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1. Genome-wide association analyses identify distinct genetic architectures for age-related macular degeneration across ancestries

Author

Gorman, Bryan R., Voloudakis, Georgios, Igo, Jr., Robert P., Kinzy, Tyler, Halladay, Christopher W., Bigdeli, Tim B., Zeng, Biao, Venkatesh, Sanan, Cooke Bailey, Jessica N., Crawford, Dana C., Markianos, Kyriacos, Dong, Frederick, Schreiner, Patrick A., Zhang, Wen, Hadi, Tamer, Anger, Matthew D., Stockwell, Amy, Melles, Ronald B., Yin, Jie, Choquet, Hélène, Kaye, Rebecca, Patasova, Karina, Patel, Praveen J., Yaspan, Brian L., Jorgenson, Eric, Hysi, Pirro G., Lotery, Andrew J., Gaziano, J. Michael, Tsao, Philip S., Fliesler, Steven J., Sullivan, Jack M., Greenberg, Paul B., Wu, Wen-Chih, Assimes, Themistocles L., Pyarajan, Saiju, Roussos, Panos, Peachey, Neal S., and Iyengar, Sudha K.

Published
2024
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2. A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation

Author

Gorman, Bryan R., Francis, Michael, Nealon, Cari L., Halladay, Christopher W., Duro, Nalvi, Markianos, Kyriacos, Genovese, Giulio, Hysi, Pirro G., Choquet, Hélène, Afshari, Natalie A., Li, Yi-Ju, Gaziano, J. Michael, Hung, Adriana M., Wu, Wen-Chih, Greenberg, Paul B., Pyarajan, Saiju, Lass, Jonathan H., Peachey, Neal S., and Iyengar, Sudha K.

Published
2024
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4. Genetic diversity fuels gene discovery for tobacco and alcohol use

Author

Saunders, Gretchen RB, Wang, Xingyan, Chen, Fang, Jang, Seon-Kyeong, Liu, Mengzhen, Wang, Chen, Gao, Shuang, Jiang, Yu, Khunsriraksakul, Chachrit, Otto, Jacqueline M, Addison, Clifton, Akiyama, Masato, Albert, Christine M, Aliev, Fazil, Alonso, Alvaro, Arnett, Donna K, Ashley-Koch, Allison E, Ashrani, Aneel A, Barnes, Kathleen C, Barr, R Graham, Bartz, Traci M, Becker, Diane M, Bielak, Lawrence F, Benjamin, Emelia J, Bis, Joshua C, Bjornsdottir, Gyda, Blangero, John, Bleecker, Eugene R, Boardman, Jason D, Boerwinkle, Eric, Boomsma, Dorret I, Boorgula, Meher Preethi, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Chasman, Daniel I, Chavan, Sameer, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Iona, Cho, Michael H, Choquet, Hélène, Cole, John W, Cornelis, Marilyn C, Cucca, Francesco, Curran, Joanne E, de Andrade, Mariza, Dick, Danielle M, Docherty, Anna R, Duggirala, Ravindranath, Eaton, Charles B, Ehringer, Marissa A, Esko, Tõnu, Faul, Jessica D, Fernandes Silva, Lilian, Fiorillo, Edoardo, Fornage, Myriam, Freedman, Barry I, Gabrielsen, Maiken E, Garrett, Melanie E, Gharib, Sina A, Gieger, Christian, Gillespie, Nathan, Glahn, David C, Gordon, Scott D, Gu, Charles C, Gu, Dongfeng, Gudbjartsson, Daniel F, Guo, Xiuqing, Haessler, Jeffrey, Hall, Michael E, Haller, Toomas, Harris, Kathleen Mullan, He, Jiang, Herd, Pamela, Hewitt, John K, Hickie, Ian, Hidalgo, Bertha, Hokanson, John E, Hopfer, Christian, Hottenga, JoukeJan, Hou, Lifang, Huang, Hongyan, Hung, Yi-Jen, Hunter, David J, Hveem, Kristian, Hwang, Shih-Jen, Hwu, Chii-Min, Iacono, William, Irvin, Marguerite R, Jee, Yon Ho, Johnson, Eric O, Joo, Yoonjung Y, Jorgenson, Eric, Justice, Anne E, Kamatani, Yoichiro, Kaplan, Robert C, Kaprio, Jaakko, Kardia, Sharon LR, and Keller, Matthew C

Subjects
Genetics, Alcoholism, Alcohol Use and Health, Prevention, Human Genome, Substance Misuse, Aetiology, 2.1 Biological and endogenous factors, Cancer, Good Health and Well Being, Humans, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Multifactorial Inheritance, Risk Factors, Tobacco Use, Alcohol Drinking, Transcriptome, Sample Size, Genetic Loci, Internationality, Europe, 23andMe Research Team, Biobank Japan Project, General Science & Technology
Abstract

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Published
2022

7. Large-scale multitrait genome-wide association analyses identify hundreds of glaucoma risk loci

Author

Han, Xikun, Gharahkhani, Puya, Hamel, Andrew R., Ong, Jue Sheng, Rentería, Miguel E., Mehta, Puja, Dong, Xianjun, Pasutto, Francesca, Hammond, Christopher, Young, Terri L., Hysi, Pirro, Lotery, Andrew J., Jorgenson, Eric, Choquet, Hélène, Hauser, Michael, Cooke Bailey, Jessica N., Nakazawa, Toru, Akiyama, Masato, Shiga, Yukihiro, Fuller, Zachary L., Wang, Xin, Hewitt, Alex W., Craig, Jamie E., Pasquale, Louis R., Mackey, David A., Wiggs, Janey L., Khawaja, Anthony P., Segrè, Ayellet V., and MacGregor, Stuart

Published
2023
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8. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Author

Little, Amarise, Hu, Yao, Sun, Quan, Jain, Deepti, Broome, Jai, Chen, Ming-Huei, Thibord, Florian, McHugh, Caitlin, Surendran, Praveen, Blackwell, Thomas W, Brody, Jennifer A, Bhan, Arunoday, Chami, Nathalie, de Vries, Paul S, Ekunwe, Lynette, Heard-Costa, Nancy, Hobbs, Brian D, Manichaikul, Ani, Moon, Jee-Young, Preuss, Michael H, Ryan, Kathleen, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Abecasis, Goncalo R, Almasy, Laura, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Choquet, Hélène, Correa, Adolfo, Curran, Joanne E, Faraday, Nauder, Fornage, Myriam, Glahn, David C, Hou, Lifang, Jorgenson, Eric, Kooperberg, Charles, Lewis, Joshua P, Lloyd-Jones, Donald M, Loos, Ruth JF, Min, Yuan-I, Mitchell, Braxton D, Morrison, Alanna C, Nickerson, Deborah A, North, Kari E, O'Connell, Jeffrey R, Pankratz, Nathan, Psaty, Bruce M, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Smith, Albert V, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Conomos, Matthew P, Laurie, Cecelia A, Mathias, Rasika A, Li, Yun, Auer, Paul L, Consortium, NHLBI Trans-Omics for Precision Medicine, Thornton, Timothy, Reiner, Alexander P, Johnson, Andrew D, and Raffield, Laura M

Subjects
Biological Sciences, Genetics, Hematology, Biotechnology, Clinical Research, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Platelets, Genome-Wide Association Study, Humans, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Precision Medicine, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Published
2022

10. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program

Author

Mikhaylova, Anna V, McHugh, Caitlin P, Polfus, Linda M, Raffield, Laura M, Boorgula, Meher Preethi, Blackwell, Thomas W, Brody, Jennifer A, Broome, Jai, Chami, Nathalie, Chen, Ming-Huei, Conomos, Matthew P, Cox, Corey, Curran, Joanne E, Daya, Michelle, Ekunwe, Lynette, Glahn, David C, Heard-Costa, Nancy, Highland, Heather M, Hobbs, Brian D, Ilboudo, Yann, Jain, Deepti, Lange, Leslie A, Miller-Fleming, Tyne W, Min, Nancy, Moon, Jee-Young, Preuss, Michael H, Rosen, Jonathon, Ryan, Kathleen, Smith, Albert V, Sun, Quan, Surendran, Praveen, de Vries, Paul S, Walter, Klaudia, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Zhong, Xue, Abecasis, Goncalo R, Almasy, Laura, Barnes, Kathleen C, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Chavan, Sameer, Cho, Michael H, Choquet, Hélène, Correa, Adolfo, Cox, Nancy, DeMeo, Dawn L, Faraday, Nauder, Fornage, Myriam, Gerszten, Robert E, Hou, Lifang, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kooperberg, Charles, Kundu, Kousik, Laurie, Cecelia A, Lettre, Guillaume, Lewis, Joshua P, Li, Bingshan, Li, Yun, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani, Meyers, Deborah A, Mitchell, Braxton D, Morrison, Alanna C, Ngo, Debby, Nickerson, Deborah A, Nongmaithem, Suraj, North, Kari E, O’Connell, Jeffrey R, Ortega, Victor E, Pankratz, Nathan, Perry, James A, Psaty, Bruce M, Rich, Stephen S, Soranzo, Nicole, Rotter, Jerome I, Silverman, Edwin K, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Thornton, Timothy A, Vasan, Ramachandran S, Zein, Joe, Mathias, Rasika A, Consortium, NHLBI Trans-Omics for Precision Medicine, Reiner, Alexander P, and Auer, Paul L

Subjects
Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, blood-cell counts, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Published
2021

12. European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation

Author

Budu-Aggrey, Ashley, Kilanowski, Anna, Sobczyk, Maria K., Shringarpure, Suyash S., Mitchell, Ruth, Reis, Kadri, Reigo, Anu, Mägi, Reedik, Nelis, Mari, Tanaka, Nao, Brumpton, Ben M., Thomas, Laurent F., Sole-Navais, Pol, Flatley, Christopher, Espuela-Ortiz, Antonio, Herrera-Luis, Esther, Lominchar, Jesus V. T., Bork-Jensen, Jette, Marenholz, Ingo, Arnau-Soler, Aleix, Jeong, Ayoung, Fawcett, Katherine A., Baurecht, Hansjorg, Rodriguez, Elke, Alves, Alexessander Couto, Kumar, Ashish, Sleiman, Patrick M., Chang, Xiao, Medina-Gomez, Carolina, Hu, Chen, Xu, Cheng-jian, Qi, Cancan, El-Heis, Sarah, Titcombe, Philip, Antoun, Elie, Fadista, João, Wang, Carol A., Thiering, Elisabeth, Wu, Baojun, Kress, Sara, Kothalawala, Dilini M., Kadalayil, Latha, Duan, Jiasong, Zhang, Hongmei, Hadebe, Sabelo, Hoffmann, Thomas, Jorgenson, Eric, Choquet, Hélène, Risch, Neil, Njølstad, Pål, Andreassen, Ole A., Johansson, Stefan, Almqvist, Catarina, Gong, Tong, Ullemar, Vilhelmina, Karlsson, Robert, Magnusson, Patrik K. E., Szwajda, Agnieszka, Burchard, Esteban G., Thyssen, Jacob P., Hansen, Torben, Kårhus, Line L., Dantoft, Thomas M., Jeanrenaud, Alexander C.S.N., Ghauri, Ahla, Arnold, Andreas, Homuth, Georg, Lau, Susanne, Nöthen, Markus M., Hübner, Norbert, Imboden, Medea, Visconti, Alessia, Falchi, Mario, Bataille, Veronique, Hysi, Pirro, Ballardini, Natalia, Boomsma, Dorret I., Hottenga, Jouke J., Müller-Nurasyid, Martina, Ahluwalia, Tarunveer S., Stokholm, Jakob, Chawes, Bo, Schoos, Ann-Marie M., Esplugues, Ana, Bustamante, Mariona, Raby, Benjamin, Arshad, Syed, German, Chris, Esko, Tõnu, Milani, Lili A., Metspalu, Andres, Terao, Chikashi, Abuabara, Katrina, Løset, Mari, Hveem, Kristian, Jacobsson, Bo, Pino-Yanes, Maria, Strachan, David P., Grarup, Niels, Linneberg, Allan, Lee, Young-Ae, Probst-Hensch, Nicole, Weidinger, Stephan, Jarvelin, Marjo-Riitta, Melén, Erik, Hakonarson, Hakon, Irvine, Alan D., Jarvis, Deborah, Nijsten, Tamar, Duijts, Liesbeth, Vonk, Judith M., Koppelmann, Gerard H., Godfrey, Keith M., Barton, Sheila J., Feenstra, Bjarke, Pennell, Craig E., Sly, Peter D., Holt, Patrick G., Williams, L. Keoki, Bisgaard, Hans, Bønnelykke, Klaus, Curtin, John, Simpson, Angela, Murray, Clare, Schikowski, Tamara, Bunyavanich, Supinda, Weiss, Scott T., Holloway, John W., Min, Josine L., Brown, Sara J., Standl, Marie, and Paternoster, Lavinia

Published
2023
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13. Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Author

Hu, Yao, Stilp, Adrienne M, McHugh, Caitlin P, Rao, Shuquan, Jain, Deepti, Zheng, Xiuwen, Lane, John, de Bellefon, Sébastian Méric, Raffield, Laura M, Chen, Ming-Huei, Yanek, Lisa R, Wheeler, Marsha, Yao, Yao, Ren, Chunyan, Broome, Jai, Moon, Jee-Young, de Vries, Paul S, Hobbs, Brian D, Sun, Quan, Surendran, Praveen, Brody, Jennifer A, Blackwell, Thomas W, Choquet, Hélène, Ryan, Kathleen, Duggirala, Ravindranath, Heard-Costa, Nancy, Wang, Zhe, Chami, Nathalie, Preuss, Michael H, Min, Nancy, Ekunwe, Lynette, Lange, Leslie A, Cushman, Mary, Faraday, Nauder, Curran, Joanne E, Almasy, Laura, Kundu, Kousik, Smith, Albert V, Gabriel, Stacey, Rotter, Jerome I, Fornage, Myriam, Lloyd-Jones, Donald M, Vasan, Ramachandran S, Smith, Nicholas L, North, Kari E, Boerwinkle, Eric, Becker, Lewis C, Lewis, Joshua P, Abecasis, Goncalo R, Hou, Lifang, O’Connell, Jeffrey R, Morrison, Alanna C, Beaty, Terri H, Kaplan, Robert, Correa, Adolfo, Blangero, John, Jorgenson, Eric, Psaty, Bruce M, Kooperberg, Charles, Walton, Russell T, Kleinstiver, Benjamin P, Tang, Hua, Loos, Ruth JF, Soranzo, Nicole, Butterworth, Adam S, Nickerson, Debbie, Rich, Stephen S, Mitchell, Braxton D, Johnson, Andrew D, Auer, Paul L, Li, Yun, Mathias, Rasika A, Lettre, Guillaume, Pankratz, Nathan, Laurie, Cathy C, Laurie, Cecelia A, Bauer, Daniel E, Conomos, Matthew P, Reiner, Alexander P, and Consortium, NHLBI Trans-Omics for Precision Medicine

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Biotechnology, Clinical Research, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, base editing, red blood cell traits, whole-genome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Published
2021

14. A multi-ethnic genome-wide association study implicates collagen matrix integrity and cell differentiation pathways in keratoconus.

