MYD88 mutations in clonal hematopoiesis promote inflammation and hematopoietic stem cell expansion

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Philbrook , Emma Uible , View ORCID Profile Lynn Lee , Kwangmin Choi , Puneet Agarwal , Courtnee A. Clough , Pravin Patel , Kathryn A. Wikenheiser-Brokamp , Kathleen Hueneman , Hans Christian Reinhardt , Tzyy-Jye Doong , Arletta Lozanski , Gerard Lozanski , Tamanna Haque , Erin Hertlein , John C. Byrd , View ORCID Profile Daniel T. Starczynowski doi: https://doi.org/10.1101/2025.06.19.660202 Jennifer Yeung 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sophia Y. Philbrook 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emma Uible 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lynn Lee 2 Division of Oncology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lynn Lee Kwangmin Choi 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Puneet Agarwal 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Courtnee A. Clough 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Pravin Patel 3 Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania , Philadelphia, PA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kathryn A. Wikenheiser-Brokamp 4 Division of Pathology and Laboratory Medicine, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kathleen Hueneman 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hans Christian Reinhardt 5 Department of Hematology and Stem Cell Transplantation, West German Cancer Center, Partner Site Essen, University Hospital Essen , Essen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tzyy-Jye Doong 6 Division of Hematology, Department of Internal Medicine, The Ohio State University , Columbus, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Arletta Lozanski 6 Division of Hematology, Department of Internal Medicine, The Ohio State University , Columbus, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gerard Lozanski 7 Department of Pathology, The Ohio State University , Columbus, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tamanna Haque 8 Division of Leukemia, Memorial Sloan Kettering Cancer Center , New York, NY Find this author on Google Scholar Find this author on PubMed Search for this author on this site Erin Hertlein 9 Department of Internal Medicine, University of Cincinnati , Cincinnati, OH 10 University of Cincinnati Cancer Center , Cincinnati, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site John C. Byrd 9 Department of Internal Medicine, University of Cincinnati , Cincinnati, OH 10 University of Cincinnati Cancer Center , Cincinnati, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: byrd2jc{at}ucmail.uc.edu Daniel.Starczynowski{at}cchmc.org Daniel T. Starczynowski 1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital , Cincinnati, OH 10 University of Cincinnati Cancer Center , Cincinnati, USA 11 Department of Cancer Biology, University of Cincinnati , Cincinnati, OH 12 Department of Pediatrics, University of Cincinnati , Cincinnati, OH Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Daniel T. Starczynowski For correspondence: byrd2jc{at}ucmail.uc.edu Daniel.Starczynowski{at}cchmc.org Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by expansion of mutant hematopoietic stem and progenitor cells (HSPCs) and an increased risk of chronic diseases and cancers. While mutations in DNMT3A , TET2 , and ASXL1 are common in CHIP, the contribution of less frequent gene mutations is not well understood. Here, we report MYD88 mutations, including lymphoma-associated and novel variants in blood cells of the general population and newly diagnosed solid cancer patients. MYD88 CHIP mutations in HSPCs activate NF-κB, indicating a gain-of-function activity. Modeling MYD88 CHIP in mice, Myd88 L252P (equivalent of human L265P) expression resulted in a competitive fitness advantage of HSPCs. Myd88 L252P HSPCs exhibit a myeloid cell bias and inflammation, leading to hematologic disease. Single-cell RNA sequencing indicated that Myd88 L252P expands distinct hematopoietic and immune cell clusters and activates immune-related pathways in HSPCs. An IRAK1/4 inhibitor suppressed MYD88-dependent NF-κB activation and reversed Myd88 L252P cell expansion. Overall, MYD88 mutations contribute to CHIP by inducing innate immune pathways in HSPCs and inflammatory disease. Introduction Clonal hematopoiesis is an age-associated process in which the hematopoietic system is disproportionately derived from a single hematopoietic stem cell (HSC) clone 1 . This phenomenon, known as clonal hematopoiesis of indeterminate potential (CHIP), is defined by somatic mutations in known blood cancer-associated genes with a variant allele fraction (VAF) of 2% or greater in individuals without evidence of hematologic malignancy 1 , 2 . Individuals with CHIP are at an increased risk of developing a variety of age-related chronic diseases, including hematologic malignancies, such as myelodysplastic syndromes (MDS) or acute myeloid leukemia (AML), as well as cardiovascular diseases 1 , 2 . Depending on the cancer-associated mutation, certain individuals could also be at risk for lymphoid malignancies. CHIP-associated mutations confer a selective advantage, leading to an expanded clone. In the context of CHIP, mutations in a few genes, such as DNMT3A, TET2 , and ASXL1 , account for the majority of cases 3 – 6 . Less frequently mutated, but still prevalent genes, such as TP53 and U2AF1 , are associated with a higher risk of malignant transformation and adverse outcome 7 , 8 . This suggests that certain CHIP mutations confer varying risks of disease progression. Moreover, other genes, though less frequently mutated, collectively contribute to a significant proportion of CHIP cases 9 . The contribution and pathogenesis of these less common, but highly prevalent, gene mutations to CHIP remain poorly understood. Dysregulated innate immune and inflammatory signaling, and alterations in the immune microenvironment, are critical mechanisms underlying clonal hematopoiesis 10 . Low-grade, chronic inflammation and other microenvironmental factors favor the expansion of HSCs with CHIP mutations over normal HSCs 10 . HSPCs with CHIP-related mutations also exhibit differential activation of innate immune and inflammatory pathways compared to age-matched HSPCs 10 – 13 . This dysregulation in immune-related pathways further contributes to the selective advantage of mutant HSCs and immune effector cells in CHIP. The Toll-like receptor (TLR) and Interleukin 1 receptor (IL1R) superfamily plays a key role in CHIP 4 , 10 . Upon activation, the Myeloid Differentiation Primary Response 88 (MYD88) adaptor, recruits IL-1 receptor-associated kinases (IRAKs) and TRAF6, leading to the activation of NF-κB and other transcription factors. Dysregulation of IRAK1, IRAK4, and TRAF6 has been implicated in the competitive fitness advantage of CHIP mutant HSPCs and altered immune cell activation 14 – 16 . TET2 mutations in CHIP are associated with clonal expansion of HSPCs and increased inflammatory signaling via IRAK-TRAF6, which can drive the development of atherosclerosis 6 . Similar effects have been observed with TNFα-induced activation of NF-κB and the expansion of DNMT3a -mutant HSPCs. 