SRA EpiHealth has conducted an interview with board member of EpiHealth Professor Martin Englund and postdoc Andrea Dell'isola about the EpiHealth cohort, how they plan to use it in their research, and what it means to them and SRA EpiHealth.
Martin has been awarded research support from SRA EpiHealth for the employment of Andrea as a postdoc for the project “The role of lifestyle and metabolic health in the pathogenesis and management of osteoarthritis”. He heads the Clinical Epidemiology Unit (CEU), Orthopedics, which is a cross-disciplinary research group at Department of Clinical Sciences Lund, Lund University www.clinicalepidemiology.se.
Martin is an epidemiologist and translational science investigator. He completed his MD in 1998 and received his PhD in Orthopedics in 2004. He did a two-year postdoctoral training at Boston University, United States, where he also earned his MSc degree in Epidemiology. Martin focuses on osteoarthritis research, including preclinical experiments as well as clinical studies, imaging and epidemiological research using population-based register data. He is a current consolidator grant recipient by the European Research Council (ERC), and a past Distinguished Young Researcher awardee by the Swedish Research Council.
Andrea is a physiotherapist and postdoc with extensive knowledge of osteoarthritis clinical studies and an interest in using data from the EpiHealth cohort. The EpiHealth cohort comprises a total of 25,104 individuals from Uppsala and Malmö in the age groups 45-75 years. The data was collected during the years 2010-2016 and include lung function (spirometry), inch ECG, blood pressure, body composition, cognitive test (Trial-Making-Test), fasting blood glucose and blood fats. A questionnaire about sociodemographic lifestyle factors, previous illnesses is also included in the EpiHealth cohort. A biobank is also available for future use and a DNA extraction with GWAS analysis has been carried out throughout the cohort.
Martin explains, “I have been involved in the EpiHealth cohort steering group since the inception (beginning of 2010) and the beauty with EpiHealth data is that the large number of participants enables the possibility to effectively evaluate risk factors. We also have access to de-identified information about lifestyle factors such as diet and environment exposure which is typically not available in other registers. Also, by now the cohort has a long follow-up time, more than 10 years for many of the participants”.
We continue the interview by asking Martin to provide us with some information about the expertise of his research team. “Epidemiology is a cross-disciplinary field, and our team members have a mixed background: Some are molecular scientists, medical physicists or have degrees and expertise in bioinformatics, statistics or health economy. Others are healthcare professionals with a typical clinical background as physician or in physical therapy. The mix gives us a multifactorial view on osteoarthritis and helps bring the field forward”, says Martin. He further says: “There are “three legs” in our research focus: molecular mechanisms of the disease, imaging of structural findings, and register-based epidemiologic studies and burden of disease”.
We ask Andrea if he would like to tell us a bit more about his particular research project and explain to the reader what osteoarthritis is. “Osteoarthritis is a type of degenerative joint disease [AD1] typically characterized by the breakdown of joint cartilage, joint inflammation and bone remodeling. The most common symptoms are joint pain and stiffness. Usually, the symptoms progress slowly over the years, but exercise can prevent functional decline. When we use data from the EpiHealth cohort we have the possibility to identify clinical phenotypes which are groups of people with certain characteristics which may influence the joint disease mechanisms. A common subgroup sees OA coexisting with other metabolic diseases such as diabetes, obesity, and high blood pressure, often due to inactive lifestyles and inappropriate diet. Early signs of the disease are usually found in people in their forties but progress when people are 60 years or older. The EpiHealth dataset helps us to look at disease development and how this will impact people over 10 years. Little is known about the interplay between lifestyle factors, metabolic health and osteoarthritis which we are trying to investigate”.
During the interview we talk about the scientific research methods that are being used and if barriers have been identified. Andrea explains “We are doing quantitative research with the use of advanced statistical models to try to understand the causal link(s) between lifestyle factors, overall health and the development of musculoskeletal diseases such as osteoarthritis. However, it is a lengthy process to receive all the data and link data from all registers. It takes time”.
We are also talking about the key messages of the research project and the use of EpiHealth datasets. Andrea explains “A single treatment of osteoarthritis is no longer viable and optimal. We are therefore looking at links between diseases since they often come in clusters. Big datasets are therefore essential to us which is why we are using the EpiHealth cohort”.
We also discuss the use of networks in research and Martin explains that they have a vast network. “We are collaborating with multiple research groups from Europe, USA, Australia and Asia, and we use a number of international datasets apart from EpiHealth data. In Sweden we have also created our own Biobank of joint tissues from patients who have undergone total knee joint replacement. Joint tissues from deceased donors are also collected in collaboration with The Tissue Bank and Forensic Medicine, Skåne University Hospital. We also collaborate with EpiHealth members from Uppsala”.
For more information about CEU, epidemiological research and osteoarthritis, please visit: