Detecting differentially methylated loci for Illumina Array methylation data based on human ovarian cancer data

Background

It is well known that DNA methylation, as an epigenetic factor, has an important effect on gene expression and disease development. Detecting differentially methylated loci under different conditions, such as cancer types or treatments, is of great interest in current research as it is important in cancer diagnosis and classification. However, inappropriate testing approaches can result in large false positives and/or false negatives. Appropriate and powerful statistical methods are desirable but very limited in the literature.

Results

In this paper, we propose a nonparametric method to detect differentially methylated loci under multiple conditions for Illumina Array Methylation data. We compare the new method with other methods using simulated and real data. Our study shows that the proposed one outperforms other methods considered in this paper.

Conclusions

Due to the unique feature of the Illumina Array Methylation data, commonly used statistical tests will lose power or give misleading results. Therefore, appropriate statistical methods are crucial for this type of data. Powerful statistical approaches remain to be developed.

Availability

R codes are available upon request.

The ANO3/MUC15 locus is associated with eczema in families ascertained through asthma

BACKGROUND

A previous genome-wide linkage scan in 295 families of the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA) reported strong evidence of linkage of 11p14 to eczema.

OBJECTIVE

Our purpose was to conduct fine-scale mapping of the 11p14 region to identify the genetic variants associated with eczema.

METHODS

Association analyses were first conducted in the family sample from the French EGEA by using 2 methods: the family-based association method and logistic regression. Replication of the EGEA findings was sought in French Canadian and United Kingdom family samples, which, similarly to EGEA samples, were ascertained through asthma. We also tested for association in 2 German samples ascertained through eczema.

RESULTS

We found significant association of eczema with 11p14 genetic variants in the vicinity of the linkage peak in EGEA (P = 10(-4) for rs1050153 by using the family-based association method, which reached the multiple testing-corrected threshold of 10(-4); P = .003 with logistic regression). Pooled analysis of the 3 asthma-ascertained samples showed strong improvement in the evidence for association (P = 6 × 10(-6) for rs293974, P = 3 × 10(-5) for rs1050153, and P = 8 × 10(-5) for rs15783). No association was observed in the eczema-ascertained samples.

CONCLUSION

The significant single nucleotide polymorphisms are located within the overlapping anoctamin 3 (ANO3) and mucin 15 (MUC15) genes. Several lines of evidence suggest that MUC15 is a strong candidate for eczema. Further investigation is needed to confirm our findings and to better understand the role of the ANO3/MUC15 locus in eczema and its relationship with respect to asthma.

Polymorphisms in regulators of xenobiotic transport and metabolism genes PXR and CAR do not affect multiple myeloma risk: a case-control study in the context of the IMMEnSE consortium

The exposure to pesticides and toxic compounds in xenobiotic transport and metabolism genes has been shown to affect risk of developing multiple myeloma (MM). Therefore, we hypothesized that genetic variations in xenobiotic transport and metabolism regulator genes PXR (NR1I2) and CAR (NR1I3) could determine a difference in MM susceptibility. Ten tagging single-nucleotide polymorphisms (SNPs) for PXR and seven for the CAR genes were selected and genotyped in 627 MM cases and 883 controls collected in the context of the International Multiple Myeloma rESEarch (IMMEnSE) consortium. None of the 17 SNPs investigated showed significant association with MM risk either alone or when combined in haplotypes. Significant SNP-SNP interactions were not found, neither with 58 previously genotyped polymorphisms in ABC transporters. We can therefore exclude that common genetic variants in the xenobiotic transport and metabolism regulator genes PXR and CAR affect MM risk.

Genetic signatures in choline and 1-carbon metabolism are associated with the severity of hepatic steatosis

Choline metabolism is important for very low-density lipoprotein secretion, making this nutritional pathway an important contributor to hepatic lipid balance. The purpose of this study was to assess whether the cumulative effects of multiple single nucleotide polymorphisms (SNPs) across genes of choline/1-carbon metabolism and functionally related pathways increase susceptibility to developing hepatic steatosis. In biopsy-characterized cases of nonalcoholic fatty liver disease and controls, we assessed 260 SNPs across 21 genes in choline/1-carbon metabolism. When SNPs were examined individually, using logistic regression, we only identified a single SNP (PNPLA3 rs738409) that was significantly associated with severity of hepatic steatosis after adjusting for confounders and multiple comparisons (P=0.02). However, when groupings of SNPs in similar metabolic pathways were defined using unsupervised hierarchical clustering, we identified groups of subjects with shared SNP signatures that were significantly correlated with steatosis burden (P=0.0002). The lowest and highest steatosis clusters could also be differentiated by ethnicity. However, unique SNP patterns defined steatosis burden irrespective of ethnicity. Our results suggest that analysis of SNP patterns in genes of choline/1-carbon metabolism may be useful for prediction of severity of steatosis in specific subsets of people, and the metabolic inefficiencies caused by these SNPs should be examined further.

Fine mapping of a region of chromosome 11q23.3 reveals independent locus associated with risk of glioma

Background

A single nucleotide polymorphism (SNP) at locus 11q23.3 (rs498872) in the near 5′-UTR of the PHLDB1 gene was recently implicated as a risk factor for gliomas in a genome-wide association study, and this involvement was confirmed in three additional studies.

Methodology/Principal Findings

To identify possible causal variants in the region, the authors genotyped 15 tagging SNPs in the 200 kb genomic region at 11q23.3 locus in a Chinese Han population-based case-control study with 983 cases and 1024 controls. We found evidence for an association between two independent loci (both the PHLDB1 and the ACRN1 genes) and a predisposition for gliomas. Among the multiple significant SNPs in the PHLDB1 gene region, the rs17749 SNP was the most significant [P = 1.31×10⁻⁶ in a recessive genetic model]. Additionally, two novel SNPs (rs2236661 and rs494560) that were independent of rs17749 were significantly associated with glioma risk in a recessive genetic model [P = 1.31×10⁻⁵ and P = 3.32×10⁻⁵, respectively]. The second novel locus was within the ARCN1 gene, and it was associated with a significantly reduced risk for glioma.

Conclusions/Significance

Our data strongly support PHLDB1 as a susceptibility gene for glioma, also shedding light on a new potentially candidate gene, ARCN1.

Admixture mapping of coronary artery calcified plaque in African Americans with type 2 diabetes mellitus

BACKGROUND

The presence and severity of coronary artery calcified plaque (CAC) differs markedly between individuals of African and European descent, suggesting that admixture mapping may be informative for identifying genetic variants associated with subclinical cardiovascular disease.

METHODS AND RESULTS

Admixture mapping of CAC was performed in 1040 unrelated African Americans with type 2 diabetes mellitus from the African American-Diabetes Heart Study, Multi-Ethnic Study of Atherosclerosis and Family Heart Study using the Illumina custom ancestry informative marker panel. All cohorts obtained computed tomography scanning of the coronary arteries using identical protocols. For each ancestry informative marker, the probability of inheriting 0, 1, and 2 copies of a European-derived allele was determined. Linkage analysis was performed by testing for association between each ancestry informative marker using these probabilities and CAC, accounting for global ancestry, age, sex, and study. Markers on 1p32.3 in the GLIS1 gene (rs6663966, logarithm of odds [LOD]=3.7), 1q32.1 near CHIT1 (rs7530895, LOD=3.1), 4q21.2 near PRKG2 (rs1212373, LOD=3.0), and 11q25 in the OPCML gene (rs6590705, LOD=3.4) had statistically significant LOD scores, whereas markers on 8q22.2 (rs6994682, LOD=2.7), 9p21.2 (rs439314, LOD=2.7), and 13p32.1 (rs7492028, LOD=2.8) manifested suggestive evidence of linkage. These regions were uniformly characterized by higher levels of European ancestry associating with higher levels or odds of CAC. Findings were replicated in 1350 African Americans without diabetes mellitus and 2497 diabetic European Americans from Multi-Ethnic Study of Atherosclerosis and the Diabetes Heart Study.

