Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

Wang, Anqi; Shen, Jiayi; Rodriguez, Alex A.; Saunders, Edward J.; Chen, Fei; Janivara, Rohini; Darst, Burcu F.; Sheng, Xin; Xu, Yili; Chou, Alisha J.; Benlloch, Sara; Dadaev, Tokhir; Brook, Mark N.; Plym, Anna; Sahimi, Ali; Hoffman, Thomas J.; Takahashi, Atushi; Matsuda, Koichi; Momozawa, Yukihide; Fujita, Masashi; Laisk, Triin; Figuerêdo, Jéssica; Muir, Kenneth; Ito, Shuji; Liu, Xiaoxi; ,; Yamanashi, Yuji; Furukawa, Yoichi; Morisaki, Takayuki; Murakami, Yoshinori; Muto, Kaori; Nagai, Akiko; Obara, Wataru; Yamaji, Ken; Takahashi, Kazuhisa; Asai, Satoshi; Takahashi, Yasuo; Suzuki, Takao; Sinozaki, Nobuaki; Yamaguchi, Hiroki; Minami, Shiro; Murayama, Shigeo; Yoshimori, Kozo; Nagayama, Satoshi; Obata, Daisuke; Higashiyama, Masahiko; Masumoto, Akihide; Koretsune, Yukihiro; Uchio, Yuji; Kubo, Michiaki; Kamatani, Yoichiro; Lophatananon, Artitaya; Wan, Peggy; Andrews, Caroline; Lori, Adriana; Choudhury, Parichoy P.; Schleutker, Johanna; Tammela, Teuvo L. J.; Sipeky, Csilla; Auvinen, Anssi; Giles, Graham G.; Southey, Melissa C.; MacInnis, Robert J.; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Rentsch, Christopher T.; Cho, Kelly; Mcmahon, Benjamin H.; Neal, David E.; Donovan, Jenny L.; Hamdy, Freddie C.; Martin, Richard M.; Nordestgaard, Borge G.; Nielsen, Sune F.; Weischer, Maren; Bojesen, Stig E.; Røder, Andreas; Stroomberg, Hein V.; Batra, Jyotsna; Chambers, Suzanne; Horvath, Lisa; Clements, Judith A.; Tilly, Wayne; Risbridger, Gail P.; Gronberg, Henrik; Aly, Markus; Szulkin, Robert; Eklund, Martin; Nordstrom, Tobias; Pashayan, Nora; Dunning, Alison M.; Ghoussaini, Maya; Travis, Ruth C.; Key, Tim J.; Riboli, Elio; Park, Jong Y.; Sellers, Thomas A.; Lin, Hui-Yi; Albanes, Demetrius; Weinstein, Stephanie; Cook, Michael B.; Mucci, Lorelei A.; Giovannucci, Edward; Lindstrom, Sara; Kraft, Peter; Hunter, David J.; Penney, Kathryn L.; Turman, Constance; Tangen, Catherine M.; Goodman, Phyllis J.; Thompson, Ian M.; Hamilton, Robert J.; Fleshner, Neil E.; Finelli, Antonio; Parent, Marie-Élise; Stanford, Janet L.; Ostrander, Elaine A.; Koutros, Stella; Beane Freeman, Laura E.; Stampfer, Meir; Wolk, Alicja; Håkansson, Niclas; Andriole, Gerald L.; Hoover, Robert N.; Machiela, Mitchell J.; Sørensen, Karina Dalsgaard; Borre, Michael; Blot, William J.; Zheng, Wei; Yeboah, Edward D.; Mensah, James E.; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Wu, Yudong; Zhao, Shan-Chao; Sun, Zan; Thibodeau, Stephen N.; McDonnell, Shannon K.; Schaid, Daniel J.; West, Catharine M. L.; Barnett, Gill; Maier, Christiane; Schnoeller, Thomas; Luedeke, Manuel; Kibel, Adam S.; Drake, Bettina F.; Cussenot, Olivier; Cancel-Tassin, Geraldine; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; John, Esther M.; Grindedal, Eli Marie; Maehle, Lovise; Khaw, Kay-Tee; Ingles, Sue A.; Stern, Mariana C.; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Rosenstein, Barry S.; Kerns, Sarah L.; Ostrer, Harry; Teixeira, Manuel R.; Paulo, Paula; Brandão, Andreia; Watya, Stephen; Lubwama, Alexander; Bensen, Jeannette T.; Butler, Ebonee N.; Mohler, James L.; Taylor, Jack A.; Kogevinas, Manolis; Dierssen-Sotos, Trinidad; Castaño-Vinyals, Gemma; Cannon-Albright, Lisa; Teerlink, Craig C.; Huff, Chad D.; Pilie, Patrick; Yu, Yao; Bohlender, Ryan J.; Gu, Jian; Strom, Sara S.; Multigner, Luc; Blanchet, Pascal; Brureau, Laurent; Kaneva, Radka; Slavov, Chavdar; Mitev, Vanio; Leach, Robin J.; Brenner, Hermann; Chen, Xuechen; Holleczek, Bernd; Schöttker, Ben; Klein, Eric A.; Hsing, Ann W.; Kittles, Rick A.; Murphy, Adam B.; Logothetis, Christopher J.; Kim, Jeri; Neuhausen, Susan L.; Steele, Linda; Ding, Yuan Chun; Isaacs, William B.; Nemesure, Barbara; Hennis, Anselm J. M.; Carpten, John; Pandha, Hardev; Michael, Agnieszka; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Xu, Jianfeng; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Newcomb, Lisa F.; Lin, Daniel W.; Fowke, Jay H.; Neslund-Dudas, Christine M.; Rybicki, Benjamin A.; Gamulin, Marija; Lessel, Davor; Kulis, Tomislav; Usmani, Nawaid; Abraham, Aswin; Singhal, Sandeep; Parliament, Matthew; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Larkin, Samantha; Townsend, Paul A.; Aukim-Hastie, Claire; Bush, William S.; Aldrich, Melinda C.; Crawford, Dana C.; Srivastava, Shiv; Cullen, Jennifer; Petrovics, Gyorgy; Casey, Graham; Wang, Ying; Tettey, Yao; Lachance, Joseph; Tang, Wei; Biritwum, Richard B.; Adjei, Andrew A.; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Yamoah, Kosj; Govindasami, Koveela; Chokkalingam, Anand P.; Keaton, Jacob M.; Hellwege, Jacklyn N.; Clark, Peter E.; Jalloh, Mohamed; Gueye, Serigne M.; Niang, Lamine; Ogunbiyi, Olufemi; Shittu, Olayiwola; Amodu, Olukemi; Adebiyi, Akindele O.; Aisuodionoe-Shadrach, Oseremen I.; Ajibola, Hafees O.; Jamda, Mustapha A.; Oluwole, Olabode P.; Nwegbu, Maxwell; Adusei, Ben; Mante, Sunny; Darkwa-Abrahams, Afua; Diop, Halimatou; Gundell, Susan M.; Roobol, Monique J.; Jenster, Guido; van Schaik, Ron H. N.; Hu, Jennifer J.; Sanderson, Maureen; Kachuri, Linda; Varma, Rohit; McKean-Cowdin, Roberta; Torres, Mina; Preuss, Michael H.; Loos, Ruth J. F.; Zawistowski, Matthew; Zöllner, Sebastian; Lu, Zeyun; Van Den Eeden, Stephen K.; Easton, Douglas F.; Ambs, Stefan; Edwards, Todd L.; Mägi, Reedik; Rebbeck, Timothy R.; Fritsche, Lars; Chanock, Stephen J.; Berndt, Sonja I.; Wiklund, Fredrik; Nakagawa, Hidewaki; Witte, John S.; Gaziano, J. Michael; Justice, Amy C.; Mancuso, Nick; Terao, Chikashi; Eeles, Rosalind A.; Kote-Jarai, Zsofia; Madduri, Ravi K.; Conti, David V.; Haiman, Christopher A.

