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Association of Daily Steps with Incident Non-Alcoholic Fatty Liver Disease: Evidence from the UK Biobank Cohort.
PurposeLow physical activity has been shown to be associated with higher risk of non-alcoholic fatty liver disease (NAFLD). However, the strength and shape of this association are currently uncertain due to a reliance on self-reported physical activity measures. This report aims to investigate the relationship of median daily step count with NAFLD using accelerometer-derived step count from a large prospective cohort study.MethodsThe wrist-worn accelerometer sub-study of the UK Biobank (N = ~100,000) was used to characterise median daily step count over a seven-day period. NAFLD cases were ascertained via record linkage with hospital inpatient data and death registers or by using a measure of liver fat from imaging. Cox proportional hazards models were employed to assess the association between step count and NAFLD, adjusting for age, sociodemographic, and lifestyle factors. Mediation analyses were conducted.ResultsAmong 91,031 participants (709,440 person-years of follow-up), there were 762 incident NAFLD cases. Higher step count was log-linearly and inversely associated with risk of NAFLD. A 1000-step increase (representing 10 minutes of walking) was associated with a 12% (95% CI: 10%-14%) lower hazard of NAFLD. When using imaging to identify NAFLD, a 1,000-step increase was associated with a 6% (95% CI: 6%-7%) lower risk. There was evidence for mediation by adiposity, accounting for 39% of the observed association.ConclusionsDaily step count, a modifiable risk factor, is log-linearly and inversely associated with NAFLD. This association was only partially explained by adiposity. These findings from a large cohort study may have important implications for strategies to lower NAFLD risk.
Sex-specific cardiometabolic multimorbidity, metabolic syndrome and left ventricular function in heart failure with preserved ejection fraction in the UK Biobank.
BackgroundCardiometabolic disturbances play a central role in the pathogenesis of heart failure with preserved ejection fraction (HFpEF). Due to its complexity, HFpEF is a challenging condition to treat, making phenotype-specific disease management a promising approach. However, HFpEF phenotypes are heterogenous and there is a lack of detailed evidence on the different, sex-specific profiles of cardiometabolic multimorbidity and metabolic syndrome present in HFpEF.MethodsWe performed a retrospective, modified cross-sectional study examining a subset of participants in the UK Biobank, an ongoing multi-centre prospective cohort study in the United Kingdom. We defined HFpEF as a record of a heart failure diagnosis using ICD-10 code I50, coupled with a left ventricular ejection fraction (LVEF) ≥ 50% derived from cardiac magnetic resonance (CMR) imaging. We examined sex-specific differences in cardiometabolic comorbidity burden and metabolic syndrome, performed latent class analysis (LCA) to identify distinct clusters of patients based on their cardiometabolic profile, and compared CMR imaging-derived parameters of left ventricular function at rest in the different clusters identified to reflect possible differences in adverse cardiac remodelling.ResultsWe ascertained HFpEF in 445 participants, of which 299 (67%) were men and 146 (33%) women. The median age was 70 years old (interquartile range: [66.0-74.0]). A combination of hypertension and obesity was the most prevalent cardiometabolic pattern both in men and women with HFpEF. Most men had 2-3 clinical cardiometabolic comorbidities while most women had 1-2, despite a similar metabolic syndrome profile (p = 0.05). LCA revealed three distinct, clinically relevant phenogroups, namely (1) a most male and multimorbid group (n = 117); (2) a group with a high prevalence of severe obesity, abnormal waist circumference and with the highest relative proportion of females (n = 116); and finally (3) a group with an apparently lower comorbidity burden aside from hypertension (n = 212). There were significant differences in clinical measurements and medication across the three phenogroups identified. Cardiac output at rest was significantly higher in group 2 vs. group 3 (males: median 5.6 L/min vs. 5.2 L/min, p ConclusionWomen with cardiometabolic HFpEF had a lower comorbidity burden compared to men despite a similar metabolic syndrome profile. Based on patients' cardiometabolic profile, we identified three distinct subgroups which differed in body shape and mass, lipid biomarker and medication profile, as well as in cardiac output at rest both in men and women. These factors may affect disease trajectory, treatment options and outcomes in those subgroups. Subject to further validation, our findings provide a refined characterisation of the cardiometabolic HFpEF phenotype, contributing towards a better understanding of the condition to enable phenotype-specific disease management.
