setiawan V Wendy VW Shen Hongbing H Siegel Erin M EM Sieh Weiva W Singer Christian F CF Slattery Martha L ML Sorensen Karina Dalsgaard KD Southey Melissa C MC Spurdle Amanda B AB Stanford Janet L JL Stevens Victoria L VL Stintzing Sebastian S Stone Jennifer J Sundfeldt Karin K Sutphen Rebecca R Swerdlow Anthony J AJ Tajara Eloiza H EH Tangen Catherine M CM Tardon Adonina A Taylor Jack A JA Teare M Dawn MD Teixeira Manuel R MR Terry Mary Beth MB Terry Kathryn L KL Thibodeau Stephen N SN Thomassen Mads M Bjørge Line L Tischkowitz Marc M Toland Amanda E AE Torres Diana D Townsend Paul A PA Travis Ruth C RC Tung Nadine N Tworoger Shelley S SS Ulrich Cornelia M CM Usmani Nawaid N Vachon Celine M CM Van Nieuwenhuysen Els E Vega Ana A Aguado-Barrera Miguel Elías ME Wang Qin Q Webb Penelope M PM Weinberg Clarice R CR Weinstein Stephanie S Weissler Mark C MC Weitzel Jeffrey N JN West Catharine M L CML White Emily E Whittemore Alice S AS Wichmann H-Erich HE Wiklund Fredrik F Winqvist Robert R Wolk Alicja A Woll Penella P Woods Michael M Wu Anna H AH Wu Xifeng X Yannoukakos Drakoulis D Zheng Wei W Zienolddiny Shanbeh S Ziogas Argyrios A Zorn Kristin K KK Lane Jacqueline M JM Saxena Richa R Thomas Duncan D Hung Rayjean J RJ Diergaarde Brenda B McKay James J Peters Ulrike U Hsu Li L García-Closas Montserrat M Eeles Rosalind A RA Chenevix-Trench Georgia G Brennan Paul J PJ Haiman Christopher A CA Simard Jacques J Easton Douglas F DF Gruber Stephen B SB Pharoah Paul D P PDP Price Alkes L AL Pasaniuc Bogdan B Amos Christopher I CI Kraft Peter P Lindström Sara S

Nature communications 20190125 1

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 cor ...[more]

PMID: 30683880

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Project description:Heritability enrichment analysis is an important means of exploring the genetic architecture of complex traits in human genetics. Heritability enrichment is typically defined as the proportion of an SNP subset explained heritability, divided by the proportion of SNPs. Heritability enrichment enables better study of underlying complex traits, such as functional variant/gene subsets, biological networks and metabolic pathways detected through integrating explosively increased omics data. This would be beneficial for genomic prediction of disease risk in humans and genetic values estimation of important economical traits in livestock and plant species. However, in livestock, factors affecting the heritability enrichment estimation of complex traits have not been examined. Previous studies on humans reported that the frequencies, effect sizes, and levels of linkage disequilibrium (LD) of underlying causal variants (CVs) would affect the heritability enrichment estimation. Therefore, the distribution of heritability across the genome should be fully considered to obtain the unbiased estimation of heritability enrichment. To explore the performance of different heritability enrichment models in livestock populations, we used the VanRaden, GCTA and α models, assuming different α values, and the LDAK model, considering LD weight. We simulated three types of phenotypes, with CVs from various minor allele frequency (MAF) ranges: genome-wide (0.005 ≤ MAF ≤ 0.5), common (0.05 ≤ MAF ≤ 0.5), and uncommon (0.01 ≤ MAF < 0.05). The performances of the models with two different subsets (one of which contained known CVs and the other consisting of randomly selected markers) were compared to verify the accuracy of heritability enrichment estimation of functional variant sets. Our results showed that models with known CV subsets provided more robust enrichment estimation. Models with different α values tended to provide stable and accurate estimates for common and genome-wide CVs (relative deviation 0.5-2.2%), while tending to underestimate the enrichment of uncommon CVs. As the α value increased, enrichments from 15.73% higher than true value (i.e., 3.00) to 48.93% lower than true value for uncommon CVs were observed. In addition, the long-range LD windows (e.g., 5000 kb) led to large bias of the enrichment estimations for both common and uncommon CVs. Overall, heritability enrichment estimations were sensitive for the α value assumption and LD weight consideration of different models. Accuracy would be greatly improved by using a suitable model. This study would be helpful in understanding the genetic architecture of complex traits and provides a reference for genetic analysis in the livestock population.

Project description:BACKGROUND:Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. METHODS:Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. RESULTS:GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (? = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (? = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (? = 0.51, SE =0.18), and bladder and lung (? = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. CONCLUSION:Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

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Shared heritability and functional enrichment across six solid cancers.

Publications

Shared heritability and functional enrichment across six solid cancers.

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