Myths and Methodologies: Standardisation in human physiology research-should we control the controllables?

The premise of research in human physiology is to explore a multifaceted system whilst identifying one or a few outcomes of interest. Therefore, the control of potentially confounding variables requires careful thought regarding the extent of control and complexity of standardisation. One common factor to control prior to testing is diet, as food and fluid provision may deviate from participants' habitual diets, yet a self-report and replication method can be flawed by under-reporting. Researchers may also need to consider standardisation of physical activity, whether it be through familiarisation trials, wash-out periods, or guidance on levels of physical activity to be achieved before trials. In terms of pharmacological agents, the ethical implications of standardisation require researchers to carefully consider how medications, caffeine consumption and oral contraceptive prescriptions may affect the study. For research in females, it should be considered whether standardisation between- or within-participants in regards to menstrual cycle phase is most relevant. The timing of measurements relative to various other daily events is relevant to all physiological research and so it can be important to standardise when measurements are made. This review summarises the areas of standardisation which we hope will be considered useful to anyone involved in human physiology research, including when and how one can apply standardisation to various contexts.

Effects of physical form of ß-lactoglobulin and calcium ingestion on GLP-1 secretion, gastric emptying and energy intake in humans: a randomised crossover trial.

The aim of this study was to assess whether adding Ca2+ to aggregate or native forms of ß-lactoglobulin alters gut hormone secretion, gastric emptying rates and energy intake in healthy men and women. Fifteen healthy adults (mean ± sd: 9M/6F, age: 24 ± 5 years) completed four trials in a randomised, double-blind, crossover design. Participants consumed test drinks consisting of 30 g of ß-lactoglobulin in a native form with (NATIVE + MINERALS) and without (NATIVE) a Ca2+-rich mineral supplement and in an aggregated form both with (AGGREG + MINERALS) and without the mineral supplement (AGGREG). Arterialised blood was sampled for 120 min postprandially to determine gut hormone concentrations. Gastric emptying was determined using 13C-acetate and 13C-octanoate, and energy intake was assessed with an ad libitum meal at 120 min. A protein × mineral interaction effect was observed for total glucagon-like peptide-1 (GLP-1TOTAL) incremental AUC (iAUC; P < 0·01), whereby MINERALS + AGGREG increased GLP-1TOTAL iAUC to a greater extent than AGGREG (1882 ± 603 v. 1550 ± 456 pmol·l-1·120 min, P < 0·01), but MINERALS + NATIVE did not meaningfully alter the GLP-1 iAUC compared with NATIVE (1669 ± 547 v. 1844 ± 550 pmol·l-1·120 min, P = 0·09). A protein × minerals interaction effect was also observed for gastric emptying half-life (P < 0·01) whereby MINERALS + NATIVE increased gastric emptying half-life compared with NATIVE (83 ± 14 v. 71 ± 8 min, P < 0·01), whereas no meaningful differences were observed between MINERALS + AGGREG v. AGGREG (P = 0·70). These did not result in any meaningful changes in energy intake (protein × minerals interaction, P = 0·06). These data suggest that the potential for Ca2+ to stimulate GLP-1 secretion at moderate protein doses may depend on protein form. This study was registered at clinicaltrials.gov (NCT04659902).

Myths and Methodologies: Standardisation in Human Physiology Research-Should We Control the Controllables?

The premise of research in human physiology is to explore a multifaceted system whilst identifying one or a few outcomes of interest. Therefore, the control of potentially confounding variables requires careful thought regarding the extent of control and complexity of standardisation. One common factor to control prior to testing is diet, as food and fluid provision may deviate from participants' habitual diets, yet a self-report and replication method can be flawed by under-reporting. Researchers may also need to consider standardisation of physical activity, whether it be through familiarisation trials, wash-out periods, or guidance on levels of physical activity to be achieved before trials. In terms of pharmacological agents, the ethical implications of standardisation require researchers to carefully consider how medications, caffeine consumption and oral contraceptive prescriptions may affect the study. For research in females, it should be considered whether standardisation between- or within-participants in regards to menstrual cycle phase is most relevant. The timing of measurements relative to various other daily events is relevant to all physiological research and so it can be important to standardise when measurements are made. This review summarises the areas of standardisation which we hope will be considered useful to anyone involved in human physiology research, including when and how one can apply standardisation to various contexts.

Whey Protein-Enriched and Carbohydrate-Rich Breakfasts Attenuate Insulinemic Responses to an ad libitum Lunch Relative to Extended Morning Fasting: A Randomized Crossover Trial.

