Role of next generation sequencing in clinical care

Transcription

1 Role of next generation sequencing in clinical care Anne Slavotinek Division of Genetics, Department of Pediatrics, UCSF Structure 1. Next generation technologies 2. Consent and secondary findings 3. Genetics of diabetes/clinical examples 1

2 Sanger sequencing National Human Genome Research Institute's Talking Glossary Sanger sequencing 2

3 Exome sequencing Illumina - exons are variably covered - fill in can improve coverage Exon Coverage Sarah Garcia, Personalis 3

4 Whole exome sequencing (WES) What is an exome? -protein encoding regions of genes -1-2% of genome, but 85% mutations % of exome covered Uses of whole exome sequencing: -non-specific phenotypes e.g. intellectual disability -atypical presentations -rare, novel phenotypes -phenotypes difficult to confirm with clinical testing -diseases where testing is expensive -typically sent as a trio with both biological parents From: Korf and Rehm, New Approaches to Molecular Diagnosis Figure Legend: Date of download: 9/6/2014 Copyright 2014 American Medical Association. All rights reserved. 4

5 What to expect? Type of Mutation Novel Non-Novel Total Missense 303 (AA) /192 (C) 10,828/9,319 11,131/9,511 Nonsense 5/5 98/89 103/93 Synonymous 209/109 12,567/10,536 12,776/10,645 Splice 2/2 36/32 38/34 Total 520/307 23,529/19,976 24,049/20,283 AA = African American C = Caucasian 3 general types of results: - positive - negative - variant of uncertain significance (VUS) Bamshad et al., general categories of results: - primary findings - secondary findings Exome Sequencing Sequence variants need to be sorted to find relevant ones: 1) Deleteriousness of variant -frameshift, nonsense > missense -sequence conservation; protein domain -SIFT, PolyPhen-2, Mutation Taster, CADD 2) Existing biological/functional information -segregation with disease -variant not seen in unaffected individuals -expression pattern -predicted function; pathway/gene interactions -animal models Jessica van Ziffle 5

6 Diagnostic Yield/Discovery De Ligt et al,. NEJM, patients with ID - trio approach -total yield 16% Srivastava, Ann Neurol, patients with neurodevelopmental disabilities -total yield 41% -19 AD, 11 AR, 1 X-linked, 1 AD and AR -changed management in all situations -yield depends on testing indication Whole exome sequencing - exome is being considered earlier - exotyping - phenotyping, genotyping, reinterpretation of phenotypic data (Pinto et al., 2016) - digenic diseases and blended phenotypes Whole genome sequencing - analysis of deep intronic regions, non-coding RNA, regulatory regions Glissen et al., trios with severe ID; array and exome negative - WGS had yield of 42% (13 SNVs and 8 CNVs) - no mutations in regulatory regions 6

7 Panel Sequencing - panel targets <150, not 24,000 genes - all exons are sequenced - insertions/deletions detected; algorithm vs exon array - use a panel when clinical evaluation suggests a diagnosis - will not result in secondary/incidental findings - may still result in variants of unknown significance Exome Sequencing There are THREE outcomes from arrays/panel testing: - we may find the cause of the condition in you and your family - we may NOT find the cause of the condition in you and your family - we may get a result that we cannot interpret There are FIVE outcomes from WES testing: The previous three PLUS -we may find another change in the DNA of medical significance but not for the condition we tested you for -we may find family relationships to not be what you thought they were (misattributed parentage) Bob Nussbaum 7

8 Exome sequencing Advantages of WES: -syndromes with high genetic heterogeneity -syndromes that are incompletely characterized -Neveling et al., WES covers 81% of known pathogenic mutations on gene sets -improved diagnostic yield compensates for reduced sensitivity - even if all genes that could have been ordered by physicians had been tested, the larger number of genes captured by the exome would still have led to a clearly superior diagnostic yield at a fraction of the cost Elements of Consent Bick and Dimmock, basic genetics (genes, mutations) -inheritance patterns -penetrance and expressivity -types of DNA variants (pathogenic, benign, VUS) -incidental findings -false positives, false negatives -scientific discoveries that may result from test results -interaction of genes, environment -information privacy -non-paternity -Genetic Information Nondiscrimination Act of