17 , 18 Moreover, patients with solid tumors who harbor tumor-infiltrating CHIP mutant cells have a higher risk of tumor recurrence and mortality compared to patients without CHIP, likely due to increased local inflammation 19 . To mitigate this inflammatory environment, inhibition of IL-1β has been shown to suppress mutant CHIP cells, partially restore normal hematopoiesis, and reduce cardiovascular disease in mouse models and early-stage clinical trials 20 , 21 . Mutations in DNMT3a, TET2 , and ASXL1 constitute approximately 70% of CHIP 1 , 22 – 25 . It remains unclear whether the less common CHIP mutations similarly contribute to increased inflammation-related comorbidities, cardiovascular disease, or an elevated risk of hematologic malignancies. Understanding the role of less common CHIP mutations and their impact on the competitive advantage of mutant HSCPs and altered immune cells offers valuable insights into potential therapeutic targets in affected individuals. Our interest was piqued by recurrent mutations in MYD88 , which have been identified in multiple clonal hematopoiesis studies, but often attributed to lymphoid origin monoclonal B-cell lymphocytosis. Mutations in MYD88 , such as the amino acid substitution of Leucine 265 to Proline (L265P), are commonly found in lymphoid malignancies, such as Waldenstrom’s macroglobulinemia and chronic lymphocytic leukemia 26 . These gain-of-function mutations result in the constitutive activation of NF-κB, promoting cell survival and proliferation independent of external stimuli. MYD88 mutations have also been identified within CD34+ HSPCs at a preneoplastic stage in human lymphomagenesis 27 . Collectively, these findings suggest that MYD88 mutations occur in multi-lineage HSPCs, confer a competitive fitness advantage associated with CHIP, and increase the risk of certain malignancies. Results Recurrent CHIP-associated MYD88 mutations To determine the distribution of MYD88 mutations in healthy adult individuals, we analyzed published sequencing data of 200,618 individuals aged 40-70 years from the UK Biobank (UKBB) 28 . The genes with the highest prevalence of candidate somatic nonsense mutations were DNMT3A, TET2 , and ASXL1 . Genes, such as ZBTB33 , YLPM1, ZNF318, JAK2 , and SRCAP , with lower frequency mutations in CHIP have been shown to also confer a competitive advantage to HSPCs 29 – 31 . The number of MYD88 mutations in this cohort is in a similar range as the lower frequency CHIP mutations ( Figure 1A ). To examine the frequency of MYD88 mutations in additional published CHIP cohorts, we analyzed 6 additional independent studies, consisting mostly of individuals of European ancestry ( Supplemental Tables 1-2 ). The studies included both healthy individuals and those diagnosed with cytopenias or cancer. Collectively, 1-27 MYD88 CHIP mutations were reported, representing ∼0.5-2% of identified CHIP individuals ( Figure 1B ). To confirm these observations in an independent cohort, we performed targeted error-corrected sequencing of mononuclear cells from newly diagnosed solid tumor cancer patients ( Supplemental Table 3 ). In this cohort, we observed a higher than expected proportion (∼4%) of individuals harboring MYD88 CHIP mutations: 10 mutations in 9 individuals out of 218 confirmed CHIP cases among 454 cancer patients sequenced ( Figure 1C ). The validation cohort consists entirely of individuals from the rural Appalachian region, all of whom are Caucasian, with newly diagnosed solid tumors, which are geographically underrepresented in prior genomic studies. The variant allele frequency of MYD88 ranged from 2-36% ( Supplemental Table 3 ). By comparison, the TCGA and MSK cohorts have a MYD88 mutation frequency of 0.32% and 0.14%, respectively ( Supplemental Table 2 ). The mutations in MYD88 were missense variants clustered in the death domain and TIR domain ( Figure 1C ). Among all MYD88 CHIP variants, we noted a high frequency of the oncogenic mutation at L265P within the TIR domain commonly found in B-cell lymphomas. In the Appalachian cohort, we also identified mutations at A45G, T71I, S85P within the death domain, R140Q in the linker region, and C203R within the TIR domain ( Figure 1C ). Although the C203R variant is located within a GC-rich region, which results in lower quality reads, an examination of the Genome Aggregation Database revealed that MYD88 CHIP variants have been reported at or near this residue within the TIR domain in other cohorts. This suggests that mutations within the TIR domain, beyond L265P, can influence MYD88-dependent signaling 32 ( Supplemental Table 4 ). These mutations were not previously reported among MYD88 variants detected in human lymphoma 33 . Moreover, mutations in MYD88 are not reported in MDS and AML 34 . Future studies should examine a larger and more genetically diverse cohort to better understand the broader relevance of these findings. Furthermore, since we detected MYD88 mutations in blood cells from tumor patients, the potential contribution of MYD88-mutant CHIP to solid tumor progression warrants further investigation. Overall, the MYD88 mutations identified in CHIP, which appear to be underreported, were not associated with a B cell malignancy diagnosis, suggesting they may have a distinct role in CHIP. Download figure Open in new tab Figure 1. CHIP-associated MYD88 mutations confer a gain-of-function. (A) The distribution of identified CHIP-associated somatic mutations ranked by frequency in UK Biobank (Bernstein, Nature Genetics, 2024). ( B ) The frequency of MYD88 mutations identified in the indicated population cohorts. (C) Lollipop diagram of CHIP-associated mutations identified in MYD88. CHIP-associated mutations were identified in individuals with no known disease phenotype (black), a solid tumor cancer diagnosis 15 , or lymphoma (blue). ( D ) Prediction of human MYD88 protein structure using AlphaFold 72 . Highlighted residues are implicated in CHIP: A45, T71, S85, R140, C203, and L265. (E) Prediction of protein-protein interactions using AlphaFold 3. Predicted aligned error 29 score of the indicated human MYD88 dimers: WT and WT, WT and L265P, WT and T71I, WT and R140Q, WT and A45G, WT and S85P, and WT and C203R. ( F ) Representative immunoblots of MDSL MYD88 knockout (KO) cells expressing WT and CHIP-related MYD88 mutants from 3 independent experiments. Quantification of phosphorylated IKKβ (relative to total IKKβ) immunoblots (right panel). (G) Quantitative RT-PCR (RT-PCR) analysis of NF-κB target genes ( TNFA and IL1B ) in THP1 MYD88 KO cells transduced with lentiviral vectors encoding WT MYD88 or the CHIP mutations (L265P, T71I, R140Q, and C203R) Data from 3 independent biological replicates. ( H ) Immunoblots of cKit+ enriched BM cells from Myd88 WT and Myd88 L252P mice treated with 1 μM 4-hydroxytamoxifen (4-OHT) for 72 hours to induce Cre recombination. MYD88 mutations result in NF-κB activation Previous studies revealed that the L265P mutation results in spontaneous MYD88 assembly and constitutive NF-κB signaling in B cells without receptor activation 35 . Structural modeling using AlphaFold3 revealed that the CHIP mutations are clustered in key oligomerization regions of MYD88 ( Figure 1D ). Next, we aimed to gain insight into whether CHIP mutations in MYD88 affect oligomer formation. To assess this, we utilized predicted aligned error 29 , a measure of AlphaFold3’s confidence in the relative positioning of two residues within the predicted protein structure 36 . Comparisons between WT-WT MYD88 protein dimers and WT-mutant dimers revealed a lower mean PAE score for the WT-mutant MYD88 dimers ( Figure 1E , Supplemental Figure 1A ). This analysis predicts that all MYD88 mutants have a structural orientation favoring a stable dimer formation. To determine whether MYD88 CHIP mutations result in constitutive NF-κB signaling in hematopoietic cells, we generated isogenic cells expressing the individual MYD88 CHIP mutations. We selected CHIP mutants that were recurrent and with the highest variant allele frequency: T71I, R140Q, C203R, and L265P. Endogenous MYD88 was deleted in myeloid-derived THP1 and MDSL cells using CRISPR/Cas9, and then the MYD88 KO cells were transduced with vectors encoding either WT MYD88 or the CHIP mutants. RNA sequencing revealed that MYD88 CHIP mutants lead to increased, yet