Abstract
Aims
This study investigated the role of plasma proteins in obesity to identify predictive biomarkers and explore underlying biological mechanisms.
Methods
In the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study, 809 proteins were measured in 2045 individuals (564 obese and 1481 non-obese). Multivariate logistic regression adjusted for confounders (basic and full models) was used to identify obesity-associated proteins. Priority-Lasso was applied for feature selection, followed by machine learning models (support vector machine [SVM], random forest [RF], k-nearest neighbour [KNN] and adaptive boosting [Adaboost]) for prediction. Correlation and enrichment analyses were performed to elucidate relationships between protein biomarkers, obesity risk factors and perturbed pathways. Mendelian randomisation (MR) assessed causal links between proteins and obesity.
Results
A total of 16 proteins were identified as significantly associated with obesity through multivariable logistic regression in the basic model and subsequent Priority-Lasso analysis. Enrichment analyses highlighted immune response, lipid metabolism and inflammation regulation were linked to obesity. Machine learning models demonstrated robust predictive performance with area under the curves (AUC) of 0.820 (SVM), 0.805 (RF), 0.791 (KNN) and 0.819 (Adaboost). All 16 proteins correlated with obesity-related risk factors such as blood pressure and lipid levels. MR analysis identified AFM, CRP and CFH as causal and potentially modifiable proteins.
Conclusions
The protein signatures identified in our study showed promising predictive potential for obesity. These findings warrant further investigation to evaluate their clinical applicability, offering insights into obesity prevention and treatment strategies.

Purpose of review

The aim of this review is to examine recent advancements in RNA-targeted therapies for the management of severe hypertriglyceridemia (sHTG) and prevention of sHTG-associated acute pancreatitis.

Recent findings

Recent developments in RNA-targeted therapies, aimed at inhibiting apolipoprotein C-III (apoC-III), have demonstrated substantial and sustained reductions in triglyceride levels. Novel therapies, including antisense oligonucleotides (ASOs) and small interfering RNA (siRNA), such as volanesorsen, olezarsen, and plozasiran, have shown promising results in recent trials. These therapies not only effectively lower plasma triglyceride levels but also significantly reduce the incidence of acute pancreatitis.

Summary

SHTG is a high-burden metabolic disorder that is associated with a significantly increased incidence and severity of acute pancreatitis. Traditional lifestyle interventions and conventional therapies, including fibrates and n-3 fatty acids, often provide only modest reductions in triglycerides and fail to prevent sHTG-associated acute pancreatitis. The emergence of novel and targeted RNA-therapies represents a potential breakthrough in the management of sHTG and acute pancreatitis prevention.

Professor Christina Vogel (The Center for Food Policy, City St George’s) and Dr. Preeti Dhuria (University of Southampton) discuss how weak enforcement lets retailers bypass UK obesity regulations.

Abstract
Aims
Obesity and its complications contribute to the burden of cardiovascular disease (CVD). Here, we characterised individuals with high body mass index (BMI) and established CVD by assessing healthcare resource utilisation (HCRU) and costs, incidence of cardiovascular (CV) events and mortality.
Materials and Methods
This was a retrospective open cohort study using UK Discover data (study period: January 2004 to December 2019). Included were individuals aged ≥45 years with BMI ≥ 27 kg/m2, without type 1 or type 2 diabetes, and with established CVD (previous myocardial infarction, stroke or peripheral artery disease). Serial annual cross sections were assembled to generate prevalence and incidence cohorts and for mapping of HCRU, costs and the incidence of selected events. CVD and mortality trajectories were modelled using a Markov model. HCRU and costs were layered onto this model to obtain associated trajectories.
Results
In 2019, annual per-person healthcare costs for individuals with high BMI and established CVD (n = 27 313) were £3364. During 2015–2019, the incidence of major adverse CV events was 2812 per 100,000 person-years; the incidences of all-cause and CV mortality were 2896 and 774 per 100,000 person-years, respectively. Over 2022–2031, this population is projected to accrue estimated healthcare costs of £40.8 million. HCRU trajectory drivers included a history of CV events, older age, and multimorbidity.
Conclusions
Owing to a high disease and treatment burden, people with a history of CVD living with high BMI incur substantial healthcare costs and are at risk of mortality.