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A multichannel microfluidic platform for real-time monitoring of epithelial barrier integrity by electrical impedance has been developed. Growth and polarization of human epithelial cells from the airway or gastrointestinal tract was continuously monitored over 5 days in 8 parallel, individually perfused microfluidic chips. Electrical impedance data were continuously recorded to monitor cell barrier formation using a low-cost bespoke impedance analyser. Data was analysed using an electric circuit model to extract the equivalent transepithelial electrical resistance and epithelial cell layer capacitance. The cell barrier integrity steadily increased overtime, achieving an average resistance of 418 ± 121 Ω cm 2 (airway cells) or 207 ± 59 Ω cm 2 (gastrointestinal cells) by day 5. The utility of the polarized airway epithelial barrier was demonstrated using a 24 hour challenge with double stranded RNA to mimic viral infection. This caused a rapid decrease in barrier integrity in association with disruption of tight junctions, whereas simultaneous treatment with a corticosteroid reduced this effect. The platform is able to measure barrier integrity in real-time and is scalable, thus has the potential to be used for drug development and testing.

Parkinson's disease (PD) is a major and progressive neurodegenerative disorder, yet the biological mechanisms involved in its aetiology are poorly understood. Evidence links this disorder with mitochondrial dysfunction and/or impaired lysosomal degradation - key features of the autophagy of mitochondria, known as mitophagy. Here, we investigated the role of LRRK2, a protein kinase frequently mutated in PD, in this process in vivo. Using mitophagy and autophagy reporter mice, bearing either knockout of LRRK2 or expressing the pathogenic kinase-activating G2019S LRRK2 mutation, we found that basal mitophagy was specifically altered in clinically relevant cells and tissues. Our data show that basal mitophagy inversely correlates with LRRK2 kinase activity in vivo. In support of this, use of distinct LRRK2 kinase inhibitors in cells increased basal mitophagy, and a CNS penetrant LRRK2 kinase inhibitor, GSK3357679A, rescued the mitophagy defects observed in LRRK2 G2019S mice. This study provides the first in vivo evidence that pathogenic LRRK2 directly impairs basal mitophagy, a process with strong links to idiopathic Parkinson's disease, and demonstrates that pharmacological inhibition of LRRK2 is a rational mitophagy-rescue approach and potential PD therapy., Competing Interests: FS, AP, PR, GB, AR, IG No competing interests declared, (© 2021, Singh et al.)

Background: With increasing concerns about the impact of frequent antibiotic usage on the human microbiome, it is important to characterize the potential for such effects in early antibiotic drug development clinical trials. In a randomised Phase 2a clinical trial study that evaluated the pharmacokinetics of repeated oral doses of gepotidacin, a first-in-chemical-class triazaacenaphthylene antibiotic with a distinct mechanism of action, in adult females with uncomplicated urinary tract infections for gepotidacin (GSK2140944) we evaluated the potential changes in microbiome composition across multiple time points and body-sites ( ClinicalTrials.gov : NCT03568942)., Results: Samples of gastrointestinal tract (GIT), pharyngeal cavity and vaginal microbiota were collected with consent from 22 patients at three time points relative to the gepotidacin dosing regimen; Day 1 (pre-dose), Day 5 (end of dosing) and Follow-up (Day 28 ± 3 days). Microbiota composition was determined by DNA sequencing of 16S rRNA gene variable region 4 amplicons. By Day 5, significant changes were observed in the microbiome diversity relative to pre-dose across the tested body-sites. However, by the Follow-up visit, microbiome diversity changes were reverted to compositions comparable to Day 1. The greatest range of microbiome changes by body-site were GIT followed by the pharyngeal cavity then vagina. In Follow-up visit samples we found no statistically significant occurrences of pathogenic taxa., Conclusion: Our findings suggest that gepotidacin alteration of the human microbiome after 5 days of dosing is temporary and rebound to pre-dosing states is evident within the first month post-treatment. We recommend that future antibiotic drug trials include similar exploratory investigations into the duration and context of microbiome modification and recovery., Trial Registration: NCT03568942 . Registered 26 June 2018.