BACKGROUND: Typical breakfast foods are rich in carbohydrate, so they not only elevate blood glucose during the morning, but also elicit a second-meal effect that can attenuate blood glucose responses in the afternoon. OBJECTIVES: To determine whether a reduced-carbohydrate protein-enriched breakfast can elicit similar effects on glucose control later in the day but without hyperglycemia in the morning. METHODS: In a randomized crossover design, 12 healthy men and women (age 22 ± 2 y, BMI 24.1 ± 3.6 kg·m-2; Mean ± SD) completed 3 experimental conditions. In all conditions, participants consumed an ad libitum lunch at 1200 ± 1 h but differed in terms of whether they had fasted all morning (control) or had consumed a standardized porridge breakfast at 0900 ± 1 h (320 ± 50 kcal; prescribed relative to resting metabolic rate) that was either carbohydrate-rich (50 ± 10 g CHO) or protein-enriched (that is, isoenergetic substitution of carbohydrate for 15 g whey protein isolate). RESULTS: The protein-enriched breakfast reduced the morning glycemic response (iAUC 87 ± 36 mmol·L-1·180 min) relative to the carbohydrate-rich breakfast (119 ± 37 mmol·L-1·180 min; P = 0.03). Despite similar energy intake at lunch in all 3 conditions (protein-enriched 769 ± 278 kcal; carbohydrate-rich 753 ± 223 kcal; fasting 790 ± 227 kcal), postlunch insulinemic responses were markedly attenuated when breakfasts had been consumed that were either protein-enriched (18.0 ± 8.0 nmol·L-1·120 min; P = 0.05) or carbohydrate-rich (16.0 ± 7.7 nmol·L-1·120 min; P = 0.005), relative to when lunch was consumed in an overnight fasted state (26.9 ± 13.5 nmol·L-1·120 min). CONCLUSIONS: Breakfast consumption attenuates insulinemic responses to a subsequent meal, achieved with consumption of energy-matched breakfasts typically high in carbohydrates or enriched with whey protein isolate relative to extended morning fasting. TRIAL REGISTRATION NUMBER: NCT03866720 (clinicaltrials.gov).

Nutrient timing and metabolic regulation.

Daily (circadian) rhythms coordinate our physiology and behaviour with regular environmental changes. Molecular clocks in peripheral tissues (e.g. liver, skeletal muscle and adipose) give rise to rhythms in macronutrient metabolism, appetite regulation and the components of energy balance such that our bodies can align the periodic delivery of nutrients with ongoing metabolic requirements. The timing of meals both in absolute terms (i.e. relative to clock time) and in relative terms (i.e. relative to other daily events) is therefore relevant to metabolism and health. Experimental manipulation of feeding-fasting cycles can advance understanding of the effect of absolute and relative timing of meals on metabolism and health. Such studies have extended the overnight fast by regular breakfast omission and revealed that morning fasting can alter the metabolic response to subsequent meals later in the day, whilst also eliciting compensatory behavioural responses (i.e. reduced physical activity). Similarly, restricting energy intake via alternate-day fasting also has the potential to elicit a compensatory reduction in physical activity, and so can undermine weight-loss efforts (i.e. to preserve body fat stores). Interrupting the usual overnight fast (and therefore also the usual sleep cycle) by nocturnal feeding has also been examined and further research is needed to understand the importance of this period for either nutritional intervention or nutritional withdrawal. In summary, it is important for dietary guidelines for human health to consider nutrient timing (i.e. when we eat) alongside the conventional focus on nutrient quantity and nutrient quality (i.e. how much we eat and what we eat).

Qualitative Differences Between the IFNα subtypes and IFNß Influence Chronic Mucosal HIV-1 Pathogenesis.

The Type I Interferons (IFN-Is) are innate antiviral cytokines that include 12 different IFNα subtypes and IFNß that signal through the IFN-I receptor (IFNAR), inducing hundreds of IFN-stimulated genes (ISGs) that comprise the 'interferome'. Quantitative differences in IFNAR binding correlate with antiviral activity, but whether IFN-Is exhibit qualitative differences remains controversial. Moreover, the IFN-I response is protective during acute HIV-1 infection, but likely pathogenic during the chronic stages. To gain a deeper understanding of the IFN-I response, we compared the interferomes of IFNα subtypes dominantly-expressed in HIV-1-exposed plasmacytoid dendritic cells (1, 2, 5, 8 and 14) and IFNß in the earliest cellular targets of HIV-1 infection. Primary gut CD4 T cells from 3 donors were treated for 18 hours ex vivo with individual IFN-Is normalized for IFNAR signaling strength. Of 1,969 IFN-regulated genes, 246 'core ISGs' were induced by all IFN-Is tested. However, many IFN-regulated genes were not shared between the IFNα subtypes despite similar induction of canonical antiviral ISGs such as ISG15, RSAD2 and MX1, formally demonstrating qualitative differences between the IFNα subtypes. Notably, IFNß induced a broader interferome than the individual IFNα subtypes. Since IFNß, and not IFNα, is upregulated during chronic HIV-1 infection in the gut, we compared core ISGs and IFNß-specific ISGs from colon pinch biopsies of HIV-1-uninfected (n = 13) versus age- and gender-matched, antiretroviral-therapy naïve persons with HIV-1 (PWH; n = 19). Core ISGs linked to inflammation, T cell activation and immune exhaustion were elevated in PWH, positively correlated with plasma lipopolysaccharide (LPS) levels and gut IFNß levels, and negatively correlated with gut CD4 T cell frequencies. In sharp contrast, IFNß-specific ISGs linked to protein translation and anti-inflammatory responses were significantly downregulated in PWH, negatively correlated with gut IFNß and LPS, and positively correlated with plasma IL6 and gut CD4 T cell frequencies. Our findings reveal qualitative differences in interferome induction by diverse IFN-Is and suggest potential mechanisms for how IFNß may drive HIV-1 pathogenesis in the gut.

