scholarly journals 963. Whole Blood Transcriptome Analysis Reveals Differences in Erythropoiesis and Neurologically Relevant Pathways Between Cerebral Malaria and Severe Malarial Anemia

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S35-S35
Author(s):  
Srinivas Nallandhighal ◽  
Gregory Park ◽  
Yen-Yi Ho ◽  
Robert Opoka ◽  
Chandy John ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cerebral Malaria ◽  
Severe Malaria ◽  
Whole Blood ◽  
Heme Oxygenase 1 ◽  
Specific Gene ◽  
Severe Malarial Anemia ◽  
Specific Gene Expression ◽  
Blood Transcriptome ◽  
Malarial Anemia

Abstract Background Plasmodium falciparum malaria can rapidly progress to severe disease that can lead to death if left untreated. Severe malaria cases commonly present as severe malarial anemia (SMA), defined in children as hemoglobin (Hb) <5 g/dL with parasitemia, or as cerebral malaria (CM), which manifests as parasitemia with acute neurological deficits and has an inpatient mortality rate of ~20%. The molecular and cellular processes that lead to CM and SMA are unclear. Methods In a cross-sectional study, we compared genome-wide transcription profiles of whole blood obtained from Ugandan children with acute CM (n = 17) or SMA (n = 17) and community children without P. falciparum infection (n = 12) who were enrolled in a parent cohort study of severe malaria. We determined the relationships between gene expression, hematological indices, and plasma biomarkers, including inflammatory cytokines. Results Both CM and SMA demonstrated enrichment of dendritic cell activation, inflammatory/TLR/chemokines, monocyte, and neutrophil modules but depletion of lymphocyte modules. Neurodegenerative disease and neuroinflammation pathways were enriched in CM. Increased Nrf2 pathway gene expression corresponded with increased plasma heme oxygenase-1 and the heme catabolite bilirubin in a manner specific to children with both SMA and sickle cell disease. Reticulocyte-specific gene expression was markedly decreased in CM relative to SMA despite higher Hb levels and appropriate increases in plasma erythropoietin. Viral sensing/interferon regulatory factor (IRF) 2 module (M111) expression and plasma IP-10 levels both negatively correlated with reticulocyte-specific signatures, but only M111 expression independently predicted decreased reticulocyte-specific gene expression after controlling for leukocyte count, Hb level, parasitemia, and clinical syndrome by multiple regression. Conclusion Differences in the blood transcriptome of CM and SMA relate to neurologically relevant pathways and erythropoiesis. Erythropoietic suppression during severe malaria is more pronounced during CM versus SMA and is positively associated with IRF2 blood signatures. Future studies are needed to validate these findings. Disclosures All authors: No reported disclosures.

scholarly journals Predicting tissue-specific gene expression from whole blood transcriptome

2020 ◽  
Author(s):  
Mahashweta Basu ◽  
Kun Wang ◽  
Eytan Ruppin ◽  
Sridhar Hannenhalli
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Specific Gene ◽  
Specific Expression ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Tissue Specific Gene ◽  
Tissue Specific Expression ◽  
Specific Gene Expression ◽  
Blood Transcriptome

AbstractComplex diseases are systemic, largely mediated via transcriptional dysregulation in multiple tissues. Thus, knowledge of tissue-specific transcriptome in an individual can provide important information about an individual’s health. Unfortunately, with a few exceptions such as blood, skin, and muscle, an individual’s tissue-specific transcriptome is not accessible through non-invasive means. However, due to shared genetics and regulatory programs between tissues, the transcriptome in blood may be predictive of those in other tissues, at least to some extent. Here, based on GTEx data, we address this question in a rigorous, systematic manner, for the first time. We find that an individual’s whole blood gene expression and splicing profile can predict tissue-specific expression levels in a significant manner (beyond demographic variables) for many genes. On average, across 32 tissues, the expression of about 60% of the genes is predictable from blood expression in a significant manner, with a maximum of 81% of the genes for the musculoskeletal tissue. Remarkably, the tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including Hypertension and Type 2 diabetes, substantially surpassing predictors built directly from the blood transcriptome. The code for our pipeline for tissue-specific gene expression prediction – TEEBoT, is provided, enabling others to study its potential translational value in other indications.

