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Kunutsor SK, Zaccardi F, Balasubramanian VG, Gillies CL, Aroda VR, Seidu S, Davies MJ, Khunti K. Glycaemic control and macrovascular and microvascular outcomes in type 2 diabetes: Systematic review and meta-analysis of cardiovascular outcome trials of novel glucose-lowering agents. Diabetes Obes Metab 2024; 26:1837-1849. [PMID: 38379094 DOI: 10.1111/dom.15500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/22/2024]
Abstract
AIM Using a systematic review and meta-analysis of placebo-controlled cardiovascular outcome trials (CVOTs) of newer glucose-lowering agents [sodium-glucose cotransporter-2 inhibitors (SGLT-2is), glucagon-like peptide-1 receptor agonists (GLP-1RAs), and dipeptidyl peptidase-4 inhibitors (DPP-4is)] in type 2 diabetes (T2D), we aimed to determine the macrovascular and microvascular outcomes of these agents and clarify the relationships between glycated haemoglobin (HbA1c) reduction and risk of these outcomes. MATERIALS AND METHODS Randomized controlled trials were identified from MEDLINE, Embase and the Cochrane Library until September 2023. Study-specific hazard ratios with 95% confidence intervals (CIs) were pooled, and meta-regression was used to assess the relationships between outcomes and between trial arm HbA1c reductions. RESULTS Twenty unique CVOTs (six SGLT-2is, nine GLP-1RAs, five DPP-4is), based on 169 513 participants with T2D, were eligible. Comparing SGLT-2is, GLP-1RAs and DPP-4is with placebo, the hazard ratios (95% CIs) for 3-point major adverse cardiovascular events were 0.88 (0.82-0.94), 0.85 (0.79-0.92) and 1.00 (0.94-1.06), respectively. SGLT-2is and GLP-1RAs consistently reduced the risk of several macrovascular and microvascular complications, particularly kidney events. DPP-4is showed no macrovascular benefits. There was potential evidence of an inverse linear relationship between HbA1c reduction and 3-point major adverse cardiovascular event risk (estimated risk per 1% reduction in HbA1c: 0.84, 95% CI 0.67-1.06; p = .14; R2 = 14.2%), which was driven by the component of non-fatal stroke (R2 = 100.0%; p = .094). There were non-significant inverse linear relationships between HbA1c reduction and the risk of several vascular outcomes. CONCLUSIONS SGLT-2is and GLP-1RAs showed consistent risk reductions in macrovascular and microvascular outcomes. The vascular benefits of SGLT-2is and GLP-1RAs in patients with T2D extend beyond mere glycaemic control.
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Affiliation(s)
- Setor K Kunutsor
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, UK
| | - Francesco Zaccardi
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, UK
| | - Victoria G Balasubramanian
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- College of Life Sciences, University of Leicester, Leicester, UK
| | - Clare L Gillies
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, UK
| | - Vanita R Aroda
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Samuel Seidu
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, UK
| | - Melanie J Davies
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, UK
| | - Kamlesh Khunti
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, Leicester, UK
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Graham H, Madigan C, Daley AJ. A randomised controlled trial to investigate the feasibility and acceptability of a small change approach to prevent weight gain. J Behav Med 2024; 47:232-243. [PMID: 37932643 PMCID: PMC10944418 DOI: 10.1007/s10865-023-00455-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/13/2023] [Indexed: 11/08/2023]
Abstract
A weight gain prevention strategy showing merit is a small change approach (increase energy expenditure and/or decrease energy intake by 100-200 kcal/day). Studies have tested a small change approach in intensive interventions involving multiple contacts, unsuitable for delivery at scale. The aim here was to assess the feasibility and acceptability of a remote small change weight gain prevention intervention. A randomised controlled trial of 122 participants was conducted. The intervention was a remote 12-week small change weight gain prevention programme (targeting dietary and/or physical activity behaviours). The comparator group received a healthy lifestyle leaflet. Data were collected at baseline and 12-weeks. The primary outcome was the feasibility and acceptability, assessed against three stop-go traffic light criteria: retention, number of participants randomised per month and adherence to a small change approach. Participants' opinions of a small change approach and weight change were also measured. The traffic light stop-go criteria results were green for recruitment (122 participants recruited in three months) and retention (91%) and red for intervention adherence. Most participants (62%) found a small change approach helpful for weight management and the mean difference in weight was - 1.1 kg (95% CI - 1.7, - 0.4), favouring the intervention group. Excluding intervention adherence, the trial was feasible and acceptable to participants. Despite adherence being lower than expected, participants found a small change approach useful for weight management and gained less weight than comparators. With refinement to increase intervention adherence, progress to an effectiveness trial is warranted.ISRCTN18309466: 12/04/2022 (retrospectively registered).
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Affiliation(s)
- Henrietta Graham
- The Centre for Lifestyle Medicine and Behaviour (CLIMB), School of Sport Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK.
| | - Claire Madigan
- The Centre for Lifestyle Medicine and Behaviour (CLIMB), School of Sport Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK
| | - Amanda J Daley
- The Centre for Lifestyle Medicine and Behaviour (CLIMB), School of Sport Exercise and Health Sciences, Loughborough University, Loughborough, LE11 3TU, UK
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Henson J, Tziannou A, Rowlands AV, Edwardson CL, Hall AP, Davies MJ, Yates T. Twenty-four-hour physical behaviour profiles across type 2 diabetes mellitus subtypes. Diabetes Obes Metab 2024; 26:1355-1365. [PMID: 38186324 DOI: 10.1111/dom.15437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/05/2023] [Accepted: 12/17/2023] [Indexed: 01/09/2024]
Abstract
AIM To investigate how 24-h physical behaviours differ across type 2 diabetes (T2DM) subtypes. MATERIALS AND METHODS We included participants living with T2DM, enrolled as part of an ongoing observational study. Participants wore an accelerometer for 7 days to quantify physical behaviours across 24 h. We used routinely collected clinical data (age at onset of diabetes, glycated haemoglobin level, homeostatic model assessment index of beta-cell function, homeostatic model assessment index of insulin resistance, body mass index) to replicate four previously identified subtypes (insulin-deficient diabetes [INS-D], insulin-resistant diabetes [INS-R], obesity-related diabetes [OB] and age-related diabetes [AGE]), via k-means clustering. Differences in physical behaviours across the diabetes subtypes were assessed using generalized linear models, with the AGE cluster as the reference. RESULTS A total of 564 participants were included in this analysis (mean age 63.6 ± 8.4 years, 37.6% female, mean age at diagnosis 53.1 ± 10.0 years). The proportions in each cluster were as follows: INS-D: n = 35, 6.2%; INS-R: n = 88, 15.6%; OB: n = 166, 29.4%; and AGE: n = 275, 48.8%. Compared to the AGE cluster, the OB cluster had a shorter sleep duration (-0.3 h; 95% confidence interval [CI] -0.5, -0.1), lower sleep efficiency (-2%; 95% CI -3, -1), lower total physical activity (-2.9 mg; 95% CI -4.3, -1.6) and less time in moderate-to-vigorous physical activity (-6.6 min; 95% CI -11.4, -1.7), alongside greater sleep variability (17.9 min; 95% CI 8.2, 27.7) and longer sedentary time (31.9 min; 95% CI 10.5, 53.2). Movement intensity during the most active continuous 10 and 30 min of the day was also lower in the OB cluster. CONCLUSIONS In individuals living with T2DM, the OB subtype had the lowest levels of physical activity and least favourable sleep profiles. Such behaviours may be suitable targets for personalized therapeutic lifestyle interventions.
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Affiliation(s)
- Joseph Henson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Aikaterina Tziannou
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Alex V Rowlands
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), UniSA Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Charlotte L Edwardson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Andrew P Hall
- Hanning Sleep Laboratory, Leicester General Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Melanie J Davies
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Thomas Yates
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
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Shivam V, Gillies CL, Goff LM, Zaccardi F, Khunti K. Taste perception genomics in gestational diabetes mellitus: A systematic review. Diabetes Obes Metab 2024; 26:1544-1547. [PMID: 38192264 DOI: 10.1111/dom.15449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 01/10/2024]
Affiliation(s)
- Vishnu Shivam
- Research and Development, Vedanadhi, Salem, India
- Intern, Coimbatore Medical College and Hospital, Coimbatore, India
| | - Clare L Gillies
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Louise M Goff
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | | | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
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Aarestrup J, Pedersen DC, Bjerregaard LG, Jensen BW, Leth-Møller KB, Jacobsen RK, Johnson W, Baker JL. Trends in childhood body mass index between 1936 and 2011 showed that underweight remained more common than obesity among 398 970 Danish school children. Acta Paediatr 2024; 113:818-826. [PMID: 37776041 DOI: 10.1111/apa.16980] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/28/2023] [Accepted: 09/19/2023] [Indexed: 10/01/2023]
Abstract
AIM To examine trends in all body mass index (BMI) groups in children from 1936 to 2011. METHODS We included 197 694 girls and 201 276 boys from the Copenhagen School Health Records Register, born between 1930 and 1996, with longitudinal weight and height measurements (6-14 years). Using International Obesity Task Force criteria, BMI was classified as underweight, normal-weight, overweight and obesity. Sex- and age-specific prevalences were calculated. RESULTS From the 1930s, the prevalence of underweight was stable until a small increase occurred from 1950 to 1970s, and thereafter it declined into the early 2000s. Using 7-year-olds as an example, underweight changed from 10% to 7% in girls and from 9% to 6% in boys during the study period. The prevalence of overweight plateaued from 1950 to 1970s and then steeply increased from 1970s onwards and in 1990-2000s 15% girls and 11% boys at 7 years had overweight. The prevalence of obesity particularly increased from 1980s onwards and in 1990-2000s 5% girls and 4% boys at 7 years had obesity. These trends slightly differed by age. CONCLUSION Among Danish schoolchildren, the prevalence of underweight was greater than overweight until the 1980s and greater than obesity throughout the period. Thus, monitoring the prevalence of childhood underweight remains an important public health issue.
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Affiliation(s)
- J Aarestrup
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - D C Pedersen
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - L G Bjerregaard
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - B W Jensen
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - K B Leth-Møller
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - R K Jacobsen
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - W Johnson
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - J L Baker
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
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Martine-Edith G, Johnson W, Petherick ES. Relationships Between Exposure to Gestational Diabetes Treatment and Neonatal Anthropometry: Evidence from the Born in Bradford (BiB) Cohort. Matern Child Health J 2024; 28:557-566. [PMID: 38019368 PMCID: PMC10914642 DOI: 10.1007/s10995-023-03851-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2023] [Indexed: 11/30/2023]
Abstract
OBJECTIVES To examine the relationships between gestational diabetes mellitus (GDM) treatment and neonatal anthropometry. METHODS Covariate-adjusted multivariable linear regression analyses were used in 9907 offspring of the Born in Bradford cohort. GDM treatment type (lifestyle changes advice only, lifestyle changes and insulin or lifestyle changes and metformin) was the exposure, offspring born to mothers without GDM the control, and birth weight, head, mid-arm and abdominal circumference, and subscapular and triceps skinfold thickness the outcomes. RESULTS Lower birth weight in offspring exposed to insulin (- 117.2 g (95% CI - 173.8, - 60.7)) and metformin (- 200.3 g (- 328.5, - 72.1)) compared to offspring not exposed to GDM was partly attributed to lower gestational age at birth and greater proportion of Pakistani mothers in the treatment groups. Higher subscapular skinfolds in offspring exposed to treatment compared to those not exposed to GDM was partly attributed to higher maternal glucose concentrations at diagnosis. In fully adjusted analyses, offspring exposed to GDM treatment had lower weight, smaller abdominal circumference and skinfolds at birth than those not exposed to GDM. Metformin exposure was associated with smaller offspring mid-arm circumference (- 0.3 cm (- 0.6, - 0.07)) than insulin exposure in fully adjusted models with no other differences found. CONCLUSIONS FOR PRACTICE Offspring exposed to GDM treatment were lighter and smaller at birth than those not exposed to GDM. Metformin-exposed offspring had largely comparable birth anthropometric characteristics to those exposed to insulin.
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Affiliation(s)
- Gilberte Martine-Edith
- School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK
| | - William Johnson
- School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK
| | - Emily S Petherick
- School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Loughborough, LE11 3TU, UK.
