Genetic variation in cytokine-related genes and migraine susceptibility

Migraine is classified by the World Health Organization (WHO) as being one of the top 20 most debilitating diseases. According to the neurovascular hypothesis, neuroinflammation may promote the activation and sensitisation of meningeal nociceptors, inducing the persistent throbbing headache characterized in migraine. The tumor necrosis factor (TNF) gene cluster, made up of TNFα, lymphotoxin α (LTA), and lymphotoxin β (LTB), has been implicated to influence the intensity and duration of local inflammation. It is thought that sterile inflammation mediated by LTA, LTB, and TNFα contributes to threshold brain excitability, propagation of neuronal hyperexcitability and thus initiation and maintenance of a migraine attack. Previous studies have investigated variants within the TNF gene cluster region in relation to migraine susceptibility, with largely conflicting results. The aim of this study was to expand on previous research and utilize a large case-control cohort and range of variants within the TNF gene cluster to investigate the role of the TNF gene cluster in migraine. Nine single nucleotide polymorphisms (SNPs) were selected for investigation as follows: rs1800683, rs2229094, rs2009658, rs2071590, rs2239704, rs909253, rs1800630, rs1800629, and rs3093664. No significant association with migraine susceptibility was found for any of the SNPs tested, with further testing according to migraine subtype and gender also showing no association for disease risk. Haplotype analysis showed that none of the tested haplotypes were significantly associated with migraine.

Library Research Support in developing, testing and promoting an open cyberinfrastructure

QUT Library continues to rethink research support with eResearch as a primary driver. The support to the development of the Lens, an open global cyberinfrastructure, has been especially important in the light of technology transfer promotion, and partly in the response to researchers’ needs in following the innovation landscapes not only within the scientific but also patent literature. The Lens http://www.lens.org/lens/ project makes innovation more efficient, fair, transparent and inclusive. It is a joint effort between Cambia http://www.cambia.org.au and Queensland University of Technology (QUT). The Lens serves more than 84 million patent documents in the world as open, annotatable digital public goods that are integrated with scholarly and technical literature along with regulatory and business data. Users can link from search results to visualization and document clusters; from a patent document description to its full-text; from there, if applicable, the sequence data can also be found. Figure 1 shows a BLAST Alignment (DNA) using the Lens. A unique feature of the Lens is the ability to embed search and BLAST results into blogs and websites, and provide real-time updates to them. PatSeq Explorer http://www.lens.org/lens/bio/patseqexplorer allows users to navigate patent sequences that map onto the human genome and in the future, many other genomes. PatSeq Explorer offers three level views for the sequence information and links each group of sequences at the chromosomal level to their corresponding patent documents in the Lens. By integrating sequence and patent search and document clustering capabilities, users can now understand the big and small details on the true extent and scope of genetic sequence patents. QUT Library supported Cambia in developing, testing and promoting the Lens. This poster demonstrates QUT Library’s provision of best practice and holistic research support to a research group and how QUT Librarians have acquired new capabilities to meet the needs of the researchers beyond traditional research support practices.

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

Phage library screening for the rapid identification and in vivo testing of candidate genes for a DNA vaccine against Mycoplasma mycoides subsp. mycoides small colony biotype

