Diabetes is a complex disease characterized by a combination of different and little understood, causes. The current classification system for the disease characterizes diabetes into three broad types: type 1 diabetes, type 2 diabetes, and gestational diabetes, but these three categories do not adequately reflect its sheer heterogeneity. This has severe negative implications for the planning of treatment regimens and identifying which patients are at risk of developing complications or comorbidities. Building on previous research which identified five novel diabetes subgroups in Scandinavian diabetes patient cohorts, this study sought to comprehensively characterize differences in inflammation biomarkers between these subgroups using Olink’s inflammation biomarker panel.
Dr. Andrzej Krolewski (Find his profile here), the head of the Genetics and Epidemiology section of the Harvard Medical School, has been working on the genetics of type 1 and type 2 diabetes. For the last 30 years, he has been actively investigating diabetic kidney disease in patient cohorts from the Joslin diabetes center, where he is also a researcher.
To wrap up this month’s theme of Olink Explore 1536, here is an example of Olink Explore in action: To better understand the pathology of severe COVID-19 and why SARS-Co-V2 elicits a severe response in some patients, but not in others.
The following study illustrates how transcriptomics and proteomics complement one another to clarify the pathology of a complex, and little understood disease. Atopic dermatitis (AD) is the most common chronic skin condition affecting up to 20% of children and 7-10% of adults, depending on the population. The disease is incredibly complex and heterogenous, so finding an effective treatment has proven to be quite difficult. Moreover, the use of the skin biopsy as a method of sample collection is incredibly invasive and can cause scarring. Therefore, Rojahn et al. (2020) sought to test a less invasive and painful method known as skin blistering, which, unlike skin biopsies, would allow both transcriptomic analysis from skin cells, and proteomic analysis of the interstitial fluid from the blister.
To achieve the goal of precision medicine, not only do different molecular profiles need to be understood in disease populations, but they must also be understood in the context of healthy populations. This especially applies to the stability of molecular profiles among healthy individuals over time, as this will clarify what qualifies as a ‘normal range’ of clinical parameters in health and disease research. The following study by Tebani et al. (2020) conducted a longitudinal analysis of the blood profiles from 100 healthy individuals to understand how they varied both between different individuals, and within an individual over time.