Covariate adjustment in family-based association studies

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates

We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM) approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype), because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D) from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan.

Testing gene-environment interactions in family-based association studies using trait-based ascertained samples

The study of gene-environment interactions is an increasingly important aspect of genetic epidemiological investigation. Historically, it has been difficult to study gene-environment interactions using a family-based design for quantitative traits or when parent-offspring trios were incomplete. The QBAT-I provides researchers a tool to estimate and test for a gene-environment interaction in families of arbitrary structure that are sampled without regard to the phenotype of interest, but is vulnerable to inflated type I error if families are ascertained on the basis of the phenotype. In this study, we verified the potential for type I error of the QBAT-I when applied to samples ascertained on a trait of interest. The magnitude of the inflation increases as the main genetic effect increases and as the ascertainment becomes more extreme. We propose an ascertainment-corrected score test that allows the use of the QBAT-I to test for gene-environment interactions in ascertained samples. Our results indicate that the score test and an ad hoc method we propose can often restore the nominal type I error rate, and in cases where complete restoration is not possible, dramatically reduce the inflation of the type I error rate in ascertained samples.

Testing for genetic association in the presence of linkage and gene-covariate interactions

In order to study family-based association in the presence of linkage, we extend a generalized linear mixed model proposed for genetic linkage analysis (Lebrec and van Houwelingen (2007), Human Heredity 64, 5-15) by adding a genotypic effect to the mean. The corresponding score test is a weighted family-based association tests statistic, where the weight depends on the linkage effect and on other genetic and shared environmental effects. For testing of genetic association in the presence of gene-covariate interaction, we propose a linear regression method where the family-specific score statistic is regressed on family-specific covariates. Both statistics are straightforward to compute. Simulation results show that adjusting the weight for the within-family variance structure may be a powerful approach in the presence of environmental effects. The test statistic for genetic association in the presence of gene-covariate interaction improved the power for detecting association. For illustration, we analyze the rheumatoid arthritis data from GAW15. Adjusting for smoking and anti-cyclic citrullinated peptide increased the significance of the association with the DR locus.

Recommendations for using standardised phenotypes in genetic association studies

Genetic association studies of complex traits often rely on standardised quantitative phenotypes, such as percentage of predicted forced expiratory volume and body mass index to measure an underlying trait of interest (eg lung function, obesity). These phenotypes are appealing because they provide an easy mechanism for comparing subjects, although such standardisations may not be the best way to control for confounders and other covariates. We recommend adjusting raw or standardised phenotypes within the study population via regression. We illustrate through simulation that optimal power in both population- and family-based association tests is attained by using the residuals from within-study adjustment as the complex trait phenotype. An application of family-based association analysis of forced expiratory volume in one second, and obesity in the Childhood Asthma Management Program data, illustrates that power is maintained or increased when adjusted phenotype residuals are used instead of typical standardised quantitative phenotypes.

Genetic analysis of familial non-syndromic primary failure of eruption

OBJECTIVES

While some eruption disorders occur as part of a medical syndrome, primary failure of eruption (PFE) - defined as a localized failure of secondary tooth eruption - exists without systemic involvement. Recent studies support that heredity may play an important role in the pathogenesis of PFE. The objective of our human genetic study is to investigate the genetic contribution to PFE.

MATERIALS AND METHODS

Four candidate genes POSTN, RUNX2, AMELX, and AMBN) were investigated because of their relationship to tooth eruption or putative relationship to each other. Families and individuals were ascertained based on the clinical diagnosis of PFE. Pedigrees were constructed and analyzed by inspection to determine the mode of inheritance in four families. The candidate genes were directly sequenced for both unrelated affected individuals and unaffected individuals. A genome wide scan using 500 microsatellite markers followed by linkage analysis was carried out for one family.

RESULTS

Pedigree analysis of families suggests an autosomal dominant inheritance pattern with complete penetrance and variable expressivity. Sequence analysis revealed two non-functional polymorphisms in the POSTN gene and no other sequence variations in the remaining candidate genes. Genotyping and linkage analysis of one family yielded a LOD score of 1.51 for markers D13S272; D15S118 and D17S831 on chromosomes 13, 15 and 17 respectively.

CONCLUSIONS

While LOD scores were not significant evidence of linkage, extension of current pedigrees and novel SNP chip technology holds great promise for identification of a causative locus for PFE.