CONCLUSIONS

Fine mapping these regions will likely identify novel genetic variants that contribute to CAC and clarify racial differences in susceptibility to subclinical cardiovascular disease.

A gene-centric study of common carotid artery remodelling

Background

Expansive remodelling is the process of compensatory arterial enlargement in response to atherosclerotic stimuli. The genetic determinants of this process are poorly characterized.

Methods

Genetic association analyses of inter-adventitial common carotid artery diameter (ICCAD) in the IMPROVE study (n = 3427) using the Illumina 200k Metabochip was performed. Single nucleotide polymorphisms (SNPs) that met array-wide significance were taken forward for analysis in three further studies (n = 5704), and tested for association with Abdominal Aortic Aneurysm (AAA).

Results

rs3768445 on Chromosome 1q24.3, in a cluster of protein coding genes (DNM3, PIGC, C1orf105) was associated with larger ICCAD in the IMPROVE study. For each copy of the rare allele carried, ICCAD was on average 0.13 mm greater (95% CI 0.08–0.18 mm, P = 8.2 × 10⁻⁸). A proxy SNP (rs4916251, R² = 0.99) did not, however, show association with ICCAD in three follow-up studies (P for replication = 0.29). There was evidence of interaction between carotid intima-media thickness (CIMT) and rs4916251 on ICCAD in two of the cohorts studies suggesting that it plays a role in the remodelling response to atherosclerosis. In meta-analysis of 5 case–control studies pooling data from 5007 cases and 43,630 controls, rs4916251 was associated with presence of AAA 1.10, 95% CI 1.03–1.17, p = 2.8 × 10⁻³, I² = 18.8, Q = 0.30). A proxy SNP, rs4916251 was also associated with increased expression of PIGC in aortic tissue, suggesting that this may the mechanism by which this locus affects vascular remodelling.

Conclusions

Common variation at 1q24.3 is associated with expansive vascular remodelling and risk of AAA. These findings support a hypothesis that pathways involved in systemic vascular remodelling play a role in AAA development.

Design and analysis of multiple diseases genome-wide association studies without controls

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case-control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case-control GWAS as well as those with shared controls.

Bitter taste receptor polymorphisms and human aging

Several studies have shown that genetic factors account for 25% of the variation in human life span. On the basis of published molecular, genetic and epidemiological data, we hypothesized that genetic polymorphisms of taste receptors, which modulate food preferences but are also expressed in a number of organs and regulate food absorption processing and metabolism, could modulate the aging process. Using a tagging approach, we investigated the possible associations between longevity and the common genetic variation at the three bitter taste receptor gene clusters on chromosomes 5, 7 and 12 in a population of 941 individuals ranging in age from 20 to 106 years from the South of Italy. We found that one polymorphism, rs978739, situated 212 bp upstream of the TAS2R16 gene, shows a statistically significant association (p = 0.001) with longevity. In particular, the frequency of A/A homozygotes increases gradually from 35% in subjects aged 20 to 70 up to 55% in centenarians. These data provide suggestive evidence on the possible correlation between human longevity and taste genetics.

Genome-wide association study identifies candidate markers for bull fertility in Holstein dairy cattle

The decline in the reproductive efficiency of dairy cattle has become a challenging problem worldwide. Female fertility is now taken into account in breeding goals while generally less attention is given to male fertility. The objective of this study was to perform a genome-wide association study in Holstein bulls to identify genetic variants significantly related to sire conception rate (SCR), a new phenotypic evaluation of bull fertility. The analysis included 1755 sires with SCR data and 38,650 single nucleotide polymorphisms (SNPs) spanning the entire bovine genome. Associations between SNPs and SCR were analyzed using a mixed linear model that included a random polygenic effect and SNP genotype either as a linear covariate or as a categorical variable. A multiple testing correction approach was used to account for the correlation between SNPs because of linkage disequilibrium. After genome-wide correction, eight SNPs showed significant association with SCR. Some of these SNPs are located close to or in the middle of genes with functions related to male fertility, such as the sperm acrosome reaction, chromatin remodeling during the spermatogenesis, and the meiotic process during male germ cell maturation. Some SNPs showed marked dominance effects, which provide more evidence for the relevance of non-additive effects in traits closely related to fitness such as fertility. The results could contribute to the identification of genes and pathways associated with male fertility in dairy cattle.

Evaluation of Parkinson disease risk variants as expression-QTLs

The recent Parkinson Disease GWAS Consortium meta-analysis and replication study reports association at several previously confirmed risk loci SNCA, MAPT, GAK/DGKQ, and HLA and identified a novel risk locus at RIT2. To further explore functional consequences of these associations, we investigated modification of gene expression in prefrontal cortex brain samples of pathologically confirmed PD cases (N = 26) and controls (N = 24) by 67 associated SNPs in these 5 loci. Association between the eSNPs and expression was evaluated using a 2-degrees of freedom test of both association and difference in association between cases and controls, adjusted for relevant covariates. SNPs at each of the 5 loci were tested for cis-acting effects on all probes within 250 kb of each locus. Trans-effects of the SNPs on the 39,122 probes passing all QC on the microarray were also examined. From the analysis of cis-acting SNP effects, several SNPs in the MAPT region show significant association to multiple nearby probes, including two strongly correlated probes targeting the gene LOC644246 and the duplicated genes LRRC37A and LRRC37A2, and a third uncorrelated probe targeting the gene DCAKD. Significant cis-associations were also observed between SNPs and two probes targeting genes in the HLA region on chromosome 6. Expanding the association study to examine trans effects revealed an additional 23 SNP-probe associations reaching statistical significance (p<2.8 × 10(-8)) including SNPs from the SNCA, MAPT and RIT2 regions. These findings provide additional context for the interpretation of PD associated SNPs identified in recent GWAS as well as potential insight into the mechanisms underlying the observed SNP associations.

SNP set association analysis for familial data

Genome-wide association studies (GWAS) are a popular approach for identifying common genetic variants and epistatic effects associated with a disease phenotype. The traditional statistical analysis of such GWAS attempts to assess the association between each individual single-nucleotide polymorphism (SNP) and the observed phenotype. Recently, kernel machine-based tests for association between a SNP set (e.g., SNPs in a gene) and the disease phenotype have been proposed as a useful alternative to the traditional individual-SNP approach, and allow for flexible modeling of the potentially complicated joint SNP effects in a SNP set while adjusting for covariates. We extend the kernel machine framework to accommodate related subjects from multiple independent families, and provide a score-based variance component test for assessing the association of a given SNP set with a continuous phenotype, while adjusting for additional covariates and accounting for within-family correlation. We illustrate the proposed method using simulation studies and an application to genetic data from the Genetic Epidemiology Network of Arteriopathy (GENOA) study.

P2RX7: expression responds to sleep deprivation and associates with rapid cycling in bipolar disorder type 1

Context

Rapid cycling is a severe form of bipolar disorder with an increased rate of episodes that is particularly treatment-responsive to chronotherapy and stable sleep-wake cycles. We hypothesized that the P2RX7 gene would be affected by sleep deprivation and be implicated in rapid cycling.

Objectives

To assess whether P2RX7 expression is affected by total sleep deprivation and if variation in P2RX7 is associated with rapid cycling in bipolar patients.

