Using a whole genome co-expression network to inform the functional characterisation of predicted genomic elements from Mycobacterium tuberculosis transcriptomic data.

A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the 'hub' elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation. This data set provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation.

Comparing clinical trial population representativeness to real-world populations: an external validity analysis encompassing 43 895 trials and 5 685 738 individuals across 989 unique drugs and 286 conditions in England.

BACKGROUND: Randomised controlled trials (RCTs) inform prescription guidelines, but stringent eligibility criteria exclude individuals with vulnerable characteristics, which we define as comorbidities, concomitant medication use, and vulnerabilities due to age. Poor external validity can result in inadequate treatment decision information. Our first aim was to quantify the extent of exclusion of individuals with vulnerable characteristics from RCTs for all prescription drugs. Our second aim was to quantify the prevalence of individuals with vulnerable characteristics from population electronic health records who are actively prescribed such drugs. In tandem, these two aims will allow us to assess the representativeness between RCT and real-world populations and identify vulnerable populations potentially at risk of inadequate treatment decision information. When a vulnerable population is highly excluded from RCTs but has a high prevalence of individuals actively being prescribed the same medication, there is likely to be a gap in treatment decision information. Our third aim was to investigate the use of real-world evidence in contributing towards quantifying missing treatment risk or benefit through an observational study. METHODS: We extracted RCTs from ClinicalTrials.gov from its inception to April 28, 2021, and primary care records from the Clinical Practice Research Datalink Gold database from Jan 1, 1998, to Dec 31, 2020. We referred to the British National Formulary to classify prescription drugs into drug categories. We conducted descriptive analyses and quantified RCT exclusion and prevalence of individuals with vulnerable characteristics for comparison to identify populations without treatment decision information. Exclusion and prevalence were assessed separately for different age groups, individual clinical specialities, and for quantities of concomitant conditions by clinical specialities, where multimorbidity was defined as having two or more clinical specialties, and medications prescribed, where polypharmacy was defined as having five or more medications prescribed. Population trends of individuals with multimorbidity or polypharmacy were assessed separately by age group. We conducted an observational cohort study to validate the use of real-world evidence in contributing towards quantifying treatment risk or benefit for patients with dementia on anti-dementia drugs with and without a contraindicated clinical speciality. To do so, we identified the clinical specialities that anti-dementia drug RCTs highly excluded yet had corresponding high prevalence in the real-world population, forming the groups with highest risk of having scarce treatment decision information. Cox regression was used to assess if the risk of mortality outcomes differs between both groups. FINDINGS: 43 895 RCTs from ClinicalTrials.gov and 5 685 738 million individuals from primary care records were used. We considered 989 unique drugs and 286 conditions across 13 drug-category cohorts. For the descriptive analyses, the median RCT exclusion proportion across 13 drug categories was 81·5% (IQR 76·7-85·5) for adolescents (aged <18 years), 26·3% (IQR 21·0-29·5) for individuals older than 60 years, 40·5% (IQR 33·7-43·0) for individuals older than 70 years, and 52·9% (IQR 47·1-56·0) for individuals older than 80 years. Multimorbidity had a median exclusion proportion of 91·1% (IQR 88·9-91·8) and median prevalence of 41·0% (IQR 34·9-46·0). Concomitant medication use had a median exclusion proportion of 52·5% (IQR 50·0-53·7) and a median prevalence of 94·3% (IQR 84·3-97·2), and polypharmacy had a median prevalence of 47·7% (IQR 38·0-56·1). Population trends show increasing multimorbidity with age and consistently high polypharmacy across age groups. Populations with cardiovascular or otorhinolaryngological comorbidities had the highest risk of having scarce treatment decision information. For the observational study, populations with cardiovascular or psychiatric comorbidities had highest risk of having scarce treatment decision information. Patients with dementia with an anti-dementia prescription and contraindicated cardiovascular condition had a higher risk of mortality (hazard ratio [HR] 1·20 [95% CI 1·13-1·28 ; p<0·0001]) compared with patients with dementia without a contraindicated cardiovascular condition. Patients with dementia with comorbid delirium (HR 1·25 [95% CI 1·06-1·48]; p<0·0088), intellectual disability (HR 2·72 [95% CI 1·53-4·81]; p=0·0006), and schizophrenia and schizotypal delusional disorders (HR 1·36 [95% CI 1·02-1·82]; p=0·036) had a higher risk of mortality compared with patients with dementia without these conditions. INTERPRETATION: Overly stringent RCT exclusion criteria do not appropriately account for the heterogeneity of vulnerable characteristics observed in real-world populations. Treatment decision information is scarce for such individuals, which might affect health outcomes. We discuss the challenges facing the inclusivity of such individuals and highlight the strength of real-world evidence as an integrative solution in complementing RCTs and increasing the completeness of evidence-based medicine assessments in evaluating the effectiveness of treatment decisions. FUNDING: Wellcome Trust, National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre, NIHR Great Ormond Street Hospital Biomedical Research Centre, Academy of Medical Sciences, and the University College London Overseas Research Scholarship.

