# paper.pdf ## Metadata - PDFFormatVersion=1.6 - Language=EN-US - IsLinearized=true - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Author=Kumar, Ramesh - Custom.Company=Indiana University - Custom.GrammarlyDocumentId=ecfc0d57-6cd0-4bc2-9215-3f1c9ade7640 - CreationDate=D:20260109121654-05'00' - Creator=Acrobat PDFMaker 25 for Word - ModDate=D:20260109121810-05'00' - Producer=Adobe PDF Library 25.1.20 - xmp:modifydate=2026-01-09T12:18:10-05:00 - xmp:createdate=2026-01-09T12:16:54-05:00 - xmp:metadatadate=2026-01-09T12:18:10-05:00 - xmp:creatortool=Acrobat PDFMaker 25 for Word - xmpmm:documentid=uuid:aa825b9a-ed08-4a83-83f7-7210188d7788 - xmpmm:instanceid=uuid:c5a2baca-77ed-4a37-a5d2-9975f6707646 - xmpmm:subject=6 - dc:format=application/pdf - dc:creator=Kumar, Ramesh - pdf:producer=Adobe PDF Library 25.1.20 - pdfx:company=Indiana University - pdfx:grammarlydocumentid=ecfc0d57-6cd0-4bc2-9215-3f1c9ade7640 ## Contents ### Page 1 Supplementary Materials for: Inflammatory Bowel Disease Augments Clonal Hematopoiesis of Indeterminate Potential 1,# , Linke Li2,3, # , Sarah Urbut 3,4 , Mesbah Uddin3,4 , Abhishek Niroula 3,5 , , , , , Xuepeng Wang1 , Kanaka Sai Ram Padam 1 , Mark Kelley 1 ,3,4,6 ,2,3,6,& and1,& This file contains the following: - 1. Supplemental Methods - 2. Supplemental Table 1 - 3. Supplemental Table 2 - 4. Supplemental Table 3 - 5. Supplemental Table 4 - 6. Supplemental Table 5 - 7. Supplemental Table 6 - 8. Supplemental Table 7 - 9. Supplemental Table 8 - 10. Supplemental Table 9 - 11. Supplemental Table 10 - 12. Supplemental Table 11 - 13. Supplemental Table 12 - 14. Supplemental Table 13 - 15. Supplemental Figure 1 - 16. Supplemental Figure 2 - 17. Supplemental Figure 3 - 18. Supplemental Figure 4 - 19. Supplemental Figure 5 - 20. Supplemental Figure 6 - 21. Supplemental Figure 7 - 22. Supplemental Figure 8 - 23. Supplemental Figure 9 - 24. Supplemental Figure 10 - 25. Supplemental Figure 11 - 26. Supplemental Figure 12 ### Page 2 Supplemental Methods Study population The UK Biobank recruited approximately 500,000 individuals aged between 40-69 years over 2006-2010 at 22 assessment centers across the UK. At enrollment, participants provided biological samples and detailed baseline clinical information. Longitudinal follow-ups were conducted through medical history, hospital admission records, and mortality data. Further details on the UK Biobank have been described elsewhere (1). In this analysis, we first included 441,632 unrelated participants from the UK Biobank who underwent exome sequencing from collected blood samples and had no history of hematologic cancer at baseline (2). One participant in each pair with a third-degree related determined by centrally calculated kinship coefficients in the UK Biobank was further removed to ensure unrelatedness between participants in the cohort. Two percent of participants had missing covariate data; these individuals were excluded, yielding a final analytical dataset of 431,279 participants before excluding those with prevalent diseases for each specific analysis. The All of Us Research Program (AoU) is a National Institute of Health-led health prospective cohort that aims to establish a large longitudinal cohort with comprehensive health and genetics information for population and precision health research, focusing on diverse populations in the U.S. (3, 4). Demographic information, diagnoses and other clinical information, such as smoking status, were ascertained from electronic health records (EHR). In this study, we included 211,028 unrelated participants with quality-controlled whole genome sequencing (WGS) data, who were free of hematological malignancies and had complete demographic information. DNA sequencing and CHIP detection As previously reported, the exomes of roughly 450,000 UK Biobank participants were sequenced from blood-derived DNA at the Regeneron Genetics Center: IDT's xGen probe library was used ### Page 3 for exome capture, followed by sequencing on the Illumina NovaSeq platform. The resulting FASTQ files for each sample were aligned to the GRCh38 reference genome, and duplicate reads were identified with Picard3 MarkDuplicates. Then, SAMtools was used to convert the binary alignment (BAM) files into CRAM files, which underwent quality control checks before submission to the UK Biobank data repository (2). CHIP was identified using GATK Mutect2 (for exome capture, followed by sequencing on the Illumina NovaSeq platform. The resulting FASTQ files for each sample were aligned to the GRCh38 reference genome, and duplicate reads were identified with Picard3 MarkDuplicates. Then, SAMtools was used to convert the binary alignment (BAM) files into CRAM files, which underwent quality control checks before submission to the UK Biobank data repository (2). CHIP was identified using GATK Mutect2 (for exome capture, followed by sequencing on the Illumina NovaSeq platform. The resulting FASTQ files for each sample were aligned to the GRCh38 reference genome, and duplicate reads were identified with Picard3 MarkDuplicates. Then, SAMtools was used to convert the binary alignment (BAM) files into CRAM files, which underwent quality control checks before submission to the UK Biobank data repository (2). CHIP was identified using GATK Mutect2 (for exome capture, followed by sequencing on the Illumina NovaSeq platform. The resulting FASTQ files for each sample were aligned to the GRCh38 reference genome, and duplicate reads were identified with Picard3 MarkDuplicates. Then, SAMtools was used to convert the binary alignment (BAM) files into CRAM files, which underwent quality control checks before submission to the UK Biobank data repository (2). CHIP was identified using GATK Mutect2 (for exome capture, followed by sequencing on the Illumina NovaSeq platform. The resulting FASTQ files for each sample were aligned to the GRCh38 reference genome, and duplicate reads were identified with Picard3 MarkDuplicates. Then, SAMtools was used to convert the binary alignment (BAM) files into CRAM files, which underwent quality control checks before submission to the UK Biobank data repository (2). CHIP was identified using GATK Mutect2 (for exome capture, followed by sequencing on the Illumina NovaSeq platform. The resulting FASTQ files for each sample were aligned to the GRCh38 reference genome, and duplicate reads were identified with Picard3 MarkDuplicates. Then, SAMtools was used to convert the binary alignment (BAM) files into CRAM files, which