A new strategy for rapidly selecting and testing genetic vaccines has been developed, in which a whole genome library is cloned into a bacteriophage λ ZAP Express vector which contains both prokaryotic (Plac) and eukaryotic (PCMV) promoters upstream of the insertion site. The phage library is plated on Escherichia coli cells, immunoblotted, and probed with hyperimmune and/or convalescent-phase antiserum to rapidly identify vaccine candidates. These are then plaque purified and grown as liquid lysates, and whole bacteriophage particles are then used directly to immunize the host, following which PCMV-driven expression of the candidate vaccine gene occurs. In the example given here, a semirandom genome library of the bovine pathogen Mycoplasma mycoides subsp. mycoides small colony (SC) biotype was cloned into λ ZAP Express, and two strongly immunodominant clones, λ-A8 and λ-B1, were identified and subsequently tested for vaccine potential against M. mycoides subsp. mycoides SC biotype-induced mycoplasmemia. Sequencing and immunoblotting indicated that clone λ-A8 expressed an isopropyl-β-d-thiogalactopyranoside (IPTG)-inducible M. mycoides subsp. mycoides SC biotype protein with a 28-kDa apparent molecular mass, identified as a previously uncharacterized putative lipoprotein (MSC_0397). Clone λ-B1 contained several full-length genes from the M. mycoides subsp. mycoides SC biotype pyruvate dehydrogenase region, and two IPTG-independent polypeptides, of 29 kDa and 57 kDa, were identified on immunoblots. Following vaccination, significant anti-M. mycoides subsp. mycoides SC biotype responses were observed in mice vaccinated with clones λ-A8 and λ-B1. A significant stimulation index was observed following incubation of splenocytes from mice vaccinated with clone λ-A8 with whole live M. mycoides subsp. mycoides SC biotype cells, indicating cellular proliferation. After challenge, mice vaccinated with clone λ-A8 also exhibited a reduced level of mycoplasmemia compared to controls, suggesting that the MSC_0397 lipoprotein has a protective effect in the mouse model when delivered as a bacteriophage DNA vaccine. Bacteriophage-mediated immunoscreening using an appropriate vector system offers a rapid and simple technique for the identification and immediate testing of putative candidate vaccines from a variety of pathogens.

Environmental, personal, and genetic determinants of response to vitamin D supplementation in older adults

CONTEXT AND OBJECTIVE: Suboptimal vitamin D status can be corrected by vitamin D supplementation, but individual responses to supplementation vary. We aimed to examine genetic and nongenetic determinants of change in serum 25-hydroxyvitamin D (25(OH)D) after supplementation. DESIGN AND PARTICIPANTS: We used data from a pilot randomized controlled trial in which 644 adults aged 60 to 84 years were randomly assigned to monthly doses of placebo, 30 000 IU, or 60 000 IU vitamin D3 for 12 months. Baseline characteristics were obtained from a self-administered questionnaire. Eighty-eight single-nucleotide polymorphisms (SNPs) in 41 candidate genes were genotyped using Sequenom MassArray technology. Serum 25(OH)D levels before and after the intervention were measured using the Diasorin Liaison platform immunoassay. We used linear regression models to examine associations between genetic and nongenetic factors and change in serum 25(OH)D levels. RESULTS: Supplement dose and baseline 25(OH)D level explained 24% of the variability in response to supplementation. Body mass index, self-reported health status, and ambient UV radiation made a small additional contribution. SNPs in CYP2R1, IRF4, MC1R, CYP27B1, VDR, TYRP1, MCM6, and HERC2 were associated with change in 25(OH)D level, although only CYP2R1 was significant after adjustment for multiple testing. Models including SNPs explained a similar proportion of variability in response to supplementation as models that included personal and environmental factors. CONCLUSION: Stepwise regression analyses suggest that genetic variability may be associated with response to supplementation, perhaps suggesting that some people might need higher doses to reach optimal 25(OH)D levels or that there is variability in the physiologically normal level of 25(OH)D.

The v-MFG test: Investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

Achievements in forest tree genetic improvement in Australia and New Zealand 2: Development of Corymbia species and hybrids for plantations in eastern Australia

This paper describes the establishment of provenance seedling seed orchards of three spotted gums and cadaga (all species of Corymbia ex Eucalyptus). It also discusses the limitations of growing the spotted gums as pure species including: lack of mass flowering, susceptibility to a fungal shoot blight and low amenability to vegetative propagation. These limitations, together with observation of putative natural hybrids of the spotted gums with cadaga, and the early promise of manipulated hybrids, led to an intensive breeding and testing program. Many hybrid families have significant advantages in growth and tolerance to disease, insects and frost, and can be vegetatively propagated. They also exhibit broad environmental plasticity, allowing the best varieties to be planted across a wider range of sites than the spotted gums, resulting in more land being suitable for plantation development.

