A high-density association screen of 155 ion transport genes for involvement with common migraine

The clinical overlap between monogenic Familial Hemiplegic Migraine (FHM) and common migraine subtypes, and the fact that all three FHM genes are involved in the transport of ions, suggest that ion transport genes may underlie susceptibility to common forms of migraine. To test this leading hypothesis, we examined common variation in 155 ion transport genes using 5257 single nucleotide polymorphisms (SNPs) in a Finnish sample of 841 unrelated migraine with aura cases and 884 unrelated non-migraine controls. The top signals were then tested for replication in four independent migraine case-control samples from the Netherlands, Germany and Australia, totalling 2835 unrelated migraine cases and 2740 unrelated controls. SNPs within 12 genes (KCNB2, KCNQ3, CLIC5, ATP2C2, CACNA1E, CACNB2, KCNE2, KCNK12, KCNK2, KCNS3, SCN5A and SCN9A) with promising nominal association (0.00041 < P < 0.005) in the Finnish sample were selected for replication. Although no variant remained significant after adjusting for multiple testing nor produced consistent evidence for association across all cohorts, a significant epistatic interaction between KCNB2 SNP rs1431656 (chromosome 8q13.3) and CACNB2 SNP rs7076100 (chromosome 10p12.33) (pointwise P = 0.00002; global P = 0.02) was observed in the Finnish case-control sample. We conclude that common variants of moderate effect size in ion transport genes do not play a major role in susceptibility to common migraine within these European populations, although there is some evidence for epistatic interaction between potassium and calcium channel genes, KCNB2 and CACNB2. Multiple rare variants or trans-regulatory elements of these genes are not ruled out.

Consistently replicating locus linked to migraine on 10q22-q23

Here, we present the results of two genome-wide scans in two diverse populations in which a consistent use of recently introduced migraine-phenotyping methods detects and replicates a locus on 10q22-q23, with an additional independent replication. No genetic variants have been convincingly established in migraine, and although several loci have been reported, none of them has been consistently replicated. We employed the three known migraine-phenotyping methods (clinical end diagnosis, latent-class analysis, and trait-component analysis) with robust multiple testing correction in a large sample set of 1675 individuals from 210 migraine families from Finland and Australia. Genome-wide multipoint linkage analysis that used the Kong and Cox exponential model in Finns detected a locus on 10q22-q23 with highly significant evidence of linkage (LOD 7.68 at 103 cM in female-specific analysis). The Australian sample showed a LOD score of 3.50 at the same locus (100 cM), as did the independent Finnish replication study (LOD score 2.41, at 102 cM). In addition, four previously reported loci on 8q21, 14q21, 18q12, and Xp21 were also replicated. A shared-segment analysis of 10q22-q23 linked Finnish families identified a 1.6-9.5 cM segment, centered on 101 cM, which shows in-family homology in 95% of affected Finns. This region was further studied with 1323 SNPs. Although no significant association was observed, four regions warranting follow-up studies were identified. These results support the use of symptomology-based phenotyping in migraine and suggest that the 10q22-q23 locus probably contains one or more migraine susceptibility variants.

Separate and interacting effects within the catechol-O-methyltransferase (COMT) are associated with schizophrenia

Several lines of evidence have implicated the catechol-O-methyltransferase (COMT) gene as a candidate for schizophrenia (SZ) susceptibility, not only because it encodes a key dopamine catabolic enzyme but also because it maps to the velocardiofacial syndrome region of chromosome 22q11 which has long been associated with SZ predisposition. The interest in COMT as a candidate SZ risk factor has led to numerous case-control and family-based studies, with the majority placing emphasis on examining a functional Val/Met polymorphism within this enzyme. Unfortunately, these studies have continually produced conflicting results. To assess the genetic contribution of other COMT variants to SZ susceptibility, we investigated three single-nucleotide polymorphisms (SNPs) (rs737865, rs4633, rs165599) in addition to the Val/Met variant (rs4680) in a highly selected sample of Australian Caucasian families containing 107 patients with SZ. The Val/Met and rs4633 variants showed nominally significant associations with SZ (P<0.05), although neither of the individual SNPs remained significant after adjusting for multiple testing (most significant P=0.1174). However, haplotype analyses showed strong evidence of an association; the most significant being the three-marker haplotype rs737865-rs4680-rs165599 (global P=0.0022), which spans more than 26 kb. Importantly, conditional analyses indicated the presence of two separate and interacting effects within this haplotype, irrespective of gender. In addition, our results indicate the Val/Met polymorphism is not disease-causing and is simply in strong linkage disequilibrium with a causative effect, which interacts with another as yet unidentified variant approximately 20 kb away. These results may help explain the inconsistent results reported on the Val/Met polymorphism and have important implications for future investigations into the role of COMT in SZ susceptibility.