Late effects of cancer in children, teenagers and young adults: Population-based study on the burden of 183 conditions, in-patient and critical care admissions and years of life lost.

BACKGROUND: Children, teenagers and young adults who survived cancer are prone to developing late effects. The burden of late effects across a large number of conditions, in-patient hospitalisation and critical care admissions have not been described using a population-based dataset. We aim to systematically quantify the cumulative burden of late effects across all cancer subtypes, treatment modalities and chemotherapy drug classes. METHODS: We employed primary care records linked to hospitals, the death registry and cancer registry from 1998-2020. CTYA survivors were 25 years or younger at the time of cancer diagnosis had survived ≥5 years post-diagnosis. Year-of-birth and sex-matched community controls were used for comparison. We considered nine treatment types, nine chemotherapy classes and 183 physical and mental health late effects. Cumulative burden was estimated using mean cumulative count, which considers recurring events. Multivariable logistic regression was used to investigate the association between treatment exposures and late effects. Excess years of life lost (YLL) attributable to late effects were estimated. FINDINGS: Among 4,063 patients diagnosed with cancer, 3,466 survived ≥ 5 years (85%); 13,517 matched controls were identified. The cumulative burden of late effects at age 35 was the highest in survivors of leukaemia (23.52 per individual [95% CI:19.85-29.33]) and lowest in survivors of germ cell tumours (CI:6.04 [5.32-6.91]). In controls, the cumulative burden was 3.99 (CI:3.93-4.08) at age 35 years. When survivors reach age 45, the cumulative burden for immunological conditions and infections was the highest (3.27 [CI:3.01-3.58]), followed by cardiovascular conditions (3.08 [CI:1.98-3.29]). Survivors who received chemotherapy and radiotherapy had the highest disease burden compared to those who received surgery only. These patients also had the highest burden of hospitalisation (by age 45: 10.43 [CI:8.27-11.95]). Survivors who received antimetabolite chemotherapy had the highest disease and hospitalisation burden, while the lowest burden is observed in those receiving antitumour antibiotics. Regression analyses revealed that survivors who received only surgery had lower odds of developing cardiovascular (adjusted odds ratio 0.73 [CI:0.56-0.94]), haematological (aOR 0.51 [CI:0.37-0.70]), immunology and infection (aOR 0.84 [CI:0.71-0.99]) and renal (aOR 0.51 [CI:0.39-0.66]) late effects. By contrast, the opposite trend was observed in survivors who received chemo-radiotherapy. High antimetabolite chemotherapy cumulative dose was associated with increased risks of subsequent cancer (aOR 2.32 [CI:1.06-4.84]), metastatic cancer (aOR 4.44 [CI:1.29-11.66]) and renal (aOR 3.48 [CI:1.36-7.86]) conditions. Patients who received radiation dose of ≥50 Gy experienced higher risks of developing metastatic cancer (aOR 5.51 [CI:2.21-11.86]), cancer (aOR 3.77 [CI:2.22-6.34]), haematological (aOR 3.43 [CI:1.54-6.83]) and neurological (aOR 3.24 [CI:1.78-5.66]) conditions. Similar trends were observed in survivors who received more than three teletherapy fields. Cumulative burden analyses on 183 conditions separately revealed varying dominance of different late effects across cancer types, socioeconomic deprivation and treatment modalities. Late effects are associated with excess YLL (i.e., the difference in YLL between survivors with or without late effects), which was the most pronounced among survivors with haematological comorbidities. INTERPRETATION: To our knowledge, this is the first study to dissect and quantify the importance of late morbidities on subsequent survival using linked electronic health records from multiple settings. The burden of late effects is heterogeneous, as is the risk of premature mortality associated with late effects. We provide an extensive knowledgebase to help inform treatment decisions at the point of diagnosis, future interventional trials and late-effects screening centred on the holistic needs of this vulnerable population.

