Recent Discoveries of Epilepsy Related Genes: A Preview of the Future

Pediatric State of the Art Symposium

Genetics of Catastrophic Infantile Epilepsies: From Gene Discovery to Practical Clinical Applications

December 9, 2013

Erin Heinzen, Pharm.D., Ph.D. Center for Human Genome Variation

Duke University

American Epilepsy Society | Annual Meeting

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Disclosure

NONE

American Epilepsy Society | 2013 Annual Meeting 2

Learning Objectives

1. To provide an overview of gene discovery in epilepsy

2. To discuss recent studies using next-generation sequencing to investigate the role of de novo mutations in epileptic encephalopathies

3. To discuss what is needed to better characterize these discoveries to be able to apply the knowledge to clinical practice

American Epilepsy Society | 2013 Annual Meeting 3

Gene discovery in epilepsy

15q11.2

15q13.3

16p13.11

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Massively-parallel sequencing/next-generation sequencing: Conceptual overview

GENOMIC DNA

FRAGMENTED GENOMIC

DNA

SEQUENCE FRAGMENTS IN PARALLEL AND ALIGN

TO THE REFERENCE GENOME

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REFERENCE GENOME

TGCATA TGAATA TGCATA TGAATA TGCATA TGAATA TGAATA TGCATA TGAATA TGCATA

CCAGTC CCACTC CCACTC CCACTC CCACTC CCACTC CCACTC CCACTC CCACTC CCACTC

Alignment and Variant Calling

CCAGTC CC- - TC CCAGTC CC- - TC CCAGTC CC- - TC CCAGTC CC- - TC CCAGTC CC- - TC

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heterozygous deletion

homozygous deletion

duplication

Windows

Detecting copy number variants from NGS data

ERDS (Estimation by Read Depth with SNvs) Average read depth (RD) of every 2-kb window were calculated, followed

by GC corrections. A paired Hidden Markov model was applied to infer copy numbers of every window by utilizing both RD information and heterozygosity information.

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NGS Study Designs

Multiplex families

Case-control studies

Trio sequencing of

sporadic diseases

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Number of publications reporting de novo mutations as the cause of a disease

Nu

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rep

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de

no

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mu

tati

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2010 2011 2012

Epi4K Consortium

Epi4K Consortium. Epi4K: gene discovery in 4,000 genomes, Epilepsia, 2012 Aug;53(8):1457-67.

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Epi4K Collaborative Workflow – Project 1

EXOME SEQUENCE 1. ROLE OF KNOWN

GENES 2. NOVEL GENES

1. EPILEPTIC ENCEPHALOPATHIES • INFANTILE SPASMS • LENNOX GASTAUT

2. MALFORMATIONS OF CORTICAL DEVELOPMENT

• POLYMICROGYRIA • PERIVENTRICULAR NODULAR HETEROTOPIAA

1. PHENOTYPIC SPECTRUM

2. ROLE OF THE GENE IN PARTICULAR PATIENT POPULATIONS

TARGETED SEQUENCING IN LARGER PATIENT

POPULATIONS

FUNCTIONAL STUDIES

1. MOLECULAR CONSEQUENCES

2. PHARMACOLOGIC MODULATION

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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 LG 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

Exome sequenced 149 IS probands, 115 LGS probands and their

unaffected parents

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De novo mutation calling

• GATK Unified Genotyper – Multi-sample calling within each trio identifying variants that met the following criteria:

• Candidate de novo mutations were absent from populations controls

• Sanger sequencing was used to confirm the was present and de novo

Epi4K and EPGP Investigators. Nature 2013.

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Distribution of de novo mutations in 264 EE probands

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NumberofEEproab

nds

Numberofdenovomuta onsperEEproband

0 1 2 3 4 5 6

likelihood analysis to test for presence of risk factors in these data (adapted from the model established in Neale et al, Nature 2013)

Epi4K and EPGP Investigators. Nature 2013.

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Genic tolerance to functional variation

Hypothesis: Genes intolerant to standing functional variation are more likely to carry mutations that cause disease

ExomeVariantServer: database of variants in 6500 individuals

• 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

= RVIS Petrovski S, et al. PLoS Genet. 2013 Aug;9(8):e1003709.

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Adapted from Petrovski S, et al. PLoS Genet. 2013 Aug;9(8):e1003709.

RVIS for OMIM disease genes

OMIM disease genes (n=2131)

Genes not reported in OMIM to cause disease (14,712)

OMIM haploinsufficiency genes (n=175)

OMIM recessive genes (n=817)

OMIM de novo genes (n=467)

OMIM dominant-negative (n=364)

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RVIS Percentiles

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um

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tive

per

cen

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f O

MIM

dis

eas

e

g

enes

exp

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Neurodevelopmental genes tend to have lower RVIS

Neurodevelopmental disease gene list from Goh et al. 2007. The Human Disease Network. PNAS 104(21): 8685-8690

Adapted from Petrovski S, et al. PLoS Genet. 2013 Aug;9(8):e1003709.

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Distribution of de novo mutations in intolerant genes in 264 EE probands

Number of de novo coding mutations observed in intolerant

genes per IS/LGS trios

likelihood analysis • significant excess of de novo mutations in the

∼4,000 “intolerant” genes • ~90 EE genes • Mutation effect size of ~81

Epi4K and EPGP Investigators. Nature 2013.

