Browsing by Subject "Functional clustering"

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    Biological heterogeneity in idiopathic pulmonary arterial hypertension identified through unsupervised transcriptomic profiling of whole blood
    (Springer Nature, 2021-12-07) Kariotis, Sokratis; Jammeh, Emmanuel; Swietlik, Emilia M.; Pickworth, Josephine A.; Rhodes, Christopher J.; Otero, Pablo; Wharton, John; Iremonger, James; Dunning, Mark J.; Pandya, Divya; Mascarenhas, Thomas S.; Errington, Niamh; Thompson, A. A. Roger; Romanoski, Casey E.; Rischard, Franz; Garcia, Joe G. N.; Yuan, Jason X.-J.; Schwantes An, Tae-Hwi; Desai, Ankit A.; Coghlan, Gerry; Lordan, Jim; Corris, Paul A.; Howard, Luke S.; Condliffe, Robin; Kiely, David G.; Church, Colin; Pepke-Zaba, Joanna; Toshner, Mark; Wort, Stephen; Gräf, Stefan; Morrell, Nicholas W.; Wilkins, Martin R.; Lawrie, Allan; Wang, Dennis; UK National PAH Cohort Study Consortium; Medicine, School of Medicine
    Idiopathic pulmonary arterial hypertension (IPAH) is a rare but fatal disease diagnosed by right heart catheterisation and the exclusion of other forms of pulmonary arterial hypertension, producing a heterogeneous population with varied treatment response. Here we show unsupervised machine learning identification of three major patient subgroups that account for 92% of the cohort, each with unique whole blood transcriptomic and clinical feature signatures. These subgroups are associated with poor, moderate, and good prognosis. The poor prognosis subgroup is associated with upregulation of the ALAS2 and downregulation of several immunoglobulin genes, while the good prognosis subgroup is defined by upregulation of the bone morphogenetic protein signalling regulator NOG, and the C/C variant of HLA-DPA1/DPB1 (independently associated with survival). These findings independently validated provide evidence for the existence of 3 major subgroups (endophenotypes) within the IPAH classification, could improve risk stratification and provide molecular insights into the pathogenesis of IPAH.
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    Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s Disease
    (Springer Nature, 2021-01-11) Johnson, Travis S.; Xiang, Shunian; Dong, Tianhan; Huang, Zhi; Cheng, Michael; Wang, Tianfu; Yang, Kai; Ni, Dong; Huang, Kun; Zhang, Jie; Biostatistics, School of Public Health
    Alzheimer’s disease (AD) brains are characterized by progressive neuron loss and gliosis. Previous studies of gene expression using bulk tissue samples often fail to consider changes in cell-type composition when comparing AD versus control, which can lead to differences in expression levels that are not due to transcriptional regulation. We mined five large transcriptomic AD datasets for conserved gene co-expression module, then analyzed differential expression and differential co-expression within the modules between AD samples and controls. We performed cell-type deconvolution analysis to determine whether the observed differential expression was due to changes in cell-type proportions in the samples or to transcriptional regulation. Our findings were validated using four additional datasets. We discovered that the increased expression of microglia modules in the AD samples can be explained by increased microglia proportions in the AD samples. In contrast, decreased expression and perturbed co-expression within neuron modules in the AD samples was likely due in part to altered regulation of neuronal pathways. Several transcription factors that are differentially expressed in AD might account for such altered gene regulation. Similarly, changes in gene expression and co-expression within astrocyte modules could be attributed to combined effects of astrogliosis and astrocyte gene activation. Gene expression in the astrocyte modules was also strongly correlated with clinicopathological biomarkers. Through this work, we demonstrated that combinatorial analysis can delineate the origins of transcriptomic changes in bulk tissue data and shed light on key genes and pathways involved in AD.