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F Quiaoit

Publications and source records attributed to F Quiaoit.

10 recordsLinked to original sources
PubMed1999

An efficient, robust and unified method for mapping complex traits (III): combined linkage/linkage-disequilibrium analysis.

Extending the method for linkage analysis [Zhao et al., 1998a: Am. J. Med. Genet. 77:366-383; 1998b: Am. J. Med. Genet. 79:49-61], this article describes a method for the linkage-disequilibrium analysis, and for combining linkage and linkage-disequilibrium analyses. As highly dense markers are increasingly used in genome scans, one or more markers are not only linked with the disease genes if they exist, but also likely in linkage-disequilibrium with those putative genes. Hence, linkage-disequilibrium analysis potentially offers additional information about positions of putative disease genes. Combining both linkage and linkage-disequilibrium signals, this approach is able to improve positional signals. As before, the proposed method is a model-based approach, but semiparametric via the estimating equation technique. Under the assumptions of penetrance and allele frequency, this method efficiently estimates recombination fractions for linkage analysis and odds ratios for linkage-disequilibrium analysis. As described in two previous papers, this method is relatively more robust than the lod score methods, since it requires weaker assumption than conditional independence. While the estimated recombination fractions are used for inference as part of linkage analysis, the estimated odds ratios are used for linkage-disequilibrium inference and combined linkage, and linkage-disequilibrium parameters can be used to test combined linkage/linkage-disequilibrium analysis. This approach has been implemented, named gSCAN, and its compiled version is available for trial on request via the web site (http:/lynx.fhcrc.org/qge). We applied this new approach to affected sib-pair data collected for the genome scan to localize type 1 diabetes genes. Under an assumed autosomal dominant gene model, the linkage analysis confirms an earlier suggestion of one major gene around D6S281. Interestingly, the linkage-disequilibrium analysis suggests several additional signals around D6S250, GATA30, D6S311, D6S441, D6S442, D6S415, D6S411, D6S305, and a290xh9. The linkage analysis, on the other hand, suggests a signal around D6S281, while providing supporting evidence for several other marker loci. However, the combined analysis did not provide strong support for any of the findings, implying that linkage and linkage-disequilibrium findings are not consistent.

Alleles↗
PubMed1998

An efficient, robust, and unified method for mapping complex traits (II): multipoint linkage analysis.

Extending the method for two-point linkage analysis [Zhao et al., 1998: Am J Med Genet 77:366-383], this paper introduces a semiparametric method for multipoint linkage analysis, expected to gain efficiency by using multiple markers simultaneously. Overcoming the longstanding statistical and computational challenge to the parametric approaches (or lod score methods) for multipoint linkage analysis, this semiparametric approach, based on the estimating equation technique, yields statistically efficient and yet robust estimates and enjoys the computational efficiency in processing multiple markers from large pedigrees. Its computational burden increases linearly with the sizes of pedigrees and with the number of marker loci. To illustrate this semiparametric method, we apply it to marker data gathered for the Breast Cancer Consortium. The result supports the earlier finding of the positive linkage with BRCA1 and has also shown that the multipoint linkage analysis has an improved power. In addition, we have applied this method to analyze genome scanning data that have been used to localize genes responsible for type 1 diabetes. In support of the earlier findings, the genome scanning detects the linkage signals on chromosome 6 but does not support the earlier suggestions of two major genes in that genome segment. Through sensitivity analysis, it appears that the results are robust to misspecification of penetrance and allele frequency.

Automation↗
PubMed1998

Efficient, robust, and unified method for mapping complex traits (I): two-point linkage analysis.

The completion of a preliminary human genome map and development of molecular methods have enabled researchers to assay a large number of polymorphic markers that are evenly spaced along the entire human genome. Among many applications, marker data are valuable for mapping complex traits through linkage or linkage-disequilibrium analysis, the former of which is the focus of this paper, the first in a series on this subject. Formalizing the concept and computation for linkage analysis, Elston and Stewart [1971; Human Heredity 21:523-542] introduced a likelihood function to capture relevant genetic information and a recursive algorithm for computing the likelihood function. However, the computing burden is prohibitive in processing complex pedigrees. Since that fundamental development, improving the computational algorithm and extending the method has been a dynamic area of research. The primary objective of this communication is to introduce a semiparametric method for linkage analysis. It is a particularly suitable approach with desirable properties for mapping complex traits that may be binary, continuous, and partially observed (i.e., censored). It incorporates candidate genes, environmental factors, and their interactions with the putative gene and is expected to be robust and efficient in comparison with likelihood-based methods. The properties of the estimates have been studied in finite samples with a limited simulation study. This method is illustrated with an application to family data contributed to the Breast Cancer Consortium.

Algorithms↗
PubMed1998

Mapping of complex traits by single-nucleotide polymorphisms.

