State estimation for nonlinear state-space transmission models of tuberculosis.

Given the high prevalence of tuberculosis (TB) and the mortality rate associated with the disease, numerous models, such as the Gammaitoni and Nucci (GN) model, were developed to model the risk of transmission. These models typically rely on a quanta generation rate as a measurement of infectivity. Since the quanta generation rate cannot be measured directly, the unique contribution of this work is to develop state estimators to estimate the quanta generation rate from available measurements. To estimate the quanta generation rate, the GN model is adapted into an augmented single-room GN model and a simplified two-room GN model. Both models are shown to be observable, i.e., it is theoretically possible to estimate the quanta generation rate given available measurements. Kalman filters are used to estimate the quanta generation rate. First, a continuous-time extended Kalman filter is used for both adapted models using a simulation and measurement sampling rate of 60 s. Accurate quanta generate rate estimates are achieved in both cases. A more realistic scenario is also considered with a measurement sampling rate of one day. For these estimates, a hybrid extended Kalman filter (HEKF) is used. Accurate quanta generation rate estimates are achieved for the more realistic scenario. Future work could potentially use the HEKFs, the adapted models, and real-time measurements in a control system feedback loop to reduce the transmission of TB in confined spaces such as hospitals.

Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field.

Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.

Modeling the Airborne Infection Risk of Tuberculosis for a Research Facility in eMalahleni, South Africa.

A detailed mathematical modeling framework for the risk of airborne infectious disease transmission in indoor spaces was developed to enable mathematical analysis of experiments conducted at the Airborne Infections Research (AIR) facility, eMalahleni, South Africa. A model was built using this framework to explore possible causes of why an experiment at the AIR facility did not produce expected results. The experiment was conducted at the AIR facility from August 31, 2015 to December 4, 2015, in which the efficacy of upper room germicidal ultraviolet (GUV) irradiation as an environmental control was tested. However, the experiment did not produce the expected outcome of having fewer infections in the test animal room than the control room. The simulation results indicate that dynamic effects, caused by switching the GUV lights, power outages, or introduction of new patients, did not result in the unexpected outcomes. However, a sensitivity analysis highlights that significant uncertainty exists with risk of transmission predictions based on current measurement practices, due to the reliance on large viable literature ranges for parameters.

The sensitivity of 38 heart rate variability measures to the addition of artifact in human and artificial 24-hr cardiac recordings.

BACKGROUND: Artifact is common in cardiac RR interval data derived from 24-hr recordings and has a significant impact on heart rate variability (HRV) measures. However, the relative impact of progressively added artifact on a large group of commonly used HRV measures has not been assessed. This study compared the relative sensitivity of 38 commonly used HRV measures to artifact to determine which measures show the most change with increasing increments of artifact. A secondary aim was to ascertain whether short-term and long-term HRV measures, as groups, share similarities in their sensitivity to artifact. METHODS: Up to 10% of artifact was added to 20 artificial RR (ARR) files and 20 human cardiac recordings, which had been assessed for artifact by a cardiac technician. The added artifact simulated deletion of RR intervals and insertion of individual short RR intervals. Thirty-eight HRV measures were calculated for each file. Regression analysis was used to rank the HRV measures according to their sensitivity to artifact as determined by the magnitude of slope. RESULTS: RMSSD, SDANN, SDNN, RR triangular index and TINN, normalized power and relative power linear measures, and most nonlinear methods examined are most robust to artifact. CONCLUSION: Short-term time domain HRV measures are more sensitive to added artifact than long-term measures. Absolute power frequency domain measures across all frequency bands are more sensitive than normalized and relative frequency domain measures. Most nonlinear HRV measures assessed were relatively robust to added artifact, with Poincare plot SD1 being most sensitive.

Interaction between the FTO gene, body mass index and depression: meta-analysis of 13701 individuals.

BackgroundDepression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the FTO gene, suggesting its implication in the association between depression and obesity.AimsTo confirm these findings by investigating the FTO polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis.MethodThe sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT.ResultsIn the replication cohorts, we observed a significant interaction between FTO, BMI and depression with fixed effects meta-analysis (ß = 0.12, P = 2.7 × 10-4) and with the Han/Eskin random effects method (P = 1.4 × 10-7) but not with traditional random effects (ß = 0.1, P = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (ß = 0.12, P = 0.027) being highly significant based on the Han/Eskin model (P = 6.9 × 10-8). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of FTOConclusionsThis meta-analysis provides additional support for a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P < 0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P < 0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Patterns and determinants of care seeking for obstetric complications in rural northwest Bangladesh: analysis from a prospective cohort study.

