Index: Karolinska Institutet: KI North: Department of Medicine, Solna


An investigation of BAFF receptor regulation following malaria infection


Supervisor: Christopher Sundling, PhD, Assistant professor
Department: Department of Medicine, Solna
Postal Address: Center for Molecular Medicine, L8:01
Karolinska University Hospital
171 76 Stockholm
Telephone: 0703-233246

E-mail: christopher.sundling@ki.se
Homepage: https://ki.se/en/people/ceriks


Background
BAFF is a key cytokine for B cell homeostasis during steady state. However, during infections, such as malaria we and others have observed a dramatic increase in BAFF levels, which could have a strong influence on the pathogen-specific B cell response. We have further observed that this increase is mostly found in individuals infected with malaria for the first time and not in those repeatedly infected. In addition we could see that the increase in BAFF levels inversely correlate with BAFF receptor (BAFF-R) levels on all B cell subsets. The BAFF-R can be regulated by several mechanisms, such as shedding of the receptor or control of receptor RNA expression via micro RNA 142. We hypothesize that the dynamic interplay of BAFF and BAFF-R is important in regulating the B cell response during malaria infection and further that the ratio of BAFF to BAFF-R could be valuable as an indication of clinical disease severity.

Aim
In this project we will investigate the regulation of BAFF and BAFF-R following malaria infection and correlate with clinical disease severity.

Workplan
We have established a cohort consisting of individuals with differential previous exposure to malaria parasites (n=65). We sampled these individuals at the acute infection, day 10, and 1, 3, 6, and 12 months after infection. We have isolated PBMCs and plasma from ~180 time-points.

BAFF and BAFF-R levels will be measured in plasma at multiple time-points using ELISA (~180 samples). BAFF-R RNA and miRNA142 expression will then be determined by Taqman probe-based qPCR from selected time-points (20 samples).

The generated data will be correlated with BAFF-R levels on B cells (data already generated), parasite levels and clinical parameters associated with disease severity.

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