Johan Mellergård

Presentation

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease that affects the central nervous system and is a common cause of neurological disability in young adults. In my research group, we are interested in the mechanisms that drive the different disease courses in MS, ranging from the relapsing phase to the progressive stage characterized by a slowly increasing loss of function. By analyzing potential biomarkers of disease activity and disease progression in blood, cerebrospinal fluid, and through quantitative MRI at various stages of the disease, our overall aim is to enable more personalized treatments for this complex condition in the future.

Alongside my research activities, I also work as a senior consultant neurologist at the Neurology Clinics in Linköping and Norrköping, and I am an adjunct lecturer at the Medical Programme at Linköping University.

Research description

Bioinformatic tools for exploring and identifying mechanisms that drive disease activity and progression in multiple sclerosis.

Multiple sclerosis (MS) is a complex inflammatory, demyelinating, and neurodegenerative disease of the central nervous system (CNS), and is one of the leading causes of non-traumatic disability in young adults. There is a critical need for biomarkers that reflect the underlying pathological mechanisms driving the considerable heterogeneity observed across different MS disease courses and that can be readily monitored. Identifying such biomarkers would enable clinicians to make more informed decisions regarding personalized treatment strategies and would support the development of new therapies.

Conventional magnetic resonance imaging (MRI) remains a cornerstone for both diagnosis and disease monitoring in MS. However, it lacks the sensitivity required to detect and differentiate the complex pathology underlying the diverse clinical manifestations of the disease. Consequently, there is an urgent need to discover novel biomarker candidates.

An exploratory and translational strategy to identify new biomarkers in plasma, cerebrospinal fluid (CSF), and via MRI will generate large and complex datasets, necessitating the use of machine-learning approaches for data analysis. Building on our previous work employing this methodology, we aim to further expand these targeted proteomic analyses and integrate them with molecular information from microRNAs (miRNAs) and data obtained from advanced quantitative MRI (qMRI) techniques, with the goal of identifying biomarkers that can guide personalized treatment in MS.

Research centre

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Wallenberg Centre for Molecular Medicine at LiU

WCMM at LiU focuses on the medicine-technology interface, and build upon our existing strengths in research within medical technology, materials science and bioengineering.

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Center for Social and Affective Neuroscience - CSAN

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Department of Biomedical and Clinical Sciences (BKV)

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Faculty of Medicine and Health Sciences (MEDFAK)

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