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Genetics of chronic obstructive pulmonary disease.

The marked variability in the development of chronic obstructive pulmonary disease (COPD) in response to cigarette smoking has been known for decades, but severe alpha 1-antitrypsin deficiency (PI Z) remains the only proven genetic risk factor for COPD. With cigarette smoking, PI Z subjects tend to develop more severe pulmonary impairment at an earlier age than non-smoking PI Z individuals. However, PI Z individuals exhibit wide variability in pulmonary function impairment, even among individuals with similar smoking histories. Therefore, other genes and environmental exposures are also likely involved. The role of heterozygosity for the Z allele as a risk factor for COPD remains controversial, but accumulating evidence suggests that at least some PI MZ individuals are at increased risk of developing airflow obstruction. In individuals without alpha 1-antitrypsin deficiency, familial aggregation of COPD has been reported in several studies. To study novel genetic determinants of COPD, our research group enrolled 44 severe, early-onset COPD probands (FEV1 < 40%, age < 53 yrs, non-PI Z) and 266 of their relatives. A marked female predominance was noted among the early-onset COPD probands. In addition, increased risk to current or ex-smoking first-degree relatives of early-onset COPD probands for reduced FEV1, chronic bronchitis and spirometric bronchodilator responsiveness has been demonstrated. These data strongly support the genetic basis for the development of COPD and the potential for gene-by-environment interaction. A variety of studies have examined candidate gene loci with association studies, comparing the distribution of variants in genes hypothesized to be involved in the development of COPD in COPD patients and control subjects. For most genetic loci which have been tested, there have been inconsistent results. Genetic heterogeneity could contribute to difficulty in replicating associations between studies. In addition, case-control association studies are susceptible to supporting associations based purely on population stratification, which can result from incomplete matching between cases and controls--including differences in ethnicity. No association studies in COPD have been reported which used family-based controls, a study design which is immune to such population stratification effects. More importantly, no linkage studies have been published in COPD to identify regions of the genome which are likely to contain COPD susceptibility genes--regions in which association studies are likely to be more productive.

Humans↗

Low hanging fruit: a subset of human cSNPs is both highly non-uniform and predictable.

We present a point mutation classification method that contrasts SNP databases and has the potential to illuminate the relative mutational load of genes caused by codon bias. We group point variation gleaned from public databases by their wild-type and mutant codons, e.g. codon mutation classes (CMCs, 576 possible such as ACG-->ATG), whose frequencies in a database are assembled into a BLOSUM-style matrix describing the likelihood of observing all possible single base codon changes as tuned by the intertwined effects of mutation rate and selection. The rankings of the CMCs in any database are reshuffled according to the population stratification of the typical genotyping experiment producing that resource's data. Analysis of four independent databases reveals that a considerable fraction of mutation in functional genes can be described by a few CMCs regardless of gene identity or population stratification in the genotyping experiment. For example, the top 5% (29/576) of CMCs account for 27.4% of the observed variants in dbSNP while the bottom 5% account for only 0.02%. For non-synonymous disease-causing mutation, 40.8% are described by the top 5% of all possible non-silent CMCs (22/438). Overall, the most observed polymorphism is a G-->A transition at CpG dinucleotides causing ACG, TCG, GCG, and CCG to frequently undergo silent mutation in any gene due to the putative lack of impact on the protein product. In order to assess how well CMC spectrums estimate the aggregate non-synonymous mutational trends of a single gene, a CMC matrix was applied to seven unrelated genes to compute the most likely point mutations. In excess of 87% of these mutation predictions are historically known to play an important role in a disease state according to published literature. CMC-based mutation prediction may aid design and execution of direct association genotyping studies.

Base Sequence↗

Association between the CHRM2 gene and intelligence in a sample of 304 Dutch families.

The CHRM2 gene is thought to be involved in neuronal excitability, synaptic plasticity and feedback regulation of acetylcholine release and has previously been implicated in higher cognitive processing. In a sample of 667 individuals from 304 families, we genotyped three single-nucleotide polymorphisms (SNPs) in the CHRM2 gene on 7q31-35. From all individuals, standardized intelligence measures were available. Using a test of within-family association, which controls for the possible effects of population stratification, a highly significant association was found between the CHRM2 gene and intelligence. The strongest association was between rs324650 and performance IQ (PIQ), where the T allele was associated with an increase of 4.6 PIQ points. In parallel with a large family-based association, we observed an attenuated - although still significant - population-based association, illustrating that population stratification may decrease our chances of detecting allele-trait associations. Such a mechanism has been predicted earlier, and this article is one of the first to empirically show that family-based association methods are not only needed to guard against false positives, but are also invaluable in guarding against false negatives.

Adolescent↗

Candidate gene analysis for quantitative traits using the transmission disequilibrium test: the example of the melanocortin 4-receptor in pigs.

Population-wide associations between loci due to linkage disequilibrium can be used to map quantitative trait loci (QTL) with high resolution. However, spurious associations between markers and QTL can also arise as a consequence of population stratification. Statistical methods that cannot differentiate between loci associations due to linkage disequilibria from those caused in other ways can render false-positive results. The transmission-disequilibrium test (TDT) is a robust test for detecting QTL. The TDT exploits within-family associations that are not affected by population stratification. However, some TDTs are formulated in a rigid form, with reduced potential applications. In this study we generalize TDT using mixed linear models to allow greater statistical flexibility. Allelic effects are estimated with two independent parameters: one exploiting the robust within-family information and the other the potentially biased between-family information. A significant difference between these two parameters can be used as evidence for spurious association. This methodology was then used to test the effects of the fourth melanocortin receptor (MC4R) on production traits in the pig. The new analyses supported the previously reported results; i.e., the studied polymorphism is either causal or in very strong linkage disequilibrium with the causal mutation, and provided no evidence for spurious association.

Alleles↗

The (GT)n polymorphism and haplotype of the COL1A2 gene, but not the (AAAG)n polymorphism of the PTHR1 gene, are associated with bone mineral density in Chinese.

Collagen type I alpha2 (COL1A2) and parathyroid hormone (PTH)/PTH-related peptide receptor (PTHR1) are two prominent candidate genes for bone mineral density (BMD). To test their importance for BMD variation in Chinese, we recruited 388 nuclear families composed of both parents and at least one healthy daughter with a total of 1,220 individuals, and simultaneously analyzed population stratification, total-family association, and within-family association between BMD at the spine and hip and the (GT)n marker in the intron 1 of the COL1A2 gene and the (AAAG)n marker in the P3 promoter of PTHR1 gene. We also performed these association analyses with haplotypes of the MspI and (GT)n polymorphisms in the COL1A2 gene. Significant within-family association was found between the M(GT)12 haplotype and trochanter BMD (P<0.001). Individuals with this haplotype have, on average, 9.53% lower trochanter BMD than the non-carriers. Suggestive evidence of the within-family association was detected between the (GT)17 allele and BMD at the spine (P=0.012), hip (P=0.011), femoral neck (P=0.032), trochanter (P=0.023), and intertrochanter (P=0.034). The association was confirmed by subsequent permutation tests. For the association, the proportion of phenotypic variance explained by the detected markers ranged from 1.2 to 3.9%, with the highest 3.9% at the trochanter for the M(GT)12 haplotype. This association indicates that there is strong linkage disequilibrium between the polymorphisms (MspI and GT repeat polymorphism) in the COL1A2 gene and a nearby quantitative trait locus (QTL) underlying BMD variation in Chinese, or the markers themselves may have an important effect on the variation of BMD. On the other hand, no significant within-family association, population stratification and total-family association between the PTHR1 polymorphism and BMD were found in our Chinese population.

Adult↗

A note on exact tests of Hardy-Weinberg equilibrium.

Deviations from Hardy-Weinberg equilibrium (HWE) can indicate inbreeding, population stratification, and even problems in genotyping. In samples of affected individuals, these deviations can also provide evidence for association. Tests of HWE are commonly performed using a simple chi2 goodness-of-fit test. We show that this chi2 test can have inflated type I error rates, even in relatively large samples (e.g., samples of 1,000 individuals that include approximately 100 copies of the minor allele). On the basis of previous work, we describe exact tests of HWE together with efficient computational methods for their implementation. Our methods adequately control type I error in large and small samples and are computationally efficient. They have been implemented in freely available code that will be useful for quality assessment of genotype data and for the detection of genetic association or population stratification in very large data sets.

Genetics, Population↗

Corin gene minor allele defined by 2 missense mutations is common in blacks and associated with high blood pressure and hypertension.

BACKGROUND: The natriuretic peptide system contributes to blood pressure regulation. Atrial and brain natriuretic peptides are cleaved into smaller biologically active molecules by corin, a transmembrane serine protease expressed in cardiomyocytes. METHOD AND RESULTS: This genotype-phenotype genetic association study included replication samples and genomic control to correct for population stratification. Sequencing of the human corin gene identified 2 nonsynonymous, nonconservative single nucleotide polymorphisms (Q568P and T555I) in near-complete linkage disequilibrium, thus describing a single minor I555 (P568) corin gene allele. This allele was present in the heterozygote state in &12% of blacks but was extremely rare in whites (<0.5% were homozygous for the minor allele). In our primary population sample, the Dallas Heart Study, after adjustment for potential confounders, including population stratification, the corin I555 (P568) allele remained independently associated with increased risk for prevalent hypertension (odds ratio, 1.63; 95% CI, 1.11 to 2.38; P=0.013). The corin I555 (P568) allele also was associated with higher systolic blood pressure in subjects not using antihypertensive medication in unadjusted (133.7+/-20.7 versus 129.4+/-17.4 mm Hg; P=0.029) and adjusted (132.5+/-1.6 versus 128.9+/-0.6 mm Hg; P=0.029) analyses. The independent association of the minor corin allele with increased risk for prevalent hypertension was confirmed in the Multi-Ethnic Study of Atherosclerosis (odds ratio, 1.50; 95% CI, 1.09 to 2.06; P=0.014). In addition, the association of the minor corin I555 (P568) allele with higher systolic blood pressure was confirmed in adjusted analysis in the Chicago Genetics of Hypertension Study (125.8+/-1.9 versus 121.4+/-0.7 mm Hg; P=0.03). CONCLUSIONS: The corin I555 (P568) allele is common in blacks and is associated with higher blood pressure and an increased risk for prevalent hypertension.

Adult↗

Clinical methods in psychiatric genetics. I. Robustness of genetic marker investigative strategies.

Population stratification, secondary effects of illness or treatment, biological heterogeneity of a clinical syndrome, or complex biology underlying a syndrome (where only one component is measured) are conditions which may obscure the association of a genetic risk factor with a clinical syndrome. We consider several investigative strategies under each of these conditions. Only segregation-based paradigms are robust to genetic heterogeneity and population stratification. But secondary effects on the risk factor produced by illness or treatment require other strategies for their detection.

Chromosome Aberrations↗

Combined linkage and association tests in mx.

Statistical methods aimed at the detection of genes for quantitative traits suffer from two problems: (i) when a linkage approach is employed, relatively large sample sizes are usually required; and (ii) when an association approach is employed, effects of population stratification may blur genuine locus-trait associations. The variance components method proposed by Fulker et al. (1999) addressed both these problems; it is statistically powerful because it involves a combined analysis of linkage and association and can include information from multiplex families, which reduces the overall amount of necessary individual genotypes. In addition, it includes an explicit test for the presence of spurious association. After a brief illustration of the various ways in which population stratification may affect locus-trait associations, the implementation in Mx (Neale, 1997) of the method as proposed by Fulker et al. (1999) is discussed and illustrated. In addition, an extension to this method is proposed that allows the use of (variable) sibship sizes greater than two, the estimation of additive and dominance association effects, and the use of multiple alleles. These extensions can be implemented when parental genotypes are available or unavailable.

Alleles↗

The VDR, COL1A1, PTH, and PTHR1 gene polymorphisms are not associated with bone size and height in Chinese nuclear families.

