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3. Telomere length associates with chronological age and mortality across racially diverse pulmonary fibrosis cohorts

Author

Adegunsoye, Ayodeji, Newton, Chad A, Oldham, Justin M, Ley, Brett, Lee, Cathryn T, Linderholm, Angela L, Chung, Jonathan H, Garcia, Nicole, Zhang, Da, Vij, Rekha, Guzy, Robert, Jablonski, Renea, Bag, Remzi, Voogt, Rebecca S, Ma, Shwu-Fan, Sperling, Anne I, Raghu, Ganesh, Martinez, Fernando J, Strek, Mary E, Wolters, Paul J, Garcia, Christine Kim, Pierce, Brandon L, and Noth, Imre

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Good Health and Well Being, Humans, Pulmonary Fibrosis, Ethnicity, Proportional Hazards Models, Racial Groups, Telomere, Leukocytes
Abstract

Pulmonary fibrosis (PF) is characterized by profound scarring and poor survival. We investigated the association of leukocyte telomere length (LTL) with chronological age and mortality across racially diverse PF cohorts. LTL measurements among participants with PF stratified by race/ethnicity were assessed in relation to age and all-cause mortality, and compared to controls. Generalized linear models were used to evaluate the age-LTL relationship, Cox proportional hazards models were used for hazard ratio estimation, and the Cochran-Armitage test was used to assess quartiles of LTL. Standardized LTL shortened with increasing chronological age; this association in controls was strengthened in PF (R = -0.28; P

Published
2023

8. Supplementary Figure 5 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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9. Supplementary Table 19 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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10. Supplementary Figure 3 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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11. Supplementary Figure 2 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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12. Supplementary Table 4 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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13. Supplementary Table 3 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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14. Supplementary Figure 8 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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15. Supplementary Figure 4 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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16. Supplementary Figure 9 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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17. Data from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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18. Supplementary Figure 6 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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19. Supplementary Table 2 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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20. Supplementary Table 7 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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21. Supplementary Figure 1 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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22. Supplementary Table 9 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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23. Supplementary Table 5 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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24. Supplementary Table 8 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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25. Supplementary Table 6 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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26. Supplementary Figure 7 from The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

Author

Delgado, Dayana, primary, Gillard, Marc, primary, Tong, Lin, primary, Demanelis, Kathryn, primary, Oliva, Meritxell, primary, Gleason, Kevin J., primary, Chernoff, Meytal, primary, Chen, Lin, primary, Paner, Gladell P., primary, Vander Griend, Donald, primary, and Pierce, Brandon L., primary

Published
2024
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29. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis

Author

Yang, Fan, Wang, Jiebiao, Consortium, The GTEx, Pierce, Brandon L, Chen, Lin S, Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Im, Hae Kyung, Jo, Brian, Kang, Eun Yong, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, and Wang, Gao

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, Generic health relevance, Good Health and Well Being, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Selection, Genetic, Tissue Distribution, GTEx Consortium, Medical and Health Sciences, Bioinformatics
Abstract

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (cis-eQTLs). More research is needed to identify effects of genetic variation on distant genes (trans-eQTLs) and understand their biological mechanisms. One common trans-eQTLs mechanism is "mediation" by a local (cis) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are "cis-mediators" of trans-eQTLs, including those "cis-hubs" involved in regulation of many trans-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis-hubs and trans-eQTL regulation across tissue types.

Published
2017

30. Lessons Learned From Past Gene-Environment Interaction Successes.

Author

Ritz, Beate R, Chatterjee, Nilanjan, Garcia-Closas, Montserrat, Gauderman, W James, Pierce, Brandon L, Kraft, Peter, Tanner, Caroline M, Mechanic, Leah E, and McAllister, Kimberly

Subjects
Epidemiology, Health Sciences, Patient Safety, Genetics, Aetiology, 2.1 Biological and endogenous factors, Biomedical Research, Disease, Environmental Exposure, Gene-Environment Interaction, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Models, Biological, exposure, gene-environment, genome-wide association studies, interactions, metabolism genes, pathway genes, pharmacogenomics, Mathematical Sciences, Medical and Health Sciences
Abstract

Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment interaction (G×E) has been a focus of research for several years. In this article, select examples of G×E from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples can be broadly categorized as studies of single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some G×E successes depended on the availability of high-quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations. In several examples, large population sizes were required to detect G×Es. Other examples illustrated the impact of accurately defining scale of the interactions (i.e., additive or multiplicative). Last, model systems and functional approaches provided insights into G×E in several examples. Future studies may benefit from these lessons learned.

