Nutrigenomics: lessons learned and future perspectives

Immunotherapy targeting the obese white adipose tissue microenvironment: Focus on non-communicable diseases

Obesity triggers inflammatory responses in the microenvironment of white adipose tissue, resulting in chronic systemic inflammation and the subsequent development of non-communicable diseases, including type 2 diabetes, coronary heart disease, and breast cancer. Current therapy approaches for obesity-induced non-communicable diseases persist in prioritizing symptom remission while frequently overlooking the criticality of targeting and alleviating inflammation at its source. Accordingly, this review highlights the importance of the microenvironment of obese white adipose tissue and the promising potential of employing immunotherapy to target it as an effective therapeutic approach for non-communicable diseases induced by obesity. Additionally, this review discusses the challenges and offers perspective about the immunotherapy targeting the microenvironment of obese white adipose tissue.

Molecular pathways and nutrigenomic review of insulin resistance development in gestational diabetes mellitus

Gestational diabetes mellitus is a condition marked by raised blood sugar levels and insulin resistance that usually occurs during the second or third trimester of pregnancy. According to the World Health Organization, hyperglycemia affects 16.9% of pregnancies worldwide. Dietary changes are the primarily alternative treatment for gestational diabetes mellitus. This paper aims to perform an exhaustive overview of the interaction between diet, gene expression, and the metabolic pathways related to insulin resistance. The intake of foods rich in carbohydrates can influence the gene expression of glycolysis, as well as foods rich in fat, can disrupt the beta-oxidation and ketogenesis pathways. Furthermore, vitamins and minerals are related to inflammatory processes regulated by the TLR4/NF-κB and one carbon metabolic pathways. We indicate that diet regulated gene expression of PPARα, NOS, CREB3L3, IRS, and CPT I, altering cellular physiological mechanisms and thus increasing or decreasing the risk of gestational diabetes. The alteration of gene expression can cause inflammation, inhibition of fatty acid transport, or on the contrary help in the modulation of ketogenesis, improve insulin sensitivity, attenuate the effects of glucotoxicity, and others. Therefore, it is critical to comprehend the metabolic changes of pregnant women with gestational diabetes mellitus, to determine nutrients that help in the prevention and treatment of insulin resistance and its long-term consequences.

Associations between Nutrigenomic Effects and Incidences of Microbial Resistance against Novel Antibiotics

Nutrigenomics is the study of the impact of diets or nutrients on gene expression and phenotypes using high-throughput technologies such as transcriptomics, proteomics, metabolomics, etc. The bioactive components of diets and nutrients, as an environmental factor, transmit information through altered gene expression and hence the overall function and traits of the organism. Dietary components and nutrients not only serve as a source of energy but also, through their interactions with genes, regulate gut microbiome composition, the production of metabolites, various biological processes, and finally, health and disease. Antimicrobial resistance in pathogenic and probiotic microorganisms has emerged as a major public health concern due to the presence of antimicrobial resistance genes in various food products. Recent evidence suggests a correlation between the regulation of genes and two-component and other signaling systems that drive antibiotic resistance in response to diets and nutrients. Therefore, diets and nutrients may be alternatively used to overcome antibiotic resistance against novel antibiotics. However, little progress has been made in this direction. In this review, we discuss the possible implementations of nutrigenomics in antibiotic resistance against novel antibiotics.

Development of a Structural Equation Model to Examine the Relationships between Genetic Polymorphisms and Cardiovascular Risk Factors

Genome-wide association studies (GWASs) have been used to discover genetic polymorphisms that affect cardiovascular diseases (CVDs). Structural equation modelling (SEM) has been identified as a robust multivariate analysis tool. However, there is a paucity of research that has conducted SEM in African populations. The purpose of this study was to create a model that may be used to examine the relationships between genetic polymorphisms and their respective cardiovascular risk (CVR) factors. The procedure involved three steps. Firstly, the creation of latent variables and the hypothesis model. Next, confirmatory factor analysis (CFA) to examine the relationships between the latent variables, SNPs, dyslipidemia and metabolic syndrome, with their respective indicators. Then finally, model fitting using JASP statistical software v.0.16.4.0. The indicators for the SNPs and dyslipidemia all indicated significant factor loadings, -0.96 to 0.91 (p = <0.001) and 0.92 to 0.96 (p ≤ 0.001), respectively. The indicators for metabolic syndrome also had significant coefficients of 0.20 (p = 0.673), 0.36 (p = 0.645) and 0.15 (p = 0.576), but they were not statistically significant. There were no significant relationships observed between the SNPs, dyslipidemia and metabolic syndrome. The SEM produced an acceptable model according to the fit indices.

