Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

A two-stages global sensitivity analysis by using the δ sensitivity index in presence of correlated inputs: application on a tumor growth inhibition model based on the dynamic energy budget theory.

Global sensitivity analysis (GSA) evaluates the impact of variability and/or uncertainty of the model parameters on given model outputs. GSA is useful for assessing the quality of Pharmacometric model inference. Indeed, model parameters can be affected by high (estimation) uncertainty due to the sparsity of data. Independence between model parameters is a common assumption of GSA methods. However, ignoring (known) correlations between parameters may alter model predictions and, then, GSA results. To address this issue, a novel two-stages GSA technique based on the δ index, which is well-defined also in presence of correlated parameters, is here proposed. In the first step, statistical dependencies are neglected to identify parameters exerting causal effects. Correlations are introduced in the second step to consider the real distribution of the model output and investigate also the 'indirect' effects due to the correlation structure. The proposed two-stages GSA strategy was applied, as case study, to a preclinical tumor-in-host-growth inhibition model based on the Dynamic Energy Budget theory. The aim is to evaluate the impact of the model parameter estimate uncertainty (including correlations) on key model-derived metrics: the drug threshold concentration for tumor eradication, the tumor volume doubling time and a new index evaluating the drug efficacy-toxicity trade-off. This approach allowed to rank parameters according to their impact on the output, discerning whether a parameter mainly exerts a causal or 'indirect' effect. Thus, it was possible to identify uncertainties that should be necessarily reduced to obtain robust predictions for the outputs of interest.

Insulin-like Growth Factor 1, Growth Hormone, and Anti-Müllerian Hormone Receptors Are Differentially Expressed during GnRH Neuron Development.

Gonadotropin-releasing hormone (GnRH) neurons are key neuroendocrine cells in the brain as they control reproduction by regulating hypothalamic-pituitary-gonadal axis function. In this context, anti-Müllerian hormone (AMH), growth hormone (GH), and insulin-like growth factor 1 (IGF1) were shown to improve GnRH neuron migration and function in vitro. Whether AMH, GH, and IGF1 signaling pathways participate in the development and function of GnRH neurons in vivo is, however, currently still unknown. To assess the role of AMH, GH, and IGF1 systems in the development of GnRH neuron, we evaluated the expression of AMH receptors (AMHR2), GH (GHR), and IGF1 (IGF1R) on sections of ex vivo mice at different development stages. The expression of AMHR2, GHR, and IGF1R was assessed by immunofluorescence using established protocols and commercial antibodies. The head sections of mice were analyzed at E12.5, E14.5, and E18.5. In particular, at E12.5, we focused on the neurogenic epithelium of the vomeronasal organ (VNO), where GnRH neurons, migratory mass cells, and the pioneering vomeronasal axon give rise. At E14.5, we focused on the VNO and nasal forebrain junction (NFJ), the two regions where GnRH neurons originate and migrate to the hypothalamus, respectively. At E18.5, the median eminence, which is the hypothalamic area where GnRH is released, was analyzed. At E12.5, double staining for the neuronal marker ß-tubulin III and AMHR2, GHR, or IGF1R revealed a signal in the neurogenic niches of the olfactory and VNO during early embryo development. Furthermore, IGF1R and GHR were expressed by VNO-emerging GnRH neurons. At E14.5, a similar expression pattern was found for the neuronal marker ß-tubulin III, while the expression of IGF1R and GHR began to decline, as also observed at E18.5. Of note, hypothalamic GnRH neurons labeled for PLXND1 tested positive for AMHR2 expression. Ex vivo experiments on mouse sections revealed differential protein expression patterns for AMHR2, GHR, and IGF1R at any time point in development between neurogenic areas and hypothalamic compartments. These findings suggest a differential functional role of related systems in the development of GnRH neurons.

Targeted Plasma Proteomics to Predict the Development of Carotid Plaques.