underwent quality control checks before submission to the UK Biobank data repository (2). CHIP was identified using GATK Mutect2 ( WGS in AoU was performed using Illumina PCR-free whole genome technology and sequenced using the NovaSeq platform and processed using DRAGEN software with corresponding configurations, and sequencing data preparation had been documented previously (10). WGS of ~250,000 individuals were used in this study from the 2 batched releases (~98,000 participants in 2022 and ~150,000 participants in 2023). Similar to CHIP calling in the UK Biobank, Mutect2 was used (11) separately in the 2 batches. As suggested by Vlasschaert et al. (11), the optimal minimum allele depth (minAD) thresholds for CHIP were different in the UK Biobank and All of Us; the minAD of 3 in defining CHIP status would increase the risk of false positive results and contamination in UK Biobank compared to minAD of 5, and in contrast to the UK Biobank, AoU has a lower contamination using minAD 3. Hence, in this study, we define CHIP status based on minAD of 5 in UK Biobank and minAD of 3 in AoU. Genotype processing ### Page 4 Comprehensive details on the quality control and imputation processes of the UK Biobank genotyping data had been documented previously (1, 2). Briefly, genotyping was conducted using either UK BiLEVE Axiom (Affymetrix Research Service Laboratory) or UK Biobank Axiom arrays, and imputation was performed using the Haplotype Reference Consortium (HRC) or a merged UK10K+1000 Genomes reference panel. Principle component analysis (PCA) was then carried out with fastPCA on a pruned set of 147,604 single nucleotide variants (SNVs) among unrelated participants. Study outcomes The three outcomes for this study were IBD, CD, and UC, where IBD was derived as a combination of UC and CD. In the UK Biobank, both UC and CD were defined by a combination of self-reported health information, hospital inpatient data, and UK death registries. Details of ICD codes and field codes used can be found in supplemental Table 2. Participants with a history of UC or CD at baseline were classified as having prevalent IBD. Among participants who were free of IBD at baseline, a new diagnosis or incidence of CD or UC during the follow-up period was considered an incident IBD event. If a participant was diagnosed with both CD and UC during follow-up, the earlier diagnosis date determined the time to the IBD event. Parallelly, the same codes (supplemental Table 2) were used to curate diagnoses for UC and CD, and thus IBD, from the Controlled Tier Dataset v8 for AoU. Given the relatively small number of cases, we only focused on IBD to replicate the UK Biobank’s discovery. Two-sample Mendelian randomization We performed two-sample Mendelian randomization (MR) analyses for the significant association discovered between CHIP and disease outcomes. Given that most large-scale IBD GWAS are conducted for CD and UC separately, we focused our analysis on these specific subtypes.Outcome summary statistics of genome-wide association analysis (GWAS) of both UC and CD ### Page 5 were obtained from Verma et.al. (12), and exposure summary statistics of CHIP and its driver mutation from our multi-cohort, multi-ancestry meta-analysis of CHIP GWAS with 648,992 participants from UK Biobank, Trans-Omics for Precision Medicine (TOPMed) Program, Vanderbilt BioVU, and Mass General Brigham Biobank (13); we limited the ancestry of both summary statistics to European ancestry. Genetic instruments of CHIP (and its driver mutations) were restricted to unrelated (r 2 <0.1 within 1Mb) genome-wide significant (P <5×10⁻6 ) variants. Inverse-variance weighting was used as the main MR method, and sensitivity analyses included MR-Egger and MR using a Robust Adjusted Profile Score (MR-RAPS). Dextran sulfate sodium (DSS)-induced Chronic Ulcerative Colitis (cUC) model 8-10-week-old B6-wild-type (WT), D3a-/- (KO) and/ or D3a+/- (heterozygous) mice were used to develop chronic Ulcerative Colitis (cUC) model by oral administration of DSS (MW 36-50 kDa colitis grade, MP Biomedicals, Santa Ana, CA) in sterile drinking water. Mice were treated for 3-4 cycles with DSS in drinking water for 5 days followed by 7 days of rest. Mice were monitored daily during DSS and recovery cycles as described previously (14). One week after the last cycle of DSS, mice were sacrificed, and tissue samples were harvested for analysis. Assessment of progression of myelopoiesis in DSS-induced cUC model The progression of myelopoiesis in mice was assessed in each resting cycle by counting white blood cells (WBCs) using Element HT5-Heska and flow-cytometry analysis of peripheral blood stained with CD11b, Gr-1 and B220 antibodies. Colon lengths measurement in DSS-induced cUC model Colon lengths were measured on sacrifice day from the ileocecal junction to the rectum and presented in centimeters (cm). Isolation of lymphocytes from the lamina propria (LP) of the colon ### Page 6 Colons were opened longitudinally, washed with PBS, and cut into small pieces. For epithelialremoval, tissue was washed for three 20 min in RPMI 1640 with 5% heat-inactivated fetal bovineserum (FBS), 100 U/mL penicillin, 100 μg/mL streptomycin, 25 mM HEPES, 2 mM L-glutamine,55 μM 2-ME, and 2 mM EDTA at 37 °C. Tissue was then digested in RPMI 1640 containing 1 mg/mL Collagenase IV and 200 U/mL DNase I at 37 °C for 1 h. The suspension was filtered through a 70 μm strainer, centrifuged at 450 × g for 10 min at 4 °C, washed once, and LPlymphocytes were enriched on a 40/ 70% Percoll gradient. Cells were collected for downstream analysis. Immunophenotyping Single cell suspension preparation and immunophenotyping were performed as previously described (15). Briefly, bone marrow was flushed with Iscove Modified Dulbecco Medium (IMDM, Invitrogen), and spleens were crushed between the microscopic slides, flushed using syringe filled with IMDM and filtered through a 50μm nylon filters. Red blood cells (RBCs) from bone marrow and splenocytes were lysed in a 0.8% NH4Cl RBC lysis buffer for 5 min at room temperature and then cells were resuspended in phosphate buffered saline containing 1% bovine serum albumin (BSA, Sigma) and 10% rat serum (Sigma). After counting the cells in cell viability analyzer (Vi- CELL-XR, Bechmann Coulter) equal number of cells were used for staining with flow antibodies. For intracellular flow cytometry (ICFC), freshly prepared bone marrow cells and colonic LPL cells were pre-stained by using cell surface antibodies