LINKAGE ANALYSIS OF LUNG CANCER

Linkage analysis is a statistical analysis of pedigree data that
looks for evidence of cosegregation through the generations
in human pedigrees of alleles at a genetic “susceptibility” locus
and some known genetic “marker” locus (usually a DNA polymorphism).
Linkage analysis is a very powerful method for
detecting genetic loci that are highly penetrant (after adjusting
for environmental risk factors). However, power decreases as
the susceptibility allele becomes more common and less penetrant.
Because cigarette smoking is an extremely strong risk
factor for lung cancer, 4 it is appropriate to seek models that
incorporate effects from this risk factor.
Bailey-Wilson et al. 113 published the first evidence of linkage
of a lung cancer susceptibility locus to a region of chromosome
6q. Data were collected at eight recruitment sites by the
Genetic Epidemiology of Lung Cancer Consortium (GELCC):
the University of Cincinnati, University of Colorado, Johns
Hopkins School of Public Health, Karmanos Cancer Institute,
Saccomanno Research Institute, Louisiana State University
Health Sciences Center, Mayo Clinic, and Medical College of
Ohio. Of the 26,108 lung cancer cases screened at GELCC
sites for this study, 13.7% had at least one first-degree relative
with lung cancer. Following the initial family history screening
process, additional information was collected from the 3541
families with at least one first-degree relative with lung cancer.
Probands and/or their family representatives were contacted to
collect data regarding additional persons affected with any cancers
in the extended family, vital status of affected individuals,
availability of archival tissue, and willingness of family members
to participate in the study. Further pedigree development and
biospecimen collection (blood, buccal cells, or fixed tissue) were
performed on 771 families with three or more first-degree relatives
affected with lung cancer. Cancers were verified by medical
records, pathology reports, cancer registry records, or death
certificates for 69% of individuals affected with either lung or
throat (LT) cancer, and by reports of multiple family members
for the other 31% of family members affected with LT. Of these
families, only 52 had enough biospecimens available to make
them informative for linkage analyses. DNA isolated from blood
was genotyped at the Center for Inherited Disease Research
(CIDR, a National Institutes of Health [NIH]- supported core
research facility), and DNA from buccal cells and archival tissue
and sputum were genotyped at the University of Cincinnati,
for a panel of 392 microsatellite (short tandem repeat polymorphism,
STRP) marker loci. The data were checked for errors
and then analyzed using parametric and nonparametric linkage
methods. Marker allele frequencies were calculated separately,
and linkage analyses were performed separately for the white
American and African American families, with the results combined
in overall tests of linkage.
The primary analytical approach assumed a model with
10% penetrance in carriers and 1% penetrance in the noncarriers.
This analytical approach weights information only
from the affected subjects. This linkage model was used as
the primary analytical approach because of uncertainty about
the strength of relationship between smoking behavior and
lung cancer risk in the high-risk families that were studied,
and because the complex “gene environment” models from
the published segregation analyses were not currently available
in any multipoint linkage analysis program. In addition,
because about 90% of the affected family members smoked,
weighting only the affected individuals in the simple dominant,
low-penetrance model has the effect of jointly allowing
for smoking status, while ignoring information from unaffected
subjects. Genetic heterogeneity (different families having
different genetic causation) was allowed for during the
analysis. Secondary analyses used more complex models that
included age and pack-years of cigarette smoking to modify the
penetrances. A genetic regressive model obtained from segregation
analyses by Sellers et al. 96 was used. Nonparametric analyses
were also performed as secondary analyses with variance
components models using SOLAR (binary trait option) and
mixed effects Cox regression models, in which time to onset of
disease is modeled as a quantitative trait.
Multipoint parametric linkage under the simple dominant
low-penetrance affected-only model (Fig. 4.1) yielded a
maximum heterogeneity lod (HLOD) score of 2.79 at 155 cM
(marker D6S2436) on chromosome 6q23–25 in the 52 families,
with 67% of families estimated to be linked. Multipoint
analysis of a subset of 38 families with four affected relatives
gave an HLOD of 3.47 at this same location, with 78% of
families estimated to be linked, whereas for the 23 highest-risk
families (five or more affected in two or more generations), the
multipoint HLOD score was 4.26, with 94% of these families
estimated to be linked to this region. Nonparametric analyses
and the two-point parametric analyses that used the Sellers
et al. model 60,96 all provided additional support for linkage
to this region.
Additional families have been collected by the GELCC
to confirm this linkage result in an independent sample and
to narrow the critical region that may contain a susceptibility
gene. In addition, several other regions showed suggestive evidence
of linkage and these are being pursued.