Macronutrient composition of plant-based diets and breast cancer risk: the E3N prospective cohort study.

PURPOSE: Recent evidence suggests that plant-based diets may reduce the risk of breast cancer (BC). However, the macronutrient composition of plant-based diets and its potential impact on BC risk has not been well explored. This analysis investigated the association of macronutrient composition with BC risk across a spectrum of plant-based diet indexes using a multidimensional approach. DESIGN: This study followed 64,655 participants from the Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale (E3N) cohort from 1993 to 2014. Diets were evaluated using validated 208-item diet history questionnaires at baseline (1993) and follow-up (2005), to calculate adherence to the overall plant-based diet (PDI), healthful plant-based diet (hPDI), and unhealthful plant-based diet (uPDI). The association of macronutrient composition with BC risk was assessed via generalized additive time-dependent Cox models across different levels of these indexes. Response surfaces were generated to visualize compositional associations at the 25th, 50th, and 75th percentile of each index (low, moderate, and high). RESULTS: A total of 3,932 incident BC cases were identified during the 21-year follow-up. There was a significant association between macronutrient composition and BC risk for hPDI, uPDI, and PDI (all P < 0.001). Akaike information criterion favored the hPDI model for characterizing the association between macronutrients and BC. BC risk was highest for individuals with a lower hPDI score who also consumed a diet containing lower protein (10%), lower carbohydrate (35%), and higher fat (55%). The lowest risk of BC was observed in those with higher hPDI scores with the lowest intake of protein (10%). At higher PDI and uPDI, diets containing higher protein (30%) and fat (45%) had the highest BC risk. CONCLUSION: These results demonstrate a complex relationship between macronutrient composition, plant-based diet quality, and BC risk. Further research is needed to examine specific foods that may be driving these associations. REGISTRY: The protocol is registered at clinicaltrials.gov as NCT03285230.

Mice Regulate Dietary Amino Acid Balance and Energy Intake by Selecting between Complementary Protein Sources.

BACKGROUND: A balanced intake of protein and constituent amino acids (AAs) requires adjustments to total food intake (protein leverage [PL]) and food selection to balance deficits and excesses (complementary feeding). We provided mice with choices of casein and whey, 2 protein sources that are complementary in AA balance, across a range of protein concentrations (P%) of digestible energy (DE). OBJECTIVES: We aimed to determine if: 1) PL operates similarly for casein and whey; 2) one protein source is preferred at control P%; 3) the preference changes as P% falls; and 4) AA intakes under control and low P% levels identify AAs that drive changes in protein selection. METHODS: Food intake and plasma fibroblast growth factor-21 (FGF21) concentrations were measured in mice at various P% (P7.5%-P33%). For direct comparisons, defined diets were used in which the protein source was either casein or whey. In food choice studies, mice had access to foods in which both casein and whey were provided at the same P% level at the same time. RESULTS: PL operated at different P% thresholds in casein (13%)- and whey (10%)-based diets, and the magnitude of PL was greater for casein. Although mice preferred casein under control conditions (P23%), a pronounced preference shift to whey occurred as P% fell to P13% and P10%. At low P%, increases in food intake were accompanied by increases in plasma FGF21, a protein hunger signal. Among AAs deficient in casein and enriched in whey, the intake of Cys was the most invariant as P% changed between P23% and P10%, appearing to drive the switch in protein preference. CONCLUSIONS: Mice selected between complementary protein sources, casein and whey, achieving stable total energy intake and regulated intake of AAs as P% varied. Supplementation of low P% casein diets with one whey-enriched AA, Cys, suppressed plasma FGF21 and total food intake.

Dietary macronutrient composition impacts gene regulation in adipose tissue.

