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Your search keyword '"Goddard, Michael"' showing total 277 results
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277 results on '"Goddard, Michael"'

5. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data

Author

Wainschtein, Pierrick, Jain, Deepti, Zheng, Zhili, Cupples, L Adrienne, Shadyab, Aladdin H, McKnight, Barbara, Shoemaker, Benjamin M, Mitchell, Braxton D, Psaty, Bruce M, Kooperberg, Charles, Liu, Ching-Ti, Albert, Christine M, Roden, Dan, Chasman, Daniel I, Darbar, Dawood, Lloyd-Jones, Donald M, Arnett, Donna K, Regan, Elizabeth A, Boerwinkle, Eric, Rotter, Jerome I, O’Connell, Jeffrey R, Yanek, Lisa R, de Andrade, Mariza, Allison, Matthew A, McDonald, Merry-Lynn N, Chung, Mina K, Fornage, Myriam, Chami, Nathalie, Smith, Nicholas L, Ellinor, Patrick T, Vasan, Ramachandran S, Mathias, Rasika A, Loos, Ruth JF, Rich, Stephen S, Lubitz, Steven A, Heckbert, Susan R, Redline, Susan, Guo, Xiuqing, Chen, Y-D Ida, Laurie, Cecelia A, Hernandez, Ryan D, McGarvey, Stephen T, Goddard, Michael E, Laurie, Cathy C, North, Kari E, Lange, Leslie A, Weir, Bruce S, Yengo, Loic, Yang, Jian, and Visscher, Peter M

Subjects
Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, Alleles, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Multifactorial Inheritance, Polymorphism, Single Nucleotide, TOPMed Anthropometry Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

Published
2022

6. Assortative mating biases marker-based heritability estimators

Author

Border, Richard, O’Rourke, Sean, de Candia, Teresa, Goddard, Michael E, Visscher, Peter M, Yengo, Loic, Jones, Matt, and Keller, Matthew C

Subjects
Biological Sciences, Genetics, Biological Psychology, Statistics, Mathematical Sciences, Psychology, Algorithms, Bias, Computer Simulation, Female, Genetics, Population, Genome-Wide Association Study, Humans, Likelihood Functions, Linkage Disequilibrium, Male, Mendelian Randomization Analysis, Models, Genetic, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Reproduction
Abstract

Many traits are subject to assortative mating, with recent molecular genetic findings confirming longstanding theoretical predictions that assortative mating induces long range dependence across causal variants. However, all marker-based heritability estimators implicitly assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments and likelihood-based estimators are biased in the presence of assortative mating and derive corrected heritability estimators for traits subject to assortment. Finally, we demonstrate that the empirical patterns of estimates across methods and sample sizes for real traits subject to assortative mating are congruent with expected assortative mating-induced biases. For example, marker-based heritability estimates for height are 14% - 23% higher than corrected estimates using UK Biobank data.

