Approved Research

Uncovering potential multifaceted links between genetic, biological, environmental, behavioral, and clinical factors in the development and progression of respiratory diseases.

Lay summary

Our research project, addressing the growing global challenge of respiratory diseases, aims to understand how various factors like genetics, environment, lifestyle, and clinical treatments interact and influence these diseases. With the rise in air pollution and an aging population, diseases such as lung cancer, idiopathic pulmonary fibrosis, and pulmonary hypertension are becoming more common and severe. While these diseases are often linked to genetic factors, others like chronic obstructive pulmonary disease (COPD), pneumonia, and interstitial lung disease (ILD) seem to be more influenced by lifestyle, environmental, and clinical factors.

The goal of our study is to explore these connections in depth. We plan to first analyze clinical data to find potential links between respiratory diseases and various influencing factors. Then, we'll dive deeper into biological and histological data to understand the underlying molecular mechanisms. This approach will help us propose new strategies for early prevention, better clinical treatments, and identifying new therapeutic targets for these diseases.

To ensure our findings are accurate and reliable, we'll use advanced statistical methods to analyze the data in detail. This includes processing initial data with generalized estimating equations and then using sophisticated techniques like Cox proportional risk models, logistic regression, or restricted cubic splines (RCS) for further analysis. RCS is particularly important for us as it helps in understanding the nonlinear relationships that are often present in medical data but hard to model with traditional methods.

Moreover, we'll employ machine learning algorithms to analyze complex biological data (multi-omics data), which will help us understand how different biological systems interact. Combined with a technique called Mendelian randomization, this approach will help us confirm significant findings in our histological data.

Over the course of three years, our team will categorize data into major disease areas such as interstitial lung disease, pulmonary embolism, respiratory neoplasms, infectious diseases, COPD, and bronchial asthma. We will then conduct an in-depth analysis to uncover how different factors affect various aspects of these diseases, including onset, progression, treatment, and prognosis. Our comprehensive research aims to provide scientific evidence that can support early prevention, effective clinical treatments, and better outcomes for patients, ultimately reducing the burden of respiratory diseases on public health.