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    Understanding host and microbial metabolites in functional gut disorders : a thesis presented in particle fulfilment of the requirements for the degree of Doctor of Philosophy in Nutritional Science at Massey University, Palmerston North, New Zealand
    (Massey University, 2021) James, Crystal Shanalee
    Interactions between diet, host, and the gut microbiome can result in beneficial or detrimental effects on human health. Functional gut disorders (FGDs) are an example of the negative effects of these interactions. However, an understanding of the mechanisms behind FGDs remains unknown. Metabolomics is a powerful tool to understand possible mechanisms. It was hypothesised that key metabolite groups in faecal samples would differ between or within FGD subtypes and healthy controls reflective of mechanistic perturbations. This PhD aimed to characterise the metabolite profile of FGD individuals (functional constipation (FC), IBS-constipation (IBS-C), functional diarrhoea (FD), IBS-diarrhoea (IBS-D), IBS-mixed (IBS-M)) and healthy controls. The concentration of faecal bile acids and plasma amino acids were quantified to ascertain changes in known metabolites associated with FGDs. The faecal metabolome was characterised to potentially identify wider perturbations, and this was then integrated with dietary intake, plasma metabolome abundance and faecal microbiota composition for a systems biology analysis. Constipation (FC + IBS-C) and diarrhoea (FD + IBS-D) were combined to determine differences between healthy controls and disease states. Faecal bile acid concentrations differed between all FGD participants and healthy controls. In the combined analysis of the diarrhoea (FD+IBS-D) and constipation (FC+IBS-C) groups, the diarrhoea group had a higher concentration of bile acids than the constipation group or healthy control group. The concentration of plasma amino acids did not differ between FGD participants and healthy controls. Furthermore, analysis of key amino acid groups showed that only the concentration of branched chain amino acids were different between all subtypes and healthy controls. Characterisation of faecal polar, semi-polar and lipid metabolites showed a differential relative abundance of some polar and semi-polar metabolites (e.g., riboflavin, nicotinic acid) between diarrhoea and healthy control groups, and constipation and healthy control groups. Substantial changes in the abundance of some lipids (e.g., ceramides, triglycerides) were evident between constipation and healthy control groups, and diarrhoea and healthy control groups. Integration of the faecal metabolome with other datasets (faecal microbiome, plasma metabolome, dietary intake) showed the faecal metabolome and microbiome separated healthy controls from constipation or diarrhoea. Additionally, differential positive and negative correlations were observed between faecal lipids (triglycerides and diglycerides) and microbial species (Firmicutes and Bacteroidetes). This PhD thesis presents novel insights into the metabolite signature characterising FGD participants and healthy controls and provides directions for future research.
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    Dietary patterns in the older New Zealand adult and their associations with cognitive function and metabolic syndrome : the Researching Eating, Activity, and Cognitive Health (REACH) study : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Nutritional Science at Massey University, Albany, New Zealand
    (Massey University, 2021) Mumme, Karen
    Background: The global population is ageing. Ageing and poor diet are common risk factors for cognitive decline and metabolic syndrome which reduce functionality in later years. A dietary pattern approach considers the full complexity of the diet. Dietary patterns in an older New Zealand context have not been identified nor their associations with cognitive function or metabolic syndrome. Aims and objectives: This thesis, referred to as the REACH (Researching, Eating, Activity, and Cognitive Health) study, explored associations between dietary patterns and cognitive function and metabolic syndrome in older New Zealand adults. To achieve the aim a food frequency questionnaire (FFQ) was assessed for reproducibility, relative validity, and its suitability to derive robust dietary patterns. Further, associations between these dietary patterns and their nutrient and energy intake; the socio-demographic and lifestyle factors of the participants; and cognitive function and metabolic syndrome outcomes were examined. Method: Community-dwelling adults from Auckland, New Zealand were recruited (aged 65-74 years, 36% male, n 371). Dietary patterns were derived from a 109-item FFQ using 57 food groups and principal component analysis. Nutrient, energy, and alcohol intake were calculated using FOODfiles, the New Zealand Food composition database. The REACH FFQ and its derived dietary patterns were assessed for reproducibility and relative validity in a sub-set of the REACH participants (n 294). Reproducibility was assessed using an identical FFQ (FFQ2) administered one month after the initial REACH FFQ. A 4-day food record (4-DFR), collected