Epi4K. Epi4K Consortium. Epi4K: gene discovery in 4,000 genomes, Epilepsia, 2012 Aug;53(8):

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1 Epi4K Epi4K Consortium. Epi4K: gene discovery in 4,000 genomes, Epilepsia, 2012 Aug;53(8):

2 Genetics of Epileptic Encephalopathies Infantile Spasms (IS) 1 in 3000 live births and onset between 4-12 months of life Characteristic chaotic interictal & EEG pattern of hypsarrhythmia, the sine qua non of the syndrome 50-60% of IS cases have developmental brain malformations, tuberous sclerosis complex, chromosomal syndromes and metabolic conditions Patients may evolve into LGS Lennox-Gastaut syndrome (LGS) Onset between 1-8 years Characterized by mixed seizure types and intellectual disabilities Cause unknown in about 25-35% cases, symptomatic of structural or metabolic abnormalities

3 Epi4K Project 1 Hypothesis and Strategy Hypothesis Significant number of IS and LGS cases of unknown cause are due to dominant de novo mutations Research Strategy Conduct whole exome sequencing on 300 family trios that include patients with cryptogenic IS/LGS and their unaffected parents (samples from EPGP collection) Screen de novo point mutations and de novo CNVs Evaluate rare inherited variants

4 Epi4K Project 1- Participants Contributed by EPGP The Epilepsy Phenome/Genome Project: an actively enrolling 5-year NINDSfunded study to consent 5,250 participants in families with epilepsy with detailed phenotyping, medical records, EEG, and MRI data available for all. All Project 1 samples are from the IS-LGS arm of EPGP (Elliott Sherr). DNA (Coriell Institute) Phenotyping Interviews Medical Records EEG & MRI Scientific Core Review IS/LGS 447 families enrolled IGE/LRE 1073 first degree pairs enrolled PMG/PVNH 187 families enrolled IS/LGS cryptogenic or FCD Proband with epilepsy, both biological parents enrolled with blood sample Both first degree relatives have idiopathic IGE/LRE Onset <45 PMG or bilateral PVNH Proband with epilepsy, both biological parents enrolled with blood sample No confirmed genetic syndrome

5 Number of EE proabnds Distribution of de novo mutations in 264 trios Number of de novo muta ons per EE proband

6 Do we see more than expected under the null? Likelihood analysis by Andrew Allen (cf Neale et al 2012) (η)proportion of the exome sequence that can carry disease-influencing mutations (η) (γ) the relative risk given the presence of at least one deleterious mutation versus having none

7 Do we see more than expected under the null? Nope

8 Motivation for intolerance score Genes intolerant to standing functional variation are more likely to carry mutations that cause disease Y = Number of damaging coding variants >0.1% MAF Regressor (X) = Total number of coding variants Score (S) = Studentized residuals from regressing Y on X Slave Petrovski

9 Exome Variant Server N = 4300 EA AA (13,006 chromosomes sequenced to average median depth of 111x) n = 1.87M variants (of the missense/lgd variants, 86.9% have <0.1% frequency) HGNC (CCDS) = genes with >70% CCDS bases 10x average coverage. Tennessen et al. Science (N=2440 samples) Frequency Spectrum: most variants are very rare Participating Groups: Seattle GO - University of Washington, Seattle, WA Broad GO - Broad Institute of MIT and Harvard, Cambridge, MA WHISP GO - Ohio State University Medical Centre, Columbus, OH Lung GO - University of Washington, Seattle, WA WashU GO - Washington University, St. Louis, MO Heart GO - University of Virginia Health System, Charlottesville, VA ChargeS GO - University of Texas Health Sciences Centre at Houston

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11 Fn(x): Percentage (%) explained Extreme disorder class comparison: Intolerance Score Percentiles (0.1%) p=1.8x10-4, FET p=2.8x10-3, FET %Developmental Genes %Immunological genes % 50% 75% 100% Residual Variation Score Percentile bins of 25% Disorder Classes from Goh et al The Human Disease Network. PNAS 104(21):