Plasma glucagon-like peptide-1 responses to ingestion of protein with increasing doses of milk minerals rich in calcium.

A high dose of whey protein hydrolysate fed with milk minerals rich in calcium (Capolac®) results in enhanced glucagon-like peptide-1 (GLP-1) concentrations in lean individuals; however, the effect of different calcium doses ingested alongside protein is unknown. The present study assessed the dose response of calcium fed alongside 25 g whey protein hydrolysate on GLP-1 concentrations in individuals with overweight/obesity. Eighteen adults (mean ± sd: 8M/10F, 34 ± 18 years, 28·2 ± 2·9 kgm-2) completed four trials in a randomised, double-blind, crossover design. Participants consumed test solutions consisting of 25 g whey protein hydrolysate (CON), supplemented with 3179 mg (LOW), 6363 mg (MED) or 9547 mg (HIGH) Capolac® on different occasions, separated by at least 48 h. The calcium content of test solutions equated to 65, 892, 1719 and 2547 mg, respectively. Arterialised-venous blood was sampled over 180 min to determine plasma concentrations of GLP-1TOTAL, GLP-17-36amide, insulin, glucose, NEFA, and serum concentrations of calcium and albumin. Ad libitum energy intake was measured at 180 min. Time-averaged incremental AUC (iAUC) for GLP-1TOTAL (pmol·l-1·min-1) did not differ between CON (23 ± 4), LOW (25 ± 6), MED (24 ± 5) and HIGH (24 ± 6). Energy intake (kcal) did not differ between CON (940 ± 387), LOW (884 ± 345), MED (920 ± 334) and HIGH (973 ± 390). Co-ingestion of whey protein hydrolysate with Capolac® does not potentiate GLP-1 release in comparison with whey protein hydrolysate alone. The study was registered at clinical trials (NCT03819972).

Nocturnal whey protein ingestion impairs post-prandial glucose tolerance at breakfast.

Poor post-prandial glucose control is a risk factor for multiple health conditions. The second-meal effect refers to the progressively improved glycaemic control with repeated feedings, an effect which is achievable with protein ingestion at the initial eating occasion. The most pronounced glycaemic response each day therefore typically occurs following breakfast, so the present study investigated whether ingesting protein during the night could improve glucose control at the first meal of the day. In a randomised crossover design, fifteen adults (seven males, eight females; age, 22 (sd 3) years; BMI, 24·0 (sd 2·8) kg/m2; fasting blood glucose, 4·9 (sd 0·5) mmol/l) woke at 04.00 (sd 1) hours to ingest 300 ml water with or without 63 g whey protein. Participants then completed a mixed-macronutrient meal tolerance test (1 g carbohydrate/kg body mass, 2356 (sd 435) kJ), 5 h 39 min following the nocturnal feeding. Nocturnal protein ingestion increased the glycaemic response (incremental AUC) to breakfast by 43·5 (sd 55·5) mmol × 120 min/l (P = 0·009, d = 0·94). Consistent with this effect, individual peak blood glucose concentrations were 0·6 (sd 1·0) mmol/l higher following breakfast when protein had been ingested (P = 0·049, d = 0·50). Immediately prior to breakfast, rates of lipid oxidation were 0·02 (sd 0·03) g/min higher (P = 0·045) in the protein condition, followed by an elevated post-prandial energy expenditure (0·38 (sd 0·50) kJ/min, P = 0·018). Post-prandial appetite and energy intake were similar between conditions. The present study reveals a paradoxical second-meal phenomenon whereby nocturnal whey protein feeding impaired subsequent glucose tolerance, whilst increasing post-prandial energy expenditure.

The effects of glucose-fructose co-ingestion on repeated performance during a day of intensified rugby union training in professional academy players.