between FFQ administrations, assessed relative validity. Cognitive function, covering six domains (global cognition, attention and vigilance, executive function, episodic memory, working memory and spatial memory), was assessed using COMPASS (Computerised Mental Performance Assessment System). Self-administered questionnaires collected health (medication and supplement intake), demographic and lifestyle [including sex, education levels, living status (alone or with someone), smoking status, physical activity levels, address (for Index of Multiple Deprivation)], and physical activity (International Physical Activity Questionnaire) data. A fasted blood sample was collected for measuring genetic [Apolipoprotein E -ε4 (APOE -ε4)] and biochemical markers (triglycerides, high- and low-density lipoprotein cholesterol). Blood pressure and anthropometric measures [weight, height, waist circumference, and body fat % (using dual X-ray absorptiometry)] were collected. Metabolic syndrome was defined by the National Cholesterol Education Program Adult Treatment Panel III. Abstract ii Statistical analyses performed: Reproducibility and relative validity of the REACH FFQ (food group intakes) and its derived dietary patterns (scores) were assessed using Spearman correlation coefficients (acceptable correlation rho=0.20-0.49), weighted kappa statistic (κw) (acceptable statistic κw=0.20-0.60), and Bland-Altman analysis including mean difference, limits of agreement, plots, and slope of bias. The similarity between dietary pattern loadings were assessed using Tucker’s congruence coefficient. Linear or logistic regression were used to examine associations between dietary patterns and their nutrients; socio-demographic and lifestyle factors; and health outcomes. Confounding adjustments included age, sex, education, index of multiple deprivation, energy intake, APOE -ε4, and physical activity. Results: In the validation study, the FFQ food groups showed good reproducibility (mean correlation coefficient = 0.69, mean κw = 0.62) and acceptable relative validity (mean correlation coefficient = 0.45, mean κw = 0.38) though Bland Altman plots showed bias and mean differences significantly different to zero in some food groups. Three similar dietary patterns were identified from each dietary assessment tool: ‘Mediterranean style’, ‘Western’, and ‘prudent’. Congruence coefficients between factor loadings ranged from 0.54 to 0.80. Correlations of dietary pattern scores ranged from 0.47 to 0.59 (reproducibility) and 0.33 to 0.43 (validity) (all P<0.001); weighted kappa scores from 0.40 to 0.48 (reproducibility) and 0.27 to 0.37 (validity); limits of agreement from ± 1.79 to ± 2.09 (reproducibility) and ± 2.09 to ± 2.27 (validity); a slope of bias was seen in the ‘prudent’ pattern for reproducibility and validity (P<0.001). From the full REACH dietary data set, three valid dietary patterns were derived explaining 18% of the variation in the diet. The ‘Mediterranean style’ pattern (salad vegetables; leafy cruciferous vegetables; other vegetables; avocados and olives; alliums; nuts and seeds; white fish and shellfish; oily fish; berries; water; salad dressings; cruciferous vegetables; eggs; cheese; tomatoes; and all other fruit) was associated with higher levels of beta-carotene equivalents, vitamin E, and folate intake (all P<0.001, all R2 ≥ 0.26), along with being female, having a higher physical activity level, and higher education (P<0.001, R2 = 0.07). The ‘Western’ pattern (processed meat; sauces and condiments; cakes, biscuits and puddings; meat pies and chips; processed fish; confectionery; vegetable oils; beer; chocolate; salad dressings; cheese; and sweetened cereal) was associated with higher daily energy intake (P<0.001, R2 = 0.43), along with being male, having a higher alcohol intake, living with others, and a secondary education (males only) (P<0.001, R2 = 0.16). The ‘prudent’ pattern (dried legumes; soy-based foods; fresh and frozen legumes; whole grains; carrots; and Abstract iii spices) was associated with a higher fibre and carbohydrate intake (both P<0.001, both R2 ≥ 0.25), along with higher physical activity and lower alcohol intake (P<0.001, R2 = 0.15). Neither the ‘Mediterranean style’ nor ‘prudent’ patterns were associated with either cognitive function or metabolic syndrome. The ‘Western’ pattern was not associated with cognitive function, but was positively associated with metabolic syndrome [odds ratio = 1 .67 (95% CI 1.08, 2.63)] (P=0.02). Being younger (P<0.05), female (P<0.001), having a higher education (P<0.01) or no APOE -ε4 allele (P<0.05) were associated with better cognitive function. Higher deprivation (P<0.001) was associated with metabolic syndrome. Conclusion: A novel and robust study with valid tools did not find any associations between dietary patterns and cognitive function in older adults living in New Zealand. Age, sex, education, and the APOE -ε4 allele were more predictive of cognitive function than the dietary patterns. A ‘Western’ dietary pattern and higher deprivation were predictive of metabolic syndrome. To reduce the odds of metabolic syndrome, actions should aim to improve deprivation, and shift people’s dietary intake away from the ‘Western’ dietary pattern.
