Multi-omics approaches for precision obesity management : Potentials and limitations of omics in precision prevention, treatment and risk reduction of obesity

Autolysosomal Dysfunction in Obesity-induced Metabolic Inflammation and Related Disorders

PURPOSE OF REVIEW

Obesity is a global health crisis affecting individuals across all age groups, significantly increasing the risk of metabolic disorders such as type 2 diabetes (T2D), metabolic dysfunction-associated fatty liver disease (MAFLD), and cardiovascular diseases. The World Health Organization reported in 2022 that 2.5 billion adults were overweight, with 890 million classified as obese, emphasizing the urgent need for effective interventions. A critical aspect of obesity's pathophysiology is meta-inflammation-a chronic, systemic low-grade inflammatory state driven by excess adipose tissue, which disrupts metabolic homeostasis. This review examines the role of autolysosomal dysfunction in obesity-related metabolic disorders, exploring its impact across multiple metabolic organs and evaluating potential therapeutic strategies that target autophagy and lysosomal function.

RECENT FINDINGS

Emerging research highlights the importance of autophagy in maintaining cellular homeostasis and metabolic balance. Obesity-induced lysosomal dysfunction impairs the autophagic degradation process, contributing to the accumulation of damaged organelles and toxic aggregates, exacerbating insulin resistance, lipotoxicity, and chronic inflammation. Studies have identified autophagic defects in key metabolic tissues, including adipose tissue, skeletal muscle, liver, pancreas, kidney, heart, and brain, linking autophagy dysregulation to the progression of metabolic diseases. Preclinical investigations suggest that pharmacological and nutritional interventions-such as AMPK activation, caloric restriction mimetics, and lysosomal-targeting compounds-can restore autophagic function and improve metabolic outcomes in obesity models. Autolysosomal dysfunction is a pivotal contributor to obesity-associated metabolic disorders , influencing systemic inflammation and metabolic dysfunction. Restoring autophagy and lysosomal function holds promise as a therapeutic strategy to mitigate obesity-driven pathologies. Future research should focus on translating these findings into clinical applications, optimizing targeted interventions to improve metabolic health and reduce obesity-associated complications.

Live Biotherapeutic Products for Metabolic Diseases: Development Strategies, Challenges, and Future Directions

Metabolic diseases, such as obesity, type 2 diabetes, and non-alcoholic fatty liver disease, have emerged as major global health challenges. Recent research has revealed that the gut microbiome is closely associated with the development of these conditions. The Food and Drug Administration has recognized certain probiotic strains with therapeutic potential, classifying them as live biotherapeutic products (LBPs). LBPs, which are derived from naturally occurring microorganisms, may present an effective strategy for treating metabolic diseases by restoring gut microbiota balance and regulating metabolic functions. This review explores the development of LBPs specifically for metabolic disease treatments, covering every phase from strain identification, non-clinical and clinical trials, manufacturing and formulation to regulatory approval. Furthermore, it addresses the challenges involved in the commercialization of these therapies. By offering critical insights into the research and development of LBPs for metabolic disease treatment, this review aims to contribute to the progress of these promising therapies.

Precision medicine for obesity: current evidence and insights for personalization of obesity pharmacotherapy

Obesity is a chronic and complex disease associated with increased morbidity, mortality, and financial burden. It is expected that by 2030 one of two people in the United States will have obesity. The backbone for obesity management continues to be lifestyle interventions, consisting of calorie deficit diets and increased physical activity levels, however, these interventions are often insufficient to achieve sufficient and maintained weight loss. As a result, multiple patients require additional interventions such as antiobesity medications or bariatric interventions in order to achieve clinically significant weight loss and improvement or resolution of obesity-associated comorbidities. Despite the recent advances in the field of obesity pharmacotherapy that have resulted in never-before-seen weight loss outcomes, comorbidity improvement, and even reduction in cardiovascular mortality, there is still a significant interindividual variability in terms of response to antiobesity medications, with a subset of patients not achieving a clinically significant weight loss. Currently, the trial-and-error paradigm for the selection of antiobesity medications results in increased costs and risks for developing side effects, while also reduces engagement in weight management programs for patients with obesity. The implementation of a precision medicine framework to the selection of antiobesity medications might help reduce heterogeneity and optimize weight loss outcomes by identifying unique subsets of patients, or phenotypes, that have a better response to a specific intervention. The detailed study of energy balance regulation holds promise, as actionable behavioral and physiologic traits could help guide antiobesity medication selection based on previous mechanistic studies. Moreover, the rapid advances in genotyping, multi-omics, and big data analysis might hold the key to discover additional signatures or phenotypes that might respond better to a certain intervention and might permit the widespread adoption of a precision medicine approach for obesity management.