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Henson J, Covenant A, Hall AP, Herring L, Rowlands AV, Yates T, Davies MJ. Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review. Diabetes Care 2024; 47:331-343. [PMID: 38394635 DOI: 10.2337/dci23-0037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/27/2023] [Indexed: 02/25/2024]
Abstract
For the first time, the latest American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) consensus guidelines have incorporated a growing body of evidence linking health outcomes associated with type 2 diabetes to the movement behavior composition over the whole 24-h day. Of particular note, the importance of sleep as a key lifestyle component in the management of type 2 diabetes is promulgated and presented using three key constructs: quantity, quality, and timing (i.e., chronotype). In this narrative review we highlight some of the key evidence justifying the inclusion of sleep in the latest consensus guidelines by examining the associations of quantity, quality, and timing of sleep with measures of glycemia, cardiovascular disease risk, and mortality. We also consider potential mechanisms implicated in the association between sleep and type 2 diabetes and provide practical advice for health care professionals about initiating conversations pertaining to sleep in clinical care. In particular, we emphasize the importance of measuring sleep in a free-living environment and provide a summary of the different methodologies and targets. In summary, although the latest ADA/EASD consensus report highlights sleep as a central component in the management of type 2 diabetes, placing it, for the first time, on a level playing field with other lifestyle behaviors (e.g., physical activity and diet), the evidence base for improving sleep (beyond sleep disorders) in those living with type 2 diabetes is limited. This review should act as a timely reminder to incorporate sleep into clinical consultations, ongoing diabetes education, and future interventions.
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Affiliation(s)
- Joseph Henson
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, U.K
| | - Alix Covenant
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, U.K
| | - Andrew P Hall
- University Hospitals of Leicester NHS Trust, Leicester, U.K
- Hanning Sleep Laboratory, Leicester General Hospital, Leicester, U.K
| | - Louisa Herring
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, U.K
- University Hospitals of Leicester NHS Trust, Leicester, U.K
| | - Alex V Rowlands
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, U.K
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), UniSA Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Thomas Yates
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, U.K
| | - Melanie J Davies
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, U.K
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Goldney J, Henson J, Edwardson CL, Khunti K, Davies MJ, Yates T. Long-term ambient air pollution exposure and prospective change in sedentary behaviour and physical activity in individuals at risk of type 2 diabetes in the UK. J Public Health (Oxf) 2024; 46:e32-e42. [PMID: 38103023 PMCID: PMC10901272 DOI: 10.1093/pubmed/fdad263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Air pollution may be a risk factor for physical inactivity and sedentary behaviour (SED) through discouraging active lifestyles, impairing fitness and contributing to chronic diseases with potentially important consequences for population health. METHODS Using generalized estimating equations, we examined the associations between long-term particulate matter with diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10) and nitrogen dioxide (NO2) and annual change in accelerometer-measured SED, moderate-to-vigorous physical activity (MVPA) and steps in adults at risk of type 2 diabetes within the Walking Away from Type 2 Diabetes trial. We adjusted for important confounders including social deprivation and measures of the built environment. RESULTS From 808 participants, 644 had complete data (1605 observations; 64.7% men; mean age 63.86 years). PM2.5, NO2 and PM10 were not associated with change in MVPA/steps but were associated with change in SED, with a 1 ugm-3 increase associated with 6.38 (95% confidence interval: 0.77, 12.00), 1.52 (0.49, 2.54) and 4.48 (0.63, 8.34) adjusted annual change in daily minutes, respectively. CONCLUSIONS Long-term PM2.5, NO2 and PM10 exposures were associated with an annual increase in SED: ~11-22 min/day per year across the sample range of exposure (three standard deviations). Future research should investigate whether interventions to reduce pollution may influence SED.
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Affiliation(s)
- Jonathan Goldney
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Joseph Henson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Charlotte L Edwardson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- Leicester Real World Evidence Unit, Leicester Diabetes Centre, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Melanie J Davies
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Thomas Yates
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
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Mayne RS, Biddle GJH, Edwardson CL, Hart ND, Daley AJ, Heron N. The relationship between general practitioner movement behaviours with burnout and fatigue. BMC Prim Care 2024; 25:60. [PMID: 38365606 PMCID: PMC10870505 DOI: 10.1186/s12875-024-02289-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/01/2024] [Indexed: 02/18/2024]
Abstract
BACKGROUND Physical inactivity is associated with feelings of burnout and fatigue, which in turn are associated with reduced performance among healthcare practitioners. This study explored movement behaviours of general practitioners (GPs) and the association between these behaviours with burnout and fatigue. METHODS GPs in Northern Ireland were asked to wear a thigh-worn accelerometer for seven days and complete validated questionnaires to assess the association between daily number of steps, time spent sitting and standing with feelings of burnout and fatigue. RESULTS Valid accelerometer data were obtained from 47 (77.0%) participants. Average workday sitting time, standing time and number of steps were 10.6 h (SD 1.5), 3.8 h (SD 1.3), and 7796 steps (SD 3116) respectively. Participants were less sedentary (8.0 h (SD 1.6)) and more active (4.7 h (SD 1.4) standing time and 12,408 steps (SD 4496)) on non-workdays. Fourteen (30.4%) participants reported burnout and sixteen (34.8%) reported severe fatigue. There were no significant associations between sitting, standing and step counts with burnout or fatigue (p > 0.05). CONCLUSION GPs were less active on workdays compared to non-workdays and exhibited high levels of sitting. Feelings of burnout and fatigue were highly prevalent, however movement behaviours were not found to be associated with burnout and fatigue. Given the increased sedentariness among GPs on workdays compared to non-workdays, GPs should consider how they can improve their movement behaviours on workdays to help optimise their wellbeing.
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Affiliation(s)
- Richard S Mayne
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK.
| | - Gregory J H Biddle
- School of Sport, Exercise and Health Sciences, The Centre for Lifestyle Medicine and Behaviour, Loughborough University, Loughborough, UK
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester General Hospital, Leicester, UK
| | - Charlotte L Edwardson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester General Hospital, Leicester, UK
| | - Nigel D Hart
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Amanda J Daley
- School of Sport, Exercise and Health Sciences, The Centre for Lifestyle Medicine and Behaviour, Loughborough University, Loughborough, UK
| | - Neil Heron
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
- School of Medicine, Keele University, David Weatherall Building, Keele, UK
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Kunutsor SK, Bhattacharjee A, Connelly MA, Bakker SJL, Dullaart RPF. Alcohol Consumption, High-Density Lipoprotein Particles and Subspecies, and Risk of Cardiovascular Disease: Findings from the PREVEND Prospective Study. Int J Mol Sci 2024; 25:2290. [PMID: 38396968 PMCID: PMC10889823 DOI: 10.3390/ijms25042290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/10/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
The associations of HDL particle (HDL-P) and subspecies concentrations with alcohol consumption are unclear. We aimed to evaluate the interplay between alcohol consumption, HDL parameters and cardiovascular disease (CVD) risk. In the PREVEND study of 5151 participants (mean age, 53 years; 47.5% males), self-reported alcohol consumption and HDL-P and subspecies (small, medium, and large) by nuclear magnetic resonance spectroscopy were assessed. Hazard ratios (HRs) with 95% CIs for first CVD events were estimated. In multivariable linear regression analyses, increasing alcohol consumption increased HDL-C, HDL-P, large and medium HDL, HDL size, and HDL subspecies (H3P, H4P, H6 and H7) in a dose-dependent manner. During a median follow-up of 8.3 years, 323 first CVD events were recorded. Compared with abstainers, the multivariable adjusted HRs (95% CIs) of CVD for occasional to light, moderate, and heavy alcohol consumers were 0.72 (0.55-0.94), 0.74 (0.54-1.02), and 0.65 (0.38-1.09), respectively. These associations remained consistent on additional adjustment for each HDL parameter. For CVD, only HDL-C was associated with a statistically significant decreased risk of CVD in a fully adjusted analysis (HR 0.84, 95% CI 0.72-0.97 per 1 SD increment). For coronary heart disease, HDL-C, HDL-P, medium HDL, HDL size, and H4P showed inverse associations, whereas HDL-C and HDL size modestly increased stroke risk. Except for H6P, alcohol consumption did not modify the associations between HDL parameters and CVD risk. The addition of HDL-C, HDL size, or H4P to a CVD risk prediction model containing established risk factors improved risk discrimination. Increasing alcohol consumption is associated with increased HDL-C, HDL-P, large and medium HDL, HDL size, and some HDL subspecies. Associations of alcohol consumption with CVD are largely independent of HDL parameters. The associations of HDL parameters with incident CVD are generally not attenuated or modified by alcohol consumption.
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Affiliation(s)
- Setor K. Kunutsor
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester LE5 4WP, UK
| | - Atanu Bhattacharjee
- Division of Population Health and Genomics, University of Dundee, Dundee DD1 4HN, UK;
| | | | - Stephan J. L. Bakker
- Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands;
| | - Robin P. F. Dullaart
- Division of Endocrinology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands;
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11
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Rick EM, Woolnough K, Richardson M, Monteiro W, Craner M, Bourne M, Cousins DJ, Swoboda I, Wardlaw AJ, Pashley CH. Identification of allergens from Aspergillus fumigatus-Potential association with lung damage in asthma. Allergy 2024. [PMID: 38334146 DOI: 10.1111/all.16032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 02/10/2024]
Abstract
BACKGROUND Component-resolved diagnosis allows detection of IgE sensitization having the advantage of reproducibility and standardization compared to crude extracts. The main disadvantage of the traditional allergen identification methods, 1- or 2-dimensional western blotting and screening of expression cDNA libraries with patients' IgEs, is that the native structure of the protein is not necessarily maintained. METHODS We used a novel immunoprecipitation technique in combination with mass spectrometry to identify new allergens of Aspergillus fumigatus. Magnetic Dynabeads coupled with anti-human IgE antibodies were used to purify human serum IgE and subsequently allergens from A. fumigatus protein extract. RESULTS Of the 184 proteins detected by subsequent mass peptide fingerprinting, a subset of 13 were recombinantly expressed and purified. In a panel of 52 A. fumigatus-sensitized people with asthma, 23 non-fungal-sensitized asthmatics and 18 healthy individuals, only the former showed an IgE reaction by immunoblotting and/or ELISA. We discovered 11 proteins not yet described as A. fumigatus allergens, with fructose-bisphosphate aldolase class II (FBA2) (33%), NAD-dependent malate dehydrogenase (31%) and Cu/Zn superoxide dismutase (27%) being the most prevalent. With respect to these three allergens, native versus denatured protein assays indicated a better recognition of the native proteins. Seven of 11 allergens fulfilled the WHO/IUIS criteria and were accepted as new A. fumigatus allergens. CONCLUSION In conclusion, we introduce a straightforward method of allergen identification from complex allergenic sources such as A. fumigatus by immunoprecipitation combined with mass spectrometry, which has the advantage over traditional methods of identifying allergens by maintaining the structure of the proteins.
