Association study of the dystrobrevin-binding gene with schizophrenia in Australian and Indian samples

Numerous studies have reported association between variants in the dystrobrevin binding protein 1 (dysbindin) gene (DTNBP1) and schizophrenia. However, the pattern of results is complex and to date, no specific risk marker or haplotype has been consistently identified. The number of single nucleotide polymorphisms (SNPs) tested in these studies has ranged from 5 to 20. We attempted to replicate previous findings by testing 16 SNPs in samples of 41 Australian pedigrees, 194 Australian cases and 180 controls, and 197 Indian pedigrees. No globally significant evidence for association was observed in any sample, despite power calculations indicating sufficient power to replicate several previous findings. Possible explanations for our results include sample differences in background linkage disequilibrium and/or risk allele effect size, the presence of multiple risk alleles upon different haplotypes, or the presence of a single risk allele upon multiple haplotypes. Some previous associations may also represent false positives. Examination of Caucasian HapMap phase II genotype data spanning the DTNBP1 region indicates upwards of 40 SNPs are required to satisfactorily assess all nonredundant variation within DTNBP1 and its potential regulatory regions for association with schizophrenia. More comprehensive studies in multiple samples will be required to determine whether specific DTNBP1 variants function as risk factors for schizophrenia.

A comparison of DNA pools constructed following whole genome amplification for two-stage SNP genotyping designs

Genotyping in DNA pools reduces the cost and the time required to complete large genotyping projects. The aim of the present study was to evaluate pooling as part of a strategy for fine mapping in regions of significant linkage. Thirty-nine single nucleotide polymorphisms (SNPs) were analyzed in two genomic DNA pools of 384 individuals each and results compared with data after typing all individuals used in the pools. There were no significant differences using data from either 2 or 8 heterozygous individuals to correct frequency estimates for unequal allelic amplification. After correction, the mean difference between estimates from the genomic pool and individual allele frequencies was .033. A major limitation of the use of DNA pools is the time and effort required to carefully adjust the concentration of each individual DNA sample before mixing aliquots. Pools were also constructed by combining DNA after Multiple Displacement Amplification (MDA). The MDA pools gave similar results to pools constructed after careful DNA quantitation (mean difference from individual genotyping .040) and MDA provides a rapid method to generate pools suitable for some applications. Pools provide a rapid and cost-effective screen to eliminate SNPs that are not polymorphic in a test population and can detect minor allele frequencies as low as 1% in the pooled samples. With current levels of accuracy, pooling is best suited to an initial screen in the SNP validation process that can provide high-throughput comparisons between cases and controls to prioritize SNPs for subsequent individual genotyping.

A genomewide screen for autism susceptibility loci

We report the analysis of 335 microsatellite markers genotyped in 110 multiplex families with autism. All families include at least two "affected" siblings, at least one of whom has autism; the remaining affected sibs carry diagnoses of either Asperger syndrome or pervasive developmental disorder. Affected sib-pair analysis yielded multipoint maximum LOD scores (MLS) that reach the accepted threshold for suggestive linkage on chromosomes 5, X, and 19. Nominal evidence for linkage (point-wise P<.05) was obtained on chromosomes 2, 3, 4, 8, 10, 11, 12, 15, 16, 18, and 20, and secondary loci were found on chromosomes 5 and 19. Analysis of families sharing alleles at the putative X chromosomal linked locus and one or more other putative linked loci produced an MLS of 3.56 for the DXS470-D19S174 marker combination. In an effort to increase power to detect linkage, scan statistics were used to evaluate the significance of peak LOD scores based on statistical evidence at adjacent marker loci. This analysis yielded impressive evidence for linkage to autism and autism-spectrum disorders with significant genomewide P values <.05 for markers on chromosomes 5 and 8 and with suggestive linkage evidence for a marker on chromosome 19.

Exclusion of angiotensinogen gene in molecular basis of human hypertension: Sibpair linkage and association analyses in Australian anglo-caucasians

Linkage with essential hypertension has been claimed for a microsatellite marker near the angiotensinogen gene (AGT; chromosome 1q42), as has association for the AGT variants M235T, G(-6)A and A(-20)C. To more rigorously evaluate AGT as a candidate gene for hypertension we performed sibpair analysis with multiple microsatellite markers surrounding this locus and using more sophisticated analysis programs. We also performed an association study of the AGT variants in unrelated subjects with a strong family history (two affected parents). For the linkage study, single and multiplex polymerase chain reaction (PCRs) and automated genescan analysis were conducted on DNA from 175 Australian Anglo-Celtic Caucasian hypertensives for the following markers: D1S2880-(2.1 cM)-D1S213-(2.8 cM)-D1S251-(6.5 cM)-AGT-(2.0 cM) -D1S235. Statistical evaluation of genotype data by nonparametric methods resulted in the following scores: Single-point analysis - SPLINK, P > 0.18; APM method, P > 0.25; ASPEX, MLOD < 0.28; SIB-PAIR, P > 0. 24; Multipoint analysis - MAPMAKER/SIBS, MLOD < 0.24; GENEHUNTER, P > 0.35. Exclusion scores of Lod -4.1 to -5.1 were obtained for these markers using MAPMAKER/SIBS for a lambda(s) of 1.6. The association study of G(-6)A, A(-20)C and M235T variants in 111 hypertensives with strong family history and 190 normotensives with no family history showed significant linkage disequilibrium between particular haplotypes, but we could find no association with hypertension. The present study therefore excludes AGT in the etiology of hypertension, at least in the population of Australian Anglo-Celtic Caucasians studied.

