1
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Jia G, Ping J, Guo X, Yang Y, Tao R, Li B, Ambs S, Barnard ME, Chen Y, Garcia-Closas M, Gu J, Hu JJ, Huo D, John EM, Li CI, Li JL, Nathanson KL, Nemesure B, Olopade OI, Pal T, Press MF, Sanderson M, Sandler DP, Shu XO, Troester MA, Yao S, Adejumo PO, Ahearn T, Brewster AM, Hennis AJM, Makumbi T, Ndom P, O'Brien KM, Olshan AF, Oluwasanu MM, Reid S, Butler EN, Huang M, Ntekim A, Qian H, Zhang H, Ambrosone CB, Cai Q, Long J, Palmer JR, Haiman CA, Zheng W. Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction. Nat Genet 2024; 56:819-826. [PMID: 38741014 PMCID: PMC11284829 DOI: 10.1038/s41588-024-01736-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/25/2024] [Indexed: 05/16/2024]
Abstract
We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.
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Affiliation(s)
- Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Yu Chen
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | | | - Jian Gu
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer J Hu
- Department of Public Health Sciences, University of Miami School of Medicine, Miami, FL, USA
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Esther M John
- Departments of Epidemiology & Population Health and of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher I Li
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Katherine L Nathanson
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, New York, NY, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Tuya Pal
- Division of Genetic Medicine, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael F Press
- Department of Pathology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Melissa A Troester
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Elm & Carlton Streets, Buffalo, NY, USA
| | - Prisca O Adejumo
- Department of Nursing, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Abenaa M Brewster
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Anselm J M Hennis
- George Alleyne Chronic Disease Research Centre, University of the West Indies, Bridgetown, Barbados
- Department of Family, Population and Preventive Medicine, Stony Brook University, New York, NY, USA
| | | | - Paul Ndom
- Yaounde General Hospital, Yaounde, Cameroon
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Andrew F Olshan
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mojisola M Oluwasanu
- Department of Health Promotion and Education, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Sonya Reid
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ebonee N Butler
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maosheng Huang
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Atara Ntekim
- Department of Radiation Oncology, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Huijun Qian
- Department of Statistics and Operation Research, University of North Carolina, Chapel Hill, NC, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Elm & Carlton Streets, Buffalo, NY, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
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2
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Grieshop K, Ho EKH, Kasimatis KR. Dominance reversals: the resolution of genetic conflict and maintenance of genetic variation. Proc Biol Sci 2024; 291:20232816. [PMID: 38471544 DOI: 10.1098/rspb.2023.2816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 02/05/2024] [Indexed: 03/14/2024] Open
Abstract
Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g. habitat, developmental stage, trait or sex) being dominant in that context but recessive where deleterious. This context dependence at least partially mitigates the fitness consequence of heterozygotes carrying one non-beneficial allele for their context and can result in balancing selection that maintains alternative alleles. Dominance reversals are theoretically plausible and are supported by mounting empirical evidence. Here, we highlight the importance of beneficial dominance reversals as a mechanism for the mitigation of genetic conflict and review the theory and empirical evidence for them. We identify some areas in need of further research and development and outline three methods that could facilitate the identification of antagonistic genetic variation (dominance ordination, allele-specific expression and allele-specific ATAC-Seq (assay for transposase-accessible chromatin with sequencing)). There is ample scope for the development of new empirical methods as well as reanalysis of existing data through the lens of dominance reversals. A greater focus on this topic will expand our understanding of the mechanisms that resolve genetic conflict and whether they maintain genetic variation.
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Affiliation(s)
- Karl Grieshop
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada M5S 1A1
- Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, 10691 Stockholm, Sweden
| | - Eddie K H Ho
- Department of Biology, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA
| | - Katja R Kasimatis
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada M5S 1A1
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
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3
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Chen DZ, Roshandel D, Wang Z, Sun L, Paterson AD. Comprehensive whole-genome analyses of the UK Biobank reveal significant sex differences in both genotype missingness and allele frequency on the X chromosome. Hum Mol Genet 2024; 33:543-551. [PMID: 38073250 PMCID: PMC10939428 DOI: 10.1093/hmg/ddad201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/13/2023] [Accepted: 11/14/2023] [Indexed: 03/03/2024] Open
Abstract
The UK Biobank is the most used dataset for genome-wide association studies (GWAS). GWAS of sex, essentially sex differences in minor allele frequencies (sdMAF), has identified autosomal SNPs with significant sdMAF, including in the UK Biobank, but the X chromosome was excluded. Our recent report identified multiple regions on the X chromosome with significant sdMAF, using short-read sequencing of other datasets. We performed a whole genome sdMAF analysis, with ~410 k white British individuals from the UK Biobank, using array genotyped, imputed or exome sequencing data. We observed marked sdMAF on the X chromosome, particularly at the boundaries between the pseudo-autosomal regions (PAR) and the non-PAR (NPR), as well as throughout the NPR, consistent with our earlier report. A small fraction of autosomal SNPs also showed significant sdMAF. Using the centrally imputed data, which relied mostly on low-coverage whole genome sequence, resulted in 2.1% of NPR SNPs with significant sdMAF. The whole exome sequencing also displays sdMAF on the X chromosome, including some NPR SNPs with heterozygous genotype calls in males. Genotyping, sequencing and imputation of X chromosomal SNPs requires further attention to ensure the integrity for downstream association analysis.
