![]() Levels of many proteins vary significantly between individuals with obesity and normal-weight individuals 11, 12. Given that proteins are the main building blocks of an organism, and also potential drug targets, proteome-wide association analysis seems to be the obvious next step in obesity research 10. Individuals in the upper tail of the GPS distribution can be susceptible to genetic effects comparable to carriers of single rare monogenic disease variants 9. These scores approximated a normal distribution in the population and there is a considerable correlation between the GPS and measured BMI ( R 2 ~ 0.3). Genome-wide polygenic scores (GPS) are currently being used to quantify inherited disease susceptibility 9 and can explain ~13.9% of the variance in BMI which is more than twice the variance in BMI explained by using only the GWAS loci 3. However, these GWAS mapped associations still do not fully explain the molecular mechanisms leading to increased BMI. Through genome-wide association studies (GWAS), more than 900 genetic variants have been identified to be associated with BMI 3. Although some diseases can result from a single rare monogenic mutation with a large effect, most common diseases are the consequence of a cumulative effect of polygenic inheritance encompassing numerous variants, each making only a small contribution to the overall disease risk 8. The dramatic increase in obesity rates clearly points toward nongenetic factors or environmental factors as major drivers, most likely in interaction with genetic variants 7. ![]() The genetic composition is determined at conception and can be used to make predictions regarding disease susceptibility. Therefore, a better understanding of the interaction between lifestyle choices, environmental factors, and genetic predisposition is critical for developing effective treatments and preventive interventions 5, 6. Obesity greatly increases the risk of several chronic diseases such as depression, type 2 diabetes, cardiovascular disease, and certain cancers, putting a great burden on the healthcare system. Based on the latest estimates in European Union countries, 30–70% of adults are affected by overweight and 10–30% by obesity (World Health Organization). Due to an increasingly sedentary lifestyle and a transition to consumption of more and more processed foods, the prevalence of worldwide obesity has tripled over the past 40 years 4. Genome-wide association studies of BMI identified genetic variants that can account for ~2.7–6% of the observed variance in body mass index (BMI) 2, 3. Obesity is a multifactorial disorder with still poorly understood causative mechanisms and a large polygenic contribution 1. Combined with animal model and tissue-specific gene expression data, our findings suggest potential therapeutic targets further elucidating the role of these proteins in obesity associated pathologies. ![]() Mendelian randomization suggests a bi-directional causal relationship of BMI with LEPR/LEP, IGFBP1, and WFIKKN2, a protein-to-BMI relationship for AGER, DPT, and CTSA, and a BMI-to-protein relationship for another 21 proteins. ![]() These proteins are involved in lipid metabolism and inflammatory pathways impacting clinically relevant pathways of adiposity. 24 proteins also associate with a genome-wide polygenic score (GPS) for BMI. We observe 152 replicated protein associations with BMI. We show that BMI is associated with widespread changes in the plasma proteome. Here, we investigate the associations between over 1000 blood circulating proteins and body mass index (BMI) in three studies including over 4600 participants. Many proteins have been linked to complex disorders and are also under substantial genetic control. Blood circulating proteins are confounded readouts of the biological processes that occur in different tissues and organs. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |