Multipoint development of the weighted pairwise correlation (WPC) linkage method for pedigrees of arbitrary size and application to the analysis of breast cancer and alcoholism familial data

Genome-wide linkage analysis of malaria infection intensity and mild disease

Although balancing selection with the sickle-cell trait and other red blood cell disorders has emphasized the interaction between malaria and human genetics, no systematic approach has so far been undertaken towards a comprehensive search for human genome variants influencing malaria. By screening 2,551 families in rural Ghana, West Africa, 108 nuclear families were identified who were exposed to hyperendemic malaria transmission and were homozygous wild-type for the established malaria resistance factors of hemoglobin (Hb)S, HbC, alpha(+) thalassemia, and glucose-6-phosphate-dehydrogenase deficiency. Of these families, 392 siblings aged 0.5-11 y were characterized for malaria susceptibility by closely monitoring parasite counts, malaria fever episodes, and anemia over 8 mo. An autosome-wide linkage analysis based on 10,000 single-nucleotide polymorphisms was conducted in 68 selected families including 241 siblings forming 330 sib pairs. Several regions were identified which showed evidence for linkage to the parasitological and clinical phenotypes studied, among them a prominent signal on Chromosome 10p15 obtained with malaria fever episodes (asymptotic z score = 4.37, empirical p-value = 4.0 x 10(-5), locus-specific heritability of 37.7%; 95% confidence interval, 15.7%-59.7%). The identification of genetic variants underlying the linkage signals may reveal as yet unrecognized pathways influencing human resistance to malaria.

The role of estrogen in the initiation of breast cancer

Estrogens are considered to play a major role in promoting the proliferation of both the normal and the neoplastic breast epithelium. Their role as breast carcinogens has long been suspected and recently confirmed by epidemiological studies. Three major mechanisms are postulated to be involved in their carcinogenic effects: stimulation of cellular proliferation through their receptor-mediated hormonal activity, direct genotoxic effects by increasing mutation rates through a cytochrome P450-mediated metabolic activation, and induction of aneuploidy. Recently it has been fully demonstrated that estrogens are carcinogenic in the human breast by testing in an experimental system the natural estrogen 17beta-estradiol (E(2)) by itself or its metabolites 2-hydroxy, 4-hydroxy, and 16-a-hydroxy-estradiol (2-OH-E(2), 4-OH-E(2), and 16-alpha-OH E(2)), respectively, by inducing neoplastic transformation of human breast epithelial cells (HBEC) MCF-10F in vitro to a degree at least similar to that induced by the chemical carcinogen benz(a)pyrene (BP). Neither Tamoxyfen (TAM) nor ICI-182,780 abrogated the transforming efficiency of estrogen or its metabolites. The E(2) induced expression of anchorage independent growth, loss of ductulogenesis in collagen, invasiveness in Matrigel, is associated with the loss of 9p11-13 and only invasive cells that exhibited a 4p15.3-16 deletion were tumorigenic. Tumors were poorly differentiated ER-alpha and progesterone receptor negative adenocarcinomas that expressed keratins, EMA and E-cadherin. The E(2) induced tumors and tumor-derived cell lines exhibited loss of chromosome 4, deletions in chromosomes 3p12.3-13, 8p11.1-21, 9p21-qter, and 18q, and gains in 1p, and 5q15-qter. The induction of complete transformation of the human breast epithelial cell MCF-10F in vitro confirms the carcinogenicity of E(2), supporting the concept that this hormone could act as an initiator of breast cancer in women. This model provides a unique system for understanding the genomic changes that intervene for leading normal cells to tumorigenesis and for testing the functional role of specific genomic events taking place during neoplastic transformation.

17-Beta-estradiol induces transformation and tumorigenesis in human breast epithelial cells

Breast cancer is a malignancy whose dependence on estrogen exposure has long been recognized even though the mechanisms whereby estrogens cause cancer are not clearly understood. This work was performed to determine whether 17beta-estradiol (E2), the predominant circulating ovarian steroid, is carcinogenic in human breast epithelial cells and whether nonreceptor mechanisms are involved in the initiation of breast cancer. For this purpose, the effect of four 24 h alternate periods of 70 nM E2 treatment of the estrogen receptor alpha (ER-alpha) negative MCF-10F cell line on the in vitro expression of neoplastic transformation was evaluated. E2 treatment induced the expression of anchorage-independent growth, loss of ductulogenesis in collagen, invasiveness in Matrigel, and loss of 9p11-13. Only invasive cells that exhibited a 4p15.3-16 deletion were tumorigenic. Tumors were poorly differentiated ER-alpha and progesterone receptor-negative adenocarcinomas that expressed keratins, EMA, and E-cadherin. Tumors and tumor-derived cell lines exhibited loss of chromosome 4, deletions in chromosomes 3p12.3-13, 8p11.1-21, 9p21-qter, and 18q, and gains in 1p, and 5q15-qter. The induction of complete transformation of MCF-10F cells in vitro confirms the carcinogenicity of E2, supporting the concept that this hormone could act as an initiator of breast cancer in women. This model provides a unique system for understanding the genomic changes that intervene for leading normal cells to tumorigenesis and for testing the functional role of specific genomic events taking place during neoplastic transformation.

Weighting affected sib pairs by marker informativity

For the analysis of affected sib pairs (ASPs), a variety of test statistics is applied in genomewide scans with microsatellite markers. Even in multipoint analyses, these statistics might not fully exploit the power of a given sample, because they do not account for incomplete informativity of an ASP. For meta-analyses of linkage and association studies, it has been shown recently that weighting by informativity increases statistical power. With this idea in mind, the first aim of this article was to introduce a new class of tests for ASPs that are based on the mean test. To take into account how much informativity an ASP contributes, we weighted families inversely proportional to their marker informativity. The weighting scheme is obtained by use of the de Finetti representation of the distribution of identity-by-descent values. We derive the limiting distribution of the weighted mean test and demonstrate the validity of the proposed test. We show that it can be much more powerful than the classical mean test in the case of low marker informativity. In the second part of the article, we propose a Monte Carlo simulation approach for evaluating significance among ASPs. We demonstrate the validity of the simulation approach for both the classical and the weighted mean test. Finally, we illustrate the use of the weighted mean test by reanalyzing two published data sets. In both applications, the maximum LOD score of the weighted mean test is 0.6 higher than that of the classical mean test.

A test of linkage for complex discrete and continuous traits in nuclear families

This article presents a score test for genetic linkage in nuclear families which applies to any trait having a distribution belonging to the exponential family, which includes binary and normal distributions, and distributions which are skewed or have nonnormal kurtosis. The specific distribution need not be specified and the method applies to sibships of arbitrary size. Tests of complex genetic effects are given, including unspecified mode of inheritance or additive, dominant, overdominant, and recessive modes of inheritance, covariates, multiple-locus models, including gene-gene interactions, and gene-environment interactions. The relation of our method to the Haseman-Elston methods is studied theoretically and by simulation.