Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes.

AIMS/HYPOTHESIS: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed. RESULTS: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%. CONCLUSIONS/INTERPRETATION: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study.

AIMS/HYPOTHESIS: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. METHODS: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic. RESULTS: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. CONCLUSIONS/INTERPRETATION: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. DATA AVAILABILITY: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch .

Phenotype-based targeted treatment of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes.

AIMS/HYPOTHESIS: A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA). METHODS: We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA1c) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people with type 2 diabetes from Scotland (SCI-Diabetes [Tayside & Fife]). Differences in glycaemic outcome with GLP1-RA by sex seen in clinical data were replicated in clinical trial data (HARMONY programme: liraglutide [n=389] and albiglutide [n=1682]). As secondary outcomes, we evaluated the impacts of targeting therapy based on glycaemic response on weight change, tolerability and longer-term risk of new-onset microvascular complications, macrovascular complications and adverse kidney events. RESULTS: Model development identified marked heterogeneity in glycaemic response, with 4787 (17.5%) of the development cohort having a predicted HbA1c benefit >3 mmol/mol (>0.3%) with SGLT2i over GLP1-RA and 5551 (20.3%) having a predicted HbA1c benefit >3 mmol/mol with GLP1-RA over SGLT2i. Calibration was good in hold-back validation, and external validation in an independent Scottish dataset identified clear differences in glycaemic outcomes between those predicted to benefit from each therapy. Sex, with women markedly more responsive to GLP1-RA, was identified as a major treatment effect modifier in both the UK observational datasets and in clinical trial data: HARMONY-7 liraglutide (GLP1-RA): 4.4 mmol/mol (95% credible interval [95% CrI] 2.2, 6.3) (0.4% [95% CrI 0.2, 0.6]) greater response in women than men. Targeting the two therapies based on predicted glycaemic response was also associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications. CONCLUSIONS/INTERPRETATION: Precision medicine approaches can facilitate effective individualised treatment choice between SGLT2i and GLP1-RA therapies, and the use of routinely collected clinical features for treatment selection could support low-cost deployment in many countries.

Small airway fibroblasts from patients with chronic obstructive pulmonary disease exhibit cellular senescence.

Small airway disease (SAD) is a key early-stage pathology of chronic obstructive pulmonary disease (COPD). COPD is associated with cellular senescence whereby cells undergo growth arrest and express the senescence-associated secretory phenotype (SASP) leading to chronic inflammation and tissue remodeling. Parenchymal-derived fibroblasts have been shown to display senescent properties in COPD, however small airway fibroblasts (SAFs) have not been investigated. Therefore, this study investigated the role of these cells in COPD and their potential contribution to SAD. To investigate the senescent and fibrotic phenotype of SAF in COPD, SAFs were isolated from nonsmoker, smoker, and COPD lung resection tissue (n = 9-17 donors). Senescence and fibrotic marker expressions were determined using iCELLigence (proliferation), qPCR, Seahorse assay, and ELISAs. COPD SAFs were further enriched for senescent cells using FACSAria Fusion based on cell size and autofluorescence (10% largest/autofluorescent vs. 10% smallest/nonautofluorescent). The phenotype of the senescence-enriched population was investigated using RNA sequencing and pathway analysis. Markers of senescence were observed in COPD SAFs, including senescence-associated ß-galactosidase, SASP release, and reduced proliferation. Because the pathways driving this phenotype were unclear, we used cell sorting to enrich senescent COPD SAFs. This population displayed increased p21CIP1 and p16INK4a expression and mitochondrial dysfunction. RNA sequencing suggested these senescent cells express genes involved in oxidative stress response, fibrosis, and mitochondrial dysfunction pathways. These data suggest COPD SAFs are senescent and may be associated with fibrotic properties and mitochondrial dysfunction. Further understanding of cellular senescence in SAFs may lead to potential therapies to limit SAD progression.NEW & NOTEWORTHY Fibroblasts and senescence are thought to play key roles in the pathogenesis of small airway disease and COPD; however, the characteristics of small airway-derived fibroblasts are not well explored. In this study we isolate and enrich the senescent small airway-derived fibroblast (SAF) population from COPD lungs and explore the pathways driving this phenotype using bulk RNA-seq.