Author

Hardcastle, Alison J, Liskova, Petra, Bykhovskaya, Yelena, McComish, Bennet J, Davidson, Alice E, Inglehearn, Chris F, Li, Xiaohui, Choquet, Hélène, Habeeb, Mahmoud, Lucas, Sionne EM, Sahebjada, Srujana, Pontikos, Nikolas, Lopez, Karla E Rojas, Khawaja, Anthony P, Ali, Manir, Dudakova, Lubica, Skalicka, Pavlina, Van Dooren, Bart TH, Geerards, Annette JM, Haudum, Christoph W, Faro, Valeria Lo, Tenen, Abi, Simcoe, Mark J, Patasova, Karina, Yarrand, Darioush, Yin, Jie, Siddiqui, Salina, Rice, Aine, Farraj, Layal Abi, Chen, Yii-Der Ida, Rahi, Jugnoo S, Krauss, Ronald M, Theusch, Elisabeth, Charlesworth, Jac C, Szczotka-Flynn, Loretta, Toomes, Carmel, Meester-Smoor, Magda A, Richardson, Andrea J, Mitchell, Paul A, Taylor, Kent D, Melles, Ronald B, Aldave, Anthony J, Mills, Richard A, Cao, Ke, Chan, Elsie, Daniell, Mark D, Wang, Jie Jin, Rotter, Jerome I, Hewitt, Alex W, MacGregor, Stuart, Klaver, Caroline CW, Ramdas, Wishal D, Craig, Jamie E, Iyengar, Sudha K, O'Brart, David, Jorgenson, Eric, Baird, Paul N, Rabinowitz, Yaron S, Burdon, Kathryn P, Hammond, Chris J, Tuft, Stephen J, and Hysi, Pirro G

Abstract

Keratoconus is characterised by reduced rigidity of the cornea with distortion and focal thinning that causes blurred vision, however, the pathogenetic mechanisms are unknown. It can lead to severe visual morbidity in children and young adults and is a common indication for corneal transplantation worldwide. Here we report the first large scale genome-wide association study of keratoconus including 4,669 cases and 116,547 controls. We have identified significant association with 36 genomic loci that, for the first time, implicate both dysregulation of corneal collagen matrix integrity and cell differentiation pathways as primary disease-causing mechanisms. The results also suggest pleiotropy, with some disease mechanisms shared with other corneal diseases, such as Fuchs endothelial corneal dystrophy. The common variants associated with keratoconus explain 12.5% of the genetic variance, which shows potential for the future development of a diagnostic test to detect susceptibility to disease.

Published
2021

15. Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

Author

Wen, Jia, Xie, Munan, Rowland, Bryce, Rosen, Jonathan D, Sun, Quan, Chen, Jiawen, Tapia, Amanda L, Qian, Huijun, Kowalski, Madeline H, Shan, Yue, Young, Kristin L, Graff, Marielisa, Argos, Maria, Avery, Christy L, Bien, Stephanie A, Buyske, Steve, Yin, Jie, Choquet, Hélène, Fornage, Myriam, Hodonsky, Chani J, Jorgenson, Eric, Kooperberg, Charles, Loos, Ruth JF, Liu, Yongmei, Moon, Jee-Young, North, Kari E, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Zhao, Wei, Shang, Lulu, Wang, Tao, Zhou, Xiang, Reiner, Alexander P, Raffield, Laura M, and Li, Yun

Subjects
Biological Sciences, Genetics, Biotechnology, Hematology, Human Genome, Atherosclerosis, Clinical Research, Good Health and Well Being, Black or African American, Blood Cells, Cohort Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Transcriptome, White People, TWAS, non-European populations, ancestry, expression analysis
Abstract

BackgroundThousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed.MethodsTo derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants.ResultsOur results revealed 24 suggestive signals (p < 1 × 10-4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN.ConclusionsThese analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Published
2021

17. Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations

Author

Chen, Ming-Huei, Raffield, Laura M, Mousas, Abdou, Sakaue, Saori, Huffman, Jennifer E, Moscati, Arden, Trivedi, Bhavi, Jiang, Tao, Akbari, Parsa, Vuckovic, Dragana, Bao, Erik L, Zhong, Xue, Manansala, Regina, Laplante, Véronique, Chen, Minhui, Lo, Ken Sin, Qian, Huijun, Lareau, Caleb A, Beaudoin, Mélissa, Hunt, Karen A, Akiyama, Masato, Bartz, Traci M, Ben-Shlomo, Yoav, Beswick, Andrew, Bork-Jensen, Jette, Bottinger, Erwin P, Brody, Jennifer A, van Rooij, Frank JA, Chitrala, Kumaraswamynaidu, Cho, Kelly, Choquet, Hélène, Correa, Adolfo, Danesh, John, Di Angelantonio, Emanuele, Dimou, Niki, Ding, Jingzhong, Elliott, Paul, Esko, Tõnu, Evans, Michele K, Floyd, James S, Broer, Linda, Grarup, Niels, Guo, Michael H, Greinacher, Andreas, Haessler, Jeff, Hansen, Torben, Howson, Joanna MM, Huang, Qin Qin, Huang, Wei, Jorgenson, Eric, Kacprowski, Tim, Kähönen, Mika, Kamatani, Yoichiro, Kanai, Masahiro, Karthikeyan, Savita, Koskeridis, Fotis, Lange, Leslie A, Lehtimäki, Terho, Lerch, Markus M, Linneberg, Allan, Liu, Yongmei, Lyytikäinen, Leo-Pekka, Manichaikul, Ani, Martin, Hilary C, Matsuda, Koichi, Mohlke, Karen L, Mononen, Nina, Murakami, Yoshinori, Nadkarni, Girish N, Nauck, Matthias, Nikus, Kjell, Ouwehand, Willem H, Pankratz, Nathan, Pedersen, Oluf, Preuss, Michael, Psaty, Bruce M, Raitakari, Olli T, Roberts, David J, Rich, Stephen S, Rodriguez, Benjamin AT, Rosen, Jonathan D, Rotter, Jerome I, Schubert, Petra, Spracklen, Cassandra N, Surendran, Praveen, Tang, Hua, Tardif, Jean-Claude, Trembath, Richard C, Ghanbari, Mohsen, Völker, Uwe, Völzke, Henry, Watkins, Nicholas A, Zonderman, Alan B, Program, VA Million Veteran, Wilson, Peter WF, Li, Yun, Butterworth, Adam S, Gauchat, Jean-François, Chiang, Charleston WK, and Li, Bingshan

Subjects
Genetics, Good Health and Well Being, Asian People, Genome-Wide Association Study, HEK293 Cells, Humans, Interleukin-7, Mutation, Missense, Phenotype, Polymorphism, Single Nucleotide, White People, VA Million Veteran Program, interleukin-7, genetic architecture, fine-mapping, selective sweeps, polygenic trait score, phenome-wide association study, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Published
2020

18. A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Author

Bailey-Wilson, Joan E., Baird, Paul N., Barathi, Veluchamy A., Biino, Ginevra, Burdon, Kathryn P., Campbell, Harry, Chen, Li Jia, Cheng, Ching-Yu, Chew, Emily Y., Craig, Jamie E., Deangelis, Margaret M., Delcourt, Cécile, Ding, Xiaohu, Fan, Qiao, Fossarello, Maurizio, Foster, Paul J., Gharahkhani, Puya, Guggenheim, Jeremy A., Guo, Xiaobo, Haarman, Annechien E.G., Haller, Toomas, Hammond, Christopher J., Han, Xikun, Hayward, Caroline, He, Mingguang, Hewitt, Alex W., Hoang, Quan, Hysi, Pirro G., Iglesias, Adriana I., Igo, Robert P., Iyengar, Sudha K., Jonas, Jost B., Kähönen, Mika, Kaprio, Jaakko, Khawaja, Anthony P., Klein, Barbara E., Lass, Jonathan H., Lee, Kris, Lehtimäki, Terho, Lewis, Deyana, Li, Qing, Li, Shi-Ming, Lyytikäinen, Leo-Pekka, MacGregor, Stuart, Mackey, David A., Martin, Nicholas G., Meguro, Akira, Metspalu, Andres, Middlebrooks, Candace, Miyake, Masahiro, Mizuki, Nobuhisa, Musolf, Anthony, Nickels, Stefan, Oexle, Konrad, Pang, Chi Pui, Pärssinen, Olavi, Paterson, Andrew D., Pfeiffer, Norbert, Polasek, Ozren, Rahi, Jugnoo S., Raitakari, Olli, Rudan, Igor, Sahebjada, Srujana, Saw, Seang-Mei, Simpson, Claire L., Stambolian, Dwight, Tai, E-Shyong, Tedja, Milly S., Tideman, J. Willem L., Tsujikawa, Akitaka, van Duijn, Cornelia M., Verhoeven, Virginie J.M., Vitart, Veronique, Wang, Ningli, Wang, Ya Xing, Wedenoja, Juho, Wei, Wen Bin, Williams, Cathy, Williams, Katie M., Wilson, James F., Wojciechowski, Robert, Yam, Jason C.S., Yamashiro, Kenji, Yap, Maurice K.H., Yazar, Seyhan, Yip, Shea Ping, Young, Terri L., Zhou, Xiangtian, Allen, Naomi, Aslam, Tariq, Atan, Denize, Barman, Sarah, Barrett, Jenny, Bishop, Paul, Black, Graeme, Bunce, Catey, Carare, Roxana, Chakravarthy, Usha, Chan, Michelle, Chua, Sharon, Cipriani, Valentina, Day, Alexander, Desai, Parul, Dhillon, Bal, Dick, Andrew, Doney, Alexander, Egan, Cathy, Ennis, Sarah, Foster, Paul, Fruttiger, Marcus, Gallacher, John, Garway-Heath, David, Gibson, Jane, Gore, Dan, Guggenheim, Jeremy, Hammond, Chris, Hardcastle, Alison, Harding, Simon, Hogg, Ruth, Hysi, Pirro, Keane, Pearse A., Khaw, Peng Tee, Khawaja, Anthony, Lascaratos, Gerassimos, Littlejohns, Thomas, Lotery, Andrew, Luthert, Phil, MacGillivray, Tom, Mackie, Sarah, McGuinness, Bernadette, McKay, Gareth, McKibbin, Martin, Mitry, Danny, Moore, Tony, Morgan, James, Muthy, Zaynah, O'Sullivan, Eoin, Owen, Chris, Patel, Praveen, Paterson, Euan, Peto, Tunde, Petzold, Axel, Pontikos, Nikolas, Rahi, Jugnoo, Rudnicka, Alicja, Self, Jay, Sergouniotis, Panagiotis, Sivaprasad, Sobha, Steel, David, Stratton, Irene, Strouthidis, Nicholas, Sudlow, Cathie, Tapp, Robyn, Thaung, Caroline, Thomas, Dhanes, Trucco, Emanuele, Tufail, Adnan, Vernon, Stephen, Viswanathan, Ananth, Williams, Katie, Woodside, Jayne, Yates, Max, Yip, Jennifer, Zheng, Yalin, Clark, Rosie, Lee, Samantha Sze-Yee, Du, Ran, Wang, Yining, Kneepkens, Sander C.M., Charng, Jason, Huang, Yu, Hunter, Michael L., Jiang, Chen, Tideman, J.Willem L., Melles, Ronald B., Klaver, Caroline C.W., Choquet, Hélène, and Ohno-Matsui, Kyoko

Published
2023
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19. Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Author

Kowalski, Madeline H, Qian, Huijun, Hou, Ziyi, Rosen, Jonathan D, Tapia, Amanda L, Shan, Yue, Jain, Deepti, Argos, Maria, Arnett, Donna K, Avery, Christy, Barnes, Kathleen C, Becker, Lewis C, Bien, Stephanie A, Bis, Joshua C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Buyske, Steve, Cai, Jianwen, Cho, Michael H, Choi, Seung Hoan, Choquet, Hélène, Cupples, L Adrienne, Cushman, Mary, Daya, Michelle, de Vries, Paul S, Ellinor, Patrick T, Faraday, Nauder, Fornage, Myriam, Gabriel, Stacey, Ganesh, Santhi K, Graff, Misa, Gupta, Namrata, He, Jiang, Heckbert, Susan R, Hidalgo, Bertha, Hodonsky, Chani J, Irvin, Marguerite R, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kardia, Sharon LR, Kelly, Tanika N, Kooperberg, Charles, Lasky-Su, Jessica A, Loos, Ruth JF, Lubitz, Steven A, Mathias, Rasika A, McHugh, Caitlin P, Montgomery, Courtney, Moon, Jee-Young, Morrison, Alanna C, Palmer, Nicholette D, Pankratz, Nathan, Papanicolaou, George J, Peralta, Juan M, Peyser, Patricia A, Rich, Stephen S, Rotter, Jerome I, Silverman, Edwin K, Smith, Jennifer A, Smith, Nicholas L, Taylor, Kent D, Thornton, Timothy A, Tiwari, Hemant K, Tracy, Russell P, Wang, Tao, Weiss, Scott T, Weng, Lu-Chen, Wiggins, Kerri L, Wilson, James G, Yanek, Lisa R, Zöllner, Sebastian, North, Kari E, Auer, Paul L, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology & Hemostasis Working Group, Raffield, Laura M, Reiner, Alexander P, and Li, Yun

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology & Hemostasis Working Group, Humans, Genetic Predisposition to Disease, Computational Biology, Genetics, Population, Gene Frequency, Linkage Disequilibrium, Databases, Genetic, Adult, Aged, Aged, 80 and over, Middle Aged, African Americans, Hispanic Americans, United States, Female, Male, Genome-Wide Association Study, beta-Globins, Genotyping Techniques, Precision Medicine, Whole Genome Sequencing, Genetics, Population, Databases, Genetic, and over, Developmental Biology
Abstract

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count 86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Published
2019

20. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Author

Liu, Mengzhen, Jiang, Yu, Wedow, Robbee, Li, Yue, Brazel, David M, Chen, Fang, Datta, Gargi, Davila-Velderrain, Jose, McGuire, Daniel, Tian, Chao, Zhan, Xiaowei, Choquet, Hélène, Docherty, Anna R, Faul, Jessica D, Foerster, Johanna R, Fritsche, Lars G, Gabrielsen, Maiken Elvestad, Gordon, Scott D, Haessler, Jeffrey, Hottenga, Jouke-Jan, Huang, Hongyan, Jang, Seon-Kyeong, Jansen, Philip R, Ling, Yueh, Mägi, Reedik, Matoba, Nana, McMahon, George, Mulas, Antonella, Orrù, Valeria, Palviainen, Teemu, Pandit, Anita, Reginsson, Gunnar W, Skogholt, Anne Heidi, Smith, Jennifer A, Taylor, Amy E, Turman, Constance, Willemsen, Gonneke, Young, Hannah, Young, Kendra A, Zajac, Gregory JM, Zhao, Wei, Zhou, Wei, Bjornsdottir, Gyda, Boardman, Jason D, Boehnke, Michael, Boomsma, Dorret I, Chen, Chu, Cucca, Francesco, Davies, Gareth E, Eaton, Charles B, Ehringer, Marissa A, Esko, Tõnu, Fiorillo, Edoardo, Gillespie, Nathan A, Gudbjartsson, Daniel F, Haller, Toomas, Harris, Kathleen Mullan, Heath, Andrew C, Hewitt, John K, Hickie, Ian B, Hokanson, John E, Hopfer, Christian J, Hunter, David J, Iacono, William G, Johnson, Eric O, Kamatani, Yoichiro, Kardia, Sharon LR, Keller, Matthew C, Kellis, Manolis, Kooperberg, Charles, Kraft, Peter, Krauter, Kenneth S, Laakso, Markku, Lind, Penelope A, Loukola, Anu, Lutz, Sharon M, Madden, Pamela AF, Martin, Nicholas G, McGue, Matt, McQueen, Matthew B, Medland, Sarah E, Metspalu, Andres, Mohlke, Karen L, Nielsen, Jonas B, Okada, Yukinori, Peters, Ulrike, Polderman, Tinca JC, Posthuma, Danielle, Reiner, Alexander P, Rice, John P, Rimm, Eric, Rose, Richard J, Runarsdottir, Valgerdur, Stallings, Michael C, Stančáková, Alena, Stefansson, Hreinn, Thai, Khanh K, Tindle, Hilary A, Tyrfingsson, Thorarinn, and Wall, Tamara L

Subjects
Substance Misuse, Human Genome, Brain Disorders, Tobacco, Tobacco Smoke and Health, Genetics, Alcoholism, Alcohol Use and Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Stroke, Cancer, Cardiovascular, Good Health and Well Being, Alcohol Drinking, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Phenotype, Risk, Smoking, Tobacco Use Disorder, 23andMe Research Team, HUNT All-In Psychiatry, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

Published
2019

21. Genome-Wide Association Study Identifies Two Common Loci Associated with Pigment Dispersion Syndrome/Pigmentary Glaucoma and Implicates Myopia in its Development

Author

Simcoe, Mark J., Shah, Ameet, Fan, Baojian, Choquet, Hélène, Weisschuh, Nicole, Waseem, Naushin H., Jiang, Chen, Melles, Ronald B., Ritch, Robert, Mahroo, Omar A., Wissinger, Bernd, Jorgenson, Eric, Wiggs, Janey L., Garway-Heath, David F., Hysi, Pirro G., and Hammond, Christopher J.

