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Biology subjects

Menon, U.

Publications and source records attributed to Menon, U..

5 recordsLinked to original sources

In vivo lineage tracing across human tissues using methylation barcodes in the protocadherin gene cluster

Resolving the lineage history of human cells is fundamental to understanding ageing and cancer but remains hampered by a lack of native, high-resolution markers. Here, we identify the protocadherin (PCDH) gene cluster as a naturally occurring, highly diverse methylation barcode. While PCDH methylation creates neuronal diversity in the brain, we show that stochastic methylation patterns in this region are maintained as heritable, evolvable lineage markers across multiple non-neuronal tissues, including blood, kidney, prostate, and bladder. By tracking these barcodes in serial samples over a decade, we reveal clonal dynamics with high fidelity, quantitatively recapitulating genetic clone sizes. Crucially, PCDH barcodes identify "cryptic" clonal expansions invisible to standard driver-mutation sequencing and resolve subclonal architectures via continuous epimutation. This native barcoding system provides a scalable, driver-agnostic framework for reconstructing somatic evolution in humans.

genomics↗

Methylation dynamics in the decades preceding acute myeloid leukaemia

DNA methylation is emerging as a highly sensitive and specific marker of cancer initiation and progression. How these cancer-specific methylation changes are established in the decades before cancer, however, remains largely unknown. Here, we use a unique collection of longitudinal blood samples collected annually up to 15 years prior to a diagnosis of acute myeloid leukaemia to sensitively track the dynamics of DNA methylation changes at high temporal resolution. We identify thousands of differentially methylated regions (DMRs) that exhibit altered patterns of methylation up to 10 years before acute myeloid leukaemia (AML) diagnosis. Most of these DMRs are strongly associated with expanding clones carrying somatic driver mutations. We identify a subset of epigenetic driver DMRs characterised by recurrent CpG alterations that are highly shared across pre-AML cases. These are likely to reflect early epigenetic reprogramming associated with AML development. We also reveal large numbers of stochastic passenger CpGs whose differential methylation results from hitch-hiking with clonal expansions driven by somatically acquired genetic events. These passenger CpGs can be exploited for lineage tracing to discover clonal expansions driven by missing driver mutations. Our findings show widespread changes in methylation patterns during the early stages of cancer development which could be utilised for risk prediction and therapeutic intervention.

genomics↗

Evolutionary dynamics in the decades preceding acute myeloid leukaemia

Somatic evolution in ageing tissues underlies many cancers. However, our quantitive understanding of the rules governing this pre-cancerous evolution remains incomplete. Here we exploit a unique collection of serial blood samples collected annually up to 15 years prior to diagnosis of acute myeloid leukaemia (AML) to provide a quantitative description of pre-cancerous evolutionary dynamics. Using deep duplex sequencing and evolutionary theory, we quantify the acquisition ages and fitness effects of the key driver events in AML development. The first driver mutations are typically acquired in the first few decades of life when the blood remains highly polyclonal. These early slow-growing clones subsequently acquire multiple further driver mutations which confer selective advantages up to 100-fold larger than the early drivers. These faster-growing clones harbouring multiple driver mutations can cause complete somatic sweeps of the blood decades before diagnosis, a feature strongly associated with future AML. Once established in the blood, the dynamics of driver mutations are highly predictable. Trajectories are shaped by strong clonal competition between lineages with limited evidence of other extrinsic factors playing a major role. Our data show that the clonal dynamics of blood are consistent with a set of remarkably simple evolutionary rules which strike a balance between chance and determinism.

cancer biology↗

Evaluating causal associations between previously reported risk factors and epithelial ovarian cancer: a Mendelian randomization analysis

BackgroundPreviously reported observational associations between risk factors and epithelial ovarian cancer (EOC) could reflect residual confounding, reverse causation, or measurement error. Mendelian randomization (MR) uses genetic variants as proxies for modifiable risk factors to strengthen causal inference in observational studies.\n\nMethodsWe used MR to evaluate the causal role of 13 previously reported risk factors in overall and histotype-specific EOC in up to 25,509 case subjects and 40,941 controls in the Ovarian Cancer Association Consortium. Inverse-variance weighted models were employed to generate effect estimates and MR-Egger, weighted median, and weighted mode were performed to examine evidence of horizontal pleiotropy. A Bonferroni-corrected P-value threshold was used to establish \"strong evidence\" (P<0.0038) and \"suggestive evidence\" (0.0038<P<0.05) for associations.\n\nResultsThere was strong or suggestive evidence that 9 of 13 risk factors were causally associated with overall or histotype-specific EOC. Genetic liability to endometriosis was strongly associated with EOC (OR per log odds higher liability: 1.27,95%CI:1.16-1.40;P=6.94x10-7) and lifetime smoking exposure was suggestively associated with EOC (OR per unit increase in smoking score:1.36,95%CI:1.04-1.78;P=0.02). In histotype-stratified analyses, the strongest associations found were between: height and clear cell carcinoma (OR per SD increase:1.36,95%CI:1.15-1.61;P=0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset:1.09,95% CI:1.02-1.16;P=0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per log odds higher liability:0.74,95% CI:0.62-0.90;P=0.002). There was little evidence that genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone-binding globulin were associated with ovarian cancer or its subtypes.\n\nConclusionsOur comprehensive examination of possible etiological drivers of ovarian carcinogenesis supports a causal role for few of these factors in epithelial ovarian cancer and suggests distinct etiologies across histotypes.

epidemiology↗

Metabolic profiling of adiponectin levels in adults: Mendelian randomization analysis

BackgroundAdiponectin, a circulating adipocyte-derived protein has insulin-sensitizing, anti-inflammatory, anti-atherogenic, and cardiomyocyte-protective properties in animal models. However, the systemic effects of adiponectin in humans are unknown.\n\nObjectivesOur aims were to define the metabolic profile associated with higher blood adiponectin concentration and investigate whether variation in adiponectin concentration affects the systemic metabolic profile.\n\nMethodsWe applied multivariable regression in up to 5,906 adults and Mendelian randomization (using cis-acting genetic variants in the vicinity of the adiponectin gene as instrumental variables) for analysing the causal effect of adiponectin in the metabolic profile of up to 38,058 adults. Participants were largely European from six longitudinal studies and one genome-wide association consortium.\n\nResultsIn the multivariable regression analyses, higher circulating adiponectin was associated with higher HDL lipids and lower VLDL lipids, glucose levels, branched-chain amino acids, and inflammatory markers. However, these findings were not supported by Mendelian randomization analyses for most metabolites. Findings were consistent between sexes and after excluding high risk groups (defined by age and occurrence of previous cardiovascular event) and one study with admixed population.\n\nConclusionOur findings indicate that blood adiponectin concentration is more likely to be an epiphenomenon in the context of metabolic disease than a key determinant.

epidemiology↗