Renin-angiotensin-aldosterone system polymorphisms: a role or a hole in occurrence and long-term prognosis of acute myocardial infarction at young age

<p>Abstract</p> <p>Background</p> <p>The renin-angiotensin-aldosterone system (RAAS) is involved in the cardiovascular homeostasis as shown by previous studies reporting a positive association between specific RAAS genotypes and an increased risk of myocardial infarction. Anyhow the prognostic role in a long-term follow-up has not been yet investigated.</p> <p>Aim of the study was to evaluate the influence of the most studied RAAS genetic Single Nucleotide Polymorphisms (SNPs) on the occurrence and the long-term prognosis of acute myocardial infarction (AMI) at young age in an Italian population.</p> <p>Methods</p> <p>The study population consisted of 201 patients and 201 controls, matched for age and sex (mean age 40 ± 4 years; 90.5% males). The most frequent conventional risk factors were smoke (p < 0.001), family history for coronary artery diseases (p < 0.001), hypercholesterolemia (p = 0.001) and hypertension (p = 0.002). The tested genetic polymorphisms were angiotensin converting enzyme insertion/deletion (ACE I/D), angiotensin II type 1 receptor (AGTR1) A1166C and aldosterone synthase (CYP11B2) C-344T. Considering a long-term follow-up (9 ± 4 years) we compared genetic polymorphisms of patients with and without events (cardiac death, myocardial infarction, revascularization procedures).</p> <p>Results</p> <p>We found a borderline significant association of occurrence of AMI with the ACE D/I polymorphism (DD genotype, 42% in cases vs 31% in controls; p = 0.056). DD genotype remained statistically involved in the incidence of AMI also after adjustment for clinical confounders.</p> <p>On the other hand, during the 9-year follow-up (65 events, including 13 deaths) we found a role concerning the AGTR1: the AC heterozygous resulted more represented in the event group (p = 0.016) even if not independent from clinical confounders. Anyhow the Kaplan-Meier event free curves seem to confirm the unfavourable role of this polymorphism.</p> <p>Conclusion</p> <p>Polymorphisms in RAAS genes can be important in the onset of a first AMI in young patients (ACE, CYP11B2 polymorphisms), but not in the disease progression after a long follow-up period. Larger collaborative studies are needed to confirm these results.</p

The Finnish Cardiovascular Study (FINCAVAS): characterising patients with high risk of cardiovascular morbidity and mortality

BACKGROUND: The purpose of the Finnish Cardiovascular Study (FINCAVAS) is to construct a risk profile – using genetic, haemodynamic and electrocardiographic (ECG) markers – of individuals at high risk of cardiovascular diseases, events and deaths. METHODS AND DESIGN: All patients scheduled for an exercise stress test at Tampere University Hospital and willing to participate have been and will be recruited between October 2001 and December 2007. The final number of participants is estimated to reach 5,000. Technically successful data on exercise tests using a bicycle ergometer have been collected of 2,212 patients (1,400 men and 812 women) by the end of 2004. In addition to repeated measurement of heart rate and blood pressure, digital high-resolution ECG at 500 Hz is recorded continuously during the entire exercise test, including the resting and recovery phases. About 20% of the patients are examined with coronary angiography. Genetic variations known or suspected to alter cardiovascular function or pathophysiology are analysed to elucidate the effects and interactions of these candidate genes, exercise and commonly used cardiovascular medications. DISCUSSION: FINCAVAS compiles an extensive set of data on patient history, genetic variation, cardiovascular parameters, ECG markers as well as follow-up data on clinical events, hospitalisations and deaths. The data enables the development of new diagnostic and prognostic tools as well as assessments of the importance of existing markers

Mutations disrupting neuritogenesis genes confer risk for cerebral palsy

In addition to commonly associated environmental factors, genomic factors may cause cerebral palsy. We performed whole-exome sequencing of 250 parent-offspring trios, and observed enrichment of damaging de novo mutations in cerebral palsy cases. Eight genes had multiple damaging de novo mutations; of these, two (TUBA1A and CTNNB1) met genome-wide significance. We identified two novel monogenic etiologies, FBXO31 and RHOB, and showed that the RHOB mutation enhances active-state Rho effector binding while the FBXO31 mutation diminishes cyclin D levels. Candidate cerebral palsy risk genes overlapped with neurodevelopmental disorder genes. Network analyses identified enrichment of Rho GTPase, extracellular matrix, focal adhesion and cytoskeleton pathways. Cerebral palsy risk genes in enriched pathways were shown to regulate neuromotor function in a Drosophila reverse genetics screen. We estimate that 14% of cases could be attributed to an excess of damaging de novo or recessive variants. These findings provide evidence for genetically mediated dysregulation of early neuronal connectivity in cerebral palsy

