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Hlne Blanch

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Siblings of centenarians are 8 17 more likely to become ... Jean-Christophe Beaudoin. Laetitia Gressin. Val rie Morel. Patricia Pasturaud. Mourad Sahbatou ... – PowerPoint PPT presentation

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Title: Hlne Blanch


1
Genetics of Longevity
  • Hélène Blanché
  • Fondation Jean Dausset - CEPH

2
Longevity a complex trait
  • Twin study 2872 Danish pairs (Herskind et al.
    1996)
  • Heritability 0.25
  • Siblings of centenarians are 8 17 more likely
    to become centenarian as compared to controls
    (Perls et al. 2002)
  • Association study
  • Linkage analysis

3
Collection of biological samples
  • Started at CEPH in 1991
  • DNA, plasma, serum, PBL, lymphoblastoïd cell
    lines
  • 980 unrelated centenarians
  • 500 nonagenarians belonging to 240 families
  • 550 offspring of nonagenarians belonging to 180
    families

4
Cohorts available
  • Japan
  • China
  • Germany
  • United Kingdom
  • Italy
  • Denmark
  • Finland
  • Netherlands
  • United States

5
Main results of association studies
  • Lots of associations which were never clearly
    replicated except for APOE, frailty gene.
  • Genes tested at CEPH (between 1997 and 2000)
  • APOE
  • ACE
  • WRN
  • LMNA
  • TERT, TERC
  • KLOTHO
  • SOD2, SOD3
  • GSR, CAT, GPX1, GPX3, CYP2D6, GSTM1, NAT2

6
Linkage studies
  • A linkage signal on chromosome 4q published by
    Puca et al. in 2001.
  • 308 nonagenarians, 138 families
  • Not yet confirmed.
  • MTP (microsomal transfer protein) was found
    associated with longevity in a US population. Not
    confirmed in French, Danish, German, Dutsch
    cohorts

7
GEHA (Genetics of Healthy Aging)
  • Started in 2004
  • Integrated Project of EU 6thFP
  • 5 years, 25 Partners.

8
Aims of GEHA
  • To recruit 2650 sib-pairs of elderly people and
    2650 matched younger controls
  • To search for candidate regions/genes
  • To test whether different populations share the
    same genes involved in aging and longevity
  • To identify mtDNA haplogroups and mtDNA mutations
    associated with longevity
  • To identify gender-specific genes differently
    involved in healthy aging and longevity

9
(No Transcript)
10
Set up of a standardized protocol
  • Acceptable by all local ethics committees
  • Informed consent, information file
  • Standardized case sheet to assess and record data
  • socio-demographic information,
  • lifestyle habits,
  • health and morbidity,
  • medication,
  • sensorial function,
  • cognitive function and depression (SMMSE),
  • functional activity, physical performances (ADL
    test, Hand grip test, Chair stand test).
  • Training of people in charge of the recruitment

11
A phenotypic database
  • Centralized database in Odense and local data
    stored in each recruiting center
  • EPIDATA, a standardized procedure to enter data
    online via a VPN (crypted connection) to the
    centralized database
  • Restricted access by login/password

12
Recruitment identification of volunteers
  • Identification of elderly sib-pairs
  • On census data or other available lists
  • Contact people by phone or mail
  • Visit at elderlys home, nursing home
  • Identification of unrelated controls (60-75 years
    old)

13
Organization of a visit
  • Interview of the volunteer in presence of a proxy
    if necessary (MD or trained nurse)
  • Presentation of the project
  • Answer to all questions
  • Informed consent is signed
  • Collect of information
  • Cognitive and physical tests
  • Collect of biological sample
  • About 2 hours per volunteer

14
Biological samples and treatments
  • 2 EDTA tubes labeled with bar codes (PID)
  • - one is frozen without any treatment for further
    DNA extraction
  • - one is centrifuged to isolate plasma and blood
    pellet
  • 3rd tube either EDTA or heparin, labeled with bar
    code (PID)
  • - isolation of plasma and blood pellet
  • - isolation of PBL for establishment of cell
    lines
  • Cheek swab if blood donation is not possible

15
Update on recruitment, March 2006
  • 3500 families contacted
  • 40.7 gave a positive answer
  • 51 were excluded
  • 9.7 one sib died
  • 11.1 dementia
  • 27.5 immediate refusal
  • 2.7 one sib was unreachable
  • 8.3 of contacted families are in stand-by
  • 881 sib-pairs and 881 controls were recruited

16
KTL a centralized DNA extraction center
  • For each individual, one frozen whole blood
    sample is sent to KTL
  • Extractions are performed on a Gentra automate
  • Each DNA is labeled with a new ID (GID). KTL has
    the correspondence table between PID and GID
  • 943 DNAs were extracted (including 19 cheek swab
    samples) (March 2006)

17
9 Genetic Platforms
Mitochondrial genome
Nuclear genome
18
A genotypic database
  • Centralized in Kiel Genedigger
  • Connections between phenotypic and genotypic
    databases only allowed for partners involved in
    analyses after approval of the Steering Committee

19
Genome scan
  • Illumina Linkage panel
  • 136 sib-pairs are genotyped at CNG
  • 600 next sib-pairs should be available in
    September 2006
  • Analyses on 736 sib-pairs will be performed at
    the end of 2006.

20
Association studies
  • Chr4q region (linkage data)
  • Chr11p15.5 region (SIRT3, KRAS, IGF2, INS, TH),
    a 2.4 Mb region.

21
Chr11p15.5 region selection of SNPs
  • Search for TagSNP typed for the HapMap project
    (build 34), 30 CEPH trios
  • LDselect (Carlson)
  • Analysis of 587 SNPs (MAF 5 )
  • 337 TagSNPs were identified

22
Chr11p15.5 region results
  • Germany 377 cases and 376 controls
  • Central Italy 307 cases and 352 controls
  • 214 SNPs out of 337 TagSNPs were typed
    successfully on cohorts
  • No association was identified in one population
    and replicated in the other
  • Replication on French centenarians and controls?

23
Future of genetic studies in GEHA
  • Genome scan
  • Analysis of 736 sib-pairs
  • Confirmation of positive signals on a new
    sib-pair population
  • Association study
  • French cohort tested on positive signals
    identified on either German or Central-Italian
    cohorts
  • Follow up of candidate regions identified during
    the genome scan

24
Acknowledgments
  • GEHA main collaborators
  • Claudio Franceschi, University of Bologna
  • Stefan Schreiber, University Hospital Schleswig
    Holstein, Kiel
  • Eline Slagboom, Leiden University Medical Center
  • Markus Perola, KTL, Helsinki
  • CEPH
  • Jean-Christophe Beaudoin
  • Laetitia Gressin
  • Valérie Morel
  • Patricia Pasturaud
  • Mourad Sahbatou
  • Mark Lathrop
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