Population admixture may appear to mask, change or reverse genetic effects of genes underlying complex traits

Association of ARRDC3 and NFIA variants with bovine congestive heart failure in feedlot cattle

BACKGROUND

Bovine congestive heart failure (BCHF) has become increasingly prevalent among feedlot cattle in the Western Great Plains of North America with up to 7% mortality in affected herds. BCHF is an untreatable complex condition involving pulmonary hypertension that culminates in right ventricular failure and death. Genes associated with BCHF in feedlot cattle have not been previously identified. Our aim was to search for genomic regions associated with this disease.

METHODS

A retrospective, matched case-control design with 102 clinical BCHF cases and their unaffected pen mates was used in a genome-wide association study. Paired nominal data from approximately 560,000 filtered single nucleotide polymorphisms (SNPs) were analyzed with McNemar's test.

RESULTS

Two independent genomic regions were identified as having the most significant association with BCHF: the arrestin domain-containing protein 3 gene ( ARRDC3), and the nuclear factor IA gene ( NFIA, mid- p-values, 1x10 -8 and 2x10 -7, respectively). Animals with two copies of risk alleles at either gene were approximately eight-fold more likely to have BCHF than their matched pen mates with either one or zero risk alleles at both genes (CI 95 = 3-17). Further, animals with two copies of risk alleles at both genes were 28-fold more likely to have BCHF than all others ( p-value = 1×10 -7, CI 95 = 4-206). A missense variant in ARRDC3 (C182Y) represents a potential functional variant since the C182 codon is conserved among all other jawed vertebrate species observed. A two-SNP test with markers in both genes showed 29% of 273 BCHF cases had homozygous risk genotypes in both genes, compared to 2.5% in 198 similar unaffected feedlot cattle. This and other DNA tests may be useful for identifying feedlot animals with the highest risk for BCHF in the environments described here.

CONCLUSIONS

Although pathogenic roles for variants in the ARRDC3 and NFIA genes are unknown, their discovery facilitates classifying animals by genetic risk and allows cattle producers to make informed decisions for selective breeding and animal health management.

Association of ARRDC3 and NFIA variants with bovine congestive heart failure in feedlot cattle

Background

Bovine congestive heart failure (BCHF) has become increasingly prevalent among feedlot cattle in the Western Great Plains of North America with up to 7% mortality in affected herds. BCHF is an untreatable complex condition involving pulmonary hypertension that culminates in right ventricular failure and death. Genes associated with BCHF in feedlot cattle have not been previously identified. Our aim was to search for genomic regions associated with this disease.

Methods

A retrospective, matched case-control design with 102 clinical BCHF cases and their unaffected pen mates was used in a genome-wide association study. Paired nominal data from approximately 560,000 filtered single nucleotide polymorphisms (SNPs) were analyzed with McNemar's test.

Results

Two independent genomic regions were identified as having the most significant association with BCHF: the arrestin domain-containing protein 3 gene ( ARRDC3), and the nuclear factor IA gene ( NFIA, mid- p-values, 1x10 -8 and 2x10 -7, respectively). Animals with two copies of risk alleles at either gene were approximately eight-fold more likely to have BCHF than their matched pen mates with either one or zero risk alleles at both genes (CI 95 = 3-17). Further, animals with two copies of risk alleles at both genes were 28-fold more likely to have BCHF than all others ( p-value = 1×10 -7, CI 95 = 4-206). A missense variant in ARRDC3 (C182Y) represents a potential functional variant since the C182 codon is conserved among all other jawed vertebrate species observed. A two-SNP test with markers in both genes showed 29% of 273 BCHF cases had homozygous risk genotypes in both genes, compared to 2.5% in 198 similar unaffected feedlot cattle. This and other DNA tests may be useful for identifying feedlot animals with the highest risk for BCHF in the environments described here.

Conclusions

Although pathogenic roles for variants in the ARRDC3 and NFIA genes are unknown, their discovery facilitates classifying animals by genetic risk and allows cattle producers to make informed decisions for selective breeding and animal health management.

Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels

KEY MESSAGE

An original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and dominance QTLs involved in heterotic group complementarity and hybrid performance. Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from inter-group crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple-environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibited overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs contributed to a part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrate how admixed panels combined with dedicated GWAS modeling allow the identification of new QTLs that could not be revealed by a classical hybrid panel analyzed with traditional modeling.

Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.

Canditate metabolites for ash dieback tolerance in Fraxinus excelsior

Ash dieback, a forest epidemic caused by the invasive fungus Hymenoscyphus fraxineus, threatens ash trees throughout Europe. Within Fraxinus excelsior populations, a small proportion of genotypes show a low susceptibility to the pathogen. We compared the metabolomes from a cohort of low-susceptibility ash genotypes with a cohort of high-susceptibility ash genotypes. This revealed two significantly different chemotypes. A total of 64 candidate metabolites associated with reduced or increased susceptibility in the chemical families secoiridoids, coumarins, flavonoids, phenylethanoids, and lignans. Increased levels of two coumarins, fraxetin and esculetin, were strongly associated with reduced susceptibility to ash dieback. Both coumarins inhibited the growth of H. fraxineus in vitro when supplied at physiological concentrations, thereby validating their role as markers for low susceptibility to ash dieback. Similarly, fungal growth inhibition was observed when the methanolic bark extract of low-susceptibility ash genotypes was supplied. Our findings indicate the presence of constitutive chemical defense barriers against ash dieback in ash.

The Vitamin D Receptor Gene Polymorphisms in Asthmatic Children: A Case-Control Study

Background: The association between vitamin D receptor (VDR) polymorphisms and the risk of asthma remains unclear. This study aimed to investigate the effect of VDR gene polymorphisms and VDR mRNA expression levels on respiratory function, nitric oxide levels in expiratory air, and serum vitamin D levels in children with asthma. Materials and Methods: The study included 80 healthy children (control group) and 100 asthmatic children (asthma group) between the age of 5 and 18 years. The VDR genotypes (ApaI, TaqI, and FokI) and VDR mRNA levels were determined in all groups. Results: There was no statistically significant difference in vitamin D levels between the asthma group and the control group (P > 0.05). A significant association was found between both genotype (CC) of the TaqI polymorphism [odds ratio (OR) = 0.2, 95% confidence interval (CI) (0.07-0.5), P = 0.003] and genotype (CA) of ApaI polymorphisms [OR = 0.2, 95% CI (0.07-0.8), P = 0.02], and asthma risk. In addition, when single-nucleotide polymorphism allelic frequencies between asthma and control groups were compared there is no significant association (P > 0.05). When compared to control group, VDR mRNA expression in asthma group decreased in genotypes CC and CA of ApaI and in genotypes TT and TC of TaqI (P < 0.05). Conclusion: The results provide supporting evidence for an association between TaqI and ApaI polymorphisms and asthma susceptibility.

