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Martins, D.

Publications and source records attributed to Martins, D..

At least 19 recordsLinked to original sources

Coral Probiotics Buffer Adjacent Ecosystem-Level Responses to Extreme Marine Heatwave

Probiotics can enhance coral thermal tolerance, yet their ecosystem-level effects remain unknown. Here, we present the first long-term in-situ test of whether coral-targeted probiotics influence adjacent cryptobenthic reef communities during a record marine heatwave. Probiotics were applied to Pocillopora favosa and Acropora spp. coral colonies for 18 months, spanning the fourth global bleaching event. Cryptobenthic communities were assessed using biomimetic monitoring structures integrating biodiversity surveys, molecular profiling, microbial network analyses, and metabolic assays. Before the heatwave, probiotic and control patches were comparable across structural, microbial, and functional metrics. Following thermal stress, control patches exhibited pronounced losses of cryptobenthic invertebrate abundance and taxonomic breadth, microbial network fragmentation, and net carbonate dissolution. In contrast, probiotic-treated patches retained higher biodiversity, cohesive microbial interaction architectures, and positive calcification. These findings demonstrate that coral-targeted probiotics can scale from host-level intervention to buffer adjacent ecosystem-level responses to extreme marine heatwaves under accelerating climate change. TeaserA coral-targeted probiotic strategy enhances multi-trophic resilience under heat stress.

microbiology↗

Divergent Biological Consequences of APOE Isoforms Across Industrialized and Non-Industrial Environments

The apolipoprotein {varepsilon}4 (APOE {varepsilon}4) isoform directly alters cholesterol and immune biology and is associated with an increased risk of neurodegenerative and cardiometabolic disease in industrialized settings; nevertheless, APOE {varepsilon}4--which is ancestral in humans--has persisted over evolutionary time. One potential explanation is that the costs and benefits of APOE {varepsilon}4 were significantly different in the environments in which humans evolved compared to those we experience today. In support, previous work has suggested that living in a high pathogen environment, engaging in high levels of physical activity, or eating a low fat diet can dampen the detrimental effects of APOE {varepsilon}4, and has revealed positive effects for fertility. However, direct tests of whether APOE isoforms are associated with different biological outcomes in non-industrial versus industrialized contexts are lacking. Working with the Turkana of Kenya and the Orang Asli of Peninsular Malaysia--two Indigenous groups in which individuals of shared ancestry span a continuum of subsistence, non-industrial to urban, industrialized lifestyles--we investigated how APOE genotypes impact cholesterol, immunological, and reproductive traits and tested for genotype x environment (GxE) interactions. First, we confirmed established genotype effects across lifestyles, showing that more APOE {varepsilon}4 alleles are associated with higher total cholesterol, higher LDL cholesterol, and lower HDL cholesterol. Second, we tested for lifestyle interactions, finding lifestyle-dependent effects of genotype on innate immune biomarkers in the Orang Asli but not Turkana. Finally, we show that more APOE {varepsilon}4 alleles are correlated with an extended reproductive lifespan, however this effect is relatively weak, is not consistent across populations, and does not correspond with a higher reproductive output. Together, our study provides evidence that industrialized environments can modify the biology of APOE {varepsilon}4; however, we find that APOE {varepsilon}4 is not universally beneficial in non-industrial contexts, highlighting the role of local environmental variation in determining its specific costs and benefits.

evolutionary biology↗

Multimodal imaging suggests potential immune-vascular contributions to altered regional brain perfusion and oxygen metabolism in Post-COVID-19 Syndrome

