With the rapid aging of population, the morbidity of neurological diseases grows, bringing heavier economic burden meanwhile threatening human health. In order to identify people at higher risk of neurological diseases and take timely interventions to prevent or cure them, better understanding to their relevant risk factors is a necessity. The purpose of our research is to discover risk factors and biomarkers relevant to different neurological diseases with brain neuroimaging, genetic and biochemical data, and explore the interaction among risk factors and their relationship with neurological diseases, using mathematical models based on machine learning algorithms. The neurological diseases we mainly focus on are cerebral small vessel disease (lacunar infarction, white matter degeneration), stroke, alzheimer’s disease, vascular dementia,
Primary headache (migraine, tension-type headache, trigeminal autonomic headache), neuralgia, pathological neuralgia, Parkinson’s.The large amount of clinical, imaging and genetic data provided by UK Biobank makes it possible to deepen our understanding into the interaction and causality of different risk factors in the pathophysiological mechanism of neurological diseases. Consistent with the aims of the UK Biobank, this research will hopefully provide new models for the diagnosis, classification, prevention and prognosis of neurological diseases, helping medical professionals accurately recognize the risk of neurological diseases and understand the pathogenic mechanism, furthermore laying basis for discovery of better diagnosis and treatment to neurological diseases. Project duration: this project will last for 3 years. An additional 12 months access to data after completion of the project will be required.