Initiation of glucose-lowering drugs reduces the anticoagulant effect of warfarin-But not through altered drug metabolism in patients with type 2 diabetes.

AIMS: Drug metabolism might be altered in patients with type 2 diabetes. We aimed to evaluate if initiation of glucose-lowering drugs impacts warfarin efficacy and drug metabolism. METHODS: First, we conducted a register-based self-controlled cohort study on Danish and Scottish warfarin users. Warfarin efficacy (international normalized ratio [INR]) was compared before and after initiation of glucose-lowering drugs. Second, we conducted a clinical pharmacokinetic trial comprising treatment-naïve type 2 diabetes patients. Patients ingested probe drugs for drug-metabolizing enzymes (the Basel Cocktail) before initiating glucose-lowering treatment, and after 3 and 12 weeks of treatment. Drug metabolism, glycaemic control, and inflammation were assessed on each visit. RESULTS: In the Danish and Scottish cohorts (n = 982 and n = 44, respectively), initiating glucose-lowering drugs reduced warfarin efficacy. INR decreased from 2.47 to 2.21 in the Danish cohort (mean difference -0.26; 95% CI -0.35; -0.17) and from 2.33 to 2.13 in the Scottish cohort (-0.21; 95% CI -0.52; 0.11) after initiation of glucose-lowering treatment. This impact on INR was more pronounced among individuals with stronger effects of glucose-lowering treatment. In the clinical pharmacokinetic trial (n = 10), initiating metformin did not affect drug metabolism after 3 weeks (geometric mean ratio of CYP3A metabolic ratio: 1.12 [95% CI: 0.95; 1.32]) or 12 weeks of metformin treatment. Glycaemic control improved during treatment, while inflammation remained low and unchanged during treatment. CONCLUSIONS: In conclusion, initiation of glucose-lowering drugs among chronic warfarin users seems associated with a reduction in INR, particularly among individuals with a large decrease in HbA1c . This effect seems unrelated to CYP enzyme activity and warfarin drug metabolism.

Women's health behaviour change after receiving breast cancer risk estimates with tailored screening and prevention recommendations.

BACKGROUND: The Predicting Risk of Cancer at Screening (PROCAS) study provided women who were eligible for breast cancer screening in Greater Manchester (United Kingdom) with their 10-year risk of breast cancer, i.e., low (≤1.5%), average (1.5-4.99%), moderate (5.-7.99%) or high (≥8%). The aim of this study is to explore which factors were associated with women's uptake of screening and prevention recommendations. Additionally, we evaluated women's organisational preferences regarding tailored screening. METHODS: A total of 325 women with a self-reported low (n = 60), average (n = 125), moderate (n = 80), or high (n = 60) risk completed a two-part web-based survey. The first part contained questions about personal characteristics. For the second part women were asked about uptake of early detection and preventive behaviours after breast cancer risk communication. Additional questions were posed to explore preferences regarding the organisation of risk-stratified screening and prevention. We performed exploratory univariable and multivariable regression analyses to assess which factors were associated with uptake of primary and secondary breast cancer preventive behaviours, stratified by breast cancer risk. Organisational preferences are presented using descriptive statistics. RESULTS: Self-reported breast cancer risk predicted uptake of (a) supplemental screening and breast self-examination, (b) risk-reducing medication and (c) preventive lifestyle behaviours. Further predictors were (a) having a first degree relative with breast cancer, (b) higher age, and (c) higher body mass index (BMI). Women's organisational preferences for tailored screening emphasised a desire for more intensive screening for women at increased risk by further shortening the screening interval and moving the starting age forward. CONCLUSIONS: Breast cancer risk communication predicts the uptake of key tailored primary and secondary preventive behaviours. Effective communication of breast cancer risk information is essential to optimise the population-wide impact of tailored screening.

Autophagy in asthma and chronic obstructive pulmonary disease.