Post-COVID-19 Syndrome (PCS) frequently presents with persistent fatigue, cognitive impairment, and emotional symptoms. Although structural brain changes remain subtle, growing evidence implicates functional and metabolic disruptions in ongoing symptomatology. We used multimodal MRI to investigate cerebral perfusion and oxygen metabolism in PCS and examined their associations with cognitive function and peripheral biomarkers. We enrolled 40 individuals with prior mild SARS-CoV-2 infection, including 20 with persistent fatigue and 20 recovered controls matched for age, sex, BMI, and acute COVID-19 severity. Participants underwent structural MRI, arterial spin labelling (ASL) to quantify regional cerebral blood flow (CBF), and asymmetric spin echo imaging to estimate oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO{square}). We assessed cognition using an online battery and measured serum levels of TNF-, IL-6, IL-8, IL-13, IFN-{gamma}, GFAP, and S100{beta}, alongside blood routine tests. We performed ANCOVAs on predefined regions of interest (hippocampus, anterior cingulate cortex [ACC], insula, amygdala, striatum), followed by Bayesian inference and exploratory whole-brain analyses. PCS participants showed increased CMRO{square} in the hippocampus and decreased CMRO{square} in the ACC. Subfield analysis revealed elevated OEF and CMRO{square} across most hippocampal regions, excluding the entorhinal cortex. Whole-brain analyses identified increased perfusion in salience-related regions (insula, ACC, thalamus) and decreased perfusion in posterior cortical and cerebellar areas, in the absence of grey matter volume differences. Higher hippocampal metabolism positively correlated with cognitive performance, suggesting compensatory adaptation to sustain function. In contrast, lower ACC CMRO{square} correlated with depressive symptoms, reduced motivation, and elevated TNF- and GFAP, consistent with neurovascular uncoupling possibly driven by immune-glial activation. These findings reveal distinct physiological disruptions in PCS, with potential implications for stratified, metabolism-focused interventions.

neuroscience↗

Brain dynamics of attentional, default-mode and limbic networks are disrupted at rest in Post-COVID-19 Syndrome

BackgroundPost-COVID-19 Syndrome (PCS) is characterised by persistent fatigue, cognitive impairments, and affective symptoms, yet its underlying neural mechanisms remain poorly understood. While static neuroimaging studies have identified resting-state connectivity abnormalities in PCS, such approaches fail to capture the brains dynamic functional organisation. This represents a missed opportunity to understand how alterations at the dynamic macroscale interactions give rise to the complex and fluctuating symptom profile of PCS. Cognitive and emotional processes rely on the brains capacity to flexibly reconfigure large-scale networks over time; disruptions in the exploration and transition between brain states may therefore play a central role in PCS pathophysiology. MethodsResting-state fMRI data were acquired from 20 individuals with PCS (mean age = 41.8 years, SD = 9.4) and 20 age- and sex-matched healthy controls (mean age = 40.6 years, SD = 8.1) using a multi-echo sequence. Following denoising with multi-echo independent component analysis, we applied Leading Eigenvector Dynamics Analysis (LEiDA) to identify recurrent patterns of whole-brain phase synchrony. The optimal number of dynamic brain states was determined using the Dunn index. For each state, we quantified probability of occurrence, lifetime, and transition probabilities, and mapped spatial topographies onto canonical functional networks. Group differences were assessed using ANCOVAs controlling for age, sex, and handedness. Exploratory associations with clinical symptoms, cognitive performance, and inflammatory markers were examined using both frequentist and Bayesian approaches. ResultsFive recurrent dynamic brain states were identified. Compared with controls, PCS participants showed reduced probability of occurrence and shorter lifetime of a visual/dorsal attention state, alongside increased probability of a limbic/default mode network (DMN) state. PCS was also characterised by reduced transitions between visual/dorsal attention and frontoparietal-DMN states, and increased transitions from somatomotor/visual states toward the limbic-DMN configuration. Exploratory analyses revealed that greater expression of the limbic-DMN state was negatively associated with global cognitive performance (MoCA) and positively associated with serum IL-1{beta} levels. ConclusionsPCS is associated with a reorganisation of intrinsic brain dynamics, marked by a shift from externally oriented attentional states toward limbic-DMN configurations. This imbalance may reflect reduced cognitive flexibility and increased sensitivity to interoceptive or affective signals. The observed links between dynamic brain-state expression, cognitive impairment, and peripheral inflammation support a systems-level mechanism through which immune signalling may influence neural function in PCS. Dynamic functional connectivity offers a sensitive framework for capturing these alterations and may inform future mechanistic models of post-viral dysfunction and therapeutic targeting. HighlightsO_LIPost-COVID-19 Syndrome (PCS) is linked to altered intrinsic brain dynamics at rest. C_LIO_LIPatients show reduced engagement of visual and attentional brain states. C_LIO_LIIncreased recruitment of limbic-DMN states suggests a shift toward more internally, emotionally charged focussed brain activity. C_LIO_LIBrain-state dynamics are putatively associated with global cognition and IL-1{beta}. C_LIO_LIReduced brain-state flexibility may underlie cognitive and emotional symptoms in PCS. C_LI

