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

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

3. 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
kbC>T

4. 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%

5. 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

6. 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

7. Contributors to CFTR2

8. 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

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

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

11. 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

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

13. Sweat chloride concentrations in 10,108 F508del homozygotes
Mean mEq/L
60 mEq/L
Number of patients
Sweat chloride concentration

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

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

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

17. 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

18. 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

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

20. 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 ~ (9/8400 genes without ACMG mutations)
2000 ‘healthy’ CFTR genes in 2000 fathers provides 80% power to detect variants at at type I error rate of 0.05

21. 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

22. 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%

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

24. 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

26. G551D
I148T
D1152H

27. 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

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

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