The PVBC index has not been tested clinically.We previously showed in animals that the ratio of inspired tidal volume  and inspiratory esophageal pressure (Pes) and Vtinsp. We applied 11 different NAVA levels, increasing them every 3 minutes in steps of 0.3 cm H2O/μV from 0 to 3.0 cmH2O/μV. At each NAVA level, one breath was non-assisted (NAVA level 0). PVBC indices were calculated by relating Vtinsp/EAdipk of the non-assisted breath to Vtinsp/EAdipk of the assisted breath(s) using one (N1PVBC) or the mean value of five preceding assisted breaths (X5PVBC). During assisted breaths, inspiratory changes in Pes (∆Pes) and transpulmonary (ΔPtp) pressures were used to calculate the relative contribution of patient to total inspiratory lung-distending pressures (ΔPes/ΔPtp). Matching of respiratory drive indices and squaring of the PVBC was evaluated for their effect on the correlation between PVBC and ΔPes/ΔPtp. Linear regression analysis and Bland-Altman analysis were applied to compare indices.We studied 12 intubated and mechanically ventilated patients with acute respiratory failure and measured EAdiX5PVBC2) improved determination coefficients (P <0.05), adjusted the regression slope and intercept between PVBC and ΔPes/ΔPtp toward identity (P <0.05) and reduced bias (P <0.05). Matching EAdipk between non-assisted and assisted breaths within the range of 0.77 to 1.30 improved the relationship between X5PVBC2 and ΔPes/ΔPtp (P <0.05) and abolished the need for EAdi normalization in the PVBC calculation ).Using an average of five assisted breaths prior to the non-assisted breath and squaring the PVBC  between non-assisted and assisted breaths are limited. PVBC could help to quantify and standardize the adjustment of the level of assist, and hence reduce the risks of excessive ventilatory assist in patients.This clinical study confirms previous experimental results showing that the PVBCNCT01663480. Registered 9 August 2012.ClinicalTrials.gov  The aim of today’s approach to mechanical ventilation is generally to achieve more spontaneous breathing and greater use of so-called partial ventilatory assist, whereby the ventilator and the patient share the inspiratory work. In order for partial ventilatory assist to be efficient in patients who are spontaneously breathing, it must be synchronized in terms of both its timing and its magnitude. However, conventional modes of partial ventilatory assist are often associated with patient–ventilator asynchrony or dyssynchrony -3. Neurainsp) and peak inspiratory electrical activity of the diaphragm (EAdipk) was used for both an assisted breath and a subsequent breath with no assistance [One of the biggest unknowns with the use of partial ventilatory assist is the relative contribution of patient effort and ventilator assistance during a breath. An index for quantifying the respective patient and ventilator breath contributions (PVBCs) using an experimental model of acute respiratory failure (ARF) in animals ventilated with NAVA was recently published . In the sistance .To validate the PVBC index in our previous study , we measinsp and EAdipk between a non-assisted breath and the preceding ventilator-assisted breath(s) would allow the calculation of the PVBC index in humans. We carried out the study with the following assumptions. (1) EAdipk during an inspiration reflects neural demand to generate Vtinsp. (2) If adding synchronized assistance to the patient’s neural inspiratory demand, the resulting Vtinsp depends on the sum of patient and ventilator pressure contribution. (3) If the neural inspiratory demands are different for two consecutive breaths, normalizing the Vtinsp to EAdipk , a PVBC index can be constructed using the ratio of Vtinsp/EAdipk without ventilatory assistance to Vtinsp/EAdipk with assistance no-assist/(Vtinsp/ΔEAdipk)assist); a PVBC index close to 1 suggests that Vtinsp is generated by the patient, whereas a PVBC index close to 0 indicates that Vtinsp is generated by the ventilator. (5) If the patient’s neural inspiratory demand is similar during both non-assisted and assisted breaths, the ratio of Vtinsp alone during the non-assisted and assisted breaths should reflect the relative contribution of the patient vis-à-vis patient + ventilator.On the basis of the findings of our previous experimental study, we designed the present study to evaluate the PVBC index in humans with ARF. Similar to our previous work in animals , the undIf reliable, PVBC could help to quantify and standardize the adjustment of the level of ventilatory assistance and reduce the risks of excessive ventilatory assistance in patients.This trial was conducted in a 30-bed general intensive care unit (ICU) of a teaching hospital affiliated with Southeast University in China. The protocol was approved by the Institutional Ethics Committee of Zhongda Hospital , and informed consent was obtained from the patients or their next of kin. The trial is registered at ClinicalTrials.gov (NCT01663480).Patients were eligible for inclusion if they were (1) intubated or tracheotomized, (2) undergoing assisted mechanical ventilation, (3) considered (by the attending physician) to be able to tolerate a short period of spontaneous breathing  and (4) awake.The exclusion criteria were (1) age <18 years; (2) history of esophageal varices; (3) gastroesophageal surgery in the previous 12 months or gastroesophageal bleeding in the previous 30 days; (4) coagulation disorders ; (5) history of acute central or peripheral nervous system disorder or severe neuromuscular disease; (6) history of leukemia, severe chronic liver disease, solid organ transplantation, malignant tumor (because of their immunocompromised state and increased risk of infection); or (7) severe cardiac disease (to avoid provocation of hemodynamic instability).Patients were ventilated with a SERVO-i ventilator . A nasogastric feeding tube  with electrodes to measure EAdi and balloons to measure esophageal pressure (Pes) and gastric pressure (Pga) were inserted through the nose. After verifying the correct positioning of the esophageal balloon by an occlusion test with spontaneous breaths , and aftThroughout the protocol, EAdi, Paw, flow, Pes and Pga waveforms were recorded by using a custom-made system (NeuroVent Research) for offline analysis. EAdi, Paw, flow and tidal volume (Vt) were acquired from the SERVO-i ventilator via the RS232 serial port at a sampling rate of 100 Hz. Pes and Pga were acquired at 2 KHz using via a DT 304 A/D board (data translation) and synchronized to the RS232 serial port signals at 100 Hz. Ptp was calculated as Paw − Pes.2) were set as prescribed by the attending physician. The NAVA level was then increased every 3 minutes in steps of 0.3 cmH2O/μV to a NAVA level of at least 3.0 cmH2O/μV. The upper pressure limit was set to 45 cmH2O in order not to interfere with the titration. At each NAVA level, one non-assisted breath was obtained by reducing the NAVA level to 0 (hereafter NAVA zero breath). PEEP was unchanged during these breaths. At every NAVA level, one inspiratory occlusion was performed to measure neuromechanical efficiency (NME), as described below.Patients were receiving intravenous analgesia with morphine at 1 to 2 mg/hr, and no sedative was used during the experimental period. Patients were ventilated in pressure support mode (set by the attending physician) for 30 minutes after the nasogastric tube insertion. Patients were then switched to NAVA, with the NAVA level initially set to 0 for 3 minutes. Positive end-expiratory pressure (PEEP) and fraction of inspired oxygen  and peak airway pressure (Pawpk) were calculated. As well, ΔPes and ΔPtp between the onset of EAdi to their respective peak values were calculated. Note that the Pes signal has a negative trajectory and negative peak. Note also that peak values were obtained anytime during Ti and were not exactly matched in time.At each NAVA level, the last five breaths (prior to the NAVA zero breath) were analyzed. Figure e Figure . During R2 = 0.94 to 0.97), and, for this reason, mean values are not reported. Of note, the mean values represented 60% to 70% of the peak values.Mean values for changes in EAdi and Pes were also calculated for each Ti period. Mean EAdi was obtained by integration during the Ti period and then divided by Ti. Mean Pes and Ptp were calculated the same way; however, values used during Ti integration were subtracted by the values measured at onset each of Ti. The mean and peak values for EAdi, ΔPes, Paw and ΔPtp were closely related (range of Breathing frequency (Fb) was calculated on a breath-by-breath basis as 60 divided by total breath time .paradox) between onset of EAdi and the lowest value observed during Ti for the assisted breath(s) preceding the non-assisted breath.In order to quantify presence of paradoxical expiratory muscle relaxation during the neural inspiration, we calculated the change in Pga no-assist/(Vtinsp/EAdipk)assist. Another index, PVBC2, was calculated, simply by squaring PVBC [PVBC was calculated as  was used as a direct index to quantify the patient inspiratory muscle effort (ΔPes) contribution to total lung-distending pressure (ΔPtp) during assisted breaths . As the 2 were related to ΔPes/ΔPtp [2 indices as described in the subsections below.In our previous study using the experimental animal model, both PVBC and PVBCPes/ΔPtp  during i2 indices in two ways: (1) using the same method described previously [N1PVBC and N1PVBC2); and (2) using PVBC and PVBC2 calculated with five averaged EAdi values from the five preceding breaths (“X5”) (referred to as X5PBVC and X5PBVC2).We calculated the PVBC and PVBCeviously , applyinpk and Ti. As mentioned in the Introduction above, to calculate the PVBC-related indices, we assumed that either respiratory drive should be fairly similar for the unassisted and the assisted breaths or breaths could be corrected by using respiratory drive to “normalize” Vtinsp [pk with and without assist  as well as Ti with and without assist (Tino-assist/Tiassist) at each NAVA level. Assuming that a ratio of 1 was a perfect match, we arbitrarily decided upon five ranges that successively reduced the degrees of freedom for either EAdipk,no-assist/EAdipk,assist or Tino-assist/Tiassist: 0.63 to 1.60, 0.67 to 1.50, 0.71 to 1.40, 0.77 to 1.30 and 0.83 to 1.20. Each range was selected to show the same relative changes above and below 1.0. We also tested if closely matched EAdipk values between non-assisted and assisted breaths could eliminate the need for EAdi normalization in the PVBC indices. For this purpose, we calculated PVBC simply as the ratio between Vtinsp for non-assisted to assisted breaths , subsequently referred to as PVBCβ (using same annotations as the PVBC).Respiratory drive can be interpreted from both EAdi” Vtinsp . To evalStatistical analysis was performed with SigmaPlot 12.5 . Values in the text and figures are mean ± 95% confidence interval, unless otherwise indicated.R2-values for the PVBC–ΔPes/ΔPtp relationship, one-way repeated-measures analysis of variance was performed. Post hoc comparison was performed by using the Student–Newman–Keuls test. A significant difference was defined as P <0.05. Bland-Altman analysis was used to study agreement between methods.The relationship between different variables was tested with linear regression analysis. To identify the impact of averaging and breath matching on 2 = 0.4 or 0.5), with oxygen saturation ranging from 95% to 100%.As shown in Table 2O/μV.All subjects reached a NAVA level of 3.0 cmHparadox, the largest magnitude of paradoxical expiratory muscle relaxations during Ti, were −0.08 (0.06) and −0.08 (0.05) cmH2O during the single and five assisted breaths (preceding the non-assisted breaths), respectively.Group mean values for ΔPgapk, EAdipk, ΔPes and Vtinsp  