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Affiliation(s)
- Eva-Maria Rick
- Department of Respiratory Sciences, Aerobiology and Mycology Group, Institute for Lung Health, Leicester Biomedical Research Centre - Respiratory, University of Leicester, Leicester, UK
- Division of Clinical and Molecular Allergology, Airway Research Center North (ARCN), Member of the German Center for Lung Research, Borstel Sulfeld, Germany
| | - Kerry Woolnough
- Department of Allergy and Respiratory Medicine, Leicester Biomedical Research Centre - Respiratory, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, UK
| | - Matthew Richardson
- Department of Allergy and Respiratory Medicine, Leicester Biomedical Research Centre - Respiratory, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, UK
| | - William Monteiro
- Department of Allergy and Respiratory Medicine, Leicester Biomedical Research Centre - Respiratory, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, UK
| | - Michelle Craner
- Department of Allergy and Respiratory Medicine, Leicester Biomedical Research Centre - Respiratory, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, UK
| | - Michelle Bourne
- Department of Allergy and Respiratory Medicine, Leicester Biomedical Research Centre - Respiratory, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, UK
| | - David John Cousins
- Department of Respiratory Sciences, Aerobiology and Mycology Group, Institute for Lung Health, Leicester Biomedical Research Centre - Respiratory, University of Leicester, Leicester, UK
| | - Ines Swoboda
- Competence Center for Molecular Biotechnology, Molecular Biotechnology Section, FH Campus Wien, University of Applied Sciences, Vienna, Austria
| | - Andrew John Wardlaw
- Department of Respiratory Sciences, Aerobiology and Mycology Group, Institute for Lung Health, Leicester Biomedical Research Centre - Respiratory, University of Leicester, Leicester, UK
- Department of Allergy and Respiratory Medicine, Leicester Biomedical Research Centre - Respiratory, University Hospitals of Leicester NHS Trust, Glenfield Hospital, Leicester, UK
| | - Catherine Helen Pashley
- Department of Respiratory Sciences, Aerobiology and Mycology Group, Institute for Lung Health, Leicester Biomedical Research Centre - Respiratory, University of Leicester, Leicester, UK
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12
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Lightfoot CJ, Wilkinson TJ, Vadaszy N, Graham-Brown MPM, Davies MJ, Yates T, Smith AC. Improving self-management behaviour through a digital lifestyle intervention: An internal pilot study. J Ren Care 2024. [PMID: 38296833 DOI: 10.1111/jorc.12488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/07/2023] [Accepted: 01/12/2024] [Indexed: 02/02/2024]
Abstract
BACKGROUND Self-management is a key component of successful chronic kidney disease (CKD) management. Here, we present the findings from the internal pilot of a multicentre randomised controlled trial (RCT) aimed to test the effect of a digital self-management programme ('My Kidneys & Me' (MK&M)). METHODS Participants (aged ≥18 years and CKD stages 3-4) were recruited from hospital kidney services across England. Study processes were completed virtually. Participants were randomised 2:1 to either intervention (MK&M) or control group. The first 60 participants recruited were included in a 10-week internal pilot which assessed study feasibility and acceptability against pre-specified progression criteria: 1) eligibility and recruitment, acceptability of 2) randomisation and 3) outcomes, 4) MK&M activation, and 5) retention and attrition rates. Semi-structured interviews further explored views on trial participation. RESULTS Of the 60 participants recruited, 41 were randomised to MK&M and 19 to control. All participants completed baseline measures and 62% (n=37) completed post-intervention outcome measures. All progression criteria met the minimum thresholds to proceed. Nine participants were interviewed. The themes identified were satisfaction with study recruitment processes (openness to participate, reading and agreeing to "terms and conditions"), acceptability of study design (remote study participation, acceptability of randomisation, completion of online assessment(s)), and methods to improve recruitment and retention (personalised approach, follow-up communication). CONCLUSION This internal pilot demonstrated the feasibility and acceptability of a virtually run RCT. Progression criteria thresholds to proceed to the definitive RCT were met. Areas for improvement were identified and protocol amendments were made to improve trial delivery.
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Affiliation(s)
- Courtney J Lightfoot
- Leicester Kidney Lifestyle Team, Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Thomas J Wilkinson
- Leicester Kidney Lifestyle Team, Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Noemi Vadaszy
- Leicester Kidney Lifestyle Team, Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Matthew P M Graham-Brown
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Department of Renal Medicine, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Melanie J Davies
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Thomas Yates
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Alice C Smith
- Leicester Kidney Lifestyle Team, Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
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13
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Abell L, Maher F, Jennings AC, Gray LJ. A systematic review of simulation studies which compare existing statistical methods to account for non-compliance in randomised controlled trials. BMC Med Res Methodol 2023; 23:300. [PMID: 38104108 PMCID: PMC10724933 DOI: 10.1186/s12874-023-02126-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023] Open
Abstract
INTRODUCTION Non-compliance is a common challenge for researchers and may reduce the power of an intention-to-treat analysis. Whilst a per protocol approach attempts to deal with this issue, it can result in biased estimates. Several methods to resolve this issue have been identified in previous reviews, but there is limited evidence supporting their use. This review aimed to identify simulation studies which compare such methods, assess the extent to which certain methods have been investigated and determine their performance under various scenarios. METHODS A systematic search of several electronic databases including MEDLINE and Scopus was carried out from conception to 30th November 2022. Included papers were published in a peer-reviewed journal, readily available in the English language and focused on comparing relevant methods in a superiority randomised controlled trial under a simulation study. Articles were screened using these criteria and a predetermined extraction form used to identify relevant information. A quality assessment appraised the risk of bias in individual studies. Extracted data was synthesised using tables, figures and a narrative summary. Both screening and data extraction were performed by two independent reviewers with disagreements resolved by consensus. RESULTS Of 2325 papers identified, 267 full texts were screened and 17 studies finally included. Twelve methods were identified across papers. Instrumental variable methods were commonly considered, but many authors found them to be biased in some settings. Non-compliance was generally assumed to be all-or-nothing and only occurring in the intervention group, although some methods considered it as time-varying. Simulation studies commonly varied the level and type of non-compliance and factors such as effect size and strength of confounding. The quality of papers was generally good, although some lacked detail and justification. Therefore, their conclusions were deemed to be less reliable. CONCLUSIONS It is common for papers to consider instrumental variable methods but more studies are needed that consider G-methods and compare a wide range of methods in realistic scenarios. It is difficult to make conclusions about the best method to deal with non-compliance due to a limited body of evidence and the difficulty in combining results from independent simulation studies. PROSPERO REGISTRATION NUMBER CRD42022370910.
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Affiliation(s)
- Lucy Abell
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Francesca Maher
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Angus C Jennings
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Laura J Gray
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
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14
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Ungvari Z, Fazekas-Pongor V, Csiszar A, Kunutsor SK. The multifaceted benefits of walking for healthy aging: from Blue Zones to molecular mechanisms. GeroScience 2023; 45:3211-3239. [PMID: 37495893 PMCID: PMC10643563 DOI: 10.1007/s11357-023-00873-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/11/2023] [Indexed: 07/28/2023] Open
Abstract
Physical activity, including walking, has numerous health benefits in older adults, supported by a plethora of observational and interventional studies. Walking decreases the risk or severity of various health outcomes such as cardiovascular and cerebrovascular diseases, type 2 diabetes mellitus, cognitive impairment and dementia, while also improving mental well-being, sleep, and longevity. Dose-response relationships for walking duration and intensity are established for adverse cardiovascular outcomes. Walking's favorable effects on cardiovascular risk factors are attributed to its impact on circulatory, cardiopulmonary, and immune function. Meeting current physical activity guidelines by walking briskly for 30 min per day for 5 days can reduce the risk of several age-associated diseases. Additionally, low-intensity physical exercise, including walking, exerts anti-aging effects and helps prevent age-related diseases, making it a powerful tool for promoting healthy aging. This is exemplified by the lifestyles of individuals in Blue Zones, regions of the world with the highest concentration of centenarians. Walking and other low-intensity physical activities contribute significantly to the longevity of individuals in these regions, with walking being an integral part of their daily lives. Thus, incorporating walking into daily routines and encouraging walking-based physical activity interventions can be an effective strategy for promoting healthy aging and improving health outcomes in all populations. The goal of this review is to provide an overview of the vast and consistent evidence supporting the health benefits of physical activity, with a specific focus on walking, and to discuss the impact of walking on various health outcomes, including the prevention of age-related diseases. Furthermore, this review will delve into the evidence on the impact of walking and low-intensity physical activity on specific molecular and cellular mechanisms of aging, providing insights into the underlying biological mechanisms through which walking exerts its beneficial anti-aging effects.
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Affiliation(s)
- Zoltan Ungvari
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary.
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | | | - Anna Csiszar
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Translational Medicine, Semmelweis University, Budapest, Hungary
| | - Setor K Kunutsor
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Gwendolen Road, Leicester, LE5 4WP, UK.
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15
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Abell L, Maher F, Begum S, Booth S, Broomfield J, Lee S, Smith E, Stannard R, Teece L, Vounzoulaki E, Worboys H, Gray LJ. Incorporation of patient and public involvement in statistical methodology research: a survey assessing current practices and attitudes of researchers. Res Involv Engagem 2023; 9:100. [PMID: 37891693 PMCID: PMC10612225 DOI: 10.1186/s40900-023-00507-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 10/16/2023] [Indexed: 10/29/2023]
Abstract
BACKGROUND Patient and public involvement (PPI) ensures that research is designed and conducted in a manner that is most beneficial to the individuals whom it will impact. It has an undisputed place in applied research and is required by many funding bodies. However, PPI in statistical methodology research is more challenging and work is needed to identify where and how patients and the public can meaningfully input in this area. METHODS A descriptive cross-sectional research study was conducted using an online questionnaire, which asked statistical methodologists about themselves and their experience conducting PPI, either to inform a grant application or during a funded statistical methodology project. The survey included both closed-text responses, which were reported using summary statistics, and open-ended questions for which common themes were identified. RESULTS 119 complete responses were recorded. Individuals who completed the survey displayed an even range of ages, career lengths and positions, with the majority working in academia. 40.3% of participants reported undertaking PPI to inform a grant application and the majority reported that the inclusion of PPI was received positively by the funder. Only 21.0% of participants reported undertaking PPI during a methodological project. 31.0% of individuals thought that PPI was "very" or "extremely" relevant to statistical methodology research, with 45.5% responding "somewhat" and 24.4% answering "not at all" or "not very". Arguments for including PPI were that it can provide the motivation for research and shape the research question. Negative opinions included that it is too technical for the public to understand, so they cannot have a meaningful impact. CONCLUSIONS This survey found that the views of statistical methodologists on the inclusion of PPI in their research are varied, with some individuals having particularly strong opinions, both positive and negative. Whilst this is clearly a divisive topic, one commonly identified theme was that many researchers are willing to try and incorporate meaningful PPI into their research but would feel more confident if they had access to resources such as specialised training, guidelines, and case studies.
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Affiliation(s)
- Lucy Abell
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Francesca Maher
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Samina Begum
- Statistical Methodology PPI Group, University of Leicester, Leicester, UK
| | - Sarah Booth
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Jonathan Broomfield
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Sangyu Lee
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Ellesha Smith
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Rachael Stannard
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Lucy Teece
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | | | - Hannah Worboys
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Laura J Gray
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
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16
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Henson J, De Craemer M, Yates T. Sedentary behaviour and disease risk. BMC Public Health 2023; 23:2048. [PMID: 37858149 PMCID: PMC10588158 DOI: 10.1186/s12889-023-16867-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 09/29/2023] [Indexed: 10/21/2023] Open
Abstract
Sedentary behaviour has become the new reference of living, which has paralleled the increase in the prevalence of multiple chronic diseases. Here, we highlight the evidence to date and propose specific topics of interest for the Collection at BMC Public Health, titled "Sedentary behaviour and disease risk".
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Affiliation(s)
- Joseph Henson
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, LE5 4PW, Leicester, UK.
| | | | - Thomas Yates
- NIHR Leicester Biomedical Research Centre, Diabetes Research Centre, College of Life Sciences, University of Leicester, LE5 4PW, Leicester, UK
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17
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Maher F, Teece L, Major RW, Bradbury N, Medcalf JF, Brunskill NJ, Booth S, Gray LJ. Using the kidney failure risk equation to predict end-stage kidney disease in CKD patients of South Asian ethnicity: an external validation study. Diagn Progn Res 2023; 7:22. [PMID: 37798742 PMCID: PMC10552237 DOI: 10.1186/s41512-023-00157-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 09/11/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND The kidney failure risk equation (KFRE) predicts the 2- and 5-year risk of needing kidney replacement therapy (KRT) using four risk factors - age, sex, urine albumin-to-creatinine ratio (ACR) and creatinine-based estimated glomerular filtration rate (eGFR). Although the KFRE has been recalibrated in a UK cohort, this did not consider minority ethnic groups. Further validation of the KFRE in different ethnicities is a research priority. The KFRE also does not consider the competing risk of death, which may lead to overestimation of KRT risk. This study externally validates the KFRE for patients of South Asian ethnicity and compares methods for accounting for ethnicity and the competing event of death. METHODS Data were gathered from an established UK cohort containing 35,539 individuals diagnosed with chronic kidney disease. The KFRE was externally validated and updated in several ways taking into account ethnicity, using recognised methods for time-to-event data, including the competing risk of death. A clinical impact assessment compared the updated models through consideration of referrals made to secondary care. RESULTS The external validation showed the risk of KRT differed by ethnicity. Model validation performance improved when incorporating ethnicity and its interactions with ACR and eGFR as additional risk factors. Furthermore, accounting for the competing risk of death improved prediction. Using criteria of 5 years ≥ 5% predicted KRT risk, the competing risks model resulted in an extra 3 unnecessary referrals (0.59% increase) but identified an extra 1 KRT case (1.92% decrease) compared to the previous best model. Hybrid criteria of predicted risk using the competing risks model and ACR ≥ 70 mg/mmol should be used in referrals to secondary care. CONCLUSIONS The accuracy of KFRE prediction improves when updated to consider South Asian ethnicity and to account for the competing risk of death. This may reduce unnecessary referrals whilst identifying risks of KRT and could further individualise the KFRE and improve its clinical utility. Further research should consider other ethnicities.