We tested the relationship of the ApaI, Eco31I, BstBI, and (AAAG)n polymorphisms in the vitamin D receptor (VDR), collagen type I alpha-1 (COL1A1), parathyroid hormone (PTH), and parathyroid hormone (PTH)/PTH-related peptide receptor (PTHR1) genes with variations in bone size (BS) and height. Population stratification, total-family association, and within-family association were used to test these relationships in 400 Chinese nuclear families with a total of 1256 individuals. The BS at hip and spine was measured using a Hologic QDR 2000 dual-energy X-ray absorptiometry (DXA) scanner. The minor allele frequencies were 29.2%, 36.0%, and 14.0% for the VDR-ApaI, COL1A1-Eco31I, and PTH-BstBI markers, respectively. (AAAG)5 and (AAAG)6 of the PTHR1 gene are two major alleles in the Chinese people. Significant population stratification was found between the spine BS and PTHR1-(AAAG)5 (P = 0.048) and PTHR1-(AAAG)6 (P = 0.023), as well as between PTHR1-(AAAG)5 and height (P = 0.048), but we did not detect any significant within-family association or total-family association between the VDR, COL1A1, PTH, and PTHR1 gene polymorphisms and the variations in BS and height in our sample. Our results do not support that the VDR, COL1A1, PTH, and PTHR1 genes have an important influence on the variation in BS and height in our Chinese population.

Absorptiometry, Photon↗

Mapping disease genes: family-based association studies.

With recent rapid advances in mapping of the human genome, including highly polymorphic and closely linked markers, studies of marker associations with disease are increasingly relevant for mapping disease genes. The use of nuclear-family data in association studies was initially developed to avoid possible ethnic mismatching between patients and randomly ascertained controls. The parental marker alleles not transmitted to an affected child or never transmitted to an affected sib pair form the so-called AFBAC (affected family-based controls) population. In this paper, the theoretical foundation of the AFBAC method is proved for any single-locus model of disease and for any nuclear family-based ascertainment scheme. In a random-mating population, when there is a marker association with disease, the AFBAC population provides an unbiased estimate of the overall population (control) marker alleles when the recombination fraction (theta) between the marker and disease genes is sufficiently small that it can be taken as zero (theta = 0). With population stratification, only marker associations present in the subpopulations will be detected with family-based analyses. Of more importance, however, is the fact that, when theta not equal to 0, differences between transmitted parental (patient) marker allele frequencies and non- or never-transmitted parental marker allele frequencies (implying a marker association with disease) can only be observed for marker genes linked to a disease gene (theta < 1/2). Thus, associations of unlinked marker loci with disease at the population level, caused by population stratification, migration, or admixture, are eliminated. This validates the use of family-based association tests as an appropriate strategy for mapping disease genes.

Chromosome Mapping↗

Tests of linkage and association of the COL1A2 gene with bone phenotypes' variation in Chinese nuclear families.

In the present study, we simultaneously test linkage and/or association of the collagen type I alpha 2 (COL1A2) gene with bone mineral density (BMD) and bone area. A total of 1280 subjects from 407 Chinese nuclear families (including both parents and their daughters) were genotyped for an intragenic marker MspI in the COL1A2 gene. BMD and bone area at the lumbar spine and hip were measured by dual-energy X-ray absorptiometry. Applying the QTDT (quantitative transmission disequilibrium test) program, we performed tests for population stratification, within-family association (via transmission disequilibrium test), total association, linkage, and linkage while modeling association. Significant or marginal within-family associations were found with BMD at the lumbar spine (P = 0.013), trochanter (P = 0.004), and total hip (P = 0.053) and with bone area at the intertrochanteric region (P = 0.024) and total hip (P = 0.048). The positive associations were confirmed in permutations except for bone area at total hip (P > 0.10). A small proportion (<1%) of the population variance of bone phenotypes can be explained by the MspI polymorphism; however, it may be underestimated given the significant population stratification detected in our sample. Due to the limited number of sib pairs in this sample, we did not find evidence of linkage. In summary, the MspI polymorphism is likely to be in linkage disequilibrium with a nearby functional mutation affecting BMD and bone area.

