Issues with the design of the study

Certain issues need to be addressed prior to interpreting the data as a whole. Compliance needs to be considered as a potential issue in this outpatient / community dietary intervention. The next issue is the phenotype of the cohort, and as to whether they are representative of the general population or a clinically relevant sub-group. The final issue is whether the washout period was adequate such that the two intervention periods can be viewed as being truly separate assessments.

a. Compliance with the study

The subjects appeared to be well motivated. All visits were attended and no drop outs occurred. Direct observation of monosaccharide and food consumption was only possible at study visits. There are no biomarkers specific for intakes of monosaccharides, though a few assessments can be used to infer compliance in this study. These are weight change, serum triglycerides and rates

of fasted carbohydrate oxidation. Due to the isoenergetic nature of the first period these ‘compliance’ assessments are only feasible during the second hyperenergetic period. In this period the energy content in the monosaccharides was greater than that normally consumed in drinks by the subjects, and so one would expect weight, carbohydrate oxidation and serum triglycerides to increase. This occurred in 25, 27 and 23 out of the 32 subjects respectively. Overall 2 failed to have either of these features present during the second period and 3 had only 1 feature present. They were evenly split between the groups. Neither of these assessment processes was designed, nor wholly reliable, as compliance monitors. The above suggests that compliance can be assumed to be acceptable overall.

b. The cohort’s phenotype

The cohort was explicitly recruited on the basis of them being centrally overweight healthy men who were not vegetarian, did not drink excessive alcohol, and drank small volumes of sugar-sweetened drinks. These factors will now be discussed in turn.

The health screen identified active health problems requiring ongoing medical review, or chronic treatment, and screened for previously unidentified diabetes, liver, renal or cardiac disease as well. The primary research question was to ascertain the hepatic effects of a high monosaccharide intake and so liver biochemistry had to be normal and the presence of hepatic disease including viruses, haemochromatosis, or alcohol abuse were actively screened for.

In order to classify as being centrally overweight the target measurements were a body mass index (BMI) between 25 and 32kg/m² with a waist circumference greater than 94cm, a predictor of increased coronary heart disease risk (Han, Lean et al. 1996). The addition of a minimum waist circumference helped to exclude individuals whose elevated BMI originated primarily from increased muscle as opposed to adipose tissue. This simple process was chosen as it was felt to be easy to understand and reproduce. Significantly overweight individuals were excluded due to the ethics of modestly overfeeding them and the feasibility of performing MRI based assessments. Central (visceral) obesity drives systemic and hepatic insulin resistance. Le et al. previously demonstrated an increased metabolic response to fructose in an overweight and insulin resistant cohort compared to a healthy weight and insulin sensitive cohort. A waist greater than 94cm is an independent and more powerful predictor for metabolic risk than waist to hip

ratio or body mass index (Wang, Rimm et al. 2005) and a useful predictor of coronary artery risk (Han, Lean et al. 1996).

Gonadal hormones influence carbohydrate metabolism. As these differ between men and women and vary with the menstrual cycle, women were excluded. Furthermore, women had previously been shown to be more resistant to the metabolic changes induced by fructose (Bantle, Raatz et al. 2000; Couchepin, Le et al. 2008; Stanhope, Schwarz et al. 2009). Recently a further paper has explored this in greater detail (Tran, Jacot-Descombes et al. 2010). Given the differing body sizes and composition of men and women these are very difficult studies to do as it is unclear if the amount of monosaccharide in gender comparative studies should be uniform, or weight or lean mass adjusted. Tran et al. compared outcomes in age and BMI matched men and women, but not weight or body fat percentage matched. The amount of fructose consumed was dependent on fat free mass and hence was significantly smaller in the female than the male group. The influence of this on the findings is difficult to fully account for. The insulin, lactate and uric acid response was smaller in women than men. There was lower tracer-labeled fructose enrichment into VLDL with women and a failure to suppress lipid oxidation. This supports the theory that women may be less vulnerable to fructose induced lipid disorders, though of course they also received less fructose.

Vegetarians were excluded from the present study as their requirements for differing foodstuffs than omnivores would have added another potentially confounding or complicating variable. In order to minimise the potential for symptomatic monosaccharide malabsorption, subjects were screened for pre-existing gastrointestinal symptoms or an intolerance to a test drink containing 50g of fructose.