BACKGROUND: Cardiovascular risk stratification in primary prevention is a clinical challenge. We recently identified a large set of circulating proteins improving the risk prediction for cardiovascular events. We now evaluate which of these proteins predicts the development of subclinical carotid atherosclerosis (SCA) in primary cardiovascular prevention. METHODS: Three hundred sixty-eight proteins were quantified, by proximity extension assay, from the plasma collected at basal visit from 586 subjects without previous cardiovascular events and without preclinical atherosclerosis. These subjects were reevaluated 11 years after median follow-up (10-12) in a longitudinal observational analysis, to assess the development of SCA, defined as the formation of focal lesion in any carotid tract and detected by carotid ultrasound at basal visit and after follow-up. Common carotid (intima-media thickness [IMT]) was also measured by ultrasound during the same follow-up to identify subjects with faster common carotid intima-media thickness (IMT) progression (increase IMT)>1.3 mm in the common carotid tract). RESULTS: The variation of 68 proteins predicted SCA development and, among them, higher levels of PIgR2 (polymeric immunoglobulin receptor), chemokine (C-C motif) ligand 18, CA1 (carbonic anhydrase 1), Fc gamma receptor IIa and reduced MMP10 (matrix metallopeptidase 10), GT (gastrotropin), IL7R (interleukin 7 receptor) were the most predictive for SCA development. These 7 proteins improved the sensitivity and the specificity for SCA development versus risk factors (age, sex, overweight, hypertension, low HDL-cholesterol, high triglyceride); area under the curve: 0.747 ([0.707-0.784] versus 0.620 [0.577-0.663]; P<0.001). Vice versa, 25 proteins (not in common with the previous 68) predicted faster common carotid IMT progression. Among them, increased IL7D (interleukin 7), chemokine (C-X-C motif) ligand 1, and reduced TNFS13B (TNF superfamily member 13b) significantly increased the sensitivity and the specificity to predict faster common carotid IMT progression as compared with same risk factors (area under the curve: 0.719 [0.680-0.756] versus 0.569 [0.527-0.610]; P<0.001). CONCLUSIONS: A new set of circulating proteins have been identified that may be considered as markers of preclinical atherosclerosis development. The difference of the protein identified to predict SCA versus IMT progression may reflect different etiological factors.

Clinical practice gaps and challenges in non-alcoholic steatohepatitis care: An international physician needs assessment.

BACKGROUND AND AIMS: Even as several pharmacological treatments for non-alcoholic steatohepatitis (NASH) are in development, the incidence of NASH is increasing on an international scale. We aim to assess clinical practice gaps and challenges of hepatologists and endocrinologists when managing patients with NASH in four countries (Germany/Italy/United Kingdom/United States) to inform educational interventions. METHODS: A sequential mixed-method design was used: qualitative semi-structured interviews followed by quantitative online surveys. Participants were hepatologists and endocrinologists practising in one of the targeted countries. Interview data underwent thematic analysis and survey data were analysed with chi-square and Kruskal-Wallis tests. RESULTS: Most interviewees (n = 24) and surveyed participants (89% of n = 224) agreed that primary care must be involved in screening for NASH, yet many faced challenges involving and collaborating with them. Endocrinologists reported low knowledge of which blood markers to use when suspecting NASH (56%), when to order an MRI (65%) or ultrasound/FibroScan® (46%), and reported sub-optimal skills interpreting alanine aminotransferase (ALT, 37%) and aspartate aminotransferase (AST, 38%) blood marker test results, causing difficulty during diagnosis. Participants believed that more evidence is needed for upcoming therapeutic agents; yet, they reported sub-optimal knowledge of eligibility criteria for clinical trials. Knowledge and skill gaps when managing comorbidities, as well as skill gaps facilitating patient lifestyle changes were reported. CONCLUSIONS: Educational interventions are needed to address the knowledge and skill gaps identified and to develop strategies to optimize patient care, which include implementing relevant care pathways, encouraging referrals and testing, and multidisciplinary collaboration, as suggested by the recent Global Consensus statement on NAFLD.

Characterisation of individual ferritin response in patients receiving chelation therapy.