Published
2022

8. A saturated map of common genetic variants associated with human height

Author

Yengo, Loïc, Vedantam, Sailaja, Marouli, Eirini, Sidorenko, Julia, Bartell, Eric, Sakaue, Saori, Graff, Marielisa, Eliasen, Anders U., Jiang, Yunxuan, Raghavan, Sridharan, Miao, Jenkai, Arias, Joshua D., Graham, Sarah E., Mukamel, Ronen E., Spracklen, Cassandra N., Yin, Xianyong, Chen, Shyh-Huei, Ferreira, Teresa, Highland, Heather H., Ji, Yingjie, Karaderi, Tugce, Lin, Kuang, Lüll, Kreete, Malden, Deborah E., Medina-Gomez, Carolina, Machado, Moara, Moore, Amy, Rüeger, Sina, Sim, Xueling, Vrieze, Scott, Ahluwalia, Tarunveer S., Akiyama, Masato, Allison, Matthew A., Alvarez, Marcus, Andersen, Mette K., Ani, Alireza, Appadurai, Vivek, Arbeeva, Liubov, Bhaskar, Seema, Bielak, Lawrence F., Bollepalli, Sailalitha, Bonnycastle, Lori L., Bork-Jensen, Jette, Bradfield, Jonathan P., Bradford, Yuki, Braund, Peter S., Brody, Jennifer A., Burgdorf, Kristoffer S., Cade, Brian E., Cai, Hui, Cai, Qiuyin, Campbell, Archie, Cañadas-Garre, Marisa, Catamo, Eulalia, Chai, Jin-Fang, Chai, Xiaoran, Chang, Li-Ching, Chang, Yi-Cheng, Chen, Chien-Hsiun, Chesi, Alessandra, Choi, Seung Hoan, Chung, Ren-Hua, Cocca, Massimiliano, Concas, Maria Pina, Couture, Christian, Cuellar-Partida, Gabriel, Danning, Rebecca, Daw, E. Warwick, Degenhard, Frauke, Delgado, Graciela E., Delitala, Alessandro, Demirkan, Ayse, Deng, Xuan, Devineni, Poornima, Dietl, Alexander, Dimitriou, Maria, Dimitrov, Latchezar, Dorajoo, Rajkumar, Ekici, Arif B., Engmann, Jorgen E., Fairhurst-Hunter, Zammy, Farmaki, Aliki-Eleni, Faul, Jessica D., Fernandez-Lopez, Juan-Carlos, Forer, Lukas, Francescatto, Margherita, Freitag-Wolf, Sandra, Fuchsberger, Christian, Galesloot, Tessel E., Gao, Yan, Gao, Zishan, Geller, Frank, Giannakopoulou, Olga, Giulianini, Franco, Gjesing, Anette P., Goel, Anuj, Gordon, Scott D., Gorski, Mathias, Grove, Jakob, Guo, Xiuqing, Gustafsson, Stefan, Haessler, Jeffrey, Hansen, Thomas F., Havulinna, Aki S., Haworth, Simon J., He, Jing, Heard-Costa, Nancy, Hebbar, Prashantha, Hindy, George, Ho, Yuk-Lam A., Hofer, Edith, Holliday, Elizabeth, Horn, Katrin, Hornsby, Whitney E., Hottenga, Jouke-Jan, Huang, Hongyan, Huang, Jie, Huerta-Chagoya, Alicia, Huffman, Jennifer E., Hung, Yi-Jen, Huo, Shaofeng, Hwang, Mi Yeong, Iha, Hiroyuki, Ikeda, Daisuke D., Isono, Masato, Jackson, Anne U., Jäger, Susanne, Jansen, Iris E., Johansson, Ingegerd, Jonas, Jost B., Jonsson, Anna, Jørgensen, Torben, Kalafati, Ioanna-Panagiota, Kanai, Masahiro, Kanoni, Stavroula, Kårhus, Line L., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kawaguchi, Takahisa, Kember, Rachel L., Kentistou, Katherine A., Kim, Han-Na, Kim, Young Jin, Kleber, Marcus E., Knol, Maria J., Kurbasic, Azra, Lauzon, Marie, Le, Phuong, Lea, Rodney, Lee, Jong-Young, Leonard, Hampton L., Li, Shengchao A., Li, Xiaohui, Li, Xiaoyin, Liang, Jingjing, Lin, Honghuang, Lin, Shih-Yi, Liu, Jun, Liu, Xueping, Lo, Ken Sin, Long, Jirong, Lores-Motta, Laura, Luan, Jian’an, Lyssenko, Valeriya, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamakou, Vasiliki, Mangino, Massimo, Manichaikul, Ani, Marten, Jonathan, Mattheisen, Manuel, Mavarani, Laven, McDaid, Aaron F., Meidtner, Karina, Melendez, Tori L., Mercader, Josep M., Milaneschi, Yuri, Miller, Jason E., Millwood, Iona Y., Mishra, Pashupati P., Mitchell, Ruth E., Møllehave, Line T., Morgan, Anna, Mucha, Soeren, Munz, Matthias, Nakatochi, Masahiro, Nelson, Christopher P., Nethander, Maria, Nho, Chu Won, Nielsen, Aneta A., Nolte, Ilja M., Nongmaithem, Suraj S., Noordam, Raymond, Ntalla, Ioanna, Nutile, Teresa, Pandit, Anita, Christofidou, Paraskevi, Pärna, Katri, Pauper, Marc, Petersen, Eva R. B., Petersen, Liselotte V., Pitkänen, Niina, Polašek, Ozren, Poveda, Alaitz, Preuss, Michael H., Pyarajan, Saiju, Raffield, Laura M., Rakugi, Hiromi, Ramirez, Julia, Rasheed, Asif, Raven, Dennis, Rayner, Nigel W., Riveros, Carlos, Rohde, Rebecca, Ruggiero, Daniela, Ruotsalainen, Sanni E., Ryan, Kathleen A., Sabater-Lleal, Maria, Saxena, Richa, Scholz, Markus, Sendamarai, Anoop, Shen, Botong, Shi, Jingchunzi, Shin, Jae Hun, Sidore, Carlo, Sitlani, Colleen M., Slieker, Roderick C., Smit, Roelof A. J., Smith, Albert V., Smith, Jennifer A., Smyth, Laura J., Southam, Lorraine, Steinthorsdottir, Valgerdur, Sun, Liang, Takeuchi, Fumihiko, Tallapragada, Divya Sri Priyanka, Taylor, Kent D., Tayo, Bamidele O., Tcheandjieu, Catherine, Terzikhan, Natalie, Tesolin, Paola, Teumer, Alexander, Theusch, Elizabeth, Thompson, Deborah J., Thorleifsson, Gudmar, Timmers, Paul R. H. J., Trompet, Stella, Turman, Constance, Vaccargiu, Simona, van der Laan, Sander W., van der Most, Peter J., van Klinken, Jan B., van Setten, Jessica, Verma, Shefali S., Verweij, Niek, Veturi, Yogasudha, Wang, Carol A., Wang, Chaolong, Wang, Lihua, Wang, Zhe, Warren, Helen R., Bin Wei, Wen, Wickremasinghe, Ananda R., Wielscher, Matthias, Wiggins, Kerri L., Winsvold, Bendik S., Wong, Andrew, Wu, Yang, Wuttke, Matthias, Xia, Rui, Xie, Tian, Yamamoto, Ken, Yang, Jingyun, Yao, Jie, Young, Hannah, Yousri, Noha A., Yu, Lei, Zeng, Lingyao, Zhang, Weihua, Zhang, Xinyuan, Zhao, Jing-Hua, Zhao, Wei, Zhou, Wei, Zimmermann, Martina E., Zoledziewska, Magdalena, Adair, Linda S., Adams, Hieab H. H., Aguilar-Salinas, Carlos A., Al-Mulla, Fahd, Arnett, Donna K., Asselbergs, Folkert W., Åsvold, Bjørn Olav, Attia, John, Banas, Bernhard, Bandinelli, Stefania, Bennett, David A., Bergler, Tobias, Bharadwaj, Dwaipayan, Biino, Ginevra, Bisgaard, Hans, Boerwinkle, Eric, Böger, Carsten A., Bønnelykke, Klaus, Boomsma, Dorret I., Børglum, Anders D., Borja, Judith B., Bouchard, Claude, Bowden, Donald W., Brandslund, Ivan, Brumpton, Ben, Buring, Julie E., Caulfield, Mark J., Chambers, John