Lifestyle Genomics最新文献

Introduction: This study aimed to determine the frequency of genetic testing awareness, the number of individuals who have undergone genetic testing, and the subsequent behavior changes following testing.

Methods: The analysis utilized recent data from the Health Information National Trends Survey (HINTS) 6, collected between March and September 2022, from a diverse sample of adults aged 18 and older. Logistic regressions were applied to assess predictors of outcome variables. A p value of < 0.05 was considered statistically significant.

Results: Among the 4,631 respondents, 81.6% reported being aware of genetic testing, 28.7% (n = 1,327) had undergone some form of testing, and 16.3% of those tested reported making behavioral changes based on their results. Ancestry-related genetic testing was the most widely recognized and frequently utilized. However, behavioral changes were most commonly reported among individuals who underwent disease-specific genetic testing, especially those who perceived themselves to be at high risk, were motivated to take preventive measures, and received assistance in understanding their results. Within this subgroup, lifestyle modification was the most frequently cited change, followed by adjustments in dietary supplement use, increased health screenings, and changes to medications. Additionally, individuals from racial and ethnic minority groups were more likely than non-Hispanic white respondents to undergo specific types of genetic testing and to report behavior changes in response to the findings.

Conclusion: The study highlights an increasing awareness and involvement in genetic testing, though a smaller percentage of individuals have altered their behavior based on the test results. Additionally, the study identifies genetic literacy as a key factor in predicting behavior changes.

Background: Precision nutrition is based on the integration of individual's phenotypical and biological characteristics including genetic variants, epigenetic marks, gut microbiota profiles, and metabolite fingerprints as well as medical history, lifestyle practices, and environmental and cultural factors. Thus, nutriomics areas including nutrigenomics, nutrigenetics, nutriepigenetics, nutrimetabolomics, and nutrimetagenomics have emerged to comprehensively understand the complex interactions between nutrients, diet, and the human body's molecular processes through precision nutrition.

Summary: This document from the Ibero-American Network of Nutriomics and Precision Nutrition (RINN22; https://rinn22.com/) provides a comprehensive overview of the concepts of precision nutrition approaches to guide their application in clinical and public health as well as establish the position of RINN22 regarding the current and future state of precision nutrition.

Key messages: The progress and participation of nutriomics to precision nutrition is an essential pillar for addressing diet-related diseases and developing innovative managing strategies, which will be promoted by advances in bioinformatics, machine learning, and integrative software, as well as the description of specific novel biomarkers. In this context, synthesizing and critically evaluating the latest developments, potential applications, and future needs in the field of nutrition is necessary with a holistic perspective, incorporating progress in omics technologies aimed at precision nutrition interventions. This approach must address and confront healthy, social, food security, physically active lifestyle, sanitation, and sustainability challenges with preventive, participatory, and predictive strategies of personalized, population, and planetary nutrition for a precision tailored health.

Reviewers:

Introduction: Excess fructose intake has been linked to increased risk of dyslipidemia, insulin resistance, hyperuricemia, inflammation, and obesity. In this human study, we investigated if serum C-reactive protein (CRP) concentrations change after fructose consumption, and whether genetic variants and obesity status influence this change.

Methods: Blood was drawn before and at four time points after administration of a fructose load (n = 57). Serum concentrations of CRP were measured, and 11 single nucleotides polymorphisms (SNPs) (rs1205, rs1417938, rs1470515, rs3093068, rs6588158, rs16842568, rs2259820, rs157581, rs2794521, rs3093062, rs17700633), previously associated with serum CRP were genotyped and assessed for their association with CRP levels.

Results: Participants identifying as White (n = 37) had higher mean CRP levels across all time points compared to those identifying as Black (n = 20). Participants with obesity (body mass index ≥30 kg/m2) (n = 25) were younger and had higher mean CRP levels throughout the study period compared to those without (n = 32). All SNPs were in Hardy-Weinberg equilibrium and their effect allele frequencies ranged between 11 and 96%. Baseline CRP was associated with CRP SNPs rs1417938 and rs2794521 (p < 0.005); rs2794521 was also associated with CRP response to fructose challenge (p < 0.005). The variability in response to fructose and genetic associations was mainly observed in individuals without obesity. Obesity status was associated with early changes in CRP (0-30 min and 30-60 min) whereas CRP SNPs were associated with later changes (60-120 min and 120-180 min).

Conclusion: Changes in serum CRP were associated with obesity status or SNPs based on the time elapsed since fructose ingestion. Larger studies are needed to confirm and validate these associations.

In the article by Sierra-Ruelas et al. entitled "Uncoupling Proteins Variants Are Linked to Hypercholesterolemia and Abdominal Obesity in Metabolically Unhealthy Women" [Lifestyle Genomics. 2025;18:27-35; https://doi.org/10.1159/000543484], there is an error introduced during production which resulted in the different superscript letters (b, c and d) in Table 1 being changed to the same superscript "a" value.The original article has been updated.

Introduction: Prior work in predominantly European ancestry populations has explained how the risk associated with demographic, lifestyle, and health factors differs with underlying genetic susceptibility to type 2 diabetes (T2D), but less is known about these relationships in Black Americans.

Methods: We used covariate-adjusted logistic regression models of T2D to examine interactions between a published trans-ancestry derived T2D polygenic risk score (PRS) and various demographic, lifestyle, and health-related factors among 28,251 self-identified Black Americans from six cohort studies.

Results: The results are generally consistent with prior work in White populations. The PRS showed a significant interaction with body mass index, with a greater effect on T2D risk in individuals who were leaner (pinteraction = 0.038).

Conclusion: These results contribute to understanding the relationship between genetics and other T2D risk factors in Black Americans who have a high burden of T2D, potentially informing targeted prevention strategies.