AIMS: To develop a drug-disease model describing iron overload and its effect on ferritin response in patients affected by transfusion-dependent haemoglobinopathies and investigate the contribution of interindividual differences in demographic and clinical factors on chelation therapy with deferiprone or deferasirox. METHODS: Individual and mean serum ferritin data were retrieved from 13 published studies in patients affected by haemoglobinopathies receiving deferiprone or deferasirox. A nonlinear mixed effects modelling approach was used to characterise iron homeostasis and serum ferritin production taking into account annual blood consumption, baseline demographic and clinical characteristics. The effect of chelation therapy was parameterised as an increase in the iron elimination rate. Internal and external validation procedures were used to assess model performance across different study populations. RESULTS: An indirect response model was identified, including baseline ferritin concentrations and annual blood consumption as covariates. The effect of chelation on iron elimination rate was characterised by a linear function, with different slopes for each drug (0.0109 [90% CI: 0.0079-0.0131] vs. 0.0013 [90% CI: 0.0008-0.0018] L/mg mo). In addition to drug-specific differences in the magnitude of the ferritin response, simulation scenarios indicate that ferritin elimination rates depend on ferritin concentrations at baseline. CONCLUSION: Modelling of serum ferritin following chronic blood transfusion enabled the evaluation of drug-induced changes in iron elimination rate and ferritin production. The use of a semi-mechanistic parameterisation allowed us to disentangle disease-specific factors from drug-specific properties. Despite comparable chelation mechanisms, deferiprone appears to have a significantly larger effect on the iron elimination rate than deferasirox.

Functional genomics meta-analysis to identify gene set enrichment networks in cardiac hypertrophy.

In order to take advantage of the continuously increasing number of transcriptome studies, it is important to develop strategies that integrate multiple expression datasets addressing the same biological question to allow a robust analysis. Here, we propose a meta-analysis framework that integrates enriched pathways identified through the Gene Set Enrichment Analysis (GSEA) approach and calculates for each meta-pathway an empirical p-value. Validation of our approach on benchmark datasets showed comparable or even better performance than existing methods and an increase in robustness with increasing number of integrated datasets. We then applied the meta-analysis framework to 15 functional genomics datasets of physiological and pathological cardiac hypertrophy. Within these datasets we grouped expression sets measured at time points that represent the same hallmarks of heart tissue remodeling ('aggregated time points') and performed meta-analysis on the expression sets assigned to each aggregated time point. To facilitate biological interpretation, results were visualized as gene set enrichment networks. Here, our meta-analysis framework identified well-known biological mechanisms associated with pathological cardiac hypertrophy (e.g., cardiomyocyte apoptosis, cardiac contractile dysfunction, and alteration in energy metabolism). In addition, results highlighted novel, potentially cardioprotective mechanisms in physiological cardiac hypertrophy involving the down-regulation of immune cell response, which are worth further investigation.

Leptin, Resistin, and Proprotein Convertase Subtilisin/Kexin Type 9: The Role of STAT3.

In a condition of dysfunctional visceral fat depots, as in the case of obesity, alterations in adipokine levels may be detrimental for the cardiovascular system. The proinflammatory leptin and resistin adipokines have been described as possible links between obesity and atherosclerosis. The present study was aimed at evaluating whether proprotein convertase subtilisin/kexin type 9 (PCSK9), a key regulator of low-density lipoprotein metabolism, is induced by leptin and resistin through the involvement of the inflammatory pathway of STAT3. In HepG2 cells, leptin and resistin up-regulated PCSK9 gene and protein expression, as well as the phosphorylation of STAT3. Upon STAT3 silencing, leptin and resistin lost their ability to activate PCSK9. The knockdown of STAT3 did not affect the expression of leptin and resistin receptors or that of PCSK9. The analysis of the human PCSK9 promoter region showed that the two adipokines raised PCSK9 promoter activity via the involvement of a sterol regulatory element motif. In healthy males, a positive association between circulating leptin and PCSK9 levels was found only when the body mass index was <25 kg/m2. In conclusion, this study identified STAT3 as one of the molecular regulators of leptin- and resistin-mediated transcriptional induction of PCSK9.

Anti-Müllerian Hormone, Growth Hormone, and Insulin-Like Growth Factor 1 Modulate the Migratory and Secretory Patterns of GnRH Neurons.