Diet is a key lifestyle component that influences metabolic health through several factors, including total energy intake and macronutrient composition. While the impact of caloric intake on gene expression and physiological phenomena in various tissues is well described, the influence of dietary macronutrient composition on these parameters is less well studied. Here, we use the Nutritional Geometry framework to investigate the role of macronutrient composition on metabolic function and gene regulation in adipose tissue. Using ten isocaloric diets that vary systematically in their proportion of energy from fat, protein, and carbohydrates, we find that gene expression and splicing are highly responsive to macronutrient composition, with distinct sets of genes regulated by different macronutrient interactions. Specifically, the expression of many genes associated with Bardet-Biedl syndrome is responsive to dietary fat content. Splicing and expression changes occur in largely separate gene sets, highlighting distinct mechanisms by which dietary composition influences the transcriptome and emphasizing the importance of considering splicing changes to more fully capture the gene regulation response to environmental changes such as diet. Our study provides insight into the gene regulation plasticity of adipose tissue in response to macronutrient composition, beyond the already well-characterized response to caloric intake.

The Relationship between Dietary Macronutrient Composition and Telomere Length Among US Adults.

The role of dietary macronutrients and energy intake in the aging process has been well-established. However, previous research has mainly focused on the association between leukocyte telomere length (LTL) and individual macronutrients, while the effects of macronutrient composition on LTL remain unclear. This cross-sectional analysis involved 4130 US adults (44.8 ± 17.0 years; 51% female) from the National Health and Nutrition Examination Survey during 1999-2002. A single 24-h dietary recall is used to collect dietary data. The relationship between dietary macronutrient composition and LTL is examined using three-dimensional generalized additive models. After adjustment for age, sex, ethnicity, education, physical activity, BMI, and dietary quality, a three-dimensional association of macronutrient composition with LTL (P = 0.02) is revealed. Diets lower in protein (5-10%), higher in carbohydrates (75%), and lower in fat (15-20%) are associated with the longest LTL corresponding to 7.7 years of slower biological aging. Diets lowest in protein (5%) and carbohydrate (40%), while highest in dietary fat (55%) are associated with the shortest LTL, corresponding to accelerated biological aging of 4.4 years. The associations appeared magnified with higher energy intake. These findings support a complex relationship between dietary macronutrients and biological aging independent of diet quality.

Low-Fat, High-Carbohydrate Diets Reduce Body Weight and Sperm Count but Increase Sperm Motility in Mice.

BACKGROUND: Male reproduction is impacted by both over- and under-nutrition, demonstrated by animal studies using high-fat and low-protein dietary interventions. Little is known about the impacts of low-fat, high-carb diets and types of dietary carbohydrates on sperm traits. OBJECTIVES: Using a nutritional geometry approach, we investigated the effects of partially or completely substituting glucose for fructose in isocaloric diets containing either 10%, 20%, or 30% fat (by energy) on sperm traits in mice. METHODS: Male C57BL/6J mice were fed 1 of 15 experimental diets for 18 wk starting from 8 wk of age. Reproductive organs were then harvested, and sperm concentration, motility, and velocity were measured using Computer-Assisted Sperm Analysis. RESULTS: Increasing dietary fat from 10% to 30% while maintaining energy density at 14.3 kJ/g and protein content at 20% resulted in increased body weight and sperm production but reduced the percentage of motile sperm. Body weight and seminal vesicle weight were maximized on diets containing a 50:50 mix of fructose and glucose, but carbohydrate type had few significant impacts on epididymal sperm traits. CONCLUSIONS: The opposing impacts of dietary fat on mouse sperm quantity and quality observed suggest that male fertility may not be optimized by a single diet; rather, context-specific dietary guidelines targeted to specific concerns in semen quality may prove useful in treating male infertility.

Evidence for protein leverage on total energy intake, but not body mass index, in a large cohort of older adults.

BACKGROUND: Protein leverage (PL) is the phenomenon of consuming food until absolute intake of protein approaches a 'target value', such that total energy intake (TEI) varies passively with the ratio of protein: non-protein energy (fat + carbohydrate) in the diet. The PL hypothesis (PLH) suggests that the dilution of protein in energy-dense foods, particularly those rich in carbohydrates and fats, combines with protein leverage to contribute to the global obesity epidemic. Evidence for PL has been reported in younger adults, children and adolescents. This study aimed to test for PL and the protein leverage hypothesis (PLH) in a cohort of older adults. METHODS: We conducted a retrospective analysis of dietary intake in a cohort of 1699 community-dwelling older adults aged 67-84 years from the NuAge cohort. We computed TEI and the energy contribution (EC) from each macronutrient. The strength of leverage of macronutrients was assessed through power functions ( TEI = µ * EC L ). Body mass index (BMI) was calculated, and mixture models were fitted to predict TEI and BMI from macronutrients' ECs. RESULTS: In this cohort of older adults, 53% of individuals had obesity and 1.5% had severe cases. The mean TEI was 7673 kJ and macronutrients' ECs were 50.4%, 33.2% and 16.4%, respectively for carbohydrates, fat, and protein. There was a strong negative association (L = -0.37; p < 0.001) between the protein EC and TEI. Each percent of energy intake from protein reduced TEI by 77 kJ on average, ceteris paribus. However, BMI was unassociated with TEI in this cohort. CONCLUSIONS: Findings indicate clear evidence for PL on TEI, but not on BMI, likely because of aging, body composition, sarcopenia, or protein wasting.

Toward reconciling the roles of FGF21 in protein appetite, sweet preference, and energy expenditure.

Fibroblast growth factor 21 (FGF21), an endocrine signal robustly increased by protein restriction independently of an animal's energy status, exerts profound effects on feeding behavior and metabolism. Here, we demonstrate that considering the nutritional contexts within which FGF21 is elevated can help reconcile current controversies over its roles in mediating macronutrient preference, food intake, and energy expenditure. We show that FGF21 is primarily a driver of increased protein intake in mice and that the effect of FGF21 on sweet preference depends on the carbohydrate balance of the animal. Under no-choice feeding, FGF21 infusion either increased or decreased energy expenditure depending on whether the animal was fed a high- or low-energy diet, respectively. We show that while the role of FGF21 in mediating feeding behavior is complex, its role in promoting protein appetite is robust and that the effects on sweet preference and energy expenditure are macronutrient-state-dependent effects of FGF21.

Evidence for the protein leverage hypothesis in preschool children prone to obesity.

BACKGROUND & AIMS: The protein leverage hypothesis (PLH) proposed that strict regulation of protein intake drives energy overconsumption and obesity when diets are diluted by fat and/or carbohydrates. Evidence about the PLH has been found in adults, while studies in children are limited. Thus, we aimed to test the PLH by assessing the role of dietary protein on macronutrients, energy intake, and obesity risk using data from preschool children followed for 1.3 years. METHODS: 553 preschool children aged 2-6 years from the 'Healthy Start' project were included. EXPOSURES: The proportion of energy intake from protein, fat, and carbohydrates collected from a 4-day dietary record. OUTCOMES: Energy intake, BMI z-score, fat mass (FM) %, waist- (WHtR) and hip-height ratio (HHtR). Power function analysis was used to test the leverage of protein on energy intake. Mixture models were used to explore interactive associations of macronutrient composition on all these outcomes, with results visualized as response surfaces on the nutritional geometry. RESULTS: Evidence for the PLH was confirmed in preschool children. The distribution of protein intake (% of MJ, IQR: 3.2) varied substantially less than for carbohydrate (IQR: 5.7) or fat (IQR: 6.3) intakes, suggesting protein intake is most tightly regulated. Absolute energy intake varied inversely with dietary percentage energy from protein (L = -0.14, 95% CI: -0.25, -0.04). Compared to children with high fat or carbohydrate intakes, children with high dietary protein intake (>20% of MJ) had a greater decrease in WHtR and HHtR over the 1.3-year follow-up, offering evidence for the PLH in prospective analysis. But no association was observed between macronutrient distribution and changes in BMI z-score or FM%. CONCLUSIONS: In this study in preschool children, protein intake was the most tightly regulated macronutrient, and energy intake was an inverse function of dietary protein concentration, indicating the evidence for protein leverage. Increases in WHtR and HHtR were principally associated with the dietary protein dilution, supporting the PLH. These findings highlight the importance of protein in children's diets, which seems to have significant implications for childhood obesity risk and overall health.

Determining the metabolic effects of dietary fat, sugars and fat-sugar interaction using nutritional geometry in a dietary challenge study with male mice.

The metabolic effects of sugars and fat lie at the heart of the "carbohydrate vs fat" debate on the global obesity epidemic. Here, we use nutritional geometry to systematically investigate the interaction between dietary fat and the major monosaccharides, fructose and glucose, and their impact on body composition and metabolic health. Male mice (n = 245) are maintained on one of 18 isocaloric diets for 18-19 weeks and their metabolic status is assessed through in vivo procedures and by in vitro assays involving harvested tissue samples. We find that in the setting of low and medium dietary fat content, a 50:50 mixture of fructose and glucose (similar to high-fructose corn syrup) is more obesogenic and metabolically adverse than when either monosaccharide is consumed alone. With increasing dietary fat content, the effects of dietary sugar composition on metabolic status become less pronounced. Moreover, higher fat intake is more harmful for glucose tolerance and insulin sensitivity irrespective of the sugar mix consumed. The type of fat consumed (soy oil vs lard) does not modify these outcomes. Our work shows that both dietary fat and sugars can lead to adverse metabolic outcomes, depending on the dietary context. This study shows how the principles of the two seemingly conflicting models of obesity (the "energy balance model" and the "carbohydrate insulin model") can be valid, and it will help in progressing towards a unified model of obesity. The main limitations of this study include the use of male mice of a single strain, and not testing the metabolic effects of fructose intake via sugary drinks, which are strongly linked to human obesity.

Vegetarian Dietary Patterns and Cardiometabolic Risk in People With or at High Risk of Cardiovascular Disease: A Systematic Review and Meta-analysis.

IMPORTANCE: Plant-based diets are known to improve cardiometabolic risk in the general population, but their effects on people at high risk of cardiovascular diseases (CVDs) remain inconclusive. OBJECTIVE: To assess the association of vegetarian diets with major cardiometabolic risk factors, including low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c (HbA1c), systolic blood pressure (SBP), and body weight in people with or at high risk of CVDs. DATA SOURCES: This meta-analysis was registered before the study was conducted. Systematic searches performed included Embase, MEDLINE, CINAHL, and CENTRAL from inception until July 31, 2021. STUDY SELECTION: Eligible randomized clinical trials (RCTs) that delivered vegetarian diets in adults with or at high risk of CVDs and measured LDL-C, HbA1c or SBP were included. Of the 7871 records screened, 29 (0.4%; 20 studies) met inclusion criteria. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data including demographics, study design, sample size, and diet description, and performed risk of bias assessment. A random-effects model was used to assess mean changes in LDL-C, HbA1c, SBP, and body weight. The overall certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool. MAIN OUTCOMES AND MEASURES: Mean differences between groups in changes (preintervention vs postintervention) of LDL-C, HbA1c, and SBP; secondary outcomes were changes in body weight and energy intake. RESULTS: Twenty RCTs involving 1878 participants (range of mean age, 28-64 years) were included, and mean duration of intervention was 25.4 weeks (range, 2 to 24 months). Four studies targeted people with CVDs, 7 focused on diabetes, and 9 included people with at least 2 CVD risk factors. Overall, relative to all comparison diets, meta-analyses showed that consuming vegetarian diets for an average of 6 months was associated with decreased LDL-C, HbA1c, and body weight by 6.6 mg/dL (95% CI, -10.1 to -3.1), 0.24% (95% CI, -0.40 to -0.07), and 3.4 kg (95% CI, -4.9 to -2.0), respectively, but the association with SBP was not significant (-0.1 mm Hg; 95% CI, -2.8 to 2.6). The GRADE assessment showed a moderate level of evidence for LDL-C and HbA1c reduction. CONCLUSIONS AND RELEVANCE: In this study, consuming a vegetarian diet was associated with significant improvements in LDL-C, HbA1c and body weight beyond standard therapy in individuals at high risk of CVDs. Additional high-quality trials are warranted to further elucidate the effects of healthy plant-based diets in people with CVDs.

Diet Quality, Microbial Lignan Metabolites, and Cardiometabolic Health among US Adults.

The gut microbiome has been shown to play a role in the relationship between diet and cardiometabolic health. We sought to examine the degree to which key microbial lignan metabolites are involved in the relationship between diet quality and cardiometabolic health using a multidimensional framework. This analysis was undertaken using cross-sectional data from 4685 US adults (age 43.6 ± 16.5 years; 50.4% female) participating in the National Health and Nutrition Examination Survey for 1999-2010. Dietary data were collected from one to two separate 24-hour dietary recalls and diet quality was characterized using the 2015 Healthy Eating Index. Cardiometabolic health markers included blood lipid profile, glycemic control, adiposity, and blood pressure. Microbial lignan metabolites considered were urinary concentrations of enterolignans, including enterolactone and enterodiol, with higher levels indicating a healthier gut microbial environment. Models were visually examined using a multidimensional approach and statistically analyzed using three-dimensional generalized additive models. There was a significant interactive association between diet quality and microbial lignan metabolites for triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, insulin, oral glucose tolerance, adiposity, systolic blood pressure, and diastolic blood pressure (all p < 0.05). Each of these cardiometabolic health markers displayed an association such that optimal cardiometabolic health was only observed in individuals with both high diet quality and elevated urinary enterolignans. When comparing effect sizes on the multidimensional response surfaces and model selection criteria, the strongest support for a potential moderating relationship of the gut microbiome was observed for fasting triglycerides and oral glucose tolerance. In this study, we revealed interactive associations of diet quality and microbial lignan metabolites with cardiometabolic health markers. These findings suggest that the overall association of diet quality on cardiometabolic health may be affected by the gut microbiome.

Evidence for protein leverage in a general population sample of children and adolescents.

BACKGROUND/OBJECTIVES: The strong regulation of protein intake can lead to overconsumption of total energy on diets with a low proportion of energy from protein, a process referred to as protein leverage. The protein leverage hypothesis posits that protein leverage explains variation in energy intake and potentially obesity in ecological settings. Here, we tested for protein leverage and the protein leverage hypothesis in children and adolescents. SUBJECTS/METHODS: A population sample of children, mean (SD) age 7.6 (0.4) years (n = 422), followed up at age 9.8 (0.4) years (n = 387) and at age 15.8 (0.4) years (n = 229), participating for the Physical Activity and Nutrition in Children (PANIC) study. EXPOSURES: 4-day food records-related proportional energy intake of proteins, fats, and carbohydrates. OUTCOMES: energy intake, body mass index (BMI) z-score and dual-energy X-ray absorptiometry-related energy expenditure. RESULTS: Proportional energy intake of proteins was inversely associated with energy intake following power functions at all 3 ages (mean [95%CI] strength of leverage of L = -0.36 [-0.47 to -0.25]; L = -0.26 [-0.37 to -0.15]; L = -0.25 [-0.38 to -0.13]; all P < 0.001). Mixture analysis indicated that variance in energy intake was associated primarily with the proportional intake of energy from proteins, not with either fats or carbohydrates. At all 3 ages, energy intake was not associated with BMI z-score but positively associated with energy expenditure (all P < 0.001). CONCLUSIONS: This study provides evidence consistent with protein leverage in a population sample of children and adolescents. Increased energy intake on diets with lower protein content was counterbalanced by increased energy expenditure and therefore did not translate into increased adiposity.

Nutritional geometry framework of sleep.