12 Fn(x): Cumulative Percentage explained Known EE genes are intolerant to common functional variation Of the 15 OMIM EE genes, ARX was not sufficiently covered in EVS data to generate a tolerance score. Phenotype MIM number OMIM Phenotype HGNC Score EIEE 5 SPTAN1 [D] 0.30% EE NEW KCNT1 [D] 1.60% EIEE 11 SCN2A [D] 1.80% EIEE 13 SCN8A [D] 2.30% Dravet SCN1A [D] 4.00% EIEE 9 PCDH19 [D] 10.40% EIEE 12 PLCB1 [R] 11.50% EIEE 4 STXBP1 [D] 14.80% EIEE 7 KCNQ2 [D] 15.80% EIEE 2 CDKL5 [D] 15.80% EIEE 10 PNKP [R] 20.80% LGS MAPK10 [D] 23.70% EIEE 8 ARHGEF9 [R] 44.60% EIEE 3 SLC25A22 [R] 63.00% Percentile Scores Example, 10% = most intolerant ~1700 (10%) genes of 16,956 assessed genes with CCDS transcript(s).

13 Do we see more De Novo mutations than expected under the null In Intolerant genes (4264 genes)? Yes (p<10-3) MLE estimates: η (90 EE genes) γ 81

14 Percent of de novo mutations in intolerant genes Enrichment of de novo mutation in intolerant genes SCORE GENES BASED ON THEIR TOLERANCE TO COMMON FUNCTIONAL VARIATION Y = Number of damaging coding variants >0.1% MAF Regressor (X) = Total number of coding variants Score (S) = Studentized residuals from regressing Y on X EE ID ASD CONTROLS

15 Identification of individual genes The mutation rate (M) of each gene was calculated using the trinucleotide mutation rate matrix provided by Drs. Shamil Sunyaev and Paz Polak. P = 1 Poisson cumulative distribution function (x-1, λ) where, x is the observed de novo mutant number for the specific gene, λ is calculated as 2S*M for genes on autosome or (2f + m)*m for genes on chromosome X (S is the number of trios; f and m are the number of sequenced female and male probands, respectively). Genes on Y chromosome were not part of these analyses.

16 Probabilities of getting greater than or equal observed de novo SNVs tally by chance Gene Chromosome Average effectively captured length (bp) Weighted mutation rate De novo mutation number p-value SCN1A x x10-9 *** STXBP x x10-11 *** GABRB x x10-10 *** CDKL5 X x x10-7 ** ALG13 # X x x10-12 *** DNM x x10-4 HDAC x x10-4 SCN2A # x x10-9 *** SCN8A x x10-4 # Two de novo mutants in gene ALG13 occur at the same position. The probability of this special case obtains P = 5.5x10-12

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18 Gene CACNA1A Genes previously implicated in neuropsychiatric disease Disorder Familial hemiplegic migraine, episodic ataxia with and without seizures (Ophoff et al., 1996, Yamazaki et al., 2011), autism (O Roak et al., 2012) CHD2 Autism (Endele et al., 2010), intellectual disability with seizures (Rauch et al., 2012) GABRB3 Autism (Iossifov et al., 2012) FLNA periventricular heterotopia (Robertson et al., 2006) GRIN1 intellectual disability (Hamdan et al., 2011) GRIN2B Autism (O Roak et al., 2012), intellectual disability (Endele et al., 2010) HNRNPU Multiple congenital abnormalities with seizures (Need et al., 2012) IQSEC2 Intellectual disability (Rauch et al., 2012, Shoubridge et al., 2010) Infantile spasms (Morleo et al., 2008) MTOR Hemimegalencephaly (somatic mutation) (Lee et al., 2012) NEDD4L Photosensitive epilepsy (Dibbens et al., 2007) infantile epilepsy (Hitomi et al., manuscript submitted) HNRNPH1 RNA binding protein

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20 TNK2 mutation causes epilepsy by blocking binding to NEDD (Chantal DePondt) (a) TNK2 716V (b) TNK2 716M EGF EGF EGFR a b Reduced expression EGFR a b NEDD TNK2 ERK NEDD TNK2 ERK Degradation Epilepsy

21 Percent of causal de novo muta ons Pathogenic Mutations Identified By Epi4K To Date / /28 2/28 1/28 missense splice nonsense frame-shi indel

22 Key conclusions to date Newly identified genes are converging on pathways RNA binding proteins HNRNPU and HNRNPHI implicated in epileptic encephalopathies for first time Dysregulation of EGF/ERK signaling implicated in encephalopathies for first time Functional analyses are a key part of interpretation (and ultimate utility)

23 Implications For some conditions, in the near future, most patients presenting with disease may have an identified causal or contributing mutation Translational programs can tailor treatment to the mutations that are carried For example, screening programs to test activity against ion channels with specific mutations