Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies

Background
Automated candidate gene prediction systems allow geneticists to hone in on disease genes more rapidly by identifying the most probable candidate genes linked to the disease phenotypes under investigation. Here we assessed the ability of eight different candidate gene prediction systems to predict disease genes in intervals previously associated with type 2 diabetes by benchmarking their performance against genes implicated by recent genome-wide association studies.

Results
Using a search space of 9556 genes, all but one of the systems pruned the genome in favour of genes associated with moderate to highly significant SNPs. Of the 11 genes associated with highly significant SNPs identified by the genome-wide association studies, eight were flagged as likely candidates by at least one of the prediction systems. A list of candidates produced by a previous consensus approach did not match any of the genes implicated by 706 moderate to highly significant SNPs flagged by the genome-wide association studies. We prioritized genes associated with medium significance SNPs.

Conclusion
The study appraises the relative success of several candidate gene prediction systems against independent genetic data. Even when confronted with challengingly large intervals, the candidate gene prediction systems can successfully select likely disease genes. Furthermore, they can be used to filter statistically less-well-supported genetic data to select more likely candidates. We suggest consensus approaches fail because they penalize novel predictions made from independent underlying databases. To realize their full potential further work needs to be done on prioritization and annotation of genes.

Environmental and genetic determinants of vitamin D insufficiency in 12-month-old infants

We aimed to investigate the relationship between genetic and environmental exposure and vitamin D status at age one, stratified by ethnicity. This study included 563 12-month-old infants in the HealthNuts population-based study. DNA from participants' blood samples was genotyped using Sequenom MassARRAY MALDI-TOF system on 28 single nucleotide polymorphisms (SNPs) in six genes. Using logistic regression, we examined associations between environmental exposure and SNPs in vitamin D pathway and filaggrin genes and vitamin D insufficiency (VDI). VDI, defined as serum 25-hydroxyvitamin D3(25(OH)D3) level ≤50 nmol/L, was measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Infants were stratified by ethnicity determined by parent's country of birth. Infants formula fed at 12 months were associated with reduced odds of VDI compared to infants with no current formula use at 12 months. This association differed by ethnicity (P;bsubesub;= 0.01). The odds ratio (OR) of VDI was 0.29 for Caucasian infants (95% CI, 0.18-0.47) and 0.04 for Asian infants (95% CI, 0.006-0.23). Maternal vitamin D supplementation during pregnancy and/or breastfeeding were associated with increased odds of infants being VDI (OR, 2.39; 95% CI, 1.11-5.18 and OR, 2.5; 95% CI, 1.20-5.24 respectively). Presence of a minor allele for any GC SNP (rs17467825, rs1155563, rs2282679, rs3755967, rs4588, rs7041) was associated with increased odds of VDI. Caucasian infants homozygous (AA) for rs4588 had an OR of 2.49 of being associated with VDI (95% CI, 1.19-5.18). In a country without routine infant vitamin D supplementation or food chain fortification, formula use is strongly associated with a reduced risk of VDI regardless of ethnicity. There was borderline significance for an association between filaggrin mutations and VDI. However, polymorphisms in vitamin D pathway related genes were associated with increased likelihood of being VDI in infancy. © 2014 Elsevier B.V. All rights reserved.

Effects of early-life environment and epigenetics on cardiovascular disease risk in children: highlighting the role of twin studies

Cardiovascular disease (CVD) is the leading cause of death worldwide and originates in early life. The exact mechanisms of this early-life origin are unclear, but a likely mediator at the molecular level is epigenetic dysregulation of gene expression. Epigenetic factors have thus been posited as the likely drivers of early-life programming of adult-onset diseases. This review summarizes recent advances in epidemiology and epigenetic research of CVD risk in children, with a particular focus on twin studies. Classic twin studies enable partitioning of phenotypic variance within a population into additive genetic, shared, and nonshared environmental variances, and are invaluable in research in this area. Longitudinal cohort twin studies, in particular, may provide important insights into the role of epigenetics in the pathogenesis of CVD. We describe candidate gene and epigenome-wide association studies (EWASs) and transgenerational epigenetic inheritance of CVD, and discuss the potential for evidence-based interventions. Identifying epigenetic changes associated with CVD-risk biomarkers in children will provide new opportunities to unravel the underlying biological mechanism of the origins of CVD and enable identification of those at risk for early-life interventions to alter the risk trajectory and potentially reduce CVD incidence later in life.

