Biology subjects

Moran, C.

Publications and source records attributed to Moran, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Metabolic complexity in the human brain supports metastable network dynamics and declines in normative ageing

The adaptive capacity of the brain is tied to the complexity of its neural activity. While entropy of brain signals has been used to characterise this complexity in haemodynamic and electrophysiological systems, it remains unknown whether entropy contributes to the temporal dynamics of the metabolic signals of the brain (glucodynamics) and how metabolic entropy may relate to network organisation, brain ageing and cognitive decline. Here, we combined dynamic functional PET (fPET) with 18F-fluoroedeoxyglucose and simultaneously acquired functional magnetic resonance imaging (fMRI) in 84 adults to investigate multiscale entropy (MSE) in the brain. We report that metabolic complexity measured with PET MSE represents non-linear, high-frequency complexity, whereas hemodynamic complexity reflects non-linearly constrained neurovascular phase dynamics. Greater metabolic complexity was associated with greater network metastability, particularly in unimodal and higher-order associative networks. Greater regional metabolic complexity also correlated with greater cortical thickness, cerebral metabolic rates of glucose (CMRglc) and cerebral blood flow, and was lower in older than younger adults. In contrast, global and network haemodynamic MSE was not significant associated with network dynamics. Higher global metabolic complexity was associated with better cognitive performance, and voxel-level derived MSE clusters were \associated with cognitive performance in both modalities, with varied cluster sizes and spatial locations. However, these associations were largely accounted for by age variance. We conclude that temporal complexity in cerebral glucose is associated with the dynamics of the underlying metabolic signals, enables metastable network states and declines in ageing. Entropy of metabolic brain signals offers promise as a neurobiologically grounded metric of brain ageing.

neuroscience↗

bioRxiv2026

Type 1 immunity linked to CMV exposure improves long-term survival in sepsis without shock

Dysregulated immune responses are at the core of sepsis pathology and can drive both acute organ dysfunction and long-term morbidity and mortality. To better understand the association between specific immune histories, perturbations and sepsis outcomes, we combined immune phenotyping, functional cytokine production assays and antibody repertoire profiling. While sepsis immune profiles were highly heterogeneous, we identified a strong association between the frequency of CXCR3-expressing CD4 memory T cells at time of enrollment and six-month survival in sepsis without shock. Surprisingly, the same population was linked to improved organ function trajectories in septic shock patients but did not influence six-month survival, highlighting the importance of considering physiological states to define immune predictors. Finally, phage display profiling revealed that these Th1 cells were generally expanded in CMV-seropositive individuals, suggesting that previous and latent infections may modulate sepsis outcomes.

immunology↗

bioRxiv2026

Directed information flow across the metabolic network of the human brain

Brain function is organised in distributed circuits in which regional engagement unfolds over time, reflecting coordinated and temporally ordered patterns of neural computation and information flow. Neural activity also depends on a reliable and scalable supply of glucose. Yet, the temporal order and direction of metabolic signalling in brain circuits remain unknown. Here, we combine functional Positron Emission Tomography (fPET) with [18F]-flurodeoxyglucose and Granger causality analysis to characterise directed metabolic connectivity in cognitive control, memory and affective regulatory circuits in 86 healthy adults. We observed widespread directed metabolic influences within the circuits, with the strength of connections a significant predictor of cognition and affect. The behavioural value of the connections was also governed by the efficiency with which baseline glucose metabolism was converted into adaptive functional connections. We conclude that the brain is organised into metabolic circuits that coordinate temporally ordered connectivity to support information transfer. Directed connections vary in their efficiency of glucose use and functional benefit, suggesting that metabolic signalling does not follow a simple "more is better" rule but reflects context-dependent optimisation across cognitive systems. Author SummaryActivity in the regions of brain circuits unfolds over time, reflecting coordinated and temporally ordered patterns of neural computation. However, it is currently unclear how the intrinsic architecture of the human brains metabolic network supports temporally ordered information flow. Using functional Positron Emission Tomography (fPET) and Granger causality analysis, we identify widespread directed metabolic influences within cognitive control, memory, and affective regulatory circuits. We report that metabolic signalling reflects structured, hierarchical dynamics that predict cognitive performance and psychosocial function. Our results indicate that the brain optimises energetic resources through context-dependent signalling: proactive control requires high metabolic investment, while memory circuits benefit from economical use of glucose. These findings suggest that the brains metabolic architecture is organised to support information flow in functional circuits.

neuroscience↗

bioRxiv2026

Metabolic Connectivity Gradients of the Human Brain

The functional architecture of the brain is organised along continuous, macro-scale gradients. However, it is unknown if the metabolic architecture of the brain displays similar gradient characteristics. Here, we use functional positron emission tomography (fPET) with 18F-fluorodeoxyglucose (FDG) to characterise the brains metabolic connectivity gradients and determine how neurobiological mechanisms shape these gradients to support cognition across the adult lifespan. We identified four principal metabolic connectivity gradients, with the primary axis recapitulating the canonical unimodal-to-transmodal hierarchy from other imaging modalities. Subsequent gradients delineated specialised dimensions of metabolic organisation, including association system differentiation, hemispheric asymmetry, and sensory system segregation. These gradients were coupled to cortical thickness, baseline rates of glucose metabolism, blood flow, and gene expression related to energy metabolism, such that transmodal, control and default mode poles were more metabolically active, more interconnected, had greater cortical thickness, and were more strongly related to the expression of genes related to cellular energy production, than unimodal and sensory poles. A reduction in gradient strength at the gradient poles was associated with older age and predicted worse cognitive performance. We conclude that the brains metabolic organisation constitutes a genetically grounded, structurally and energetically constrained gradient hierarchy that supports cognitive function and undergoes a reorganisation in ageing. TeaserThe brains metabolic architecture forms macro-scale gradients linking genes, neurobiology, and cognitive ageing.

neuroscience↗

bioRxiv2025

Glucodynamic Network Transitions of the Human Brain

The human brain achieves cognitive flexibility by rapidly switching between large-scale functional network states. While state switching is assumed to be energetically demanding, the direct metabolic foundation underpinning state switching has not been characterised. Here, we combine functional FDG-PET (fPET) imaging and sliding-window analyses to characterise metabolic network state switching in 85 adults (20-89 years). Four recurring metabolic network states were identified: a highly prevalent, sparsely connected baseline alongside three transient, globally integrated network states of cognitive control and attention. Cognitive performance relied on the capacity to mobilise the integrated associative system states. Flexible network switching was enabled by the moment-to-moment dynamic range of the underlying regional glucose signals. Neurotransmitter analyses revealed a low-dimensional neurochemical hierarchy that mapped to the dynamic network states, anchored by a dominant axis of endocannabinoid, metabolic, serotonergic and GABAergic systems. The dynamic metabolic network architecture was also attenuated in older adults, who exhibited a loss of network flexibility and were anchored to the sparsely connected baseline state. These findings reveal that functional network state switching is an emergent property of the brains metabolic architecture. This understanding may provide critical new insights into the metabolic basis of brain ageing, neurodegeneration and psychiatric conditions.

neuroscience↗

bioRxiv2025

Genomic and morphometric evidence for Austronesian-mediated pig translocation in the Pacific

Human mediated translocation of non-native pig species (genus Sus) to the islands of Wallacea and Oceania has significantly altered local ecosystems. To investigate the timing and trajectory of these introductions, we conducted both genomic analyses of 576 pig nuclear genomes and a geometric morphometric analysis of 714 modern and ancient dental remains. Our analyses demonstrate that feral and domestic pigs in Wallacea and Oceania possess diverse ancestries resulting from the introduction of multiple, sequential pig populations followed by gene flow. Despite the variability in their genomic ancestry these pigs all possess a distinct tooth morphology, and a genetic link to the Chinese domestic pig populations that accompanied the dispersal of Austronesian language speakers [~]4,000-3,000 years ago via Taiwan and the Philippines.

