Quantification of the power of Hardy-Weinberg equilibrium testing to detect genotyping error

Deviation from Hardy-Weinberg equilibrium has become an accepted test for genotyping error. While it is generally considered that testing departures from Hardy-Weinberg equilibrium to detect genotyping error is not sensitive, little has been done to quantify this sensitivity. Therefore, we have examined various models of genotyping error, including error caused by neighboring SNPs that degrade the performance of genotyping assays. We then calculated the power of chi-square goodness-of-fit tests for deviation from Hardy-Weinberg equilibrium to detect such error. We have also examined the affects of neighboring SNPs on risk estimates in the setting of case-control association studies. We modeled the power of departure from Hardy-Weinberg equilibrium as a test to detect genotyping error and quantified the effect of genotyping error on disease risk estimates. Generally, genotyping error does not generate sufficient deviation from Hardy-Weinberg equilibrium to be detected. As expected, genotyping error due to neighboring SNPs attenuates risk estimates, often drastically. For the moment, the most widely accepted method of detecting genotyping error is to confirm genotypes by sequencing and/or genotyping via a separate method. While these methods are fairly reliable, they are also costly and time consuming.     

Description of microsatellite markers and genotyping performances using feathers and buccal swabs for the Ivory gull (Pagophila eburnea)

We report 22 new polymorphic microsatellites for the Ivory gull (Pagophila eburnea), and we describe how they can be efficiently co-amplified using multiplexed polymerase chain reactions. In addition, we report DNA concentration, amplification success, rates of genotyping errors and the number of genotyping repetitions required to obtain reliable data with three types of noninvasive or nondestructive samples: shed feathers collected in colonies, feathers plucked from living individuals and buccal swabs. In two populations from Greenland (n=21) and Russia (Severnaya Zemlya Archipelago, n=21), the number of alleles per locus varied between 2 and 17, and expected heterozygosity per population ranged from 0.18 to 0.92. Twenty of the markers conformed to Hardy-Weinberg and linkage equilibrium expectations. Most markers were easily amplified and highly reliable when analysed from buccal swabs and plucked feathers, showing that buccal swabbing is a very efficient approach allowing good quality DNA retrieval. Although DNA amplification success using single shed feathers was generally high, the genotypes obtained from this type of samples were prone to error and thus need to be amplified several times. The set of microsatellite markers described here together with multiplex amplification conditions and genotyping error rates will be useful for population genetic studies of the Ivory gull.     

How Many Genetic Variants Remain to Be Discovered?

A great majority of genetic markers discovered in recent genome-wide association studies have small effect sizes, and they explain only a small fraction of the genetic contribution to the diseases. How many more variants can we expect to discover and what study sizes are needed? We derive the connection between the cumulative risk of the SNP variants to the latent genetic risk model and heritability of the disease. We determine the sample size required for case-control studies in order to achieve a certain expected number of discoveries in a collection of most significant SNPs. Assuming similar allele frequencies and effect sizes of the currently validated SNPs, complex phenotypes such as type-2 diabetes would need approximately 800 variants to explain its 40% heritability. Much smaller numbers of variants are needed if we assume rare-variants but higher penetrance models. We estimate that up to 50,000 cases and an equal number of controls are needed to discover 800 common low-penetrant variants among the top 5000 SNPs. Under common and rare low-penetrance models, the very large studies required to discover the numerous variants are probably at the limit of practical feasibility. Under rare-variant with medium- to high-penetrance models (odds-ratios between 1.6 and 4.0), studies comparable in size to many existing studies are adequate provided the genotyping technology can interrogate more and rarer variants.     

Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies

We report the development and validation of experimental methods, study designs, and analysis software for pooling-based genomewide association (GWA) studies that use high-throughput single-nucleotide-polymorphism (SNP) genotyping microarrays. We first describe a theoretical framework for establishing the effectiveness of pooling genomic DNA as a low-cost alternative to individually genotyping thousands of samples on high-density SNP microarrays. Next, we describe software called "GenePool," which directly analyzes SNP microarray probe intensity data and ranks SNPs by increased likelihood of being genetically associated with a trait or disorder. Finally, we apply these methods to experimental case-control data and demonstrate successful identification of published genetic susceptibility loci for a rare monogenic disease (sudden infant death with dysgenesis of the testes syndrome), a rare complex disease (progressive supranuclear palsy), and a common complex disease (Alzheimer disease) across multiple SNP genotyping platforms. On the basis of these theoretical calculations and their experimental validation, our results suggest that pooling-based GWA studies are a logical first step for determining whether major genetic associations exist in diseases with high heritability.     

Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer

Genome-wide association studies (GWAS) have identified 14 tagging single nucleotide polymorphisms (tagSNPs) that are associated with the risk of colorectal cancer (CRC), and several of these tagSNPs are near bone morphogenetic protein (BMP) pathway loci. The penalty of multiple testing implicit in GWAS increases the attraction of complementary approaches for disease gene discovery, including candidate gene- or pathway-based analyses. The strongest candidate loci for additional predisposition SNPs are arguably those already known both to have functional relevance and to be involved in disease risk. To investigate this proposition, we searched for novel CRC susceptibility variants close to the BMP pathway genes GREM1 (15q13.3), BMP4 (14q22.2), and BMP2 (20p12.3) using sample sets totalling 24,910 CRC cases and 26,275 controls. We identified new, independent CRC predisposition SNPs close to BMP4 (rs1957636, P = 3.93×10(-10)) and BMP2 (rs4813802, P = 4.65×10(-11)). Near GREM1, we found using fine-mapping that the previously-identified association between tagSNP rs4779584 and CRC actually resulted from two independent signals represented by rs16969681 (P = 5.33×10(-8)) and rs11632715 (P = 2.30×10(-10)). As low-penetrance predisposition variants become harder to identify-owing to small effect sizes and/or low risk allele frequencies-approaches based on informed candidate gene selection may become increasingly attractive. Our data emphasise that genetic fine-mapping studies can deconvolute associations that have arisen owing to independent correlation of a tagSNP with more than one functional SNP, thus explaining some of the apparently missing heritability of common diseases.     

Effect of CD14 -260C>T polymorphism on the mortality of critically ill patients

The CD14 receptor seems to be an important part of the innate immune system. A mutant CD14 can produce a reduced signal in response to infection, as a result of which an adequate inflammatory innate response is not induced, leading to a systemic infection. Defects in the innate immunity increase patient susceptibility to systemic infections and can produce a deregulated inflammatory response causing sepsis, organ failure or death in critically ill patients. We evaluated the CD14 -260C>T polymorphism genotyping as a genetic tool for risk evaluation of critically ill patients admitted to an intensive care unit (ICU) in Southern Brazil. We monitored the patients daily during their entire ICU and post-ICU (hospital) stay (measured from the ICU admission day to a maximum of 224 days). A total of 85 patients, aged 19-95 years (mean = 56 years, median = 58 years), were included in this study. Patient mortality was 58.8%. The genotypic (TT = 0.27, TC = 0.41, CC = 0.32) and allelic (T = 0.48, C = 0.52) frequencies did not differ from the values expected by the Hardy-Weinberg model and genotype distribution was random for all clinical characteristics at ICU admission. We found a statistically significant difference favouring the survival of patients with TT genotype (P = 0.042), suggesting that this CD14 gene polymorphism could be a candidate for further study in the search for a complementary prognostic tool for patient risk evaluation. Our study describes, for the first time, the effect of the CD14 gene polymorphism in critically ill Brazilian patients. Our data suggest that patients carrying the TT genotype have a better survival outcome.     

A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic

Resequencing is an emerging tool for identification of rare disease-associated mutations. Rare mutations are difficult to tag with SNP genotyping, as genotyping studies are designed to detect common variants. However, studies have shown that genetic heterogeneity is a probable scenario for common diseases, in which multiple rare mutations together explain a large proportion of the genetic basis for the disease. Thus, we propose a weighted-sum method to jointly analyse a group of mutations in order to test for groupwise association with disease status. For example, such a group of mutations may result from resequencing a gene. We compare the proposed weighted-sum method to alternative methods and show that it is powerful for identifying disease-associated genes, both on simulated and Encode data. Using the weighted-sum method, a resequencing study can identify a disease-associated gene with an overall population attributable risk (PAR) of 2%, even when each individual mutation has much lower PAR, using 1,000 to 7,000 affected and unaffected individuals, depending on the underlying genetic model. This study thus demonstrates that resequencing studies can identify important genetic associations, provided that specialised analysis methods, such as the weighted-sum method, are used.     

