Zaynab Mousavian Poster 2024

Zaynab Mousavian

Dr Zaynab Mousavian

Karolinska Institutet, Sweden

Protein-based Biomarker Discovery in Tuberculosis


Poster Abstract

Tuberculosis (TB) is a deadly infectious disease that affects millions of people globally. TB proteomics signature discovery has been a rapidly growing area of research that aims to identify protein biomarkers for the early detection, diagnosis, and treatment monitoring of TB. In an initial exploratory study, we identified a 12-protein plasma signature for active TB diagnosis from a Swedish cohort. This signature exhibited strong association with disease severity and was significantly enriched in individuals with active TB across diverse TB transcriptomic datasets. The 12- marker signature has now been further validated (AUC=0.95) in an independent Italian TB cohort with promising data indicating the signature can be condensed to 6-markers providing similar sensitivity and specificity as 12 markers, which increases feasibility to design a blood-based clinical test for diagnosis of active TB. Further validation in larger patient cohorts as well as evaluation for performance in suspect TB cases will be done to validate the signature as a possible screening test for active TB as specified in WHO target product profile.
In a separate study, we conducted a comprehensive review of proteomics biomarker discovery in the TB context. In this review, we have highlighted recent advances in this field and how it is moving from the study of single proteins to high-throughput profiling and from only using proteomics to include additional types of data in multi-omics studies. This review covers the different sample types and experimental technologies used in TB proteomics signature discovery. We also describe the signatures in the context of hypothesis-based protein targeting and the use of unbiased discovery approaches. Within this framework, the review explores the association between the identified proteins and underlying biological pathways. Furthermore, this review presents an analysis of the frequency of proteins in different published signatures, highlighting potential robust biomarker candidates. 



Zaynab obtained her PhD in Bioinformatics from the University of Tehran, Iran, in 2017. Currently, she works as a research specialist at the Department of Medicine, Solna, at Karolinska Institutet (KI), under the guidance of Dr. Christopher Sundling and Prof. Gunilla Källenius. Her primary role involves identifying a plasma protein signature for the diagnosis of active tuberculosis (TB). With a strong foundation in computer science and significant expertise in systems biology and biomarker discovery, Zaynab is deeply passionate about advancing precision medicine in infectious diseases, specifically in tuberculosis. She is dedicated to understanding the mechanism of the disease through the integration of multi-omics data using systems biology approaches and machine learning techniques.