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7 results on '"Moleboheng Seutloali"'

1. Figure S1 from A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa

Author

Joseph Lachance, Lindsay N. Petersen, Timothy R. Rebbeck, Elizabeth Pugh, Marcia Adams, Caroline V. Andrews, Jo McBride, Michelle Mawhinney, Chrissie M. Ongaco, Peng Zhang, Marcos H. Woehrmann, Christopher Warren, Mayowa B. Fadipe, Moleboheng Seutloali, Yuri Quintana, Alfred I. Neugut, Hayley Irusen, Wenlong C. Chen, Maureen Joffe, Maxwell M. Nwegbu, Oseremen I. Aisuodionoe-Shadrach, Akin T. Orunmuyi, Akindele O. Adebiyi, Afua O.D. Abrahams, James E. Mensah, Ben Adusei, Nana Yaa F. Snyper, Serigne M. Gueye, Mohamed Jalloh, Ilir Agalliu, Shakuntala Baichoo, Ann W. Hsing, Pedro W. Fernandez, Anuradha Mittal, Desiree C. Petersen, Melanie H. Quiver, Corinne N. Simonti, Michelle S. Kim, Paidamoyo Kachambwa, Olabode Ajayi, and Maxine Harlemon

Abstract

Figure S1. Cross-validation error in ADMIXTURE analyses. The best fit to data occurs at K = 3.

Published
2023
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2. Table S1 from A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa

Author

Joseph Lachance, Lindsay N. Petersen, Timothy R. Rebbeck, Elizabeth Pugh, Marcia Adams, Caroline V. Andrews, Jo McBride, Michelle Mawhinney, Chrissie M. Ongaco, Peng Zhang, Marcos H. Woehrmann, Christopher Warren, Mayowa B. Fadipe, Moleboheng Seutloali, Yuri Quintana, Alfred I. Neugut, Hayley Irusen, Wenlong C. Chen, Maureen Joffe, Maxwell M. Nwegbu, Oseremen I. Aisuodionoe-Shadrach, Akin T. Orunmuyi, Akindele O. Adebiyi, Afua O.D. Abrahams, James E. Mensah, Ben Adusei, Nana Yaa F. Snyper, Serigne M. Gueye, Mohamed Jalloh, Ilir Agalliu, Shakuntala Baichoo, Ann W. Hsing, Pedro W. Fernandez, Anuradha Mittal, Desiree C. Petersen, Melanie H. Quiver, Corinne N. Simonti, Michelle S. Kim, Paidamoyo Kachambwa, Olabode Ajayi, and Maxine Harlemon

Abstract

Successfully called markers on the MADCaP Array. This tab-delimited file includes genomic positions, inclusion criteria, and overlap with other arrays.

Published
2023
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3. Data from A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa

Author

Joseph Lachance, Lindsay N. Petersen, Timothy R. Rebbeck, Elizabeth Pugh, Marcia Adams, Caroline V. Andrews, Jo McBride, Michelle Mawhinney, Chrissie M. Ongaco, Peng Zhang, Marcos H. Woehrmann, Christopher Warren, Mayowa B. Fadipe, Moleboheng Seutloali, Yuri Quintana, Alfred I. Neugut, Hayley Irusen, Wenlong C. Chen, Maureen Joffe, Maxwell M. Nwegbu, Oseremen I. Aisuodionoe-Shadrach, Akin T. Orunmuyi, Akindele O. Adebiyi, Afua O.D. Abrahams, James E. Mensah, Ben Adusei, Nana Yaa F. Snyper, Serigne M. Gueye, Mohamed Jalloh, Ilir Agalliu, Shakuntala Baichoo, Ann W. Hsing, Pedro W. Fernandez, Anuradha Mittal, Desiree C. Petersen, Melanie H. Quiver, Corinne N. Simonti, Michelle S. Kim, Paidamoyo Kachambwa, Olabode Ajayi, and Maxine Harlemon

Abstract

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. Samples from Ghana and Nigeria clustered together, whereas samples from Senegal and South Africa yielded distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores for prostate cancer were higher in Nigeria than in Senegal. In summary, individual and population-level differences in prostate cancer risk were revealed using a novel genotyping array.Significance:This study presents 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.

Published
2023
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4. Table S2 from A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa

Author

Joseph Lachance, Lindsay N. Petersen, Timothy R. Rebbeck, Elizabeth Pugh, Marcia Adams, Caroline V. Andrews, Jo McBride, Michelle Mawhinney, Chrissie M. Ongaco, Peng Zhang, Marcos H. Woehrmann, Christopher Warren, Mayowa B. Fadipe, Moleboheng Seutloali, Yuri Quintana, Alfred I. Neugut, Hayley Irusen, Wenlong C. Chen, Maureen Joffe, Maxwell M. Nwegbu, Oseremen I. Aisuodionoe-Shadrach, Akin T. Orunmuyi, Akindele O. Adebiyi, Afua O.D. Abrahams, James E. Mensah, Ben Adusei, Nana Yaa F. Snyper, Serigne M. Gueye, Mohamed Jalloh, Ilir Agalliu, Shakuntala Baichoo, Ann W. Hsing, Pedro W. Fernandez, Anuradha Mittal, Desiree C. Petersen, Melanie H. Quiver, Corinne N. Simonti, Michelle S. Kim, Paidamoyo Kachambwa, Olabode Ajayi, and Maxine Harlemon

Abstract

This .xlsx file lists Axiom genotyping solution QC thresholds. Genotyping metrics for both pegs of the MADCaP Array are listed here. This file also includes Benjamini-Hochberg adjusted p-values (FDR = 5%) for pairwise comparisons of derived allele frequencies, ancestry proportions of cases and controls, cumulative runs of homozygosity, and PRS distributions.

