Related Experiment Video
Updated: Jun 5, 2026

Isolation and Analysis of Brain-sequestered Leukocytes from Plasmodium berghei ANKA-infected Mice
Published on: January 2, 2013
Plasma Proteomics Reveals Distinct Signatures in Occult and Microfilaremic Loa loa Infections
Clemens Dierks1,2, Pinkus Tober-Lau2, Luzia Veletzky3,4
1Institute of Biochemistry, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
Background:
Loiasis, caused by the filarial nematode Loa loa, imposes a significant disease burden in endemic regions in West and Central Africa. Manifestations include adult worms in soft tissue (e.g., the conjunctiva of the eye) and microfilaria in peripheral blood, with clinical presentations ranging from asymptomatic infections to life-threatening organ involvement. Diagnosis remains challenging due to variable microfilaria counts, frequent amicrofilaremic occult infections, and unreliable serological tests. The untargeted plasma proteome reflects broad (patho-)physiological responses, providing valuable insights into the host and disease.
Methods:
Applying high-throughput plasma proteomics, we investigated the host responses of 274 patients with different L. loa disease states, including occult loiasis (n = 148), microfilaremia (n = 42), or both (n = 84), compared to 136 L. loa-negative controls. Differentially abundant proteins between L. loa-infected individuals and negative controls were validated using targeted proteomics.
Results:
Five proteins (IGHG3, IGHG4, ACTBL2, LCP1, and IGLV9-49) were elevated in infected individuals compared to healthy controls. IGHG3, IGHG4, ACTB, and LCP1 increased from L. loa negative over individuals with history of eye worm migration to microfilaremic patients, indicating a comparatively pronounced proteomic host response to microfilaria in the blood. Sixty-three proteins differed depending on self-reported symptoms. The proteomic signatures enabled accurate classification of individuals with occult loiasis (area under the receiver operating characteristic curve [AUROC] = 0.73) and microfilaremia (AUROC = 0.84) by a random forest machine learning model.
Conclusions:
Overall, infection with Loa loa alters the host plasma proteome, exhibiting distinct host responses in different infection states and allowing for molecular disease classification of this highly neglected parasitic disease.
Related Concept Videos
Rapid Identification of Pathogens
Toxoplasmosis

