Search

Aims: We aimed to determine the association between serum interleukin‐6 (IL‐6) concentrations and new‐onset heart failure (HF) in persons with type 2 diabetes (T2D). Methods and results: We performed a case–control study nested in the Diabetes Care System Cohort, a prospective cohort of persons with T2D in primary care. We included 724 participants, of whom 141 developed HF during 5 years of follow‐up and 583 were age‐ and sex‐matched controls. IL‐6 was measured at baseline and categorized into four groups: Group 1 was composed of participants with IL‐6 below the detection limit of 1.5 pg/mL, and the remainder were divided into tertiles. We performed logistic regression analyses with categorized IL‐6 or continuous IL‐6 as the determinant and new‐onset HF as the outcome adjusted for follow‐up time, age, sex, glycated haemoglobin, estimated glomerular filtration rate, albumin/creatinine ratio, and cardiovascular disease at baseline. Effect modification by sex was tested. Participants were 70.7 ± 9.0 years, and 38% were women. In comparison with Group 1, all tertiles were associated with an increased risk of HF with odds ratios of 2.1 [95% confidence interval (CI): 1.2–2.9], 2.8 (95% CI: 2.0–3.7), and 2.1 (95% CI: 1.3–3.0), respectively, for Tertiles 1–3. Continuous IL‐6 was associated with the development of HF with an odds ratio of 1.2 (95% CI: 1.0–1.5). No effect modification by sex was observed. Conclusions: Higher IL‐6 levels are associated with the development of HF in persons with T2D. Further research should determine whether IL‐6‐lowering interventions could prevent the development of HF. [ABSTRACT FROM AUTHOR]

Summary: This study aims to determine the association between social jetlag and parameters of metabolic syndrome and type 2 diabetes (T2D) in a systematic review and meta‐analysis. A systematic literature search was conducted in PubMed/Embase/Scopus until May 2022. Included studies described an association between social jetlag and parameters of the metabolic syndrome and/or T2D, were available full text and written in English or Dutch. Data extraction and quality assessment were performed on pre‐piloted forms independently by two reviewers. Results were meta‐analysed using random‐effects analysis. A total of 6,290 titles/abstracts were screened, 176 papers were read full‐text, 68 studies were included. Three studies were rated as low quality, 27 were moderate, and 38 were high quality. High quality studies showed that having social jetlag compared to no social jetlag was significantly associated with higher body mass index in 20 studies (0.49 kg/m2, 95% confidence interval [CI] 0.21–0.77; I2 = 100%), higher waist circumference in seven studies (1.11 cm, 95% CI 0.42–1.80; I2 = 25%), higher systolic blood pressure in 10 studies (0.37 mmHg, 95% CI 0.00–0.74; I2 = 94%) and higher glycated haemoglobin in 12 studies (0.42%, 95% CI 0.12– 0.72; I2 = 100%). No statistically significant associations were found for obesity, abdominal obesity, high‐ and low‐density lipoprotein levels, cholesterol, triglycerides, diastolic blood pressure, hypertension, fasting glucose, homeostatic model assessment for insulin resistance, metabolic syndrome or T2D. Sensitivity analyses did not reduce heterogeneity. Despite substantial heterogeneity, social jetlag is associated with certain parameters of the metabolic syndrome and T2D, but not with prevalent metabolic syndrome or T2D. These findings should be interpreted with caution as the level of evidence is low and mostly based on cross‐sectional data. Longitudinal studies are needed to further assess the direction of causality. [ABSTRACT FROM AUTHOR]

Objective: Social jet lag, i.e., the discordance among social and biological rhythms, is associated with poor metabolic control. This study aimed to assess cross‐sectional and longitudinal associations among social jet lag and glycemic and metabolic control in people with type 2 diabetes. Methods: In a prospective cohort (N = 990) with type 2 diabetes, social jet lag was measured at baseline using daily diaries and was categorized (high, moderate, or low). Metabolic outcomes were assessed at baseline and at 1 and 2 years of follow‐up. Associations among social jet lag and glycemic and metabolic control were analyzed using linear regression and linear mixed models adjusted for confounding factors. Analyses were stratified for work status (retired vs. working; p value for interaction = 0.007 for glycated hemoglobin [HbA1c]). Results: In working people, a cross‐sectional association between high social jet lag and HbA1c (1.87 mmol/mol [95% CI: 0.75 to 2.99]) and blood pressure (5.81 mm Hg [95% CI: 4.04 to 7.59]) was observed. For retired people, high social jet lag was negatively associated with HbA1c (−1.58 mmol/mol [95% CI: −2.54 to −0.62]), glucose (−0.19 mmoL/L [95% CI:−0.36 to −0.01]), and blood pressure (−3.70 mm Hg [95% CI: −5.36 to −2.04]), and the association with BMI was positive (1.12 kg/m2 [95% CI: 0.74 to 1.51]). Prospective associations had the same direction as cross‐sectional findings but were nonsignificant for working or retired people. Conclusions: Social jet lag was cross‐sectionally, but not prospectively, associated with glycemic and metabolic markers. Interaction with work status was present, and directions of the associations were generally detrimental in the working population, whereas higher social jet lag was associated with improved glycemic and metabolic control for retired people. [ABSTRACT FROM AUTHOR]