evolutionary biology↗

bioRxiv2025

Brain glucodynamic variability is an essential feature of the metabolism-cognition relationship

Variability ensures that complex biological systems, including the brain, are capable of responding to changing environmental demands. While the importance of neural variability in electrophysiological and haemodynamic aspects of brain activity is beginning to be understood, little is known about how variability in molecular activity influences brain function. Here we examine how temporal variability in glucodynamics, or time-varying glucose use, is related to cognition in 35 younger and 43 older adults. Stationary metabolic rates of glucose were not directly associated with cognition. Rather, higher glucodynamic variability, and its coherence into metabolic networks, was associated with better cognitive performance. Lower glucodynamic variability in ageing was associated with altered metabolic network efficiency and reduced cognitive performance. Our results demonstrate for the first time that variability in cerebral glucose metabolism is biologically and functionally relevant to cognition and the network architecture of the brain. Cognition is influenced by time-varying glucose metabolism and its coherent fluctuations in metabolic networks. A loss of glucodynamics in ageing reduces the efficiency of the metabolic connectome and contributes to reduced cognitive performance. The study of glucodynamics significantly advances our understanding of metabolic brain changes in health, ageing and disease. Significance statementThe human brain has a high energy requirement and must be able to dynamically adjust its energy supply as needed. However, the dynamic nature of brain glucose use is not well understood. In this work, we identify the variability in glucodynamics - the moment-to-moment fluctuations in glucose use - as an important biological feature supporting cognition and mediating age-related changes in brain function. We report that higher glucodynamic variability is associated with higher metabolic network efficiency and enhanced cognitive performance. Older adults exhibit reduced glucodynamic variability, reduced network efficiency and impaired cognition. Our results demonstrate that glucodynamics are important to our understanding of energy-dependent cognitive processes, the efficiency of metabolic brain networks, and the energetic basis of cognitive ageing.

neuroscience↗

bioRxiv2025

Lack of ADAP1/Centaurin-α1 Ameliorates Cognitive Impairment and Neuropathological Hallmarks in a Mouse Model of Alzheimer's Disease

ArfGAP, with dual PH domain-containing protein 1/Centaurin-1 (ADAP1CentA1), is a brain-enriched and highly conserved Arf6 GTPase-activating and Ras-anchoring protein. ADAP1 is involved in dendritic outgrowth and arborization, synaptogenesis, and axonal polarization by regulating the dynamics of the actin cytoskeleton. An increased level of ADAP1 and its association with amyloid plaques in the human Alzheimers disease (AD) brain suggest a role for this protein in AD progression. To understand the role of ADAP1/CentA1 in neurodegeneration, we crossbred CentA1 KO mice with the hAPP-J20 mouse model of AD (J20 x CentA1 KO). We then evaluated the gene expression profile and the behavioral and neuropathological hallmarks of AD to determine the impact of eliminating ADAP1/CentA1 expression on AD-related phenotypes. Spatial memory assessed by the Morris Water Maze test showed significant impairment in J20 mice, which was rescued by the deletion of CentA1. Neuropathological hallmarks of AD, such as deposits of amyloid plaques and neuroinflammation, were significantly reduced in the AD model mice with CentA1 KO background. To identify potential mediators of AD phenotype rescue, we analyzed differentially expressed genes (DEGs) between genotypes, by employing transcriptome profiling with Nanostring nCounter Neuropathology and Neuroinflammation panels. We found significant upregulation of genes associated with apoptosis and gliosis in the brain of J20 mice. However, many of these genes, including the pro-apoptotic gene, Bid, were restored in the brains of J20 x CentA1 KO mice compared to J20 mice. In summary, our data indicate that CentA1 is required for the progression of AD phenotypes and that targeting CentA1 signaling at mitochondria might have therapeutic potential for AD prevention or treatment. SIGNIFICANCE STATEMENTADAP1/Centaurin-1 (CentA1) is highly enriched in the brain and increased CentA1 level has been linked to Alzheimers disease (AD). However, the precise role of ADAP1 in the pathogenesis of AD is poorly understood. We found that genetic deletion of CentA1 in the AD model mice rescues the pathological hallmarks of AD, including loss of dendritic spines in the hippocampus, amyloid plaque deposition, neuroinflammation and spatial memory deficits. Transcriptome analysis of forebrain samples using NanoString nCounter panels for 880 genes, identified the pro-apoptotic protein, Bid, with significantly reduced expression in the J20 mice on ADAP1 KO background. These findings point towards a role of ADAP1 in the activation of the mitochondrial pathways of death associated with the progression of neurodegeneration.

neuroscience↗

bioRxiv2024

Neural evidence for action-related somatosensory predictions

The tactile consequences of self-initiated movements are thought to be predicted by a forward model, yet the precise neural implementation of these predictions remains unclear. In non- motor contexts, expectations are thought to activate sensory neurons tuned towards the expected stimulus. This acts as a predictive template against which afferent sensory input is compared. It is unclear whether forward model predictions have a similar neural instantiation. Here we employed time-resolved multivariate decoding on human electroencephalography (EEG) during self-generated movements to examine the content of predictive neural activity. Human participants performed index finger movements which were predictably paired with a vibration to either the index or ring finger of the opposite, passive hand. On some trials the tactile stimulus was unexpectedly omitted. Results revealed above-chance finger decoding in the pre-movement period supporting a predictive representation of expected stimulation location. As the movement approached, this predictive activity became similar to late-stage processing of a physical tactile stimulus. On omission trials, we found that despite the absence of afferent input, finger location could be decoded [~]120 ms after expected stimulus onset. This shows a stimulus-specific omission response. Together these findings indicate that self-generated movement pre-activates neurons tuned towards expected tactile consequences.

neuroscience↗

bioRxiv2024

Sex differences in the rates and association of cerebral blood flow and glucose metabolism in normative ageing.

It is well established that there is a local increase in cerebral blood flow and glucose metabolism in response to neuronal events. However, there is a paucity of sex disaggregated studies measuring the relationship between cerebral blood flow and glucose metabolism, despite metabolic and vascular factors being considered primary drivers of age-related cognitive decline and dementias like Alzheimers, which disproportionally affect women. Here we address this gap by assessing the association of cerebral blood flow and glucose metabolism in the functional networks of 79 younger and older females and males, who completed a simultaneous MR/PET scan and cognitive battery. Our results extend previously reported age-related declines in CBF and CMRGLC by demonstrating that their interrelationship changes with age and sex. Older age was associated with a reduction in the correlation strength between network CBF and CMRGLC. CBF-CMRGLC associations across people were moderated by sex, with significant negative associations in older females, a pattern not seen in older males nor younger adults. People with higher CBF-CMRGLC correlations had better cognitive performance. We conclude that older adults lose synchronised vascular and metabolic dynamics in large-scale functional network, which are necessary for cognitive processes. Older females show strong, negative network CBF-CMRGLC correlations, possibly reflecting a compensatory response in the face or attenuated rates of blood flow and glucose metabolism. The associations of CBF and CMRGLC may serve as a biomarker for brain heath and neurological conditions.

