Rino Bellocco

The overall aim is to utilize multi-omics approach to identify novel etiopathogenesis and early detection biomarkers for stomach cancer and its precursor lesions. To achieve this aim, first we will use stored serum samples to perform metabolomics profiling among 12,599 twin subjects, among whom 1034 were deemed to have chronic atrophic gastritis based on measured pepsinogen I and II levels. Logistic regression will be used to search for metabolites related to the risk of chronic atrophic gastritis. Second, we will further measure serum proteome by using two quantitatively precise proteomics assays, among the above-mentioned twin subjects. Identified protein biomarkers will be combined with metabolomics biomarkers to create a prediction model for chronic atrophic gastritis. Last, we have created a cohort of subjects who were histopathologically diagnosed with chronic atrophic gastritis or more severe precursor lesions. They were followed for stomach cancer occurrence, and a nested case-control study will be performed. Baseline formalin-fixed paraffin-embedded tissue blocks will be retrieved for both stomach cancer cases and their matched controls, and patterns of tissue proteome and transcriptome will be compared, to identify driving factors associated with progression of precursor lesions to malignancy. The results will hopefully improve our understanding of the etiological factors and provide promising early detection biomarkers for stomach cancer and its precursor lesions.

Background A recent study on Swedish data showed that the incidence of type 2 diabetes (T2D) is strongly related to occupational groups. Therefore, socioeconomic determinants of T2D are becoming a growing concern. After disease onset, correct use of antidiabetic medication (ADM) is a key factor for proper disease control and prevention of long-term severe consequences. A recent study from our team on a population of pregnant women showed associations between socioeconomic factors such as income, educational level, and country of origin, and ADM interruption. Currently, no study has yet investigated ADM use and socioeconomic inequalities in the larger population of T2D patients.Aim First, to identify socioeconomic differences in T2D patients with different ADM use patterns including treatment interruption and provide insights for policy makers. Second, to investigate associations between ADM use patterns and long-term complications of T2D, such as retinopathy and renal failure, in relation to specific socioeconomic disadvantaged groups. Ultimately, ADM use patterns and socioeconomic disparities will be investigated in relationship to comedication patterns used as proxies to evaluate the impact of comorbidities.Methods Patients’ ADM use is difficult to evaluate in a clinical trial setting since therapies for chronic diseases (such as T2D) may be life-long, but Swedish national registers offer a valuable opportunity. In the proposed project, Swedish national and diabetes quality register data will be used to identify individuals with T2D. The study population will be followed over time to provide a life course assessment of ADM use patterns in relation to socioeconomic factors, T2D complications, and comedication patterns. To properly adjust for confounding and allow for causality assessment in observational data, advanced causal inference methods such as inverse probability weighting will be used.