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1. AACLiteNet: A Lightweight Model for Detection of Fine-Grained Abdominal Aortic Calcification

Author

Ilyas, Zaid, Saleem, Afsah, Suter, David, Reid, Siobhan, Schousboe, John, Leslie, William, Lewis, Joshua, and Gilani, Syed Zulqarnain

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, taking 17.9 million lives annually. Abdominal Aortic Calcification (AAC) is an established marker for CVD, which can be observed in lateral view Vertebral Fracture Assessment (VFA) scans, usually done for vertebral fracture detection. Early detection of AAC may help reduce the risk of developing clinical CVDs by encouraging preventive measures. Manual analysis of VFA scans for AAC measurement is time consuming and requires trained human assessors. Recently, efforts have been made to automate the process, however, the proposed models are either low in accuracy, lack granular level score prediction, or are too heavy in terms of inference time and memory footprint. Considering all these shortcomings of existing algorithms, we propose 'AACLiteNet', a lightweight deep learning model that predicts both cumulative and granular level AAC scores with high accuracy, and also has a low memory footprint, and computation cost (Floating Point Operations (FLOPs)). The AACLiteNet achieves a significantly improved one-vs-rest average accuracy of 85.94% as compared to the previous best 81.98%, with 19.88 times less computational cost and 2.26 times less memory footprint, making it implementable on portable computing devices., Comment: 10 pages including references

Published
2024

2. Can AI Understand Human Personality? -- Comparing Human Experts and AI Systems at Predicting Personality Correlations

Author

Schoenegger, Philipp, Greenberg, Spencer, Grishin, Alexander, Lewis, Joshua, and Caviola, Lucius

Subjects
Computer Science - Computers and Society, K.4.0, J.4
Abstract

We test the abilities of specialised deep neural networks like PersonalityMap as well as general LLMs like GPT-4o and Claude 3 Opus in understanding human personality. Specifically, we compare their ability to predict correlations between personality items to the abilities of lay people and academic experts. We find that when compared with individual humans, all AI models make better predictions than the vast majority of lay people and academic experts. However, when selecting the median prediction for each item, we find a different pattern: Experts and PersonalityMap outperform LLMs and lay people on most measures. Our results suggest that while frontier LLMs' are better than most individual humans at predicting correlations between personality items, specialised models like PersonalityMap continue to match or exceed expert human performance even on some outcome measures where LLMs underperform. This provides evidence both in favour of the general capabilities of large language models and in favour of the continued place for specialised models trained and deployed for specific domains., Comment: 45 pages, 6 figures

Published
2024

3. Exploring Multiscale Quantum Media: High-Precision Efficient Numerical Solution of the Fractional Schr\'odinger equation, Eigenfunctions with Physical Potentials, and Fractionally-Enhanced Quantum Tunneling

Author

Lewis, Joshua M. and Carr, Lincoln D.

Subjects
Quantum Physics
Abstract

Fractional evolution equations lack generally accessible and well-converged codes excepting anomalous diffusion. A particular equation of strong interest to the growing intersection of applied mathematics and quantum information science and technology is the fractional Schr\"odinger equation, which describes sub-and super-dispersive behavior of quantum wavefunctions induced by multiscale media. We derive a computationally efficient sixth-order split-step numerical method to converge the eigenfunctions of the FSE to arbitrary numerical precision for arbitrary fractional order derivative. We demonstrate applications of this code to machine precision for classic quantum problems such as the finite well and harmonic oscillator, which take surprising twists due to the non-local nature of the fractional derivative. For example, the evanescent wave tails in the finite well take a Mittag-Leffer-like form which decay much slower than the well-known exponential from integer-order derivative wave theories, enhancing penetration into the barrier and therefore quantum tunneling rates. We call this effect \emph{fractionally enhanced quantum tunneling}. This work includes an open source code for communities from quantum experimentalists to applied mathematicians to easily and efficiently explore the solutions of the fractional Schr\"odinger equation in a wide variety of practical potentials for potential realization in quantum tunneling enhancement and other quantum applications.

Published
2024

4. Determinants of mosaic chromosomal alteration fitness.

Author

Pershad, Yash, Mack, Taralynn, Poisner, Hannah, Jakubek, Yasminka, Stilp, Adrienne, Mitchell, Braxton, Lewis, Joshua, Boerwinkle, Eric, Loos, Ruth, Chami, Nathalie, Wang, Zhe, Barnes, Kathleen, Pankratz, Nathan, Fornage, Myriam, Redline, Susan, Psaty, Bruce, Bis, Joshua, Shojaie, Ali, Silverman, Edwin, Cho, Michael, Yun, Jeong, DeMeo, Dawn, Levy, Daniel, Johnson, Andrew, Mathias, Rasika, Taub, Margaret, Arnett, Donna, North, Kari, Raffield, Laura, Carson, April, Doyle, Margaret, Rich, Stephen, Guo, Xiuqing, Cox, Nancy, Roden, Dan, Franceschini, Nora, Desai, Pinkal, Reiner, Alex, Auer, Paul, Scheet, Paul, Jaiswal, Siddhartha, Weinstock, Joshua, Bick, Alexander, and Rotter, Jerome

Subjects
Humans, Mosaicism, Chromosome Aberrations, Clonal Hematopoiesis, Male, Female, Genome-Wide Association Study, Janus Kinase 2, Telomerase, Loss of Heterozygosity, Cross-Sectional Studies, Mutation, Middle Aged, Hematopoietic Stem Cells, Polymorphism, Single Nucleotide, Aged
Abstract

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

Published
2024

6. Impact of provision of abdominal aortic calcification results on fruit and vegetable intake: 12-week randomized phase 2 controlled trial

Author

Radavelli-Bagatini, Simone, Bondonno, Catherine P., Dalla Via, Jack, Sim, Marc, Gebre, Abadi K., Blekkenhorst, Lauren C., Connolly, Emma L., Bondonno, Nicola P., Schousboe, John T., Woodman, Richard J., Zhu, Kun, Mullin, Shelby, Szulc, Pawel, Jackson, Ben, Dimmock, James, Schlaich, Markus P., Cox, Kay L., Kiel, Douglas P., Lim, Wai H., Stanley, Mandy, Devine, Amanda, Thompson, Peter L., Williams, Evan J., Wood, Lisa G., Sim, Moira, Daly, Robin M., Hodgson, Jonathan M., and Lewis, Joshua R.