to the last titration step at NAVA level 3.0 cm H2O/μV (NME = 1.70 ± 0.86 cmH2O/μV).The NME did not change significantly from NAVA level zero  and Tino-assist/Tiassist (blue symbols) on the determination coefficients  between PVBC indices and ΔPes/ΔPtp. PVBC versus ΔPes/ΔPtp showed higher determination coefficients (y-axes) when calculated from the average of five preceding assisted breaths compared with when they were calculated with one assisted breath. Better matching of EAdipk,no-assist/EAdipk,assist increased determination coefficients for PVBC indices with five breaths average, reaching significance with matching criteria  at 0.77 to 1.30.Figure x-axes in Figure y-axes in Figure pk,no-assist/EAdipk,assist of 0.77 to 1.30 provided the best combination of highest R2 values, lowest variability and least exclusion of data points not meeting matching criteria. In summary, this analysis showed the highest determination coefficients between the PVBC indices and ΔPes/ΔPtp when the PVBC was calculated using an average of five assisted breaths with EAdipk,no-assist/EAdipk,assist within the 0.77 to 1.30 range. The distribution of EAdipk,no-assist/EAdipk,assist for all patients and NAVA levels is presented in Figure Improved matching of Ti , ΔPtp (including PEEP), PEEP, EAdipk, Vtinsp, and Fb for increasing NAVA levels. With progressive increases in NAVA level, there was a concomitant reduction in EAdipk until a point where the increase in Vt plateaued. Fb did not change for the titration of NAVA levels.Figure X5PVBC, X5PVBC2 and ΔPes/ΔPtp with increasing NAVA levels. Figures x-axes) plotted against X5PVBC and X5PVBC2 (y-axes), respectively. Figure insp by EAdipk (referred to as X5PVBCβ and X5PVBCβ2). The proportionality between X5PVBCβ versus ΔPes/ΔPtp as well as X5PVBCβ2 versus ΔPes/ΔPtp is demonstrated in Figure Figure X5PVBC and X5PVBC2 as well as X5PVBCβ and X5PVBCβ2 (panels A and D) decreased in a fashion similar to that of ΔPes/ΔPtp, showing less contribution by the patient. Squaring the indices significantly adjusted the regression coefficients and moved the intercepts for X5PVBC2 (panel C) and X5PVBCβ2 (panel F) closer to zero.As the NAVA level increased, X5PVBC, X5PVBC2, X5PVBCβ and X5PVBCβ2 indices versus ΔPes/ΔPtp. Squared indices, X5PVBC2 and X5PVBCβ2, reduced bias (P <0.05), and better agreement for lower (P <0.05) and upper (P <0.05) levels of adjustment with regards to ΔPes/ΔPtp. All data in Figure pk ratio inclusion criteria of 0.77-1.30 between single non-assisted breath and mean of previous 5 breaths.Table insp corrected for neural inspiratory drive for a non-assisted breath (Vtinsp/EAdipk)no-assist to that during an assisted breath assist) resulted in a PVBC index that closely reflected the ratio between patient (ΔPes) and total (patient + ventilator = ΔPtp) mechanical inspiratory effort. We also demonstrate that selection of non-assisted and assisted breaths with well-matched neural efforts improved the reliability of the PVBC index. Computation using an average of the five preceding assisted breaths, squaring PVBC and including only breaths with EAdi ratios for non-assisted and assisted breaths between 0.8 and 1.3 resulted in the most reliable PVBC (X5PVBC2) index. Using EAdi to match non-assisted and assisted breaths eliminated the need to correct for changes in neural respiratory drive and allowed computation of PVBC based on inspiratory volume alone.The results of the present study validate a clinical index that can be used to quantify the relative inspiratory effort of a patient during assisted ventilation. Comparison of Vtet al. [R2) between PVBC indices and ΔPes/ΔPtp improved when neural inspiratory drive was matched between assisted and non-assisted breaths. Neural drive can be considered to have two major components: (1) neural breathing frequency  and (2) amplitude . Our finding that matching assisted and non-assisted breaths for Ti had little effect on R2 between PVBC and ΔPes/ΔPtp suggests that temporal variability in neural drive had little influence on the accuracy of the PVBC index. However, EAdipk had a strong impact in improving the fit between PVBC and ΔPes/ΔPtp, suggesting that the magnitude of neural inspiratory effort is important for the accuracy of the PVBC index.The results of our clinical study of patients with ARF generally confirm those of the previous study in animals by Grasselli et al. . We founTransesophageal measurements of EAdi mainly represent motor unit activation for a portion of the crural diaphragm. Despite this, studies have demonstrated that the EAdi provides a good measure of the global diaphragm activation in healthy subjects  and mechR2 values) between PVBC and ΔPes/ΔPtp when an average of five assisted breaths was used compared with a single breath. We did not apply this approach for the non-assisted breaths because of clinical concerns about removing the assist for several breaths and the potential of altering respiratory muscle recruitment for the various breaths.The present study demonstrates a better fit to the regression line  confirms our initial hypothesis that when inspiratory effort is matched between assisted and non-assisted breaths, Vtinsp must change if synchronized assist is added or removed. Hence, the ratio of Vtinsp values for non-assisted and assisted breaths should be close to a value of 1 when no assist is being provided  and near zero when a breath is fully assumed by the ventilator.Our finding that a ratio of EAdi between assisted and non-assisted breaths of 0.78 to 1.30 produced equally good fit to ΔPes/ΔPtp when we calculated pk, showed extremely strong relationships to their respective mean values. Given that pressures and EAdi are presented as peak values on the ventilator, we preferred to present results that had the closest relationship to clinical implementation.The results given in the present study relate to peak values . Regarding Paw, one could argue that because NAVA does not have a plateau pressure, peak and mean values would provide different information. Regression analysis indicated extremely high correlation between the peak and mean values for Paw. Similarly, other variables, such as ΔPes, ΔPtp and EAdiparadox, calculated as the change in Pga between onset of EAdi and the lowest value observed during Ti for the assisted breath(s) preceding the non-assisted breath, was miniscule. The latter shows that end-expiratory expiratory muscle relaxation was not an important contributor to our results.In spontaneously breathing patients recovering from acute respiratory failure, expiratory muscle contraction during expiration followed by expiratory muscle relaxation during the ensuing inspiration may invalidate and amplify the decrease in esophageal pressure . Such anX5PVBC2 and X5PVBCβ2 showed values about 0.1 relative units higher than ΔPes/ΔPtp. One reason for higher PVBC indices was that ΔPes decreases more than EAdi during assisted breaths. In fact, EAdipk does not reach zero when ΔPes indicates 100% unloading [pk, non-assisted breaths can generate more Vtinsp than during assisted breaths [2O. These factors would act to shift PVBC indices upward.As depicted in Figure nloading . This me breaths . Moreovepk by 3 cmH2O above target, causing a pressure off-cycling algorithm to be activated. If this happens, the Pawpk is somewhat (3 cmH2O) higher than expected and the ΔPes/ΔPtp ratio would be lower than expected, especially at the lowest NAVA levels. Another reason that the ΔPes/ΔPtp ratio was less than 1.0 at the lowest NAVA level could be that Paw was lost because the endotracheal tube resistance led to overestimation of the Paw used to calculate Ptp.Relaxation of the chest wall or expiratory muscle recruitment prior to EAdi off-cycling opens the expiratory valve during assisted breaths. This is due to the increase in PawOur finding of a 16% bias with the Bland-Altman analysis probably relates to a combination of overestimating PVBC as well as underestimating ΔPes/ΔPtp.pk or Ti matching, we would lose the PVBC calculation for that NAVA level. If applied as an automatic function for use in the clinic, the non-assisted breaths could be repeated intermittently to increase the likelihood of obtaining acceptable and reproducible PVBC values.A limitation of this study’s design is that we did only one “PVBC maneuver” (NAVA zero breath) per NAVA level. Consequently, if the breath without assist failed to meet the inclusion criteria for EAdiBreathing patterns are affected by many factors, and stable activation and rhythm require a low level of disturbance. The protocol of the present study was performed by manual interventions by the investigators at the bedside, which could have distracted the patients compared with a system with built-in algorithms for non-assisted breaths and occlusions.pk for each NAVA level. Viale and colleagues showed that about five breaths were sufficient for patients to adapt and adjust to the new assist level during pressure support ventilation [2 and pH on respiratory drive. To the contrary, our data showing that 78% of the breaths fell within the 0.77 to 1.30 matching criteria (one breath to the next) strongly suggest that the first unassisted breath is affected little by removal of ventilatory assist.Three minutes at each NAVA level could be considered short; however, our data indicate that this was sufficient to produce clear reductions in both ΔPes and EAditilation . In the pk values of about 10 μV when the NAVA level was adjusted to match Pawpk during pressure support, providing clinically acceptable Vt levels [X5PVBC2 and X5PVBCβ2 indices of about 0.5 . It is interesting to observe that at an EAdi of 10 μV, the ΔPes was about −5 cmH2O, which could be considered a normal workload. As demonstrated previously during synchronized assist with NAVA, breathing frequency provided little information about acute changes in respiratory load and drive. As depicted in Figure X5PVBC2 and X5PVBCβ2 indices of about 0.3 to 0.4 . Although the highest precision of 0.3  obtained with X5PVBCβ2 could be considered somewhat low, targeting X5PVBCβ2 of 0.5 while monitoring EAdi with a target 10 μV would likely improve the ability to control patient unloading. This type of monitoring would have a direct impact on how to set the ventilator’s assist and, perhaps more important, would provide clinical studies aimed at ensuring avoidance of overassist and optimizing assist for faster weaning. In the present study, PVBC analysis was done by neurally synchronized and proportional assist. Principally, the comparison of Vtinsp for assisted and non-assisted breaths of similar EAdi amplitude should also work with pressure support ventilation; however, future studies are required.In previous clinical studies, researchers have reported, on average, EAdit levels ,22,23.  and inspiratory peak electrical activity of the diaphragm (EAdipk) between non-assisted and assisted breaths, defined as patient and ventilator breath contributions (PVBCs), can be used to predict the relative contribution of the inspiratory muscles versus that of the ventilator during neurally adjusted ventilatory assist (NAVA).The ratio of inspired tidal volume (Vtpk whose ratio between non-assisted and assisted breaths is within the range of 0.77 to 1.30 resulted in a clinically useful PVBC index.Computation of PVBC as a ratio of tidal volumes from one non-assisted breath to the average of five preceding assisted breaths, squaring PVBC and including only breaths with EAdi


Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes.The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices  in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations.Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis.Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately. Meta-analysis or the quantitative synthesis of evidence, usually from systematic reviews, has become a popular tool in healthcare evaluations ,2. LargeWhen summarising effectiveness evidence, correlations between the effectiveness estimates typically arise at either within-study and or between-study levels. At the within-study level, correlations arise mainly due to differences in patient-level characteristics. They are rarely reported in the published literature and usually have to be estimated from external sources such as individual patient level data if available or elicited from expert opinion ,11,14,15A second area of rapid methodological development is network meta-analysis (NMA) , also knet al.[et al.[Approaches to extend NMA methodology to multiple outcome settings have been proposed in the literature ,25-27, iet al. proposedet al. and alsol.[et al.. The proThe remainder of this paper is structured as follows: the example dataset is first described followed by a Methods section describing the statistical models developed and implementation of the models. These are followed by sections presenting the results of applying the methods to the motivating dataset and a discussion.The example data comes from a recently updated Cochrane systematic review of home safety education and provision of safety equipment for injury prevention in children . The moda) Safe storage of medicinesb) Safe storage of other household products (e.g. cleaning products) andc) Possession of a poison control centre (PCC) telephone number.Thirteen of the 22 studies considered at least two of the three outcomes. Of these, 8 considered storage of medicines and storage of other household products, 2 considered storage of other household products and possession of a PCC telephone number, and 3 considered all three outcome measures. Individual patient data (IPD) were available for 8 of the 13 studies, of which 7 were in a format suitable for the analysis reported here as explained by the footnotes in Table We classified the interventions trialled in the 22 studies into 9 relatively homogenous treatment packages:1) Usual care (UC)2) Education (E)3) Education + provision of free/low cost equipment (E + FE)4) Education + provision of free/low cost equipment + home safety inspection (E + FE + HSI)5) Education + provision of free/low cost equipment + fitting of equipment (E + FE + F)6) Education + home safety inspection (E + HSI)7) Education + provision of free/low cost equipment + home safety inspection + fitting of equipment (E + FE + HSI + F)8) Education + home visit (E + HV)9) Provision of free/low cost equipment (FE).et al. (2007) [Figure . (2007)  which coIn this section, we first present the NMA statistical model for one binary outcome measure and then extend it to compare multiple interventions across multiple outcomes. Throughout the paper, we refer to these single and multiple outcome models as univariate and multivariate NMAs respectively. Where studies report multiple outcomes, these will not be independent as each household provides information on the different outcome measures within intervention arms. The multivariate model takes this correlation structure into account by allowing the intervention effects measured by one outcome to be correlated with the intervention effects measured by other outcomes.rik events out of a total of nik households in the kth-arm  of the ith-study follow a binomial distribution with underlying event probability pik:Given arm-level binary data of the form presented in Table μib is a study-specific baseline effect (i.e. the log-odds for the control group in study i with baseline treatment b), i(bk) is a study-specific log-odds ratio, d(bk) is the pooled effect of treatment k relative to treatment b  and b and k are included in study i[d(bk), can be expressed as functions of basic parameters with reference to a common comparator or baseline treatment (i.e. dbk)( = dAk)( − dAb) [A of equation (2) above). Multi-arm studies (i.e. studies with more than 2 treatment groups) present a special problem in network meta-analysis because they produce evidence on multiple treatment effects that are correlated through sharing a common reference or ‘baseline’ treatment. Under a homogenous variance assumption ) . Throughnt is σ22. The homj, given the previous 1, ⋯, (j − 1) arms are:then the marginal and conditional univariate distributions for arm 3) prior distribution for the pooled mean effects relative to usual care, dAk) prior distribution for the between-study standard deviation on the log odds ratio scale σ[The analysis is conducted within a Bayesian framework requiring prior distributions to be specified for all model parameters. Accordingly, we specified minimally informative prior distributions corresponding to a Normal  NMA with competing risks model [We extend the univariate NMA model defined above to the multiple outcomes settings in order to account for correlations between intervention effects on different outcomes. The method presented here follows from Ades ks model  where onet al. (2010), a multinomial likelihood was appropriate as the three binary outcomes  are mutually exclusive and event probabilities sum to 1 across outcomes. A multinomial likelihood will not be appropriate for our example dataset because each household can have one, two or all three outcomes simultaneously so that the event probabilities do not sum to 1 across outcomes. Instead, we use a Normal distribution on the log-odds scale to take account of the within-study correlations between outcomes. We assume that in each study i and for each k-th arm, the estimates mth outcome  jointly follow a multivariate normal distribution:Note that in Ades μib1, μib2, ⋯, μibM) and (δi(bk)1, δi(bk)2, ⋯, δi(bk)M) represent vectors of ‘true’ baseline and study-specific effects in study i with baseline treatment b respectively. The quantities θik1, θik2, ⋯, θikM) represent vectors of observed and ‘true’ log-odds of response in arm k of study i and Sik is the associated within-study covariance matrix usually assumed known but estimated in practice from the data [Sik using standard formulae for log-odds and variance of the log-odds [Sik were calculated from estimates of within-study correlations m and n (m ≠ n) in arm k of study i obtained from studies with IPD  as the between-study model following standard terminology in multivariate meta-analysis [ith study is thus given by:We refer to equation 5) as the within-study model and the model describing the distribution of the  as the wanalysis ,11,38,39‘true’ effects δi(bk)m  jointly follow a Normal distribution with mean effects dbk)m(. The parameters in equation (6) have the same interpretation as in equation (2) except that they are now specific to each outcome. The covariance matrix Σbk) specific to each k versus b comparison. Fitting the full model would thus require a large number of possibly multi-arm studies in order to make Σbk)( identifiable [Σbk) and (4) to the multiple outcome setting. We show in Appendix A, that under evidence consistency and the homogenous between-study covariance structure  arms are:where μibm and dk)m [ΣM × M)  and mores (2009)  to exprerd et al.):R contain correlation terms and diagonal elements equal 1. Lu and Ades [R can be written as R = LTL using Cholesky decomposition where L is an upper triangular matrix. The spherical parameterization technique [R in terms of sine and cosine functions of the elements in L. Using this later technique, we specified Uniform  prior distributions for the spherical coordinate φmn in our model to ensure that elements of the correlation matrix R lie in the interval . Finally, the elements of V1/2 correspond to the between-study standard deviation terms in ΣM × M) prior distributions as in the univariate case (model 1).where the off-diagonal elements of and Ades  and alsoand Ades  showed technique ,43 can bet al.[k relative to usual care intervention dAk)m specified for dAk)m, dAk)m thus embodies an assumption of equal or constant relative potency of treatments across outcomes which imply exchangeability of the relative effects between the non-reference/baseline treatments indicated by equation (11). For our example dataset, this implies that missing intervention effects for comparisons with the usual care intervention can be predicted directly from equation (10) as a linear combination of τ controls the accuracy of the constant relative potency assumption. Values of τ close to zero would thus indicate a high degree of confidence (and support from the data) in the parallelism of effect profiles across outcomes and the constant relative potency assumption. Conversely, larger values of τ would indicate otherwise.The parameter αk, γm and τ are given minimally informative prior distributions. For the mean effects, this is a normal distribution with zero mean and large variance:Multi-arm studies are included in model 3 based on equations (8) and (9) in the same way as in model 2. To complete model 3, the parameters τ a Uniform  prior distribution, considered to be minimally informative on the log-odds ratio scale. Sensitivity analyses were conducted to assess the impact of specifying alternative prior distributions for τ that are also considered minimally informative [We give ormative :τ ~ N, τ ≥ 0i. Normal prior distribution centred on 0 with large variance and constrained to be positive, τ− 2 ~ Gamma.ii. Gamma prior distribution placed on the precision: The results of the sensitivity analyses are presented in Additional file K interventions and M outcomes, there will be (K − 1) × M equation (10) that are used to estimate a total of (K − 1) + M hyper-parameters (i.e. (K − 1) of αk and M of γm hyper-parameters). Therefore no more than ((K − 1) × M) − ((K − 1) + M) missing values in total are allowed. For example, for K = 3 treatments and M = 2 outcomes, data has to be available on both outcomes for both treatment comparisons with the baseline when the prior distributions are non-informative. When large number of data on outcomes is missing, placing informative prior distributions on the hyper-parameters can improve convergence.There is a limitation to the number of data  on outcomes allowed to be missing for the model hyper-parameters to be identifiable. For ΣM × M) using the estimates of the correlations between the observed outcome events (Pearson correlation) as follows:We fitted a total of four models, models 1 and 3 as described above and two versions of model 2. In model 2a, we specified an inverse-Wishart prior distribution for the between-study covariance matrix m and n effects measured on the log-odds scale in arm k of study i, and var (rmn)are the mean and variance of the within-study correlation between outcomes m and n effects measured by IPD respectively.where We also assessed consistency of the evidence within each network using a method based on node splitting . We founet al.[We fitted all models described above in WinBUGS  using Maet al.. The WinParameters of interest were the posterior median estimate  of the pooled intervention effects relative to the usual care intervention and the posterior median estimate  of the between-study standard deviation and correlation terms. Summary forest plots displaying effectiveness estimates relative to usual care on the odds ratio (OR) scale are presented in Figure Posterior median and 95% credible intervals of the between-study standard deviations and correlations are presented in Table It can be seen from Figure τ  = 1.24 (95% CrI 1.01 to 2.87).The posterior median and 95% credible intervals of intervention effects relative to usual care were unaffected by placing alternative minimally informative prior distributions on  τ Table  were simet al.’s (2010) NMA with competing risks paper [We have presented methods for simultaneous comparison of multiple treatments across multiple outcome measures while preserving the internal randomisation of individual studies. Our method may be viewed as an extension of Ades ks paper  wherein In this particular application of the multivariate approach, accounting for the correlation between outcomes alone (models 2a and 2b) did not reduce the uncertainty around estimates of intervention effects compared to analysing each outcome separately (model 1). Assuming that intervention effects are exchangeable across outcome did however lead to a modest reduction in uncertainty around effectiveness estimates (model 3).et al.[σ1 and σ2 on the log odds ratio scale  rather than the study-specific treatment difference (log-odds ratio) as is often done in multivariate meta-analysis ,4,15,38.k versus b comparison, the assumption is that the between-study correlations would be the same across the different sets of bk comparisons. We suggested this structure to simplify the covariance structure and reduce the number of parameters in the model. Appropriateness of such modelling assumptions would need to be considered carefully and assessed when it is feasible to do so.At the between-study level, we assumed a common correlation structure across treatments in addition to the common variance assumption underlying most practical application of NMA methods. The common correlation assumption implies that if several separate multivariate meta-analyses were conducted with the same outcomes, each with a different set of ΣM × M) the problem of missing within-study correlations and ii) the requirement for a relatively large number of studies to estimate all model parameters. The problem of missing within-study correlations has traditionally hampered the widespread application of multivariate meta-analysis ,10,15. IΣbk), a relatively large number of studies in comparison to the total number of outcomes being considered may still be needed. We are unable to answer the question of how many studies should be considered large enough for a NMA with multiple outcomes. As a guide, Wei and Higgins [The second data issue concerns the number of studies needed to estimate the full unstructured between-study covariance matrix presented in equation (6). We anticipate a large number of multi-arm studies reporting across the three outcomes will be needed to identify  Higgins  recentlyet al.[et al.[et al.’s[Another limitation of the multivariate models presented here is that they rely on the normal approximation to binomial distribution to incorporate the within-study correlations in the model. The normal approximation frequently fails and may not provide adequate fit to the data in the presence of studies with zero or a small number of events, necessitating use of continuity corrections. We were unable to use the exact binomial distribution as our primary interest was to develop models for summary binary data where outcomes are not mutually exclusive, and where it is not reasonable to assume that within-study correlations are zero so that the likelihood factorises easily as in Arends et al.. Furtherl.[et al. where pa[et al.’s NMA modeWe assessed the consistency of each outcome network separately using the method of node splitting . We founOur initial motivation for a multiple outcome NMA was to estimate intervention effects for all the outcomes, including effects of interventions on outcomes not considered by any of the studies included in the analysis. This requires the correlation structure between effects on multiple outcomes to be appropriately modelled and also ensuring the mechanism of “borrow strength” across outcomes through the assumption of exchangeability of the random effect across outcomes. This implies a priori assumption that outcomes are related but different and that there is no way of knowing the order of magnitude of effects on outcomes. If this assumption does not hold, it may potentially lead to worse or more biased effectiveness estimates. In our example, the outcomes are similar and measured on the same scale. It would be clearly inappropriate to assume that intervention effects are exchangeable across outcomes that are different in some important respects such as being measured on different scales (e.g. where one outcome reports a weighted mean difference and another outcome reports a log-odds ratio) as such estimates will differ in terms of the precision with which they are estimated.Our aim in this paper was to present methods for simultaneous comparison of multiple treatments across multiple outcome measures while preserving the internal randomisation of individual studies. Application of the method to the poison prevention data yielded similar point estimates of treatment effect to those obtained from a univariate NMA but the uncertainty around the multivariate estimates increased or decreased depending on the prior distribution specified for the between-study covariance structure. The proposed method followed the usual hierarchical approach to multivariate meta-analysis where correlations between outcomes are modelled at the within-study and or between-study levels.i with K treatments labelled A, B, C, …, K reporting a total of M outcomes labelled 1, 2, …, M. A random effects between-study model can be represented as:For a multi-arm study δi(Ak)m and dAk)m( are study-specific and mean effect of treatment k relative A (reference treatment) on outcome m in study i respectively and ΣFULL is the full (K-1) × (K-1) blocks of M × M within-treatment between-outcome covariance matrix. The parameters in ΣFULL have the following interpretation: relative to A on outcome m across studies.Where δi(Ak)m and δi(Ak)n (i.e. the correlation between the effect of treatment k relative to A on outcome m and the effect of treatment k relative to A on outcome n (m ≠ n)) specific to the Ak comparison.δi(Ah)m and δi(Ak)m (i.e. the correlation between the effect of treatment h relative to A on outcome m and the effect of treatment k relative to A (h ≠ k) on outcome m because they share a common comparator A).The diagonal block matrices in ΣFULL thus carry terms for the between-study variance  configuration, the covariance between outcome m and n effects across studies can be expressed as a covariance between two sums under evidence consistency:outcomes . This imsis case ,34. Secoρmn in the diagonal block of matrices and ΣFULL leading to the following simplificationfollowing simplification of the between-study covariance matrix:The homogenous between-study correlation assumption implies A as b, (δi(AB)1, ⋯, δi(AK)m) as dAB)1M as Finally by relabeling the reference treatment CrI: Credible interval; IPD: Individual patient data; MCMC: Markov Chain Monte Carlo; NMA: Network meta-analysis; PCC: Poison centre control number.The authors declare that they have no competing interests.FAA drafted the initial manuscript, conducted the analysis and coordinated contributions from all authors in drafting the final manuscript. NJC designed the study and revised the manuscript to improve general readability. SB contributed to developing the statistical analysis and interpretation of the results. SJH contributed to preparing the data for analysis, drafting the network diagrams and revision of the initial and final drafts. DK provided the data for analysis, defined the outcomes and interventions and revision of the final drafts.DRJ participated in designing the study and revision of the final manuscript. AJS conceived the original idea and participated developing the statistical model. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2288/14/92/prepub(WinBUGS Code for model 2): Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.Click here for file


Prochlorococcus cyanobacteria. However, in the oligotrophic open ocean, the majority of their cells in the top half of the photic layer have levels of photosynthetic pigmentation barely detectable by flow cytometry, suggesting low efficiency of CO2 fixation compared with other phytoplankton living in the same waters. To test the latter assumption, CO2 fixation rates of flow cytometrically sorted 14C-labelled phytoplankton cells were directly compared in surface waters of the open Atlantic Ocean (30°S to 30°N). CO2 fixation rates of Prochlorococcus are at least 1.5–2.0 times higher than CO2 fixation rates of the smallest plastidic protists and Synechococcus cyanobacteria when normalised to photosynthetic pigmentation assessed using cellular red autofluorescence. Therefore, our data indicate that in oligotrophic oceanic surface waters, pigment minimisation allows Prochlorococcus cells to harvest plentiful sunlight more effectively than other phytoplankton.Nearly half of the Earth's surface is covered by the ocean populated by the most abundant photosynthetic organisms on the planet— Prochlorococcus (Pro) cyanobacteria are the most abundant phytoplankton in the ocean, inhabiting nutrient-depleted environments from the equator up to 40–50° of latitude (Pro is very low (∼0.1 fg divinyl chlorophyll per cell), and consequently their carbon to chlorophyll ratios are very high (93.3–122 mg C per mg chlorophyll-a) in comparison with Synechococcus cyanobacteria and small picoeukaryotes (38–58 mg C per mg chlorophyll-a)  vs 90° side light scatter  nutrient-replete but less illuminated parts of the water column, Pro pigmentation is much more intense  pigment levels are decreased as a result of the combined effects of high irradiance and nutrient limitation that diminishes capacity of the cells to cope with this stress, or (2) constitutively low cellular levels of photosynthetically active pigmentation are adequately physiologically balanced for these environmental conditions. In the former case, Pro red autofluorescence-normalised CO2 fixation should be low compared with other phytoplankton, whereas red autofluorescence-normalised CO2 fixation of Pro cells will be comparable with, or higher than, red autofluorescence-normalised CO2 fixation by other phytoplankton cells if the latter were true.We put to the test two alternative explanations that account for the extremely low photopigmentation of 2 fixation of surface Pro is high compared with the smallest eukaryotic phytoplankton and Synechococcus cyanobacteria. These results demonstrate that the dim red autofluorescence of surface Pro does not prevent them attaining high CO2 fixation rates across the Atlantic Ocean.Here, we present direct experimental evidence that red autofluorescence-normalised COJames Cook in October–November 2010  bottles attached to a standard conductivity–temperature–depth profiler on the 20th cruise of the Atlantic Meridional Transect programme aboard the UK Royal Research Ship ber 2010 . Seawateber 2010  additionSynechococcus (Syn) and Pro cyanobacteria were determined in unstained, fixed  samples according to Pro cells were counted in both unstained (Prounst) and stained fixed samples (Prost) on the basis of their red autofluorescence and 90° side light scatter, and their nucleic acid content (green fluorescence) and 90° side light scatter, respectively. Subsamples for Prost counting were taken from a 20 l carboy and fixed with 1% paraformaldehyde for 1 h in the dark at room temperature and stained with SYBR Green I dye (Sigma-Aldrich) (Concentrations of the Aldrich)  was addeSyn abundances: Northern subtropical gyre (NG), equatorial waters (EQ), Southern subtropical gyre (SG) and Southern temperate waters (ST) . Samples were then incubated at ambient temperatures ) in a 6 l water tank illuminated by a warm white light-emitting diode array  adjusted to a constant output of 500 μmol photons m−2 s−1. The chosen light intensity equals half the irradiance reaching the water surface at noon-time in the equatorial region  were acid-soaked overnight (10% HCl) and rinsed twice with 30 ml sample sea water. After washing, 60 ml of seawater sample was added to each bottle and spiked with trace metal-clean 14CO3 were used to determine total CO2 fixation during a time series and to measure CO2 fixation of flow cytometrically sorted phytoplankton populations, respectively. Time series were carried out to ensure linear uptake of label and to guarantee that the small volumes of sorted cells are representative of the whole community  and incubated for 1 h at room temperature. Subsequently, the complete sample was filtered onto a 0.2 μm polycarbonate filter , washed three times with ultra-clean water  and placed in a scintillation vial. Before addition of 5 ml scintillation cocktail , 1 ml of 10% HCl was added, the vial gently swirled and incubated for 10–30 min to fume out non-incorporated NaH14CO3. Dark CO2 fixation rates were <3% of paired CO2 fixation rates in the light in all experiments . Three 1.6 ml subsamples were taken directly to determine total CO2 fixation and to sort Prost. In order to sort adequate cell numbers of cyanobacteria (Prounst and Syn), 20 ml of the sample was concentrated on a 0.6 μm polycarbonate filter  mounted in a filtration unit  using a syringe pump  at a flow rate of 2.5 ml min−1. This pore size was selected as it was shown in an earlier publication  a parallel incubation was carried out where 2.6 ml of nutrient-enriched sea water from 300 m depth was added to 60 ml of seawater sample from 20 m to simulate a mixing event  according to side scatter and green fluorescence properties. In addition, Pro was sorted according to red autofluorescence from 0.6 μm concentrated unstained samples (Prounst), as earlier studies indicated a cell diameter of >0.6 μm  before counting. Radioassaying of samples was carried out using an ultra-low-level liquid scintillation counter .Different phytoplankton populations were sorted according to light scattering properties (90° or side light scatter), relative concentration of SYBR Green I stain per particle , phycoerythrin content  and chlorophyll content  using a FACSort instrument (Becton-Dickinson). Because of their low pigmentation in surface waters, we used two approaches to sort SH >86%, , was sorProst and Prounst surface populations were determined on Atlantic Meridional Transect (AMT)-4 at 11 stations spanning NG, EQ and SG regions using a size fractionation method  and Prounst  were significantly different . Mean cell biovolumes were calculated assuming a spherical cell shape. For Pro and Syn cells, conversion factors of 184 and 211 fg C μm−3  indicated that the Prounst cells comprised a subpopulation of the Prost population . The cells among the sorted Prost populations not hybridising with the Pro-targeted probe could either be Pro cells with ribosomal contents below detection level of FISH  or they could be by-sorted non-Pro cells displaying similar DNA fluorescence and side light scatter properties. A small proportion of sorted cells (5–6%) could not be detected by FISH with the universal bacterial probe  using size fractionation revealed that Prost cells were systematically smaller than Prounst cells across the Atlantic Ocean , showing increased rates in the EQ  whereas Syn showed on average 60% higher biomass-specific CO2 fixation than Pro  had no significant effect on CO2 fixation rates of either Pro or Syn cells . Moreover, comparisons of CO2 fixation rates of Pro populations from surface waters and deeper water (bottom of the thermocline) revealed no significant differences in CO2 fixation rates when exposed to the same light conditions, despite stronger red fluorescence of deeper Pro cells (To assess whether cellular COro cells .2 fixation rates using 14C-tracer is technically challenging and has been attempted only in three other studies so far (2 fixation rates of four distinct phytoplankton groups across the Atlantic Ocean. Cellular CO2 fixation rates measured in the equatorial region are comparable to those measured in the North East Atlantic (2 fixation by Pro inhabiting the deeper waters (Pro could contribute more than a half to the total CO2 fixation in the low-latitude Ocean. These estimates concur with our results from surface waters (Direct determination of group-specific COAtlantic . Our slie waters .−2 s−1 ;Pro cyanobacteria in surface waters of the low-latitude Atlantic Ocean. How do Pro cells remain numerous, effective CO2 fixers in these waters (A combination of high sunlight irradiance (up to 3000 μmol photons me waters  with virSyn cyanobacteria can easily be detected in the same waters by their photosynthetic pigmentation, suggesting that the required nutrients are still bioavailable to those cells. Furthermore, CO2 fixation rates of Pro remained unchanged in our deep water addition experiments to simulate mixing events, suggesting that Pro are not nutrient limited, at least with regard to CO2 fixation (Pro were estimated. In addition, Pro cells populating the deeper parts of the mixed layer, where nutrients are still scarce but irradiance is less intense, exhibit stronger red autofluorescence (Biosynthesis of photosynthetic pigments like chlorophyll requires certain inorganic nutrients, for example, nitrogen and iron, that are depleted in the subtropical gyres, and constrained nutrient bioavailability can lead to reduced cellular pigmentation (fixation . These fPro cells produce only low amounts of photosynthetic pigmentation in order to achieve efficient CO2 fixation with minimal effort using light energy for photosynthesis as well as for photoheterotrophy, that is, redirecting a part of the collected light energy for actively importing organic molecules (Syn cells that spend considerable energy on the production of photoprotective pigments (Syn and Pro showed that the Pro response to photo-damage is modelled to minimise energy demand, for example, during high irradiance periods of the day the main metabolic processes are downregulated (2 fixation rates of Pro in comparison with Syn (Syn cells in oligotrophic waters despite their higher biomass-specific CO2 fixation rates. On the other hand, the difference in biomass-specific CO2 fixation rates between Pro and Syn is comparatively small given the higher pigment content, up to 10 times at 1000 μmol m−2 s−1 light in cultures (Perhaps olecules . This wopigments . Moleculwith Syn  are, percultures  of the l2 fixation by Pro is likely related to the high geometrical absorption cross-section owing to their small cell size (Pro is further increased by the unique pigment, chlorophyll a2 (Pro cells with minimal photosynthetic pigmentation to become highly efficient CO2 fixers (High red autofluorescence-normalised COphyll a2  with abs2 fixers .Pro are highly efficient CO2 fixers in surface waters of the Atlantic Ocean and their red autofluorescence-normalised CO2 fixation rates are higher than those of Syn and small plastidic protists. These findings indicate that Pro should be specially taken into account when photosynthetic pigmentation data are used for deducing biological CO2 fixation in the oligotrophic open ocean.The results presented here demonstrate that


Rev-erb 1α. In order to elucidate clock gene regulation of genes involved in lipid metabolism in Atlantic salmon , the orphan nuclear receptor Rev-erb 1α was cloned and 24 h expression of clock genes, transcription factors and genes involved in cholesterol and lipid metabolism determined in liver of parr acclimated to a long-day photoperiod, which was previously shown to elicit rhythmic clock gene expression in the brain. Of the 31 genes analysed, significant daily expression was demonstrated in the clock gene Bmal1, transcription factor genes Srebp1, Lxr, Pparα and Pparγ, and several lipid metabolism genes Hmgcr, Ipi, ApoCII and El. The possible regulatory mechanisms and pathways, and the functional significance of these patterns of expression were discussed. Importantly and in contrast to mammals, Per1, Per2, Fas, Srebp2, Cyp71α and Rev-erb 1α did not display significant daily rhythmicity in salmon. The present study is the first report characterising 24 h profiles of gene expression in liver of Atlantic salmon. However, more importantly, the predominant role of lipids in the nutrition and metabolism of fish, and of feed efficiency in determining farming economics, means that daily rhythmicity in the regulation of lipid metabolism will be an area of considerable interest for future research in commercially important species.In mammals, several genes involved in liver lipid and cholesterol homeostasis are rhythmically expressed with expression shown to be regulated by clock genes via  Salmo salar) will greatly improve the efficiency and sustainability of aquaculture Fish are universally acknowledged as a healthy food and are the major source in our diet of the essential and highly beneficial omega-3 (n-3) long-chain polyunsaturated fatty acids (LC-PUFA) Daily rhythms in animal behaviour, physiology and metabolism are driven by cell autonomous clocks that are synchronised by environmental cycles, but maintain ≈24 h rhythms even in the absence of environmental cues Rev-erb 1α mRNA is rhythmically expressed and subject to regulation by the negative components, Cryptochrome (Cry) and Period (Per), of the molecular clock In mice, a number of genes intrinsically involved in lipid metabolism were shown to be mediated by nuclear receptor subfamily 1, group D, member 1  a component of the molecular clock Srebp1) or cholesterol biosynthesis (Srebp2) Srebp1 transcription can also be activated through the LXRE response element by liver X receptor (LXR), a nuclear receptor that regulates the metabolism of several important lipids, including cholesterol and bile acids The regulation of genes involved in cholesterol and lipid homeostasis by REV-ERB 1α is mediated through sterol regulatory element binding protein (SREBP) pathways and SREBP target genes Srebps, Ppars and Lxr have been cloned and studied in salmon Clock, Per1, Per2 and Bmal1 have been isolated in salmonids Rev-erb 1α cDNA and determine its pattern of expression in a 24 h cycle in salmon.The cDNAs of transcription factors key to lipid, fatty acid and cholesterol metabolism including 3 (1000 L) tank at the Niall Bromage Freshwater Research Facilities . The fish were acclimated to a long day photoperiod cycle (LD 16 h light: 08 h dark) in early March when water temperature was on average 4.6±0.7°C. Feed, EWOS micro parr diet , was offered continuously in excess, during the day and night via a clockwork belt feeder. After 1 month, liver tissue samples were collected from 6 individuals every 4 h over a 24 h period. Briefly, experimental animals were sacrificed via lethal anaesthesia and decapitation. Feeding activity in all animals sampled was confirmed by observing the presence of faecal materials in the intestinal tract. Liver samples were immediately frozen in liquid nitrogen and stored at −70°C until use. A dim red light was used for nocturnal sampling. All experiments were subjected to ethical review by the University of Stirling through the Animal and Welfare and Ethical Review body. The project was conducted under UK Home Office project Licence number PPL 60/03969 in accordance with the amended Animals Scientific Procedures Act implementing EU Directive 2010/63.Stock Atlantic salmon parr  were maintained in a single 1 mApproximately 100 mg of liver tissue was homogenised in 1 ml of TRIzol and RNA extracted according to manufacturer’s instructions . The resulting RNA pellets were resuspended in MilliQ water to a final RNA concentration of approximately 100 ng/µl. Total RNA concentration was determined by ND-1000 Nanodrop spectrophotometer . In order to eliminate DNA contamination 5 µg of total RNA was treated with DNase enzyme following DNA-free kit guidelines . cDNA was synthesised using 1 µg of DNase-treated RNA and random primers in 20 µl reactions and the High capacity reverse transcription kit without RNase inhibiter according to the manufacturer’s protocol (Applied Biosystems). Final reactions were diluted with DNA/RNA-free water to a final volume of 200 µl. All cDNA samples were stored at −20°C until use in qPCR.Salmo salar Rev-erb 1α was cloned as follows: two Atlantic salmon expressed sequence tag clones (Genbank ID: DY724083 and DY731913) were identified by BLAST analysis of published vertebrate Rev-erb 1α sequences. 5′ and 3′ ends from the constructed contig were amplified using Rapid Amplification of cDNA Ends (RACE)-PCR with the RACE cDNAs generated from 1 µg of salmon whole brain total RNA using the SMART RACE kit as described in the user manual . The 5′ and 3′ RACE amplicons were generated by two rounds of PCR using Rev-erb 1α 1 5′R1 and Rev-erb 1α 5′R2 primers or Rev-erb 1α 3′F1 and Rev-erb 1α 3′F2, respectively (www.dnastar.com). Sequencing was performed using a Beckman 8800 autosequencer and Lasergene SEQman software (DNASTAR) used to edit and assemble DNA sequences.ectively . The finRev-erb 1α, all qPCR assays were established and verified previously Bmal 1, Clock, Per1, Per2 and Rev-erb 1α; lipid-associated transcription factor genes, Srebp1, Srebp2, Lxr, Pparα and Pparγ; and key genes involved in major lipid pathways including fatty acid synthesis  and catabolism (Cpt1 and Aco), cholesterol metabolism  and lipoprotein metabolism  (With the exception of nd Lplc) . qPCR prβ-actin, EF-α and GAPDH) analysis highlighted elongation factor α (EF-α) as the most appropriate housekeeping gene with the greatest stability .GeNorm analysis was carried out on three potential housekeeping genes over the long day liver diel profile to determine the most stable and appropriate reference gene for this tissue. Of the three genes studied (http://www.circadian.org/softwar.html). Acro analysis determines both the significance, acrophase (peak in expression) mean and amplitude of raw data using the equation:p value was less than 0.05 for all statistical analysis. All results are presented as % of mean expression whereby each normalized copy number value was converted to a % of the average total copy number of the gene of interest. Data were then presented as mean ± SEM in relation to zeitgeber time (ZT) whereby ZT 00∶00 occurred at lights on and lights off was at ZT 16∶00.Analysis of Variance (ANOVA) was used to determine significant effects of time and Tukey’s test was used to determine the significance of differences between sample time points and mean of different sample sets . Data were then fitted to a cosine wave in order to determine the presence of a significant daily rhythm. Raw data was analysed using Acro circadian analysis programs  and fugu (Takifugu rubripes), with the Atlantic salmon protein displaying 57% and 71% identities with human and zebrafish (Danio rerio) Rev-erb 1α sequences, respectively.A 2987 bp full-length cDNA sequence (Accession number: 1714461) was obtained by several runs of 5′ and 3′ RACE PCR. This contained an open reading frame (ORF) of 1824 bp encoding a putative protein of 608 amino acids and 3′ and 5′ untranslated regions (UTR) of 349 bp and an 814 bp, respectively. Atlantic salmon putative REV-ERB 1α possessed a ligand binding domain, and the predicted DNA binding domain composed of two C4-type zinc fingers, each one containing a group of four coordinating cysteine residues, as well as one crystal form similar to human 1HLZ-A 1α and β . HomologBmal 1 displayed a significant daily pattern of expression when results were fitted to a cosine wave using Acro analysis  liver Bmal1 expression identified in this study, particularly in the absence of additional rhythmic expression of other clock genes, may indicate an additional function of Bmal1 in the liver of the Atlantic salmon. Interestingly Bmal1 itself can be regulated by elements of lipid metabolism pathways. Specifically PPARα has been shown to control Bmal1 expression in the liver via direct binding to a PPRE located in the Bmal1 promoter Bmal1 and Pparα in the liver appeared to be in phase with their acrophases occurring at 13∶00±3.09 and 13∶00±2.73, respectively, indicating that expression and regulation of these genes may be related as in mammals. In addition, Bmal1 is a direct target of vascular PparγBmal1 is unknown in the liver.The molecular clock mechanism is based on an autoregulatory feedback loop that takes approximately 24 h to complete and synchronises a multitude of molecular, physiological and behavioural process to the daily 24 h cycle Clock, Per1 and Per2 did not display oscillatory patterns in a 24 h cycle, however, the results for Clock and Per2 are consistent with those previously obtained in the brain of Atlantic salmon In contrast to previous studies on teleost liver Rev-erb 1α, a key connection between the molecular clock and liver lipid metabolism in mammals, played a similar role in Atlantic salmon. Alignment and phylogenetic analysis showed that the sequence identified displayed considerable similarity to other vertebrate Rev-erb 1α sequences, and presented homologous predicted structural components with human REV-ERB 1α protein Rev-erb 1α expression over the 24 h period revealed no temporal differences in levels of mRNA expression in the salmon liver. This finding does not discount regulation of protein as opposed to transcript level or the potential presence of additional copies or homologs of Rev-erb 1α. Salmonids have undergone two further genome duplication events in comparison to mammals With regard to the temporal regulation and expression of the liver lipid metabolism it was necessary to determine if Rev-erb 1α was shown to regulate the expression of Srebps and its target genes Srebp1 was observed in the salmon liver despite the lack of rhythmic expression of Rev-erb 1α, which may infer protein level or non- Rev-erb 1α regulation of the pathway. Although Srebp1 target genes did not similarly display significant rhythmic expression, the peak expression of Srebp1 at ZT 14∶00 was coincidental with higher expression of several genes including D6 Fad, Elovl5a, Fas, Cpt1 and Aco, all known to be target genes of Srebp1 in mammals One of the most interesting findings of the present study was the strong rhythmicity displayed by the transcription factors. Of the 31 genes examined in the present study, 9 followed a rhythmic pattern in Atlantic salmon liver, with transcription factors representing the most consistent group (four out of five genes). Although precisely how the circadian clock acts to control metabolic rhythms is still unclear, for instance, Ppar expression showed rhythmic variation as described for mammals Pparα and γ expression followed a rhythmic pattern, with Pparα reaching a peak at ZT 14∶00 concurrently with Srebps, whereas Pparγ peaked at ZT 9∶00 which contrasts to the results of Huang et al. El and ApoCII, two genes involved in lipoprotein metabolism, appeared to be linked to lipid availability. Thus, an increase in the expression of El, a phospholipid and triacylglycerol hydrolysing enzyme, was observed during the dark phase, a period when feeding is low and release of lipid from lipoproteins is likely required. In contrast, ApoCII, which is important in the formation of very-low density lipoproteins, is higher at the middle of the light phase when there is greatest feeding and thus high plasma lipid levels promoting liver lipoprotein production. The physical drivers of rhythmic expression in both the clock genes as well as lipid metabolism remain to be determined, however it is likely that either photoperiod, feed availability or an interaction of the two will control the expression patterns observed. Interestingly in sea bream, while Vera et al. The PPARs family members are known to regulate lipid metabolism and energy homeostasis in several teleost species Lxr, which reached its zenith at dusk when both Srebp1 and 2 were at their nadir. Mammalian Lxrα is activated by binding oxysterols (cholesterol metabolites) arising from increased intracellular cholesterol Lxr transcript could be related to the daily rhythm of cholesterol biosynthesis in the salmon liver, displaying higher de novo production during the dark phase when there is a fasting state, as reported for humans Another transcription factor that displayed a significant daily rhythm was Hmgcr), the rate-limiting enzyme in cholesterol biosynthesis Hmgcr acrophase was reached at ZT 10∶00, whereas Srebp1 acrophase occurred three hours later, inconsistent with Hmgcr being a Srebp target gene in this species. In agreement with the present data, recent studies, both in vivo and in vitro, have shown that this pathway is likely to be regulated differently in salmon compared to mammals Hmgcr and Lxr, as similarly described for mammals In addition, when intracellular levels of cholesterol are low, SREBPs are cleaved and released to act as transcription factors. In mammalian systems SREBPs accumulate in the nucleus and trigger the synthesis of HMG-CoA reductase (Ipi), an enzyme in the cholesterol synthesis pathway from mevalonate pyrophosphate to farnesyl pyrophosphate, displayed a rhythmic expression, reaching its peak at around ZT 9∶00. This enzyme did not follow the tendency observed by Srebps, Lxr or Cyp71a, but it must be noted that each one of the synthetic steps is under rigid negative feedback regulation by some intermediate substrates and not only by the final product, cholesterol. This could also explain why the other cholesterol metabolism genes Mev, Dhcr7 and Abca1 show different expression profiles, depending on which step is being promoted at that moment.In mammals, the mechanisms involved in the conversion of cholesterol to bile acid appear to be under a degree of daily regulation via REV-ERB 1α Overall the current study provided clear evidence for the conservation of rhythmic daily regulation of liver lipid metabolism in teleosts as has been reported in mammals In conclusion, the current study has provided the first evidence for the daily expression of genes involved in cholesterol and lipid homeostasis in the liver of Atlantic salmon under an LD cycle. Transcription factors appear to present a strong rhythmic expression, which could indicate their role as synchronisers. However, the expression of some target genes did not display a significant daily expression, denoting that this activation pathway may differ among mammals and teleosts or that other entraining factors may regulate their expression in liver. These findings provide the basis towards understanding the role of the circadian clock in the regulation of lipid metabolism in teleost fish and provide a novel approach to improve fish aquaculture by optimising feeding protocols and/or environmental conditions to match fish lipid metabolism rhythms.Figure S1Alignment of the deduced protein sequence for Atlantic salmon REV-ERB 1α along with tilapia, zebrafish, as well as human. The conserved amino acids are shaded in grey. Predicted DNA binding domain (top) and ligand binding domain (bottom) identified using a CDD search (TIF)Click here for additional data file.Figure S2Phylogenetic analysis of the deduced amino acid sequence for REV-ERB 1α in relation to other vertebrate REV-ERB 1α and REV-ERB 1β sequences. The evolutionary history was inferred using the neighbour-joining method (TIF)Click here for additional data file.Table S1Abbreviation, full name and function of all genes investigated.(DOCX)Click here for additional data file.Table S2Primer pairs and sequences for Rev-erb1α identification including primer name, purpose, sequence and annealing temperature.(DOCX)Click here for additional data file.Table S3Primers used for qRT-PCR.(DOCX)Click here for additional data file.


Apodemus sylvaticus) and field voles (Microtus agrestis), detectable at a low frequency in bank voles (Myodes glareolus), but absent from house mice (Mus musculus). The viruses identified have a genomic organization consistent with other anelloviruses, but form two clear phylogenetic groups that are as distinct from each other as from defined genera.Anelloviruses are a family of small circular ssDNA viruses with a vast genetic diversity. Human infections with the prototype anellovirus, torque teno virus (TTV), are ubiquitous and related viruses have been described in a number of other mammalian hosts. Despite over 15 years of investigation, there is still little known about the pathogenesis and possible disease associations of anellovirus infections, arising in part due to the lack of a robust cell culture system for viral replication or tractable small-animal model. We report the identification of diverse anelloviruses in several species of wild rodents. The viruses are highly prevalent in wood mice ( Anelloviridae are now considered to be virtually ubiquitous , field voles (Microtus agrestis), bank voles (Myodes glareolus) and house mice (Mus musculus) from the UK using a sequence-independent rolling circle amplification (RCA) method combined with traditional restriction digest/cloning that has previously been applied for the identification of novel circular DNA viral species  to an uncultured anellovirus database entry (GenBank accession number HQ335012.1). Two sequences from the serum-derived library from the same mouse also had identical sequences of 86 nt with low similarity (E = 1.3) to a TTMV isolate (GenBank accession number AB303565.1) and a TTV sequence from a macaque (GenBank accession number AB041958.2). These four sequences were provisionally designated rodent TTV (RoTTV).In order to screen wild rodent populations for anelloviruses, six RCA libraries were constructed: two from wild house mice spleens, two from wild wood mice sera, and one each from a wild wood mouse spleen and a laboratory mouse spleen. A number of colonies from each library were screened by PCR using plasmid-specific primers for the amplification of inserted sequences . AmplicoUsing opposite polarity primers based on these sequences , the entire remaining genome was amplified by PCR using the RCA template from the original source samples. The amplicons were then cloned and sequenced. Construction and analysis of these two genome clones  showed that they were of a size consistent with previously described TTMV genomes (2237 and 2235 nt) and resembled known anelloviruses in genomic organization.n = 30, Pentlands n = 18, Cheshire n = 64 and Edinburgh n = 10), but no significant difference was seen.The RoTTV599 and RoTTV664 genome clones were found to have sequences in the UTR that were partially conserved in previously described anelloviruses. Primers based on these sequences . Following removal of primer sequences, the inserts were found to measure 71–78 bp and showed substantial sequence divergence . Based oGiven the generally high detection frequency of anellovirus sequences in wood mice and the two vole species, the lack of detection in house mice was unexpected. To broaden the testing of this species, the source of house mice tested was expanded to include a further 29 samples . All 29 samples tested negative using the PanTTV PCR assay. To further test the possibility that an anellovirus with a UTR sequence that is not detectable using this assay may have been present, an additional five RCA clone libraries were generated from wild house mice samples. Sequencing of 102 colonies from these libraries revealed no anellovirus matches.Inverse primers, based on common cloned UTR sequences, were designed for the amplification of full-length RoTTV genomes from the four identified sets . DNA extracted from the liver, spleen, serum and/or faecal supernatants of seven PanTTV PCR-positive animals  was amplified by RCA followed by PCR amplification with type-specific primers. Amplicons from the RoTTV1_inv  and RoTTV2_inv PCRs were ~2.2 and 2.5 kpb, respectively. A total of 15 RoTTV1 and 13 RoTTV2 genome clones were fully sequenced and included in the subsequent analysis along with the two original clones (GenBank accession numbers KJ194604–KJ194633). The RoTTV sequences were aligned with published TTV sequences in the UTR and numbered accordingly. In two wood mice, AS_1012 and AS_1014, it was possible to sequence genome clones from both spleen tissue and faecal supernatants. RoTTV1 and RoTTV2 clones generated from the different samples in these animals showed up to 99.8 % identity, indicating that anellovirus sequences found in faeces can be representative of those present in tissue and additionally that RoTTV could potentially be spread by the faecal–oral route.A representative genomic map, showing major ORFs, of the 15 RoTTV1 clones and two original clones is shown in blastp analysis of the translated amino acid sequences encoded by the ORFs positionally equivalent to ORF2 and ORF1 showed close similarity to these coding regions. The other major potential coding regions  showed no identifiable homology to sequences in the protein database and, unlike RoTTV1 ORF3 and ORF4, did not contain a start codon. It is predicted that these ORFs would be expressed through splicing with ORF2 and ORF1 as has been shown in other anelloviruses  were used for subsequent phylogenetic and pairwise-comparison analysis. A phylogenetic tree containing all RoTTVs and representative sequences from the 11 currently classified anellovirus genera  is shown in n = 129, TTMV n = 14, TTMDV n = 21) and RoTTVs  are shown in The translated RoTTV ORF1 sequences, along with 164 anellovirus ORF1 sequences available in GenBank, were aligned using Based on the complete genome sequences, two sets of specific nested primers were constructed based on sequences distinct between RoTTV1 and RoTTV2 in the ORF1 coding region . All wild rodent DNA samples were screened using these specific PCRs . RoTTV1 A total of 21 samples  were positive using the type-specific PCRs that were previously negative with the PanTTV PCR. In these cases, it was likely that the higher detection rate of the type-specific primers allowed for the detection of lower-titre viruses. In seven samples that were previously found to be PanTTV-positive , no detection of RoTTV1 or RoTTV2 could be found, suggesting that further divergent RoTTVs may be present.BstUI restriction enzyme was chosen for the digestion of RCA-amplified DNA as it has a four-base recognition site and should therefore cut more frequently than more commonly used six-base cutters (approximately once every 256 bp versus once every 4096 bp in a random sequence). Whilst lacking the depth of coverage provided by next-generation sequencing, we have clearly supported previous findings that, with appropriate sample enrichment, this method has the ability to identify such novel sequences following screening of a modest number of colonies and at a fraction of the cost.The amplification of viral genomes by RCA has become increasingly widely used since its first reported application in 2004  and other wild mammalian populations tested, including wild boar (84 %)  there is a high rate of infection, at least in the wood mouse and field vole species; (ii) the presence of multiple genotypes of virus or even multiple species/genera can be found in a single individual at a given time; and (iii) the presence of viral DNA can be found in multiple sites in an individual. Our population studies focussed on detection in spleen and liver tissue. Although these tissues are generally not currently considered as sites of viral replication, their use for the detection of anellovirus DNA has been well documented (Mus musculus) prove to be unproductive, it should still be possible to experimentally infect laboratory-bred wood mice to give a tractable animal model. Such infections would allow for the direct investigation into a number of unanswered or contentious questions in anellovirus infection, including transmission routes, persistence, viral species differences, pathogenesis and disease associations.Studies into the basic virology, pathogenesis and disease associations of human TTV have been limited by a number of complicating factors, including the high degree of genetic variability leading to many false-negative tests, the difficulty in identification of negative control populations and the lack of a robust cell culture system for viral replication. Given the broad range of laboratory reagents and background knowledge available for studies in rodents, we believe that RoTTV will prove a valuable resource for anellovirus research. Should experimental infection of the well-studied laboratory mouse strains  and Scotland (Pentlands and Borders) as part of DEFRA  project SE01526 (−1) in lysis buffer  at 53 °C overnight. Total nucleic acids from crude lysates were extracted using standard phenol : chloroform : isoamyl alcohol extraction methods and concentrated using ethanol precipitation. Samples were carefully resuspended in TE buffer using broad-ended tips and avoiding vortexing to minimize shearing of genomic DNA. For the extraction of DNA from faecal samples, three to five faecal pellets were first incubated with 200 µl PBS, and mixed by inversion and vortexing for 5 min. Samples were pelleted by centrifugation at 15 000 g for 5 min. DNA was extracted from the supernatants using the QIAamp DNA Blood Mini kit (Qiagen) following the manufacturer’s instructions.Brain, spleen and serum samples from rodents were digested using Proteinase K  according to the manufacturer’s instructions. To prevent contamination, all samples were fractionated on individual gels with fresh buffer in an electrophoresis tank that was cleaned thoroughly with 10 % MicroSol3 solution and rinsed with distilled HRCA was performed using the Repli-G Mini kit (Qiagen) according to the manufacturer’s instructions, with the exceptions that Phi-29 polymerase (NEB) was used in place of the supplied enzyme, as we had previously observed marginally better amplified product yield with the NEB enzyme, and the denaturation step prior to amplification was excluded to select for ssDNAs. Between 10 and 100 ng total nucleic acid extracted from serum or size-fractionated nucleic acid from spleen or brain tissue was used as template for the RCA reactions.BstUI restriction endonuclease (NEB) for 4 h and terminal phosphates were removed using Antarctic phosphatase (NEB) according to the manufacturer’s instructions. Digested fragments were ligated into the pCR-Blunt II-TOPO vector (Life Technologies) and these ligation reactions were used to transform TOP 10 F′ chemically competent Escherichia coli which were plated on LB/Agar plates supplemented with 50 µg kanamycin ml−1. Amplicons from PCRs were ligated into the pGEM-T Easy vector (Promega) and these ligation reactions were used to transform TOP 10 F′ chemically competent E. coli, which were plated on LB/Agar plates supplemented with 100 µg ampicillin, 0.5 µM IPTG and 80 µg X-Gal ml−1.RCA DNA samples were digested with Nested and hemi-nested PCRs for RoTTV ORF1 and PanTTV screening as well as single-round PCR for species identification were performed using GoTaq DNA polymerase (Promega) and primers listed in Table S1. Reactions were performed using 0.5 µg samples of extracted nucleic acid as template under the following conditions: 30 cycles of 18 s at 94 °C, 21 s at 50 °C and 60 s at 72 °C, and a final extension of 5 min at 72 °C.Taq High Fidelity (Life Technologies). Reactions were performed using 10× AccuPrime PCR Buffer I, 1 µl amplified DNA by RCA as template and the inverted primers shown in Table S1, and cycled under the following condition: 30 cycles of 18 s at 94 °C, 21 s at 50 °C and 3 min at 72 °C, and a final extension of 5 min at 72 °C.Full-length PCR were carried out using AccuPrime For colony testing, primers specific for the M13F and M13R sites located on opposite sides of the multiple cloning site of the pCR-Blunt II-TOPO and pGEM-T Easy vectors were used. Plasmid-containing colonies were picked from LB/Agar plates directly into PCR master mix. Reactions for screening clones were performed under the following conditions: initial bacterial lysis/denaturation 2 min at 94 °C, 30 cycles of 18 s at 94 °C, 30 s at 50 °C and 60 s at 72 °C, and a final extension of 5 min at 72 °C. Reactions for full-length genome clones were performed under the following conditions: initial bacterial lysis/denaturation 2 min at 94 °C, 30 cycles of 18 s at 94 °C, 30 s at 50 °C and 3 min at 72 °C, and a final extension of 5 min at 72 °C.blastn or blastx).PCR amplicons were sequenced using either the M13F primer used in the colony screening or both Mt_F and Mt_R primers for species identification. Further sequencing of full-length genome clones was performed by primer walking. Sequencing was carried out using BigDye Terminator v3.1 (Applied Biosystems) according to the manufacturer’s instructions. Sequences were read by Edinburgh Genomics. Sequences, with vector nucleotides removed, were submitted for analysis using the NCBI  Basic Local Alignment Search Tool for nucleotide or translated sequence homology (sse v1.1 (sse v1.1 software or NCBI ORF Finder, were submitted for analysis using NCBI protein blast. Phylogenetic trees were reconstructed using maximum-likelihood methods as implemented in the mega6 software package (Sequence analysis and assembly was performed using sse v1.1 . Protein


The next-generation sequencing revolution has substantially increased our understanding of the mutated genes that underlie complex neurodevelopmental disease. Exome sequencing has enabled us to estimate the number of genes involved in the etiology of neurodevelopmental disease, whereas targeted sequencing approaches have provided the means for quick and cost-effective sequencing of thousands of patient samples to assess the significance of individual genes. By leveraging such technologies and clinical exome sequencing, a genotype-first approach has emerged in which patients with a common genotype are first identified and then clinically reassessed as a group. This approach has proven a powerful methodology for refining disease subtypes. We propose that the molecular characterization of these genetic subtypes has important implications for diagnostics and also for future drug development. Classifying patients into subgroups with a common genetic etiology and applying treatments tailored to the specific molecular defect they carry is likely to improve management of neurodevelopmental disease in the future. Neurodevelopmental disorders (NDs) refer to a complex collection of phenotypes that encompass clinically recognizable disorders such as autism spectrum disorders (ASD), intellectual disability (ID), epilepsy and schizophrenia. The diagnosis of NDs has classically fallen within the clinical realm. The diagnosis of epilepsy is somewhat quantitative, with the frequency, onset and family history of seizure events being considered for classification , whereas2] = 40–80 % [2 = 70–88 % [2 = 64–81 % [Earlier versions of the DSM included phenotypic subtypes for many mental health disorders that have since been eliminated owing to inconsistent diagnoses between clinicians. However, the study of these disorders, ASD and ID in particular, has shown that disease subtypes do exist  . Twin st 40–80 % , h2 = 70 64–81 % , respect 64–81 % , whereas 64–81 %  and 3.7– 64–81 % . Phenoty 64–81 % .SYNGAP1, ARID1B and ADNP, are likely to contribute to both ASD and ID, whereas mutations in genes such as STXBP1 and WDR45 might contribute to ID and epilepsy but not ASD  of families have highlighted the importance of rare, de novo gene-disruptive mutations in the genetic etiology of NDs. These studies frequently implicated the same copy number variant, biochemical pathway or even the same gene as an underlying factor of seemingly diverse clinical and etiological outcomes Table . One claThe goal of this Opinion is to review advances in the discovery of candidate genes based on next-generation sequencing of patients and the impact of these advances on refining specific subtypes of ND. Linking genotypes to deep clinical phenotypes  is providing important insight into ND risk gene models –18. We pCHD8, ADNP and DYRK1A [The affordable application of next-generation sequencing in the clinical and research arenas has rapidly increased our understanding of the genetic variation that underlies NDs. Exome and targeted sequencing studies of patients with ND have revealed dozens of new genes emerging as high-risk candidate loci in recent years Table . WES seqd DYRK1A  among ASp < 10-6) of the Fisher’s exact test p value are indeed significant for recurrent de novo mutation burden — such as GRIN2B, which has a de novo p value of 0.001 after correction. Therefore, although some genes  reach only nominal significance for an overall increased burden in disruptive mutations in ND cases compared with unaffected controls, based on a de novo model they may prove to be bona fide ND risk genes.We combined the results of multiple published WES, WGS and targeted sequencing studies including 5001–5922 individuals with ASD  , 23–28, The discovery of recurrently mutated genes has been used to successfully identify additional patients with disruptive mutations in these risk genes who, when collectively phenotyped, define new syndromic and sub-syndromic forms of ND –18. ThesCHD8 is an ASD-associated gene linked with macrocephaly and gastrointestinal dysfunction [ADNP mutations are associated with ASD and the complete loss of expressive language [ARID1B, ANKRD11, CTNNB1, STXBP1 and CHAMP1). SCN1A mutations have been primarily observed in epilepsy [CHD2 and DYRK1A), often with very specific clinical manifestations  and FMRP targets in ASD, ID and epilepsy (p < 0.00001) [Beyond genetic subtypes, network-based approaches that more globally predict the effects of ND risk genes on molecular pathways have repeatedly shown an enrichment for synapse function and gene transcription/chromatin remodeling , 39. AltSYNGAP1, SCN2A, STXBP1, GRIN2B and SCN1A  [Studies of simplex ASD and ID families have highlighted an enrichment for gene-disruptive mutations in transcription and chromatin remodeling pathways  , 39, 45. defects . Some ND [ARID1B  and CHD81B [CHD8 , which h1B [CHD8 , 50   (Table 1 (1–3 %) .TSC and PTEN have also been implicated in tumorigenesis and ND owing to their role in transcription and cell growth [TSC mutations [Mutations in the mTOR pathway involving genes such as l growth . Rapalogutations . SimilarThe success of the genotype-first approach for subtyping NDs can be primarily attributed to technological advances that make WES and targeted sequencing fast and cost-effective. ND candidate gene discovery can be maximized by combining many datasets from overlapping conditions  to (1) increase the genetic evidence supporting individual ND risk gene models, (2) build stronger molecular interaction networks that implicate specific pathways in disease biology and (3) assess the robustness of genotype–phenotype links. Beyond providing a potential genetic explanation for disease to families, our understanding of the biological pathways that are disrupted by specific variants is leading to improved assessment of disease risk in families and to the prospect of tailored treatments for patients with these debilitating diseases.