This study assessed the effects of glucose-fructose co-ingestion during recovery from high-intensity rugby training on subsequent performance. Nine professional, senior academy Rugby Union players performed two trials in a double-blind, randomized, crossover design. Identical rugby training sessions were separated by a 3-hour recovery period, during which participants ingested protein (0.3 g×kg BM×h-1) and carbohydrate-containing (0.8 g×kg BM×h-1) recovery drinks, comprised of glucose polymers (GLUCOSE ONLY) or a glucose-fructose mixture (GLUCOSE+FRUCTOSE). Performance outcomes were determined from global positioning systems combined with accelerometry and heart rate monitoring. Mean speed during sessions 1 (am) and 2 (pm) of GLUCOSE ONLY was (mean±SD) 118±6 and 117±4 m×min-1, respectively. During GLUCOSE+FRUCTOSE, mean speed during session 1 and 2 was 117±4 and 116±5 m×min-1, respectively (time x trial interaction, p = 0.61). Blood lactate concentrations were higher throughout recovery in GLUCOSE+FRUCTOSE (mean ±SD: 1-h 3.2 ±2.0 mmol×L-1; 3-h 2.1 ±1.2 mmol×L-1) compared to GLUCOSE ONLY (1-h 2.0 ±1.0 mmol×L-1; 3-h 1.4 ±1.0 mmol×L-1; trial effect p = 0.05). Gastrointestinal discomfort low in both conditions. These data suggest glucose-fructose mixtures consumed as protein-carbohydrate recovery drinks following rugby training do not enhance subsequent performance compared to glucose-based recovery drinks.

A prospective study of associations between in utero exposure to gestational diabetes mellitus and metabolomic profiles during late childhood and adolescence.

AIMS/HYPOTHESIS: This study aimed to: (1) identify metabolite patterns during late childhood that differ with respect to exposure to maternal gestational diabetes mellitus (GDM); (2) examine the persistence of GDM/metabolite associations 5 years later, during adolescence; and (3) investigate the associations of metabolite patterns with adiposity and metabolic biomarkers from childhood through adolescence. METHODS: This study included 592 mother-child pairs with information on GDM exposure (n = 92 exposed), untargeted metabolomics data at age 6-14 years (T1) and at 12-19 years (T2), and information on adiposity and metabolic risk biomarkers at T1 and T2. We first consolidated 767 metabolites at T1 into factors (metabolite patterns) via principal component analysis (PCA) and used multivariable regression to identify factors that differed by GDM exposure, at α = 0.05. We then examined associations of GDM with individual metabolites within factors of interest at T1 and T2, and investigated associations of GDM-related factors at T1 with adiposity and metabolic risk throughout T1 and T2 using mixed-effects linear regression models. RESULTS: Of the six factors retained from PCA, GDM exposure was associated with greater odds of being in quartile (Q)4 (vs Q1-3) of 'Factor 4' at T1 after accounting for age, sex, race/ethnicity, maternal smoking habits during pregnancy, Tanner stage, physical activity and total energy intake, at α = 0.05 (OR 1.78 [95% CI 1.04, 3.04]; p = 0.04). This metabolite pattern comprised phosphatidylcholines, diacylglycerols and phosphatidylethanolamines. GDM was consistently associated with elevations in a subset of individual compounds within this pattern at T1 and T2. While this metabolite pattern was not related to the health outcomes in boys, it corresponded with greater adiposity and a worse metabolic profile among girls throughout the follow-up period. Each 1-unit increment in Factor 4 corresponded with 0.17 (0.08, 0.25) units higher BMI z score, 8.83 (5.07, 12.59) pmol/l higher fasting insulin, 0.28 (0.13, 0.43) units higher HOMA-IR, and 4.73 (2.15, 7.31) nmol/l higher leptin. CONCLUSIONS/INTERPRETATION: Exposure to maternal GDM was nominally associated with a metabolite pattern characterised by elevated serum phospholipids in late childhood and adolescence at α = 0.05. This metabolite pattern was associated with greater adiposity and metabolic risk among female offspring throughout the late childhood-to-adolescence transition. Future studies are warranted to confirm our findings.

Glucose control upon waking is unaffected by hourly sleep fragmentation during the night, but is impaired by morning caffeinated coffee.