Genetic background of bipolar disorder and related cognitive impairments

Bipolar disorder (BP) is a complex psychiatric disorder characterized by episodes of mania and depression. BP affects approximately 1% of the world’s population and shows no difference in lifetime prevalence between males and females. BP arises from complex interactions among genetic, developmental and environmental factors, and it is likely that several predisposing genes are involved in BP. The genetic background of BP is still poorly understood, although intensive and long-lasting research has identified several chromosomal regions and genes involved in susceptibility to BP. This thesis work aims to identify the genetic variants that influence bipolar disorder in the Finnish population by candidate gene and genome-wide linkage analyses in families with many BP cases. In addition to diagnosis-based phenotypes, neuropsychological traits that can be seen as potential endophenotypes or intermediate traits for BP were analyzed. In the first part of the thesis, we examined the role of the allelic variants of the TSNAX/DISC1 gene cluster to psychotic and bipolar spectrum disorders and found association of distinct allelic haplotypes with these two groups of disorders. The haplotype at the 5’ end of the Disrupted-in-Schizophrenia-1 gene (DISC1) was over-transmitted to males with psychotic disorder (p = 0.008; for an extended haplotype p = 0.0007 with both genders), whereas haplotypes at the 3’ end of DISC1 associated with bipolar spectrum disorder (p = 0.0002; for an extended haplotype p = 0.0001). The variants of these haplotypes also showed association with different cognitive traits. The haplotypes at the 5’ end associated with perseverations and auditory attention, while the variants at the 3’ end associated with several cognitive traits including verbal fluency and psychomotor processing speed. Second, in our complete set of BP families with 723 individuals we studied six functional candidate genes from three distinct signalling systems: serotonin-related genes (SLC6A4 and TPH2), BDNF -related genes (BDNF, CREB1 and NTRK2) and one gene related to the inflammation and cytokine system (P2RX7). We replicated association of the functional variant Val66Met of BDNF with BP and better performance in retention. The variants at the 5’ end of SLC6A4 also showed some evidence of association among males (p = 0.004), but the widely studied functional variants did not yield any significant results. A protective four-variant haplotype on P2RX7 showed evidence of association with BP and executive functions: semantic and phonemic fluency (p = 0.006 and p = 0.0003, respectively). Third, we analyzed 23 bipolar families originating from the North-Eastern region of Finland. A genome-wide scan was performed using the 6K single nucleotide polymorphism (SNP) array. We identified susceptibility loci at chromosomes 7q31 with a LOD score of 3.20 and at 9p13.1 with a LOD score of 4.02. We followed up both linkage findings in the complete set of 179 Finnish bipolar families. The finding on chromosome 9p13 was supported (maximum LOD score of 3.02), but the susceptibility gene itself remains unclarified. In the fourth part of the thesis, we wanted to test the role of the allelic variants that have associated with bipolar disorder in recent genome-wide association studies (GWAS). We could confirm findings for the DFNB31, SORCS2, SCL39A3, and DGKH genes. The best signal in this study comes from DFNB31, which remained significant after multiple testing corrections. Two variants of SORCS2 were allelic replications and presented the same signal as the haplotype analysis. However, no association was detected with the PALB2 gene, which was the most significantly associated region in the previous GWAS. Our results indicate that BP is heterogeneous and its genetic background may accordingly vary in different populations. In order to fully understand the allelic heterogeneity that underlies common diseases such as BP, complete genome sequencing for many individuals with and without the disease is required. Identification of the specific risk variants will help us better understand the pathophysiology underlying BP and will lead to the development of treatments with specific biochemical targets. In addition, it will further facilitate the identification of environmental factors that alter risk, which will potentially provide improved occupational, social and psychological advice for individuals with high risk of BP.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Allozyme and RAPD variation in the eastern Pacific yellowfin tuna (Thunnus albacares)