1234560 1 2 3 4 5

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Test for excess mutation in individual genes as a function of the mutation rate and size

The mutation rate (M) of each gene was calculated using the tri-

nucleotide 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.

Epi4K and EPGP Investigators. Nature 2013.

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Gene Chr Average effectively

sequenced length (bp)

Weighted

mutation rate

De novo

mutation

number

p-value†

SCN1A 2 6063.70 1.61x10-4 5 1.12x10-9 ***

STXBP1 9 1917.51 6.44x10-5 5 1.16x10-11 ***

GABRB3 15 1206.86 3.78x10-5 4 4.11x10-10 ***

CDKL5 X 2798.38 5.44x10-5 3 4.90x10-7 **

ALG13 # X 475.05 1.03x10-5 2 7.77x10-12 ***

DNM1 9 2323.37 9.10x10-5 2 2.84x10-4

HDAC4 2 2649.82 1.16x10-4 2 4.57x10-4

SCN2A # 2 5831.21 1.52x10-4 2 1.14x10-9 ***

SCN8A 12 5814.48 1.64x10-4 2 9.14x10-4 # Two de novo mutants occur at the same position.

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A protein–protein interaction network of genes with de novo mutations

Epi4K and EPGP Investigators. Nature 2013. 21

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What’s next?

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Epi4K and EPGP Investigators. Nature 2013.

Nakamura et al. AJHG 2013.

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Glycosylation defects in EE

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Epi4K Additional exome

sequencing of EE trios

EuroEPINOMICS Exome sequencing of EE

trios

NEW EE GENES AND ASSOCIATED

CLINICAL PHENOTYPES

Epi4K Targeted NGS of EE candidate

genes in ~600 EE trios

EPIGEN Consortium Targeted NGS of EE

candidate genes in 500 adult EE patients

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iPSC-derived neurons to unravel disease pathophysiology

• Differentiate human stem cells carrying mutations into inhibitory neurons, excitatory neurons, and glia cells.

• Create functioning network of neurons in vitro to study the effects of the mutations, and to test compounds that will reverse the pathophysiological changes.

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Multi Electrode Array (MEA)

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iPSC-derived neuron activity

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Acknowledgements

Epi4K Consortium Samuel F. Berkovic, David B. Goldstein, Daniel H. Lowenstein, Andrew S. Allen, Patrick Cossette, Norman Delanty, Dennis Dlugos, Evan E. Eichler, Michael P. Epstein, Tracy Glauser, Yujun Han, Erin L. Heinzen, Yuki Hitomi, Katherine B. Howell, Michael R. Johnson, Ruben Kuzniecky, Daniel H. Lowenstein, Yi-Fan Lu, Maura R. Z. Madou, Anthony G. Marson, Heather C. Mefford, Sahar Esmaeeli Nieh, Terence J. O'Brien, Ruth Ottman, Slavé Petrovski, Annapurna Poduri, Elizabeth K. Ruzzo, Ingrid E. Scheffer, Elliott H. Sherr & Christopher J. Yuskaitis

Epilepsy Phenome/Genome Project Bassel Abou-Khalil, Brian K. Alldredge, Jocelyn F. Bautista, Samuel F. Berkovic, Alex Boro, Gregory D. Cascino, Damian Consalvo, Patricia Crumrine, Orrin Devinsky, Dennis Dlugos, Michael P. Epstein, Miguel Fiol, Nathan B. Fountain, Jacqueline French, Daniel Friedman, Eric B. Geller, Tracy Glauser, Simon Glynn, Sheryl R. Haut, Jean Hayward, Sandra L. Helmers, Sucheta Joshi, Andres Kanner, Heidi E. Kirsch, Robert C. Knowlton, Eric H. Kossoff, Rachel Kuperman, Ruben Kuzniecky, Daniel H. Lowenstein, Shannon M. McGuire, Paul V. Motika, Edward J. Novotny, Ruth Ottman, Juliann M. Paolicchi, Jack M. Parent, Kristen Park, Annapurna Poduri, Ingrid E. Scheffer, Renée A. Shellhaas, Elliott H. Sherr, Jerry J. Shih, Rani Singh, Joseph Sirven, Michael C. Smith, Joseph Sullivan, Liu Lin Thio, Anu Venkat, Eileen P. G. Vining, Gretchen K. Von Allmen, Judith L. Weisenberg, Peter Widdess-Walsh & Melodie R. Winawer

EuroEPINOMICS Peter De Jonghe, Ingo Helbig, Anna-Elina Lehesjoki, Holgar Lerche, Arvid Suls, Sarah Weckhuysen, Johanna Jaehn, Bobby Koeleman, Hiltrud Muhle, Padhraig Gormley, Sarah Von Spiczak, Silke Appenzeller

EpiGen Consortium David Goldstein, Norman Delanty, Gianpiero Cavalleri, Chantal Depondt, Danielle Andrade

Funding National Institute of Neurological Disorders and Stroke

– The Epilepsy Phenome/Genome Project NS053998

– Epi4K Project 1 – Epileptic Encephalopathies NS077364

– Epi4K – Administrative Core NS077274

– Epi4K Sequencing, Biostatistics and Bioinformatics Core NS077303 and Epi4K – Phenotyping and Clinical Informatics Core NS077276)

Finding a Cure for Epilepsy and Seizures Richard Thalheimer Philanthropic Fund.

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