doi:10.1038/s41588-023-01534-4

Cited by 22 publications

(8 citation statements)

References 66 publications

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“…Bim −/− mice develop plasmacytosis; autoimmune kidney disease. BIK Malignant neoplasm of prostate (+/−) Wang et al [ 75 ]. Novel risk variants for prostate cancer identified in the BIK locus in multi-ancestry GWAS.…”

Section: Resultsmentioning

confidence: 99%

The broad impact of cell death genes on the human disease phenome

Rich,

Lin,

Gamazon

et al. 2024

Cell Death Dis

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Cell death mediated by genetically defined signaling pathways influences the health and dynamics of all tissues, however the tissue specificity of cell death pathways and the relationships between these pathways and human disease are not well understood. We analyzed the expression profiles of an array of 44 cell death genes involved in apoptosis, necroptosis, and pyroptosis cell death pathways across 49 human tissues from GTEx, to elucidate the landscape of cell death gene expression across human tissues, and the relationship between tissue-specific genetically determined expression and the human phenome. We uncovered unique cell death gene expression profiles across tissue types, suggesting there are physiologically distinct cell death programs in different tissues. Using summary statistics-based transcriptome wide association studies (TWAS) on human traits in the UK Biobank (n ~ 500,000), we evaluated 513 traits encompassing ICD-10 defined diagnoses and laboratory-derived traits. Our analysis revealed hundreds of significant (FDR < 0.05) associations between genetically regulated cell death gene expression and an array of human phenotypes encompassing both clinical diagnoses and hematologic parameters, which were independently validated in another large-scale DNA biobank (BioVU) at Vanderbilt University Medical Center (n = 94,474) with matching phenotypes. Cell death genes were highly enriched for significant associations with blood traits versus non-cell-death genes, with apoptosis-associated genes enriched for leukocyte and platelet traits. Our findings are also concordant with independently published studies (e.g. associations between BCL2L11/BIM expression and platelet & lymphocyte counts). Overall, these results suggest that cell death genes play distinct roles in their contribution to human phenotypes, and that cell death genes influence a diverse array of human traits.