Candidate disease gene prediction using Gentrepid: application to a genome-wide association study on coronary artery disease

Current single-locus-based analyses and candidate disease gene prediction methodologies used in genome-wide association studies (GWAS) do not capitalize on the wealth of the underlying genetic data, nor functional data available from molecular biology. Here, we analyzed GWAS data from the Wellcome Trust Case Control Consortium (WTCCC) on coronary artery disease (CAD). Gentrepid uses a multiple-locus-based approach, drawing on protein pathway- or domain-based data to make predictions. Known disease genes may be used as additional information (seeded method) or predictions can be based entirely on GWAS single nucleotide polymorphisms (SNPs) (ab initio method). We looked in detail at specific predictions made by Gentrepid for CAD and compared these with known genetic data and the scientific literature. Gentrepid was able to extract known disease genes from the candidate search space and predict plausible novel disease genes from both known and novel WTCCC-implicated loci. The disease gene candidates are consistent with known biological information. The results demonstrate that this computational approach is feasible and a valuable discovery tool for geneticists.

Novel therapeutics for cononary artery disease from genome-wide association study data

Abstract
Background: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.
Methods: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatics modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.
Results: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).
Conclusions: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

Development of molecular techniques for the genetic analysis of abalone populations

Three DNA techniques: random amplified polymorphic DNA (RAPD), minisatellite, and microsatellite analyses, were developed for use in abalone population genetic structure studies. The techniques were assessed using sample sets of blacklip and greenlip abalone. The study identifies a potential for the application of these DNA markers in abalone fisheries management, but microsatellites are the recommended method for future studies.

Identification and genetic determination of an early life risk disposition for depressive disorder : atypical stress-related behaviour in early childhood

Progress in psychiatric genetics has been slow despite evidence of high heritability for most mental disorders. We argue that greater use of early detectable intermediate traits (endophenotypes) with the highest likely aetiological significance to depression, rather than complex clinical phenotypes, would be advantageous. Longitudinal data from the Western Australian Pregnancy Cohort (Raine) Study were used to identify an early life behavioural endophenotype for atypical hypothalamic-pituitaryadrenocortical function in adolescence, a neurobiological indicator of anxiety and depression. A set of descriptors representing rigid and reactive behaviour at age 1 year discriminated those in the top 20% of the free salivary cortisol exposure at age 17 years. Genetic association analysis revealed a male-sensitive effect to variation in three specific single nucleotide polymorphisms within selected genes underpinning the overall stress response. Furthermore, support for a polygenic effect on stress-related behaviour in childhood is presented.

Analysis of genome-wide association study data using the protein knowledge base

Article 98

Antidepressant pharmacogenetics

Purpose of review: This article reviews recent literature published over the period March 2012–August 2013 on antidepressant pharmacogenetics, with a focus on clinical translation and methodological challenges.

Recent findings: Recently, various polymorphisms associated with differential antidepressant efficacy, tolerability, and safety have emerged in association studies, but mixed findings, limited effect sizes, and poor control of confounders have prevented findings translating to practice. Although promising steps have been made, empirically robust clinically translatable pharmacogenetic tests are not yet established. The complex neurobiology of major depressive disorder (MDD) together with the evolving understanding of genetic processes present research challenges for clinical translation.

Summary: Early reports of clinical utility are published. The current evidence base for antidepressant pharmacogenetics is, however, not yet empirically robust enough to inform routine prescribing guidelines. Over the coming years, genetically guided versus unguided trials will help determine if antidepressant pharmacogenetics merits more widespread application.

Homocysteine as a potential biomarker in bipolar disorders: a critical review and suggestions for improved studies

Introduction: Homocysteine levels have been associated with major depression, but associations with bipolar disorder remain less clear. Some data suggest homocysteine levels have potential as a biomarker of treatment response; however the literature is mixed.

Areas covered: Oxidized forms of homocysteine can be potentially neurotoxic leading to glutamate toxicity, apoptotic transformation and neurodegenerative processes. High homocysteine may be a risk biomarker for bipolar disorders, but the empirical base remains too weak for firm conclusions. This review discusses the current literature for homocysteine levels as a biomarker.

Expert opinion: It is premature to foreclose the utility of homocysteine levels as a biomarker for bipolar disorder due the methodological inadequacies in the existing literature. These methodological design issues include lack of control for the confounding variables of concurrent medication, phase of bipolar disorder, gender, age, nutritional status, thyroid, liver and renal function, smoking or lean body mass. Well-powered association studies with confounder control could help shed more light on the important clinical question of homocysteine's utility as a biomarker in bipolar disorder. Future experiments are needed to examine the outcome of interventions modulating homocysteine for treating bipolar disorder. Only prospective randomized control trials will provide definitive evidence of the utility of homocysteine as a biomarker or therapeutic target.