Published
2024
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7. Cruciferous vegetables lower blood pressure in adults with mildly elevated blood pressure in a randomized, controlled, crossover trial: the VEgetableS for vaScular hEaLth (VESSEL) study

Author

Connolly, Emma L., Liu, Alex H., Radavelli-Bagatini, Simone, Shafaei, Armaghan, Boyce, Mary C., Wood, Lisa G., McCahon, Lyn, Koch, Henrietta, Sim, Marc, Hill, Caroline R., Parmenter, Benjamin H., Bondonno, Nicola P., Devine, Amanda, Croft, Kevin D., Mithen, Richard, Gan, Seng Khee, Schultz, Carl J., Woodman, Richard J., Bondonno, Catherine P., Lewis, Joshua R., Hodgson, Jonathan M., and Blekkenhorst, Lauren C.

Published
2024
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8. Rab4A-directed endosome traffic shapes pro-inflammatory mitochondrial metabolism in T cells via mitophagy, CD98 expression, and kynurenine-sensitive mTOR activation

Author

Huang, Nick, Winans, Thomas, Wyman, Brandon, Oaks, Zachary, Faludi, Tamas, Choudhary, Gourav, Lai, Zhi-Wei, Lewis, Joshua, Beckford, Miguel, Duarte, Manuel, Krakko, Daniel, Patel, Akshay, Park, Joy, Caza, Tiffany, Sadeghzadeh, Mahsa, Morel, Laurence, Haas, Mark, Middleton, Frank, Banki, Katalin, and Perl, Andras

Published
2024
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9. SCOL: Supervised Contrastive Ordinal Loss for Abdominal Aortic Calcification Scoring on Vertebral Fracture Assessment Scans

Author

Saleem, Afsah, Ilyas, Zaid, Suter, David, Hassan, Ghulam Mubashar, Reid, Siobhan, Schousboe, John T., Prince, Richard, Leslie, William D., Lewis, Joshua R., and Gilani, Syed Zulqarnain

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Abdominal Aortic Calcification (AAC) is a known marker of asymptomatic Atherosclerotic Cardiovascular Diseases (ASCVDs). AAC can be observed on Vertebral Fracture Assessment (VFA) scans acquired using Dual-Energy X-ray Absorptiometry (DXA) machines. Thus, the automatic quantification of AAC on VFA DXA scans may be used to screen for CVD risks, allowing early interventions. In this research, we formulate the quantification of AAC as an ordinal regression problem. We propose a novel Supervised Contrastive Ordinal Loss (SCOL) by incorporating a label-dependent distance metric with existing supervised contrastive loss to leverage the ordinal information inherent in discrete AAC regression labels. We develop a Dual-encoder Contrastive Ordinal Learning (DCOL) framework that learns the contrastive ordinal representation at global and local levels to improve the feature separability and class diversity in latent space among the AAC-24 genera. We evaluate the performance of the proposed framework using two clinical VFA DXA scan datasets and compare our work with state-of-the-art methods. Furthermore, for predicted AAC scores, we provide a clinical analysis to predict the future risk of a Major Acute Cardiovascular Event (MACE). Our results demonstrate that this learning enhances inter-class separability and strengthens intra-class consistency, which results in predicting the high-risk AAC classes with high sensitivity and high accuracy., Comment: Accepted in conference MICCAI 2023

Published
2023

10. Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Author

Jakubek, Yasminka, Zhou, Ying, Stilp, Adrienne, Bacon, Jason, Wong, Justin, Ozcan, Zuhal, Arnett, Donna, Barnes, Kathleen, Bis, Joshua, Boerwinkle, Eric, Brody, Jennifer, Carson, April, Chasman, Daniel, Chen, Jiawen, Cho, Michael, Conomos, Matthew, Cox, Nancy, Doyle, Margaret, Fornage, Myriam, Guo, Xiuqing, Kardia, Sharon, Lewis, Joshua, Loos, Ruth, Ma, Xiaolong, Machiela, Mitchell, Mack, Taralynn, Mathias, Rasika, Mitchell, Braxton, Mychaleckyj, Josyf, North, Kari, Pankratz, Nathan, Peyser, Patricia, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Vasan, Ramachandran, Redline, Susan, Rich, Stephen, Silverman, Edwin, Smith, Jennifer, Smith, Aaron, Taub, Margaret, Taylor, Kent, Yun, Jeong, Li, Yun, Desai, Pinkal, Bick, Alexander, Reiner, Alexander, Scheet, Paul, Auer, Paul, and Rotter, Jerome

Subjects
Humans, Black People, Genome-Wide Association Study, Hispanic or Latino, Precision Medicine, Mosaicism, Genome, Human
Abstract

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

Published
2023

12. The genetic determinants of recurrent somatic mutations in 43,693 blood genomes

Author

Weinstock, Joshua S, Laurie, Cecelia A, Broome, Jai G, Taylor, Kent D, Guo, Xiuqing, Shuldiner, Alan R, O’Connell, Jeffrey R, Lewis, Joshua P, Boerwinkle, Eric, Barnes, Kathleen C, Chami, Nathalie, Kenny, Eimear E, Loos, Ruth JF, Fornage, Myriam, Redline, Susan, Cade, Brian E, Gilliland, Frank D, Chen, Zhanghua, Gauderman, W James, Kumar, Rajesh, Grammer, Leslie, Schleimer, Robert P, Psaty, Bruce M, Bis, Joshua C, Brody, Jennifer A, Silverman, Edwin K, Yun, Jeong H, Qiao, Dandi, Weiss, Scott T, Lasky-Su, Jessica, DeMeo, Dawn L, Palmer, Nicholette D, Freedman, Barry I, Bowden, Donald W, Cho, Michael H, Vasan, Ramachandran S, Johnson, Andrew D, Yanek, Lisa R, Becker, Lewis C, Kardia, Sharon, He, Jiang, Kaplan, Robert, Heckbert, Susan R, Smith, Nicholas L, Wiggins, Kerri L, Arnett, Donna K, Irvin, Marguerite R, Tiwari, Hemant, Correa, Adolfo, Raffield, Laura M, Gao, Yan, de Andrade, Mariza, Rotter, Jerome I, Rich, Stephen S, Manichaikul, Ani W, Konkle, Barbara A, Johnsen, Jill M, Wheeler, Marsha M, Custer, Brian S, Duggirala, Ravindranath, Curran, Joanne E, Blangero, John, Gui, Hongsheng, Xiao, Shujie, Williams, L Keoki, Meyers, Deborah A, Li, Xingnan, Ortega, Victor, McGarvey, Stephen, Gu, C Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M Benjamin, Darbar, Dawood, Roden, Dan, Albert, Christine, Kooperberg, Charles, Desai, Pinkal, Blackwell, Thomas W, Abecasis, Goncalo R, Smith, Albert V, Kang, Hyun M, Mathias, Rasika, Natarajan, Pradeep, Jaiswal, Siddhartha, Reiner, Alexander P, Bick, Alexander G, and Consortium, NHLBI Trans-Omics for Precision Medicine

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Lung, Genetic Testing, Clinical Research, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Humans, Middle Aged, Hematopoiesis, Mutation, Germ-Line Mutation, Mutation, Missense, Phenotype, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Published
2023

13. Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis.