Antithrombotic therapy in patients with liver disease: population-based insights on variations in prescribing trends, adherence, persistence and impact on stroke and bleeding.

BACKGROUND: Patients with liver disease have complex haemostasis and due to such contraindications, landmark randomised controlled trials investigating antithrombotic medicines have often excluded these patients. As a result, there has been limited consensus on the safety, efficacy and monitoring practices of anticoagulant and antiplatelet therapy in patients with liver disease. This study aims to investigate prescribing prevalence, adherence, persistence and impact of adherence on bleeding and stroke risk in people with and without liver disease taking anticoagulants and antiplatelets. METHODS: We employed a population-based cohort consisting of person-level linked records from primary care, secondary care and the death registry. The cohort consisted of 3,929,596 adults aged ≥ 30 years during the study period of 1998 to 2020 and registered with an NHS general practitioner in England. The primary outcome was prescribing prevalence, adherence to and persistence with anticoagulant and antiplatelet therapy comparing patients with and without liver disease. Risk factors for non-adherence and non-persistence were analysed using multivariable logistic regression and Cox regression. Impact of adherence on bleeding and ischaemic stroke was assessed. FINDINGS: Among patients with any of the six liver diseases (ALD, autoimmune liver disease, cirrhosis, HBV, HCV and NAFLD), we identified 4,237 individuals with incident atrial fibrillation (indication for anticoagulants) and 4,929 individuals with incident myocardial infarction, transient ischaemic attack, unstable angina or peripheral arterial disease (indication for antiplatelets). Among patients without liver disease, 321,510 and 386,643 individuals were identified as having indications for anticoagulant and antiplatelet therapy, respectively. Among drug-naïve individuals, prescribing prevalence was lower in patients with liver disease compared with individuals without liver disease: anticoagulants (20.6% [806/3,921] vs. 33.5% [103,222/307,877]) and antiplatelets (56.2% [2,207/3,927] vs. 71.1% [249,258/350,803]). Primary non-adherence rates (stopping after one prescription) were higher in patients with liver disease, compared with those without liver disease: anticoagulants (7.9% [64/806] vs. 4.7% [4,841/103,222]) and antiplatelets (6.2% [137/2,207] vs. 4.4% [10,993/249,258]). Among individuals who were not primary non-adherent and had at least 12 months of follow-up, patients with liver disease however had a higher one-year adherence rate: anticoagulants (33.1% [208/628] vs. 29.4% [26,615/90,569]) and antiplatelets (40.9% [743/1,818] vs. 34.4% [76,834/223,154]). Likelihood of non-adherence was lower in apixaban and rivaroxaban (relative to warfarin) and lower in clopidogrel (relative to aspirin). Increased comorbidity burden (by CHA2DS2VASc score) was associated with decreased risk of non-adherence and non-persistence with anticoagulants. Overall rates of 'non-adherent, non-persistent' were highest in warfarin (compared with apixaban and rivaroxaban) and aspirin (compared with clopidogrel or dipyridamole) in patients with and without liver disease. Among patients without liver disease, not taking antithrombotic medications for >3 months was associated with a higher risk of stroke, however, adherence to these medications was also associated with a small increase in risk of bleeding. Patients with liver disease (when compared with those without liver disease) had higher risks of stroke, especially when they stopped taking antiplatelets for >3 months. Patients with liver disease who were adherent to antiplatelets, however, had a higher risk of bleeding compared with patients without liver disease. INTERPRETATION: Use of antithrombotic medicines in patients with and without liver disease is suboptimal with heterogeneity across medicines. As patients with liver disease are excluded from major randomised trials for these drugs, our results provide real-world evidence that may inform medicine optimisation strategies. We outline challenges and opportunities for tackling non-adherence, which begins with understanding patients' views of medicines to help them make informed decisions about appropriate use. FUNDING: AGL is supported by funding from the Wellcome Trust (204841/Z/16/Z), National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre (BRC714/HI/RW/101440), NIHR Great Ormond Street Hospital Biomedical Research Centre (19RX02), the Health Data Research UK Better Care Catalyst Award (CFC0125) and the Academy of Medical Sciences (SBF006\1084). The funders have no role in the writing of the manuscript or the decision to submit it for publication.