Evaluation of reference genes for qPCR in human liver and kidney tissue from individuals with obesity

Given the obesity epidemic and the prevalence of comorbidities, there is an ongoing need to understand the health consequences of this disease state better. Understanding gene expression signals will facilitate the identification of mechanisms of kidney and liver dysfunction/disease often present in individuals with obesity. qPCR is the standard method for studying changes in relative gene expression. Reference genes (RGs) are obligatory for accurately normalizing mRNA transcript levels across samples. Despite the prevalence of qPCR, the reliability of the data is often compromised because RGs are still used without validation or have proven to be unstable in different tissues and various diseases. In this study, we validated seven reference genes (ACTB, B2M, RPLP0, HPRT1, GAPDH, 18S rRNA, and PPIA) using human liver tissue from 15 lean individuals and 17 individuals with a BMI ≥ 25 and human kidney tissue from 13 lean individuals and 15 individuals with a BMI ≥ 25. Cross-validation of expression stability was performed using the RefFinder platform with four algorithms: NormFinder, BestKeeper, geNorm, and the comparative ΔCt method. In obesity-related studies, the most suitable reference genes in gene expression studies are RPLP0 and HPRT1 in human kidney tissue and RPLP0 and GAPDH in the liver.

Microarray Analysis of Visceral Adipose Tissue in Obese Women Reveals Common Crossroads Among Inflammation, Metabolism, Addictive Behaviors, and Cancer: AKT3 and MAPK1 Cross Point in Obesity

Background: Visceral adipose tissue (VAT) abnormalities are directly associated with obesity-associated disorders. The underlying mechanisms that confer increased pathological risk to VAT in obesity have not been fully described. Methods: A case-control study was conducted that included 10 women with obesity (36.80 ± 7.39 years, BMI ≥ 30 kg/m2) and 10 women of normal weight (32.70 ± 9.45 years, BMI < 24.9 kg/m2). RNA was extracted from greater omentum biopsies, and, using a DNA microarray, differential transcriptomic expression of VAT in women with obesity was evaluated taking as a reference that of women with normal weight. The differentially expressed genes (DEGs) were classified into functional biological processes and signaling pathways; moreover, the protein-protein interaction (PPI) networks were integrated for a deeper analysis of the pathways and genes involved in the central obesity-associated disorders. The expression of TNF-α, MAPK, and AKT proteins was also quantified in VAT. Results: The VAT of women with obesity had 3808 DEGs, mainly associated with the cellular process of inflammation and carbohydrates and lipid metabolism. Overexpressed genes were associated with inflammatory, metabolic, hormonal, neuroendocrine, carcinogenic, and infectious pathways. Cellular processes related to addictive behaviors were notable. MAPK and PI3K-AKT pathways were overexpressed, and Mapk1 and Akt3 genes were common crossing points among obesity-associated disorders' pathways. The increased expression of MAPK, AKT, and TNF proteins was confirmed in the VAT of women with obesity. Conclusion: VAT confers a complex and blended pathogenic transcriptomic profile in obese patients, where abnormal processes are mainly controlled by activating intracellular signaling pathways that exhibit a high degree of redundancy. Identifying shared cross points between those pathways could allow specific targeting treatments to exert a widespread effect over multiple pathogenic processes.

Precision prevention in occupational health: a conceptual analysis and development of a unified understanding and an integrative framework

Introduction

Precision prevention implements highly precise, tailored health interventions for individuals by directly addressing personal and environmental determinants of health. However, precision prevention does not yet appear to be fully established in occupational health. There are numerous understandings and conceptual approaches, but these have not yet been systematically presented or synthesized. Therefore, this conceptual analysis aims to propose a unified understanding and develop an integrative conceptual framework for precision prevention in occupational health.

Methods

Firstly, to systematically present definitions and frameworks of precision prevention in occupational health, six international databases were searched for studies published between January 2010 and January 2024 that used the term precision prevention or its synonyms in the context of occupational health. Secondly, a qualitative content analysis was conducted to analyze the existing definitions and propose a unified understanding. Thirdly, based on the identified frameworks, a multi-stage exploratory development process was applied to develop and propose an integrative conceptual framework for precision prevention in occupational health.

Results

After screening 3,681 articles, 154 publications were reviewed, wherein 29 definitions of precision prevention and 64 different frameworks were found, which can be summarized in eight higher-order categories. The qualitative content analysis revealed seven themes and illustrated many different wordings. The proposed unified understanding of precision prevention in occupational health takes up the identified themes. It includes, among other things, a contrast to a "one-size-fits-all approach" with a risk- and resource-oriented data collection and innovative data analytics with profiling to provide and improve tailored interventions. The developed and proposed integrative conceptual framework comprises three overarching stages: (1) data generation, (2) data management lifecycle and (3) interventions (development, implementation and adaptation).