Aims The HFA-PEFF score was developed to optimize diagnosis and to aid in early recognition of heart failure (HF) with preserved ejection fraction (HFpEF) in patients who present with HF-like symptoms. Recognizing early-HFpEF phenogroups is essential to better understand progression towards overt HFpEF and pave the way for early intervention and treatment. Whether the HFA-PEFF domain scores can identify ‘early-HFpEF’ phenogroups remains unknown. The aims of this pilot study are to (i) identify distinct phenogroups by cluster analysis of HFA-PEFF domain scores in subjects that present with HF-like symptoms and (ii) study whether these phenogroups may be associated with distinct blood proteome profiles. Methods and results Subjects referred to the Cardiology Centers of the Netherlands, location Utrecht, with non-acute possibly cardiac-related symptoms (such as dyspnoea or fatigue) were prospectively enrolled in the HELPFul cohort (N = 507) and were included in the current analysis. Inclusion criteria for this study were (i) age ≥ 45 years and (ii) a left ventricular ejection fraction (LVEF) ≥ 50%, in the absence of a history of HF, coronary artery disease, congenital heart disease, or any previous cardiac interventions. Multinominal-based clustering with latent class model using the HFA-PEFF domain scores (functional, structural, and biomarker scores) as input was used to detect distinct phenotypic clusters. For each bootstrapping run, the 92 Olink proteins were analysed for their association with the identified phenogroups. Four distinct phenogroups were identified in the current analysis (validated by bootstrapping 1000×): (i) no left ventricular diastolic dysfunction (no LVDD, N = 102); (ii) LVDD with functional left ventricular (LV) abnormalities (N = 204); (iii) LVDD with functional and structural LV abnormalities (N = 204); and (iv) LVDD with functional and structural LV abnormalities and elevated BNP (N = 107). The HFA-PEFF total score risk categories significantly differed between the phenogroups (P < 0.001), with an increase of the HFA-PEFF score from Phenogroup 1 to 4 (low/intermediate/high HFA-PEFF risk score: Phenogroup 1: 88%/12%/0%; Phenogroup 2: 9%/91%/0%; Phenogroup 3: 0%/92%/8%; Phenogroup 4: 5%/83%/12%). Thirty-two out of the 92 Olink protein biomarkers significantly differed among the phenogroups. The top eight biomarkers—N-terminal prohormone brain natriuretic peptide, growth differentiation factor-15, matrix metalloproteinase-2, osteoprotegerin, tissue inhibitor of metalloproteinase-4, chitinase-3-like protein 1, insulin-like growth factor-binding protein 2, and insulin-like growth factor-binding protein 7—are mainly involved in inflammation and extracellular matrix remodelling, which are currently proposed key processes in HFpEF pathophysiology. Conclusions This study identified distinct phenogroups by using the HFA-PEFF domain scores in ambulant subjects referred for HF-like symptoms. The newly identified phenogroups accompanied by their circulating biomarkers profile might aid in a better understanding of the pathophysiological processes involved during the early stages of the HFpEF syndrome. [ABSTRACT FROM AUTHOR]

Aim: Diagnosing heart failure with preserved ejection fraction (HFpEF) in the non‐acute setting remains challenging. Natriuretic peptides have limited value for this purpose, and a multitude of studies investigating novel diagnostic circulating biomarkers have not resulted in their implementation. This review aims to provide an overview of studies investigating novel circulating biomarkers for the diagnosis of HFpEF and determine their risk of bias (ROB). Methods and results: A systematic literature search for studies investigating novel diagnostic HFpEF circulating biomarkers in humans was performed up until 21 April 2020. Those without diagnostic performance measures reported, or performed in an acute heart failure population were excluded, leading to a total of 28 studies. For each study, four reviewers determined the ROB within the QUADAS‐2 domains: patient selection, index test, reference standard, and flow and timing. At least one domain with a high ROB was present in all studies. Use of case‐control/two‐gated designs, exclusion of difficult‐to‐diagnose patients, absence of a pre‐specified cut‐off value for the index test without the performance of external validation, the use of inappropriate reference standards and unclear timing of the index test and/or reference standard were the main bias determinants. Due to the high ROB and different patient populations, no meta‐analysis was performed. Conclusion: The majority of current diagnostic HFpEF biomarker studies have a high ROB, reducing the reproducibility and the potential for clinical care. Methodological well‐designed studies with a uniform reference diagnosis are urgently needed to determine the incremental value of circulating biomarkers for the diagnosis of HFpEF. [ABSTRACT FROM AUTHOR]