Morning coffee is a common remedy following disrupted sleep, yet each factor can independently impair glucose tolerance and insulin sensitivity in healthy adults. Remarkably, the combined effects of sleep fragmentation and coffee on glucose control upon waking per se have never been investigated. In a randomised crossover design, twenty-nine adults (mean age: 21 (sd 1) years, BMI: 24·4 (sd 3·3) kg/m2) underwent three oral glucose tolerance tests (OGTT). One following a habitual night of sleep (Control; in bed, lights-off trying to sleep approximately 23.00-07.00 hours), the others following a night of sleep fragmentation (as Control but waking hourly for 5 min), with and without morning coffee approximately 1 h after waking (approximately 300 mg caffeine as black coffee 30 min prior to OGTT). Individualised peak plasma glucose and insulin concentrations were unaffected by sleep quality but were higher following coffee consumption (mean (normalised CI) for Control, Fragmented and Fragmented + Coffee, respectively; glucose: 8·20 (normalised CI 7·93, 8·47) mmol/l v. 8·23 (normalised CI 7·96, 8·50) mmol/l v. 8·96 (normalised CI 8·70, 9·22) mmol/l; insulin: 265 (normalised CI 247, 283) pmol/l; and 235 (normalised CI 218, 253) pmol/l; and 310 (normalised CI 284, 337) pmol/l). Likewise, incremental AUC for plasma glucose was higher in the Fragmented + Coffee trial compared with Fragmented. Whilst sleep fragmentation did not alter glycaemic or insulinaemic responses to morning glucose ingestion, if a strong caffeinated coffee is consumed, then a reduction in glucose tolerance can be expected.

Co-ingestion of whey protein hydrolysate with milk minerals rich in calcium potently stimulates glucagon-like peptide-1 secretion: an RCT in healthy adults.

PURPOSE: To examine whether calcium type and co-ingestion with protein alter gut hormone availability. METHODS: Healthy adults aged 26 ± 7 years (mean ± SD) completed three randomized, double-blind, crossover studies. In all studies, arterialized blood was sampled postprandially over 120 min to determine GLP-1, GIP and PYY responses, alongside appetite ratings, energy expenditure and blood pressure. In study 1 (n = 20), three treatments matched for total calcium content (1058 mg) were compared: calcium citrate (CALCITR); milk minerals rich in calcium (MILK MINERALS); and milk minerals rich in calcium plus co-ingestion of 50 g whey protein hydrolysate (MILK MINERALS + PROTEIN). In study 2 (n = 6), 50 g whey protein hydrolysate (PROTEIN) was compared to MILK MINERALS + PROTEIN. In study 3 (n = 6), MILK MINERALS was compared to the vehicle of ingestion (water plus sucralose; CONTROL). RESULTS: MILK MINERALS + PROTEIN increased GLP-1 incremental area under the curve (iAUC) by ~ ninefold (43.7 ± 11.1 pmol L-1 120 min; p < 0.001) versus both CALCITR and MILK MINERALS, with no difference detected between CALCITR (6.6 ± 3.7 pmol L-1 120 min) and MILK MINERALS (5.3 ± 3.5 pmol L-1 120 min; p > 0.999). MILK MINERALS + PROTEIN produced a GLP-1 iAUC ~ 25% greater than PROTEIN (p = 0.024; mean difference: 9.1 ± 6.9 pmol L-1 120 min), whereas the difference between MILK MINERALS versus CONTROL was small and non-significant (p = 0.098; mean difference: 4.2 ± 5.1 pmol L-1 120 min). CONCLUSIONS: When ingested alone, milk minerals rich in calcium do not increase GLP-1 secretion compared to calcium citrate. Co-ingesting high-dose whey protein hydrolysate with milk minerals rich in calcium increases postprandial GLP-1 concentrations to some of the highest physiological levels ever reported. Registered at ClinicalTrials.gov: NCT03232034, NCT03370484, NCT03370497.

Skipping Breakfast Before Exercise Creates a More Negative 24-hour Energy Balance: A Randomized Controlled Trial in Healthy Physically Active Young Men.

BACKGROUND: At rest, omission of breakfast lowers daily energy intake, but also lowers energy expenditure, attenuating any effect on energy balance. The effect of breakfast omission on energy balance when exercise is prescribed is unclear. OBJECTIVES: The aim of this study was to assess the effect on 24-h energy balance of omitting compared with consuming breakfast prior to exercise. METHODS: Twelve healthy physically active young men (age 23 ± 3 y, body mass index 23.6 ± 2.0 kg/m2) completed 3 trials in a randomized order (separated by >1 week): a breakfast of oats and milk (431 kcal; 65 g carbohydrate, 11 g fat, 19 g protein) followed by rest (BR); breakfast before exercise (BE; 60 min cycling at 50 % peak power output); and overnight fasting before exercise (FE). The 24-h energy intake was calculated based on the food consumed for breakfast, followed by an ad libitum lunch, snacks, and dinner. Indirect calorimetry with heart-rate accelerometry was used to measure substrate utilization and 24-h energy expenditure. A [6,6-2H2]glucose infusion was used to investigate tissue-specific carbohydrate utilization. RESULTS: The 24-h energy balance was -400 kcal (normalized 95% CI: -230, -571 kcal) for the FE trial; this was significantly lower than both the BR trial (492 kcal; normalized 95% CI: 332, 652 kcal) and the BE trial (7 kcal; normalized 95% CI: -153, 177 kcal; both P < 0.01 compared with FE). Plasma glucose utilization in FE (mainly representing liver glucose utilization) was positively correlated with energy intake compensation at lunch (r = 0.62, P = 0.03), suggesting liver carbohydrate plays a role in postexercise energy-balance regulation. CONCLUSIONS: Neither exercise energy expenditure nor restricted energy intake via breakfast omission were completely compensated for postexercise. In healthy men, pre-exercise breakfast omission creates a more negative daily energy balance and could therefore be a useful strategy to induce a short-term energy deficit. This trial was registered at clinicaltrials.gov as NCT02258399.