neuroscience↗

Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome

Post-COVID-19 syndrome encompasses persistent cognitive, neurological, and psychiatric symptoms following SARS-CoV-2 infection, profoundly affecting global quality of life. Clarifying the neurobiological basis of these symptoms is vital for effective therapeutic interventions. This study utilized normative modelling of brain structure ("CentileBrain") to quantify individualized deviations in cortical thickness, surface area, and subcortical volumes among 20 patients experiencing persistent fatigue following mild COVID-19, compared to 20 matched healthy controls. Group-level analyses on deviation scores revealed subtle yet distinct regional alterations in cortical thickness, specifically decreased thickness within orbitofrontal cortices and increased thickness in occipital/sensory cortices. Although at the individual regional level, the proportion of patients exhibiting infranormal or supranormal thickness values was relatively low (<35%) and comparable to controls, deviations frequently clustered within structurally connected circuits, affecting up to 50% more of patients. Spatial analysis of regional cortical thickness alterations correlated significantly with the constitutive expression patterns of TMPRSS2, an essential protein facilitating SARS-CoV-2 cellular entry. Canonical correlation analyses further identified specific cell-type distributions and neuroreceptor densities predictive of regional thickness changes, highlighting neurons and molecular targets associated with serotoninergic, cannabinoid, cholinergic, and glutamatergic signalling pathways. Network-diffusion modelling constrained by a canonical structural connectome significantly outperformed null models based on permuted connectomes and Euclidean distance metrics, identifying posterior-parietal regions as probable initiation points ("seeds") for network-wide structural changes. Seed likelihood correlated positively with TMPRSS2 expression levels, suggesting that these posterior-parietal regions may be particularly susceptible to SARS-CoV-2 infection. This highlights a plausible mechanism where structural alterations could propagate through connected neural networks, although direct evidence of such propagation requires further investigation. These findings provide novel insights into potential mechanisms underlying neural circuit disruptions in post-COVID-19 fatigue and suggest avenues for therapeutic neuromodulation. HighlightsO_LINormative modelling revealed heterogenous individualised cortical structural deviations in patients with PCS. C_LIO_LIRegional deviations in cortical thickness and surface area clustered within anatomically connected circuits, affecting up to 50% more of PCS participants. C_LIO_LIStructural changes were significantly associated with regional TMPRSS2 expression, implicating SARS-CoV-2 entry pathways in PCS-related brain alterations. C_LIO_LINetwork diffusion modelling identified posterior-temporoparietal regions as likely epicentres of pathology propagation through the structural connectome. C_LIO_LICortical deviations were linked to neuronal and microglial cell-type densities and receptor systems including serotonergic, glutamatergic, cannabinoid and cholinergic pathways, suggesting targets for neuroimmune-informed interventions. C_LI

neuroscience↗

Multiparametric MRI and imaging transcriptomics reveal molecular and cellular correlates of neurodegeneration in experimental multiple system atrophy

Multiple system atrophy (MSA) is an atypical Parkinsonian disorder marked by oligodendroglial -synucleinopathy and selective neurodegeneration. Although MRI can capture regional atrophy and microstructural alterations in MSA brain, the molecular substrates underlying these phenotypes remain poorly defined. Imaging transcriptomics provides a computational framework to relate spatial imaging patterns to brain-wide gene expression. While this approach has been applied to human MSA, interpretation is constrained by limited experimental control and lack of disease-matched molecular validation. Here, we apply imaging transcriptomics in a controlled preclinical setting by integrating high-resolution ex vivo multimodal MRI with transcriptomic mapping in the PLP-Syn mouse model of MSA. Structural and diffusion MRI revealed distinct patterns of regional atrophy and microstructural abnormalities. Atlas-based analyses associated imaging phenotypes to gene programs related to oligodendrocyte biology, energy metabolism, and neuroinflammation, with modality-specific signatures. These associations were supported by independent RNA-sequencing and showed convergence with human MSA findings. Our work benchmarks MRI-transcriptomic relationships in MSA and provides a translational framework for interpreting imaging biomarkers in synucleinopathies.

neuroscience↗

Transcriptome-informed brain cartography of polygenic risk and association with brain structure in major psychiatric disorders