BACKGROUND: In communities with low rates of institutional delivery, little data exist on care-seeking behavior for potentially life-threatening obstetric complications. In this analysis, we sought to describe care-seeking patterns for self-reported complications and near misses in rural Bangladesh and to identify factors associated with care seeking for these conditions. METHODS: Utilizing data from a community-randomized controlled trial enrolling 42,214 pregnant women between 2007 and 2011, we used multivariable multinomial logistic regression to explore the association of demographic and socioeconomic factors, perceived need, and service availability with care seeking for obstetric complications or near misses. We also used multivariable multinomial logistic regression to analyze the factors associated with care seeking by type of obstetric complication (eclampsia, sepsis, hemorrhage, and obstructed labor). RESULTS: Out of 9,576 women with data on care seeking for obstetric complications, 77% sought any care, with 29% (n = 2,150) visiting at least one formal provider and 70% (n = 5,149) visiting informal providers only. The proportion of women seeking at least one formal provider was highest among women reporting eclampsia (57%), followed by hemorrhage (28%), obstructed labor (22%), and sepsis (17%) (p < 0.001). In multivariable analyses, socioeconomic factors such as living in a household from the highest wealth quartile (Relative Risk Ratio of 1.49; 95% CI of [1.33-1.73]), women's literacy (RRR of 1.21; 95% CI of [1.05-1.42]), and women's employment (RRR of 1.10; 95% CI of [1.01-1.18]) were significantly associated with care seeking from formal providers. Service factors including living less than 10 kilometers from a health facility (RRR of 1.16; 95% CI of [1.05-1.28]) and facility availability of comprehensive obstetric services (RRR of 1.25; 95% CI of 1.04-1.36) were also significantly associated with seeking care from formal providers. CONCLUSIONS: While the majority of women reporting obstetric complications sought care, less than a third visited health facilities. Improvements in socioeconomic factors such as maternal literacy, coupled with improved geographic access and service availability, may increase care seeking from formal facilities. Enhancing community awareness on symptoms of hemorrhage, sepsis, and obstructed labor and their consequences may promote care seeking for obstetric complications in rural Bangladesh. TRIAL REGISTRATION NUMBER: NCT00860470 .

Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders.

Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD.

A mega-analysis of genome-wide association studies for major depressive disorder.

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

Lipoprotein (A) in clinical practice.

Lipoprotein (a) is a strong and independent risk factor for atherosclerosis severity and a predictor of the risk of ischaemic heart disease and stroke. Many questions are still unanswered in relation to the clinical relevance of the scientific observations on Lp(a) and its application in the realms of cardiovascular prevention. Lp(a), a lipoprotein subtype, is linked to the Apo(a) gene located on chromosome 6q26-27 independently associated with increased risk of coronary artery disease (CAD). For this review, data sources from Cochrane, Pubmed, MEDLINE from 1960 till 2012 were analysed systematically. At least one-off measurement of plasma Lp(a) was found to be indicated in those with premature coronary disease when no real causative factor was identified. Management seemed promising with PCSK9 I, apheresis, CETPI, dietary choices and ACEi. There was clear evidence that Lp(a) is a definite risk marker for atherosclerotic cardiovascular disease (CVD).

Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: a genome-wide association and polygenic scoring study.

Epidemiological studies have recognized a genetic diathesis for suicidal behavior, which is independent of other psychiatric disorders. Genome-wide association studies (GWAS) on suicide attempt (SA) and ideation have failed to identify specific genetic variants. Here, we conduct further GWAS and for the first time, use polygenic score analysis in cohorts of patients with mood disorders, to test for common genetic variants for mood disorders and suicide phenotypes. Genome-wide studies for SA were conducted in the RADIANT and GSK-Munich recurrent depression samples and London Bipolar Affective Disorder Case-Control Study (BACCs) then meta-analysis was performed. A GWAS on suicidal ideation during antidepressant treatment had previously been conducted in the Genome Based Therapeutic Drugs for Depression (GENDEP) study. We derived polygenic scores from each sample and tested their ability to predict SA in the mood disorder cohorts or ideation status in the GENDEP study. Polygenic scores for major depressive disorder, bipolar disorder and schizophrenia from the Psychiatric Genomics Consortium were used to investigate pleiotropy between psychiatric disorders and suicide phenotypes. No significant evidence for association was detected at any SNP in GWAS or meta-analysis. Polygenic scores for major depressive disorder significantly predicted suicidal ideation in the GENDEP pharmacogenetics study and also predicted SA in a combined validation dataset. Polygenic scores for SA showed no predictive ability for suicidal ideation. Polygenic score analysis suggests pleiotropy between psychiatric disorders and suicidal ideation whereas the tendency to act on such thoughts may have a partially independent genetic diathesis.