Anti-Müllerian hormone (AMH) is secreted by Sertoli or granulosa cells. Recent evidence suggests that AMH may play a role in the pathogenesis of hypogonadotropic hypogonadism (HH) and that its serum levels could help to discriminate HH from delayed puberty. Moreover, the growth hormone (GH)/insulin-like growth factor 1 (IGF1) system may be involved in the function of gonadotropin-releasing hormone (GnRH) neurons, as delayed puberty is commonly found in patients with GH deficiency (GHD) or with Laron syndrome, a genetic form of GH resistance. The comprehension of the stimuli enhancing the migration and secretory activity of GnRH neurons might shed light on the causes of delay of puberty or HH. With these premises, we aimed to better clarify the role of the AMH, GH, and IGF1 on GnRH neuron migration and GnRH secretion, by taking advantage of previously established models of immature (GN11 cell line) and mature (GT1-7 cell line) GnRH neurons. Expression of Amhr, Ghr, and Igf1r genes was confirmed in both cell lines. Cells were then incubated with increasing concentrations of AMH (1.5-150 ng/mL), GH (3-1000 ng/mL), or IGF1 (1.5-150 ng/mL). All hormones were able to support GN11 cell chemomigration. AMH, GH, and IGF1 significantly stimulated GnRH secretion by GT1-7 cells after a 90-min incubation. To the best of our knowledge, this is the first study investigating the direct effects of GH and IGF1 in GnRH neuron migration and of GH in the GnRH secreting pattern. Taken together with previous basic and clinical studies, these findings may provide explanatory mechanisms for data, suggesting that AMH and the GH-IGF1 system play a role in HH or the onset of puberty.

BDNF Val66Met polymorphism alters food intake and hypothalamic BDNF expression in mice.

Obesity, a rising public health burden, is a multifactorial disease with an increased risk for patients to develop several pathological conditions including type 2 diabetes mellitus, hypertension, and cardiovascular disease. Increasing evidence suggests a relationship between the human brain-derived neurotrophic factor (BDNF) Val66Met single-nucleotide polymorphism (SNP) and obesity, although the underlying mechanisms of this connection are still not completely understood. In the present study, we found that homozygous knock-in BDNFMet/Met mice were overweight and hyperphagic compared to wildtype BDNFVal/Val mice. Increased food intake was associated with reduction of total BDNF and BDNF1, BDNF4 and BDNF6 transcripts in the hypothalamus of BDNFMet/Met mice. In contrast, in the white adipose tissue total BDNF and Glut4 expression levels were augmented, while sirtuin 1 and leptin receptor (Ob-R) expression levels were reduced in BDNFMet/Met mice. Moreover, plasmatic leptin levels were decreased in BDNFMet/Met mice. However, BDNFVal/Val and BDNFMet/Met mice showed a similar response to the insulin tolerance test and glucose tolerance test. Altogether, these results suggest that BDNF Val66Met SNP strongly contributes to adipose tissue pathophysiology, resulting in reduced circulating leptin levels and hypothalamic expression of BDNF, which, in turn, promote increased food intake and overweight in BDNFMet/Met mice.

Multifactorial Activation of NLRP3 Inflammasome: Relevance for a Precision Approach to Atherosclerotic Cardiovascular Risk and Disease.

Chronic low-grade inflammation, through the specific activation of the NACHT leucine-rich repeat- and PYD-containing (NLRP)3 inflammasome-interleukin (IL)-1ß pathway, is an important contributor to the development of atherosclerotic cardiovascular disease (ASCVD), being triggered by intracellular cholesterol accumulation within cells. Within this pathological context, this complex pathway is activated by a number of factors, such as unhealthy nutrition, altered gut and oral microbiota, and elevated cholesterol itself. Moreover, evidence from autoinflammatory diseases, like psoriasis and others, which are also associated with higher cardiovascular disease (CVD) risk, suggests that variants of NLRP3 pathway-related genes (like NLRP3 itself, caspase recruitment domain-containing protein (CARD)8, caspase-1 and IL-1ß) may carry gain-of-function mutations leading, in some individuals, to a constitutive pro-inflammatory pattern. Indeed, some reports have recently associated the presence of specific single nucleotide polymorphisms (SNPs) on such genes with greater ASCVD prevalence. Based on these observations, a potential effective strategy in this context may be the identification of carriers of these NLRP3-related SNPs, to generate a genomic score, potentially useful for a better CVD risk prediction, and, possibly, for personalized therapeutic approaches targeted to the NLRP3-IL-1ß pathway.

Hydromethanolic Extracts from Adansonia digitata L. Edible Parts Positively Modulate Pathophysiological Mechanisms Related to the Metabolic Syndrome.