neuroscience↗

bioRxiv2024

The representation of stimulus features during stable fixation and active vision

Predictive updating of an objects spatial coordinates from its retinotopic pre-saccadic to post-saccadic position contributes to stable visual perception. However, whether object features are predictively represented at the remapped location remains contested. Many previous studies showing evidence of feature remapping neglect the spatially invariant representation of features in the visual system. For example, feature-based attention boosts attended features across the entire visual field, potentially contributing to the maintenance of stimulus features across saccades. We set out to characterise the spatiotemporal dynamics of feature processing during stable fixation and active vision. To do so, we applied multivariate decoding methods to electroencephalography (EEG) data collected while participants viewed brief visual stimuli. Stimuli appeared at different locations across the visual field at either high or low spatial frequency (SF). During fixation, classifiers were trained to decode SF presented at one parafoveal location and cross-tested on SF from either the same, adjacent or more peripheral locations. When training and testing on the same location, SF was classified shortly after stimulus onset ([~]80 ms). Decoding of SF at locations farther from the trained location emerged later ([~]150-300 ms), with decoding latency modulated by eccentricity. This analysis provides a detailed time course for the spread of feature information across the visual field. Next, we investigated how active vision impacts the emergence of SF information. In the presence of a saccade, the decoding time of peripheral SF at parafoveal locations was accelerated, indicating predictive anticipation of SF due to the saccade. Crucially however, this predictive effect was not limited to the specific remapped location. Rather, peripheral SF was correctly classified, at an accelerated time course, at all parafoveal positions. This indicates a spatially coarse remapping of stimulus features during active vision, likely enabling a smooth transition on saccade landing. Significance StatementMaintaining a continuous representation of object features across saccades is vital for stable vision. In order to characterise the spatiotemporal dynamics of stimulus feature representation in the brain, we presented stimuli at a high and low spatial frequency at multiple locations across the visual field. Applying EEG-decoding methods we tracked the neural representation of spatial frequency during both stable fixation and active vision. Using this approach, we provide a detailed time course for the spread of feature information across the visual field during fixation. In addition, when a saccade is imminent, we discovered that the spread of feature information is expedited such that access to peripheral spatial frequency is accelerated.

neuroscience↗

bioRxiv2024

Metabolic connectivity has greater predictive utility for age and cognition than functional connectivity.

Recently developed high temporal resolution functional [18F]-fluorodeoxyglucose positron emission tomography (fPET) offers promise as a method for indexing the dynamic metabolic state of the brain in vivo by directly measuring a timeseries of metabolism at the post-synaptic neuron. This is distinct from functional magnetic resonance imaging (fMRI) that reflects a combination of metabolic, haemodynamic and vascular components of neuronal activity. The value of using fPET to understand healthy brain ageing and cognition over fMRI is currently unclear. Here we use simultaneous fPET/fMRI to compare metabolic and functional connectivity and test their predictive ability for ageing and cognition. Whole-brain fPET connectomes showed moderate topological similarities to fMRI connectomes in 40 younger (mean age 27.9 years; range 20-42) and 46 older (mean 75.8; 60-89) adults. There were more age-related within- and between-network connectivity and graph metric differences in fPET than fMRI. fPET was also associated with performance in more cognitive domains than fMRI. These results suggest that ageing is associated with a reconfiguration of metabolic connectivity that differs from haemodynamic alterations. We conclude that metabolic connectivity has greater predictive utility for age and cognition than functional connectivity and that measuring glucodynamic changes has promise as a biomarker for age-related cognitive decline.

neuroscience↗

bioRxiv2024

Metabolic connectivity in ageing.

Information transfer across the brain has a high energetic cost and requires the efficient use of glucose. Positron emission tomography (PET) studies have shown that ageing is associated with a decline in regional rates of cerebral glucose metabolism. However, until recently, it has not been possible to measure the timecourse of molecular activity within an individual using PET, preventing the study of metabolic network connectivity across the brain. Here we report the results of the first high temporal resolution functional PET study examining metabolic connectivity and cognitive function in ageing. The metabolic connectomes of 40 younger (mean age 27.9 years; range 20-42) and 46 older (mean 75.8; 60-89) adults were characterised by high connectivity strength in the frontal, temporal, motor, parietal and medial cortices. Ageing was associated with lower global integration of metabolic hub regions, indicating disrupted information transfer across the metabolic network in older adults. In younger adults, a high proportion of glucose was used to support hubs in the frontal regions. Older adults had a smaller energy budget in comparison to younger adults, and older adults used a higher proportion of energy to support mostly posterior hub regions. This difference in the metabolic network topology in older adults was associated with worse cognitive performance. We conclude that ageing is associated with reduced metabolic connectivity, an altered metabolic network topology and a high glucose cost in hub regions. Our results highlight the fundamental role that metabolism plays in supporting information transfer in the brain and the unique insights that metabolic connectivity provides into the ageing brain.