Autophagy (or macroautophagy) is a key cellular process that removes damaged molecules (particularly proteins) and subcellular organelles to maintain cellular homeostasis. There is growing evidence that abnormalities in autophagy may contribute to the pathogenesis of many chronic diseases, including asthma and chronic obstructive pulmonary disease (COPD). In asthma, increased autophagy plays a role in promoting type 2 immune responses and eosinophilic inflammation, whereas decreased autophagy may be important in neutrophilic asthma. Acute exposure to cigarette smoke may activate autophagy, resulting in ciliary dysfunction and death of airway epithelial cells, whereas in stable COPD most studies have demonstrated an impairment in autophagy, with reduced autophagic flux and accumulation of abnormal mitochondria (defective mitophagy) and linked to cellular senescence. Autophagy may be increased or decreased in different cell types and depending on the cellular environment, making it difficult to target autophagy therapeutically. Several existing drugs may activate autophagy, including rapamycin, metformin, carbamazepine, cardiac glycosides and statins, whereas others, such as chloroquine, inhibit this process. However, these drugs are nonspecific and more selective drugs are now in development, which may prove useful as novel agents to treat asthma and COPD in the future.

The impact of birthweight on subsequent phenotype of type 2 diabetes in later life.

AIMS: It is well established that low birthweight is associated with subsequent risk of type 2 diabetes (T2DM). The aim of our study was to use a large birth cohort linked to a national diabetes registry to investigate how birthweight impacts the phenotype at diagnosis of T2DM and the subsequent rate of glycaemic deterioration. METHODS: We linked the Walker Birth Cohort (48,000 births, 1952-1966, Tayside, Scotland) to the national diabetes registry in Scotland (SCI-Diabetes). Birthweight was adjusted for gestational age. Simple linear regression was performed to assess the impact of the adjusted birthweight on the diabetes phenotype at diagnosis. This was then built up into a multiple regression model to allow for the adjustment of confounding variables. A cox proportional hazards model was then used to evaluate the impact of birthweight on diabetes progression. RESULTS: Lower birthweights were associated with a 293 day younger age of diagnosis of T2DM per 1 kg reduction in birthweight, p = 0.005; and a 1.29 kg/m2 lower BMI at diagnosis per 1 kg reduction in birthweight, p < 0.001. There was no significant association of birthweight on diabetes progression. CONCLUSION: For the first time, we have shown that a lower birthweight is associated with younger onset of T2DM, with those with lower birthweight also being slimmer at diagnosis. These results suggest that lower birthweight impacts on T2DM phenotype via reduced beta-cell function rather than insulin resistance.

Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for example due to changes in temperature or mechanical drift. It is also useful for automated slide scanning or multiwell plate imaging where the sample(s) to be imaged may not be in the same horizontal plane throughout the image data acquisition. To address the impact of (thermal or mechanical) fluctuations over time in the optical autofocus system itself, we utilize a convolutional neural network (CNN) that is trained over multiple days to account for such fluctuations. To address the trade-off between axial precision and range of the autofocus, we implement orthogonal optical readouts with separate CNN training data, thereby achieving an accuracy well within the 600 nm depth of field of our 1.3 numerical aperture objective lens over a defocus range of up to approximately +/-100 µm. We characterize the performance of this autofocus system and demonstrate its application to automated multiwell plate single molecule localization microscopy.

Many microscopy experiments involve extended imaging of samples over timescales from minutes to days, during which the microscope can 'drift' out of focus. When imaging at high magnification, the depth of field is of the order of one micron and so the imaging system should keep the sample in the focal plane of the microscope objective lens to this precision. Unfortunately, temperature changes in the laboratory can cause thermal expansion of microscope components that can move the focal plane by more than a micron and such changes can occur on a timescale of minutes. This is a particular issue for super-resolved microscopy experiments using single molecule localization microscopy (SMLM) techniques, for which 1000s of images are acquired, and for automated imaging of multiple samples in multiwell plates. It is possible to maintain the sample in the focal plane focus position by either automatically moving the sample or adjusting the imaging system, for example by moving the objective lens. This is called 'autofocus' and is frequently achieved by reflecting a light beam from the microscope coverslip and measuring its position of beam profile as a function of defocus of the microscope. The correcting adjustment is then usually calculated analytically but there is recent interest in using machine learning techniques to determine the required focussing adjustment. Here, we present a system that uses a neural network to determine the required defocus correcting adjustment from camera images of a laser beam that is reflected from the coverslip. Unfortunately, this approach will only work when the microscope is in the same condition as it was when the neural network was trained - and this can be compromised by the same drift of the optical system that causes the defocus needing to be corrected. We show, however, that by training a neural network over an extended period, for example 10 days, this approach can 'learn' about the optical system drifts and provide the required autofocus function. We also show that an optical system utilizing a rectangular slit can make two measurements of the defocus simultaneously, with one measurement being optimized for high accuracy over a limited range (±10 µm) near focus and the other providing lower accuracy but over a much longer range (±100 µm). This robust autofocus system is suitable for automated super-resolved microscopy of arrays of samples in a multiwell plate using SMLM, for which an experiment routinely lasts more than 5 h.