MetaboVariation: Exploring Individual Variation in Metabolite Levels

To date, most metabolomics biomarker research has focused on identifying disease biomarkers. However, there is a need for biomarkers of early metabolic dysfunction to identify individuals who would benefit from lifestyle interventions. Concomitantly, there is a need to develop strategies to analyse metabolomics data at an individual level. We propose "MetaboVariation", a method that models repeated measurements on individuals to explore fluctuations in metabolite levels at an individual level. MetaboVariation employs a Bayesian generalised linear model to flag individuals with intra-individual variations in their metabolite levels across multiple measurements. MetaboVariation models repeated metabolite levels as a function of explanatory variables while accounting for intra-individual variation. The posterior predictive distribution of metabolite levels at the individual level is available, and is used to flag individuals with observed metabolite levels outside the 95% highest posterior density prediction interval at a given time point. MetaboVariation was applied to a dataset containing metabolite levels for 20 metabolites, measured once every four months, in 164 individuals. A total of 28% of individuals with intra-individual variations in three or more metabolites were flagged. An R package for MetaboVariation was developed with an embedded R Shiny web application. To summarize, MetaboVariation has made considerable progress in developing strategies for analysing metabolomics data at the individual level, thus paving the way toward personalised healthcare.

The promise of new anti-obesity therapies arising from knowledge of genetic obesity traits

Obesity is a multifactorial and complex disease that often manifests in early childhood with a lifelong burden. Polygenic and monogenic obesity are driven by the interaction between genetic predisposition and environmental factors. Polygenic variants are frequent and confer small effect sizes. Rare monogenic obesity syndromes are caused by defined pathogenic variants in single genes with large effect sizes. Most of these genes are involved in the central nervous regulation of body weight; for example, genes of the leptin-melanocortin pathway. Clinically, patients with monogenic obesity present with impaired satiety, hyperphagia and pronounced food-seeking behaviour in early childhood, which leads to severe early-onset obesity. With the advent of novel pharmacological treatment options emerging for monogenic obesity syndromes that target the central melanocortin pathway, genetic testing is recommended for patients with rapid weight gain in infancy and additional clinical suggestive features. Likewise, patients with obesity associated with hypothalamic damage or other forms of syndromic obesity involving energy regulatory circuits could benefit from these novel pharmacological treatment options. Early identification of patients affected by syndromic obesity will lead to appropriate treatment, thereby preventing the development of obesity sequelae, avoiding failure of conservative treatment approaches and alleviating stigmatization of patients and their families.

Folate Related Pathway Gene Analysis Reveals a Novel Metabolic Variant Associated with Alzheimer’s Disease with a Change in Metabolic Profile

Metabolic disorders may be important potential causative pathways to Alzheimer’s disease (AD). Cerebrospinal fluid (CSF) decreasing output, raised intracranial pressure, and ventricular enlargement have all been linked to AD. Cerebral folate metabolism may be a key player since this is significantly affected by such changes in CSF, and genetic susceptibilities may exist in this pathway. In the current study, we aimed to identify whether any single nucleotide polymorphism (SNPs) affecting folate and the associated metabolic pathways were significantly associated with AD. We took a functional nutrigenomics approach to look for SNPs in genes for the linked folate, methylation, and biogenic amine neurotransmitter pathways. Changes in metabolism were found with the SNPs identified. An abnormal SNP in methylene tetrahydrofolate dehydrogenase 1 (MTHFD1) was significantly predictive of AD and associated with an increase in tissue glutathione. Individuals without these SNPs had normal levels of glutathione but significantly raised MTHFD1. Both changes would serve to decrease potentially neurotoxic levels of homocysteine. Seven additional genes were associated with Alzheimer’s and five with normal ageing. MTHFD1 presents a strong prediction of susceptibility and disease among the SNPs associated with AD. Associated physiological changes present potential biomarkers for identifying at-risk individuals.

UK food policy: implications for nutritionists

Implications of the ‘changing world’ for nutrition and nutritionists are considered, using the UK within a global context as an illustration. The first section summarises the slow recognition by policy makers of the significance of the changing world of food and nutrition. The second section ‘Food system stress is now at a critical level’ considers the present scale of global food system stress and the failure so far sufficiently to narrow the gap between evidence and policy change. The year 2021 was earmarked when three major UN conferences had the opportunity to chart food changes ahead. The third section ‘Multi-criteria analysis helps frame 21st century nutrition science’ proposes that multi-criteria analysis is an essential methodology for nutrition within this more complex policy world; nutrition studies can no long exclude social and environmental criteria. The penultimate section ‘Nutrition science can reconnect its life science, social and environmental nutrition traditions to contribute to new paradigm formation’ suggests that nutrition science can now recombine three traditions within its own history to address this complexity: social nutrition, environmental nutrition and life sciences. The final section ‘Priorities ahead’ concludes that this multi-criteria approach to nutrition offers new routes for science and policy influence. Five priorities are identified: (1) clarification of the features of a good food system; (2) new sustainable dietary guidelines which integrate different determinants of sustainability; (3) helping consumer engagement with change; (4) developing improved policy frameworks and (5) contributing to professional channels in these processes. In the UK, while the challenge of narrowing the gap between evidence, policy and change remains daunting, the risks of not attempting to improve the transition to an ecologically sound public health nutrition are even greater.