Author

Weinstock, Joshua, Gopakumar, Jayakrishnan, Burugula, Bala, Uddin, Md, Jahn, Nikolaus, Belk, Julia, Bouzid, Hind, Daniel, Bence, Miao, Zhuang, Ly, Nghi, Mack, Taralynn, Luna, Sofia, Prothro, Katherine, Mitchell, Shaneice, Laurie, Cecelia, Broome, Jai, Taylor, Kent, Guo, Xiuqing, Sinner, Moritz, von Falkenhausen, Aenne, Kääb, Stefan, Shuldiner, Alan, OConnell, Jeffrey, Lewis, Joshua, Boerwinkle, Eric, Barnes, Kathleen, Chami, Nathalie, Kenny, Eimear, Loos, Ruth, Fornage, Myriam, Hou, Lifang, Lloyd-Jones, Donald, Redline, Susan, Cade, Brian, Psaty, Bruce, Bis, Joshua, Brody, Jennifer, Silverman, Edwin, Yun, Jeong, Qiao, Dandi, Palmer, Nicholette, Freedman, Barry, Bowden, Donald, Cho, Michael, DeMeo, Dawn, Vasan, Ramachandran, Yanek, Lisa, Becker, Lewis, Kardia, Sharon, Peyser, Patricia, He, Jiang, Rienstra, Michiel, Van der Harst, Pim, Kaplan, Robert, Heckbert, Susan, Smith, Nicholas, Wiggins, Kerri, Arnett, Donna, Irvin, Marguerite, Tiwari, Hemant, Cutler, Michael, Knight, Stacey, Muhlestein, J, Correa, Adolfo, Raffield, Laura, Gao, Yan, de Andrade, Mariza, Rotter, Jerome, Rich, Stephen, Tracy, Russell, Konkle, Barbara, Johnsen, Jill, Wheeler, Marsha, Smith, J, Melander, Olle, Nilsson, Peter, Custer, Brian, Duggirala, Ravindranath, Curran, Joanne, Blangero, John, McGarvey, Stephen, Williams, L, Xiao, Shujie, Yang, Mao, Gu, C, Chen, Yii-Der, Lee, Wen-Jane, Kane, John, Pullinger, Clive, Shoemaker, M, Darbar, Dawood, Roden, Dan, Albert, Christine, Kooperberg, Charles, Zhou, Ying, Manson, JoAnn, Desai, Pinkal, Johnson, Andrew, Mathias, Rasika, and Blackwell, Thomas

Subjects
Animals, Humans, Mice, Alleles, Clonal Hematopoiesis, Genome-Wide Association Study, Hematopoiesis, Hematopoietic Stem Cells, Mutation, Promoter Regions, Genetic
Abstract

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis1. These lesions are precursors for blood cancers2-6, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.

Published
2023

14. Whole-genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles

Author

Huffman, Jennifer E., Nicholas, Jayna, Hahn, Julie, Heath, Adam S., Raffield, Laura M., Yanek, Lisa R., Brody, Jennifer A., Thibord, Florian, Almasy, Laura, Bartz, Traci M., Bielak, Lawrence F., Bowler, Russell P., Carrasquilla, Germán D., Chasman, Daniel I., Chen, Ming-Huei, Emmert, David B., Ghanbari, Mohsen, Haessler, Jeffrey, Hottenga, Jouke-Jan, Kleber, Marcus E., Le, Ngoc-Quynh, Lee, Jiwon, Lewis, Joshua P., Li-Gao, Ruifang, Luan, Jian'an, Malmberg, Anni, Mangino, Massimo, Marioni, Riccardo E., Martinez-Perez, Angel, Pankratz, Nathan, Polasek, Ozren, Richmond, Anne, Rodriguez, Benjamin A. T., Rotter, Jerome I., Steri, Maristella, Suchon, Pierre, Trompet, Stella, Weiss, Stefan, Zare, Marjan, Auer, Paul, Cho, Michael H., Christofidou, Paraskevi, Davies, Gail, de Geus, Eco, Deleuze, Jean-François, Delgado, Graciela E., Ekunwe, Lynette, Faraday, Nauder, Gögele, Martin, Greinacher, Andreas, Gao, He, Howard, Tom, Joshi, Peter K., Kilpeläinen, Tuomas O., Lahti, Jari, Linneberg, Allan, Naitza, Silvia, Noordam, Raymond, Paüls-Vergés, Ferran, Rich, Stephen S., Rosendaal, Frits R., Rudan, Igor, Ryan, Kathleen A., Souto, Juan Carlos, van Rooij, Frank J. A., Wang, Heming, Zhao, Wei, Becker, Lewis C., Beswick, Andrew, Brown, Michael R., Cade, Brian E., Campbell, Harry, Cho, Kelly, Crapo, James D., Curran, Joanne E., de Maat, Moniek P. M., Doyle, Margaret, Elliott, Paul, Floyd, James S., Fuchsberger, Christian, Grarup, Niels, Guo, Xiuqing, Harris, Sarah E., Hou, Lifang, Kolcic, Ivana, Kooperberg, Charles, Menni, Cristina, Nauck, Matthias, O'Connell, Jeffrey R., Orrù, Valeria, Psaty, Bruce M., Räikkönen, Katri, Smith, Jennifer A., Soria, Jose Manuel, Stott, David J., van Hylckama Vlieg, Astrid, Watkins, Hugh, Willemsen, Gonneke, Wilson, Peter W. F., Ben-Shlomo, Yoav, Blangero, John, Boomsma, Dorret, Cox, Simon R., Dehghan, Abbas, Eriksson, Johan G., Fiorillo, Edoardo, Fornage, Myriam, Hansen, Torben, Hayward, Caroline, Ikram, M. Arfan, Jukema, J. Wouter, Kardia, Sharon L. R., Lange, Leslie A., März, Winfried, Mathias, Rasika A., Mitchell, Braxton D., Mook-Kanamori, Dennis O., Morange, Pierre-Emmanuel, Pedersen, Oluf, Pramstaller, Peter P., Redline, Susan, Reiner, Alexander, Ridker, Paul M., Silverman, Edwin K., Spector, Tim D., Völker, Uwe, Wareham, Nicholas J., Wilson, James F., Yao, Jie, Trégouët, David-Alexandre, Johnson, Andrew D., Wolberg, Alisa S., de Vries, Paul S., Sabater-Lleal, Maria, Morrison, Alanna C., and Smith, Nicholas L.

