Mutational signatures of DNA mismatch repair deficiency in C. elegans and human cancers

Throughout their lifetime, cells are subject to extrinsic and intrinsic mutational processes leaving behind characteristic signatures in the genome. DNA mismatch repair (MMR) deficiency leads to hypermutation and is found in different cancer types. Although it is possible to associate mutational signatures extracted from human cancers with possible mutational processes, the exact causation is often unknown. Here, we use C. elegans genome sequencing of pms-2 and mlh-1 knockouts to reveal the mutational patterns linked to C. elegans MMR deficiency and their dependency on endogenous replication errors and errors caused by deletion of the polymerase epsilon subunit pole-4. Signature extraction from 215 human colorectal and 289 gastric adenocarcinomas revealed three MMR-associated signatures, one of which closely resembles the C. elegans MMR spectrum and strongly discriminates microsatellite stable and unstable tumors (AUC = 98%). A characteristic difference between human and C. elegans MMR deficiency is the lack of elevated levels of N (C) under barG > NTG mutations in C. elegans, likely caused by the absence of cytosine (CpG) methylation in worms. The other two human MMR signatures may reflect the interaction between MMR deficiency and other mutagenic processes, but their exact cause remains unknown. In summary, combining information from genetically defined models and cancer samples allows for better aligning mutational signatures to causal mutagenic processes

The chromatin remodelling enzymes SNF2H and SNF2L position nucleosomes adjacent to CTCF and other transcription

Within the genomes of metazoans, nucleosomes are highly organised adjacent to the binding sites for a subset of transcription factors. Here we have sought to investigate which chromatin remodelling enzymes are responsible for this. We find that the ATP-dependent chromatin remodelling enzyme SNF2H plays a major role organising arrays of nucleosomes adjacent to the binding sites for the architectural transcription factor CTCF sites and acts to promote CTCF binding. At many other factor binding sites SNF2H and the related enzyme SNF2L contribute to nucleosome organisation. The action of SNF2H at CTCF sites is functionally important as depletion of CTCF or SNF2H affects transcription of a common group of genes. This suggests that chromatin remodelling ATPase's most closely related to the Drosophila ISWI protein contribute to the function of many human gene regulatory elements

An international study to investigate and optimise the safety of discontinuing valproate in young men and women with epilepsy: protocol

Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men’s offspring, prompting recommendations to restrict use in everybody aged <55 years. This study will evaluate mortality and morbidity risks associated with valproate withdrawal by emulating a hypothetical randomised-controlled trial (called a “target trial”) using retrospective observational data. The data will be drawn from ∼250m mainly US patients in the TriNetX repository and ∼60m UK patients in Clinical Practice Research Datalink (CPRD). These will be scanned for individuals aged 16–54 years with epilepsy and on valproate who either continued, switched to lamotrigine or levetiracetam, or discontinued valproate between 2015–2018, creating four groups. Randomisation to these groups will be emulated by baseline confounder adjustment using g-methods. Mortality and morbidity outcomes will be assessed and compared between groups over five years, employing time-to-first-event and recurrent events analyses. A causal prediction model will be developed from these data to aid in predicting the safest alternative antiseizure medications. Together, these findings will optimise informed decision-making about valproate withdrawal and alternative treatment selection, providing immediate and vital information for patients, clinicians and regulators

An international study to investigate and optimise the safety of discontinuing valproate in young men and women with epilepsy: protocol

Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men’s offspring, prompting recommendations to restrict use in everybody aged <55 years. This study will evaluate mortality and morbidity risks associated with valproate withdrawal by emulating a hypothetical randomised-controlled trial (called a “target trial”) using retrospective observational data. The data will be drawn from ~250m mainly US patients in the TriNetX repository and ~60m UK patients in Clinical Practice Research Datalink (CPRD). These will be scanned for individuals aged 16–54 years with epilepsy and on valproate who either continued, switched to lamotrigine or levetiracetam, or discontinued valproate between 2014–2024, creating four groups. Randomisation to these groups will be emulated by baseline confounder adjustment using g-methods. Mortality and morbidity outcomes will be assessed and compared between groups over 1–10 years, employing time-to-first-event and recurrent events analyses. A causal prediction model will be developed from these data to aid in predicting the safest alternative antiseizure medications Together, these findings will optimise informed decision-making about valproate withdrawal and alternative treatment selection, providing immediate and vital information for patients, clinicians and regulators

Risk of type 2 diabetes, MASLD and cardiovascular disease in people living with polycystic ovary syndrome.