Psychiatric disorders are complex, polygenic conditions characterized by patterned structural brain alterations. Whether these changes reflect transcriptional dysregulation driven by genetic risk remains unclear. We introduce a novel imaging-transcriptomics framework that integrates transcriptome-wide association studies (TWAS) with brain transcriptomic atlases to predict macroscale structural brain abnormalities across seven disorders: ADHD, ASD, AN, BD, MDD, OCD, and schizophrenia (SCZ). We generated disorder-specific Gene Expression-based Disorder Associated Risk (GEDAR) maps and assessed their spatial correlation with observed brain alterations thereby establishing a structured approach to map polygenic transcriptional risk onto macroscale brain phenotypes. We found significant transcriptomic-anatomical correlations in MDD (cortical and subcortical), SCZ (subcortical), and ADHD (subcortical), indicating that regional transcriptional vulnerability might contribute to varying extents to the anatomical expression of genetic risk in these disorders. Pathway enrichment analysis on genetically predicted differentially expressed genes for those disorders where we found spatial correlations between GEDAR maps and observed structural changes revealed immune-related processes as dominant in MDD and SCZ, and neurodevelopmental pathways in ADHD. ASD, AN, OCD, and cortical SCZ lacked significant associations. Importantly, spatial transcriptomic-anatomical alignment did not scale with between-disorder differences in heritability, pointing instead toward additional influences like developmental timing or environmental interactions. These findings underscore the potential and limitations of imaging transcriptomics as a framework for bridging the gap between genetic architecture and systems-level brain changes in psychiatric disorders.

neuroscience↗

Transcriptional and neurochemical signatures of cerebral blood flow alterations in schizophrenia and the clinical high-risk state for psychosis

The brain integrates multiple scales of description, from the level of cells and molecules to large-scale networks and behaviour, and understanding the relationships between these layers may be fundamental to advancing our understanding of how the brain works in health and disease. Recent neuroimaging research has shown that alterations in brain function that are associated with schizophrenia spectrum disorders (SSD) are already present in young adults at clinical high-risk for psychosis (CHR-P), yet the cellular and molecular determinants of these alterations are not well understood. Here, combining regional cerebral blood flow (rCBF) data with existing transcriptomic and neurotransmitter data, we show that cell-types involved in stress response and inflammation, as well as the dopamine, acetylcholine, GABAA and NMDA receptor systems, align as shared and distinct cellular and neurochemical signatures of rCBF phenotypes in people with SSD and those at CHR-P. Decoding the biological pathways involved in neuroimaging-based psychosis phenotypes may provide a basis for the development of novel interventions.

neuroscience↗

Normative Modelling of Molecular-based Functional Neurocircuits Captures Clinical Heterogeneity Transdiagnostically in Neuropsychiatric Patients

Clinical neuroscience principally aims to delineate the neurobiology underpinning the symptoms of various disorders, with the ultimate goal of developing mechanistically informed treatments for these conditions. This has been hindered by the complex hierarchical organisation of the brain and extreme heterogeneity of neuropsychiatric disorders. However, recent advances in multimodal analytic techniques - such as Receptor Enriched Analysis of Connectivity by Targets (REACT) - have allowed to integrate the functional dynamics seen in fMRI with the brains receptor landscape, providing novel trans-hierarchical insights. Similarly, normative modelling of brain features has allowed translational neuroscience to move beyond group average differences between patients and controls and characterise deviations from health at an individual level. Here, we bring these novel methods together for the first time in order to address these two longstanding translational barriers in clinical neuroscience. REACT was used create functional networks enriched with the main modulatory (noradrenaline, dopamine, serotonin, acetylcholine), inhibitory (GABA), and excitatory (glutamate) neurotransmitter systems in a large group of healthy participants [N=607]. Next, we generated normative models of these networks across the spectrum of healthy ageing and demonstrated that these capture deviations within and across patients with Schizophrenia, Bipolar-disorder, and ADHD [N=119]. Our results align with prior accounts of excitatory-inhibitory imbalance in schizophrenia and bipolar disorder, with the former also related to deviations within the cholinergic system. Our transdiagnostic analyses also emphasised the substantial overlap in symptoms and deviations across these disorders. Altogether, this work provides impetus for the development of novel biomarkers that characterise both molecular- and systems-level dysfunction at the individual level, helping facilitate the transition towards mechanistically targeted treatments. Significance statementHuman beings show enormous variability, with inter-individual differences spanning from neurotransmitters to networks. Understanding how these mechanisms interact across scales and produce heterogenous symptomatology within psychiatric disorders presents an enormous challenge. Here, we provide a novel analytic framework to overcome these barriers, combining molecular-enriched neuroimaging with normative modelling to examine neuropathology across scales at the individual level. Our results converge on prior neurobiological accounts of schizophrenia and bipolar disorder as well as the heterogeneity of ADHD. Moreover, we map symptomatology to molecular-enriched functional networks transdiagnostically across these disorders. By bridging the gap between dysfunctional brain networks and underlying neurotransmitter systems, these methods can facilitate the transition from one-size-fits-all approaches to personalized pharmacological interventions at the individual level.

