RT Journal Article
SR Electronic
T1 A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 702910
DO 10.1101/702910
A1 Maxine Harlemon
A1 Olabode Ajayi
A1 Paidamoyo Kachambwa
A1 Michelle S. Kim
A1 Corinne N. Simonti
A1 Melanie H. Quiver
A1 Desiree C. Petersen
A1 Anuradha Mittal
A1 Pedro Fernandez
A1 Ann W. Hsing
A1 Shakuntala Baichoo
A1 Ilir Agalliu
A1 Mohamed Jalloh
A1 Serigne M. Gueye
A1 Nana Yaa Snyper
A1 Ben Adusei
A1 James E. Mensah
A1 Afua O.D. Abrahams
A1 Akindele O. Adebiyi
A1 Akin Orunmuyi
A1 Oseremen I. Aisuodionoe-Shadrach
A1 Maxwell M. Nwegbu
A1 Maureen Joffe
A1 Wenlong C. Chen
A1 Hayley Irusen
A1 Alfred I. Neugut
A1 Yuri Quintana
A1 Moleboheng Seutloali
A1 Mayowa Fadipe
A1 Christopher Warren
A1 Marcos H. Woehrmann
A1 Peng Zhang
A1 Chrissie Ongaco
A1 Michelle Mawhinney
A1 Jo McBride
A1 Caroline Andrews
A1 Marcia Adams
A1 Elizabeth Pugh
A1 Timothy R. Rebbeck
A1 Lindsay Petersen
A1 Joseph Lachance
YR 2019
UL http://biorxiv.org/content/early/2019/07/15/702910.abstract
AB 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.