improving the interpretation of rare variants through ... · sian ellard, thalia antoniadi and emma...
TRANSCRIPT
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Sian Ellard, Thalia Antoniadi and Emma Baple
Improving the interpretation of rare variants through inter-disciplinary working
▪ Guidelines▪ Training▪ Clinical practice
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Sian Ellard, Thalia Antoniadi and Emma Baple
Improving the interpretation of rare variants through inter-disciplinary working
▪ Guidelines▪ Training▪ Clinical practice
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Steve Abbs, NEQAS
Inconsistent variant classification
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Next generation sequencing identifies more novel/rare variants
Single gene Small panel Large panel Exome Genome≤1 A few Many >200 >500,000
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5
4
3
2
1
Pathogenic
Likely pathogenic (>90%)
Uncertain significance
Likely benign (>90%)
Benign
2015: New guidelines from the USA
“This result does not confirm a diagnosis of disorder X and should not be used for clinical decision making”
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5
4
3
2
1
Pathogenic
Likely pathogenic (>90%)
Uncertain significance
Likely benign (>90%)
Benign
2015: New guidelines from the USA
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Summary of evidence framework
Richards et al 2015 Genetics in Medicine; Jarvik and Browning 2016 Am J Hum Genet
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Rules for combining evidence criteria
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Assess the evidence for a variant across all patients for which information is available
Publications
Public/NHS databases
Laboratory database
Patient referredfor testing
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Putting the ACMG guidelines into practice
Principles
▪ Use the guidelines as a framework to determine whether there is sufficient evidence to classify the variant as likely pathogenic or likely benign
▪ Use each data item only once (like Bayes’ theorem)
▪ Incorporate clinical data (functional and gene specific phenotype)
▪ Use your professional judgement
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Patient Name: X
Gene: RYR1
Variant description: HGVS NM_000540.2: c.7306T>C (p.Cys2436Arg)
Variant location: GRCh37 (hg19): 19:38,990,639
Variant classification:
(Pathogenic/Likely pathogenic/ Uncertain
significance/Likely benign/Benign)
Likely Pathogenic
Evidence for variant classification (ACMG code – level)
▪ Cysteine is present at position 2436 of RYR1 in 150 orthologues, paralogues and other
homologous sequences. This residue is known to be important for redox-sensing. In silico
protein modelling suggests that a p.Cys2436Arg substitution would cause perturbation to the
secondary structure within that region and also to that of the neighbouring RYDR_ITPR
domain sequences. This variant maps to a known mutation hotspot for malignant
hyperthermia (PM1 - supporting).
▪ This variant has not been reported in the ExAC database (PM2 – moderate).
▪ The p.Cys2436Arg variant has been inherited in trans with a p. Glu3035Gln variant (PM3 –
moderate).
▪ The p.Cys2436 residue is conserved across 14 species from human to lamprey (Consurf score
9) and is predicted likely to be deleterious using SIFT, PolyPhen and AlignGVGD (PP3 –
supporting).
Appendix 1 - Evidence for variant classification using ACMG guidelines (Richards et al 2015 PMID 25741868)
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Variant classification and interpretation workshop: November 4th 2016
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Improving the quality of variant interpretation for clinical diagnosis
Train the trainers: February 28th 2017
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Monthly WebEx for regional trainers
Cases
▪ Two cases per month circulated
▪ Submit classifications before meeting
▪ Review cases at meeting
▪ Present previous worked case examples
▪ Share ideas for local implementation
▪ Forum for questions/discussion
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Draft UK guidelines for variant classification
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Additional guidance for de novo variants
PS2 – (Strong) De novo (both maternity and paternity confirmed) in a patient with the
disease and no family history.
Note that the genotype must be consistent with the phenotype.
If a de novo variant was identified by trio exome or genome sequencing then maternity and
paternity have already both been confirmed . If a de novo variant is identified by trio exome
or genome sequencing and the patient’s phenotype is non-specific (eg intellectual disability),
this criterion would be used at a lower level.
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Mutation hotspot and/or functional domain
PM1 – (Moderate) Located in a mutational hot spot and/or critical and well-established
functional domain (eg active site of an enzyme) without benign variation.
Plot functional domains, ExAC/gnomAD variants, HGMDPro/ClinVar/LOVD etc variants and
Consurf/conservation plots to show reported pathogenic variants, proxy population and
benign variants and amino acid conservation for a region of a gene.
