Lunch eating predicts weight-loss effectiveness in carriers of the common allele at PERILIPIN1: the ONTIME (Obesity, Nutrigenetics, Timing, Mediterranean) study

Meal timing and its role in obesity and associated diseases

Meal timing emerges as a crucial factor influencing metabolic health that can be explained by the tight interaction between the endogenous circadian clock and metabolic homeostasis. Mistimed food intake, such as delayed or nighttime consumption, leads to desynchronization of the internal circadian clock and is associated with an increased risk for obesity and associated metabolic disturbances such as type 2 diabetes and cardiovascular diseases. Conversely, meal timing aligned with cellular rhythms can optimize the performance of tissues and organs. In this review, we provide an overview of the metabolic effects of meal timing and discuss the underlying mechanisms. Additionally, we explore factors influencing meal timing, including internal determinants such as chronotype and genetics, as well as external influences like social factors, cultural aspects, and work schedules. This review could contribute to defining meal-timing-based recommendations for public health initiatives and developing guidelines for effective lifestyle modifications targeting the prevention and treatment of obesity and associated metabolic diseases. Furthermore, it sheds light on crucial factors that must be considered in the design of future food timing intervention trials.

Chrononutrition in traditional European medicine-Ideal meal timing for cardiometabolic health promotion

Meal timing plays a crucial role for cardiometabolic health, given the circadian regulation of cardiometabolic function. However, to the best of our knowledge, no concept of meal timing exists in traditional European medicine (TEM). Therefore, in this narrative review, we aim to define the optimal time slot for energy intake and optimal energy distribution throughout the day in a context of TEM and explore further implications. By reviewing literature published between 2002 and 2022, we found that optimal timing for energy intake may be between 06:00 and 09:00, 12:00 and 14:00, and between 15:00 and 18:00, with high energy breakfast, medium energy lunch and low energy dinner and possibly further adjustments according to one's chronotype and genetics. Also, timing and distribution of energy intake may serve as a novel therapeutic strategy to optimize coction, a concept describing digestion and metabolism in TEM. Please cite this article as: Eberli NS, Colas L, Gimalac A. Chrononutrition in traditional European medicine-Ideal meal timing for cardiometabolic health promotion. J Integr Med. 2024; 22(2);115-125.

A genomics perspective of personalized prevention and management of obesity

This review discusses the landscape of personalized prevention and management of obesity from a nutrigenetics perspective. Focusing on macronutrient tailoring, we discuss the impact of genetic variation on responses to carbohydrate, lipid, protein, and fiber consumption. Our bioinformatic analysis of genomic variants guiding macronutrient intake revealed enrichment of pathways associated with circadian rhythm, melatonin metabolism, cholesterol and lipoprotein remodeling and PPAR signaling as potential targets of macronutrients for the management of obesity in relevant genetic backgrounds. Notably, our data-based in silico predictions suggest the potential of repurposing the SYK inhibitor fostamatinib for obesity treatment in relevant genetic profiles. In addition to dietary considerations, we address genetic variations guiding lifestyle changes in weight management, including exercise and chrononutrition. Finally, we emphasize the need for a refined understanding and expanded research into the complex genetic landscape underlying obesity and its management.

CETP and APOA2 polymorphisms are associated with weight loss and healthy eating behavior changes in response to digital lifestyle modifications

Response to digital healthcare lifestyle modifications is highly divergent. This study aimed to examine the association between single nucleotide polymorphism (SNP) genotypes and clinical efficacy of a digital healthcare lifestyle modification. We genotyped 97 obesity-related SNPs from 45 participants aged 18-39 years, who underwent lifestyle modification via digital cognitive behavioral therapy for obesity for 8 weeks. Anthropometric, eating behavior phenotypes, and psychological measures were analyzed before and after the intervention to identify their clinical efficacy. CETP (rs9939224) SNP significantly predict "super-responders" with greater body mass index (BMI) reduction (p = 0.028; GG - 2.91%, GT - 9.94%), while APOA2 (rs5082) appeared to have some potential for predicting "poor-responders" with lower BMI reduction (p = 0.005; AA - 6.17%, AG + 2.05%, and GG + 5.11%). These SNPs was also associated with significant differences in eating behavior changes, healthy diet proportions, health diet diversity, emotional and restrained eating behavior changes. Furthermore, classification using gene-gene interactions between rs9939224 and rs5082 significantly predicted the best response, with a greater decrease in BMI (p = 0.038; - 11.45% for the best response group (CEPT GT/TT × APOA2 AA) vs. + 2.62% for the worst response group (CEPT GG × APOA2 AG/GG)). CETP and APOA2 SNPs can be used as candidate markers to predict the efficacy of digital healthcare lifestyle modifications based on genotype-based precision medicine.Trial registration: NCT03465306, ClinicalTrials.gov. Registered March, 2018.

