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 3905insT

E60X

D1152H

V520FP67L

R1077P

711+5G>A

R668CY569D

P205SQ220X

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

CFTR2CFTR239,545 patients

Clinical information

CFTR1(CF Mutation Database)

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 mutationClinically consistent mutation

Sweat chloride concentrations in 10,108 F508del homozygotes

05

001

000

150

02

000

Fre

que

ncy

0 50 100 150 200 250Sweat chloride

60 mEq/L

Sweat chloride concentration

Mean 103 + 16.8 mEq/L

Num

ber

of p

atie

nts

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 mutationClinically consistent mutation

Functionally consistent mutationFunctionally 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 mutationFunctionally consistent mutation

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

Clinically consistent mutationClinically consistent mutation

Functionally consistent mutationFunctionally consistent mutation

Genetically consistent mutationGenetically 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 mutationGenetically 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 mutationClinically consistent mutation

Functionally consistent mutationFunctionally consistent mutation

Genetically consistent mutationGenetically 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