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Affiliation(s)
- Desmond Zeya Chen
- Program in Genetics and Genome Biology, The Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 1X8, Canada
| | - Delnaz Roshandel
- Program in Genetics and Genome Biology, The Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 1X8, Canada
| | - Zhong Wang
- Department of Statistics and Data Science, Faculty of Science, National University of Singapore, 21 Lower Kent Ridge Rd, Singapore 119077, Singapore
| | - Lei Sun
- Department of Statistical Science, Faculty of Arts and Science, University of Toronto, 700 University Ave., Toronto, ON M5G 1Z5, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON M5T 3M7, Canada
| | - Andrew D Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 1X8, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON M5T 3M7, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON M5T 3M7, Canada
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4
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Gao Z. Unveiling recent and ongoing adaptive selection in human populations. PLoS Biol 2024; 22:e3002469. [PMID: 38236800 PMCID: PMC10796035 DOI: 10.1371/journal.pbio.3002469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.
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Affiliation(s)
- Ziyue Gao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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5
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Khramtsova EA, Wilson MA, Martin J, Winham SJ, He KY, Davis LK, Stranger BE. Quality control and analytic best practices for testing genetic models of sex differences in large populations. Cell 2023; 186:2044-2061. [PMID: 37172561 PMCID: PMC10266536 DOI: 10.1016/j.cell.2023.04.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 01/31/2023] [Accepted: 04/07/2023] [Indexed: 05/15/2023]
Abstract
Phenotypic sex-based differences exist for many complex traits. In other cases, phenotypes may be similar, but underlying biology may vary. Thus, sex-aware genetic analyses are becoming increasingly important for understanding the mechanisms driving these differences. To this end, we provide a guide outlining the current best practices for testing various models of sex-dependent genetic effects in complex traits and disease conditions, noting that this is an evolving field. Insights from sex-aware analyses will not only teach us about the biology of complex traits but also aid in achieving the goals of precision medicine and health equity for all.
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Affiliation(s)
- Ekaterina A Khramtsova
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Lower Gwynedd Township, PA, USA.
| | - Melissa A Wilson
- School of Life Sciences, Center for Evolution and Medicine, Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85282, USA
| | - Joanna Martin
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Stacey J Winham
- Department of Quantitative Health Sciences, Division of Computational Biology, Mayo Clinic, Rochester, MN, USA
| | - Karen Y He
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Lower Gwynedd Township, PA, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Barbara E Stranger
- Center for Genetic Medicine, Department of Pharmacology, Northwestern University, Chicago, IL, USA.
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6
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Zhu C, Ming MJ, Cole JM, Edge MD, Kirkpatrick M, Harpak A. Amplification is the primary mode of gene-by-sex interaction in complex human traits. CELL GENOMICS 2023; 3:100297. [PMID: 37228747 PMCID: PMC10203050 DOI: 10.1016/j.xgen.2023.100297] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 12/15/2022] [Accepted: 03/13/2023] [Indexed: 05/27/2023]
Abstract
Sex differences in complex traits are suspected to be in part due to widespread gene-by-sex interactions (GxSex), but empirical evidence has been elusive. Here, we infer the mixture of ways in which polygenic effects on physiological traits covary between males and females. We find that GxSex is pervasive but acts primarily through systematic sex differences in the magnitude of many genetic effects ("amplification") rather than in the identity of causal variants. Amplification patterns account for sex differences in trait variance. In some cases, testosterone may mediate amplification. Finally, we develop a population-genetic test linking GxSex to contemporary natural selection and find evidence of sexually antagonistic selection on variants affecting testosterone levels. Our results suggest that amplification of polygenic effects is a common mode of GxSex that may contribute to sex differences and fuel their evolution.