Design

Gene expression analysis in peripheral blood mononuclear cells (PBMCs) from healthy volunteers and case-case and case-control SNP/haplotype association analyses in patients.

Participants

Healthy volunteers at the sleep research center, University of California, Irvine Medical Center (UCIMC), USA (n = 8) and Swedish outpatients recruited from specialized psychiatric clinics for bipolar disorder, diagnosed with bipolar disorder type 1 (n = 569; rapid cycling: n = 121) and anonymous blood donor controls (n = 1,044).

Results

P2RX7 RNA levels were significantly increased during sleep deprivation in PBMCs from healthy volunteers (p = 2.3*10⁻⁹). The P2RX7 rs2230912 _A allele was more common (OR = 2.2, p = 0.002) and the ACGTTT haplotype in P2RX7 (rs1718119 to rs1621388) containing the protective rs2230912_G allele (OR = 0.45–0.49, p = 0.003–0.005) was less common, among rapid cycling cases compared to non-rapid cycling bipolar patients and blood donor controls.

Conclusions

Sleep deprivation increased P2RX7 expression in healthy persons and the putatively low-activity P2RX7 rs2230912 allele A variant was associated with rapid cycling in bipolar disorder. This supports earlier findings of P2RX7 associations to affective disorder and is in agreement with that particularly rapid cycling patients have a more vulnerable diurnal system.

PRKCB is associated with calcineurin inhibitor-induced renal dysfunction in heart transplant recipients

OBJECTIVES

Single nucleotide polymorphisms (SNPs) in the transforming growth factor-β1 gene (TGFB1) have been inconsistently associated with calcineurin inhibitor (CNI)-induced renal dysfunction following cardiac transplantation. The impact of genetic variants related to the renin-angiotensin-aldosterone system (RAAS) and natriuretic peptides, which are implicated in CNI nephrotoxicity, is unknown. The primary objective of this study was to validate the association between two common variants in TGFB1 (rs1800470, rs1800471) and postcardiac transplant renal function. The secondary objective was to investigate the effect of candidate genes related to the RAAS, natriuretic peptides, and other elements involved in the intracellular signaling of these pathways.

METHODS

We conducted a retrospective cohort study of 158 heart transplant recipients treated with CNIs, and evaluated the association between select SNPs and the estimated glomerular filtration rate as calculated by the Modification of Diet in Renal Disease simplified formula. A total of 273 SNPs distributed in 44 genes were tested.

RESULTS

No association was observed between TGFB1 variants and renal function. One polymorphism in the protein kinase C-β gene (PRKCB; rs11074606), which is implicated in the RAAS intracellular signaling, was significantly associated with post-transplant estimated glomerular filtration rate after adjusting for possible confounders (P=0.00049). This marker is in linkage disequilibrium with two variants located in putative regulatory regions of the gene (rs2283541, rs1013316).

CONCLUSION

Our results suggest that PRKCB may be a potential predictor of CNI-induced nephrotoxicity in heart transplant recipients, and could therefore be a promising candidate to identify patients who are most susceptible to this adverse drug reaction.

Mapping genetic variants associated with beta-adrenergic responses in inbred mice

β-blockers and β-agonists are primarily used to treat cardiovascular diseases. Inter-individual variability in response to both drug classes is well recognized, yet the identity and relative contribution of the genetic players involved are poorly understood. This work is the first genome-wide association study (GWAS) addressing the values and susceptibility of cardiovascular-related traits to a selective β₁-blocker, Atenolol (ate), and a β-agonist, Isoproterenol (iso). The phenotypic dataset consisted of 27 highly heritable traits, each measured across 22 inbred mouse strains and four pharmacological conditions. The genotypic panel comprised 79922 informative SNPs of the mouse HapMap resource. Associations were mapped by Efficient Mixed Model Association (EMMA), a method that corrects for the population structure and genetic relatedness of the various strains. A total of 205 separate genome-wide scans were analyzed. The most significant hits include three candidate loci related to cardiac and body weight, three loci for electrocardiographic (ECG) values, two loci for the susceptibility of atrial weight index to iso, four loci for the susceptibility of systolic blood pressure (SBP) to perturbations of the β-adrenergic system, and one locus for the responsiveness of QTc (p<10⁻⁸). An additional 60 loci were suggestive for one or the other of the 27 traits, while 46 others were suggestive for one or the other drug effects (p<10⁻⁶). Most hits tagged unexpected regions, yet at least two loci for the susceptibility of SBP to β-adrenergic drugs pointed at members of the hypothalamic-pituitary-thyroid axis. Loci for cardiac-related traits were preferentially enriched in genes expressed in the heart, while 23% of the testable loci were replicated with datasets of the Mouse Phenome Database (MPD). Altogether these data and validation tests indicate that the mapped loci are relevant to the traits and responses studied.

Gene expression profiles in Parkinson disease prefrontal cortex implicate FOXO1 and genes under its transcriptional regulation

Parkinson disease (PD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN) region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9) of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR) of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1) transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR-significant group of genes (177 genes covered by 189 probes), suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs) selected from a recent meta-analysis of PD genome-wide association studies (GWAS) were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression-SNP (eSNP) analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK) gene and a probe in the spermine oxidase (SMOX) gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD-relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms.

Identification of sialyltransferase 8B as a generalized susceptibility gene for psychotic and mood disorders on chromosome 15q25-26

We previously identified a significant bipolar spectrum disorder linkage peak on 15q25-26 using 35 extended families with a broad clinical phenotype, including bipolar disorder (types I and II), recurrent unipolar depression and schizoaffective disorder. However, the specific gene(s) contributing to this signal had not been identified. By a fine mapping association study in an Australian case-control cohort (n = 385), we find that the sialyltransferase 8B (ST8SIA2) gene, coding for an enzyme that glycosylates proteins involved in neuronal plasticity which has previously shown association to both schizophrenia and autism, is associated with increased risk to bipolar spectrum disorder. Nominal single point association was observed with SNPs in ST8SIA2 (rs4586379, P = 0.0043; rs2168351, P = 0.0045), and a specific risk haplotype was identified (frequency: bipolar vs controls = 0.41 vs 0.31; χ(2) = 6.46, P = 0.011, OR = 1.47). Over-representation of the specific risk haplotype was also observed in an Australian schizophrenia case-control cohort (n = 256) (χ(2) = 8.41, P = 0.004, OR = 1.82). Using GWAS data from the NIMH bipolar disorder (n = 2055) and NIMH schizophrenia (n = 2550) cohorts, the equivalent haplotype was significantly over-represented in bipolar disorder (χ(2) = 5.91, P = 0.015, OR = 1.29), with the same direction of effect in schizophrenia, albeit non-significant (χ(2) = 2.3, P = 0.129, OR = 1.09). We demonstrate marked down-regulation of ST8SIA2 gene expression across human brain development and show a significant haplotype×diagnosis effect on ST8SIA2 mRNA levels in adult cortex (ANOVA: F(1,87) = 6.031, P = 0.016). These findings suggest that variation the ST8SIA2 gene is associated with increased risk to mental illness, acting to restrict neuronal plasticity and disrupt early neuronal network formation, rendering the developing and adult brain more vulnerable to secondary genetic or environmental insults.

Meta-analysis of Parkinson's disease: identification of a novel locus, RIT2

OBJECTIVE

Genome-wide association (GWAS) methods have identified genes contributing to Parkinson's disease (PD); we sought to identify additional genes associated with PD susceptibility.

METHODS

A 2-stage design was used. First, individual level genotypic data from 5 recent PD GWAS (Discovery Sample: 4,238 PD cases and 4,239 controls) were combined. Following imputation, a logistic regression model was employed in each dataset to test for association with PD susceptibility and results from each dataset were meta-analyzed. Second, 768 single-nucleotide polymorphisms (SNPs) were genotyped in an independent Replication Sample (3,738 cases and 2,111 controls).

