Cell, network and mouse modelling of genetic epilepsies for mechanism, diagnosis and therapy. December 7 th 2013

Transcription

1 Cell, network and mouse modelling of genetic epilepsies for mechanism, diagnosis and therapy December 7 th 213 Steven Petrou, PhD Deputy Director, The Florey Institute Deputy Director, The Centre for Neural Engineering The University of Melbourne, Australia American Epilepsy Society Annual Meeting

2 Disclosure Name of Commercial Interest NONE Type of Financial Relationship NONE American Epilepsy Society 213 Annual Meeting

3 Learning Objectives Understand how different models of genetic epilepsy can reveal direct and emergent pathologies Understand how this knowledge may inform therapeutic strategy American Epilepsy Society 213 Annual Meeting

4 Opportunity for translation provided by explosion in genetics knowledge Examined 264 trios (792 exomes) 329 variants discovered

5 Models for revealing disease state biomarkers and pathology 1. Mouse 2. Single Cell a. Biophysics b. Structure-function 3. Neuronal Network a. Primary cultures b. Human stem cell based

6 1. MOUSE MODELS

7 Mouse model reveals emergent pathologies Novel epileptogenic mechanism in model of Early Onset Epileptic Encephalopathy (EOEE) suggests targeted therapeutic intervention

8 Early onset epileptic encephalopathies (EOEE) Defined by frequent and severe epileptic seizures with progressive developmental regression, possible psychomotor deficits as seen in Dravet syndrome Difficult to treat Increasing recognition of underlying genetic defects SCN1B gene, homozygous R125C (Patino, 29) Patient presented with Dravet Syndrome We previously developed the het SCN1B(C121W) mouse Does the homozygous mouse model Dravet? Modified from: Patino, G.A. (29), A functional null mutation of SCN1B

9 Characteristics of the homozygous C121W mouse Survival Altered gait Premature death Spontaneous seizures More rapid progression to tonicclonic seizure following heating Petrou, unpublished data 213

10 Pharmacosensitivity of the homozygous C121W mouse similar to Dravet Syndrome Similar pharmacosensitivity to human Dravet patients Suggests shared pathological mechanism Petrou, unpublished data 213

11 In stark contrast to SCN1A based Dravet models, CA1 interneurons appear normal Petrou, unpublished data 213

12 BUT, hippocampal excitatory neurons from our homozygous C121W mice are more excitable WT (n =8), Hom (n = 8) Petrou, unpublished data 213

13 Changes in input resistance explains neuronal excitability Increased input resistance (R in ) may be major contributor to increased excitability WT (n=15), Hom (n=1); *P<.5 Petrou, unpublished data 213

14 Reduced neuronal arborisation might explain the changes in cellular properties Petrou, unpublished data 213

15 Can we use our information on cellular dysfunction to predict drug efficacy? Drugs that specifically target and reduce R in may rescue the seizure phenotype Retigabine Activates KCNQ2/3 channels Reduces R in Modified from: Surti TS (25), Identification by mass spectrometry and

16 In vitro: Retigabine reverses the neuronal deficit Reduces input resistance in homozygous neurons Shifts homozygous input-output relationship Petrou, unpublished data 213

17 In vivo: Retigabine reduces seizure susceptibility Petrou, unpublished data 213

18 Summary Homozygous mice as a mouse model of Dravet Phenotype corresponds to SCN1A mouse model of Dravet Thermogenic seizure susceptibility Premature death, unstable gait, severe seizures Altered excitatory neuron firing distinguishes this pathology from that of SCN1A based models Increased R in underlies changes in firing properties Mutant neurons display reduced dendritic arborisation as primary pathology Emergent properties Retigabine reverses cellular and behavioral deficits Potential example of disease mechanism based therapy

19 2. SINGLE CELL MODELS

20 Genotype-phenotype correlation and pharmacological modulation of hkcnt1 channel mutations causing epilepsy

21 KCNT1 based epilepsies In 211 ADNFLE (Autosomal Dominant Nocturnal Frontal Lobe Epilepsy) was thought to be a disorder of nicotinic acetylcholine receptors In 212 KCNT1 was discovered (Heron et al., 212, Nature Genetics) as a gene for more severe ADNFLE with psychiatric features expanding the genetic architecture At the same time Barcia et al (212, Nature Genetics) showed that KCNT1 was also associated with a very severe epileptic encephalopathy, Epilepsy of Infancy with Migrating Focal Seizures (EIMFS) characterised by drugresistant seizures and developmental delay EIMFS and ADNFLE are allelic yet clinically distinct and the mechanism by which KCNT1 mutations produce this phenotypic spectrum is intriguing

