Postprandial lipaemia (PPL) is characterised by the dynamic changes in TAG and TAG-rich lipoproteins (i.e. chylomicrons, VLDL and their remnants) that occur following ingestion of dietary lipid(Reference Pirillo, Norata and Catapano1). Chylomicrons, specifically, transport reassembled TAG from the enterocytes to the liver and their number (characterised by apoB48 which is constitutive) and/or size increase when a fat-containing meal is ingested, then return to baseline over several hours as TAG are cleared from circulation(Reference Tomkin and Owens2). The nature of the PPL response is recognised as an important risk factor for CVD(Reference Pirillo, Norata and Catapano1). In fact, non-fasting TAG concentrations are a more significant risk factor for CHD events than fasting levels(Reference Nakajima, Nagamine and Fujita3). Oral fat tolerance tests (OFTT) in which an individual consumes a standard high amount of fat with serial blood sampling for analysis of blood lipids can be used to study PPL and identify individuals with impaired lipid metabolism(Reference Lairon, Lopez-Miranda and Williams4). For example, chylomicron overproduction is a characteristic of individuals with insulin resistance, type 2 diabetes(Reference Dias, Moughan and Wood5) and obesity(Reference Wong, Chan and Pang6); smaller and more numerous chylomicrons have been reported in older v. younger populations(Reference Milan, Nuora and Pundir7) and in hypertriacylglycerolaemic abdominally obese v. lean women(Reference Mekki, Christofilis and Charbonnier8). Smaller chylomicrons are also postulated to clear more slowly from circulating plasma(Reference Nordestgaard and Freiberg9), which correlates with their potential atherogenicity as they are able to penetrate the arterial wall and induce inflammation and oxidative stress in the subendothelial space(Reference Proctor, Vine and Mamo10). OFTT can also be used to study the influence of dietary strategies on the extent and/or duration of PPL. Such investigations are especially warranted in overweight and obese individuals as they tend to have impaired lipid metabolism, involving increased production and/or insufficient clearance of TAG-rich lipoproteins, resulting in elevated plasma TAG levels and prolonged PPL(Reference Dias, Moughan and Wood5,Reference Tiihonen, Rautonen and Alhoniemi11) .
Fruit and vegetable consumption, which is generally recommended to reduce CVD risk, may impact PPL. This is partly related to their contents of dietary fibre, which can alter various parameters that contribute to lipid digestion and absorption(Reference Fock and Khoo12). For example, apple skin contains the soluble fibre pectin. Apple pectin is a polysaccharide consisting of a homogalacturonan backbone esterified with methoxyl groups(Reference Thakur, Singh and Handa13). It has a relatively high molecular weight (104–106 Da) and degree of esterification (>70 %)(Reference Miceli-Garcia14) and gels at a pH of 3·6 in the presence of a co-solute (e.g. sucrose), inducing viscosity(Reference Thakur, Singh and Handa13). Apple pectin consumption has been shown to delay gastric emptying(Reference Schwartz, Levine and Singh15,Reference Di Lorenzo, Williams and Hajnal16) and to lower fasting blood cholesterol(Reference Brouns, Theuwissen and Adam17,Reference Miettinen and Tarpila18) in humans. In another instance, purified pectin (unknown source but highly esterified) also reduced fasting plasma TAG in a hamster model(Reference Trautwein, Kunath-Rau and Erbersdobler19), and pectin-rich dried beet pulp powder lowered the postprandial TAG response in pigs(Reference Leclere, Lairon and Champ20). In vitro, pectins have also been shown to alter the rate and/or extent of lipid digestion(Reference Lin and Wright21,Reference Espinal-Ruiz, Parada-Alfonso and Restrepo-Sánchez22) and to bind bile salts(Reference Cheewatanakornkool, Chaidedgumjorn and Sotanaphun23,Reference Dongowski24) , which otherwise promote the solubilisation of hydrolysed lipids in the digestate. Apples are also rich in polyphenols, mainly flavanols (e.g. catechin and proanthocyanidins) and hydroxycinnamic acid derivatives(Reference Vrhovsek, Rigo and Tonon25) that can play a role in PPL. For example, apple procyanidins inhibited pancreatic lipase activity in vitro and reduced postprandial TAG elevation in mice(Reference Sugiyama, Akazome and Shoji26). Apple procyanidins also reduced the secretion of TAG-rich lipoproteins in human Caco-2/TC7 enterocytes in vitro, pointing to a possible hypolipidaemic effect in vivo (Reference Vidal, Hernandez-Vallejo and Pauquai27). Another study with rats found that apple pectin improved large intestinal fermentation and reduced fasting plasma TAG and cholesterol more efficiently in the presence of apple polyphenols, suggesting synergy between these molecules(Reference Aprikian, Duclos and Guyot28) with respect to PPL. That said, human studies related to apples and lipaemia have largely focused on fasting blood lipids and have yielded mixed results. In hyperlipidaemic overweight men, 8-week consumption of Golden Delicious apples (300 g/d) increased fasting serum TAG and VLDL(Reference Vafa, Haghighatjoo and Shidfar29), whereas another study found that 4-week consumption of whole apples (unknown variety) (550 g/d) or apple pomace (22 g/d), compared with fibre-free apple juice (500 ml/d), decreased fasting LDL-cholesterol concentrations in healthy participants, highlighting the role of apple fibres in lowering LDL(Reference Ravn-Haren, Dragsted and Buch-Andersen30). Whole apples and apple-derived products also contain sugars, especially fructose, which can also impact PPL(Reference Lairon, Play and Jourdheuil-Rahmani31).
