The Clinical and Functional TRanslation of CFTR (CFTR2) Project Garry Cutting on behalf of the CFTR2 project team

CF Transmembrane conductance Regulator Serohijos A. W. R. et.al. PNAS;2008;105:3256-3261 CF Transmembrane conductance Regulator (CFTR)

CFTRdele 22,23 R1077P N1303K D1152H R117H-5T/7T S1251N 3905insT 711+5G>A G542X DF508 p.Phe508del F1074L E60X R349L M470V Y569D R668C G551D Q220X V520F P67L P205S 3849+10kbC>T

The genetic testing gap Fraction of all mutations reported in the CFTR gene 70% Fraction of all mutations that occur in patients with CF 49% Fraction of CF patients with both mutations identified <0.1% F508del 23 ACMG mutations 1.2% 85% 72%

Existing resources for CFTR mutations The Toronto CF Mutation Database Mutation-driven: Information deposited by genetic laboratories, primarily research Online Mendelian Inheritance in Man (OMIM) Publication-driven: Information from manuscripts authored by researchers

A new repository for clinical data associated with CFTR mutations (CF Mutation Database) Gene information 1893 mutations Link by mutation CFTR2 39,545 patients Clinical information

Contributors to CFTR2

Summary of clinical data collected CFTR2 Database 39,545 patients 23 registries/clinics CFTR Genotype 70,466 CF chromosomes with a mutation identified 1674 patients with both mutations unknown 5276 patients with 1 mutation unknown 250 measurements excluded Sweat Chloride Concentration 14,403 patients missing sweat data 24,892 patients Pancreatic Status 30,236 patients 9309 unknown Lung Function (FEV1%predicted) 23,338 patients 3 measurements <5 % predicted excluded 16,204 patients missing PFT data

Where did we start? 160 mutations are seen in 9 or more patients in the CFTR2 database Allele frequency of 0.0001 or .01% This represents 97% of total identified CFTR mutations

How do we determine which mutations cause CF and which ones don’t?

Clinical Expert Committee Christiane De Boeck, MD, PhD - University Hospital of Leuven, Belgium Peter Durie, MD - Hospital for Sick Children, Toronto, Canada Stuart Elborn, MD - Queen's University, Belfast, UK Phil Farrell, MD, PhD – Univ. Wisconsin, USA Michael Knowles, MD - University of North Carolina, Chapel Hill, USA Isabelle Sermet, MD, PhD- Necker Hospital, Paris, France

Clinically consistent mutation Elevated sweat chloride concentration Reduced FEV1 % predicted Exocrine pancreatic disease Infection with Pseudomonas aeruginosa Other features (meconium ileus, male infertility (CBAVD)

Sweat chloride concentrations in 10,108 F508del homozygotes Mean 103 + 16.8 mEq/L 60 mEq/L Number of patients Sweat chloride concentration

How do we isolate the effect of a mutation in patients that carry two mutations? 7 7 CFTR

How do we determine which mutations cause CF and which ones don’t? Clinically consistent mutation Functionally consistent mutation

Predicted effect of 160 mutations upon CFTR function Change in one amino acid

CFTR Function Expert Committee Margarida Amaral, PhD - University of Lisbon, Portugal Bob Bridges, PhD - Rosalind Franklin University, Illinois, US Gergely Lukacs, MD - McGill University, Montreal, Canada David Sheppard, PhD – Bristol University, UK Phil Thomas, PhD - UT Southwestern, Dallas, US

Functionally consistent mutation CFTR procession and function (Fred Van Goor) Fisher Rat Thyroid (FRT) cells expressing CFTR from single cDNA integration Characterize the processing and function of CFTR CFTR processing (Phil Thomas) HeLa transient expression FRT stable expression CFTR splicing (Margarida Amaral) CFTR minigene plasmids HEK293 stable expression CFBE41o- stable expression (planned) In vivo (when possible) Site-directed mutagenesis Cell line generation mRNA level: Quantitative PCR CFTR Maturation: Western Blot CFTR Function: Ussing Chamber FRT cell lines created analyzed for 57 missense and 2 deletion mutations

How do we determine which mutations cause CF and which ones don’t? Clinically consistent mutation Functionally consistent mutation Genetically consistent mutation

Genetically consistent mutation Fertile fathers of CF patients should carry only one mutation that causes CF Confirm that none of the clinically and functionally consistent mutations occur as the second mutation in a father of a CF patient Mutations occurring in at least 9 patients have a frequency ~0.0012 (9/8400 genes without ACMG mutations) 2000 ‘healthy’ CFTR genes in 2000 fathers provides 80% power to detect variants at 0.002 at type I error rate of 0.05

How do we determine which mutations cause CF and which ones don’t? Clinically consistent mutation Functionally consistent mutation Genetically consistent mutation CF-causing mutation

Improving genetic testing for CF Fraction of all mutations reported in the CFTR gene Fraction of all mutations that occur in patients with CF 85% Fraction of CF patients with both mutations identified 72% 1.2% 23 ACMG mutations 160 CFTR2 mutations 8.4% 97% 90%

What is the best way to present this information in a public database?

CFTR2 Patient Advocacy Committee Barbara Karczeski MS(Genetic Counselor)- Johns Hopkins DNA Diagnostic Lab, Baltimore, MD Michelle Huckaby Lewis, MD, JD (Ethics expert) – Berman Institute of Bioethics/Genetics and Public Policy Center, Johns Hopkins, Baltimore MD Bruce Marshall, MD (CFF representative) - CF Foundation, Bethesda, MD, USA Juliet Page (Patient representative) - Annapolis, MD, USA

G551D I148T D1152H

Summary Data from nearly 40,000 CF patients into the CFTR2 database have been instrumental in: Increasing the list of clinically, functionally and genetically vetted ‘CF-causing’ mutations from 23 to ~160 (more to follow..) Providing complete CFTR mutation information on 9 out of 10 patients with CF Creating the infrastructure for new studies into the relationship between CFTR function and the CF phenotype

CFTR2 Team Vertex Pharmaceuticals and NIDDK R37 DK44003 Julian Zielenski Vertex Pharmaceuticals and NIDDK R37 DK44003

Thanks to the CF clinical and research community for making this project possible