Challenges in Pharmacological Intervention in Perilipins (PLINs) to Modulate Lipid Droplet Dynamics in Obesity and Cancer

Perilipins (PLINs) are the most abundant proteins in lipid droplets (LD). These LD-associated proteins are responsible for upgrading LD from inert lipid storage structures to fully functional organelles, fundamentally integrated in the lipid metabolism. There are five distinct perilipins (PLIN1-5), each with specific expression patterns and metabolic activation, but all capable of regulating the activity of lipases on LD. This plurality creates a complex orchestrated mechanism that is directly related to the healthy balance between lipogenesis and lipolysis. Given the essential role of PLINs in the modulation of the lipid metabolism, these proteins can become interesting targets for the treatment of lipid-associated diseases. Since reprogrammed lipid metabolism is a recognized cancer hallmark, and obesity is a known risk factor for cancer and other comorbidities, the modulation of PLINs could either improve existing treatments or create new opportunities for the treatment of these diseases. Even though PLINs have not been, so far, directly considered for pharmacological interventions, there are many established drugs that can modulate PLINs activity. Therefore, the aim of this study is to assess the involvement of PLINs in diseases related to lipid metabolism dysregulation and whether PLINs can be viewed as potential therapeutic targets for cancer and obesity.

Genetics: A Starting Point for the Prevention and the Treatment of Obesity

Obesity is a common, serious, and costly disease. More than 1 billion people worldwide are obese-650 million adults, 340 million adolescents, and 39 million children. The WHO estimates that, by 2025, approximately 167 million people-adults and children-will become less healthy because they are overweight or obese. Obesity-related conditions include heart disease, stroke, type 2 diabetes, and certain types of cancer. These are among the leading causes of preventable, premature death. The estimated annual medical cost of obesity in the United States was nearly $173 billion in 2019 dollars. Obesity is considered the result of a complex interaction between genes and the environment. Both genes and the environment change in different populations. In fact, the prevalence changes as the result of eating habits, lifestyle, and expression of genes coding for factors involved in the regulation of body weight, food intake, and satiety. Expression of these genes involves different epigenetic processes, such as DNA methylation, histone modification, or non-coding micro-RNA synthesis, as well as variations in the gene sequence, which results in functional alterations. Evolutionary and non-evolutionary (i.e., genetic drift, migration, and founder's effect) factors have shaped the genetic predisposition or protection from obesity in modern human populations. Understanding and knowing the pathogenesis of obesity will lead to prevention and treatment strategies not only for obesity, but also for other related diseases.

Breakfast Size and Prevalence of Metabolic Syndrome in the European Prospective Investigation into Cancer and Nutrition (EPIC) Spanish Cohort

BACKGROUND

Recent evidence suggest that energy distribution during the daytimecould be a potential determinant for the development of metabolic syndrome (MetS).

OBJECTIVE

To cross-sectionally assess the association between breakfast size and the prevalence of MetS in Spanish adults.

METHODS

Our study included a subset of 3644 participants from the European Prospective Investigation into Cancer and Nutrition Spain study recontacted between 2017-2018. Information on diet, sociodemographic, lifestyle, sleep quality, and chronotype was collected using standardized questionnaires, while anthropometric and blood pressure data were measured in a face-to-face personal interview by a nurse. MetS was defined according to the Adult Treatment Panel III (ATPIII) definition by measuring serum levels of total cholesterol, tryglycerides and glucose. Breakfast size was calculated as: (energy from breakfast/total energy intake) * 2000 kcal. To evaluate the association between breakfast size and MetS prevalence, a multivariable logistic regression model adjusted by potential confounders was used to estimate OR and 95% CI.

RESULTS

Prevalence of MetS in our study was 40.7%. The mean breakfast size was 306.6 * 2000 kcal (15% of the total daily energy intake), with 14 (0.4%) participants skipping breakfast. Participants in the highest quartile of breakfast size had a lower MetS prevalence compared to participants in the lowest quartile (OR_Q4vsQ1 = 0.62; 95% CI = 0.51-0.76; p-trend < 0.001). No modification of the estimated ORs by sex, breakfast time, and number of eating occasions per day were observed.

CONCLUSION

Our results suggest that higher breakfast size is associated with lower prevalence of MetS in Spanish adults, supporting the importance of a high energy breakfast. Further prospective studies are necessary to confirm these findings.

The association of energy and macronutrient intake at breakfast and cardiovascular disease in Chinese adults: From a 14-year follow-up cohort study

Background

We aimed to examine the associations between energy and macronutrient intakes at breakfast and the incidence of cardiovascular events among Chinese adults.

Methods

There were 12,937 participants from the China Health and Nutrition Survey who met the study criteria and completed six rounds of questionnaires in 1997, 2000, 2004, 2006, 2009, and 2011. Combined weighing methods with 24-h dietary recall were used to measure dietary intake throughout the day. Intakes of macronutrients at breakfast were calculated using energy provided by nutrients as a percentage of breakfast energy. We calculated hazard ratios using a multivariable Cox frailty model with random intercepts to account for household clustering.