Antidepressant Switching as a Proxy Phenotype for Drug Nonresponse: Investigating Clinical, Demographic, and Genetic Characteristics.
BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) are a first-line pharmacological therapy in major depressive disorder (MDD), but treatment response rates are low. Clinical trials lack the power to study the genetic contribution to SSRI response. Real-world evidence from electronic health records provides larger sample sizes, but novel response definitions are needed to accurately define SSRI nonresponders. METHODS: In the UK Biobank (UKB) (N = 38,813) and Generation Scotland (N = 1777) datasets, SSRI switching was defined using ≤90-day gap between prescriptions for an SSRI and another antidepressant in primary care. Nonswitchers were participants with ≥3 consecutive prescriptions for an SSRI. In the UKB, clinical, demographic, and polygenic score (PGS) associations with switching were determined, and the common-variant heritability was estimated. RESULTS: In the UKB, 5133 (13.2%) SSRI switchers and 33,680 nonswitchers were defined. The mean time to switch was 28 days (interquartile range, 17-49). Switching patterns were consistent across the UKB and Generation Scotland (n = 498 switchers). Higher annual income and educational levels (odds ratio [OR] [95% CI] for a university degree, 0.73 [0.67-0.79] compared with no qualifications) were associated with lower levels of switching. PGSs for nonremission, based on clinical studies, were associated with increased risk of switching (OR, 1.07 [1.02-1.12], p = .007). MDD PGSs and family history of depression were not significantly associated with switching. Using genome-wide complex trait Bayesian, the single nucleotide polymorphism-based heritability was approximately 4% (SE 0.016) on the observed scale. CONCLUSIONS: This study identified SSRI switching as a proxy for nonresponse, scalable across biobanks with electronic health records, capturing demographics and genetics of treatment nonresponse, and independent of MDD genetics.
Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): preliminary results of a randomised, controlled, open-label, platform trial
SUMMARY Background Tocilizumab is a monoclonal antibody that binds to the receptor for interleukin (IL)-6, reducing inflammation, and is commonly used to treat rheumatoid arthritis. We evaluated the safety and efficacy of tocilizumab in adult patients admitted to hospital with COVID-19 with evidence of both hypoxia and systemic inflammation. Methods This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein [CRP] ≥75 mg/L) were eligible for randomisation to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg to 800 mg (depending on weight) given intravenously. A second dose could be given 12 to 24 hours later if the patient’s condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov ( NCT04381936 ). Findings Between 23 April 2020 and 24 January 2021, 4116 adults were included in the assessment of tocilizumab, including 562 (14%) patients receiving invasive mechanical ventilation, 1686 (41%) receiving non-invasive respiratory support, and 1868 (45%) receiving no respiratory support other than oxygen. Median CRP was 143 [IQR 107-204] mg/L and 3385 (82%) patients were receiving systemic corticosteroids at randomisation. Overall, 596 (29%) of the 2022 patients allocated tocilizumab and 694 (33%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·86; 95% confidence interval [CI] 0·77-0·96; p=0·007). Consistent results were seen in all pre-specified subgroups of patients. In particular, a clear mortality benefit was seen in those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital alive within 28 days (54% vs. 47%; rate ratio 1·22; 95% CI 1·12-1·34; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (33% vs. 38%; risk ratio 0·85; 95% CI 0·78-0·93; p=0·0005). Interpretation In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the level of respiratory support and were additional to the benefits of systemic corticosteroids. Funding UK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).
The effect of D-cycloserine on brain connectivity over a course of pulmonary rehabilitation - A randomised control trial with neuroimaging endpoints.