Modeling Heterogeneity in the Genetic Architecture of Ethnically Diverse Groups Using Random Effect Interaction Models

In humans, most genome-wide association studies have been conducted using data from Caucasians and many of the reported findings have not replicated in other populations. This lack of replication may be due to statistical issues (small sample sizes or confounding) or perhaps more fundamentally to differences in the genetic architecture of traits between ethnically diverse subpopulations. What aspects of the genetic architecture of traits vary between subpopulations and how can this be quantified? We consider studying effect heterogeneity using Bayesian random effect interaction models. The proposed methodology can be applied using shrinkage and variable selection methods, and produces useful information about effect heterogeneity in the form of whole-genome summaries (e.g., the proportions of variance of a complex trait explained by a set of SNPs and the average correlation of effects) as well as SNP-specific attributes. Using simulations, we show that the proposed methodology yields (nearly) unbiased estimates when the sample size is not too small relative to the number of SNPs used. Subsequently, we used the methodology for the analyses of four complex human traits (standing height, high-density lipoprotein, low-density lipoprotein, and serum urate levels) in European-Americans (EAs) and African-Americans (AAs). The estimated correlations of effects between the two subpopulations were well below unity for all the traits, ranging from 0.73 to 0.50. The extent of effect heterogeneity varied between traits and SNP sets. Height showed less differences in SNP effects between AAs and EAs whereas HDL, a trait highly influenced by lifestyle, exhibited a greater extent of effect heterogeneity. For all the traits, we observed substantial variability in effect heterogeneity across SNPs, suggesting that effect heterogeneity varies between regions of the genome.

Tamoxifen and CYP2D6: A Controversy in Pharmacogenetics

Tamoxifen reduces the rate of breast cancer recurrence by about one-half. It is converted to more active metabolites by enzymes encoded by polymorphic genes, including cytochrome P450 2D6 (CYP2D6) and transported by ATP-binding cassette transporters. Genetic polymorphisms that confer reduced CYP2D6 activity or concurrent use of CYP2D6-inhibiting drugs may reduce the clinical efficacy of tamoxifen. The issue of the clinical utility of CYP2D6 genotype testing is subject to considerable and ongoing academic and clinical controversy. In this chapter, we outline tamoxifen's clinical pharmacology and give an overview of the research to date on the association between CYP2D6 inhibition and tamoxifen effectiveness. Based on the evidence to date, the impact of drug-induced and/or gene-induced inhibition of CYP2D6 activity is likely to be null or small, or at most moderate in subjects carrying two reduced function alleles. Future research should examine the effect of polymorphisms in genes encoding enzymes in tamoxifen's complete metabolic pathway, should comprehensively evaluate other biomarkers that affect tamoxifen effectiveness, such as the transport enzymes, and focus on subgroups of patients, such as premenopausal breast cancer patients, for whom tamoxifen is the only guideline approved endocrine therapy.

Collaborative cross mice in a genetic association study reveal new candidate genes for bone microarchitecture

Background

The microstructure of trabecular bone is a composite trait governed by a complex interaction of multiple genetic determinants. Identifying these genetic factors should significantly improve our ability to predict of osteoporosis and its associated risks. Genetic mapping using collaborative cross mice (CC), a genetically diverse recombinant inbred mouse reference panel, offers a powerful tool to identify causal loci at a resolution under one mega base-pairs, with a relatively small cohort size.

Here, we utilized 31 CC lines (160 mice of both sexes in total) to perform genome-wide haplotype mapping across 77,808 single-nucleotide polymorphisms (SNPs). Haplotype scans were refined by imputation with the catalogue of sequence variation segregating in the CC to suggest potential candidate genes. Trabecular traits were obtained following microtomographic analysis, performed on 10-μm resolution scans of the femoral distal metaphysis. We measured the trabecular bone volume fraction (BV/TV), number (Tb.N), thickness (Tb.Th), and connectivity density (Conn.D).

Results

Heritability of these traits ranged from 0.6 to 0.7. In addition there was a significant (P < 0.01) sex effect in all traits except Tb.Th. Our haplotype scans yielded six quantitative trait loci (QTL) at 1 % false discovery rate; BV/TV and Tb.Th produced two proximal loci each, on chromosome 2 and 7, respectively, and Tb.N and Conn.D yielded one locus on chromosomes 8 and 14, respectively. We identified candidate genes with previously-reported functions in bone biology, and implicated unexpected genes whose function in bone biology has yet to be assigned. Based on the literature, among the genes that ranked particularly high in our analyses (P < 10^-6) and which have a validated causal role in skeletal biology, are Avp, Oxt, B2m (associated with BV/TV), Cnot7 (with Tb.N), Pcsk6, Rgma (with Tb.Th), Rb1, and Cpb2 (with Conn.D). Other candidate genes strongly suggested by our analyses are Sgcz, Fgf20 (associated with Tb.N), and Chd2 (with Tb.Th).

Conclusion

We have demonstrated for the first time genome-wide significant association between several genetic loci and trabecular microstructural parameters for genes with previously reported experimental observations, as well as proposing a role for new candidate genes with no previously characterized skeletal function.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2213-x) contains supplementary material, which is available to authorized users.

Systemic lupus erythematosus-associated neutrophil cytosolic factor 2 mutation affects the structure of NADPH oxidase complex

In a case-control association study with 3716 North Americans of Hispanic descent and 4867 North Americans of European descent, we show that the associations of rs17849502 (NCF2 His-389 → Gln) and rs13306575 (NCF2 Arg-395 → Trp) with systemic lupus erythematosus are independent. We have shown that His-389 → Gln disrupts the binding of NCF2 to the ZF domain of VAV1, resulting in decreased NADPH oxidase activity. With respect to Arg-395 → Trp, using protein docking and structure analyses, we provide a model for the involvement of this mutation in the structure and function of the NADPH oxidase complex. This model assigns a central role to Arg-395 in the structure and stability of the quaternary NCF2/NCF4/VAV1/RAC1 NADPH oxidase complex. Arg-395 stabilizes the C-terminal tail of NCF4 and the conformation of NCF2 loop 395-402, which in turn stabilize the evolutionarily conserved interactions of NCF2/NCF4 with the DH domain of VAV1 and RAC1 region 120-137. Our findings are consistent with the high levels of conservation of all of the residues involved in these interactions.

GWAS identifies novel SLE susceptibility genes and explains the association of the HLA region

In a Genome Wide Association Study (GWAS) of individuals of European ancestry afflicted with Systemic Lupus Erythematosus (SLE) the extensive utilization of imputation, stepwise multiple regression, lasso regularization, and increasing study power by utilizing False Discovery Rate (FDR) instead of a Bonferroni multiple test correction enabled us to identify 13 novel non-human leukocyte antigen (HLA) genes and confirmed the association of 4 genes previously reported to be associated. Novel genes associated with SLE susceptibility included two transcription factors (EHF, and MED1), two components of the NFκB pathway (RASSF2 and RNF114), one gene involved in adhesion and endothelial migration (CNTN6), and two genes involved in antigen presentation (BIN1 and SEC61G). In addition, the strongly significant association of multiple single nucleotide polymorphisms (SNPs) in the HLA region was assigned to HLA alleles and serotypes and deconvoluted into four primary signals. The novel SLE-associated genes point to new directions for both the diagnosis and treatment of this debilitating autoimmune disease.