neuroscience↗

Leishmaniinae: evolutionary inferences based on protein expression profiles (PhyloQuant) congruent with phylogenetic relationships among Leishmania, Endotrypanum, Porcisia, Zelonia, Crithidia, and Leptomonas

Evolutionary relationships among parasites of the subfamily Leishmaniinae, which comprises pathogen agents of leishmaniasis, were inferred based on differential protein expression profiles from mass spectrometry-based quantitative data using the PhyloQuant method. Evolutionary distances following identification and quantification of protein and peptide abundances using Proteome Discoverer (PD) and MaxQuant (MQ) softwares were estimated for 11 species from 6 Leishmaniinae genera. Results clustered all dixenous species of the genus Leishmania, subgenera L. (Leishmania), L. (Viannia) and L. (Mundinia), sister to the dixenous species of genera Endotrypanum and Porcisia. Positioned basal to the assemblage formed by all these parasites were the species of genera Zelonia, Crithidia and Leptomonas, so far described as monoxenous of insects although eventually reported from humans. Inferences based on protein expression profiles were congruent with currently established phylogeny using DNA sequences. Our results reinforce PhyloQuant as a valuable approach to infer evolutionary relationships consistent with genera, subgenera, and species-specific biological characteristics, able to resolve within Leishmaniinae, which is comprised of very tightly related trypanosomatids that are just beginning to be phylogenetically unravelled. In additional to evolutionary history, mapping of species-specific protein expression is paramount to understand differences in infection processes, disease presentations, tissue tropisms, potential to jump from insects to vertebrates including humans, and potential targets for species-specific diagnostic and drug development.

evolutionary biology↗

Adaptations to water stress and pastoralism in the Turkana of northwest Kenya

The Turkana people inhabit arid regions of east Africa--where temperatures are high and water is scarce--and they practice subsistence pastoralism, such that their diet is primarily composed of animal products. Working with Turkana communities, we sequenced 367 genomes and identified 8 regions putatively involved in adaptation to water stress and pastoralism. One of these regions includes a putative enhancer for STC1--a kidney-expressed gene involved in the response to dehydration and the metabolism of purine-rich foods such as red meat. We show that STC1 is induced by antidiuretic hormone in humans, is associated with urea levels in the Turkana themselves, and is under strong selection in this population (s[~]0.041). This work highlights that partnerships with subsistence-level groups can lead to new models of human physiology with biomedical relevance.

evolutionary biology↗

The functional circuits related to serotonin transporter and serotonin 1A receptor are differentially associated to serotonin transporter availability after an acute citalopram challenge

BackgroundSelective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of serotonin 1A receptors (5-HT1AR). AimWe investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge. MethodsWe analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography. Results5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low dose group compared to the high dose group at rest and the placebo group during the task. ConclusionsTaken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.

neuroscience↗

The Effects of Propofol Anaesthesia on Molecular-enriched Networks During Resting-state and Naturalistic Stimulation

Placing a patient in a state of anaesthesia is crucial for modern surgical practice. However, the mechanisms by which anaesthetic drugs, such as propofol, impart their effects on consciousness remain poorly understood. Propofol potentiates GABAergic transmission, which purportedly has direct actions on cortex as well as indirect actions via ascending neuromodulatory systems. Functional imaging studies to date have been limited in their ability to unravel how these effects on neurotransmission impact system-level dynamics of the brain. Here, we leveraged advances in multi-modal imaging, Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), to investigate how different levels of propofol-induced sedation alters neurotransmission-related functional connectivity (FC), both at rest and when individuals are exposed to naturalistic auditory stimulation. Propofol increased GABA-A- and noradrenaline transporter-enriched FC within occipital and somatosensory regions respectively. Additionally, during auditory stimulation, the network related to the vesicular acetylcholine transporter showed reduced FC within the right superior temporal gyrus, regardless of level of anaesthesia, and a spatial configuration correlating with a broad range of meta-analytic measures of audition- and emotion-related cognition. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic-related network changes under anaesthesia and describe a cognition-related reconfiguration of the cholinergic network, highlighting the utility of REACT to explore the molecular substrates consciousness and cognition.