The epitheliogenesis imperfecta locus maps to equine chromosome 8 in American Saddlebred horses

Epitheliogenesis imperfecta (EI) is a hereditary junctional mechanobullous disease that occurs in newborn American Saddlebred foals. The pathological signs of epitheliogenesis imperfecta closely match a similar disease in humans known as Herlitz junctional epidermolysis bullosa, which is caused by a mutation in one of the genes (LAMA3, LAMB3 and LAMC2) coding for the subunits of the laminin 5 protein (laminin alpha3, laminin beta3 and laminin gamma2). The LAMA3 gene has been assigned to equine chromosome 8 and LAMB3 and LAMC2 have been mapped to equine chromosome 5. Linkage disequilibrium between microsatellite markers that mapped to equine chromosome 5 and equine chromosome 8 and the EI disease locus was tested in American Saddlebred horses. The allele frequencies of microsatellite alleles at 11 loci were determined for both epitheliogenesis imperfecta affected and unaffected populations of American Saddlebred horses by genotyping and direct counting of alleles. These were used to determine fit to Hardy-Weinberg equilibrium for control and EI populations using Chi square analysis. Two microsatellite loci located on equine chromosome 8q, ASB14 and AHT3, were not in Hardy-Weinberg equilibrium in affected American Saddlebred horses. In comparison, all of the microsatellite markers located on equine chromosome 5 were in Hardy-Weinberg equilibrium in affected American Saddlebred horses. This suggested that the EI disease locus was located on equine chromosome 8q, where LAMA3 is also located.     

Examination of Candidate Exonic Variants for Association to Alzheimer Disease in the Amish

Alzheimer disease (AD) is the most common cause of dementia. As with many complex diseases, the identified variants do not explain the total expected genetic risk that is based on heritability estimates for AD. Isolated founder populations, such as the Amish, are advantageous for genetic studies as they overcome heterogeneity limitations associated with complex population studies. We determined that Amish AD cases harbored a significantly higher burden of the known risk alleles compared to Amish cognitively normal controls, but a significantly lower burden when compared to cases from a dataset of unrelated individuals. Whole-exome sequencing of a selected subset of the overall study population was used as a screening tool to identify variants located in the regions of the genome that are most likely to contribute risk. By then genotyping the top candidate variants from the known AD genes and from linkage regions implicated previous studies in the full dataset, new associations could be confirmed. The most significant result (p = 0.0012) was for rs73938538, a synonymous variant in LAMA1 within the previously identified linkage peak on chromosome 18. However, this association is specific to the Amish and did not generalize when tested in a dataset of unrelated individuals. These results suggest that additional risk variation in the Amish remains to be identified and likely resides outside of the classical protein coding gene regions.     

Polymorphism Interaction Analysis (PIA): a method for investigating complex gene-gene interactions

Background  

The risk of common diseases is likely determined by the complex interplay between environmental and genetic factors, including single nucleotide polymorphisms (SNPs). Traditional methods of data analysis are poorly suited for detecting complex interactions due to sparseness of data in high dimensions, which often occurs when data are available for a large number of SNPs for a relatively small number of samples. Validation of associations observed using multiple methods should be implemented to minimize likelihood of false-positive associations. Moreover, high-throughput genotyping methods allow investigators to genotype thousands of SNPs at one time. Investigating associations for each individual SNP or interactions between SNPs using traditional approaches is inefficient and prone to false positives.     

Genome-wide association study as a method to analyze the genome architecture in polygenic diseases,with the example of multiple sclerosis

Genome-wide association study (GWAS) provides a powerful tool for investigating the genetic architecture of human polygenic diseases and is generally used to identify the genetic factors of disease susceptibility, clinical phenotypes, and treatment response. The differences in allele frequencies of single nucleotide polymorphisms (SNPs) distributed throughout the genome are analyzed with a microarray technique or other technologies that allow simultaneous genotyping at several tens of thousands to several millions of SNPs per sample. Owing to its power to find out highly reliable differences between patients and controls, GWAS became a common approach to identification of the genetic susceptibility factors in complex diseases of a polygenic nature. Using multiple sclerosis (MS) as a prototype complex disease, the review considers the main achievements and challenges of using GWAS to identify the genes involved in the disease and, therefore, to better understand the pathogenetic molecular mechanisms and genetic risk factors.     

Use of parents, sibs, and unrelated controls for detection of associations between genetic markers and disease.