Clincial pharmacogenetics and potential application in personalized medicine

The current `fixed-dosage strategy' approach to medicine, means there is much inter-individual variation in drug response. Pharmacogenetics is the study of how inter-individual variations in the DNA sequence of specific genes affect drug responses. This article will highlight current  pharmacogenetic knowledge on important drug metabolizing enzymes, drug transporters and drug targets to understand interindividual variability in drug clearance and responses in clinical practice and potential use in  personalized medicine. Polymorphisms in the cytochrome P450 (CYP) family may have had the most impact on the fate of pharmaceutical drugs. CYP2D6, CYP2C19 and CYP2C9 gene polymorphisms and gene duplications account for the most frequent variations in phase I metabolism of drugs since nearly 80% of drugs in use today are metabolised by these enzymes. Approximately 5% of Europeans and 1% of Asians lack CYP2D6 activity, and these  individuals are known as poor metabolizers. CYP2C9 is another clinically significant drug metabolising enzyme that demonstrates genetic variants. Studies into CYP2C9 polymorphism have highlighted the importance of the CYP2C9*2 and CYP2C9*3 alleles. Extensive polymorphism also occurs in a majority of Phase II drug metabolizing enzymes. One of the most important polymorphisms is thiopurine S-methyl transferases (TPMT) that catalyzes the S-methylation of thiopurine drugs. With respect to drug transport  polymorphism, the most extensively studied drug transporter is  P-glycoprotein (P-gp/MDR1), but the current data on the clinical impact is limited. Polymorphisms in drug transporters may change drug's distribution, excretion and response. Recent advances in molecular research have revealed many of the genes that encode drug targets demonstrate genetic polymorphism. These variations, in many cases, have altered the targets sensitivity to the specific drug molecule and thus have a profound effect on drug efficacy and toxicity. For example, the β2-adrenoreceptor, which is encoded by the ADRB2 gene, illustrates a clinically significant genetic variation in drug targets. The variable number tandem repeat polymorphisms in serotonin transporter (SERT/SLC6A4) gene are associated with response to antidepressants. The distribution of the common variant alleles of genes that encode drug metabolizing enzymes, drug transporters and drug targets has been found to vary among different populations. The promise of pharmacogenetics lies in its potential to identify the right drug at the right dose for the right individual. Drugs with a narrow therapeutic index are thought to benefit more from pharmacogenetic studies. For example, warfarin serves as a good practical example of how pharmacogenetics can be utilized prior to commencement of therapy in order to achieve maximum efficacy and minimum toxicity. As such, pharmacogenetics has the potential to achieve optimal quality use of medicines, and to improve the efficacy and safety of both prospective and licensed drugs.

Dopamine transporter (DAT1) VNTR polymorphism and alcoholism in two culturally different populations of South India

It is well established that the central dopaminergic reward pathway is likely involved in alcohol intake and the progression of alcohol dependence. Dopamine transporter (DAT1) mediates the active re-uptake of DA from the synapse and is a principal regulator of dopaminergic neurotransmission. The gene for the human DAT1 displays several polymorphisms, including a 40-bp variable number of tandem repeats (VNTR) ranging from 3 to 16 copies in the 3′-untranslated region (UTR) of the gene. To assess the role of this gene in alcoholism, we genotyped the VNTR of DAT1 gene in a sample of 206 subjects from the Kota population (111 alcohol dependence cases and 95 controls) and 142 subjects from Badaga population (81 alcohol dependence cases and 61 controls). Both populations inhabit a similar environmental zone, but have different ethnic histories. Phenotype was defined based on the DSM-IV criteria. Genotyping was performed using PCR and electrophoresis. The association of DAT1 with alcoholism was tested by using the Clump v1.9 program which uses the Monte Carlo method. In both Kota and Badaga populations, the allele A10 was the most frequent allele followed by allele A9. The genotypic distribution is in Hardy–Weinberg equilibrium in both cases and control groups of Kota and Badaga populations. The DAT1 VNTR was significantly associated with alcoholism in Badaga population but not in Kota population. Our results suggest that the A9 allele of the DAT gene is involved in vulnerability to alcoholism, but that these associations are population specific.