Family History Study on Cancer Risk
Ontology highlight
ABSTRACT:
DISEASE(S): Ovarian Cancer,Family Characteristics,Disease Susceptibility,Lynch Syndrome,Colorectal Cancer,Genetic Predisposition,Genetic Predisposition To Disease,Colorectal Neoplasms, Hereditary Nonpolyposis,Breast Cancer,Cancer
PROVIDER: 2320566 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Background & Aims Obesity is a major risk factor for metabolic associated steatotic liver disease (MASLD) which can progress from metabolic associated steatotic liver (MASL) to metabolic associated steatohepatitis (MASH). There are currently no effective and validated screening tools to stratify obese patients with a greater risk for MASH, independent of liver fibrosis, at a population level. We aimed to characterise the highly abundant and small protein plasma proteomes of worsening MASLD and overlay the liver-secreted proteome to generate a predictive model to stratify patients with and without MASH. Methods Venous blood and liver wedge biopsies were taken from 160 patients undergoing bariatric surgery. MASLD severity was assessed histologically. Liver biopsies from a subset of 96 patients were precision-cut and cultured to assess liver-secreted proteins. Proteomic analysis was performed using liquid chromatography-tandem mass spectrometry on the plasma and the incubation medium cutoff the liver slices. Results Current non-invasive scores failed to stratify MASH in our cohort. The top200 plasma proteome exhibited mild changes in patients with MASH compared to those with No pathology, while the SPEA approach identified substantial differences in plasma proteins of patients with MASH compared to those without MASH. Liver-secreted proteins were remodelled in MASH compared to MASL and individuals with No pathology. There were no significant changes in the liver-secreted proteins and plasma proteome when comparing MASL to those with No pathology. The APASHA model, comprised of APOF, PCSK9, AFM, and S100A6, HbA1c % and AZGP1 stratified MASH in the discovery (AUROC: 0.887, p<0.0001) and validation cohorts (AUROC:0.7673, p=0.0002) and outcompeted other non-invasive scores. Conclusions These proteomic investigations provide a detailed description of liver-secreted and plasma proteome with worsening MASLD. MASH remodels plasma and liver-secreted proteins. Plasma proteomics generated the APASHA model validated in two Australian bariatric cohorts. Further investigation is warranted to interrogate the utility of the APASHA model as a non-invasive risk prediction model in additional cohorts.
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Project description:Objective. Gout is linked with an excess risk of cardiovascular disease (CVD) and there is a need for new tests to assess and stratify high-risk patients. The Coronary Event Risk Test (CERT) based on the determination of plasma ceramides is an efficient event and death risk prediction tool. In this brief report, we focused on the application of the CERT score on hyperuricemia and gout patients for the first time.
Methods. Plasma was collected in a single center from 94 hyperuricemic patients, 196 gout patients and 53 controls. Liquid chromatography coupled with mass spectrometry was used to determine the ceramide levels. The CERT score was calculated based on the conventionally used algorithm which provides a 12-point scale that classifies patients from low-risk (score 0-2) to high-risk groups (score 10-12).
Results. We found significantly elevated CERT score in patients with gout and hyperuricemia compared to healthy controls. Increased and high-risk CERT score (>7) was 2-fold (11.7%, p-value<0.01) and 5.5-fold (31.12%, p-value<0.001) more frequent in hyperuricemic (median = 3) and gout (median = 5) patients, respectively, compared with controls (median = 2).
Conclusion. Our findings show that the CERT score can be used to stratify high-risk gout patients independently on conventional CVD markers. Additionally, we found that patients with hyperuricemia also showed increased CERT score and CVD risk. These results show for the first time how the CERT score can be used in rheumatology practice to stratify and manage gout and hyperuricemic patients by this novel predictive tool.
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Project description:Background & Aims Obesity is a major risk factor for metabolic associated steatotic liver disease (MASLD) which can progress from metabolic associated steatotic liver (MASL) to metabolic associated steatohepatitis (MASH). There are currently no effective and validated screening tools to stratify obese patients with a greater risk for MASH, independent of liver fibrosis, at a population level. We aimed to characterise the highly abundant and small protein plasma proteomes of worsening MASLD and overlay the liver-secreted proteome to generate a predictive model to stratify patients with and without MASH. Methods Venous blood and liver wedge biopsies were taken from 160 patients undergoing bariatric surgery. MASLD severity was assessed histologically. Liver biopsies from a subset of 96 patients were precision-cut and cultured to assess liver-secreted proteins. Proteomic analysis was performed using liquid chromatography-tandem mass spectrometry on the plasma and the incubation medium cutoff the liver slices. Results Current non-invasive scores failed to stratify MASH in our cohort. The top200 plasma proteome exhibited mild changes in patients with MASH compared to those with No pathology, while the SPEA approach identified substantial differences in plasma proteins of patients with MASH compared to those without MASH. Liver-secreted proteins were remodelled in MASH compared to MASL and individuals with No pathology. There were no significant changes in the liver-secreted proteins and plasma proteome when comparing MASL to those with No pathology. The APASHA model, comprised of APOF, PCSK9, AFM, and S100A6, HbA1c % and AZGP1 stratified MASH in the discovery (AUROC: 0.887, p<0.0001) and validation cohorts (AUROC:0.7673, p=0.0002) and outcompeted other non-invasive scores. Conclusions These proteomic investigations provide a detailed description of liver-secreted and plasma proteome with worsening MASLD. MASH remodels plasma and liver-secreted proteins. Plasma proteomics generated the APASHA model validated in two Australian bariatric cohorts. Further investigation is warranted to interrogate the utility of the APASHA model as a non-invasive risk prediction model in additional cohorts. Lay Summary: Metabolic-associated steatohepatitis (MASH), a more advanced form of metabolic-associated steatotic liver disease (MASLD), alters the levels of many proteins secreted by the liver and in the blood and those. The APASHA model, which is based on proteins that change in the blood or are secreted by the liver in cases of MASH, could potentially be developed into a simple blood test to predict MASH in high-risk groups.
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