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PubMed2003

A general class of association tests for family-based data using weight functions.

Based on the symmetry of transmitted/nontransmitted alleles from heterozygous parents under the null hypothesis of no association, the work proposed here establishes a general statistical framework for constructing association tests with data from nuclear families with multiple affected children. A class of association tests is proposed for both diallelic and multiallelic markers. The proposed test statistics reduce to the transmission disequilibrium test for trios, to T(su) by Martin et al. ([1997] Am. J. Hum. Genet. 61:439-448) for affected sib pairs, and to the pedigree disequilibrium test by Martin et al. ([2000] Am. J. Hum. Genet. 67:146-154); [2001] Am. J. Hum. Genet. 68:1065-1067) when using affected sibships only. The association test used in simulation and for real data (sitosterolemia) is the one which has the best overall power in detecting association. This association test is generally more powerful than the association tests proposed by Martin et al. ([2000] Am. J. Hum. Genet. 67:146-154); [2001] Am. J. Hum. Genet. 68:1065-1067) when using only affected sibships. For the sitosterolemia data set, the association test has its most significant result (P-value=0.0012) for the marker locus on the same bacterial artificial chromosome as the disease locus.

Alleles↗
PubMed2005

Association testing with Mendel.

This report presents an overview of association testing strategies from a user's perspective, with particular attention to the capabilities of the computer program Mendel. Association testing is driven by the nature of the study sample, the nature of the disease trait, and the kind of markers employed. The practicing statistician must also choose whether to conduct parametric or nonparametric tests. Because of the complexities involved, Mendel offers users several analysis options. The different options are tied together by shared input and output conventions and a shared language for defining models. Mendel also features new statistics and theory found in no other genetics software. The most important innovations include: association testing by penetrance estimation, expansion of matched-pair designs to permutation unit designs, and a rigorous implementation of the measured genotype approach for quantitative trait loci. This report explains how Mendel imputes allele counts and conducts both asymptotic and permutation tests in the measured genotype framework.

Analysis of Variance↗
PubMed1997

Expanded norms for the Controlled Oral Word Association Test.

The Controlled Oral Word Association Test (COWAT) is a measure of a person's ability to make verbal associations to specified letters (i.e., C, F, and L). This measure is a useful component of a neuropsychological battery as it is able to detect changes in word association fluency often found with various disorders. In order to generate current norms for the elderly and aid in interpreting their performance, the COWAT was administered to a group of community-dwelling elderly persons. Information regarding total numbers of words produced as well as frequency of perseverations, breaking set, using the same word stem, and using a proper noun is provided.

Age Factors↗
PubMed2003

Genetic association tests for family data with missing parental genotypes: a comparison.

We consider three tests for genetic association in data from nuclear families (the Family-Based Association Test (FBAT) test proposed by Rabinowitz and Laird ([2000] Hum. Hered. 50:211-223), a second test proposed by Rabinowitz ([2002] J. Am. Stat. Assoc. 97:742-758), and the Family Genotype Analysis Program (FGAP) nonfounder or partial score test proposed by Clayton ([1999] Am. J. Hum. Genet. 65:1170-1177) and Whittemore and Tu ([2000] Am. J. Hum. Genet. 66:1329-1340)). We show that each test statistic arises from the efficient score of the family data as the solution to a set of constraints on its null expectation. Moreover, the FBAT and Rabinowitz tests (but not the FGAP test) are locally the most powerful among all tests satisfying their constraints. We used simulations to examine how the three tests perform in situations when their assumptions are violated and the number of families is not huge. We found that the FBAT test tended to have less power than the other two tests, particularly when applied to families in whom all offspring were affected. The Rabinowitz and FGAP tests performed similarly, although the latter tended to extract more information from families containing one typed parent. While none of the tests showed good power to detect rare, recessively acting genes, the Rabinowitz test with a sample variance estimate performed particularly poorly in this case. However, the Rabinowitz test with a model-based variance had power comparable to that of the FGAP test, and more accurate type I error rates. We conclude that for the situations we considered, the Rabinowitz test with model-based variance has good power without forfeiting robustness against misspecification of parental genotype probabilities. However, its utility is limited by the lack of a simple algorithm to apply it to families with varying structures and phenotypes.

