Approved projects
BCFgenetics: Unravelling the genetics of insulin secretory function
Lead author: Anne Lundager Madsen, Postdoc researcher at Region Midt (through Steno or AUH)
The overall aim is to understand the genetics behind beta-cell function (BCF). We will use an in-house BCF-GWAS to apply various analyses and data to unravel the dynamics influencing the insulin secretory function.
bmihom: Calculating Homeostatic BMI Index
Lead author: Nuno Nogueira, Postdoc researcher at Aarhus University
The aim of this project aims to link deviations from homeostatic BMI with fat mass, lean mass, and mortality risk. Further, it intends to examine the connection between genetically predicted BMI and observed BMI and how it relates to mortality risk. We will assess deviations from homeostatic BMI using a combination of phenotypic and genetic data to explore their potential impact on health indicators. Genetic risk scores for adult and childhood BMI will help us understand the implications of genetically predicted BMI versus observed BMI on mortality risk.
GitHub: github.com/steno-aarhus/bmihom
bopa-hf: Body composition, sarcopenia, physical activity, malnutrition and risk of heart failure
Lead author: Andreas Bugge Tinggaard, PhD student at Aarhus University
The aim of the project is to investigate the associations between the following domains and the incidence of heart failure. 1) Body composition based on DXA-derived measurements. 2) Daily physical activity based on accelerometry metrics. 3) Physical capacity based on DXA data, handgrip and gait speed. 4) Malnutrition based on weight loss, DXA data and CRP. Furthermore, the project aims at investigating the impact of the four domains on survival in heart failure patients.
GitHub: github.com/steno-aarhus/bopa-hf
dash-hf: DASH diet and heart failure
Lead author: Daniel Ibsen, Postdoc researcher at Aarhus University
The aim is to investigate the association between adherence to the DASH diet and risk of heart failure and subtypes of heart failure. We will use multi-state models to investigate transitions of cardiovascular diseases.
GitHub: github.com/steno-aarhus/dash-hf
dmm: Multimorbidity-Disease trajectories, risk factors and the consequence
Lead author: Jie Zhang, Postdoc researcher at Aarhus University
With the growing number of people suffering from diabetes-multimorbidity, and its heterogeneity in presentation and outcome, there is an urgent need to gain a deeper understanding of the mechanisms that determine different courses of progression towards diabetes-multimorbidity. The overall aim of the project is to describe the disease transition processes that lead to diabetes-multimorbidity and to determine drivers of multimorbidity trajectories. We will apply advanced epidemiological methods to three large populations using a multi-dimensional and multi-stage approach. There are two specific aims for the project. 1) To map the heterogeneity in trajectories of diabetes-multimorbidity and to identify risk factors contributing to pronounced diabetes-multimorbidity. This will be achieved by using a machine learning approach for risk prediction, which involves combining a genetic algorithm with a random forest classifier to enhance the results. 2) To understand mortality risk at different stages of the diabetes-multimorbidity trajectory, by comparing mortality as people transition from a healthy condition to single disease, and diabetes-multimorbidity using multi-state models. To develop a web application that helps clinicians visualize the potential impact of an intervention or achieving tighter therapeutic targets on the future risk of all components of diabetes-multimorbidity. This step will be conducted by integrating results from aims 1 and 2 using simulation approaches.
GitHub: github.com/steno-aarhus/dmm
kimo: Unraveling the Relationship Between Kidney Function and Cardiovascular Risk
Lead author: Jie Zhang, Postdoc researcher at Aarhus University
The study aims to examine the association between kidney function and cardiovascular diseases (CVD) and mortality in the general population, and examine whether this potential association is causal by employing the Mendelian Randomization (MR) approach. Firstly, we will investigate the association between kidney function (eGFR-based on plasma creatinine CKD-EPI, and possibly also cystatin C) and risk of MI, heart failure, stroke and all-cause mortality in 500,000 individuals from the UK Biobank. Then we will assess the causal direction between kidney function and CVD risk using a bidirectional MR analysis.
GitHub: github.com/steno-aarhus/kimo
lega: Legume consumption and risk of gallbladder disease
Lead author: Fie Langmann, PhD student at Aarhus University
Higher legume consumption is recommended as a meat substitute to increase healthiness and minimize the climate impact from humans diets. Legumes has in animal studies and a few human studies shown to increase gallstone formation through altering the lipid metabolism in the liver. A high consumption of legumes may thus be associated with an increased risk of gallstones, yet there exists very few studies investigating this in human populations, particularly due to low consumption of legumes in many countries. Aim: To investigate the association between substituting meat, poultry, and fish for legumes and the risk of developing gallstone diseases in a cohort with moderate to high legume consumption.
GitHub: github.com/steno-aarhus/lega
legliv: Legume consumption and risk of primary liver cancer
Lead author: Niels Bock, Research year student at Aarhus University
Non-alcoholic fatty liver disease (NAFLD) may be considered the hepatic manifestation of metabolic syndrome. NAFLD-related primary liver cancer is a growing concern, and preventive interventions are critical. We will statistically model replacement of red meat consumption with legumes in relation to incident primary liver cancer and assess whether the association is mediated through NAFLD.
GitHub: github.com/steno-aarhus/legliv
leha: Prospective study on association between legume consumption and risk of hepatic and biliary disease in UKB
Lead author: Fie Langmann, PhD student at Aarhus University
The primary objective of this study is to examine the potential connection between legume consumption and the risk of various hepato-biliary disorders, including non-alcoholic steatohepatitis (NASH), non-alcoholic fatty liver disease (NAFLD), cholelithiasis, cholecystitis, cholecystectomy, pancreatitis, and pancreatectomy. The investigation takes into account possible factors that could influence this association.The study focuses on a population comprising individuals enrolled in the UK Biobank (UKB) who did not exhibit hepato-biliary diseases at the baseline assessment. Eligible participants are those who have completed one or more 24-hour dietary recall surveys. The intervention or exposure of interest is the daily consumption of legumes in grams, specifically looking at scenarios where legumes replace meat in the diet. In essence, the study seeks to explore whether legume consumption, when considered against potential confounding variables, is associated with the occurrence of hepato-biliary disorders, offering insights into dietary factors that may impact liver and gallbladder health.
GitHub: github.com/steno-aarhus/leha
met-diet: Dietary patterns, metabolites and cardiometabolic risk factors
Lead author: Daniel Ibsen, Postdoc researcher at Aarhus University
Aim: To map out likely causal pathways using metabolites to link dietary patterns to changes in adiposity and metabolic health markersPopulation: UK Biobank will be used as a validation cohort for cross-sectional analysis conducted in the Fenland Study. We excluded those with diabetes at baseline. Intervention/exposure: Adherence to the Mediterranean diet, Alternate Healthy Eating Index and the EAT-Lancet diet scoreComparison: Those with low adherence to the dietary patterns.Mediators: 249 plasma metabolites including routine lipids, lipoprotein subclass profiling with lipid concentrations within 14 subclasses, fatty acid composition, amino acids, ketone bodies and glycolysis metabolites.Outcome: BMI, waist circumference, blood pressure, blood lipids, blood glucose, insulin, HOMA-IR
GitHub: github.com/steno-aarhus/met-diet