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PubMed2006

Approaches to handling incomplete data in family-based association testing.

The high throughput of data arising from the complete sequence of the human genome has left statistical geneticists with a rich and extensive information source. The wide availability of software and the increase in computing power has improved the possibilities to access and process such data. One problem is incompleteness of the data: unobserved or partially observed data points due to technical reasons or reasons associated with the patient's status or erroneous measurements of phenotype or genotype, to name a few. When not properly accounted for, these sources of incompleteness may seriously jeopardize the credibility of results from analyses. In this paper we provide some perspectives on the occurrence and analysis of different forms of incomplete data in family-based genetic association testing.

Data Interpretation, Statistical↗
PubMed2005

A meta-analysis on the correlation between the implicit association test and explicit self-report measures.

Theoretically, low correlations between implicit and explicit measures can be due to (a) motivational biases in explicit self reports, (b) lack of introspective access to implicitly assessed representations, (c) factors influencing the retrieval of information from memory, (d) method-related characteristics of the two measures, or (e) complete independence of the underlying constructs. The present study addressed these questions from a meta-analytic perspective, investigating the correlation between the Implicit Association Test (IAT) and explicit self-report measures. Based on a sample of 126 studies, the mean effect size was .24, with approximately half of the variability across correlations attributable to moderator variables. Correlations systematically increased as a function of (a) increasing spontaneity of self-reports and (b) increasing conceptual correspondence between measures. These results suggest that implicit and explicit measures are generally related but that higher order inferences and lack of conceptual correspondence can reduce the influence of automatic associations on explicit self-reports.

Association↗
PubMed2006

Avian diversity and West Nile virus: testing associations between biodiversity and infectious disease risk.

The emergence of several high profile infectious diseases in recent years has focused attention on our need to understand the ecological factors contributing to the spread of infectious diseases. West Nile virus (WNV) is a mosquito-borne zoonotic disease that was first detected in the United States in 1999. The factors accounting for variation in the prevalence of WNV are poorly understood, but recentideas suggesting links between high biodiversity and reduced vector-borne disease risk may help account for distribution patterns of this disease. Since wild birds are the primary reservoir hosts for WNV, we tested associations between passerine (Passeriform) bird diversity, non-passerine (all other orders) bird diversity and virus infection rates in mosquitoes and humans to examine the extent to which bird diversity is associated with WNV infection risk. We found t h at non-passerine species richness (number of non-passerine species) was significantly negatively correlated with both mosquito and human infection rates, whereas there was no significant association between passerine species richness and any measure of infection risk. Our findings suggest that non-passerine diversity may play a role in dampening WNV amplification rates in mosquitoes, minimizing human disease risk.

Animals↗
PubMed2004

Association test algorithm between a qualitative phenotype and a haplotype or haplotype set using simultaneous estimation of haplotype frequencies, diplotype configurations and diplotype-based penetrances.

Analysis of the association between haplotypes and phenotypes is becoming increasingly important. We have devised an expectation-maximization (EM)-based algorithm to test the association between a phenotype and a haplotype or a haplotype set and to estimate diplotype-based penetrance using individual genotype and phenotype data from cohort studies and clinical trials. The algorithm estimates, in addition to haplotype frequencies, penetrances for subjects with a given haplotype and those without it (dominant mode). Relative risk can thus also be estimated. In the dominant mode, the maximum likelihood under the assumption of no association between the phenotype and presence of the haplotype (L(0max)) and the maximum likelihood under the assumption of association (L(max)) were calculated. The statistic -2 log(L(0max)/L(max)) was used to test the association. The present algorithm along with the analyses in recessive and genotype modes was implemented in the computer program PENHAPLO. Results of analysis of simulated data indicated that the test had considerable power under certain conditions. Analyses of two real data sets from cohort studies, one concerning the MTHFR gene and the other the NAT2 gene, revealed significant associations between the presence of haplotypes and occurrence of side effects. Our algorithm may be especially useful for analyzing data concerning the association between genetic information and individual responses to drugs.

Algorithms↗
PubMed1998

A method for testing association patterns of social animals.