Introduction: Investigating variation in genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs are key to characterizing pharmacogenomic (PGx) relationships. ADME gene variation is relatively well characterized in European and Asian populations, but data from African populations are under-studied-which has implications for drug safety and effective use in Africa. Results: We identified significant ADME gene variation in African populations using data from 458 high-coverage whole genome sequences, 412 of which are novel, and from previously available African sequences from the 1,000 Genomes Project. ADME variation was not uniform across African populations, particularly within high impact coding variation. Copy number variation was detected in 116 ADME genes, with equal ratios of duplications/deletions. We identified 930 potential high impact coding variants, of which most are discrete to a single African population cluster. Large frequency differences (i.e., >10%) were seen in common high impact variants between clusters. Several novel variants are predicted to have a significant impact on protein structure, but additional functional work is needed to confirm the outcome of these for PGx use. Most variants of known clinical outcome are rare in Africa compared to European populations, potentially reflecting a clinical PGx research bias to European populations. Discussion: The genetic diversity of ADME genes across sub-Saharan African populations is large. The Southern African population cluster is most distinct from that of far West Africa. PGx strategies based on European variants will be of limited use in African populations. Although established variants are important, PGx must take into account the full range of African variation. This work urges further characterization of variants in African populations including in vitro and in silico studies, and to consider the unique African ADME landscape when developing precision medicine guidelines and tools for African populations., Competing Interests: GlaxoSmithKline provided funding for this project. The authors SB, MC, CC, ASG, PT and FJG are all employees of GlaxoSmithKline and participated in the analysis and writing of the paper. GlaxoSmithKline had no additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The content is solely responsibility of the authors and does not necessarily represent the official views of GlaxoSmithKline. The remaining authors declare no conflicts of interest., (Copyright © 2021 da Rocha, Othman, Botha, Cottino, Twesigomwe, Ahmed, Drögemöller, Fadlelmola, Machanick, Mbiyavanga, Panji, Wright, Adebamowo, Matshaba, Ramsay, Simo, Simuunza, Tiemessen, Baldwin, Chiano, Cox, Gross, Thomas, Gamo and Hazelhurst.)

The pharmaceutical industry is continuing to face high research and development (R&D) costs and low overall success rates of clinical compounds during drug development. There is an increasing demand for development and validation of healthy or disease-relevant and physiological human cellular models that can be implemented in early-stage discovery, thereby shifting attrition of future therapeutics to a point in discovery at which the costs are significantly lower. There needs to be a paradigm shift in the early drug discovery phase (which is lengthy and costly), away from simplistic cellular models that show an inability to effectively and efficiently reproduce healthy or human disease-relevant states to steer target and compound selection for safety, pharmacology, and efficacy questions. This perspective article covers the various stages of early drug discovery from target identification (ID) and validation to the hit/lead discovery phase, lead optimization, and preclinical safety. We outline key aspects that should be considered when developing, qualifying, and implementing complex in vitro models (CIVMs) during these phases, because criteria such as cell types (e.g., cell lines, primary cells, stem cells, and tissue), platform (e.g., spheroids, scaffolds or hydrogels, organoids, microphysiological systems, and bioprinting), throughput, automation, and single and multiplexing endpoints will vary. The article emphasizes the need to adequately qualify these CIVMs such that they are suitable for various applications (e.g., context of use) of drug discovery and translational research. The article ends looking to the future, in which there is an increase in combining computational modeling, artificial intelligence and machine learning (AI/ML), and CIVMs.

The interaction between airway microbiome and host in chronic obstructive pulmonary disease (COPD) is poorly understood. Here we used a multi-omic meta-analysis approach to characterize the functional signature of airway microbiome in COPD. We retrieved all public COPD sputum microbiome datasets, totaling 1640 samples from 16S rRNA gene datasets and 26 samples from metagenomic datasets from across the world. We identified microbial taxonomic shifts using random effect meta-analysis and established a global classifier for COPD using 12 microbial genera. We inferred the metabolic potentials for the airway microbiome, established their molecular links to host targets, and explored their effects in a separate meta-analysis on 1340 public human airway transcriptome samples for COPD. 29.6% of differentially expressed human pathways were predicted to be targeted by microbiome metabolism. For inferred metabolite-host interactions, the flux of disease-modifying metabolites as predicted from host transcriptome was generally concordant with their predicted metabolic turnover in microbiome, suggesting a synergistic response between microbiome and host in COPD. The meta-analysis results were further validated by a pilot multi-omic study on 18 COPD patients and 10 controls, in which airway metagenome, metabolome, and host transcriptome were simultaneously characterized. 69.9% of the proposed "microbiome-metabolite-host" interaction links were validated in the independent multi-omic data. Butyrate, homocysteine, and palmitate were the microbial metabolites showing strongest interactions with COPD-associated host genes. Our meta-analysis uncovered functional properties of airway microbiome that interacted with COPD host gene signatures, and demonstrated the possibility of leveraging public multi-omic data to interrogate disease biology.