Published
2024
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15. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J. F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A, Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L, Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C, Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S, Pleiness, Jacob, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D. C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Hui-Heng Sheu, Wayne, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent D., Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T, Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Lindstrom, Sara, Wang, Lu, Smith, Erin N., Gordon, William, van Hylckama Vlieg, Astrid, Brody, Jennifer A., Pattee, Jack W., Haessler, Jeffrey, Brumpton, Ben M., Chasman, Daniel I., Suchon, Pierre, Chen, Ming-Huei, Turman, Constance, Germain, Marine, Wiggins, Kerri L., MacDonald, James, Braekkan, Sigrid K., Armasu, Sebastian M., Pankratz, Nathan, Jackson, Rabecca D., Nielsen, Jonas B., Giulianini, Franco, Puurunen, Marja K., Ibrahim, Manal, Heckbert, Susan R., Bammler, Theo K., Frazer, Kelly A., McCauley, Bryan M., Taylor, Kent, Pankow, James S., Reiner, Alexander P., Gabrielsen, Maiken E., Deleuze, Jean-François, O'Donnell, Chris J., Kim, Jihye, McKnight, Barbara, Kraft, Peter, Hansen, John-Bjarne, Rosendaal, Frits R., Heit, John A., Psaty, Bruce M., Tang, Weihong, Hveem, Kristian, Ridker, Paul M., Morange, Pierre-Emmanuel, Johnson, Andrew D., Kabrhel, Christopher, AlexandreTrégouët, David, Smith, Nicholas L., de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc-Quynh, Bebo, Allison, Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Lewis, Joshua P., Rodriguez, Benjamin A. T., Polasek, Ozren, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David-Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Davies, Gail, Delgado, Graciela E., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., Osburn, William O., O'Connell, Jeffrey R., Beswick, Andrew, Kolcic, Ivana, Souto, Juan Carlos, Becker, Lewis C., Hansen, Torben, Doyle, Margaret F., Harris, Sarah E., Moissl, Angela P., Rich, Stephen S., Campbell, Harry, Stott, David J., Soria, Jose Manuel, de Maat, Moniek P. M., Brody, Lawrence C., Auer, Paul L., Ben-Shlomo, Yoav, Hayward, Caroline, Mathias, Rasika A., Kilpeläinen, Tuomas O., Lange, Leslie A., Cox, Simon R., März, Winfried, Rotter, Jerome I., Mook-Kanamori, Dennis O., Wilson, James F., van der Harst, Pim, Jukema, J. Wouter, Ikram, M. Arfan, Desch, Karl C., Sabater-Lleal, Maria, Lowenstein, Charles J., and Morrison, Alanna C.

Published
2024
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16. 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

17. Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program

Author

Wheeler, Marsha M, Stilp, Adrienne M, Rao, Shuquan, Halldórsson, Bjarni V, Beyter, Doruk, Wen, Jia, Mihkaylova, Anna V, McHugh, Caitlin P, Lane, John, Jiang, Min-Zhi, Raffield, Laura M, Jun, Goo, Sedlazeck, Fritz J, Metcalf, Ginger, Yao, Yao, Bis, Joshua B, Chami, Nathalie, de Vries, Paul S, Desai, Pinkal, Floyd, James S, Gao, Yan, Kammers, Kai, Kim, Wonji, Moon, Jee-Young, Ratan, Aakrosh, Yanek, Lisa R, Almasy, Laura, Becker, Lewis C, Blangero, John, Cho, Michael H, Curran, Joanne E, Fornage, Myriam, Kaplan, Robert C, Lewis, Joshua P, Loos, Ruth JF, Mitchell, Braxton D, Morrison, Alanna C, Preuss, Michael, Psaty, Bruce M, Rich, Stephen S, Rotter, Jerome I, Tang, Hua, Tracy, Russell P, Boerwinkle, Eric, Abecasis, Goncalo R, Blackwell, Thomas W, Smith, Albert V, Johnson, Andrew D, Mathias, Rasika A, Nickerson, Deborah A, Conomos, Matthew P, Li, Yun, Þorsteinsdóttir, Unnur, Magnússon, Magnús K, Stefansson, Kari, Pankratz, Nathan D, Bauer, Daniel E, Auer, Paul L, and Reiner, Alex P

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Good Health and Well Being, Humans, Genome-Wide Association Study, Whole Genome Sequencing, Blood Cells
Abstract

Genome-wide association studies have identified thousands of single nucleotide variants and small indels that contribute to variation in hematologic traits. While structural variants are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of structural variants to quantitative blood cell trait variation is unknown. Here we utilized whole genome sequencing data in ancestrally diverse participants of the NHLBI Trans Omics for Precision Medicine program (N = 50,675) to detect structural variants associated with hematologic traits. Using single variant tests, we assessed the association of common and rare structural variants with red cell-, white cell-, and platelet-related quantitative traits and observed 21 independent signals (12 common and 9 rare) reaching genome-wide significance. The majority of these associations (N = 18) replicated in independent datasets. In genome-editing experiments, we provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