Association indices were originally developed to describe species co-occurrences, but have been used increasingly to measure associations between individuals. However, no statistical method has been published that allows one to test the extent to which the observed association index values differ from those of a randomly associating population. Here, we describe an adaptation of a test developed by Manly (1995, Ecology, 76, 1109-1115), which uses the observed association data as a basis for a computer-generated randomization. The observed pattern of association is tested against a randomly created one while retaining important features of the original data, for example group size and sighting frequency. We applied this new method to test four data sets of associations from two populations of Hector's dolphin, Cephalorhynchus hectori, using the Half-Weight Index (HWI) as an example of a measure of association. The test demonstrated that populations with similar median HWI values showed clear differences in association patterns, that is, some were associating nonrandomly whereas others were not. These results highlight the benefits of using this new testing method in order to validate the analysis of association indices. Copyright 1998 The Association for the Study of Animal Behaviour.

Journal Article↗
PubMed1992

Empirical Bayes methods for testing associations with large numbers of candidate genes in the presence of environmental risk factors, with applications to HLA associations in IDDM.

Standard regression models for disease incidence data can be used to test for associations between a disease and measured genetic and environmental factors and their interactions. Complications arise when the gene is not observed, requiring segregation and linkage analysis approaches, or when the candidate gene(s) are found to be highly polymorphic, as in the HLA region. We propose a Bayesian approach to the latter problem, in which the log relative risks for all alleles at a given locus are taken to be independent and exchangeable, assuming there is no preferential zygotic assortment and negligible recombination. Multi-locus problems can be addressed either by adding exchangeable interaction terms or by adopting a multivariate prior for haplotype effects. Some simulations based on our current work on family studies of IDDM are discussed.

Alleles↗
PubMed1999

Association tests using unaffected-sibling versus pseudo-sibling controls.

We used family-matched case-control data to screen the genome for markers associated with disease in the simulated data set. Two different types of controls were considered: (1) unaffected siblings and (2) 'pseudo siblings,' a comparison sample created using the parental alleles. The scans were conducted on the first replicate of each study population. Overall, the two methods identified 14 marker loci associated with disease at the 0.001 significance level. Marker D1G24 (locus D) was the only true disease locus found by both approaches. No associations were found at any of the markers flanking the unobserved disease susceptibility loci (A, B, or C). We subsequently pooled the 25 replicates from a single population. This large sample still did not yield any associations at the flanking markers. We tested for association at locus D using a pseudo-sib approach restricted to alleles shared identical by descent between affected sib pairs. The power was 44% (11/25 replicates) at a significance level of 0.001.

Alleles↗
PubMed2006

Relaxing haplotype block models for association testing.

The arrival of publicly available genome-wide variation data is creating new opportunities for reconciling model-based methods for associating genotypes and phenotypes with the complexities of real genome data. Such data is particularly valuable for testing the utility of models of conserved haplotype structure to association studies. While there is much interest in "haplotype block" models that assume population-wide regions of low diversity, there is also evidence that such models eliminate correlations potentially useful to association studies. We investigate the value of relaxing the rigidity of block models by developing an association testing method using the previously developed "haplotype motif" model, which retains the notion of representing haploid sequences as concatenations of conserved haplotypes but abandons the assumption of population-wide block boundaries. We compare the effectiveness of motif, block, and single-variant models at finding association with simulated phenotypes using real and simulated data. We conclude that the benefits of haplotype models in any form are modest, but that haplotype models in general and block-free models in particular are useful in picking up correlations near the boundaries of the detectable level.

Chromosomes, Human, Pair 22↗
PubMed2006

Association testing of the positional and functional candidate gene SLC1A1/EAAC1 in early-onset obsessive-compulsive disorder.