Background: Airway bacterial dysbiosis is a feature of chronic obstructive pulmonary disease (COPD). However, there is limited comparative data of the lung microbiome between healthy smokers, non-smokers and COPD., Methods: We compared the 16S rRNA gene-based sputum microbiome generated from pair-ended Illumina sequencing of 124 healthy subjects (28 smokers and 96 non-smokers with normal lung function), with single stable samples from 218 COPD subjects collected from three UK clinical centres as part of the COPDMAP consortium., Results: In healthy subjects Firmicutes, Bacteroidetes and Actinobacteria were the major phyla constituting 88% of the total reads, and Streptococcus, Veillonella, Prevotella, Actinomyces and Rothia were the dominant genera. Haemophilus formed only 3% of the healthy microbiome. In contrast, Proteobacteria was the most dominant phylum accounting for 50% of the microbiome in COPD subjects, with Haemophilus and Moraxella at genus level contributing 25 and 3% respectively. There were no differences in the microbiome profile within healthy and COPD subgroups when stratified based on smoking history. Principal coordinate analysis on operational taxonomic units showed two distinct clusters, representative of healthy and COPD subjects (PERMANOVA, p = 0·001)., Conclusion: The healthy and COPD sputum microbiomes are distinct and independent of smoking history. Our results underline the important role for Gammaproteobacteria in COPD.

A recent study by Dvořák et al. supports metabolite mimicry as a drug development strategy. A potent agonist of the human pregnane X receptor (hPXR) was designed from two ligands that are products of the microbial catabolism of tryptophan. Its validity was demonstrated in cellular assays and a murine colitis model expressing hPXR by a significant reduction in inflammation biomarkers., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Here we review recent studies that illustrate three areas where the microbiome directly impacts drug development: (1) microbial effects on drug safety and efficacy, (2) the effects of drugs on causing collateral restructuring of microbiome communities, and (3) the potential side-effects of novel therapies targeting the microbiome. On the basis of the findings of these and other studies, we advocate the systematic incorporation of microbiome analyses in early to late stage clinical trials as a strategy to increase the overall success rate of the drug discovery and development process.

Growing evidence suggests that peripheral factors to the brain driving neuro-inflammation could affect Alzheimer's Disease (AD) and Parkinson's Disease (PD) severity. Herpes simplex virus type 1 (HSV1) infection has been associated with AD while other related viruses, including cytomegalovirus (CMV), Epstein-Bar virus and human herpesvirus 6 (HHV6), are known to infect neurons. Here we compare gene expression profiles between AD or PD patients to those afflicted with herpes viral infections as to discover novel potential neuro-inflammation pathways. We found multiple significant differentially expressed genes (DEGs) shared between AD/PD and viral infections including SESN3 which has a genetic association for increased AD risk. Pathway enrichment analysis revealed viruses shared Oxidative Stress Defense System and LRRK2 pathways with AD and PD, respectively. We further processed our data to identify novel target and drug-repurposing opportunities including anti-inflammatory therapy, immune-modulators and cholinesterase inhibitors which could lead to new therapeutics paradigms for these neurodegenerative diseases.

Background: Little is known about the interactions between the lung microbiome and host response in chronic obstructive pulmonary disease (COPD)., Methods: We performed a longitudinal 16S ribosomal RNA gene-based microbiome survey on 101 sputum samples from 16 healthy subjects and 43 COPD patients, along with characterization of host sputum transcriptome and proteome in COPD patients., Results: Dysbiosis of sputum microbiome was observed with significantly increased relative abundance of Moraxella in COPD versus healthy subjects and during COPD exacerbations, and Haemophilus in COPD ex-smokers versus current smokers. Multivariate modeling on sputum microbiome, host transcriptome and proteome profiles revealed that significant associations between Moraxella and Haemophilus, host interferon and pro-inflammatory signaling pathways and neutrophilic inflammation predominated among airway host-microbiome interactions in COPD. While neutrophilia was positively correlated with Haemophilus, interferon signaling was more strongly linked to Moraxella. Moreover, while Haemophilus was significantly associated with host factors both in stable state and during exacerbations, Moraxella-associated host responses were primarily related to exacerbations., Conclusions: Our study highlights a significant airway host-microbiome interplay associated with COPD inflammation and exacerbations. These findings indicate that Haemophilus and Moraxella influence different components of host immune response in COPD, and that novel therapeutic strategies should consider targeting these bacteria and their associated host pathways in COPD.