Published
2017

31. Mapping potential pathways from polygenic liability through brain structure to psychological problems across the transition to adolescence.

Author

Lahey, Benjamin B., Durham, E. Leighton, Brislin, Sarah J., Barr, Peter B., Dick, Danielle M., Moore, Tyler M., Pierce, Brandon L., Tong, Lin, Reimann, Gabrielle E., Jeong, Hee Jung, Dupont, Randolph M., and Kaczkurkin, Antonia N.

Subjects
ADOLESCENT development, RISK assessment, ATTENTION-deficit hyperactivity disorder, RESEARCH funding, RISK-taking behavior, BRAIN, MENTAL illness, CELLULAR signal transduction, MAGNETIC resonance imaging, UNSAFE sex, QUALITY control, STRUCTURAL equation modeling, DESCRIPTIVE statistics, GENETIC risk score, TEENAGERS' conduct of life, BEHAVIOR disorders in children, LONGITUDINAL method, GRAY matter (Nerve tissue), CHILD Behavior Checklist, NEURORADIOLOGY, QUALITY assurance, FACTOR analysis, COMPARATIVE studies, DATA analysis software, TRANSITION to adulthood, GENETICS, GENOTYPES, ADOLESCENCE
Abstract

Background: We used a polygenic score for externalizing behavior (extPGS) and structural MRI to examine potential pathways from genetic liability to conduct problems via the brain across the adolescent transition. Methods: Three annual assessments of child conduct problems, attention‐deficit/hyperactivity problems, and internalizing problems were conducted across across 9–13 years of age among 4,475 children of European ancestry in the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). Results: The extPGS predicted conduct problems in each wave (R2 = 2.0%–2.9%). Bifactor models revealed that the extPRS predicted variance specific to conduct problems (R2 = 1.7%–2.1%), but also variance that conduct problems shared with other measured problems (R2 =.8%–1.4%). Longitudinally, extPGS predicted levels of specific conduct problems (R2 = 2.0%), but not their slope of change across age. The extPGS was associated with total gray matter volume (TGMV; R2 =.4%) and lower TGMV predicted both specific conduct problems (R2 = 1.7%–2.1%) and the variance common to all problems in each wave (R2 = 1.6%–3.1%). A modest proportion of the polygenic liability specific to conduct problems in each wave was statistically mediated by TGMV. Conclusions: Across the adolescent transition, the extPGS predicted both variance specific to conduct problems and variance shared by all measured problems. The extPGS also was associated with TGMV, which robustly predicted conduct problems. Statistical mediation analyses suggested the hypothesis that polygenic variation influences individual differences in brain development that are related to the likelihood of conduct problems during the adolescent transition, justifying new research to test this causal hypothesis. [ABSTRACT FROM AUTHOR]

Published
2024
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32. The impact of inherited genetic variation on DNA methylation in prostate cancer and benign tissues of African American and European American men

Author

Delgado, Dayana, primary, Gillard, Marc, additional, Tong, Lin, additional, Demanelis, Kathryn, additional, Oliva, Meritxell, additional, Gleason, Kevin J., additional, Chernoff, Meytal, additional, Chen, Lin, additional, Paner, Gladell P., additional, Vander Griend, Donald, additional, and Pierce, Brandon L., additional

Published
2024
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33. OTTERS:a powerful TWAS framework leveraging summary-level reference data