AIMS: Sleep is a fundamental physiological function and is essential for all animals. Sleep is affected by diet compositions including protein (P) and carbohydrates (C), but there has not been a systematic investigation on the effect of dietary macronutrient balance on sleep. MAIN METHODS: We used the nutritional geometry framework (NGF) to explore the interactive effects on sleep of protein (P) and carbohydrates (C) in the model organism Drosophila. Both female and male flies were fed various diets containing seven ratios of protein-to-carbohydrates at different energetic levels for 5 days and sleep was monitored by the Drosophila Activity Monitor (DAM) system. KEY FINDINGS: Our results showed that the combination of low protein and high carbohydrates (LPHC) prolonged sleep time and sleep quality, with fewer sleep episodes and longer sleep duration. We further found that the effects of macronutrients on sleep mirrored levels of hemolymph glucose and whole-body glycogen. Moreover, transcriptomic analyses revealed that a high-protein, low-carbohydrate (HPLC) diet significantly elevated the gene expression of metabolic pathways when compared to the LPHC diet, with the glycine, serine, and threonine metabolism pathway being most strongly elevated. Further studies confirmed that the contents of glycine, serine, and threonine affected sleep. SIGNIFICANCE: Our results demonstrate that sleep is affected by the dietary balance of protein and carbohydrates possibly mediated by the change in glucose, glycogen, glycine, serine, and threonine.

Multi-Nutrient Analysis of Dietary Macronutrients with All-Cause, Cardiovascular, and Cancer Mortality: Data from NHANES 1999-2014.

Macronutrients are a major component of the human diet. However, few studies have assessed their collective association with mortality. We sought to evaluate the associations of macronutrient intake with all-cause, cardiovascular, and cancer mortality in US adults using a multi-nutrient approach. This prospective cohort analysis used data from the National Health and Nutrition Examination Survey from the years 1999 to 2014. The participants included 33,681 US adults aged 20−85 years (52.5% female). The maximum follow-up time was 16.8 years, with a total of 4398 total deaths, including 772 cardiovascular deaths and 952 cancer deaths. The associations between mortality and dietary macronutrients were explored using three-dimensional generalized additive models, allowing for visual and statistical inference of complex nonlinear associations. Absolute macronutrient intake demonstrated a three-way interactive association with all-cause mortality (p < 0.001), cardiovascular mortality (p = 0.02), and cancer mortality (p = 0.05), adjusted for age, sex, ethnicity, socioeconomic status, dietary quality, and lifestyle. Compositionally, a high caloric diet composed of moderately high protein (20%), moderate fat (30%), and moderate carbohydrate (50%) levels was associated with the highest mortality risk. Across the total energy intake levels, lower mortality risk was observed in two separate regions consisting of higher protein (30%), higher carbohydrate (60%), and lower fat levels (10%) or lower protein (10%), moderate carbohydrate (45%), and higher fat levels (45%). These findings highlight a complex nonlinear and interactive association between macronutrients and all-cause mortality such that several distinct dietary compositions are associated with similarly high or low risk. Future research is needed to explore the drivers of these associations and whether they differ across varying dietary patterns and populations.

A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations.

The log response ratio, lnRR, is the most frequently used effect size statistic for meta-analysis in ecology. However, often missing standard deviations (SDs) prevent estimation of the sampling variance of lnRR. We propose new methods to deal with missing SDs via a weighted average coefficient of variation (CV) estimated from studies in the dataset that do report SDs. Across a suite of simulated conditions, we find that using the average CV to estimate sampling variances for all observations, regardless of missingness, performs with minimal bias. Surprisingly, even with missing SDs, this simple method outperforms the conventional approach (basing each effect size on its individual study-specific CV) with complete data. This is because the conventional method ultimately yields less precise estimates of the sampling variances than using the pooled CV from multiple studies. Our approach is broadly applicable and can be implemented in all meta-analyses of lnRR, regardless of 'missingness'.

Estimating Genetic Variance in Life-Span Response to Diet: Insights From Statistical Simulation.