In summary, apples as a complex food matrix show potential to alter fasting lipids, but their role in PPL has not been investigated. Therefore, the present study aimed to use an OFTT to explore the effects of whole Gala apple (a common variety produced in Ontario, Canada) consumption on PPL (plasma TAG, apoB48, chylomicrons and remnants particle sizes and fatty acid (FA) composition), as well as on gastric emptying, glycaemia and insulinaemia. Overweight and obese individuals were selected given their greater propensity for impaired PPL metabolism and because fruit and vegetable consumption is recommended to these individuals as a strategy both for weight management and metabolic disease risk reduction(Reference Lichtenstein, Appel and Brands32). It was hypothesised that apple consumption would reduce the magnitude of PPL by slowing down gastric emptying of the OFTT meal.
Materials and methods
Participants
Participants were recruited through flyer, Internet, newspaper and radio advertisements in Guelph, Ontario, Canada, and the surrounding communities. Inclusion criteria were: 18–75 years; BMI ≥ 25·0 kg/m2; generally healthy; non-alcoholic; non-smoker; non-diabetic; free of digestive, cardiovascular or inflammatory diseases/disorders; stable body weight (<5 % fluctuation) for the previous 3 months and no intention to gain or lose weight. Individuals were excluded if they were: hospitalised due to serious medical conditions within the last year; taking medications that could interfere with the study outcomes; allergic or intolerant to any ingredients in the test meals; pregnant, breast-feeding or post-menopausal. A fasting TAG concentration ≥ 1·69 mmol/l was initially required, but it was not feasible to find hyperlipidaemic individuals who were otherwise eligible, so this criteria was removed. Of the 179 persons screened, fifty-one were invited for further screening, among which twenty-eight met the criteria and were enrolled in the study, all of which took place from January 2017 to September 2018.
Study design and protocols
This was a randomised, cross-over acute meal study conducted at the Human Nutraceutical Research Unit at the University of Guelph. The study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human participants were approved by the University of Guelph Human Research Ethics Board (REB no. 16JA013) and registered at clinicaltrials.gov (NCT03523403, The Apple Study: Investigating the Effects of Whole Apple Consumption on Risk Factors for Chronic Metabolic Diseases in Overweight and Obese Adults, https://clinicaltrials.gov/ct2/show/NCT03523403). All participants provided written informed consent. Each participant attended two study visits separated by a 1-week wash-out period. They were randomised based on their order of study enrolment using a random number table (generated by Excel, Microsoft Ltd, organised by an external party) to consume a dairy-based OFTT meal with or without apples at each visit. Due to the nature of the treatments, participants and researchers were not blinded at each study visit, although samples and data were coded based only on study visit days in order to conceal treatment allocation during their handling and analyses. For 2 weeks before the first study visit, participants were counselled to avoid foods from a three-page long list of foods rich in polyphenols and/or dietary fibres (e.g. berries, purple and red potatoes, chocolate and coffee), but to otherwise maintain their dietary and exercise habits which were recorded in a study diary. For 48 h before each study visit, participants abstained from alcohol, exercise and over-the-counter medications (including acetaminophen-containing products). Participants consumed a standardised low-fat (12·0–12·5 g fat per serving) dinner the night before each study visit. This consisted of one serving of vegetarian lasagna (President’s Choice Blue Menu), a cranberry almond granola bar (President’s Choice Chewy Trail Mix), a pudding (Hunt’s, chocolate or vanilla flavoured), and a juice box (President’s Choice, apple or fruit punch). On the morning of each study visit, participants arrived at the research centre having fasted for 10–12 h and completed a brief questionnaire for compliance to protocol. Water consumption was encouraged for up to 1 h before a phlebotomist inserted an intravenous catheter for fasting and periodic blood sampling over 6 h. Participants consumed the test meals within 15 min, and baseline (i.e. 0 min) was from when they started to consume the meal. Throughout the day, participants remained seated with only short washroom breaks.