Self reported alcohol consumption greater than 21 units a week was used as an exclusion factor. The reliability of such volunteer supplied information has to be questioned. This exclusion was not mentioned in the volunteer information sheet and so potential recruits were not forewarned. Liver biochemistry was also checked pre study enrolment. Ultimately the reliable exclusion of alcohol excess is impossible, though this mirrors the clinical setting that this translational study was designed to address. During the study periods alcohol consumption was allowed at two units a day and nil for 24 hours pre a study visit. It was felt that complete

abstinence would in some subjects have resulted in the study being as much an assessment of the washout from alcohol as a ‘wash-in’ of monosaccharides.

Another difficult assessment issue was that of baseline fructose consumption. The enzymes that initiate hepatic fructose metabolism, fructokinase and aldolase, are induced by fructose exposure (Koo, Wallig et al. 2008; Ouyang, Cirillo et al. 2008). Clearly the metabolic response to a high fructose diet may differ between high and low-baseline consumers. The clinical evidence to support this hypothesis however only comes from a single and very small study (Stirpe, Della Corte et al. 1970). In that study the postprandial uric acid concentration following consumption of 1g/kg of fructose in the fasted state was measured for 2 hours following normal food intakes, a 2 week low fructose intake and a 3 week high fructose intake in a patient with gout and the child of a patient with gout. The increase in postprandial uricaemia reflected the preceding fructose intake. This data has never been replicated. Nonetheless the aim was to exclude high baseline fructose consumers. A complete dietary assessment was not practical prior to enrolment of each subject, and there are no data to help identify which cut-off value should be used. The total monosaccharide dose supplied in the present study was equivalent to that present in 2 litres of cola per day. A pragmatic approach taken was to exclude those with daily sugar sweetened beverage consumption greater than 500ml of cola. Again this exclusion was not mentioned in the volunteer information sheet and so they were specifically not forewarned prior to reporting their standard intake patterns.

The subjects were clearly a select group, though representative of a substantial proportion of the UK male adult population. Indeed 48% of UK adult males have both a waist greater than 94cm and a BMI between 25 and 35kg/m² (HSE 2006), and 72% drink less than 21 units of alcohol a week (Alcohol 2010).

c. Effects and adequacy of the washout phase.

Many prior studies of fructose lack an energy control. As a result it remained unclear as to whether much of the previously published data could be attributed to a high fructose or high energy intake. Glucose was chosen as the energy comparator as it is a similar macronutrient with the same energy density.

The study was not a crossover design. This was specifically designed so as to facilitate the comparison of a high fructose or glucose intake in an energy balanced and overfeeding setting. The reason for this was that most of the prior data generated had been hyperenergetic and no study had previously compared the

findings in both settings. It was anticipated that only limited changes may occur during the isoenergetic phase and so a crossover of two isoenergetic phases may have generated limited outcome differences. It was also felt that if the study was merely a crossover of two hyperenergetic periods then the outcomes could only be viewed as a consequence of fructose versus glucose in combination with energy overfeeding and not directly attributable to the macronutrient. The approach decided upon facilitated the exploration of both energy settings. The limitation of this approach is that inter-monosaccharide outcome comparisons are not as robust as the inter-energy setting comparisons as they were comprised of differing individuals.

The first period for each subject was the isoenergetic phase as this was predicted to induce less of a metabolic challenge. It was then followed by six weeks ‘washout’ and then the hyperenergetic phase. No prior study has published with repeated baseline assessments and so it was not possible to be certain that a six week duration of the ‘washout’ would be truly adequate. As a result, all of the analyses were repeated at the baseline of the second period. Hence the final issues that need to be addressed are whether the washout phase was adequate and whether the two groups had truly returned to their baseline ‘metabolic state’.

In comparison between the two baseline assessments there were no differences in terms of weight, ectopic lipids, serum triglycerides, insulin resistance, renal and liver function, and whole body oxidative metabolism. There was a significant difference in NEFAs in both groups and a trend for lower uric acid in the glucose group, though this did not reach statistical significance. The interpretation of the biological/clinical significance of these isolated findings is not possible. As a result it seems likely that the washout was adequate and that the two baseline assessments were reflective of each other.

3.9.2. Subject specific issues