C., Chandak, Giriraj R., Chanock, Stephen J., Chaturvedi, Nish, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Ching-Yu, Christophersen, Ingrid E., Ciullo, Marina, Cole, John W., Collins, Francis S., Cooper, Richard S., Cruz, Miguel, Cucca, Francesco, Cupples, L. Adrienne, Cutler, Michael J., Damrauer, Scott M., Dantoft, Thomas M., de Borst, Gert J., de Groot, Lisette C. P. G. M., De Jager, Philip L., de Kleijn, Dominique P. V., Janaka de Silva, H., Dedoussis, George V., den Hollander, Anneke I., Du, Shufa, Easton, Douglas F., Elders, Petra J. M., Eliassen, A. Heather, Ellinor, Patrick T., Elmståhl, Sölve, Erdmann, Jeanette, Evans, Michele K., Fatkin, Diane, Feenstra, Bjarke, Feitosa, Mary F., Ferrucci, Luigi, Ford, Ian, Fornage, Myriam, Franke, Andre, Franks, Paul W., Freedman, Barry I., Gasparini, Paolo, Gieger, Christian, Girotto, Giorgia, Goddard, Michael E., Golightly, Yvonne M., Gonzalez-Villalpando, Clicerio, Gordon-Larsen, Penny, Grallert, Harald, Grant, Struan F. A., Grarup, Niels, Griffiths, Lyn, Gudnason, Vilmundur, Haiman, Christopher, Hakonarson, Hakon, Hansen, Torben, Hartman, Catharina A., Hattersley, Andrew T., Hayward, Caroline, Heckbert, Susan R., Heng, Chew-Kiat, Hengstenberg, Christian, Hewitt, Alex W., Hishigaki, Haretsugu, Hoyng, Carel B., Huang, Paul L., Huang, Wei, Hunt, Steven C., Hveem, Kristian, Hyppönen, Elina, Iacono, William G., Ichihara, Sahoko, Ikram, M. Arfan, Isasi, Carmen R., Jackson, Rebecca D., Jarvelin, Marjo-Riitta, Jin, Zi-Bing, Jöckel, Karl-Heinz, Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Kähönen, Mika, Kamatani, Yoichiro, Kang, Kui Dong, Kaprio, Jaakko, Kardia, Sharon L. R., Karpe, Fredrik, Kato, Norihiro, Kee, Frank, Kessler, Thorsten, Khera, Amit V., Khor, Chiea Chuen, Kiemeney, Lambertus A. L. M., Kim, Bong-Jo, Kim, Eung Kweon, Kim, Hyung-Lae, Kirchhof, Paulus, Kivimaki, Mika, Koh, Woon-Puay, Koistinen, Heikki A., Kolovou, Genovefa D., Kooner, Jaspal S., Kooperberg, Charles, Köttgen, Anna, Kovacs, Peter, Kraaijeveld, Adriaan, Kraft, Peter, Krauss, Ronald M., Kumari, Meena, Kutalik, Zoltan, Laakso, Markku, Lange, Leslie A., Langenberg, Claudia, Launer, Lenore J., Le Marchand, Loic, Lee, Hyejin, Lee, Nanette R., Lehtimäki, Terho, Li, Huaixing, Li, Liming, Lieb, Wolfgang, Lin, Xu, Lind, Lars, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Loeffler, Markus, London, Barry, Lubitz, Steven A., Lye, Stephen J., Mackey, David A., Mägi, Reedik, Magnusson, Patrik K. E., Marcus, Gregory M., Vidal, Pedro Marques, Martin, Nicholas G., März, Winfried, Matsuda, Fumihiko, McGarrah, Robert W., McGue, Matt, McKnight, Amy Jayne, Medland, Sarah E., Mellström, Dan, Metspalu, Andres, Mitchell, Braxton D., Mitchell, Paul, Mook-Kanamori, Dennis O., Morris, Andrew D., Mucci, Lorelei A., Munroe, Patricia B., Nalls, Mike A., Nazarian, Saman, Nelson, Amanda E., Neville, Matt J., Newton-Cheh, Christopher, Nielsen, Christopher S., Nöthen, Markus M., Ohlsson, Claes, Oldehinkel, Albertine J., Orozco, Lorena, Pahkala, Katja, Pajukanta, Päivi, Palmer, Colin N. A., Parra, Esteban J., Pattaro, Cristian, Pedersen, Oluf, Pennell, Craig E., Penninx, Brenda W. J. H., Perusse, Louis, Peters, Annette, Peyser, Patricia A., Porteous, David J., Posthuma, Danielle, Power, Chris, Pramstaller, Peter P., Province, Michael A., Qi, Qibin, Qu, Jia, Rader, Daniel J., Raitakari, Olli T., Ralhan, Sarju, Rallidis, Loukianos S., Rao, Dabeeru C., Redline, Susan, Reilly, Dermot F., Reiner, Alexander P., Rhee, Sang Youl, Ridker, Paul M., Rienstra, Michiel, Ripatti, Samuli, Ritchie, Marylyn D., Roden, Dan M., Rosendaal, Frits R., Rotter, Jerome I., Rudan, Igor, Rutters, Femke, Sabanayagam, Charumathi, Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sanghera, Dharambir K., Sattar, Naveed, Schmidt, Börge, Schmidt, Helena, Schmidt, Reinhold, Schulze, Matthias B., Schunkert, Heribert, Scott, Laura J., Scott, Rodney J., Sever, Peter, Shiroma, Eric J., Shoemaker, M. Benjamin, Shu, Xiao-Ou, Simonsick, Eleanor M., Sims, Mario, Singh, Jai Rup, Singleton, Andrew B., Sinner, Moritz F., Smith, J. Gustav, Snieder, Harold, Spector, Tim D., Stampfer, Meir J., Stark, Klaus J., Strachan, David P., ‘t Hart, Leen M., Tabara, Yasuharu, Tang, Hua, Tardif, Jean-Claude, Thanaraj, Thangavel A., Timpson, Nicholas J., Tönjes, Anke, Tremblay, Angelo, Tuomi, Tiinamaija, Tuomilehto, Jaakko, Tusié-Luna, Maria-Teresa, Uitterlinden, Andre G., van Dam, Rob M., van der Harst, Pim, Van der Velde, Nathalie, van Duijn, Cornelia M., van Schoor, Natasja M., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Völzke, Henry, Wacher-Rodarte, Niels H., Walker, Mark, Wang, Ya Xing, Wareham, Nicholas J., Watanabe, Richard M., Watkins, Hugh, Weir, David R., Werge, Thomas M., Widen, Elisabeth, Wilkens, Lynne R., Willemsen, Gonneke, Willett, Walter C., Wilson, James F., Wong, Tien-Yin, Woo, Jeong-Taek, Wright, Alan F., Wu, Jer-Yuarn, Xu, Huichun, Yajnik, Chittaranjan S., Yokota, Mitsuhiro, Yuan, Jian-Min, Zeggini, Eleftheria, Zemel, Babette S., Zheng, Wei, Zhu, Xiaofeng, Zmuda, Joseph M., Zonderman, Alan B., Zwart, John-Anker, Chasman, Daniel I., Cho, Yoon Shin, Heid, Iris M., McCarthy, Mark I., Ng, Maggie C. Y., O’Donnell, Christopher J., Rivadeneira, Fernando, Thorsteinsdottir, Unnur, Sun, Yan V., Tai, E. Shyong, Boehnke, Michael, Deloukas, Panos, Justice, Anne E., Lindgren, Cecilia M., Loos, Ruth J. F., Mohlke, Karen L., North, Kari E., Stefansson, Kari, Walters, Robin G., Winkler, Thomas W., Young, Kristin L., Loh, Po-Ru, Yang, Jian, Esko, Tõnu, Assimes, Themistocles L., Auton, Adam, Abecasis, Goncalo R., Willer, Cristen J., Locke, Adam E., Berndt, Sonja I., Lettre, Guillaume, Frayling, Timothy M., Okada, Yukinori, Wood, Andrew R., Visscher, Peter M., and Hirschhorn, Joel N.