The potential use of clinically approved beta-lactams for Buruli ulcer (BU) treatment was investigated with representative classes analyzed in vitro for activity against Mycobacterium ulcerans. Beta-lactams tested were effective alone and displayed a strong synergistic profile in combination with antibiotics currently used to treat BU, i.e. rifampicin and clarithromycin; this activity was further potentiated in the presence of the beta-lactamase inhibitor clavulanate. In addition, quadruple combinations of rifampicin, clarithromycin, clavulanate and beta-lactams resulted in multiplicative reductions in their minimal inhibitory concentration (MIC) values. The MIC of amoxicillin against a panel of clinical isolates decreased more than 200-fold within this quadruple combination. Amoxicillin/clavulanate formulations are readily available with clinical pedigree, low toxicity, and orally and pediatric available; thus, supporting its potential inclusion as a new anti-BU drug in current combination therapies., Competing Interests: RGdR and AML are employees of GlaxoSmithKline, a producer of the generic drug amoxicillin/clavulanate. All other authors declare no conflicts of interest.

Objective: Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD., Participants and Methods: We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models., Results: The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer's combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications., Conclusion: Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression.

Background: Mendelian randomization studies have so far restricted attention to linear associations relating the genetic instrument to the exposure, and the exposure to the outcome. In some cases, however, observational data suggest a non-linear association between exposure and outcome. For example, alcohol consumption is consistently reported as having a U-shaped association with cardiovascular events. In principle, Mendelian randomization could address concerns that the apparent protective effect of light-to-moderate drinking might reflect 'sick-quitters' and confounding., Methods: The Alcohol-ADH1B Consortium was established to study the causal effects of alcohol consumption on cardiovascular events and biomarkers, using the single nucleotide polymorphism rs1229984 in ADH1B as a genetic instrument. To assess non-linear causal effects in this study, we propose a novel method based on estimating local average treatment effects for discrete levels of the exposure range, then testing for a linear trend in those effects. Our method requires an assumption that the instrument has the same effect on exposure in all individuals. We conduct simulations examining the robustness of the method to violations of this assumption, and apply the method to the Alcohol-ADH1B Consortium data., Results: Our method gave a conservative test for non-linearity under realistic violations of the key assumption. We found evidence for a non-linear causal effect of alcohol intake on several cardiovascular traits., Conclusions: We believe our method is useful for inferring departure from linearity when only a binary instrument is available. We estimated non-linear causal effects of alcohol intake which could not have been estimated through standard instrumental variable approaches., (© The Author 2014; Published by Oxford University Press on behalf of the International Epidemiological Association.)

Objective: To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease., Design: Mendelian randomisation meta-analysis of 56 epidemiological studies., Participants: 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers., Main Outcome Measures: Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption., Results: Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95))., Conclusions: Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health., (© Holmes et al 2014.)

Objectives: Genomewide association studies (GWAS) have identified clear evidence of genetic markers for nicotine dependence. Other smoking phenotypes have been tested, but the results are less consistent. The tendency to relapse versus the ability to maintain long-term abstinence has received little attention in genetic studies; thus, our aim was to provide a better biological understanding of this phenotype through the identification of genetic loci associated with smoking relapse., Methods: We carried out a GWAS on data from two European population-based collections, including a total of 835 cases (relapsers) and 990 controls (abstainers). Top-ranked findings from the discovery phase were tested for replication in two additional independent European population-based cohorts., Results: Of the seven top markers from the discovery phase, none were consistently associated with smoking relapse across all samples and none reached genomewide significance. A single-nucleotide polymorphism rs1008509, within the Xylosyltransferase II (XYLT2) gene, was suggestively associated with smoking relapse in the discovery phase (β=-0.504; P=5.6E-06) and in the first replication sample (ALSPAC) (β=-0.27; P=0.004; n=1932), but not in the second sample (KORA) (β=0.19; P=0.138; n=912). We failed to identify an association between loci implicated previously in other smoking phenotypes and smoking relapse., Conclusion: Although no genomewide significant findings emerged from this study, we found that loci implicated in other smoking phenotypes were not associated with smoking relapse, which suggests that the neurobiology of smoking relapse and long-term abstinence may be distinct from biological mechanisms implicated in the development of nicotine dependence.