PRKCA: a positional candidate gene for body mass index and asthma

Asthma incidence and prevalence are higher in obese individuals. A potential mechanistic basis for this relationship is pleiotropy. We hypothesized that significant linkage and candidate-gene association would be found for body mass index (BMI) in a population ascertained on asthma affection status. Linkage analysis for BMI was performed on 657 subjects in eight Costa Rican families enrolled in a study of asthma. Family-based association studies were conducted for BMI with SNPs within a positional candidate gene, PRKCA. SNPs within PRKCA were also tested for association with asthma. Association studies were conducted in 415 Costa Rican parent-child trios and 493 trios participating in the Childhood Asthma Management Program (CAMP). Although only modest evidence of linkage for BMI was obtained for the whole cohort, significant linkage was noted for BMI in females on chromosome 17q (peak LOD = 3.39). Four SNPs in a candidate gene in this region (PRKCA) had unadjusted association p values < 0.05 for BMI in both cohorts, with the joint p value for two SNPs remaining significant after adjustment for multiple comparisons (rs228883 and rs1005651, joint p values = 9.5 x 10(-)(5) and 5.6 x 10(-)(5)). Similarly, eight SNPs had unadjusted association p values < 0.05 for asthma in both populations, with one SNP remaining significant after adjustment for multiple comparisons (rs11079657, joint p value = 2.6 x 10(-)(5)). PRKCA is a pleiotropic locus that is associated with both BMI and asthma and that has been identified via linkage analysis of BMI in a population ascertained on asthma.

Association of VEGF polymorphisms with childhood asthma, lung function and airway responsiveness

Vascular endothelial growth factor (VEGF) is an angiogenic factor implicated in asthma severity. The objective of the present study was to determine whether VEGF single nucleotide polymorphisms (SNPs) are associated with asthma, lung function and airway responsiveness. The present authors analysed 10 SNPs in 458 white families in the Childhood Asthma Management Program (CAMP). Tests of association with asthma, lung function and airway responsiveness were performed using PBAT software (Golden Helix, Inc. Bozeman, MT, USA; available at www.goldenhelix.com). Family and population-based, revpeated measures analysis of airflow obstruction were conducted. Replication studies were performed in 412 asthmatic children and their parents from Costa Rica. Associations with asthma, lung function and airway responsiveness were observed in both cohorts. SNP rs833058 was associated with asthma in both cohorts. This SNP was also associated with increased airway responsiveness in both populations. An association of rs4711750 and its haplotype with forced expiratory volume in 1 s (FEV(1))/forced vital capacity (FVC) ratio in both cohorts was observed. Longitudinal analysis in CAMP confirmed an association of rs4711750 with FEV(1)/FVC decline over approximately 4.5 yrs of observation. VEGF polymorphisms are associated with childhood asthma, lung function and airway responsiveness in two populations, suggesting that VEGF polymorphisms influence asthma susceptibility, airflow obstruction and airways responsiveness.

Evidence of linkage in a Hispanic cohort with a Class III dentofacial phenotype

Despite the prevalence of craniofacial disorders, the genetic contribution remains poorly understood. Class III malocclusion represents a specific craniofacial problem that can be handicapping, both functionally and socially. We hypothesized that the Class III phenotype is genetically linked to specific loci that regulate maxillary or mandibular growth. To determine the region linked to the Class III phenotype in four Hispanic families, we performed a genome-wide scan and linkage analysis using 500 microsatellite markers. Pedigree and linkage analyses revealed that the Class III phenotype (primarily maxillary deficiency) segregates in an autosomal-dominant manner, and that 5 loci (1p22.1, 3q26.2, 11q22, 12q13.13, and 12q23) are suggestive of linkage. Candidate genes within the 12q23 region (ZLR=2.93) include IGF1, HOXC, and COL2A1. Chromosome 1 results (ZLR=2.92) were similar to those reported previously in an Asian cohort with mandibular prognathism, suggesting that a common upstream genetic element may be responsible for both mandibular prognathism and maxillary deficiency.

Differential effectiveness of depression disease management for rural and urban primary care patients

CONTEXT

Federally qualified health centers across the country are adopting depression disease management programs following federally mandated training; however, little is known about the relative effectiveness of depression disease management in rural versus urban patient populations.

PURPOSE

To explore whether a depression disease management program has a comparable impact on clinical outcomes over 2 years in patients treated in rural and urban primary care practices and whether the impact is mediated by receiving evidence-based care (antidepressant medication and specialty care counseling).