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    New pathways to obesity prevention and metabolic health : the relationship between diet and the gut microbiome : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Nutritional Science at Massey University, Tāmaki Makaurau, Aotearoa New Zealand
    (Massey University, 2020) Renall, Nikki
    Background Diet is one of the key drivers of the global obesity epidemic. Based on the results of rodent experiments, the gut microbiota may play an important role in this multifaceted disease. Additionally, the microbiota is known to be influenced by the habitual diets consumed by humans. Aims and objectives The aim of this PhD research was to characterise the habitual dietary intake of two New Zealand populations (Pacific and New Zealand European (NZE) women) with different metabolic disease risk and body fat profiles (lean and obese). The first objective of the research was to explore the relationship between habitual macronutrient intake in relation to body fat content and metabolic health markers. The second objective was to characterise a posteriori dietary patterns (derived from multiple days of dietary assessment) and to explore the association with body fat content and metabolic health markers. The third objective was to explore the characteristics of microbiota composition in relation to habitual diet (dietary patterns, foods, and nutrients), body fat content and metabolic health markers. Methods Between July 2016 and September 2017, Pacific (n=126) and NZE (n=161) women, aged 18-45 years, living in Auckland, New Zealand, were recruited to a cross-sectional study, based on their body mass index (lean and obese) and stratified as having low (<35 % body fat) or high (≥35 % body fat) body fat percentage (BF%). Dietary intake was assessed using a 5-day estimated, non-consecutive, food record and a validated semi-quantitative food frequency questionnaire, which were used to calculate habitual dietary intake using the National Cancer Institute (NCI) method. Body composition and BF% were assessed by dual-energy x-ray absorptiometry. Fasting blood samples were analysed for metabolic biomarkers (lipid and glucose profiles). Bulk DNA was extracted from faecal samples and the metagenomic sequences associated with the microbiota were analysed using MetaPhlAN and QIIME2 software. Enterotypes characterising the microbiotas of the participants were predicted in R and the species that defined enterotypes were determined using STAMP software. A posteriori dietary patterns were identified using principal component analysis. Adjusted multivariate regression models were conducted to explore the association between BF% and habitual macronutrient intake and adherence to dietary patterns, as well as the association between microbiota composition and habitual diet. Results There were no significant differences in BF% between Pacific and NZE women (p=0.498). Higher energy adjusted habitual dietary fibre (DF) intake was associated with lower BF% (β= -0.35, p≤ 0.001) for both Pacific and NZE women, and this relationship became stronger after further adjustments for protein (g/day), total carbohydrate (g/day), and total fat (g/day) intake (β= -0.47, p≤ 0.001). Women in the highest tertile of DF intake were older, had lower concentrations of fasting plasma insulin, and lower socioeconomic deprivation levels. Four dietary patterns that explained 30.9 % of the observed variance in habitual diet were identified. Higher adherence to dietary patterns characterised by core foods (the “colourful vegetable, plant protein, and dairy” and “fruit, starchy vegetables, and nuts” patterns) were inversely associated with BF%. In contrast, patterns characterised by more ‘discretionary’ foods (“sweet and fat rich carbohydrate”) and less diversity of core foods (“animal meat and fat”) were positively associated with BF% for both Pacific and NZE women. Three enterotypes were identified by higher relative abundance of specific bacterial species: enterotype 1 was characterised by Pacific and NZE women (n=146) and the abundances of Faecalibacterium prausnitzii and Eubacterium rectale. Enterotype 2 (n=70) was characterised by Pacific women, Bifidobacterium adolescentis, Bifidobacterium bifidum, and Lactobacillus ruminis; and by higher BF%, visceral adipose tissue, and concentrations of fasting insulin. Enterotype 3 (n=70) was predominately found in older NZE women with lower deprivation, and characterised by Akkermansia muciniphila, Ruminococcus bromii, Subdoligranulum species, and Methanobrevibacter smithii. Adherence to the “colourful vegetables, plant protein, and dairy” dietary pattern was positively associated with enterotypes 1 and 3 and negatively with enterotype 2. Conclusion Consuming more core foods rich in dietary fibre was associated with enterotypes 1 and 3, including lower adiposity and metabolic disease risks. In contrast, consuming more discretionary foods was associated with enterotype 2, higher adiposity and metabolic disease risks. This PhD research highlights habitual diet-microbiota-host associations, which are similar for a population of women with different metabolic disease risk, body fat profiles, and deprivation levels. Whether the microbiota is a cause or consequence of metabolic health has yet to be elucidated. However, habitually consuming more core foods rich in dietary fibre is associated with microbiota composition, and lower metabolic disease risks.