neuroscience↗

Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI

Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) is a novel analytical strategy that enriches functional connectivity (FC) information from functional MRI (fMRI) with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the FC analysis. So far, this integrative approach has been used in blood oxygen level-dependent (BOLD) fMRI studies only, providing new insights into the brain mechanisms underlying specific disorders and its response to pharmacological challenges. In this study, we demonstrate that the application of REACT can be further extended to arterial spin labelling (ASL) fMRI. Some of the advantages of this extension include the combination of neurotransmitter specific information provided by molecular imaging with a quantitative marker of neuronal activity, the suitability of ASL for pharmacological MRI (phMRI) studies assessing drug effects on baseline brain function, and the possibility to acquire images that are not affected by susceptibility artifacts in the regions linked to major neurotransmitter systems. In this work, we tested the feasibility of applying REACT to resting state ASL fMRI and compared the molecular-enriched FC maps derived from ASL data with those derived from BOLD data. We applied REACT to high-resolution, whole-brain simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL- and BOLD-based FC maps related to six molecular systems, including the transporters of dopamine, noradrenaline, serotonin and vesicular acetylcholine, and the GABA-A and mGlu5 receptors. We then compared the ASL and BOLD FC maps in terms of spatial similarity, using the Dice Similarity Index and the voxel-wise spatial correlation. On a data subsample (N=19) we also evaluated the test-retest reproducibility of each modality using the regional intraclass correlation coefficient, and compared the two modalities. Our results showed robust spatial patterns of molecular-enriched functional connectivity for both modalities, moderate to high similarity between BOLD- and ASL-derived FC maps and mixed results in terms of reproducibility (i.e., none of the modalities outperformed the other). Overall, our findings show that the ASL signal is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits. Considering the more direct link of ASL imaging with neuronal acrivity compared to BOLD and its suitability for phMRI studies, this new integrative approach could become a valuable asset in clinical studies investigating functional alterations in patients with brain disorders, or in pharmacological studies investigating the effects of new or existing compounds on the brain.

neuroscience↗

Digital data repository and automatic analysis framework for FDOPA PET neuroimaging

IntroductionFDOPA PET has been used extensively to image the human brain in many clinical disorders and has the potential to be used for patient stratification and individualized treatment. However, to reach its full and effective clinical translation, FDOPA PET requires both a robust data infrastructure and analytical protocol that are capable of ensuring high quality data and metadata, accurate biological quantification, and replicable results. In this study we evaluate a digital data repository and automated analytical framework for FDOPA PET neuroimaging that can produce an individualised quantification of dopamine synthesis capacity in the living human brain. MethodsThe imaging platform XNAT was used to store the Kings College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. A fully automated analysis pipeline for imaging processing and data quantification was developed in Python and integrated in XNAT using the Docker technology. Reproducibility was assessed in test-retest datasets both in controls and patients with psychosis. The agreement between the automated analysis estimates and the results derived by the manual analysis were compared. Finally, using a sample of healthy controls (N=115), a sensitivity analysis was performed to explore the impact of experimental and demographic variables on the FDOPA PET measures. ResultsThe final data repository includes 892 FDOPA PET scans organized from 23 different studies, collected at five different imaging sites. After removing commercials studies, the infrastructure consisted of 792 FDOPA PET scans from 666 individuals (female 33.9%, healthy controls 29.1%) collected from four different imaging sites between 2004-2021. The automated analysis pipeline provided results that were in agreement with the results from the manual analysis, with a Pearsons correlation that ranged from 0.64 to 0.99 for Kicer, and from 0.79 to 1.00 for SUVR. The mean absolute difference between the two pipelines ranges from 3.4% to 9.4% for Kicer, and from 2.5% to 12.4% for SUVR. Moreover, we found good reproducibility of the data analysis by the automated pipeline (in the whole striatum for the Kicer: ICC for the controls = 0.71, ICC for the psychotic patients = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p <0.001), with women showing greater dopamine synthesis capacity than men, while the effects of weight, age, injected radioactivity, and scanner, varied by brain region and parameter of interest. ConclusionsCombining information from different neuroimaging studies has allowed us to test comprehensively the automated pipeline for quantification of dopamine synthesis capacity using FDOPA PET data and to validate its replicability and reproducibility performances on a large sample size. This validation process is a necessary methodological step for the development of the clinical application of FDOPA PET as precision medicine biomarker. The proposed infrastructure is generalisable behind the FDOPA radiotracer.