Published
2022
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22. Genome-wide meta-analysis identifies 22 loci for normal tension glaucoma with significant overlap with high tension glaucoma.

Author

Diaz-Torres, Santiago, He, Weixiong, Yu, Regina, Han, Xikun, Hamel, Andrew R., Young, Terri L., Lotery, Andrew J., Jorgenson, Eric, Choquet, Hélène, Hauser, Michael, Cooke Bailey, Jessica N., Nakazawa, Toru, Shiga, Yukihiro, Segrè, Ayellet V., Khawaja, Anthony P., Hammond, Christopher J., Hysi, Pirro G., Pasquale, Louis R., Wu, Yeda, and Kubo, Michiaki

Subjects
OPEN-angle glaucoma, INTRAOCULAR pressure, DRUG target, GLAUCOMA, NEUROPROTECTIVE agents
Abstract

Primary open-angle glaucoma typically presents as two subtypes. This study aimed to elucidate the shared and distinct genetic architectures of normal-tension (NTG) and high-tension glaucoma (HTG), motivated by the need to develop intraocular pressure (IOP)-independent drug targets for the disease. We conducted a comprehensive multi-ethnic meta-analysis, prioritized variants based on functional annotation, and explored drug-gene interactions. We further assessed the genetic overlap between NTG and HTG using pairwise GWAS analysis. We identified 22 risk loci associated with NTG, 17 of which have not previously been reported for NTG. Two loci, BMP4 and TBKBP1, have not previously been associated with glaucoma at the genome-wide significance level. Our results indicate that while there is a significant overlap in risk loci between tension subtypes, the magnitude of the effect tends to be lower in NTG compared to HTG, particularly for IOP-related loci. Additionally, we identified a potential role for biologic immunomodulatory treatments as neuroprotective agents. This study investigates the genetic similarities and differences between two subtypes of glaucoma (normal tension and high tension). Multi-ethnic meta-analysis reveals overlapping risk loci, with a lower effect magnitude in normal tension glaucoma. The authors also use their gene discovery approach to highlight possible neuro-protective drug targets for glaucoma. [ABSTRACT FROM AUTHOR]

Published
2024
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23. A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci

Author

Hoffmann, Thomas J, Choquet, Hélène, Yin, Jie, Banda, Yambazi, Kvale, Mark N, Glymour, Maria, Schaefer, Catherine, Risch, Neil, and Jorgenson, Eric

Subjects
Biological Sciences, Genetics, Obesity, Prevention, Human Genome, Clinical Research, 2.1 Biological and endogenous factors, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, Generic health relevance, Body Mass Index, Body Weight, Ethnicity, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Middle Aged, Multifactorial Inheritance, Sex Factors, adult body mass index, adult BMI, genome-wide association study, obesity, Developmental Biology, Biochemistry and cell biology
Abstract

Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.

Published
2018

24. A multiethnic genome-wide association study of primary open-angle glaucoma identifies novel risk loci.

Author

Choquet, Hélène, Paylakhi, Seyyedhassan, Kneeland, Stephen C, Thai, Khanh K, Hoffmann, Thomas J, Yin, Jie, Kvale, Mark N, Banda, Yambazi, Tolman, Nicholas G, Williams, Pete A, Schaefer, Catherine, Melles, Ronald B, Risch, Neil, John, Simon WM, Nair, K Saidas, and Jorgenson, Eric

Subjects
Retinal Ganglion Cells, Animals, Mice, Inbred C57BL, Humans, Mice, Mice, Mutant Strains, Glaucoma, Open-Angle, Genetic Predisposition to Disease, Proteins, Transcription Factors, Risk Factors, Cohort Studies, Gene Expression, Intraocular Pressure, Mutation, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, Ethnic Groups, Female, Male, Genome-Wide Association Study, Gene Knockdown Techniques, Genetic Loci, LIM-Homeodomain Proteins, United Kingdom, Formins, Inbred C57BL, Mutant Strains, Glaucoma, Open-Angle, Polymorphism, Single Nucleotide, and over
Abstract

Primary open-angle glaucoma (POAG) is a leading cause of irreversible vision loss, yet much of the genetic risk remains unaccounted for, especially in African-Americans who have a higher risk for developing POAG. We conduct a multiethnic genome-wide association study (GWAS) of POAG in the GERA cohort, with replication in the UK Biobank (UKB), and vice versa, GWAS in UKB with replication in GERA. We identify 24 loci (P

Published
2018

27. A large multi-ethnic genome-wide association study identifies novel genetic loci for intraocular pressure.

Author

Choquet, Hélène, Thai, Khanh K, Yin, Jie, Hoffmann, Thomas J, Kvale, Mark N, Banda, Yambazi, Schaefer, Catherine, Risch, Neil, Nair, K Saidas, Melles, Ronald, and Jorgenson, Eric

Subjects
Humans, Glaucoma, Genetic Predisposition to Disease, Intraocular Pressure, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, African Americans, Asian Continental Ancestry Group, European Continental Ancestry Group, Hispanic Americans, Female, Male, Genome-Wide Association Study, Genetic Loci, Polymorphism, Single Nucleotide, and over
Abstract

Elevated intraocular pressure (IOP) is a major risk factor for glaucoma, a leading cause of blindness. IOP heritability has been estimated to up to 67%, and to date only 11 IOP loci have been reported, accounting for 1.5% of IOP variability. Here, we conduct a genome-wide association study of IOP in 69,756 untreated individuals of European, Latino, Asian, and African ancestry. Multiple longitudinal IOP measurements were collected through electronic health records and, in total, 356,987 measurements were included. We identify 47 genome-wide significant IOP-associated loci (P

Published
2017

28. Association between lifetime smoking and cutaneous squamous cell carcinoma:A 2-sample Mendelian randomization study

Author

Lee, Truelian, George, Christopher D., Jiang, Chen, Asgari, Maryam M., Nijsten, Tamar, Pardo, Luba M., Choquet, Hélène, Lee, Truelian, George, Christopher D., Jiang, Chen, Asgari, Maryam M., Nijsten, Tamar, Pardo, Luba M., and Choquet, Hélène

Abstract

Background/Purpose: Cutaneous squamous cell carcinoma (cSCC) is one of the most common malignancies worldwide. While several environmental risk factors for cSCC are well established, there is conflicting evidence on cigarette smoking (and its potential causal effect) and cSCC risk. Furthermore, it is unclear if these potential associations represent causal, modifiable risk factors for cSCC development. This study aims to assess the nature of the associations between cigarette smoking traits (smoking initiation, amount smoked, and lifetime smoking exposure) and cSCC risk using two-sample Mendelian randomization analyses. Methods: Genetic instruments, based on common genetic variants associated with cigarette smoking traits (P < 5 × 10−8), were derived from published genome-wide association studies (GWASs). For cSCC, we used GWAS summary statistics from the Kaiser Permanente GERA cohort (7701 cSCC cases and 60,167 controls; all non-Hispanic Whites). Results: We found modest evidence that genetically determined lifetime smoking was associated with cSCC (inverse-variance weighted method: OR[95% CI] = 1.47[1.09-1.98]; P =.012), suggesting it may be a causal risk factor for cSCC. We did not detect any evidence of association between genetically determined smoking initiation or amount smoked and cSCC risk. Conclusion: Study findings highlight the importance of smoking prevention and may support risk-stratified cSCC screening strategies based on carcinogen exposure and other genetic and clinical information.