Author

Dai, Qile, Zhou, Geyu, Zhao, Hongyu, Võsa, Urmo, Franke, Lude, Battle, Alexis, Teumer, Alexander, Lehtimäki, Terho, Raitakari, Olli T., Esko, Tõnu, Agbessi, Mawussé, Ahsan, Habibul, Alves, Isabel, Andiappan, Anand Kumar, Arindrarto, Wibowo, Awadalla, Philip, Beutner, Frank, Jan Bonder, Marc, Boomsma, Dorret I., Christiansen, Mark W., Claringbould, Annique, Deelen, Patrick, Favé, Marie-Julie, Frayling, Timothy, Gharib, Sina A., Gibson, Greg, Heijmans, Bastiaan T., Hemani, Gibran, Jansen, Rick, Kähönen, Mika, Kalnapenkis, Anette, Kasela, Silva, Kettunen, Johannes, Kim, Yungil, Kirsten, Holger, Kovacs, Peter, Krohn, Knut, Kronberg, Jaanika, Kukushkina, Viktorija, Kutalik, Zoltan, Lee, Bernett, Loeffler, Markus, Marigorta, Urko M., Mei, Hailang, Milani, Lili, Montgomery, Grant W., Müller-Nurasyid, Martina, Nauck, Matthias, Nivard, Michel G., Penninx, Brenda, Perola, Markus, Pervjakova, Natalia, Pierce, Brandon L., Powell, Joseph, Prokisch, Holger, Psaty, Bruce M., Ripatti, Samuli, Rotzschke, Olaf, Rüeger, Sina, Saha, Ashis, Scholz, Markus, Schramm, Katharina, Seppälä, Ilkka, Slagboom, Eline P., Stehouwer, Coen D. A., Stumvoll, Michael, Sullivan, Patrick, ‘t Hoen, Peter A. C., Thiery, Joachim, Tong, Lin, Tönjes, Anke, van Dongen, Jenny, van Iterson, Maarten, van Meurs, Joyce, Veldink, Jan H., Verlouw, Joost, Visscher, Peter M., Völker, Uwe, Westra, Harm-Jan, Wijmenga, Cisca, Yaghootkar, Hanieh, Yang, Jian, Zeng, Biao, Zhang, Futao, Epstein, Michael P., Yang, Jingjing, Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Biological Psychology, Amsterdam Reproduction & Development, APH - Methodology, APH - Personalized Medicine, Internal Medicine, Tampere University, Department of Clinical Chemistry, and Clinical Medicine

Subjects
Multidisciplinary, 1182 Biochemistry, cell and molecular biology, General Physics and Astronomy, 3111 Biomedicine, General Chemistry, Medical Genetics, General Biochemistry, Genetics and Molecular Biology, Medicinsk genetik
Abstract

Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies. Godkänd;2023;Nivå 0;2023-04-06 (hanlid);Funder: for more funders see the article https://doi.org/10.1038/s41467-023-36862-w

Published
2023

34. Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction

Author

Hoffmann, Thomas J, primary, Graff, Rebecca E, additional, Madduri, Ravi K, additional, Rodriguez, Alex A, additional, Cario, Clint L, additional, Feng, Karen, additional, Jiang, Yu, additional, Wang, Anqi, additional, Klein, Robert J, additional, Pierce, Brandon L, additional, Eggener, Scott, additional, Tong, Lin, additional, Blot, William, additional, Long, Jirong, additional, Rebbeck, Timothy, additional, Lachance, Joseph, additional, Andrews, Caroline, additional, Adebiyi, Akindele O, additional, Adusei, Ben, additional, Aisuodionoe-Shadrach, Oseremen I, additional, Fernandez, Pedro W, additional, Jalloh, Mohamed, additional, Janivara, Rohini, additional, Chen, Wenlong C, additional, Mensah, James E, additional, Agalliu, Ilir, additional, Berndt, Sonja I, additional, Shelley, John P, additional, Schaffer, Kerry, additional, Machiela, Mitchell J, additional, Freedman, Neal D, additional, Huang, Wen-Yi, additional, Li, Shengchao A, additional, Goodman, Phyllis J, additional, Till, Cathee, additional, Thompson, Ian, additional, Lilja, Hans, additional, Van Den Eeden, Stephen K, additional, Chanock, Stephen J, additional, Mosley, Jonathan D, additional, Conti, David V, additional, Haiman, Christopher A, additional, Justice, Amy C, additional, Kachuri, Linda, additional, and Witte, John S, additional