distinct and variable, expression of NF-κB target genes, as compared to WT MYD88-expressing cells ( Supplemental Figure 1B ). These differences in NF-κB activation are expected, as individual CHIP-associated mutations may variably affect MYD88 signaling complex assembly, downstream effector recruitment, or stability. Consistent with findings in B-cell malignancies 35 , expression of MYD88 L265P in myeloid-derived cells resulted in constitutive activation of NF-κB, as indicated by increased phosphorylation of IKKβ, independent of TLR activation, as compared to WT MYD88 ( Figure 1F,G ). The other CHIP-associated MYD88 mutants - T71I, R140Q, C203R - also promoted activation of IKKβ, although to variable extents ( Figure 1F,G ). Increased expression of TNFA and IL1B , two canonical NF-κB target genes, further confirmed gain-of-function activity of MYD88 CHIP mutants ( Figure 1G ). Although the MYD88 CHIP mutants exhibit elevated baseline NF-κB activation, the addition of IL-1β did not result in enhanced signaling ( Supplemental Figure 1C ). Together, these results indicate that CHIP-associated MYD88 mutations confer gain-of-function activity, leading to constitutive, ligand-independent activation of the NF-κB pathway. Download figure Open in new tab Supplemental Figure 1. Characterization of MYD88 CHIP mutant. (A) Representative PAE analysis of human MYD88 dimers. The lower left quadrant (orange box) shows the expected possition error for the respective dimers: WT and WT, WT and A45G, WT and T71I, WT and S84P, WT and R140Q, WT and C203R, and WT and L265P. (B) Heatmap of differentially expressed NF-κB target genes (Z score) from THP1 MYD88 KO cells transduced with lentiviral vectors encoding WT MYD88 or the CHIP mutations (L265P, T71I, R140Q, and C203R). (C) Immunoblot analysis of THP1 MYD88 KO cells transduced with lentiviral vectors encoding WT MYD88 or the CHIP mutations (L265P, T71I, R140Q, and C203R) follwoing treatment with IL-1β. Ratio of pIKKβ relative to total IKKβ is shown below. Although MYD88 L265P results in constitutive NF-κB signaling in B cells 35 , 37 , it remains unclear whether this mutation similarly activates NF-κB in HSPCs. Since MYD88 L265P is the most common MYD88 CHIP mutation, we investigated its role in HSPCs by characterizing a conditional Myd88 L252P allele (Myd88 L252P ) expressed from the endogenous locus following inducible Cre-mediated recombination 37 . The murine Myd88 L252P corresponds to the orthologous position of human MYD88 L265P. Myd88 L252P mice were crossed to Rosa26 CreERT 2 mice to allow for recombination following tamoxifen treatment 38 . We focused on characterizing the homozygous Myd88 L252P mice, as there is evidence of bi-allelic MYD88 mutations in patients 27 , 39 , and the heterozygous expression of the mutant allele has been shown to elicit a modest effect on NF-κB activation in mouse cells 40 . To confirm Cre-inducible Myd88 L252P expression, we isolated BM cells from littermates WT ( Myd88 WT/WT ;RosaCreERT2 ) and Myd88 L252P/L252P ( Myd88 L252P ;RosaCreERT2 ) mice. 4-hydroxytamoxifen (4-OHT) treatment of Myd88 L252P BM cells resulted in Cre-induced recombination of the Myd88 locus, resulting in expression of Myd88 L252P -mutant mRNA ( Supplemental Figure 2A ). 4-OHT-induced expression of Myd88 L252P in cKit+ BM HSPCs resulted in IKKβ and RelA/p65 phosphorylation, an indication of NF-κB activation ( Figure 1H ). In contrast, WT HSPCs did not exhibit evidence of baseline NF-κB activation, suggesting that MYD88 CHIP mutations are sufficient to induce NF-κB activation in HSPCs. Download figure Open in new tab Supplemental Figure 2. Characterization of Myd88 L252P mice. (A) Genotyping analysis of Myd88 WT ;Rosa-CreERT2 and MyD88 L252P ;RosaCreERT2 homozygous mice following 4-OHT induced recombiation. ( B ) Proportions of donor-derived CD45.2 CD11b+Gr1lo and CD11b+Grhi cells in the PB of Myd88 WT and Myd88 L252P on left panel. Error bars represent SEM (n = 11-13 per group). (C) Representative flow cytometry gating of donor-derived CD45.2 CD11b+Gr1lo and CD11b+Grhi cells in the PB of Myd88 WT or Myd88 L252P . Error bars represent SEM. Significance was determine with a Student’s t-test for two groups or ANOVA for multiple groups (*, P < 0.05; **, P < 0.01; ***, P < 0.001). (D) Representative flow cytometry gating of donor-derived CD45.1 and CD45.2 LK (Lin-cKit+Sca1-), LSK (Lin-ckit+Sca1+), LT-HSC (LSK CD150+CD48-), ST-HSC (LSK CD150-CD48-), MPP (LSK CD150-CD48+), CMP (LK CD34+16/32-), MEP (LK CD34-CD16/32-), GMP (LK CD34+CD16/32+), CLP (Lin-ckit-Sca1loCD127+CD135+) from the BM of mice competitively engafted with Myd88 WT or Myd88 L252P BM cells. (E) Representative images of spleens and BM sections (Hematoxylin and Eosin) from recipient mice transplanted with Myd88 WT and Myd88 L252P BM cells. MYD88 mutations result in a competitive fitness advantage Expression of CHIP mutations in murine HSPCs can result in increased serial colony replating, an indicator of enhanced self-renewal potential. To determine whether MYD88 CHIP mutations have a cell-intrinsic effect on HSPCs, we assessed the colony-forming potential of HSPCs (cKit+) isolated from WT and Myd88 L252P/L252P (herein referred to as Myd88 L252P ) mice in methylcellulose. HSPCs from Myd88 L252P mice formed a greater number of colonies, predominantly resulting from increased myeloid-lineage forming colonies, as compared to WT HSPCs ( Figure 2A ). Moreover, Myd88 L252P HSPCs exhibited an increase in colony replating potential for up to 5 serial platings as compared to WT HSPCs ( Figure 2B,C ). The increase in colony replating observed in Myd88 L252P HSPCs is comparable to more common CHIP variants 41 – 48 . Download figure Open in new tab Figure 2. Myd88 L252P confers an HSPC competitive advantage, myeloid-biased hematopoiesis, and leads to an immune-related hematologic disease. ( A ) 4-OHT (1 μM) treated cKit+ enriched BM cells (n = 1000) from Myd88 WT and Myd88 L252P mice were plated in methylcellulose and assessed for colony formation (n = 3 per group from biological replicates): erythroid progenitor cells (BFU-E), granulocyte-macrophage progenitors (CFU-G/M/GM), and multi-potential granulocyte, erythroid, macrophage, megakaryocyte progenitor cells (CFU-GEMM). ( B ) Serial colony replating potential of cKit-enriched BM cells from MYD88 WT and MYD88 L252P mice in methylcellulose. Error bars represent the SEM (n = 3 per group from biological replicates). ( C ) Representative images of colonies from panel B. (C) Experimental overview of competitive BM transplants (cBMT). ( E ) Summary of donor-derived Myd88 WT and Myd88 L252P PB proportions (CD45.2) from the cBMT recipient mice at the indicated time points (n = 14-15 mice per group). ( F ) Representative flow cytometry plots of donor-derived CD45.1 (WT) or CD45.2 (Myd88 WT or Myd88 L252P ) PB cells from primary cBMTs. ( G ) Proportions of donor-derived CD45.2 populations from the PB of primary cBMTs: myeloid (CD11b + ), T (CD3 + ), and B (B220 + ) cells at the indicated time points (n= 11-13 mice per group). Error bars represent SEM (n = 11-13 per group). ( H ) Proportions of donor-derived CD45.2 populations from the BM of primary cBMTs at 16 weeks (n = 7-10 mice per group): LK (Lin - cKit + Sca1 - ), LSK (Lin - ckit + Sca1 + ), LT-HSC (LSK CD150 + CD48 - ), ST-HSC (LSK CD150 - CD48 - ), MPP (LSK CD150 - CD48 + ), CMP (LK CD34 + 16/32 - ), MEP (LK CD34 - CD16/32 - ), GMP (LK CD34 + CD16/32 + ), CLP (Lin - ckit - Sca1 lo CD127 + CD135 + ). ( I ) Experimental overview of non-competitive BM transplants (BMT). ( J ) Complete PB counts of MYD88 WT and MYD88 L252P at the indicated time points post BM transplantation and tamoxifen administration. Error bars represent SEM (n = 7-8 mice per group). ( K ) Kaplan-Meier survival curves for recipient