Preexercise breakfast ingestion versus extended overnight fasting increases postprandial glucose flux after exercise in healthy men.

The aim of this study was to characterize postprandial glucose flux after exercise in the fed versus overnight fasted state and to investigate the potential underlying mechanisms. In a randomized order, twelve men underwent breakfast-rest [(BR) 3 h semirecumbent], breakfast-exercise [(BE) 2 h semirecumbent before 60 min of cycling (50% peak power output)], and overnight fasted exercise [(FE) as per BE omitting breakfast] trials. An oral glucose tolerance test (OGTT) was completed after exercise (after rest on BR). Dual stable isotope tracers ([U-13C] glucose ingestion and [6,6-2H2] glucose infusion) and muscle biopsies were combined to assess postprandial plasma glucose kinetics and intramuscular signaling, respectively. Plasma intestinal fatty acid binding (I-FABP) concentrations were determined as a marker of intestinal damage. Breakfast before exercise increased postexercise plasma glucose disposal rates during the OGTT, from 44 g/120 min in FE {35 to 53 g/120 min [mean (normalized 95% confidence interval)] to 73 g/120 min in BE [55 to 90 g/120 min; P = 0.01]}. This higher plasma glucose disposal rate was, however, offset by increased plasma glucose appearance rates (principally OGTT-derived), resulting in a glycemic response that did not differ between BE and FE ( P = 0.11). Plasma I-FABP concentrations during exercise were 264 pg/ml (196 to 332 pg/ml) lower in BE versus FE ( P = 0.01). Breakfast before exercise increases postexercise postprandial plasma glucose disposal, which is offset (primarily) by increased appearance rates of orally ingested glucose. Therefore, metabolic responses to fed-state exercise cannot be readily inferred from studies conducted in a fasted state.

Venous blood provides lower glucagon-like peptide-1 concentrations than arterialized blood in the postprandial but not the fasted state: Consequences of sampling methods.

NEW FINDINGS: What is the central question of this study? Glucagon-like peptide-1 (GLP-1) is an important obesity/diabetes target, with effects dependent on circulating GLP-1 concentrations. Peripheral tissues extract GLP-1; therefore, sampling venous versus arterialized blood might provide different GLP-1 concentrations. This study examined whether arterialization alters GLP-1 concentrations during fasting and feeding. What is the main finding and its importance? This study demonstrates that venous blood provides lower postprandial but not fasting GLP-1 concentrations versus arterialized blood. Therefore, when accurate assessment of postprandial peripheral availability of GLP-1 is required, blood sampling methods should be considered carefully, reported clearly, and arterialization is recommended. ABSTRACT: Glucagon-like peptide-1 (GLP-1) displays concentration-dependent effects on metabolism, appetite and angiogenesis; therefore, accurate determination of circulating GLP-1 concentrations is important. In this study, we compared GLP-1 concentrations in venous versus arterialized blood in both fasted and fed conditions. Venous and arterialized blood samples were obtained simultaneously from 10 young, healthy men before and 30, 60 and 120 min after ingestion of 75 g glucose. Plasma GLP-1 concentrations increased in response to glucose ingestion (time effect, P < 0.01) and to a lesser extent in venous versus arterialized plasma (time × arterialization interaction, P < 0.01). Accordingly, the plasma incremental area under the curve was lower in venous versus arterialized plasma (974 ± 88 versus 1214 ± 115 pmol l (120 min)-1 , respectively, P = 0.049). In the postprandial state, there was a positive relationship between arterialized GLP-1 concentrations and the venous-arterialized difference in GLP-1 concentrations (r2  = 0.51; P < 0.01). Both arterialized and venous peak GLP-1 concentrations showed positive relationships with peak arterialized insulin concentrations (both r2  > 0.6, P < 0.01). Venous sampling results in lower concentrations of GLP-1 in the postprandial but not the fasted state compared with arterialized blood. This absolute difference is biologically meaningful and is magnified when GLP-1 availability is high. Therefore, sampling from arterialized blood may provide a better chance of detecting small differences in postprandial GLP-1 availability with interventions. If absolute GLP-1 concentrations are of interest, the blood sampling method should be considered carefully and reported clearly.

Prior exercise alters the difference between arterialised and venous glycaemia: implications for blood sampling procedures.