and then fixed with BioLegend Cytofix and washed using BioLegend Cytoperm three times. Then pre-stained cells were re-stained with the appropriate indicated antibodies of intracellular proteins. The stained single-cell suspensions were subjected to multi-parametric flow cytometric analysis using LSR-II, and LSR Fortessa flow cytometers with diva software (BD biosciences), and the data were analyzed using FlowJo software (v10.7.0). A list of complete reagents used in this study is provided in Supplemental Table 3. ### Page 7 Competitive repopulation assay For competitive bone marrow transplantation (BMT) assay, recipient (F1 mice, CD45.1 + /CD45.2+ ) mice were irradiated at 1100 cGy from a cesium source using a split two dose of 700cGy and 400 cGy at an interval of 4 hrs. 0.2×10 6 BM mono-nuclear donor cells from WT-control or D3a-/- mice (CD45.2+ ) along with 0.2×10 6 Boy/J (CD45.1+ ) BM mono-nuclear competitor cells were transplanted by intravenous injection into lethally irradiated F1 recipient mice. Engraftment of donor cells in the peripheral blood was assessed at 4 weeks post-transplant by flow cytometry. F1 mice were randomized into the following groups: 1) WT+Veh, 2) WT+DSS+Veh, 3) WT+DSS+APX3330, 4) D3a-/-+Veh, 5) D3a-/-+DSS+Veh, and 6) D3a-/-+DSS+APX3330. Groups 1, 2, and 4, 5 were gavaged with vehicle (Veh), and groups 3 and 6 were gavaged with APX3330 at 50 mg/kg, mouse body weight, two times a day. The treatment regimen commenced 7 days prior to the initiation of DSS (3%, w/v in sterile drinking water) and continued throughout the DSS treatment cycles. One week after the final dose of DSS, mice were sacrificed for complete analysis. In vivo APE1/Ref-1 inhibitor APX3330 drug treatment For APX3330 treatment, mice were randomized as described in the competitive repopulation assay and in primary, non-competitive experiments, as indicated in the figure legends when necessary. APX3330 drug was dissolved in Cremophor: Ethanol (1:1) (Cremophor from Sigma, catalog no. C5135) for stock solution preparation and diluted with 0.5% methylcellulose prior to use. Mice were treated either with vehicle or APX3330 drug at 50 mg/kg body weight, twice a day by oral gavage, one week prior to the start of DSS treatment and continued throughout the 4 DSStreatment cycles. Western blotting ### Page 8 Protein extracts from the colon lamina propria (LP) cells and BM were prepared in RIPA buffer with protease and phosphatase inhibitors. Equal amounts were separated by 4%-20% SDS- polyacrylamide gel, transferred to nitrocellulose, blocked with 5% milk in 0.1% Tween-20/ Tris- buffered saline (TBS-T), and incubated with primary antibodies overnight at 4°C. After washing inTBS-T buffer, membranes were incubated with HRP-conjugated secondary antibodies for 1 h atroom temperature and developed with Super Signal West Dura, ECL substrate (ThermoFisher). Peripheral blood serum cytokine profiling Peripheral blood (PB) serum was collected and analyzed for cytokines and chemokines by Eve Technologies (Canada) as described before (16). Results are expressed as picograms/milliliter (pg/mL). CODEX multiplexing on colon Tissue CODEX (CO-Detection by indEXing) multiplex tissue imaging was performed on colon sections from the following cohorts: WT-DSS+Veh, Dnmt3a (D3a-/-)-DSS+Veh, and D3a-/--DSS-APX3330. Fresh-frozen tissues were embedded in OCT and sectioned at 10μm thickness for samplepreparation, as described in our previous publication (17). Antibody staining included both inventoried antibodies purchased from Akoya (CD11b, F4/80, CD45, B220, CD3, and CD4), and customized antibodies for Gr-1, and APE1 prepared by in-house conjugation. Three antibodies were stained per cycle, and each cycle was paired with a corresponding blank for background subtraction. By employing multiple staining cycles, this approach enabled simultaneous detection of several markers within the same tissue section. Whole-slide scans were acquired in QPTIFF format and images were obtained using Akoya’s Phenochart software (v2.2.0). Image analysis was performed as described in our previous publication (17). Spatial cell segmentation and quantitative analyses were conducted using the Indica Labs HALO platform, which provides single-nuclei segmentation and accurate cell ### Page 9 identification while minimizing artifacts. Quantification was performed on whole colon sections, and cell frequencies were calculated across cohorts as described (17). Statistical analysis In the UK Biobank, Cox's proportional-hazard models were used (Survival R package version "3.1.12") to examine the association between the presence of CHIP - defined as (i) any CHIP mutation across all driver mutations, (ii) large-CHIP clones, (VAF≥10%), and (iii) individual CHIP gene mutations and their large clones. Analyses were stratified by sex, as well as by age groups (i.e., <45, 45-60, >60 years old). Follow-up time began at study enrollment and extended until the first occurrence of the outcome, death, loss of follow-up, or the end of the study. Models were adjusted for age at enrollment, sex, first 10 principal components of genetic ancestry, BMI, smoking status, and white British ancestry. Unlike the UK Biobank cohort, which has various conditions and medical records throughout long follow-up periods, AoU has a relatively short follow-up (2018-2021 enrollment). Therefore, we combined prevalent and incident cases and adopted a cross-sectional design with applying logistic regression and adjusting for age, sex, race, 10 principal components, BMI, and smoking status. Statistical significance was defined using two-tailed P values, and a significance level of 0.05. All UK Biobank analyses were performed with R version 4.0.0, and the analyses of AoU wereperformed with R version 4.4.0 in the AoU research workbench. All mouse data are presented as mean ± SEM, and the statistical significance was assessed by one-way or two-way analysis of variance (ANOVA) with Tukey’s multiple comparison test using GraphPad Prism version 10 (GraphPad, San Diego, CA). P values <0.05 were considered statistically significant. Study approval ### Page 10 The secondary use of human data for the present analysis was approved by the Massachusetts General Hospital Institutional Review Board (protocol 2021P002228) and facilitated through UK Biobank Application 7089. All animal procedures were conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee (IACUC) at Indiana University School of Medicine. ### Page 11 Supplemental