Precision Nutrition and Childhood Obesity: A Scoping Review

The Metabolic Programming of Pubertal Onset

BACKGROUND

There is increasing evidence that maternal factors such as nutritional status (both under and over-nutrition) and diabetes, alongside prenatal exposure to endocrine disrupting chemicals (EDCs), are associated with early pubertal onset in offspring. Such children are also at increased risk of the metabolic syndrome during adolescence and young adulthood.

AIM

This literature review focuses on the role of the prenatal environment in programming pubertal onset, and the impact of prenatal metabolic stressors on the declining average age of puberty.

METHOD

A review of all relevant literature was conducted in PubMed by the authors.

OUTCOME

The mechanism for this appears to be mediated through metabolic signals, such as leptin and insulin, on the kisspeptin-neuronal nitric oxide-gonadotropin releasing hormone (KiNG) axis. Exposed children have an elevated risk of childhood obesity and display a phenotype of hyperinsunlinaemia and hyperleptinaemia. These metabolic changes permit an earlier attainment of the nutritional "threshold" for puberty. Unfortunately, this cycle may be amplified across subsequent generations, however early intervention may help "rescue" progression of this programming.

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.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Pilot Study Assessing the Baseline Physical Activity and Knowledge of Heart Health of Elementary School-Aged Children in Rural South Carolina and the Impact of an Interactive Educational Program

PURPOSE

This study asked whether, if provided with education on heart-healthy habits, elementary school children in Abbeville, Greenwood, and Saluda counties in South Carolina would retain and desire to implement healthy nutrition and increased exercise. We hypothesized that teaching children about heart-healthy habits would increase their activity levels and improve their desire to be active.

METHODS

This was a longitudinal survey study. Children at local after-school programs were given a pre-survey, the Kids' Activity and Nutrition Questionnaire (KAN-Q), to assess their activity levels, diet, and knowledge of heart health. The children had a 15-minute educational period followed by an interactive program. Students completed the same survey at each of the three sessions.

FINDINGS

A total of 44 children answered the survey questions at the beginning of each session. Out of the 10 behavioral questions, six indicated a favorable shift towards adopting healthier habits. Whole grain consumption increased to 71% from 32% (p<0.01). Vegetable consumption increased from 39% to 88%, and fruit consumption increased from 68% to 92% (p<0.01). There was a 30% decrease in the consumption of sugary drinks (p<0.01), and a reduction in hours watching television (p=0.05). All four knowledge-based questions had an increase in correct responses across the three sessions (p<0.01).

CONCLUSION

To augment behavior, a dual approach of education on nutrition and exercise leads to improved nutrition choices and exercise habits for primary prevention of cardiovascular risk factors in elementary school-aged children. These habits improve adherence to increased physical activity and better nutrition after school.

The effect of low birth weight as an intrauterine exposure on the early onset of sarcopenia through possible molecular pathways