Proliferator-activated receptor gamma Pro12Ala interacts with the insulin receptor substrate 1 Gly972Arg and increase the risk of insulin resistance and diabetes in the mixed ancestry population from South Africa

BACKGROUND

The peroxisome proliferator-activated receptor gamma (PPARG), Pro12Ala and the insulin receptor substrate (IRS1), Gly972Arg confer opposite effects on insulin resistance and type 2 diabetes mellitus (T2DM). We investigated the independent and joint effects of PPARG Pro12Ala and IRS1 Gly972Arg on markers of insulin resistance and T2DM in an African population with elevated risk of T2DM. In all 787 (176 men) mixed-ancestry adults from the Bellville-South community in Cape Town were genotyped for PPARG Pro12Ala and IRS1 Gly972Arg by two independent laboratories. Glucose tolerance status and insulin resistance/sensitivity were assessed.

RESULTS

Genotype frequencies were 10.4% (PPARG Pro12Ala) and 7.7% (IRS1 Gly972Arg). Alone, none of the polymorphisms predicted prevalent T2DM, but in regression models containing both alleles and their interaction term, PPARG Pro12 conferred a 64% higher risk of T2DM. Furthermore PPARG Pro12 was positively associated in adjusted linear regressions with increased 2-hour post-load insulin in non-diabetic but not in diabetic participants.

CONCLUSION

The PPARG Pro12 is associated with insulin resistance and this polymorphism interacts with IRS1 Gly972Arg, to increase the risk of T2DM in the mixed-ancestry population of South Africa. Our findings require replication in a larger study before any generalisation and possible application for risk stratification.

Using the unified relationship matrix adjusted by breed-wise allele frequencies in genomic evaluation of a multibreed population

The observed low accuracy of genomic selection in multibreed and admixed populations results from insufficient linkage disequilibrium between markers and trait loci. Failure to remove variation due to the population structure may also hamper the prediction accuracy. We verified if accounting for breed origin of alleles in the calculation of genomic relationships would improve the prediction accuracy in an admixed population. Individual breed proportions derived from the pedigree were used to estimate breed-wise allele frequencies (AF). Breed-wise and across-breed AF were estimated from the currently genotyped population and also in the base population. Genomic relationship matrices (G) were subsequently calculated using across-breed (GAB) and breed-wise (GBW) AF estimated in the currently genotyped and also in the base population. Unified relationship matrices were derived by combining different G with pedigree relationships in the evaluation of genomic estimated breeding values (GEBV) for genotyped and ungenotyped animals. The validation reliabilities and inflation of GEBV were assessed by a linear regression of deregressed breeding value (deregressed proofs) on GEBV, weighted by the reliability of deregressed proofs. The regression coefficients (b1) from GAB ranged from 0.76 for milk to 0.90 for protein. Corresponding b1 terms from GBW ranged from 0.72 to 0.88. The validation reliabilities across 4 evaluations with different G were generally 36, 40, and 46% for milk, protein, and fat, respectively. Unexpectedly, validation reliabilities were generally similar across different evaluations, irrespective of AF used to compute G. Thus, although accounting for the population structure in GBW tends to simplify the blending of genomic- and pedigree-based relationships, it appeared to have little effect on the validation reliabilities.

Inherited susceptibility to chronic lymphocytic leukemia: evidence and prospects for the future

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the United States and one of the most heritable cancers. A family history of the disease is perhaps the best defined risk factor, and approximately 15-20% of CLL patients have a family member with CLL or a related lymphoproliferative disorder. Much effort has been devoted to trying to elucidate the mechanisms underlying this genetic risk. Familial CLL appears to be clinically and biologically similar to sporadic CLL, and most if not all CLL appears to be preceded by monoclonal B-cell lymphocytosis (MBL), which does appear to occur at higher frequency in relatives in families with CLL. Neither linkage studies nor candidate gene association studies have proven particularly informative in CLL, but genomewide association studies have identified multiple low-risk variants that together explain about 16% of the familial risk of CLL. Studies of individual families have identified higher-risk single nucleotide polymorphisms or copy number variants associated with disease risk in those families. Current efforts to identify additional risk loci are focused on applying next-generation sequencing to the germline of informative CLL families as well as individuals with sporadic CLL.

Genome-wide pathway association studies of multiple correlated quantitative phenotypes using principle component analyses

Genome-wide pathway association studies provide novel insight into the biological mechanism underlying complex diseases. Current pathway association studies primarily focus on single important disease phenotype, which is sometimes insufficient to characterize the clinical manifestations of complex diseases. We present a multi-phenotypes pathway association study(MPPAS) approach using principle component analysis(PCA). In our approach, PCA is first applied to multiple correlated quantitative phenotypes for extracting a set of orthogonal phenotypic components. The extracted phenotypic components are then used for pathway association analysis instead of original quantitative phenotypes. Four statistics were proposed for PCA-based MPPAS in this study. Simulations using the real data from the HapMap project were conducted to evaluate the power and type I error rates of PCA-based MPPAS under various scenarios considering sample sizes, additive and interactive genetic effects. A real genome-wide association study data set of bone mineral density (BMD) at hip and spine were also analyzed by PCA-based MPPAS. Simulation studies illustrated the performance of PCA-based MPPAS for identifying the causal pathways underlying complex diseases. Genome-wide MPPAS of BMD detected associations between BMD and KENNY_CTNNB1_TARGETS_UP as well as LONGEVITYPATHWAY pathways in this study. We aim to provide a applicable MPPAS approach, which may help to gain deep understanding the potential biological mechanism of association results for complex diseases.

Association of vitamin D receptor gene polymorphisms with susceptibility to asthma in Tunisian children: A case control study

BACKGROUND

Vitamin D and its nuclear receptor (VDR) are linked to asthma in a genetic and immunologic basis. Polymorphisms in the VDR gene may alter the actions of vitamin D and then influence the development and the severity of asthma.

AIMS

We aimed at elucidating the genetic association of VDR gene polymorphisms with susceptibility to asthma in Tunisian children and with serum vitamin D levels.

METHODS

The study included 155 patients recruited from Abderrahmen MAMI hospital in Tunisia and two hundred twenty five healthy individuals matched with patients in age and sex for comparison. VDR genotypes were determined by PCR-RFLP method using endonuclease FokI, BsmI, TaqI and ApaI and vitamin D was assessed with a radioimmunoassay kit.

RESULTS

The distribution of genotype frequencies differed significantly between asthmatics and controls (FokI: P=0.04; BsmI: P=0.006; TaqI: P=0.006). Haplotype analyses revealed a significant association between bAt and bat haplotypes and asthma (P=0.00076, P=0.016). When patients were stratified according to atopic status and stage of severity, no significant association was detected with VDR variants. No association was found between VDR SNPs and serum 25-hydroxyvitamin D levels.

CONCLUSION

Our study shows a relation between VDR gene polymorphisms and susceptibility to asthma in children.