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Affiliation(s)
- Francesca Maher
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Lucy Teece
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Rupert W Major
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- John Walls Renal Unit, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Naomi Bradbury
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - James F Medcalf
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- John Walls Renal Unit, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Nigel J Brunskill
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- John Walls Renal Unit, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Sarah Booth
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Laura J Gray
- Department of Population Health Sciences, University of Leicester, Leicester, UK.
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18
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Aung H, McAuley H, Porter K, Richardson M, Wright A, Brightling CE, Greening NJ. Differences in hospital admissions for acute exacerbations of COPD during the COVID-19 pandemic stratified by stable-state blood eosinophil count. Eur Respir J 2023; 62:2301125. [PMID: 37770078 PMCID: PMC10568037 DOI: 10.1183/13993003.01125-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 09/07/2023] [Indexed: 10/03/2023]
Abstract
Acute exacerbations of COPD (AECOPD) are driven through different triggers, including infection such as viruses and bacteria. However, nearly 40% of exacerbations are associated with a blood eosinophilia and related to type 2 inflammation (T2-high) [1]. Hospital admission for exacerbations of COPD fell only in non-T2-high patients during the COVID-19 pandemic and only in non-eosinophilic admissions. Phenotyping of AECOPD, including at time of exacerbation, is needed for personalised management. https://bit.ly/3ZiUtYx
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Affiliation(s)
- Hnin Aung
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
| | - Hamish McAuley
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
| | - Kate Porter
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
| | - Matthew Richardson
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
| | - Adam Wright
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
| | - Christopher E Brightling
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
| | - Neil J Greening
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Institute for Lung Health, NIHR Leicester BRC, Glenfield Hospital, Leicester, UK
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Katsarova SS, Redman E, Arsenyadis F, Brady EM, Rowlands AV, Edwardson CL, Goff LM, Khunti K, Yates T, Hall AP, Davies MJ, Henson J. Differences in Dietary Intake, Eating Occasion Timings and Eating Windows between Chronotypes in Adults Living with Type 2 Diabetes Mellitus. Nutrients 2023; 15:3868. [PMID: 37764651 PMCID: PMC10537296 DOI: 10.3390/nu15183868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/29/2023] Open
Abstract
Chronotype studies investigating dietary intake, eating occasions (EO) and eating windows (EW) are sparse in people with type 2 Diabetes mellitus (T2DM). This analysis reports data from the CODEC study. The Morningness-Eveningness questionnaire (MEQ) assessed chronotype preference. Diet diaries assessed dietary intake and temporal distribution. Regression analysis assessed whether dietary intake, EW, or EO differed by chronotype. 411 participants were included in this analysis. There were no differences in energy, macronutrient intake or EW between chronotypes. Compared to evening chronotypes, morning and intermediate chronotypes consumed 36.8 (95% CI: 11.1, 62.5) and 20.9 (95% CI: -2.1, 44.1) fewer milligrams of caffeine per day, respectively. Evening chronotypes woke up over an hour and a half later than morning (01:36 95% CI: 01:09, 02:03) and over half an hour later than intermediate chronotypes (00:45 95% CI: 00:21; 01:09. Evening chronotypes went to sleep over an hour and a half later than morning (01:48 95% CI: 01:23; 02:13) and an hour later than intermediate chronotypes (01:07 95% CI: 00:45; 01:30). Evening chronotypes' EOs and last caffeine intake occurred later but relative to their sleep timings. Future research should investigate the impact of chronotype and dietary temporal distribution on glucose control to optimise T2DM interventions.
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Affiliation(s)
- Stanislava S. Katsarova
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
- Diabetes Research Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | - Emma Redman
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
- Diabetes Research Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | - Franciskos Arsenyadis
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
- Diabetes Research Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | - Emer M. Brady
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Alex V. Rowlands
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, Division of Health Sciences, University of South Australia, Adelaide, SA 5001, Australia
| | - Charlotte L. Edwardson
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
| | - Louise M. Goff
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
| | - Kamlesh Khunti
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
- NIHR Applied Health Research Collaboration—East Midlands (NUHR ARC-EM), Leicester Diabetes Centre, Leicester LE5 4PW, UK
| | - Thomas Yates
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
| | - Andrew P. Hall
- Diabetes Research Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
- Hanning Sleep Laboratory, Leicester General Hospital, Leicester LE5 4PW, UK
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Melanie J. Davies
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
| | - Joseph Henson
- NIHR Leicester Biomedical Research Centre, Leicester General Hospital, College of Life Sciences, University of Leicester, Leicester LE5 4PW, UK (J.H.)
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Dattani A, Brady EM, Alfuhied A, Gulsin GS, Steadman CD, Yeo JL, Aslam S, Banovic M, Jerosch-Herold M, Xue H, Kellman P, Costet P, Cvijic ME, Zhao L, Ebert C, Liu L, Gunawardhana K, Gordon D, Chang CP, Arnold JR, Yates T, Kelly D, Hogrefe K, Dawson D, Greenwood J, Ng LL, Singh A, McCann GP. Impact of diabetes on remodelling, microvascular function and exercise capacity in aortic stenosis. Open Heart 2023; 10:e002441. [PMID: 37586847 PMCID: PMC10432628 DOI: 10.1136/openhrt-2023-002441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/04/2023] [Indexed: 08/18/2023] Open
Abstract
OBJECTIVE To characterise cardiac remodelling, exercise capacity and fibroinflammatory biomarkers in patients with aortic stenosis (AS) with and without diabetes, and assess the impact of diabetes on outcomes. METHODS Patients with moderate or severe AS with and without diabetes underwent echocardiography, stress cardiovascular magnetic resonance (CMR), cardiopulmonary exercise testing and plasma biomarker analysis. Primary endpoint for survival analysis was a composite of cardiovascular mortality, myocardial infarction, hospitalisation with heart failure, syncope or arrhythmia. Secondary endpoint was all-cause death. RESULTS Diabetes (n=56) and non-diabetes groups (n=198) were well matched for age, sex, ethnicity, blood pressure and severity of AS. The diabetes group had higher body mass index, lower estimated glomerular filtration rate and higher rates of hypertension, hyperlipidaemia and symptoms of AS. Biventricular volumes and systolic function were similar, but the diabetes group had higher extracellular volume fraction (25.9%±3.1% vs 24.8%±2.4%, p=0.020), lower myocardial perfusion reserve (2.02±0.75 vs 2.34±0.68, p=0.046) and lower percentage predicted peak oxygen consumption (68%±21% vs 77%±17%, p=0.002) compared with the non-diabetes group. Higher levels of renin (log10renin: 3.27±0.59 vs 2.82±0.69 pg/mL, p<0.001) were found in diabetes. Multivariable Cox regression analysis showed diabetes was not associated with cardiovascular outcomes, but was independently associated with all-cause mortality (HR 2.04, 95% CI 1.05 to 4.00; p=0.037). CONCLUSIONS In patients with moderate-to-severe AS, diabetes is associated with reduced exercise capacity, increased diffuse myocardial fibrosis and microvascular dysfunction, but not cardiovascular events despite a small increase in mortality.
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Affiliation(s)
- Abhishek Dattani
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Emer M Brady
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Aseel Alfuhied
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Gaurav S Gulsin
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Christopher D Steadman
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
- Department of Cardiology, Poole Hospital NHS Foundation Trust, Poole, UK
| | - Jian L Yeo
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Saadia Aslam
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Marko Banovic
- Cardiology Department, Clinical Centre of Serbia, Belgrade, Serbia
| | | | - Hui Xue
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Peter Kellman
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | | | | | - Lei Zhao
- Bristol Myers Squibb Co, Princeton, New Jersey, USA
| | | | - Laura Liu
- Bristol Myers Squibb Co, Princeton, New Jersey, USA
| | | | - David Gordon
- Bristol Myers Squibb Co, Princeton, New Jersey, USA
| | | | - J Ranjit Arnold
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Thomas Yates
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Damian Kelly
- Cardiology Department, Royal Derby Hospital, Derby, UK
| | - Kai Hogrefe
- Cardiology Department, Kettering General Hospital NHS Foundation Trust, Kettering, UK
| | - Dana Dawson
- Cardiovascular Medicine Research Unit, University of Aberdeen, Aberdeen, UK
| | - John Greenwood
- Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
- Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Leong L Ng
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Anvesha Singh
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Gerry P McCann
- Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
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21
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Liu W, Deng W, Chen M, Dong Z, Zhu B, Yu Z, Tang D, Sauler M, Lin C, Wain LV, Cho MH, Kaminski N, Zhao H. A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases. PLoS Genet 2023; 19:e1010825. [PMID: 37523391 PMCID: PMC10414598 DOI: 10.1371/journal.pgen.1010825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 08/10/2023] [Accepted: 06/12/2023] [Indexed: 08/02/2023] Open
Abstract
Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. In this manuscript, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed good statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblasts in lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs.
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Affiliation(s)
- Wei Liu
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Wenxuan Deng
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Ming Chen
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Zihan Dong
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Biqing Zhu
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Zhaolong Yu
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Daiwei Tang
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Maor Sauler
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Chen Lin
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Hongyu Zhao
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
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22
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Debiec R, Lawday D, Bountziouka V, Beeston E, Greengrass C, Bramley R, Sehmi S, Kharodia S, Newton M, Marshall A, Krzeminski A, Zafar A, Chahal A, Heer A, Khunti K, Joshi N, Lakhani M, Farooqi A, Patel R, Samani NJ. Evaluating the clinical effectiveness of the NHS Health Check programme: a prospective analysis in the Genetics and Vascular Health Check (GENVASC) study. BMJ Open 2023; 13:e068025. [PMID: 37253489 PMCID: PMC10230936 DOI: 10.1136/bmjopen-2022-068025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 04/18/2023] [Indexed: 06/01/2023] Open
Abstract
OBJECTIVE The aim of the study was to assess the clinical effectiveness of the national cardiovascular disease (CVD) prevention programme-National Health Service Health Check (NHSHC) in reduction of CVD risk. DESIGN Prospective cohort study. SETTING 147 primary care practices in Leicestershire and Northamptonshire in England, UK. PARTICIPANTS 27 888 individuals undergoing NHSHC with a minimum of 18 months of follow-up data. OUTCOME MEASURES The primary outcomes were NHSHC attributed detection of CVD risk factors, prescription of medications, changes in values of individual risk factors and frequency of follow-up. RESULTS At recruitment, 18% of participants had high CVD risk (10%-20% 10-year risk) and 4% very high CVD risk (>20% 10-year risk). New diagnoses or hypertension (HTN) was made in 2.3% participants, hypercholesterolaemia in 0.25% and diabetes mellitus in 0.9%. New prescription of stains and antihypertensive medications was observed in 5.4% and 5.4% of participants, respectively. Total cholesterol was decreased on average by 0.38 mmol/L (95% CI -0.34 to -0.41) and 1.71 mmol/L (-1.48 to -1.94) in patients with initial cholesterol >5 mmol/L and >7.5 mmol/L, respectively. Systolic blood pressure was decreased on average by 2.9 mm Hg (-2.3 to -3.7), 15.7 mm Hg (-14.1 to -17.5) and 33.4 mm Hg (-29.4 to -37.7), in patients with grade 1, 2 and 3 HTN, respectively. About one out of three patients with increased CVD risk had no record of follow-up or treatment. CONCLUSIONS Majority of patients identified with increased CVD risk through the NHSHC were followed up and received effective clinical interventions. However, one-third of high CVD risk patients had no follow-up and therefore did not receive any treatment. Our study highlights areas of focus which could improve the effectiveness of the programme. TRIAL REGISTRATION NUMBER NCT04417387.
