Abstract: Risk assessment and diagnosis of a complex disorder often requires measuring an underlying quantitative phenotype. Association studies in unrelated populations can implicate genetic factors contributing to disease risk, and experiments using pooled DNA provide a less costly but necessarily less powerful alternative to methods based on individual genotyping. Although the sample sizes required for pooling and individual genotyping studies have been compared in certain instances, general results have not been reported in the context of association studies, nor have there been clear comparisons of pooling based on quantitative and qualitative (affected/unaffected) phenotypes. Here we use exact numerical calculations and analytical approximations to examine the sample size requirements of association tests for quantitative traits and affected-unaffected studies using pooled DNA.

Abstract: The invention relates to a system and methods for detecting an association in a population of individuals between a genetic locus or loci and a quantitative phenotype. In particular, the present invention relates to family based tests of association using pooled DNA. Disclosed are systems and methods for optimizing pooled tests as an explicit function of measurement error, and for family-based tests that eliminate stratification effects. Also disclosed are modules for identifying functional genetic variants and linked markers using systems and methods that are feasible with current-day instruments.

Abstract: The invention relates to systems and methods for detecting nucleic acid molecule encoding GENE-X having nucleotide polymorphisms indicative of increased risk for DISEASE-X. The invention also relates to a method for identifying individuals who are carriers of the genetic risk factor or are at increased risk. The method includes obtaining a biological sample from an individual and testing the individual for the nucleotide polymorphism, wherein the disease risk may increase with the expression of ALLELE-X.

Abstract: While SNP-based marker sets and population-level DNA repositories are approaching sufficient size for whole-genome association studies, individual genotyping remains very costly. Pooled DNA tests are a less costly alternative, but uncertainty about loss of power due to allele frequency measurement error and population stratification hinder their use. Here we describe how to optimize pooled tests as an explicit function of measurement error, and we present family-based tests that eliminate stratification effects. We show that identification of functional genetic variants and linked markers may be feasible with current-day instruments.

Abstract: Identifying the genetic determinants for disease and disease predisposition remains one of the outstanding goals of the human genome project. When large patient populations are available, genetic approaches using single nucleotide polymorphism markers have the potential to identify relevant genes directly. While individual genotyping is the most powerful method for establishing association, determining allele frequencies in DNA pooled on the basis of phenotypic value can also reveal association at a much-reduced cost. Here we analyze pooling methods to establish association between a genetic polymorphism and a quantitative phenotype. Exact results are provided for the statistical power for a number of pooling designs where the phenotype is described by a variance components model and the fraction of the population pooled is optimized to minimize the population requirements.

Abstract: Identifying the genetic components of complex diseases is one of the most important goals of the human genome project. These diseases and their underlying risk factors are often better described by quantitative phenotypes than by an arbitrary distinction between affected and unaffected individuals. Association studies are able to identify genetic loci contributing to these quantitative trait loci directly at the cost of requiring large population sizes. Studies of sib pair populations have been suggested to increase power when populations are stratified, and tests on pooled DNA may reduce the experimental burden, but these approaches have been analyzed primarily in the context of affected/unaffected disease phenotypes. Disclosed herein are efficient methods for QTL mapping using DNA pooled from sib pairs. A preferred test using a single set of pools is to select unrelated sibs with extreme phenotypic values, requiring a population size approximately 1.5× larger than for individual genotyping.

Abstract: Risk assessment and diagnosis of a complex disorder often requires measuring an underlying quantitative phenotype. Association studies in unrelated populations can implicate genetic factors contributing to disease risk, and experiments using pooled DNA provide a less costly but necessarily less powerful alternative to methods based on individual genotyping. Although the sample sizes required for pooling and individual genotyping studies have been compared in certain instances, general results have not been reported in the context of association studies, nor have there been clear comparisons of pooling based on quantitative and qualitative (affected/unaffected) phenotypes. Here we use exact numerical calculations and analytical approximations to examine the sample size requirements of association tests for quantitative traits and affected-unaffected studies using pooled DNA.