Metabolic syndrome includes a cluster of risk factors for many pathological conditions, including hyperglycemia, abdominal obesity, hyperlipidemia, and hypertension. Adansonia digitata L. (also known as baobab) is used in traditional African Medicine and recent studies showed that it improves the metabolism of carbohydrates and lipids. The aim of this study is to investigate the mechanisms of action associated with the beneficial effects of extracts from the edible parts of baobab (fruit pulp, leaves, raw and toasted seeds), evaluating their inhibitory activity against: alpha-amylase, alpha-glucosidase, angiotensin-converting enzyme, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase, and pancreatic lipase. Baobab fruit pulp and leaf extracts resulted to be the most active ones and were then tested on the differentiation process of SW-872 human liposarcoma cells to mature adipocytes. The addition of these latter extracts did not affect triglyceride accumulation, indicating a neutral impact on this parameter. The findings here reported help to explain the growing amount of evidence on the biological properties of baobab and provide suggestions about their use in food and nutraceutical fields.

Bicuspid aortic valve, atherosclerosis and changes of lipid metabolism: Are there pathological molecular links?

Bicuspid aortic valve (BAV) is recognized as a syndrome including aortic valve diseases and aortic wall alterations, such as aortic dilatation, dissection and rupture, but also coronary atherosclerosis. The current evidence, although partially controversial, suggests that several molecular mechanisms promoting atherosclerosis are activated in BAV patients and are involved in the progression of the related diseases, from aortic stenosis to aortopathies, along with altered hemodynamics. Among these factors, dyslipidemia (i.e., high LDL cholesterol, high lipoprotein (a)) and the activation of specific pro-inflammatory pathways (nucleotide-binding oligomerization domain-like receptor containing pyrin domain 3 inflammasome and Toll-like receptor 4) appear to play a pivotal role in the progression of BAV-associated diseases. The further elucidation of such molecular mechanisms may lead to a better and personalized prognosis and follow-up for BAV patients and suggest novel pharmacological approaches to prevent disease progression.

Comprehensive kinome NGS targeted expression profiling by KING-REX.

BACKGROUND: Protein kinases are enzymes controlling different cellular functions. Genetic alterations often result in kinase dysregulation, making kinases a very attractive class of druggable targets in several human diseases. Existing approved drugs still target a very limited portion of the human 'kinome', demanding a broader functional knowledge of individual and co-expressed kinase patterns in physiologic and pathologic settings. The development of novel rapid and cost-effective methods for kinome screening is therefore highly desirable, potentially leading to the identification of novel kinase drug targets. RESULTS: In this work, we describe the development of KING-REX (KINase Gene RNA EXpression), a comprehensive kinome RNA targeted custom assay-based panel designed for Next Generation Sequencing analysis, coupled with a dedicated data analysis pipeline. We have conceived KING-REX for the gene expression analysis of 512 human kinases; for 319 kinases, paired assays and custom analysis pipeline features allow the evaluation of 3'- and 5'-end transcript imbalances as readout for the prediction of gene rearrangements. Validation tests on cell line models harboring known gene fusions demonstrated a comparable accuracy of KING-REX gene expression assessment as in whole transcriptome analyses, together with a robust detection of transcript portion imbalances in rearranged kinases, even in complex RNA mixtures or in degraded RNA. CONCLUSIONS: These results support the use of KING-REX as a rapid and cost effective kinome investigation tool in the field of kinase target identification for applications in cancer biology and other human diseases.

Cow's Milk Consumption and Health: A Health Professional's Guide.