No genetic support for a contribution of prostaglandins to the aetiology of androgenetic alopecia

MADAM, Androgenetic alopecia (AGA) is a common age-dependent trait, characterized by a progressive loss of hair from the scalp. The hair loss may commence during puberty and up to 80% of white men experience some degree of AGA during their lifetime.1 Research has established that two essential aetiological factors for AGA are a genetic predisposition and the presence of androgens (male sex hormones).1,2 A recent meta-analysis of genome-wide association studies (GWAS) has increased the number of identified loci associated with this trait at the molecular level to a total of eight.3 However, despite these successes, a large fraction of the genetic contribution remains to be identified. One way to identify further genetic loci is to combine the resource of GWAS datasets with knowledge about specific biological factors likely to be involved in the development of disease. The focused evaluation of a limited number of candidate genes in GWAS datasets avoids the necessity for extensive correction for multiple testing, which typically limits the power for detecting genetic loci at a genome-wide level.4 Because the presence of genetic association suggests that candidate genes are likely to operate early in the causative chain of events leading to the phenotype, this approach may also function to favour biological pathways for their importance in the development of AGA.

Design and testing of stand-specific bucking instructions for use on modern cut-to-length harvesters

This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit

The use of genetic correlations to evaluate associations between SNP markers and quantitative traits

Open-pollinated progeny of Corymbia citriodora established in replicated field trials were assessed for stem diameter, wood density, and pulp yield prior to genotyping single nucleotide polymorphisms (SNP) and testing the significance of associations between markers and assessment traits. Multiple individuals within each family were genotyped and phenotyped, which facilitated a comparison of standard association testing methods and an alternative method developed to relate markers to additive genetic effects. Narrow-sense heritability estimates indicated there was significant additive genetic variance within this population for assessment traits ( h ˆ 2 =0.28to0.44 ) and genetic correlations between the three traits were negligible to moderate (r G = 0.08 to 0.50). The significance of association tests (p values) were compared for four different analyses based on two different approaches: (1) two software packages were used to fit standard univariate mixed models that include SNP-fixed effects, (2) bivariate and multivariate mixed models including each SNP as an additional selection trait were used. Within either the univariate or multivariate approach, correlations between the tests of significance approached +1; however, correspondence between the two approaches was less strong, although between-approach correlations remained significantly positive. Similar SNP markers would be selected using multivariate analyses and standard marker-trait association methods, where the former facilitates integration into the existing genetic analysis systems of applied breeding programs and may be used with either single markers or indices of markers created with genomic selection processes.

The genetic associations of acute anterior uveitis and their overlap with the genetics of ankylosing spondylitis

Acute anterior uveitis (AAU) involves inflammation of the iris and ciliary body of the eye. It occurs both in isolation and as a complication of ankylosing spondylitis (AS). It is strongly associated with HLA-B*27, but previous studies have suggested that further genetic factors may confer additional risk. We sought to investigate this using the Illumina Exomechip microarray, to compare 1504 cases with AS and AAU, 1805 with AS but no AAU and 21 133 healthy controls. We also used a heterogeneity test to test the differences in effect size between AS with AAU and AS without AAU. In the analysis comparing AS+AAU+ cases versus controls, HLA-B*27 and HLA-A*02:01 were significantly associated with the presence of AAU (P<10−300 and P=6 × 10−8, respectively). Secondary independent association with PSORS1C3 (P=4.7 × 10−5) and TAP2 (P=1.1 × 10−5) were observed in the major histocompatibility complex. There was a new suggestive association with a low-frequency variant at zinc-finger protein 154 in the AS without AAU versus control analysis (zinc-finger protein 154 (ZNF154), P=2.2 × 10−6). Heterogeneity testing showed that rs30187 in ERAP1 has a larger effect on AAU compared with that in AS alone. These findings also suggest that variants in ERAP1 have a differential impact on the risk of AAU when compared with AS, and hence the genetic risk for AAU differs from AS.

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.

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

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.