METHODS

A preplanned secondary analysis was conducted in a consecutively sampled cohort of 479 depressed primary care patients recruited from 12 practices in 10 states across the country participating in the Quality Enhancement for Strategic Teaming study.

FINDINGS

Depression disease management improved the mental health status of urban patients over 18 months but not rural patients. Effects were not mediated by antidepressant medication or specialty care counseling in urban or rural patients.

CONCLUSIONS

Depression disease management appears to improve clinical outcomes in urban but not rural patients. Because these programs compete for scarce resources, health care organizations interested in delivering depression disease management to rural populations need to advocate for programs whose clinical effectiveness has been demonstrated for rural residents.

An extension of the weighted dissimilarity test to association study in families

Association studies for complex diseases based on pedigree haplotype or genotype data have received increasing attention in the last few years. The similarity tests are appealing for these studies because they take into account of the DNA structure, but they have blind areas on which significant association can not be detected. Recently, we developed a dissimilarity method for this problem based on independent haplotype data, which eliminates the blind areas of the existing methods. As DNA collected on families are common in practice, and the data are either of the form of genotype or haplotype. Here we extend our method for association study to data on families. It can be used to evaluate different designs in terms of power. Simulation studies confirmed that the extended method improves the type I error rate and power. Applying this method to the Genetic Analysis Workshop 14 alcoholism data, we find that markers rs716581, rs1017418, rs1332184 and rs1943418 on chromosomes 1, 2, 9 and 18 yield strong signal (with P value 0.001 or lower) for association with alcoholism. Our work can serve as a guide in the design of association studies in families.

Family-based association tests for ordinal traits adjusting for covariates

We present a class of family-based association tests (FBATs) for ordinal traits that adjust for the effects of covariates. For complex diseases, especially mental health conditions including nicotine dependence and substance use, the outcome variables are often recorded in an ordinal rather than quantitative scale. The naturally recorded ordinal traits are commonly analyzed either as quantitative traits or are dichotomized. It has been demonstrated repeatedly in recent studies that these commonly used approaches to dealing with ordinal traits are inadequate and result in loss of power. In this report, we make use of conditional likelihood to derive score test statistics that belong to a general class of FBATs. We conducted simulation studies to compare the type I error and power of our proposed test with existing tests. The empirical result suggests that our test produces reasonable type I errors and has power far exceeding (often doubling) those of existing tests. We applied our proposed test to a data set on alcohol dependence and found that six single nucleotide polymorphisms (SNPs) are significantly associated (P-values < or =0.001) with alcohol dependence after adjusting for gender and age. Three of the SNPs (rs619, rs1972373, and rs1571423) or their tightly linked regions have been suggested in the literature from the analysis of the same data, demonstrating the consistent findings between various methods. The other three SNPs (rs485874, rs718251, and rs1869907) are identified for the first time using this data set, underscoring the potential power of our proposed test.

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.

Variants in estrogen-biosynthesis genes CYP17 and CYP19 and breast cancer risk: a family-based genetic association study

BACKGROUND

Case-control studies have reported inconsistent results concerning breast cancer risk and polymorphisms in genes that control endogenous estrogen biosynthesis. We report findings from the first family-based association study examining associations between female breast cancer risk and polymorphisms in two key estrogen-biosynthesis genes CYP17 (T-->C promoter polymorphism) and CYP19 (TTTA repeat polymorphism).

METHODS

We conducted the study among 278 nuclear families containing one or more daughters with breast cancer, with a total of 1123 family members (702 with available constitutional DNA and questionnaire data and 421 without them). These nuclear families were selected from breast cancer families participating in the Metropolitan New York Registry, one of the six centers of the National Cancer Institute's Breast Cancer Family Registry. We used likelihood-based statistical methods to examine allelic associations.

RESULTS

We found the CYP19 allele with 11 TTTA repeats to be associated with breast cancer risk in these families. We also found that maternal (but not paternal) carrier status of CYP19 alleles with 11 repeats tended to be associated with breast cancer risk in daughters (independently of the daughters' own genotype), suggesting a possible in utero effect of CYP19. We found no association of a woman's breast cancer risk either with her own or with her mother's CYP17 genotype.

CONCLUSION

This family-based study indicates that a woman's personal and maternal carrier status of CYP19 11 TTTA repeat allele might be related to increased breast cancer risk. However, because this is the first study to report an association between CYP19 11 TTTA repeat allele and breast cancer, and because multiple comparisons have been made, the associations should be interpreted with caution and need confirmation in future family-based studies.