Adult↗

Systemic sclerosis: the susceptible host (genetics and environment).

It is becoming evident that several genetic factors participate in modulating susceptibility to SSc and its clinical manifestations. Some genes that specifically affect ECM metabolism and vascular function may be unique to SSc and scleroderma-related disorders; others, such as those genes involved in regulating immune tolerance, are likely shared with other autoimmune diseases. The effect of genetic variations (or polymorphisms) that are found in most of these genes taken individually will likely have only a small or modest effect on disease risk; only a few genetic variations are expected to be highly penetrant. Moreover, genetic studies in SSc have to deal with the additional issues of heterogeneous phenotypes, low disease prevalence in the general population, and an even greater paucity of multiplex families that makes traditional linkage studies difficult, if not impossible. Alternative approaches include allelic association studies, but conventional case-controls designs may be subject to selection bias and will require large sample sizes if the genes that are under investigation confer only modest (OR = 1.5-2.0) disease risk (Fig. 2). The simultaneous examination of several genes that are biologically relevant to a specific disease process to attain higher aggregate ORs, is one approach that was used in several reports that were cited in this review. The use of family-based controls, such as in the transmission-disequilibrium test (based on assessment of the transmitted or nontransmitted alleles that are associated with disease from heterozygous parents to affected offspring), would provide more robustness to spurious associations from population stratification, but is actually less powerful and efficient than case-control designs. Furthermore, for many late adult-onset diseases the effort required to obtain samples from living parents are for a variety of reasons not trivial. The success of these allelic association-based approaches depends on the identification of likely candidate disease genes (or at least markers in disequilibrium with disease genes), careful definition/ascertainment of disease phenotypes to minimize genetic heterogeneity, and for case-control designs, strategies to account for population stratification or admixture. The identification of candidate genes will be aided by rapid progress in the Human Genome Project and other genome efforts that will eventually identify all human genetic variations. Although this will lead to better understanding of the genes that might be involved in complex diseases, much work is required to understand the basic biology of how disease genotypes become clinical phenotypes. This is especially daunting in complex diseases, such as SSc, where the phenotype (including disease susceptibility and clinical presentation) is influenced by dynamic interactions between genetic variations and environment. Multi-center collaborative efforts with research paradigms that integrate genetic and environmental factors (including sociodemographic variables) will be required to elucidate the contribution of environment and genetics in the pathogenesis of SSc.

Environmental Exposure↗

Family-based study of DRD2 alleles in alcohol and drug dependence.

Numerous case-control studies have addressed the hypothesis that variant alleles of the dopamine D2 receptor gene (DRD2) increase the liability for alcohol and/or drug dependence, and both positive and negative results have been reported. Because population frequencies of these alleles vary considerably, the conflicting results could be due to population stratification bias. Using the transmission disequilibrium test, the present study examined linkage disequilibrium of alcohol and drug (opioid and/or cocaine) dependence with three DRD2 polymorphic systems: (a) TaqI A, (b) TaqI D, and (c) the functional -141CIns/Del promoter systems. DNA samples were collected from small nuclear families (SNFs), where one or more offspring met DSM-III-R or DSM-IV criteria for alcohol and/or drug dependence. Because positive association between DRD2 alleles and alcohol and/or drug dependence has been reported only in populations of European ancestry, we limited the present study to European Americans (EAs). No evidence for linkage disequilibrium was found for any of the polymorphic systems when examined in relation to any substance dependence, alcohol dependence (with or without drug dependence), or drug dependence (with or without alcohol dependence). These results are consistent with those from a recent family-based study of alcohol dependence. Together, these studies suggest that the conflicting findings from case-control studies of the association between alleles of DRD2 and substance dependence may be attributable to population stratification in some samples.

Alcoholism↗

Genetic association mapping at the crossroads: which test and why? Overview and practical guidelines.