mice transplanted with MYD88 WT (n = 12) and MYD88 L252P BM cells (n = 13 mice per group). Data from 2 independent biological replicates. ( L ) Weight of spleen isolated from recipient mice transplanted with Myd88 WT and Myd88 L252P BM cells. Error bars represent SEM (n = 7 mice per group). ( M ) Representative images of spleen sections (Hematoxylin and Eosin), PB smears (Wright-Giemsa), and lungs (Hematoxylin and Eosin) from recipient mice transplanted with Myd88 WT and Myd88 L252P BM cells. White arrows denote infiltrates of monocytes or neutrophils in the spleen. Scale bars of H&E and Wright-Giemsa images represent 50 μm. Error bars represent SEM. Significance was determined with a Student’s t-test for two groups or ANOVA for multiple groups (*, P < 0.05; **, P < 0.01; ***, P < 0.001). To evaluate the impact of Myd88 mutations on clonal hematopoiesis, we performed in vivo competitive repopulation assays using BM cells from Myd88 WT ;Rosa26CreERT2 (hereafter WT) and Myd88 L252P ;Rosa26CreERT2 (hereafter Myd88 L252P ) mice transplanted with equal numbers of WT competitor cells into lethally irradiated recipient mice. Following engraftment, mice were administered with tamoxifen to induce expression of the Myd88 mutant allele and then analyzed every 4 weeks ( Figure 2D ). Donor-derived Myd88 L252P cells outcompeted WT cells over time in the peripheral blood ( Figure 2E,F ). In the competitive BM transplantation, Myd88 L252P expression contributed to an expansion of donor-derived myeloid cells (CD11b) and a relative suppression of B cells (B220) ( Figure 2G ). This contrasts with the B cell-restricted CD19-Cre Myd88 L252P model, which shows no changes in the B220⁺ population in the BM 40 . We observed an expansion of Myd88 L252P immature neutrophils (CD11b + Gr1 Low )( Supplementary Figure 2B,C ). Since Myd88 L252P expression resulted in the expansion of myeloid cells in the PB, we next examined the HSPC proportions in the BM of these mice. The proportions of donor-derived Myd88 L252P long-term HSCs (49.05 vs 23.73%), multi-potent progenitors (72.74 vs 44.5%), and common lymphoid progenitors (CLP)(71.74 vs 32.26%) were significantly increased as compared to WT donor-derived populations ( Figure 2H and Supplemental Figure 2D ). We postulate that the increase in donor-derived Myd88 L252P CLPs is a compensatory response to the reduced proportions of mature B cells and may eventually contribute to the increased expansion of B cells as observed in B cell malignancies. These observations suggest that MYD88 CHIP mutations promote myeloid-biased hematopoiesis, with a particular effect on monocytes and immature neutrophils, and a competitive fitness advantage of HSPCs. Moreover, the ability of MYD88 L252P to promote both lymphoid and myeloid cell alterations highlights the versatility of MYD88 mutations and their capacity to drive clonal expansion across different hematopoietic lineages even in the absence of eventual progression to myeloid malignancy. MYD88 mutations result in an inflammatory disease MYD88 CHIP mutations are associated with a heightened risk of lymphoid malignancies and increased all-cause mortality 49 – 51 . Moreover, MYD88 CHIP mutations were observed in certain individuals with a VAF exceeding >30% 52 , suggesting that the majority of the BM and blood cells contain the mutation. To determine whether MYD88 CHIP mutations can lead to increased mortality and lymphoid malignancy development, we next evaluated the effect of Myd88 L252P expression on hematopoiesis in a non-competitive BM transplantation model ( Figure 2I ). Mice transplanted with Myd88 L252P BM cells exhibited increased neutrophils (P < 0.01) and monocytes (P < 0.05), resembling a myeloproliferative disorder, and reduced red blood cells (P < 0.01) and platelets (P < 0.001) 12 weeks post-transplantation as compared to mice transplanted with WT BM cells ( Figure 2J ). No significant changes in lymphocytes were observed in mice transplanted with Myd88 L252P BM cells. Interestingly, CH individuals with unexplained anemia have been found to harbor MYD88 mutations 53 , supporting the observation of reduced red blood cells in the Myd88 L252P mice. Recipient mice transplanted with Myd88 L252P BM cells had a shorter overall survival as compared to control mice ( Figure 2K ). Nearly all (∼90%) Myd88 L252P recipient mice succumbed to disease within 1 year following BM transplantation. Moribund Myd88 L252P recipient mice exhibited enlarged spleens and disruption of spleen architecture, including extramedullary hematopoiesis ( Figure 2L,M , Supplemental Figure 2E ). The spleens of Myd88 L252P recipient mice had infiltrates of monocytes and neutrophils, features not observed in B cell-specific expression of Myd88 L252P . The liver of Myd88 L252P recipient mice also displayed mild periportal mononuclear cell infiltrates with hepatocyte injury and occasional apoptotic hepatocytes ( Supplemental Figure 2E ). Additionally, the lungs of Myd88 L252P recipient mice harbored peribronchiolar and perivascular inflammation, characterized by lymphocyte infiltration, which likely contributes to the observed morbidity and reduced overall survival in these mutant mice ( Figure 2M ). B cell expression of Myd88 L252P resulted in the expansion of splenic small mature lymphocytes or large blastoid cells in the liver 37 . However, examination of the BM and PB in Myd88 L252P recipient mice did not reveal a lymphoid or myeloid malignancy, suggesting that MYD88 CHIP mutations do not result in overt hematologic cancer. Conversely, B cell-specific MYD88 L252P expression harbored lymphoma cells or activated lymphocytes 37 . These findings revealed that expression of Myd88 L252P in hematopoietic cells results in distinct myeloid and lymphoid phenotypes. Since we observed significant changes in mature immune cells and a non-malignant hematologic disease in Myd88 L252P recipient mice, we posited that the MYD88 CHIP mutations contribute to disease due to chronic NF-κB-induced cytokine production. Thus, to determine whether Myd88 L252P recipient mice exhibit altered cytokine expression, we collected plasma from the BM of the non-competitive BM transplantation models and profiled 32 murine cytokines ( Figure 2I ). Peripheral blood plasma from Myd88 L252P recipient mice had a broad increase in multiple cytokines, such as IL-6, TNFα, G-CSF, MIG, MIP1α, and IFNψ ( Figure 3A,B , Supplemental Table 5 ). Chronic inflammation can enhance myeloid expansion and selectively expand the mutant clones at the expense of suppressing normal HSCs, indicating that persistent inflammatory signaling is a critical driver of CHIP progression 11 , 54 , 55 . Collectively, these findings suggest that MYD88 CHIP promotes an inflammatory milieu, which can lead to increased mortality. Download figure Open in new tab Figure 3. scRNA-seq of Myd88 L252P BM HSPCs reveals broad immune and inflammatory signaling dysregulation. ( A ) PB plasma cytokines were evaluated after 20 weeks in recipient mice transplanted with Myd88 WT (n = 12) and Myd88 L252P (n = 13) BM cells. A heatmap of plasma cytokine levels is shown and color-coded according to Z score (high, red; middle, orange; low, blue). ( B ) Representative cytokines from Myd88 L252P PB are normalized to Myd88 WT PB. Significance was determined with a Student’s t-test for two groups or ANOVA for multiple groups (*, P < 0.05; **, P < 0.01; ***, P < 0.001). ( C ) BM cells were harvested from recipient mice transplanted with Myd88 WT and Myd88 L252P BM cells (n = 2 mice per group) after 12 weeks, and cKit+ cells were enriched by magnetic selection. Barcoded cells were pooled and analyzed by 10X single-cell RNA (scRNA) sequencing. UMAP of 900 Myd88 WT and 1195 Myd88 L252P cells representing 13 clusters. (D) Percentage of each cell cluster from