Environment, Inflammation and Metabolic Diseases Study

Overview

The aim is to establish an effective and practical early warning model for endocrine and metabolic diseases based on an environmental-gene-protein panoramic network, to uncover new mechanisms underlying the onset and progression of these diseases, and to screen for novel therapeutic targets.

Detailed description

This study aims to establish a specialized resource database for metabolic diseases-the Chongqing Environment, Inflammation, and Metabolic Diseases Study (EIMDS). The cohort will include approximately 8,000 community-based individuals who have been followed up for over 5 years, with clinical, biochemical, and endpoint event assessments conducted every two years, along with the collection of blood and urine samples. Based on the EIMDS cohort,this study will explore the risk factors for endocrine and metabolic diseases from a population perspective. Furthermore, by employing technologies such as whole-transcriptome sequencing, proteomics and phosphoproteomics, ATAC-seq, and single-cell sequencing,this study aim to elucidate the molecular mechanisms underlying endocrine and metabolic diseases and identify potential drug targets.

Interventions

• Other observe
  A single observational cohort of study participants undergoing baseline biochemical screening for autonomous aldosterone secretion (AAS). No experimental interventions or treatments are administered. All participants receive standard clinical care and undergo standardized baseline assessments, including measurement of plasma aldosterone concentration (PAC) and plasma renin concentration (PRC) for AAS classification, as well as collection of demographic, clinical, biochemical, anthropometric data

Primary outcome measures

• The prevalence of autonomous secretion of aldosterone [Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years]

Secondary outcome measures (3)

• Identification of key risk factors associated with autonomous aldosterone secretion [Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years]
• Association of autonomous aldosterone secretion with chronic kidney disease and metabolic disorders [Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years]
• Screening of key proteins, signaling pathways and potential biomarkers associated with autonomous aldosterone secretion using proteomic analysis [Time frame: The follow-up period from baseline enrollment to the completion of follow-up examinations was approximately 5 years]

Eligibility criteria

Inclusion criteria

• All individuals who voluntarily participated in the physical examination

Exclusion criteria

Participants with incomplete data

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

China · 1 center

• The First Affiliated Hospital of Chongqing Medical University — Chongqing

Publications

• Zhang PP, Han Q, Sheng MX, Du CY, Wang YL, Cheng XF, Xu HX, Li CC, Xu YJ. Identification of Circular RNA Expression Profiles in White Adipocytes and Their Roles in Adipogenesis. Front Physiol. 2021 Aug 19;12:728208. doi: 10.3389/fphys.2021.728208. eCollection 2021. PMID 34489740
• Guo X, Zhang Z, Zeng T, Lim YC, Wang Y, Xie X, Yang S, Huang C, Xu M, Tao L, Zeng H, Sun L, Li X. cAMP-MicroRNA-203-IFNgamma network regulates subcutaneous white fat browning and glucose tolerance. Mol Metab. 2019 Oct;28:36-47. doi: 10.1016/j.molmet.2019.07.002. Epub 2019 Jul 6. PMID 31327757
• Arner P, Kulyte A. MicroRNA regulatory networks in human adipose tissue and obesity. Nat Rev Endocrinol. 2015 May;11(5):276-88. doi: 10.1038/nrendo.2015.25. Epub 2015 Mar 3. PMID 25732520
• Mulatero P, Monticone S, Burrello J, Veglio F, Williams TA, Funder J. Guidelines for primary aldosteronism: uptake by primary care physicians in Europe. J Hypertens. 2016 Nov;34(11):2253-7. doi: 10.1097/HJH.0000000000001088. PMID 27607462
• Xu Z, Yang J, Hu J, Song Y, He W, Luo T, Cheng Q, Ma L, Luo R, Fuller PJ, Cai J, Li Q, Yang S; Chongqing Primary Aldosteronism Study (CONPASS) Group. Primary Aldosteronism in Patients in China With Recently Detected Hypertension. J Am Coll Cardiol. 2020 Apr 28;75(16):1913-1922. doi: 10.1016/j.jacc.2020.02.052. PMID 32327102
• Chen X, Mao Y, Hu J, Han S, Gong L, Luo T, Yang S, Qing H, Wang Y, Du Z, Mei M, Zheng L, Lv X, Tang Y, Zhao Q, Zhou Y, He JC, Li Q, Wang Z. Perirenal Fat Thickness Is Significantly Associated With the Risk for Development of Chronic Kidney Disease in Patients With Diabetes. Diabetes. 2021 Oct;70(10):2322-2332. doi: 10.2337/db20-1031. Epub 2021 Jun 22. PMID 34593536
• Hu J, Yang S, Zhang A, Yang P, Cao X, Li X, Goswami R, Wang Y, Luo T, Liao K, Cheng Q, Xiao X, Li Q. Abdominal Obesity Is More Closely Associated With Diabetic Kidney Disease Than General Obesity. Diabetes Care. 2016 Oct;39(10):e179-80. doi: 10.2337/dc16-1025. Epub 2016 Aug 18. No abstract available. PMID 27538755
• Hu J, Hu Y, Hertzmark E, Yuan C, Liu G, Stampfer MJ, Rimm EB, Hu FB, Wang M, Sun Q. Weight Change, Lifestyle, and Mortality in Patients With Type 2 Diabetes. J Clin Endocrinol Metab. 2022 Feb 17;107(3):627-637. doi: 10.1210/clinem/dgab800. PMID 34741524

Identifiers

NCT: NCT07512609 · EIMDS

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