Published
2022
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15. The extracellular heparan sulfatase SULF2 limits myeloid IFNβ signaling and Th17 responses in inflammatory arthritis.

Author

Swart, Maarten, Redpath, Andia N., Ogbechi, Joy, Cardenas, Ryan, Topping, Louise, Compeer, Ewoud B., Goddard, Michael, Chanalaris, Anastasios, Williams, Richard, Brewer, Daniel S., Smart, Nicola, Monaco, Claudia, and Troeberg, Linda

Abstract

Heparan sulfate (HS) proteoglycans are important regulators of cellular responses to soluble mediators such as chemokines, cytokines and growth factors. We profiled changes in expression of genes encoding HS core proteins, biosynthesis enzymes and modifiers during macrophage polarisation, and found that the most highly regulated gene was Sulf2, an extracellular HS 6-O-sulfatase that was markedly downregulated in response to pro-inflammatory stimuli. We then generated Sulf2+/− bone marrow chimeric mice and examined inflammatory responses in antigen-induced arthritis, as a model of rheumatoid arthritis. Resolution of inflammation was impaired in myeloid Sulf2+/− chimeras, with elevated joint swelling and increased abundance of pro-arthritic Th17 cells in synovial tissue. Transcriptomic and in vitro analyses indicated that Sulf2 deficiency increased type I interferon signaling in bone marrow-derived macrophages, leading to elevated expression of the Th17-inducing cytokine IL6. This establishes that dynamic remodeling of HS by Sulf2 limits type I interferon signaling in macrophages, and so protects against Th17-driven pathology. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Allele-specific binding variants causing ChIP-seq peak height of histone modification are not enriched in expression QTL annotations.

Author

Ghoreishifar, Mohammad, Chamberlain, Amanda J., Xiang, Ruidong, Prowse-Wilkins, Claire P., Lopdell, Thomas J., Littlejohn, Mathew D., Pryce, Jennie E., and Goddard, Michael E.

Subjects
GENE expression, LOCUS (Genetics), LINKAGE disequilibrium, NUCLEOTIDE sequence, IMMUNOPRECIPITATION, SUPPORT vector machines
Abstract

Background: Genome sequence variants affecting complex traits (quantitative trait loci, QTL) are enriched in functional regions of the genome, such as those marked by certain histone modifications. These variants are believed to influence gene expression. However, due to the linkage disequilibrium among nearby variants, pinpointing the precise location of QTL is challenging. We aimed to identify allele-specific binding (ASB) QTL (asbQTL) that cause variation in the level of histone modification, as measured by the height of peaks assayed by ChIP-seq (chromatin immunoprecipitation sequencing). We identified DNA sequences that predict the difference between alleles in ChIP-seq peak height in H3K4me3 and H3K27ac histone modifications in the mammary glands of cows. Results: We used a gapped k-mer support vector machine, a novel best linear unbiased prediction model, and a multiple linear regression model that combines the other two approaches to predict variant impacts on peak height. For each method, a subset of 1000 sites with the highest magnitude of predicted ASB was considered as candidate asbQTL. The accuracy of this prediction was measured by the proportion where the predicted direction matched the observed direction. Prediction accuracy ranged between 0.59 and 0.74, suggesting that these 1000 sites are enriched for asbQTL. Using independent data, we investigated functional enrichment in the candidate asbQTL set and three control groups, including non-causal ASB sites, non-ASB variants under a peak, and SNPs (single nucleotide polymorphisms) not under a peak. For H3K4me3, a higher proportion of the candidate asbQTL were confirmed as ASB when compared to the non-causal ASB sites (P < 0.01). However, these candidate asbQTL did not enrich for the other annotations, including expression QTL (eQTL), allele-specific expression QTL (aseQTL) and sites conserved across mammals (P > 0.05). Conclusions: We identified putatively causal sites for asbQTL using the DNA sequence surrounding these sites. Our results suggest that many sites influencing histone modifications may not directly affect gene expression. However, it is important to acknowledge that distinguishing between putative causal ASB sites and other non-causal ASB sites in high linkage disequilibrium with the causal sites regarding their impact on gene expression may be challenging due to limitations in statistical power. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Genome-wide association and expression quantitative trait loci in cattle reveals common genes regulating mammalian fertility.

Author

Forutan, Mehrnush, Engle, Bailey N., Chamberlain, Amanda J., Ross, Elizabeth M., Nguyen, Loan T., D'Occhio, Michael J., Snr, Alf Collins, Kho, Elise A., Fordyce, Geoffry, Speight, Shannon, Goddard, Michael E., and Hayes, Ben J.

Subjects
LOCUS (Genetics), CATTLE crossbreeding, CATTLE fertility, HEIFERS, GENOME-wide association studies, MAMMAL fertility, FERTILITY, GENETIC variation
Abstract

Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals. The authors identify the genetic variants and genes associated with four fertility-related traits in a well-phenotyped cattle population. [ABSTRACT FROM AUTHOR]

Published
2024
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20. A common regulatory haplotype doubles lactoferrin concentration in milk.

Author

Lopdell, Thomas J., Trevarton, Alexander J., Moody, Janelle, Prowse-Wilkins, Claire, Knowles, Sarah, Tiplady, Kathryn, Chamberlain, Amanda J., Goddard, Michael E., Spelman, Richard J., Lehnert, Klaus, Snell, Russell G., Davis, Stephen R., and Littlejohn, Mathew D.