RESULTS

Genome-wide significance was reached for SNPs in SNCA (rs356165; G: odds ratio [OR]=1.37; p=9.3×10(-21)), MAPT (rs242559; C: OR=0.78; p=1.5×10(-10)), GAK/DGKQ (rs11248051; T: OR=1.35; p=8.2×10(-9)/rs11248060; T: OR=1.35; p=2.0×10(-9)), and the human leukocyte antigen (HLA) region (rs3129882; A: OR=0.83; p=1.2×10(-8)), which were previously reported. The Replication Sample confirmed the associations with SNCA, MAPT, and the HLA region and also with GBA (E326K; OR=1.71; p=5×10(-8) Combined Sample) (N370; OR=3.08; p=7×10(-5) Replication sample). A novel PD susceptibility locus, RIT2, on chromosome 18 (rs12456492; p=5×10(-5) Discovery Sample; p=1.52×10(-7) Replication sample; p=2×10(-10) Combined Sample) was replicated. Conditional analyses within each of the replicated regions identified distinct SNP associations within GBA and SNCA, suggesting that there may be multiple risk alleles within these genes.

INTERPRETATION

We identified a novel PD susceptibility locus, RIT2, replicated several previously identified loci, and identified more than 1 risk allele within SNCA and GBA.

Meat-related mutagen exposure, xenobiotic metabolizing gene polymorphisms and the risk of advanced colorectal adenoma and cancer

Meat mutagens, including heterocyclic amines (HCAs), polycyclic aromatic hydrocarbons (PAHs) and N-nitroso compounds (NOCs), may be involved in colorectal carcinogenesis depending on their activation or detoxification by phase I and II xenobiotic metabolizing enzymes (XME). Using unconditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI), we examined the intake of five meat mutagens and >300 single nucleotide polymorphisms (SNPs) in 18 XME genes in relation to advanced colorectal adenoma (1205 cases and 1387 controls) and colorectal cancer (370 cases and 401 controls) within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Dietary intake of meat mutagens was assessed using a food frequency questionnaire with a detailed meat-cooking module. An interaction was observed between 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) intake and the NAT1 polymorphism rs6586714 in the adenoma study (P(interaction) = 0.001). Among individuals carrying a GG genotype, high MeIQx intake was associated with a 43% increased risk of adenoma (95% CI 1.11-1.85, P(trend) = 0.07), whereas the reverse was observed among carriers of the A variant (OR = 0.50, 95% CI 0.30-0.84, P(trend) = 0.01). In addition, we observed some suggestive (P < 0.05) modifying effects for SNPs in other XME genes (UGT1A, CYP2E1, EPHX1, AHR and GSTM3), but these were not significant after adjustment for multiple testing. This large and comprehensive study of XME genes, meat mutagens and the risk of colorectal tumours found that a NAT1 polymorphism modified the association between MeIQx intake and colorectal adenoma risk.

Genetic variation in TRPS1 may regulate hip geometry as well as bone mineral density

Trps1 has been proposed as a candidate gene for a mouse bone mineral density (BMD) QTL on Chromosome (Chr) 15, but it remained unclear if this gene was associated with BMD in humans. We used newly available data and advanced bioinformatics techniques to confirm that Trps1 is the most likely candidate gene for the mouse QTL. In short, by combining the raw genetic mapping data from two F2 generation crosses of inbred strains of mice, we narrowed the 95% confidence interval of this QTL down to the Chr 15 region spanning from 6 to 24cM. This region contains 131 annotated genes. Using block haplotyping, all other genes except Trps1 were eliminated as candidates for this QTL. We then examined associations of 208 SNPs within 10kb of TRPS1 with BMD and hip geometry, using human genome-wide association study (GWAS) data from the GEFOS consortium. After correction for multiple testing, six TRPS1 SNPs were significantly associated with femoral neck BMD (P=0.0015-0.0019; adjusted P=0.038-0.048). We also found that three SNPs were highly associated with femoral neck width in women (rs10505257, P=8.6×10(-5), adjusted P=2.15×10(-3); rs7002384, P=5.5×10(-4), adjusted P=01.38×10(-2)). In conclusion, we demonstrated that combining association studies in humans with murine models provides an efficient strategy to identify new candidate genes for bone phenotypes.

Association between milk protein gene variants and protein composition traits in dairy cattle

The objective of this study was to identify DNA markers in the 4 casein genes (CSN1S1, CSN1S2, CSN2, and CSN3) and the 2 major whey protein genes (LALBA and LGB) that show associations with milk protein profile measured by reverse-phase HPLC. Fifty-three single nucleotide polymorphisms (SNP) were genotyped for cows in a unique resource population consisting of purebred Holstein and (Holstein × Jersey) × Holstein crossbred animals. Seven traits were analyzed, including concentrations of α(S)-casein (CN), β-CN, κ-CN, α-lactalbumin, β-lactoglobulin, and 2 additional secondary traits, the total concentration of the above 5 milk proteins and the α(S)-CN to β-CN ratio. A substantial fraction of phenotypic variation could be explained by the additive genetic component for the 7 milk protein composition traits studied. Moreover, several SNP were significantly associated with all examined traits at an experiment-wise error rate of 0.05, except for α-lactalbumin. Importantly, the significant SNP explained a large proportion of the phenotypic variation of milk protein composition. Our findings could be used for selecting animals that produce milk with desired composition or desired processing and manufacturing properties.

Genetic variants of FOXP2 and KIAA0319/TTRAP/THEM2 locus are associated with altered brain activation in distinct language-related regions

Recent advances have been made in the genetics of two human communication skills: speaking and reading. Mutations of the FOXP2 gene cause a severe form of language impairment and orofacial dyspraxia, while single-nucleotide polymorphisms (SNPs) located within a KIAA0319/TTRAP/THEM2 gene cluster and affecting the KIAA0319 gene expression are associated with reading disability. Neuroimaging studies of clinical populations point to partially distinct cerebral bases for language and reading impairments. However, alteration of FOXP2 and KIAA0319/TTRAP/THEM2 polymorphisms on typically developed language networks has never been explored. Here, we genotyped and scanned 94 healthy subjects using fMRI during a reading task. We studied the correlation of genetic polymorphisms with interindividual variability in brain activation and functional asymmetry in frontal and temporal cortices. In FOXP2, SNPs rs6980093 and rs7799109 were associated with variations of activation in the left frontal cortex. In the KIAA0319/TTRAP/THEM2 locus, rs17243157 was associated with asymmetry in functional activation of the superior temporal sulcus (STS). Interestingly, healthy subjects bearing the KIAA0319/TTRAP/THEM2 variants previously identified as enhancing the risk of dyslexia showed a reduced left-hemispheric asymmetry of the STS. Our results confirm that both FOXP2 and KIAA0319/TTRAP/THEM2 genes play an important role in human language development, but probably through different cerebral pathways. The observed cortical effects mirror previous fMRI results in developmental language and reading disorders, and suggest that a continuum may exist between these pathologies and normal interindividual variability.

Nonparametric evaluation of quantitative traits in population-based association studies when the genetic model is unknown

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

PERMORY-MPI: a program for high-speed parallel permutation testing in genome-wide association studies

PERMORY is software for accelerated permutation testing of genome-wide association studies (GWAS). We have parallelized PERMORY using the Message-Passing Interface resulting in a nearly linear speedup. Furthermore, we added accelerated analysis of GWAS using quantitative phenotypes, and an accurate estimation of the effective number of independent tests.