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Affiliation(s)
- Radoslaw Debiec
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Daniel Lawday
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Vasiliki Bountziouka
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
- Department of Food Science and Nutrition, University of the Aegean, Lemnos, Greece
| | - Emma Beeston
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Chris Greengrass
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Richard Bramley
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Sue Sehmi
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Shireen Kharodia
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Michelle Newton
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | - Andrea Marshall
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
| | | | - Azhar Zafar
- Diabetes Research Centre, University of Leicester, Leicester, UK
- Diabetes and Cardiovascular Medicine General Practice Alliance Federation Research and Training Academy, Northampton, UK
| | - Anuj Chahal
- South Leicestershire Medical Group, Kibworth Beauchamp, UK
| | | | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | | | - Mayur Lakhani
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Azhar Farooqi
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Riyaz Patel
- Institute of Cardiovascular Science, University College London, London, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences and NIHR Cardiovascular Research Centre, University of Leicester, Leicester, UK
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23
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Thackray AE, Hinton EC, Alanazi TM, Dera AM, Fujihara K, Hamilton-Shield JP, King JA, Lithander FE, Miyashita M, Thompson J, Morgan PS, Davies MJ, Stensel DJ. Exploring the acute effects of running on cerebral blood flow and food cue reactivity in healthy young men using functional magnetic resonance imaging. Hum Brain Mapp 2023; 44:3815-3832. [PMID: 37145965 DOI: 10.1002/hbm.26314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 03/17/2023] [Accepted: 04/06/2023] [Indexed: 05/07/2023] Open
Abstract
Acute exercise suppresses appetite and alters food-cue reactivity, but the extent exercise-induced changes in cerebral blood flow (CBF) influences the blood-oxygen-level-dependent (BOLD) signal during appetite-related paradigms is not known. This study examined the impact of acute running on visual food-cue reactivity and explored whether such responses are influenced by CBF variability. In a randomised crossover design, 23 men (mean ± SD: 24 ± 4 years, 22.9 ± 2.1 kg/m2 ) completed fMRI scans before and after 60 min of running (68% ± 3% peak oxygen uptake) or rest (control). Five-minute pseudo-continuous arterial spin labelling fMRI scans were conducted for CBF assessment before and at four consecutive repeat acquisitions after exercise/rest. BOLD-fMRI was acquired during a food-cue reactivity task before and 28 min after exercise/rest. Food-cue reactivity analysis was performed with and without CBF adjustment. Subjective appetite ratings were assessed before, during and after exercise/rest. Exercise CBF was higher in grey matter, the posterior insula and in the region of the amygdala/hippocampus, and lower in the medial orbitofrontal cortex and dorsal striatum than control (main effect trial p ≤ .018). No time-by-trial interactions for CBF were identified (p ≥ .087). Exercise induced moderate-to-large reductions in subjective appetite ratings (Cohen's d = 0.53-0.84; p ≤ .024) and increased food-cue reactivity in the paracingulate gyrus, hippocampus, precuneous cortex, frontal pole and posterior cingulate gyrus. Accounting for CBF variability did not markedly alter detection of exercise-induced BOLD signal changes. Acute running evoked overall changes in CBF that were not time dependent and increased food-cue reactivity in regions implicated in attention, anticipation of reward, and episodic memory independent of CBF.
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Affiliation(s)
- Alice E Thackray
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, UK
| | - Elanor C Hinton
- National Institute for Health and Care Research (NIHR) Bristol Biomedical Research Centre Nutrition Theme, University of Bristol, Bristol, UK
| | - Turki M Alanazi
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- Department of Respiratory Therapy, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Al Ahsa, Saudi Arabia
- King Abdullah International Medical Research Center, Al Ahsa, Saudi Arabia
| | - Abdulrahman M Dera
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- College of Sport Sciences, Jeddah University, Saudi Arabia
| | - Kyoko Fujihara
- Graduate School of Sport Sciences, Waseda University, Tokorozawa, Japan
| | - Julian P Hamilton-Shield
- National Institute for Health and Care Research (NIHR) Bristol Biomedical Research Centre Nutrition Theme, University of Bristol, Bristol, UK
| | - James A King
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, UK
| | - Fiona E Lithander
- National Institute for Health and Care Research (NIHR) Bristol Biomedical Research Centre Nutrition Theme, University of Bristol, Bristol, UK
- Liggins Institute, University of Auckland, Auckland, New Zealand
- Department of Nutrition and Dietetics, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | | | - Julie Thompson
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- University Hospitals of Leicester NHS Trust, Infirmary Square, Leicester, UK
| | - Paul S Morgan
- Radiological Sciences, School of Medicine, University of Nottingham, UK
- National Institute for Health and Care Research (NIHR) Nottingham Biomedical Research Centre, Nottingham, UK
| | - Melanie J Davies
- National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - David J Stensel
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
- National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, UK
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
- Department of Sports Science and Physical Education, The Chinese University of Hong Kong, Ma Liu Shui, Hong Kong
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24
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Tan PS, Patone M, Clift AK, Dambha-Miller H, Saatci D, Ranger TA, Garriga C, Zaccardi F, Shah BR, Coupland C, Griffin SJ, Khunti K, Hippisley-Cox J. Factors influencing influenza, pneumococcal and shingles vaccine uptake and refusal in older adults: a population-based cross-sectional study in England. BMJ Open 2023; 13:e058705. [PMID: 36927589 PMCID: PMC10030484 DOI: 10.1136/bmjopen-2021-058705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
OBJECTIVES Uptake of influenza, pneumococcal and shingles vaccines in older adults vary across regions and socioeconomic backgrounds. In this study, we study the coverage and factors associated with vaccination uptake, as well as refusal in the unvaccinated population and their associations with ethnicity, deprivation, household size and health conditions. DESIGN, SETTING AND PARTICIPANTS This is a cross-sectional study of adults aged 65 years or older in England, using a large primary care database. Associations of vaccine uptake and refusal in the unvaccinated with ethnicity, deprivation, household size and health conditions were modelled using multivariable logistic regression. OUTCOME MEASURE Influenza, pneumococcal and shingles vaccine uptake and refusal (in the unvaccinated). RESULTS This study included 2 054 463 patients from 1318 general practices. 1 711 465 (83.3%) received at least one influenza vaccine, 1 391 228 (67.7%) pneumococcal vaccine and 690 783 (53.4%) shingles vaccine. Compared with White ethnicity, influenza vaccine uptake was lower in Chinese (OR 0.49; 95% CI 0.45 to 0.53), 'Other ethnic' groups (0.63; 95% CI 0.60 to 0.65), black Caribbean (0.68; 95% CI 0.64 to 0.71) and black African (0.72; 95% CI 0.68 to 0.77). There was generally lower vaccination uptake among more deprived individuals, people living in larger household sizes (three or more persons) and those with fewer health conditions. Among those who were unvaccinated, higher odds of refusal were associated with the black Caribbean ethnic group and marginally with increased deprivation, but not associated with higher refusal in those living in large households or those with lesser health conditions. CONCLUSION Certain ethnic minority groups, deprived populations, large households and 'healthier' individuals were less likely to receive a vaccine, although higher refusal was only associated with ethnicity and deprivation but not larger households nor healthier individuals. Understanding these may inform tailored public health messaging to different communities for equitable implementation of vaccination programmes.
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Affiliation(s)
- Pui San Tan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Martina Patone
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Ashley Kieran Clift
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Hajira Dambha-Miller
- Primary Care Research Centre, University of Southampton Faculty of Medicine, Southampton, UK
| | - Defne Saatci
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Tom A Ranger
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Cesar Garriga
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Francesco Zaccardi
- University of Leicester, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Baiju R Shah
- Sunnybrooke Health Sciences Centre, Toronto, Ontario, Canada
| | - Carol Coupland
- Division of Primary Care, University of Nottingham, Nottingham, UK
| | - Simon J Griffin
- The Primary Care Unit, University of Cambridge, Cambridge, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Julia Hippisley-Cox
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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25
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Chudasama YV, Khunti K. Healthy lifestyle choices and microvascular complications: New insights into diabetes management. PLoS Med 2023; 20:e1004152. [PMID: 36626355 PMCID: PMC9831294 DOI: 10.1371/journal.pmed.1004152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Yogini Chudasama and Kamlesh Khunti discuss new evidence, published in PLOS Medicine, highlighting the importance of healthy lifestyle behaviours in diabetes management.
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Affiliation(s)
- Yogini V. Chudasama
- Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, United Kingdom
| | - Kamlesh Khunti
- Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, United Kingdom
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26
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Rousham EK, Goudet S, Markey O, Griffiths P, Boxer B, Carroll C, Petherick ES, Pradeilles R. Unhealthy Food and Beverage Consumption in Children and Risk of Overweight and Obesity: A Systematic Review and Meta-Analysis. Adv Nutr 2022; 13:1669-1696. [PMID: 35362512 PMCID: PMC9526862 DOI: 10.1093/advances/nmac032] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/25/2022] [Accepted: 03/25/2022] [Indexed: 01/28/2023] Open
Abstract
This WHO-commissioned review contributed to the update of complementary feeding recommendations, synthesizing evidence on effects of unhealthy food and beverage consumption in children on overweight and obesity. We searched PubMed (Medline), Cochrane CENTRAL, and Embase for articles, irrespective of language or geography. Inclusion criteria were: 1) randomized controlled trials (RCTs), non-RCTs, cohort studies, and pre/post studies with control; 2) participants aged ≤10.9 y at exposure; 3) studies reporting greater consumption of unhealthy foods/beverages compared with no or low consumption; 4) studies assessing anthropometric and/or body composition; and 5) publication date ≥1971. Unhealthy foods and beverages were defined using nutrient- and food-based approaches. Risk of bias was assessed using the ROBINS-I (risk of bias in nonrandomized studies of interventions version I) and RoB2 [Cochrane RoB (version 2)] tools for nonrandomized and randomized studies, respectively. Narrative synthesis was complemented by meta-analyses where appropriate. Certainty of evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation. Of 26,542 identified citations, 60 studies from 71 articles were included. Most studies were observational (59/60), and no included studies were from low-income countries. The evidence base was low quality, as assessed by ROBINS-I and RoB2 tools. Evidence synthesis was limited by the different interventions and comparators across studies. Evidence indicated that consumption of sugar-sweetened beverages (SSBs) and unhealthy foods in childhood may increase BMI/BMI z-score, percentage body fat, or odds of overweight/obesity (low certainty of evidence). Artificially sweetened beverages and 100% fruit juice consumption make little/no difference to BMI, percentage body fat, or overweight/obesity outcomes (low certainty of evidence). Meta-analyses of a subset of studies indicated a positive association between SSB intake and percentage body fat, but no association with change in BMI and BMI z-score. High-quality epidemiological studies that are designed to assess the effects of unhealthy food consumption during childhood on risk of overweight/obesity are needed to contribute to a more robust evidence base upon which to design policy recommendations. This protocol was registered at https://www.crd.york.ac.uk/PROSPERO as CRD42020218109.