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Affiliation(s)
- Carrie Zhu
- Department of Population Health, The University of Texas at Austin, Austin, TX, USA
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Matthew J. Ming
- Department of Population Health, The University of Texas at Austin, Austin, TX, USA
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Jared M. Cole
- Department of Population Health, The University of Texas at Austin, Austin, TX, USA
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Michael D. Edge
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Mark Kirkpatrick
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Arbel Harpak
- Department of Population Health, The University of Texas at Austin, Austin, TX, USA
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
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7
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Khramtsova EA, Winham SJ, Davis LK, Stranger BE, Wilson MA. Toward a deeper understanding of gene-by-sex interaction models. CELL GENOMICS 2023; 3:100324. [PMID: 37228751 PMCID: PMC10203255 DOI: 10.1016/j.xgen.2023.100324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
In this issue of Cell Genomics, Zhu et al.1 propose amplification as the primary mode for gene-by-sex interactions in complex traits. Khramtsova et al. preview their modeling approach and discuss implications for the future work on the genomics of sex differences.
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Affiliation(s)
- Ekaterina A. Khramtsova
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Spring House, PA, USA
| | - Stacey J. Winham
- Department of Quantitative Health Sciences, Division of Computational Biology, Mayo Clinic, Rochester, MN, USA
| | - Lea K. Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Barbara E. Stranger
- Center for Genetic Medicine, Department of Pharmacology, Northwestern University, Chicago, IL, USA
| | - Melissa A. Wilson
- School of Life Sciences, Center for Evolution and Medicine, Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85282, USA
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8
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Jia G, Ping J, Shu X, Yang Y, Cai Q, Kweon SS, Choi JY, Kubo M, Park SK, Bolla MK, Dennis J, Wang Q, Guo X, Li B, Tao R, Aronson KJ, Chan TL, Gao YT, Hartman M, Ho WK, Ito H, Iwasaki M, Iwata H, John EM, Kasuga Y, Kim MK, Kurian AW, Kwong A, Li J, Lophatananon A, Low SK, Mariapun S, Matsuda K, Matsuo K, Muir K, Noh DY, Park B, Park MH, Shen CY, Shin MH, Spinelli JJ, Takahashi A, Tseng C, Tsugane S, Wu AH, Yamaji T, Zheng Y, Dunning AM, Pharoah PDP, Teo SH, Kang D, Easton DF, Simard J, Shu XO, Long J, Zheng W. Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics. Am J Hum Genet 2022; 109:2185-2195. [PMID: 36356581 PMCID: PMC9748250 DOI: 10.1016/j.ajhg.2022.10.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/20/2022] [Indexed: 11/10/2022] Open
Abstract
By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10-8 and a Bonferroni-corrected p < 4.6 × 10-6, respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy.
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Affiliation(s)
- Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Xiang Shu
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, Korea; Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun, Korea
| | - Ji-Yeob Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sue K Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kristan J Aronson
- Department of Public Health Sciences and Queen's Cancer Research Institute, Queen's University, Kingston, ON, Canada
| | - Tsun L Chan
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong SAR, China; Department of Molecular Pathology, Hong Kong Sanatorium & Hospital, Hong Kong SAR, China
| | - Yu-Tang Gao
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Mikael Hartman
- Department of Surgery, National University Hospital, Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Weang Kee Ho
- Department of Applied Mathematics, Faculty of Engineering, University of Nottingham Malaysia Campus, Semenyih, Selangor, Malaysia
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan; Department of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Hiroji Iwata
- Department of Breast Oncology, Aichi Cancer Center, Nagoya, Aichi, Japan
| | - Esther M John
- Departments of Epidemiology, Cancer Prevention Institute of California, Fremont, CA, USA; Departments of Health Research and Policy, School of Medicine, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Yoshio Kasuga
- Department of Surgery, Nagano Matsushiro General Hospital, Nagano, Japan
| | - Mi-Kyung Kim
- Division of Cancer Epidemiology and Management, National Cancer Center, Goyang, Korea
| | - Allison W Kurian
- Departments of Health Research and Policy, School of Medicine, Stanford University, Stanford, CA, USA
| | - Ava Kwong
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong SAR, China; Department of Surgery, University of Hong Kong, Hong Kong SAR, China; Department of Surgery, Hong Kong Sanatorium & Hospital, Hong Kong SAR, China
| | - Jingmei Li
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Human Genetics, Genome Institute of Singapore, Singapore, Singapore; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Artitaya Lophatananon
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK; Institute of Population Health, University of Manchester, Manchester, UK
| | - Siew-Kee Low
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan; Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenneth Muir
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK; Institute of Population Health, University of Manchester, Manchester, UK
| | - Dong-Young Noh
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea; Department of Surgery, Seoul National University Hospital, Seoul, South Korea
| | - Boyoung Park
- Department of Medicine, Hanyang University College of Medicine, Seoul, Korea
| | - Min-Ho Park
- Department of Surgery, Chonnam National University Medical School, Gwangju, Korea
| | - Chen-Yang Shen
- College of Public Health, China Medical University, Taichong, Taiwan; Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Min-Ho Shin
- Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, Korea
| | - John J Spinelli
- Department of Cancer Control Research, British Columbia Cancer Agency, Vancouver, BC, Canada; School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Atsushi Takahashi
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Chiuchen Tseng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Shoichiro Tsugane
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Ying Zheng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Soo-Hwang Teo
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia; Department of Surgery, Faculty of Medicine, University Malaya, Kuala Lumpar, Malaysia
| | - Daehee Kang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea; Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Korea
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval, Research Center, Québec City, QC, Canada
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA.
