Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors.

BACKGROUND: Heart failure (HF) is the leading cause of hospitalization in individuals over 65 years of age. Identifying noninvasive methods to detect HF may address the epidemic of HF. Seismocardiography which measures cardiac vibrations transmitted to the chest wall has recently emerged as a promising technology to detect HF. OBJECTIVES: In this multicenter study, the authors examined whether seismocardiography using commercially available smartphones can differentiate control subjects from patients with stage C HF. METHODS: Both inpatients and outpatients with HF were enrolled from Finland and the United States. Inpatients with HF were assessed within 2 days of admission, and outpatients were assessed in the ambulatory setting. In a prespecified pooled data analysis, algorithms were derived using logistic regression and then validated using a bootstrap aggregation method. RESULTS: A total of 217 participants with HF (174 inpatients and 172 outpatients) and 786 control subjects from cardiovascular clinics were enrolled. The mean age of participants with acute HF was 64 ± 13 years, 64.9% were male, left ventricular ejection fraction was 39% ± 15%, and median N-terminal pro-B-type natriuretic peptide was 5,778 ng/L (Q1-Q3: 1,933-6,703). The majority (74%) of participants with HF had reduced EF, and 38% had atrial fibrillation. Across both HF cohorts, the algorithms had an area under the receiver operating characteristic curve of 0.95 with a sensitivity of 85%, specificity of 90%, and accuracy of 89% for the detection of HF, with a decision threshold of 0.5. The positive and negative likelihood ratios were 8.50 and 0.17, respectively. The accuracy of the algorithms was not significantly different in subgroups based on age, sex, body mass index, and atrial fibrillation. CONCLUSIONS: Smartphone-based assessment of cardiac function using seismocardiography is feasible and differentiates patients with HF from control subjects with high diagnostic accuracy. (Recognition of Heart Failure With Micro Electro-mechanical Sensors FI; NCT04444583; Recognition of Heart Failure With Micro Electro-mechanical Sensors [NCT04378179]; Detection of Coronary Artery Disease With Micro Electro-mechanical Sensors; NCT04290091).

The Role of Inflammatory Cytokines as Intermediates in the Pathway from Increased Adiposity to Disease.

OBJECTIVE: This study aimed to investigate the role of cytokines as intermediates in the pathway from increased adiposity to disease. METHODS: BMI and circulating levels of up to 41 cytokines were measured in individuals from three Finnish cohort studies (n = 8,293). Mendelian randomization (MR) was used to assess the impact of BMI on circulating cytokines and the impact of BMI-driven cytokines on risk of obesity-related diseases. RESULTS: Observationally, BMI was associated with 19 cytokines. For every SD increase in BMI, causal effect estimates were strongest for hepatocyte growth factor, monocyte chemotactic protein-1 (MCP-1), and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and were as ratios of geometric means 1.13 (95% CI: 1.08-1.19), 1.08 (95% CI: 1.04-1.14), and 1.13 (95% CI: 1.04-1.21), respectively. TRAIL was associated with a small increase in the odds of coronary artery disease (odds ratio: 1.03; 95% CI: 1.00-1.06). There was inconsistent evidence for a protective role of MCP-1 against inflammatory bowel diseases. CONCLUSIONS: Observational and MR estimates of the effect of BMI on cytokine levels were generally concordant. There was little evidence for an effect of raised levels of BMI-driven cytokines on disease. These findings illustrate the challenges of MR when applied in the context of molecular mediation.

First-in-Humans Study of 68Ga-DOTA-Siglec-9, a PET Ligand Targeting Vascular Adhesion Protein 1.

Sialic acid-binding immunoglubulinlike lectin 9 (Siglec-9) is a ligand of vascular adhesion protein 1. A 68Ga-labeled peptide of Siglec-9, 68Ga-DOTA-Siglec-9, holds promise as a novel PET tracer for imaging of inflammation. This first-in-humans study investigated the safety, tolerability, biodistribution, and radiation dosimetry of this radiopharmaceutical. Methods: Six healthy men underwent dynamic whole-body PET/CT. Serial venous blood samples were drawn from 1 to 240 min after intravenous injection of 162 ± 4 MBq of 68Ga-DOTA-Siglec-9. In addition to γ-counting, the plasma samples were analyzed by high-performance liquid chromatography to detect intact tracer and radioactive metabolites. Radiation doses were calculated using the OLINDA/EXM software, version 2.2. In addition, a patient with early rheumatoid arthritis was studied with both 68Ga-DOTA-Siglec-9 and 18F-FDG PET/CT to determine the ability of the new tracer to detect arthritis. Results:68Ga-DOTA-Siglec-9 was well tolerated by all subjects. 68Ga-DOTA-Siglec-9 was rapidly cleared from the blood circulation, and several radioactive metabolites were detected. The organs with the highest absorbed doses were the urinary bladder wall (0.38 mSv/MBq) and kidneys (0.054 mSv/MBq). The mean effective dose was 0.022 mSv/MBq (range, 0.020-0.024 mSv/MBq). Most importantly, however, 68Ga-DOTA-Siglec-9 was comparable to 18F-FDG in detecting arthritis. Conclusion: Intravenous injection of 68Ga-DOTA-Siglec-9 was safe and biodistribution was favorable for testing of the tracer in larger group of patients with rheumatoid arthritis, as is planned for the next phase of clinical trials. The effective radiation dose of 68Ga-DOTA-Siglec-9 was within the same range as the effective radiation doses of other 68Ga-labeled tracers. Injection of 150 MBq of 68Ga-DOTA-Siglec-9 would expose a subject to 3.3 mSv. These findings support the possible repeated clinical use of 68Ga-DOTA-Siglec-9, such as in trials to elucidate the treatment efficacy of novel drug candidates.

