Investigating the genetic relationship between Alzheimer’s disease and cancer using GWAS summary statistics
- 950 Downloads
Growing evidence from both epidemiology and basic science suggest an inverse association between Alzheimer’s disease (AD) and cancer. We examined the genetic relationship between AD and various cancer types using GWAS summary statistics from the IGAP and GAME-ON consortia. Sample size ranged from 9931 to 54,162; SNPs were imputed to the 1000 Genomes European panel. Our results based on cross-trait LD Score regression showed a significant positive genetic correlation between AD and five cancers combined (colon, breast, prostate, ovarian, lung; r g = 0.17, P = 0.04), and specifically with breast cancer (ER-negative and overall; r g = 0.21 and 0.18, P = 0.035 and 0.034) and lung cancer (adenocarcinoma, squamous cell carcinoma and overall; r g = 0.31, 0.38 and 0.30, P = 0.029, 0.016, and 0.006). Estimating the genetic correlation in specific functional categories revealed mixed positive and negative signals, notably stronger at annotations associated with increased enhancer activity. This suggests a role of gene expression regulators in the shared genetic etiology between AD and cancer, and that some shared variants modulate disease risk concordantly while others have effects in opposite directions. Due to power issues, we did not detect cross-phenotype associations at individual SNPs. This genetic overlap is not likely driven by a handful of major loci. Our study is the first to examine the co-heritability of AD and cancer leveraging large-scale GWAS results. The functional categories highlighted in this study need further investigation to illustrate the details of the genetic sharing and to bridge between different levels of associations.
We thank the International Genomics of Alzheimer’s Project (IGAP) and the GAME-ON network for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i–Select chip was funded by the French National Foundation on Alzheimer’s disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant No. 503480), Alzheimer’s Research UK (Grant No. 503176), the Wellcome Trust (Grant No. 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) Grant No. 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA Grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association Grant ADGC–10–196728. We also thank members of individual studies from the GAME-ON network whose tremendous efforts altogether made this work possible:
Members of CORECT: CORECT acknowledges the following investigators: Kendra Blalock, Peter T. Campbell, Graham Casey, David V. Conti, Christopher K. Edlund, Jane Figueiredo, W. James Gauderman, Jian Gong, Roger C. Green, Stephen B. Gruber, John F. Harju, Tabitha A. Harrison, Eric J. Jacobs, Mark A. Jenkins, Shuo Jiao, Li Li, Yi Lin, Frank J. Manion, Victor Moreno, Bhramar Mukherjee, Ulrike Peters, Leon Raskin, Fredrick R. Schumacher, Daniela Seminara, Gianluca Severi, Stephanie L. Stenzel, and Duncan C. Thomas.
Members of DRIVE: DRIVE acknowledges the following GWASs and investigators that shared genome-wide summary data as part of the breast cancer GWAS meta-analysis: the Australian Breast Cancer Family Study (ABCFS) (John L. Hopper, Melissa C. Southey, Enes Makalic, Daniel F. Schmidt), the British Breast Cancer Study (BBCS) (Olivia Fletcher, Julian Peto, Lorna Gibson, Isabel dos Santos Silva), the Breast and Prostate Cancer Cohort Consortium (BPC3) (David J. Hunter, Sara Lindström, Peter Kraft), the Breast Cancer Family Registries (BCFR) (Habib Ahsan, Alice Whittemore), the Dutch Familial Bilateral Breast Cancer Study (DFBBCS) (Quinten Waisfisz, Hanne Meijers-Heijboer, Muriel Adank, Rob B. van der Luijt, Andre G. Uitterlinden, Albert Hofman), German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) (Alfons Meindl, Rita K. Schmutzler, Bertram Müller-Myhsok, Peter Lichtner), the Helsinki Breast Cancer Study (HEBCS) (Heli Nevanlinna, Taru A. Muranen, Kristiina Aittomäki, Carl Blomqvist), the Mammary Carcinoma Risk Factor Investigation (MARIE) (Jenny Chang-Claude, Rebecca Hein, Norbert Dahmen, Lars Beckman), SardiNIA (Laura Crisponi), the Singapore and Sweden Breast Cancer Study (SASBAC) (Per Hall, Kamila Czene, Astrid Irwanto, Jianjun Liu), and the UK2 (Douglas F. Easton, Clare Turnbull, and Nazneen Rahman).
Members of ELLIPSE: ELLIPSE acknowledges the following GWASs and investigators that shared genome-wide summary data as part of the prostate cancer GWAS meta-analysis: CRUK (Rosalind Eeles, Douglas F. Easton, Zsofia Kote-Jarai, Kenneth Muir, Graham Giles, Gianluca Severi, David Neal, Jenny L. Donovan, Freddie C. Hamdy), CAPS1 and CAPS2 (Fredrik Wiklund, Henrik Gronberg), BPC3-MEC (Christopher Haiman, Fred Schumacher), BPC3-EPIC (Ruth Travis, Elio Riboli), BPC3-Harvard (Peter Kraft, David Hunter), BPC3-ACS (Susan Gapstur), and PEGASUS (Sonja Berndt, Stephen Chanock).
Members of TRICL: TRICL acknowledges the following investigators: Younghun Han, Li Su, Yongyue Wei, Rayjean J. Hung, Yonathan Brhane, John McLaughlin, Paul Brennan, James D. McKay, Heike Bickeböller, Albert Rosenberger, Richard S. Houlston, Neil Caporaso, Maria Teresa Landi, Joachim Heinrich, Angela Risch, Xifeng Wu, Yuanqing Ye, David C. Christiani, and Christopher I. Amos.
Compliance with ethical standards
This research was funded by the US Department of Veterans Affairs Merit Award Grant Clinical Science R&D [I01CX000934-01A1] (PI:Driver). The Genetic Association and Mechanisms in Oncology (GAME-ON) network was supported by the National Institutes of Health [U19CA148065 (DRIVE), U19CA148107 (CORECT), U19CA148127 (TRICL), and U19CA148537 (ELLIPSE)].
Conflict of interest
The authors declare that they have no conflicts of interest.
- Ibanez K, Boullosa C, Tabares-Seisdedos R, Baudot A, Valencia A (2014) Molecular evidence for the inverse comorbidity between central nervous system disorders and cancers detected by transcriptomic meta-analyses. PLoS Genet 10:e1004173. doi: 10.1371/journal.pgen.1004173 CrossRefPubMedPubMedCentralGoogle Scholar
- Lee SH, Yang J, Goddard ME, Visscher PM, Wray NR (2012) Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood. Bioinformatics 28:2540–2542. doi: 10.1093/bioinformatics/bts474 CrossRefPubMedPubMedCentralGoogle Scholar