A unified association analysis approach for family and unrelated samples correcting for stratification

There are two common designs for association mapping of complex diseases: case-control and family-based designs. A case-control sample is more powerful to detect genetic effects than a family-based sample that contains the same numbers of affected and unaffected persons, although additional markers may be required to control for spurious association. When family and unrelated samples are available, statistical analyses are often performed in the family and unrelated samples separately, conditioning on parental information for the former, thus resulting in reduced power. In this report, we propose a unified approach that can incorporate both family and case-control samples and, provided the additional markers are available, at the same time corrects for population stratification. We apply the principal components of a marker matrix to adjust for the effect of population stratification. This unified approach makes it unnecessary to perform a conditional analysis of the family data and is more powerful than the separate analyses of unrelated and family samples, or a meta-analysis performed by combining the results of the usual separate analyses. This property is demonstrated in both a variety of simulation models and empirical data. The proposed approach can be equally applied to the analysis of both qualitative and quantitative traits.     

Family-based versus unrelated case-control designs for genetic associations

The most simple and commonly used approach for genetic associations is the case-control study design of unrelated people. This design is susceptible to population stratification. This problem is obviated in family-based studies, but it is usually difficult to accumulate large enough samples of well-characterized families. We addressed empirically whether the two designs give similar estimates of association in 93 investigations where both unrelated case-control and family-based designs had been employed. Estimated odds ratios differed beyond chance between the two designs in only four instances (4%). The summary relative odds ratio (ROR) (the ratio of odds ratios obtained from unrelated case-control and family-based studies) was close to unity (0.96 [95% confidence interval, 0.91-1.01]). There was no heterogeneity in the ROR across studies (amount of heterogeneity beyond chance I(2) = 0%). Differences on whether results were nominally statistically significant (p < 0.05) or not with the two designs were common (opposite classification rates 14% and 17%); this reflected largely differences in power. Conclusions were largely similar in diverse subgroup analyses. Unrelated case-control and family-based designs give overall similar estimates of association. We cannot rule out rare large biases or common small biases.     

The power of genomic control

Although association analysis is a useful tool for uncovering the genetic underpinnings of complex traits, its utility is diminished by population substructure, which can produce spurious association between phenotype and genotype within population-based samples. Because family-based designs are robust against substructure, they have risen to the fore of association analysis. Yet, if population substructure could be ignored, this robustness can come at the price of power. Unfortunately it is rarely evident when population substructure can be ignored. Devlin and Roeder recently have proposed a method, termed "genomic control" (GC), which has the robustness of family-based designs even though it uses population-based data. GC uses the genome itself to determine appropriate corrections for population-based association tests. Using the GC method, we contrast the power of two study designs, family trios (i.e., father, mother, and affected progeny) versus case-control. For analysis of trios, we use the TDT test. When population substructure is absent, we find GC is always more powerful than TDT; furthermore, contrary to previous results, we show that as a disease becomes more prevalent the discrepancy in power becomes more extreme. When population substructure is present, however, the results are more complex: TDT is more powerful when population substructure is substantial, and GC is more powerful otherwise. We also explore general issues of power and implementation of GC within the case-control setting and find that, economically, GC is at least comparable to and often less expensive than family-based methods. Therefore, GC methods should prove a useful complement to family-based methods for the genetic analysis of complex traits.     

Cigarette smoking strongly modifies the association of LOC387715 and age-related macular degeneration

We used iterative association mapping to identify a susceptibility gene for age-related macular degeneration (AMD) on chromosome 10q26, which is one of the most consistently implicated linkage regions for this disorder. We employed linkage analysis methods, followed by family-based and case-control association analyses, using two independent data sets. To identify statistically the most likely AMD-susceptibility allele, we used the Genotype-IBD Sharing Test (GIST) and conditional haplotype analysis. To incorporate the two most important known AMD risk factors--smoking and the Y402H variant of the complement factor H gene (CFH)--we used logistic regression modeling to test for gene-gene and gene-environment interactions in the case-control data set and used the ordered-subset analysis to account for genetic linkage heterogeneity in the family-based data set. Our results strongly implicate a coding change (Ala69Ser) in the LOC387715 gene as the second major identified AMD-susceptibility allele, confirming earlier suggestions. This variant's effect on AMD is statistically independent of CFH and is of similar magnitude to the effect of Y402H. The overall effect is driven primarily by a strong association in smokers, since we observed significant evidence for a statistical interaction between the LOC387715 variant and a history of cigarette smoking. This gene-environment interaction is supported by statistically independent family-based and case-control analysis methods. We estimate that CFH, LOC387715, and cigarette smoking together explain 61% of the population-attributable risk (PAR) of AMD. The adjusted PAR percentage estimates are 20% for smoking, 36% for LOC387715, and 43% for CFH. We demonstrate, for the first time, that a genetic susceptibility coupled with a modifiable lifestyle factor such as cigarette smoking confers a significantly higher risk of AMD than either factor alone.     