Sarcopenia, a musculoskeletal disease characterized by the progressive loss of skeletal muscle mass, strength, and physical performance, presents significant challenges to global public health due to its adverse effects on mobility, morbidity, mortality, and healthcare costs. This comprehensive review explores the intricate connections between sarcopenia and low birth weight (LBW), emphasizing the developmental origins of health and disease (DOHaD) hypothesis, inflammatory processes (inflammaging), mitochondrial dysfunction, circadian rhythm disruptions, epigenetic mechanisms, and genetic variations revealed through genome-wide studies (GWAS). A systematic search strategy was developed using PubMed to identify relevant English-language publications on sarcopenia, LBW, DOHaD, inflammaging, mitochondrial dysfunction, circadian disruption, epigenetic mechanisms, and GWAS. The publications consist of 46.2% reviews, 21.2% cohort studies, 4.8% systematic reviews, 1.9% cross-sectional studies, 13.4% animal studies, 4.8% genome-wide studies, 5.8% epigenome-wide studies, and 1.9% book chapters. The review identified key factors contributing to sarcopenia development, including the DOHaD hypothesis, LBW impact on muscle mass, inflammaging, mitochondrial dysfunction, the influence of clock genes, the role of epigenetic mechanisms, and genetic variations revealed through GWAS. The DOHaD theory suggests that LBW induces epigenetic alterations during foetal development, impacting long-term health outcomes, including the early onset of sarcopenia. LBW correlates with reduced muscle mass, grip strength, and lean body mass in adulthood, increasing the risk of sarcopenia. Chronic inflammation (inflammaging) and mitochondrial dysfunction contribute to sarcopenia, with LBW linked to increased oxidative stress and dysfunction. Disrupted circadian rhythms, regulated by genes such as BMAL1 and CLOCK, are associated with both LBW and sarcopenia, impacting lipid metabolism, muscle mass, and the ageing process. Early-life exposures, including LBW, induce epigenetic modifications like DNA methylation (DNAm) and histone changes, playing a pivotal role in sarcopenia development. Genome-wide studies have identified candidate genes and variants associated with lean body mass, muscle weakness, and sarcopenia, providing insights into genetic factors contributing to the disorder. LBW emerges as a potential early predictor of sarcopenia development, reflecting the impact of intrauterine exposures on long-term health outcomes. Understanding the complex interplay between LBW with inflammaging, mitochondrial dysfunction, circadian disruption, and epigenetic factors is essential for elucidating the pathogenesis of sarcopenia and developing targeted interventions. Future research on GWAS and the underlying mechanisms of LBW-associated sarcopenia is warranted to inform preventive strategies and improve public health outcomes.

Understanding risk and causal mechanisms for developing obesity in infants and young children: A National Institutes of Health workshop

Obesity in children remains a major public health problem, with the current prevalence in youth ages 2-19 years estimated to be 19.7%. Despite progress in identifying risk factors, current models do not accurately predict development of obesity in early childhood. There is also substantial individual variability in response to a given intervention that is not well understood. On April 29-30, 2021, the National Institutes of Health convened a virtual workshop on "Understanding Risk and Causal Mechanisms for Developing Obesity in Infants and Young Children." The workshop brought together scientists from diverse disciplines to discuss (1) what is known regarding epidemiology and underlying biological and behavioral mechanisms for rapid weight gain and development of obesity and (2) what new approaches can improve risk prediction and gain novel insights into causes of obesity in early life. Participants identified gaps and opportunities for future research to advance understanding of risk and underlying mechanisms for development of obesity in early life. It was emphasized that future studies will require multi-disciplinary efforts across basic, behavioral, and clinical sciences. An exposome framework is needed to elucidate how behavioral, biological, and environmental risk factors interact. Use of novel statistical methods may provide greater insights into causal mechanisms.

Integrating (Nutri-)Metabolomics into the One Health Tendency-The Key for Personalized Medicine Advancement

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment, can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases, or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals, and the environment is of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase in risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, and, in particular, nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

What Happens In Utero Does Not Stay In Utero: a Review of Evidence for Prenatal Epigenetic Programming by Per- and Polyfluoroalkyl Substances (PFAS) in Infants, Children, and Adolescents

PURPOSE OF REVIEW

Review human literature on the relationship between prenatal exposure to per- and polyfluoroalkyl substances (PFAS) and epigenetic modifications in infants, children, and adolescents < 18 years of age.

RECENT FINDINGS

Eleven studies were identified, with study populations located in the U.S., Taiwan, Japan, and the Kingdom of Denmark. Many studies (n = 5) were cross-sectional, with PFAS exposure and epigenetic outcomes measured in the same tissue collected at delivery via cord blood or dried newborn blood spots. The other six studies were prospective, with prenatal PFAS measured on maternal blood during pregnancy and DNA methylation (DNAm) assessed in cord blood and childhood peripheral leukocytes (n = 1 study). Epigenetic marks of interest included global DNAm measures (LINE-1, Alu, and an ELISA-based method), candidate genes (IFG2, H19, and MEST), and epigenome-wide DNA methylation via array-based methods (Infinium 450 K and EPIC). Two studies using array-based methods employed discovery and validation paradigms, in which a small subset of loci (n = 6 and n = 4) were replicated in the discovery population. One site (TNXB) was a hit in two independent studies. Collectively, loci associated with PFAS were in regions involved in growth and development, lipid metabolism, and nutrient metabolism. There is moderate human evidence supporting associations of prenatal PFAS exposure on DNAm at birth, with one study suggesting sustained effects into childhood. Future studies are warranted to link PFAS-associated DNAm to health outcomes, as well as to investigate the role of other epigenetic marks such as hydroxymethylation, miRNA expression, and histone modifications.