Oral glucose tolerance and insulin sensitivity are common measures, but are determined using various blood sampling methods, employed under many different experimental conditions. This study established whether measures of oral glucose tolerance and oral glucose-derived insulin sensitivity (insulin sensitivity indices; ISI) differ when calculated from venous v. arterialised blood. Critically, we also established whether any differences between sampling methods are consistent across distinct metabolic conditions (after rest v. after exercise). A total of ten healthy men completed two trials in a randomised order, each consisting of a 120-min oral glucose tolerance test (OGTT), either at rest or post-exercise. Blood was sampled simultaneously from a heated hand (arterialised) and an antecubital vein of the contralateral arm (venous). Under both conditions, glucose time-averaged AUC was greater from arterialised compared with venous plasma but importantly, this difference was larger after rest relative to after exercise (0·99 (sd 0·46) v. 0·56 (sd 0·24) mmol/l, respectively; P<0·01). OGTT-derived ISIMatsuda and ISICederholm were lower when calculated from arterialised relative to venous plasma and the arterialised-venous difference was greater after rest v. after exercise (ISIMatsuda: 1·97 (sd 0·81) v. 1·35 (sd 0·57) arbitrary units (au), respectively; ISICederholm : 14·76 (sd 7·83) v. 8·70 (sd 3·95) au, respectively; both P<0·01). Venous blood provides lower postprandial glucose concentrations and higher estimates of insulin sensitivity, compared with arterialised blood. Most importantly, these differences between blood sampling methods are not consistent after rest v. post-exercise, preventing standardised venous-to-arterialised corrections from being readily applied.

Substituting carbohydrate at lunch for added protein increases fat oxidation during subsequent exercise in healthy males.

CONTEXT: How pre-exercise meal composition influences metabolic and health responses to exercise later in the day is currently unclear. OBJECTIVE: Examine the effects of substituting carbohydrate for protein at lunch on subsequent exercise metabolism, appetite, and energy intake. METHODS: Twelve healthy males completed three trials in randomized, counterbalanced order. Following a standardized breakfast (779 ± 66 kcal; ∼08:15), participants consumed a lunch (1186 ± 140 kcal; ∼13:15) containing either 0.2 g·kg-1 carbohydrate and ∼2 g·kg-1 protein (LO-CARB), 2 g·kg-1 carbohydrate and ∼0.4 g·kg-1 protein (HI-CARB), or fasted (FAST). Participants later cycled at ∼60% V̇O2peak for 1 h (∼16:15) and post-exercise ad-libitum energy intake was measured (∼18:30). Substrate oxidation, subjective appetite, and plasma concentrations of glucose, insulin, non-esterified fatty acids (NEFA), peptide YY (PYY), glucagon-like peptide-1 (GLP-1), and acylated ghrelin (AG) were measured for 5 h post-lunch. RESULTS: Fat oxidation was greater during FAST (+11.66 ± 6.63 g) and LO-CARB (+8.00 ± 3.83 g) than HI-CARB (p < 0.001), with FAST greater than LO-CARB (+3.67 ± 5.07 g; p < 0.05). NEFA were lowest in HI-CARB and highest in FAST, with insulin demonstrating the inverse response (all p < 0.01). PYY and GLP-1 demonstrated a stepwise pattern, with LO-CARB greatest and FAST lowest (all p < 0.01). AG was lower during HI-CARB and LO-CARB versus FAST (p < 0.01). Energy intake in LO-CARB was lower than FAST (-383 ± 233 kcal; p < 0.001) and HI-CARB (-313 ± 284 kcal; p < 0.001). CONCLUSION: Substituting carbohydrate for protein in a pre-exercise lunch increased fat oxidation, suppressed subjective and hormonal appetite, and reduced post-exercise energy intake.

Characterising 24-h skeletal muscle gene expression alongside metabolic & endocrine responses under diurnal conditions.

CONTEXT: Skeletal muscle plays a central role in the storage, synthesis, and breakdown of nutrients, yet little research has explored temporal responses of this human tissue, especially with concurrent measures of systemic biomarkers of metabolism. OBJECTIVE: To characterise temporal profiles in skeletal muscle expression of genes involved in carbohydrate metabolism, lipid metabolism, circadian clocks, and autophagy and descriptively relate them to systemic metabolites and hormones during a controlled laboratory protocol. METHODS: Ten healthy adults (9M/1F, mean ± SD: age: 30 ± 10 y; BMI: 24.1 ± 2.7 kg·m-2) rested in the laboratory for 37 hours with all data collected during the final 24 hours of this period (i.e., 0800-0800 h). Participants ingested hourly isocaloric liquid meal replacements alongside appetite assessments during waking before a sleep opportunity from 2200-0700 h. Blood samples were collected hourly for endocrine and metabolite analyses, with muscle biopsies occurring every 4 h from 1200 h to 0800 h the following day to quantify gene expression. RESULTS: Plasma insulin displayed diurnal rhythmicity peaking at 1804 h. Expression of skeletal muscle genes involved in carbohydrate metabolism (Name - Acrophase; GLUT4 - 1440 h; PPARGC1A -1613 h; HK2 - 1824 h) and lipid metabolism (FABP3 - 1237 h; PDK4 - 0530 h; CPT1B - 1258 h) displayed 24 h rhythmicity that reflected the temporal rhythm of insulin. Equally, circulating glucose (0019 h), NEFA (0456 h), glycerol (0432 h), triglyceride (2314 h), urea (0046 h), CTX (0507 h) and cortisol concentrations (2250 h) also all displayed diurnal rhythmicity. CONCLUSION: Diurnal rhythms were present in human skeletal muscle gene expression as well systemic metabolites and hormones under controlled diurnal conditions. The temporal patterns of genes relating to carbohydrate and lipid metabolism alongside circulating insulin are consistent with diurnal rhythms being driven in part by the diurnal influence of cyclic feeding and fasting.