Quantitative similarity-based association tests using population samples

Although genetic association studies using unrelated individuals may be subject to bias caused by population stratification, alternative methods that are robust to population stratification, such as family-based association designs, may be less powerful. Furthermore, it is often more feasible and less expensive to collect unrelated individuals. Recently, several statistical methods have been proposed for case-control association tests in a structured population; these methods may be robust to population stratification. In the present study, we propose a quantitative similarity-based association test (QSAT) to identify association between a candidate marker and a quantitative trait of interest, through use of unrelated individuals. For the QSAT, we first determine whether two individuals are from the same subpopulation or from different subpopulations, using genotype data at a set of independent markers. We then perform an association test between the candidate marker and the quantitative trait, through incorporation of such information. Simulation results based on either coalescent models or empirical population genetics data show that the QSAT has a correct type I error rate in the presence of population stratification and that the power of the QSAT is higher than that of family-based association designs.     

Association between MSX1 variants and oral clefts in Han Chinese in western China

Previous animal and association studies have shown that the MSX1 gene is associated with oral clefts. Our aim was to investigate association between variants in the MSX1 gene and oral clefts in a Han Chinese population. Our study group consisted of 206 nonsyndromic oral cleft (NSOC) nuclear families (including the patients and their parents) and 224 controls. The three variants evaluated in this study were single-nucleotide polymorphisms rs3821949 and rs12532 and a missense mutation P147Q. Polymerase chain reaction-restriction fragment length polymorphism was used to genotype the three markers. Case-control and family-based association analyses were carried out. In the case-control analysis, no significant differences in genotypic or allelic frequencies were observed in any of the two single-nucleotide polymorphisms between patients and controls. Although the homozygous T allele for P147Q was not detected in any sample in this population, heterozygotes were more prevalent in NSOC (1.2%) when compared with the controls (0%). The analyses for family-based association did not suggest association between any of the three variants and NSOC. No significant association was found between NSOC and rs3821949 or rs12532 in MSX1 gene, whereas an association was observed between the P147Q variant and cleft lip with cleft palate in the case-control analysis.     

The BTNL2 gene and sarcoidosis susceptibility in African Americans and Whites

The BTNL2 gene is a member of the B7 receptor family that probably functions as a T-cell costimulatory molecule. It resides in the class II major histocompatibility complex (MHC) region of chromosome 6p and has recently been associated with sarcoidosis susceptibility in a white German population. We sought to replicate the BTNL2 association in an African American family-based study population (n=219 nuclear families) and two case-control populations--one African American (n=295 pairs) and one white (n=366 pairs). Ten SNPs were detected within a 490-bp region spanning exon/intron 5 of BTNL2. Haplotype variation within this region was significantly associated with sarcoidosis in all three study populations but more so in whites (P=.0006) than in the African American case-control (P=.02) or family-based (P=.03) samples. The previously reported BTNL2 SNP with the strongest sarcoidosis association, rs2076530, was also the SNP with the strongest association in our white population (P<.0001). The A allele of rs2076530 results in a premature exon-splice site and increases risk for sarcoidosis (odds ratio=2.03; 95% confidence interval 1.32-3.12). Although rs2076530 was not associated with sarcoidosis in either African American sample, a three-locus haplotype that included rs2076530 was associated with sarcoidosis across all three study samples. Multivariable logistic regression analyses showed that BTNL2 effects are independent of human leukocyte antigen class II genes in whites but may interact antagonistically in African Americans. Our results underscore the complexity of genetic risk for sarcoidosis emanating from the MHC region.     

Family study designs in the age of genome-wide association studies: experience from the Framingham Heart Study

PURPOSE OF REVIEW: The past year has seen the publication of many genome-wide association studies, most of which are case-control studies. These publications are at the forefront of current research into the examination of genetic effects for numerous diseases, including diabetes, heart disease and cancer. Over the past 25 years the tour de force of genetics research has been in family studies, using segregation, linkage and association analyses. Are these approaches now passé? Here we discuss the role of family studies in modern genetics research, using results from the Framingham Heart Study as examples. RECENT FINDINGS: Family studies permit both linkage and association analyses. Importantly, family-based association tests that consider transmission of genetic variants within a family provide important information on the genetic etiology of disease traits and avoid the potential of false-positive findings due to population substructure. SUMMARY: Family-based study designs continue to contribute much to the modern era of genome-wide association studies.     

