TY - JOUR T1 - A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa JF - bioRxiv DO - 10.1101/702910 SP - 702910 AU - Maxine Harlemon AU - Olabode Ajayi AU - Paidamoyo Kachambwa AU - Michelle S. Kim AU - Corinne N. Simonti AU - Melanie H. Quiver AU - Desiree C. Petersen AU - Anuradha Mittal AU - Pedro Fernandez AU - Ann W. Hsing AU - Shakuntala Baichoo AU - Ilir Agalliu AU - Mohamed Jalloh AU - Serigne M. Gueye AU - Nana Yaa Snyper AU - Ben Adusei AU - James E. Mensah AU - Afua O.D. Abrahams AU - Akindele O. Adebiyi AU - Akin Orunmuyi AU - Oseremen I. Aisuodionoe-Shadrach AU - Maxwell M. Nwegbu AU - Maureen Joffe AU - Wenlong C. Chen AU - Hayley Irusen AU - Alfred I. Neugut AU - Yuri Quintana AU - Moleboheng Seutloali AU - Mayowa Fadipe AU - Christopher Warren AU - Marcos H. Woehrmann AU - Peng Zhang AU - Chrissie Ongaco AU - Michelle Mawhinney AU - Jo McBride AU - Caroline Andrews AU - Marcia Adams AU - Elizabeth Pugh AU - Timothy R. Rebbeck AU - Lindsay Petersen AU - Joseph Lachance Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/07/15/702910.abstract N2 - Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. We find that samples from Ghana and Nigeria cluster together, while samples from Senegal and South Africa yield distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores were also generated for each genome in the MADCaP pilot dataset, and we found that predicted risks of CaP are lower in Senegal and higher in Nigeria.Significance We have developed an Africa-specific genotyping array which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers. ER -