the scRNA-seq analysis of 900 Myd88 WT or 1195 Myd88 L252P cells. (E) Heatmap of the top 50 differentially expressed genes in individual Myd88 WT or Myd88 L252P cells within the indicated clusters. (F) Gene ontogeny pathway analysis of the indicated clusters. All error bars represent SEM. Significance was determined with a Student’s t-test for two groups or ANOVA for multiple groups (*, P < 0.05; **, P < 0.01; ***, P < 0.001). scRNA-seq reveals insights into MYD88 -mutant CHIP To understand how Myd88 L252P HSPCs result in a competitive fitness advantage, myeloid expansion, and inflammatory pathology, we performed single-cell RNA sequencing (scRNA-seq) on 10,000 sorted cKit+ BM cells isolated from recipient mice engraftment with either WT or Myd88 L252P BM cells 16 weeks following engraftment (as in Figure 2I ). We identified 13 major cell lineage clusters in both WT and Myd88 L252P cKit+ BM cells ( Figure 3C ). Consistent with our flow cytometry analysis, Myd88 L252P cKit+ BM cells showed an expansion of neutrophil, common myeloid progenitor (CMP), and megakaryocyte-erythroid progenitor (MEP) clusters compared to the WT BM cells ( Figure 3D ). Moreover, clusters consisting of granulocyte monocyte progenitors (GMP), eosinophils, and B cells were reduced in the Myd88 L252P BM as compared to WT mice ( Figure 3D ). We then sought to delineate the developmental trajectory between the immature HSPCs and the committed progenitors by a pseudotime analysis 56 . The trajectory of Myd88 L252P cells towards neutrophils was more prominent as compared to WT cells ( Supplemental Figure 3A ). These findings indicate that the MYD88 mutation promotes the myeloid commitment of BM HSPCs and expands immature neutrophils. Download figure Open in new tab Supplemental Figure 3. Pseudotime analysis and IRAK1/4-inhibitor treatment of Myd88 L252P BM cells. (A) BM cells were harvested, and cKit+ cells were enriched by magnetic selection. Cells were analyzed by 10X single-cell RNA (scRNA) sequencing. UMAP of 10,000 cells representing 13 clusters from recipient mice transplanted with Myd88 WT or Myd88 L252P BM collected at 12 weeks. Pseudotime trajectory of scRNA-seq profiles of the major clusters as defined by the indicated genes. (C) Immunoblotting of Myd88 WT and Myd88 L252P cKit+ BM cells incubated with 4-OHT to induce recombination for 72 hours followed by treatment with vehicle (DMSO) or 1 μM IRAK1/4-inhibitor (IRAK1/4-inh; NCGC-1481) for 24 hours. (C) Proportion of donor-derived Myd88 WT (n = 5) and (C) Myd88 L252P (n = 5) CD45.2 populations from the BM of cBMTs following treatment with vehicle or IRAK1/4-inh: LK (Lin-cKit+Sca1-), LSK (Lin-ckit+Sca1+), LT-HSC (LSK CD150+CD48-), ST-HSC (LSK CD150-CD48-), MPP (LSK CD150-CD48+), CMP (LK CD34+16/32-), MEP (LK CD34-CD16/32-), GMP (LK CD34+CD16/32+), CLP (Lin-ckit-Sca1loCD127+CD135+). Data is representative from 2 independent biological replicates. Error bars represent SEM. Significance was determined with a Student’s t-test for two groups or ANOVA for multiple groups (*, P<.05; **, P < 0.01). To identify mechanisms by which Myd88 L252P promotes long-term fitness advantage, we focused on the HSPC clusters. Our findings revealed a substantial increase in upregulated differentially expressed genes (DEGs) in Myd88 L252P clusters containing HSPCs (LSK/MPP), monocytes, neutrophils, and CLP compared to WT clusters ( Figure 3E and Supplemental Table 6 ). Gene Ontology (GO) analyses highlighted enrichment for Type I interferon, innate immune response, myeloid differentiation, and stem cell maintenance programs in Myd88 L252P HSPCs as compared to WT HSPCs ( Figure 3F ). Similarly, Myd88 L252P clusters containing monocytes and neutrophils had a significant increase in the number of DEGs as compared to WT cells ( Figure 3E ). Within the myeloid cell clusters, Myd88 L252P cells demonstrated increased inflammatory genes ( Figure 3F ). Myd88 L252P clusters containing lymphocyte progenitors exhibited enrichment of autophagy and cell death programs ( Figure 3F ). While common CHIP mutations typically drive myeloid-biased hematopoiesis, our findings reveal that MYD88 mutations may have a more complex role, influencing both myeloid and lymphoid programs. IRAK1/4 inhibition suppresses MYD88- mutant cells The size of the mutant hematopoietic cell pool can predict the progression to hematological cancers and immune-related conditions, therefore, strategies to prevent the expansion of mutant clones are clinically desirable. Individuals with MYD88 CHIP mutations are at an increased risk of hematological cancers and cardiopulmonary diseases 49 – 51 . As such, preventing the expansion of MYD88 CHIP mutant clones, or other CHIP mutant clones exhibiting IRAK1/4 signaling, could be a feasible clinical intervention. IRAK4 inhibitors have been explored as potential therapies for lymphoid malignancies driven by MYD88 mutations 16 , 57 . In preclinical studies, IRAK1/4 inhibition suppressed pre-leukemic and MDS/AML cells, suggesting that dysregulation of IRAK1/4 is a key driver of mutant HSPCs and a potential therapeutic target 14 , 16 , 58 – 61 . To determine whether MYD88-dependent signaling is responsible for the competitive advantage of MYD88 CHIP mutant cells, we used an inhibitor (NCGC-1481, herein “IRAK1/4-inh”) to suppress IRAK1 and IRAK4, the proximal effectors of MYD88 62 – 64 . The IRAK1/4-inh effectively repressed NF-κB activation and innate immune ( Ifng ) and inflammatory ( Mip1a and Tnfa ) gene expression in Myd88 L252P cKit+ BM cells, but not in Myd88 WT cells ( Figure 4A , Supplemental Figure 3B ). Since Myd88 L252P HSPCs acquire an enhanced colony-replating phenotype, we aimed to determine if this was due to increased innate immune signaling. Treatment with the IRAK1/4-inh did not affect the primary colony-forming potential of either Myd88 WT or Myd88 L252P cKit+ BM cells. However, it significantly reduced the secondary, tertiary, and quaternary colony-forming potential of Myd88 L252P cKit+ cells, while having no effect on Myd88 WT cells ( Figure 4B ). Download figure Open in new tab Figure 4. IRAK1/4 inhibition suppresses innate immune signaling, clonal expansion, and the competitive fitness advantage of Myd88 L252P HSPCs. (A) Quantitative RT-PCR (RT-PCR) analysis of the indicated cytokines genes in Myd88 WT and Myd88 L252P cKit+ BM cells incubated with 4-OHT to induce recombination for 72 hours followed by treatment with vehicle (DMSO) or 1 μM IRAK1/4-inhibitor (IRAK1/4-inh; NCGC-1481) for 24 hours (n = 3 per group from biological replicates). (B) cKit+ enriched BM cells incubated with 4-OHT (1 μM) were serially plated in methylcellulose and assessed for colony formation in the presence of vehicle (DMSO) or 1 μM IRAK1/4-inh (NCGC-1481) (n = 3 per group from biological replicates). (C) Experimental overview of competitive BM transplants (cBMT) following administration of the IRAK1/4-inh (NCGC-1481). Chimeric mice were administered daily with either vehicle control (PBS) or IRAK1/4-inh (30 mg/kg) via intraperitoneal (IP) injection for 6 weeks. FACS analysis of PB was performed pre- and post-administration at weeks 0, 2, 4, and 6. (D) Percent change (related to pre-treatment) in PB chimerism of individual donor-derived CD45.2 cells following administration of vehicle or IRAK1/4-inh at the indicated time points (n = 10 for Myd88 WT ; n = 26 for Myd88 L252P ). Data from 2 independent biological replicates. (E) Proportions of PB donor-derived myeloid (CD11b), T (CD3), and B (B220) cells within the CD45.2 populations of Myd88 WT (n = 10) and Myd88 L252P (n = 26) chimeric mice following treatment with vehicle or IRAK1/4-inh at the indicated time points. Data from 2 independent biological replicates. Error bars represent SEM. Significance was determined with a Student’s t-test for