Exploring Community-Specific Associations among Obesity, Meta-Inflammation, and the Gut Microbiome in the Context of Native Hawaiian and Other Pacific Islander Health Disparities on Oʻahu
Date
2024
Authors
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
Native Hawaiians and other Pacific Islanders (NHPIs) face a higher prevalence of obesity-related diseases and are more likely to be classified as obese according to conventional body mass index (BMI) standards. However, BMI is differentially effective as an indicator of obesity-related health risk, and its generalized application may introduce biases in clinical or comparative research settings. Community-specific characterizations of obesity risk are needed to improve the accuracy and relevance of health disparities research for NHPIs. Community clinic events were held for study recruitment, health-related survey administration, clinical health measure collection, blood sample collection, and at-home stool collection kit distribution. Point-of-care glycosylated hemoglobin (A1c; %) tests were used to designate type 2 diabetes mellitus (T2DM) categories/risk status according to thresholds recommended by the American Diabetes Association. Blood pressure (BP) was also measured, and hypertension (HT) status was determined according to 2017 guidelines recommended by the American College of Cardiology. Community-specific definitions for metabolically healthy (MH; non- or pre-diabetic and non-hypertensive) and metabolically unhealthy (MU; diabetic and/or hypertensive) obesity were obtained for each racial-ethnic group in an NHPI-enriched cohort. To achieve this, receiver operating characteristic (ROC) areas under the curve (AUC) values were used to compare the predictive performance of various anthropometric indices for MU status. These included WC (waist circumference), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), WHT.5R (waist-to-height0.5 ratio), ABSI (A body shape index), BAI (body adiposity index), BRI (body roundness index), and WWI (weight-adjusted waist index). Ideal thresholds were then back-calculated for each anthropometric index to maximize accurate classifications for T2DM risk and HT. Youden’s J statistic was then calculated for each threshold to determine their predictive performance for MU status.
Plasma concentrations of GLP-1, IFN-α, IFN-γ, IL-1β, IL-10, IL-12, IL-13, IL-18, IL-3, IL-6, IL-8 (CXCL8), Insulin, MCP-1 (CCL2), PYY, TNF-α, TNFRI, and VEGF-A (pg/ml) were measured using the 17-Plex Human ProcartaPlex Panel (ThermoFisher Scientific, Warrington, England). Linear discriminant analysis (LDA) was performed to determine the contribution of each biomarker to the separation between MH and MU risk status. Plasma concentrations between ethnic groups were compared using Kruskal and Wilcox rank-sum tests. Ethnic-specific associations between significant meta-inflammatory factors and MH/OB risk were then compared by logistic regression.
Home stool sample self-collection kits were distributed to participants upon biometric data collection. Each kit included one sample tube containing RNAlater (5 ml; a sample preservative supplied by ThermoFisher Scientific, Waltham, MA). DNA (40 ng) isolated from each stool sample was subjected to polymerase chain reaction (PCR) amplification targeting 16S rDNA hypervariable regions V2-4-8 and V3-6,7-9 (Ion Torrent 16S Metagenomics Kit; ThermoFisher Scientific, Warrington, England). 16S rDNA libraries were prepared from 150 ng of pooled amplicons (Ion Plus Fragment Library Kit; ThermoFisher Scientific, Austin, TX, USA) and barcoded using Ion Xpress Barcode Adapters (Life Technologies, Carlsbad, CA, USA). DNA libraries were pooled (80 pmol from up to 60 libraries) and loaded onto Ion 530™ chips (Ion S5 Next-Generation Sequencing System) in preparation for sequencing.
16S Metagenomics Kit analysis was performed using Ion Reporter Software v5.18.4.0 (ThermoFisher Scientific). Chimeric sequences were automatically identified and removed. Reads were mapped to reference databases Greengenes v13.5 and MicroSEQ ID v3.0. Gut microbiome profiles were compiled using metagenome taxonomic data via the Curated MicroSEQ(R) 16S Reference Library v2013.1. Differential abundance analyses were performed using Analysis of Compositions of Microbiomes with Bias Correction; the ‘ANCOM-BC2’ in R.
Anthropometric thresholds associated with MU risk were generally highest among Part/NHPIs compared to other groups. Part/NHPI-specific BMI thresholds resembled the conventional cutoff, ranging from 27.81 to 30.25 kg/m2, while those for Asian, White, and Mixed groups were relatively lower, ranging from 23.62 to 25.36 kg/m2. However, anthropometric indices were less effective as health risk predictors for NHPIs than for White (P=2.3E-5) and Mixed (P=0.030) groups. BRI emerged as the most consistent and effective predictor of T2DM and HT risk across the total cohort, suggesting that its use in clinical and research settings may better capture obesity-related health disparities in NHPI-inclusive communities than BMI. However, the effectiveness of anthropometric indices varies among diverse populations and is least effective for NHPIs compared to other racial-ethnic groups.
The features that strongly contributed to the distinction between MH and MU risk categories were age, gender, BRI, IFN-α, IFN-γ, IL-10, IL-12, IL-13, IL-1β, IL-6, IL-8, and TNF-α. Among significant meta-inflammatory biomarkers, IFN-α, IL-10, IL-13, IL-1β, and TNF-α were the most important features in the distinction between MH and MU risk status for NHPIs. After adjusting for age and gender, IL-1β levels were significantly higher in NHPIs compared to the White group (P<0.01). GLP-1 levels were lower in the NHPI group than in the White or Mixed groups (P<0.001). PYY was also lower in NHPIs compared to Part NHPIs and the Mixed group (P<0.01). MCP-1 was lower in NHPIs compared to Asian and Mixed groups (P<0.001), and IL-3 was lower in NHPIs compared to White (P<0.001) and Mixed groups (P<0.01).
At the genus level, NHPIs had the highest prevalence of Eggerthella, Blautia, Megamonas, Veillonella, Lachnoclostridium, Lactobacillus, Fusobacterium, Haemophilus, Klebsiella, and Mannheimia and the lowest prevalence of Ruminiclostridium, Barnesiella, Prevotella, Herbaspirillum, Desulfovibrio, and Akkermansia compared to other racial-ethnic groups. Gut bacterial taxa that were more prevalent in NHPIs than other groups have been previously linked to inflammation, T2DM, HT, or gastrointestinal complications. Those less prevalent in NHPIs than other groups were variably associated with beneficial metabolic effects. However, these associations were primarily observed in NHPI-exclusive study populations. In NHPIs, A1c levels were positively associated with unclassified members of Clostridiales, Flavonifractor, Megasphaera, and Turicibacter but negatively associated with Mannheimia and Megamonas. There were no significant associations between gut bacterial genera and A1c levels in the Asian, White, or Mixed groups.
Racial-ethnic differences in obesity, meta-inflammation, and the gut microbiome may contribute to racial-ethnic differences in metabolic health risk. BRI was the most effective predictor for metabolic outcomes in an ethnically diverse population. Still, anthropometric indices may be less effective as health risk indicators for NHPIs than other groups. Meta-inflammation may differentially associate with metabolic outcomes between racial-ethnic groups, and the association may be stronger in NHPIs than in other groups. Gut bacterial associations with metabolic outcomes also differed by race-ethnicity. Further community-specific research is necessary to characterize these differences effectively.
Description
Keywords
Molecular biology, Biology, health disparities, hypertension, meta-inflammation, NHPI, obesity, type 2 diabetes mellitus
Citation
Extent
101 pages
Format
Geographic Location
Time Period
Related To
Related To (URI)
Table of Contents
Rights
All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.