Metabolic biomarkers and gallstone disease - a population-based study

Area of Science:

• Metabolic health and disease epidemiology
• Genetics and personalized medicine
• Gastroenterology and hepatology

Background:

• Gallstone disease is a prevalent condition with multifactorial etiology.
• Obesity and metabolic dysfunction are increasingly recognized as risk factors for gallstone formation.
• Understanding the interplay between metabolic biomarkers, genetic susceptibility, and gallstone disease is crucial for public health.

Purpose of the Study:

• To investigate the associations between metabolic biomarkers of obesity (insulin resistance, vascular dysfunction, systemic inflammation) and gallstone disease.
• To examine the role of genetic susceptibility in the development of gallstone disease.
• To explore the relationship between metabolic syndrome and gallstone disease in a population-based study.

Main Methods:

• Cross-sectional study including 2650 participants, with 422 diagnosed with gallstone disease via ultrasound.
• Multivariable logistic regression models were employed to estimate associations between metabolic biomarkers and gallstone disease.
• Odds ratios (OR) and 95% confidence intervals (CI) were calculated to quantify the strength of these associations.

Main Results:

• Gallstone disease showed significant associations with fasting glucose, fasting insulin, homeostasis model assessment insulin resistance (HOMA-IR), metabolic syndrome, white blood cell count, and C-reactive protein.
• Several genetic variants (MC4R, MAP2K5, NRXN3, HHEX, FAIM2, apolipoprotein E4) were associated with gallstone disease.
• The association between body mass index (BMI) and gallstone disease was found to be mediated by insulin resistance.

Conclusions:

• Biomarkers indicative of insulin resistance and systemic inflammation are associated with gallstone disease.
• Genetic risk alleles for obesity and type 2 diabetes are linked to gallstone disease.
• Further research is warranted to explore temporal relationships and validate genetic associations in diverse populations for potential preventive strategies.