neuroscience↗

bioRxiv2024

Insulin resistance alters the coupling between cerebral blood flow and glucose metabolism in younger and older adults: Implications for neurovascular coupling

Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of insulin resistance and age to the coupling of cerebral blood flow and glucose metabolism; a critical process in the supply of energy for the brain. Thirty-four younger (20-42 years) and 41 older (66-86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive coupling. In insulin resistant younger adults, coupling showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates and coupling of cerebral blood flow and metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.

neuroscience↗

bioRxiv2023

Aβ Amyloid Scaffolds the Accumulation of Matrisome and Additional Proteins in Alzheimer's Disease

We report a highly significant correlation between human Alzheimers disease (AD) brain proteome changes and those in CRND8 APP695NL/F transgenic mice. Comparing protein changes observed in the CRND8 mice with co-expression networks derived from human Alzheimers disease (AD), reveals both conserved and divergent module changes. Many proteins in the most highly conserved module (M42, matrisome) accumulate in plaques, cerebrovascular amyloid (CAA), dystrophic neuronal processes, or a combination thereof. Overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), in CRND8 mice brains leads to increased accumulation of A{beta} in plaques and in blood vessels; further, recombinant MDK and PTN enhance A{beta} aggregation into amyloid structures. Multiple M42 proteins bind to fibrillar A{beta}42 and a non-human amyloid fibril in vitro. Supporting this binding data, MDK and PTN co-accumulate with transthyretin (TTR) amyloid in the heart. Notably, our findings establish that proteomic changes in modules observed in human AD brains define an A{beta} amyloid "responsome" that is well conserved from mouse models to humans. Further, distinct amyloid structures appear to serve as scaffolds, facilitating the co-accumulation of proteins with signaling functions, and this co-accumulation may contribute to downstream pathological sequalae. Overall, this contextualized understanding of proteomic changes and their interplay with amyloid deposition provides valuable insights into the complexity of AD pathogenesis and potential biomarkers and therapeutic targets.

neuroscience↗

bioRxiv2023

Decoding Remapped Spatial Information in the Peri-Saccadic Period

It has been suggested that, prior to a saccade, visual neurons predictively respond to stimuli that will fall in their receptive fields after completion of the saccade. This saccadic remapping process is thought to compensate for the shift of the visual world across the retina caused by eye movements. To map the timing of this predictive process in the brain, we recorded neural activity using electroencephalography (EEG) during a saccade task. Participants made saccades between two fixation points while covertly attending to oriented gratings briefly presented at various locations on the screen. Data recorded during trials in which participants maintained fixation were used to train classifiers on stimuli in different positions. Subsequently, data collected during saccade trials were used to test for the presence of remapped stimulus information at the post-saccadic retinotopic location in the peri-saccadic period, providing unique insight into when remapped information becomes available. We found that the stimulus could be decoded at the remapped location [~]180 ms post-stimulus onset, but only when the stimulus was presented 100-200 ms before saccade onset. Within this range, we found that the timing of remapping was dictated by stimulus onset rather than saccade onset. We conclude that presenting the stimulus immediately before the saccade allows for optimal integration of the corollary discharge signal with the incoming peripheral visual information, resulting in a remapping of activation to the relevant post-saccadic retinotopic neurons. Significance StatementEach eye movement leads to a shift of the visual world across the retina, such that the visual input before and after the eye movement do not match. Despite this, we perceive the visual world as stable. A predictive mechanism known as saccadic remapping is thought to contribute to this stability. We use a saccade task with time-resolved EEG decoding to obtain a fine-grained analysis of the temporal dynamics of the saccadic remapping process. Probing different stimulus-saccade latencies and an array of stimulus locations, we identify when remapped information becomes available in the visual cortex. We describe a critical window in which feedforward visual information and the preparatory motor signals interact to allow for predictive remapping of a stimulus.