Subjects
LACTOFERRIN, HAPLOTYPES, LOCUS (Genetics), WHEY proteins, GENE mapping, MILK
Abstract

Background: Bovine lactoferrin (Lf) is an iron absorbing whey protein with antibacterial, antiviral, and antifungal activity. Lactoferrin is economically valuable and has an extremely variable concentration in milk, partly driven by environmental influences such as milking frequency, involution, or mastitis. A significant genetic influence has also been previously observed to regulate lactoferrin content in milk. Here, we conducted genetic mapping of lactoferrin protein concentration in conjunction with RNA-seq, ChIP-seq, and ATAC-seq data to pinpoint candidate causative variants that regulate lactoferrin concentrations in milk. Results: We identified a highly-significant lactoferrin protein quantitative trait locus (pQTL), as well as a cislactotransferrin (LTF) expression QTL (cis-eQTL) mapping to the LTF locus. Using ChIP-seq and ATAC-seq datasets representing lactating mammary tissue samples, we also report a number of regions where the openness of chromatin is under genetic influence. Several of these also show highly significant QTL with genetic signatures similar to those highlighted through pQTL and eQTL analysis. By performing correlation analysis between these QTL, we revealed an ATAC-seq peak in the putative promotor region of LTF, that highlights a set of 115 high-frequency variants that are potentially responsible for these effects. One of the 115 variants (rs110000337), which maps within the ATAC-seq peak, was predicted to alter binding sites of transcription factors known to be involved in lactation-related pathways. Conclusions: Here, we report a regulatory haplotype of 115 variants with conspicuously large impacts on milk lactoferrin concentration. These findings could enable the selection of animals for high-producing specialist herds. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Phantom epistasis between unlinked loci

Author

Hemani, Gibran, Powell, Joseph E., Wang, Huanwei, Shakhbazov, Konstantin, Westra, Harm-Jan, Esko, Tonu, Henders, Anjali K., McRae, Allan F., Martin, Nicholas G., Metspalu, Andres, Franke, Lude, Montgomery, Grant W., Goddard, Michael E., Gibson, Greg, Yang, Jian, and Visscher, Peter M.

Published
2021
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29. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Author

O'Dushlaine, Colm, Rossin, Lizzy, Lee, Phil H, Duncan, Laramie, Parikshak, Neelroop N, Newhouse, Stephen, Ripke, Stephan, Neale, Benjamin M, Purcell, Shaun M, Posthuma, Danielle, Nurnberger, John I, Lee, S Hong, Faraone, Stephen V, Perlis, Roy H, Mowry, Bryan J, Thapar, Anita, Goddard, Michael E, Witte, John S, Absher, Devin, Agartz, Ingrid, Akil, Huda, Amin, Farooq, Andreassen, Ole A, Anjorin, Adebayo, Anney, Richard, Anttila, Verneri, Arking, Dan E, Asherson, Philip, Azevedo, Maria H, Backlund, Lena, Badner, Judith A, Bailey, Anthony J, Banaschewski, Tobias, Barchas, Jack D, Barnes, Michael R, Barrett, Thomas B, Bass, Nicholas, Battaglia, Agatino, Bauer, Michael, Bayes, Monica, Bellivier, Frank, Bergen, Sarah E, Berrettini, Wade, Betancur, Catalina, Bettecken, Thomas, Biederman, Joseph, Binder, Elisabeth B, Black, Donald W, Blackwood, Douglas HR, Bloss, Cinnamon S, Boehnke, Michael, Boomsma, Dorret I, Breuer, Rene, Bruggeman, Richard, Cormican, Paul, Buccola, Nancy G, Buitelaar, Jan K, Bunney, William E, Buxbaum, Joseph D, Byerley, William F, Byrne, Enda M, Caesar, Sian, Cahn, Wiepke, Cantor, Rita M, Casas, Miguel, Chakravarti, Aravinda, Chambert, Kimberly, Choudhury, Khalid, Cichon, Sven, Mattheisen, Manuel, Cloninger, C Robert, Collier, David A, Cook, Edwin H, Coon, Hilary, Cormand, Bru, Corvin, Aiden, Coryell, William H, Craig, David W, Craig, Ian W, Crosbie, Jennifer, Cuccaro, Michael L, Curtis, David, Czamara, Darina, Datta, Susmita, Dawson, Geraldine, Day, Richard, De Geus, Eco J, Degenhardt, Franziska, Djurovic, Srdjan, Donohoe, Gary J, Doyle, Alysa E, Duan, Jubao, Dudbridge, Frank, Duketis, Eftichia, Ebstein, Richard P, Edenberg, Howard J, Elia, Josephine, Ennis, Sean, Etain, Bruno, and Fanous, Ayman

Subjects
Human Genome, Brain Disorders, Serious Mental Illness, Schizophrenia, Genetics, Depression, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Brain, Databases, Genetic, Genetic Predisposition to Disease, Genome-Wide Association Study, Histones, Humans, Mental Disorders, Signal Transduction, Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, Neurosciences, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Published
2015

37. Use of dry-matter intake recorded at multiple time periods during lactation increases the accuracy of genomic prediction for dry-matter intake and residual feed intake in dairy cattle.

Author

Bolormaa, Sunduimijid, Haile-Mariam, Mekonnen, Marett, Leah C., Miglior, Filippo, Baes, Christine F., Schenkel, Flavio S., Connor, Erin E., Manzanilla-Pech, Coralia I. V., Wall, Eileen, Coffey, Mike P., Goddard, Michael E., MacLeod, Iona M., and Pryce, Jennie E.