PM1 Plot for SOX10 variant
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Setting a threshold for constraint scores
PP2 – (Supporting) Missense variant in a gene that has a low rate of benign missense variation and in which missense variants are a common mechanism of disease.
ExAC constraint scores can be used as evidence for a low rate of benign variation (Lek et al 2016 Nature 536:285-291). Z scores ≥3 (marked amber in ExAC) are significant but it is important to consider constraint for the region encompassing the variant, not just across the entire gene (see Samocha et al 2017 bioRxiv).
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Specificity of the phenotype
PP4 – (Supporting) Patient’s phenotype or family history is highly specific for a disease
with a single genetic aetiology.
This incorporates the prior probability that a patient will have a pathogenic variant in a
particular gene or genes. It does not have to be limited to diseases where there is a single
genetic aetiology.
▪ Test strategy – single gene, panel or trio exome/genome?
▪ Genetic heterogeneity of the disorder
▪ Specificity of the phenotype
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Is the variant allele frequency too high?
Classifying benign variants
BS1 – (Strong) Allele frequency is greater than expected for disorder.
A very useful tool is available to determine whether the allele frequency of the variant is greater than expected for the disorder (Whiffin et al 2016 bioRxiv). In the absence of precise information about the disease prevalence and penetrance we recommend using conservative settings (by selecting the highest likely prevalence and the lowest likely penetrance) to see if the variant frequency on the ExAC database exceeds the maximum credible allele frequency. The tool can be accessed at http://cardiodb.org/allelefrequencyapp/.
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NOTCH2 p.Arg1895His variant in patient with ?Alagille syndrome
http://cardiodb.org/allelefrequencyapp/
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Improving the interpretation of rare variants through inter-disciplinary working
▪ Guidelines▪ Training: local implementation▪ Clinical practice
Sian Ellard, Thalia Antoniadi and Emma Baple
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The Plan.
• CPD sessions
• ‘Pair’ scientists and clinicians
• Provide the training material and circulate the training cases for classification
• Collect the classification
• Organise a feedback session
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Logistics…
• Identify the staff involved in variant interpretation: 80!!!
• Attempt pairing people according to their interests
• 1-2 clinical and 1-2 scientific staff per team: 34 teams!
Clinical Genetics: 44 Laboratory: 36
Consultants: 16 Senior scientists: 13
Counsellors: 23 Scientists: 23
Registrars: 5 STPs: 14
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Organised the training in ‘rounds’
• Round 1: 29 teams were sent the cases for classification and were given little time to submit
• Feedback session – 24 April 2017
• Round 2: remaining teams and others that didn’t make it to the first round were given ample time to meet and complete the cases
• Feedback session – 15 June 2017
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• Presentation of the additional notes• Classification of the training cases and discussion
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Variant classifications during workshop
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pre- training classifications
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Moving forwards
• Organising the WebEx participation
- a different team working up of the cases each time
- attending the WebEx
- feeding back in a CPD session – 5 July 2017
- one CPD session every 6-8 weeks
• Round 3: to take place in Autumn
• Working on updating the reporting templates (>600..)
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What did the Guidelines ever do for us?
• Support the way towards consistency
• Provide the framework for dialogue
• Bringing the scientific and clinical expertise together to help with these variants that are sitting on the fence:
Can this variant explain this patient’s symptoms?
• Improve these communication networks between the scientists and the clinicians
• Essential infrastructure in view of 100,000 genomes and the wider application of WES and WGS
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acknowledgments
• Helen Cox, Consultant Clinical Geneticist
• ACGS and Health Education England
• All the staff in WMRGL and CGU for their engagement and lively debate in the feedback sessions!
...we should be doing this with our non-genetics clinical colleagues, too
...shed light on some doubts and helped me see and interpret things differently
...appreciated the difficulties in interpretation from each other’s perspective
...I haven’t realised how variant classification was so prone to subjectivity
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Sian Ellard, Thalia Antoniadi and Emma Baple
Improving the interpretation of rare variants through inter-disciplinary working
▪ Guidelines▪ Training▪ Clinical practice
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Genome 4-5M
Exome 40,000
Panel 0->10
Disease-causing variant (or variant pair)
A cautionary tale…
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• Move from:
“Guilty until proven Innocent”
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• To:
“Innocent until proven Guilty”
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NHS: A unique opportunity for MDT working
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What is a Genomics MDT?Means different things to different people and in different places
▪ Who should attend?