Results

During follow-up, we documented 453 (3.6 per 1,000 person-years) major cardiovascular events, 195 (1.5 per 1,000 person-years) myocardial infarctions, and 293 (2.3 per 1,000 person-years) strokes. In Chinese adults, more breakfast carbohydrates or less proteins intake was associated with the reduced risk of cardiovascular diseases. Especially for women, higher intake of breakfast carbohydrates was associated with a lower risk of major cardiovascular events (quintile 5 vs. quintile 1, HR 0.47 [95%CI 0.30-0.74]; p _trend = 0.0008) and stroke (quintile 5 vs. quintile 1, HR 0.48 [95%CI 0.26-0.88]; p _trend = 0.0006). Higher intake of breakfast proteins was associated with a higher risk of major cardiovascular events (quintile 5 vs. quintile 1, HR 1.77 [95%CI 1.12-2.79]; p _trend = 0.1162), myocardial infarction (quintile 5 vs. quintile 1, HR 2.49 [95%CI 1.21-5.11]; p _trend = 0.2641). There was a significant association between breakfast fat intake and cardiovascular diseases in the adult population, but less significant correlation was found in Chinese men or women. Breakfast fat intake was positively associated with the risk of major cardiovascular events (quintile 5 vs. quintile 1, HR 1.74 [95%CI 1.27-2.36]; p _trend = 0.0070), myocardial infarction (quintile 5 vs. quintile 1, HR 2.03 [95%CI 1.23-3.37]; p _trend = 0.0168), and stroke (quintile 5 vs. quintile 1, HR 1.64 [95%CI 1.12-2.41]; p _trend = 0.0732). There was a significant reduction in major cardiovascular events and stroke when breakfast energy intake was moderated, even if the independence of skipping breakfast.

Conclusion

High carbohydrate intake and low protein and fat intake at breakfast may contribute to cardiovascular health while maintaining a moderate energy intake.

Precision Nutrition: Recent Advances in Obesity

"Precision nutrition" is an emerging area of nutrition research that focuses on understanding metabolic variability within and between individuals and helps develop customized dietary plans and interventions to maintain optimal individual health. It encompasses nutritional genomic (gene-nutrient interactions), epigenetic, microbiome, and environmental factors. Obesity is a complex disease that is affected by genetic and environmental factors and thus a relevant target of precision nutrition-based approaches. Recent studies have shown significant associations between obesity phenotypes (body weight, body mass index, waist circumference, and central and regional adiposity) and genetic variants, epigenetic factors (DNA methylation and noncoding RNA), microbial species, and environment (sociodemographics and physical activity). Additionally, studies have also shown that the interactions between genetic variants, microbial metabolites, and epigenetic factors affect energy balance and adiposity. These include variants in FTO, MC4R, PPAR, APOA, and FADS genes, DNA methylation in CpG island regions, and specific miRNAs and microbial species such as Firmicutes, Bacteriodes, Clostridiales, etc. Similarly, studies have shown that microbial metabolites, folate, B-vitamins, and short-chain fatty acids interact with miRNAs to influence obesity phenotypes. With the advent of next-generation sequencing and analytical approaches, the advances in precision nutrition have the potential to lead to new paradigms, which can further lead to interventions or customized treatments specific to individuals or susceptible groups of individuals. This review highlights the recent advances in precision nutrition as applied to obesity and projects the importance of precision nutrition in obesity and weight management.

Late isocaloric eating increases hunger, decreases energy expenditure, and modifies metabolic pathways in adults with overweight and obesity

Late eating has been linked to obesity risk. It is unclear whether this is caused by changes in hunger and appetite, energy expenditure, or both, and whether molecular pathways in adipose tissues are involved. Therefore, we conducted a randomized, controlled, crossover trial (ClinicalTrials.gov NCT02298790) to determine the effects of late versus early eating while rigorously controlling for nutrient intake, physical activity, sleep, and light exposure. Late eating increased hunger (p < 0.0001) and altered appetite-regulating hormones, increasing waketime and 24-h ghrelin:leptin ratio (p < 0.0001 and p = 0.006, respectively). Furthermore, late eating decreased waketime energy expenditure (p = 0.002) and 24-h core body temperature (p = 0.019). Adipose tissue gene expression analyses showed that late eating altered pathways involved in lipid metabolism, e.g., p38 MAPK signaling, TGF-β signaling, modulation of receptor tyrosine kinases, and autophagy, in a direction consistent with decreased lipolysis/increased adipogenesis. These findings show converging mechanisms by which late eating may result in positive energy balance and increased obesity risk.

Extended Inter-Meal Interval Negatively Impacted the Glycemic and Insulinemic Responses after Both Lunch and Dinner in Healthy Subjects

This study aimed to investigate the glycemic and insulinemic effects of lunch timing based on a fixed feeding window, and the effects of apple preload on postprandial glucose and insulin responses after nutrient-balanced lunch and the subsequent high-fat dinner in healthy participants. Twenty-six participants completed four randomized, crossover experimental trials: (1) early standardized lunch at 12:00 (12S); (2) apple preload to 12S (12A+S); (3) late standardized lunch at 14:00 (14S); and (4) apple preload to 14S (14A+S); wherein twenty participants’ blood samples were collected for insulin analysis following the lunch trails. In each experimental trial, each participant equipped with a continuous glucose monitor (CGM) was provided with a standardized breakfast and a high-fat dinner to be consumed at 8:00 and 18:00, respectively. The late lunch (14S) resulted in significantly elevated glucose peak, delayed insulin peak time, decreased insulin sensitivity, and increased insulin resistance following the lunch; also decreased glycemic response following the subsequent dinner and larger blood glucose fluctuation over the 24-h period compared with the 12S. The 14A+S significantly reduced the glucose peak, the insulin peak time and the glycemic variability following the lunch, also the 24-h glycemic variability compared with the 14S. The insulin sensitivity was significantly improved in the 12A+S, compared with that of the 12S. In conclusion, the present study found that an extra 2-h inter-meal fasting before and after lunch resulted in elevated glycemic response in both macronutrient-balanced meal and high-fat meal in healthy subjects. The negative impact of a late lunch could be partly reversed by the apple preload, without a trade-off of insulin secretion.