Family↗
PubMed1997

Genotype relative-risks and association tests for nuclear families with missing parental data.

The development of a new method for testing the association of genetic markers with disease is presented. This approach is applicable when sampling nuclear families with one or more affected siblings and when neither, one, or both parents are missing marker genotype data. All siblings, affected and not affected, are used to probabilistically infer the missing parental marker data. A likelihood ratio statistic, which treats marker allele frequencies as nuisance parameters, is presented to test whether all marker relative risks are equal to one (i.e., no marker association). This approach offers a solution to test for marker associations when parents are difficult to obtain.

Algorithms↗
PubMed2006

Clustering of haplotypes based on phylogeny: how good a strategy for association testing?

Haplotypes are now widely used in association studies between markers and disease susceptibility locus. However, when a large number of markers are considered, the number of possible haplotypes increases leading to two problems: an increased number of degrees of freedom that may result in a lack of power and the existence of rare haplotypes that may be difficult to take into account in the statistical analysis. In a recent paper, Durrant et al proposed a method, CLADHC, to group haplotypes based on distance matrices and showed that this could considerably increase the power of the association test as compared to either single-locus analysis or haplotype analysis without prior grouping. Although the authors considered different one-disease-locus susceptibility models in their simulations, they did not study the impact of the linkage disequilibrium (LD) pattern and of the susceptibility allele frequency on their conclusions. Here, we show, using haplotype data from five regions of the genome of different lengths and with different LD patterns, that, when a single disease susceptibility locus is simulated, the prior grouping of haplotypes based on the algorithm of Durrant et al does not increase the power of association testing except in very particular situations of LD patterns and allele frequencies.

Computer Simulation↗
PubMed2001

The family based association test method: strategies for studying general genotype--phenotype associations.

With possibly incomplete nuclear families, the family based association test (FBAT) method allows one to evaluate any test statistic that can be expressed as the sum of products (covariance) between an arbitrary function of an offspring's genotype with an arbitrary function of the offspring's phenotype. We derive expressions needed to calculate the mean and variance of these test statistics under the null hypothesis of no linkage. To give some guidance on using the FBAT method, we present three simple data analysis strategies for different phenotypes: dichotomous (affection status), quantitative and censored (eg, the age of onset). We illustrate the approach by applying it to candidate gene data of the NIMH Alzheimer Disease Initiative. We show that the RC-TDT is equivalent to a special case of the FBAT method. This result allows us to generalise the RC-TDT to dominant, recessive and multi-allelic marker codings. Simulations compare the resulting FBAT tests to the RC-TDT and the S-TDT. The FBAT software is freely available.

Alzheimer Disease↗
PubMed2002

Robust TDT-type candidate-gene association tests.

In studies of association between genetic markers and a disease, the transmission disequilibrium test (TDT) has become a standard procedure. It was introduced originally as a test for linkage in the presence of association and can be used as a test for association under appropriate assumptions. The power of the TDT test for association between a candidate gene and disease depends on the underlying genetic model and the TDT is the optimal test if the additive model holds. Related methods have been obtained for a given mode of inheritance (e.g. dominant or recessive). Quite often, however, the true model is unknown and selection of a single method of analysis is problematic, since use of a test optimal for one genetic model usually leads to a substantial loss of power if another genetic model is the true one. The general approach of efficiency robustness has suggested two types of robust procedures, which we apply to TDT-type association tests. When the plausible range of alternative models is wide (e.g. dominant through recessive) our results indicate that the maximum (MAX) of several test statistics, each of which is optimal for quite different models, has good power under all genetic models. In situations where the set of possible models can be narrowed (e.g. dominant through additive) a simple linear combination also performs well. In general, the MAX has better power properties than the TDT for the study of candidate genes when the mode of inheritance is unknown.

Alleles↗
PubMed2004

Is the implicit association test immune to faking?

One of the main advantages of measures of automatic cognition is supposed to be that they are less susceptible to faking than explicit tests. It is an empirical question, however, to what degree these measures can be faked, and the response might well differ for different measures. We tested whether the Implicit Association Test (IAT, Greenwald, McGhee, & Schwartz, 1998) cannot be faked as easily as explicit measures of the same constructs. We chose the Big-Five dimensions conscientiousness and extraversion as the constructs of interest. The results show, indeed, that the IAT is much less susceptible to faking than questionnaire measures are, even if no selective faking of single dimensions of the questionnaire occurred. However, given limited experience, scores on the IAT, too, are susceptible to faking.