Detecting the association between genetic markers and complex diseases can be a critical first step toward identification of the genetic basis of disease. Misleading associations can be avoided by choosing as controls the parents of diseased cases, but the availability of parents often limits this design to early-onset disease. Alternatively, sib controls offer a valid design. A general multivariate score statistic is presented, to detect the association between a multiallelic genetic marker locus and affection status; this general approach is applicable to designs that use parents as controls, sibs as controls, or even unrelated controls whose genotypes do not fit Hardy-Weinberg proportions or that pool any combination of these different designs. The benefit of this multivariate score statistic is that it will tend to be the most powerful method when multiple marker alleles are associated with affection status. To plan these types of studies, we present methods to compute sample size and power, allowing for varying sibship sizes, ascertainment criteria, and genetic models of risk. The results indicate that sib controls have less power than parental controls and that the power of sib controls can be increased by increasing either the number of affected sibs per sibship or the number of unaffected control sibs. The sample-size results indicate that the use of sib controls to test for associations, by use of either a single-marker locus or a genomewide screen, will be feasible for markers that have a dominant effect and for common alleles having a recessive effect. The results presented will be useful for investigators planning studies using sibs as controls.     

Epistasis and Its Implications for Personal Genetics

The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity.     

Fine-Mapping the HOXB Region Detects Common Variants Tagging a Rare Coding Allele: Evidence for Synthetic Association in Prostate Cancer

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10⁻¹⁴). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.     

不宁腿综合征遗传学研究进展

不宁腿综合征(Restless legs syndrome, RLS)遗传学研究近年来获得了许多重要的进展, 极大地丰富了对于这种疾病分子机制的认识。RLS是一种常见的复杂疾病, 几个遗传流行病学和双生子研究对RLS遗传组分进行了剖析, 说明RLS是一个遗传性很强的性状, 其遗传力约为50%。采用基于模型的连锁分析方法或者是不依赖于模型的连锁分析方法目前已定位了5个重要的RLS疾病连锁位点: 12q13-23, 14q13-21, 9p24-22, 2q33和20p13, 为定位克隆RLS致病基因或者易感基因提供了连锁图谱。最新基于高通量的SNPs分型平台开展的全基因组分析确立3个与RLS显著关联的区域: 6p21.2, 2p14和15q23。文章结合作者近年来从事不宁腿综合征遗传学的研究工作, 对该领域的重要成果进行了汇总和评述。     

The genetic epidemiology of human primary osteoarthritis: current status

Osteoarthritis (OA) is a common disease characterised by the degeneration of the cartilage of synovial joints such as the hip and knee. In the past ten years a large number of twin-pair, sibling-risk and segregation studies have been conducted on the disease, and these have revealed a major genetic component that is transmitted in a nonmendelian manner. OA therefore fits best into the complex, multifactorial class of common diseases. With a genetic component established, genome-wide linkage scans were performed, and these uncovered several genomic intervals likely to harbour OA susceptibility. In the past few years these intervals have started to yield genes containing OA-associated variants. This is therefore a very exciting period in the molecular genetic analysis of this common disease. The genes that have so far been implicated in susceptibility include the interleukin 1 gene (IL1) cluster at chromosome 2q11.2-q13, the matrilin 3 gene (MATN3) at 2p24.1, the IL-4 receptor alpha-chain gene (IL4R) at 16p12.1, the secreted frizzled-related protein 3 gene (FRZB) at 2q32.1, the metalloproteinase gene ADAM12 at 10q26.2 and, most recently, the asporin gene (ASPN) at 9q22.31. The evidence for involvement of these genes in OA is more compelling for some than others, with the IL1 and ASPN associations being the most convincing to date. It is imperative that the veracity of each of the associations be tested by genotyping additional cohorts and that their global relevance be assessed by genotyping OA cohorts from different ethnic backgrounds. The gene products of IL1, IL4R, FRZB and ASPN regulate cartilage chondrocyte differentiation and survival, and their effects on the chondrocyte are potentially amenable to therapeutic intervention. The latest genetics is therefore providing new insights for the development of novel OA treatments.     

