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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