Automatism↗
PubMed2002

Predictive validity of an Implicit Association Test for assessing anxiety.

The Implicit Association Test (IAT) was adapted to measure anxiety by assessing associations of self (vs. other) with anxiety-related (vs. calmness-related) words. Study 1 showed that the IAT-Anxiety exhibited good internal consistency and adequate stability. Study 2 revealed that the IAT-Anxiety was unaffected by a faking instruction. Study 3 examined the predictive validity of implicit and explicit measures and showed that the IAT-Anxiety was related to changes in experimenter-rated anxiety and performance decrements after failure. Study 4 found that several behavioral indicators of anxiety during a stressful speech were predicted by the IAT. Taken together, these studies show that the IAT-Anxiety is a reliable measure that is able to predict criterion variables above questionnaire measures of anxiety and social desirability.

Adult↗
PubMed1991

The morphometric histopathology of undescended testes and testes associated with incarcerated inguinal hernia: a comparative study.

The underlying injury to undescended testes may be hormonal, a transient perinatal form fruste of hypogonadotropic hypogonadism characterized by blunting of the surge in gonadotropins normally seen at age 60 to 90 days. Ischemia is the underlying injury to testes associated with incarcerated inguinal hernias. To determine if the histopathology of these 2 injuries is different histomorphometric analyses were performed on semithin microscopic sections of biopsies of 21 control testes, 17 undescended testes and 13 intrascrotal testes associated with incarcerated inguinal hernias. The infants in all groups were 30 to 120 days old. The results showed that, as in previous studies, undescended testes at this age are characterized by hypoplasia of Leydig cells, normal germ cell counts and defective maturation of gonocytes into adult dark spermatogonia. In contrast, testes associated with incarcerated inguinal hernias were characterized by hyperplasia of Leydig cells, reduced germ cell counts and normal maturation of gonocytes into adult dark spermatogonia. One might conclude that the underlying injury of undescended testes, presumably the blunted surge of gonadotropins, causes a primary hypoplasia and hypofunction of Leydig cells, which in turn causes a secondary defect in transformation of gonocytes into spermatogonia. In contrast, ischemia may primarily cause a tubular epithelial lesion leaving the hypothalamic-pituitary-gonadal axis intact and allowing normal transformation of gonocytes into spermatogonia. Reduced gonadotropins and ischemia appear to produce distinctly different primary and secondary pathophysiological effects on the testes.

Biopsy↗
PubMed2007

Interpretation of simultaneous linkage and family-based association tests in genome screens.

Linkage and association analyses have played important roles in identifying susceptibility genes for complex diseases. Linkage tests and family-based tests of association are often applied in the same data to help fine-map disease loci or validate results. This paradigm increases efficiency by making maximal use of family data sets. However, it is not intuitively clear under what conditions association and linkage tests performed in the same data set may be correlated. Understanding this relationship is important for interpreting the combined results of both tests. We used computer simulations and theoretical statements to estimate the correlation between linkage statistics (affected sib pair maximum LOD scores) and family-based association statistics (pedigree disequilibrium test (PDT) and association in the pressure of linkage (APL)) under various hypotheses. Different types of pedigrees were studied: nuclear families with affected sib pairs, extended pedigrees and incomplete pedigrees. Both simulation and theoretical results showed that when there is no linkage or no association, the linkage and association tests are not correlated. When there is linkage and association in the data, the two tests have a positive correlation. We concluded that when linkage and association tests are applied in the same data, the type I error rate of neither test will be affected and that power can be increased by applying tests conditionally.

Alleles↗
PubMed2005

Genomic screening in family-based association testing.

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p = 0.004) and ttth1-ttth4 (p = 0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association.

Family↗
PubMed2006

The single category implicit association test as a measure of implicit social cognition.