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Changes of synaptic connections between neurons are thought to be the physiological basis of learning. These changes can be gated by neuromodulators that encode the presence of reward. We study a family of reward-modulated synaptic learning rules for spiking neurons on a learning task in continuous space inspired by the Morris Water maze. The synaptic update rule modifies the release probability of synaptic transmission and depends on the timing of presynaptic spike arrival, postsynaptic action potentials, as well as the membrane potential of the postsynaptic neuron. The family of learning rules includes an optimal rule derived from policy gradient methods as well as reward modulated Hebbian learning. The synaptic update rule is implemented in a population of spiking neurons using a network architecture that combines feedforward input with lateral connections. Actions are represented by a population of hypothetical action cells with strong mexican-hat connectivity and are read out at theta frequency. We show that in this architecture, a standard policy gradient rule fails to solve the Morris watermaze task, whereas a variant with a Hebbian bias can learn the task within 20 trials, consistent with experiments. This result does not depend on implementation details such as the size of the neuronal populations. Our theoretical approach shows how learning new behaviors can be linked to reward-modulated plasticity at the level of single synapses and makes predictions about the voltage and spike-timing dependence of synaptic plasticity and the influence of neuromodulators such as dopamine. It is an important step towards connecting formal theories of reinforcement learning with neuronal and synaptic properties

A reafferent and feed-forward model of song syntax generation in the Bengalese finch

Adult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons

Bi-allelic variants in SPATA5L1 lead to intellectual disability, spastic-dystonic cerebral palsy, epilepsy, and hearing loss

Spermatogenesis-associated 5 like 1 (SPATA5L1) represents an orphan gene encoding a protein of unknown function. We report 28 bi-allelic variants in SPATA5L1 associated with sensorineural hearing loss in 47 individuals from 28 (26 unrelated) families. In addition, 25/47 affected individuals (53%) presented with microcephaly, developmental delay/intellectual disability, cerebral palsy, and/or epilepsy. Modeling indicated damaging effect of variants on the protein, largely via destabilizing effects on protein domains. Brain imaging revealed diminished cerebral volume, thin corpus callosum, and periventricular leukomalacia, and quantitative volumetry demonstrated significantly diminished white matter volumes in several individuals. Immunofluorescent imaging in rat hippocampal neurons revealed localization of Spata5l1 in neuronal and glial cell nuclei and more prominent expression in neurons. In the rodent inner ear, Spata5l1 is expressed in the neurosensory hair cells and inner ear supporting cells. Transcriptomic analysis performed with fibroblasts from affected individuals was able to distinguish affected from controls by principal components. Analysis of differentially expressed genes and networks suggested a role for SPATA5L1 in cell surface adhesion receptor function, intracellular focal adhesions, and DNA replication and mitosis. Collectively, our results indicate that bi-allelic SPATA5L1 variants lead to a human disease characterized by sensorineural hearing loss (SNHL) with or without a nonprogressive mixed neurodevelopmental phenotype

Context-Dependent Encoding of Fear and Extinction Memories in a Large-Scale Network Model of the Basal Amygdala

The basal nucleus of the amygdala (BA) is involved in the formation of context-dependent conditioned fear and extinction memories. To understand the underlying neural mechanisms we developed a large-scale neuron network model of the BA, composed of excitatory and inhibitory leaky-integrate-and-fire neurons. Excitatory BA neurons received conditioned stimulus (CS)-related input from the adjacent lateral nucleus (LA) and contextual input from the hippocampus or medial prefrontal cortex (mPFC). We implemented a plasticity mechanism according to which CS and contextual synapses were potentiated if CS and contextual inputs temporally coincided on the afferents of the excitatory neurons. Our simulations revealed a differential recruitment of two distinct subpopulations of BA neurons during conditioning and extinction, mimicking the activation of experimentally observed cell populations. We propose that these two subgroups encode contextual specificity of fear and extinction memories, respectively. Mutual competition between them, mediated by feedback inhibition and driven by contextual inputs, regulates the activity in the central amygdala (CEA) thereby controlling amygdala output and fear behavior. The model makes multiple testable predictions that may advance our understanding of fear and extinction memories

Significance of vascular endothelial growth factor in growth and peritoneal dissemination of ovarian cancer

Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis which drives endothelial cell survival, proliferation, and migration while increasing vascular permeability. Playing an important role in the physiology of normal ovaries, VEGF has also been implicated in the pathogenesis of ovarian cancer. Essentially by promoting tumor angiogenesis and enhancing vascular permeability, VEGF contributes to the development of peritoneal carcinomatosis associated with malignant ascites formation, the characteristic feature of advanced ovarian cancer at diagnosis. In both experimental and clinical studies, VEGF levels have been inversely correlated with survival. Moreover, VEGF inhibition has been shown to inhibit tumor growth and ascites production and to suppress tumor invasion and metastasis. These findings have laid the basis for the clinical evaluation of agents targeting VEGF signaling pathway in patients with ovarian cancer. In this review, we will focus on VEGF involvement in the pathophysiology of ovarian cancer and its contribution to the disease progression and dissemination