Table 1. List of 74 hematopoietic genes and variants queried for calling clonal hematopoiesis of indeterminate potential. | Gene name | Reported mutations used for variant calling | | - | - | | ASXL1 | Frameshift/nonsense/splice-site p.358-1541 | | ASXL2 | Frameshift/nonsense/splice-site in p.380-1435 | | BCOR | Frameshift/nonsense/splice-site | | BCORL1 | Frameshift/nonsense/splice-site | | BRAF | G464E, G464V, G466E, G466V, G469R, G469E, G469A, G469V, V471F, V472S,L485W, N581S, I582M, I592M, I592V, D594N, D594G, D594V, D594E, F595L, F595S, G596R, L597V, L597S, L597Q, L597R, A598V, T599I, V600M, V600L, V600K, V600R, V600E, V600A, V600G, V600D, K601E, K601N, R603*, W604R, W604G, S605G, S605F, S605N, G606E, G606A, G606V, H608R, H608L, G615R, S616P, S616F, L618S, L618W | | BRCC3 | Frameshift/nonsense/splice-site | | CBL | RING finger missense p.381-421 | | CBLB | RING finger missense p.372-412 | | CEBPA | Frameshift/nonsense/splice-site | | CREBBP | Frameshift/nonsense/splice-site, D1435E, R1446L, R1446H, R1446C, Y1450C, P1476R, Y1482H, H1487Y, W1502C, Y1503D, Y1503H, Y1503F, S1680del | | CTCF | Frameshift/nonsense, R377C, R377H, P378A, P378L | | CUX1 | Frameshift/nonsense | | DNMT3A | Frameshift/nonsense/splice-site, F290I, F290C, F290S, G293R, L295P, L295Q, L295V, V296G, V296L, V296M, W297C, W297L, W297R, W297G, G298W, G298R, G298E, W306C, P307S, P307R, P307L, P307T, G308D, I310F, I310L, I310S, I310T, S312F, R326G, R326H, R326L, R326C, R326S, V328A, V328D, V328G, F331V, G332R, G332E, S337A, S337L, S337P, V339A, V339M, V339G, L344Q, L344P, L344R, L347P, L347R, L347Q,S352N,Y365C, R366C, R366P, R366H, R366G, A368D, A368T, A368V, I369N, I369S, V372D, L373Q, A376P, A376T, A376V, R379H, R379L, R379C, R379S, D389N, I407T, I407N, I407S, W409R, A410D, A410T, G413V, F414L, F414I, F414S, F414V, F414C, K468R, E477Q, E477K, V483G, R484Q, R484W, C494Y, C497G, C497R, C497Y, G498E, | ### Page 12 | H506R, G511E, C514Y, Q527H, Q527P, D529N, D529V, D531N, D531Y, Y533C,S535F, S535P, C537G, C537R, C540Y, G543A, G543S, G543C, G543D, G543V, L547H, L547P, L547F, L547R, C537Y, M548I, M548L, M548K, M548R, M548T, G542V,G550R, C554Y, R556K, R556S, R556G, C559R, C559Y, C562Y, V563M, P580L, W581R, W581G, W581C, W581S, C583S, C583Y, C586G, C586R, C586Y, K589N, L595P, R596W, R598Q, R604Q, R604W, P633H, P633L, I634F, I634T, R635G, R635L, R635P, R635W, R635Q, V636A, V636G, V636M, V636L, L637R, L637P, L637Q, S638F, S638P, S638Y, L639R, L639V, L639F, A644T, T645A, G646V, G646E, L647H, L648P, V649G, V649L, V649M, L650V, L650Q, L653W, L653F, I655N, I655T, Q656K, V657A, V657M, V657G, D658V, D658Y, R659C, R659G, R659H, Y660C, Y660N, Y660F, Y660H, Y660D, A662D, S663L, S663W, E664K, V665G, V665L, S669F, S669P, M674V, V675A, V675M, R676L, R676W, R676Q, I681N, I681S, I681M, M682R, Y683D, V684F, G685R, G685E, G685A, D686Y, D686G, D686H, D686V, V687L, D686A, V687F, R688C, R688G, R688H, V690G, V690F, V690D, T691I, I695N, H694Y, H694P, I695F I695T, Q696P,W698C, W698R, W698S G699R, G699S, G699D, G699V, P700L, P700S, P700R, P700Q, P700T, P700A, F701V, D702A, D702G. D702E, D702V, D702N, D702Y, L703P, L703R, L703V, V704A, V704M, V704G, I705F, I705T, I705S, I705N, G706E, G706W, G706R, G706V, G707C, G707D, G707S, G707R, G707V, C710S, C710Y, D712A, L713F, S714C, V716D, V716F, V716I, N717S, N717I, P718L, R720C, R720H, R720G, R720S, K721R, K721T, K721N, Y724C, E725K, G726V, G728D, R729Q, R729W, R729G, R729L, F731C, F731L, F731Y, F731I, F731V, F732del, F732C, F732I, F732S, F732L, F732V, E733G, E733A, E733V, F734L, F734C, F734V, Y735C, Y735N, Y735S, Y735F, Y735H, R736G, R736H, R736C, R736L, R736P, R736S, L737H, L737P, L737V, L737F, L737R, L737P, L738P, L738Q, H739P, A741G, A741V, R742L, R742G, R742P, P743H, P743R, P743L, P743S, R749C, R749L, R749H, R749G, P750R, F751L, F751C, F751I, F751V, F752del, F752C, F752L, F752I, F752V, W753G, W753C, W753L, W753R, W753S, L754P, L754R, L754H, F755S, F755I, F755L, M761I, M761V, G762C, V763G, V763I, K766E, D768E, D768H, D768V, D768Y, I769N, I769S, I769T, I769V, S770L, S770W, S770P, R771G, R771L, R771P, R771Q, F772C, F772I, F772V, L773H, L773I, L773R, L773V, E774A, E774K, E774D, E774G, E774V, S775F, S775P, P777A, P777H, P777L, P777R, P777T, P777S, V778M, I780N, I780S, I780T, D781G, V785M, A787G, A787S, H789Q, R790W, A791V, R792C, | | - | ### Page 13 | Frameshift/nonsense, L240Q, I363M Frameshift/nonsense, VF1148_1149del, D1399N, D1399Y, P1452L, Y1467N, Y1467H, Y1467C, R1627W, A1629V | R792H, R792S, F794L, F794V, W795S, W795G, W795C, W795L, W795R,G796A, G796C, G796D, G796V, N797D, N797Y, N797H, L798P, L798H, N797K, N797S, P799L, P799A, P799T, P799S, P799R, P799H, G800S, M801I, M801R, M801T, M801V, R803S, R803G, R803K, R803T, R803W, R803M, P804L, P804S, L815Q, H821D, H821P, H821R, K826N, K826T, K826R, S828N, K829R, T835M, N838D, S839P, K841N, K841T, K841Q, Q842E, Q842R, G843S, P849L, M853R, M852L, M852V, D857N, W860R, E863D, E863G, E863K, E863V, F868S, F868L, G869S, G869V, F870V, H873R, Y874C, R879D, M880I, M880L, M880V, S881R, S881I, R882H, R882P, R882L, R882C, R882G, R882S, A884P, A884V, R885K, Q886E, Q886R, L889P, L889R, G890D, G890R, G890S, G890V, W893S, V895M, P896L, P898S, V897G, V897D, I898T, R899P, R899L, R899G, R899H, R899C, R899S, L901P, L901R, L901H, L901V, A903P, A903T, P904L, P904Q, P904A, P904R, P904S, L905R, L905P, L905Q, L905V, K906E, E907G, Y908C, Y908D, Y908N, F909C, A910P, A910V, C911R, C911Y | EED | EP300 | | - | - | - | - | | ETNK1 | N244S, N244T, N244K | | ETV6 | Frameshift/nonsense | | EZH2 | Frameshift/nonsense, Q62R, N102S, F145S, F145C, F145Y, F145L, G159R, E164D, R202Q, K238E, E244K, R283Q, H292R, P488S, R497Q, R561H, T568I, K629E, Y641N, Y641H, Y641S, Y641C, Y641F, D659Y, D659G, V674M, A677G, A677V, R679C, R679H, R685C, R685H, A687V, N688I, N688K, H689Y, S690P, I708V, I708T, I708M, E720K, E740K | | FLT3 | V579A, V592I, F594L, FY590-591GD, D835Y, D835H, D835E, del835 | | GATA1 | Frameshift/nonsense | | GATA2 | Frameshift/nonsense, R293Q, N317H, A318T, A318V, A318G, G320D, L321P, L321F, L321V, Q328P, R330Q, R361L, L359V, A372T, R384G, R384K | | GATA3 | Frameshift/nonsense/splice-site ZNF domain, R276W, R276Q, N286T, L348V | | GNA13 | I34T, G57S, S62F, M68K, Q134R, Y145F, L152F, E167D, Q169H, R264H, E273K, V322G, V362G, L371F | | GNAS | R201(844) G, R201(844) S, R201(844) C, R201(844) H, R201(844)L, Q227(870)K, Q227(870)R, Q227(870)L, Q227(870)H, R374(1017)C | | GNB1 | K57N, K57M, K57E, K57T, I80T, I80N | ### Page 14 | IDH1 | R132C, R132G, R132H, R132L, R132P, R132V | | - | - | | IDH2 | R140W, R140Q, R140L, R140G, R172W, R172G, R172K, R172T, R172M,R172N, R172S | | IKZF1 | Frameshift/nonsense | | IKZF2 | Frameshift/nonsense | | IKZF3 | Frameshift/nonsense | | JAK1 | T478A, T478S, V623A, A634D, L653F, R724H, R724Q, R724P, T782M, L783F | | JAK2 | N533D, N533Y, N533S, H538R, K539E, K539L, I540T, I540V, V617F, R683S, R683G, del/ins537-539L, del/ins538-539L, del/ins540-543MK, del/ins540-544MK, del/ins541-543K, del542-543, del543-544, ins11546-547 | | JAK3 | M511T, M511I, A572V, A572T, A573V, R657Q, V715I, V715A | | KDM6A | Frameshift/nonsense/splice-site, del419 | | KIT | ins503, V559A, V559D, V559G, V559I, V560D, V560A, V560G, V560E, del560, E561K, del579, P627L, P627T, R634W, K642E, V654A, V654E, H697D, E761D, K807R, D816H, D816Y, D816F, D816I, D816V, D816H, del551-559 | | KRAS | G12D, G12A, G12E, G12V, G13D, G13C, G13Y, G13F, G13R, G13A, G13V, G13E, V14I, L19F, T58I, G60D, G60A, G60V, Q61K, Q61E, Q61P, Q61R, Q61L, Q61H, K117E, K117N, A146T, A146P, A146V | | LUC7L2 | Frameshift/nonsense/splice-site | | MLL | Frameshift/nonsense | | MLL2 | Frameshift/nonsense | | MPL | S505G, S505N, S505C, L510P, del513, W515A, W515R, W515K, W515S, W515L, A519T, A519V, Y591D, W515-518KT | | NF1 | Frameshift/nonsense | | NPM1 | Frameshift p. W288fs (insertion at c.859_860, 860_861, 862_863, 863_864) | | NRAS | G12S, G12R, G12C, G12N, G12P, G12Y, G12D, G12A, G12V, G12E, G13S, G13R, G13C, G13N, G13P, G13Y, G13D, G13A, G13V, G13E, G60E, G60R, Q61R, Q61L, Q61K, Q61P, Q61H, Q61Q | | NXF1 | Frameshift/nonsense/splice-site | | PDS5B | Frameshift/nonsense/splice-site, R1292Q | | PHF6 | Frameshift/nonsense/splice-site, A40D, M125I, S246Y, F263L, R274Q, C297Y, H302Y, H329L | | PHIP | Frameshift/nonsense/splice-site | | PPM1D | Frameshift/nonsense, exon 5 or 6 | ### Page 15 | PRPF8 | M1307I, C1594W, D1598Y, D1598N, D1598V (ADD MORE VARS) | | - | - | | PTEN | Frameshift/nonsense, D24G, R47G, F56V, L57W, H61R, K66N, Y68H, C71Y,F81C, Y88C, D92G, D92V, D92E, H93Y, H93D, H93Q, N94I, P95L, I101T, C105F, C105S, D107Y, L112V, H123Y, C124R, C124S, K125E, A126D, K128N, R130G, R130Q, R130L, G132D, I135V, I135K, C136R, C136F, K144Q, A151T, D153Y, D153N, Y155H, Y155C, R159K, R159S, R161K, R161I, G165R, G165E, S170N, S170I, R173C, Y174D, Y177C, H196Y, R234W, G251C, D252Y, F271S, D326G | | PTPN11 | G60V, G60R, G60A, D61Y, D61V, D61G, Y63C, E69K, E69G, E69D, E69Q, F71L, F71K, A72T, A72V, A72D, T73I, E76K, E76Q, E76M, E76A, E76G, E139G, E139D, N308D, N308T, N339S, P491L, S502P, S502A, S502L, G503V, G503G, G503A, G503E, Q506P, T507A, T507K | | RAD21 | Frameshift/nonsense/splice-site, R65Q, H208R, Q474R | | RUNX1 | Frameshift/nonsense/splice-site, S73F, H78Q, H78L, R80C, R80P, R80H, L85Q, P86L, P86H, S114L, D133Y, L134P, R135G, R135K, R135S, R139Q, R142S, A165V, R174Q, R177L, R177Q, A224T, D171G, D171V, D171N, R205W, R223C | | SETBP1 | D868N, D868T, S869N, G870S, I871T, D880N, D880Q | | SETD2 | Frameshift/nonsense, V1190M | | SETDB1 | Frameshift/nonsense, K715E | | SF3B1 | G347V, R387W, R387Q, E592K, E622D, Y623C, R625L, R625C, R625G, N626D, R630G, H662Q, H662D, T663I, K666N, K666Q, K666T, K666E, K666R, K700E, V701F, A708T, G740R, G740E, G742D, A744P, A745P, K748E, R775P, D781G, E783K, R831Q, L833F, E862K, R957Q | | SFRS2 | Y44H, P95H, P95L, P95T, P95R, P95A, P107H, P95fs | | SMC1A | K190T, R586W, M689V, R807H, R1090H, R1090C | | SMC3 | Frameshift/nonsense, R155I, Q367E, D392V, K571R, R661P, G662C | | SRCAP | Frameshift/nonsense/splice-site | | STAG1 | Frameshift/nonsense/splice-site, H1085Y | | STAG2 | Frameshift/nonsense/splice-site | | SUZ12 | Frameshift/nonsense | ### Page 16 | TET2 | Frameshift/nonsense/splice-site, missense mutations in catalytic domains (p.1104-1481 and 1843-2002), D1121Y, D1129Y, C1133R, C1133W, C1135Y, C1135F, C1135W, G1137D, G1137V, E1137K, E1137D, E1141K, E1144K, Y1148C, L1151R, G1152R, A1153T, A1153V, G1154S, C1156Y, V1157M, I1160F, I1160S, R1161G, R1161S, M1164I, E1165K, E1165D, R1167G, R1167K, R1167S, R1167M, L1172R, A1174T, I1175T, V1180D, M1185I, E1186A, G1187S, K1188R, G1192V, C1193Y, C1193W, P1194L, P1194R, I1195V, K1197E, W1198C, W1198R, V1201I, E1207D, L1209P, L1210P, C1211Y, L1212S, V1213M, V1213E, R1214W, R1214Q, R1216Q, H1219D, H1219R, H1219Y, C1221Y, C1221R, C1221S, C1221W, C1221F, L1229R, G1235E, R1235W, L1238V, A1241S, K1243R, K1243N, L1244P, Y1245C, Y1245N, L1248P, L1248R, L1252P, L1252V, G1256C, R1261C, R1261S, R1261H, R1261P, R1262W, C1263F, C1263Y, N1266D, N1266K, N1266H, N1266Y, N1266S, C1271W, C1271S, C1273S, C1273W, C1273R, Q1274P, G1275R, G1275V, G1282R, G1282D, R1283P, S1284F, F1287V, G1288D, G1288V, C1289F, C1289W, S1290L, W1291C, S1292R, M1293I, Y1294C, G1297E, G1297R, C1298Y, C1298S, K1299M, K1299Q, K1299N, F1300V, F1300L, F1300I, S1303G, S1303R, K1310Q, L1311Q, E1318E, L1322Q, L1322P, L1322R, L1326W, L1329P, L1329Q, L1332P, M1333K, L1340R, L1340P, Y1345D, Y1345C, Q1348K, Q1348R, I1349N, E1352K, A1355V, C1358S, C1358W, R1359C, R1359L, R1359P, R1359H, R1359G, R1359S, L1360R, G1361C, G1361S, G1361D, R1366H, R1366L, R1366C, P1367L, P1367S, P1367R, F1368L, G1370V, G1370R, V1371D, A1373P, A1376V, D1376G, F1377V, F1377I, C1378R, C1378Y, C1378F, H1380Y, H1380L, H1380R, H1380Q, R1380C, H1380D, H1382R, H1382P, R1383G, H1386D, R1387H, N1387S, T1393A, C1395Y, T1397I, L1398R, F1398C, F1398L, L1398H, L1398P, H1401Y, E1401A, N1403S, Q1414R, Q1414H, Q1414K, V1416I, V1417F, P1419R, D1427V, Q1435K, V1438F, G1861E, G1861R, G1861V, A1863V, H1868Y, H1868P, H1868L, G1869W, S1870L, L1872P, I1873T, I1873S, A1876T, A1876V, R1878P, R1878H, E1879Q, E1879G, E1879D, H1881N, H1881L, T1884A, T1884I, P1889L, N1890S, P1894T, P1894R, P1894L, P1894H, R1896G, I1897N, S1898F, V1900F, E1900K, V1900D, Y1902H, Y1902C, Q1903R, A1903V, H1904R, H1904Q, K1905E, T1905A, H1912R, H1912D, H1912Y, G1913D, A1919D, F1922S, Y1923H, H1925Q, K1934N, R1966C, D1981A, S1982Y | | - | - | ### Page 17 | TP53 | Frameshift/nonsense/splice-site, S46F, G105C, G105R, G105D, G108S, G108C,R110L, R110C, T118A, T118R, T118I, S127F, S127Y, L130V, L130F, K132Q, K132E, K132W, K132R, K132M, K132N, F134V. F134L, F134S, C135W, C135S, C135F, C135G, C135Y, Q136K, Q136E, Q136P, Q136R, Q136L, Q136H, A138P, A138V, A138A, A138T, T140I, C141R, C141G, C141A, C141Y, C141S, C141F, C141W, V143M, V143A, V143E, L145Q, W146C, W146L, L145R, V147G, P151T, P151A, P151S, P151H, P151R, P152S, P152R, P152L, T155P, T155A, V157F, R158H, R158L, A159V, A159P, A159S, A159D, A161T, A161D, Y163N, Y163H, Y163D, Y163S, Y163C, K164E, K164M, K164N, K164P, H168Y, H168P, H168R, H168L, H168Q, M169I, M169T, M169V, E171K, E171Q, E171G, E171A, E171V, E171D, V172D, V173M, V173L, V173G, R174W, R175G, R175C, R175H, C176R, C176G, C176Y, C176F, C176S, P177R, P177L, H178D, H178P, H178Q, H179Y, H179R, H179D, H179Q, R181C, R181Y, R181H, D186G, G187S, P190L, P190T, H193N, H193P, H193L, H193R, L194F, L194R, I195F, I195N, I195T, R196P, V197L, G199V, Y205D, Y205N, Y205C, V203M, Y205H, D208V, R213Q, R213P, F212I, R213L, R213Q, H214D, H214P, H214R, S215G, S215I, S215R, V216M, V217G, Y220N, Y220H, Y220S, Y220C, E224D, I232F, I232N, I232T, I232S, Y234N, Y234H, Y234S, Y234C, Y236N, Y236H, Y236C, M237V, M237K, M237I, C238R, C238G, C238Y, C238W, N239T, N239S, S241Y, S241C, S241F, C242G, C242Y, C242S, C242F, G244S, G244C, G244D, G245S, G245R, G245C, G245D, G245A, G245V, G245S, M246V, M246K, M246R, M246I, N247I, R248W, R248G, R248Q, R249G, R249W, R249T, R249M, P250L, I251N, L252P, I254S, I255F, I255N, I255S, L257Q, L257P, E258K, E258Q, D259Y, S261T, G262D, G262V, L265P, G266R, G266E, G266V, R267W, R267Q, R267P, E271K, V272M, V272L, R273S, R273G, R273C, R273H, R273P, R273L, V274F, V274D, V274A, V274G, V274L, C275Y, C275S, C275F, A276P, C277F, C277Y, P278T, P278A, P278S, P278H, P278R, P278L, G279E, R280G, R280K, R280T, R280I, R280S, D281N, D281H, D281Y, D281G, D281E, D281V, R282G, R282W, R282Q, R282P, E285K, E285V, E286G, E286V, E286K, K320N, L330R, G334V, R337C, R337L, A347T, L348F, T377P | | - | - | | U2AF1 | D14G, S34F, S34Y, R35L, R156H, R156Q, Q157R, Q157P | | U2AF2 | R18W, Q143L, M144I, L187V, Q190L | | WT1 | Frameshift/nonsense/splice-site | | YLPM1 | Frameshift/nonsense/splice-site | ### Page 18 | ZBTB33 | Frameshift/nonsense/splice-site, A9P, D11V, D11G, S15C, L19P, Q25E, Q25R,R26C, R26H, C32G, C32Y, V34G, V34D, T35P, R41Q, A45P, L50I, S54G, Y56C, Q59P, Q59K, V67I, V68D, L70R, R74G, I77F, I77N, Y86C, I90N, E100G, L108V, I113K, I113T, A114T, A114V, L116H, Y434H, Y434C, A435V, I437T, G438S, G438V, T441A, Y442C, D443G, I446S, P447A, L459F, E485D, Y494C, C496R, C496F, C496S, C496Y, R501T, Y503S, L509V, H512Y, H512R, N514K, S517C, Y522C, Y522H, R525C, Y526N, Y526D, C527R, C527Y, P532S, L533F, A534V, A534T, E535Q, E535K, E535A, R537C, R537H, R537L, T538A, T538R, H540N, E541K, H543D, H544R, E547K, R549K, Y550C, Q551P, C552G, C552Y, C555Y, Y562C, Q563P, S566P, Y584C, S591A | | - | - | | ZNF318 | Frameshift/nonsense/splice-site | | ZRSR2 | Frameshift/nonsense, E133G, C181F, D185G, C187Y, H191Y, I202N, F239V, F239Y, N261Y, C280R, C302R, C326R, H330R | ### Page 19 Supplemental Table 2. Fields and Codes Used in UK Biobank Phenotype Curation. | Label | Field | Coding | | - | - | - | | Ulcerative Colitis | 20002 | 1463 | | 41202 | K51,K51.0,K51.1,K51.2,K51.3,K51.4,K51.5,K51.8,K51.9 | | 41204 | K51,K51.0,K51.1,K51.2,K51.3,K51.4,K51.5,K51.8,K51.9 | | 40001 | K51,K51.0,K51.1,K51.2,K51.3,K51.4,K51.5,K51.8,K51.9 | | 40002 | K51,K51.0,K51.1,K51.2,K51.3,K51.4,K51.5,K51.8,K51.9 | | 41203 | 556,5569 | | 41205 | 556,5569 | | Crohn's Disease | 20002 | 1462 | | 41202 | K50,K50.0,K50.1,K50.8,K50.9 | | 41204 | K50,K50.0,K50.1,K50.8,K50.9 | | 40001 | K50,K50.0,K50.1,K50.8,K50.9 | | 40002 | K50,K50.0,K50.1,K50.8,K50.9 | | 41203 | 555,5550,5551,5552,5559 | | 41205 | 555,5550,5551,5552,5559 | ### Page 20 Supplemental Table 3. A list of reagents used in current study. | Reagents | Company | Catalog No. | | - | - | - | | Mouse Flow Antibodies | | Lineage cocktail antibodies Pacific Blue | Biolegend | Cat # 133310 | | C-KIT APC | Biolegend | Cat # 105812 | | Sca1 PE | Biolegend | Cat # 108108 | | CD48 FITC | Biolegend | Cat # 103404 | | CD150 PerCP/Cy5.5 | Biolegend | Cat # 115922 | | CD150 PE/Cy7 | Biolegend | Cat # 115914 | | CD34 FITC | eBiosciences | Cat #11-0341-82 | | CD16/32 PE/Cy7 | Biolegend | Cat # 101318 | | C-KIT APC/Cy7 | Biolegend | Cat # 105826 | | CD127 BV605 | Biolegend | Cat # 135041 | | CD45 Pacific Blue | Biolegend | Cat # 157212 | | B220 PE | Biolegend | Cat # 103208 | | B220 PerCP/Cy5.5 | Biolegend | Cat # 103236 | | Gr1 PerCP/Cy5.5 | Biolegend | Cat # 108408 | | Gr1 APC/Cy7 | Biolegend | Cat # 108424 | | CD11b PE | Biolegend | Cat # 101208 | | CD11b APC/Cy7 | Biolegend | Cat # 101226 | | CD3 PE/Cy7 | Biolegend | Cat # 100220 | | CD4 APC | Biolegend | Cat # 100412 | | CD4 FITC | Biolegend | Cat # 100406 | | CD8 PerCP/Cy5.5 | Biolegend | Cat # 100734 | | F4/80 PE/Cy7 | Biolegend | Cat # 123114 | | Ly6G PE | Biolegend | Cat # 127608 | | Ly6C FITC | Biolegend | Cat # 128006 | | Ly6C PerCP/Cy5.5 | Biolegend | Cat # 128012 | | CD45.1 APC | Biolegend | Cat # 110714 | | CD45.1 PE-CF594 | BD Biosciences | Cat # 562452 | | CD45.2 BV711 | Biolegend | Cat # 109847 | | CD45.2 FITC | Biolegend | Cat # 109806 | | FOXP3 AF488 | Biolegend | Cat # 126406 | | CD25 APC/Cy7 | Biolegend | Cat # 101918 | | IL-17A APC/Cy7 | Biolegend | Cat # 506940 | | IFN-γ BV605 | Biolegend | Cat # 505840 | | G-CSF AF700 | R&D Systems | Cat # IC414N-100ug | | GM-CSF PE/Cy7 | Biolegend | Cat # 505412 | | HIF-1α PE | eBiosciences | Cat #12-7528-82 | | p-NF-kB p65 (Ser536) PE | Invitrogen | Cat # MA5-37165 | | Rat IgG2a, k Isotype PE/Cy7 | Biolegend | Cat # 400521 | | Rat IgG1, k Isotype AF700 | Biolegend | Cat # 400420 | | Rat IgG2b, k Isotype PE | Biolegend | Cat # 400608 | | Rat IgG1, k Isotype PE | Biolegend | Cat # 400407 | | Rat IgG1, k Isotype BV605 | Biolegend | Cat # 400433 | | Rat IgG1, k Isotype APC/Cy7 | Biolegend | Cat # 400422 | | Western blot Antibodies | | Cyclophilin B | Cell Signaling | Cat # 43603T | ### Page 21 | p-IĸBα (Ser32) | Cell Signaling | Cat # 2859T | | - | - | - | | APE1 | Novus Biologicals | Cat # NB100-101 | | Other Reagents | | Cyto-Fast Fix/Perm Buffer Set | Biolegend | Cat # 426803 | | FOXP3 Fix/Perm Buffer Set (4X) | Biolegend | Cat # 421403 | ### Page 22 Supplemental Table 4A. Characteristics of the study population in the UK Biobank(N=431,279). | Large ASXL1 | - | 1,189 (72.9%) | | - | - | - | | Metrics¹ | No CHIP (N=416,533) | CHIP (N=14,746) | P Value² | | Age (yr) | 56.9 (8.07) | 61.2 (6.68) | <0.001 | | Male | 190,570 (45.8%) | 6,920 (46.9%) | | White British Ancestry | 349,239 (83.8%) | 12,541 (85.0%) | | Age Groups | | <45 | 43,485 (10.4%) | 429 (2.9%) | | >60 | 176,580 (42.4%) | 9,771 (66.3%) | | 45-60 | 196,468 (47.2%) | 4,546 (30.8%) | | BMI (kg/m²) | 27.4 (4.76) | 27.5 (4.62) | 0.03 | | Smoking Status | <0.001 | | Prefer not to answer | 1,645 (0.4%) | 89 (0.6%) | | Never | 228,277 (54.8%) | 7,041 (47.7%) | | Previous | 143,282 (34.4%) | 5,836 (39.6%) | | Current | 43,329 (10.4%) | 1,780 (12.1%) | | Among CHIP carriers | | DNMT3A | - | 9,186 (62.3%) | - | | Large DNMT3A³ | - | 5,475 (59.6%) | - | | TET2 | - | 2,133 (14.5%) | - | | Large TET2 | - | 1,656 (77.6%) | - | | ASXL1 | - | 1,632 (11.1%) | - - | | 1 Metrics are presented as mean (SD) for continuous variables, and n (%) for categoricalvariables.2 P values are calculated with 2-sample t-test for continuous variables, and χ² test forcategorical variables3Large CHIP was defined as VAF ≥10% | ### Page 23 | Metrics¹ | No CHIP (N=416,533) | CHIP (N=14,746) | P Value² | | - | - | - | - | | The study population was restricted to unrelated individuals in the UK Biobank who hadexome sequencing data and were free of hematological cancer at baseline, withunrelatedness defined as less than third-degree relatedness. For individual analysis onulcerative colitis, Crohn's disease, and inflammatory bowel disease, study population wasfurther restricted to the individuals free of the outcome disease at baseline. | ### Page 24 Supplemental Table 4B. Characteristics of the study population in All of Us (N=211,028). | Metrics¹ | No CHIP (N=202,884) | CHIP (N=8,144) | P Value² | | - | - | - | - | | Age (yr) | 51.2 (16.8) | 64.9 (13.7) | <0.001 | | Male | 79,460 (39.2%) | 3,491 (42.9%) | <0.001 | | White | 110,812 (54.6%) | 5,352 (65.7%) | <0.001 | | Age Groups | <0.001 | | <45 | 74,377 (36.7%) | 743 (9.1%) | | >60 | 70,931 (35.0%) | 5,700 (70.0%) | | 45-60 | 57,576 (28.4%) | 1,701 (20.9%) | <0.001 | | BMI (kg/m²) | 29.8 (8.01) | 29.1 (7.57) | <0.001 | | Smoking Status | <0.001 | | Never | 122,128 (60.2%) | 4,359 (53.5%) | | Previous | 45,785 (22.6%) | 2,589 (31.8%) | | Current | 34,971 (17.2%) | 1,196 (14.7%) | | Among CHIP carriers | | DNMT3A | - | 4,059 (49.8%) | - | | Large DNMT3A³ | - | 2,707 (66.7%) | - | | TET2 | - | 1,389 (17.1%) | - | | Large TET2 | - | 1,089 (78.4%) | - | | ASXL1 | - | 598 (7.3%) | - | | Large ASXL1 | - | 511 (85.5%) | - | | 1 Metrics are presented as mean (SD) for continuous variables, and n (%) forcategorical variables. | | 2 P values are calculated with 2-sample t-test for continuous variables, and χ² test forcategorical variables | | 3 Large CHIP was defined as VAF >10% | ### Page 25 | Metrics¹ | No CHIP (N=202,884) | CHIP (N=8,144) | P Value² | | - | - | - | - | | The study population was restricted to unrelated individuals in All of Us who had whole-genome sequencing data, passed quality-control and were free of hematologicalmalignancies at baseline. | ### Page 26 Supplemental Table 5. Incidence rate of IBD in sex and age subgroups in the UKBiobank (N=431,279). | IBD | UC | CD | | - | - | - | | Subgroup | No CHIP | CHIP | No CHIP | CHIP | No CHIP | CHIP | | Sex | Female | 43.95 | 61.84 | 32.49 | 40.09 | 19.16 | 34.11 | | Male | 53.69 | 61.73 | 42.56 | 45.25 | 19.64 | 28.84 | | Age Group | <45 | 42.18 | 51.91 | 30.27 | 34.50 | 21.54 | 51.69 | | 45-60 | 43.00 | 51.84 | 32.98 | 35.01 | 17.77 | 23.28 | | >60 | 56.15 | 67.12 | 43.50 | 46.47 | 20.68 | 34.86 | | Incidence rate in 100,000 person-years; | | The study population was restricted to unrelated individuals in the UK Biobank who had exomesequencing data and were free of hematological cancer at baseline, with unrelatedness defined asless than third-degree relatedness. For individual analysis on ulcerative colitis, Crohn's disease, andinflammatory bowel disease, study population was further restricted to the individuals free of theoutcome disease at baseline. | ### Page 27 Supplemental Table 6. Heterogeneity p-values. | Phenotype | CHIP | Group 1 | Group 2 | Group 3 | Pheterogeneity | | - | - | - | - | - | - | | IBD (UKB Analysis) | CHIP | Female | Male | - | 0.25165882 | | IBD (UKB Analysis) | Large CHIP | Female | Male | - | 0.46775935 | | IBD (AoU Analysis) | CHIP | Female | Male | - | 0.03123634 | | IBD (AoU Analysis) | Large CHIP | Female | Male | - | 0.06357874 | | Crohn's Disease | CHIP | Female | Male | - | 0.44852847 | | Crohn's Disease | Large CHIP | Female | Male | - | 0.71267165 | | Crohn's Disease | DNMT3A | Female | Male | - | 0.29886294 | | Crohn's Disease | Large DNMT3A | Female | Male | - | 0.54827489 | | Crohn's Disease | TET2 | Female | Male | - | 0.35674155 | | Crohn's Disease | Large TET2 | Female | Male | - | 0.51306547 | | Crohn's Disease | ASXL1 | Female | Male | - | 0.66309565 | | Crohn's Disease | Large ASXL1 | Female | Male | - | 0.62975027 | | Crohn's Disease | CHIP | <45 | 45-60 | >60 | 0.47812855 | | Crohn's Disease | Large CHIP | <45 | 45-60 | >60 | 0.69901070 | | Crohn's Disease | DNMT3A | <45 | 45-60 | >60 | 0.49294465 | | Crohn's Disease | Large DNMT3A | <45 | 45-60 | >60 | 0.81774114 | | Crohn's Disease | TET2 | <45 | 45-60 | >60 | 0.26356265 | | Crohn's Disease | Large TET2 | <45 | 45-60 | >60 | 0.19370888 | | Crohn's Disease | ASXL1 | <45 | 45-60 | >60 | 0.91454883 | | Crohn's Disease | Large ASXL1 | <45 | 45-60 | >60 | 0.85905128 | | Ulcerative Colitis | TET2 | <45 | 45-60 | >60 | 0.10136847 | | Ulcerative Colitis | Large TET2 | <45 | 45-60 | >60 | 0.08091369 | 1 IBD: Inflammatory Bowel Disease; 2 Pheterogeneity generated using meta-analysis between results of subgroup analysis (metagen() from R package “meta”). ### Page 28 Supplemental Table 7. Sex subgroup analysis of theassociations between CHIP andincidence of IBD¹ in UK Biobank and All of Us. | Presence of CHIP | Presence of Large CHIP² | | - | - | | Cohort | Stratum | Effect Size3 (95% CI) | P value | Effect Size (95% CI) | Pvalue | | UKBiobank | Male | 1.04 (0.79-1.37) | 0.80 | 1.05 (0.75-1.46) | 0.79 | | Female | 1.29 (1.002-1.67) | 0.049 | 1.24 (0.90-1.70) | 0.18 | | All of Us | Male | 0.87 (0.64-1.17) | 0.36 | 0.87 (0.61-1.24) | 0.44 | | Female | 1.29 (1.06-1.58) | 0.01 | 1.30 (1.03-1.64) | 0.03 | | 1 IBD: Inflammatory Bowel Disease.2Large CHIP was defined as VAF ≥10%.3 For AoU (logistic regression): the effect size is odds ratio (OR); for UKB (survival analysis): theeffect size is hazard ratio (HR);Models were adjusted for age at the time of enrollment, White British ancestry, BMI and smokingstatus; Participants with prevalent hematological cancers or IBD were removed from theanalysis. | ### Page 29 Supplemental Table 8. Sex subgroup analysis of the associations between CHIP andincidence of Crohn's disease. | Presence of CHIP | Presence of Large CHIP¹ | | - | - | | Stratum | HR (95% CI) | P value | HR (95% CI) | P value | | CHIP | Male | 1.37 (0.91-2.05) | 0.13 | 1.55 (0.98-2.46) | 0.06 | | Female | 1.68 (1.19-2.37) | 0.003 | 1.74 (1.15-2.62) | 0.008 | | DNMT3A | Male | 1.26 (0.73-2.20) | 0.41 | 1.64 (0.88-3.08) | 