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International Biometric Society ALTERNATIVE TESTS FOR GENETIC ASSOCIATION ON TRIO STUDIES Maria J Batista1, Debashree Ray2, Suely Giolo3, Alexandre Pereira4, Mariza de Andrade5, Júlia Soler6 1 Federal University of Ceara, Brazil, 2University of Minnesota, USA, 3Federal University of Parana, Brazil, 4Heart Institute, University of Sao Paulo, Brazil, 5Mayo Clinic, USA, 6 University of Sao Paulo, Brazil . Trio designs (father, mother and son/daughter) are useful for association and/or linkage between diseases and genetic variants for complex and rare early-onset diseases such as Alzheimer, schizophrenia and autism. Transmission Disequilibrium Test (TDT) is commonly used to test association in trio studies and is equivalent to McNemar test for 2 × 2 contingency tables, which summarize transmitted and no transmitted alleles from heterozygous parents. Many extensions of TDT have been proposed in the literature, for instance, the genotypic TDT (gTDT) based on exact and asymptotic likelihood methods assuming specific genetic mode of inheritance, additive, dominant, or recessive (Schaid, 1999), exact closed-form solutions for gTDT (Schwender et al., 2012), and an asymptotic interval mapping procedure using TDT extensions based on the symmetry tests in 4 x 4 contingency tables built from haplotypes defined by a pair of flanking markers around the putative disease genes (Narain, 2007). In this work, we extended the results by Narain (2007) and obtained exact solutions appropriated to analyze sparse tables (with cells of low counts) common in interval haplotype analysis. Furthermore, considering paired data we used conditional logistic regression models incorporate covariates in the association analysis such as offspring sex, parents age and specific characteristics of each parental chromosome (e.g., its size). We applied the proposed methods in a Brazilian population consisting of 71 trios of healthy parents and offspring with a congenital heart disease with genotype data available from Affymetrix 6.0 SNP array. The analyses were run using PLINK and R. Our results showed that our method compared to unilocus analysis is more flexible when dealing with sparse tables and correcting for false discoveries. International Biometric Conference, Florence, ITALY, 6 – 11 July 2014