Evidence for an X-linked genetic component in familial typical migraine

Migraine is a common complex disorder that shows strong familial aggregation. There is a general increased prevalence of migraine in females compared with males, with recent studies indicating that migraine affects 18% of females compared with 6% of males. This preponderance of females among migraine sufferers coupled with evidence of an increased risk of migraine in first degree relatives of male probands but not in relatives of female probands suggests the possibility of an X-linked dominant gene. We report here the localization of a typical migraine susceptibility locus to the X chromosome. Of three large multigenerational migraine pedigrees two families showed significant excess allele sharing to Xq markers (P = 0.031 and P = 0.012). Overall analysis of data from all three pedigrees gave significant evidence in support of linkage and heterogeneity (HLOD = 3.1). These findings provide conclusive evidence that familial typical migraine is a heterogeneous disorder. We suggest that the localization of a migraine susceptibility locus to the X chromosome could in part explain the increased risk of migraine in relatives of male probands and may be involved in the increased female prevalence of this disorder.

Association of a low density lipoprotein receptor microsatellite variant with obesity

OBJECTIVE: To determine whether a microsatellite polymorphism located towards the 3' end of the low density lipoprotein receptor gene (LDLR) is associated with obesity. DESIGN: A cross-sectional case-control study. SUBJECTS: One hundred and seven obese individuals, defined as a body mass index (BMI) > or = 26 kg/m2, and 163 lean individuals, defined as a BMI < 26 kg/m2. MEASUREMENTS: BMI, blood pressure, serum lipids, alleles of LDLR microsatellite (106 bp, 108 bp and 112 bp). RESULTS: There was a significant association between variants of the LDLR microsatellite and obesity, in the overall tested population, due to a contributing effect in females (chi 2 = 12.3, P = 0.002), but not in males (chi 2 = 0.3, P = 0.87). In females, individuals with the 106 bp allele were more likely to be lean, while individuals with the 112 bp and/or 108 bp alleles tended to be obese. CONCLUSIONS: These results suggest that in females, LDLR may play a role in the development of obesity.

PolyPatEx : an R package for paternity exclusion in autopolyploids

Microsatellite markers have demonstrated their value for performing paternity exclusion and hence exploring mating patterns in plants and animals. Methodology is well established for diploid species, and several software packages exist for elucidating paternity in diploids; however, these issues are not so readily addressed in polyploids due to the increased complexity of the exclusion problem and a lack of available software. We introduce polypatex, an r package for paternity exclusion analysis using microsatellite data in autopolyploid, monoecious or dioecious/bisexual species with a ploidy of 4n, 6n or 8n. Given marker data for a set of offspring, their mothers and a set of candidate fathers, polypatex uses allele matching to exclude candidates whose marker alleles are incompatible with the alleles in each offspring–mother pair. polypatex can analyse marker data sets in which allele copy numbers are known (genotype data) or unknown (allelic phenotype data) – for data sets in which allele copy numbers are unknown, comparisons are made taking into account all possible genotypes that could arise from the compared allele sets. polypatex is a software tool that provides population geneticists with the ability to investigate the mating patterns of autopolyploids using paternity exclusion analysis on data from codominant markers having multiple alleles per locus.

Disease-associated polymorphisms in ERAP1 do not alter endoplasmic reticulum stress in patients with ankylosing spondylitis

The mechanism by which human leukocyte antigen B27 (HLA-B27) contributes to ankylosing spondylitis (AS) remains unclear. Genetic studies demonstrate that association with and interaction between polymorphisms of endoplasmic reticulum aminopeptidase 1 (ERAP1) and HLA-B27 influence the risk of AS. It has been hypothesised that ERAP1-mediated HLA-B27 misfolding increases endoplasmic reticulum (ER) stress, driving an interleukin (IL) 23-dependent, pro-inflammatory immune response. We tested the hypothesis that AS-risk ERAP1 variants increase ER-stress and concomitant pro-inflammatory cytokine production in HLA-B27 + but not HLA-B27-AS patients or controls. Forty-nine AS cases and 22 healthy controls were grouped according to HLA-B27 status and AS-associated ERAP1 rs30187 genotypes: HLA-B27 + ERAP1 risk, HLA-B27 + ERAP1 protective, HLA-B27-ERAP1 risk and HLA-B27-ERAP1 protective. Expression levels of ER-stress markers GRP78 (8 kDa glucose-regulated protein), CHOP (C/EBP-homologous protein) and inflammatory cytokines were determined in peripheral blood mononuclear cell and ileal biopsies. We found no differences in ER-stress gene expression between HLA-B27 + and HLA-B27-cases or healthy controls, or between cases or controls stratified by carriage of ERAP1 risk or protective alleles in the presence or absence of HLA-B27. No differences were observed between expression of IL17A or TNF (tumour necrosis factor) in HLA-B27 + ERAP1 risk, HLA-B27 + ERAP1 protective and HLA-B27-ERAP1 protective cases. These data demonstrate that aberrant ERAP1 activity and HLA-B27 carriage does not alter ER-stress levels in AS, suggesting that ERAP1 and HLA-B27 may influence disease susceptibility through other mechanisms. © 2015 Macmillan Publishers Limited.

Evaluation of a 7-gene genetic profile for athletic endurance phenotype in Ironman championship triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.

The effects of height and BMI on prostate cancer incidence and mortality: A Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium

Background Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. Methods We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. Results The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). Conclusions We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.