Molecular geneticists are developing the third-generation human genome map with single-nucleotide polymorphisms (SNPs), which can be assayed via chip-based microarrays. One use of these SNP markers is the ability to locate loci that may be responsible for complex traits, via linkage/linkage-disequilibrium analysis. In this communication, we describe a semiparametric method for combined linkage/linkage-disequilibrium analysis using SNP markers. Asymptotic results are obtained for the estimated parameters, and the finite-sample properties are evaluated via a simulation study. We also applied this technique to a simulated genome-scan experiment for mapping a complex trait with two major genes. This experiment shows that separate linkage and linkage-disequilibrium analyses correctly detected the signals of both major genes; but the rates of false-positive signals seem high. When linkage and linkage-disequilibrium signals were combined, the analysis yielded much stronger and clearer signals for the presence of two major genes than did two separate analyses.

Biosensing Techniques↗
PubMed1997

A population-based family study (II): Segregation analysis.

We used segregation analysis to investigate the genetic etiology of the disease in Problem 2A. Under the assumption of a dominant major gene, our analysis suggests a major gene with relative risk of 58 and an allele frequency of 0.013. Under an additive gene assumption, it appears that there may be two genes with relative risks of 39 and 17 and allele frequencies of 0.015 and 0.075, respectively.

Case-Control Studies↗
PubMed1996

Family history and risk of colorectal cancer in the multiethnic population of Hawaii.

Increased risk of colorectal cancer in individuals with family history of the disease has been observed consistently in past studies. However, limited attention has been given to the influence of ethnicity, the characteristics of the proband's tumor, and kinship. A population-based case-control study was conducted between 1987 and 1991 in Hawaii among 1,192 incident colorectal cancer cases and 1,192 sex-, age-, and ethnicity-matched population controls. The study identified 7,673 relatives for the cases and 7,823 relatives for the controls. With an estimating equation-based regression method, relatives of cases were found to have a 2.5-fold increased risk of colorectal cancer compared with relatives of controls (95% confidence interval (CI) 1.8-3.4) after adjustment for covariates. This increase in risk was greater for Japanese (odds ratio (OR) = 3.0, 95% CI 1.7-5.4) than Caucasians (OR = 1.8, 95% CI 1.2-2.9), for siblings (OR = 3.1, 95% CI 2.1-4.6) than parents (OR = 2.0, 95% CI 1.1-3.1), and when the index patient was diagnosed before the age of 55 years (OR = 4.1, 95% CI 2.1-8.0) with multiple tumors (OR = 9.5, 95% CI 4.4-20.6), with a distant stage (OR = 4.6, 95% CI 2.7-7.8), or with cancer of the right colon (OR = 3.0, 95% CI 2.0-4.4) or the rectum (OR = 3.0, 95% CI 1.8-4.8). The increase in risk was not affected by the relative's sex. Relatives of cases were not at increased risk for other common cancers. It is estimated that approximately 11.1% and 6.5% of colorectal cancers are attributable to a first degree family history of the disease for Japanese and Caucasians, respectively. These data and those of previous studies strongly suggest that individuals with a family history of colorectal cancer in a first degree relative are at increased risk for the disease and should receive regular diagnostic screening. Characteristics of the index case, such as age and stage at diagnosis, subsite and number of tumors, and race, as well as kinship, may be important in assessing the colorectal cancer risk of a relative.

Aged↗
PubMed1993

Evaluation of the sampling plan used in collecting data for a study of LDL subclass pattern.

The genetic epidemiologic study of coronary heart disease conducted by a group in the Donner Laboratory used survey and ad hoc sampling plans, resulting in a random and an ad hoc sample of families, respectively. These two samples were used to evaluate the ad hoc sampling plan used in that study. Following the description of data collection, we adjusted for ascertainment, but still found that the aggregation patterns of many lipoproteins in the ad hoc sample were different from those in the random sample.

Adult↗
PubMed1992

A method for assessing patterns of familial resemblance in complex human pedigrees, with an application to the nevus-count data in Utah kindreds.

An analytic method is described for estimating phenotypic correlations between pairs of members of specific relationships in pedigrees. In estimating correlations, this new method allows simultaneous adjustment for available covariates such as age, gender, environmental factors, and variables reflecting ascertainment mode, through mean- and variance-regression models. The estimated correlations and regression coefficients corresponding to covariates are consistent and asymptotically normally distributed. Differing from a full-likelihood approach, this new method does not require the assumption of a particular joint distribution of phenotypes from a pedigree, such as the multivariate normal distribution, but instead only requires correct specification of mean- and variance-regression models. Within this framework, missing data, if they are missing completely at random, can be ignored without biasing estimates. The method is illustrated by an application using nevus-count data from 28 Utah kinships. The results from the analysis are that covariate-adjusted nevus counts are correlated between parents and children (correlation .22; P less than .001) and between siblings (correlation .32; P less than .001), while the correlation of -.04 between husband and wife is not significantly different (P = .31) from 0. This result is consistent with a genetic etiology of nevus count.

Dysplastic Nevus Syndrome↗