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My Personal Odyssey with Big Data - Brad Popovich


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CityAge: The Data Effect Vancouver

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My Personal Odyssey with Big Data - Brad Popovich

  1. 1. My  Personal  Odyssey  with  Big  Data   Brad  Popovich   Chief  Scien2fic  Officer   December  5,    2013  
  2. 2. The  early  days  of  exploring  my  personal  genome   •  1976:  My  first  whole  genome  analysis  (46  XY)   •  1980-­‐2000:  I  looked  at  almost  every  gene  I  could   in  my  personal  genome  for  CFTR,  FMR1,  DMD,   DM,  HD,  SCA,  SMA,  MELAS,  MERRF,  etc.   •  LiUle  concern  personally   •  ExcepWon:  APOE       2
  3. 3. 3 3  
  4. 4. My  early  concern:  Demen<a     •  PosiWve  family  history:     •  Increase  life  Wme  risk  (20-­‐25%  vs.  10%)   •  APOE   •  e4/e4:  further  increase  in  risk   •  Good  news:   •  APP  (2012)  protecWve  mutaWon  (A673T)     4
  5. 5. 2013-­‐2014:  My  personal  Whole  Genome   Sequence  (WGS)     Logical  next  step   •  It’s  my  personal  “blue  print”   •  Provides  potenWal  for  informed  decision  making     •  It’s  accessible   •  Learn  the  difference  between  talking  about   genomics  vs.  being  a  consumer   5
  6. 6. Consumer  driven  genomics     WGS      2007:  First  offered  by  Knome  ($350k)    2009:  Illumina  ($45k)    2013:  TesWng  now  offered  by  several  labs/ companies  for  approximately  $5k   Genotyping  tesWng  available  from  several  labs/ companies  (e.g.  23andMe  @  $99)   •  FDA  (November  2013)   •  Class  acWon  suit  (December  2013)   6
  7. 7. Obtaining  my  personal  WGS     Presently  several  opWons  for  WGS   Illumina:  Understand  Your  Genome  (UYG)   •  Physician  referral  required   •  Reason  for  my  referral:  General  medical  knowledge  -­‐   not  for  any  specific  medical  quesWon   •  DNA  sequence  generated  in  CAP/CLIA  accredited  lab   •  UYG  Course  in  March  2014   •  Sokware  tool  provided:  MyGenome  App   •  App  allows  future  genomic  interrogaWon   7  
  8. 8. FDA  Approval:  November  19,  2013     •  For  the  first  Wme,  the  U.S.  Food  and  Drug  AdministraWon  has  cleared  a  next-­‐ generaWon  sequencer  for  use  in  clinical  laboratories,  advancing  the  use  of  genomic   medicine  in  rouWne  medical  care.     •  Francis  Collins  (NEJM):  "The  markeWng  authorizaWon  for  the  first  next-­‐generaWon   genome  sequencer  represents  a  significant  step  forward  in  the  ability  to  generate   genomic  informaWon  that  will  ulWmately  improve  paWent  care.  The  availability  of   high-­‐throughput  DNA  sequencers  will  enable  physicians  to  take  a  comprehensive   look  at  a  paWent's  geneWc  blueprint,  or  genome,  to  search  for  a  wide  range  of   variaWons  or  changes  that  increase  risk  of  disease,  drive  the  disease  process,  and/or   affect  response  to  medicaWons  and  other  treatments.  Such  informaWon  has  the   potenWal  to  benefit  paWents  in  many  ways.  This  acWon  reflects  our  naWon's   commitment  to  a  future  in  which  health-­‐care  professionals  will  be  able  to  use  each   person's  unique  genome”   •  FDA  also  approved  the  first  test  system  based  on  two  devices  -­‐  the  Illumina   MiSeqDx  instrument  and  the  reagents  in  the  Illumina  Universal  Kit  -­‐  to  allow   laboratories  to  develop  and  validate  sequencing  of  any  part  of  the  paWent's   8 genome.  
