Browsing by Author "Walakira, Andrew"

Now showing 1 - 4 of 4
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    Associations between red blood cell variants and malaria among children and adults from three areas of Uganda: a prospective cohort study
    (Malaria Journal, 2020) Kakande, Elijah; Greenhouse, Bryan; Bajunirwe, Francis; Drakeley, Chris; Nankabirwa, Joaniter I.; Walakira, Andrew; Nsobya, Samuel L.; Katureebe, Agaba; Rek, John; Arinaitwe, Emmanuel; Rosenthal, Philip J.; Kamya, Moses R.; Dorsey, Grant; Rodriguez‑Barraquer, Isabel
    Multiple red blood cell (RBC) variants appear to offer protection against the most severe forms of Plasmodium falciparum malaria. Associations between these variants and uncomplicated malaria are less clear. Data from a longitudinal cohort study conducted in 3 sub-counties in Uganda was used to quantify associations between three red blood cell variants Hb [AA, AS, S (rs334)], alpha thalassaemia 3.7 kb deletion, and glucose-6-phosphate dehydrogenase deficiency A—(G6PD 202A genotype) and malaria incidence, parasite prevalence, parasite density (a measure of anti-parasite immunity) and body temperature adjusted for parasite density (a measure of anti-disease immunity). All analyses were adjusted for age, average household entomological inoculation rate, and study site. Results for all variants were compared to those for wild type genotypes.
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    Detecting gene–gene interactions from GWAS using diffusion kernel principal components
    (Bmc Bioinformatics, 2022) Walakira, Andrew; Ocira, Junior; Duroux, Diane; Fouladi, Ramouna; Moškon, Miha; Rozman, Damjana; Steen, Kristel Van
    Genes and gene products do not function in isolation but as components of complex networks of macromolecules through physical or biochemical interactions. Dependencies of gene mutations on genetic background (i.e., epistasis) are believed to play a role in understanding molecular underpinnings of complex diseases such as inflammatory bowel disease (IBD). However, the process of identifying such interactions is complex due to for instance the curse of high dimensionality, dependencies in the data and non-linearity. Here, we propose a novel approach for robust and computationally efficient epistasis detection. We do so by first reducing dimensionality, per gene via diffusion kernel principal components (kpc). Subsequently, kpc gene summaries are used for downstream analysis including the construction of a gene-based epistasis network. We show that our approach is not only able to recover known IBD associated genes but also additional genes of interest linked to this difficult gastrointestinal disease.
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    Guided extraction of genome-scale metabolic models for the integration and analysis of omics data
    (Computational and Structural Biotechnology Journal, 2021) Walakira, Andrew; Rozman, Damjana; Režen, Tadeja; Mraz, Miha; Moškon, Miha
    Omics data can be integrated into a reference model using various model extraction methods (MEMs) to yield context-specific genome-scale metabolic models (GEMs). How to chose the appropriate MEM, thresholding rule and threshold remains a challenge. We integrated mouse transcriptomic data from a Cyp51 knockout mice diet experiment (GSE58271) using five MEMs (GIMME, iMAT, FASTCORE, INIT and tINIT) in a combination with a recently published mouse GEM iMM1865. Except for INIT and tINIT, the size of extracted models varied with the MEM used (t-test: p-value < 0.001). The Jaccard index of iMAT models ranged from 0.27 to 1.0. Out of the three factors under study in the experiment (diet, gender and genotype), gender explained most of the vari- ability (> 90%) in PC1 for FASTCORE. In iMAT, each of the three factors explained less than 40% of the variability within PC1, PC2 and PC3. Among all the MEMs, FASTCORE captured the most of the true variability in the data by clustering samples by gender. Our results show that for the efficient use of MEMs in the context of omics data integration and analysis, one should apply various MEMs, thresholding rules, and thresholding values to select the MEM and its configuration that best captures the true variability in the data. This selection can be guided by the methodology as proposed and used in this paper. Moreover, we describe certain approaches that can be used to analyse the results obtained with the selected MEM and to put these results in a biological context.
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    Impact of Antimalarial Treatment and Chemoprevention on the Drug Sensitivity of Malaria Parasites Isolated from Ugandan Children
    (Antimicrobial agents and chemotherapy, 2015) Tumwebaze, Patrick; Conrad, Melissa D.; Walakira, Andrew; LeClair, Norbert; Byaruhanga, Oswald; Nakazibwe, Christine; Okiring, Jaffer; Kakuru, Abel; Bigira, Victor; Kapisi, James; Kamya, Moses R.; Greenhouse, Bryan; Nsobya, Samuel L.; Rosenthal, Philip J.
    Changing treatment practices may be selecting for changes in the drug sensitivity of malaria parasites. We characterized ex vivo drug sensitivity and parasite polymorphisms associated with sensitivity in 459 Plasmodium falciparum samples obtained from subjects enrolled in two clinical trials in Tororo, Uganda, from 2010 to 2013. Sensitivities to chloroquine and monodesethylamodiaquine varied widely; sensitivities to quinine, dihydroartemisinin, lumefantrine, and piperaquine were generally good. Associations between ex vivo drug sensitivity and parasite polymorphisms included decreased chloroquine and monodesethylamodiaquine sensitivity and increased lumefantrine and piperaquine sensitivity with pfcrt 76T, as well as increased lumefantrine sensitivity with pfmdr1 86Y, Y184, and 1246Y. Over time, ex vivo sensitivity decreased for lumefantrine and piperaquine and increased for chloroquine, the prevalences of pfcrt K76 and pfmdr1 N86 and D1246 increased, and the prevalences of pfdhfr and pfdhps polymorphisms associated with antifolate resistance were unchanged. In recurrent infections, recent prior treatment with artemether-lumefantrine was associated with decreased ex vivo lumefantrine sensitivity and increased prevalence of pfcrt K76 and pfmdr1 N86, 184F, and D1246. In children assigned chemoprevention with monthly dihydroartemisinin-piperaquine with documented circulating piperaquine, breakthrough infections had increased the prevalence of pfmdr1 86Y and 1246Y compared to untreated controls. The noted impacts of therapy and chemoprevention on parasite polymorphisms remained significant in multivariate analysis correcting for calendar time. Overall, changes in parasite sensitivity were consistent with altered selective pressures due to changing treatment practices in Uganda. These changes may threaten the antimalarial treatment and preventive efficacies of artemether-lumefantrine and dihydroartemisinin-piperaquine, respectively.