Hepcidin Is Essential for Alveolar Macrophage Function and Is Disrupted by Smoke in a Murine Chronic Obstructive Pulmonary Disease Model.

Chronic obstructive pulmonary disease (COPD) is a debilitating lung disease associated with cigarette smoking. Alterations in local lung and systemic iron regulation are associated with disease progression and pathogenesis. Hepcidin, an iron regulatory peptide hormone, is altered in subjects with COPD; however, the molecular role of hepcidin in COPD pathogenesis remains to be determined. In this study, using a murine model of smoke-induced COPD, we demonstrate that lung and circulating hepcidin levels are inhibited by cigarette smoke. We show that cigarette smoke exposure increases erythropoietin and bone marrow-derived erythroferrone and leads to expanded but inefficient erythropoiesis in murine bone marrow and an increase in ferroportin on alveolar macrophages (AMs). AMs from smokers and subjects with COPD display increased expression of ferroportin as well as hepcidin. Notably, murine AMs exposed to smoke fail to increase hepcidin in response to Gram-negative or Gram-positive infection. Loss of hepcidin in vivo results in blunted functional responses of AMs and exaggerated responses to Streptococcus pneumoniae infection.

The feasibility of implementing risk stratification into a national breast cancer screening programme: a focus group study investigating the perspectives of healthcare personnel responsible for delivery.

BACKGROUND: Providing women with personalized estimates of their risk of developing breast cancer, as part of routine breast cancer screening programmes, allows women at higher risk to be offered more frequent screening or drugs to reduce risk. For this to be feasible, the concept and practicalities have to be acceptable to the healthcare professionals who would put it in to practice. The present research investigated the acceptability to healthcare professionals who were responsible for the implementation of this new approach to screening in the ongoing BC-Predict study. METHODS: Four focus groups were conducted with 29 healthcare professionals from a variety of professional backgrounds working within three breast screening services in north-west England. An inductive-manifest thematic analysis was conducted. RESULTS: Overall, healthcare professionals viewed the implementation of personalised breast cancer risk estimation as a positive step, but discussion focused on concerns. Three major themes are presented. (1) Service constraints highlights the limited capacity within current breast services and concerns about the impact of additional workload. (2) Risk communication concerns the optimal way to convey risk to women within resource constraints. (3) Accentuating inequity discusses how risk stratification could decrease screening uptake for underserved groups. CONCLUSIONS: Staff who implemented risk stratification considered it a positive addition to routine screening. They considered it essential to consider improving capacity and demands on healthcare professional time. They highlighted the need for skilled communication of risks and new pathways of care to ensure that stratification could be implemented in financially and time constrained settings without impacting negatively on women.

Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study.

AIMS/HYPOTHESIS: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. METHODS: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster. RESULTS: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression. CONCLUSIONS/INTERPRETATION: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.

Extending screening intervals for women at low risk of breast cancer: do they find it acceptable?

