Chandra, Tamir

Summary Background Clonal haematopoiesis (CH), the age-related expansion of mutated blood stem cells, is detectable in around 10% of people in their seventies, rises steeply with age, and is associated with several diseases. Its relationship with neurodegeneration remains contentious, with conflicting evidence for both protective and detrimental effects on Alzheimer’s disease (AD). Methods Here, we applied COMET, a mutation-agnostic, methylation-based predictor of clonal haematopoiesis burden that estimates predicted VAF (pVAF), to examine longitudinal associations between clonal burden and brain structure in the Lothian Birth Cohort 1936. In addition, to capture broader clonal burden, we developed CIMS, a novel methylation-based score derived from clonal haematopoiesis of indeterminate potential (CHIP) EWAS summary statistics, which reflects the epigenetic profile of both mutant and wild-type blood immune cells. Blood DNA methylation and structural MRI data were available at three timepoints spanning ages 73–79 years. The analytic dataset comprised 1,091 participants, of whom 808 (pVAF) and 836 (CIMS) contributed clonality data and 744 had brain MRI; 479–481 had complete baseline and longitudinal imaging measures with covariates. Trajectories were modelled with latent growth curve models fitted by full information maximum likelihood. Findings Longitudinal trajectories of clonality and grey matter volume were significantly associated over 6 years (Std. est. = −0.176, p adj = 0.030), revealing a progressive, left-lateralised cortical atrophy pattern affecting medial temporal and parietal regions. This pattern showed significant spatial correspondence with established AD signatures ( r = 0.357, p = 0.003), suggesting that clonality is linked to AD-related patterns of neurodegeneration. Subcortical analyses revealed nominal relative preservation of the caudate and did not detect a statistically significant association with hippocampal volume, suggesting potential divergence from the canonical AD subcortical profile. The CIMS confirmed global atrophy but revealed divergent tissue-type and regional patterns, suggesting the two measures may capture distinct aspects of CH biology. Interpretation Together, these findings suggest that CH burden may mark biological processes associated with structural brain atrophy in cognitively healthy older adults, with clonality showing a regional pattern that resembles the one reported in AD. CH burden may therefore be a candidate marker of adverse brain ageing; whether it tracks AD pathology in particular, rather than age-related neurodegeneration more broadly, remains to be tested.

Abstract How embryonic cells generate large clones of cells in the adult represents a fundamental question in biology. Here using melanocyte stem cells (McSCs) in the zebrafish as a model we explore the function of the master melanocyte transcription factor (MITF) in safeguarding McSCs in embryonic development and their potential to pigment large clones in the adult. MITF is well known is for its role in the specification of melanoblasts from the neural crest (NC) and their differentiation into melanocytes, yet little is known about how this activity shapes the stem cell lineages. Here, we use live imaging coupled with single-cell transcriptomics and lineage tracing to show that MITF ( mitfa in zebrafish) protects the melanocyte stem cell (McSC) fate in zebrafish. Utilizing a temperature sensitive mitfa vc7 mutant, we show that loss of Mitfa activity leads to a surprising premature and aberrant expansion of McSC progeny at the niche during embryogenesis, coupled with novel emergent transcriptional cell states. Linage tracing of McSCs from the embryonic to juvenile stages reveals Mitfa activity is subsequently required in regeneration by Schwann cell-like and melanocyte stem cell progenitors that serve as a reservoir for fast-responding pigment progenitors. Thus, the impact of Mitfa loss on the melanocyte lineage is cell-state and stage-specific. The emergent cell states resulting from mitfa loss may have important implications for understanding how reduced MITF activity contributes to human genetic disease and melanoma.

Abstract Clonal hematopoiesis (CH) is characterized by expanding blood cell clones carrying somatic mutations in healthy aged individuals and is associated with various age-related diseases and all-cause mortality. While CH mutations affect diverse genes associated with myeloid malignancies, their mechanisms of expansion and disease associations remain poorly understood. We investigate the relationship between clonal fitness and clinical outcomes by integrating data from three longitudinal aging cohorts (n=713, observations=2,341). We demonstrate pathway-specific fitness advantage and clonal composition influence clonal dynamics. Further, the timing of mutation acquisition is necessary to determine the extent of clonal expansion reached during the host individual’s lifetime. We introduce MACS120, a metric combining mutation context, timing, and variant fitness to predict future clonal growth, outperforming traditional variant allele frequency measurements in predicting clinical outcomes. Our unified analytical framework enables standardized clonal dynamics inference across cohorts, advancing our ability to predict and potentially intervene in CH-related pathologies.