Sex-Dependent Mediation of Leptin in the Association of Perilipin Polymorphisms with BMI and Plasma Lipid Levels in Children

Variations in the perilipin (PLIN) gene have been suggested to be associated with obesity and its related alterations, but a different nutritional status seems to contribute to differences in these associations. In our study, we examined the association of several polymorphisms at the PLIN locus with obesity and lipid profile in children, and then analyzed the mediation of plasma leptin levels on these associations. The single-nucleotide polymorphisms (SNPs) rs894160, rs1052700, and rs2304795 in PLIN1, and rs35568725 in PLIN2, were analyzed by RT-PCR in 1264 children aged 6–8 years. Our results showed a contrasting association of PLIN1 rs1052700 with apolipoprotein (Apo) A-I levels in boys and girls, with genotype TT carriers showing significantly higher Apo A-I levels in boys and significantly lower Apo A-I levels in girls. Significant associations of the SNP PLIN2 rs35568725 with high-density lipoprotein cholesterol (HDL-cholesterol), Apo A-I, and non-esterified fatty acids (NEFA) were observed in boys but not in girls. The associations of the SNPs studied with body mass index (BMI), NEFA, and Apo A-I in boys and girls were different depending on leptin concentration. In conclusion, we describe the mediation of plasma leptin levels in the association of SNPs in PLIN1 and PLIN2 with BMI, Apo A-I, and NEFA. Different leptin levels by sex may contribute to explain the sex-dependent association of the PLIN SNPs with these variables.

How Accurately Can We Recall the Timing of Food Intake? A Comparison of Food Times from Recall-Based Survey Questions and Daily Food Records

BACKGROUND

There currently are no standard, low-cost, and validated methods to assess the timing of food intake.

OBJECTIVES

The aim of this study was to validate simple, recall-based questions that can characterize food timing in free-living populations.

METHODS

The concordance between recall-based survey questions and food times estimated from multiple daily food records was assessed in 249 generally healthy, free-living adults from the Shift Work, Heredity, Insulin, and Food Timing (SHIFT) Study. At baseline, participants were asked: "At what time do you first start and stop eating on weekdays/workdays and weekends/non-workdays?" and "At what time do you have your main meal on weekdays/workdays and weekends/non-workdays?" Participants were then asked to complete ≤14 d of food records noting the start time of each eating occasion. The timing of the first, last, and main (largest percentage calories) eating occasions were determined from food records. Wilcoxon matched pairs signed rank and Kendall's coefficient of concordance were used to compare differences and determine agreements between the methods for these food timing parameters, as well as for the midpoint between first and last eating occasion.

RESULTS

Eating occasions on work and free days showed significant agreements between the 2 methods, except for the main eating occasion on free days. Significant agreements were generally modest and ranged from 0.16 (workdays main eating occasion) to 0.45 (workdays first eating occasion). Generally, times based on recall were later than those estimated from food records, and the differences in estimated times were smaller on workdays compared with free days, and smaller for the first compared with the last eating occasion. Main eating occasions from food records often varied between lunch and dinner times, contributing to low concordance with recalled times.

CONCLUSIONS

Modest agreements were found between food times derived from simple, recall-based survey questions and food times estimated from multiple-day food records. Single administration of these questions can effectively characterize the overall timing of eating occasions within a population for chrononutrition research purposes.

A Clinical-Genetic Score for Predicting Weight Loss after Bariatric Surgery: The OBEGEN Study

Around 30% of the patients that undergo bariatric surgery (BS) do not reach an appropriate weight loss. The OBEGEN study aimed to assess the added value of genetic testing to clinical variables in predicting weight loss after BS. A multicenter, retrospective, longitudinal, and observational study including 416 patients who underwent BS was conducted (Clinical.Trials.gov- NCT02405949). 50 single nucleotide polymorphisms (SNPs) from 39 genes were examined. Receiver Operating Characteristic (ROC) curve analysis were used to calculate sensitivity and specificity. Satisfactory response to BS was defined as at nadir excess weight loss >50%. A good predictive model of response [area under ROC of 0.845 (95% CI 0.805–0.880), p < 0.001; sensitivity 90.1%, specificity 65.5%] was obtained by combining three clinical variables (age, type of surgery, presence diabetes) and nine SNPs located in ADIPOQ, MC4R, IL6, PPARG, INSIG2, CNR1, ELOVL6, PLIN1 and BDNF genes. This predictive model showed a significant higher area under ROC than the clinical score (p = 0.0186). The OBEGEN study shows the key role of combining clinical variables with genetic testing to increase the predictability of the weight loss response after BS. This finding will permit us to implement a personalized medicine which will be associated with a more cost-effective clinical practice.