Published
2023
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37. The contribution of parent-to-offspring transmission of telomeres to the heritability of telomere length in humans

Author

Delgado, Dayana A., Zhang, Chenan, Gleason, Kevin, Demanelis, Kathryn, Chen, Lin S., Gao, Jianjun, Roy, Shantanu, Shinkle, Justin, Sabarinathan, Mekala, Argos, Maria, Tong, Lin, Ahmed, Alauddin, Islam, Tariqul, Rakibuz-Zaman, Muhammad, Sarwar, Golam, Shahriar, Hasan, Rahman, Mahfuzar, Yunus, Muhammad, Doherty, Jennifer A., Jasmine, Farzana, Kibriya, Muhammad G., Ahsan, Habibul, and Pierce, Brandon L.

Published
2019
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39. Screening for gene–environment (G×E) interaction using omics data from exposed individuals: an application to gene-arsenic interaction

Author

Argos, Maria, Tong, Lin, Roy, Shantanu, Sabarinathan, Mekala, Ahmed, Alauddin, Islam, Md. Tariqul, Islam, Tariqul, Rakibuz-Zaman, Muhammad, Sarwar, Golam, Shahriar, Hasan, Rahman, Mahfuzar, Yunus, Md., Graziano, Joseph H., Jasmine, Farzana, Kibriya, Muhammad G., Zhou, Xiang, Ahsan, Habibul, and Pierce, Brandon L.

Published
2018
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41. Supplementary Methods, Tables 1 - 6 from A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

Author

Ahsan, Habibul, primary, Halpern, Jerry, primary, Kibriya, Muhammad G., primary, Pierce, Brandon L., primary, Tong, Lin, primary, Gamazon, Eric, primary, McGuire, Valerie, primary, Felberg, Anna, primary, Shi, Jianxin, primary, Jasmine, Farzana, primary, Roy, Shantanu, primary, Brutus, Rachelle, primary, Argos, Maria, primary, Melkonian, Stephanie, primary, Chang-Claude, Jenny, primary, Andrulis, Irene, primary, Hopper, John L., primary, John, Esther M., primary, Malone, Kathi, primary, Ursin, Giske, primary, Gammon, Marilie D., primary, Thomas, Duncan C., primary, Seminara, Daniela, primary, Casey, Graham, primary, Knight, Julia A., primary, Southey, Melissa C., primary, Giles, Graham G., primary, Santella, Regina M., primary, Lee, Eunjung, primary, Conti, David, primary, Duggan, David, primary, Gallinger, Steve, primary, Haile, Robert, primary, Jenkins, Mark, primary, Lindor, Noralane M., primary, Newcomb, Polly, primary, Michailidou, Kyriaki, primary, Apicella, Carmel, primary, Park, Daniel J., primary, Peto, Julian, primary, Fletcher, Olivia, primary, dos Santos Silva, Isabel, primary, Lathrop, Mark, primary, Hunter, David J., primary, Chanock, Stephen J., primary, Meindl, Alfons, primary, Schmutzler, Rita K., primary, Müller-Myhsok, Bertram, primary, Lochmann, Magdalena, primary, Beckmann, Lars, primary, Hein, Rebecca, primary, Makalic, Enes, primary, Schmidt, Daniel F., primary, Bui, Quang Minh, primary, Stone, Jennifer, primary, Flesch-Janys, Dieter, primary, Dahmen, Norbert, primary, Nevanlinna, Heli, primary, Aittomäki, Kristiina, primary, Blomqvist, Carl, primary, Hall, Per, primary, Czene, Kamila, primary, Irwanto, Astrid, primary, Liu, Jianjun, primary, Rahman, Nazneen, primary, Turnbull, Clare, primary, Dunning, Alison M., primary, Pharoah, Paul, primary, Waisfisz, Quinten, primary, Meijers-Heijboer, Hanne, primary, Uitterlinden, Andre G., primary, Rivadeneira, Fernando, primary, Nicolae, Dan, primary, Easton, Douglas F., primary, Cox, Nancy J., primary, and Whittemore, Alice S., primary

Published
2023
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47. Data from A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

Author

Ahsan, Habibul, primary, Halpern, Jerry, primary, Kibriya, Muhammad G., primary, Pierce, Brandon L., primary, Tong, Lin, primary, Gamazon, Eric, primary, McGuire, Valerie, primary, Felberg, Anna, primary, Shi, Jianxin, primary, Jasmine, Farzana, primary, Roy, Shantanu, primary, Brutus, Rachelle, primary, Argos, Maria, primary, Melkonian, Stephanie, primary, Chang-Claude, Jenny, primary, Andrulis, Irene, primary, Hopper, John L., primary, John, Esther M., primary, Malone, Kathi, primary, Ursin, Giske, primary, Gammon, Marilie D., primary, Thomas, Duncan C., primary, Seminara, Daniela, primary, Casey, Graham, primary, Knight, Julia A., primary, Southey, Melissa C., primary, Giles, Graham G., primary, Santella, Regina M., primary, Lee, Eunjung, primary, Conti, David, primary, Duggan, David, primary, Gallinger, Steve, primary, Haile, Robert, primary, Jenkins, Mark, primary, Lindor, Noralane M., primary, Newcomb, Polly, primary, Michailidou, Kyriaki, primary, Apicella, Carmel, primary, Park, Daniel J., primary, Peto, Julian, primary, Fletcher, Olivia, primary, dos Santos Silva, Isabel, primary, Lathrop, Mark, primary, Hunter, David J., primary, Chanock, Stephen J., primary, Meindl, Alfons, primary, Schmutzler, Rita K., primary, Müller-Myhsok, Bertram, primary, Lochmann, Magdalena, primary, Beckmann, Lars, primary, Hein, Rebecca, primary, Makalic, Enes, primary, Schmidt, Daniel F., primary, Bui, Quang Minh, primary, Stone, Jennifer, primary, Flesch-Janys, Dieter, primary, Dahmen, Norbert, primary, Nevanlinna, Heli, primary, Aittomäki, Kristiina, primary, Blomqvist, Carl, primary, Hall, Per, primary, Czene, Kamila, primary, Irwanto, Astrid, primary, Liu, Jianjun, primary, Rahman, Nazneen, primary, Turnbull, Clare, primary, Dunning, Alison M., primary, Pharoah, Paul, primary, Waisfisz, Quinten, primary, Meijers-Heijboer, Hanne, primary, Uitterlinden, Andre G., primary, Rivadeneira, Fernando, primary, Nicolae, Dan, primary, Easton, Douglas F., primary, Cox, Nancy J., primary, and Whittemore, Alice S., primary

Published
2023
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49. Supplemental Tables S1-S3 from Determinants and Consequences of Arsenic Metabolism Efficiency among 4,794 Individuals: Demographics, Lifestyle, Genetics, and Toxicity

Author

Jansen, Rick J., primary, Argos, Maria, primary, Tong, Lin, primary, Li, Jiabei, primary, Rakibuz-Zaman, Muhammad, primary, Islam, Md. Tariqul, primary, Slavkovich, Vesna, primary, Ahmed, Alauddin, primary, Navas-Acien, Ana, primary, Parvez, Faruque, primary, Chen, Yu, primary, Gamble, Mary V., primary, Graziano, Joseph H., primary, Pierce, Brandon L., primary, and Ahsan, Habibul, primary

Published
2023
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50. OTTERS: a powerful TWAS framework leveraging summary-level reference data