Test meal treatments
During each study visit, participants consumed the OFTT meal, which was a 500 ml mixture of 35 % fat whipping cream and skimmed milk, standardised with additional skimmed milk powder such that each meal provided 1 g fat/kg body weight and 14·6 g protein. Extra Strength Tylenol® (00559407) containing 1500 mg acetaminophen was ground and added to each meal shortly before consumption by participants, for indirect assessment of gastric emptying(Reference Willems, Otto Quartero and Numans33). Fat consumption was based on body weight to take into account the larger blood volume in overweight and obese participants(Reference Lairon, Lopez-Miranda and Williams4), but the same approach did not apply for acetaminophen to avoid potential overdose in extremely obese participants (total amount taken in a day should not exceed 4000 mg(34)). Regarding protein, its content in the cream-skimmed milk mixture decreased with an increasing fat content; therefore, skimmed milk powder was added to eliminate any potential PPL-lowering effects based on differences in protein consumption(Reference Westphal, Taneva and Kästner35). The OFTT meal was well tolerated by most participants, although one participant vomited 20 min after its consumption and discontinued participation. Three Gala apples (Martin’s Family Fruit Farm and Norfolk Fruit Growers Association) were cored and sliced without removing the skin (approximately 200 g total) and then consumed along with the OFTT meal at one of the study visits. The pectin and total polyphenol contents of the Gala apples were measured using colorimetric assays. Whole apples were cored and sliced and then freeze-dried (VirTis Genesis 35 L pilot lyophilizer; Stone Ridge). For pectin analysis, alcohol insoluble solids were extracted from the dried apples and then hydrolysed by sulphuric acid to galacturonic acid, which was reacted with m-hydroxydiphenyl. Absorption was measured at 525 nm using a UV–vis spectrophotometer (Hewlett Packard 8451 A Diode Array Spectrophotometer), and concentration was determined using a standard curve based on d-galacturonic acid (0–0·5 mg/ml)(Reference Melton, Smith, Wrolstad, Acree and Decker36). For the total phenolic analysis, the dried apples were homogenised with acidified methanol to remove vitamin C and the extract was mixed with the Folin–Ciocalteu reagent and sodium carbonate solution, followed by absorbance measurements at 750 nm and using a standard curve based on gallic acid (0–0·156 mg/ml)(Reference Almeida, de Sousa and Arriaga37). The meals’ nutrient compositions are provided in Table 1.
Nutrient composition of the test meals*
OFTT, oral fat tolerance test.
* Values calculated based on nutrient reports in Health Canada Nutrients Database(46), unless otherwise stated.
† To convert kcal to kJ, multiply by 4·184.
‡ Calculated based on product labels (for the OFTT meal) and nutrient reports in Health Canada Nutrients Database (for apples).
§ Depends on participants’ body weight, aiming to provide 1 g fat/kg body weight.
‖ Presented as galacturonic acid equivalents.
¶ Presented as gallic acid equivalents.
Blood sampling and analysis
Blood samples were taken at baseline, every 20 min within the first 3 h, and at 4, 5 and 6 h. All samples were drawn from the antecubital vein into EDTA vacutainer tubes via an intravenous line (Vacutainer®; K2EDTA, BD). After centrifugation at 625 g (Allegra TM X-22 R Centrifuge; Beckman Coulter Incorporated) at 4°C for 10 min, plasma was collected, aliquoted into cryovials in small volumes and immediately stored at −80°C until analysis by commercial assays. Plasma concentrations of the primary outcome, that is, plasma TAG (Wako Diagnostics), and secondary outcomes, that is, apoB48 (Cloud Clone), acetaminophen (Neogen), glucose (Wako Diagnostics) and insulin (Mercodia AB) were determined according to the manufacturers’ instructions. The intra-assay variabilities were 10·0, 7·3, 5·3, 8·8 and 5·9 % for TAG, apoB48, acetaminophen, glucose and insulin, respectively. Fasting cholesterol concentrations were determined immediately from a drop of whole venous blood using the Cholestech LDX Lipid Analyzer (Cholestech).
Chylomicron-rich fraction analysis
The chylomicron-rich fraction (CMRF) was separated from plasma based on Vors et al.(Reference Vors, Pineau and Gabert38) with slight modifications for determination of the secondary outcomes CMRF particle size and FA composition(Reference Almeida, de Sousa and Arriaga37). Briefly, 3·0 ml plasma was overlaid with 2·5 ml saline solution (d = 1·006 g/ml) and centrifuged at 3·9 × 105 g (at r max; Beckman Coulter) at room temperature for 23 min (Sorvall WX Ultra 80; ThermoFisher Scientific). The top layer, which was white and cloudy, was aspirated for immediate particle size analysis by dynamic light scattering (NanoZetasizer S, Malvern Instruments), using a refractive index of 1·450 for human plasma protein and absorption of 0·001 as input parameters for calculations(Reference Milan39). A portion was also stored in an Eppendorf tube at −80°C and analysed for FA composition by GC within 1 month of sample collection. Lipid extractions for GC analysis were performed based on the Folch method with slight modifications(Reference Martin, Nieto-Fuentes and Señoráns40). Briefly, 0·03 ml of CMRF was vortexed with 0·97 ml of 0·1m KCl and 4 ml of chloroform–methanol (2:1) until well mixed. The mixture was flushed with N2 and set at 4°C overnight before centrifugation at 300 g for 10 min. The lower chloroform layer was collected and dried under N2 and then saponified by 2 ml of 0·5m KOH in methanol at 100°C for 1 h. After cooling to room temperature, methylation was carried out with 2 ml hexane and 2 ml 14 % BF3-methanol at 100°C for 1 h. After the mixture was cooled, 2 ml water was added to stop the methylation and the mixture vortexed and centrifuged at 300 g for 10 min. The top hexane layer containing the FA methyl esters was collected and dried down under N2 and then reconstituted in 1 ml of hexane for analysis. FA methyl esters were separated by GC (Agilent 6890 Network GC System; Agilent Technologies) with a Supelco SP 2560 fused-silica capillary column (100 m × 0·25 mm internal diameter, 0·2 μm film thickness; Sigma-Aldrich). The FA composition is presented as % total area count, calculated by dividing the peak area of the target FA by the total area. SFA and unsaturated fatty acids (UFA) from C10 : 0 to C24 : 0 were grouped separately for calculating their % total area counts and the ratio between them (SFA:UFA ratio). The same methods were used to determine FA profiles of the OFTT meal.