The SERPINE2 gene is associated with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a complex human disease likely influenced by multiple genes, cigarette smoking, and gene-by-smoking interactions, but only severe alpha 1-antitrypsin deficiency is a proven genetic risk factor for COPD. Prior linkage analyses in the Boston Early-Onset COPD Study have demonstrated significant linkage to a key intermediate phenotype of COPD on chromosome 2q. We integrated results from murine lung development and human COPD gene-expression microarray studies with human COPD linkage results on chromosome 2q to prioritize candidate-gene selection, thus identifying SERPINE2 as a positional candidate susceptibility gene for COPD. Immunohistochemistry demonstrated expression of serpine2 protein in mouse and human adult lung tissue. In family-based association testing of 127 severe, early-onset COPD pedigrees from the Boston Early-Onset COPD Study, we observed significant association with COPD phenotypes and 18 single-nucleotide polymorphisms (SNPs) in the SERPINE2 gene. Association of five of these SNPs with COPD was replicated in a case-control analysis, with cases from the National Emphysema Treatment Trial and controls from the Normative Aging Study. Family-based and case-control haplotype analyses supported similar regions of association within the SERPINE2 gene. When significantly associated SNPs in these haplotypic regions were included as covariates in linkage models, LOD score attenuation was observed most markedly in a smokers-only linkage model (LOD 4.41, attenuated to 1.74). After the integration of murine and human microarray data to inform candidate-gene selection, we observed significant family-based association and independent replication of association in a case-control study, suggesting that SERPINE2 is a COPD-susceptibility gene and is likely influenced by gene-by-smoking interaction.     

No association of sequence variants in the neuropeptide Y2 receptor (NPY2R) gene with early onset obesity in Germans.

The neuropeptide Y2 receptor (NPY2R) has been implicated in body weight regulation both in humans and rodents. We investigated if genetic variation in the NPY2R gene is associated with obesity in German extremely obese children and adolescents. The coding sequence and predicted promoter of the NPY2R were screened for variations. Subsequently, case-control (184 extremely obese children and adolescents: mean body mass index [BMI] 35.7+/-6.1 kg/m(2), 277 lean students: mean BMI 18.2+/-1.1 kg/m(2)) and family-based (770 parental pairs with a total of 1081 obese off-spring) association analyses were conducted in independent samples. We identified 14 sequence variants (seven novel variants including two coding variants c.369C >T and c.834G >A), five of which were detected once, each in the heterozygous state. In case-control analyses we did not detect association with obesity for seven common (minor allele frequency >1%) variants (all p >0.16); additional gender-stratified analyses employing several genetic models and haplotype analyses were also nonsignificant. Furthermore, in a family-based association study for coding synonymous SNP rs1047214 (Ile195) we found no evidence for a transmission disequilibrium in the total or in the gender-stratified PDT analyses (all p >0.50). In conclusion, we did not find evidence for an involvement of genetic variation in the NPY2R in early onset obesity in German samples.     

catmap: Case-control And TDT Meta-Analysis Package

Background  

Risk for complex disease is thought to be controlled by multiple genetic risk factors, each with small individual effects. Meta-analyses of several independent studies may be helpful to increase the ability to detect association when effect sizes are modest. Although many software options are available for meta-analysis of genetic case-control data, no currently available software implements the method described by Kazeem and Farrall (2005), which combines data from independent family-based and case-control studies.     

A rapid generalized least squares model for a genome-wide quantitative trait association analysis in families

Genome-wide association studies (GWAS) using family data involve association analyses between hundreds of thousands of markers and a trait for a large number of related individuals. The correlations among relatives bring statistical and computational challenges when performing these large-scale association analyses. Recently, several rapid methods accounting for both within- and between-family variation have been proposed. However, these techniques mostly model the phenotypic similarities in terms of genetic relatedness. The familial resemblances in many family-based studies such as twin studies are not only due to the genetic relatedness, but also derive from shared environmental effects and assortative mating. In this paper, we propose 2 generalized least squares (GLS) models for rapid association analysis of family-based GWAS, which accommodate both genetic and environmental contributions to familial resemblance. In our first model, we estimated the joint genetic and environmental variations. In our second model, we estimated the genetic and environmental components separately. Through simulation studies, we demonstrated that our proposed approaches are more powerful and computationally efficient than a number of existing methods are. We show that estimating the residual variance-covariance matrix in the GLS models without SNP effects does not lead to an appreciable bias in the p values as long as the SNP effect is small (i.e. accounting for no more than 1% of trait variance).     

Validation of prostate cancer risk-related loci identified from genome-wide association studies using family-based association analysis: evidence from the International Consortium for Prostate Cancer Genetics (ICPCG)

Multiple prostate cancer (PCa) risk-related loci have been discovered by genome-wide association studies (GWAS) based on case-control designs. However, GWAS findings may be confounded by population stratification if cases and controls are inadvertently drawn from different genetic backgrounds. In addition, since these loci were identified in cases with predominantly sporadic disease, little is known about their relationships with hereditary prostate cancer (HPC). The association between seventeen reported PCa susceptibility loci was evaluated with a family-based association test using 1,979 hereditary PCa families of European descent collected by members of the International Consortium for Prostate Cancer Genetics, with a total of 5,730 affected men. The risk alleles for 8 of the 17 loci were significantly over-transmitted from parents to affected offspring, including SNPs residing in 8q24 (regions 1, 2 and 3), 10q11, 11q13, 17q12 (region 1), 17q24 and Xp11. In subgroup analyses, three loci, at 8q24 (regions 1 and 2) plus 17q12, were significantly over-transmitted in hereditary PCa families with five or more affected members, while loci at 3p12, 8q24 (region 2), 11q13, 17q12 (region 1), 17q24 and Xp11 were significantly over-transmitted in HPC families with an average age of diagnosis at 65?years or less. Our results indicate that at least a subset of PCa risk-related loci identified by case-control GWAS are also associated with disease risk in HPC families.     

Genetic association of the catalase gene (CAT) with vitiligo susceptibility

Vitiligo susceptibility is a complex genetic trait that may involve genes important for melanin biosynthesis, response to oxidative stress, and/or regulation of autoimmunity, as well as environmental factors. We report here case-control and family-based association studies for the catalase gene (CAT) in vitiligo patients. The CAT gene was selected as a candidate gene because of the reduction of catalase enzyme activity (EC 1.11.1.6) and concomitant accumulation of excess hydrogen peroxide observed in the entire epidermis of vitiligo patients. One of three CAT genetic markers studied was found to be informative for genotypic analysis of Caucasian vitiligo patients and control subjects. Both case/control and family-based genetic association studies of the T/C single nucleotide polymorphism (SNP) in exon 9 of the CAT gene, which is detectable with the restriction endonuclease BstX I, suggest possible association between the CAT gene and vitiligo susceptibility. The observations that T/C heterozygotes are more frequent among vitiligo patients than controls and that the C allele is transmitted more frequently to patients than controls suggest that linked mutations in or near the CAT gene might contribute to a quantitative deficiency of catalase activity in the epidermis and the accumulation of excess hydrogen peroxide (H2O2). The CAT gene may, therefore, be a susceptibility gene in some vitiligo patients, further supporting the epidermal oxidative stress model for vitiligo pathogenesis.     

Association mapping in structured populations

The use, in association studies, of the forthcoming dense genomewide collection of single-nucleotide polymorphisms (SNPs) has been heralded as a potential breakthrough in the study of the genetic basis of common complex disorders. A serious problem with association mapping is that population structure can lead to spurious associations between a candidate marker and a phenotype. One common solution has been to abandon case-control studies in favor of family-based tests of association, such as the transmission/disequilibrium test (TDT), but this comes at a considerable cost in the need to collect DNA from close relatives of affected individuals. In this article we describe a novel, statistically valid, method for case-control association studies in structured populations. Our method uses a set of unlinked genetic markers to infer details of population structure, and to estimate the ancestry of sampled individuals, before using this information to test for associations within subpopulations. It provides power comparable with the TDT in many settings and may substantially outperform it if there are conflicting associations in different subpopulations.     

Joint analysis for genome-wide association studies in family-based designs

In family-based data, association information can be partitioned into the between-family information and the within-family information. Based on this observation, Steen et al. (Nature Genetics. 2005, 683-691) proposed an interesting two-stage test for genome-wide association (GWA) studies under family-based designs which performs genomic screening and replication using the same data set. In the first stage, a screening test based on the between-family information is used to select markers. In the second stage, an association test based on the within-family information is used to test association at the selected markers. However, we learn from the results of case-control studies (Skol et al. Nature Genetics. 2006, 209-213) that this two-stage approach may be not optimal. In this article, we propose a novel two-stage joint analysis for GWA studies under family-based designs. For this joint analysis, we first propose a new screening test that is based on the between-family information and is robust to population stratification. This new screening test is used in the first stage to select markers. Then, a joint test that combines the between-family information and within-family information is used in the second stage to test association at the selected markers. By extensive simulation studies, we demonstrate that the joint analysis always results in increased power to detect genetic association and is robust to population stratification.     