Joint temporal dietary and physical activity patterns: associations with health status indicators and chronic diseases

BACKGROUND

Diet and physical activity (PA) are independent risk factors for obesity and chronic diseases including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). The temporal sequence of these exposures may be used to create patterns with relations to health status indicators.

OBJECTIVES

The objectives were to create clusters of joint temporal dietary and PA patterns (JTDPAPs) and to determine their association with health status indicators including BMI, waist circumference (WC), fasting plasma glucose, glycated hemoglobin, triglycerides, HDL cholesterol, total cholesterol, blood pressure, and disease status including obesity, T2DM, and MetS in US adults.

METHODS

A 24-h dietary recall and random day of accelerometer data of 1836 participants from the cross-sectional NHANES 2003-2006 data were used to create JTDPAP clusters by constrained dynamic time warping, coupled with a kernel k-means clustering algorithm. Multivariate regression models determined associations between the 4 JTDPAP clusters and health and disease status indicators, controlling for potential confounders and adjusting for multiple comparisons.

RESULTS

A JTDPAP cluster with proportionally equivalent energy consumed at 2 main eating occasions reaching ≤1600 and ≤2200 kcal from 11:00 to 13:00 and from 17:00 to 20:00, respectively, and the highest PA counts among 4 clusters from 08:00 to 20:00, was associated with significantly lower BMI (P < 0.0001), WC (P = 0.0001), total cholesterol (P = 0.02), and odds of obesity (OR: 0.2; 95% CI: 0.1, 0.5) than a JTDPAP cluster with proportionally equivalent energy consumed reaching ≤1600 and ≤1800 kcal from 11:00 to 14:00 and from 17:00 to 21:00, respectively, and high PA counts from 09:00 to 12:00.

CONCLUSIONS

The joint temporally patterned sequence of diet and PA can be used to cluster individuals with meaningful associations to BMI, WC, total cholesterol, and obesity. Temporal patterns hold promise for future development of lifestyle patterns that integrate additional temporal and contextual activities.

Daily Rhythm of Fractal Cardiac Dynamics Links to Weight Loss Resistance: Interaction with CLOCK 3111T/C Genetic Variant

The effectiveness of weight loss treatment displays dramatic inter-individual variabilities, even with well-controlled energy intake/expenditure. This study aimed to determine the association between daily rhythms of cardiac autonomic control and weight loss efficiency and to explore the potential relevance to weight loss resistance in humans carrying the genetic variant C at CLOCK 3111T/C. A total of 39 overweight/obese Caucasian women (20 CLOCK 3111C carriers and 19 non-carriers) completed a behaviour–dietary obesity treatment of ~20 weeks, during which body weight was assessed weekly. Ambulatory electrocardiographic data were continuously collected for up to 3.5 days and used to quantify the daily rhythm of fractal cardiac dynamics (FCD), a non-linear measure of autonomic function. FCD showed a 24 h rhythm (p < 0.001). Independent of energy intake and physical activity level, faster weight loss was observed in individuals with the phase (peak) of the rhythm between ~2–8 p.m. and with a larger amplitude. Interestingly, the phase effect was significant only in C carriers (p = 0.008), while the amplitude effect was only significant in TT carriers (p < 0.0001). The daily rhythm of FCD and CLOCK 3111T/C genotype is linked to weight loss response interactively, suggesting complex interactions between the genetics of the circadian clock, the daily rhythm of autonomic control, and energy balance control.

Infancy and Childhood Obesity Grade Predicts Weight Loss in Adulthood: The ONTIME Study

We examined the relationships between intergenerational obesity, weight and size at birth, and obesity from infancy to adolescence with weight loss in response to a dietary intervention. We studied 4264 participants (3369 women; mean age 41.5 ± 12.9 years) of the ONTIME study. Participants followed a weight-loss treatment based on a Mediterranean diet. Associations between grandparental and parental obesity grade, birth weight and size, and obesity grade in infancy, childhood and adolescence with total weight loss in response to treatment were assessed, using multivariate linear regression models. A lower weight loss (kg) in response to treatment was found among participants who were obese during infancy (beta coefficient -2.13 kg; 95% CI, -3.96, -0.30; p = 0.023). Furthermore, obesity during infancy and also during childhood was associated with a slower weekly rate of weight loss during treatment (p < 0.05). In conclusion, obesity in infancy and in childhood impairs the weight-loss response to dietary treatments in adulthood. Tackling obesity throughout early life may improve the effectiveness of weight-loss interventions in adulthood.

Meal Timing of Subtypes of Macronutrients Consumption With Cardiovascular Diseases: NHANES, 2003 to 2016

CONTEXT

Emerging evidence suggests that not only the quantity but also the quality and food sources of macronutrients plays an important role in CVD. However, limited studies have examined the association of meal timing of different quality of macronutrients with CVD risk.

OBJECTIVE

This study aimed to examine the association of subtypes of macronutrient consumption at dinner vs breakfast with cardiovascular diseases (CVD).

METHODS

A total of 27 911 participants from the National Health and Nutrition Examination Survey (2003-2016) were included. The differences of subtypes of macronutrients at dinner vs breakfast (Δratio) were categorized into quintiles. Multiple logistic regression models and isocaloric substitution effects of subtypes were performed.