9 Limits to informed consent - Can you really give informed consent when you look so widely [at the genome]? Is that manageable for patients?... (patient representative) - In any case I think that it's very naïve to think that a patient is more able to choose [which results to receive] when he knows more. There are limits to what patients can comprehend. Decision-making in principle does not get easier, the more elaborately a patient is informed.the quality is important and also a discussion... (ethicist) - greater detail can lead to less understanding - overwhelming; information overload - thousands variants identified; need biological parents for interpretation - only variants relevant to presentation reported - if parental samples included, only one report generated Elements of Consent Limitations -not every gene tested / not 100% coverage -not all kind of DNA variants -not all genetic changes in exome -current genetic knowledge not comprehensive Familial relationships/consanguinity Protection against genetic discrimination Secondary findings -different depending on labs -possible information on parents 9

10 Secondary Findings Green et al., Genet Med, 2013 Results not related to the indication for ordering the test, but that may, nonetheless, be of medical value or utility to the ordering physician or patient ACMG recommendations: -actively look for known pathogenic or expected pathogenic variants -59 genes, 24 conditions -prevention and/or treatment available -may be asymptomatic for a long time -excludes conditions screened by NBS -in proband AND for family members (if WES performed), irrespective of proband results -..failure to report a laboratory test result conveying the near certainty of an adverse yet potentially preventable medical outcome would be unethical. Interpretation of Secondary Findings Goal: Maximize positive predictive value LOW SENSITIVITY High false negative rate Data as generated by WES, not same standard as primary variant finding -recommendations to be reviewed periodically -system to submit new genes Amendola et al., 2015 European ancestry 112 genes medically actionable genes: 2.0% ACMG 56: 0.7% African ancestry 112 genes medically actionable genes: 1.1% ACMG 56: 0.5% 10

11 Secondary Findings - Considerations Burke et al., 2013: -screening results, not diagnostic test results -ascertainment bias, as mutations identified in those with disease -unknown natural history -phenotypic spectrum and penetrance not known -lack of controlled studies regarding interventions -prior probability of disease is low -costs should not be generated if patients do not wish for results Shahmirzadi et al., /200 (93.5%) chose to receive 1 categories of IF -manageable if consented well, understand implications -conditions/sequence variants need to be curated Importance of reinterpretation of negative results 11

12 Genetics of Familial Hyperinsulinism (FHI) - hypoglycemia (neonatal onset, mild to severe) (Glaser, 2013) Autosomal recessive ABCC8 (45%) /KCNJ11 (FHI-K ATP ) (5%) - associated with large for gestational age infants - severe refractory hypoglycemia with poor response to medical management - may require pancreatic resection Autosomal dominant ABCC8/KCNJ11 (FHI-K ATP ) - normal for gestational age - present around one year of age (2 d - 30 y) - responds to diet, diazoxide - other genes include GLUD1 (5%), HNF4A (5%), GCK, HADH, UCP2 (<1%) Genetics of Familial Hyperinsulinism (FHI) FHI - good situation for gene panel testing -diagnosis relatively straightforward -genetically heterogeneous -known genes explain much of genetic variation -panels vary in number of genes included and gene coverage -want to do both sequencing analysis and del/dup testing -Panel 1: ABCC8, AKT2, AKT3, GCK, GLUD1, HADH, HK1, HNF1A, HNF4A, INS, INSR, KCNJ11, PDX1, PGM1, SLC16A1, UCP2 -coverage: 96% at 20x -Panel 2: 50 genes; includes some metabolic conditions -panel includes non-coding variants; omits some exons 12

13 Genetics of MODY Anik et al., % of DM in Europe; 21 45/1,000,000 children and 100/1,000,000 adults -monogenic (AD) inheritance -early onset of DM (<25 y) -lack of autoimmune process/insulin resistance with lack of obesity -endogenous insulin secretion is preserved -80% are misdiagnosed as T1D, T2D ->10 known genes -GCK, HNF1A, HNF4A, and HNF1B genes commonest causes in UK -represent 32%, 52%, 10%, and 6% of MODY respectively -another good situation for gene panel testing Examples of available panels: Genetics of MODY Panel 1: GCK, HNF1A, HNF1B, HNF4A, PDX1 -lists sensitivity Panel 2: 13 gene panel that includes non-coding variants -ABCC8, BLK, GCK, HNF1A, HNF1B, HNF4A, INS, KCNJ11, KLF11, NEUROD1, PAX4, PDX1, RFX6 -lists non-coding variants Limitations: -complex inversions/balanced translocations -gene conversions -mitochondrial DNA variants/repeat expansion disorders -single exon deletions/duplications 13

