Epigenetic mechanisms of osteoarthritis risk in human skeletal development.

The epigenome, including the methylation of cytosine bases at CG dinucleotides, is intrinsically linked to transcriptional regulation. The tight regulation of gene expression during skeletal development is essential, with ~1/500 individuals born with skeletal abnormalities. Furthermore, increasing evidence is emerging to link age-associated complex genetic musculoskeletal diseases, including osteoarthritis (OA), to developmental factors including joint shape. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged patients. Despite this, our knowledge of temporal changes to the methylome during human cartilage development has been limited. We quantified DNA methylation at ~700,000 individual CpGs across the epigenome of developing human articular cartilage in 72 samples ranging from 7-21 post-conception weeks, a time period that includes cavitation of the developing knee joint. We identified significant changes in 8% of all CpGs, and >9400 developmental differentially methylated regions (dDMRs). The largest hypermethylated dDMRs mapped to transcriptional regulators of early skeletal patterning including MEIS1 and IRX1. Conversely, the largest hypomethylated dDMRs mapped to genes encoding extracellular matrix proteins including SPON2 and TNXB and were enriched in chondrocyte enhancers. Significant correlations were identified between the expression of these genes and methylation within the hypomethylated dDMRs. We further identified 811 CpGs at which significant dimorphism was present between the male and female samples, with the majority (68%) being hypermethylated in female samples. Following imputation, we captured the genotype of these samples at >5 million variants and performed epigenome-wide methylation quantitative trait locus (mQTL) analysis. Colocalization analysis identified 26 loci at which genetic variants exhibited shared impacts upon methylation and OA genetic risk. This included loci which have been previously reported to harbour OA-mQTLs (including GDF5 and ALDH1A2), yet the majority (73%) were novel (including those mapping to CHST3, FGF1 and TEAD1). To our knowledge, this is the first extensive study of DNA methylation across human articular cartilage development. We identify considerable methylomic plasticity within the development of knee cartilage and report active epigenomic mediators of OA risk operating in prenatal joint tissues.

Deep Sedation in Pediatric Patients With Single Ventricle Physiology Outside of the Operating Room.

Background: Advancements in palliative surgery of patients with single ventricle physiology have led to an increase in the need for deep sedation protocols for painful procedures. However, positive pressure ventilation during anesthesia can result in unfavorable cardiopulmonary interactions. This patient population may benefit from sedation from these painful procedures. Methods: This study aims to demonstrate the safety and efficacy of deep sedation by pediatric intensivists outside the operating room for children with single ventricle physiology. This is a single-center, retrospective chart review on consecutive pediatric patients with single ventricle physiology who received deep sedation performed by pediatric intensivists between 2013 and 2020. Results: Thirty-three sedations were performed on 27 unique patients. The median age was 3.7 years (25th%-75th%: 2.1-15.6). The majority of the sedations, 88% (29/33), were done on children with Fontan physiology and 12% (4/33) were status-post superior cavopulmonary anastomosis. The primary cardiac defect was hypoplastic left heart in 63% (17/27) of all sedation procedures. There were 24 chest tube placements and 9 cardioversions. Ketamine alone [median dose 1.5 mg/kg (range 0.8-3.7)], ketamine [median dose 1 mg/kg (range 0.1-2.1)] with propofol [median dose 2.3 mg/kg (range 0.7-3.8)], and ketamine [median dose 1.5 mg/kg (range 0.4-3.0)] with morphine [median dose 0.06 mg/kg (range 0.03-0.20)] were the most common sedation regimens used. Adverse events (AEs) occurred in 4 patients (15%), three of which were transient AEs. All sedation encounters were successfully completed. Conclusion: Procedural deep sedation can be safely and effectively administered to single ventricle patients by intensivist-led sedation teams in selective case.

Epigenetic Contributions to Clinical Risk Prediction of Cardiovascular Disease.

