Socioeconomic status can influence genetic risk for many complex diseases

Differences in socioeconomic status (SES) are known to be associated with differences in the risk of developing diseases. While people with lower SES are more likely to develop complex diseases such as diabetes and cardiovascular disease, people with higher SES are at increased risk of developing certain types of cancer.

Using biobank and national registry data, researchers from Finland have now found that people with lower SES (educational attainment and occupation) have a greater genetic susceptibility to developing many other complex diseases such as rheumatoid arthritis, lung cancer, depression and alcohol use disorders. as well as type 2 diabetes, while people of higher SES are at greater risk of developing breast, prostate and all cancers.

Dr. Fiona Hagenbeek, a postdoctoral researcher at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland, who will present her group’s work at the annual conference of the European Society of Human Geneticssays these promising initial results mean it is likely that polygenic risk scores, which measure an individual’s risk of a particular disease based on genetic information, could be added to screening protocols for multiple diseases and in different countries.

“Understanding that the impact of polygenic scores on disease risk is context-dependent could lead to further stratified screening protocols,” she says. “For example, in the future, screening protocols for breast cancer could be adjusted so that women with a high genetic risk and who are highly educated are screened earlier or more often than women with a lower genetic risk or less education.”

The researchers used genomics, SES and health data from approximately 280,000 Finnish individuals in the FinnGen study, a research project in genomics and personalized medicine that aims to understand the genetic basis of diseases. The participants were between 35 and 80 years old at the time of participating in the study.

The study aimed to systematically assess the evidence of gene-environment interaction (GxE) through differential genetic susceptibility to disease in diverse socio-economic groups. Although previous studies have demonstrated the presence of such a difference in risk, this is the first to systematically assess GxE for SES in 19 complex diseases that have a high burden in high-income countries.

“Most clinical risk prediction models include basic demographic information such as biological sex and age, recognizing that disease incidence differs between men and women, and is age-dependent,” says Dr. Hagenbeek.

“Recognizing that such context also matters when integrating genetic information into healthcare is an important first step. But now we can show that the genetic prediction of disease risk also depends on an individual’s socio-economic background. So while our genetic information is not constantly changing, over our lifetime the impact of genetics on disease risk changes as we age or our circumstances change.”

The researchers hope that the study will be continued to see if further differences can be identified when looking at more specific aspects of educational and professional performance. Although their current results for occupation generally mirror those for education, they are not completely consistent, indicating that each may provide unique information about the interplay between socioeconomic status and genetics on disease risk. Expanding the list of socioeconomic indices to be studied could provide new insights into how the overlapping aspects of a person’s socioeconomic environment, together with genetic information, can influence disease risk.

The researchers will also compare their results from biobank studies from Finland, Britain, Norway and Estonia through the INTERVENE consortium, allowing them to determine whether country- or biobank-specific issues are involved.

“Our study focused exclusively on individuals of European descent, and it will also be important in the future to see whether our observations about the interplay between socioeconomic status and genetics for disease risk are replicated among people of multiple ancestry in countries with higher and lower incomes. ,” says Dr. Hagenbeek.

“Since the overall goal of integrating genetic information into healthcare is to facilitate personalized medicine, we should not treat genetic information as ‘one size fits all’. Instead, we should investigate the conditions that modify genetic risk and then take into account when predicting diseases.”

Professor Alexandre Reymond, from the Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland, and chair of the conference, added: “To truly move towards personalized healthcare it will be essential to measure both genetic and environmental risks . We must thank our Finnish colleagues for their part in leading this effort.”