Published
2022

18. 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

19. Genome sequencing unveils a regulatory landscape of platelet reactivity.

Author

Keramati, Ali R, Chen, Ming-Huei, Rodriguez, Benjamin AT, Yanek, Lisa R, Bhan, Arunoday, Gaynor, Brady J, Ryan, Kathleen, Brody, Jennifer A, Zhong, Xue, Wei, Qiang, NHLBI Trans-Omics for Precision (TOPMed) Consortium, Kammers, Kai, Kanchan, Kanika, Iyer, Kruthika, Kowalski, Madeline H, Pitsillides, Achilleas N, Cupples, L Adrienne, Li, Bingshan, Schlaeger, Thorsten M, Shuldiner, Alan R, O'Connell, Jeffrey R, Ruczinski, Ingo, Mitchell, Braxton D, Faraday, Nauder, Taub, Margaret A, Becker, Lewis C, Lewis, Joshua P, Mathias, Rasika A, and Johnson, Andrew D

Subjects
NHLBI Trans-Omics for Precision (TOPMed) Consortium, Blood Platelets, K562 Cells, Humans, Thrombosis, GTP-Binding Proteins, RGS Proteins, Receptors, Cell Surface, Platelet Function Tests, Chromosome Mapping, Base Sequence, Platelet Aggregation, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, HEK293 Cells, Whole Genome Sequencing
Abstract

Platelet aggregation at the site of atherosclerotic vascular injury is the underlying pathophysiology of myocardial infarction and stroke. To build upon prior GWAS, here we report on 16 loci identified through a whole genome sequencing (WGS) approach in 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) participants deeply phenotyped for platelet aggregation. We identify the RGS18 locus, which encodes a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with expression quantitative trait loci (eQTL) signatures for RGS18 expression in platelets. Gene-based approaches implicate the SVEP1 gene, a known contributor of coronary artery disease risk. Sentinel variants at RGS18 and PEAR1 are associated with thrombosis risk and increased gastrointestinal bleeding risk, respectively. Our WGS findings add to previously identified GWAS loci, provide insights regarding the mechanism(s) by which genetics may influence cardiovascular disease risk, and underscore the importance of rare variant and regulatory approaches to identifying loci contributing to complex phenotypes.

Published
2021

20. 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

22. Allelic Heterogeneity at the CRP Locus Identified by Whole-Genome Sequencing in Multi-ancestry Cohorts

Author

Raffield, Laura M, Iyengar, Apoorva K, Wang, Biqi, Gaynor, Sheila M, Spracklen, Cassandra N, Zhong, Xue, Kowalski, Madeline H, Salimi, Shabnam, Polfus, Linda M, Benjamin, Emelia J, Bis, Joshua C, Bowler, Russell, Cade, Brian E, Choi, Won Jung, Comellas, Alejandro P, Correa, Adolfo, Cruz, Pedro, Doddapaneni, Harsha, Durda, Peter, Gogarten, Stephanie M, Jain, Deepti, Kim, Ryan W, Kral, Brian G, Lange, Leslie A, Larson, Martin G, Laurie, Cecelia, Lee, Jiwon, Lee, Seonwook, Lewis, Joshua P, Metcalf, Ginger A, Mitchell, Braxton D, Momin, Zeineen, Muzny, Donna M, Pankratz, Nathan, Park, Cheol Joo, Rich, Stephen S, Rotter, Jerome I, Ryan, Kathleen, Seo, Daekwan, Tracy, Russell P, Viaud-Martinez, Karine A, Yanek, Lisa R, Zhao, Lue Ping, Lin, Xihong, Li, Bingshan, Li, Yun, Dupuis, Josée, Reiner, Alexander P, Mohlke, Karen L, Auer, Paul L, Group, TOPMed Inflammation Working, and Consortium, NHLBI Trans-Omics for Precision Medicine

Subjects
Human Genome, Clinical Research, Biotechnology, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Asian People, Black People, C-Reactive Protein, Cohort Studies, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, White People, Whole Genome Sequencing, TOPMed Inflammation Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, c-reactive protein, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (∼38× coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (∼10% and ∼1% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23 mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97 mg/L and major allele homozygotes with mean CRP of 4.11 mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.

Published
2020

26. Disentangling the genetics of lean mass.

Author

Karasik, David, Zillikens, M, Hsu, Yi-Hsiang, Aghdassi, Ali, Akesson, Kristina, Amin, Najaf, Barroso, Inês, Bennett, David, Bertram, Lars, Bochud, Murielle, Borecki, Ingrid, Broer, Linda, Buchman, Aron, Byberg, Liisa, Campbell, Harry, Campos-Obando, Natalia, Cauley, Jane, Cawthon, Peggy, Chambers, John, Chen, Zhao, Cho, Nam, Choi, Hyung, Chou, Wen-Chi, Cummings, Steven, de Groot, Lisette, De Jager, Phillip, Demuth, Ilja, Diatchenko, Luda, Econs, Michael, Eiriksdottir, Gudny, Enneman, Anke, Eriksson, Joel, Eriksson, Johan, Estrada, Karol, Evans, Daniel, Feitosa, Mary, Fu, Mao, Gieger, Christian, Grallert, Harald, Gudnason, Vilmundur, Lenore, Launer, Hayward, Caroline, Hofman, Albert, Homuth, Georg, Huffman, Kim, Husted, Lise, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Johnson, Toby, Biffar, Reiner, Jordan, Joanne, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas, Klopp, Norman, Kloth, Jacqueline, Koller, Daniel, Kooner, Jaspal, Kraus, William, Kritchevsky, Stephen, Kutalik, Zoltán, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Langdahl, Bente, Lerch, Markus, Lewis, Joshua, Lill, Christina, Lind, Lars, Lindgren, Cecilia, Liu, Yongmei, Livshits, Gregory, Ljunggren, Östen, Loos, Ruth, Lorentzon, Mattias, Luan, Jianan, Luben, Robert, Malkin, Ida, McGuigan, Fiona, Medina-Gomez, Carolina, Meitinger, Thomas, Melhus, Håkan, Mellström, Dan, Michaëlsson, Karl, Mitchell, Braxton, Morris, Andrew, Mosekilde, Leif, Nethander, Maria, Newman, Anne, OConnell, Jeffery, Oostra, Ben, Orwoll, Eric, Palotie, Aarno, Peacock, Munro, Perola, Markus, and Peters, Annette

Subjects
ADAMTS Proteins, Absorptiometry, Photon, Adipose Tissue, Adolescent, Adult, Aged, Aged, 80 and over, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Composition, Body Fluid Compartments, Electric Impedance, Extracellular Matrix Proteins, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Muscle, Skeletal, Phenotype, Polymorphism, Single Nucleotide, RNA-Binding Proteins, Receptor, Melanocortin, Type 4, Versicans, White People, Young Adult
Abstract

BACKGROUND: Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. OBJECTIVES: To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. METHODS: We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). RESULTS: Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as sumo wrestler loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed body builder loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in body builder loci were associated with metabolic protection. CONCLUSIONS: In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass.

