Human Plasma Proteomic Profile of Clonal Hematopoiesis

doi:10.1101/2023.07.25.550557

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[Preprint]. 2024 Oct 31:2023.07.25.550557.

doi: 10.1101/2023.07.25.550557.

Human Plasma Proteomic Profile of Clonal Hematopoiesis

Zhi Yu^{1

2}, Amélie Vromman³, Ngoc Quynh H Nguyen^{4

5}, Art Schuermans^{1

2}, Thiago Rentz³, Shamsudheen K Vellarikkal³, Md Mesbah Uddin^{1

2}, Abhishek Niroula^{1

6

7}, Gabriel Griffin^{1

8

9}, Michael C Honigberg^{1

2

10}, Amy E Lin^{1

3

6}, Christopher J Gibson^{1

6}, Daniel H Katz^{11

12}, Usman Tahir^{10

11}, Shi Fang³, Sara Haidermota^{1

2}, Shriienidhie Ganesh^{1

2}, Tajmara Antoine^{1

2}, Joshua Weinstock^{13

14}, Thomas R Austin^{15

16}, Vasan S Ramachandran^{17

18}, Gina M Peloso¹⁹, Whitney Hornsby^{1

2}, Peter Ganz²⁰, JoAnn E Manson^{21

22}, Bernhard Haring^{23

24}, Charles L Kooperberg²⁵, Alexander P Reiner^{25

26}, Joshua C Bis^{14

27}, Bruce M Psaty^{15

16

26

27}, Yuan-I Min²⁸, Adolfo Correa²⁸, Leslie A Lange²⁹, Wendy S Post³⁰, Jerome I Rotter³¹, Stephen S Rich³², James G Wilson¹¹, Benjamin L Ebert^{1

6

10}, Bing Yu^{4

5}, Christie M Ballantyne³³, Josef Coresh³⁴, Vijay G Sankaran^{1

35

36

37}, Alexander G Bick³⁸, Siddhartha Jaiswal³⁹, Robert E Gerszten^{10

11}; NHLBI Trans-Omics for Precision Medicine; Peter Libby³, Rajat M Gupta³, Pradeep Natarajan^{1

2

10}

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Cardiovascular Division, Brigham and Women's Hospital Heart & Vascular Center, Boston, MA, USA.
⁴ Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
⁵ Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
⁶ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
⁷ Department of Laboratory Medicine, Lund University, Lund, Sweden.
⁸ Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
⁹ Department of Pathology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹⁰ Department of Medicine, Harvard Medical School, Boston, MA, USA.
¹¹ Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹² Department of Cardiovascular Medicine, Stanford University, Stanford, CA, USA.
¹³ Department of Genetics, Stanford University, Stanford, CA, USA.
¹⁴ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
¹⁵ Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.
¹⁶ Department of Epidemiology, University of Washington, Seattle, WA, USA.
¹⁷ Department of Medicine, School of Medicine, Boston University, Boston, MA, USA.
¹⁸ Framingham Heart Study, Framingham, MA, USA.
¹⁹ Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
²⁰ Division of Cardiology, Zuckerberg San Francisco General Hospital and Department of Medicine, University of California, San Francisco, CA, USA.
²¹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
²² Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
²³ Department of Medicine III, Saarland University Hospital, Homburg, Germany.
²⁴ Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
²⁵ Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
²⁶ Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA.
²⁷ Department of Medicine, University of Washington, Seattle, WA, USA.
²⁸ Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
²⁹ Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA.
³⁰ Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
³¹ The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
³² Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
³³ Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
³⁴ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
³⁵ Division of Hematology and Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
³⁶ Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
³⁷ Harvard Stem Cell Institute, Cambridge, MA, USA.
³⁸ Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
³⁹ Department of Pathology and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA.

PMID: 39554199
PMCID: PMC11565774
DOI: 10.1101/2023.07.25.550557

Human Plasma Proteomic Profile of Clonal Hematopoiesis

Zhi Yu et al. bioRxiv. 2024.

[Preprint]. 2024 Oct 31:2023.07.25.550557.

doi: 10.1101/2023.07.25.550557.

Authors

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
³ Cardiovascular Division, Brigham and Women's Hospital Heart & Vascular Center, Boston, MA, USA.
⁴ Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
⁵ Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
⁶ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
⁷ Department of Laboratory Medicine, Lund University, Lund, Sweden.
⁸ Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
⁹ Department of Pathology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹⁰ Department of Medicine, Harvard Medical School, Boston, MA, USA.
¹¹ Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹² Department of Cardiovascular Medicine, Stanford University, Stanford, CA, USA.
¹³ Department of Genetics, Stanford University, Stanford, CA, USA.
¹⁴ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
¹⁵ Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.
¹⁶ Department of Epidemiology, University of Washington, Seattle, WA, USA.
¹⁷ Department of Medicine, School of Medicine, Boston University, Boston, MA, USA.
¹⁸ Framingham Heart Study, Framingham, MA, USA.
¹⁹ Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
²⁰ Division of Cardiology, Zuckerberg San Francisco General Hospital and Department of Medicine, University of California, San Francisco, CA, USA.
²¹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
²² Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
²³ Department of Medicine III, Saarland University Hospital, Homburg, Germany.
²⁴ Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
²⁵ Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
²⁶ Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA.
²⁷ Department of Medicine, University of Washington, Seattle, WA, USA.
²⁸ Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
²⁹ Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA.
³⁰ Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
³¹ The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
³² Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
³³ Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
³⁴ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
³⁵ Division of Hematology and Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
³⁶ Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
³⁷ Harvard Stem Cell Institute, Cambridge, MA, USA.
³⁸ Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
³⁹ Department of Pathology and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA.