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Affiliation(s)
- E K Rousham
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - S Goudet
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - O Markey
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - P Griffiths
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - B Boxer
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - C Carroll
- School of Health and Related Research, The University of Sheffield, Sheffield, United Kingdom
| | - E S Petherick
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, United Kingdom
| | - R Pradeilles
- Centre for Global Health and Human Development, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
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27
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Gogoi M, Wobi F, Qureshi I, Al-Oraibi A, Hassan O, Chaloner J, Nellums LB, Pareek M. "The vaccination is positive; I don't think it's the panacea": A qualitative study on COVID-19 vaccine attitudes among ethnically diverse healthcare workers in the United Kingdom. PLoS One 2022; 17:e0273687. [PMID: 36084076 PMCID: PMC9462779 DOI: 10.1371/journal.pone.0273687] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 08/12/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Globally, healthcare workers (HCWs) were prioritised for receiving vaccinations against the coronavirus disease-2019 (COVID-19). Previous research has shown disparities in COVID-19 vaccination uptake among HCWs based on ethnicity, job role, sex, age, and deprivation. However, vaccine attitudes underpinning these variations and factors influencing these attitudes are yet to be fully explored. METHODS We conducted a qualitative study with 164 HCWs from different ethnicities, sexes, job roles, migration statuses, and regions in the United Kingdom (UK). Interviews and focus groups were conducted online or telephonically, and recorded with participants' permission. Recordings were transcribed and a two-pronged analytical approach was adopted: content analysis for categorising vaccine attitudes and thematic analysis for identifying factors influencing vaccine attitudes. FINDINGS We identified four different COVID-19 vaccine attitudes among HCWs: Active Acceptance, Passive Acceptance, Passive Decline, and Active Decline. Content analysis of the transcripts showed that HCWs from ethnic minority communities and female HCWs were more likely to either decline (actively/passively) or passively accept vaccination-reflecting hesitancy. Factors influencing these attitudes included: trust; risk perception; social influences; access and equity; considerations about the future. INTERPRETATION Our data show that attitudes towards COVID-19 vaccine are diverse, and elements of hesitancy may persist even after uptake. This has implications for the sustainability of the COVID-19 vaccine programme, particularly as new components (for example boosters) are being offered. We also found that vaccine attitudes differed by ethnicity, sex and job role, which calls for an intersectional and dynamic approach for improving vaccine uptake among HCWs. Trust, risk perception, social influences, access and equity and future considerations all influence vaccine attitudes and have a bearing on HCWs' decision about accepting or declining the COVID-19 vaccine. Based on our findings, we recommend building trust, addressing structural inequities and, designing inclusive and accessible information to address hesitancy.
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Affiliation(s)
- Mayuri Gogoi
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
| | - Fatimah Wobi
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
| | - Irtiza Qureshi
- Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Amani Al-Oraibi
- Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Osama Hassan
- Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Jonathan Chaloner
- Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Laura B. Nellums
- Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Manish Pareek
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
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Gunn S, Henson J, Robertson N, Maltby J, Brady EM, Henderson S, Hadjiconstantinou M, Hall AP, Rowlands AV, Yates T, Davies MJ. Self-compassion, sleep quality and psychological well-being in type 2 diabetes: a cross-sectional study. BMJ Open Diabetes Res Care 2022; 10:10/5/e002927. [PMID: 36171016 PMCID: PMC9528571 DOI: 10.1136/bmjdrc-2022-002927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 09/04/2022] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION Low self-compassion and poor sleep quality have been identified as potential key predictors of distress in type 2 diabetes (T2D). This study investigated relationships between sleep behaviors (sleep duration, social jetlag and daytime sleepiness), diabetes-related distress (DRD) and self-compassion in people with T2D. RESEARCH DESIGN AND METHODS This cross-sectional study used data from 467 people with T2D derived from self-report questionnaires, accelerometer-assessed sleep measures and demographic information (clinicaltrials.gov registration: NCT02973412). All participants had a diagnosis of T2D and no comorbid sleep disorder (excluding obstructive sleep apnea). Hierarchical multiple regression and mediation analysis were used to quantify relationships between self-compassion, sleep variables and DRD. RESULTS Significant predictors of DRD included two negative subscales of the Self-Compassion Scale (SCS), and daytime sleepiness. The 'overidentified' and 'isolation' SCS subscales were particularly important in predicting distress. Daytime sleepiness also partially mediated the influence of self-compassion on DRD, potentially through self-care around sleep. CONCLUSIONS Daytime sleepiness and negative self-compassion have clear associations with DRD for people with T2D. The specific negative subscale outcomes suggest that strengthening individuals' ability to mindfully notice thoughts and experiences without becoming enmeshed in them, and reducing a sense of separateness and difference, might be key therapeutic targets for improving well-being in T2D. Psychological interventions should include approaches focused on reducing negative self-compassion and improving sleep behavior. Equally, reducing DRD may carry beneficial outcomes for sleep and self-compassion. Further work is however crucial to establish causation and long-term impact, and for development of relevant clinical resources.
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Affiliation(s)
- Sarah Gunn
- Psychology and Vision Sciences, University of Leicester, Leicester, UK
| | - Joseph Henson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Noelle Robertson
- Psychology and Vision Sciences, University of Leicester, Leicester, UK
| | - John Maltby
- Psychology and Vision Sciences, University of Leicester, Leicester, UK
| | - Emer M Brady
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Sarah Henderson
- Psychology and Vision Sciences, University of Leicester, Leicester, UK
| | | | - Andrew P Hall
- Hanning Sleep Laboratory, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Alex V Rowlands
- NIHR Leicester Biomedical Research Centre and Diabetes Research Centre, University of Leicester, Leicester, UK
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, University of South Australia Division of Health Sciences, Adelaide, South Australia, Australia
| | - Thomas Yates
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
| | - Melanie J Davies
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
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Martin CA, Pan D, Nazareth J, Aujayeb A, Bryant L, Carr S, Gray LJ, Gregary B, Gupta A, Guyatt AL, Gopal A, Hine T, John C, McManus IC, Melbourne C, Nellums LB, Reza R, Simpson S, Tobin MD, Woolf K, Zingwe S, Khunti K, Pareek M. Access to personal protective equipment in healthcare workers during the COVID-19 pandemic in the United Kingdom: results from a nationwide cohort study (UK-REACH). BMC Health Serv Res 2022; 22:867. [PMID: 35790970 PMCID: PMC9255515 DOI: 10.1186/s12913-022-08202-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 06/15/2022] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Healthcare workers (HCWs) are at high risk of SARS-CoV-2 infection. Effective use of personal protective equipment (PPE) reduces this risk. We sought to determine the prevalence and predictors of self-reported access to appropriate PPE (aPPE) for HCWs in the UK during the COVID-19 pandemic. METHODS We conducted cross sectional analyses using data from a nationwide questionnaire-based cohort study administered between December 2020-February 2021. The outcome was a binary measure of self-reported aPPE (access all of the time vs access most of the time or less frequently) at two timepoints: the first national lockdown in the UK in March 2020 (primary analysis) and at the time of questionnaire response (secondary analysis). RESULTS Ten thousand five hundred eight HCWs were included in the primary analysis, and 12,252 in the secondary analysis. 35.2% of HCWs reported aPPE at all times in the primary analysis; 83.9% reported aPPE at all times in the secondary analysis. In the primary analysis, after adjustment (for age, sex, ethnicity, migration status, occupation, aerosol generating procedure exposure, work sector and region, working hours, night shift frequency and trust in employing organisation), older HCWs and those working in Intensive Care Units were more likely to report aPPE at all times. Asian HCWs (aOR:0.77, 95%CI 0.67-0.89 [vs White]), those in allied health professional and dental roles (vs those in medical roles), and those who saw a higher number of COVID-19 patients compared to those who saw none (≥ 21 patients/week 0.74, 0.61-0.90) were less likely to report aPPE at all times. Those who trusted their employing organisation to deal with concerns about unsafe clinical practice, compared to those who did not, were twice as likely to report aPPE at all times. Significant predictors were largely unchanged in the secondary analysis. CONCLUSIONS Only a third of HCWs in the UK reported aPPE at all times during the first lockdown and that aPPE had improved later in the pandemic. We also identified key determinants of aPPE during the first UK lockdown, which have mostly persisted since lockdown was eased. These findings have important implications for the safe delivery of healthcare during the pandemic.
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Affiliation(s)
- Christopher A Martin
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Daniel Pan
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Joshua Nazareth
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Avinash Aujayeb
- Respiratory Department, Northumbria Specialist Emergency Care Hospital, Cramlington, UK
| | - Luke Bryant
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - Sue Carr
- University Hospitals Leicester NHS Trust, Leicester Royal Infirmary, Leicester, UK
- General Medical Council, London, UK
| | - Laura J Gray
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Bindu Gregary
- Lancashire Clinical Research Facility, Royal Preston Hospital, Fulwood, UK
| | - Amit Gupta
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Anna L Guyatt
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Alan Gopal
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| | - Thomas Hine
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Catherine John
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Carl Melbourne
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Laura B Nellums
- Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Rubina Reza
- Centre for Research & Development, Derbyshire Healthcare NHS Foundation Trust, Derby, UK
| | - Sandra Simpson
- Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Stephen Zingwe
- Research and Development Department, Berkshire Healthcare NHS Foundation Trust, Bracknell, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Manish Pareek
- Department of Respiratory Sciences, University of Leicester, Leicester, UK.
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, UK.
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30
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Martin CA, Pan D, Melbourne C, Teece L, Aujayeb A, Baggaley RF, Bryant L, Carr S, Gregary B, Gupta A, Guyatt AL, John C, McManus IC, Nazareth J, Nellums LB, Reza R, Simpson S, Tobin MD, Woolf K, Zingwe S, Khunti K, Abrams KR, Gray LJ, Pareek M. Risk factors associated with SARS-CoV-2 infection in a multiethnic cohort of United Kingdom healthcare workers (UK-REACH): A cross-sectional analysis. PLoS Med 2022; 19:e1004015. [PMID: 35617423 PMCID: PMC9187071 DOI: 10.1371/journal.pmed.1004015] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 06/10/2022] [Accepted: 05/09/2022] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Healthcare workers (HCWs), particularly those from ethnic minority groups, have been shown to be at disproportionately higher risk of infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) compared to the general population. However, there is insufficient evidence on how demographic and occupational factors influence infection risk among ethnic minority HCWs. METHODS AND FINDINGS We conducted a cross-sectional analysis using data from the baseline questionnaire of the United Kingdom Research study into Ethnicity and Coronavirus Disease 2019 (COVID-19) Outcomes in Healthcare workers (UK-REACH) cohort study, administered between December 2020 and March 2021. We used logistic regression to examine associations of demographic, household, and occupational risk factors with SARS-CoV-2 infection (defined by polymerase chain reaction (PCR), serology, or suspected COVID-19) in a diverse group of HCWs. The primary exposure of interest was self-reported ethnicity. Among 10,772 HCWs who worked during the first UK national lockdown in March 2020, the median age was 45 (interquartile range [IQR] 35 to 54), 75.1% were female and 29.6% were from ethnic minority groups. A total of 2,496 (23.2%) reported previous SARS-CoV-2 infection. The fully adjusted model contained the following dependent variables: demographic factors (age, sex, ethnicity, migration status, deprivation, religiosity), household factors (living with key workers, shared spaces in accommodation, number of people in household), health factors (presence/absence of diabetes or immunosuppression, smoking history, shielding status, SARS-CoV-2 vaccination status), the extent of social mixing outside of the household, and occupational factors (job role, the area in which a participant worked, use of public transport to work, exposure to confirmed suspected COVID-19 patients, personal protective equipment [PPE] access, aerosol generating procedure exposure, night shift pattern, and the UK region of workplace). After adjustment, demographic and household factors associated with increased odds of infection included younger age, living with other key workers, and higher religiosity. Important occupational risk factors associated with increased odds of infection included attending to a higher number of COVID-19 positive patients (aOR 2.59, 95% CI 2.11 to 3.18 for ≥21 patients per week versus none), working in a nursing or midwifery role (1.30, 1.11 to 1.53, compared to doctors), reporting a lack of access to PPE (1.29, 1.17 to 1.43), and working in an ambulance (2.00, 1.56 to 2.58) or hospital inpatient setting (1.55, 1.38 to 1.75). Those who worked in intensive care units were less likely to have been infected (0.76, 0.64 to 0.92) than those who did not. Black HCWs were more likely to have been infected than their White colleagues, an effect which attenuated after adjustment for other known risk factors. This study is limited by self-selection bias and the cross sectional nature of the study means we cannot infer the direction of causality. CONCLUSIONS We identified key sociodemographic and occupational risk factors associated with SARS-CoV-2 infection among UK HCWs, and have determined factors that might contribute to a disproportionate odds of infection in HCWs from Black ethnic groups. These findings demonstrate the importance of social and occupational factors in driving ethnic disparities in COVID-19 outcomes, and should inform policies, including targeted vaccination strategies and risk assessments aimed at protecting HCWs in future waves of the COVID-19 pandemic. TRIAL REGISTRATION The study was prospectively registered at ISRCTN (reference number: ISRCTN11811602).
