When did it started? ”.. Whole genome duplications occurred 500 million years ago (mya) in vertebrates, while an additional duplication occurred in teleosts about 350 to 320 mya ..
Evolution of neurotransmitter gamma-aminobutyric acid, glutamate and their receptor http://www.bioline.org.br/pdf?zr12088 https://pubmed.ncbi.nlm.nih.gov/23266985/
Consequences of the evolution of the GABA(A) receptor gene family https://pubmed.ncbi.nlm.nih.gov/16075381/
GABA also evolued in plats -> https://digital.library.adelaide.edu.au/dspace/bitstream/2440/124330/3/hdl_124330.pdf
Evolution of synapses and neurotransmitter systems: The divide-and-conquer model for early neural cell-type evolution – https://www.sciencedirect.com/science/article/abs/pii/S095943882100129X
”Nervous systems evolved around 560 million years ago to coordinate and empower animal bodies. Ctenophores – one of the earliest-branching lineages — are thought to share a few neuronal genes with bilaterians and may have evolved neurons convergently. Here we review our current understanding of the evolution of neuronal molecules in nonbilaterians. We also reanalyse single-cell sequencing data in light of new cell-cluster identities from a ctenophore and uncover evidence supporting the homology of one ctenophore neuron-type with neurons in Bilateria. The specific coexpression of the presynaptic proteins Unc13 and RIM with voltage-gated channels, neuropeptides and homeobox genes pinpoint a spiking sensory-peptidergic cell in the ctenophore mouth. Similar Unc13-RIM neurons may have been present in the first eumetazoans to rise to dominance only in stem Bilateria. We hypothesise that the Unc13-RIM lineage ancestrally innervated the mouth and conquered other parts of the body with the rise of macrophagy and predation during the Cambrian explosion.
More links
https://www.nature.com/articles/s41559-022-01828-6
Premetazoan Origin of Neuropeptide Signaling – https://academic.oup.com/mbe/article/39/4/msac051/6547593?login=false
Discovery of GABA
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6295731/
”Some scientific discoveries land with a boom only to fizzle out and become a small blip—but there are times when this order is reversed. Such was the case with the discovery of γ-aminobutyric acid (GABA) in the brain, reported in 1950. In a study published in the Journal of Biological Chemistry (1), preceded by a brief conference report shortly before that (2), Eugene Roberts (Fig. 1) and Sam Frankel not only identified GABA as a major amine in the brain, but also reported that it is produced and preferentially accumulates in this organ”.
Meta studies
Brain GABA levels across psychiatric disorders: A systematic literature review and meta‐analysis of 1H‐MRS studies https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6867515/
” The inhibitory gamma‐aminobutyric acid (GABA) system is involved in the etiology of most psychiatric disorders, including schizophrenia, autism spectrum disorder (ASD) and major depressive disorder (MDD). It is therefore not surprising that proton magnetic resonance spectroscopy (1H‐MRS) is increasingly used to investigate in vivo brain GABA levels. However, integration of the evidence for altered in vivo GABA levels across psychiatric disorders is lacking … In conclusion, this meta‐analysis provided evidence for lower brain GABA levels in ASD (autism spectrum disorder) and in depressed (but not remitted) MDD (major depressive disorder) patients compared with healthy controls. Findings in schizophrenia were more equivocal. Even though future 1H‐MRS studies could greatly benefit from a longitudinal design and consensus on the preferred analytical approach, it is apparent that 1H‐MRS studies have great potential in advancing our understanding of the role of the GABA system in the pathogenesis of psychiatric disorders. Hum Brain Mapp 37:3337–3352, 2016”
Review With Meta-Analysis of Multimodal 1H-MRS-fMRI Studies https://pubmed.ncbi.nlm.nih.gov/33762983/
” Multimodal neuroimaging studies combining proton magnetic resonance spectroscopy (1H-MRS) to quantify GABA and/or glutamate concentrations and functional magnetic resonance imaging (fMRI) to measure brain activity non-invasively have advanced understanding of how neurochemistry and neurophysiology may be related at a macroscopic level …
Functional MRS studies of GABA and glutamate/Glx – A systematic review and meta-analysis
https://www.sciencedirect.com/science/article/abs/pii/S0149763422004298
” Conclusion: We established effect sizes and directionality of the GABA, Glx and Glu response in all currently available fMRS studies. Our results demonstrated relatively small effect sizes and large heterogeneity, limiting the current state of fMRS as a technique in investigating neurodynamic responses in the healthy brain. However, we attempt to address these limitations and hope that advances in these approaches have promise for application in atypical brain function. fMRS of clinical conditions is ..
The trajectory of cortical GABA across the lifespan, an individual participant data meta-analysis of edited MRS studies https://elifesciences.org/articles/62575
” γ-Aminobutyric acid (GABA) is the principal inhibitory neurotransmitter in the human brain and can be measured with magnetic resonance spectroscopy (MRS). Conflicting accounts report decreases and increases in cortical GABA levels across the lifespan. This incompatibility may be an artifact of the size and age range of the samples utilized in these studies. No single study to date has included the entire lifespan. In this study, eight suitable datasets were integrated to generate a model of the trajectory of frontal GABA estimates (as reported through edited MRS; both expressed as ratios and in institutional units) across the lifespan. Data were fit using both a log-normal curve and a nonparametric spline as regression models using a multi-level Bayesian model utilizing the Stan language. Integrated data show that an asymmetric lifespan trajectory of frontal GABA measures involves an early period of increase, followed by a period of stability during early adulthood, with a gradual decrease during adulthood and aging that is described well by both spline and log-normal models. The information gained will provide a general framework to inform expectations of future studies based on the age of the population being studied.
Synopsis – coming