Published
2024

29. The Polygenic and Monogenic Basis of Blood Traits and Diseases

Author

Vuckovic, Dragana, Bao, Erik L., Akbari, Parsa, Lareau, Caleb A., Mousas, Abdou, Jiang, Tao, Chen, Ming-Huei, Raffield, Laura M., Tardaguila, Manuel, Huffman, Jennifer E., Ritchie, Scott C., Megy, Karyn, Ponstingl, Hannes, Penkett, Christopher J., Albers, Patrick K., Wigdor, Emilie M., Sakaue, Saori, Moscati, Arden, Manansala, Regina, Lo, Ken Sin, Qian, Huijun, Akiyama, Masato, Bartz, Traci M., Ben-Shlomo, Yoav, Beswick, Andrew, Bork-Jensen, Jette, Bottinger, Erwin P., Brody, Jennifer A., van Rooij, Frank J.A., Chitrala, Kumaraswamy N., Wilson, Peter W.F., Choquet, Hélène, Danesh, John, Di Angelantonio, Emanuele, Dimou, Niki, Ding, Jingzhong, Elliott, Paul, Esko, Tõnu, Evans, Michele K., Felix, Stephan B., Floyd, James S., Broer, Linda, Grarup, Niels, Guo, Michael H., Guo, Qi, Greinacher, Andreas, Haessler, Jeff, Hansen, Torben, Howson, Joanna M.M., Huang, Wei, Jorgenson, Eric, Kacprowski, Tim, Kähönen, Mika, Kamatani, Yoichiro, Kanai, Masahiro, Karthikeyan, Savita, Koskeridis, Fotios, Lange, Leslie A., Lehtimäki, Terho, Linneberg, Allan, Liu, Yongmei, Lyytikäinen, Leo-Pekka, Manichaikul, Ani, Matsuda, Koichi, Mohlke, Karen L., Mononen, Nina, Murakami, Yoshinori, Nadkarni, Girish N., Nikus, Kjell, Pankratz, Nathan, Pedersen, Oluf, Preuss, Michael, Psaty, Bruce M., Raitakari, Olli T., Rich, Stephen S., Rodriguez, Benjamin A.T., Rosen, Jonathan D., Rotter, Jerome I., Schubert, Petra, Spracklen, Cassandra N., Surendran, Praveen, Tang, Hua, Tardif, Jean-Claude, Ghanbari, Mohsen, Völker, Uwe, Völzke, Henry, Watkins, Nicholas A., Weiss, Stefan, Cai, Na, Kundu, Kousik, Watt, Stephen B., Walter, Klaudia, Zonderman, Alan B., Cho, Kelly, Li, Yun, Loos, Ruth J.F., Knight, Julian C., Georges, Michel, Stegle, Oliver, Evangelou, Evangelos, Okada, Yukinori, Roberts, David J., Inouye, Michael, Johnson, Andrew D., Auer, Paul L., Astle, William J., Reiner, Alexander P., Butterworth, Adam S., Ouwehand, Willem H., Lettre, Guillaume, Sankaran, Vijay G., and Soranzo, Nicole

Published
2020
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30. Relationships of visual impairment and eye conditions with imaging markers, cognition, and diagnoses of dementia: a bi-directional Mendelian randomization study

Author

Ferguson, Erin L, primary, Thoma, Mary, additional, Buto, Peter, additional, Wang, Jingxuan, additional, Glymour, M. Maria, additional, Hoffmann, Thomas J, additional, Choquet, Hélène, additional, Andrews, Shea J, additional, Yaffe, Kristine, additional, Casaletto, Kaitlin, additional, and Brenowitz, Willa D, additional

Published
2024
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32. GLIS1 regulates trabecular meshwork function and intraocular pressure and is associated with glaucoma in humans

Author

Nair, K. Saidas, Srivastava, Chitrangda, Brown, Robert V., Koli, Swanand, Choquet, Hélène, Kang, Hong Soon, Kuo, Yien-Ming, Grimm, Sara A., Sutherland, Caleb, Badea, Alexandra, Johnson, G. Allan, Zhao, Yin, Yin, Jie, Okamoto, Kyoko, Clark, Graham, Borrás, Terete, Zode, Gulab, Kizhatil, Krishnakumar, Chakrabarti, Subhabrata, John, Simon W. M., Jorgenson, Eric, and Jetten, Anton M.

Published
2021
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34. Polymorphisms in inflammatory and immune response genes associated with cerebral cavernous malformation type 1 severity.

Author

Choquet, Hélène, Pawlikowska, Ludmila, Nelson, Jeffrey, McCulloch, Charles E, Akers, Amy, Baca, Beth, Khan, Yasir, Hart, Blaine, Morrison, Leslie, Kim, Helen, and Brain Vascular Malformation Consortium (BVMC) Study

Subjects
Brain Vascular Malformation Consortium (BVMC) Study, Brain, Humans, Hemangioma, Cavernous, Central Nervous System, Cerebral Hemorrhage, Inflammation, Microtubule-Associated Proteins, Receptors, Interleukin-6, Receptors, Transforming Growth Factor beta, Proto-Oncogene Proteins, Interleukin-4, Magnetic Resonance Imaging, Severity of Illness Index, Genes, MHC Class II, Polymorphism, Genetic, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Female, Male, Scavenger Receptors, Class A, Toll-Like Receptor 4, Young Adult, KRIT1 Protein, Lipopolysaccharide Receptors, Receptor, Transforming Growth Factor-beta Type II, Hispanic or Latino, Protein Serine-Threonine Kinases, Rare Diseases, Neurosciences, Brain Disorders, Clinical Research, Genetics, 2.1 Biological and endogenous factors, Aetiology, Cerebral cavernous malformation, CCM1 disease severity, Intracerebral hemorrhage, Brain lesion count, Inflammation and immune response modifier genes, Clinical Sciences, Neurology & Neurosurgery
Abstract

BackgroundFamilial cerebral cavernous malformation type 1 (CCM1) is an autosomal dominant disease caused by mutations in the Krev Interaction Trapped 1 (KRIT1/CCM1) gene, and characterized by multiple brain lesions that often result in intracerebral hemorrhage (ICH), seizures, and neurological deficits. Carriers of the same genetic mutation can present with variable symptoms and severity of disease, suggesting the influence of modifier factors. Evidence is emerging that inflammation and immune response play a role in the pathogenesis of CCM. The purpose of this study was to investigate whether common variants in inflammatory and immune response genes influence the severity of familial CCM1 disease, as manifested by ICH and greater brain lesion count.MethodsHispanic CCM1 patients (n=188) harboring the founder Q455X 'common Hispanic mutation' (CHM) in the KRIT1 gene were analyzed at baseline. Participants were enrolled between June 2010 and March 2014 either through the Brain Vascular Malformation Consortium (BVMC) study or through the Angioma Alliance organization. Clinical assessment and cerebral susceptibility-weighted magnetic resonance imaging were performed to determine ICH as well as total and large (≥5 mm in diameter) lesion counts. Samples were genotyped on the Affymetrix Axiom Genome-Wide LAT1 Human Array. We analyzed 830 variants in 56 inflammatory and immune response genes for association with ICH and residuals of log-transformed total or large lesion count adjusted for age at enrollment and gender. Variants were analyzed individually or grouped by sub-pathways or whole pathways.ResultsAt baseline, 30.3% of CCM1-CHM subjects had ICH, with a mean ± standard deviation (SD) of 60.1±115.0 (range 0-713) for total lesions and 4.9±8.7 (range 0-104) for large lesions. The heritability estimates explained by all autosomal variants were 0.20 (SE=0.31), 0.81 (SE=0.17), and 0.48 (SE=0.19), for ICH, total lesion count, and large lesion count, respectively. TGFBR2 rs9823731 was significantly associated with ICH as well as with the total and large lesion counts (p≤0.017). Further, IL-4 rs9327638, CD14 rs778588, IL-6R rs114660934 and MSR1 rs62489577 were associated with two markers of disease severity. Finally, the whole pathway was associated with total lesion count (p=0.005) with TLR-4 rs10759930, CD14 rs778588, IL-6R rs114660934 and IGH rs57767447 mainly bearing this association. Eicosanoid signaling, extracellular pattern recognition, and immune response sub-pathways were also associated with the total lesion count.ConclusionsThese results suggest that polymorphisms in inflammatory and immune response pathways contribute to variability in CCM1 disease severity and might be used as predictors of disease severity. In particular, TGFBR2 rs9823731 was associated with all three markers of CCM1 disease severity tested, suggesting that TGFBR2 might be a key participant in the mechanism underlying CCM1 disease severity and phenotype variability. However, further longitudinal studies in larger sample sizes are needed to confirm these findings.