Introduction: Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a circulating enzyme with pro-inflammatory and oxidative activities associated with cardiovascular disease and ischemic stroke. While high plasma Lp-PLA2 activity was reported as a risk factor for dementia in the Rotterdam study, no association between Lp-PLA2 mass and dementia or Alzheimer's disease (AD) was detected in the Framingham study. The objectives of the current study were to explore the relationship of plasma Lp-PLA2 activity with cognitive diagnoses (AD, amnestic mild cognitive impairment (aMCI), and cognitively healthy subjects), cardiovascular markers, cerebrospinal fluid (CSF) markers of AD, and apolipoprotein E (APOE) genotype., Methods: Subjects with mild AD (n = 78) and aMCI (n = 59) were recruited from the Memory Clinic, University Hospital, Basel, Switzerland; cognitively healthy subjects (n = 66) were recruited from the community. Subjects underwent standardised medical, neurological, neuropsychological, imaging, genetic, blood and CSF evaluation. Differences in Lp-PLA2 activity between the cognitive diagnosis groups were tested with ANOVA and in multiple linear regression models with adjustment for covariates. Associations between Lp-PLA2 and markers of cardiovascular disease and AD were explored with Spearman's correlation coefficients., Results: There was no significant difference in plasma Lp-PLA2 activity between AD (197.1 (standard deviation, SD 38.4) nmol/min/ml) and controls (195.4 (SD 41.9)). Gender, statin use and low-density lipoprotein cholesterol (LDL) were independently associated with Lp-PLA2 activity in multiple regression models. Lp-PLA2 activity was correlated with LDL and inversely correlated with high-density lipoprotein (HDL). AD subjects with APOE-ε4 had higher Lp-PLA2 activity (207.9 (SD 41.2)) than AD subjects lacking APOE-ε4 (181.6 (SD 26.0), P = 0.003) although this was attenuated by adjustment for LDL (P = 0.09). No strong correlations were detected for Lp-PLA2 activity and CSF markers of AD., Conclusion: Plasma Lp-PLA2 was not associated with a diagnosis of AD or aMCI in this cross-sectional study. The main clinical correlates of Lp-PLA2 activity in AD, aMCI and cognitively healthy subjects were variables associated with lipid metabolism.

The aim of this study was to identify whether age at onset (AAO) identifies Bipolar Disorder (BD) subtypes, and to test whether the subgroups were confirmed by different clinical profiles. Admixture analysis was applied to determine a model that best fit the observed distribution of AAO in 964 BD patients. Three distributions of AAO were identified, and age means were 16.1 (S.D. 4.2), 25.4 (S.D. 2.5) and 32.2 (S.D. 9.5) years. A significant increased rate of suicide attempts, Bipolar I (BD I) caseness, and depressive onset was observed in the early-onset group when compared to those with later-onset by means of χ². Findings from extant studies and our results are remarkably consistent in showing that BD can be subdivided into three groups based on AAO distributions, and that early-onset is associated with higher rates of suicide attempts., (Copyright © 2009 Elsevier Ltd. All rights reserved.)

Objective: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides., Methods and Results: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9))., Conclusions: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.

Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.