The most recent scientific evidence supports the consumption of cow's milk and dairy products as part of a balanced diet. However, these days, the public and practicing physicans are exposed to a stream of inconsistent (and often misleading) information regarding the relationship between cow's milk intake and health in the lay press and in the media. The purpose of this article, in this context, is to facilitate doctor-patient communication on this topic, providing physicians with a series of structured answers to frequently asked patient questions. The answers range from milk and milk-derived products' nutritional function across the life span, to their relationship with diseases such as osteoporosis and cancer, to lactose intolerance and milk allergy, and have been prepared by a panel of experts from the Italian medical and nutritional scientific community. When consumed according to appropriate national guidelines, milk and its derivatives contribute essential micro- and macronutrients to the diet, especially in infancy and childhood where bone mass growth is in a critical phase. Furthermore, preliminary evidence suggests potentially protective effects of milk against overweight, obesity, diabetes, and cardiovascular disease, while no clear data suggest a significant association between milk intake and cancer. Overall, current scientific literature suggests that an appropriate consumption of milk and its derivatives, according to available nutritional guidelines, may be beneficial across all age groups, with the exception of specific medical conditions such as lactose intolerance or milk protein allergy. Key teaching points: Milk and its derivatives contribute essential micro and macronutrients to the diet, when consumed according to appropriate national guidelines, especially in infancy and childhood where bone mass growth is in a critical phase. Preliminary evidence suggests potentially protective effects of milk against overweight, obesity, diabetes and cardiovascular disease No clear data are available about the association between milk intake and cancer. Current scientific literature suggests that an appropriate consumption of milk and its derivatives may be beneficial at all ages, with the exception of specific medical conditions such as lactose intolerance or milk protein allergy.

Integration of enzymatic data in Bacillus subtilis genome-scale metabolic model improves phenotype predictions and enables in silico design of poly-γ-glutamic acid production strains.

BACKGROUND: Genome-scale metabolic models (GEMs) allow predicting metabolic phenotypes from limited data on uptake and secretion fluxes by defining the space of all the feasible solutions and excluding physio-chemically and biologically unfeasible behaviors. The integration of additional biological information in genome-scale models, e.g., transcriptomic or proteomic profiles, has the potential to improve phenotype prediction accuracy. This is particularly important for metabolic engineering applications where more accurate model predictions can translate to more reliable model-based strain design. RESULTS: Here we present a GEM with Enzymatic Constraints using Kinetic and Omics data (GECKO) model of Bacillus subtilis, which uses publicly available proteomic data and enzyme kinetic parameters for central carbon (CC) metabolic reactions to constrain the flux solution space. This model allows more accurate prediction of the flux distribution and growth rate of wild-type and single-gene/operon deletion strains compared to a standard genome-scale metabolic model. The flux prediction error decreased by 43% and 36% for wild-type and mutants respectively. The model additionally increased the number of correctly predicted essential genes in CC pathways by 2.5-fold and significantly decreased flux variability in more than 80% of the reactions with variable flux. Finally, the model was used to find new gene deletion targets to optimize the flux toward the biosynthesis of poly-γ-glutamic acid (γ-PGA) polymer in engineered B. subtilis. We implemented the single-reaction deletion targets identified by the model experimentally and showed that the new strains have a twofold higher γ-PGA concentration and production rate compared to the ancestral strain. CONCLUSIONS: This work confirms that integration of enzyme constraints is a powerful tool to improve existing genome-scale models, and demonstrates the successful use of enzyme-constrained models in B. subtilis metabolic engineering. We expect that the new model can be used to guide future metabolic engineering efforts in the important industrial production host B. subtilis.

Correction to: Nutraceutical approach for the management of cardiovascular risk - a combination containing the probiotic Bifidobacterium longum BB536 and red yeast rice extract: results from a randomized, double-blind, placebo-controlled study.

Following publication of the original article [1], the authors reported an error in the affiliation of the third author, Sara Gandini. The correct affiliation should read: Division of Epidemiology and Biostatistics, IEO, European Institute of Oncology IRCCS, Milan, Italy.

Nutraceutical approach for the management of cardiovascular risk - a combination containing the probiotic Bifidobacterium longum BB536 and red yeast rice extract: results from a randomized, double-blind, placebo-controlled study.

BACKGROUND: Probiotics incorporated into dairy products have been shown to reduce total (TC) and LDL cholesterolemia (LDL-C) in subjects with moderate hypercholesterolemia. More specifically, probiotics with high biliary salt hydrolase activity, e.g. Bifidobacterium longum BB536, may decrease TC and LDL-C by lowering intestinal cholesterol reabsorption and, combined with other nutraceuticals, may be useful to manage hypercholesterolemia in subjects with low cardiovascular (CV) risk. This study was conducted to evaluate the efficacy and safety of a nutraceutical combination containing Bifidobacterium longum BB536, red yeast rice (RYR) extract (10 mg/day monacolin K), niacin, coenzyme Q10 (Lactoflorene Colesterolo®). The end-points were changes of lipid CV risk markers (LDL-C, TC, non-HDL-cholesterol (HDL-C), triglycerides (TG), apolipoprotein B (ApoB), HDL-C, apolipoprotein AI (ApoAI), lipoprotein(a) (Lp(a), proprotein convertase subtilisin/kexin type 9 (PCSK9)), and of markers of cholesterol synthesis/absorption. METHODS: A 12-week randomized, parallel, double-blind, placebo-controlled study. Thirty-three subjects (18-70 years) in primary CV prevention and low CV risk (SCORE: 0-1% in 24 and 2-4% in 9 subjects; LDL-C: 130-200 mg/dL) were randomly allocated to either nutraceutical (N = 16) or placebo (N = 17). RESULTS: Twelve-week treatment with the nutraceutical combination, compared to placebo, significantly reduced TC (- 16.7%), LDL-C (- 25.7%), non-HDL-C (- 24%) (all p < 0.0001), apoB (- 17%, p = 0.003). TG, HDL-C, apoAI, Lp(a), PCSK9 were unchanged. Lathosterol:TC ratio was significantly reduced by the nutraceutical combination, while campesterol:TC ratio and sitosterol:TC ratio did not change, suggesting reduction of synthesis without increased absorption of cholesterol. No adverse effects and a 97% compliance were observed. CONCLUSIONS: A 12-week treatment with a nutraceutical combination containing the probiotic Bifidobacterium longum BB536 and RYR extract significantly improved the atherogenic lipid profile and was well tolerated by low CV risk subjects. TRIAL REGISTRATION: NCT02689934 .

Irisin and BDNF serum levels and behavioral disturbances in Alzheimer's disease.

Behavioral dysfunctions (BPSD) represent the most important problem in Alzheimer's dementia (AD) management. We assessed the serum levels of two myokines in AD patients, preliminary investigating, as secondary aim, their role as potential biomarkers for agitation/aggression (AA) and aberrant motor behavior (AMB): irisin, since it is able to modify the motor pattern, and BDNF, since it was transcribed following irisin stimulation. Forty AD patients were recruited and characterized according to the expressed neuropsychiatric syndrome. Myokines were measured by ELISA. Irisin serum levels were slightly elevated in AA+ patients (+ 10.0%; p < 0.05) and correlated with the duration of AA (r = 0.74, p < 0.03). BDNF failed to show such differences. We propose that these selected myokines are not useful as surrogate markers for agitation in AD, but might represent interesting secondary outcomes when testing drugs for those BPSD implying elevated motor activity.

Accounting for inter-correlation between enzyme abundance: a simulation study to assess implications on global sensitivity analysis within physiologically-based pharmacokinetics.

Physiologically based pharmacokinetic (PBPK) models often include several sets of correlated parameters, such as organ volumes and blood flows. Because of recent advances in proteomics, it has been demonstrated that correlations are also present between abundances of drug-metabolising enzymes in the liver. As the focus of population PBPK has shifted the emphasis from the average individual to theoretically conceivable extremes, reliable estimation of the extreme cases has become paramount. We performed a simulation study to assess the impact of the correlation between the abundances of two enzymes on the pharmacokinetics of drugs that are substrate of both, under assumptions of presence or lack of such correlations. We considered three semi-physiological models representing the cases of: (1) intravenously administered drugs metabolised by two enzymes expressed in the liver; (2) orally administered drugs metabolised by CYP3A4 expressed in the liver and gut wall; (3) intravenously administered drugs that are substrates of CYP3A4 and OATP1B1 in the liver. Finally, the impact of considering or ignoring correlation between enzymatic abundances on global sensitivity analysis (GSA) was investigated using variance based GSA on a reduced PBPK model for repaglinide, substrate of CYP3A4 and CYP2C8. Implementing such correlations can increase the confidence interval for population pharmacokinetic parameters (e.g., AUC, bioavailability) and impact the GSA results. Ignoring these correlations could lead to the generation of implausible parameters combinations and to an incorrect estimation of pharmacokinetic related parameters. Thus, known correlations should always be considered in building population PBPK models.