BACKGROUND: Cardiovascular disease (CVD) is among the leading causes of death worldwide. The discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN-a cardiovascular risk prediction tool recommended for use in Scotland-was examined in tandem with epigenetic and proteomic features in risk prediction models in ≥12 657 participants from the Generation Scotland cohort. METHODS: Previously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cTnI (cardiac troponin I). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (ncases≥1274; ncontrols≥11 383) and visualized in a tailored R application. Splitting the cohort into independent training (n=6880) and test (n=3659) subsets, a composite CVD EpiScore was then developed. RESULTS: Sixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI (P<0.05), over a follow-up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response, and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (hazard ratio, 1.32; P=3.7×10-3; 0.3% increase in C-statistic). CONCLUSIONS: EpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the etiology of the disease.

Integration of datasets for individual prediction of DNA methylation-based biomarkers.

BACKGROUND: Epigenetic scores (EpiScores) can provide biomarkers of lifestyle and disease risk. Projecting new datasets onto a reference panel is challenging due to separation of technical and biological variation with array data. Normalisation can standardise data distributions but may also remove population-level biological variation. RESULTS: We compare two birth cohorts (Lothian Birth Cohorts of 1921 and 1936 - nLBC1921 = 387 and nLBC1936 = 498) with blood-based DNA methylation assessed at the same chronological age (79 years) and processed in the same lab but in different years and experimental batches. We examine the effect of 16 normalisation methods on a novel BMI EpiScore (trained in an external cohort, n = 18,413), and Horvath's pan-tissue DNA methylation age, when the cohorts are normalised separately and together. The BMI EpiScore explains a maximum variance of R2=24.5% in BMI in LBC1936 (SWAN normalisation). Although there are cross-cohort R2 differences, the normalisation method makes a minimal difference to within-cohort estimates. Conversely, a range of absolute differences are seen for individual-level EpiScore estimates for BMI and age when cohorts are normalised separately versus together. While within-array methods result in identical EpiScores whether a cohort is normalised on its own or together with the second dataset, a range of differences is observed for between-array methods. CONCLUSIONS: Normalisation methods returning similar EpiScores, whether cohorts are analysed separately or together, will minimise technical variation when projecting new data onto a reference panel. These methods are important for cases where raw data is unavailable and joint normalisation of cohorts is computationally expensive.

Cellular heterogeneity of the developing worker honey bee (Apis mellifera) pupa: a single cell transcriptomics analysis.

It is estimated that animals pollinate 87.5% of flowering plants worldwide and that managed honey bees (Apis mellifera) account for 30-50% of this ecosystem service to agriculture. In addition to their important role as pollinators, honey bees are well-established insect models for studying learning and memory, behavior, caste differentiation, epigenetic mechanisms, olfactory biology, sex determination, and eusociality. Despite their importance to agriculture, knowledge of honey bee biology lags behind many other livestock species. In this study, we have used scRNA-Seq to map cell types to different developmental stages of the worker honey bee (prepupa at day 11 and pupa at day 15) and sought to determine their gene expression signatures. To identify cell-type populations, we examined the cell-to-cell network based on the similarity of the single-cells transcriptomic profiles. Grouping similar cells together we identified 63 different cell clusters of which 17 clusters were identifiable at both stages. To determine genes associated with specific cell populations or with a particular biological process involved in honey bee development, we used gene coexpression analysis. We combined this analysis with literature mining, the honey bee protein atlas, and gene ontology analysis to determine cell cluster identity. Of the cell clusters identified, 17 were related to the nervous system and sensory organs, 7 to the fat body, 19 to the cuticle, 5 to muscle, 4 to compound eye, 2 to midgut, 2 to hemocytes, and 1 to malpighian tubule/pericardial nephrocyte. To our knowledge, this is the first whole single-cell atlas of honey bees at any stage of development and demonstrates the potential for further work to investigate their biology at the cellular level.

Blood-based epigenome-wide analyses of 19 common disease states: A longitudinal, population-based linked cohort study of 18,413 Scottish individuals.