BACKGROUND: Trials of risk estimation in breast cancer screening programmes, in order to identify women at higher risk and offer extra screening/preventive measures, are ongoing. It may also be feasible to introduce less frequent screening for women at low-risk of breast cancer. This study aimed to establish views of women at low-risk of breast cancer regarding the acceptability of extending breast screening intervals for low-risk women beyond 3 y. METHODS: Semi-structured interviews were used to explore views of low-risk women, where "low-risk" was defined as less than 2% estimated 10-year risk of breast cancer aged > 46 years. Low-risk women were identified via the BC-Predict study, where following routine screening, women were given their 10-year risk of breast cancer by letter, along with additional information explaining breast cancer risk factors. To gain diversity of views, purposive sampling by ethnicity and socioeconomic background was used to recruit women. Data were analysed using thematic analysis. RESULTS: Twenty-three women participated in individual interviews. Three themes are reported: (1) A good opportunity to receive risk estimation, where women found it worthwhile to receive a low-risk result although some were surprised if expecting a higher risk result; (2) Multi-faceted acceptability of extended screening intervals, with reactions to less frequent screening dependent on whether women were confident in being low-risk status and current safety evidence, (3) Passive approval versus informed choice, highlighting that women found it difficult to consider choosing less frequent screening without professionals' recommendations, as they generally viewed attending breast screening as positive. CONCLUSIONS: Risk assessment and receiving a low-risk of breast cancer is acceptable although, further research is required with more diverse samples of women. Any recommendation of less frequent screening in this risk group should be evidence-based in order to be acceptable. Communication needs to be carefully developed, with a focus on ensuring informed choice, prior to trialling any extended screening recommendations in future studies.

In a cohort of individuals with type 2 diabetes using the drug sulfasalazine, HbA1c lowering is associated with haematological changes.

OBJECTIVES: Several small studies indicate the sulphonamide component of the drug sulfasalazine lowers HbA1c. We investigated reduction of HbA1c following incident prescription of sulfasalazine and related aminosalicylates, lacking the sulphonamide group, in an observational cohort. RESEARCH DESIGN AND METHODS: Individuals in the Scottish Care Information Diabetes Collaboration (SCI-Diabetes) with type 2 diabetes and incident prescription for an aminosalicylate drug (sulfasalazine, mesalazine, olsalazine or balsalazide) were identified. Baseline and 6-month HbA1c were required for eligibility, to calculate HbA1c response. To investigate association with haemolysis, change in components of full blood count was assessed. Paired t-tests compared difference in baseline and treatment HbA1c measures and other clinical variables. RESULTS: In all, 113 individuals treated with sulfasalazine and 103 with mesalazine (lacking the sulphonamide group) were eligible, with no eligible individuals treated with olsalazine or balsalazide. Baseline characteristics were similar. Mean (SD) HbA1c reduction at 6 months was -9 ± 16 mmol/mol (-0.9 ± 1.4%) (p < 0.0001) in those taking sulfasalazine with no reduction in those taking mesalazine (2 ± 16 mmol/mol (0.2 ± 1.4%). Sulfasalazine but not mesalazine was associated with a mean (SD) increase in mean cell volume of 3.7 ± 5.6 fl (p < 0.0001) and decrease in red cell count of -0.2 ± 0.4 × 10-12 /L (p < 0.0001). CONCLUSIONS: In this observational, population-based study, sulfasalazine initiation was associated with a 6-month reduction in HbA1c . This correlated with haematological changes suggesting haemolytic effects of sulfasalazine. Haemolysis is proposed to contribute to HbA1c lowering through the sulphonamide pharmacophore. This suggests that HbA1c is not a reliable measure of glycaemia in individuals prescribed sulfasalazine.

Phenotypic comparison between smoking and non-smoking chronic obstructive pulmonary disease.

BACKGROUND: Although COPD among non-smokers (NS-COPD) is common, little is known about this phenotype. We compared NS-COPD subjects with smoking COPD (S-COPD) patients in a rural Indian population using a variety of clinical, physiological, radiological, sputum cellular and blood biomarkers. METHODS: Two hundred ninety subjects (118 healthy, 79 S-COPD, 93 NS-COPD) performed pre- and post-bronchodilator spirometry and were followed for 2 years to study the annual rate of decline in lung function. Body plethysmography, impulse oscillometry, inspiratory-expiratory HRCT, induced sputum cellular profile and blood biomarkers were compared between 49 healthy, 45 S-COPD and 55 NS-COPD subjects using standardized methods. Spirometric response to oral corticosteroids was measured in 30 female NS-COPD patients. RESULTS: Compared to all male S-COPD subjects, 47% of NS-COPD subjects were female, were younger by 3.2 years, had greater body mass index, a slower rate of decline in lung function (80 vs 130 mL/year), more small airways obstruction measured by impulse oscillometry (p < 0.001), significantly less emphysema (29% vs 11%) on CT scans, lower values in lung diffusion parameters, significantly less neutrophils in induced sputum (p < 0.05) and tended to have more sputum eosinophils. Hemoglobin and red cell volume were higher and serum insulin lower in S-COPD compared to NS-COPD. Spirometric indices, symptoms and quality of life were similar between S-COPD and NS-COPD. There was no improvement in spirometry in NS-COPD patients after 2 weeks of an oral corticosteroid. CONCLUSIONS: Compared to S-COPD, NS-COPD is seen in younger subjects with equal male-female predominance, is predominantly a small-airway disease phenotype with less emphysema, preserved lung diffusion and a slower rate of decline in lung function.