Linkage analysis identifies a novel locus for restless legs syndrome on chromosome 2q in a South Tyrolean population isolate

Restless legs syndrome (RLS) is a common neurological condition with three loci (12q, 14q, and 9p) described so far, although none of these genes has yet been identified. We report a genomewide linkage scan of patients with RLS (n=37) assessed in a population isolate (n=530) of South Tyrol (Italy). Using both nonparametric and parametric analyses, we initially obtained suggestive evidence of a novel locus on chromosome 2q, with nominal evidence of linkage on chromosomes 5p and 17p. Follow-up genotyping yielded significant evidence of linkage (nonparametric LOD score 5.5, P相似文献   

Current strategies in the search for low penetrance genes in cancer

The genetic etiology of most cancers remains largely unclear and it has been hypothesised that common genetic variants with modest effects on disease susceptibility cause the bulk of this unexplained risk. Case-control association studies are considered the most effective strategy to identify these low-penetrance genes. While traditionally, such studies have focused on putative functional single nucleotide polymorphisms (SNPs) in candidate genes, a more comprehensive approach can now be taken, as a result of a number of recent developments: the mapping of the human genome, including the identification of almost ten million SNPs; and the development of high-throughput genotyping technologies that enable hundreds of thousands of SNPs to be genotyped in a single reaction, in multiple subjects and at an affordable cost. All common genomic variation can be captured by genotyping SNPs in gene-, pathway- or genome-wide-based strategies and these are now being applied to many diseases, including cancer. We present an outline of each of these approaches, including recent published examples, and discuss a number of challenges that remain to be addressed.     

Genome-wide association study of allergic diseases in Russians of Western Siberia

Genome-wide association studies are currently considered as one of the most powerful tools to establishing the genetic basis of complex diseases. A number of such studies were carried out for allergic diseases; however, in Russian population this analysis has not been performed so far. For the first time, we performed genome-wide association study of allergic diseases in Russian inhabitants of Western Siberia. Two new loci associated with childhood bronchial asthma were identified (20q13.12, rs2425656, P = 1.99 x 10(-7); 1q32.1, rs3817222, rs12734001, P = 2.18 x 10(-7) and 2.79 x 10(-7), respectively) as well as one locus, associated with allergic rhinitis (2q36.1, rs1597167, P = 3.69 x 10(-7)). Genes located in the loci, YWHAB and PPP1R12B for asthma and KCNE4 for allergic rhinitis, are new genes for these diseases. It was found that BAT1 (6p21.33), MAGI2 (7q21.11) and ACPL2 (3q23) genes are, likely, common (syntropic) genes of allergic disease and a topic sensitisation. It was shown that RIT2 (18q12.3) and (5q31.1) genes can be involved in the control of lung function. The results of the study enlarge the body of data on genetic factors of allergy and expand the list of genes underlying these diseases.     

Combined effects of thrombosis pathway gene variants predict cardiovascular events

The genetic background of complex diseases is proposed to consist of several low-penetrance risk loci. Addressing this complexity likely requires both large sample size and simultaneous analysis of different predisposing variants. We investigated the role of four thrombosis genes: coagulation factor V (F5), intercellular adhesion molecule 1 (ICAM1), protein C (PROC), and thrombomodulin (THBD) in cardiovascular diseases. Single allelic gene variants and their pair-wise combinations were analyzed in two independently sampled population cohorts from Finland. From among 14,140 FINRISK participants (FINRISK-92, n = 5,999 and FINRISK-97, n = 8,141), we selected for genotyping a sample of 2,222, including 528 incident cardiovascular disease (CVD) cases and random subcohorts totaling 786. To cover all known common haplotypes (>10%), 54 single nucleotide polymorphisms (SNPs) were genotyped. Classification-tree analysis identified 11 SNPs that were further analyzed in Cox's proportional hazard model as single variants and pair-wise combinations. Multiple testing was controlled by use of two independent cohorts and with false-discovery rate. Several CVD risk variants were identified: In women, the combination of F5 rs7542281 x THBD rs1042580, together with three single F5 SNPs, was associated with CVD events. Among men, PROC rs1041296, when combined with either ICAM1 rs5030341 or F5 rs2269648, was associated with total mortality. As a single variant, PROC rs1401296, together with the F5 Leiden mutation, was associated with ischemic stroke events. Our strategy to combine the classification-tree analysis with more traditional genetic models was successful in identifying SNPs-acting either in combination or as single variants--predisposing to CVD, and produced consistent results in two independent cohorts. These results suggest that variants in these four thrombosis genes contribute to arterial cardiovascular events at population level.