FTO and MC4R gene variants are associated with obesity in polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility in women. It is also associated with metabolic disturbances that place women at increased risk for obesity and type 2 diabetes. There is strong evidence for familial clustering of PCOS and a genetic predisposition. However, the gene(s) responsible for the PCOS phenotypes have not been elucidated. This two-phase family-based and case-control genetic study was designed to address the question of whether SNPs identified as susceptibility loci for obesity in genome-wide association studies (GWAS) are also associated with PCOS and elevated BMI. Members of 439 families having at least one offspring with PCOS were genotyped for 15 SNPs previously shown to be associated with obesity. Linkage and association with PCOS was assessed using the transmission/disequilibrium test (TDT). These SNPs were also analyzed in an independent case-control study involving 395 women with PCOS and 176 healthy women with regular menstrual cycles. Only one of these 15 SNPs (rs2815752 in NEGR1) was found to have a nominally significant association with PCOS (χ² = 6.11, P = 0.013), but this association failed to replicate in the case-control study. While not associated with PCOS itself, five SNPs in FTO and two in MC4R were associated with BMI as assessed with a quantitative-TDT analysis, several of which replicated association with BMI in the case-control cohort. These findings demonstrate that certain SNPs associated with obesity contribute to elevated BMI in PCOS, but do not appear to play a major role in PCOS per se. These findings support the notion that PCOS phenotypes are a consequence of an oligogenic/polygenic mechanism.     

A comparative study of sibship tests of linkage and/or association.

Population-based tests of association have used data from either case-control studies or studies based on trios (affected child and parents). Case-control studies are more prone to false-positive results caused by inappropriate controls, which can occur if, for example, there is population admixture or stratification. An advantage of family-based tests is that cases and controls are well matched, but parental data may not always be available, especially for late-onset diseases. Three recent family-based tests of association and linkage utilize unaffected siblings as surrogates for untyped parents. In this paper, we propose an extension of one of these tests. We describe and compare the four tests in the context of a complex disease for both biallelic and multiallelic markers, as well as for sibships of different sizes. We also examine the consequences of having some parental data in the sample.     

Alcohol dependence and polymorphisms of serotonin-related genes

Genetic factors have a non-specific but significant impact on the risk of alcohol-dependence. Molecular genetic analyses are now less devoted to the genes involved in the metabolism of ethanol, focusing on core concepts of addiction, such as arousal, pleasure, reward, craving, and impulsivity. Indeed, the neuro-cognitive functions, temperament traits and psycho-behavioral specificities of patients with alcohol abuse or dependence led to select new sets of candidate genes. One of them are related to serotonin transmission, as serotonin modulates dopaminergic pathways, and is also stimulated by many addictive susbtances. The genetic analyses of serotonin in alcohol-dependence are mainly focused on the serotonin transporter gene (5-HTT), as one polymorphism within the promoter has a functional impact. From the 16 case-control association studies yet performed, many are positive, and one family-based study showed a large excess of transmission of the short allele. We performed a meta-analysis of the case-control studies showing that the S allele could be a risk factor for a phenotype related to alcohol-dependence (OR=1.31), with still unknown boundaries. Other genes coding for serotonin receptors were analysed with mainly negative results, for example the 5-HT2A, 5-HT2C, 5-HT5A and 5-HT7 receptors. The 5-HT1B could be more interesting as being located in a locus linked to alcohol preference in rodents, and associated with antisocial alcoholism in two human studies. Genetics may thus provide new insights about the different mechanisms which explain why some subjects are more at risk for the development of alcohol abuse or dependence. Genes involved in the transmission, reuptake and metabolism of serotonin constitute a set of candidate genes that could be involved in core aspects of alcoholism, such as the tendency to prefer immediate reward, despite negative consequences.     

Combining evidence for association from transmission disequilibrium and case-control studies using single-nucleotide polymorphisms

The aim of the present analysis is to combine evidence for association from the two most commonly used designs in genetic association analysis, the case-control design and the transmission disequilibrium test (TDT) design. The cases here are affected offspring from nuclear families and are used in both the case-control and TDT designs. As a result, inference from these designs is not independent. We applied a simple logistic regression method for combining evidence for association from case-control and TDT designs to single-nucleotide polymorphism data purchased on a region on chromosome 3, replicate 1 of the Aipotu population. Combining the evidence from the case-control and TDT designs yielded a 5-10% reduction in the standard errors of the relative risk estimates. The authors did not know the results before the analyses were conducted.