Risk stratified breast cancer screening: UK healthcare policy decision-making stakeholders' views on a low-risk breast screening pathway.

BACKGROUND: There is international interest in risk-stratification of breast screening programmes to allow women at higher risk to benefit from more frequent screening and chemoprevention. Risk-stratification also identifies women at low-risk who could be screened less frequently, as the harms of breast screening may outweigh benefits for this group. The present research aimed to elicit the views of national healthcare policy decision-makers regarding implementation of less frequent screening intervals for women at low-risk. METHODS: Seventeen professionals were purposively recruited to ensure relevant professional group representation directly or indirectly associated with the UK National Screening Committee and National Institute for Health and Care Excellence (NICE) clinical guidelines. Interviews were analysed using thematic analysis. RESULTS: Three themes are reported: (1) producing the evidence defining low-risk, describing requirements preceding implementation; (2) the impact of risk stratification on women is complicated, focusing on gaining acceptability from women; and (3) practically implementing a low-risk pathway, where feasibility questions are highlighted. CONCLUSIONS: Overall, national healthcare policy decision-makers appear to believe that risk-stratified breast screening is acceptable, in principle. It will however be essential to address key obstacles prior to implementation in national programmes.

The introduction of risk stratified screening into the NHS breast screening Programme: views from British-Pakistani women.

BACKGROUND: UK national guidelines suggest women at high-risk of breast cancer should be offered more frequent screening or preventative medications. Currently, only 1 in 6 high-risk women are identified. One route to identify more high-risk women is via multifactorial risk assessment as part of the UK's NHS Breast Screening Programme (NHSBSP). As lower socioeconomic and minority ethnic populations continue to experience barriers to screening, it is important that any new service does not exacerbate issues further. To inform service development, this study explored views of women from underserved backgrounds regarding the introduction of risk stratification into the NHSBSP. METHODS: Nineteen semi-structured interviews were conducted with British-Pakistani women from low socioeconomic backgrounds from East Lancashire, UK. Fourteen interviews were conducted via an interpreter. RESULTS: Thematic analysis produced three themes. Attitudes toward risk awareness concerns the positive views women have toward the idea of receiving personalised breast cancer risk information. Anticipated barriers to accessibility emphasises the difficulties associated with women's limited English skills for accessing information, and their I.T proficiency for completing an online risk assessment questionnaire. Acceptability of risk communication strategy highlights the diversity of opinion regarding the suitability of receiving risk results via letter, with the option for support from a healthcare professional deemed essential. CONCLUSIONS: The idea of risk stratification was favourable amongst this underserved community. To avoid exacerbating inequities, this new service should provide information in multiple languages and modalities and offer women the opportunity to speak to a healthcare professional about risk. This service should also enable completion of personal risk information via paper questionnaires, as well as online.

European women's perceptions of the implementation and organisation of risk-based breast cancer screening and prevention: a qualitative study.