AVAILABILITY AND IMPLEMENTATION

Free download from http://permory.org.

Comprehensive investigation of genetic variation in the 8q24 region and multiple myeloma risk in the IMMEnSE consortium

Genome-wide association studies (GWAS) have shown that the 8q24 region harbours multiple independent cancer susceptibility loci, even though it is devoid of genes. Given that no GWAS data are currently available for multiple myeloma (MM), we tested the hypothesis that genetic variants in this region could play a role in MM risk. We genotyped 20 single nucleotide polymorphisms of 8q24 in 1188 MM cases and 2465 controls and found a statistically significant (P = 0·0022) association between rs2456449 and MM risk. These data provide further evidence that the genetic variability in the 8q24 region is associated with cancer risk, particularly haematological malignancies.

Genetic variation in the toll-like receptor 4 and prostate cancer incidence and mortality

BACKGROUND

Common genetic variants in the Toll-like receptor 4 (TLR4), which is involved in inflammation and immune response pathways, may be important for prostate cancer.

METHODS

In a large nested case-control study of prostate cancer in the Physicians' Health Study (1982-2004), 10 single nucleotide polymorphisms (SNPs) were selected and genotyped to capture common variation within the TLR4 gene as well as 5 kb up and downstream. Unconditional logistic regression was used to assess associations of these SNPs with total prostate cancer incidence, and with prostate cancers defined as advanced stage/lethal (T3/T4, M1/N1(T1-T4), lethal) or high Gleason grade (7 (4 + 3) or greater). Cox-proportional hazards regression was used to assess progression to metastases and death among prostate cancer cases.

RESULTS

The study included 1,267 controls and 1,286 incident prostate cancer cases, including 248 advanced stage/lethal and 306 high grade cases. During a median follow-up of 10.6 years, 183 men died of prostate cancer or developed distant metastases. No statistically significant associations between the TLR4 SNPs were found for total prostate cancer incidence, including SNPs for which an association was reported in other published studies. Additionally, there were no significant associations with TLR4 SNPS and the incidence of advanced stage/lethal, or high grade cancers; nor was there evidence among prostate cancer cases for associations of TLR4 SNPs with progression to prostate cancer specific mortality or bony metastases.

CONCLUSIONS

Results from this prospective nested case-control study suggest that genetic variation across TLR4 alone is not strongly associated with prostate cancer risk or mortality.

Rapid and robust resampling-based multiple-testing correction with application in a genome-wide expression quantitative trait loci study

Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. In a typical eQTL study, the huge number of genetic markers and expression traits and their complicated correlations present a challenging multiple-testing correction problem. The resampling-based test using permutation or bootstrap procedures is a standard approach to address the multiple-testing problem in eQTL studies. A brute force application of the resampling-based test to large-scale eQTL data sets is often computationally infeasible. Several computationally efficient methods have been proposed to calculate approximate resampling-based P-values. However, these methods rely on certain assumptions about the correlation structure of the genetic markers, which may not be valid for certain studies. We propose a novel algorithm, rapid and exact multiple testing correction by resampling (REM), to address this challenge. REM calculates the exact resampling-based P-values in a computationally efficient manner. The computational advantage of REM lies in its strategy of pruning the search space by skipping genetic markers whose upper bounds on test statistics are small. REM does not rely on any assumption about the correlation structure of the genetic markers. It can be applied to a variety of resampling-based multiple-testing correction methods including permutation and bootstrap methods. We evaluate REM on three eQTL data sets (yeast, inbred mouse, and human rare variants) and show that it achieves accurate resampling-based P-value estimation with much less computational cost than existing methods. The software is available at http://csbio.unc.edu/eQTL.

Brain structure in healthy adults is related to serum transferrin and the H63D polymorphism in the HFE gene

Control of iron homeostasis is essential for healthy central nervous system function: iron deficiency is associated with cognitive impairment, yet iron overload is thought to promote neurodegenerative diseases. Specific genetic markers have been previously identified that influence levels of transferrin, the protein that transports iron throughout the body, in the blood and brain. Here, we discovered that transferrin levels are related to detectable differences in the macro- and microstructure of the living brain. We collected brain MRI scans from 615 healthy young adult twins and siblings, of whom 574 were also scanned with diffusion tensor imaging at 4 Tesla. Fiber integrity was assessed by using the diffusion tensor imaging-based measure of fractional anisotropy. In bivariate genetic models based on monozygotic and dizygotic twins, we discovered that partially overlapping additive genetic factors influenced transferrin levels and brain microstructure. We also examined common variants in genes associated with transferrin levels, TF and HFE, and found that a commonly carried polymorphism (H63D at rs1799945) in the hemochromatotic HFE gene was associated with white matter fiber integrity. This gene has a well documented association with iron overload. Our statistical maps reveal previously unknown influences of the same gene on brain microstructure and transferrin levels. This discovery may shed light on the neural mechanisms by which iron affects cognition, neurodevelopment, and neurodegeneration.

Flexible semiparametric analysis of longitudinal genetic studies by reduced rank smoothing

In family-based longitudinal genetic studies, investigators collect repeated measurements on a trait that changes with time along with genetic markers. Since repeated measurements are nested within subjects and subjects are nested within families, both the subject-level and measurement-level correlations must be taken into account in the statistical analysis to achieve more accurate estimation. In such studies, the primary interests include to test for quantitative trait locus (QTL) effect, and to estimate age-specific QTL effect and residual polygenic heritability function. We propose flexible semiparametric models along with their statistical estimation and hypothesis testing procedures for longitudinal genetic designs. We employ penalized splines to estimate nonparametric functions in the models. We find that misspecifying the baseline function or the genetic effect function in a parametric analysis may lead to substantially inflated or highly conservative type I error rate on testing and large mean squared error on estimation. We apply the proposed approaches to examine age-specific effects of genetic variants reported in a recent genome-wide association study of blood pressure collected in the Framingham Heart Study.

Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets

Current genome-wide association studies (GWAS) use commercial genotyping microarrays that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs is further boosted by advanced statistical genotype-imputation algorithms and large SNP databases for reference human populations. The testing of a huge number of SNPs needs to be taken into account in the interpretation of statistical significance in such genome-wide studies, but this is complicated by the non-independence of SNPs because of linkage disequilibrium (LD). Several previous groups have proposed the use of the effective number of independent markers (M_e) for the adjustment of multiple testing, but current methods of calculation for M_e are limited in accuracy or computational speed. Here, we report a more robust and fast method to calculate M_e. Applying this efficient method [implemented in a free software tool named Genetic type 1 error calculator (GEC)], we systematically examined the M_e, and the corresponding p-value thresholds required to control the genome-wide type 1 error rate at 0.05, for 13 Illumina or Affymetrix genotyping arrays, as well as for HapMap Project and 1000 Genomes Project datasets which are widely used in genotype imputation as reference panels. Our results suggested the use of a p-value threshold of ~10⁻⁷ as the criterion for genome-wide significance for early commercial genotyping arrays, but slightly more stringent p-value thresholds ~5 × 10⁻⁸ for current or merged commercial genotyping arrays, ~10⁻⁸ for all common SNPs in the 1000 Genomes Project dataset and ~5 × 10⁻⁸ for the common SNPs only within genes.