Published
2019

27. Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies

Author

Chen, Han, Huffman, Jennifer E, Brody, Jennifer A, Wang, Chaolong, Lee, Seunggeun, Li, Zilin, Gogarten, Stephanie M, Sofer, Tamar, Bielak, Lawrence F, Bis, Joshua C, Blangero, John, Bowler, Russell P, Cade, Brian E, Cho, Michael H, Correa, Adolfo, Curran, Joanne E, de Vries, Paul S, Glahn, David C, Guo, Xiuqing, Johnson, Andrew D, Kardia, Sharon, Kooperberg, Charles, Lewis, Joshua P, Liu, Xiaoming, Mathias, Rasika A, Mitchell, Braxton D, O’Connell, Jeffrey R, Peyser, Patricia A, Post, Wendy S, Reiner, Alex P, Rich, Stephen S, Rotter, Jerome I, Silverman, Edwin K, Smith, Jennifer A, Vasan, Ramachandran S, Wilson, James G, Yanek, Lisa R, Consortium, NHLBI Trans-Omics for Precision Medicine, Group, TOPMed Hematology and Hemostasis Working, Redline, Susan, Smith, Nicholas L, Boerwinkle, Eric, Borecki, Ingrid B, Cupples, L Adrienne, Laurie, Cathy C, Morrison, Alanna C, Rice, Kenneth M, and Lin, Xihong

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Biotechnology, Aetiology, 2.5 Research design and methodologies (aetiology), Generic health relevance, Good Health and Well Being, Chromosomes, Human, Pair 4, Cloud Computing, Female, Fibrinogen, Genetic Association Studies, Genetics, Population, Humans, Male, Models, Genetic, National Heart, Lung, and Blood Institute (U.S.), Precision Medicine, Research Design, Time Factors, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed, generalized linear mixed model, population structure, rare variants, relatedness, variant set association test, whole-genome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

With advances in whole-genome sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and sequence kernel association test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-set mixed model association tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program. SMMATs share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be fit only once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMATs correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

Published
2019

29. Randomized evaluation of the loss‐of‐function carboxylesterase 1 (CES1) G143E variant on clopidogrel and ticagrelor pharmacodynamics.

Author

Lewis, Joshua P., Ryan, Kathleen A., Streeten, Elizabeth A., Whitlatch, Hilary B., Daue, Melanie, Tanner, Keith, Perry, James A., O'Connell, Jeffrey R., Shuldiner, Alan R., and Mitchell, Braxton D.

Subjects
*MEDICAL care, *CORONARY artery disease, *MEDICAL care standards, *ARACHIDONIC acid, *MISSENSE mutation, *BLOOD platelet aggregation
Abstract

Antiplatelet therapy with a P2Y12 receptor inhibitor, in combination with aspirin, is standard of care for medical management of patients with coronary artery disease, and flexibility in prescribing options among these medications offers great potential for individualizing patient care. Previously, we showed that a loss‐of‐function missense mutation (G143E) in carboxylesterase 1 (CES1), the primary enzyme responsible for clopidogrel degradation, significantly impacts on‐clopidogrel platelet aggregation and recurrent cardiovascular event risk. In the current investigation, we conducted a prospective randomized crossover study of clopidogrel (75 mg/day for 7 days) and ticagrelor (180 mg/day for 7 days) in 50 individuals stratified by CES1 G143E genotype (N = 34 143GG and 16 143GE) to determine the effect of drug choice on inhibition of platelet aggregation (IPA). Consistent with prior reports, we observed strong association between G143E and adenosine diphosphate‐stimulated platelet aggregation following clopidogrel administration (IPA = 71.6 vs. 48.0% in 143E‐allele carriers vs. non‐carriers, respectively, p = 3.8 × 10−5). Similar significant effects on platelet aggregation were also noted between 143E‐allele carriers versus non‐carriers in response to stimulation with arachidonic acid (45.8 vs. 25.8%, p = 0.04), epinephrine (44.4 vs. 18.8%, p = 0.03), and collagen (5 μg/mL, 25.8 vs. 11.4%, p = 3.7 × 10−3). In contrast, no relationship between CES1 G143E and IPA was observed following ticagrelor administration regardless of the platelet agonist used. Collectively, these data suggest that on‐clopidogrel platelet aggregation is substantially modified by CES1 G143E genotype, that this variant does not modify ticagrelor pharmacodynamics, and that more consistent inhibition of platelet aggregation may be achieved by using ticagrelor in patients who carry clopidogrel response‐modifying alleles in CES1. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Ecological Chokepoints

Author

Lewis, Joshua

Abstract

What does keeping the lower Mississippi River open for shipping have to do with coastal land loss, regional ecological change, and a pile of rocks? Joshua Lewis explores the relationship between transportation and ecological chokepoints in Louisiana.

Published
2018

35. Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Author

Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics
Abstract

A correction to this article has been published and is linked from the HTML version of this article.

Published
2017

36. Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology

Author

Brody, Jennifer A, Morrison, Alanna C, Bis, Joshua C, O'Connell, Jeffrey R, Brown, Michael R, Huffman, Jennifer E, Ames, Darren C, Carroll, Andrew, Conomos, Matthew P, Gabriel, Stacey, Gibbs, Richard A, Gogarten, Stephanie M, Gupta, Namrata, Jaquish, Cashell E, Johnson, Andrew D, Lewis, Joshua P, Liu, Xiaoming, Manning, Alisa K, Papanicolaou, George J, Pitsillides, Achilleas N, Rice, Kenneth M, Salerno, William, Sitlani, Colleen M, Smith, Nicholas L, Heckbert, Susan R, Laurie, Cathy C, Mitchell, Braxton D, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Wilson, James G, Boerwinkle, Eric, Psaty, Bruce M, and Cupples, L Adrienne

Subjects
Biological Sciences, Genetics, Biotechnology, Networking and Information Technology R&D (NITRD), Lung, Human Genome, 2.5 Research design and methodologies (aetiology), Aetiology, Generic health relevance, Good Health and Well Being, Big Data, Fibrinogen, Genetics, Population, Genome, Humans, Information Dissemination, Mobile Applications, Molecular Epidemiology, Regression Analysis, Software, Workflow, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, TOPMed Hematology and Hemostasis Working Group, CHARGE Analysis and Bioinformatics Working Group, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations.

