Autoimmune, inflammatory and oncologic skin disease affecting 3-10% of the population. However, the understanding of infectious, inflammatory, oncologic, and autoimmune skin diseases is still limited. To address this limitation, In this study, we intended to apply for epidemiological! blood biomarkers, omics (genomics, epigenomics, transcriptomics, proteomics, metabolomics and lipidomics), comorbidities, dietary, activity, behavioural, drug use, hormonal, sleep pattern, social economy and environmental factors data of skin diseases (such as scleroderma, dermatomyositis, lupus erythematosus, eczema, acne, atopic dermatitis, actinic dermatitis, contact dermatitis, psoriasis, urticaria, scalp alopecia, vitiligo, and elanoma). Our objective was to uncover new risk factors, new prognostic biomarkers and study the links between skin diseases and comorbid disorders. The present study was based on following objectives. 1) systemically investigate and compare the influence of environmental, occupational, genetic, dietary, medication use, sleep, intake of trace elements, lifestyle behaviours and socio-economic factors on skin diseases. 2) explore the causal link between diabetes and its complications (The cardiovascular, digestive, endocrine, hepatobiliary, respiratory and genitourinary systems diseases). 3) To find new biomarkers for skin diseases using machine learning algorithms and multiple statistical methods to assess the impact of risk factors on diseases. The etiology of these disorders remains uncertain and the deeper mechanisms of the comorbidity are yet to be uncovered. Given the gravity of this situation!it has become paramount to allocate resourses and prioritize efforts towards the prevention and trearment of these conditions.