Stock structure of eastern Pacific yellowfin tuna was investigated by analyzing allozymes and random amplified polymorphic DNAs (RAPDs) from 10 samples of 20–30 individuals each, collected between 1994 and 1996 from fishing vessels operating in the Inter-American Tropical Tuna Commission (IATTC) yellowfin regulatory area (CYRA). Allozyme analysis resolved 28 loci, eight of which were polymorphic under the 0.95 criterion: Aat-S*, Glud, Gpi-F*, Gpi-S*, La, Lgg, Pap-F*, and 6-Pgd, resulting in a mean heterozygosity over all allozyme loci of H = 0.052. Four polymorphic RAPD loci were selected for analysis, resulting in a mean heterozygosity of H = 0.43. Eight of 45 pairwise comparisons of allozyme allele frequencies among the ten samples showed significant differences after correction for multiple testing (P<0.0001), all of which involved comparisons with the Gulf of California sample. Confirmation of this signal of population structure would have management implications. No significant divergence in RAPD allele frequencies was observed among samples. Weir and Cockerham θ estimated for allozyme loci (θ=0.048; P<0.05) and RAPD loci (θ=0.030; P>0.05) revealed little population structure among samples. Mantel tests demonstrated that the genetic relationships among samples did not correspond to an isolation-by-distance model for either class of marker. Four of eight comparisons of coastal and offshore samples revealed differences of allele frequencies at the Gpi-F* locus (P<0.05), although none of these differences was significant after correction for multiple testing (P>0.001). Results are consistent with the hypothesis that the CYRA yellowfin tuna samples comprise a single genetic stock, although gene flow appears to be greater among coastal samples than between coastal and offshore samples.

Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001

Toivonen, H., Srinivasan, A., King, R. D., Kramer, S. and Helma, C. (2003) Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001. Bioinformatics 19: 1183-1193

Robust test method for time-course microarray experiments.

BACKGROUND: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data. RESULTS: In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity. CONCLUSIONS: Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk.

Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int  = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int  = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.

BACE1 Polymorphisms Do Not Influence Platelet Membrane β-secretase Activity or Genetic Susceptibility for Alzheimer’s Disease in the Northern Irish Population

ß-Site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) is a biological and positional candidate gene for Alzheimer’s disease (AD). BACE1 is a protease that catalyses APP cleavage at the ß-secretase site. We evaluated all common and putatively functional polymorphisms in the genomic region encompassing BACE1 for an association with AD, and for functional effects on platelet ß-secretase activity. Tag SNPs (n = 10) derived from phase II of the International HapMap Project, and a nonsynonymous variant, were successfully genotyped in 901 Caucasian individuals from Northern Ireland using Sequenom iPLEX and TaqMan technologies. APOE genotyping was performed by PCR-RFLP. Platelet membrane ß-secretase activity was assayed in a subset of individuals (n = 311). Hardy–Weinberg equilibrium was observed for all variants. Evidence for an association with AD was observed with multi-marker haplotype analyses (P = 0.01), and with rs676134 when stratified for APOE genotype (P = 0.02), however adjusting for multiple testing negated the evidence for association of this variant with AD. ?2 analysis of genotype and allele frequencies in cases versus controls for individual SNPs revealed no evidence for association (5% level). No genetic factors were observed that significantly influenced platelet membrane ß-secretase activity. We have selected an appropriate subset of variants suitable for comprehensive genetic investigation of the BACE1 gene. Our results suggest that common BACE1 polymorphisms and putatively functional variants have no significant influence on genetic susceptibility to AD, or platelet ß-secretase activity, in this Caucasian Northern Irish population.

Genetic association analyses of non-synonymous single nucleotide polymorphisms in diabetic nephropathy

Aims/hypothesis: Diabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.

Methods: White type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A ? 2 test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.

Results: We assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.

Conclusions/interpretation: The nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.

Genetic analysis of coronary artery disease single nucleotide polymorphisms in diabetic nephropathy

Background. Diabetic nephropathy is a leading cause of end-stage renal disease. Premature mortality is common in patients with nephropathy, largely due to cardiovascular disease. Genetic variants implicated in macrovascular disease are therefore excellent candidates to assess for association with diabetic nephropathy. Recent genome-wide association studies have identified a total of 15 single-nucleotide polymorphisms (SNPs) that are reproducibly associated with cardiovascular disease.