Multivariate Genome-wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy.

Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.

Genome-wide association study identifies seven novel loci associating with circulating cytokines and cell adhesion molecules in Finns.

BACKGROUND: Inflammatory processes contribute to the pathophysiology of multiple chronic conditions. Genetic factors play a crucial role in modulating the inflammatory load, but the exact mechanisms are incompletely understood. OBJECTIVE: To assess genetic determinants of 16 circulating cytokines and cell adhesion molecules (inflammatory phenotypes) in Finns. METHODS: Genome-wide associations of the inflammatory phenotypes were studied in Northern Finland Birth Cohort 1966 (N=5284). A subsequent meta-analysis was completed for 10 phenotypes available in a previous genome-wide association study, adding up to 13 577 individuals in the study. Complementary association tests were performed to study the effect of the ABO blood types on soluble adhesion molecule levels. RESULTS: We identified seven novel and six previously reported genetic associations (p<3.1×10-9). Three loci were associated with soluble vascular cell adhesion molecule-1 (sVCAM-1) level, one of which was the ABO locus that has been previously associated with soluble E-selectin (sE-selectin) and intercellular adhesion molecule-1 (sICAM-1) levels. Our findings suggest that the blood type B associates primarily with sVCAM-1 level, while the A1 subtype shows a robust effect on sE-selectin and sICAM-1 levels. The genotypes in the ABO locus associating with higher soluble adhesion molecule levels tend to associate with lower circulating cholesterol levels and lower cardiovascular disease risk. CONCLUSION: The present results extend the knowledge about genetic factors contributing to the inflammatory load. Our findings suggest that two distinct mechanisms contribute to the soluble adhesion molecule levels in the ABO locus and that elevated soluble adhesion molecule levels per se may not increase risk for cardiovascular disease.

Metabolic profiling of pregnancy: cross-sectional and longitudinal evidence.

BACKGROUND: Pregnancy triggers well-known alterations in maternal glucose and lipid balance but its overall effects on systemic metabolism remain incompletely understood. METHODS: Detailed molecular profiles (87 metabolic measures and 37 cytokines) were measured for up to 4260 women (24-49 years, 322 pregnant) from three population-based cohorts in Finland. Circulating molecular concentrations in pregnant women were compared to those in non-pregnant women. Metabolic profiles were also reassessed for 583 women 6 years later to uncover the longitudinal metabolic changes in response to change in the pregnancy status. RESULTS: Compared to non-pregnant women, all lipoprotein subclasses and lipids were markedly increased in pregnant women. The most pronounced differences were observed for the intermediate-density, low-density and high-density lipoprotein triglyceride concentrations. Large differences were also seen for many fatty acids and amino acids. Pregnant women also had higher concentrations of low-grade inflammatory marker glycoprotein acetyls, higher concentrations of interleukin-18 and lower concentrations of interleukin-12p70. The changes in metabolic concentrations for women who were not pregnant at baseline but pregnant 6 years later (or vice versa) matched (or were mirror-images of) the cross-sectional association pattern. Cross-sectional results were consistent across the three cohorts and similar longitudinal changes were seen for 653 women in 4-year and 497 women in 10-year follow-up. For multiple metabolic measures, the changes increased in magnitude across the three trimesters. CONCLUSIONS: Pregnancy initiates substantial metabolic and inflammatory changes in the mothers. Comprehensive characterisation of normal pregnancy is important for gaining understanding of the key nutrients for fetal growth and development. These findings also provide a valuable molecular reference in relation to studies of adverse pregnancy outcomes.

Circulating Cytokines Predict the Development of Insulin Resistance in a Prospective Finnish Population Cohort.

CONTEXT: Metabolic inflammation contributes to the development of insulin resistance (IR), but the roles of different inflammatory and other cytokines in this process remain unclear. OBJECTIVE: We aimed at analyzing the value of different cytokines in predicting future IR. DESIGN, SETTING, AND PARTICIPANTS: We measured the serum concentrations of 48 cytokines from a nationwide cohort of 2200 Finns (the Cardiovascular Risk in Young Finns Study), and analyzed their role as independent risk factors for predicting the development of IR 4 years later. MAIN OUTCOME MEASURES: We used cross-sectional regression analysis adjusted for known IR risk factors (high age, body mass index, systolic blood pressure, triglycerides, smoking, physical inactivity, and low high-density lipoprotein cholesterol), C-reactive protein and 37 cytokines to find the determinants of continuous baseline IR (defined by homeostatic model assessment). A logistic regression model adjusted for the known risk factors, baseline IR, and 37 cytokines was used to predict the future IR. RESULTS: Several cytokines, often in a sex-dependent manner, remained as independent determinants of current IR. In men, none of the cytokines was an independent predictive risk marker of future IR. In women, in contrast, IL-17 (odds ratio, 1.42 for 1-SD change in ln-transformed IL-17) and IL-18 (odds ratio, 1.37) were independently associated with the future IR. IL-17 levels also independently predicted the development of incident future IR (odds ratio, 1.48). CONCLUSIONS: The systemic levels of the T helper 1 cell cytokine IL-18 and the T helper 17 cell cytokine IL-17 thus may have value in predicting future insulin sensitivity in women independently of classical IR risk factors.