Adipocyte hypertrophy in mesenchymal stem cells from infants of mothers with obesity.

OBJECTIVE: Fat content of adipocytes derived from infant umbilical cord mesenchymal stem cells (MSCs) predicts adiposity in children through 4 to 6 years of age. This study tested the hypothesis that MSCs from infants born to mothers with obesity (Ob-MSCs) exhibit adipocyte hypertrophy and perturbations in genes regulating adipogenesis compared with MSCs from infants of mothers with normal weight (NW-MSCs). METHODS: Adipogenesis was induced in MSCs embedded in three-dimensional hydrogel structures, and cell size and number were measured by three-dimensional imaging. Proliferation and protein markers of proliferation and adipogenesis in undifferentiated and adipocyte differentiating cells were measured. RNA sequencing was performed to determine pathways linked to adipogenesis phenotype. RESULTS: In undifferentiated MSCs, greater zinc finger protein (Zfp)423 protein content was observed in Ob- versus NW-MSCs. Adipocytes from Ob-MSCs were larger but fewer than adipocytes from NW-MSCs. RNA sequencing analysis showed that Zfp423 protein correlated with mRNA expression of genes enriched for cell cycle, MSC lineage specification, inflammation, and metabolism pathways. MSC proliferation was not different before differentiation but declined faster in Ob-MSCs upon adipogenic induction. CONCLUSIONS: Ob-MSCs have an intrinsic propensity for adipocyte hypertrophy and reduced hyperplasia during adipogenesis in vitro, perhaps linked to greater Zfp423 content and changes in cell cycle pathway gene expression.

Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes.

Background: Continuous glucose monitors (CGMs) provide high-frequency information regarding daily glucose variation and are recognised as effective for improving glycaemic control in individuals living with diabetes. Despite increased use in individuals with non-diabetic blood glucose concentrations (euglycemia), their utility as a health tool in this population remains unclear. Objectives: To characterise variation in time in range (TIR) and glycaemic variability in large populations without diabetes or impaired glucose tolerance; describe associations between CGM-derived glycaemic metrics and metabolic and cardiometabolic health traits; identify key diet and lifestyle factors associated with TIR and glycaemic variability. Design: Glycaemic variability (coefficient of variation) and time spent in both the ADA secondary target range (TIRADA; 3.9-7.8 mmol/L) and a more stringent range (TIR3.9-5.6; 3.9-5.6 mmol/L) were calculated during free-living in PREDICT 1, PREDICT 2, and PREDICT 3 euglycaemic community-based volunteer cohorts. Associations between CGM derived glycaemic metrics, markers of cardiometabolic health, diet (food frequency questionnaire and logged diet records), diet-habits, and lifestyle were explored. Results: Data from N=4135 participants (Mean SD; Age: 47 12 y; Sex: 83% Female, BMI: 27 6 kg/m2). Median glycaemic variability was 14.8% (IQR 12.6-17.6%), median TIRADA was 95.8% (IQR 89.6-98.6%) and TIR3.9-5.6 was 75.0% (IQR 64.6-82.8%). Greater TIR3.9-5.6 was associated with lower HbA1c, ASCVD 10y risk and HOMA-IR (all p < 0.05). Lower glycaemic variability was associated with lower % energy derived from carbohydrate (rs: 0.17, p < 0.01), ultra-processed foods (NOVA 4, % EI; rs: 0.12, p = 0.01) and a longer overnight fasting duration (rs: -0.10, p = 0.01). Conclusions: A stringent TIR target provides sensitivity to detect changes in HOMA-IR, ASCVD 10 y risk and HbA1c that were not detected using ADA secondary targets. Associations among TIR, glycaemic variability, dietary intake (e.g. carbohydrate and protein) and habits (e.g. nocturnal fasting duration) highlight potential strategic targets to improve glycaemic metrics derived from continuous glucose monitors.