Combining traditional therapies such as pulmonary rehabilitation with brain-targeted drugs may offer new therapeutic opportunities for the treatment of chronic breathlessness. Recently, we asked whether D-cycloserine, a partial NMDA-receptor agonist which may enhance behavioural therapies, modifies the relationship between breathlessness related brain activity and breathlessness anxiety over pulmonary rehabilitation. However, whether any changes are supported by alterations to underlying brain structure remains unknown. Here we examine the effect of D-cycloserine over a course of pulmonary rehabilitation on the connectivity between key brain regions associated with the processing of breathlessness anxiety. 72 participants with mild-to-moderate COPD took part in a longitudinal study in parallel to their pulmonary rehabilitation course. Diffusion tensor brain imaging and clinical measures of respiratory function were collected at three time points (before, during and after pulmonary rehabilitation). Participants were assigned to 250mg of D-cycloserine or placebo, which they were administered with on four occasions in a randomised, double-blind procedure. Following the first four sessions of pulmonary rehabilitation (visit 2), during which D-cycloserine was administered, improvements in breathlessness anxiety were linked with increased insula-hippocampal structural connectivity in the D-cycloserine group when compared to the placebo group. No differences were found between the two groups following the completion of the full pulmonary rehabilitation course 4-6 weeks later (visit 3). The action of D-cycloserine on brain connectivity appears to be restricted to within a short time-window of its administration. This temporary boost of the brain connectivity of two key regions associated with the evaluation of how unpleasant an experience is may support the re-evaluation of breathlessness cues, illustrated improvements in breathlessness anxiety. Trial registration ClinicalTrials.gov (NCT01985750).
BNPower: a power calculation tool for data-driven network analysis for whole-brain connectome data
Network analysis of whole-brain connectome data is widely employed to examine systematic changes in connections among brain areas caused by clinical and experimental conditions. In these analyses, the connectome data, represented as a matrix, are treated as outcomes, while the subject conditions serve as predictors. The objective of network analysis is to identify connectome subnetworks whose edges are associated with the predictors. Data-driven network analysis is a powerful approach that automatically organizes individual predictor-related connections (edges) into subnetworks, rather than relying on pre-specified subnetworks, thereby enabling network-level inference. However, power calculation for data-driven network analysis presents a challenge due to the data-driven nature of subnetwork identification, where nodes, edges, and model parameters cannot be pre-specified before the analysis. Additionally, data-driven network analysis involves multivariate edge variables and may entail multiple subnetworks, necessitating the correction for multiple testing (e.g., family-wise error rate (FWER) control). To address this issue, we developed BNPower, a user-friendly power calculation tool for data-driven network analysis. BNPower utilizes simulation analysis, taking into account the complexity of the data-driven network analysis model. We have implemented efficient computational strategies to facilitate data-driven network analysis, including subnetwork extraction and permutation tests for controlling FWER, while maintaining low computational costs. The toolkit, which includes a graphical user interface and source codes, is publicly available at the following GitHub repository: https://github.com/bichuan0419/brain_connectome_power_tool
Epidemiology and excess mortality of antimicrobial resistance in bacteraemias among cancer patients: a cohort study using routinely collected health data from regional hospital trusts in Oxford and Oslo, 2008-2018.
OBJECTIVES: We investigated the epidemiology and impact on mortality of antimicrobial resistance (AMR) in cancer patients with bacteraemia at Oxford University Hospitals (OxUH), UK, and Oslo University Hospital (OsUH), Norway, during 2008-2018. DESIGN: Historical cohort study. SETTING: Regional hospital trusts with multiple sites in OxUH and OsUH. METHODS: Patients with cancer and blood cultures positive for one of six pathogen groups during a hospital stay within 3 years following their first cancer diagnosis were followed for 30 days after their first bacteraemia episode. We determined the number of cases and the proportion of infections with an AMR phenotype. Excess mortality and the population-attributable fraction (PAF) due to AMR were estimated by contrasting observed mortality at the end of follow-up with an estimated counterfactual scenario where AMR was absent from all bacteraemias, using inverse probability weighting. MAIN OUTCOME MEASURE: 30-day all-cause mortality following the first bacteraemia episode. MAIN EXPOSURE MEASURE: A resistant phenotype of the causative pathogen. RESULTS: The study included 1929 patients at OxUH and 1640 patients at OsUH. The highest resistance proportions were found for vancomycin resistance in enterococci (85/314, 27.1%) and carbapenem-resistance in Pseudomonas aeruginosa (63/260, 24.2%) at OxUH, and third-generation cephalosporin resistance in Escherichia coli (62/743, 8.3%) and Klebsiella pneumoniae (14/223, 6.3%) at OsUH. Observed mortality for all infections was 26.4% at OxUH, with an estimated counterfactual mortality without AMR of 24.7%, yielding an excess mortality of 1.7% (95% CI: 0.8 to 2.5%). The PAF was 6.3% (95% CI: 2.9 to 9.6%), meaning an estimated 32 of 509 deaths could be attributed to AMR. Limited events at OsUH precluded a similar estimate. CONCLUSIONS: Despite estimating modest excess mortality, the mortality attributable to resistance in these two high-income, low-prevalence settings highlights the potential for escalation if global resistance trends continue to worsen.