Abstract Background: Age-related clonal hematopoiesis (ARCH) is a precursor state to blood cancers and is associated with epigenetic age acceleration (EpiAgeAccel). While ARCH is associated with increased all-cause mortality and cardiovascular disease, not much is known about these risks with therapy-related clonal hematopoiesis (t-CH) – CH occurring in the context of prior cytotoxic chemotherapy/radiation exposure. Methods: Patients were prospectively recruited for CH and EpiAge assessment from Mayo Clinic between 2022 and 2024. CH status was determined using error corrected sequencing on peripheral blood (PB) DNA (sensitivity 0.5% VAF). Patients with CH were classified as t-CH if they had received chemotherapy or radiation prior to CH detection. All other CH cases were classifed as ARCH. For EpiAge analysis, PB DNA was analyzed using the Illumina MethylationEPIC array. The resulting beta values were used to obtain epigentic age estimates using Horvath’s clock, Hannum’s Clock, PhenoAge, DunedinPACE, and estimated telomere lengths (DNAmTL). Results: 106 (62%) of 170 patients assessed were found to have CH. CH patients were classified into ARCH-63 (59%) and t-CH-43 (41%). While the median chronological age (69 vs 67 years) was similar between ARCH and t-CH, t-CH patients had lower Hgb [10.9g/dL vs. 13g/dL (p=0.0001)], lower platelet [146x109/L vs. 192x109/L (p=0.0132)] and lower WBC [4.4x109/L vs. 5.2x109/L (p=0.0345)]. The 3 most common ARCH mutations were TET2 (20%), DNMT3A (19%), and ASXL1 (14%), while PPM1D (27%), TET2 (18%), and DNMT3A (14%) were most frequent in t-CH. There was no significant difference in median EpiAge via Horvath (68 vs 67.5years p=0.2826), Hannum (65 vs 66 years p=0.9333), or PhenoAge (55 vs 56 years p=0.618) between ARCH and t-CH. However, DunedinPACE of aging was higher in t-CH (1.27 vs 1.18 bioyear/chronoyear p=0.0148) and median DNAmTL was shorter in t-CH (6.35 vs 6.49kb p=0.0247), compared to ARCH (Note patients with telomere biology disorders were excluded). Multivariable regression analysis adjusting for chronologic age, smoking status, and male sex showed that both ARCH and t-CH had EpiAgeAccel via Horvath(5.8years p=0.0001, 3.4 years p=0.051), Hannum(5years p=0.001, 4.5 years p=0.007), and PhenoAge (6.7years p=0.002, 7.6 years p=0.002) clocks. t-CH more than doubled DunedinPACE (0.2 bioyear/chronoyear, p<0.001) of aging compared to ARCH (0.08 bioyear/chronoyear, p=0.026). t-CH also demonstrated a significant decrease in DNAmTL (0.34kb, p<0.001) in comparison to ARCH (0.17kb, p=0.015). With a median follow-up of 20 months, t-CH was associated with worse overall survival in comparison to ARCH, and non-CH patients (p=0.013, 93% vs. 90% alive at 10 months, 87 vs. 72% alive at 20 months). Conclusion: Our prospective CH cohort study validates the association between CH and EpiAgeAccel using several different methylation clocks and for the first time highlights an increased pace of aging and shorter DNAmTL in the context of inferior survival outcomes in t-CH. Citation Format: Marissa Li, Jenna Fernandez, Kristina Kirschner, Tamir Chandra, Kristen McCullough, Sarah Aug, Terra Lasho, Christy Finke, James Foran, Cecilia Arana Yi, Yael Kusne, Talha Badar, Abhishek Mangaonkar, Naseema Gangat, Rachel Simon, Alejandro Ferrer, Mrinal Patnaik. A prospective cohort study of biological aging and epigenetic age acceleration in 106 patients with age and therapy-related clonal hematopoiesis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Methylation, Clonal Hematopoiesis, and Cancer; 2025 Feb 1-4; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2025;85(3 Suppl):Abstract nr A015.