Klotho locus, metabolic traits, and serum hemoglobin in hospitalized older patients: a genetic association analysis

Klotho (KL) gene has been involved in severe alterations of physiological biochemical parameters leading to premature aging-like phenotypes and strikingly shortening lifespan. KL participates to the regulation of a number of intracellular biochemical pathways, including lipid profile and glucose metabolism. Aim of this study was to investigate the possible association between KL locus and biological parameters commonly accepted as indicators of the clinical status in hospitalized older patients. We genotyped the single-nucleotide polymorphisms (SNPs) rs9536314, rs1207568, and rs564481 at the KL locus in 594 hospitalized older patients (65-99 years), consecutively attending a geriatric ward, and tested the association of these KL variants with biological quantitative traits using analyses of covariance and genetic risk score models. Significant associations of rs9536314 with serum levels of hemoglobin, albumin, and high-density lipoprotein cholesterol (HDL-C) as well as significant associations of rs564481 with serum levels of hemoglobin, fasting insulin, and fasting glucose were observed. Gender-segregated analyses confirmed these associations, and suggested that the associations of KL genotypes with HDL-C, fasting glucose and fasting insulin levels may be driven by the female gender, while the association with serum levels of hemoglobin may be driven by the male gender. The association of KL genotypes with creatinine levels was found only in females, while the association with insulin-like growth factor-1 (IGF-1) and lymphocytes count (LC) was found only in males. The genetic risk score (GRS) models further confirmed significant associations among KL SNPs and hemoglobin, total cholesterol, and HDL-C. Gender-segregated analyses with the GRS-tagged approach confirmed the associations with HDL-C, fasting glucose, and fasting insulin levels in females, and with hemoglobin and LC in males. Our findings suggested that KL locus may influence quantitative traits such as serum levels of lipid, fasting glucose, albumin and hemoglobin in hospitalized older patients, with some gender differences suggested for creatinine, IGF-1 levels, and LC, thus being one of the genetic factors possibly contributing to age-related diseases and longevity.

Statistical epistasis and functional brain imaging support a role of voltage-gated potassium channels in human memory

Despite the current progress in high-throughput, dense genome scans, a major portion of complex traits' heritability still remains unexplained, a phenomenon commonly termed “missing heritability.” The negligence of analytical approaches accounting for gene-gene interaction effects, such as statistical epistasis, is probably central to this phenomenon. Here we performed a comprehensive two-way SNP interaction analysis of human episodic memory, which is a heritable complex trait, and focused on 120 genes known to show differential, memory-related expression patterns in rat hippocampus. Functional magnetic resonance imaging was also used to capture genotype-dependent differences in memory-related brain activity. A significant, episodic memory-related interaction between two markers located in potassium channel genes (KCNB2 and KCNH5) was observed (P_{nominal combined} = 0.000001). The epistatic interaction was robust, as it was significant in a screening (P_nominal = 0.0000012) and in a replication sample (P_nominal = 0.01). Finally, we found genotype-dependent activity differences in the parahippocampal gyrus (P_nominal = 0.001) supporting the behavioral genetics finding. Our results demonstrate the importance of analytical approaches that go beyond single marker statistics of complex traits.

Accounting for population stratification in practice: a comparison of the main strategies dedicated to genome-wide association studies

Genome-Wide Association Studies are powerful tools to detect genetic variants associated with diseases. Their results have, however, been questioned, in part because of the bias induced by population stratification. This is a consequence of systematic differences in allele frequencies due to the difference in sample ancestries that can lead to both false positive or false negative findings. Many strategies are available to account for stratification but their performances differ, for instance according to the type of population structure, the disease susceptibility locus minor allele frequency, the degree of sampling imbalanced, or the sample size. We focus on the type of population structure and propose a comparison of the most commonly used methods to deal with stratification that are the Genomic Control, Principal Component based methods such as implemented in Eigenstrat, adjusted Regressions and Meta-Analyses strategies. Our assessment of the methods is based on a large simulation study, involving several scenarios corresponding to many types of population structures. We focused on both false positive rate and power to determine which methods perform the best. Our analysis showed that if there is no population structure, none of the tests led to a bias nor decreased the power except for the Meta-Analyses. When the population is stratified, adjusted Logistic Regressions and Eigenstrat are the best solutions to account for stratification even though only the Logistic Regressions are able to constantly maintain correct false positive rates. This study provides more details about these methods. Their advantages and limitations in different stratification scenarios are highlighted in order to propose practical guidelines to account for population stratification in Genome-Wide Association Studies.

Angiotensin-converting enzyme (ACE) genotypes and disability in hospitalized older patients

The association between angiotensin-converting enzyme (ACE) genotypes and functional decline in older adults remains controversial. To assess if ACE gene variations influences functional abilities at older age, the present study explored the association between the common ACE insertion/deletion (I/D) polymorphism and disability measured with activities of daily living (ADL) in hospitalized older patients. We analyzed the frequency of the ACE genotypes (I/I, I/D, and D/D) in a population of 2,128 hospitalized older patients divided according to presence or absence of ADL disability. Logistic regression analysis adjusted for possible confounding factors, identified an association between the I/I genotype with ADL disability (OR=1.54, 95% CI 1.04-2.29). This association was significant in men (OR=2.01, 95% CI 1.07-3.78), but not in women (OR=1.36, 95% CI 0.82-2.25). These results suggested a possible role of the ACE polymorphism as a genetic marker for ADL disability in hospitalized older patients.

Genome-wide detection of allele specific copy number variation associated with insulin resistance in African Americans from the HyperGEN study

African Americans have been understudied in genome wide association studies of diabetes and related traits. In the current study, we examined the joint association of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with fasting insulin and an index of insulin resistance (HOMA-IR) in the HyperGEN study, a family based study with proband ascertainment for hypertension. This analysis is restricted to 1,040 African Americans without diabetes. We generated allele specific CNV genotypes at 872,243 autosomal loci using Birdsuite, a freely available multi-stage program. Joint tests of association for SNPs and CNVs were performed using linear mixed models adjusting for covariates and familial relationships. Our results highlight SNPs associated with fasting insulin and HOMA-IR (rs6576507 and rs8026527, 3.7*10⁻⁷≤P≤1.1*10⁻⁵) near ATPase, class V, type 10A (ATP10A), and the L Type voltage dependent calcium channel (CACNA1D, rs1401492, P≤5.2*10⁻⁶). ATP10A belongs to a family of aminophospholipid-transporting ATPases and has been associated with type 2 diabetes in mice. CACNA1D has been linked to pancreatic beta cell generation in mice. The two most significant copy variable markers (rs10277702 and rs361367; P<2.0*10⁻⁴) were in the beta variable region of the T-cell receptor gene (TCRVB). Human and mouse TCR has been shown to mimic insulin and its receptor and could contribute to insulin resistance. Our findings differ from genome wide association studies of fasting insulin and other diabetes related traits in European populations, highlighting the continued need to investigate unique genetic influences for understudied populations such as African Americans.

No association between polymorphisms and haplotypes of COL1A1 and COL1A2 genes and osteoporotic fracture in postmenopausal Chinese women

AIM

To study whether genetic polymorphisms of COL1A1 and COL1A2 genes affected the onset of fracture in postmenopausal Chinese women.