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Section: Resultsmentioning

confidence: 99%

The broad impact of cell death genes on the human disease phenome

Rich,

Lin,

Gamazon

et al. 2024

Cell Death Dis

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“…Prostate cancer (access ID: GCST90274714), uterine fibroids (access ID: GCST009158), hypothyroidism (access ID: GCST90204167), coronary artery disease (access ID: GCST005194), melanoma (access ID: GCST90011809), and thyroid cancer (access ID: GCST90011813) summary statistics were retrieved from the GWAS Catalog (https://www.ebi.ac.uk/gwas/). Prostate cancer included 122,188 cases and 604,640 controls of European ancestry [17], uterine fibroids comprised 20,406 cases and 223,918 controls of European ancestry [18], hypothyroidism included 51,194 cases and 443,383 controls of European ancestry [19], coronary artery disease comprised 34,541 cases and 261,984 controls of European ancestry [20], melanoma included 6,777 cases and 410,350 controls of European ancestry [21], and thyroid cancer included 762 cases and 410,350 controls of European ancestry [21]. The GWAS summary statistics for multiple sclerosis (access ID: ieu-b-18) [22], TL (access ID: ieu-b-4879) [8], and 102 CD8+ T cells subpopulations [23] ( Supplementary Table 1 ) were downloaded from the ieu open gwas project (https://gwas.mrcieu.ac.uk/datasets/).…”

Section: Methodsmentioning

confidence: 99%

Integrative proteogenomics study identifies the indirect effect of circulating proteins on 8 diseases via telomere length

Li,

Gong

2023

Preprint

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Growing evidence has revealed the associations between telomere length and diseases; however, the mechanisms behind these links are not fully understood. In this study, by applying proteome-wide Mendelian randomisation (MR), multiple sensitivity analyses, colocalization, single-cell RNA-sequencing, and mediation analysis, the potential mechanisms that link 4,907 plasma proteins, telomere length, and 8 diseases were identified. Following MR analysis for the effects of plasma protein levels on telomere length, 34 proteins were found to be causally related to telomere length. Among these, 8 proteins (PSMB4, PARP1, GDI2, MAX, GMPR2, ARPC1B, ATOX1, and NUDT5) were found to be well colocalized with telomere length (posterior probability >80%). 21 mediation pairs were revealed for the indirect effect of circulating proteins on 8 diseases via telomere length. Furthermore, 35 proteins, including CD8A, were found to be influenced by telomere length among 4,907 proteins. No significant mediation pairs for circulating proteins that mediate the effects of telomere length on disease have been identified. Overall, our study provided insights into understanding the biology of telomeres and prioritized the identified proteins as prospective intervention targets for the disease.

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“…Previous efforts have demonstrated that leveraging the heterogeneity of LD and minor allele frequency (MAF) across diverse ancestries improves the precision of statistical fine-mapping and therefore enhances our biological understanding of complex diseases [20][21][22][23][24][25] and molecular traits [26][27][28][29][30][31][32] .…”

Section: Introductionmentioning

confidence: 99%

“…Statistical fine-mapping aims to resolve precisely this issue 15–19 , yet pervasive LD signals limit the resolution of these approaches. Previous efforts have demonstrated that leveraging the heterogeneity of LD and minor allele frequency (MAF) across diverse ancestries improves the precision of statistical fine-mapping and therefore enhances our biological understanding of complex diseases 20–25 and molecular traits 26–32 .…”

Section: Introductionmentioning

confidence: 99%

Improved multi-ancestry fine-mapping identifiescis-regulatory variants underlying molecular traits and disease risk

Lu,

Wang,

Carr

et al. 2024

Preprint

Self Cite

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Multi-ancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. However, existing approaches fail to reflect shared genetic architectures. To solve this limitation, we present the Sum of Shared Single Effects (SuShiE) model, which leverages LD heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations, and estimate ancestry-specific expression prediction weights. We apply SuShiE to mRNA expression measured in PBMCs (n=956) and LCLs (n=814) together with plasma protein levels (n=854) from individuals of diverse ancestries in the TOPMed MESA and GENOA studies. We find SuShiE fine-maps cis-molQTLs for 16% more genes compared with baselines while prioritizing fewer variants with greater functional enrichment. SuShiE infers highly consistent cis-molQTL architectures across ancestries on average; however, we also find evidence of heterogeneity at genes with predicted loss-of-function intolerance, suggesting that environmental interactions may partially explain differences in cis-molQTL effect sizes across ancestries. Lastly, we leverage estimated cis-molQTL effect-sizes to perform individual-level TWAS and PWAS on six white blood cell-related traits in AOU Biobank individuals (n=86k), and identify 44 more genes compared with baselines, further highlighting its benefits in identifying genes relevant for complex disease risk. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.

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Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

Cited by 22 publications

References 66 publications

The broad impact of cell death genes on the human disease phenome

The broad impact of cell death genes on the human disease phenome

Integrative proteogenomics study identifies the indirect effect of circulating proteins on 8 diseases via telomere length

Improved multi-ancestry fine-mapping identifiescis-regulatory variants underlying molecular traits and disease risk

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