Abstract Background Polycystic ovary syndrome (PCOS) is associated with adverse clinical outcomes which may differ according to PCOS phenotype. Methods Using UK Biobank data, we compared the incidence of type 2 diabetes (T2D), metabolic dysfunction associated steatotic liver disease (MASLD), cardiovascular disease (CVD), hormone-dependent cancers, and dementia between PCOS participants, and age- and BMI-matched controls. We also compared multi-organ (liver, cardiac and brain) magnetic resonance imaging (MRI) data and examined the impact of PCOS phenotype (hyperandrogenic and normoandrogenic) on these outcomes. Results We included 1008 women with PCOS (defined by diagnostic codes, self-reported diagnoses, or clinical/biochemical features of hyperandrogenism and a/oligomenorrhoea), and 5017 matched controls (5:1 ratio); median age, 61 years, body mass index, 28.4 kg/m². Adjusted Cox proportional hazard modelling demonstrated PCOS participants had greater incident T2D (HR 1.47; 95% CI, 1.11-1.95) and all-cause CVD (1.76; 1.35-2.30). No between-group differences existed for cancers or dementia. Liver MRI confirmed more PCOS participants had hepatic steatosis (proton density fat fraction &amp;gt;5.5%: 35.9 vs. 23.9% (p=0.02)), and higher fibroinflammation (corrected T1 (cT1) (721.4 vs. 701.5ms (p=&amp;lt;0.01)), vs. controls. No between-group difference existed for cardiac (bi-ventricular/atrial structure and function) or brain (grey and white matter volumes) imaging. Normoandrogenic (but not hyperandrogenic) PCOS participants had greater incident all-cause CVD (1.82; 1.29-2.56) while hyperandrogenic (but not normoandrogenic) PCOS participants were more likely to have hepatic steatosis (8.96 vs. 6.04 vs. 5.23% (p=0.03)) with greater fibro-inflammation (776.3 vs. 707.7 vs. 701.9 ms (p=&amp;lt;0.01)). Conclusions Cardiometabolic disease may be increased in PCOS patients with a disease phenotype-specific pattern. </jats:sec

The predictive accuracy of cardiovascular risk prediction tools in inflammatory arthritis and psoriasis: An observational validation study using the Clinical Practice Research Datalink

Objectives Cardiovascular risk prediction tools developed for the general population often underperform for individuals with rheumatoid arthritis (RA), and their predictive accuracy are unclear for other inflammatory conditions that also have increased cardiovascular risk. We investigated performance of QRISK-3, Framingham Risk Score (FRS) and Reynolds Risk Score (RRS) in RA, psoriatic disease (psoriatic arthritis (PsA) and psoriasis) and ankylosing spondylitis (AS). We considered osteoarthritis as a non-inflammatory comparator. Methods We utilised primary care records from the Clinical Practice Research Datalink (CPRD) Aurum database to identify individuals with each condition and calculated 10-year cardiovascular risk using each prediction tool. Discrimination and calibration of each tool in each disease was assessed. Results Time-dependent AUC for QRISK3 was 0.752 for RA (95% CI 0.734-0.777), 0.794 for AS (95% CI 0.764-0.812), 0.764 for PsA (95% CI 0.741-0.791),0.815 for psoriasis (95% CI 0.789-0.835), and 0.698 for osteoarthritis (95% CI 0.670-0.717) indicating reasonably good predictive performance. AUC for FRS were similar, and slightly lower for RRS. FRS was reasonably well calibrated for each condition but underpredicted risk for patients with RA. RRS tended to underpredict CVD risk, whilst QRISK3 overpredicted CVD risk, especially for the most high-risk individuals. Conclusions CVD risk for individuals with RA, AS and psoriatic disease were generally less accurately predicted using each of the 3 CVD risk prediction tools than reported accuracies in the original publications. Individuals with osteoarthritis also had less accurate predictions suggesting inflammation is not the sole reason for underperformance. Disease specific risk prediction tools may be required