Published
2014

35. Association of cardiovascular risk factors with disease severity in cerebral cavernous malformation type 1 subjects with the common Hispanic mutation.

Author

Choquet, Hélène, Nelson, Jeffrey, Pawlikowska, Ludmila, McCulloch, Charles E, Akers, Amy, Baca, Beth, Khan, Yasir, Hart, Blaine, Morrison, Leslie, and Kim, Helen

Subjects
Brain, Humans, Hemangioma, Cavernous, Central Nervous System, Cerebral Hemorrhage, Cardiovascular Diseases, Genetic Predisposition to Disease, Microtubule-Associated Proteins, Proto-Oncogene Proteins, Magnetic Resonance Imaging, Body Mass Index, Risk Factors, Cohort Studies, Cross-Sectional Studies, Age of Onset, Quantitative Trait, Heritable, Mutation, Missense, Point Mutation, Adolescent, Adult, Middle Aged, Child, Hispanic Americans, Mexico, Female, Male, Young Adult, KRIT1 Protein, Hispanic or Latino, Obesity, Clinical Research, Neurosciences, Prevention, Rare Diseases, Tobacco, Tobacco Smoke and Health, Brain Disorders, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Cerebrovascular disease, Familial cerebral cavernous malformations type 1, Common Hispanic mutation, Disease severity, Brain lesion count, Intracerebral hemorrhage, Cardiovascular risk factors, Clinical Sciences, Neurology & Neurosurgery
Abstract

BackgroundCerebral cavernous malformations (CCM) are enlarged vascular lesions affecting 0.1-0.5% of the population worldwide and causing hemorrhagic strokes, seizures, and neurological deficits. Familial CCM type 1 (CCM1) is an autosomal dominant disease caused by mutations in the Krev Interaction Trapped 1 (KRIT1/CCM1) gene, and is characterized by multiple brain lesions whose number and size increase with age. The number of lesions varies widely for unknown reasons, even among carriers of similar ages with the same mutation. The purpose of this study was to investigate whether cardiovascular (CV) risk factors influence potential markers of familial CCM1 disease severity, such as lesion count and history of intracerebral hemorrhage.MethodsWe analyzed baseline data from 185 Hispanic subjects, enrolled in the Brain Vascular Malformation Consortium study between June 2010 and March 2013. All subjects were carriers of the founder Q455X 'Common Hispanic Mutation' (CHM) in the KRIT1 gene, and had a clinical diagnosis of CCM or had an affected first- or second-degree relative with CCM. We performed a cross-sectional study, collecting detailed clinical information of CCM1-CHM subjects and cerebral susceptibility-weighted magnetic resonance imaging to assess lesion count. Linear or logistic regression analysis of log-lesion count or history of intracerebral hemorrhage and CV risk factors (age, gender, obesity, diabetes, hypertension, hyperlipidemia and smoking status) and related quantitative traits (body mass index, glycosylated hemoglobin levels, blood pressure, lipids levels and pack-years of cigarette smoking) was performed accommodating familial clustering.ResultsCCM1-CHM subjects were mainly female (63.8%) and symptomatic at presentation (63.2%). Lesion count was highly variable (mean ± SD: 57.7 ± 110.6; range: 0-713); 90% of CCM1-CHM subjects had multiple lesions at enrollment. Age (p < 0.001) was positively correlated with lesion count and male gender (p = 0.035) was associated with a greater number of lesions. Obesity (p = 0.001) and higher body mass index (p = 0.002) were associated with fewer lesions. No association with hypertension was detected, however, systolic blood pressure (p = 0.002) was associated with fewer lesions. No significant association with lesion count was observed for diabetes, hyperlipidemia, smoking status or for related quantitative traits. History of intracerebral hemorrhage was not significantly associated with any CV risk factors, however, we found borderline associations of hemorrhage with obesity (p = 0.062), systolic blood pressure (p = 0.083) and pack-years of cigarette smoking (p = 0.055). After correction for multiple testing, age and obesity remained significantly associated with lesion count in CCM1-CHM subjects.ConclusionsThese results suggest that several CV risk factors explain some of the variability in lesion count in Hispanic CCM1-CHM subjects. Although age, gender, obesity, body mass index and systolic blood pressure may influence familial CCM1 disease severity, further longitudinal studies in larger sample sizes are essential to confirm these findings.

Published
2014

42. Multi-ancestry GWAS of Fuchs corneal dystrophy highlights roles of laminins, collagen, and endothelial cell regulation

Author

Peachey, Neal, primary, Gorman, Bryan, additional, Francis, Michael, additional, Nealon, Cari, additional, Halladay, Christopher, additional, Duro, Nalvi, additional, Markianos, Kyriacos, additional, Genovese, Giulio, additional, Hysi, Pirro, additional, Choquet, Hélène, additional, Afshari, Natalie, additional, Li, Yi-Ju, additional, Gaziano, J. Michael, additional, Hung, Adriana, additional, Wu, Wen-Chih, additional, Greenberg, Paul, additional, Pyarajan, Saiju, additional, Lass, Jonathan, additional, and Iyengar, Sudha, additional

Published
2023
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45. A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Author