RESULTS

After adjustment of a variety of covariates, participants in the highest quintile of the Δratio of low-quality carbohydrates had a higher risk of angina (odds ratio [OR] = 1.63; 95% CI, 1.16-2.29) (Pfor trend = .007) and heart attack (OR = 1.47; 95% CI, 1.13-1.93) (Pfor trend = .068) compared with the lowest quintile. The highest quintile of the Δratio of animal protein had a higher risk of coronary heart disease (OR = 1.44; 95% CI, 1.06-1.95) (Pfor trend = .014) and angina (OR = 1.44; 95% CI, 1.01-2.07) (Pfor trend = .047). For the Δratio of unsaturated fatty acid (USFA), the highest quintile of the Δratio of USFA was related to lower stroke risk (OR = 0.76; 95% CI, 0.58-0.99) (Pfor trend = .049). Isocaloric substitution of low-quality carbohydrates/animal protein by high-quality carbohydrates/plant protein at dinner reduced CVD risk by around 10%.

CONCLUSION

This study indicated that overconsumption of low-quality carbohydrates and animal protein at dinner rather than breakfast was significantly associated with higher CVD risk and USFA consumption at dinner related to lower CVD risk among US adults. Substitution of low-quality carbohydrates or animal protein by high-quality carbohydrates or plant protein at dinner could reduce CVD risk.

The "Virtual Digital Twins" Concept in Precision Nutrition

Nutritional and lifestyle changes remain at the core of healthy aging and disease prevention. Accumulating evidence underscores the impact of genetic, metabolic, and host gut microbial factors on individual responses to nutrients, paving the way for the stratification of nutritional guidelines. However, technological advances that incorporate biological, nutritional, lifestyle, and health data at an unprecedented scale and depth conceptualize a future where preventative dietary interventions will exceed stratification and will be highly individualized. We herein discuss how genetic information combined with longitudinal metabolomic, immune, behavioral, and gut microbial parameters, and bioclinical variables could define a digital replica of oneself, a "virtual digital twin," which could serve to guide nutrition in a personalized manner. Such a model may revolutionize the management of obesity and its comorbidities, and provide a pillar for healthy aging.

Nutrigenetics-personalized nutrition in obesity and cardiovascular diseases

Epidemiological data support the view that both obesity and cardiovascular diseases (CVD) account for a high proportion of total morbidity and mortality in adults throughout the world. Obesity and CVD have complex interplay mechanisms of genetic and environmental factors, including diet. Nutrition is an environmental factor and it has a predominant and recognizable role in health management and in the prevention of obesity and obesity-related diseases, including CVD. However, there is a marked variation in CVD in patients with obesity and the same dietary pattern. The different genetic polymorphisms could explain this variation, which leads to the emergence of the concept of nutrigenetics. Nutritional genomics or nutrigenetics is the science that studies and characterizes gene variants associated with differential response to specific nutrients and relating this variation to various diseases, such as CVD related to obesity. Thus, the personalized nutrition recommendations, based on the knowledge of an individual's genetic background, might improve the outcomes of a specific dietary intervention and represent a new dietary approach to improve health, reducing obesity and CVD. Given these premises, it is intuitive to suppose that the elucidation of diet and gene interactions could support more specific and effective dietary interventions in both obesity and CVD prevention through personalized nutrition based on nutrigenetics. This review aims to briefly summarize the role of the most important genes associated with obesity and CVD and to clarify the knowledge about the relation between nutrition and gene expression and the role of the main nutrition-related genes in obesity and CVD.

Is the timing of food intake a potential indicator of low weight loss responders? A secondary analysis of three weight loss studies

Individual variability in weight loss in response to a weight loss intervention is commonly observed. Recently, the timing of food intake has been identified as one possible factor implicated in obesity and weight loss. The objective of this study was to further characterize low weight loss responders by assessing the pre-diet distribution of daily energy and macronutrient intakes. A pooled cohort of men and women (n = 122; aged 39.1 ± 8.2 years; body mass index [BMI] 33.1 ± 3.8 kg/m² ) who participated in a 12 to 15 week energy-restricted intervention (-500 to -700 kcal/d) were included in this study. Participants were categorized into two weight loss groups (ie, low [-1.3 ± 2.3 kg] and high [-6.1 ± 2.1 kg] weight loss). Food intake and distribution of energy and macronutrient intakes were assessed using a 3-day food record at baseline. The daily distribution of energy intake (% of total energy intake) was similar in the two weight loss groups with the exception of the low weight loss group who consumed a slightly lower proportion of their total energy intake before 9:00 am compared with the high weight loss group (12.5% ± 5.8% vs 15.0% ± 6.6%, respectively, P = .03). In the low weight loss group, the percentage of energy intake consumed after 8:00 pm was positively associated with total energy intake (r = 0.27, P = .04). The results of this study suggest that the timing of food intake measured prior to a weight loss intervention does not permit the characterization of low weight loss responders.

