Genetic modelling of the estrogen metabolism as a risk factor of hormone-dependent disorders

Estradiol is a pleiotropic hormone, involved in the etiology of a wide variety of diseases. Over the last decade individual genetic variability of the estradiol metabolism has been described as a significant contributor to disease susceptibility with variations depending on ethnic background. Among others, genetic variations of genes encoding cytochrome P450 (CYP) enzymes play an important role in this regard. Mutant alleles of the CYP 1A1 gene are major modulators of lung cancer risk among smokers, mediate gender differences in lung cancer Susceptibility. and have been associated with an elevated risk for developing breast, prostate, colorectal, and oral squamous cell cancer. Variants of the CYP 1B1 gene modulate the risk for developing prostate, ovarian, lung, and breast cancer. Also, mutations in the CYP 1B1 gene are the major genetic determinant of congenital glaucoma. Mutant CYP 17 alleles are associated with serum and plasma levels of steroid hormones, use of hormone replacement therapy, and the development of endometrial, prostate, and breast cancer. Available data indicate that the protective effect against breast cancer of a later age at menarche is limited to wild-type CYP 17 allele carriers. Among women with the polycystic ovary syndrome, carriage of mutant CYP 17 alleles is sufficient to aggravate the clinical presentation of the disease. Molecular variants of the CYP 19 gene are associated with an increased risk for developing breast cancer, advanced breast cancer stages, and tumor aromatase production. Carriage of a mutant catechol-O-methyltransferase allele is associated with breast cancer, neurologic disorders such as Parkinson's disease, and modulates behavior among patients with schizophrenia, alcoholics and the general population. In summary, the available evidence points to genes that encode estrogen-metabolizing enzymes as strong hereditary determinants of the susceptibility to benign as well as malignant conditions. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.