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Maternal NK cell recognition of the placenta determines reproductive outcome (360G-Wellcome-200841_Z_16_Z)

Our aim is to understand how the uterine immune system regulates placentation and reproductive success in humans. We described a new mechanism of maternal allogeneic recognition that depends on KIR expressed by uterine NK (uNK) cells and their ligands, HLA-C, on fetal trophoblast. KIR and HLA-C genes are highly polymorphic and we find reproducible and specific KIR/HLA-C genetic combinations associated with reproductive disorders. We will: 1) use high throughput typing to allele level of KIR and HLA-C genes to describe how this variation affects pregnancy success. 2) translate these genetic findings into how NK cells affect trophoblast functions exploiting our new techniques, mass cytometry and long term trophoblast cell culture. 3) use transgenic mouse models to mimic the KIR/HLA-C combinations with poor outcome to study placentation in vivo and to test therapeutic anti-KIR mAbs. From a translational perspective we will: 4) investigate whether disorders such as pre-eclampsia that are common in women undergoing assisted reproductive technology with oocyte or sperm donation can be prevented by genotyping donors for KIR/HLA-C and 5) use the extraordinary variability of KIR genes in sub-Saharan Africa to study differences that can explain the increased frequency of pregnancy disorders in African women.


05 Apr 2016

Grant details
Amount Awarded 2140661
Applicant Surname Colucci
Approval Committee Science Interview Panel
Award Date 2016-04-05T00:00:00+00:00
Financial Year 2015/16
Grant Programme: Title Investigator Award in Science
Internal ID 200841/Z/16/Z
Lead Applicant Dr Francesco Colucci
Other Applicant(s) Prof Ashley Moffett
Planned Dates: End Date 2021-12-31T00:00:00+00:00
Planned Dates: Start Date 2017-01-01T00:00:00+00:00
Recipient Org: Country United Kingdom
Region East of England
additional_data_added True
id_and_name ["University of Cambridge", "360G-Wellcome-ORG:University-of-Cambridge"]
Additional data added by GrantNav