BACKGROUND: Increased knowledge of breast cancer risk factors has meant that we are currently exploring risk-based screening, i.e. determining screening strategies based on women's varying levels of risk. This also enables risk management through primary prevention strategies, e.g. a lifestyle programme or risk-reducing medication. However, future implementation of risk-based screening and prevention will warrant significant changes in current practice and policy. The present study explores women's perceptions of the implementation and organisation of risk-based breast cancer screening and prevention to optimise acceptability and uptake. METHODS: A total of 143 women eligible for breast cancer screening in the Netherlands, the United Kingdom, and Sweden participated in focus group discussions. The focus group discussions were transcribed verbatim and the qualitative data was analysed using thematic analysis. RESULTS: Women from all three countries generally agreed on the overall proceedings, e.g. a risk assessment after which the risk estimate is communicated via letter (for below average and average risk) or consultation (for moderate and high risk). However, discrepancies in information needs, preferred risk communication format and risk counselling professional were identified between countries. Additionally, a need to educate healthcare professionals on all aspects of the risk-based screening and prevention programme was established. CONCLUSION: Women's insights identified the need for country-specific standardised protocols regarding the assessment and communication of risk, and the provision of heterogeneous screening and prevention recommendations, monitoring the principle of solidarity in healthcare policy.

MicroRNA-570 is a novel regulator of cellular senescence and inflammaging.

Diseases of accelerated aging often occur together (multimorbidity), and their prevalence is increasing, with high societal and health care costs. Chronic obstructive pulmonary disease (COPD) is one such condition, in which one half of patients exhibit ≥4 age-related diseases. Diseases of accelerated aging share common molecular pathways, which lead to the detrimental accumulation of senescent cells. These senescent cells no longer divide but release multiple inflammatory proteins, known as the senescence-associated secretory phenotype, which may perpetuate and speed disease. Here, we show that inhibiting miR-570-3p, which is increased in COPD cells, reverses cellular senescence by restoring the antiaging molecule sirtuin-1. MiR-570-3p is induced by oxidative stress in airway epithelial cells through p38 MAP kinase-c-Jun signaling and drives senescence by inhibiting sirtuin-1. Inhibition of elevated miR-570-3p in COPD small airway epithelial cells, using an antagomir, restores sirtuin-1 and suppresses markers of cellular senescence (p16INK4a, p21Waf1, and p27Kip1), thereby restoring cellular growth by allowing progression through the cell cycle. MiR-570-3p inhibition also suppresses the senescence-associated secretory phenotype (matrix metalloproteinases-2/9, C-X-C motif chemokine ligand 8, IL-1ß, and IL-6). Collectively, these data suggest that inhibiting miR-570-3p rejuvenates cells via restoration of sirtuin-1, reducing many of the abnormalities associated with cellular senescence.-Baker, J. R., Vuppusetty, C., Colley, T., Hassibi, S., Fenwick, P. S., Donnelly, L. E., Ito, K., Barnes, P. J. MicroRNA-570 is a novel regulator of cellular senescence and inflammaging.

Cellular Senescence as a Mechanism and Target in Chronic Lung Diseases.

Cellular senescence is now considered an important driving mechanism for chronic lung diseases, particularly chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis. Cellular senescence is due to replicative and stress-related senescence with activation of p53 and p16INK4a, respectively, leading to activation of p21CIP1 and cell cycle arrest. Senescent cells secrete multiple inflammatory proteins known as the senescence-associated secretory phenotype, leading to low-grade chronic inflammation, which further drives senescence. Loss of key antiaging molecules sirtuin-1 and sirtuin-6 may be important in acceleration of aging and arises from oxidative stress reducing phosphatase PTEN (phosphatase tensin homolog), thereby activating PI3K (phosphoinositide-3-kinase) and mTOR (mammalian target of rapamycin). MicroRNA-34a (miR-34a), which is regulated by PI3K-mTOR signaling, plays a pivotal role in reducing sirtuin-1/6, and its inhibition with an antagomir results in their restoration, reducing markers of senescence, reducing senescence-associated secretory phenotype, and reversing cell cycle arrest in epithelial cells from peripheral airways of patients with COPD. miR-570 is also involved in reduction of sirtuin-1 and cellular senescence and is activated by p38 mitogen-activated protein kinase. These miRNAs may be released from cells in extracellular vesicles that are taken up by other cells, thereby spreading senescence locally within the lung but also outside the lung through the circulation; this may account for comorbidities of COPD and other lung diseases. Understanding the mechanisms of cellular senescence may result in new treatments for chronic lung disease, either by inhibiting PI3K-mTOR signaling, by inhibiting specific miRNAs, or by deletion of senescent cells with senolytic therapies, already shown to be effective in experimental lung fibrosis.