Chronic obstructive pulmonary disease (COPD) is characterized by airway epithelial damage, bronchoconstriction, parenchymal destruction and mucus hypersecretion. Upon activation by a broad range of stimuli, transient receptor potential vanilloid 4 (TRPV4) functions to control airway epithelial cell volume and epithelial and endothelial permeability; it also triggers bronchial smooth muscle contraction and participates in autoregulation of mucociliary transport. These functions of TRPV4 may be important for the regulation of COPD pathogenesis, so TRPV4 is a candidate gene for COPD. We genotyped 20 single nucleotide polymorphisms (SNPs) in TRPV4, and tested qualitative COPD and quantitative FEV(1) and FEV(1)/(F)VC phenotypes in two independent large populations. The family population had 606 pedigrees including 1891 individuals, and the case-control sample included 953 COPD cases and 956 controls. Family-based association tests were performed in the family data. Logistic regression and linear models were used in the case-control data to replicate the association results. In the family data, seven out of 20 SNPs tested were associated with COPD (2.5 x 10(-4) < or = P < or = 0.04) and six SNPs were associated with FEV(1)/VC (0.02 < or = P < or = 0.03) from family-based association tests (PBAT) analysis. Four out of the seven SNPs associated with COPD demonstrated replicated associations with the same effect directions in the case-control population (0.02 < or = P < or = 0.03). Significant haplotype associations supported the results of single SNP analyses. Thus, polymorphisms in the TRPV4 gene are associated with COPD.

Background: Genetic epidemiology data suggest that younger age of onset is associated with family history (FH) of depression. The present study tested whether the presence of FH for depression or anxiety in first-degree relatives determines younger age of onset for depression., Method: A sample of 1022 cases with recurrent major depressive disorder (MDD) was recruited at the Max Planck Institute and at two affiliated hospitals. Patients were assessed using the Schedules for Clinical Assessment in Neuropsychiatry and questionnaires including demographics, medical history, questions on the use of alcohol and tobacco, personality traits and life events. Survival analysis and the Cox proportional hazard model were used to determine whether FH of depression signals earlier age of onset of depression., Results: Patients who reported positive FH had a significantly earlier age of onset than patients who did not report FH of depression (log-rank=48, df=1, p<0.0001). The magnitude of association of FH varies by age of onset, with the largest estimate for MDD onset before age 20 years (hazard ratio=2.2, p=0.0009), whereas FH is not associated with MDD for onset after age 50 years (hazard ratio=0.89, p=0.5). The presence of feelings of guilt, anxiety symptoms and functional impairment due to depressive symptoms appear to characterize individuals with positive FH of depression., Conclusions: FH of depression contributes to the onset of depression at a younger age and may affect the clinical features of the illness.

One of the mantras of scientists working in the field of pharmacogenetics is 'the right dose for the right patient'. A recent article has gone someway towards demonstrating that this goal can be achieved using genetic approaches. It is one of the first reports to show that a specific polymorphism can predict the maximum tolerated dose of two anti-epileptic drugs. However, further studies are necessary to validate these observations.

We have compared microarray data generated on Affymetrix chips from standard (8 micrograms) or low (100 nanograms) amounts of total RNA. We evaluated the gene signals and gene fold-change estimates obtained from the two methods and validated a subset of the results by real time, polymerase chain reaction assays. The correlation of low RNA derived gene signals to gene signals obtained from standard RNA was poor for less to moderately abundant genes. Genes with high abundance showed better correlation in signals between the two methods. The signal correlation between the low RNA and standard RNA methods was improved by including a reference sample in the microarray analysis. In contrast, the fold-change estimates for genes were better correlated between the two methods regardless of the magnitude of gene signals. A reference sample based method is suggested for studies that would end up comparing gene signal data from a combination of low and standard RNA templates; no such referencing appears to be necessary when comparing fold-changes of gene expression between standard and low template reactions.

Identification of reliable markers to predict drug-related adverse events (DRAEs) is an important goal of the pharmaceutical industry and others within the healthcare community. We have used genetic polymorphisms, including the most frequent source of variation (single nucleotide polymorphisms, SNPs) in the human genome, in pharmacogenetic approaches designed to predict DRAEs. Three studies exemplify the principles of using polymorphisms to identify associations in progressively larger genomic regions: polymorphic repeats within the UDP-glucuronysltransferase I (UGT1A1) gene in patients experiencing hyperbilirubinemia after administration of tranilast, an experimental drug to prevent re-stenosis following coronary revascularization; high linkage disequilibrium within the Apolipoprotein E (ApoE) gene in patients with Alzheimer Disease (AD); and the polymorphic variant HLA-B57 in patients with hypersensitivity reaction after administration of abacavir, a nucleoside reverse transcriptase inhibitor for the treatment of HIV. Together, these studies demonstrate in a stepwise manner the feasibility of using pharmacogenetic approaches to predict DRAEs.