A Metabolomics-Based Investigation of the Effects of a Short-Term Body Weight Reduction Program in a Cohort of Adolescents with Obesity: A Prospective Interventional Clinical Study

Metabolomics applied to assess the response to a body weight reduction program (BWRP) may generate valuable information concerning the biochemical mechanisms/pathways underlying the BWRP-induced cardiometabolic benefits. The aim of the present study was to establish the BWRP-induced changes in the metabolomic profile that characterizes the obese condition. In particular, a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted metabolomic approach was used to determine a total of 188 endogenous metabolites in the plasma samples of a cohort of 42 adolescents with obesity (female/male = 32/10; age = 15.94 ± 1.33 year; body mass index standard deviation score (BMI SDS) = 2.96 ± 0.46) who underwent a 3-week BWRP, including hypocaloric diet, physical exercise, nutritional education, and psychological support. The BWRP was capable of significantly improving body composition (e.g., BMI SDS, p < 0.0001), glucometabolic homeostasis (e.g., glucose, p < 0.0001), and cardiovascular function (e.g., diastolic blood pressure, p = 0.016). A total of 64 metabolites were significantly reduced after the intervention (at least p < 0.05), including 53 glycerophospholipids (23 PCs ae, 21 PCs aa, and 9 lysoPCs), 7 amino acids (tyrosine, phenylalanine, arginine, citrulline, tryptophan, glutamic acid, and leucine), the biogenic amine kynurenine, 2 sphingomyelins, and (free) carnitine (C0). On the contrary, three metabolites were significantly increased after the intervention (at least p < 0.05)-in particular, glutamine, trans-4-hydroxyproline, and the octadecenoyl-carnitine (C18:1). In conclusion, when administered to adolescents with obesity, a short-term BWRP is capable of changing the metabolomic profile in the plasma.

Personalized optimal nutrition lifestyle for self obesity management using metaalgorithms

Precision medicine applies machine learning methods to estimate the personalized optimal treatment decision based on individual information, such as genetic data and medical history. The main purpose of self obesity management is to develop a personalized optimal life plan that is easy to implement and adhere to, thereby reducing the incidence of obesity and obesity-related diseases. The methodology comprises three components. First, we apply catboost, random forest and lasso covariance test to evaluate the importance of individual features in forecasting body mass index. Second, we apply metaalgorithms to estimate the personalized optimal decision on alcohol, vegetable, high caloric food and daily water intake respectively for each individual. Third, we propose new metaalgorithms named SX and SXwint learners to compute the personalized optimal decision and compare their performances with other prevailing metalearners. We find that people who receive individualized optimal treatment options not only have lower obesity levels than others, but also have lower obesity levels than those who receive ’one-for-all’ treatment options. In conclusion, all metaalgorithms are effective at estimating the personalized optimal decision, where SXwint learner shows the best performance on daily water intake.

Time to Consider the “Exposome Hypothesis” in the Development of the Obesity Pandemic

The obesity epidemic shows no signs of abatement. Genetics and overnutrition together with a dramatic decline in physical activity are the alleged main causes for this pandemic. While they undoubtedly represent the main contributors to the obesity problem, they are not able to fully explain all cases and current trends. In this context, a body of knowledge related to exposure to as yet underappreciated obesogenic factors, which can be referred to as the “exposome”, merits detailed analysis. Contrarily to the genome, the “exposome” is subject to a great dynamism and variability, which unfolds throughout the individual’s lifetime. The development of precise ways of capturing the full exposure spectrum of a person is extraordinarily demanding. Data derived from epidemiological studies linking excess weight with elevated ambient temperatures, in utero, and intergenerational effects as well as epigenetics, microorganisms, microbiota, sleep curtailment, and endocrine disruptors, among others, suggests the possibility that they may work alone or synergistically as several alternative putative contributors to this global epidemic. This narrative review reports the available evidence on as yet underappreciated drivers of the obesity epidemic. Broadly based interventions are needed to better identify these drivers at the same time as stimulating reflection on the potential relevance of the “exposome” in the development and perpetuation of the obesity epidemic.

