Zhi Yu, Amélie Vromman, Ngoc Quynh H Nguyen, Art Schuermans, Thiago Rentz, Shamsudheen K Vellarikkal, Md Mesbah Uddin, Abhishek Niroula, Gabriel Griffin, Michael C Honigberg, Amy E Lin, Christopher J Gibson, Daniel H Katz, Usman Tahir, Shi Fang, Sara Haidermota, Shriienidhie Ganesh, Tajmara Antoine, Joshua Weinstock, Thomas R Austin, Vasan S Ramachandran, Gina M Peloso, Whitney Hornsby, Peter Ganz, JoAnn E Manson, Bernhard Haring, Charles L Kooperberg, Alexander P Reiner, Joshua C Bis, Bruce M Psaty, Yuan-I Min, Adolfo Correa, Leslie A Lange, Wendy S Post, Jerome I Rotter, Stephen S Rich, James G Wilson, Benjamin L Ebert, Bing Yu, Christie M Ballantyne, Josef Coresh, Vijay G Sankaran, Alexander G Bick, Siddhartha Jaiswal, Robert E Gerszten, Peter Libby, Rajat M Gupta, Pradeep Natarajan
{"title":"克隆性造血的人体血浆蛋白质组概况","authors":"Zhi Yu, Amélie Vromman, Ngoc Quynh H Nguyen, Art Schuermans, Thiago Rentz, Shamsudheen K Vellarikkal, Md Mesbah Uddin, Abhishek Niroula, Gabriel Griffin, Michael C Honigberg, Amy E Lin, Christopher J Gibson, Daniel H Katz, Usman Tahir, Shi Fang, Sara Haidermota, Shriienidhie Ganesh, Tajmara Antoine, Joshua Weinstock, Thomas R Austin, Vasan S Ramachandran, Gina M Peloso, Whitney Hornsby, Peter Ganz, JoAnn E Manson, Bernhard Haring, Charles L Kooperberg, Alexander P Reiner, Joshua C Bis, Bruce M Psaty, Yuan-I Min, Adolfo Correa, Leslie A Lange, Wendy S Post, Jerome I Rotter, Stephen S Rich, James G Wilson, Benjamin L Ebert, Bing Yu, Christie M Ballantyne, Josef Coresh, Vijay G Sankaran, Alexander G Bick, Siddhartha Jaiswal, Robert E Gerszten, Peter Libby, Rajat M Gupta, Pradeep Natarajan","doi":"10.1101/2023.07.25.550557","DOIUrl":null,"url":null,"abstract":"<p><p>Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes (<i>DNMT3A</i>, <i>TET2</i>, and <i>ASXL1</i>). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic <i>Tet2</i>-/- vs wild-type mice validation, disentangled causal proteomic perturbations from <i>TET2</i> CHIP. 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Human Plasma Proteomic Profile of Clonal Hematopoiesis.
Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes (DNMT3A, TET2, and ASXL1). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2-/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.
期刊介绍:
The Visual Computer publishes articles on all research fields of capturing, recognizing, modelling, analysing and generating shapes and images. It includes image understanding, machine learning for graphics and 3D fabrication.
3D Reconstruction
Computer Animation
Computational Fabrication
Computational Geometry
Computational Photography
Computer Vision for Computer Graphics
Data Compression for Graphics
Geometric Modelling
Geometric Processing
HCI and Computer Graphics
Human Modelling
Image Analysis
Image Based Rendering
Image Processing
Machine Learning for Graphics
Medical Imaging
Pattern Recognition
Physically Based Modelling
Illumination and Rendering Methods
Robotics and Vision
Saliency Methods
Scientific Visualization
Shape and Surface Modelling
Shape Analysis and Image Retrieval
Shape Matching
Sketch-based Modelling
Solid Modelling
Stylized rendering
Textures
Virtual and Augmented Reality
Visual Analytics
Volume Rendering
All papers are subject to thorough review and, if accepted, will be revised accordingly.
Original contributions, describing advances in the theory in the above mentioned fields as well as practical results and original applications, are invited.