The impact of ethnicity and intra-pancreatic fat on the postprandial metabolome response to whey protein in overweight Asian Chinese and European Caucasian women with prediabetes

Aidan Joblin-Mills; Zhanxuan Wu; Karl Fraser; Beatrix Jones; Wilson Yip; Jia Jiet Lim; Louise Lu; Ivana Sequeira; Sally Poppitt

doi:10.3389/fcdhc.2022.980856

The impact of ethnicity and intra-pancreatic fat on the postprandial metabolome response to whey protein in overweight Asian Chinese and European Caucasian women with prediabetes

Front Clin Diabetes Healthc. 2022 Oct 14:3:980856. doi: 10.3389/fcdhc.2022.980856. eCollection 2022.

Authors

Aidan Joblin-Mills^{1

2}, Zhanxuan Wu^{1

2

3}, Karl Fraser^{1

2}, Beatrix Jones^{2

4}, Wilson Yip^{2

5}, Jia Jiet Lim^{2

5}, Louise Lu^{2

5}, Ivana Sequeira^{2

5}, Sally Poppitt^{2

5}

Affiliations

¹ Food Chemistry and Structure Team, Agresearch, Palmerston North, New Zealand.
² High-Value Nutrition, National Science Challenge, Auckland, New Zealand.
³ School of Food and Nutrition, Massey University, Palmerston North, New Zealand.
⁴ Department of Statistics, University of Auckland, Auckland, New Zealand.
⁵ Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, New Zealand.

Abstract

The "Thin on the Outside Fat on the Inside" TOFI_Asia study found Asian Chinese to be more susceptible to Type 2 Diabetes (T2D) compared to European Caucasians matched for gender and body mass index (BMI). This was influenced by degree of visceral adipose deposition and ectopic fat accumulation in key organs, including liver and pancreas, leading to altered fasting plasma glucose, insulin resistance, and differences in plasma lipid and metabolite profiles. It remains unclear how intra-pancreatic fat deposition (IPFD) impacts TOFI phenotype-related T2D risk factors associated with Asian Chinese. Cow's milk whey protein isolate (WPI) is an insulin secretagogue which can suppress hyperglycemia in prediabetes. In this dietary intervention, we used untargeted metabolomics to characterize the postprandial WPI response in 24 overweight women with prediabetes. Participants were classified by ethnicity (Asian Chinese, n=12; European Caucasian, n=12) and IPFD (low IPFD < 4.66%, n=10; high IPFD ≥ 4.66%, n=10). Using a cross-over design participants were randomized to consume three WPI beverages on separate occasions; 0 g (water control), 12.5 g (low protein, LP) and 50 g (high protein, HP), consumed when fasted. An exclusion pipeline for isolating metabolites with temporal (T_0-240mins) WPI responses was implemented, and a support vector machine-recursive feature elimination (SVM-RFE) algorithm was used to model relevant metabolites by ethnicity and IPFD classes. Metabolic network analysis identified glycine as a central hub in both ethnicity and IPFD WPI response networks. A depletion of glycine relative to WPI concentration was detected in Chinese and high IPFD participants independent of BMI. Urea cycle metabolites were highly represented among the ethnicity WPI metabolome model, implicating a dysregulation in ammonia and nitrogen metabolism among Chinese participants. Uric acid and purine synthesis pathways were enriched within the high IPFD cohort's WPI metabolome response, implicating adipogenesis and insulin resistance pathways. In conclusion, the discrimination of ethnicity from WPI metabolome profiles was a stronger prediction model than IPFD in overweight women with prediabetes. Each models' discriminatory metabolites enriched different metabolic pathways that help to further characterize prediabetes in Asian Chinese women and women with increased IPFD, independently.

Keywords: ethnicity; intra-pancreatic fat deposition; machine learning; metabolomics; network topology; pathway enrichment; prediabetes; whey protein isolate.