Clark, Rosie, primary, Lee, Samantha Sze-Yee, additional, Du, Ran, additional, Wang, Yining, additional, Kneepkens, Sander C.M., additional, Charng, Jason, additional, Huang, Yu, additional, Hunter, Michael L., additional, Jiang, Chen, additional, Tideman, J.Willem L., additional, Melles, Ronald B., additional, Klaver, Caroline C.W., additional, Mackey, David A., additional, Williams, Cathy, additional, Choquet, Hélène, additional, Ohno-Matsui, Kyoko, additional, Guggenheim, Jeremy A., additional, Bailey-Wilson, Joan E., additional, Baird, Paul N., additional, Barathi, Veluchamy A., additional, Biino, Ginevra, additional, Burdon, Kathryn P., additional, Campbell, Harry, additional, Chen, Li Jia, additional, Cheng, Ching-Yu, additional, Chew, Emily Y., additional, Craig, Jamie E., additional, Deangelis, Margaret M., additional, Delcourt, Cécile, additional, Ding, Xiaohu, additional, Fan, Qiao, additional, Fossarello, Maurizio, additional, Foster, Paul J., additional, Gharahkhani, Puya, additional, Guo, Xiaobo, additional, Haarman, Annechien E.G., additional, Haller, Toomas, additional, Hammond, Christopher J., additional, Han, Xikun, additional, Hayward, Caroline, additional, He, Mingguang, additional, Hewitt, Alex W., additional, Hoang, Quan, additional, Hysi, Pirro G., additional, Iglesias, Adriana I., additional, Igo, Robert P., additional, Iyengar, Sudha K., additional, Jonas, Jost B., additional, Kähönen, Mika, additional, Kaprio, Jaakko, additional, Khawaja, Anthony P., additional, Klein, Barbara E., additional, Lass, Jonathan H., additional, Lee, Kris, additional, Lehtimäki, Terho, additional, Lewis, Deyana, additional, Li, Qing, additional, Li, Shi-Ming, additional, Lyytikäinen, Leo-Pekka, additional, MacGregor, Stuart, additional, Martin, Nicholas G., additional, Meguro, Akira, additional, Metspalu, Andres, additional, Middlebrooks, Candace, additional, Miyake, Masahiro, additional, Mizuki, Nobuhisa, additional, Musolf, Anthony, additional, Nickels, Stefan, additional, Oexle, Konrad, additional, Pang, Chi Pui, additional, Pärssinen, Olavi, additional, Paterson, Andrew D., additional, Pfeiffer, Norbert, additional, Polasek, Ozren, additional, Rahi, Jugnoo S., additional, Raitakari, Olli, additional, Rudan, Igor, additional, Sahebjada, Srujana, additional, Saw, Seang-Mei, additional, Simpson, Claire L., additional, Stambolian, Dwight, additional, Tai, E-Shyong, additional, Tedja, Milly S., additional, Tideman, J. Willem L., additional, Tsujikawa, Akitaka, additional, van Duijn, Cornelia M., additional, Verhoeven, Virginie J.M., additional, Vitart, Veronique, additional, Wang, Ningli, additional, Wang, Ya Xing, additional, Wedenoja, Juho, additional, Wei, Wen Bin, additional, Williams, Katie M., additional, Wilson, James F., additional, Wojciechowski, Robert, additional, Yam, Jason C.S., additional, Yamashiro, Kenji, additional, Yap, Maurice K.H., additional, Yazar, Seyhan, additional, Yip, Shea Ping, additional, Young, Terri L., additional, Zhou, Xiangtian, additional, Allen, Naomi, additional, Aslam, Tariq, additional, Atan, Denize, additional, Barman, Sarah, additional, Barrett, Jenny, additional, Bishop, Paul, additional, Black, Graeme, additional, Bunce, Catey, additional, Carare, Roxana, additional, Chakravarthy, Usha, additional, Chan, Michelle, additional, Chua, Sharon, additional, Cipriani, Valentina, additional, Day, Alexander, additional, Desai, Parul, additional, Dhillon, Bal, additional, Dick, Andrew, additional, Doney, Alexander, additional, Egan, Cathy, additional, Ennis, Sarah, additional, Foster, Paul, additional, Fruttiger, Marcus, additional, Gallacher, John, additional, Garway-Heath, David, additional, Gibson, Jane, additional, Gore, Dan, additional, Guggenheim, Jeremy, additional, Hammond, Chris, additional, Hardcastle, Alison, additional, Harding, Simon, additional, Hogg, Ruth, additional, Hysi, Pirro, additional, Keane, Pearse A., additional, Khaw, Peng Tee, additional, Khawaja, Anthony, additional, Lascaratos, Gerassimos, additional, Littlejohns, Thomas, additional, Lotery, Andrew, additional, Luthert, Phil, additional, MacGillivray, Tom, additional, Mackie, Sarah, additional, McGuinness, Bernadette, additional, McKay, Gareth, additional, McKibbin, Martin, additional, Mitry, Danny, additional, Moore, Tony, additional, Morgan, James, additional, Muthy, Zaynah, additional, O'Sullivan, Eoin, additional, Owen, Chris, additional, Patel, Praveen, additional, Paterson, Euan, additional, Peto, Tunde, additional, Petzold, Axel, additional, Pontikos, Nikolas, additional, Rahi, Jugnoo, additional, Rudnicka, Alicja, additional, Self, Jay, additional, Sergouniotis, Panagiotis, additional, Sivaprasad, Sobha, additional, Steel, David, additional, Stratton, Irene, additional, Strouthidis, Nicholas, additional, Sudlow, Cathie, additional, Tapp, Robyn, additional, Thaung, Caroline, additional, Thomas, Dhanes, additional, Trucco, Emanuele, additional, Tufail, Adnan, additional, Vernon, Stephen, additional, Viswanathan, Ananth, additional, Williams, Katie, additional, Woodside, Jayne, additional, Yates, Max, additional, Yip, Jennifer, additional, and Zheng, Yalin, additional

Published
2023
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47. A multiethnic genome-wide analysis of 19,420 individuals identifies novel loci associated with axial length and shared genetic influences with refractive error and myopia

Author

Melles, Ronald B., Jiang, Chen, Yin, Jie, Fan, Qiao, Guo, Xiaobo, Cheng, Ching Yu, He, Mingguang, Mackey, David A., Guggenheim, Jeremy A., Klaver, Caroline, Nair, K. Saidas, Jorgenson, Eric, Choquet, Hélène, Melles, Ronald B., Jiang, Chen, Yin, Jie, Fan, Qiao, Guo, Xiaobo, Cheng, Ching Yu, He, Mingguang, Mackey, David A., Guggenheim, Jeremy A., Klaver, Caroline, Nair, K. Saidas, Jorgenson, Eric, and Choquet, Hélène

Abstract

Introduction: Long axial length (AL) is a risk factor for myopia. Although family studies indicate that AL has an important genetic component with heritability estimates up to 0.94, there have been few reports of AL-associated loci. Methods: Here, we conducted a multiethnic genome-wide association study (GWAS) of AL in 19,420 adults of European, Latino, Asian, and African ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort, with replication in a subset of the Consortium for Refractive Error and Myopia (CREAM) cohorts of European or Asian ancestry. We further examined the effect of the identified loci on the mean spherical equivalent (MSE) within the GERA cohort. We also performed genome-wide genetic correlation analyses to quantify the genetic overlap between AL and MSE or myopia risk in the GERA European ancestry sample. Results: Our multiethnic GWA analysis of AL identified a total of 16 genomic loci, of which 5 are novel. We found that all AL-associated loci were significantly associated with MSE after Bonferroni correction. We also found that AL was genetically correlated with MSE (rg = −0.83; SE, 0.04; p = 1.95 × 10−89) and myopia (rg = 0.80; SE, 0.05; p = 2.84 × 10−55). Finally, we estimated the array heritability for AL in the GERA European ancestry sample using LD score regression, and found an overall heritability estimate of 0.37 (s.e. = 0.04). Discussion: In this large and multiethnic study, we identified novel loci, associated with AL at a genome-wide significance level, increasing substantially our understanding of the etiology of AL variation. Our results also demonstrate an association between AL-associated loci and MSE and a shared genetic basis between AL and myopia risk.

Published
2023

48. A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Author

Clark, Rosie, Lee, Samantha Sze Yee, Du, Ran, Wang, Yining, Kneepkens, Sander C.M., Charng, Jason, Huang, Yu, Hunter, Michael L., Jiang, Chen, Tideman, J. Willem L., Melles, Ronald B., Klaver, Caroline C.W., Mackey, David A., Williams, Cathy, Choquet, Hélène, Ohno-Matsui, Kyoko, Guggenheim, Jeremy A., Tedja, Milly S., van Duijn, Cornelia M., Verhoeven, Virginie J.M., Chan, Michelle, Clark, Rosie, Lee, Samantha Sze Yee, Du, Ran, Wang, Yining, Kneepkens, Sander C.M., Charng, Jason, Huang, Yu, Hunter, Michael L., Jiang, Chen, Tideman, J. Willem L., Melles, Ronald B., Klaver, Caroline C.W., Mackey, David A., Williams, Cathy, Choquet, Hélène, Ohno-Matsui, Kyoko, Guggenheim, Jeremy A., Tedja, Milly S., van Duijn, Cornelia M., Verhoeven, Virginie J.M., and Chan, Michelle

Abstract

Background: High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ −6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. Methods: The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. Findings: In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17–21%), 2% (1–3%), 8% (7–10%) and 6% (3–9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75–0.81), 0.58 (0.53–0.64), 0.71 (0.69–0.74) and 0.67 (0.62–0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92–1.24). Interpretation: Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted for. Funding: Supported by the Welsh Government and Fight for Sight ( 24WG201).

Published
2023

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