Abstract

Context: Feed is the largest expense on a dairy farm, therefore improving feed efficiency is important. Recording dry-matter intake (DMI) is a prerequisite for calculating feed efficiency. Genetic variation of feed intake and feed efficiency varies across lactation stages and parities. DMI is an expensive and difficult-to-measure trait. This raises the question of which time periods during lactation would be most appropriate to measure DMI. Aims: The aim was to evaluate whether sequence variants selected from genome-wide association studies (GWAS) for DMI recorded at multiple lactation time periods and parities would increase the accuracy of genomic estimated breeding values (GEBVs) for DMI and residual feed intake (RFI). Methods: Data of 2274 overseas lactating cows were used for the GWAS to select sequence variants. GWAS was performed using the average of the DMI phenotypes in a 30-day window of six different time periods across the lactation. The most significant sequence variants were selected from the GWAS at each time period for either first or later parities. GEBVs for DMI and RFI in Australian lactating cows were estimated using BayesRC with 50 k single nucleotide polymorphisms (SNPs) and selected GWAS sequence variants. Key results: There were differences in DMI genomic correlations and heritabilities between first and later parities and within parity across lactation time periods. Compared with using 50 k single-nucleotide polymorphisms (SNPs) only, the accuracy of DMI GEBVs increased by up to 11% by using the 50 k SNPs plus the selected sequence variants. Compared with DMI, the increase in accuracy for RFI was lower (by 6%) likely because the sequence variants were selected from GWAS for DMI not RFI. The accuracies for DMI and RFI GEBVs were highest by using selected sequence variants from the DMI GWAS in the mid- to late-lactation periods in later parity. Conclusions: Our results showed that DMI phenotypes in late lactation time periods could capture more genetic variation and increase genomic prediction accuracy through the use of custom genotype panels in genomic selection. Implications: Collecting DMI at the optimal time period(s) of lactation may help develop more accurate and cost-effective breeding values for feed efficiency in dairy cattle. Genetic improvement of feed efficiency to produce milk in dairy cattle would provide considerable economic benefits but measuring feed intake is difficult and expensive. Therefore, we used existing data to determine the best period of lactation to measure feed intake and then used advanced genomics to improve the accuracy of genomic breeding values for feed intake and efficiency. The results are an important step towards a more accurate and cost-effective approach to genetically improve dairy cow feed efficiency. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Application of Genetics and Genomics in Livestock Production.

Author

Burrow, Heather and Goddard, Michael

Subjects
LIVESTOCK productivity, GENETICS, GENOTYPE-environment interaction, CATTLE genetics, CALVES, CATTLE breeds, GENOMICS, RANGELANDS
Abstract

The delivery of genomic sequences for most livestock species over the past 10-15 years has generated the potential to revolutionize livestock production globally, by providing farmers with the ability to match individual animals to the requirements of rapidly changing climates, production systems and markets. Review Process All articles published in this Special Issue "Application of Genetics and Genomics in Livestock Production" underwent peer review by independent subject matter experts in the fields of livestock genetics and genomics. Application of Genetics and Genomics to Livestock Production: Summary of Articles 3.1. [Extracted from the article]

Published
2023
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47. Identification of Genomic Variants Causing Variation in Quantitative Traits: A Review.

Author

Meuwissen, Theo, Hayes, Ben, MacLeod, Iona, and Goddard, Michael

Subjects
LINKAGE disequilibrium, NUCLEOTIDE sequence, LOCUS (Genetics), GENOME editing, DNA sequencing
Abstract

Many of the important traits of livestock are complex or quantitative traits controlled by thousands of variants in the DNA sequence of individual animals and environmental factors. Identification of these causal variants would be advantageous for genomic prediction, to understand the physiology and evolution of important traits and for genome editing. However, it is difficult to identify these causal variants because their effects are small and they are in linkage disequilibrium with other DNA variants. Nevertheless, it should be possible to identify probable causal variants for complex traits just as we do for simple traits provided we compensate for the small effect size with larger sample size. In this review we consider eight types of evidence needed to identify causal variants. Large and diverse samples of animals, accurate genotypes, multiple phenotypes, annotation of genomic sites, comparisons across species, comparisons across the genome, the physiological role of candidate genes and experimental mutation of the candidate genomic site. [ABSTRACT FROM AUTHOR]

Published
2022
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49. Genetic studies of body mass index yield new insights for obesity biology