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9
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Polygenic signals of sex differences in selection in humans from the UK Biobank. PLoS Biol 2022; 20:e3001768. [PMID: 36067235 PMCID: PMC9481184 DOI: 10.1371/journal.pbio.3001768] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 09/16/2022] [Accepted: 07/27/2022] [Indexed: 11/19/2022] Open
Abstract
Sex differences in the fitness effects of genetic variants can influence the rate of adaptation and the maintenance of genetic variation. For example, "sexually antagonistic" (SA) variants, which are beneficial for one sex and harmful for the other, can both constrain adaptation and increase genetic variability for fitness components such as survival, fertility, and disease susceptibility. However, detecting variants with sex-differential fitness effects is difficult, requiring genome sequences and fitness measurements from large numbers of individuals. Here, we develop new theory for studying sex-differential selection across a complete life cycle and test our models with genotypic and reproductive success data from approximately 250,000 UK Biobank individuals. We uncover polygenic signals of sex-differential selection affecting survival, reproductive success, and overall fitness, with signals of sex-differential reproductive selection reflecting a combination of SA polymorphisms and sexually concordant polymorphisms in which the strength of selection differs between the sexes. Moreover, these signals hold up to rigorous controls that minimise the contributions of potential confounders, including sequence mapping errors, population structure, and ascertainment bias. Functional analyses reveal that sex-differentiated sites are enriched in phenotype-altering genomic regions, including coding regions and loci affecting a range of quantitative traits. Population genetic analyses show that sex-differentiated sites exhibit evolutionary histories dominated by genetic drift and/or transient balancing selection, but not long-term balancing selection, which is consistent with theoretical predictions of effectively weak SA balancing selection in historically small populations. Overall, our results are consistent with polygenic sex-differential-including SA-selection in humans. Evidence for sex-differential selection is particularly strong for variants affecting reproductive success, in which the potential contributions of nonrandom sampling to signals of sex differentiation can be excluded.
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10
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Delph LF, Brown KE, Ríos LD, Kelly JK. Sex‐specific natural selection on SNPs in
Silene latifolia. Evol Lett 2022; 6:308-318. [PMID: 35937470 PMCID: PMC9346077 DOI: 10.1002/evl3.283] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 02/24/2022] [Accepted: 03/13/2022] [Indexed: 01/15/2023] Open
Affiliation(s)
- Lynda F. Delph
- Department of Biology Indiana University Bloomington Indiana USA
| | - Keely E. Brown
- Department of Ecology and Evolutionary Biology University of Kansas Lawrence Kansas USA
| | - Luis Diego Ríos
- Department of Biology Indiana University Bloomington Indiana USA
| | - John K. Kelly
- Department of Ecology and Evolutionary Biology University of Kansas Lawrence Kansas USA
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11
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Ruzicka F, Connallon T. An unbiased test reveals no enrichment of sexually antagonistic polymorphisms on the human X chromosome. Proc Biol Sci 2022; 289:20212314. [PMID: 35078366 PMCID: PMC8790371 DOI: 10.1098/rspb.2021.2314] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Mutations with beneficial effects in one sex can have deleterious effects in the other. Such 'sexually antagonistic' (SA) variants contribute to variation in life-history traits and overall fitness, yet their genomic distribution is poorly resolved. Theory predicts that SA variants could be enriched on the X chromosome or autosomes, yet current empirical tests face two formidable challenges: (i) identifying SA selection in genomic data is difficult; and (ii) metrics of SA variation show persistent biases towards the X, even when SA variants are randomly distributed across the genome. Here, we present an unbiased test of the theory that SA variants are enriched on the X. We first develop models for reproductive FST-a metric for quantifying sex-differential (including SA) effects of genetic variants on lifetime reproductive success-that control for X-linked biases. Comparing data from approximately 250 000 UK Biobank individuals to our models, we find FST elevations consistent with both X-linked and autosomal SA polymorphisms affecting reproductive success in humans. However, the extent of FST elevations does not differ from a model in which SA polymorphisms are randomly distributed across the genome. We argue that the polygenic nature of SA variation, along with sex asymmetries in SA effects, might render X-linked enrichment of SA polymorphisms unlikely.