BACKGROUND: DNA methylation is a dynamic epigenetic mechanism that occurs at cytosine-phosphate-guanine dinucleotide (CpG) sites. Epigenome-wide association studies (EWAS) investigate the strength of association between methylation at individual CpG sites and health outcomes. Although blood methylation may act as a peripheral marker of common disease states, previous EWAS have typically focused only on individual conditions and have had limited power to discover disease-associated loci. This study examined the association of blood DNA methylation with the prevalence of 14 disease states and the incidence of 19 disease states in a single population of over 18,000 Scottish individuals. METHODS AND FINDINGS: DNA methylation was assayed at 752,722 CpG sites in whole-blood samples from 18,413 volunteers in the family-structured, population-based cohort study Generation Scotland (age range 18 to 99 years). EWAS tested for cross-sectional associations between baseline CpG methylation and 14 prevalent disease states, and for longitudinal associations between baseline CpG methylation and 19 incident disease states. Prevalent cases were self-reported on health questionnaires at the baseline. Incident cases were identified using linkage to Scottish primary (Read 2) and secondary (ICD-10) care records, and the censoring date was set to October 2020. The mean time-to-diagnosis ranged from 5.0 years (for chronic pain) to 11.7 years (for Coronavirus Disease 2019 (COVID-19) hospitalisation). The 19 disease states considered in this study were selected if they were present on the World Health Organisation's 10 leading causes of death and disease burden or included in baseline self-report questionnaires. EWAS models were adjusted for age at methylation typing, sex, estimated white blood cell composition, population structure, and 5 common lifestyle risk factors. A structured literature review was also conducted to identify existing EWAS for all 19 disease states tested. The MEDLINE, Embase, Web of Science, and preprint servers were searched to retrieve relevant articles indexed as of March 27, 2023. Fifty-four of approximately 2,000 indexed articles met our inclusion criteria: assayed blood-based DNA methylation, had >20 individuals in each comparison group, and examined one of the 19 conditions considered. First, we assessed whether the associations identified in our study were reported in previous studies. We identified 69 associations between CpGs and the prevalence of 4 conditions, of which 58 were newly described. The conditions were breast cancer, chronic kidney disease, ischemic heart disease, and type 2 diabetes mellitus. We also uncovered 64 CpGs that associated with the incidence of 2 disease states (COPD and type 2 diabetes), of which 56 were not reported in the surveyed literature. Second, we assessed replication across existing studies, which was defined as the reporting of at least 1 common site in >2 studies that examined the same condition. Only 6/19 disease states had evidence of such replication. The limitations of this study include the nonconsideration of medication data and a potential lack of generalizability to individuals that are not of Scottish and European ancestry. CONCLUSIONS: We discovered over 100 associations between blood methylation sites and common disease states, independently of major confounding risk factors, and a need for greater standardisation among EWAS on human disease.

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

CAGE sequencing reveals CFTR-dependent dysregulation of type I IFN signaling in activated cystic fibrosis macrophages.

An intense, nonresolving airway inflammatory response leads to destructive lung disease in cystic fibrosis (CF). Dysregulation of macrophage immune function may be a key facet governing the progression of CF lung disease, but the underlying mechanisms are not fully understood. We used 5' end centered transcriptome sequencing to profile P. aeruginosa LPS-activated human CF macrophages, showing that CF and non-CF macrophages deploy substantially distinct transcriptional programs at baseline and following activation. This includes a significantly blunted type I IFN signaling response in activated patient cells relative to healthy controls that was reversible upon in vitro treatment with CFTR modulators in patient cells and by CRISPR-Cas9 gene editing to correct the F508del mutation in patient-derived iPSC macrophages. These findings illustrate a previously unidentified immune defect in human CF macrophages that is CFTR dependent and reversible with CFTR modulators, thus providing new avenues in the search for effective anti-inflammatory interventions in CF.

Unplanned Extubation During Pediatric Cardiac Intensive Care: U.S. Multicenter Registry Study of Prevalence and Outcomes.

