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SUMMARY:Advancing clinical utility of genomic discoveries with EHR and mol
 ecular biomarkers
DTSTART;TZID=Europe/London:20261109T100000
DTEND;TZID=Europe/London:20261109T110000
DTSTAMP:20260813T194323Z
UID:847d8641-3d8b-f111-8077-7c1e521e2257
CREATED:20260729T110433Z
DESCRIPTION:For the BDI Seminar\, we will be hearing from Dr Xilin Jiang\,
  Wellcome Early-Career Fellow\, Cardiovascular Epidemiology Unit\, Univers
 ity of Cambridge. We’re delighted to host Xilin in what promises to be a
  great talk!\n\nDate: Monday 9 November\nTime: 9:00 am – 10:00 am\nTalk 
 title: Advancing clinical utility of genomic discoveries with EHR and mole
 cular biomarkers\nLocation: Big Data Institute\, Seminar Room 0\n\nAbstrac
 t\nGenome-wide association studies (GWAS) have uncovered thousands of gene
 tic risk loci\, which illuminated biological pathways and even suggested n
 ew drug targets (Minikel et al. 2024 Nature). However\, the clinical utili
 ty of GWAS findings remains limited due to three key challenges: (1) Genet
 ics alone typically explains only a small proportion of disease variance\,
  with approximately 20% of disease risk attributed to genetic variation fo
 r most common diseases\, leaving the majority of risk unexplained and limi
 ting predictive power. (2) Most risk models target disease onset\, which i
 s important for prevention but often not directly actionable for patients 
 already living with the disease. Clinicians also need to predict outcomes 
 like treatment response or disease progression\, which genetic risk scores
  for onset may not inform. (3) Implementing genomic models in real-world c
 linical settings is non-trivial: the data (genotypes\, biomarkers\, electr
 onic health records) are fragmented and messy\, and healthcare providers l
 ack the computational tools to use complex risk models in practice. I will
  introduce our past and ongoing work aiming at bridging the gap between ge
 netic discovery and medical impact: (1) predicting treatment response and 
 disease progression using electronic health records\, (2) characterizing n
 on-genetic disease variance with molecular biomarkers\, and (3) translatio
 nal deployment of molecular risk models.\n\nShort biography\nXilin Jiang i
 s a Wellcome Early-Career Fellow at the University of Cambridge working on
  developing statistical tools to identify genetic and molecular explanatio
 ns for health outcomes. Currently\, his research focuses on two ends of th
 e data spectrum: (1) on the molecular side\, genotype\, functional annotat
 ion of genes\, and molecular measures (with a focus on data that can be ob
 tained from a tube of blood\, such as plasma proteomics)\; and (2) on the 
 health outcome side\, disease onset\, disease progression\, and treatment 
 response (with a focus on outcomes that inform clinical decision-making\, 
 such as how a patient responds to a drug). In statistical terms\, his rese
 arch involves Bayesian inference for high-dimensional data\, longitudinal 
 analysis\, and causal inference. \nXilin received their DPhil in Genomic M
 edicine and Statistics from the University of Oxford\, funded by a Rhodes 
 Scholarship and a Wellcome Trust studentship. He delivered the scholar add
 ress for the Rhodes Scholar class of 2017. Before Oxford\, he received a B
 Sc from Fudan University with an overall top GPA in Natural Sciences and i
 n Biological Sciences. \n————————————————
 ————————————————————————\n
 All members of the University are welcome to join\, please let reception a
 t BDI know you’re here for the seminar and sign-in. We hope you can join
  us!\n\nWe encourage in-person attendance where possible. There is time fo
 r discussion over\, tea\, coffee and pastries after the talks.\nHybrid Opt
 ion: Please note that these meetings are closed meetings and only open to 
 members of the University of Oxford to encourage sharing of new and unpubl
 ished data. Please respect our speakers and do not share the link with any
 one outside of the university.\n\nMicrosoft Teams meeting \nJoin: https://
 teams.microsoft.com/meet/373908702888358?p=vd8zSOiJfowhIS1xQP \nMeeting ID
 : 373 908 702 888 358 \nPasscode: Qi68xL2r\n——————————
 ————————————————————————
 —\n If you wish to know more or receive information related to trainings
  and events at BDI\, please subscribe by emailing bdi-announce-subscribe@m
 aillist.ox.ac.uk. You’ll then receive an email from SYMPA and once you r
 eply you’ll be on the list!
LAST-MODIFIED:20260810T132714Z
LOCATION:Big Data Institute - Lower Ground Seminar Room 0\, Lower Ground S
 eminar Room 0 Big Data Institute Old Road Campus Oxford Oxfordshire OX3 7L
 F United Kingdom
SPEAKER:Dr Xilin Jiang (xj262@medschl.cam.ac.uk)
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