Cox, Simon R.

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 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 The prevalence of clonal hematopoiesis of indeterminate potential (CHIP) in healthy individuals increases rapidly from age 60 onwards and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in stem cells that are also drivers of myeloid malignancies. We previously reported gene specific fitness effects in two longitudinal cohorts of aging. We now set out to define fitness effects across three longitudinal cohorts of aging in a total of 713 participants. We found that fitness correlates with timing of mutations, which needs to be taken into account when predicting health outcomes. We show that fitness and the time of mutations are superior predictors of outcomes such as all-cause mortality compared to the commonly used clone size (variant allele frequency). Our new predictor even outperforms age, the most important predictor for the onset of age-related disease thus far. In conclusion, the fitness landscape of mutations and their context in terms of clonal composition and timing of mutation acquisition are important parameters to bring CH predictors into the clinic.