Cohort Profile: Guangzhou Nutrition and Health Study (GNHS): A Population-based Multi-omics Study

Abstract

Background The Guangzhou Nutrition and Health Study (GNHS) aims to assess the determinants of metabolic disease in nutritional aspects, as well as other environmental and genetic factors, and explore possible biomarkers and mechanisms with multi-omics integration. Methods The population-based sample of adults in Guangzhou, China (baseline: 40–83 years old; n = 5,118) was followed up about every 3 years. All are tracked via on-site follow-up and health information systems. We assessed detailed information on lifestyle factors, physical activities, dietary assessments, psychological health, cognitive function, body measurements, and muscle function. Instrument tests included dual-energy X-ray absorptiometry scanning, carotid artery and liver ultrasonography evaluations, vascular endothelial function evaluation, upper-abdomen and brain magnetic resonance imaging, and 14-day real-time continuous glucose monitoring tests. We also measured multi-omics, including host genome-wide genotyping, serum metabolome and proteome, gut microbiome (16S rRNA sequencing, metagenome, and internal transcribed spacer 2 sequencing), and fecal metabolome and proteome. Results The baseline surveys were conducted from 2008 to 2015. Now, we have completed 3 waves. The 3rd and 4th follow-ups have started but have yet to end. A total of 5,118 participants aged 40–83 took part in the study. The median age at baseline was approximately 59.0 years and the proportion of female participants was about 69.4%. Among all the participants, 3,628 (71%) completed at least one on-site follow-up, with a median duration of 9.48 years. Conclusion The cohort will provide data that will be influential in establishing the role of nutrition in metabolic diseases with multi-omics.

Proteome‐wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8‐year prospective study

“…The overview of study design was presented in Figure 1 . This study included 3244 participants from the Guangzhou Nutrition and Health Study (GNHS) (Ling et al., 2023 ), followed up every 3 years from 2008 to 2019. We profiled 413 serum proteins from ~20,000 proteomes at baseline (F0) and follow‐ups (F) 2 and 3 and determined bone mineral density (BMD) at F1 to F3 at lumbar spine (LS) and femoral neck (FN).…”

“…The study was based on the community‐based prospective cohort Guangzhou Nutrition and Health Study (GNHS, ClinicalTrials.gov identifier: NCT03179657) that consisted of 4048 apparently healthy participants aged 45–75 years at baseline between 2008 and 2013 (Ling et al., 2023 ). The metadata from questionnaire interviews, anthropometric measurements, and blood samples were collected every 3 years between 2008 and 2019 (Long et al., 2021 ).…”

“…The overview of study design was presented in Figure 1. This study included 3244 participants from the Guangzhou Nutrition and Health Study (GNHS) (Ling et al, 2023), followed up every F I G U R E 1 Overview of the study cohort and design. This study included 3244 participants from the Guangzhou Nutrition and Health Study (GNHS), followed up every 3 years from 2008 to 2019.…”

Gut microbiota–bile acid axis mediated the beneficial associations between dietary lignans and hyperuricemia: a prospective study

“…For a detailed methodology, refer to a previous publication. 16 Among 4048 participants, 247 were excluded due to an incomplete dietary intake survey and uric acid measurement at the baseline. To assess the impact of baseline dietary lignan intake on the incidence of hyperuricemia, we further excluded 725 participants who had hyperuricemia at the baseline and 524 individuals with missing UA information during follow-up, resulting in a final sample of 2552 subjects for analysis.…”

“…A total of 198 fecal metabolites were quantified across 15 distinct subclasses, including bile acids, amino acids, fatty acids, carnitines, indoles, and nucleosides, among others. 16 Before analysis, fecal metabolite concentrations were log-transformed and normalized.…”