Author

Locke, Adam E., Kahali, Bratati, Berndt, Sonja I., Justice, Anne E., Pers, Tune H., Day, Felix R., Powell, Corey, Vedantam, Sailaja, Buchkovich, Martin L., Yang, Jian, Croteau-Chonka, Damien C., Esko, Tonu, Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Kutalik, Zoltán, Luan, Jianʼan, Mägi, Reedik, Randall, Joshua C., Winkler, Thomas W., Wood, Andrew R., Workalemahu, Tsegaselassie, Faul, Jessica D., Smith, Jennifer A., Hua Zhao, Jing, Zhao, Wei, Chen, Jin, Fehrmann, Rudolf, Hedman, Åsa K., Karjalainen, Juha, Schmidt, Ellen M., Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bolton, Jennifer L., Bragg-Gresham, Jennifer L., Buyske, Steven, Demirkan, Ayse, Deng, Guohong, Ehret, Georg B., Feenstra, Bjarke, Feitosa, Mary F., Fischer, Krista, Goel, Anuj, Gong, Jian, Jackson, Anne U., Kanoni, Stavroula, Kleber, Marcus E., Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Medland, Sarah E., Nalls, Michael A., Palmer, Cameron D., Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J., Prokopenko, Inga, Shungin, Dmitry, Stančáková, Alena, Strawbridge, Rona J., Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W., van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V., Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Isaacs, Aaron, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M., Attwood, Antony P., Bandinelli, Stefania, Barrett, Amy, Bas, Isabelita N., Bellis, Claire, Bennett, Amanda J., Berne, Christian, Blagieva, Roza, Blüher, Matthias, Böhringer, Stefan, Bonnycastle, Lori L., Böttcher, Yvonne, Boyd, Heather A., Bruinenberg, Marcel, Caspersen, Ida H., Ida Chen, Yii-Der, Clarke, Robert, Warwick Daw, E., de Craen, Anton J. M., Delgado, Graciela, Dimitriou, Maria, Doney, Alex S. F., Eklund, Niina, Estrada, Karol, Eury, Elodie, Folkersen, Lasse, Fraser, Ross M., Garcia, Melissa E., Geller, Frank, Giedraitis, Vilmantas, Gigante, Bruna, Go, Alan S., Golay, Alain, Goodall, Alison H., Gordon, Scott D., Gorski, Mathias, Grabe, Hans-Jörgen, Grallert, Harald, Grammer, Tanja B., Gräler, Jürgen, Grönberg, Henrik, Groves, Christopher J., Gusto, Gaëlle, Haessler, Jeffrey, Hall, Per, Haller, Toomas, Hallmans, Goran, Hartman, Catharina A., Hassinen, Maija, Hayward, Caroline, Heard-Costa, Nancy L., Helmer, Quinta, Hengstenberg, Christian, Holmen, Oddgeir, Hottenga, Jouke-Jan, James, Alan L., Jeff, Janina M., Johansson, Åsa, Jolley, Jennifer, Juliusdottir, Thorhildur, Kinnunen, Leena, Koenig, Wolfgang, Koskenvuo, Markku, Kratzer, Wolfgang, Laitinen, Jaana, Lamina, Claudia, Leander, Karin, Lee, Nanette R., Lichtner, Peter, Lind, Lars, Lindström, Jaana, Sin Lo, Ken, Lobbens, Stéphane, Lorbeer, Roberto, Lu, Yingchang, Mach, François, Magnusson, Patrik K. E., Mahajan, Anubha, McArdle, Wendy L., McLachlan, Stela, Menni, Cristina, Merger, Sigrun, Mihailov, Evelin, Milani, Lili, Moayyeri, Alireza, Monda, Keri L., Morken, Mario A., Mulas, Antonella, Müller, Gabriele, Müller-Nurasyid, Martina, Musk, Arthur W., Nagaraja, Ramaiah, Nöthen, Markus M., Nolte, Ilja M., Pilz, Stefan, Rayner, Nigel W., Renstrom, Frida, Rettig, Rainer, Ried, Janina S., Ripke, Stephan, Robertson, Neil R., Rose, Lynda M., Sanna, Serena, Scharnagl, Hubert, Scholtens, Salome, Schumacher, Fredrick R., Scott, William R., Seufferlein, Thomas, Shi, Jianxin, Vernon Smith, Albert, Smolonska, Joanna, Stanton, Alice V., Steinthorsdottir, Valgerdur, Stirrups, Kathleen, Stringham, Heather M., Sundström, Johan, Swertz, Morris A., Swift, Amy J., Syvänen, Ann-Christine, Tan, Sian-Tsung, Tayo, Bamidele O., Thorand, Barbara, Thorleifsson, Gudmar, Tyrer, Jonathan P., Uh, Hae-Won, Vandenput, Liesbeth, Verhulst, Frank C., Vermeulen, Sita H., Verweij, Niek, Vonk, Judith M., Waite, Lindsay L., Warren, Helen R., Waterworth, Dawn, Weedon, Michael N., Wilkens, Lynne R., Willenborg, Christina, Wilsgaard, Tom, Wojczynski, Mary K., Wong, Andrew, Wright, Alan F., Zhang, Qunyuan, Brennan, Eoin P., Choi, Murim, Dastani, Zari, Drong, Alexander W., Eriksson, Per, Franco-Cereceda, Anders, Gådin, Jesper R., Gharavi, Ali G., Goddard, Michael E., Handsaker, Robert E., Huang, Jinyan, Karpe, Fredrik, Kathiresan, Sekar, Keildson, Sarah, Kiryluk, Krzysztof, Kubo, Michiaki, Lee, Jong-Young, Liang, Liming, Lifton, Richard P., Ma, Baoshan, McCarroll, Steven A., McKnight, Amy J., Min, Josine L., Moffatt, Miriam F., Montgomery, Grant W., Murabito, Joanne M., Nicholson, George, Nyholt, Dale R., Okada, Yukinori, Perry, John R. B., Dorajoo, Rajkumar, Reinmaa, Eva, Salem, Rany M., Sandholm, Niina, Scott, Robert A., Stolk, Lisette, Takahashi, Atsushi, Tanaka, Toshihiro, vanʼt Hooft, Ferdinand M., Vinkhuyzen, Anna A. E., Westra, Harm-Jan, Zheng, Wei, Zondervan, Krina T., Heath, Andrew C., Arveiler, Dominique, Bakker, Stephan J. L., Beilby, John, Bergman, Richard N., Blangero, John, Bovet, Pascal, Campbell, Harry, Caulfield, Mark J., Cesana, Giancarlo, Chakravarti, Aravinda, Chasman, Daniel I., Chines, Peter S., Collins, Francis S., Crawford, Dana C., Adrienne Cupples, L., Cusi, Daniele, Danesh, John, de Faire, Ulf, den Ruijter, Hester M., Dominiczak, Anna F., Erbel, Raimund, Erdmann, Jeanette, Eriksson, Johan G., Farrall, Martin, Felix, Stephan B., Ferrannini, Ele, Ferrières, Jean, Ford, Ian, Forouhi, Nita G., Forrester, Terrence, Franco, Oscar H., Gansevoort, Ron T., Gejman, Pablo V., Gieger, Christian, Gottesman, Omri, Gudnason, Vilmundur, Gyllensten, Ulf, Hall, Alistair S., Harris, Tamara B., Hattersley, Andrew T., Hicks, Andrew A., Hindorff, Lucia A., Hingorani, Aroon D., Hofman, Albert, Homuth, Georg, Kees Hovingh, G., Humphries, Steve E., Hunt, Steven C., Hyppönen, Elina, Illig, Thomas, Jacobs, Kevin B., Jarvelin, Marjo-Riitta, Jöckel, Karl-Heinz, Johansen, Berit, Jousilahti, Pekka, Wouter Jukema, J., Jula, Antti M., Kaprio, Jaakko, Kastelein, John J. P., Keinanen-Kiukaanniemi, Sirkka M., Kiemeney, Lambertus A., Knekt, Paul, Kooner, Jaspal S., Kooperberg, Charles, Kovacs, Peter, Kraja, Aldi T., Kumari, Meena, Kuusisto, Johanna, Lakka, Timo A., Langenberg, Claudia, Le Marchand, Loic, Lehtimäki, Terho, Lyssenko, Valeriya, Männistö, Satu, Marette, André, Matise, Tara C., McKenzie, Colin A., McKnight, Barbara, Moll, Frans L., Morris, Andrew D., Morris, Andrew P., Murray, Jeffrey C., Nelis, Mari, Ohlsson, Claes, Oldehinkel, Albertine J., Ong, Ken K., Madden, Pamela A. F., Pasterkamp, Gerard, Peden, John F., Peters, Annette, Postma, Dirkje S., Pramstaller, Peter P., Price, Jackie F., Qi, Lu, Raitakari, Olli T., Rankinen, Tuomo, Rao, D. C., Rice, Treva K., Ridker, Paul M., Rioux, John D., Ritchie, Marylyn D., Rudan, Igor, Salomaa, Veikko, Samani, Nilesh J., Saramies, Jouko, Sarzynski, Mark A., Schunkert, Heribert, Schwarz, Peter E. H., Sever, Peter, Shuldiner, Alan R., Sinisalo, Juha, Stolk, Ronald P., Strauch, Konstantin, Tönjes, Anke, Trégouët, David-Alexandre, Tremblay, Angelo, Tremoli, Elena, Virtamo, Jarmo, Vohl, Marie-Claude, Völker, Uwe, Waeber, Gérard, Willemsen, Gonneke, Witteman, Jacqueline C., Carola Zillikens, M., Adair, Linda S., Amouyel, Philippe, Asselbergs, Folkert W., Assimes, Themistocles L., Bochud, Murielle, Boehm, Bernhard O., Boerwinkle, Eric, Bornstein, Stefan R., Bottinger, Erwin P., Bouchard, Claude, Cauchi, Stéphane, Chambers, John C., Chanock, Stephen J., Cooper, Richard S., de Bakker, Paul I. W., Dedoussis, George, Ferrucci, Luigi, Franks, Paul W., Froguel, Philippe, Groop, Leif C., Haiman, Christopher A., Hamsten, Anders, Hui, Jennie, Hunter, David J., Hveem, Kristian, Kaplan, Robert C., Kivimaki, Mika, Kuh, Diana, Laakso, Markku, Liu, Yongmei, Martin, Nicholas G., März, Winfried, Melbye, Mads, Metspalu, Andres, Moebus, Susanne, Munroe, Patricia B., Njølstad, Inger, Oostra, Ben A., Palmer, Colin N. A., Pedersen, Nancy L., Perola, Markus, Pérusse, Louis, Peters, Ulrike, Power, Chris, Quertermous, Thomas, Rauramaa, Rainer, Rivadeneira, Fernando, Saaristo, Timo E., Saleheen, Danish, Sattar, Naveed, Schadt, Eric E., Schlessinger, David, Eline Slagboom, P., Snieder, Harold, Spector, Tim D., Thorsteinsdottir, Unnur, Stumvoll, Michael, Tuomilehto, Jaakko, Uitterlinden, André G., Uusitupa, Matti, van der Harst, Pim, Walker, Mark, Wallaschofski, Henri, Wareham, Nicholas J., Watkins, Hugh, Weir, David R., Wichmann, H-Erich, Wilson, James F., Zanen, Pieter, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Heid, Iris M., OʼConnell, Jeffrey R., Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Abecasis, Gonçalo R., Franke, Lude, Frayling, Timothy M., McCarthy, Mark I., Visscher, Peter M., Scherag, André, Willer, Cristen J., Boehnke, Michael, Mohlke, Karen L., Lindgren, Cecilia M., Beckmann, Jacques S., Barroso, Inês, North, Kari E., Ingelsson, Erik, Hirschhorn, Joel N., Loos, Ruth J. F., and Speliotes, Elizabeth K.