two groups or ANOVA for multiple groups (*, P < 0.05; **, P < 0.01; ***, P < 0.001). We next performed an in vivo competitive repopulation assay using CD45.2 BM cells from Myd88 WT or Myd88 L252P mice, as above, by transplanting equal numbers of CD45.1 WT competitor cells into lethally irradiated recipient mice. Following engraftment (4 weeks post-transplant), mice were administered tamoxifen to induce expression of the Myd88- mutant allele. One week post tamoxifen administration, chimeric recipient mice were randomized and treated daily for 6 weeks with the IRAK1/4-inh or vehicle (PBS) and analyzed every 2 weeks for hematopoietic reconstitution ( Figure 4C ). As expected, donor-derived Myd88 L252P cells in the vehicle group outcompeted WT cells ( Figure 4D ). Treatment of the Myd88 L252P recipient mice with the IRAK1/4-inh suppressed donor-derived Myd88 L252P , but not Myd88 WT cells in the PB ( Figure 4D ). The IRAK1/4-inh also suppressed donor-derived Myd88 L252P HSPCs in the BM, including MPPs, GMPs, and MEPs ( Supplemental Figure 3C ). Examination of the PB and BM following IRAK1/4 inhibitor treatment revealed that the reduced chimerism of donor-derived Myd88 L252P cells was primarily due to a decrease in the proportions of CD11b myeloid cells in the PB ( Figure 4E ). IRAK1/4-inh had negligible effects on the chimerism of Myd88 WT cells in the PB and HSPCs ( Figure 4D and Supplemental Figure 3C ). These findings suggest that the competitive advantage of MYD88-mutant CHIP cells is driven, at least in part, by IRAK1/4 signaling and can be reversed by small molecule inhibition. This highlights aberrant innate immune signaling as a mechanism underlying MYD88-mutant CHIP HSC expansion and supports IRAK1/4 inhibition as a potential therapeutic strategy. Discussion Our findings reveal that MYD88 mutations, though underreported in CHIP, confer a cell-intrinsic competitive advantage by promoting innate immune activation and chronic inflammation. This establishes a direct mechanistic link between MYD88 signaling and clonal expansion. We show that recurrent MYD88 CHIP mutations, including L265P and other TIR/death domain variants, promote NF-κB activation. In vivo, MYD88-mutant HSPCs exhibited enhanced self-renewal capacity, myeloid-biased differentiation, and competitive repopulation potential. MYD88-mutant cells also induced inflammatory disease, mimicking CHIP-associated comorbidities. These effects occurred in the absence of overt hematologic malignancy, suggesting that MYD88 mutations can drive disease through inflammation alone. Gene expression profiling revealed a shift toward myeloid lineages and enrichment of inflammatory gene programs in MYD88-mutant HSPCs. These data highlight the broad transcriptional and lineage consequences of MYD88 signaling in CHIP. Finally, we show that IRAK1/4 inhibition selectively suppresses MYD88-mutant HSPCs, reducing their fitness and expansion without affecting WT cells. These results position the MYD88–IRAK axis as a viable therapeutic target in early clonal hematopoiesis. Collectively, our study expands the landscape of CHIP beyond the canonical mutations. MYD88 mutations, while less common, may significantly impact hematopoietic output and disease risk via sustained immune signaling. Declaration of Interests DTS serves on the chair of the scientific advisory board at Kurome Therapeutics and is a consultant for and/or received funding from Kurome Therapeutics, Captor Therapeutics, Treeline Biosciences, and Tolero Therapeutics. DTS has equity in Kurome Therapeutics. JCB serves as the chair of the scientific board of Vincerx Pharma, Eilean Therapeutics, Newave Pharmaceutics, and Orange Grove Bio. JCB has served on an advisory board for Abbvie, AstraZeneca, Kartos Therapeutics, and Syndax Pharmaceutics. JCB has equity in Vincerx Pharma and Eilean Therapeutics. HCR received consulting and lecture fees from Abbvie, AstraZeneca, Vertex and Merck. HCR received research funding from AstraZeneca and Gilead Pharmaceuticals. HCR is a co-founder of CDL Therapeutics GmbH. TH has served on an advisory board for Servier, Morphosys, and Bristol Myers Squibb. The other authors declare no competing interests. Funding This work was supported in part by the National Institute of Health (U54DK126108, R35HL166430, R01CA271455, R01CA275007, 5UG1CA233338), Michael and Judy Thomas investment in pre-clinical and translational studies of clonal hematopoiesis, The CLL Society, Vigyan Singhal, Cincinnati Children’s Hospital Research Foundation, Cancer Free Kids, and Blood Cancer Discoveries Grant program through The Leukemia & Lymphoma Society, The Mark Foundation for Cancer Research and The Paul G. Allen Frontiers Group. This work was supported by NIDDK U54 DK126108 at Cincinnati Children’s Hospital Medical Center and their Flow Cytometry and Comprehensive Mouse Cores. JY was supported in part by the National Institute of Health (F32HL149280) and the American Cancer Society (PF-21-110-01-TBE). HCR received funding through the German-Israeli Foundation for Research and Development (I-65-412.20-2016), the German Research Foundation (DFG) (SFB1399 – grant no. 413326622, SFB1430 – grant no. 424228829, SFB1530 – grant no. 455784452), the Else Kröner-Fresenius Stiftung (2016_Kolleg.19), the Deutsche Krebshilfe (1117240, 70113041), the German Ministry of Education and Research (BMBF e:Med Consortium InCa, grant 01ZX1901 and 01ZX2201A), as well as from the program “Netzwerke 2021”, an initiative of the Ministry of Culture and Science of the State of North Rhine-Westphalia for the CANTAR project. Data-sharing statement Cell lines and mouse models used in these studies are publicly available through commercial sources or may be made available from the authors upon written request and material transfer agreement approval. The authors are also glad to share guidance regarding protocols and assays used in these studies upon written request. Author Contributions JY performed experiments, analyzed and interpreted data, and wrote the manuscript. JY, SP, CC, PA, LL, and EU performed experiments and analyzed and interpreted data. KH assisted with the mouse experiments. HCR generated the original Myd88 mutant mice. KC performed bioinformatics analyses. JCB and EH provided input and reagents and interpreted data. JCB, TH, GL, TJD, and AL obtained, designed the targeted CH panel and performed sequencing analysis. PP and KAW analyzed the pathology. DTS conceived and directed the study, analyzed and interpreted data, and wrote and/or edited the manuscript. All authors approved the final version of the manuscript. Materials and Methods CHIP Patients Peripheral blood samples were obtained from a cohort of 454 newly diagnosed solid tumor patients from different counties in Appalachia. All patients provided written informed consent for participation in the treatment studies in accordance with the Declaration of Helsinki. DNA extracted from peripheral blood mononuclear cells from patients were analyzed for the presence of CH. Error-corrected next-generation sequencing (NGS) of DNA using the Ion Torrent Personal Genome Machine was used for high definition (HD) sequencing for a detection depth of up to 50,000X (average 44,469X coverage with uniformity of 91.24% and being on target at 99.49%). A custom AmpliSeq HD primers panel IAH150087 was designed to detect CH-2%, which includes whole gene sequencing and hotspots. The region covered in MYD88 is described in Supplemental Table 7 . DNA was prepped on GeneAmp PCR system 9700 Dual 96-well thermal cycler from Applied Biosystems. PCR products were purified with Agencourt AMPure XP kit (A63881 Beckman Coulter, Indianapolis, Indiana). DNA libraries were prepared with Ion AmpliSeq HD Library kit (A37694) and quantified using real-time PCR with Ion Library TAQMAN