  9. 9. Whole  Genome  Sequence  (WGS)     Few  technical  barriers   •  •  ApplicaWons   •  Primarily  a  research  tool   •  Clinically:  cancer,  infecWous  diseases,  and   difficult  to  diagnosis  diseases   •  Difference  between  WGS,  exome  and  targeted   gene  panel  approaches   •  Size  of  corresponding  data  sets  for  human   •  WGS  3x109  bp    (file  size  Gb  –  Mb)   •  Exome  =  3x107  bp    (approx  1%  of  WGS)   •  BoUleneck…interpreWng  the  data   9
  10. 10. Interpre<ng  Whole  Genome  Sequence     Necessary  to  know   • What’s  normal  vs.  a  variant  across  the  enWre  genome   • Phenotypic  consequences  of  normal  vs.  variant  genotype   Current  barriers   • Size  of  human  cohorts  available  for  comparison   •  Lack  of  staWsWcal  power  to  validate  research  findings   • Quality  of  phenotypic  data   •  Lack  of  adequate  EMR,  data  standards,  QA,  and  QC   Ideal  clinical  applicaWons   • Allow  normal  vs.  abnormal  comparison  in  the  same   10 paWent  (e.g.  cancer)  
  11. 11. What  do  I  expect  to  learn  from  my  WGS?   •  What  being  a  consumer  of  genomic  informaWon  feels  like   •  Some  detected  variants  will  cause  concern   •  Will  the  HC  system  accommodate  medically  acWonable   follow-­‐up?   •  Most  variants  will  lack  the  necessary  data  to  have  clinical   uWlity   •  How  can  we  move  from  variants  of  unknown   significance  to  significant?   •  What’s  the  impact  of  waiWng?   11 •  Can  apps  ease  the  burden  on  the  system?  
  12. 12. What  do  I  expect  to  learn  from  my  WGS?   (Con<nued)   •  Family  maUers   •  Modified  risk  for  demenWa   •  CommunicaWons  with  family  members   •  Impacts  on  my  insurability   •  Life   •  Disability   •  What  professional  support  will  be  required?     12
  13. 13. Genome  BC  and  WGS   •  Many  of  the  projects  funded  by  Genome  BC  are   already  performing  WGS  on  research  subjects   •  I  anWcipate  that  in  the  near  future  most  projects   on  humans  will  be  using  WGS  or  WES   •  ObservaWon:  ASHG  and  AMP  2013   13
  14. 14. Genome  Bri<sh  Columbia  and  WGS   What  is  the  role  of  Genome  BC  in  making  WGS  clinically   useful  and  cost  effecWve?   •  Stop  geneWc  /  genomic  excepWonalism   •  Coordinate  the  large-­‐scale  collecWon  of  genomic  data  in   a  manner  that  addresses  privacy  and  confidenWality   •  Develop  strong  baseline  protecWons  for  parWcipants  in   clinical  and/or  research  applicaWons  of  WGS   •  Promote  data  access  and  sharing   •  Develop  standards  for  the  integraWon  of  genomic   informaWon  into  health  records   •  Facilitate  access  to  genomic  informaWon  so  all  BriWsh   14 Columbians  benefit  
  15. 15. What’s  missing?   A  plan!   •  R&D   •  ComputaWonal  infrastructure   •  Privacy  policy/law   •  Access  policy   •  Pla{orms   •  Data  repository   •  Clinical  implementaWon   •  Medical  evidence  and  health  economic  data     •  Linkage  of  genomic  data  into  HC  records   •  Improved  receptor  capacity   •  Physicians,  geneWc  counselors,  apps,  etc.   15
  16. 16. Applica<ons   Human   •  Cancer   •  InfecWous  diseases   •  Difficult  to  diagnose   diseases   •  Pharmacogenomics   •  Forensics   •  Public  health   •  Newborn  screening   Non-­‐human   •  Forestry   •  Fisheries   •  Environmental  monitoring   •  Agri-­‐Food  Industry   •  Mining   16
  17. 17. Conclusions   •  I  am  about  to  conclude  an  important  chapter  in  my   genomic  odyssey   •  I  plan  to  use  my  experience  to  inform  the  work  that   Genome  BC  is  doing  to  make  this  technology   accessible,  useful,  and  economically  viable  to  the   ciWzens  of  BC,  Canada,  and  beyond   •  We  need  to  end  geneWc  excepWonalism   •  We  need  leadership  and  a  plan!   17