Author

Dai, Qile, Zhou, Geyu, Zhao, Hongyu, Võsa, Urmo, Franke, Lude, Battle, Alexis, Teumer, Alexander, Lehtimäki, Terho, Raitakari, Olli T., Esko, Tõnu, Agbessi, Mawussé, Ahsan, Habibul, Alves, Isabel, Andiappan, Anand Kumar, Arindrarto, Wibowo, Awadalla, Philip, Beutner, Frank, Jan Bonder, Marc, Boomsma, Dorret I., Christiansen, Mark W., Claringbould, Annique, Deelen, Patrick, Favé, Marie-Julie, Frayling, Timothy, Gharib, Sina A., Gibson, Greg, Heijmans, Bastiaan T., Hemani, Gibran, Jansen, Rick, Kähönen, Mika, Kalnapenkis, Anette, Kasela, Silva, Kettunen, Johannes, Kim, Yungil, Kirsten, Holger, Kovacs, Peter, Krohn, Knut, Kronberg, Jaanika, Kukushkina, Viktorija, Kutalik, Zoltan, Lee, Bernett, Loeffler, Markus, Marigorta, Urko M., Mei, Hailang, Milani, Lili, Montgomery, Grant W., Müller-Nurasyid, Martina, Nauck, Matthias, Nivard, Michel G., Penninx, Brenda, Perola, Markus, Pervjakova, Natalia, Pierce, Brandon L., Powell, Joseph, Prokisch, Holger, Psaty, Bruce M., Ripatti, Samuli, Rotzschke, Olaf, Rüeger, Sina, Saha, Ashis, Scholz, Markus, Schramm, Katharina, Seppälä, Ilkka, Slagboom, Eline P., Stehouwer, Coen D. A., Stumvoll, Michael, Sullivan, Patrick, ‘t Hoen, Peter A. C., Thiery, Joachim, Tong, Lin, Tönjes, Anke, van Dongen, Jenny, van Iterson, Maarten, van Meurs, Joyce, Veldink, Jan H., Verlouw, Joost, Visscher, Peter M., Völker, Uwe, Westra, Harm-Jan, Wijmenga, Cisca, Yaghootkar, Hanieh, Yang, Jian, Zeng, Biao, Zhang, Futao, Epstein, Michael P., Yang, Jingjing, Dai, Qile, Zhou, Geyu, Zhao, Hongyu, Võsa, Urmo, Franke, Lude, Battle, Alexis, Teumer, Alexander, Lehtimäki, Terho, Raitakari, Olli T., Esko, Tõnu, Agbessi, Mawussé, Ahsan, Habibul, Alves, Isabel, Andiappan, Anand Kumar, Arindrarto, Wibowo, Awadalla, Philip, Beutner, Frank, Jan Bonder, Marc, Boomsma, Dorret I., Christiansen, Mark W., Claringbould, Annique, Deelen, Patrick, Favé, Marie-Julie, Frayling, Timothy, Gharib, Sina A., Gibson, Greg, Heijmans, Bastiaan T., Hemani, Gibran, Jansen, Rick, Kähönen, Mika, Kalnapenkis, Anette, Kasela, Silva, Kettunen, Johannes, Kim, Yungil, Kirsten, Holger, Kovacs, Peter, Krohn, Knut, Kronberg, Jaanika, Kukushkina, Viktorija, Kutalik, Zoltan, Lee, Bernett, Loeffler, Markus, Marigorta, Urko M., Mei, Hailang, Milani, Lili, Montgomery, Grant W., Müller-Nurasyid, Martina, Nauck, Matthias, Nivard, Michel G., Penninx, Brenda, Perola, Markus, Pervjakova, Natalia, Pierce, Brandon L., Powell, Joseph, Prokisch, Holger, Psaty, Bruce M., Ripatti, Samuli, Rotzschke, Olaf, Rüeger, Sina, Saha, Ashis, Scholz, Markus, Schramm, Katharina, Seppälä, Ilkka, Slagboom, Eline P., Stehouwer, Coen D. A., Stumvoll, Michael, Sullivan, Patrick, ‘t Hoen, Peter A. C., Thiery, Joachim, Tong, Lin, Tönjes, Anke, van Dongen, Jenny, van Iterson, Maarten, van Meurs, Joyce, Veldink, Jan H., Verlouw, Joost, Visscher, Peter M., Völker, Uwe, Westra, Harm-Jan, Wijmenga, Cisca, Yaghootkar, Hanieh, Yang, Jian, Zeng, Biao, Zhang, Futao, Epstein, Michael P., and Yang, Jingjing

Abstract

Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies., Godkänd;2023;Nivå 0;2023-04-06 (hanlid);Funder: for more funders see the article https://doi.org/10.1038/s41467-023-36862-w

Published
2023
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