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Affiliation(s)
- Filip Ruzicka
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
| | - Tim Connallon
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
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12
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Lin Y, Darolti I, Furman BLS, Almeida P, Sandkam BA, Breden F, Wright AE, Mank JE. Gene duplication to the Y chromosome in Trinidadian Guppies. Mol Ecol 2022; 31:1853-1863. [PMID: 35060220 DOI: 10.1111/mec.16355] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 12/06/2021] [Accepted: 01/07/2022] [Indexed: 11/29/2022]
Abstract
Differences in allele frequencies at autosomal genes between males and females in a population can result from two scenarios. First, unresolved sexual conflict over survival can produce allelic differentiation between the sexes. However, given the substantial mortality costs required to produce allelic differences between males and females at each generation, it remains unclear how many loci within the genome experience significant sexual conflict over survival. Alternatively, recent studies have shown that similarity between autosomal and Y sequences can create perceived allelic differences between the sexes. However, Y duplications are most likely in species with large non-recombining regions, in part because they simply represent larger targets for duplications. We assessed the genomes of 120 wild-caught guppies, which experience extensive predation- and pathogen-induced mortality and have a relatively small ancestral Y chromosome. We identified seven autosomal genes that show allelic differences between male and female adults. Five of these genes show clear evidence of whole or partial gene duplication between the Y chromosome and the autosomes. The remaining two genes show evidence of partial homology to the Y. Overall, our findings suggest that the guppy genome experiences a very low level of unresolved sexual conflict over survival, and instead the Y chromosome, despite its small ancestral size and recent origin, may nonetheless accumulate genes with male-specific functions.
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Affiliation(s)
- Yuying Lin
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Canada
| | - Iulia Darolti
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Canada
| | - Benjamin L S Furman
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Canada
| | - Pedro Almeida
- Department of Genetics, Evolution and Environment, University College London, United Kingdom
| | - Benjamin A Sandkam
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Canada
| | - Felix Breden
- Department of Biological Sciences, Simon Fraser University, Canada
| | - Alison E Wright
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield
| | - Judith E Mank
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Canada.,Biosciences, University of Exeter, Penryn Campus, United Kingdom
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13
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Glaser-Schmitt A, Wittmann MJ, Ramnarine TJS, Parsch J. Sexual antagonism, temporally fluctuating selection, and variable dominance affect a regulatory polymorphism in Drosophila melanogaster. Mol Biol Evol 2021; 38:4891-4907. [PMID: 34289067 PMCID: PMC8557461 DOI: 10.1093/molbev/msab215] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Understanding how genetic variation is maintained within species is a major goal of evolutionary genetics that can shed light on the preservation of biodiversity. Here, we examined the maintenance of a regulatory single-nucleotide polymorphism (SNP) of the X-linked Drosophila melanogaster gene fezzik. The derived variant at this site is at intermediate frequency in many worldwide populations but absent in populations from the ancestral species range in sub-Saharan Africa. We collected and genotyped wild-caught individuals from a single European population biannually over a period of 5 years, which revealed an overall difference in allele frequency between the sexes and a consistent change in allele frequency across seasons in females but not in males. Modeling based on the observed allele and genotype frequencies suggested that both sexually antagonistic and temporally fluctuating selection may help maintain variation at this site. The derived variant is predicted to be female-beneficial and mostly recessive; however, there was uncertainty surrounding our dominance estimates and long-term modeling projections suggest that it is more likely to be dominant. By examining gene expression phenotypes, we found that phenotypic dominance was variable and dependent upon developmental stage and genetic background, suggesting that dominance may be variable at this locus. We further determined that fezzik expression and genotype are associated with starvation resistance in a sex-dependent manner, suggesting a potential phenotypic target of selection. By characterizing the mechanisms of selection acting on this SNP, our results improve our understanding of how selection maintains genetic and phenotypic variation in natural populations.
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Affiliation(s)
- Amanda Glaser-Schmitt
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany
| | | | - Timothy J S Ramnarine
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany
| | - John Parsch
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany
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