Quantitation kit 4468802 on (Applied Biosystems ViiA7 Real-Time PCR System) instrument to allow for an optimal final dilution of the library for template preparation. Bidirectional sequencing with dual barcode support of 454 amplicons in 2 pools at 27.74kb panel size with 99.86% coverage. Template preparation was performed using Ion One Touch2 instrument with Ion 540 Kit OT2 kit (A27753), then enrich and purify Ion One Touch2 ES. Purified ISPs were run on the Ion Torrent S5 instrument using 540 Kit OT2 (A27753) and Ion 540 Chip Kit (A27766). IonAmpliseq HD Dual Barcodes kit (A37695) was used to run multiple samples on the same chip. Data was collected and analyzed on S5 Prime Sequencer Server with Torrent Suite 5.12.2. Final analysis of sequence data was performed using a combination of software: Variant Caller v.5.12.27-1, IGV5.01 (0) and Ion Reporter v.5.18. The hg19 reference sequence was used for manual analysis to assess for deviation from the reference sequence and to evaluate the quality of the sequence and the depth of coverage. Clonal hematopoiesis of MYD88 was defined with a variant allelic frequency (VAF) of 2% or greater. Reagents The inhibitor, NCGC-1481, compound was previously described 63 , 64 . 4-OHT Hydroxy-tamoxifen and tamoxifen were purchased from Millipore-Sigma. Respective human and murine cytokines, hIL3, hIL6, hTPO, mFLT3, mSCF, and mIL3, were purchased from PeproTech. Cell lines CRISPR/Cas9 targeting human MYD88 (Synthego) was used to generate MYD88 knockouts in parental THP1 and MDSL cell lines 60 . The following sgRNAs supplied by Synthego were used: sgRNA 1: UCCUGGAGCCUCAGCGCGGU; sgRNA 2: GGAGGAUGUGGAGGAGACCG; sgRNA 3: GUUCUUGAACGUGCGGACAC. MYD88 knockout cells were generated by suspending parental THP1 or MDSL cells in buffer R with Cas9-NLS and sgRNA mixture, and electroporated (1700 mV x 20 ms x 1 pulse) using the Neon Transfection system (ThermoFisher). THP1 and MDSL cells were cultured in RPMI 1640 medium supplemented with 10% FBS and 1% penicillin-streptomycin. For MDSL cells, media was supplemented with 10 ng/mL of hIL-3. Primary murine BMNCs (bone marrow monocular cells) were cultured in Iscove’s MDM with 10% FBS, 1% penicillin-streptomycin, and supplemented with 50 ng/mL of hIL6, hTPO, mSCF, mIL3, and mFLT3 cytokines. Retroviral vectors HA-tagged MYD88 plasmid was purchased from Addgene (#12287) and cloned into pCDH-EF1-IRES-copGFP expressing vector with XbaI and BstBI and used as template for MYD88 mutants. MYD88 mutants were generated with Phusion Site-Directed Mutagenesis Kit (F541, ThermoFisher Scientific). The following MYD88 primers were used to generate site-directed mutations using: L265P forward: P-CATCAGAAGCGACCGATCCCCATCAAG; L265P reverse: P-GGCACCTGGAGAGAGGCTGAGTGCAAA; T71I forward: P-ACAAGCGGACCCCATTGGCAGGCTGCT; T71I reverse: P-GTCTCCAGTTGCCGGATCTCCAAGTA; R140Q forward: P-AGCAGTGTCCCACAGACAGCAGAGCTG; R140Q reverse: P-GTCTACAGCGGCCACCTGTAAAGGCTT; C203R forward: P-CTGCCTGGCACCCGTGTCTGGTCTATT; C203R reverse P-GACATCGCGGTCAGACACACACAACTT Mice MYD88 L252P/L252P mice (ortholog of the human MYD88 p.L265P mutation), which had been previously generated and described, 37 were purchased from Jackson Laboratory (Bar Harbor, ME) and bred with Rosa26-CreERT2 mice (Jackson Laboratory) to generate littermates for all subsequent in vivo bone marrow transplantations and in vitro studies. experiments. All mouse experimental procedures were performed and bred in-house in accordance with and ethically approved by the Institutional Animal Care and Use Committee (IACUC) at Cincinnati Children’s Hospital Medical Center. Bone marrow transplantation For noncompetitive BM transplantations, BMNCs (bone marrow monocular cells) were isolated from femur and tibia of age-matched MYD88 WT/WT ;Rosa26CreERT2 or MYD88 L252P/L252P ;Rosa26CreERT2, grounded using mortar and pestle in sterile 1 XPBS with 1 mM EDTA, and filtered through a 100 μm strainer. Filtered BMNCs were pelleted at 800xg for 10 mins at 4°C, followed by red blood cell lysis in BD Pharm Lyse (BD Biosciences, 555899) and washed with sterile 1X PBS. CD45.2 + MYD88 WT/WT ;Rosa26CreERT2 or MYD88 L252P/L252P ;Rosa26CreERT2 BMNCs (1 × 10 6 ) were resuspended in 200 μL of PBS and intravenously (i.v.) administered into lethally-irradiated (7.0 Gy and 4.75 Gy after 3 h) recipient mice (CD45.1 + B6. SJLPtprcaPep3b/Boy (BoyJ); 6-10 weeks of age) as previously described 15 , 65 , 66 . For competitive BM repopulation, BMNCs derived from littermates, age and gender-matched MYD88 WT/WT ;Rosa26CreERT2 or MYD88 L252P/L252P ;Rosa26CreERT2 (CD45.2 + ) femur and tibia, were mixed with equal number of CD45.1 + BoyJ BMNCs and then injected i.v. into lethally-irradiated recipient CD45.1 BoyJ. At 4 weeks post-BM transplantation, recipient mice were injected intraperitoneally (I.P.) with 50 μL of tamoxifen (1 mg dissolved in corn oil) daily for 2 weeks to allow tamoxifen-inducible excision of floxed regions and expression of MYD88 L252P/L252P . For in vivo IRAK1/4 inhibitor study, 50 μL of NCGC-1481 at 30 mg/kg or vehicle control (1X PBS) was IP administered daily for 6 weeks. Single-cell RNA-sequencing of cKit+ BM cells BMNCs were isolated from femur and tibia, followed by RBC lysis as describe above, and incubated with cKit-enrichment magnetic antibodies against CD117 (130-091-224, Miltenyi). CD117+ HSCs were positively selected or purified in LS magnetic separation columns (130-042-401, Miltenyi). cKit-enriched cells were then incubated with a panel of cell hashing antibodies (TotalSeq-B, 155831, 155833, 155835, 155837, 155839, 155841, BioLegend) on ice for 30 mins. The scRNA-Seq assay was performed according to the manufacturer’s instructions (Chromium Next GEM Single Cell 3’ Reagent Kits v3.1 (Dual Index) with Feature Barcode technology for Cell Surface Protein, 10x Genomics). Briefly, Total-Seq B antibody-labeled cells were resuspended in the master mix and loaded together with partitioning oil and gel beads into the chip to generate a gel bead-in-emulsion (GEM). The poly-A RNA from the cell lysate contained in every GEM was reverse transcribed into cDNA, adding an Illumina TruSeq R1 primer sequence, Unique Molecular Identifier 33 and the 10x Barcode. The DNA conjugated to the Total-Seq B antibodies (Feature Barcodes (FBs)) was barcoded by adding an Illumina Nextera R1, UMI, and the 10x Barcode. The cell barcoded molecules were then cleaned up with Silane DynaBeads and amplified using 13 PCR cycles. Size selection using SPRIselect reagent was performed post amplification to separate full-length cDNA from FBs. Next, full-length, barcoded cDNA was then enzymatically fragmented, sized-selected, adapter-ligated, and amplified for library construction. During the library construction, P5, P7, i7 and i5 sample indexes, and TruSeq Read 2 were added. Separately, FBs were prepared into library constructs by incorporating P5, P7, i7 and i5 sample indexes, and TruSeq Read 2 via PCR. Samples were pooled and run on the NovaSeq X Plus sequencer with a 10B flow cell using the following sequencing parameters: R1: 28 cycles, i7: 10 cycles, i5: 10 cycles, R2: 90 cycles. The 10x Genomics scRNA-Seq libraries from mouse samples were aligned to the mm10 mouse genome and pre-processed using the Cell Ranger-multi) pipeline (v7.2.0, https://www.10xgenomics.com/support/software/cell-ranger ) with custom TotalSeq-B hashtag oligos. Normalization, dimensional reduction, clustering, integration and all downstream analyses were performed using Seurat (v5.0.3, https://satijalab.org/seurat/ ) on R/4.2.3 ( https://www.r-project.org ). Doublets were detected and removed using DoubleFinder (v2.0.4, https://github.com/chris-mcginnis-ucsf/DoubletFinder ) and downstream analyses were done using remaining cells from 900 WT MYD88 900 and 1195 MYD88 L252P/L252P