The Single Category Implicit Association Test (SC-IAT) is a modification of the Implicit Association Test that measures the strength of evaluative associations with a single attitude object. Across 3 different attitude domains--soda brand preferences, self-esteem, and racial attitudes--the authors found evidence that the SC-IAT is internally consistent and makes unique contributions in the ability to understand implicit social cognition. In a 4th study, the authors investigated the susceptibility of the SC-IAT to faking or self-presentational concerns. Once participants with high error rates were removed, no significant self-presentation effect was observed. These results provide initial evidence for the reliability and validity of the SC-IAT as an individual difference measure of implicit social cognition.

Adolescent↗
PubMed2006

Compelled to consume: the Implicit Association Test and automatic alcohol motivation.

The Implicit Association Test (IAT; A. G. Greenwald, D. E. McGhee, & J. L. K. Schwartz, 1998) has recently been used to assess the role of alcohol-affect associations in drinking behavior. The current study examined the validity of an alcohol IAT with 88 hazardous-drinking college students who completed measures of drinking behavior, an explicit measure of alcohol motivation, and an IAT that assessed alcohol-motivation associations. Regression analyses indicated that IAT scores correlated with binge drinking and cue reactivity, replicating T. P. Palfai and B. D. Ostafin's (2003) results. Results also indicated convergent validity (the IAT was related to an explicit measure of alcohol motivation) and incremental validity (IAT scores were correlated with alcohol behavior after controlling for the explicit measure). Implications for understanding the self-regulation of drinking are discussed.

Adolescent↗
PubMed2006

An efficient family-based association test using multiple markers.

In genetic association studies, multiple markers are usually employed to cover a genomic region of interest for localizing a trait locus. In this report, we propose a novel multi-marker family-based association test (T(LC)) that linearly combines the single-marker test statistics using data-driven weights. We examine the type-I error rate in a numerical study and compare its power to identify a common trait locus using tag single nucleotide polymorphisms (SNPs) within the same haplotype block that the trait locus resides with three competing tests including a global haplotype test (T(H)), a multi-marker test similar to the Hotelling-T(2) test for the population-based data (T(MM)), and a single-marker test with Bonferroni's correction for multiple testing (T(B)). The type-I error rate of T(LC) is well maintained in our numeric study. In all the scenarios we examined, T(LC) is the most powerful, followed by T(B). T(MM) and T(H) are the poorest. T(H) and T(MM) have essentially the same power when parents are available. However, when both parents are missing, T(MM) is substantially more powerful than T(H). We also apply this new test on a data set from a previous association study on nicotine dependence.

Family↗
PubMed1992

[Perception of odor quality by Free Image-Association Test].

A method was devised for evaluating odor quality. Subjects were requested to freely describe the images elicited by smelling odors. This test was named the "Free Image-Association Test (FIT)". The test was applied for 20 flavors of various foods, five odors from the standards of T&T olfactometer (Japanese standard olfactory test), butter of yak milk, and incense from Lamaism temples. The words for expressing imagery were analyzed by multidimensional scaling and cluster analysis. Seven clusters of odors were obtained. The feature of these clusters were quite similar to that of primary odors which have been suggested by previous studies. However, the clustering of odors can not be explained on the basis of the primary-odor theory, but the information processing theory originally proposed by Miller (1956). These results support the usefulness of the Free Image-Association Test for investigating odor perception based on the images associated with odors.

Adult↗
PubMed2005

Assessing implicit alcohol associations with the Implicit Association Test: fact or artifact?

Studies using bipolar Implicit Association Tests (IATs) found that heavy drinkers have negative and arousal associations with alcohol relative to soda. Study 1 examined whether these results were due to the label 'alcohol' and the choice of the contrast category 'soda'. Four unipolar IATs assessed alcohol associations with positive and negative valence, arousal, and sedation, while varying the target dimension: alcohol or beer versus soda or animals. Results showed that drinkers had the strongest associations between alcohol and negative valence with the exact strength depending on the choice of the target categories. They also showed associations between alcohol and positive valence, arousal, and to a lesser extent sedation, which were uninfluenced by composition of the target dimension. These findings indicate ambivalence in both the valence and arousal-sedation dimension, underscoring the importance of using unipolar alcohol-IATs. Further, study 2 showed that "figure-ground" asymmetries could not account for these IAT results. These findings provide support that implicit alcohol associations are not merely IAT artifacts and that they can be assessed in a meaningful way with unipolar IATs.

Adult↗