14 Genetics of DM type I Type 1 DM: % due to inherited factors -HLA amongst first loci; >50 loci from GWAS -T1DGC aggregated studies for research -41 loci; some well known (HLA, INS, PTPN22, CTLA4, IL2RA) -27/41 were novel -verified loci have candidate genes; allelic heterogeneity Robertson and Rich, 2018 Genetics of DM type I - research predominantly in Europeans - prevalence increasing for other ethnic groups - genetic risk prediction - may help with treatment - slice/exome? Robertson and Rich,

15 Personalized Medicine Whole Exome Sequencing -testing with whole exome sequencing (WES) is effective -variant return has implications for other family members -variant interpretation is likely to change -secondary findings can be medically actionable -returning results in children for adult onset disorders -how should care be delivered? -genetics versus non-genetic professionals -ad hoc versus a dedicated clinic UCSF Personalized Genomics Clinic - provides an identity for genomic services - not a gateway - interpretive and research function - supportive role for clinical testing - consent process, results provision/interpretation - registry function for annual review - database for re-analysis 15

16 UCSF Personalized Genomics Clinic - started in 2013; was 2x per month with 2 physicians - now weekly with 4 physicians - >250 patients - providers: GeneDx, UCLA, Baylor, Ambry, Personalis, Fulgent - now to UCSF - referrals: numerous testing providers from different specialties Able to: - facilitate re-analysis, longitudinal data collection - aid to clinicians in variant interpretation - dedicated clinic enables consistent provider care - trainee education Trios increase yield: 12/143 (8%) proband only 11/143 (8%) duo 120/143 (84%) trio Lee et al., 2014: trio approach increases diagnostic yield -proband only 74/338 (22%) -trio 127/410 (31%) Age group tested can influence yield: 15/143 (10.5%) 1 yr of age 60/143 (42%) 1-5 y 32/143 (22.5%) 6-10 y 20/143 (14%) y 16/143 (11%) 18+ y Posey et al., 2015: diagnostic rate: 85/ % in adults -lower than for Pediatrics; 7% had blended phenotypes 16

17 Patient examples 1. WES can result in unexpected findings that improve care -11 yo male referred to Genetics -sensorineural hearing loss at 2 yo -loss is severe to profound -diagnosed with type I diabetes after presenting with several days of emesis and abdominal pain -cytopenias, including anemia, also noted at presentation -negative Otoscope gene panel (108 gene panel) -chromosomal microarray arr(1-22)x2, (X,Y)x1 -MRI of inner ear normal Patient examples -two pathogenic variants in SLC19A2 -maternally inherited variant: c.484c>t, p.arg162ter -classified as pathogenic -paternally inherited variant: c.515g>a, p.gly172asp -previously reported variant, classified as pathogenic -biallelic pathogenic variants in SLC19A2 are associated with Thiamine-responsive megaloblastic anemia syndrome 17

18 Patient examples 2. Results have implications for other family members: -9 yo male with autism -frameshift variant in TREX1; heterozygous; paternally inherited -father had h/o iritis and fevers -AR TREX1: Aicardi-Goutieres disease -AD TREX1: chillblains; SLE -51 yo male with retinal dystrophy -deleterious variant in PRRT2; heterozygous; unknown inheritance -paroxysmal kinesogenic dyskinesia -benign seizures in grandchild -importance of experienced counselors/genetic interpretation Summary -next-generation technologies are in common use -panel and exome are most frequent tests -differ in consent process, secondary findings -testing has implications for other family members -testing can yield complicated, unanticipated results 18

19 Thank you! UCSF Genomics Medicine Initiative - Pediatrics Co-directors: Neil Risch Pui-yan Kwok Clinicians: Anne Slavotinek Joseph Shieh Marta Sabbadini Wet lab: Jessica van Ziffle Heather Pua Bioinformaticians: Mark Kvale Ugur Hodoglogil Pathology/Fellow: Jude Abadie Ethics: Barbara Koenig Library/Scholarly Communication: Megan Laurance 19