PMID: 39554199
PMCID: PMC11565774
DOI: 10.1101/2023.07.25.550557

Abstract

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.

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Figures

**Figure 1:. Scheme of the study design.**
We assessed the associations of CHIP and driver gene-specific CHIP subtypes (*DNMT3A, TET2, ASXL1*, and *JAK2*) with 1,148 circulating proteins measured by the SomaScan platform in 12,911 participants from TOPMed cohorts and 2,923 circulating proteins measured by Olink in 49,217 participants from UK Biobank. Causal relations for the associations were examined through genetic causal inference using Mendelian randomization and murine experiments contrasting plasma protein levels between *Tet2*^+/+ mice and control mice using ELISA. Pathway analyses were conducted using IPA tools. Finally, we investigated the associations between prevalent CAD and proteomics, identifying shared proteins associated with both CAD and any examined CHIP variable. CAD: Coronary artery disease. CHIP: Clonal hematopoiesis of indeterminate potential. TOPMed: ELISA: enzyme-linked immunosorbent assay. Trans-Omics for Precision Medicine. Parts of this figure have been created with BioRender.com.

**Figure 2.. CHIP and proteomics in TOPMed cohorts and UK Biobank.**
A, CHIP prevalence increased with donor age at the time of blood sampling. The center line represents the general additive model spline, and the shaded region is the 95% confidence interval (N_ARIC=8,188; N_CHS=1,689; N_JHS=2,058; N_MESA=976; N_UKB=49,217). B. More than 90% of individuals with CHIP had only one somatic CHIP driver mutation variant identified. C. Counts for four driver genes, *DNMT3A, TET2, ASXL1*, and *JAK2*, of CHIP mutations. D. CHIP clone size heterogeneity as measured by variant allele fraction by CHIP driver gene. Violin plot spanning minimum and maximum values. E. Platform and panel used for proteomics measurement by each cohort. CHIP: Clonal hematopoiesis of indeterminate potential.

**Figure 3.. Meta-analyzed associations between CHIP mutations and circulating proteome measured by SomaScan in TOPMed cohorts.**
A. All participants (N=12,911). B. Male participants only (N=5,616) vs. Female participants only (N=7,295). C. Black participants only (N=4,452) vs. White participants only (N=8,076). Proteins that are associated at FDR=0.05 level (for 4,560 testings) are labeled with the corresponding SomaScan targets and colored in blue, red, green, and orange, indicating significant associations with composite CHIP, *DNMT3A*, *TET2*, and *ASXL1*, respectively. Associations were assessed through linear regression models adjusting for age at sequencing, sex (if applicable), self-reported race (if applicable), batch (if applicable), type 2 diabetes status, smoker status, first ten principal components of genetic ancestry, and PEER factors (the number of PEER factors varies by cohorts based on the sizes of study populations: 50 for JHS, MESA, and CHS; 70 for ARIC AA; 120 for ARIC EA). AA: African Ancestry; ARIC: Atherosclerosis Risk in Communities; CHIP: Clonal hematopoiesis of indeterminate potential; CHS: Cardiovascular Heart Study; EA: European Ancestry; FDR: False discovery rate; JHS: Jackson Heart Study; MESA: Multi-Ethnic Study of Atherosclerosis; PEER: Probabilistic estimation of expression residuals.

**Figure 4.. Associations between CHIP mutations and circulating proteome measured by Olink in UK Biobank.**
A. All participants (N=41,022). B. Male participants only (N=18,831) vs. Female participants only (N=22,191). Proteins that are associated at FDR=0.005 level (for 11,668 testings) are labeled with the corresponding Olink targets and colored in blue, red, purple, and green, indicating significant associations with composite CHIP, *DNMT3A*, *TET2*, and *ASXL1*, respectively. Associations were assessed through linear regression models adjusting for age at sequencing, sex, self-reported British White ancestry (if applicable), type 2 diabetes status, current smoker status, first ten principal components of genetic ancestry, and 150 PEER factors. CHIP: Clonal hematopoiesis of indeterminate potential; FDR: False discovery rate; PEER: Probabilistic estimation of expression residuals.

