Host Blood Gene Signatures Can Detect the Progression to Severe and Cerebral Malaria

Abstract

Malaria is a major international public health problem that affects millions of patients worldwide especially in sub-Saharan Africa. Although many tests have been developed to diagnose malaria infections, we still lack reliable diagnostic biomarkers for the identification of disease severity, especially in endemic areas where the diagnosis of cerebral malaria is very difficult and requires the exclusion of all other possible causes. Previous host and pathogen transcriptomic studies have not yielded homogenous results that can be harnessed into a reliable diagnostic tool. Here we utilized a multi-cohort analysis approach using machine-learning algorithms to identify blood gene signatures that can distinguish severe and cerebral malaria from moderate and non-cerebral cases. Using a Regularized Random Forest model, we identified 28-gene and 32-gene signatures that can reliably distinguish severe and cerebral malaria, respectively. We tested the specificity of both signatures against other common infectious diseases to ensure the signatures reliability and suitability as diagnostic markers. The severe and cerebral malaria gene-signatures were further integrated through k-top scoring pairs classifiers into ten and nine gene pairs that could distinguish severe and cerebral malaria, respectively. These signatures have various implications that can be utilized as blood diagnostic tools for malaria severity in endemic countries.

The malarial blood transcriptome: translational applications

“…Many whole-blood transcriptomic malaria studies have also identified differences in gene expression between UM and the various SM syndromes [ 3 , 4 ], as well as between malaria and other acute febrile illnesses [ 20 , 21 ]. Such differences in gene expression may form the basis for future diagnostic tests that distinguish between UM and SM, and between malaria and other causes of febrile illness.…”

“…Many studies using transcriptomics to classify subjects based on current disease severity have claimed prognostic value and mention how genes are associated with disease ‘progression’ but have not formally evaluated prediction of future outcomes [ 3 , 34 , 35 ]. This has led to some confusion in the literature about the prognostic potential of transcriptomics, although classifying subjects as severe or non-severe does have intrinsic prognostic value because SM, by definition, carries an increased risk of death or disability [ 34 , 36 ].…”

“…Transcriptomic studies have been used extensively in malaria to examine host response to infection, parasite pathogenic mechanisms, and the complex interactions between the two [ 3–5 ]. These studies have focused on single cells [ 6 ] and bulk tissues during natural infections [ 7 ] and also in controlled human malaria infection studies, where healthy volunteers are intentionally infected with malaria parasites and monitored under careful clinical supervision [ 8 ].…”