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DTSTART:20190328T120000
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URL:https://murmitoyen.com/events/vanille/udem/detail/866882-multiomics-and
 -multicohort-integrative-analysis-of-full-term-preterm-and-preeclampsia-in
 -human-pregnancy
LOCATION:CHU Sainte-Justine\, 3175\, Chemin de la Côte-Sainte-Catherine\, 
 Montréal\, QC\, Canada\, H3T 1C5
SUMMARY:Multiomics and Multicohort Integrative Analysis of Full Term\, Pret
 erm\, and Preeclampsia in Human Pregnancy
DESCRIPTION:Conférence scientifique | Centre de recherche du CHU Sainte-Ju
 stine
\nTitre complet:
\nMultiomics and Multicohort Integrative Analysis o
 f Full Term\, Preterm\, and Preeclampsia in Human Pregnancy   Conférencie
 r:
\nMohammed Sajjad Ghaemi\, PhD\, chercheur postdoctoral\, Faculté de m
 édecine\, Université Stanford.
\nRésumé:Understanding the biological m
 echanisms of pregnancy through high-throughput technological advances can 
 provide novel opportunities to analyze pregnancy and its pertinent dysregu
 lations to unravel unrecognized crosstalks. Such crosstalks can shed light
 s on several lines of  investigation. From a biological perspective\, it 
 can point to important disease mechanisms such as immune programming by th
 e microbiome\, or specific interactions between proteins and cellular elem
 ents. From a diagnostic perspective\, it can reveal biomarkers from severa
 l biological domains with higher predictive power if combined. Most clinic
 al assays ( e.g. \, those based on ultrasound) can only capture abnormalit
 ies at a late pregnancy stage that lack predictive power. 
\nComplete prof
 iling of the human pregnancy can only be achieved with a coordinated set o
 f omics assays targeting various levels of biology. The maintenance of pre
 gnancy hugely relies on a finely-tuned immune balance between tolerance to
  the fetal allograft and protective mechanisms against invading pathogens.
  Demonstrating the chronology of immune adaptations to a term pregnancy pr
 ovides the framework for future studies examining deviations implicated in
  pregnancy-related pathologies including preterm birth and preeclampsia. I
 n this talk\, I will present a machine learning approach for combining dat
 a from immunome (measured using mass cytometry)\, transcriptome\, proteome
 \, metabolome\, inflammasome\, and microbiome. The central tenet of this w
 ork is that holistic analyses of pregnancy and its symbiotic interactions 
 with other biological modalities can provide a detailed and actionable und
 erstanding of the mechanisms underlying the human pregnancy. In this regar
 d\, an Elastic-Net model\, with prior distributions extracted from literat
 ure-based knowledge will be introduced to develop a predictive model of in
 ter-related biological systems that is accurately able to capture the chro
 nology of pregnancy. 
\nOur model components have highlighted existing kno
 wledge\, such as enhanced innate immune responses during pregnancy. Next\,
  I will demonstrate how integrative analysis with other assays of the same
  cohort\, including data from the transcriptome\, microbiome\, proteome\, 
 and metabolome can identify a holistic understanding of immunity during pr
 egnancy. This predictive perspective not only significantly increases the 
 predictive power by combining all available datasets\, but also is able to
  reveal unique interactions between different aspects of pregnancy and its
  dysregulations such as preterm and preeclampsia.g
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