Several studies demonstrate genetic variation in response to dietary restriction (DR) by replicating treatments across isogenic lines/strains from genetic reference panels. These studies typically quantify the response to DR as an effect size, estimated for each strain separately (eg, the difference in mean life span between groups). Such "no-pooling" analyses are expected to systematically overestimate variation in response DR, principally by overlooking sampling variance. In contrast, "partial-pooling" analyses using mixed-effects models are less prone to this bias. I demonstrate these issues using simulations, which also show that partial-pooling analyses can improve replicability among studies. Regardless of the analyses used, estimates of among-strain variation will have low precision when sample sizes are small. A worked example using survival data in mice is given. Life-span studies using genetic reference panels always have to trade-off within- and among-strain replication owing to logistical challenges. The simulation presented can also be used to help design such studies through power analysis.

Multidimensional associations between nutrient intake and healthy ageing in humans.

BACKGROUND: Little is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process. RESULTS: Ageing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don't deviate too much from norms ('homeostatic plateaus'). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space. CONCLUSION: Using multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.

Testing the protein-leverage hypothesis using population surveillance data.

It is hypothesized that humans exhibit 'protein leverage' (PL), whereby regulation of absolute protein intake results in the over-consumption of non-protein food on low percentage protein diets. Testing for PL using dietary surveillance data involves seeking evidence for a negative association between total energy intake and percentage energy from protein. However, it is unclear whether such an association might emerge without PL due to the structure of intake data (protein and non-protein intakes have different means and variances and covary). We derive a set of models that describe the association between the expected estimate of PL and the distributions of protein and non-protein intake. Models were validated via simulation. Patterns consistent with PL will not emerge simply because protein intake has a lower mean and/or variance than non-protein. Rather, evidence of PL is observed where protein has a lower index of dispersion (variance/mean) than non-protein intake. Reciprocally, the stronger PL is the lower the index of dispersion for protein intake becomes. Disentangling causality is ultimately beyond the power of observational data alone. However, we show that one can correct for confounders (e.g. age) in generating signals of PL, and describe independent measures that can anchor inferences around the role of PL.

Sex-specific effects of maternal dietary carbohydrate quality on fetal development and offspring metabolic phenotype in mice.

Objectives: In utero glycemia is an important determinant of fetal growth. Women with gestational diabetes are more likely to deliver large-for-gestational age babies that are at increased risk for obesity. The maternal nutritional state modulates the development of offspring biological systems during the critical periods of gestation and lactation. Carbohydrate typically contributes most of the dietary energy, however, there are very few mechanistic studies investigating the effects of maternal dietary carbohydrate quality on fetal and offspring outcomes. Therefore, we sought to investigate the direct effects of maternal carbohydrate quality on sex-specific offspring metabolic programming. Methods: Female C57BL/6 mice were fed one of five isocaloric diets: four high-sugar diets based on glucose, sucrose, isomaltulose or fructose (all containing 60% energy as carbohydrate), or a standard, minimally processed, chow diet, and were mated with chow-fed males. Half of the dams were sacrificed for fetus dissection and placental collection, with the remaining giving live birth. All dams were metabolically profiled before and during pregnancy, and pups were similarly profiled at 12 weeks of age. Results: Overall, glucose-fed dams were heavier and fatter than chow or isomaltulose-fed dams. Female fetuses from glucose and isomaltulose-fed mothers weighed less and had smaller livers, than those from chow-fed mothers, with isomaltulose-fed female fetuses also having decreased placental mass. In contrast, male fetuses responded differently to the maternal diets, with heart mass being significantly increased when their mothers were fed fructose-containing diets, that is, sucrose, isomaltulose and fructose. High-sugar fed female offspring weighed the same, but were significantly fatter, than chow-fed offspring at 12 weeks of age, while glucose and isomaltulose-fed male pups displayed a similar phenotype to their mothers'. Conclusion: While both glucose and isomaltulose diets constrained fetal growth in females, only placentas from isomaltulose-fed dams were significantly smaller than those from chow-fed mothers, suggesting the mechanisms through which fetal growth is reduced may be different. Female fetuses of isomaltulose-fed mothers were also lighter than sucrose-fed fetuses suggesting the glycemic index, or rate of glucose digestion and absorption, may be an important factor in determining nutrient availability to the growing fetus.