Published
2017

37. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Author

Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei

Subjects
Humans, Thinness, 17-Hydroxysteroid Dehydrogenases, Aldehyde Oxidoreductases, Extracellular Matrix Proteins, Body Composition, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Elements, Transcriptional, Versicans, Genome-Wide Association Study, Insulin Receptor Substrate Proteins, ADAMTS Proteins, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Human Genome, Genetics, 1.1 Normal biological development and functioning
Abstract

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p

Published
2017

39. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

Gezonde Vaten, Circulatory Health, de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc Quynh, Bebo, Allison, Brody, Jennifer A., Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Jain, Deepti, Lewis, Joshua P., Rodriguez, Benjamin A.T., Pankratz, Nathan, Taylor, Kent D., Polasek, Ozren, Chen, Ming Huei, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Ekunwe, Lynette, Davies, Gail, Delgado, Graciela E., Suchon, Pierre, Guo, Xiuqing, Rosendaal, Frits R., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., van der Harst, Pim, Trans-Omics for Precision Medicine (TOPMed) program, the INVENT consortium, Gezonde Vaten, Circulatory Health, de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc Quynh, Bebo, Allison, Brody, Jennifer A., Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Jain, Deepti, Lewis, Joshua P., Rodriguez, Benjamin A.T., Pankratz, Nathan, Taylor, Kent D., Polasek, Ozren, Chen, Ming Huei, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Ekunwe, Lynette, Davies, Gail, Delgado, Graciela E., Suchon, Pierre, Guo, Xiuqing, Rosendaal, Frits R., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., van der Harst, Pim, Trans-Omics for Precision Medicine (TOPMed) program, and the INVENT consortium

Published
2024

40. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc Quynh, Bebo, Allison, Brody, Jennifer A., Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Jain, Deepti, Lewis, Joshua P., Rodriguez, Benjamin A.T., Pankratz, Nathan, Taylor, Kent D., Polasek, Ozren, Chen, Ming Huei, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Ekunwe, Lynette, Davies, Gail, Delgado, Graciela E., Hansen, Torben, Chen, Wei Min, Jackson, Rebecca, Liu, Yu, Loos, Ruth J.F., Rao, D. C., Wang, Lu, Nielsen, Jonas B., Kilpeläinen, Tuomas O., de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc Quynh, Bebo, Allison, Brody, Jennifer A., Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Jain, Deepti, Lewis, Joshua P., Rodriguez, Benjamin A.T., Pankratz, Nathan, Taylor, Kent D., Polasek, Ozren, Chen, Ming Huei, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Ekunwe, Lynette, Davies, Gail, Delgado, Graciela E., Hansen, Torben, Chen, Wei Min, Jackson, Rebecca, Liu, Yu, Loos, Ruth J.F., Rao, D. C., Wang, Lu, Nielsen, Jonas B., and Kilpeläinen, Tuomas O.

Abstract

Coagulation factor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are critical to coagulation and platelet aggregation. We leveraged whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program along with TOPMed-based imputation of genotypes in additional samples to identify genetic associations with circulating FVIII and VWF levels in a single-variant meta-analysis, including up to 45 289 participants. Gene-based aggregate tests were implemented in TOPMed. We identified 3 candidate causal genes and tested their functional effect on FVIII release from human liver endothelial cells (HLECs) and VWF release from human umbilical vein endothelial cells. Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P < 5 × 10−9) at 7 new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and 1 for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multiphenotype analysis of FVIII and VWF identified another 3 new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, whereas silencing of B3GNT2, CD36, and PDIA3 decreased release of VWF by HVECs. Mendelian randomization supports causal association of higher FVIII and VWF with increased risk of thrombotic outcomes. Seven new loci were identified for FVIII and 1 for VWF, with evidence supporting causal associations of FVIII and VWF with thrombotic outcomes. B3GNT2, CD36, and PDIA3 modulate the release of FVIII and/or VWF in vitro., Coagulation factor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are critical to coagulation and platelet aggregation. We leveraged whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program along with TOPMed-based imputation of genotypes in additional samples to identify genetic associations with circulating FVIII and VWF levels in a single-variant meta-analysis, including up to 45 289 participants. Gene-based aggregate tests were implemented in TOPMed. We identified 3 candidate causal genes and tested their functional effect on FVIII release from human liver endothelial cells (HLECs) and VWF release from human umbilical vein endothelial cells. Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P < 5 × 10−9) at 7 new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and 1 for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multiphenotype analysis of FVIII and VWF identified another 3 new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, whereas silencing of B3GNT2, CD36, and PDIA3 decreased release of VWF by HVECs. Mendelian randomization supports causal association of higher FVIII and VWF with increased risk of thrombotic outcomes. Seven new loci were identified for FVIII and 1 for VWF, with evidence supporting causal associations of FVIII and VWF with thrombotic outcomes. B3GNT2, CD36, and PDIA3 modulate the release of FVIII and/or VWF in vitro.