Published
2023
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5. Table S4 from A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa

Author

Joseph Lachance, Lindsay N. Petersen, Timothy R. Rebbeck, Elizabeth Pugh, Marcia Adams, Caroline V. Andrews, Jo McBride, Michelle Mawhinney, Chrissie M. Ongaco, Peng Zhang, Marcos H. Woehrmann, Christopher Warren, Mayowa B. Fadipe, Moleboheng Seutloali, Yuri Quintana, Alfred I. Neugut, Hayley Irusen, Wenlong C. Chen, Maureen Joffe, Maxwell M. Nwegbu, Oseremen I. Aisuodionoe-Shadrach, Akin T. Orunmuyi, Akindele O. Adebiyi, Afua O.D. Abrahams, James E. Mensah, Ben Adusei, Nana Yaa F. Snyper, Serigne M. Gueye, Mohamed Jalloh, Ilir Agalliu, Shakuntala Baichoo, Ann W. Hsing, Pedro W. Fernandez, Anuradha Mittal, Desiree C. Petersen, Melanie H. Quiver, Corinne N. Simonti, Michelle S. Kim, Paidamoyo Kachambwa, Olabode Ajayi, and Maxine Harlemon

Abstract

Comprehensive list of cancer-associated loci with African allele frequencies and PBS scores. This dataset includes a total of 2,477 unique markers yielding 3,557 disease or trait associations

Published
2023
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6. Table S3 from A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa

Author

Joseph Lachance, Lindsay N. Petersen, Timothy R. Rebbeck, Elizabeth Pugh, Marcia Adams, Caroline V. Andrews, Jo McBride, Michelle Mawhinney, Chrissie M. Ongaco, Peng Zhang, Marcos H. Woehrmann, Christopher Warren, Mayowa B. Fadipe, Moleboheng Seutloali, Yuri Quintana, Alfred I. Neugut, Hayley Irusen, Wenlong C. Chen, Maureen Joffe, Maxwell M. Nwegbu, Oseremen I. Aisuodionoe-Shadrach, Akin T. Orunmuyi, Akindele O. Adebiyi, Afua O.D. Abrahams, James E. Mensah, Ben Adusei, Nana Yaa F. Snyper, Serigne M. Gueye, Mohamed Jalloh, Ilir Agalliu, Shakuntala Baichoo, Ann W. Hsing, Pedro W. Fernandez, Anuradha Mittal, Desiree C. Petersen, Melanie H. Quiver, Corinne N. Simonti, Michelle S. Kim, Paidamoyo Kachambwa, Olabode Ajayi, and Maxine Harlemon

Abstract

Markers used in PRS calculations. This list includes all markers from the Schumacher et al. 2018 CaP PRS (10) as well as proxy markers that are found on the MADCaP Array. Chromosome and positions (build hg38) listed here are for MADCaP markers used in PRS calculations. Allele frequencies and PBS scores are also included for the 139 CaP markers used in MADCaP PRS calculations. Numbers of markers on each genotyping array within 50kb of CaP-associated loci from Schumacher et al. 2018 are also included here.

Published
2023
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7. A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa

Author

Ann W. Hsing, Michelle Mawhinney, Olabode Ajayi, Moleboheng Seutloali, Anuradha Mittal, Timothy R. Rebbeck, Serigne M. Gueye, Marcos H. Woehrmann, Mohamed Jalloh, Afua O. D Abrahams, Oseremen I. Aisuodionoe-Shadrach, Peng Zhang, Akintunde T. Orunmuyi, Pedro L. Fernández, Chrissie M. Ongaco, Wenlong C. Chen, Corinne N. Simonti, Joseph Lachance, Maxwell M. Nwegbu, Jo McBride, Ben Adusei, Marcia Adams, Melanie H. Quiver, Maureen Joffe, Paidamoyo Kachambwa, Caroline Andrews, Shakuntala Baichoo, Nana Yaa Snyper, Maxine Harlemon, Michelle S Kim, Mayowa B Fadipe, Lindsay Petersen, Alfred I. Neugut, Ilir Agalliu, Elizabeth W. Pugh, Yuri Quintana, Hayley Irusen, James E. Mensah, Desiree C. Petersen, Akindele Olupelumi Adebiyi, and Christopher Warren

Subjects
0301 basic medicine, Male, Cancer Research, Black People, Disease, Biology, Polymorphism, Single Nucleotide, Genome, Article, Cohort Studies, South Africa, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Prostate, Risk Factors, Neoplasms, medicine, Humans, SNP, Genetic Predisposition to Disease, Genotyping, Allele frequency, 030304 developmental biology, Genetic association, Genetics, 0303 health sciences, Prostatic Neoplasms, medicine.disease, 3. Good health, 030104 developmental biology, medicine.anatomical_structure, Genetics, Population, Oncology, Genetic Loci, Case-Control Studies, 030220 oncology & carcinogenesis, Imputation (genetics), Genome-Wide Association Study
Abstract

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. Samples from Ghana and Nigeria clustered together, whereas samples from Senegal and South Africa yielded distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores for prostate cancer were higher in Nigeria than in Senegal. In summary, individual and population-level differences in prostate cancer risk were revealed using a novel genotyping array. Significance: This study presents 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.

Published
2019
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