Improving diagnostics and therapeutics for Mendelian diseases using precision mouse models

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1 Improving diagnostics and therapeutics for Mendelian diseases using precision mouse models Robert W. Burgess The Jackson Laboratory Center for Precision Genetics (U54 OD020351) Resource for Research on Peripheral Neuropathy (R24 NS098523) 5 October, 2017

2 What are we modeling precisely? Face Validity Does the model look right? Precision in the phenotype Construct Validity Does the phenotype happen for the right reason? Precision genetic manipulation Predictive Validity Do results in the model translate to patients? Remember the limitations of any model

3 Inherited Peripheral Neuropathies Charcot-Marie-Tooth Diseases (CMTs) Hereditary Sensory and Motor Neuropathies Dominant, recessive, X-linked Considered Mendelian, but Two Types (Demyelinating and Axonal) Distal extremities most affected Common as a class of disease 1:2500 people affected At least 80 types About half cloned in humans (better for Type1)

4 Modeling CMT Challenging cell biology to model in vitro Length dependence (1 meter in humans) Schwann cell/axon interactions Adult onset, degenerative conditions Need animal models Engineered mouse models Some success, some failures Failures from lack of precision? Need to understand mechanism to understand failures, what can failures tell us? Other organisms Rat, Zebrafish, Drosophila, spontaneous cases

5 Outline Examples of mouse models of CMT CMT4C (SH3TC2) CMT2D (GARS) Use of mice in validating VUS and in preclinical testing Gars mice to validate a de novo mutation Treating Gars with a personalized gene therapy approach Importance of considering genetic background In preclinical studies (predictive validity) Modifier genes suggest mechanism and therapies and could improve diagnosis/prognosis

6 Modeling CMT4C Recessive demyelinating neuropathy Caused by mutations in SH3TC2 Mouse models recreate loss of function Targeted knockouts (Arnaud et al., 2009; KOMP) Spontaneous allele found by phenotype (Q71X) Predictive Validity?

7 Modeling CMT2D Dominant axonal neuropathy Caused by mutations in GARS (glycyl trna synthetase) Dominant Negative or Neomorph activity Need to produce mutant protein Induced alleles found by phenotype (P278KY, C201R) Good face validity, construct validity

8 Validating the pathogenicity of a de novo GARS mutation Female patient, now four years old Severe motor neuropathy Ascertained at 13 months of age, right hemi-diaphragm paralysis, recently lost ability to stand unassisted Whole exome sequencing De novo 12 base pair deletion in GARS Can we validate the mutation as causative using mice? Can we develop a translational gene therapy approach for the human disease allele?

9 Patient allele engineered into Gars Introduced patient mutation using CRISPR/Cas9 Introduced wild type human sequence as control Mutation caused dominant axonal neuropathy Similar to previous mouse models Mice with wild type human sequence are normal Gars (huex8/huex8) Gars (ex8del12/huex8) *

10 Personalized gene therapy for CMT2D Null heterozygous mice have no phenotype Transgenic WT GARS overexpression does not suppress neuropathy Allele-specific knockdown of mutant Gars by AAV9- delivered RNAi is effective

11 Benefits and challenges of this approach: Works in multiple mouse models, including patient allele Shows benefit post-onset Does not require complete understanding of molecular mechanism No other treatment options available Requires testing different RNAi sequences for every disease-associated allele Somewhat experimental delivery

12 Considerations for preclinical studies: Rigor and reproducibility Well-powered, well designed studies Clinically relevant, quantitative outcome measures Sex, age, other biological variables Testing in more than one model (or if not, remember that) Effects of genetic background Contribution of other loci to a precision model Testing in multiple backgrounds Possible benefits of understanding modifier genes

13 Genetic Background Every inbred strain of mouse has idiosyncrasies Testing multiple backgrounds avoids reproducible N=1 preclinical trials Can expose degree of variability/robustness Can improve predictive validity Identifying modifier loci Should focus on pathways, not exact variants Can potentially improve diagnostic/prognostic ability Can potentially suggest therapeutic strategies (especially suppressors)

14 Idealized mouse model(s) Patient variant introduced into the mouse genome Construct validity, validates pathogenesis of variant Mouse phenotype matches patient disease Face validity, establishes similar pathophysiology Phenotype is tested on multiple backgrounds Modifier genetics identifies important ancillary pathways Improved predictive validity of the model Improved diagnostic/prognostic accuracy when combined with patients genomic information

15 Acknowledgements Burgess lab Emily Spaulding Kathy Morelli Inseyah Bagasrawala Kate Miers Morgane Stum Laurent Bogdanik Abby Tadenev Andrew Garrett Peter Fuest (U. Idaho) Kevin Seburn Greg Cox Sue Ackerman Scott Harper, NWCH/OSU Tony Antonellis (U. Mich.) Erik Storkebaum (MPI) Kurt Fischbeck (NIH) Will Motley James Sleigh (UCL) Albena Jordanova (Antwerp) Xiang-Lei Yang (TSRI) Paul Schimmel (TSRI) Jackson Scientific Services Funding: NIH RO1-NS054154, U54- OD020351, R24-NS098523, MDA