Figure 5.. Estimation of bi-directional genetic causal effects between CHIP mutations and associated proteins. A. Proteins measured by SomaScan in TOPMed cohorts. B. Proteins measured by Olink in UK Biobank.
For both A and B, we examined CHIP mutations’ genetic causal effects on proteins and proteins’ genetic causal effects on CHIP mutations. Only CHIP mutation-protein pairs that were significantly associated at FDR=0.05 level were examined. CHIP mutations were limited to overall CHIP, *DNMT3A*, and *TET2* given the availability of GWAS. Some proteins were not examined as no valid instruments were available. Inverse-variance weighted Mendelian randomization approach were used for the analysis.

**Figure 6.. ELISA results of Tet2−/− and WT mice for selected plasma proteins whose level changes are associated with and causal by TET2 in human.**
A. A protein of which the causal role of *TET2* is supported in both SomaScan and Olink. B. A protein of which the causal role of *TET2* is supported in SomaScan only. C. Proteins of which the causal role of *TET2* is supported in Olink only. Flt3L: FMS-related tyrosine kinase 3 ligand; LCN: Lipocalin 2; MPO: Myeloperoxidase; WT: wild-type

**Figure 7.. Significantly enriched and modulated pathways were identified among proteins associated with CHIP driver genes.**
Significantly enriched and modulated pathways corresponding to CHIP-associated proteins were derived based on known genetic and molecular relationships using IPA. The input was the Z-scores of the associations between major CHIP driver genes, i.e., *DNMT3A*, *TET2*, and *ASXL1*, and proteins that were significant at the P=0.05 level. The listed pathways fulfill two criteria: (1) within the top 30 most significantly enriched pathways by input proteins based on IPA analysis (P<0.05) and (2) being significantly modulated, either inhibited or activated, based on IPA analysis (Z>1.96). The orange indicates predicted activation, and the blue indicates predicted inhibition. The darker the color, the stronger the modulation effect. A. Significantly modulated canonical pathways implicated among proteins associated with *DNMT3A*. B. Significantly modulated canonical pathways implicated among proteins associated with *TET2*. C. Significantly modulated canonical pathways implicated among proteins associated with *ASXL1*. CHIP: Clonal hematopoiesis of indeterminate potential; IPA: Ingenuity Pathway Analysis

**Figure 8.. Upset plot showing overlapped and non-overlapped associated proteins between CHIP variables and CAD.**
A total of 68 proteins were associated with both prevalent CAD and any of the CHIP variables (composite CHIP, *DNMT3A, TET2*, and *ASXL1*) at P=0.05 level. For both CHIP variables and CAD, associations were assessed through linear regression models adjusting for age at sequencing, sex, race, batch (if applicable), type 2 diabetes status, smoker status, and the first ten principal components of genetic ancestry. PEER factors (the number of PEER factors varies by cohorts based on the sizes of study populations: 50 for JHS, MESA, and CHS; 70 for ARIC AA; 120 for ARIC EA) were adjusted in CHIP analysis only but not CAD analysis; this is because around 1/3 of them were associated with CAD, but in general not with CHIP. AA: African ancestry; ARIC: Atherosclerosis Risk in Communities; CAD: Coronary artery disease; CHIP, clonal hematopoiesis of indeterminate potential; CHS: Cardiovascular Heart Study; EA: European ancestry; FDR: False discovery rate; JHS: Jackson Heart Study; MESA: Multi-Ethnic Study of Atherosclerosis; PEER: Probabilistic estimation of expression residuals.

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References

1. Steensma DP, et al. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood 126, 9–16 (2015). - PMC - PubMed
1. Xie M, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med 20, 1472–1478 (2014). - PMC - PubMed
1. Genovese G, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med 371, 2477–2487 (2014). - PMC - PubMed
1. Jaiswal S, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med 371, 2488–2498 (2014). - PMC - PubMed
1. Kim PG, et al. Dnmt3a-mutated clonal hematopoiesis promotes osteoporosis. J Exp Med 218, (2021). - PMC - PubMed

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[1] Steensma DP, et al. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood 126, 9–16 (2015). - PMC - PubMed

[2] Steensma DP, et al. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood 126, 9–16 (2015). - PMC - PubMed

[3] Xie M, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med 20, 1472–1478 (2014). - PMC - PubMed

[4] Xie M, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med 20, 1472–1478 (2014). - PMC - PubMed

[5] Genovese G, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med 371, 2477–2487 (2014). - PMC - PubMed

[6] Genovese G, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med 371, 2477–2487 (2014). - PMC - PubMed

[7] Jaiswal S, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med 371, 2488–2498 (2014). - PMC - PubMed

[8] Jaiswal S, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med 371, 2488–2498 (2014). - PMC - PubMed

[9] Kim PG, et al. Dnmt3a-mutated clonal hematopoiesis promotes osteoporosis. J Exp Med 218, (2021). - PMC - PubMed

[10] Kim PG, et al. Dnmt3a-mutated clonal hematopoiesis promotes osteoporosis. J Exp Med 218, (2021). - PMC - PubMed

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This is a preprint.

Human Plasma Proteomic Profile of Clonal Hematopoiesis

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Human Plasma Proteomic Profile of Clonal Hematopoiesis

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