cells. For clustering functions, the dimension was set to 1:30 and resolution to 0.8. During sample integration, default parameters were used in Seurat’s FindIntegrationAnchors function, including setting anchor features to 2000. Each cluster was initially annotated using Seurat’s label-transfer function with the HSPC reference atlas 67 from Preleukemic Mouse Cell Atlas 68 , then manually re-annotated using top 100 cell marker genes as previously described 69 . The lineage trajectory and pseudo-time were predicted using Monocle3 (v1.3.4, https://cole-trapnell-lab.github.io/monocle3 ) with resolution = 1 56 . Quantitative RT-PCR Total RNA of cells were isolated using Quick-RNA MiniPrep kit (Zymo Research) and 1 μg of RNA was reverse transcribed into cDNA using High-Capacity RNA-to-cDNA kit (4387406, ThermoFisher Scientific) according to the manufacturer’s procedure. cDNA was diluted 1:5 prior to performing real-time quantitative PCR, using SYBR Green Master Mix (4309155, ThermoFisher Scientific), on an Applied Biosystems StepOne Plus Real-Time PCR System. Hematological and histological analysis Femur or spleen were fixed in formalin and then stained with hematoxylin and eoisin. Complete blood counts of PB was measured by hemacytometer (HEMAVET). Flow cytometry analysis For flow cytometric analysis of lineage positive cells or stem/progenitor HSCs, PB or BM samples were processed in 1xRBC lysis for 15 minutes, followed by incubation in the following antibodies, DAPI (D1306, ThermoFisher Scientific), 7AAD (00-6993-50, eBiosciences), CD11b-PE-Cy7 (25-0112-81, eBiosciences), Gr1-eFluor450 (48-5931-82, eBiosciences), CD3-PE (12-0031-83, eBiosciences), B220-APC (17-0452-82, eBiosciences), CD45.1-Brilliant Violet 510 (110741, BioLegend), CD48-APC (11-0481-85, eBiosciences), CD117-APC-Cy7 (135135, BioLegend), Ly-6A/E(Sca-1)-PE (12-5981-82, eBiosciences), CD135-PE-Cy5 (135312, BioLegend), CD150-PerCpCy5.5 (115922, BioLegend), CD127-Brilliant Violet 605 (35041, BioLegend) and CD45.2-APC-eFluor780 (47-0454-82, eBiosciences) or CD45.2-eFluor450 (48-0454-82, eBiosciences). Immunoblot analysis Mouse BMNCs were collected, RBCs lysed, followed by cell lysis in cold 1XRIPA with protease inhibitors. Protein concentration was quantified by bicinchoninic acid (BCA) assay (32106, Pierce) followed by resuspension in sample loading buffer. Proteins were separated by SDS-PAGE, transferred to nitrocellulose membranes and analyzed by immunoblotting. Immunoblotting was performed with the following primary antibodies: phospho-RelA (3033, Cell Signaling Technology), RelA (sc-71675, Santa Cruz), phospho-IKKα/β (2697, Cell Signaling Technology), IKKβ (2370, Cell Signaling Technology), vinculin (13901, Cell Signaling Technology), phospho-IRAK1 T209 (A1074, Assay Biotech), IRAK1 (sc-5288, Santa Cruz), phospho-IRAK4 T345/S346 (11927S, Cell Signaling Technology), IRAK4 (4363, Cell Signaling Technology), MYD88 (sc-136970, Santa Cruz). Lentiviral transduction As previously described, HEK293T cells were transfected with HA-tagged MYD88 wild-type or mutants and viral packaging (gag-pol and VSV-G) plasmids using TransIT-®LT1 transfection reagent to generate lentiviral supernatants 48 hours post-transfection. 15 Viral supernatant was harvested and filtered onto isogenic MYD88 KO cells. Transduced cells were expanded and then sorted for GFP+ population. Bulk RNA-sequencing Total RNA of transduced THP-1 MYD88 knockout cells was isolated using Quick-RNA MiniPrep kit (Zymo Research). The initial amplification step for all samples was done with the NuGEN Ovation RNA-Seq System v2. The assay was used to amplify RNA samples to generate cDNA, followed by Qubit concentration quantification. Libraries were then generated using the Illumina protocol (Nextera XT DNA Sample Preparation Kit). The size of the libraries was measured using the Agilent HS DNA chip. The concentration of the pool was optimized to acquire at least 15-20 million reads per sample. Gene set enrichment analysis The analysis of RNA sequencing was performed using iGeak 70 and gene set enrichment analysis (GSEA) was performed as previously described 71 . Clonogenic progenitor assays BMNCs were isolated from femur and tibia, followed by RBC lysis and incubation with cKit-enrichment magnetic antibodies against CD117 and positively selected or purified in LS magnetic separation columns. CD117 + HSCs were resuspended in Iscoves MDM (10-016-CV, Corning), and 1000 cKit + BM were treated with 1 μM 4-OHT and plated in MethoCult GF (M3434 or M3534; StemCell Technologies). Colonies were enumerated using StemVision (StemCell Technologies) on days 12-14. To assess serial replating capacity, colonies were pooled, resuspended in Iscoves MDM, washed twice, and then replated serially at 7.5×10 3 cells per replicate in the same medium. Profiling of plasma cytokines and chemokines by multiplex ELISA Peripheral blood (PB) was collected in EDTA tubes from the indicated non-competitive BMT recipient mice at 12 weeks post-BMT. PB was centrifuged at 1000xg for 10 mins at 4°C for plasma in the supernatant. The supernatant was transferred to cold Eppendorf tubes and immediately frozen at −70°C. Samples were thawed on ice and mixed thoroughly before being diluted 1:1 in assay buffer provided by the mouse cytokine/chemokine magnetic bead panel kit (MCYTMAG-70K-PX32, Millipore). Luminex xMAP platform was used to quantify the 32-plex mouse cytokine panel. Data Availability The RNA sequencing data generated in this study has been deposited at NCBI’s GEO repository with accession number GSE277714 (token: qzylicsqhzujpid). Statistical analysis Differences among multiple groups were assessed by one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison posttest for all possible combinations. Comparison of two groups was performed using the Mann-Whitney test or the Student’s t test (unpaired, two-tailed) when sample size allowed. Unless otherwise specified, results are depicted as the mean ± standard deviation or standard error of the mean (SEM). A normal distribution of data was assessed for data sets >30. For correlation analysis, Pearson correlation coefficient (r) was calculated. For Kaplan-Meier analysis, Mantel-Cox test was used. All graphs and analyses were generated using GraphPad Prism 10 software or using the package ggplot2 from R. Acknowledgments We thank the Comprehensive Mouse and Cancer Core (Jeff Bailey and Victoria Summey), the Viral Vector Core (Thouwa Samake), Flow Cytometry Core, and Genomics Sequencing Core at CCHMC for their assistance. We thank Donald Lynch for helpful discussion and suggestions. Footnotes Funding information on page 11 revised; manuscript file updated. References 1. ↵ Jaiswal , S. & Ebert , B.L . 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Share MYD88 mutations in clonal hematopoiesis promote inflammation and hematopoietic stem cell expansion Jennifer Yeung , Sophia Y. Philbrook , Emma Uible , Lynn Lee , Kwangmin Choi , Puneet Agarwal , Courtnee A. Clough , Pravin Patel , Kathryn A. Wikenheiser-Brokamp , Kathleen Hueneman , Hans Christian Reinhardt , Tzyy-Jye Doong , Arletta Lozanski , Gerard Lozanski , Tamanna Haque , Erin Hertlein , John C. Byrd , Daniel T. Starczynowski bioRxiv 2025.06.19.660202; doi: https://doi.org/10.1101/2025.06.19.660202 Share This Article: Copy Citation Tools MYD88 mutations in clonal hematopoiesis promote inflammation and hematopoietic stem cell expansion Jennifer Yeung , Sophia Y. Philbrook , Emma Uible , Lynn Lee , Kwangmin Choi , Puneet Agarwal , Courtnee A. Clough , Pravin Patel , Kathryn A. Wikenheiser-Brokamp , Kathleen Hueneman , Hans Christian Reinhardt , Tzyy-Jye Doong , Arletta Lozanski , Gerard Lozanski , Tamanna Haque , Erin Hertlein , John C. Byrd , Daniel T. 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