The genetic epidemiology of cancer: Interpreting family and twin studies and their implications for molecular genetic approaches

Authors
Citation
N. Risch, The genetic epidemiology of cancer: Interpreting family and twin studies and their implications for molecular genetic approaches, CANC EPID B, 10(7), 2001, pp. 733-741
Citations number
26
Categorie Soggetti
Oncology,"Onconogenesis & Cancer Research
Journal title
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
ISSN journal
10559965 → ACNP
Volume
10
Issue
7
Year of publication
2001
Pages
733 - 741
Database
ISI
SICI code
1055-9965(200107)10:7<733:TGEOCI>2.0.ZU;2-Y
Abstract
The recent completion of a rough draft of the human genome sequence has ush ered in a new era of molecular genetics research into the inherited basis o f a number of complex diseases such as cancer. At the same time, recent twi n studies have suggested a limited role of genetic susceptibility to many n eoplasms. A reappraisal of family and twin studies for many cancer sites su ggests the following general conclusions: (a) all cancers are familial to a pproximately the same degree, with only a few exceptions (both high and low ); (b) early age of diagnosis is generally associated with increased famili ality; (c) familiality does not decrease with decreasing prevalence of the tumor-in fact, the trend is toward increasing familiality with decreasing p revalence; (d) a multifactorial (polygenic) threshold model fits the twin d ata for most cancers less well than single gene or genetic heterogeneity-ty pe models; (e) recessive inheritance is less likely generally than dominant or additive models; (f) heritability decreases for rarer tumors only in th e context of the polygenic model but not in the context of single-locus or heterogeneity models; (g) although the family and twin data do not account for gene-environment interactions or confounding, they are still consistent with genes contributing high attributable risks for most cancer sites. The se results support continued search for genetic and environmental factors i n cancer susceptibility for all tumor types. Suggestions are given for opti mal study designs depending on the underlying architecture of genetic predi sposition.