The University of Auckland
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HVN FERDINAND Metadata Record - Evaluating FEijoa foR DIabetes Prevention in a Multi-ethnic New ZeAlaND Cohort: the FERDINAND study

posted on 2024-06-30, 00:10 authored by Jennifer Miles-ChanJennifer Miles-Chan, Ivana SequeiraIvana Sequeira

This metadata record and it's attached files make statements about the kinds of data collected as part of this research, and set out policies for governance of that data, now and in the future. 

Description: Prevention of type 2 diabetes (T2D) is a key global health target, with change in diet being a first line strategy. Yet the optimum composition of the diet for long term prevention, to enhance outcomes that can be achieved through weight loss, remains under considerable debate. Additionally, response to dietary intervention, in particular the postprandial glucose response (PPGR), remains poorly characterised in those at risk of diabetes. Predicting response, and in turn personalising intervention diets to optimise glycaemic improvements in high-risk individuals is an important step in understanding how diet may help to ameliorate dysglycaemia and T2D. 

The proposed FERDINAND Study is a longer-term 8 month intervention in a larger multi-ethnic cohort of ‘at risk’ adults; with the aim of evaluating a F&B product that may contribute to improved glycaemia during both weight/adipose mass loss and longer-term weight loss maintenance. Plant-derived polyphenols, commonly found in fruits such as feijoa, may provide a novel nutrition approach with evidence from prior pre-clinical, and a human clinical study, demonstrating improvement in glycaemic parameters following short-term consumption of commercially available whole feijoa powder. 

Use of machine-learning algorithms will integrate clinical responses and ‘omics outputs to predict individual response to the intervention. The outcomes of PPGR from the FERDINAND Cohort will be important as it will provide predictive algorithms that can be validated in future follow-up assessments. 



University of Auckland

Temporal coverage: start


HVN Project / Programme Name


Data access requirements

Individual participant data will not be made available. This is in accordance with the National Health and Disabilities Ethics Committees application that all data generated will only be used for this study. However, if necessary additional consent will be obtained from participants to allow the use of data for other studies.

Principal investigator organisation

University of Auckland

Collaborating researchers and affiliations

Principal Investigators:  A/P Jennifer Miles-Chan, University of Auckland, Human Nutrition Unit, 18 Carrick Place, Mt Eden Dr Ivana Sequeira-Bisson, University of Auckland, Human Nutrition Unit, 18 Carrick Place, Mt Eden Associate Investigators: Professor Sally Poppitt (University of Auckland) Dr Jia Jiet Lim (University of Auckland) Professor Mike Taylor (University of Auckland) Dr Shakeela Jayasinghe (University of Auckland) Dr Karl Fraser (AgResearch) Dr Karin Schofield (Intwood Consultants) Mr Kurt Grayson (University of Auckland) Mr William Shu (University of Auckland) Mr Ibrahim Mohamed (University of Auckland) Mr Jack Penhaligan (University of Auckland) Mr Kok Hing Lieu (University of Auckland) Mr Saif Faraj (University of Auckland) Collaborators: Professor Garth Cooper (University of Auckland and University of Manchester) A/P Lindsay Plank (University of Auckland) Dr Denise Conroy (Plant and Food Research) Dr Kieren Hollingsworth (University of Newcastle upon Tyne) Dr Olivier Gasser (Malaghan Institute) Dr Ivy Gan (Plant and Food Research) Dr Yun Sing Koh (University of Auckland)

Data description

Outcomes of the study and associated data  Co-primary outcomes - Change in fasting plasma glucose (FPG) at 6 months - Change in body weight at 6 months Associated data: Plasma glucose levels, body weight Secondary outcomes - Change in HbA1c - Composite change in postprandial 2-h continuous glucose measurement-assessed ISF-G - Mixed meal tests (MMT), Oral glucose tolerance test (OGTT) - Change in body composition including: total body fat, abdominal body fat, pancreas fat, liver fat - Change in plasma metabolome profile - Composite change in basal metabolic rate (BMR) and post prandial energy expenditure (glucose induced thermogenesis, GIT) assessed using indirect calorimetry Associated data: HbA1c levels, glucose measurements (MMT and OGTT), DXA, MRI, MRS, plasma metabolome profile, indirect calorimetry Other outcomes and associated data - Clinical biomarkers including: OGTT venous glucose, fasting and OGTT insulin, C-peptide, lipid profile (total cholesterol, LDL-C, HDL-C, triglyceride), liver function tests, inflammatory & immune markers - Faecal microbiome profile - Urine Nitrogen (dietary compliance) - Epigenetic, SNP, miRNA markers of Type 2 diabetes - Physical activity assessment (step count) - 24-hr glycaemic variability from continuous glucose management (e.g. evaluated using matrices such as standard deviation, SD; mean amplitude of glycaemic excursion, MAGE; mean of daily difference for inter-day variation, MODD; continuous overlapping net glycaemic action, CONGA)

Principal investigator contact email