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Affiliation(s)
- Christopher A. Martin
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
| | - Daniel Pan
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
| | - Carl Melbourne
- Genetic Epidemiology Research Group, Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Lucy Teece
- Biostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Avinash Aujayeb
- Respiratory Department, Northumbria Specialist Emergency Care Hospital, United Kingdom
| | - Rebecca F. Baggaley
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
| | - Luke Bryant
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
| | - Sue Carr
- Department of Nephrology, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
- General Medical Council, London, United Kingdom
| | - Bindu Gregary
- Lancashire Clinical Research Facility, Royal Preston Hospital, United Kingdom
| | - Amit Gupta
- Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Anna L. Guyatt
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Catherine John
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - I Chris McManus
- University College London Medical School, London, United Kingdom
| | - Joshua Nazareth
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
| | - Laura B. Nellums
- Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Rubina Reza
- Centre for Research & Development, Derbyshire Healthcare NHS Foundation Trust, Derby, United Kingdom
| | - Sandra Simpson
- Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom
| | - Martin D. Tobin
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Katherine Woolf
- University College London Medical School, London, United Kingdom
| | - Stephen Zingwe
- Research and Development Department, Berkshire Healthcare NHS Foundation Trust, Bracknell, United Kingdom
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, United Kingdom
| | - Keith R. Abrams
- Department of Statistics, University of Warwick, United Kingdom
| | - Laura J. Gray
- Biostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Manish Pareek
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
- Department of Infection and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
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31
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Nakao T, Bick AG, Taub MA, Zekavat SM, Uddin MM, Niroula A, Carty CL, Lane J, Honigberg MC, Weinstock JS, Pampana A, Gibson CJ, Griffin GK, Clarke SL, Bhattacharya R, Assimes TL, Emery LS, Stilp AM, Wong Q, Broome J, Laurie CA, Khan AT, Smith AV, Blackwell TW, Codd V, Nelson CP, Yoneda ZT, Peralta JM, Bowden DW, Irvin MR, Boorgula M, Zhao W, Yanek LR, Wiggins KL, Hixson JE, Gu CC, Peloso GM, Roden DM, Reupena MS, Hwu CM, DeMeo DL, North KE, Kelly S, Musani SK, Bis JC, Lloyd-Jones DM, Johnsen JM, Preuss M, Tracy RP, Peyser PA, Qiao D, Desai P, Curran JE, Freedman BI, Tiwari HK, Chavan S, Smith JA, Smith NL, Kelly TN, Hidalgo B, Cupples LA, Weeks DE, Hawley NL, Minster RL, Deka R, Naseri TT, de las Fuentes L, Raffield LM, Morrison AC, Vries PS, Ballantyne CM, Kenny EE, Rich SS, Whitsel EA, Cho MH, Shoemaker MB, Pace BS, Blangero J, Palmer ND, Mitchell BD, Shuldiner AR, Barnes KC, Redline S, Kardia SL, Abecasis GR, Becker LC, Heckbert SR, He J, Post W, Arnett DK, Vasan RS, Darbar D, Weiss ST, McGarvey ST, de Andrade M, Chen YDI, Kaplan RC, Meyers DA, Custer BS, Correa A, Psaty BM, Fornage M, Manson JE, Boerwinkle E, Konkle BA, Loos RJ, Rotter JI, Silverman EK, Kooperberg C, Danesh J, Samani NJ, Jaiswal S, Libby P, Ellinor PT, Pankratz N, Ebert BL, Reiner AP, Mathias RA, Do R, Natarajan P. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential. Sci Adv 2022; 8:eabl6579. [PMID: 35385311 PMCID: PMC8986098 DOI: 10.1126/sciadv.abl6579] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 02/16/2022] [Indexed: 05/24/2023]
Abstract
Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.
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Affiliation(s)
- Tetsushi Nakao
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Alexander G. Bick
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Margaret A. Taub
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Md M. Uddin
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Abhishek Niroula
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - Cara L. Carty
- Initiative for Research and Education to Advance Community Health, Washington State University, Seattle, WA, USA
| | - John Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Michael C. Honigberg
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Joshua S. Weinstock
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Akhil Pampana
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | - Gabriel K. Griffin
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Shoa L. Clarke
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Romit Bhattacharya
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Themistocles L. Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Leslie S. Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jai Broome
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Cecelia A. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Alyna T. Khan
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Albert V. Smith
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Thomas W. Blackwell
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Zachary T. Yoneda
- Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Juan M. Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Marguerite R. Irvin
- Department of Biostatistics, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Meher Boorgula
- Division of Biomedical Informatics and Personalized Medicine and the Colorado Center for Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kerri L. Wiggins
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - James E. Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - C. Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Dan M. Roden
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Shannon Kelly
- Vitalant Research Institute, San Francisco, CA, USA
- UCSF, Benioff Children’s Hospital Oakland, Oakland, CA, USA
| | - Solomon K. Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Donald M. Lloyd-Jones
- Division of Cardiology Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Pathology and Biochemistry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Pinkal Desai
- Division of Hematology and Oncology, Weill Cornell Medical College, New York, NY, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Barry I. Freedman
- Internal Medicine–Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Hemant K. Tiwari
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Sameer Chavan
- Division of Biomedical Informatics and Personalized Medicine and the Colorado Center for Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
| | - Tanika N. Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- National Heart Lung and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
| | - Daniel E. Weeks
- Department of Human Genetics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicola L. Hawley
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT, USA
| | - Ryan L. Minster
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - The Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Yale University School of Medicine, New Haven, CT, USA
- Department of Laboratory Medicine, Lund University, Lund, Sweden
- Initiative for Research and Education to Advance Community Health, Washington State University, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biostatistics, School of Public Health, University of Alabama, Birmingham, AL, USA
- Division of Biomedical Informatics and Personalized Medicine and the Colorado Center for Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Ministry of Health, Government of Samoa, Apia, Samoa
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Vitalant Research Institute, San Francisco, CA, USA
- UCSF, Benioff Children’s Hospital Oakland, Oakland, CA, USA
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Cardiology Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Pathology and Biochemistry, University of Vermont College of Medicine, Burlington, VT, USA
- Division of Hematology and Oncology, Weill Cornell Medical College, New York, NY, USA
- Internal Medicine–Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
- National Heart Lung and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- Department of Human Genetics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Department of Health, American Samoa Government, Pago Pago, American Samoa, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Augusta University, Augusta, GA, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
- Dean’s Office, College of Public Health, University of Kentucky, Lexington, KY, USA
- Departments of Cardiology and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Division of Cardiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Epidemiology and International Health Institute, Brown University School of Public Health, Providence, RI, USA
- Mayo Clinic, Department of Health Sciences Research, Rochester, MN, USA
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
- Division of Genetics, Genomics and Precision Medicine, University of Arizona, Tucson, AZ, USA
- Departments of Medicine and Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Bloodworks Northwest, Seattle, WA, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Department of Pathology, Stanford University, Stanford, CA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Howard Hughes Medical Institute, Boston, MA, USA
- Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ranjan Deka
- Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Take T. Naseri
- Department of Health, American Samoa Government, Pago Pago, American Samoa, USA
| | - Lisa de las Fuentes
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Paul S. Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Eimear E. Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Michael H. Cho
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | | | - Betty S. Pace
- Division of Hematology/Oncology, Department of Pediatrics, Augusta University, Augusta, GA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kathleen C. Barnes
- Division of Biomedical Informatics and Personalized Medicine and the Colorado Center for Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO, USA
| | - Susan Redline
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Gonçalo R. Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Lewis C. Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
| | - Wendy Post
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - Donna K. Arnett
- Dean’s Office, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Ramachandran S. Vasan
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- National Heart Lung and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- Departments of Cardiology and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Dawood Darbar
- Division of Cardiology, University of Illinois at Chicago, Chicago, IL, USA
| | - Scott T. Weiss
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Stephen T. McGarvey
- Department of Epidemiology and International Health Institute, Brown University School of Public Health, Providence, RI, USA
| | - Mariza de Andrade
- Mayo Clinic, Department of Health Sciences Research, Rochester, MN, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
| | - Deborah A. Meyers
- Division of Genetics, Genomics and Precision Medicine, University of Arizona, Tucson, AZ, USA
| | | | - Adolfo Correa
- Departments of Medicine and Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - JoAnn E. Manson
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric Boerwinkle
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Barbara A. Konkle
- Department of Medicine, University of Washington, Seattle, WA, USA
- Bloodworks Northwest, Seattle, WA, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | | | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | | | - Peter Libby
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Patrick T. Ellinor
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Benjamin L. Ebert
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Howard Hughes Medical Institute, Boston, MA, USA
| | | | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Yale University School of Medicine, New Haven, CT, USA
- Department of Laboratory Medicine, Lund University, Lund, Sweden
- Initiative for Research and Education to Advance Community Health, Washington State University, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biostatistics, School of Public Health, University of Alabama, Birmingham, AL, USA
- Division of Biomedical Informatics and Personalized Medicine and the Colorado Center for Personalized Medicine, School of Medicine, University of Colorado, Aurora, CO, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Ministry of Health, Government of Samoa, Apia, Samoa
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Vitalant Research Institute, San Francisco, CA, USA
- UCSF, Benioff Children’s Hospital Oakland, Oakland, CA, USA
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Cardiology Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Pathology and Biochemistry, University of Vermont College of Medicine, Burlington, VT, USA
- Division of Hematology and Oncology, Weill Cornell Medical College, New York, NY, USA
- Internal Medicine–Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Tulane University Translational Science Institute, New Orleans, LA, USA
- National Heart Lung and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- Department of Human Genetics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA
- Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Department of Health, American Samoa Government, Pago Pago, American Samoa, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Augusta University, Augusta, GA, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
- Dean’s Office, College of Public Health, University of Kentucky, Lexington, KY, USA
- Departments of Cardiology and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Division of Cardiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Epidemiology and International Health Institute, Brown University School of Public Health, Providence, RI, USA
- Mayo Clinic, Department of Health Sciences Research, Rochester, MN, USA
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
- Division of Genetics, Genomics and Precision Medicine, University of Arizona, Tucson, AZ, USA
- Departments of Medicine and Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Bloodworks Northwest, Seattle, WA, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Department of Pathology, Stanford University, Stanford, CA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Howard Hughes Medical Institute, Boston, MA, USA
- Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pradeep Natarajan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
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Alzahrani A, Hakeem J, Biddle M, Alhadian F, Hussain A, Khalfaoui L, Roach KM, Tliba O, Bradding P, Amrani Y. Human Lung Mast Cells Impair Corticosteroid Responsiveness in Human Airway Smooth Muscle Cells. Front Allergy 2021; 2:785100. [PMID: 35387008 PMCID: PMC8974721 DOI: 10.3389/falgy.2021.785100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/24/2021] [Indexed: 11/13/2022] Open
Abstract
The mechanisms underlying corticosteroid insensitivity in severe asthma have not been elucidated although some indirect clinical evidence points toward a role of mast cells. Here, we tested the hypothesis that mast cells can drive corticosteroid insensitivity in airway smooth muscle cells, a key player in asthma pathogenesis. Conditioned media from resting or FcεR1-activated human lung mast cells were incubated with serum-deprived ASM cells (1:4 dilution, 24 h) to determine their impact on the anti-inflammatory action of fluticasone on ASM cell chemokine expression induced by TNFα (10 ng/ml). Conditioned media from FcεR1-activated mast cells (but not that from non-activated mast cells or control media) significantly reduced the ability of 100 nM fluticasone to suppress ASM TNFα-dependent CCL5 and CXCL10 production at both mRNA and protein levels. In contrast, fluticasone inhibition of CXCL-8 production by TNFα was still preserved in the presence of activated mast cell conditioned media. Transcriptomic analysis validated by individual qPCR assays revealed that activated mast cell conditioned media dramatically reduced the number of anti-inflammatory genes induced by fluticasone in ASM cells. Our study demonstrates for the first time that conditioned media from FcεR1-activated mast cells blunt the anti-inflammatory action of corticosteroids in ASM cells by altering their transactivation properties. Because infiltration of mast cells within the ASM bundles is a defining feature of asthma, mast cell-derived mediators may contribute to the glucocorticoid insensitivity present in severe asthma.