Cinnamaldehyde treatment during adolescence improves white and brown adipose tissue metabolism in a male rat model of early obesity

Early obesity is a serious health problem and nutritional therapeutic strategies during young age may improve health outcomes throughout life. Cinnamaldehyde, major component of cinnamon, exhibits several beneficial metabolic effects....

Personalized nutrition approach in pediatrics: a narrative review

Dietary habits represent the main determinant of health. Although extensive research has been conducted to modify unhealthy dietary behaviors across the lifespan, obesity and obesity-associated comorbidities are increasingly observed worldwide. Individually tailored interventions are nowadays considered a promising frontier for nutritional research. In this narrative review, the technologies of importance in a pediatric clinical setting are discussed. The first determinant of the dietary balance is represented by energy intakes matching individual needs. Most emerging studies highlight the opportunity to reconsider the widely used prediction equations of resting energy expenditure. Artificial Neural Network approaches may help to disentangle the role of single contributors to energy expenditure. Artificial intelligence is also useful in the prediction of the glycemic response, based on the individual microbiome. Other factors further concurring to define individually tailored nutritional needs are metabolomics and nutrigenomic. Since most available data come from studies in adult groups, new efforts should now be addressed to integrate all these aspects to develop comprehensive and-above all-effective interventions for children. IMPACT: Personalized dietary advice, specific to individuals, should be more effective in the prevention of chronic diseases than general recommendations about diet. Artificial Neural Networks algorithms are technologies of importance in a pediatric setting that may help practitioners to provide personalized nutrition. Other approaches to personalized nutrition, while promising in adults and for basic research, are still far from practical application in pediatrics.

Towards Tailored Gut Microbiome-Based and Dietary Interventions for Promoting the Development and Maintenance of a Healthy Brain

Mental health is determined by a complex interplay between the Neurological Exposome and the Human Genome. Multiple genetic and non-genetic (exposome) factors interact early in life, modulating the risk of developing the most common complex neurodevelopmental disorders (NDDs), with potential long-term consequences on health. To date, the understating of the precise etiology underpinning these neurological alterations, and their clinical management pose a challenge. The crucial role played by diet and gut microbiota in brain development and functioning would indicate that modulating the gut-brain axis may help protect against the onset and progression of mental-health disorders. Some nutritional deficiencies and gut microbiota alterations have been linked to NDDs, suggesting their potential pathogenic implications. In addition, certain dietary interventions have emerged as promising alternatives or adjuvant strategies for improving the management of particular NDDs, at least in particular subsets of subjects. The gut microbiota can be a key to mediating the effects of other exposome factors such as diet on mental health, and ongoing research in Psychiatry and Neuropediatrics is developing Precision Nutrition Models to classify subjects according to a diet response prediction based on specific individual features, including microbiome signatures. Here, we review current scientific evidence for the impact of early life environmental factors, including diet, on gut microbiota and neuro-development, emphasizing the potential long-term consequences on health; and also summarize the state of the art regarding the mechanisms underlying diet and gut microbiota influence on the brain-gut axis. Furthermore, we describe the evidence supporting the key role played by gut microbiota, diet and nutrition in neurodevelopment, as well as the effectiveness of certain dietary and microbiome-based interventions aimed at preventing or treating NDDs. Finally, we emphasize the need for further research to gain greater insight into the complex interplay between diet, gut microbiome and brain development. Such knowledge would help towards achieving tailored integrative treatments, including personalized nutrition.

Find the Needle in the Haystack, Then Find It Again: Replication and Validation in the 'Omics Era

Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon balancing false-positive associations with generalizability. Given the foundational role of reproducibility in scientific inference, replication and validation of ‘omics findings are cornerstones of this effort. In this narrative review, we define key terms relevant to replication and validation, present issues surrounding each concept with historical and contemporary examples from genomics (the most well-established and upstream ‘omics), discuss special issues and unique considerations for replication and validation in metabolomics (an emerging field and most downstream ‘omics for which best practices remain yet to be established), and make suggestions for future research leveraging multiple ‘omics datasets.