Methods. We initially assessed these SNPs for association in UK type 1 diabetic patients with (cases; n = 597) and without (controls; n = 502) nephropathy using iPLEXTM and TaqMan® assays. Replication studies were performed with DNA genotyped in a total of 2668 individuals from the British Isles.

Results. One SNP (rs4420638) on chromosome 19q13 was found to be significantly associated with diabetic nephropathy before (P = 0.0002) and after correction for multiple testing (Pcorrected = 0.002). We replicated this finding in a phenotypically similar case–control collection comprising 709 individuals with type 1 diabetes (P = 0.002; combined P < 0.00001; OR = 1.54, 95% CI: 1.29–1.84).

Conclusions. Our case–control data suggest that rs4420638, or a functional SNP in linkage disequilibrium with this SNP, may be associated with diabetic nephropathy.

The impact of newly identified loci on coronary heart disease, stroke and total mortality in the MORGAM prospective cohorts

Recently, genome wide association studies (GWAS) have identified a number of single nucleotide polymorphisms (SNPs) as being associated with coronary heart disease (CHD). We estimated the effect of these SNPs on incident CHD, stroke and total mortality in the prospective cohorts of the MORGAM Project. We studied cohorts from Finland, Sweden, France and Northern Ireland (total N=33,282, including 1,436 incident CHD events and 571 incident stroke events). The lead SNPs at seven loci identified thus far and additional SNPs (in total 42) were genotyped using a case-cohort design.We estimated the effect of the SNPs on disease history at baseline, disease events during follow-up and classic risk factors. Multiple testing was taken into account using false discovery rate (FDR) analysis. SNP rs1333049 on chromosome 9p21.3 was associated with both CHD and stroke (HR5=.20, 95% CI 1.08-1.34 for incident CHD events and 1.15, 0.99-1.34 for incident stroke). SNP rs11670734 (19q12) was associated with total mortality and stroke. SNP rs2146807 (10q11.21) showed some association with the fatality of acute coronary event. SNP rs2943634 (2q36.3) was associated with high density lipoprotein (HDL) cholesterol and SNPs rs599839, rs4970834 (1p13.3) and rs17228212 (15q22.23) were associated with non-HDL cholesterol. SNPs rs2943634 (2q36.3) and rs12525353 (6q25.1) were associated with blood pressure. These findings underline the need for replication studies in prospective settings and confirm the candidacy of several SNPs that may play a role in the etiology of cardiovascular disease.

Association analysis of Notch pathway signalling genes in diabetic nephropathy

Several studies have provided compelling evidence implicating the Notch signalling pathway in diabetic nephropathy. Co-regulation of Notch signalling pathway genes with GREM1 has recently been demonstrated and several genes involved in the Notch pathway are differentially expressed in kidney biopsies from individuals with diabetic nephropathy. We assessed single-nucleotide polymorphisms (SNPs; n = 42) in four of these key genes (JAG1, HES1, NOTCH3 and ADAM10) for association with diabetic nephropathy using a case-control design.
Tag SNPs and potentially functional SNPs were genotyped using Sequenom or Taqman technologies in a total of 1371 individuals with type 1 diabetes (668 patients with nephropathy and 703 controls without nephropathy). Patients and controls were white and recruited from the UK and Ireland. Association analyses were performed using PLINK (http://pngu.mgh.harvard.edu/similar to purcell/plink/) and haplotype frequencies in patients and controls were compared. Adjustment for multiple testing was performed by permutation testing.
In analyses stratified by centre, we identified six SNPs, rs8708 and rs11699674 (JAG1), rs10423702 and rs1548555 (NOTCH3), rs2054096 and rs8027998 (ADAM10) as being associated with diabetic nephropathy before, but not after, adjustment for multiple testing. Haplotype and subgroup analysis according to duration of diabetes also failed to find an association with diabetic nephropathy.
Our results suggest that common variants in JAG1, HES1, NOTCH3 and ADAM10 are not strongly associated with diabetic nephropathy in type 1 diabetes among white individuals. Our findings, however, cannot entirely exclude these genes from involvement in the pathogenesis of diabetic nephropathy.