A comprehensive study of polymorphisms in the ABCB1, ABCC2, ABCG2, NR1I2 genes and lymphoma risk

Owing to their role in controlling the efflux of toxic compounds, transporters are central players in the process of detoxification and elimination of xenobiotics, which in turn is related to cancer risk. Among these transporters, ATP-binding cassette B1/multidrug resistance 1 (ABCB1/MDR1), ABCC2/multidrug resistance protein 2 (MRP2) and ABCG2/breast cancer resistance protein (BCRP) affect susceptibility to many hematopoietic malignancies. The maintenance of regulated expression of these transporters is governed through the activation of intracellular "xenosensors" like the nuclear receptor 1I2/pregnane X receptor (NR1I2/PXR). SNPs in genes encoding these regulators have also been implicated in the risk of several cancers. Using a tagging approach, we tested the hypothesis that common polymorphisms in the transporter genes ABCB1, ABCC2, ABCG2 and the regulator gene NR1I2 could be implicated in lymphoma risk. We selected 68 SNPs in the four genes, and we genotyped them in 1,481 lymphoma cases and 1,491 controls of the European case-control study (EpiLymph) using the Illumina GoldenGate™ assay technology. Carriers of the SNP rs6857600 minor allele in ABCG2 was associated with a decrease in risk of B-cell lymphoma (B-NHL) overall (p < 0.001). Furthermore, a decreased risk of chronic lymphocytic leukemia (CLL) was associated with the ABCG2 rs2231142 variant (p = 0.0004), which could be replicated in an independent population. These results suggest a role for this gene in B-NHL susceptibility, especially for CLL.

Genetic association and gene-gene interaction analyses in African American dialysis patients with nondiabetic nephropathy

BACKGROUND

African Americans have increased susceptibility to nondiabetic nephropathy relative to European Americans.

STUDY DESIGN

Follow-up of a pooled genome-wide association study (GWAS) in African American dialysis patients with nondiabetic nephropathy; novel gene-gene interaction analyses.

SETTING & PARTICIPANTS

Wake Forest sample: 962 African American nondiabetic nephropathy cases, 931 non-nephropathy controls. Replication sample: 668 Family Investigation of Nephropathy and Diabetes (FIND) African American nondiabetic nephropathy cases, 804 non-nephropathy controls.

PREDICTORS

Individual genotyping of top 1,420 pooled GWAS-associated single-nucleotide polymorphisms (SNPs) and 54 SNPs in 6 nephropathy susceptibility genes.

OUTCOMES

APOL1 genetic association and additional candidate susceptibility loci interacting with or independently from APOL1.

RESULTS

The strongest GWAS associations included 2 noncoding APOL1 SNPs, rs2239785 (OR, 0.33; dominant; P = 5.9 × 10(-24)) and rs136148 (OR, 0.54; additive; P = 1.1 × 10(-7)) with replication in FIND (P = 5.0 × 10(-21) and 1.9 × 10(-05), respectively). rs2239785 remained associated significantly after controlling for the APOL1 G1 and G2 coding variants. Additional top hits included a CFH SNP (OR from meta-analysis in the 3,367 African American cases and controls, 0.81; additive; P = 6.8 × 10(-4)). The 1,420 SNPs were tested for interaction with APOL1 G1 and G2 variants. Several interactive SNPs were detected; the most significant was rs16854341 in the podocin gene (NPHS2; P = 0.0001).

LIMITATIONS

Nonpooled GWASs have not been performed in African American patients with nondiabetic nephropathy.

CONCLUSIONS

This follow-up of a pooled GWAS provides additional and independent evidence that APOL1 variants contribute to nondiabetic nephropathy in African Americans and identified additional associated and interactive nondiabetic nephropathy susceptibility genes.

Pancreatic cancer susceptibility loci and their role in survival

Pancreatic cancer has one of the worst mortality rates of all cancers. Little is known about its etiology, particularly regarding inherited risk. The PanScan project, a genome-wide association study, identified several common polymorphisms affecting pancreatic cancer susceptibility. Single nucleotide polymorphisms (SNPs) in ABO, sonic hedgehog (SHH), telomerase reverse transcriptase (TERT), nuclear receptor subfamily 5, group A, member 2 (NR5A2) were found to be associated with pancreatic cancer risk. Moreover the scan identified loci on chromosomes 13q22.1 and 15q14, to which no known genes or other functional elements are mapped. We sought to replicate these observations in two additional, independent populations (from Germany and the UK), and also evaluate the possible impact of these SNPs on patient survival. We genotyped 15 SNPs in 690 cases of pancreatic ductal adenocarcinoma (PDAC) and in 1277 healthy controls. We replicated several associations between SNPs and PDAC risk. Furthermore we found that SNP rs8028529 was weakly associated with a better overall survival (OS) in both populations. We have also found that NR5A2 rs12029406_T allele was associated with a shorter survival in the German population. In conclusion, we found that rs8028529 could be, if these results are replicated, a promising marker for both risk and prognosis for this lethal disease.

Association study on IL4, IL13 and IL4RA polymorphisms in mite-sensitized persistent allergic rhinitis in a Chinese population

Background

The IL4, IL13, and IL4 receptor α chain (IL4RA) genes are candidate genes for atopic diseases. We hypothesized that the polymorphisms in these genes are associated with persistent allergic rhinitis (PER).

Objective

To investigate the association of the potential functional polymorphisms in IL4, IL13, and IL4RA with PER induced by house dust mites in a Chinese population.

Methods

Using the TaqMan method, we genotyped six single nucleotide polymorphisms (SNPs) including C-590T in IL4, C-1055T and Arg130Gln in IL13, and Ile50Val, Ser478Pro and Gln551Arg in IL4RA, in a case-control study of 265 patients with PER and 275 healthy controls.

Results

We found that the CT/CC genotypes in IL4 C-590T were associated with a significantly decreased risk of mite-sensitized PER [adjusted odds ratio (OR)  = 0.64, 95% confidence interval (CI) 0.45–0.92], compared to the TT genotype. Furthermore, PER patients with CT/CC genotypes had significantly lower serum levels of total IgE than those with TT genotype (P = 0.001). However, there was no significant association of the IL13 and IL4RA polymorphisms with mite-sensitized PER (P>0.05).

Conclusions

Our results suggest that the C-590T polymorphism in IL4 may contribute to the susceptibility to mite-sensitized PER in a Chinese population.

An X chromosome-wide association study in autism families identifies TBL1X as a novel autism spectrum disorder candidate gene in males

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic component. The skewed prevalence toward males and evidence suggestive of linkage to the X chromosome in some studies suggest the presence of X-linked susceptibility genes in people with ASD.

METHODS

We analyzed genome-wide association study (GWAS) data on the X chromosome in three independent autism GWAS data sets: two family data sets and one case-control data set. We performed meta- and joint analyses on the combined family and case-control data sets. In addition to the meta- and joint analyses, we performed replication analysis by using the two family data sets as a discovery data set and the case-control data set as a validation data set.

RESULTS

One SNP, rs17321050, in the transducin β-like 1X-linked (TBL1X) gene [OMIM:300196] showed chromosome-wide significance in the meta-analysis (P value = 4.86 × 10-6) and joint analysis (P value = 4.53 × 10-6) in males. The SNP was also close to the replication threshold of 0.0025 in the discovery data set (P = 5.89 × 10-3) and passed the replication threshold in the validation data set (P = 2.56 × 10-4). Two other SNPs in the same gene in linkage disequilibrium with rs17321050 also showed significance close to the chromosome-wide threshold in the meta-analysis.

CONCLUSIONS

TBL1X is in the Wnt signaling pathway, which has previously been implicated as having a role in autism. Deletions in the Xp22.2 to Xp22.3 region containing TBL1X and surrounding genes are associated with several genetic syndromes that include intellectual disability and autistic features. Our results, based on meta-analysis, joint analysis and replication analysis, suggest that TBL1X may play a role in ASD risk.