0.12 | | Female | 1.81 (1.22-2.69) | 0.003 | 2.09 (1.30-3.34) | 0.002 | | TET2 | Male | 1.07 (0.35-3.35) | 0.90 | 1.39 (0.44-4.32) | 0.57 | | Female | 2.07 (0.92-4.63) | 0.08 | 2.24 (0.93-5.41) | 0.07 | | ASXL1 | Male | 2.40 (1.13-5.07) | 0.02 | 2.37 (0.98-5.74) | 0.06 | | Female | 1.77 (0.57-5.52) | 0.32 | 1.58 (0.39-6.35) | 0.52 | | 1Large CHIP was defined as VAF ≥10%.Models were adjusted for age at the time of enrollment, White British ancestry, BMI andsmoking status; Participants with prevalent hematological cancers or Crohn’s diseasewere removed from the analysis. | ### Page 30 Supplemental Table 9. Age subgroup analysis of the associations between CHIP andincidence of Crohn's disease. | Presence of CHIP | Presence of Large CHIP¹ | | - | - | | Stratum | HR (95% CI) | P value | HR (95% CI) | P value | | CHIP | <45 | 2.35 (0.75-7.40) | 0.14 | 2.40 (0.59-9.70) | 0.22 | | 45-60 | 1.20 (0.71-2.05) | 0.49 | 1.35 (0.72-2.53) | 0.35 | | >60 | 1.63 (1.19-2.23) | 0.002 | 1.72 (1.20-2.47) | 0.003 | | DNMT3A | <45 | 2.29 (0.56-9.25) | 0.25 | 1.87 (0.26-13.38) | 0.53 | | 45-60 | 1.15 (0.59-2.23) | 0.68 | 1.55 (0.73-3.27) | 0.25 | | >60 | 1.75 (1.20-2.56) | 0.004 | 2.05 (1.31-3.21) | 0.002 | | TET2 | <45 | 8.09 (1.13-58.05) | 0.04 | 10.89 (1.51-78.31) | 0.02 | | 45-60 | 1.45 (0.36-5.84) | 0.60 | 1.99 (0.50-7.97) | 0.33 | | >60 | 1.41 (0.63-3.15) | 0.40 | 1.48 (0.61-3.57) | 0.38 | | ASXL1 | <45 | - | - | - | - | | 45-60 | 2.71 (0.87-8.46) | 0.09 | 1.29 (0.18-9.19) | 0.80 | | >60 | 2.02 (0.96-4.27) | 0.06 | 2.34 (1.05-5.25) | 0.04 | | 1Large CHIP was defined as VAF ≥10%. | | Models were adjusted for sex, age at the time of enrollment, White British ancestry, BMI andsmoking status; Participants with prevalent hematological cancers or CD were removed fromthe analysis. | ### Page 31 Supplemental Table 10. Age subgroup analysis of the associations between TET2 andincidence of UC¹. | Presence of CHIP | Presence of Large CHIP² | | - | - | | Stratum | HR (95% CI) | P value | HR (95% CI) | P value | | TET2 | <45 | 6.01 (0.84-43.02) | 0.07 | 7.84 (1.09-56.22) | 0.04 | | 45-60 | 0.41 (0.06-2.91) | 0.37 | 0.56 (0.08-3.97) | 0.56 | | >60 | 0.69 (0.31-1.55) | 0.37 | 0.73 (0.30-1.76) | 0.48 | | 1 UC: Ulcerative Colitis.2Large CHIP was defined as VAF ≥10%.Models were adjusted for sex, age at the time of enrollment, White British ancestry, BMIand smoking status; Participants with prevalent hematological cancers or UC wereremoved from the analysis. | ### Page 32 Supplemental Table 11. Mendelian randomization results between CHIP and UC / CD1 . | Exposure - Outcome | Methods¹ | OR (95% CI) | P value | | - | - | - | - | | CHIP - Crohn's Disease | IVW | 1.15 (1.03, 1.27) | 0.01 | | Egger | 1.24 (1.02, 1.50) | 0.03 | | Egger Intercept | 0.99 (0.98, 1.01) | 0.33 | | MR-RAPS | 1.15 (1.02, 1.28) | 0.02 | | DNMT3A - Crohn's Disease | IVW | 1.02 (0.94, 1.10) | 0.63 | | Egger | 1.13 (0.99, 1.29) | 0.07 | | Egger Intercept | 0.99 (0.97, 1.00) | 0.07 | | MR-RAPS | 1.03 (0.95, 1.12) | 0.43 | | TET2 - Ulcerative Colitis | IVW | 1.07 (1.04, 1.12) | 0.0002 | | Egger | 1.03 (0.97, 1.08) | 0.32 | | Egger Intercept | 1.02 (1.00, 1.03) | 0.01 | | MR-RAPS | 1.08 (1.03, 1.12) | 0.0004 | | ASXL1 - Crohn's Disease | IVW | 1.01 (0.90, 1.13) | 0.89 | | Egger | 1.01 (0.75, 1.36) | 0.94 | | Egger Intercept | 1.00 (0.95, 1.05) | 0.98 | | MR-RAPS | 1.00 (0.89, 1.12) | 0.97 | | 1 IVW: Inverse-variance weighting; MR-RAPS: MR using a Robust Adjusted ProfileScore. | | 2 UC: Ulcerative Colitis; CD: Crohn's Disease; | ### Page 33 Supplemental Table 12. Mendelian Randomization Results between UC / CD2 and CHIP. | Exposure - Outcome | Methods¹ | HR (95% CI) | Pvalue | | - | - | - | - | | Ulcerative Colitis - TET2 | IVW | 1.03 (0.99, 1.08) | 0.13 | | Egger | 1.03 (0.95, 1.11) | 0.51 | | EggerIntercept | 1.00 (0.99, 1.02) | 0.87 | | MR-RAPS | 1.04 (0.99, 1.08) | 0.11 | | Crohn's Disease - CHIP | IVW | 0.98 (0.96, 1.00) | 0.03 | | Egger | 0.96 (0.93, 0.99) | 0.01 | | EggerIntercept | 1.01 (1.00, 1.02) | 0.11 | | MR-RAPS | 0.98 (0.96, 1.00) | 0.03 | | Crohn's Disease - DNMT3A | IVW | 0.98 (0.96, 1.00) | 0.09 | | Egger | 0.95 (0.91, 1.00) | 0.04 | | EggerIntercept | 1.01 (1.00, 1.02) | 0.15 | | MR-RAPS | 0.98 (0.95, 1.00) | 0.09 | | Crohn's Disease - ASXL1 | IVW | 0.97 (0.92, 1.02) | 0.21 | | Egger | 0.95 (0.84, 1.08) | 0.42 | | EggerIntercept | 1.01 (0.97, 1.04) | 0.76 | | MR-RAPS | 0.97 (0.91, 1.02) | 0.22 | | 1 IVW: Inverse-variance weighting; MR-RAPS: MR using a Robust Adjusted ProfileScore. | | 2 UC: Ulcerative Colitis; CD: Crohn's Disease; | ### Page 34 Supplemental Table 13. Frequency of colon infiltrated immune cells in WT+DSS+Veh, D3a- /- +DSS+Veh and D3a-/- +DSS+APX3330 mice. | Marker | Phenotype | WT+DSS+Veh (%) | D3a-/-+DSS+Veh (%) | D3a-/-+DSS+APX3330 (%) | | - | - | - | - | - | | CD45 | CD45+ | 31.570349 | 53.288471 | 27.089645 | | CD3 | CD45+,CD3+,B220-,CD11b-,Gr-1- | 12.107862 | 23.504116 | 16.610832 | | CD4 | CD45+,CD3+,CD4+,CD8-,B220-,CD11b- ,Gr-1- | 3.135312 | 2.848264 | 3.61144 | | CD8 | CD45+ ,CD3+ ,CD8+ ,CD4- ,B220- ,CD11b- ,Gr-1- | 2.721316 | 7.005517 | 6.87506 | | CD11b | CD45+ ,CD11b+ ,Gr-1- ,CD3- ,B220- | 0.681137 | 1.134942 | 0.438139 | | Gr-1 | CD45+ ,Gr-1+ ,CD11b- ,CD3- ,B220- | 0.119926 | 0.558017 | 0.037152 | | CD11b+Gr-1 | CD45+ ,CD11b+ ,Gr-1+ ,CD3- ,B220- | 0.425845 | 0.347125 | 0.087756 | | F4/80 | CD45+ ,F4/80+ ,CD3- ,B220- | 4.057378 | 7.086481 | 2.229767 | ### Page 35 A. KM curve of All-cause mortality in CHIP and non-CHIP carriers in the UK Biobank ![A graph with numbers and lines AI-generated content may be incorrect.]() B. KM curve of All-cause mortality in large CHIP and non-large CHIP carriers in the UK Biobank ![A graph with numbers and lines AI-generated content may be incorrect.]() ### Page 36 ### Page 37 ### Page 38 ### Page 39 ### Page 40 ![A graph of different colored lines AI-generated content may be incorrect.]() ### Page 41 ### Page 42 ### Page 43 ![A screenshot of a computer screen AI-generated content may be incorrect.]() ### Page 44 ![A screenshot of a computer screen AI-generated content may be incorrect.]() ### Page 45 ![A screenshot of a computer screen AI-generated content may be incorrect.]() ### Page 46 ![A screenshot of a computer screen AI-generated content may be incorrect.]() ### Page 47 ### Page 48 ### Page 49 ### Page 50 ### Page 51 ### Page 52 ### Page 53 References for Supplemental Methods 1. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203-9. 2. 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