the c linical and f unctional tr anslation of cftr (cftr2) project
DESCRIPTION
The C linical and F unctional TR anslation of CFTR (CFTR2) Project. Garry Cutting on behalf of the CFTR2 project team. CF Transmembrane conductance Regulator (CFTR). Serohijos A. W. R. et.al. PNAS;2008;105:3256-3261. CFTRdele 22,23. R1077P. N1303K. D1152H. R117H-5T/7T. S1251N. - PowerPoint PPT PresentationTRANSCRIPT
The Clinical and Functional TRanslation of CFTR (CFTR2) Project
Garry Cutting on behalf of the CFTR2 project team
Serohijos A. W. R. et.al. PNAS;2008;105:3256-3261
CF Transmembrane conductance Regulator
(CFTR)
F508
p.Phe508delF1074LR349LG551D
S1251N 3905insTE60X
D1152H
V520FP67L
R1077P
711+5G>A
R668CY569DP205S
Q220X
CFTRdele 22,23
G542X
3849+10kbC>T
N1303KR117H-5T/7T
M470V
F508del
<0.1%
The genetic testing gap
72%
23 ACMG mutations
1.2% 85%
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
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
Gene information
Link by mutation
1893 mutations
CFTR239,545 patients
Clinical information
CFTR1(CF Mutation Database)
Contributors to CFTR2
CFTR2 Database39,545 patients
23 registries/clinics
Pancreatic Status
30,236 patients
9309 unknown
250 measurements excluded
Sweat Chloride Concentration
14,403 patients missing sweat data
24,892 patients
Lung Function (FEV1%predicted)
23,338 patients
3 measurements <5 % predicted excluded
16,204 patients missing PFT data
Summary of clinical data collected
CFTR Genotype
70,466 CF chromosomes with a mutation
identified
1674 patients with both mutations unknown
5276 patients with 1 mutation unknown
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
• Elevated sweat chloride concentration• Reduced FEV1 % predicted• Exocrine pancreatic disease• Infection with Pseudomonas aeruginosa• Other features (meconium ileus, male
infertility (CBAVD)
Clinically consistent mutation
Sweat chloride concentrations in 10,108 F508del homozygotes
050
010
0015
0020
00Fr
eque
ncy
0 50 100 150 200 250Sweat chloride
60 mEq/L
Sweat chloride concentration
Mean 103 + 16.8 mEq/L
Num
ber o
f pat
ient
s
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
CFTR procession and function (Fred Van Goor)Fisher Rat Thyroid (FRT) cells expressing CFTR from single cDNA integrationCharacterize the processing and function of CFTR
CFTR processing (Phil Thomas)HeLa transient expressionFRT stable expression
CFTR splicing (Margarida Amaral)CFTR minigene plasmidsHEK293 stable expressionCFBE41o- 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
Functionally consistent mutation
How do we determine which mutations cause CF and which ones don’t?
Clinically consistent mutation
Functionally consistent mutation
Genetically consistent mutation
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
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
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
Fraction of all mutations reported in the CFTR gene
23 ACMG mutations
1.2%
Improving genetic testing for CF
160 CFTR2mutations
8.4%
Fraction of CF patients with both mutations identified
72%
90%97%
Fraction of all mutations that occur in patients with CF
85%
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, MDMichelle Huckaby Lewis, MD, JD (Ethics expert) – Berman Institute
of Bioethics/Genetics and Public Policy Center, Johns Hopkins, Baltimore MDBruce Marshall, MD (CFF representative) - CF Foundation, Bethesda, MD, USAJuliet Page (Patient representative) - Annapolis, MD, USA
I148T
D1152H
G551D
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
Julian Zielenski
Vertex Pharmaceuticals and NIDDK R37 DK44003
Thanks to the CF clinical and research community for making
this project possible