Published
2015
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50. Interferon regulatory factor-5-dependent CD11c+ macrophages contribute to the formation of rupture–prone atherosclerotic plaques.

Author

Edsfeldt, Andreas, Swart, Maarten, Singh, Pratibha, Dib, Lea, Sun, Jiangming, Cole, Jennifer E., Park, Inhye, Al-Sharify, Dania, Persson, Ana, Nitulescu, Mihaela, Borges, Patricia Das Neves, Kassiteridi, Christina, Goddard, Michael E., Lee, Regent, Volkov, Petr, Orho-Melander, Marju, Maegdefessel, Lars, Nilsson, Jan, Udalova, Irina, and Goncalves, Isabel

Subjects
ATHEROSCLEROTIC plaque, INTERFERONS, INTERFERON regulatory factors, MACROPHAGES, TRANSCRIPTION factors
Abstract

Aims Inflammation is a key factor in atherosclerosis. The transcription factor interferon regulatory factor-5 (IRF5) drives macrophages towards a pro-inflammatory state. We investigated the role of IRF5 in human atherosclerosis and plaque stability. Methods and results Bulk RNA sequencing from the Carotid Plaque Imaging Project biobank were used to mine associations between major macrophage associated genes and transcription factors and human symptomatic carotid disease. Immunohistochemistry, proximity extension assays, and Helios cytometry by time of flight (CyTOF) were used for validation. The effect of IRF5 deficiency on carotid plaque phenotype and rupture in ApoE−/− mice was studied in an inducible model of plaque rupture. Interferon regulatory factor-5 and ITGAX/CD11c were identified as the macrophage associated genes with the strongest associations with symptomatic carotid disease. Expression of IRF5 and ITGAX/CD11c correlated with the vulnerability index, pro-inflammatory plaque cytokine levels, necrotic core area, and with each other. Macrophages were the predominant CD11c-expressing immune cells in the plaque by CyTOF and immunohistochemistry. Interferon regulatory factor-5 immunopositive areas were predominantly found within CD11c+ areas with a predilection for the shoulder region, the area of the human plaque most prone to rupture. Accordingly, an inducible plaque rupture model of ApoE−/−Irf5−/− mice had significantly lower frequencies of carotid plaque ruptures, smaller necrotic cores, and less CD11c+ macrophages than their IRF5-competent counterparts. Conclusion Using complementary evidence from data from human carotid endarterectomies and a murine model of inducible rupture of carotid artery plaque in IRF5-deficient mice, we demonstrate a mechanistic link between the pro-inflammatory transcription factor IRF5, macrophage phenotype, plaque inflammation, and its vulnerability to rupture. [ABSTRACT FROM AUTHOR]

Published
2022
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