Background: Age-related clonal hematopoiesis (ARCH) is a precursor state to blood cancers and is associated with epigenetic age acceleration (EpiAgeAccel) (Aging Cell, 2021). While ARCH in combination with AgeAccel has the highest risk for all cause mortality and cardiovascular disease, not much is known about context-relevant clonal hematopoiesis (CRCH) - CH occurring in the context of prior chemo/radiation, bone marrow failure and germline predisposition syndromes. CRCH has a unique mutational signature enriched in genes in DNA damage response and repair (TP53 and PPM1D). To answer this question, we assessed EpiAge in a prospective cohort of patients with both ARCH and CRCH. Methods: Patients were prospectively recruited for CH and EpiAge assessment from the Mayo Clinic CH clinic between 2022 and 2024. Demographic and clinical data including chronologic age, BMI, sex, blood counts, and medical history were recorded at the time of enrollment. CH status was determined using error corrected sequencing on peripheral blood (PB) DNA. All somatic variants with a variant allele frequency (VAF) ≥0.5% were considered as CH. For EpiAge analysis PB DNA was analyzed using the Illumina MethylationEPIC array. The resulting beta values were used to obtain epigenetic age estimates using Horvath's clock (Genome Biol., 2013), Hannum's Clock (Mol Cell., 2013), PhenoAge (Aging, 2018), DunedinPACE (eLife, 2022), and predicted telomere length (Aging, 2019). Results: 106 (62%) of 170 patients assessed were found to have CH, with the most frequent mutations being TET2 (19%), PPM1D (17%), DNMT3A (16%), ASXL1 (9%), and TP53 (6%); median VAF 9.5%. Except for a higher median chronologic age (68 vs 60 years, p<0.001) in the CH group, baseline characteristics including BMI, comorbidities, baseline blood counts, sex and tobacco use history were similar between the two groups. The CH group demonstrated significant EpiAgeAccel by all three clocks: Horvath (p=0.001), Hannum (p<0.001), and PhenoAge (p<0.001); with an increase in biological age of 4.9 years (95% CI 2-7.7) by Horvath clock, 4.8 years (95% CI 2.2-7.5) by Hannum clock, and 7 years (95% CI 2.9-10.5) by PhenoAge, after adjusting for chronologic age, sex, smoking status, and cancer history. CH was also associated with increased DunedinPACE of aging by 0.13 biological year per chronologic year (bioyear/chronoyear) (95% CI 0.06-0.2, p<0.001), and shortened telomere lengths by 0.24kb (95% CI 0.11-0.35, p<0.001) after adjusting for chronologic age and excluding patients with telomere biology disorders. CH patients were then further classified into ARCH-63 (59%) and CRCH-43 (41%). While the median chronological age (69 vs 67 years) was similar between the 2 groups, CRCH patients had lower Hgb [10.9g/dL vs. 13g/dL (p=0.0001)] , lower platelet [146x109/L vs. 192x109/L (p=0.0132)] and lower WBC [4.4x109/L vs. 5.2x109/L (p=0.0345)]. The median BMI, comorbidities, and tobacco use history were similar between the 2 groups. The 3 most common ARCH mutations were TET2 (20%), DNMT3A (19%), and ASXL1 (14%), while, PPM1D (27%), TET2 (18%), and DNMT3A (14%) were frequent in CRCH. There was no significant difference found in median EpiAge via Horvath (68 vs 67.5years p=0.2826), Hannum (65 vs 66 years p=0.9333), or PhenoAge (55 vs 56 years p=0.618) between ARCH and CRCH. However, DunedinPACE of aging was higher in CRCH (1.27 vs 1.18 bioyear/chronoyear p=0.0148) and median telomere length was shorter in CRCH (6.35 vs 6.49kb p=0.0247), in comparison to ARCH. Multivariable regression analysis was completed for both ARCH and CRCH compared to non-CH, adjusting for chronologic age, smoking status, and male sex. While both ARCH and CRCH demonstrated EpiAgeAccel via Horvath(5.8years p=0.0001, 3.4 years p=0.051), Hannum(5years p=0.001, 4.5 years p=0.007), and PhenoAge (6.7years p=0.002, 7.6 years p=0.002) clocks, CRCH more than doubled DunedinPACE (0.2 bioyear/chronoyear, p<0.001) of aging compared to ARCH (0.08 bioyear/chronoyear, p=0.026). CRCH also demonstrated double the decrease in telomere length (0.34kb, p<0.001) compared to ARCH (0.17kb, p=0.015). Conclusion: Our prospective CH cohort study validates the association between CH and EpiAgeAccel using several different methylation clocks and for the first time, highlights increased pace of aging and shorter telomere lengths in CRCH versus ARCH. Correlations with cardiovascular disease and mortality outcomes are ongoing.