METHODS

SNPs in COL1A1 and COL1A2 genes were identified via direct sequencing in 32 unrelated postmenopausal Chinese women. Ten SNPs were genotyped in 1252 postmenopausal Chinese women. The associations were examined using both single-SNP and haplotype tests using logistic regression.

RESULTS

Twenty four (4 novel) and 28 (7 novel) SNPs were identified in COL1A1 and COL1A2 gene, respectively. The distribution frequencies of 2 SNPs in COL1A1 (rs2075554 and rs2586494) and 3 SNPs in COL1A2 (rs42517, rs1801182, and rs42524) were significantly different from those documented for the European Caucasian population. No significant difference was observed between fracture and control groups with respect to allele frequency or genotype distribution in 9 selected SNPs and haplotype. No significant association was found between fragility fracture and each SNP or haplotype. The results remained the same after additional corrections for other risk factors such as weight, height, and bone mineral density.

CONCLUSION

Our results show no association between common genetic variations of COL1A1 and COL1A2 genes and fracture, suggesting the complex genetic background of osteoporotic fractures.

Genetic epidemiology of tuberculosis susceptibility: impact of study design

Several candidate gene studies have provided evidence for a role of host genetics in susceptibility to tuberculosis (TB). However, the results of these studies have been very inconsistent, even within a study population. Here, we review the design of these studies from a genetic epidemiological perspective, illustrating important differences in phenotype definition in both cases and controls, consideration of latent M. tuberculosis infection versus active TB disease, population genetic factors such as population substructure and linkage disequilibrium, polymorphism selection, and potential global differences in M. tuberculosis strain. These considerable differences between studies should be accounted for when examining the current literature. Recommendations are made for future studies to further clarify the host genetics of TB.

Genome-wide joint SNP and CNV analysis of aortic root diameter in African Americans: the HyperGEN study

Background

Aortic root diameter is a clinically relevant trait due to its known relationship with the pathogenesis of aortic regurgitation and risk for aortic dissection. African Americans are an understudied population despite a particularly high burden of cardiovascular diseases. We report a genome-wide association study on aortic root diameter among African Americans enrolled in the HyperGEN study. We invoked a two-stage, mixed model procedure to jointly identify SNP allele and copy number variation effects.

Results

Results suggest novel genetic contributors along a large region between the CRCP and KCTD7 genes on chromosome 7 (p = 4.26 × 10^-7); and the SIRPA and PDYN genes on chromosome 20 (p = 3.28 × 10^-8).

Conclusions

The regions we discovered are candidates for future studies on cardiovascular outcomes, particularly in African Americans. The methods we employed can also provide an outline for genetic researchers interested in jointly testing SNP and CNV effects and/or applying mixed model procedures on a genome-wide scale.

Controlling Population Structure in Human Genetic Association Studies with Samples of Unrelated Individuals

In genetic studies, associations between genotypes and phenotypes may be confounded by unrecognized population structure and/or admixture. Studies have shown that even in European populations, which are thought to be relatively homogeneous, population stratification exists and can affect the validity of association studies. A number of methods have been proposed to address this issue in recent years. Among them, the mixed-model based approach and the principal component-based approach have several advantages over other methods. However, these approaches have not been thoroughly evaluated on large human datasets. The objectives of this study are to (1) evaluate and compare the performance of the mixed-model approach and the principal component-based approach for genetic association mapping using human data consisting of unrelated individuals, and (2) understand the relationship between these two approaches. To achieve these goals, we simulate datasets based on the HapMap data under various scenarios. Our results indicate that the mixed-model approach performs well in controlling for population structure/admixture. It has similar performance as that based on principal component analysis. However, the approach combining mixed-model and principal component analysis does not perform as well as either method itself.

Tuberculosis as a complex trait: impact of genetic epidemiological study design

Several studies have suggested a role for human genetic risk factors in the susceptibility to developing tuberculosis (TB). However, results of these studies have been inconsistent, and one potential reason for these inconsistencies is variation in aspects of study design. Specifically, phenotype definitions and population genetic factors have varied dramatically. Since TB is a complex trait, there are many challenges in designing studies to assess appropriately human genetic risk factors for the development of TB as opposed to the acquisition of latent M. tuberculosis infection. In this review we summarize these important study design differences, with illustrations from the TB genetics literature. We cite specific examples of studies of the NRAMP1 (SLC11A1) gene and present Fisher's combined p values for different stratifications of these studies to further illustrate the impact of study design differences. Finally, we provide suggestions for the design of future genetic epidemiological studies of TB.

Genetic aspects of osteoporosis

The multiple factors contributing to the pathogenesis of osteoporosis include genetic and environmental factors. Because decrease in bone mineral density (BMD) is the major clinical indicator and a useful quantitative trait, many association and linkage studies of BMD have been conducted. Although the series of studies showed apparently significant associations, the genes have not been found that can be utilized in clinical practice. Several genes identified in robust genome-wide association studies will be the new cutting edge in genetic studies of osteoporosis. Our recent reports of functional single nucleotide polymorphism in the tissue-nonspecific alkaline phosphatase gene and gamma-carboxylase gene are presented in this review to discuss the future prospects in the genetic research of osteoporosis from the point of view of genome-nutrition interaction.

Using evidence for population stratification bias in combined individual- and family-level genetic association analyses of quantitative traits

Genetic association studies are generally performed either by examining differences in the genotype distribution between individuals or by testing for preferential allele transmission within families. In the absence of population stratification bias (PSB), integrated analyses of individual and family data can increase power to identify susceptibility loci [Abecasis et al., 2000. Am. J. Hum. Genet. 66:279-292; Chen and Lin, 2008. Genet. Epidemiol. 32:520-527; Epstein et al., 2005. Am. J. Hum. Genet. 76:592-608]. In existing methods, the presence of PSB is initially assessed by comparing results from between-individual and within-family analyses, and then combined analyses are performed only if no significant PSB is detected. However, this strategy requires specification of an arbitrary testing level alpha(PSB), typically 5%, to declare PSB significance. As a novel alternative, we propose to directly use the PSB evidence in weights that combine results from between-individual and within-family analyses. The weighted approach generalizes previous methods by using a continuous weighting function that depends only on the observed P-value instead of a binary weight that depends on alpha(PSB). Using simulations, we demonstrate that for quantitative trait analysis, the weighted approach provides a good compromise between type I error control and power to detect association in studies with few genotyped markers and limited information regarding population structure.

Lower prevalence of common filaggrin mutations in a community sample of atopic eczema: is disease severity important?

BACKGROUND

Recent studies have shown an association of loss-of-function mutations in the filaggrin gene (FLG) with ichthyosis vulgaris and atopic eczema (AE). Case selection may have distorted the hitherto reported prevalence of FLG mutations and their relation to atopic disease. The aim of the study was to determine the true population prevalence of FLG mutations in unselected children with and without reported physician diagnoses of asthma, allergic rhinitis and AE and their relationship with family history of atopic disease.

