Ingrid Kockum's research group
Genetic Epidemiology of Multiple Sclerosis
Our aim is to identify genetic risk factors for multiple sclerosis, study their function and how they together with life-style risk factors for multiple sclerosis interact.
We are trying to identify novel genetic risk variants for inflammatory diseases with focus on multiple sclerosis, both in collaboration with international consortia (e.g. MultipleMS (https://www.multiplems.eu/) and International Multiple Sclerosis Genetic Consortium (www.imsgenetics.org) and more recently together with deCODE. We are using both traditional genotyping and next generation sequencing in these studies. Currently more than 230 susceptibility variants have been identified for multiple sclerosis, the major ones being in the HLA region. We are attempting to identify which genes these variants control expression for using RNAseq data from samples from multiple sclerosis patients.
We are studying how genetic multiple sclerosis risk variants interact with multiple sclerosis risk life-style exposures such as smoking, and viral infections since this pinpoints which biological processes are acting together to cause multiple sclerosis. Several such interactions have been identified as that between HLA genes and smoking.
Immune response to viral infections such herpes virus infections (e.g. Epstein Barr, Cytmegalo Virus and Human Herpes Virus 6) is altered in multiple sclerosis, it is however unclear if this is a consequence of the disease or if these viral infections themselves affect the risk of developing MS. We are trying to address this by comparing genetic risk factors for serological response to these infections and genetic risk factors for multiple sclerosis.
Because we have access to a uniquely large and well characterized dataset of multiple sclerosis patients we are now embarking on trying to identify genetic and life-style exposure risk factors for progression/severity of multiple sclerosis. One of the stumbling blocks here is how to measure severity and progression. We will use a variety of measures ranging from standard measures such as EDSS, to patient reported outcomes and potential biomarkers such as neurofilament light. This work will be carried out in the MultipleMS project, a Horizon2020 funded project that is coordinated by Ingrid Kockum and Maja Jagodic. In this project we will also aim to stratify patients based on genetic and life-style exposures with the aim of identify subpopulations of patients that respond differently to different treatments in order to achieve personalized medicine for multiple sclerosis. We are also attempting to identify novel biomarkers for multiple sclerosis and these stratified patient populations.
- MultipleMS: Multiple manifestations of genetic and non-genetic factors in Multiple Sclerosis disentangled with a multi-omics approach to accelerate personalised medicine
- Role of genetic and lifestyle exposures in severity/outcome of multiple sclerosis
- Role of virus infections in risk for multiple sclerosis
- Genetic control of immune response to viral infections with focus on herpes viruses and JC virus
- EU-STANDS4PM: A European standardization framework for data integration and data-driven in silico models for personalized medicine
Confounding effect of blood volume and body mass index on blood neurofilament light chain levels.
Manouchehrinia A, Piehl F, Hillert J, Kuhle J, Alfredsson L, Olsson T, et al
Ann Clin Transl Neurol 2020 Jan;7(1):139-143
Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility.
Science 2019 09;365(6460):
Molecular mimicry between Anoctamin 2 and Epstein-Barr virus nuclear antigen 1 associates with multiple sclerosis risk.
Tengvall K, Huang J, Hellström C, Kammer P, Biström M, Ayoglu B, et al
Proc. Natl. Acad. Sci. U.S.A. 2019 Aug;116(34):16955-16960
Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk.
Cell 2018 11;175(6):1679-1687.e7
DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis.
Kular L, Liu Y, Ruhrmann S, Zheleznyakova G, Marabita F, Gomez-Cabrero D, et al
Nat Commun 2018 06;9(1):2397
Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients.
James T, Lindén M, Morikawa H, Fernandes SJ, Ruhrmann S, Huss M, et al
Hum. Mol. Genet. 2018 03;27(5):912-928
JC polyomavirus infection is strongly controlled by human leucocyte antigen class II variants.
Sundqvist E, Buck D, Warnke C, Albrecht E, Gieger C, Khademi M, et al
PLoS Pathog. 2014 Apr;10(4):e1004084