Pischon Lab
Molecular Epidemiology
Metabolic dysfunction and risk of chronic disease
The prevalence of metabolic abnormalities, which are considered key elements in the causal pathway to CVD but also to many other diseases, including several cancers and, purportedly, cognitive impairment, has increased substantially. It was estimated that high body mass index (BMI) accounted for 4,72 million deaths and 148 million disability-adjusted life years globally in 2017 (1). For cancer, a high BMI was among the three leading risk factors globally for cancer deaths and DALYs in 2019 (2). However, our knowledge about the contribution of metabolic factors to chronic disease risk and of the impact of genetic and non-genetic risk factors, particularly diet and physical activity, is still limited. Obesity, metabolic dyfunction, and the metabolic syndrome (MetS) were initially primarily a concern for CVD, but it became clear that they increase the risk of many other diseases. While overweight and obesity had historically been defined based on BMI (3), there is evidence that BMI does not adequately reflect body fat distribution, and that waist circumference (WC) as a measure of abdominal adiposity provides important information on the risk of disease and mortality (4,5). Abdominal obesity is mostly accounted for by visceral fat, which secretes cytokines and hormones (adipokines), and induces hepatic secretion of acute phase proteins, including C-reative protein (CRP), thereby contributing to insulin resistance, hyperinsulinemia, and chronic inflammation (6). Our research focusses on the impact of obesity and related metabolic abnormalities on disease risk, including cancer, type 2 diabetes, CVD, cognitive impairment, and mortality (7-13).
References
1) GBD 2017 Risk Factor Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1923-94.
2) GBD 2019 Cancer Risk Factors Collaborators. The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 2022;400:563-91.
3) Pischon T. BMI and mortality-time to revisit current recommendations for risk assessment. Am J Clin Nutr 2021;113:3-4.
4) Nimptsch K, Konigorski S, Pischon T. Diagnosis of obesity and use of obesity biomarkers in science and clinical medicine. Metabolism 2019;92:61-70.
5) Pischon T, Boeing H, Hoffmann K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med 2008;359:2105-20.
6) Aleksandrova K, Mozaffarian D, Pischon T. Addressing the Perfect Storm: Biomarkers in Obesity and Pathophysiology of Cardiometabolic Risk. Clin Chem 2018;64:142-53.
7) Pischon T, Nimptsch K, eds. Obesity and Cancer. Switzerland: Springer International Publishing; 2016.
8) Pischon T, Girman CJ, Hotamisligil GS, Rifai N, Hu FB, Rimm EB. Plasma adiponectin levels and risk of myocardial infarction in men. Jama 2004;291:1730-7.
9) Pai JK, Pischon T, Ma J, et al. Inflammatory Markers and the Risk of Coronary Heart Disease in Men and Women. N Engl J Med 2004;351:2599-610.
10) Feinkohl I, Janke J, Hadzidiakos D, et al. Associations of the metabolic syndrome and its components with cognitive impairment in older adults. BMC geriatrics 2019;19:77.
11) Floegel A, Kuhn T, Sookthai D, et al. Serum metabolites and risk of myocardial infarction and ischemic stroke: a targeted metabolomic approach in two German prospective cohorts. Eur J Epidemiol 2018;33:55-66.
12) Floegel A, Stefan N, Yu Z, et al. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 2013;62:639-48.
13) Pischon T. Use of obesity biomarkers in cardiovascular epidemiology. Dis Markers 2009;26:247-63.