22 KCNT1 mutations in ADNFLE and EIMFS KCNT1: (Slo2.2, K Ca 4.1, SLACK) Na+ activated potassium channel Thought to contribute to RMP and to slow hyperpolarisation following repetitive firing NH 2 ADNFLE mutants M896I R398Q Y796H R928C Least severe Disease severity Y796H NAD + binding [Na + domain ] R428Q A934T P924L M896I P924L R928C (R97C) Most severe (R899C) A934T EIMFS mutants I76M R398Q R428Q R474H RCK domains [Na + ] COOH

23 KCNT1 epilepsy mutations show increased R Q R Q H current magnitude and altered kinetics 1 Y Y H M W T R 1 WT W T M8961 M I I 1 R CR928C R C 1 R428Q R Q Q 1 1 Y R Q R Q Y H H A T A T R398Q Y796H A934T 1 P924L 1 P L P L 2 A 2 1 m s R R C R C 1 1 R Q Q Petrou, unpublished data

24 current (μa) c u r re n t a t + 1 m V ( A ) current (μa) c u r re n t a t + 1 m V ( A ) KCNT1 gain of function correlates with disease severity 8 6 **** **** 6 **** **** **** **** 4 **** 4 **** ** **** 2 2 W T M I R Q Y H R C R Q A T P L W T A D N F L E E IM F S Petrou, unpublished data 213

25 Quinidine as a potential therapy? The clinical severity of KCNT1 epilepsies creates an urgent need for intervention Quinidine is an FDA approved antiarrhythmic drug shown to inhibit rodent SLACK channels Does it act on hkcnt1 and how does it interact with mutant channels? Cinchona Tree Bark Yang et al., 26 quinine quinidine

26 Quinidine blocks human WT and mutant channels Petrou, unpublished data 213

27 3. NEURONAL NETWORK MODELS

28 The perfect storm for rapidly understanding the effect of mutations and drugs INPUTS a. Genetics discoveries in epilepsy b. Stem cell technology improvements c. Multi-electrode array readiness OUTPUTS a. Diagnostic markers b. Efficacy markers Convergence of technologies to enable breakthroughs in seizure neurobiology and drug discovery toward the promise of precision medicine

29 Modeling complex genetic interactions Role of genetic background in determining clinical heterogeneity Compare multiple mutations in isogenic cell lines to simplify mutant analysis Compare patient mutation in cell line versus patient ips neurons Rescue patient mutant to understand residual phenotype Create disease state models to explore drug action

30 CRISPR/Cas (Clustered Regularly Interspaced Palindromic Repeats/CRISPR-associated) Genome editing technologies Zinc Finger Nucleases TALENs CRISPR/Cas

31 CRISPR/Cas Homology Directed Repair Addressing off target effects: Nickase version of Cas WES of cell lines with established bioinformatics filtering Scalable

32 Stem Cell Differentiation Goal is to create a functioning network of neurons that can display sufficiently complex behavior to respond to genetic changes and drug exposure Differentiate human stem cells into Inhibitory neurons Excitatory neurons Glia

33 Multi Electrode Array: Epilepsy in a dish MEA dish Active Area Contact Pads Spikes and Bursts

34 Units Spikes Number of Units Bursts POC from mouse genetic model neurons: Sensitivity to genetic variation Wild Type Spiking C121W 25 Bursting Week Week N=6 WT C121W Petrou, unpublished data 213

35 POC: Sensitivity to drugs Spiking Week Bath Retigabine (1uM) Wash Petrou, unpublished data 213

36 POC: Sensitivity to drugs Petrou, unpublished data 213

37 MEA profiling

38 Acknowledgements Chris Reid Carol Milligan Melody Li Emma Morrisroe Sophie Crux Nuttawat Pop Suphanatarida Kay Richards Elena Gazina Verena Wimmer Bryan Leaw Sam Berkovic David Goldstein Ingrid Scheffer Leanne Dibbens Sarah Heron