neuroscience↗

bioRxiv2023

Metabolic rates of glucose in the brain networks of healthy adults vary as a function of age and levels of peripheral insulin resistance, and predict cognition

People with insulin resistance are at increased risk for cognitive decline. Insulin resistance has previously been considered primarily a condition of ageing but it is increasingly seen in younger adults. Here, we explore the question that changes in insulin function in early adulthood have both proximal effects, and moderate or even accelerate changes in cerebral metabolism in ageing. Thirty-six younger (mean 27.8 years) and 43 older (mean 75.5) participants completed a battery of tests, including blood sampling, cognitive assessment and a simultaneous PET/MR scan. Cortical thickness and cerebral metabolic rate of glucose were derived for 100 regions and 17 functional networks. Older adults had lower rates of regional cerebral glucose metabolism than younger adults across the brain even after adjusting for lower cortical thickness in older adults. In younger adults, higher insulin resistance was associated with attenuated rates of regional cerebral glucose metabolism, but this was not seen in older adults. The largest effects of insulin resistance in younger adults were in prefrontal, parietal and temporal regions; and in the control, salience ventral attention, default and somatomotor networks. Higher rates of network glucose metabolism were associated with lower reaction time and psychomotor speed. Higher levels of insulin resistance were associated with lower working memory. Our results underscore the importance of insulin sensitivity to brain health and cognitive function across the adult lifespan, even in early adulthood. Significance StatementWe show that preventing insulin resistance in early adulthood is important for ensuring efficient fuel supply for the brain and the maintenance of cognitive health across the adult lifespan. Glucose is the primary source of energy for the brain. Decreased glucose metabolism in the brain due to clinically significant levels of insulin resistance is associated with cognitive impairment. Although sub-clinical levels of insulin resistance have also been associated with brain changes, their impact on cerebral metabolism in healthy individuals is unclear. We showed for the first time that - while older adults have lower rates of cerebral metabolism - peripheral insulin resistance attenuates cerebral metabolism more so in healthy younger than healthy older adults, and impairs working memory.

neuroscience↗

bioRxiv2022

Quantitative trait and transcriptome analysis of genetic complexity underpinning cardiac interatrial septation in mice using an advanced intercross line

Unlike single-gene mutations leading to Mendelian conditions, common human diseases are likely emergent phenomena arising from multilayer, multiscale and highly interconnected interactions. Atrial and ventricular septal defects are the most common forms of cardiac congenital anomalies in humans. Atrial septal defects (ASD) show an open communication between left and right atria postnatally, potentially resulting in serious hemodynamic consequences if untreated. A milder form of atrial septal defect, patent foramen ovale (PFO), exists in about one quarter of the human population, strongly associated with ischaemic stroke and migraine. The anatomic liabilities and genetic and molecular basis of atrial septal defects remain unclear. Here, we advance our previous analysis of atrial septal variation through quantitative trait locus (QTL) mapping of an advanced intercross line (AIL) established between the inbred QSi5 and 129T2/SvEms mouse strains, that show extremes of septal phenotypes. Analysis resolved 37 unique septal QTL with high overlap between QTL for distinct septal traits. Whole genome sequencing of parental strains identified high confidence candidate deleterious variants, including in known human congenital heart disease genes, whereas transcriptome analysis of developing septa revealed networks involving ribosome, nucleosome, mitochondrial and extracellular matrix biosynthesis underlying septal variation. Analysis of variant architecture across different gene features, including enhancers and promoters, provided evidence for involvement of non-coding as well as protein coding variants. Our study provides the first high resolution picture of genetic complexity and network liability underlying common congenital heart disease, with relevance to human ASD and PFO.

genetics↗