Published
2024

41. A genetic association study of circulating coagulation Factor VIII and von Willebrand Factor levels

Author

de Vries, Paul S., primary, Reventun, Paula, additional, Brown, Michael R, additional, Heath, Adam S, additional, Huffman, Jennifer E., additional, Le, Ngoc-Quynh, additional, Bebo, Allison, additional, Brody, Jennifer A, additional, Temprano-Sagrera, Gerard, additional, Raffield, Laura M, additional, Ozel, Ayse Bilge, additional, Thibord, Florian, additional, Jain, Deepti, additional, Lewis, Joshua P, additional, Rodriguez, Benjamin A.T., additional, Pankratz, Nathan, additional, Taylor, Kent D, additional, Polasek, Ozren, additional, Chen, Ming-Huei, additional, Yanek, Lisa R, additional, Carrasquilla, German, additional, Marioni, Riccardo, additional, Kleber, Marcus E, additional, Trégouët, David-Alexandre, additional, Yao, Jie, additional, Li-Gao, Ruifang, additional, Joshi, Peter K, additional, Trompet, Stella, additional, Martinez-Perez, Angel, additional, Ghanbari, Mohsen, additional, Howard, Tom E., additional, Reiner, Alex P, additional, Arvanitis, Marios, additional, Ryan, Kathleen A, additional, Bartz, Traci M, additional, Rudan, Igor, additional, Faraday, Nauder, additional, Linneberg, Allan, additional, Ekunwe, Lynette, additional, Davies, Gail, additional, Delgado, Graciela E, additional, Suchon, Pierre, additional, Guo, Xiuqing, additional, Rosendaal, Frits R., additional, Klaric, Lucija, additional, Noordam, Raymond, additional, van Rooij, Frank J.A., additional, Curran, Joanne, additional, Wheeler, Marsha Maria, additional, Osburn, William O, additional, O'Connell, Jeffrey R, additional, Boerwinkle, Eric, additional, Beswick, Andrew, additional, Psaty, Bruce M., additional, Kolcic, Ivana, additional, Souto, Juan Carlos Carlos, additional, Becker, Lewis, additional, Hansen, Torben, additional, Doyle, Margaret F., additional, Harris, Sarah, additional, Moissl, Angela Patricia, additional, Deleuze, Jean-François, additional, Rich, Stephen S, additional, van Hylckama Vlieg, Astrid, additional, Campbell, Harry, additional, Stott, David, additional, Soria, Jose Manuel, additional, de Maat, Moniek P.M., additional, Almasy, Laura, additional, Brody, Lawrence C., additional, Auer, Paul, additional, Mitchell, Braxton D, additional, Ben-Shlomo, Yoav, additional, Fornage, Myriam, additional, Hayward, Caroline, additional, Mathias, Rasika, additional, Kilpeläinen, Tuomas O, additional, Lange, Leslie, additional, Cox, Simon R, additional, Maerz, Winfried, additional, Morange, Pierre-Emmanuel, additional, Rotter, Jerome I, additional, Mook-Kanamori, Dennis O, additional, Wilson, James, additional, van der Harst, Pim, additional, Jukema, Johan Wouter W., additional, Ikram, Mohammad Arfan, additional, Blangero, John, additional, Kooperberg, Charles, additional, Desch, Karl, additional, Johnson, Andrew D., additional, Sabater-Lleal, Maria, additional, Lowenstein, Charles, additional, Smith, Nicholas L., additional, and Morrison, Alanna, additional

Published
2024
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42. Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci

Author

Walford, Geoffrey A, Gustafsson, Stefan, Rybin, Denis, Stančáková, Alena, Chen, Han, Liu, Ching-Ti, Hong, Jaeyoung, Jensen, Richard A, Rice, Ken, Morris, Andrew P, Mägi, Reedik, Tönjes, Anke, Prokopenko, Inga, Kleber, Marcus E, Delgado, Graciela, Silbernagel, Günther, Jackson, Anne U, Appel, Emil V, Grarup, Niels, Lewis, Joshua P, Montasser, May E, Landenvall, Claes, Staiger, Harald, Luan, Jian’an, Frayling, Timothy M, Weedon, Michael N, Xie, Weijia, Morcillo, Sonsoles, Martínez-Larrad, María Teresa, Biggs, Mary L, Chen, Yii-Der Ida, Corbaton-Anchuelo, Arturo, Færch, Kristine, Gómez-Zumaquero, Juan Miguel, Goodarzi, Mark O, Kizer, Jorge R, Koistinen, Heikki A, Leong, Aaron, Lind, Lars, Lindgren, Cecilia, Machicao, Fausto, Manning, Alisa K, Martín-Núñez, Gracia María, Rojo-Martínez, Gemma, Rotter, Jerome I, Siscovick, David S, Zmuda, Joseph M, Zhang, Zhongyang, Serrano-Rios, Manuel, Smith, Ulf, Soriguer, Federico, Hansen, Torben, Jørgensen, Torben J, Linnenberg, Allan, Pedersen, Oluf, Walker, Mark, Langenberg, Claudia, Scott, Robert A, Wareham, Nicholas J, Fritsche, Andreas, Häring, Hans-Ulrich, Stefan, Norbert, Groop, Leif, O’Connell, Jeff R, Boehnke, Michael, Bergman, Richard N, Collins, Francis S, Mohlke, Karen L, Tuomilehto, Jaakko, März, Winfried, Kovacs, Peter, Stumvoll, Michael, Psaty, Bruce M, Kuusisto, Johanna, Laakso, Markku, Meigs, James B, Dupuis, Josée, Ingelsson, Erik, and Florez, Jose C

Subjects
Biomedical and Clinical Sciences, Genetics, Prevention, Human Genome, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Chemokines, CC, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Insulin Receptor Substrate Proteins, Insulin Resistance, Male, Polymorphism, Single Nucleotide, Proto-Oncogene Proteins c-bcl-2, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.

Published
2016

48. Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

Author

Jones, Garan, Trajanoska, Katerina, Santanasto, Adam J., Stringa, Najada, Kuo, Chia-Ling, Atkins, Janice L., Lewis, Joshua R., Duong, ThuyVy, Hong, Shengjun, Biggs, Mary L., Luan, Jian’an, Sarnowski, Chloe, Lunetta, Kathryn L., Tanaka, Toshiko, Wojczynski, Mary K., Cvejkus, Ryan, Nethander, Maria, Ghasemi, Sahar, Yang, Jingyun, Zillikens, M. Carola, Walter, Stefan, Sicinski, Kamil, Kague, Erika, Ackert-Bicknell, Cheryl L., Arking, Dan E., Windham, B. Gwen, Boerwinkle, Eric, Grove, Megan L., Graff, Misa, Spira, Dominik, Demuth, Ilja, van der Velde, Nathalie, de Groot, Lisette C. P. G. M., Psaty, Bruce M., Odden, Michelle C., Fohner, Alison E., Langenberg, Claudia, Wareham, Nicholas J., Bandinelli, Stefania, van Schoor, Natasja M., Huisman, Martijn, Tan, Qihua, Zmuda, Joseph, Mellström, Dan, Karlsson, Magnus, Bennett, David A., Buchman, Aron S., De Jager, Philip L., Uitterlinden, Andre G., Völker, Uwe, Kocher, Thomas, Teumer, Alexander, Rodriguéz-Mañas, Leocadio, García, Francisco J., Carnicero, José A., Herd, Pamela, Bertram, Lars, Ohlsson, Claes, Murabito, Joanne M., Melzer, David, Kuchel, George A., Ferrucci, Luigi, Karasik, David, Rivadeneira, Fernando, Kiel, Douglas P., and Pilling, Luke C.

Published
2021
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