CONTEXT: The first 2 independent linkage studies for obsessive-compulsive disorder (OCD) identified a region on 9p24 with suggestive evidence for linkage. The glutamate transporter gene solute carrier family 1, member 1 (SLC1A1) is a promising functional candidate in this region because altered glutamatergic concentrations have been found in the striatum and anterior cingulate in neuroimaging studies of pediatric OCD. OBJECTIVE: To determine whether genotypes at polymorphisms in the SLC1A1 gene region are associated with early-onset OCD. DESIGN: Family-based analysis of association using the transmission disequilibrium test, confirmed using the family-based association test. SETTING: Anxiety disorders program in an academic medical center. PARTICIPANTS: Seventy-one probands with DSM-III-R or DSM-IV OCD and their parents. METHODS: Nine single nucleotide polymorphisms spaced throughout the SLC1A1 gene region were genotyped. RESULTS: Significant association was detected at rs3780412 (P = .04) and rs301430 (P = .03), 2 common adjacent single nucleotide polymorphisms in the 3' region of SLC1A1. Analysis by sex revealed that association at rs3780412 was limited to male probands (P = .002). Significant association was also detected for the T/C haplotype at rs301430-rs301979 (P = .03), the only haplotype block identified among the 9 single nucleotide polymorphisms. Analysis by sex also revealed that the haplotype association was limited to male probands (P = .003). A deletion in the 3' flanking region of SLC1A1 was also detected that imperfectly segregated with OCD in a large, multigenerational family with multiple affected individuals. CONCLUSIONS: The 3' region of SLC1A1 may contain a susceptibility allele for early-onset OCD, with differential effects in males and females. The results also provide further support for the involvement of a glutamatergic dysfunction in the pathogenesis of early-onset OCD.

Adolescent↗
PubMed2003

Early use of clinical BRCA1/2 testing: associations with race and breast cancer risk.

When BRCA1/2 testing became commercially available in 1996, many U.S. experts voiced concern about the potential for indiscriminate use of testing among low-risk women. Supporting this concern, several early surveys of interest in genetic testing suggested that genetic testing for cancer susceptibility might appeal most to individuals at low risk of carrying a mutation. To identify factors associated with early use of clinical BRCA1/2 testing, a case-control study was conducted at a large academic health system in the metropolitan Philadelphia region. A total of 167 women underwent genetic counseling for clinical BRCA1/2 testing between 1996 and 1997 (cases) compared with 138 women who were seen in faculty general internal medicine practices over the same period (controls). In this study we measured the risk factors for breast cancer, the risk factors for carrying a BRCA1/2 mutation, and sociodemographic characteristics. Use of BRCA1/2 counseling between 1996 and 1997 was positively associated with family but no personal history of breast cancer (odds ratio (OR), 22.4; 95% confidence interval (CI), 9.3-54.3); family and personal history of breast cancer (OR, 150.3; 95% CI, 24.1-939.6); being Caucasian and non-Jewish (OR, 4.1; 95% CI, 1.3-13.5); being Caucasian and Jewish (OR, 8.8; 95% CI, 2.2-35.5); and being married (OR, 3.2; 95% CI, 1.6-6.3). Use of BRCA1/2 counseling was inversely associated with increasing age (OR, 0.07; 95% CI, 0.02-0.28 for >60 compared to <50). As suggested by the association with family history, use of counseling was associated with having a higher predicted risk of breast cancer and a higher predicted risk of carrying a BRCA1 mutation (P < 0.0001). Women who sought clinical BRCA1/2 testing in the year after it became commercially available were not the "worried well," but women at significantly increased risk of carrying a mutation. However, even after adjusting for breast cancer risk, there was a substantial racial disparity in use of BRCA1/2 testing. These findings suggest that ensuring equal access to testing for high-risk individuals irrespective of race may be as important for the future of predictive genetic testing as restricting the use of testing among low-risk individuals.

Adult↗
PubMed2006

Family-based association test of the 5HTTLPR and aggressive behavior in a general population sample of children.

BACKGROUND: A promoter polymorphism in the serotonin transporter (5HTTLPR) has functional effects on an important physiologic process involved in serotonin (5HT) signaling. Despite the fact that variation in the 5HT system has long been implicated in the etiology of aggressive behaviors, only a few association-based studies with mixed results have been reported. METHODS: We conducted family-based tests of association in a sample of 366 families from which 1187 genotypes of the 5HTTLPR were generated using polymerase chain reaction. Ratings of aggressive behavior were obtained from parents and teachers longitudinally using the Child Behavior Checklist (CBCL) and Teacher Report Form (TRF), instruments widely used in behavioral and psychiatric genetics. RESULTS: Within-family tests suggest an association between the s-allele of the 5HTTLPR and higher aggressive behavior in middle childhood. The strongest association was at age 9 and for an aggregate measure of teacher-rated aggressive behavior. CONCLUSIONS: This is the first report of an association analysis of the 5HTTLPR in a general population sample of school-age children. The results provide some support for the hypothesis that the functional effects of the 5HTTLPR s-allele are associated with higher levels of aggressive behavior in middle childhood.

Adolescent↗