Infrared near-field spectroscopy of trace explosives using an external cavity quantum cascade laser.

Utilizing a broadly-tunable external cavity quantum cascade laser for scattering-type scanning near-field optical microscopy (s-SNOM), we measure infrared spectra of particles of explosives by probing characteristic nitro-group resonances in the 7.1-7.9 µm wavelength range. Measurements are presented with spectral resolution of 0.25 cm(-1), spatial resolution of 25 nm, sensitivity better than 100 attomoles, and at a rapid acquisition time of 90 s per spectrum. We demonstrate high reproducibility of the acquired s-SNOM spectra with very high signal-to-noise ratios and relative noise of <0.02 in self-homodyne detection.

Pharmacoproteomic investigation into antidepressant response in two mouse inbred strains.

In this study, we present a pharmacoproteomic investigation of response to antidepressants two inbred strains. Our aim was to uncover molecular mechanisms underlying antidepressant action and identify new biomarkers to determine therapeutic response to two antidepressants with proven efficacy in the treatment of depression but divergent mechanisms of action. Mice were treated with the pro-noradrenergic drug nortriptyline, the pro-serotonergic drug escitalopram or saline. Quantitative proteomic analyses were undertaken on hippocampal tissue from a study design that used two inbred mouse strains, two depressogenic protocols and a control condition, (maternal separation, chronic mild stress, control), two antidepressant drugs and two dosing protocols. The proteomic analysis was aimed at the identification of specific drug-response markers. Complementary approaches, 2DE and isobaric tandem mass tagging (TMT), were applied to the selected experimental groups. To investigate the relationship between proteomic profiles, depressogenic protocols and drug response, 2DE and TMT data sets were analysed using multivariate methods. The results highlighted significant strain- and stress-related differences across both 2DE and TMT data sets and identified the three gene products involved in serotonergic (PXBD5, YHWAB, SLC25A4) and one in noradrenergic antidepressant action (PXBD6).

Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.

BACKGROUND: It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way. METHODS AND FINDINGS: The NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10(-8)). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10(-8)) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D. CONCLUSIONS: No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later in the article for the Editors' Summary.

Antidepressant-dependent mRNA changes in mouse associated with hippocampal neurogenesis in a mouse model of depression.

RATIONALE: Monoaminergic imbalances play a role in the pathogenesis of depression and most common antidepressant drugs act on monoamine neurotransmitters. However, the lag time between restoring neurochemical balance and symptom improvement suggests that the response to drugs involves complex biological events downstream of primary targets that have not yet been fully characterized. Here, we report a mouse mRNA expression study to evaluate the effect of escitalopram (a serotonergic antidepressant) and nortriptyline (a noradrenergic antidepressant) on genes that are involved in the pathogenesis of depression and to assess the similarities and differences between two drugs on gene expression levels. METHODS: Genome-wide RNA expression data from the hippocampal tissues of four inbred mouse strains (129S1/SvlmJ, C57LB/6J, DBA/2J and FVB/NJ) were treated with varying doses of either nortriptyline (NRI) or escitalopram (SSRI) and subjected to two different depressogenic protocols. Following robust multichip average normalization, we applied the nonparametric RankProd approach to identify differentially expressed genes in response to drugs across the four strains. Pathway analysis was subsequently carried out on top-ranking genes to gain further biological insights. RESULTS: A total of 371 genes were significantly differentially expressed in response to nortriptyline, whereas 383 were altered by escitalopram. Genes involved in the pathways of integrin signalling (Fnlb, Mapk1, Mapk8), synaptic transmission (Cacnb1, Dnajc5, Kcnma1, Slc1a2) or Huntington disease (Crebbp, Dlg4, Ncor1) were altered by both nortriptyline and escitalopram. Several biological processes and pathways were identified, which could explain the divergence between the molecular mechanisms of nortriptyline and escitalopram. CONCLUSION: From a large-scale animal study, we obtain gene sets comprised of commonly and differentially expressed genes in response to different antidepressant drug treatments. The results may help to characterize the response to antidepressant treatment, shed further light on the neurobiology of depressive disorders and inform future animal and human studies. Finally, the top-ranking pathways from Ingenuity provide further evidence for the hippocampal neurogenesis hypothesis of major depressive disorders.