bioengineering↗

Imaging transcriptomics: Convergent cellular, transcriptomic, and molecular neuroimaging signatures in the healthy adult human brain

The expansion of neuroimaging techniques over the last decades has opened a wide range of new possibilities to characterize brain dysfunction in several neurological and psychiatric disorders. However, the lack of specificity of most of these techniques, such as magnetic resonance imaging (MRI)-derived measures, to the underlying molecular and cellular properties of the brain tissue poses limitations to the amount of information one can extract to inform precise models of brain disease. The integration of transcriptomic and neuroimaging data, known as imaging transcriptomics, has recently emerged as an indirect way forward to test and/or generate hypotheses about potential cellular and transcriptomic pathways that might underly specific changes in neuroimaging MRI biomarkers. However, the validity of this approach is yet to be examined in-depth. Here, we sought to bridge this gap by performing imaging transcriptomic analyses of the regional distribution of well-known molecular markers, assessed by positron emission tomography (PET), in the healthy human brain. We focused on tracers spanning different elements of the biology of the brain, including neuroreceptors, synaptic proteins, metabolism, and glia. Using transcriptome-wide data from the Allen Brain Atlas, we applied partial least square regression to rank genes according to their level of spatial alignment with the regional distribution of these neuroimaging markers in the brain. Then, we performed gene set enrichment analyses to explore the enrichment for specific biological and cell-type pathways among the genes most strongly associated with each neuroimaging marker. Overall, our findings show that imaging transcriptomics can recover plausible transcriptomic and cellular correlates of the regional distribution of benchmark molecular imaging markers, independently of the type of parcellation used to map gene expression and neuroimaging data. Our data support the plausibility and robustness of imaging transcriptomics as an indirect approach for bridging gene expression, cells and macroscopical neuroimaging and improving our understanding of the biological pathways underlying regional variability in neuroimaging features.

neuroscience↗

Cellular and molecular signatures of in vivo GABAergic neurotransmission in the human brain

Diverse GABAergic interneuron microcircuits orchestrate information processing in the brain. Understanding the cellular and molecular composition of these microcircuits, and whether these can be imaged by available non-invasive in vivo methods is crucial for the study of GABAergic neurotransmission in health and disease. Here, we use human gene expression data and state-of-the-art imaging transcriptomics to uncover co-expression patterns between GABAA receptor subunits and interneuron subtype-specific markers, and to decode the cellular and molecular signatures of gold-standard GABA PET radiotracers, [11C]Ro15-4513 and [11C]flumazenil. We find that the interneuron marker somatostatin is co-expressed with GABAA receptor-subunit genes GABRA5 and GABRA2, and their distribution maps onto [11C]Ro15-4513 binding in vivo. In contrast, the interneuron marker parvalbumin co-expressed with more predominant GABAA receptor subunits (GABRA1, GABRB2 and GABRG2), and their distribution tracks [11C]flumazenil binding in vivo. These results have important implications for the non-invasive study of GABAergic microcircuit dysfunction in psychiatric conditions.

neuroscience↗

Oxytocin modulates neurocomputational mechanisms underlying prosocial reinforcement learning

Humans often act in the best interests of others. However, how we learn which actions result in good outcomes for other people and the neurochemical systems that support this prosocial learning remain poorly understood. Using computational models of reinforcement learning, functional magnetic resonance imaging and dynamic causal modelling, we examined how different doses of intranasal oxytocin, a neuropeptide linked to social cognition, impact how people learn to benefit others (prosocial learning) and whether this influence could be dissociated from how we learn to benefit ourselves (self-oriented learning). We show that a low dose of oxytocin prevented decreases in prosocial performance over time, despite no impact on self-oriented learning. Critically, oxytocin produced dose-dependent changes in the encoding of prediction errors (PE) in the midbrain-subgenual anterior cingulate cortex (sgACC) pathway specifically during prosocial learning. Our findings reveal a new role of oxytocin in prosocial learning by modulating computations of PEs in the midbrain-sgACC pathway.

neuroscience↗