Future foods: Alternative proteins, food architecture, sustainable packaging, and precision nutrition

There are numerous challenges facing the modern food and agriculture industry that urgently need to be addressed, including feeding a growing global population, mitigating and adapting to climate change, decreasing pollution, waste, and biodiversity loss, and ensuring that people remain healthy. At the same time, foods should be safe, affordable, convenient, and delicious. The latest developments in science and technology are being deployed to address these issues. Some of the most important elements within this modern food design approach are encapsulated by the MATCHING model: Meat-reduced; Automation; Technology-driven; Consumer-centric; Healthy; Intelligent; Novel; and Globalization. In this review article, we focus on four key aspects that will be important for the creation of a new generation of healthier and more sustainable foods: emerging raw materials; structural design principles for creating innovative products; developments in eco-friendly packaging; and precision nutrition and customized production of foods. We also highlight some of the most important new developments in science and technology that are being used to create future foods, including food architecture, synthetic biology, nanoscience, and sensory perception.Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2022.2033683.

Multiomics Approach to Precision Sports Nutrition: Limits, Challenges, and Possibilities

Most sports nutrition guidelines are based on group average responses and professional opinion. Precision nutrition for athletes aims to improve the individualization of nutrition practices to optimize long-term performance and health. This is a 2-step process that first involves the acquisition of individual-specific, science-based information using a variety of sources including lifestyle and medical histories, dietary assessment, physiological assessments from the performance lab and wearable sensors, and multiomics data from blood, urine, saliva, and stool samples. The second step consists of the delivery of science-based nutrition advice, behavior change support, and the monitoring of health and performance efficacy and benefits relative to cost. Individuals vary widely in the way they respond to exercise and nutritional interventions, and understanding why this metabolic heterogeneity exists is critical for further advances in precision nutrition. Another major challenge is the development of evidence-based individualized nutrition recommendations that are embraced and efficacious for athletes seeking the most effective enhancement of performance, metabolic recovery, and health. At this time precision sports nutrition is an emerging discipline that will require continued technological and scientific advances before this approach becomes accurate and practical for athletes and fitness enthusiasts at the small group or individual level. The costs and scientific challenges appear formidable, but what is already being achieved today in precision nutrition through multiomics and sensor technology seemed impossible just two decades ago.

Precision Food Parenting: A Proposed Conceptual Model and Research Agenda

Precision medicine, nutrition and behavioral interventions are attempting to move beyond the specification of therapies applied to groups, since some people benefit, some do not and some are harmed by the same therapy. Instead, precision therapies are attempting to employ diverse sets of data to individualize or tailor interventions to optimize the benefits for the receiving individuals. The benefits to be achieved are mostly in the distant future, but the research needs to start now. While precision pediatric nutrition will combine diverse demographic, behavioral and biological variables to specify the optimal foods a child should eat to optimize health, precision food parenting will combine diverse parent and child psychosocial and related variables to identify the optimal parenting practices to help a specific child accept and consume the precision nutrition specified foods. This paper presents a conceptual overview and hypothetical model of factors we believe are needed to operationalize precision food parenting and a proposed research agenda to better understand the many specified relationships, how they change over the age of the child, and how to operationalize them to encourage food parenting practices most likely to be effective at promoting healthy child food choices.

Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Precision nutrition based on phenotypical traits and the (epi)genotype: nutrigenetic and nutrigenomic approaches for obesity care

PURPOSE OF REVIEW

The purpose of this article is to rationally review and critically appraise the current knowledge in the most relevant nongenetic and genetic factors influencing obesity predisposition. This information may be translated into the implementation of personalized nutrition approaches involving precision nutrigenetic and nutrigenomic strategies for obesity monitoring and weight management.

RECENT FINDINGS

The importance and influence of several nongenetic contributors to obesity onset and individual responses to weight-loss interventions have been highlighted including the role of age, sex or perinatal feeding and others related to an individual's lifestyle and modifiable. Nutrigenetic studies have analysed potential interactions between polymorphisms influencing energy homeostasis/body composition and dietary factors in relation to adiposity phenotypes and therapy responsiveness. A second approach comprises the Nutrigenomic analysis of gene expression modifications in response to the consumption of specific nutrients or dietary bioactive compounds, which may involve epigenetic mechanisms including deoxyribonucleic acid methylation and micro-ribonucleic acid expression profiles.

SUMMARY

Taken together, these findings encompass the importance of taking into account up-to-date advances in Nutrigenetic and Nutrigenomic hallmarks, globally analysing the risk of weight gain and related outcomes after following nutrition counselling, this contributing to improve obesity care considering phenotypical traits and the genetic make-up for precision obesity care.