▪ What format should the meeting take?
▪ What are the aims of the meeting and what questions need to be answered?
▪ Which cases should be discussed?
▪ Which stage(s) in the testing pathway should involve an MDT discussion?
▪ How and where should the discussion and outcomes be documented?
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Selection of cases for testing
Phenotypedata
Primary Reviewby Clinical Scientists
EyeMDT
CardiacMDT
DDMDT
100kMDT
Sequencing
TumourMDT
Metabolic
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What a Genomics MDT is not…..
▪ A competition
▪ An opportunity to show off
▪ A time trial
▪ An excuse to prevaricate
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Clinical diagnostic exome service
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Request form
▪ Contact details
▪ Clinical details
▪ Choice of strategy▪ Trio analysis▪ Couple analysis for lethal
disorders▪ Bespoke virtual panel etc..
▪ “Pre-analysis” MDT▪ Strategy▪ Virtual panel selection▪ Pipeline selection eg.
mosaicism, multiple disorders in the family, penetrance
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Excel spreadsheet of filtered variants generated by a bioinformatician for review
by the clinical scientist
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International cooperation
Fetus 2TOP 18/40
Rapidly progressing ventriculomegaly
No genetic diagnosis
2Fetus 1
TOP 22/40Rapidly progressing ventriculomegaly
No DNA
▪ Indian couple
▪ Same region, no known consanguinity
▪ Wanting to pursue prenatal diagnosis
▪ Limited DNA
▪ Parent only strategy
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Fetus 2TOP 18/40
Rapidly progressing ventriculomegalyNo genetic diagnosis
2
POMGNT1 p.Arg497Gln/NPOMGNT1 p.Arg497Gln/N
POMGNT1 p.Arg497Gln/p.Arg497GlnNot homozygous
Fetus 1TOP 22/40
Rapidly progressing ventriculomegalyNo DNA
International cooperation
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International cooperation
ACMG category
(Richards et al 2015 PMID 25741868 )
Evidence
PM1 Located in a mutational hot spot and/or
critical and well-established functional
domain without benign variation
p.Arg497 is located within the N-lobe
of the catalytic domain. Exon 17 of
POMGNT1 represents a mutation hot
spot (HGMD Pro).
PM2 Absent from controls (or at extremely low
frequency if recessive) in population
database(s)
1/121,334 alleles (European non-
Finnish).
PP1 Co-segregation with disease in multiple affected
family members
Variant identified in parents. Co-
segregates in one affected fetus and two
unaffected siblings (1/4 x ¾ x ¾ = 1/7)
but needs to be ≤1/8 for PP1 if only one
family.
PP3 Multiple lines of computational evidence
support a deleterious effect on the gene or
gene product
p.Arg497 is conserved across 23
species; Consurf score 9. SIFT and
Polyphen predict pathogenic, Align
GVGD class C35.
Additional evidence
ClinVar: Homozygous p.Arg497Gln variant identified in a patient with progressive muscle
weakness, cerebro-ocular dysgenesis, and septo-optic dysplasia (e-mail from Emory lab).
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Criteria (*ACMG code) Level Evidence
Located in a mutational hot spot and/or critical
and well-established functional domain without
benign variation (PM1)
Moderate p.Arg497 is located within the N-lobe
of the catalytic domain. Exon 17 of
POMGNT1 represents a mutation hot
spot (HGMD Pro) with no
homozygous missense variants
reported in the ExAC database.
Absent from controls (or at extremely low
frequency if recessive) in population database(s)
(PM2)
Moderate One heterozygote (European non-
Finnish) in the ExAC database (60,667
individuals).
Co-segregation with disease in multiple affected
family members (PP1)
Supporting The p.Arg497Gln variant was
identified by exome sequence
analysis of the parents. Co-
segregation was demonstrated in one
affected fetus and two unaffected
siblings (1/4 x ¾ x ¾ = 1/7).
The Emory lab (USA)
identified this
homozygous variant in a
patient with Muscle-Eye-
Brain disease who
presented prenatally
with ventriculomegaly.
N ≤ 1 /4 if >1 FamilyMultiple lines of computational evidence
support a deleterious effect on the gene or gene
product (PP3)
Supporting p.Arg497 is conserved across 23
species; Consurf score 9. SIFT and
Polyphen predict pathogenic, Align
GVGD class C35.
