Åsa Johansson – The role of genetic and lifestyle factors on human health and on the risk of common diseases

Many people will develop a common disease at some point in their lives, such as cancer, stroke, heart attack, or diabetes. Our research aims to understand how genetics and lifestyle interact to influence disease risk, how these effects differ between men and women, and the role of hormonal factors.

Common diseases are complex and influenced by many genetic, environmental, and lifestyle factors, many of which remain unknown. We also seek to understand the molecular pathways through which these factors act and why disease risk varies between individuals.

Improved precision medicine

By combining genetic and molecular analyses of blood samples with large-scale epidemiological data, we map the impact of different risk factors and investigate who benefits most from preventive measures and treatments. Ultimately, our goal is to advance precision medicine, tailoring healthcare to everyone’s unique biological profile, to more effectively prevent disease, improve health, and deliver more targeted and personalized care.

Identifying high-risk individuals

In our research we combine advanced statistical methods and machine learning with both hypothesis-driven and data-driven approaches to understand disease risk and biology. We work with large-scale cohorts integrating multi-omics and multi-modal data, as well as clinical studies, including pragmatic trials and nationwide health registers covering the entire Swedish population.

This combination allows us to uncover novel disease mechanisms, identify high-risk individuals, and evaluate preventive and therapeutic strategies in real-world settings. By leveraging both comprehensive population-level data and detailed molecular information, we aim to translate complex biological insights into actionable knowledge for precision medicine.

We focus on four main areas of research:

1. Characterizing molecular pathways linking risk factors to disease

We investigate why some individuals develop disease while others remain healthy by studying the molecular mechanisms connecting genetic and lifestyle risk factors to disease. By integrating genetic, molecular, and multi-omics analyses with detailed clinical and epidemiological data, we map the biological pathways through which these risk factors act. This approach helps us identify potential targets for prevention and treatment and improves our understanding of individual variability in disease risk.

2. Investigating sex- and age-specific differences in disease risk

We investigate how genetic, lifestyle, and environmental factors interact differently across sexes, contributing to differences in disease susceptibility and progression. We also examine how the timing and duration of exposure to risk factors can influence disease risk across the lifespan. This approach uncovers why certain individuals are more susceptible to disease at specific stages of life and supports the development of more effective, sex- and age-informed prevention strategies.

3. Understanding the role of hormonal factors

We investigate how both endogenous hormones produced naturally by the body and exogenous hormones introduced through hormonal contraceptives or menopausal hormone therapy influence disease risk. Our research explores the molecular pathways mediating these effects and clarifies how hormones interact with genetic and lifestyle factors to shape individual susceptibility to diseases such as stroke, cancer, and metabolic disorders.

4. Identifying high-risk individuals for precision prevention and treatment

We use genetic and molecular data to identify individuals at high risk of developing common diseases. By integrating information from polygenic risk scores, rare pathogenic variant, or other omics data, we can better predict who is most likely to benefit from specific preventive measures or treatments. This approach allows for targeted interventions and treatments matched to everyone’s risk profile, ultimately improving treatment efficiency and health outcomes on an individual level.