The APOA1/C3/A4/A5 cluster and markers of allostatic load in the Boston Puerto Rican Health Study

BACKGROUND AND AIMS

The APOA1/C3/A4/A5 cluster encodes key regulators of plasma lipids. Interactions between dietary factors and single nucleotide polymorphisms (SNPs) in the cluster have been reported. Allostatic load, or physiological dysregulation in response to stress, has been implicated in shaping health disparities in ethnic groups. We aimed to determine the association between polymorphisms in the APOA1/C3/A4/A5 cluster with allostatic load parameters, alone, and in interaction with dietary fat intake in Puerto Ricans adults.

METHODS AND RESULTS

Data on demographic and anthropometric measures, lifestyle behaviors, and medication use, as well as blood and urine samples for biomarker analysis, were obtained from participants of the Boston Puerto Rican Health Study (n=821, age 45-75 y). The 12 polymorphisms analyzed were not associated with allostatic load parameters. Significant interactions were observed between dietary fat intake and APOA1-75 in association with waist circumference (WC), (P=0.005), APOC3-640 with diastolic blood pressure (DBP), (P=0.003), and APOA4 N147S and APOA5 S19W with systolic blood pressure (SBP), (P=0.001 and P=0.002, respectively). Puerto Ricans homozygous for the common allele of APOA1-75, APOA4 N147S and APOA5 S19W had lower WC and SBP when consuming <31% of total fat from energy, than participants with the minor allele. Participants heterozygous for APOC3-640 had lower DBP at total fat intake ≥31% from energy.

CONCLUSION

SNPs in APOA1/C3/A4/A5, as modulated by dietary fat intake, appear to influence allostatic load parameters in Puerto Ricans.

Association of catechol-O-methyltransferase variants with duloxetine response in major depressive disorder

Single-nucleotide and diplotype associations with 17-item Hamilton Depression Rating Scale (HAMD(17)) total score changes were examined, based on catechol-O-methyltransferase (COMT) rs165599 status in duloxetine-treated, self-identified white patients with major depressive disorder. COMT rs165737 and a diplotype containing COMT rs165599 and COMT rs165737 were associated with HAMD(17) total score changes.

Association of milk protein genes with fertilization rate and early embryonic development in Holstein dairy cattle

Concomitant with intensive selection for increased milk yield, reproductive performance of dairy cows has declined in the last decades, in part due to an unfavourable genetic relationship between these traits. Given that the six main milk protein genes (i.e. whey proteins and caseins) are directly involved in milk production and hence have been a target of the strong selection aimed at improving milk yield in dairy cattle, we hypothesized that these genes could show selection footprints associated with fertility traits. In this study, we used an in-vitro fertilization (IVF) system to test genetic association between 66 single nucleotide polymorphisms (SNPs) in the four caseins (αS1-casein, αS2-casein, β-casein and κ-casein) and the two whey protein genes (α-lactalbumin and β-lactoglobulin) with fertilization rate and early embryonic development in the Holstein breed. A total of 6893 in-vitro fertilizations were performed and a total of 4661 IVF embryos were produced using oocytes from 399 ovaries and semen samples from 12 bulls. Associations between SNPs and fertility traits were analysed using a mixed linear model with genotype as fixed effect and ovary and bull as random effects. A multiple testing correction approach was used to account for the correlation between SNPs due to linkage disequilibrium. After correction, polymorphisms in the LALBA and LGB genes showed significant associations with fertilization success and blastocyst rate. No significant associations were detected between SNPs located in the casein region and IVF fertility traits. Although the molecular mechanisms underlying the association between whey protein genes and fertility have not yet been characterized, this study provides the first evidence of association between these genes and fertility traits. Furthermore, these results could shed light on the antagonistic relationship that exists between milk yield and fertility in dairy cattle.

Pharmacogenomic prediction of anthracycline-induced cardiotoxicity in children

PURPOSE

Anthracycline-induced cardiotoxicity (ACT) is a serious adverse drug reaction limiting anthracycline use and causing substantial morbidity and mortality. Our aim was to identify genetic variants associated with ACT in patients treated for childhood cancer.

PATIENTS AND METHODS

We carried out a study of 2,977 single-nucleotide polymorphisms (SNPs) in 220 key drug biotransformation genes in a discovery cohort of 156 anthracycline-treated children from British Columbia, with replication in a second cohort of 188 children from across Canada and further replication of the top SNP in a third cohort of 96 patients from Amsterdam, the Netherlands.

RESULTS

We identified a highly significant association of a synonymous coding variant rs7853758 (L461L) within the SLC28A3 gene with ACT (odds ratio, 0.35; P = 1.8 × 10(-5) for all cohorts combined). Additional associations (P < .01) with risk and protective variants in other genes including SLC28A1 and several adenosine triphosphate-binding cassette transporters (ABCB1, ABCB4, and ABCC1) were present. We further explored combining multiple variants into a single-prediction model together with clinical risk factors and classification of patients into three risk groups. In the high-risk group, 75% of patients were accurately predicted to develop ACT, with 36% developing this within the first year alone, whereas in the low-risk group, 96% of patients were accurately predicted not to develop ACT.

CONCLUSION

We have identified multiple genetic variants in SLC28A3 and other genes associated with ACT. Combined with clinical risk factors, genetic risk profiling might be used to identify high-risk patients who can then be provided with safer treatment options.

Association of Allelic Variation in Genes Mediating Aspects of Energy Homeostasis with Weight Gain during Administration of Antipsychotic Drugs (CATIE Study)

Antipsychotic drugs are widely used in treating schizophrenia, bipolar disorder, and other psychiatric disorders. Many of these drugs, despite their therapeutic advantages, substantially increase body weight. We assessed the association of alleles of 31 genes implicated in body weight regulation with weight gain among patients being treated with specific antipsychotic medications in the clinical antipsychotic trials in intervention effectiveness study, we found that rs2237988 in Potassium Channel Inwardly Rectifying Subfamily J Member 11 (KCNJ11), rs13269119 in Solute carrier family 30 member 8 (SLC30A8), and rs9922047 in fat mass and obesity associated (FTO) were associated with percent weight gain. We also observed the significant interaction of rs11643744 by treatment effect on the weight gain.

A new approach to account for the correlations among single nucleotide polymorphisms in genome: wide association studies

In genetic association studies, such as genome-wide association studies (GWAS), the number of single nucleotide polymorphisms (SNPs) can be as large as hundreds of thousands. Due to linkage disequilibrium, many SNPs are highly correlated; assuming they are independent is not valid. The commonly used multiple comparison methods, such as Bonferroni correction, are not appropriate and are too conservative when applied to GWAS. To overcome these limitations, many approaches have been proposed to estimate the so-called effective number of independent tests to account for the correlations among SNPs. However, many current effective number estimation methods are based on eigenvalues of the correlation matrix. When the dimension of the matrix is large, the numeric results may be unreliable or even unobtainable. To circumvent this obstacle and provide better estimates, we propose a new effective number estimation approach which is not based on the eigenvalues. We compare the new method with others through simulated and real data. The comparison results show that the proposed method has very good performance.

Molecular characterization of a long range haplotype affecting protein yield and mastitis susceptibility in Norwegian Red cattle

Background

Previous fine mapping studies in Norwegian Red cattle (NRC) in the region 86-90.4 Mb on Bos taurus chromosome 6 (BTA6) has revealed a quantitative trait locus (QTL) for protein yield (PY) around 88 Mb and a QTL for clinical mastitis (CM) around 90 Mb. The close proximity of these QTLs may partly explain the unfavorable genetic correlation between these two traits in NRC. A long range haplotype covering this region was introduced into the NRC population through the importation of a Holstein-Friesian bull (1606 Frasse) from Sweden in the 1970s. It has been suggested that this haplotype has a favorable effect on milk protein content but an unfavorable effect on mastitis susceptibility. Selective breeding for milk production traits is likely to have increased the frequency of this haplotype in the NRC population.

Results

Association mapping for PY and CM in NRC was performed using genotypes from 556 SNPs throughout the region 86-97 Mb on BTA6 and daughter-yield-deviations (DYDs) from 2601 bulls made available from the Norwegian dairy herd recording system. Highest test scores for PY were found for single-nucleotide polymorphisms (SNPs) within and surrounding the genes CSN2 and CSN1S2, coding for the β-casein and α_S2-casein proteins. High coverage re-sequencing by high throughput sequencing technology enabled molecular characterization of a long range haplotype from 1606 Frasse encompassing these two genes. Haplotype analysis of a large number of descendants from this bull indicated that the haplotype was not markedly disrupted by recombination in this region. The haplotype was associated with both increased milk protein content and increased susceptibility to mastitis, which might explain parts of the observed genetic correlation between PY and CM in NRC. Plausible causal polymorphisms affecting PY were detected in the promoter region and in the 5'-flanking UTR of CSN1S2. These polymorphisms could affect transcription or translation of CSN1S2 and thereby affect the amount of α_S2-casein in milk.

Highest test scores for CM were found in the region 89-91 Mb on BTA6, very close to a cluster of genes coding for CXC chemokines. Expression levels of some of these CXC chemokines have previously been shown to increase in bovine mammary gland cell lines after exposure to bacterial cell wall components.

Conclusion

Molecular characterization of the long range haplotype from the Holstein-Friesian bull 1606 Frasse, imported into NRC in the 1970s, revealed polymorphisms that could affect transcription or translation of the casein gene CSN1S2. Sires with this haplotype had daughters with significantly elevated milk protein content and selection for milk production traits is likely to have increased the frequency of this haplotype in the NRC population. The haplotype was also associated with increased mastitis susceptibility, which might explain parts of the genetic correlation between PY and CM in NRC.

A follow-up study for left ventricular mass on chromosome 12p11 identifies potential candidate genes

Background

Left ventricular mass (LVM) is an important risk factor for cardiovascular disease. Previously we found evidence for linkage to chromosome 12p11 in Dominican families, with a significant increase in a subset of families with high average waist circumference (WC). In the present study, we use association analysis to further study the genetic effect on LVM.

Methods

Association analysis with LVM was done in the one LOD critical region of the linkage peak in an independent sample of 897 Caribbean Hispanics. Genotype data were available on 7085 SNPs from 23 to 53 MB on chromosome 12p11. Adjustment was made for vascular risk factors and population substructure using an additive genetic model. Subset analysis by WC was performed to test for a difference in genetic effects between the high and low WC subsets.

Results

In the overall analysis, the most significant association was found to rs10743465, downstream of the SOX5 gene (p = 1.27E-05). Also, 19 additional SNPs had nominal p < 0.001. In the subset analysis, the most significant difference in genetic effect between those with high and low WC occurred with rs1157480 (p = 1.37E-04 for the difference in β coefficients), located upstream of TMTC1. Twelve additional SNPs in or near 6 genes had p < 0.001.

Conclusions

The current study supports previously identified evidence by linkage for a genetic effect on LVM on chromosome 12p11 using association analysis in population-based Caribbean Hispanic cohort. SOX5 may play an important role in the regulation of LVM. An interaction of TMTC1 with abdominal obesity may contribute to phenotypic variation of LVM.

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

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

Vitamin D receptor gene as a candidate gene for Parkinson disease

Vitamin D and vitamin D receptor (VDR) have been postulated as environmental and genetic factors in neurodegeneration disorders including multiple sclerosis (MS), Alzheimer disease (AD), and recently Parkinson disease (PD). Given the sparse data on PD, we conducted a two-stage study to evaluate the genetic effects of VDR in PD. In the discovery stage, 30 tagSNPs in VDR were tested for association with risk as a discrete trait and age-at-onset (AAO) as a quantitative trait in 770 Caucasian PD families. In the validation stage, 18 VDR SNPs were tested in an independent Caucasian cohort (267 cases and 267 controls) constructed from a genome-wide association study (GWAS). In the discovery dataset, SNPs in the 5' end of VDR were associated with both risk and AAO with more significant evidence of association with AAO (P= 0.0008-0.02). These 5' SNPs were also associated with AD in another study. In the validation dataset, SNPs in the 3' end of VDR were associated with AAO (P= 0.003) but not risk. The 3' end SNP has been associated with both MS and AD in previous studies. Our findings suggest VDR as a potential susceptibility gene and support an essential role of vitamin D in PD.

POMC and TP53 genetic variability and risk of basal cell carcinoma of skin: Interaction between host and genetic factors

BACKGROUND

Basal cell carcinoma (BCC) of the skin is the most common neoplasm among the Caucasian population of the western world. Ultraviolet (UV) radiation-induced p53 activation promotes cutaneous pigmentation by increasing transcriptional activity of pro-opiomelanocortin (POMC) in the skin. Induction of POMC/α-melanocyte-stimulating hormone (α-MSH) activates the melanocortin 1 receptor (MC1R), resulting in skin pigmentation. The tumor suppressor p53 is a key player in stress responses that preserve genomic stability, responding to a variety of insults including DNA damage, hypoxia, metabolic stress and oncogene activation. Malfunction of the p53 pathway is an almost universal hallmark of human tumors. Polymorphisms in the gene encoding p53 (TP53) alter its transcriptional activity, which in turn may influence the UV radiation-induced tanning response.

OBJECTIVE

The aim of the present work is to test association between POMC and TP53 genetic variability, the possible interplay with host factors and the risk of basal cell carcinoma of skin.

METHODS

We covered the variability of the two genes we used 17 tagging polymorphisms in 529 BCC cases and 532 healthy controls. We have also tested the possible interactions between the genetic variants and three known risk factors for BCC: skin complexion, sun effect and skin response to sun exposure.

RESULTS

We did not observe any statistically significant association between SNPs in these two genes and BCC risk overall, nor interactions of SNPs with known BCC risk factors. However we found that, in the group of subjects with lower sun exposure, carriers of one copy of the C allele of the TP53 SNP rs12951053 had a decreased risk of BCC (OR=0.28, 95% CI 0.12-0.62, P=0.002).

CONCLUSIONS

We have observed that the interplay of an environmental risk factor and one polymorphism in TP53 gene could modulate the risk of BCC.

Factors affecting the effective number of tests in genetic association studies: a comparative study of three PCA-based methods

The number of tested marker becomes numerous in genetic association studies (GAS) and one major challenge is to derive the multiple testing threshold. Some approaches calculating an effective number (M(eff)) of tests in GAS were developed and have been shown to be promising. As yet, there have been no comparisons of their robustness to influencing factors. We evaluated the performance of three principal component analysis (PCA)-based M(eff) estimation formulas (M(eff-C) in Cheverud (2001), M(eff-L) in Li and Ji (2005), and M(eff-G) in Galwey (2009)). Four influencing factors including LD measurements, marker density, population samples and the total number of tested markers were considered. We validated them by the Bonferroni's method and the permutation test with 10 000 random shuffles based on three real data sets. For each factor, M(eff-C) yielded conservative threshold except with D' coefficient, and M(eff-G) would be too liberal compared with the permutation test. Our results indicated that M(eff-L) based on r(2) coefficient achieve close approximation of the permutation threshold. As for a large number of markers, we recommended to use M(eff-L) with r(2) coefficient according to fixed-length separation, as well as fixed-number separation, to obtain accurate estimate of the multiple testing threshold and to save more computational time.