scholarly journals Predicting tissue-specific gene expression from whole blood transcriptome

2021 ◽  
Vol 7 (14) ◽  
pp. eabd6991
Author(s):  
Mahashweta Basu ◽  
Kun Wang ◽  
Eytan Ruppin ◽  
Sridhar Hannenhalli
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Specific Gene ◽  
Specific Expression ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Tissue Specific Gene ◽  
Tissue Specific Expression ◽  
Specific Gene Expression ◽  
Blood Transcriptome

Complex diseases are mediated via transcriptional dysregulation in multiple tissues. Thus, knowing an individual’s tissue-specific gene expression can provide critical information about her health. Unfortunately, for most tissues, the transcriptome cannot be obtained without invasive procedures. Could we, however, infer an individual’s tissue-specific expression from her whole blood transcriptome? Here, we rigorously address this question. We find that an individual’s whole blood transcriptome can significantly predict tissue-specific expression levels for ~60% of the genes on average across 32 tissues, with up to 81% of the genes in skeletal muscle. The tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including hypertension and type 2 diabetes, substantially surpassing the blood transcriptome. The code for tissue-specific gene expression prediction, TEEBoT, is provided, enabling others to study its potential translational value in other indications.

scholarly journals Circulatory hepcidin is associated with the anti-inflammatory response but not with iron or anemic status in childhood malaria

Blood ◽  
2013 ◽  
Vol 121 (15) ◽  
pp. 3016-3022 ◽  
Author(s):  
Florence Burté ◽  
Biobele J. Brown ◽  
Adebola E. Orimadegun ◽  
Wasiu A. Ajetunmobi ◽  
Nathaniel K. Afolabi ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Cerebral Malaria ◽  
Severe Malaria ◽  
Severe Malarial Anemia ◽  
Key Points ◽  
Mild Malaria ◽  
Anti Inflammatory ◽  
Childhood Malaria ◽  
Malarial Anemia

Key Points Hepcidin rises more dramatically in mild malaria than in severe malaria. Hepcidin levels are linked to inflammation, not anemia, in severe malarial anemia and cerebral malaria.

scholarly journals Lymphocyte Perturbations in Malawian Children with Severe and Uncomplicated Malaria

2015 ◽  
Vol 23 (2) ◽  
pp. 95-103 ◽  
Author(s):  
Wilson L. Mandala ◽  
Chisomo L. Msefula ◽  
Esther N. Gondwe ◽  
James J. Gilchrist ◽  
Stephen M. Graham ◽  
...  
Keyword(s):  
Cerebral Malaria ◽  
Severe Malaria ◽  
Uncomplicated Malaria ◽  
Lymphocyte Activation ◽  
Lymphocyte Subset ◽  
Memory Cells ◽  
Age Assessment ◽  
Immune Priming ◽  
Severe Malarial Anemia ◽  
Malarial Anemia

ABSTRACTLymphocytes are implicated in immunity and pathogenesis of severe malaria. Since lymphocyte subsets vary with age, assessment of their contribution to different etiologies can be difficult. We immunophenotyped peripheral blood from Malawian children presenting with cerebral malaria, severe malarial anemia, and uncomplicated malaria (n= 113) and healthy aparasitemic children (n= 42) in Blantyre, Malawi, and investigated lymphocyte subset counts, activation, and memory status. Children with cerebral malaria were older than those with severe malarial anemia. We found panlymphopenia in children presenting with cerebral malaria (median lymphocyte count, 2,100/μl) and uncomplicated malaria (3,700/μl), which was corrected in convalescence and was absent in severe malarial anemia (5,950/μl). Median percentages of activated CD69+NK (73%) and γδ T (60%) cells were higher in cerebral malaria than in other malaria types. Median ratios of memory to naive CD4+lymphocytes were higher in cerebral malaria than in uncomplicated malaria and low in severe malarial anemia. The polarized lymphocyte subset profiles of different forms of severe malaria are independent of age. In conclusion, among Malawian children cerebral malaria is characterized by lymphocyte activation and increased memory cells, consistent with immune priming. In contrast, there are reduced memory cells and less activation in severe malaria anemia. Further studies are required to understand whether these immunological profiles indicate predisposition of some children to one or another form of severe malaria.

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