Data and statistical analyses
The required number of participants was 34, based on an a priori calculation using a two-tailed model for a matched pairs mean comparison in TAG C max, with a medium effect size (Cohen’s d coefficient = 0·5(Reference Sawilowsky41)), a probability of a type I error of 0·05 and a power of 0·8 (G* Power Software, version 3.1.9.4., Universität Düsseldorf). All measurements were completed with replicates (duplicates for plasma endpoint analyses by kits and triplicates for GC and particle size analyses), and the data were then averaged and analysed using Statistical Package for the Social Sciences version 21 (SPSS; IBM Corporation). Two outlying values (one for TAG and another one for glucose, based on z-scores method, Table 2) were excluded from the statistical analysis. Data normality was assessed using Shapiro–Wilk testing. All normally distributed data are presented as the arithmetic means with their standard errors. When not normally distributed, data were log-transformed and presented as geometric means with average transformed standard errors, as indicated. All fasting endpoints were compared between study visits 1 and 2 using paired-sample t tests. Fasting glucose and insulin concentrations were used to calculate the homoeostatic model assessment of insulin resistance (HOMA-IR), using the HOMA2 Calculator (version 2.2.3, Diabetes Trials Unit, University of Oxford). For the postprandial time-wise data, repeated-measures ANCOVA were performed with centred baseline value (i.e. individual baseline value minus mean baseline value) as a covariate, as suggested in Schneider et al.(Reference Schneider, Avivi-Reich and Mozuraitis42), and Bonferroni post hoc testing with a significance level of P < 0·05. For each endpoint, the effects of treatment (OFTT meal with or without apples), time (postprandial time points) and treatment × time interactions were assessed. Participant characteristics, including sex, age, body weight and BMI, were added into the ANCOVA models as between-subject factors or covariates (for nominal or continuous values, respectively) to assess their effects on the endpoints, but none of them was significant in the models. Therefore, the ANCOVA for each endpoint included only the centred baseline value as a covariate. Incremental AUC (iAUC) was calculated using the linear trapezoidal method (GraphPad Prism version 7.04 for Windows, www.graphpad.com) and compared using ANCOVA using centred baseline values as a covariate. Maximum concentrations (C max) of each endpoint were identified as the greatest value in an individual’s data set and maximum peak times (T max) identified as the corresponding nominal sampling time. Mean C max and median T max are reported. Values of C max were compared using paired-sample t testing, while T max values were compared using median test for two independent samples t test. Statistical analyses were also performed on change from baseline values, but no differences in results were observed from those based on absolute values (data not shown). Effect size was estimated as Cohen’s d, calculated as the difference between pairwise means divided by pooled standard deviations(Reference Sawilowsky41).
Characteristics and fasting blood measurements for male (n 9) and female (n 17) participants*
(Mean values with their standard errors; ranges)
HOMA-IR, homoeostatic model assessment of insulin resistance; CMRF, chylomicron-rich fraction; UFA, unsaturated fatty acids.
* Values are the average of the fasting measurements on both study visit days.
† n 25 (one male participant outlying value eliminated from the data sets).
‡ n 25.
§ n 16 (one female participant outlying value eliminated from the data sets).
Results
Participant characteristics
Of the twenty-eight participants enrolled, twenty-six completed the study (Fig. 1). Participant characteristics and fasting measurements are shown in Table 2. There were no differences in participant characteristics or fasting blood measurements between the two study visits (P > 0·05 for all measurements, data not shown).
Consolidated Standards of Reporting Trials (CONSORT) flow diagram of the study. HFM, high-fat meal.
Postprandial TAG and apoB48
Plasma TAG concentrations increased rapidly in the first 3 h (P < 0·05) after the consumption of both meals and began to decrease after 5 h (Fig. 2(a)). There was no effect of apple ingestion on postprandial TAG concentration (P treatment = 0·731, Fig. 2(a)). Similarly, peak TAG concentration (C max), TAG iAUC and time to peak concentration (T max) were not different when the OFTT meal was consumed alone v. with three apples (P = 0·921, 0·385 and 0·266, respectively, Table 3). There were significant effects of time (P time = 0·007), but not treatment, in terms of apoB48 concentration (P treatment = 0·088, Fig. 2(b)). ApoB48 iAUC and median T max values also did not differ between treatments (P = 0·257 and 0·375, respectively, Table 3), although apoB48 C max was higher with apples (P = 0·007, Table 3).
Postprandial plasma TAG (a) and apoB48 (b) concentrations following an oral fat tolerance test (OFTT) meal with and without apples. Data are means with their standard errors, (a) n 25 per treatment (one female participant outlying data removed from database) and (b) n 26. P time, P treatment and P treatment×time refer to results from repeated-measures ANCOVA, using centred fasting TAG (a) and apoB48 (b) values as covariates, followed by Bonferroni post hoc testing. 
, With apple; 
, without apple.
Postprandial TAG, apoB48, glucose, insulin and acetaminophen iAUC, C max and T max values following ingestion of oral fat tolerance test meals with and without apples*
(Mean values with their standard errors)
iAUC, incremental AUC; C max, maximum concentration; T max, time to reach the maximum concentration.
* iAUC and C max of different treatment groups were compared using ANCOVA with fasting values as covariates, while T max were compared using the median test. iAUC and C max values are presented as means with their standard errors and T max are medians; n 26 per treatment.
† n 25, as one female participant outlying data removed from the database.
‡ n 25, as one male participant outlying data removed from the database.
Postprandial size and fatty acid composition of the chylomicron-rich fraction
CMRF particle size increased rapidly within 2 h of meal ingestion (P < 0·05) and reached a plateau, not changing between 4 and 6 h (P = 0·420, Fig. 3(a)). There were no differences in postprandial CMRF size between treatments over 6 h (P treatment = 0·935, Fig. 3(a)). The main FA identified in the CMRF were myristic (C14 : 0), palmitic (C16 : 0), palmitoleic (C16 : 1), stearic (C18 : 0), oleic (C18 : 1c9), vaccenic (C18 : 1c11) and linoleic (C18 : 2). The OFTT meal (FA composition shown in Table 4) also contained decanoic (C10 : 0) and lauric (C12 : 0) acids, but these species were not present in appreciable amounts in the CMRF (% total area count < 2 % at peak value, data not shown). For both study visits, the baseline fasting CMRF SFA:UFA ratio was approximately 0·5 (P = 0·110). This ratio increased following OFTT meal ingestion, peaking at 6 h (0·90 (sem 0·02) and 0·84 (sem 0·02) with and without apples, respectively), but there was no difference between treatments at any time point except for a small but significant decrease without apples at 6 h (P < 0·05, Fig. 3(b)). The proportion of individual SFA, including C14 : 0, C16 : 0 and C18 : 0, did increase substantially with time (P time < 0·001, Table 4), as the UFA C16 : 1, C18 : 1c9 and c11, and C18 : 2 decreased (P time < 0·01, Table 4). However, apple consumption was not associated with any differences in CMRF FA composition (P treatment > 0·05, Table 4).
Postprandial chylomicron-rich fraction (CMRF) particle size (a) and ratio between percentage total area count of SFA and unsaturated fatty acids (UFA) (SFA:UFA ratio) (b) after consumption of an oral fat tolerance test (OFTT) meal with or without apple. Data are means with their standard errors, n 26 per treatment. P time, P treatment and P treatment×time refer to results from repeated-measures ANCOVA using centred fasting CMRF particle size (a) and SFA:UFA ratio (b) values as covariates, followed by Bonferroni post hoc testing. * P < 0·01 between with and without apples. Z-average, intensity weighted harmonic mean size measured by dynamic light scattering. , With apple; , without apple.
Fatty acid composition of the oral fat tolerance test (OFTT) meal and chylomicron-rich fraction at fasting and throughout the 6-h postprandial period*
(Mean values with their standard errors)
C14 : 0, myristic acid; C16 : 0, palmitic acid; C16 : 1, palmitoleic acid; C18 : 0, stearic acid; C18 : 1c9, oleic acid; C18 : 1c11, vaccenic acid; C18 : 2, linoleic acid.
* Values are expressed as the percentage of total area counts (%) in GC, n 3 for the OFTT meal and n 26 for postprandial measurements.
† P time and P treatment refer to main effects of time and treatment in ANCOVA after OFTT meal consumption, while P time×treatment was not reported because it was larger than 0·05 for each fatty acid.
Postprandial glucose and insulin
Glucose concentration fluctuated during the postprandial period (P time < 0·05) but did not differ between treatments (P treatment = 0·749, Fig. 4(a)). There was an expected, but statistically insignificant, early rise with the apple treatment. Apple consumption also did not influence postprandial glucose iAUC, C max and T max values (P = 0·446, 0·923 and 1·000, respectively, Table 3). Insulin concentration did increase quickly (P < 0·05) with and without apples and gradually returned to fasting levels by 360 min (Fig. 4(b)). Higher insulin concentrations were observed from 20 to 180 min when apples were ingested (P < 0·05, Fig. 4(b)). iAUC and C max values were also both higher with apples (P < 0·001, Table 4), although T max was 60 min, regardless of treatment (P = 0·760, Table 3).
Postprandial plasma glucose (a) and log-transformed plasma insulin (b) concentrations. (a) Data are means and their standard errors, n 25 per treatment (one male participant outlying data removed from database). (b) Data are geometric means and their average transformed standard errors, n 26 per treatment. P time, P treatment and P treatment×time refer to results from repeated-measures ANCOVA with Bonferroni post hoc testing. * P < 0·05 between with and without apples. , With apple; , without apple.
Postprandial acetaminophen as an indicator of gastric emptying
Acetaminophen concentration increased after ingestion of the meals and slowly decreased towards baseline after 3 h (Fig. 5, P time < 0·001). However, treatment did not have an overall effect on plasma acetaminophen concentration (P treatment = 0·065, Fig. 5), nor did apples affect acetaminophen iAUC, C max or T max (P = 0·440, 0·661 and 0·577, respectively, Table 3).
Log-transformed postprandial plasma acetaminophen concentrations. Data are geometric means and their average transformed standard errors; n 26 per treatment. P time, P treatment and P time×treatment refer to results from repeated-measures ANCOVA with Bonferroni post hoc testing. * P < 0·05 between with and without apples. , With apple; , without apple.
Discussion
While a few human studies have examined the effects of apples on fasting lipid profiles(Reference Vafa, Haghighatjoo and Shidfar29,Reference Ravn-Haren, Dragsted and Buch-Andersen30,Reference Dange and Deshpande43–Reference Avci, Atli and Ergüder45) , their influence on PPL, as a risk factor for CVD, is understudied and remains equivocal. Therefore, the present study aimed to evaluate the influence of consuming whole raw Gala apple with a dairy-based OFTT on PPL in otherwise healthy overweight and obese participants. The three small Gala apples (approximately 200 g edible parts) were equivalent to the weight of one large apple to mimic a fruit serving consumed as part of a meal(46). Postprandial glycaemia and insulinaemia were investigated, as was gastric emptying, to elucidate the mechanisms involved. The main findings were that apple consumption did not influence PPL and that gastric emptying was not implicated.
Study participants’ BMI ranged from 25·4 to 48·2 kg/m2 and with nine and seventeen participants classified as overweight and obese, respectively. The study also included both normolipidaemic (<1·69 mmol/l, n 20) and hyperlipidaemic (≥1·69 mmol/l, n 6, 2 of whom were obese) individuals. Although the average fasting plasma TAG level was 1·42 (sem 0·10) mmol/l, this ranged from 0·66 to 2·31 mmol/l. Interestingly, of the nine overweight participants, four were hyperlipidaemic and, of the seventeen obese participants, only two were hyperlipidaemic. This may have contributed to the absence of expected correlations between postprandial TAG and BMI that has been reported in other instances(Reference Nogaroto, Rodrigues and Vicari47). Overall, the observed PPL response (i.e. the extent and length of TAG elevations) was comparable to previous OFTT studies wherein the same 1 g fat/kg body weight was provided to healthy and overweight(Reference Cohn, McNamara and Cohn48–Reference Robinson, Martin and Robinson50) and obese(Reference Robinson, Martin and Robinson50) participants.
Apple consumption did not alter postprandial TAG, even though animal studies have shown attenuations when purified pectin and polyphenols were ingested(Reference Leclere, Lairon and Champ20,Reference Sugiyama, Akazome and Shoji26) . This discrepancy could be due to the relatively lower levels of these bioactives present in the test meal. For example, Leclere et al. (Reference Leclere, Lairon and Champ20) fed 30 g dried sugar beet pulp fibre containing 4·11–7·32 g soluble fibre (mainly pectin)(51) to pigs weighing approximately 30 kg. In the present study, participants weighed between 71·6 and 154·0 kg and consumed only 2·17 g pectin. Sugiyama et al. (Reference Sugiyama, Akazome and Shoji26) observed that apple polyphenol extract at 1000 mg/kg body weight completely inhibited postprandial TAG elevations in mice. This is also much higher than the levels of apple polyphenols consumed in the present study (i.e. 1·49–3·21 mg/kg body weight). In addition, procyanidins are the most active apple polyphenols in terms of lipase inhibition(Reference Sugiyama, Akazome and Shoji26). The content of procyanidins in the Gala apples consumed by participants is unknown and may have been insufficient to alter lipid digestion. Moreover, compared with the OFTT meal alone, the apple meal contained higher and different amounts of digestible carbohydrates, especially fructose and sucrose (Table 1), which can promote hypertriacylglycerolaemia(Reference Lopez-Miranda, Williams and Lairon52–Reference Saito, Kagaya and Suzuki54). The proposed mechanisms for fructose-induced hypertriacylglycerolaemia include a lower activation of adipose tissue lipoprotein lipase and reduced plasma TAG clearance(Reference Grant, Marais and Dhansay53,Reference Chong, Fielding and Frayn55) , improved de novo lipogenesis(Reference Chong, Fielding and Frayn55,Reference Parks, Skokan and Timlin56) and greater enterocyte chylomicron secretion(Reference Steenson, Umpleby and Lovegrove57). Therefore, apple consumption may have led to fructose-induced postprandial hypertriacylglycerolaemia, counteracting any lipid-lowering potential from the pectin and polyphenols present. Sample size may also have precluded observing statistical significance, as the study was underpowered. Although twenty-six participants are similar to the number of participants in studies where treatment differences in plasma TAG were observed(Reference Robinson, Martin and Robinson50,Reference Kondo, Xiao and Takahashi58,Reference Hall, Fiuza Brito and Huang59) , participants’ postprandial TAG responses were highly variable in the present study (the mean difference of TAG C max between with and without apples was −0·04 (sem 1·11) mmol/l), making the effect size very low (=0·04).
The changes observed in CMRF FA composition reflected the composition of the OFTT meal, as expected(Reference Milan, Nuora and Pundir7,Reference Mu and Høy60) . Specifically, the proportions of SFA (C16 : 0, in particular) increased in the CMRF as the UFA (C18 : 1c9 and C18 : 2) decreased, postprandially. The OFTT had an SFA:UFA ratio of 1·5 (data not shown), and the OFTT consumption significantly increased this ratio in the CMRF (i.e. from approximately 0·5 at fasting to 0·9 and 0·8 at 6 h with and without apples, respectively). The CMRF FA composition did not exactly match the meal, probably because of contributions from FA in the enterocyte storage pools(Reference Mu and Høy60). Research investigating the contribution of dietary fibre to postprandial chylomicron FA composition, in relation to CVD risk, is limited. However, there is demonstrated potential for chylomicron FA composition to influence various metabolic events associated with CVD risk, including the conversion rate from chylomicrons to remnants in rats(Reference Rahman, Avella and Botham61), interactions between chylomicron remnants with isolated rat hepatocytes(Reference Lambert, Avella and Berhane62), and chylomicron remnant-like particle uptake by macrophages in vitro (Reference De Pascale, Avella and Perona63). Nevertheless, in the present study, apple consumption had no effect on FA CMRF incorporation within the 6-h postprandial period.
A wide range of fasting apoB48 concentrations (1·29–40·74 mg/l) were observed, likely related to the variability in participants’ metabolic and health status, including fasting TAG(Reference Sakai, Uchida and Ohashi64). The levels observed are consistent with Sakai et al.(Reference Sakai, Uchida and Ohashi64), which reported fasting apoB48 levels of 5·2 v. 6·4–92·4 mg/l in normolipidaemic v. hyperlipidaemic populations. Postprandial apoB48 increased from baseline (5–10 mg/l) to similar extents as reported by Sakai et al. (Reference Sakai, Uchida and Ohashi64) where participants consumed 30 g fat/m2 body surface of 35 % cream. Because obesity has been associated with exaggerated postprandial apoB48 elevations after a fat load(Reference Wong, Chan and Pang6), differences in postprandial apoB48 increases were explored between the obese and overweight participants, but no differences were found (P = 0·649, data not shown). Changes in apoB48 point to increase in the number of circulating chylomicron and remnant particles, which were modest in the present study. In contrast, CMRF particle size increased more significantly during the postprandial period, reflecting the loading that occurs as dietary TAG are reassembled(Reference Xiao and Lewis65), and agreeing with previous observations that postprandial increases in chylomicron size are much greater than particle number(Reference Xiao and Lewis65,Reference Martins, Mortimer and Miller66) . Postprandial changes in chylomicron size and number are relevant since smaller chylomicrons (and their remnants) in higher numbers tend to increase atherosclerotic risk, due to the ability of these particles to penetrate the arterial intima(Reference Milan, Nuora and Pundir7) coupled with their slower clearance from plasma(Reference Martins, Mortimer and Miller66). However, in the present study, apples did not influence chylomicron number or size, hence did not show potential to impact atherosclerotic risk related to postprandial chylomicron metabolism.
Dietary carbohydrates contribute to postprandial glycaemia and insulinaemia and can therefore influence lipid metabolism, including PPL, through complex processes(Reference Lairon, Play and Jourdheuil-Rahmani31). Participants in the present study generally had fasting glucose and HOMA-IR values consistent with non-elevated risk for diabetes, although oral glucose tolerance tests were not performed. All twenty-six participants had a fasting plasma glucose below 7·0 mmol/l, that is, the cut-off for a diagnosis of diabetes(67). Three participants did have HOMA-IR values above 2·6, that is, the cut-off for a diagnosis of insulin resistance in a population with normal glucose metabolism(Reference Ascaso, Pardo and Real68), although factors that can influence the HOMA-IR cut-off value, including ethnicity, sex and age(Reference Gayoso-Diz, Otero-González and Rodriguez-Alvarez69), were not accounted for in the present study. The dairy-based OFTT meal in the present study contained 20·3–21·5 g sugars comprised mainly of lactose. Relative to other dietary sugars, lactose induces a low glycaemic response(Reference Ostman, Liljeberg Elmstahl and Bjorck70). This explains the minimal changes observed in postprandial glucose for the OFTT meal alone. Although the 200 g apples provided an additional 20·8 g digestible carbohydrates (i.e. 11·9 g fructose, 5·6 g sucrose and 3·3 g glucose, Table 1), this did not lead to a significant rise in postprandial glucose. This may be because much of apples’ available carbohydrate is the disaccharide fructose which induces a lower postprandial plasma glucose rise compared with other common carbohydrates, for example, glucose, dextrose and sucrose(Reference Crapo, Kolterman and Olefsky71). Also, potential rises in plasma glucose owing to the apple carbohydrates could have been offset by contributions from the soluble fibres present, for example, increased gut content viscosity(Reference Fuse, Bamba and Hosoda72,Reference Flourie, Vidon and Florent73) .
Despite the non-significant rises in postprandial glucose, insulin increased substantially both with and without apples. This may be related to the whey protein in the OFTT meal since it is known to promote insulin release(Reference Nilsson, Stenberg and Frid74). Postprandial increases in insulin with the OFTT without apples were similar, although slightly delayed, compared with that observed for whole milk containing similar amounts of protein and carbohydrates, but much less fat(Reference Panahi, El Khoury and Kubant75). The differences are potentially related to the high fat in the present study, which could lead to a slower gastric emptying comparing with lower fat meals(Reference Washington, Washington and Wilson76). Significant rises in plasma insulin were observed with apples between 20 and 180 min. This is similar to observations by Theytaz et al. (Reference Theytaz, de Giorgi and Hodson77), where fructose consumption led to higher plasma insulin, despite no effects on plasma glucose. Insulin concentration is a recognised modulator of TAG-rich lipoprotein synthesis and secretion(Reference Lairon, Play and Jourdheuil-Rahmani31). Although there was no correlation between insulin and apoB48 concentration in the present study (r 2 0·018, P = 0·169, data not shown), the higher peak insulin concentration may partly explain the higher peak apoB48 concentration observed with apple consumption. These results highlight the interactions between lipid and carbohydrate metabolism and the complexity of food matrix effects on postprandial changes, which warrants further investigation.
Gastric emptying controls the rate of digesta delivery to the upper small intestine and is affected by food composition and structure through various mechanisms(Reference Ehrlein and Schemann78). For example, as related to glucose, there is a bi-directional relationship since gastric emptying influences peak postprandial glucose concentrations, but the rate of emptying itself is modulated by acute hyperglycaemia after a meal(Reference Phillips, Deane and Jones79). Pectin, like other soluble dietary fibres, has shown potential to delay gastric emptying in human studies in purified form and at relatively high doses (10–20 g per meal)(Reference Schwartz, Levine and Singh15,Reference Di Lorenzo, Williams and Hajnal16,Reference Sandhu, El Samahi and Mena80) . In the present study, the apples contained 2·17 g pectin, which may have been too low to affect gastric emptying. Moreover, the OFTT meal alone was completely liquid and the presence of apples introduced solids, potentially altering gastric emptying dynamics(Reference Phillips, Deane and Jones79). Meal volumes also differed. The OFTT meal was 500 ml which is comparable with other OFTT studies(Reference Bahceci, Aydemir and Tuzcu81,Reference Marciani, Faulks and Wickham82) . Total meal size increased substantially with the apples (500 ml OFTT + 200 g apple) and, while similar to other mixed meal studies(Reference Tiihonen, Rautonen and Alhoniemi11,Reference Coelho, Hermsdorff and Gomide83) , would potentially lead to differences in acetaminophen distribution, emptying and absorption. Also, for comparison with other studies, it is worth noting that the OFTT beverage is an emulsion of milk fat stabilised by dairy protein and therefore susceptible to pepsinolysis and phase separation in the stomach(Reference Gallier, Ye and Singh84). The effects of whole apples on gastric emptying and lipid digestion may be different based on whether lipids are bulk or dispersed and based on the nature of any emulsifier present.
The present study is the first to examine the effects of consuming whole apples on postprandial responses in humans and has the strengths of reflecting a mixed meal scenario using a crossover study design. Nevertheless, the relatively small sample size and high inter-individual variability are limitations, as is the lack of apple compositional data, in particular the polyphenol profiles, since different polyphenols may influence lipid digestion differently(Reference Sugiyama, Akazome and Shoji26). Given that procyanidins are identified as the main effective polyphenols for lipase inhibition, it would be interesting to investigate the lipid-lowering effects of apple varieties containing higher levels of procyanidins (e.g. Red Delicious and Granny Smith apples(Reference Gu, Kelm and Hammerstone85)). Lastly, although plasma acetaminophen correlates well with liquid emptying, more direct measurements (e.g. scintigraphy) should be considered for a better representation of gastric emptying of meals containing solids(Reference Willems, Otto Quartero and Numans33).
In summary, the present study examined the influence of consuming 200 g Gala apples, with skin, on PPL, glycaemia, insulinaemia, chylomicron size and number, and gastric emptying using a dairy-based OFTT in overweight and obese adults. In this mixed meal scenario, only postprandial insulin was altered by the presence of apples, potentially owing to the relatively low levels of pectin and/or polyphenols and/or interactions between carbohydrate and lipid metabolism from the mixed meal. The most important observation is that Gala apples, as a commonly consumed food, did not attenuate the PPL response induced by a high-fat meal when consumed by overweight and obese adults. Differences in gastric emptying that might have mediated the rate of nutrient absorption were not observed using the indirect acetaminophen method. Future research should explore the amount and type of apples or apple products that could realise any benefits of apple’s functional ingredients on metabolism and CVD risk in the postprandial period and with larger numbers of participants. Also, close attention should be paid to interactions between food ingredients, for example, lipids and carbohydrates in mixed meals.
Acknowledgements
The authors thank our study participants for their contributions; Emily Ward and Liam Cox for assistance with the study visits and glucose and insulin analyses; Premila Sathasivam, James Turgeon and Nina Andrejic for blood sampling; Dr Amy Tucker for guidance and assistance with the research facility and Dr David W. L. Ma and Lyn Hillyer for support with the FA analysis.
The present study was funded by Ontario Ministry of Agriculture, Food and Rural Affairs and Ontario Apple Growers Association (grant no. UofG2014-2028). D. M. L. was supported by a scholarship from Natural Sciences and Engineering Research Council of Canada. The Ontario Ministry of Agriculture, Food and Rural Affairs, Ontario Apple Growers Association and Natural Sciences and Engineering Research Council of Canada had no role in the design, analysis or writing of this article.
X. L., D. M. L., L. E. R. and A. J. W. designed the research; X. L., D. M. L., H. R. N., L. E. R. and A. J. W. conducted the research; X. L., D. M. L., H. R. N. and A. J. W. analysed the data; X. L. and A. J. W. performed the statistical analysis; X. L. and A. J. W. wrote the paper; and X. L., D. M. L., L. E. R. and A. J. W. had primary responsibility for the final content. All authors read and approved the final manuscript.
The authors declare that there are no conflicts of interest.
