Interpretation can t happen in isolation. Jonathan S. Berg, MD/PhD Assistant Professor Department of Genetics UNC Chapel Hill

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1 Interpretation can t happen in isolation Jonathan S. Berg, MD/PhD Assistant Professor Department of Genetics UNC Chapel Hill

2 With the advent of genome-scale sequencing, variant interpretation is increasingly important Millions of variants in an average genome ~20,000 coding variants per person Most genomic variants are clinically insignificant Molecular analysis seeks to identify the small handful of clinically important variants Searching for the needle in a haystack Panning for gold Signal above the background noise

3 Individual The primary goal in a clinical setting is to establish a diagnosis - To explain symptoms - To provide anticipatory guidance - To establish appropriate treatment/management - To understand family recurrence risk Attributes of the phenotype specific to the individual Genetic Disorder Diagnosis

4 Individual Attributes of the phenotype specific to the individual Clinical diagnosis requires comparison of the phenotypic attributes specific to the individual to the composite phenotypic spectrum of a genetic disorder in a population - Family history - Specific phenotypic features - Imaging/laboratory data Genetic Disorder Diagnosis Population Attributes of the disorder among affected individuals

5 Attributes of the variant specific to the individual Individual Variant In molecular analysis there are several attributes about a genetic variant that are specific to an individual - Zygosity - Presence of other variants in cis or trans (or unknown phase) - Segregation in family vs. de novo These can be clues as to the pathogenicity of a variant but are not always sufficient!

6 Variant Some attributes of a variant can be defined independent of the case-level data - Impact on gene/transcript - Allele frequency in different populations - Presence within a haplotype Some attributes can stand alone in predicting pathogenicity, but others require additional evidence Attributes of the variant relative to the population Population

7 Attributes of the variant specific to the individual Individual Attributes of the phenotype specific to the individual Diagnosis Variant The central task is to make an assertion about the pathogenicity of the variant with respect to a specific genetic disorder Genetic Disorder Attributes of the variant relative to the population Population Attributes of the disorder among affected individuals

8 Attributes of the variant specific to the individual Variant Attributes of the variant relative to the population Genomic feature Individual Attributes of the disorder relative to pathogenesis Mode Molecular mechanism Attributes of the variant relative to functional impact Integration of individual and population data with the molecular mechanism Population Attributes of the phenotype specific to the individual Genetic Disorder Attributes of the disorder among affected individuals Diagnosis

9 Some variants are easy to figure out? rs334 NC_ :g T>A NM_ :c.20A>T NP_ :p.Glu7Val Hemoglobin beta, sickle variant

10 Most variants are more complicated Previously reported in the literature but with insufficient evidence to support pathogenicity Or more recent evidence that argues against a pathogenic role in a rare disease Novel and rare Truncating Missense Synonymous Potentially influencing splicing

11 Case-level data is vital Testing indication or scenario Diagnostic, screening, incidental finding Affected/unaffected status With what? Genetic disorder Specific phenotypic manifestation (present/absent/unknown)

12 Example: 2 year-old male NC_ :g A>C Located within KMT2D NM_ :c.15351T>G NP_ :p.Cys5117Trp Is it pathogenic?

13 Example: 2 year-old male Posterior cleft palate; status post repair Failure to thrive, hypoglycemia GI malrotation; Ladds procedure & G- tube PDA & PFO at birth, resolved Hypotonia, microcephaly, developmental delay Left undescended testicle Nystagmus Single umbilical artery Large ears, mild ptosis, arched eyebrows; suggestion of recognizable syndrome

14 Heterozygous Parental studies pending Individual Developmental delay Congenital anomalies - Cleft, PDA/PFO, malrotation, cryptorchidism Dysmorphic features - Large ears, ptosis, arched eyebrows NC_ : g a>c AD Unknown syndrome

15 Heterozygous Parental studies pending NC_ : g a>c Novel, not reported in population databases Majority of missense mutations in Kabuki syndrome occur in same exon AD KMT2D C5117W Individual Alters highly conserved cysteine within a PHD-like zincbinding domain Population Developmental delay Congenital anomalies - Cleft, PDA/PFO, malrotation, cryptorchidism Dysmorphic features - Large ears, ptosis, arched eyebrows Pathogenic? Kabuki syndrome OMIM # Growth retardation - Microcephaly - Large ears, ptosis, arched eyebrows - Cleft palate - ASD - Malrotation - Cryptorchidism - Developmental delay

16 Heterozygous Parental studies pending NC_ : g a>c Novel, not reported in population databases Majority of missense mutations in Kabuki syndrome occur in same exon AD KMT2D C5117W Individual Alters highly conserved cysteine within a PHD-like zincbinding domain Population Developmental delay Congenital anomalies - Cleft, PDA/PFO, malrotation, cryptorchidism Dysmorphic features - Large ears, ptosis, arched eyebrows Likely pathogenic Kabuki syndrome OMIM # Growth retardation - Microcephaly - Large ears, ptosis, arched eyebrows - Cleft palate - ASD - Malrotation - Cryptorchidism - Developmental delay

17 The importance of collaboration Traditional genetic testing has leveraged deep expertise of domain experts Accumulated knowledge about gene-specific variation Proprietary databases Genome-scale sequencing requires broad expertise across many genes Collective efforts of laboratories and clinicians

18 Challenges Uneven curation of existing databases Scientific literature biased toward positive results, often without sufficient evidence Inefficient capture and sharing of phenotype information between clinicians and labs Silos of expertise, proprietary databases

19 ClinGen seeks to alleviate isolation Case-level Data ClinVar Variant-level Data Data Expert Curated Variants Gene Resource ClinGenDB Curation Tool Machine Learning Algorithms Disease WGs Clinical Domain WGs by facilitating expert curation and sharing with the community

20 Acknowledgements ClinGen team U01 HG (Berg, Evans, Ledbetter, Watson) U01 HG (Bustamante, Plon) U41 HG (Rehm, Ledbetter, Martin, Mitchell, Nussbaum) NCBI ClinVar, MedGen, dbgap teams