Mind and heart: heart rate variability in major depressive disorder and coronary heart disease - a review and recommendations.

OBJECTIVE: There is a reciprocal association between major depressive disorder (MDD) and coronary heart disease (CHD). These conditions are linked by a causal network of mechanisms. This causal network should be quantitatively studied and it is hypothesised that the investigation of vagal function represents a promising starting point. Heart rate variability (HRV) has been used to investigate cardiac vagal control in the context of MDD and CHD. This review aims to examine the relationship of HRV to both MDD and CHD in the context of vagal function and to make recommendations for clinical practice and research. METHODS: The search terms 'heart rate variability', 'depression' and 'heart disease' were entered into an electronic multiple database search engine. Abstracts were screened for their relevance and articles were individually selected and collated. RESULTS: Decreased HRV is found in both MDD and CHD. Both diseases are theorized to disrupt autonomic control feedback loops on the heart and are linked to vagal function. Existing theories link vagal function to both mood and emotion as well as cardiac function. However, several factors can potentially confound HRV measures and would thus impact on a complete understanding of vagal mechanisms in the link between MDD and CHD. CONCLUSIONS: The quantitative investigation of vagal function using HRV represents a reasonable starting point in the study of the relationship between MDD and CHD. Many psychotropic and cardiac medications have effects on HRV, which may have clinical importance. Future studies of HRV in MDD and CHD should consider antidepressant medication, as well as anxiety, as potential confounders.

Acute aortic intramural hematoma presenting with painless recurrent syncope.

A patient presented with recurrent syncope due to transient severe hypotension. The patient's history, physical examination, and initial baseline investigation did not suggest a cardiovascular cause. After fluid resuscitation, a raised jugular venous pulse was noted. Bedside transthoracic echocardiogram showed a pericardial effusion and a proximally dilated aorta. Computed tomography of the thorax confirmed these findings and also demonstrated an intramural hematoma of the proximal aortic wall.The patient was transferred to a cardiothoracic center, where he was at first treated medically. He then developed sudden cardiogenic shock due to pericardial tamponade and was successfully operated on.It is important to recognize an acute intramural hematoma of the proximal aortic wall as a cardiothoracic emergency. This condition can present atypically, but nevertheless warrants urgent surgical intervention, equal to type A aortic dissection. Echocardiography can help in making the diagnosis.

A new model of care for familial hypercholesterolaemia: what is the role of cardiology?

Familial hypercholesterolaemia (FH) is a co-dominantly inherited disorder that causes marked elevation in plasma cholesterol and premature coronary heart disease. There are at least 45,000 people with FH in Australia and New Zealand, but most remain undiagnosed and undertreated. To bridge this gap in coronary prevention the FH Australasia Network has developed a model of care for FH. We present the executive summary, with a commentary contrasting the recommendations with other international guidelines and highlighting the role of the cardiologist.

Dissecting the genetic heterogeneity of depression through age at onset.

Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P < 5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P = 0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder.

Depression Case Control (DeCC) Study fails to support involvement of the muscarinic acetylcholine receptor M2 (CHRM2) gene in recurrent major depressive disorder.

It has been suggested that alteration in the muscarinic-cholinergic system is involved in modulation of mood. Three studies have reported linkage on chromosome 7 with major depressive disorder (MDD) in or close to a region containing the muscarinic receptor CHRM2 gene. A haplotype of SNPs located in CHRM2 (rs1824024-rs2061174-rs324650) has been significantly associated with MDD in a previous study. We report the first study investigating this gene in a large, adequately powered, clinical depression case-control sample (n = 1420 cases, 1624 controls). Our data fail to support association with the CHRM2 polymorphisms previously implicated in the genetic aetiology of depression. It is possible our failure to replicate may be a consequence of differences in definition of the MDD phenotype and/or ethnic differences.