OBJECTIVES: The epidemiology of unplanned extubations (UEs) and associated adverse outcomes in pediatric cardiac ICUs (CICU). DESIGN: Registry data (August 2014 to October 2020). SETTING: Forty-five Pediatric Cardiac Critical Care Consortium hospitals. PATIENTS: Patients receiving mechanical ventilation (MV) via endotracheal tube (ETT). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Fifty-six thousand five hundred eight MV courses occurred in 36,696 patients, with a crude UE rate of 2.8%. In cardiac surgical patients, UE was associated with longer duration of MV, but we failed to find such association in medical patients. In both cohorts, UE was associated with younger age, being underweight, and airway anomaly. In multivariable logistic regression, airway anomaly was associated with UE in all patients. Younger age, higher Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery score category, longer duration of MV, and initial oral rather than nasal ETT are associated with UE in the surgical group, but we failed to find such associations in the medical group. UE was associated with a higher reintubation rate compared with elective extubation (26.8 vs 4.8%; odds ratio [OR], 7.35; 95% CI, 6.44-8.39; p < 0.0001) within 1 day of event. After excluding patients having redirection of care, UE was associated with at least three-fold greater odds for each of ventilator-associated pneumonia (VAP), cardiac arrest, and use of mechanical circulatory support (MCS). However, we failed to identify an association between UE and greater odds of mortality (1.2 vs 0.8%; OR, 1.48; 95% CI, 0.86-2.54; p = 0.15), but uncertainty remains. CONCLUSIONS: UE in CICU patients is associated with greater odds of cardiac arrest, VAP, and MCS. Cardiac medical and surgical patients in the CICU appear to have different explanatory factors associated with UE, and perhaps these may be modifiable and tested in future collaborative population research.

Development and validation of DNA methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes.

Type 2 diabetes mellitus (T2D) presents a major health and economic burden that could be alleviated with improved early prediction and intervention. While standard risk factors have shown good predictive performance, we show that the use of blood-based DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Previous studies have been largely constrained by linear assumptions, the use of cytosine-guanine pairs one-at-a-time and binary outcomes. We present a flexible approach (via an R package, MethylPipeR) based on a range of linear and tree-ensemble models that incorporate time-to-event data for prediction. Using the Generation Scotland cohort (training set ncases = 374, ncontrols = 9,461; test set ncases = 252, ncontrols = 4,526) our best-performing model (area under the receiver operating characteristic curve (AUC) = 0.872, area under the precision-recall curve (PRAUC) = 0.302) showed notable improvement in 10-year onset prediction beyond standard risk factors (AUC = 0.839, precision-recall AUC = 0.227). Replication was observed in the German-based KORA study (n = 1,451, ncases = 142, P = 1.6 × 10-5).

Refining epigenetic prediction of chronological and biological age.

BACKGROUND: Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. METHODS: First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study). RESULTS: Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. CONCLUSIONS: The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.

Immuno-epigenetic signature derived in saliva associates with the encephalopathy of prematurity and perinatal inflammatory disorders.

BACKGROUND: Preterm birth is closely associated with a phenotype that includes brain dysmaturation and neurocognitive impairment, commonly termed Encephalopathy of Prematurity (EoP), of which systemic inflammation is considered a key driver. DNA methylation (DNAm) signatures of inflammation from peripheral blood associate with poor brain imaging outcomes in adult cohorts. However, the robustness of DNAm inflammatory scores in infancy, their relation to comorbidities of preterm birth characterised by inflammation, neonatal neuroimaging metrics of EoP, and saliva cross-tissue applicability are unknown. METHODS: Using salivary DNAm from 258 neonates (n = 155 preterm, gestational age at birth 23.28 - 34.84 weeks, n = 103 term, gestational age at birth 37.00 - 42.14 weeks), we investigated the impact of a DNAm surrogate for C-reactive protein (DNAm CRP) on brain structure and other clinically defined inflammatory exposures. We assessed i) if DNAm CRP estimates varied between preterm infants at term equivalent age and term infants, ii) how DNAm CRP related to different types of inflammatory exposure (maternal, fetal and postnatal) and iii) whether elevated DNAm CRP associated with poorer measures of neonatal brain volume and white matter connectivity. RESULTS: Higher DNAm CRP was linked to preterm status (-0.0107 ± 0.0008, compared with -0.0118 ± 0.0006 among term infants; p < 0.001), as well as perinatal inflammatory diseases, including histologic chorioamnionitis, sepsis, bronchopulmonary dysplasia, and necrotising enterocolitis (OR range |2.00 | to |4.71|, p < 0.01). Preterm infants with higher DNAm CRP scores had lower brain volume in deep grey matter, white matter, and hippocampi and amygdalae (ß range |0.185| to |0.218|). No such associations were observed for term infants. Association magnitudes were largest for measures of white matter microstructure among preterms, where elevated epigenetic inflammation associated with poorer global measures of white matter integrity (ß range |0.206| to |0.371|), independent of other confounding exposures. CONCLUSIONS: Inflammatory-related DNAm captures the allostatic load of inflammatory burden in preterm infants. Such DNAm measures complement biological and clinical metrics when investigating the determinants of neurodevelopmental differences.