METHODS

We used a nested case-control design by sampling children with reported doctor's diagnoses of AE, asthma and allergic rhinitis and randomly selected controls from a larger cross-sectional study (n = 1263). Most common FLG mutations R501X, 2282del4, and R2447X were screened in DNA extracted from defrosted urine samples. The relationship of the combined FLG variants with atopic diseases and with reported family history of AE, asthma, and rhinitis was assessed.

RESULTS

In the patient group one homozygote (R501X/R501X), 4 compound heterozygotes (3 R501X/2282del4, one 2282del4/R2447X), and 17 heterozygotes (10 R501X/wt, 5 2282del4/wt, and 2 R2447X/wt), in the control group 9 heterozygotes (5 R501X/wt, 4 2282del4/wt) were detected. The combined prevalence of FLG loss-of-function alleles was 5% in the control group and 9% in the atopic sample. In a subgroup analysis, the combination of allergic rhinitis and AE showed a significant relationship with FLG mutations, OR = 3.7 (1.01-12.67, p = 0.024). Likewise, significant relations with reported family history of asthma, OR = 4.35 (1.78-10.62, p = 0.0012), allergic rhinitis, OR = 2.33 (1.49-3.63, p = 0.0002), and AE, OR = 5.08 (2.78-9.30, p ≤ 0.0001) were observed. In contrast to clinical studies with higher percentages of severely affected persons, FLG mutations here showed a moderate association with atopic disease.

CONCLUSIONS

Case selection may be responsible for overestimating the prevalence of FLG mutations in atopic disease.

A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors

Confounding due to population stratification (PS) arises when differences in both allele and disease frequencies exist in a population of mixed racial/ethnic subpopulations. Genomic control, structured association, principal components analysis (PCA), and multidimensional scaling (MDS) approaches have been proposed to address this bias using genetic markers. However, confounding due to PS can also be due to non-genetic factors. Propensity scores are widely used to address confounding in observational studies but have not been adapted to deal with PS in genetic association studies. We propose a genomic propensity score (GPS) approach to correct for bias due to PS that considers both genetic and non-genetic factors. We compare the GPS method with PCA and MDS using simulation studies. Our results show that GPS can adequately adjust and consistently correct for bias due to PS. Under no/mild, moderate, and severe PS, GPS yielded estimated with bias close to 0 (mean=-0.0044, standard error=0.0087). Under moderate or severe PS, the GPS method consistently outperforms the PCA method in terms of bias, coverage probability (CP), and type I error. Under moderate PS, the GPS method consistently outperforms the MDS method in terms of CP. PCA maintains relatively high power compared to both MDS and GPS methods under the simulated situations. GPS and MDS are comparable in terms of statistical properties such as bias, type I error, and power. The GPS method provides a novel and robust tool for obtaining less-biased estimates of genetic associations that can consider both genetic and non-genetic factors.

Correcting for cryptic relatedness in population-based association studies of continuous traits

Cryptic relatedness was suggested to be an important source of confounding in population-based association studies (PBAS). The magnitude and manner of cryptic relatedness affecting the performance of PBAS of continuous traits remain to be investigated. We simulated a set of related samples through biased sampling and inbreeding, and evaluated the power and type I error rates of simple association tests (SAT) without correcting for cryptic relatedness. We also used extended likelihood ratio tests (ELRT) to conduct PBAS accounting for cryptic relatedness, and compared it with genomic control (GC). Cryptic relatedness decreased the power as well as increased the type I error rates of SAT in both biased sampling and inbreeding models. The impact of cryptic relatedness on the performance of SAT appeared to be limited in the biased sampling model. However, cryptic relatedness in inbred populations may result in excessive false positive results of SAT. Compared with SAT and GC, ELRT obtained improved power and type I error rates under various scenarios. Ignoring cryptic relatedness may increase spurious association results in PBAS. Our ELRT provides a novel approach to control cryptic relatedness in PBAS of human continuous traits.

Univariate/multivariate genome-wide association scans using data from families and unrelated samples

As genome-wide association studies (GWAS) are becoming more popular, two approaches, among others, could be considered in order to improve statistical power for identifying genes contributing subtle to moderate effects to human diseases. The first approach is to increase sample size, which could be achieved by combining both unrelated and familial subjects together. The second approach is to jointly analyze multiple correlated traits. In this study, by extending generalized estimating equations (GEEs), we propose a simple approach for performing univariate or multivariate association tests for the combined data of unrelated subjects and nuclear families. In particular, we correct for population stratification by integrating principal component analysis and transmission disequilibrium test strategies. The proposed method allows for multiple siblings as well as missing parental information. Simulation studies show that the proposed test has improved power compared to two popular methods, EIGENSTRAT and FBAT, by analyzing the combined data, while correcting for population stratification. In addition, joint analysis of bivariate traits has improved power over univariate analysis when pleiotropic effects are present. Application to the Genetic Analysis Workshop 16 (GAW16) data sets attests to the feasibility and applicability of the proposed method.

Population admixture associated with disease prevalence in the Boston Puerto Rican health study

Older Puerto Ricans living in the continental U.S. suffer from higher rates of diabetes, obesity, cardiovascular disease and depression compared to non-Hispanic White populations. Complex diseases, such as these, are likely due to multiple, potentially interacting, genetic, environmental and social risk factors. Presumably, many of these environmental and genetic risk factors are contextual. We reasoned that racial background may modify some of these risk factors and be associated with health disparities among Puerto Ricans. The contemporary Puerto Rican population is genetically heterogeneous and originated from three ancestral populations: European settlers, native Taíno Indians, and West Africans. This rich-mixed ancestry of Puerto Ricans provides the intrinsic variability needed to untangle complex gene-environment interactions in disease susceptibility and severity. Herein, we determined whether a specific ancestral background was associated with either of four major disease outcomes (diabetes, obesity, cardiovascular disease, and depression). We estimated the genetic ancestry of 1,129 subjects from the Boston Puerto Rican Health Study based on genotypes of 100 ancestry informative markers (AIMs). We examined the effects of ancestry on tests of association between single AIMs and disease traits. The ancestral composition of this population was 57.2% European, 27.4% African, and 15.4% Native American. African ancestry was negatively associated with type 2 diabetes and cardiovascular disease, and positively correlated with hypertension. It is likely that the high prevalence rate of diabetes in Africans, Hispanics, and Native Americans is not due to genetic variation alone, but to the combined effects of genetic variation interacting with environmental and social factors.

Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-TNF treatment in rheumatoid arthritis

The prediction of response (or non-response) to anti-TNF treatment for rheumatoid arthritis (RA) is a pressing clinical problem. We conducted a genome-wide association study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning anti-TNF therapy as part of Autoimmune Biomarkers Collaborative Network (ABCoN [Autoimmune Bio-markers Collaborative Network]) patient cohort. Response to therapy was determined by the change in Disease Activity Score (DAS28) observed after 14 wks. We used a two-part analysis that treated the change in DAS28 as a continuous trait and then incorporated it into a dichotomous trait of "good responder" and "nonresponder" by European League Against Rheumatism (EULAR) criteria. We corrected for multiple tests by permutation, and adjusted for potential population stratification using EIGENSTRAT. Multiple single nucleotide polymorphism (SNP) markers showed significant associations near or within loci including: the v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB) gene on chromosome 20; the type I interferon gene IFNk on chromosome 9; and in a locus on chromosome 7 that includes the paraoxonase I (PON1) gene. An SNP in the IL10 promoter (rs1800896) that was previously reported as associated with anti-TNF response was weakly associated with response in this cohort. Replications of these results in independent and larger data sets clearly are required. We provide a reference list of candidate SNPs (P < 0.01) that can be investigated in future pharmacogenomic studies.

Comparison of population-based association study methods correcting for population stratification

Population stratification can cause spurious associations in population-based association studies. Several statistical methods have been proposed to reduce the impact of population stratification on population-based association studies. We simulated a set of stratified populations based on the real haplotype data from the HapMap ENCODE project, and compared the relative power, type I error rates, accuracy and positive prediction value of four prevailing population-based association study methods: traditional case-control tests, structured association (SA), genomic control (GC) and principal components analysis (PCA) under various population stratification levels. Additionally, we evaluated the effects of sample sizes and frequencies of disease susceptible allele on the performance of the four analytical methods in the presence of population stratification. We found that the performance of PCA was very stable under various scenarios. Our comparison results suggest that SA and PCA have comparable performance, if sufficient ancestral informative markers are used in SA analysis. GC appeared to be strongly conservative in significantly stratified populations. It may be better to apply GC in the stratified populations with low stratification level. Our study intends to provide a practical guideline for researchers to select proper study methods and make appropriate inference of the results in population-based association studies.

Human genetic factors and respiratory syncytial virus disease severity

SUMMARY

To explain the wide spectrum of disease severity caused by respiratory syncytial virus (RSV) and because of the limitations of animal models to fully parallel human RSV disease, study of genetic influences on human RSV disease severity has begun. Candidate gene approaches have demonstrated associations of severe RSV in healthy infants with genetic polymorphisms that may alter the innate ability of humans to control RSV (surfactants, Toll-like receptor 4, cell surface adhesion molecules, and others) and those that may control differences in proinflammatory responses or enhanced immunopathology (specific cytokines and their receptors). These studies are reviewed. They are valuable since an understanding of the direction of a polymorphism's effect can help construct a meaningful human RSV disease pathogenesis model. However, the direction, degree, and significance of the statistical association for any given gene are equivocal among studies, and the functional significance of specific polymorphisms is often not even known. Polymorphism frequency distribution differences associated with RSV infection arising from diversity in the genetic background of the population may be confounded further by multiple-hypothesis testing and publication bias, as well as the investigator's perceived importance of a particular pathogenic disease process. Such problems highlight the limitation of the candidate gene approach and the need for an unbiased large-scale genome-wide association study to evaluate this important disease.

Polymorphisms of the tumor necrosis factor-alpha receptor 2 gene are associated with obesity phenotypes among 405 Caucasian nuclear families

The plasma level of the tumor necrosis factor-alpha receptor 2 (TNFR2) is associated with obesity phenotypes. However, the genetic polymorphisms for such an association have rarely been explored and are generally unknown. In this study, by employing a large sample of 1,873 subjects from 405 Caucasian nuclear families, we explored the association of 12 SNPs of the TNFR2 gene and obesity-related phenotypes, including body mass index (BMI), fat mass, and percentage fat mass (PFM). The within-family quantitative transmission disequilibrium test, which is robust to sample stratification, was implemented to evaluate the association of TNFR2 gene with obesity phenotypes. Evidence of association was obtained at SNP9 (rs5746059) with fat mass (P = 0.0002), BMI (P = 0.002), and PFM (P = 0.0006). The contribution of this polymorphism to the variation of fat mass and PFM was 6.24 and 7.82%, respectively. Individuals carrying allele A at the SNP9 site had a 4.6% higher fat mass and a 2.5% increased PFM compared to noncarriers. The results remained significant even after correction for multiple testing. Evidence of association between the TNFR2 gene and obesity phenotypes are also found in 700 independent Chinese Han and 1,000 random Caucasians samples. The results suggest that the TNFR2 gene polymorphisms contribute to the variation of obesity phenotypes.

HAPSIMU: a genetic simulation platform for population-based association studies

Background

Population structure is an important cause leading to inconsistent results in population-based association studies (PBAS) of human diseases. Various statistical methods have been proposed to reduce the negative impact of population structure on PBAS. Due to lack of structural information in real populations, it is difficult to evaluate the impact of population structure on PBAS in real populations.

Results

We developed a genetic simulation platform, HAPSIMU, based on real haplotype data from the HapMap ENCODE project. This platform can simulate heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model. Moreover, both qualitative and quantitative traits can be simulated using additive genetic model with various genetic parameters designated by users.

Conclusion

HAPSIMU provides a common genetic simulation platform to evaluate the impact of population structure on PBAS, and compare the relative performance of various population structure identification and PBAS methods.

Genome-wide association scans identified CTNNBL1 as a novel gene for obesity

Obesity is a major public health problem with strong genetic determination; however, the genetic factors underlying obesity are largely unknown. In this study, we performed a genome-wide association scan for obesity by examining approximately 500 000 single-nucleotide polymorphisms (SNPs) in a sample of 1000 unrelated US Caucasians. We identified a novel gene, CTNNBL1, which has multiple SNPs associated with body mass index (BMI) and fat mass. The most significant SNP, rs6013029, achieved experiment-wise P-values of 2.69 x 10(-7) for BMI and of 4.99 x 10(-8) for fat mass, respectively. The SNP rs6013029 minor allele T confers an average increase in BMI and fat mass of 2.67 kg/m(2) and 5.96 kg, respectively, compared with the alternative allele G. We further genotyped the five most significant CTNNBL1 SNPs in a French case-control sample comprising 896 class III obese adults (BMI > or = 40 kg/m(2)) and 2916 lean adults (BMI < 25 kg/m(2)). All five SNPs showed consistent associations with obesity (8.83 x 10(-3) < P < 6.96 x 10(-4)). Those subjects who were homozygous for the rs6013029 T allele had 1.42-fold increased odds of obesity compared with those without the T allele. The protein structure of CTNNBL1 is homologous to beta-catenin, a family of proteins containing armadillo repeats, suggesting similar biological functions. beta-Catenin is involved in the Wnt/beta-catenin-signaling pathway which appears to contribute to maintaining the undifferentiated state of pre-adipocytes by inhibiting adipogenic gene expression. Our study hence suggests a novel mechanism for the development of obesity, where CTNNBL1 may play an important role. Our study also provided supportive evidence for previously identified associations between obesity and INSIG2 and PFKP, but not FTO.