International cooperation
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• Non-consanguineous Caucasian parents
• One healthy older sibling
• Tonic clonic seizures from 6 months of age, controlled with antiepileptic medication
• CT and MRI normal
• Regression of skills at onset of seizures and ongoing poor developmental progress
• Walked independently at 6yrs, no meaningful vocalisations at 10yrs
• Normal growth parameters
Clinician and Clinical scientist cooperation
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• Whole exome trio - DDG2P virtual gene panel analysis through the DDD project
• Patient is heterozygous for KMT2D variant in exon 48, NM_003482 c.15485T>G (p.Val5162Gly), confirmed de novo by Sanger sequencing
Testing undertaken and variant(s) found
Heterozygous pathogenic variants in KMT2D are associated with Kabuki
syndrome:
• Characteristic facial appearance• Minor skeletal anomalies• Persistence of fetal fingertip pads• Mild/moderate intellectual disability
and postnatal growth deficiency
PS2 – Maternity and paternity confirmed by exome, BUT the patient is not a good phenotypic fit for the disorder!
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Conservation and variation in KMT2DAs previous slide, but showing data for residues encoded by exon 48 only (4882-5262); 11/21 previously reported DM mutations map within annotated functional domains or motifs
HGMD
ExA
C f
req
uen
cy
Co
nSu
rf g
rad
e
ZnF (PHD type)
5091 5137
FYRN
5175 5235
FYRC
PM1 – (Supporting) Exon 48 is a mutation hotspot, BUT there is benign variation within the same region of exon 48 as Val1562
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Classification and summary of evidence
PP3 (Multiple lines of computational evidence support a deleterious effect on the gene or gene product conservation, evolutionary, splicing impact, etc.)
PM2 (Absent from controls) - Novel, not present in gnomAD
PP2 (Missense variant in a gene that has a low rate of benign missense variation and in which missense variants are a common mechanism of disease) – ExAC constraint score >3.0 and more constraint notable in exon 48
PM1 (Supporting) - Exon 48 is a mutation hotspot, BUT there is benign variation within the same region of exon 48 as Val1562
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New DDD result!
KCHN1 c.1070G>A p.(Arg357Gln)
Temple-Baraitser syndrome and epilepsy
J Hum Genet. 2016 May;61(5):381-7. doi: 10.1038/jhg.2016.1. Epub 2016 Jan 28.De novo KCNH1 mutations in four patients with syndromic developmental delay, hypotonia and seizures
De novo KCHN1 p.(Arg357Gln) is reported as disease causing
Clinical summary
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Clinical opinionCardiff
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From OMIM:
So I asked Dr Sally Davies:Q1: What might this girl have?
•Quite hairy - Possibly Wiedemann-Steiner (KMT2A)•Large central incisors – Possibly KBG syndrome (ANKRD11) – quite a common findingin DDD project.
Q2: What about Kabuki syndrome?
No way!
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▪ Born 2001▪ Polyglucosan disease, liver cirrhosis,
myopathy and mild dilated cardiomyopathy.
▪ Requested urgently as deteriorating clinically.
▪ GBE1 test and GSD panel negative
MDT: An opportunity for education
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RBCK1 Small deletionp.Asn508fs (c.1522_1526del)/N
RBCK1 Nonsense variantp.Gln267Ter (c.799C>T)/N
RBCK1 Small deletion and nonsense variantp.Asn508fs (c.1522_1526del)/ p.Gln267Ter (c.799C>T)
▪ Polyglucosan body myopathy 1 (with or without immunodeficiency) is caused by biallelic mutations in the RBCK1 gene. Only 9 mutations described in the literature but these include nonsense, missense, small deletions and insertions
MDT: An opportunity for education
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What is a Genomics MDT?▪ Who should attend? Depends on the case and the question(s)
▪ Clinical scientist, referring clinician, clinical geneticist, bioinformatician,
Genetic Counsellor, (other) experts.
▪ What format should the meeting take? Face to face versus virtual
▪ What are the aims of the meeting and what questions need to be answered? Preparation is key
▪ Which cases should be discussed? Not every result requires an MDT, focus is mainly on variant reporting, discussion of cases when no diagnosis has been made
▪ Which stage(s) in the testing pathway should involve an MDT discussion? Depends on the case and clinical question(s)
▪ How and where should the discussion and outcomes be documented? Genetics notes, hospital notes, electronic notes, appendix of the report
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