Precision (Personalized) Nutrition: Understanding Metabolic Heterogeneity

People differ in their requirements for and responses to nutrients and bioactive molecules in the diet. Many inputs contribute to metabolic heterogeneity (including variations in genetics, epigenetics, microbiome, lifestyle, diet intake, and environmental exposure). Precision nutrition is not about developing unique prescriptions for individual people but rather about stratifying people into different subgroups of the population on the basis of biomarkers of the above-listed sources of metabolic variation and then using this stratification to better estimate the different subgroups’ dietary requirements, thereby enabling better dietary recommendations and interventions. The hope is that we will be able to subcategorize people into ever-smaller groups that can be targeted in terms of recommendations, but we will never achieve this at the individual level, thus, the choice of precision nutrition rather than personalized nutrition to designate this new field. This review focuses mainly on genetically related sources of metabolic heterogeneity and identifies challenges that need to be overcome to achieve a full understanding of the complex interactions between the many sources of metabolic heterogeneity that make people differ from one another in their requirements for and responses to foods. It also discusses the commercial applications of precision nutrition.

Modeling of an integrative prototype based on genetic, phenotypic, and environmental information for personalized prescription of energy-restricted diets in overweight/obese subjects

BACKGROUND

Interindividual variability in weight loss and metabolic responses depends upon interactions between genetic, phenotypic, and environmental factors.

OBJECTIVE

We aimed to model an integrative (nutri) prototype based on genetic, phenotypic, and environmental information for the personalized prescription of energy-restricted diets with different macronutrient distribution.

METHODS

A 4-mo nutritional intervention was conducted in 305 overweight/obese volunteers involving 2 energy-restricted diets (30% restriction) with different macronutrient distribution: a moderately high-protein (MHP) diet (30% proteins, 30% lipids, and 40% carbohydrates) and a low-fat (LF) diet (22% lipids, 18% proteins, and 60% carbohydrates). A total of 201 subjects with good dietary adherence were genotyped for 95 single nucleotide polymorphisms (SNPs) related to energy homeostasis. Genotyping was performed by targeted next-generation sequencing. Two weighted genetic risk scores for the MHP (wGRS1) and LF (wGRS2) diets were computed using statistically relevant SNPs. Multiple linear regression models were performed to estimate percentage BMI decrease depending on the dietary macronutrient composition.

RESULTS

After energy restriction, both the MHP and LF diets induced similar significant decreases in adiposity, body composition, and blood pressure, and improved the lipid profile. Furthermore, statistically relevant differences in anthropometric and biochemical markers depending on sex and age were found. BMI decrease in the MHP diet was best predicted at ∼28% (optimism-corrected adjusted R2 = 0.279) by wGRS1 and age, whereas wGRS2 and baseline energy intake explained ∼29% (optimism-corrected adjusted R2 = 0.287) of BMI decrease variability in the LF diet. The incorporation of these predictive models into a decision algorithm allowed the personalized prescription of the MHP and LF diets.

CONCLUSIONS

Different genetic, phenotypic, and exogenous factors predict BMI decreases depending on the administration of a hypocaloric MHP diet or an LF diet. This holistic approach may help to personalize dietary advice for the management of excessive body weight using precision nutrition variables.This trial was registered at clinicaltrials.gov as NCT02737267.

Timing of Breakfast, Lunch, and Dinner. Effects on Obesity and Metabolic Risk

(1) Background: Eating is fundamental to survival. Animals choose when to eat depending on food availability. The timing of eating can synchronize different organs and tissues that are related to food digestion, absorption, or metabolism, such as the stomach, gut, liver, pancreas, or adipose tissue. Studies performed in experimental animal models suggest that food intake is a major external synchronizer of peripheral clocks. Therefore, the timing of eating may be decisive in fat accumulation and mobilization and affect the effectiveness of weight loss treatments. (2) Results: We will review multiple studies about the timing of the three main meals of the day, breakfast, lunch and dinner, and its potential impact on metabolism, glucose tolerance, and obesity-related factors. We will also delve into several mechanisms that may be implicated in the obesogenic effect of eating late. Conclusion: Unusual eating time can produce a disruption in the circadian system that might lead to unhealthy consequences.

Timing of Food Intake: Identifying Contributing Factors to Design Effective Interventions

Observations that mistimed food intake may have adverse metabolic health effects have generated interest in personalizing food timing recommendations in interventional studies and public health strategies for the purpose of disease prevention and improving overall health. Small, controlled, and short-termed intervention studies suggest that food timing may be modified as it is presumed to be primarily regulated by choice. Identifying and evaluating social and biological factors that explain variability in food timing may determine whether changes in food timing in uncontrolled, free-living environments are sustainable in the long term, and may facilitate design of successful food timing-based interventions. Based on a comprehensive literature search, we summarize 1) cultural and environmental factors; 2) behavioral and personal preference factors; and 3) physiological factors that influence the time when people consume foods. Furthermore, we 1) highlight vulnerable populations who have been identified in experimental and epidemiological studies to be at risk of mistimed food intake and thus necessitating intervention; 2) identify currently used food timing assessment tools and their limitations; and 3) indicate other important considerations for the design of food timing interventions based on successful strategies that address timing of other lifestyle behaviors. Conclusions drawn from this overview may help design practical food timing interventions, develop feasible public health programs, and establish guidelines for effective lifestyle recommendations for prevention and treatment of adverse health outcomes attributed to mistimed food intake.