Until about a decade ago, genetic association testing essentially meant case control association analysis using genetic markers. Concerns about population stratification propelled family-based tests of association into widespread use and challenged the classic case control design. The literature now contains a vast collection of different family-based methods, most of which are based on the transmission/disequilibrium test (TDT). Some methods extend the original TDT to accommodate multiallelic markers, variable pedigree constellations, multiple loci, etc. Other methods go beyond the original design of the TDT to detect genetic association via haplotype sharing. Most recently, we have witnessed a revival of case control methods that control for population stratification. The purpose of this review is to help orient readers to the rapidly developing methods of association testing and enhance their understanding of the basic principles of these approaches. We present an overview of the development of genetic association tests, with practical guidelines on which test might be the most suitable for a given study.

Case-Control Studies↗

Validity, efficiency, and robustness of a family-based test of association.

We propose a new test of linkage in the presence of allelic association that uses all available information in a sample of nuclear families, including parental phenotypes, genotypes from both affected and unaffected siblings, and families with homozygous parents. The test is based on the conditional framework developed by Rabinowitz and Laird [2000: Hum Hered 50:211-223] and is thus immune to population stratification and can be applied to families with any pattern of missing information. The test statistic is a conditional likelihood ratio based on a standard two-point linkage model with allelic association, where parameters are estimated from the sample. Through a simulation study, we determined that the proposed test has near optimal power for a wide range of scenarios, outperforming FBAT both when data were complete and when parental genotypes were missing, although differences between the two tests diminish as the genetic effect is reduced. To assess robustness, we also evaluated the performance of the tests under scenarios with population stratification and found that although there is a loss of efficiency, our proposed test remains a strong competitor to FBAT.

Alleles↗

Allowing for missing data at highly polymorphic genes when testing for maternal, offspring and maternal-fetal genotype incompatibility effects.

Genes can be associated with disease through an individual's inherited genotype, the maternal genotype or the interaction between these two. When the gene is highly polymorphic, it is more difficult to identify the gene's functional role than for less polymorphic loci, because different alleles at the locus may be associated with the disease through separate and joint effects from maternal and offspring genotypes. Family-based studies are used to test genetic associations because of their robustness to population stratification. However, parental genotype data are often missing, and omitting incompletely genotyped families is inefficient. Methods have been proposed to accommodate incomplete families in family-based association studies. They are not easily generalized to allow simultaneous examination of offspring allelic, maternal allelic and maternal-fetal genotype (MFG) incompatibility effects. Since many MFG incompatibility effects occur through matching between maternal and offspring's genotypes, we present an identity-by-state (IBS) framework to incorporate incomplete families in the MFG test when modeling genetic effects produced by a polymorphic gene. Using simulations, we examine the MFG test's performance with incomplete parental genotype data and an IBS framework. The MFG test using the IBS framework is immune to population stratification and efficiently uses information from incomplete families.

Algorithms↗

Transmission/disequilibrium tests for quantitative traits.

Spielman et al. [1993] proposed a transmission-disequilibrium test (TDT), based on marker data collected on affected offspring and their parents, to test for linkage between a genetic marker and a binary trait provided there is allelic association. It has been shown that this TDT is powerful and is not affected by allelic association due to population stratification in the absence of linkage. For quantitative traits, George and Elston [1987] proposed a likelihood method to detect the effect of a candidate gene in pedigree data when familial correlations are present. This test will detect allelic association but will do so in the absence of linkage. In this paper, we investigate two new likelihood-ratio test statistics for multi-generational quantitative traits to test either for linkage in the presence of allelic association or for allelic association in the presence of linkage, such as may be due to linkage disequilibrium. We compare these two tests analytically and by simulation with respect to 1) the sample size required for the asymptotic null distributions to be valid and 2) their power to detect association in those cases in which they are not sensitive to population stratification unless linkage is present. In general, 80 nuclear families with two children each and at least one heterozygous parent, or the equivalent number of children in large pedigrees, are enough for the asymptotic null distribution of the proposed conditional and TDT methods to be valid. The theoretical power is close to the simulated power except for the case of a recessive allele with low frequency. A sampling strategy is proposed that dramatically improves power.

Alleles↗