Detectable clonal mosaicism and its relationship to aging and cancer.
In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases.
Association of multimorbidity and disease clusters with neuroimaging and cognitive outcomes in UK Biobank.
BackgroundThe relationship between multimorbidity, particularly disease clusters, with neuroimaging and cognitive outcomes that typically manifest prior to clinical diagnosis of dementia, remains understudied. This study investigated whether multimorbidity is associated with dementia-related neuroimaging and cognitive outcomes in the UK Biobank cohort.MethodsThis cross-sectional study used data from UK Biobank participants who attended imaging assessments between 2014-2023, and were free from neurological conditions, including dementia. Multimorbidity was defined as the coexistence of two or more long-term conditions, selected from a standardised criteria of 39 conditions. Latent class analyses were used to identify disease clusters. Neuroimaging outcomes were measured using magnetic resonance imaging, and cognition was assessed by seven tests measuring different cognitive domains. Multivariable linear regression was used to assess the association between multimorbidity and disease clusters with neuroimaging and cognitive outcomes.ResultsA total of 43,160 participants were included (mean [standard deviation] age, 64.2 [7.7] years, 53.1 % female). Multimorbidity was present among 14,339 (33.2 %) participants, and was associated with reduced grey matter volume, total brain volume, left hippocampal volume, increased cerebrovascular pathology as well as reduced domain-specific cognitive function. A strong dose-response relationship was observed with the increasing number of multimorbid conditions across these outcomes. A disease cluster driven by cardiometabolic conditions was consistently associated with poorer brain health across all outcomes. Disease clusters driven by respiratory, mental health and other conditions showed less consistent associations.ConclusionsMultimorbidity was strongly associated with poorer brain health, particularly within the cardiometabolic disease cluster. Given that UK Biobank participants are, on average, healthier than the general population, future studies in more diverse and representative cohorts would be valuable.
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis.
By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P<5x10(-8). These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.
Clinical Implications of Slope of GFR in Clinical Trials of CKD Progression
BackgroundSlope of the GFR is considered a validated surrogate endpoint for CKD trials. However, differing short-term and long-term treatment effects on GFR slope can create ambiguities concerning the appropriate period for evaluating slope, in part because current methods cannot separate the distinct contributions of the acute (before 3 months) and chronic (after 3 months) slopes for treatment effects on clinical endpoints (CEs).MethodsWe estimated treatment effects on the acute and chronic GFR slopes and on the established CE of kidney failure or serum creatinine doubling for 66 randomized treatment comparisons from previous CKD clinical trials. We used a novel Bayesian meta-regression framework to relate treatment effects on the established CE to both the acute and chronic slopes in a single multivariable model to determine the independent contributions of the acute and chronic slopes.ResultsTreatment effects on both the acute and chronic slopes independently predicted the treatment effect on the established CE with a high median R2 (95% credible interval) of 0.95 (0.79 to 1.00). For a fixed treatment effect on the chronic slope, each 1 ml/min per 1.73 m2 greater acute GFR decline for the treatment versus control increased the hazard ratio for the established CE by 11.4% (7.9%-15.0%), against the treatment. The optimal weights for the acute and chronic slopes were consistent with the 3-year total slope defined as the average slope extending from baseline to 3 years.ConclusionsTreatment effects on both the acute and chronic GFR slopes are independent determinants of the effects on the established CE, with variation in acute effects accounting for much of the observed variation in treatment effects on the CE across previous trials. Our results establish that acute effects affect the CE independently of treatment effects on the chronic slope and support the 3-year total slope as the primary slope-based outcome in randomized trials.