Canola with Stacked Genes Shows Moderate Resistance and Resilience against a Field Population of Plasmodiophora brassicae (Clubroot) Pathotype X.

Genetic resistance is a cornerstone for managing clubroot (Plasmodiophora brassicae). However, when used repeatedly, a clubroot resistance (CR) gene can be broken rapidly. In this study, canola inbred/hybrid lines carrying one or two CR genes (Rcr1/CRaM and Crr1rutb) were assessed against P. brassicae pathotype X by repeated exposure to the same inoculum source under a controlled environment. Lines carrying two CR genes, either Rcr1 + Crr1rutb or CRaM + Crr1rutb, showed partial resistance. Selected lines were inoculated with a field pathotype X population (L-G3) at 5 × 106 resting spores/g soil, and all clubs were returned to the soil they came from six weeks after inoculation. The planting was repeated for five cycles, with diseased roots being returned to the soil after each cycle. The soil inoculum was quantified using qPCR before each planting cycle. All lines with a single CR gene were consistently susceptible, maintaining high soil inoculum levels over time. The lines carrying two CR genes showed much lower clubroot severity, resulting in a 10-fold decline in soil inoculum. These results showed that the CR-gene stacking provided moderate resistance against P. brassicae pathotype X, which may also help reduce the pathogen inoculum buildup in soil.

High variability in cardiac education and experiences during United States paediatric critical care fellowships.

BACKGROUND: Paediatric cardiac critical care continues to become more sub-specialised, and many institutions have transitioned to dedicated cardiac ICUs. Literature regarding the effects of these changes on paediatric critical care medicine fellowship training is limited. OBJECTIVE: To describe the current landscape of cardiac critical care education during paediatric critical care medicine fellowship in the United States and demonstrate its variability. METHODS: A review of publicly available information in 2021 was completed. A supplemental REDCap survey focusing on cardiac ICU experiences during paediatric critical care medicine fellowships was e-mailed to all United States Accreditation Council of Graduate Medical Education-accredited paediatric critical care medicine fellowship programme coordinators/directors. Results are reported using inferential statistics. RESULTS: Data from 71 paediatric critical care medicine fellowship programme websites and 41 leadership responses were included. Median fellow complement was 8 (interquartile range: 6, 12). The majority (76%, 31/41) of programmes had a designated cardiac ICU. Median percentage of paediatric critical care medicine attending physicians with cardiac training was 25% (interquartile range: 0%, 69%). Mandatory cardiac ICU time was 16 weeks (interquartile range: 13, 20) with variability in night coverage and number of other learners present. A minority of programmes (29%, 12/41) mandated other cardiac experiences. Median CHD surgical cases per year were 215 (interquartile range: 132, 338). When considering the number of annual cases per fellow, programmes with higher case volume were not always associated with the highest case number per fellow. CONCLUSIONS: There is a continued trend toward dedicated cardiac ICUs in the United States, with significant variability in cardiac training during paediatric critical care medicine fellowship. As the trend toward dedicated cardiac ICUs continues and practices become more standardised, so should the education.

Feasibility and ethics of using data from the Scottish newborn blood spot archive for research.