Organ System Network Disruption Is Associated With Poor Prognosis in Patients With Chronic Liver Failure.

BACKGROUND: A healthy individual has a high degree of functional connectivity between organ systems, which can be represented graphically in a network map. Disruption of this system connectivity is associated with mortality in life-threatening acute illnesses, demonstrated by a network approach. However, this approach has not been applied to chronic multisystem diseases and may be more reliable than conventional individual organ prognostic scoring methods. Cirrhosis is a chronic disease of the liver with multisystem involvement. Development of an efficient model for prediction of mortality in cirrhosis requires a profound understanding of the pathophysiologic processes that lead to poor prognosis. In the present study, we use a network approach to evaluate the differences in organ system connectivity between survivors and non-survivors in a group of well-characterized patients with cirrhosis. METHODS: 201 patients with cirrhosis originally referred to the Clinic five at the University Hospital of Padova, with 13 clinical variables available representing hepatic, metabolic, haematopoietic, immune, neural and renal organ systems were retrospectively enrolled and followed up for 3, 6, and 12 months. Software was designed to compute the correlation network maps of organ system interaction in survivors and non-survivors using analysis indices: A. Bonferroni corrected Pearson's correlation coefficient and B. Mutual Information. Network structure was quantitatively evaluated using the measures of edges, average degree of connectivity and closeness, and qualitatively using clinical significance. Pair-matching was also implemented as a further step after initial general analysis to control for sample size and Model for End-Stage Liver Disease (MELD-Na) score between the groups. RESULTS: There was a higher number of significant correlations in survivors, as indicated by both the analysis indices of Bonferroni corrected Pearson's correlation coefficient and the Mutual Information analysis. The number of edges, average degree of connectivity and closeness were significantly higher in survivors compared to non-survivors group. Pair-matching for MELD-Na was also associated with increased connectivity in survivors compared to non-survivors over 3 and 6 months follow up. CONCLUSION: This study demonstrates the application of a network approach in evaluating functional connectivity of organ systems in liver cirrhosis, demonstrating a significant degree of network disruption in organ systems in non-survivors. Network analysis of organ systems may provide insight in developing novel prognostic models for organ allocation in patients with cirrhosis.

The role of endogenous bromotyrosine in health and disease.

Bromotyrosine is a stable by-product of eosinophil peroxidase activity, a result of eosinophil activation during an inflammatory immune response. The elevated presence of bromotyrosine in tissue, blood, and urine in medical conditions involving eosinophil activation has highlighted the potential role of bromotyrosine as a medical biomarker. This is highly beneficial in a paediatric setting as a urinary noninvasive biomarker. However, bromotyrosine and its derivatives may exert biological effects, such as protective effects in the brain and pathogenic effects in the thyroid. Understanding these pathways may yield therapeutic advancements in medicine. In this review, we summarize the existing evidence present in literature relating to bromotyrosine formation and metabolism, identify the biological actions of bromotyrosine and evaluate the feasibility of bromotyrosine as a medical biomarker.