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Affiliation(s)
- Abdulrahman Alzahrani
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
- Department of Applied Medical Sciences, Applied College, Albaha University, Albaha, Saudi Arabia
| | - Jameel Hakeem
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Michael Biddle
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Fahad Alhadian
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Aamir Hussain
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Latifa Khalfaoui
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Katy M. Roach
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Omar Tliba
- Department of Biomedical Sciences, College of Veterinary Medicine, Long Island University, Brookville, NY, United States
| | - Peter Bradding
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
| | - Yassine Amrani
- Department of Respiratory Sciences, Clinical Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
- *Correspondence: Yassine Amrani
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Walters GWM, Redman E, Gulsin GS, Henson J, Argyridou S, Yates T, Davies MJ, Parke K, McCann GP, Brady EM. Interrelationship between micronutrients and cardiovascular structure and function in type 2 diabetes. J Nutr Sci 2021; 10:e88. [PMID: 34733500 PMCID: PMC8532075 DOI: 10.1017/jns.2021.82] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 09/08/2021] [Indexed: 11/30/2022] Open
Abstract
Micronutrients are important for normal cardiovascular function. They may play a role in the increased risk of cardiovascular disease observed in people with type 2 diabetes (T2D) and T2D-related heart failure. The aims of this study were to (1) examine micronutrient status in people with T2D v. healthy controls; (2) assess any changes following a nutritionally complete meal replacement plan (MRP) compared with routine care; (3) determine if any changes were associated with changes in cardiovascular structure/function. This was a secondary analysis of data from a prospective, randomised, open-label, blinded end-point trial of people with T2D, with a nested case-control [NCT02590822]. Anthropometrics, cardiac resonance imaging and fasting blood samples (to quantify vitamins B1, B6, B12, D and C; and iron and ferritin) were collected at baseline and 12 weeks following the MRP or routine care. Comparative data in healthy controls were collected at baseline. A total of eighty-three people with T2D and thirty-six healthy controls were compared at baseline; all had micronutrient status within reference ranges. Vitamin B1 was higher (148⋅9 v. 131⋅7; P 0⋅01) and B6 lower (37⋅3 v. 52⋅9; P 0⋅01) in T2D v. controls. All thirty participants randomised to routine care and twenty-four to the MRP completed the study. There was an increase in vitamins B1, B6, D and C following the MRP, which were not associated with changes in cardiovascular structure/function. In conclusion, changes in micronutrient status following the MRP were not independently associated with improvements in cardiovascular structure/function in people with T2D.
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Key Words
- BMI, body mass index
- CMR
- CMR, cardiac magnetic resonance imaging
- CVD, cardiovascular disease
- Cardiovascular function
- EF, ejection fraction
- HF, heart failure
- LV, left ventricular
- Low calorie
- Low-energy meal replacement plan
- MRP, meal replacement plan
- Micronutrients
- PLP, pyridoxal 5-phosphate
- RCT, randomised control trial
- T2D, type 2 diabetes
- Type 2 diabetes
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Affiliation(s)
- Grace W. M. Walters
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
| | - Emma Redman
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Gaurav S. Gulsin
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
| | - Joseph Henson
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | | | - Thomas Yates
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Melanie J. Davies
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Kelly Parke
- University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Gerry P. McCann
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
| | - Emer M. Brady
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Leicester, UK
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Coles B, Zaccardi F, Ling S, Davies MJ, Samani NJ, Khunti K. Cardiovascular events and mortality in people with and without type 2 diabetes: An observational study in a contemporary multi-ethnic population. J Diabetes Investig 2021; 12:1175-1182. [PMID: 33206469 PMCID: PMC8264396 DOI: 10.1111/jdi.13464] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 11/06/2020] [Accepted: 11/13/2020] [Indexed: 12/24/2022] Open
Abstract
AIMS/INTRODUCTION The aim of this study was to examine ethnicity-specific associations between type 2 diabetes mellitus and the risk of a cardiovascular disease (CVD) event as well as risk of specific CVD phenotypes in England. METHODS We obtained data from the Clinical Practice Research Datalink for adults with and without type 2 diabetes mellitus diagnosed 2000-2006. The outcome was the first CVD event during 2007-2017 and the following components: aortic aneurysm, cerebrovascular accidents, heart failure, myocardial infarction, peripheral vascular disease and other CVD-related conditions. Flexible parametric survival models were used to estimate ethnicity-specific adjusted hazard ratios. RESULTS A total of 734,543 people with and without type 2 diabetes mellitus (29,847; 4.1%) were included; most were of white ethnicity (93.0% with and 92.3% without type 2 diabetes mellitus) followed by South Asian (3.2 and 4.6%). During a median follow-up period of 11.0 years, 67,218 events occurred (6,156 in individuals with type 2 diabetes mellitus). Type 2 diabetes mellitus was associated with a small increase in CVD events (adjusted hazard ratio 1.06, 95% confidence interval 1.02-1.09) in individuals of white ethnicity; whereas the adjusted hazard ratios were considerably higher in individuals of South Asian ethnicity (1.28, 95% confidence interval 1.09-1.51), primarily due to an increased risk of myocardial infarction (1.53, 95% confidence interval 1.08-2.18). CONCLUSIONS Despite universal access to healthcare, there are large disparities in CVD outcomes in people with and without type 2 diabetes mellitus. Other non-traditional risk factors might play a role in the higher CVD risk associated with type 2 diabetes mellitus in individuals of South Asian ethnicity.
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Affiliation(s)
- Briana Coles
- Leicester Real World Evidence UnitDiabetes Research CenterUniversity of LeicesterLeicesterUK
| | - Francesco Zaccardi
- Leicester Real World Evidence UnitDiabetes Research CenterUniversity of LeicesterLeicesterUK
| | - Suping Ling
- Leicester Real World Evidence UnitDiabetes Research CenterUniversity of LeicesterLeicesterUK
| | - Melanie J Davies
- National Institute for Health Research Leicester Biomedical Research CenterLeicester Diabetes CentreLeicesterUK
| | - Nilesh J Samani
- Department of Cardiovascular SciencesNIHR Leicester Biomedical Research CenterUniversity of LeicesterLeicesterUK
| | - Kamlesh Khunti
- National Institute for Health Research Applied Research Collaboration ‐ East MidlandsLeicester Diabetes CenterLeicesterUK
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35
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Brady EM, Hall AP, Baldry E, Chatterjee S, Daniels LJ, Edwardson C, Khunti K, Patel MI, Henson JJ, Rowlands A, Smith AC, Yates T, Davies MJ. Rationale and design of a cross-sectional study to investigate and describe the chronotype of patients with type 2 diabetes and the effect on glycaemic control: the CODEC study. BMJ Open 2019; 9:e027773. [PMID: 31719069 PMCID: PMC6858123 DOI: 10.1136/bmjopen-2018-027773] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
INTRODUCTION A person's chronotype is their entrained preference for sleep time within the 24 hours clock. It is described by the well-known concept of the 'lark' (early riser) and 'owl' (late sleeper). Evidence suggests that the 'owl' is metabolically disadvantaged due to the standard organisation of our society which favours the 'lark' and places physiological stresses on this chronotype. The aim of this study is to explore cardiometabolic health between the lark and owl in a population with an established metabolic condition - type 2 diabetes. METHODS This cross-sectional, multisite study aims to recruit 2247 participants from both secondary and primary care settings. The primary objective is to compare glycaemic control between late and early chronotypes. Secondary objectives include determining if late-chronotype is associated with poorer cardiometabolic health and other lifestyle factors, including well-being, compared with early-chronotype; describing the prevalence of the five different chronotypes in this cohort and examining the trends in glycaemic control, cardiometabolic health, well-being and lifestyle factors across chronotype. ANALYSIS The primary outcome (glycated haemoglobin (HbA1c)), linear regression analysis will compare HbA1c between early and late chronotypes, with and without adjustment for confounding variables. Chronotype will be modelled as a categorical variable with all five levels (from extreme-morning to extreme-late type), and as a continuous variable to calculate p for trend across the five categories. A number of models will be created; unadjusted through to adjusted with age, sex, ethnicity, body mass index, duration of diabetes, family history of diabetes, current medication and dietary habits. All secondary outcomes will be analysed using the same method. ETHICS Ethical approval from the West Midlands - Black Country Research Ethics Committee (16/WM/0457). DISSEMINATION The results will be disseminated through publication in peer-reviewed medical journal, relevant medical/health conferences and a summary report sent to patients. TRIAL REGISTRATION NUMBER NCT02973412 (Pre-Results).
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Affiliation(s)
- Emer M Brady
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Andrew P Hall
- The Hanning Sleep Laboratory, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Emma Baldry
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | | | - Lois J Daniels
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | | | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Mubarak I Patel
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Joseph J Henson
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Alex Rowlands
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Alice C Smith
- John Walls Renal Unit, University Hospitals of Leicester NHS Trust, UK and Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK
| | - Thomas Yates
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester, UK
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Bell JA, Hamer M, Richmond RC, Timpson NJ, Carslake D, Davey Smith G. Associations of device-measured physical activity across adolescence with metabolic traits: Prospective cohort study. PLoS Med 2018; 15:e1002649. [PMID: 30204755 PMCID: PMC6133272 DOI: 10.1371/journal.pmed.1002649] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 08/03/2018] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Multiple occasions of device-measured physical activity have not been previously examined in relation to metabolic traits. We described associations of total activity, moderate-to-vigorous physical activity (MVPA), and sedentary time from three accelerometry measures taken across adolescence with detailed traits related to systemic metabolism. METHODS AND FINDINGS There were 1,826 male and female participants recruited at birth in 1991-1992 via mothers into the Avon Longitudinal Study of Parents and Children offspring cohort who attended clinics in 2003-2005, 2005-2006, and 2006-2008 who were included in ≥1 analysis. Waist-worn uniaxial accelerometers measured total activity (counts/min), MVPA (min/d), and sedentary time (min/d) over ≥3 d at mean age 12y, 14y, and 15y. Current activity (at age 15y), mean activity across occasions, interaction by previous activity, and change in activity were examined in relation to systolic and diastolic blood pressure, insulin, C-reactive protein, and 230 traits from targeted metabolomics (nuclear magnetic resonance spectroscopy), including lipoprotein cholesterol and triglycerides, amino and fatty acids, glycoprotein acetyls, and others, at age 15y. Mean current total activity was 477.5 counts/min (SD = 164.0) while mean MVPA and sedentary time durations were 23.6 min/d (SD = 17.9) and 522.1 min/d (SD = 66.0), respectively. Mean body mass index at age 15y was 21.4 kg/m2 (SD = 3.5). Correlations between first and last activity measurement occasions were low (e.g., r = 0.40 for counts/min). Current activity was most strongly associated with cholesterol and triglycerides in high-density lipoprotein (HDL) and very low-density lipoprotein (VLDL) particles (e.g., -0.002 mmol/l or -0.18 SD units; 95% CI -0.24--0.11 for triglycerides in chylomicrons and extremely large very low-density lipoprotein [XL VLDL]) and with glycoprotein acetyls (-0.02 mmol/l or -0.16 SD units; 95% CI -0.22--0.10), among others. Associations were similar for mean activity across 3 occasions. Attenuations were modest with adjustment for fat mass index based on dual-energy X-ray absorptiometry (DXA). In mutually adjusted models, higher MVPA and sedentary time were oppositely associated with cholesterol and triglycerides in VLDL and HDL particles (MVPA more strongly with glycoprotein acetyls and sedentary time more strongly with amino acids). Associations appeared less consistent for sedentary time than for MVPA based on longer-term measures and were weak for change in all activity types from age 12y-15y. Evidence was also weak for interaction between activity types at age 15y and previous activity measures in relation to most traits (minimum P = 0.003; median P = 0.26 for counts/min) with interaction coefficients mostly positive. Study limitations include modest sample sizes and relatively short durations of accelerometry measurement on each occasion (3-7 d) and of time lengths between first and last accelerometry occasions (<4 years), which can obscure patterns from chance variation and limit description of activity trajectories. Activity was also recorded using uniaxial accelerometers which predated more sensitive triaxial devices. CONCLUSIONS Our results support associations of physical activity with metabolic traits that are small in magnitude and more robust for higher MVPA than lower sedentary time. Activity fluctuates over time, but associations of current activity with most metabolic traits do not differ by previous activity. This suggests that the metabolic effects of physical activity, if causal, depend on most recent engagement.
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Affiliation(s)
- Joshua A. Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Mark Hamer
- School of Sport, Exercise & Health Sciences, Loughborough University, Leicestershire, United Kingdom
| | - Rebecca C. Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - David Carslake
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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