Discussion

Although there are already numerous studies on precision prevention in occupational health, this conceptual analysis offers, for the first time, a proposal for a unified understanding and an integrative conceptual framework. However, the proposed unified understanding and the developed integrative conceptual framework should only be seen as an initial proposal that should be critically discussed and further developed to expand and strengthen both research on precision prevention in occupational health and its practical application in the workplace.

Trends over time in the deficit of (instrumental) activities of daily living in the Austrian population aged 65 years and older : Results from the Austrian Health Interview Survey series

BACKGROUND

Difficulties in activities of daily living (ADL) and instrumental activities of daily living (IADL) in older adults are associated with diminished quality of life and increased demand for long-term care. The present study examined the prevalence of disability among individuals aged 65 years and older in Austria, using data from the Austrian Health Interview Surveys (ATHIS).

METHODS

The ATHIS 2014 and 2019 surveys were used (N = 5853) for the analysis. Binary logistic regression was performed to measure the association between disability in at least one ADL or IADL limitation and independent variables adjusted for sociodemographic, health-related behavior and survey year.

RESULTS

The prevalence of ADL or IADL limitations increased in both sexes during the 5‑year follow-up period. For ADL limitations, the prevalence rose from 12.8% to 17.9% in men (p < 0.001) and from 19.2% to 25.7% in women (p < 0.001). The IADL limitations increased from 18.9% to 35.1% in men (p < 0.001) and from 38.2% to 50.8% in women (p < 0.001). Women reported significantly higher odds for ADL (odds ratio [OR]: 1.08, 95% confidence interval [CI]: 0.93-1.26) and IADL limitations (OR: 1.74, 95% CI: 1.53-1.98). In both sexes, participants aged 80 years and older reported higher odds for ADL (OR: 4.37, 95% CI:3.77-5.07) and IADL limitations (OR: 4.43, 95% CI: 3.86-5.09) compared to the younger group. Participants with at least one chronic disease reported higher odds for ADL (OR: 4.00, 95% CI: 3.41-4.70) and IADL limitations (OR: 4.37, 95% CI: 3.85-4.96). Primary education, single status, being born in non-EU/EFTA countries, and residing in Vienna were associated with higher odds of ADL and IADL limitations.

CONCLUSION

Gender, age, education, country of birth, residence, partnership status, number of chronic diseases, noncompliance with physical activity, and nutrition recommendations had a strong association with increased vulnerability to disability. Public health policy must address these factors for disability prevention strategies.

Exploring the Link between Oxidative Stress, Selenium Levels, and Obesity in Youth

Obesity is a worldwide increasing concern. Although in adults this is easily estimated with the body mass index, in children, who are constantly growing and whose bodies are changing, the reference points to assess weight status are age and gender, and need corroboration with complementary data, making their quantification highly difficult. The present review explores the interaction spectrum of oxidative stress, selenium status, and obesity in children and adolescents. Any factor related to oxidative stress that triggers obesity and, conversely, obesity that induces oxidative stress are part of a vicious circle, a complex chain of mechanisms that derive from each other and reinforce each other with serious health consequences. Selenium and its compounds exhibit key antioxidant activity and also have a significant role in the nutritional evaluation of obese children. The balance of selenium intake, retention, and metabolism emerges as a vital aspect of health, reflecting the complex interactions between diet, oxidative stress, and obesity. Understanding whether selenium status is a contributor to or a consequence of obesity could inform nutritional interventions and public health strategies aimed at preventing and managing obesity from an early age.

Multiomics Picture of Obesity in Young Adults

Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC-MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC-MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m2, incorporating an average of 24 proteins per model. Metabolomics showed slightly lower performance (MAE = 6.06 ± 0.33 kg/m2), followed by genomics (MAE = 6.20 ± 0.34 kg/m2). As expected, multiomic models demonstrated better accuracy, particularly the combination of proteomics and metabolomics (MAE = 4.77 ± 0.33 kg/m2), while including genomics data did not enhance the results. This manuscript is the first multiomics study of obesity in a gender-balanced cohort of young adults profiled by genomic, proteomic, and metabolomic methods. The comprehensive approach provides novel insights into the molecular mechanisms of obesity, opening avenues for more targeted interventions.

Identifying obesity subtypes: A review of studies utilising clinical biomarkers and genetic data

Obesity is a complex and multifactorial condition that poses significant health risks. Recent advancements in our understanding of obesity have highlighted the heterogeneity within this disorder. Identifying distinct subtypes of obesity is crucial for personalised treatment and intervention strategies. This review paper aims to examine studies that have utilised clinical biomarkers and genetic data to identify clusters or subtypes of obesity. The findings of these studies may provide valuable insights into the underlying mechanisms and potential targeted approaches for managing obesity-related health issues such as type 2 diabetes.