Background: Newborn heel prick blood spots are routinely used to screen for inborn errors of metabolism and life-limiting inherited disorders. The potential value of secondary data from newborn blood spot archives merits ethical consideration and assessment of feasibility for public benefit. Early life exposures and behaviours set health trajectories in childhood and later life. The newborn blood spot is potentially well placed to create an unbiased and cost-effective population-level retrospective birth cohort study. Scotland has retained newborn blood spots for all children born since 1965, around 3 million in total. However, a moratorium on research access is currently in place, pending public consultation. Methods: We conducted a Citizens' Jury as a first step to explore whether research use of newborn blood spots was in the public interest. We also assessed the feasibility and value of extracting research data from dried blood spots for predictive medicine. Results: Jurors delivered an agreed verdict that conditional research access to the newborn blood spots was in the public interest. The Chief Medical Officer for Scotland authorised restricted lifting of the current research moratorium to allow a feasibility study. Newborn blood spots from consented Generation Scotland volunteers were retrieved and their potential for both epidemiological and biological research demonstrated. Conclusions: Through the Citizens' Jury, we have begun to identify under what conditions, if any, should researchers in Scotland be granted access to the archive. Through the feasibility study, we have demonstrated the potential value of research access for health data science and predictive medicine.

Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects.

Clonal hematopoiesis of indeterminate potential (CHIP) increases rapidly in prevalence beyond age 60 and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in hematopoietic stem and progenitor cells (HSPCs). Because mutations in HSPCs often drive leukemia, we hypothesized that HSPC fitness substantially contributes to transformation from CHIP to leukemia. HSPC fitness is defined as the proliferative advantage over cells carrying no or only neutral mutations. If mutations in different genes lead to distinct fitness advantages, this could enable patient stratification. We quantified the fitness effects of mutations over 12 years in older age using longitudinal sequencing and developed a filtering method that considers individual mutational context alongside mutation co-occurrence to quantify the growth potential of variants within individuals. We found that gene-specific fitness differences can outweigh inter-individual variation and, therefore, could form the basis for personalized clinical management.

Cardiac Arrest in Children Following Cardiac Surgery: A Scoping Review of Contributing Factors.

Nearly half of children experiencing cardiac arrest following cardiac surgery do not survive hospital discharge and patients who survive often experience significant neurological impairment. Additionally, increased resource utilization following cardiac arrest translates into adverse logistical and financial consequences. Although some studies have identified patient characteristics that increase the risk of cardiac arrest after pediatric cardiac surgery, modifiable risk factors, which could provide a foundation for effective prevention strategies, have been elusive. This scoping review explores the current knowledge surrounding risk factors associated with cardiac arrest in children following cardiac surgery and provides recommendations for future research.

FutureMS cohort profile: a Scottish multicentre inception cohort study of relapsing-remitting multiple sclerosis.

PURPOSE: Multiple sclerosis (MS) is an immune-mediated, neuroinflammatory disease of the central nervous system and in industrialised countries is the most common cause of progressive neurological disability in working age persons. While treatable, there is substantial interindividual heterogeneity in disease activity and response to treatment. Currently, the ability to predict at diagnosis who will have a benign, intermediate or aggressive disease course is very limited. There is, therefore, a need for integrated predictive tools to inform individualised treatment decision making. PARTICIPANTS: Established with the aim of addressing this need for individualised predictive tools, FutureMS is a nationally representative, prospective observational cohort study of 440 adults with a new diagnosis of relapsing-remitting MS living in Scotland at the time of diagnosis between May 2016 and March 2019. FINDINGS TO DATE: The study aims to explore the pathobiology and determinants of disease heterogeneity in MS and combines detailed clinical phenotyping with imaging, genetic and biomarker metrics of disease activity and progression. Recruitment, baseline assessment and follow-up at year 1 is complete. Here, we describe the cohort design and present a profile of the participants at baseline and 1 year of follow-up. FUTURE PLANS: A third follow-up wave for the cohort has recently begun at 5 years after first visit and a further wave of follow-up is funded for year 10. Longer-term follow-up is anticipated thereafter.

A comparison of blood and brain-derived ageing and inflammation-related DNA methylation signatures and their association with microglial burdens.

Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent associations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus (ß range = 0.83-1.14, p ≤ 0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus (ß = 1.32, p = 5 × 10-4 ); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions (ß = 0.40, p = 0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.