Review and evaluation of methods correcting for population stratification with a focus on underlying statistical principles

When two or more populations have been separated by geographic or cultural boundaries for many generations, drift, spontaneous mutations, differential selection pressures and other factors may lead to allele frequency differences among populations. If these 'parental' populations subsequently come together and begin inter-mating, disequilibrium among linked markers may span a greater genetic distance than it typically does among populations under panmixia [see glossary]. This extended disequilibrium can make association studies highly effective and more economical than disequilibrium mapping in panmictic populations since less marker loci are needed to detect regions of the genome that harbor phenotype-influencing loci. However, under some circumstances, this process of intermating (as well as other processes) can produce disequilibrium between pairs of unlinked loci and thus create the possibility of confounding or spurious associations due to this population stratification. Accordingly, researchers are advised to employ valid statistical tests for linkage disequilibrium mapping allowing conduct of genetic association studies that control for such confounding. Many recent papers have addressed this need. We provide a comprehensive review of advances made in recent years in correcting for population stratification and then evaluate and synthesize these methods based on statistical principles such as (1) randomization, (2) conditioning on sufficient statistics, and (3) identifying whether the method is based on testing the genotype-phenotype covariance (conditional upon familial information) and/or testing departures of the marginal distribution from the expected genotypic frequencies.

The non-synonymous coding IKr-channel variant KCNH2-K897T is associated with atrial fibrillation: results from a systematic candidate gene-based analysis of KCNH2 (HERG)

AIMS

Atrial fibrillation (AF) is the most frequent arrhythmia in humans. Rare familial forms exist. Recent evidence indicates a genetic susceptibility to common forms of AF. The alpha-subunit of the myocardial I(Kr)-channel, encoded by the KCNH2 gene, is crucial to ventricular and atrial repolarization. Patients with mutations in KCNH2 present with higher incidence of AF. Common variants in KCNH2 have been shown to modify ventricular repolarization. We intended to investigate, whether such variants may also modulate atrial repolarization and predispose to AF.

METHODS AND RESULTS

In a two-stage association study we analysed 1207 AF-cases and 2475 controls. In stage I 40 tagSNPs (single nucleotide polymorphisms) from the KCNH2 genomic region were genotyped in 671 AF-cases and 694 controls. Of five associated variants, the common K897-allele of the KCNH2-K897T variant was replicated in n = 536 independent AF cases and n = 1781 controls in stage II [overall odds ratio 1.25, 95% confidence interval 1.11-1.41, P = 0.00033]. This association remained significant after adjustment for gender and age.

CONCLUSION

We report a genetic association finding including positive replication between the K897-allele and higher incidence of AF. This provides a molecular correlate for complex genetic predispositions to AF. The consequences of the K897T variant at the atrial level will require further functional investigations.

Searching for genes underlying susceptibility to osteoporotic fracture: current progress and future prospect

INTRODUCTION

Osteoporotic fracture (OF) is a public health problem. It is a common practice in the genetics of osteoporosis that bone mineral density (BMD) was studied as a major surrogate phenotype in gene search for risk of OF (ROF) because of their high phenotypic correlation. However, some studies indicate that the genetic correlation between BMD and ROF is very low. This implies that most genes found important for BMD may not be relevant to ROF. Ideally, employing OF per se as a direct study phenotype can directly find the relevant genes underlying ROF.

EVIDENCE

Here, we summarized some evidence supporting ROF under moderate genetic control, and the current progress of molecular genetic studies employing OF as the direct study phenotype, then give our consideration on the future prospects in the genetics of ROF.

AHSG gene polymorphisms are associated with bone mineral density in Caucasian nuclear families

PURPOSE

To investigate the role of alpha2-HS glycoprotein (AHSG) gene on bone mineral density (BMD) variation.

METHODS

A total of 665 subjects from 157 Caucasian nuclear families were genotyped at the AHSG NlaIII, SacI sites. The association and linkage between the single SNP markers and haplotypes constructed by two markers in this gene and BMDs at the spine and hip were determined by using quantitative transmission disequilibrium test (QTDT).

RESULTS

Significant within-family associations were obtained for spine BMD at both of studied markers (P = 0.036 and 0.005 at the NlaIII and SacI sites, respectively). Significant (P = 0.008 at the NlaIII locus) (P = 0.004 at the SacI locus) total associations at spine BMD were detected. Haplotype analyses confirmed those within-family and total association.

CONCLUSIONS

These data suggest the polymorphisms in the AHSG gene may have effects on BMD variation in Caucasian population.

Three common intronic variants in the maternal and fetal thiamine pyrophosphokinase gene (TPK1) are associated with birth weight

Extreme variations in birth weight increase immediate postnatal mortality and morbidity, and are also associated with the predisposition to metabolic diseases in late adulthood. Birth weight in humans is influenced by yet unknown genetic factors. Since the 7q34-q35 region showed linkage with birth weight in a recent human genome scan (p = 8.10(-5)), this study investigated the TPK1 (thiamine pyrophosphokinase) gene locus, located in 7q34-36. Having found no coding variants in the TPK1 gene, we genotyped 43 non coding SNPs spanning a region of 420kb, and used the QTDT method to test their association with birth weight in 964 individuals from 220 families of European ancestry. Family-based tests detected association of 8 SNPs with birth weight (p<0.008), but after correction for multiple tests only rs228581 C/T (p = 0.03), rs228582 A/G (p = 0.04) and rs228584 C/T (p = 0.03) were still associated with birth weight, as well as their T-A-T haplotype (p = 0.03). In addition, we found an association between maternal rs228584 genotype and offspring birth weight (p = 0.027). These observations suggest that genomic variations in the fetal and maternal TPK1 gene could contribute to the variability of birth weight in normal humans.

The effect of assortative mating upon genetic association studies: spurious associations and population substructure in the absence of admixture

Spurious associations due to confounding factors are an often cited and intensely debated concern for genetic association studies. Great attention has been focused upon the specific threat of confounding due to population stratification. This emphasis has spurred the development of many statistical genetic methods to detect and correct for the potentially confounding effects of admixture. Unfortunately, this emphasis on admixture has led some authors to suggest that if ethnically homogenous populations are used, spurious associations are unlikely to occur. We show that under small and realistic degrees of assortative mating over time, spurious associations arise even in ethnically homogeneous populations. We demonstrate that structured association and genomic control tests can, under certain conditions, correct for these spurious associations. We conclude that investigators should not assume spurious associations will not occur in association studies using ethnically homogenous populations and recommend the use of genomic control methods and/or family-based association tests within genetic association studies.

Comparison of SNP tagging methods using empirical data: association study of 713 SNPs on chromosome 12q14.3-12q24.21 for asthma and total serum IgE in an African Caribbean population

Few comparison studies have been performed on single nucleotide polymorphism (SNP) tagging methods to examine their consistency and effectiveness in terms of inferences about association with disease. We applied several SNP tagging methods to SNPs on chromosome 12q (n=713) and compared the utility of these methods to detect association for asthma and serum IgE levels among a sample of African Caribbean families from Barbados selected through asthmatic probands. We found that a high level of information regarding association is retained in Clayton's htSNP, Stram's TagSNP, and de Bakker's Tagger. We also found a high degree of consistency between TagSNP and Tagger. Using this set of 713 SNPs on chromosome 12q, our study provides insight towards analytic strategies for future studies of complex traits.