Heritability of the timing of food intake

BACKGROUND & AIMS

While environmental factors are presumed to be primary drivers of food timing, preliminary evidence suggests that genetics may be an additional determinant. The aim was to explore the relative contribution of genetics and environmental factors to variation in the timing of food intake in a Spanish twin population. Because chronotype, bedtime and wake time are related to food timing, covariance with food timing was further assessed.

METHODS

In this observational study, 53 pairs of adult (mean (SD) = 52 (6.03) years) female twins (28 monozygotic; 25 dizygotic) were recruited from the Murcia Twin Register. Zygosity was determined by DNA-testing. Timing of the three main meals of the day was assessed via 7-day dietary records, and the midpoint of food intake was computed by calculating the midpoint between breakfast and dinner times. Chronotype, bedtime and wake time were self-reported. Heritability of food timing and related traits were estimated by comparing monozygotic and dizygotic twin correlations and fitting genetic structural equation models to measured variables.

RESULTS

We observed genetic influences for food timing, with highest heritability for the midpoint of food intake (64%) in an overweight/obese population (BMI = 26.01 ± 3.77). Genetic factors contributed to a higher degree to the timing of breakfast (56%) than the timing of lunch (38%) or dinner (n.s.). Similarly, heritability estimates were larger in related behavioral traits earlier on in the day (i.e. wake time, (55%)), than those later on in the day (i.e. bedtime, (38%)). Bivariate analyses revealed a significant genetic overlap between food timing and bedtime and chronotype (rG between 0.78 and 0.91).

CONCLUSIONS

Genetic influences appear to account for a significant proportion of the variability in food timing, particularly breakfast. Thus, interventions related to food timing may be more effective when targeting afternoon/evening traits, such as lunch or dinner times. Furthermore, our data suggest shared genetic architecture underlying food timing and phenotypically related traits.

CLINICAL TRIAL

NCT03059576. https://clinicaltrials.gov/ct2/show/NCT03059576.

The Influence of Meal Frequency and Timing on Health in Humans: The Role of Fasting

The influence of meal frequency and timing on health and disease has been a topic of interest for many years. While epidemiological evidence indicates an association between higher meal frequencies and lower disease risk, experimental trials have shown conflicting results. Furthermore, recent prospective research has demonstrated a significant increase in disease risk with a high meal frequency (≥6 meals/day) as compared to a low meal frequency (1⁻2 meals/day). Apart from meal frequency and timing we also have to consider breakfast consumption and the distribution of daily energy intake, caloric restriction, and night-time eating. A central role in this complex scenario is played by the fasting period length between two meals. The physiological underpinning of these interconnected variables may be through internal circadian clocks, and food consumption that is asynchronous with natural circadian rhythms may exert adverse health effects and increase disease risk. Additionally, alterations in meal frequency and meal timing have the potential to influence energy and macronutrient intake.A regular meal pattern including breakfast consumption, consuming a higher proportion of energy early in the day, reduced meal frequency (i.e., 2⁻3 meals/day), and regular fasting periods may provide physiological benefits such as reduced inflammation, improved circadian rhythmicity, increased autophagy and stress resistance, and modulation of the gut microbiota.

Potential circadian and circannual rhythm contributions to the obesity epidemic in elementary school age children

Children gain weight at an accelerated rate during summer, contributing to increases in the prevalence of overweight and obesity in elementary-school children (i.e., approximately 5 to 11 years old in the US). Int J Behav Nutr Phys Act 14:100, 2017 explained these changes with the "Structured Days Hypothesis" suggesting that environmental changes in structure between the school year and the summer months result in behavioral changes that ultimately lead to accelerated weight gain. The present article explores an alternative explanation, the circadian clock, including the effects of circannual changes and social demands (i.e., social timing resulting from societal demands such as school or work schedules), and implications for seasonal patterns of weight gain. We provide a model for understanding the role circadian and circannual rhythms may play in the development of child obesity, a framework for examining the intersection of behavioral and biological causes of obesity, and encouragement for future research into bio-behavioral causes of obesity in children.

Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study

The composition of the diet (what we eat) has been widely related to the microbiota profile. However, whether the timing of food consumption (when we eat) influences microbiota in humans is unknown. A randomized, crossover study was performed in 10 healthy normal-weight young women to test the effect of the timing of food intake on the human microbiota in the saliva and fecal samples. More specifically, to determine whether eating late alters daily rhythms of human salivary microbiota, we interrogated salivary microbiota in samples obtained at 4 specific time points over 24 h, to achieve a better understanding of the relationship between food timing and metabolic alterations in humans. Results revealed significant diurnal rhythms in salivary diversity and bacterial relative abundance ( i.e., TM7 and Fusobacteria) across both early and late eating conditions. More importantly, meal timing affected diurnal rhythms in diversity of salivary microbiota toward an inverted rhythm between the eating conditions, and eating late increased the number of putative proinflammatory taxa, showing a diurnal rhythm in the saliva. In a randomized, crossover study, we showed for the first time the impact of the timing of food intake on human salivary microbiota. Eating the main meal late inverts the daily rhythm of salivary microbiota diversity which may have a deleterious effect on the metabolism of the host.-Collado, M. C., Engen, P. A., Bandín, C., Cabrera-Rubio, R., Voigt, R. M., Green, S. J., Naqib, A., Keshavarzian, A., Scheer, F. A. J. L., Garaulet, M. Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study.

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.