BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Assessing socioeconomic biases and parental affected status in rar
 e disease families - Dr Sana Amanat Ali 
DTSTART:20250213T100000Z
DTEND:20250213T110000Z
UID:TALK227806@talks.cam.ac.uk
CONTACT:Spencer Keene
DESCRIPTION:Abstract: Many probands recruited to the Rare Disease Arm of t
 he 100\,000 Genomes Project (100kGP) and the Deciphering Developmental Dis
 orders (DDD) project (www.ddduk.org) remain undiagnosed with diagnostic ra
 tes of ~20% and ~40% respectively. The linked health record data in the Ge
 nomics England 100\,000 Genomes project (GEL) provides opportunities to un
 derstand the factors influencing diagnostic yield. We assessed the relatio
 nship between socioeconomic deprivation and diagnostic status in DDD-like 
 families (identified through similar recruitment criteria to the DDD study
 ) in the 100kGP. We found that diagnostic yield is ~ 20% across all depriv
 ation quintiles involving denovo and inherited pathogenic variants. Curren
 t clinical pipelines stratify variants by inheritance status\, depending o
 n whether a parent is “affected” or not. If parents are incorrectly la
 belled as “unaffected”\, potentially pathogenic inherited variants are
  likely to be erroneously discarded. We suspected that the clinical annota
 tions might be missing many truly affected parents. Therefore\, we sought 
 to develop a classification model of parental affected status of ‘DDD-li
 ke’ families\, combining multiple attributes of the linked health record
  data. This model has good performance in identifying affected parents wit
 h an AUC on held-out control data of 0.81. The current model predicts that
  ~27% of parents labelled as “unaffected” may have a clinical phenotyp
 e relevant to their child’s condition. Next\, we aim to integrate the ge
 netic data to see whether transmission rate of damaging variants differs b
 etween parents who are predicted to be affected and unaffected. \n\nBiogra
 phy: Dr. Sana Amanat is a HDR-UK Postdoctoral Fellow at Wellcome Sanger In
 stitute\, Hinxton\, working within the Prof. Hurles group. Her research fo
 cuses on the linking health record data in rare disease families recruited
  to the 100\,000 genomes project to assess parental affected status and po
 tential socioeconomic biases. She obtained her PhD from the University of 
 Granada\, Spain. During her Phd\, she analysed exome sequencing of patient
 s with Meniere’s disease and extreme tinnitus phenotype. \n
LOCATION:Heart and Lung Research Institute (R.101 and 102) or Virtually vi
 a Zoom: https://sanger.zoom.us/j/96837334177?pwd=nf2mHEZTOJ74akQjszz8NqkZb
 TK5Yx.1
END:VEVENT
END:VCALENDAR