Early-life influenza A (H1N1) infection independently programs brain connectivity, HPA AXIS and tissue-specific gene expression profiles.

Early-life adversity covers a range of physical, social and environmental stressors. Acute viral infections in early life are a major source of such adversity and have been associated with a broad spectrum of later-life effects outside the immune system or "off-target". These include an altered hypothalamus-pituitary-adrenal (HPA) axis and metabolic reactions. Here, we used a murine post-natal day 14 (PND 14) Influenza A (H1N1) infection model and applied a semi-holistic approach including phenotypic measurements, gene expression arrays and diffusion neuroimaging techniques to investigate HPA axis dysregulation, energy metabolism and brain connectivity. By PND 56 the H1N1 infection had been resolved, and there was no residual gene expression signature of immune cell infiltration into the liver, adrenal gland or brain tissues examined nor of immune-related signalling. A resolved early-life H1N1 infection had sex-specific effects. We observed retarded growth of males and altered pre-stress (baseline) blood glucose and corticosterone levels at PND42 after the infection was resolved. Cerebral MRI scans identified reduced connectivity in the cortex, midbrain and cerebellum that were accompanied by tissue-specific gene expression signatures. Gene set enrichment analysis confirmed that these were tissue-specific changes with few common pathways. Early-life infection independently affected each of the systems and this was independent of HPA axis or immune perturbations.

A Holistic View of the Goto-Kakizaki Rat Immune System: Decreased Circulating Immune Markers in Non- Obese Type 2 Diabetes.

Type-2 diabetes is a complex disorder that is now considered to have an immune component, with functional impairments in many immune cell types. Type-2 diabetes is often accompanied by comorbid obesity, which is associated with low grade inflammation. However,the immune status in Type-2 diabetes independent of obesity remains unclear. Goto-Kakizaki rats are a non-obese Type-2 diabetes model. The limited evidence available suggests that Goto-Kakizaki rats have a pro-inflammatory immune profile in pancreatic islets. Here we present a detailed overview of the adult Goto-Kakizaki rat immune system. Three converging lines of evidence: fewer pro-inflammatory cells, lower levels of circulating pro-inflammatory cytokines, and a clear downregulation of pro-inflammatory signalling in liver, muscle and adipose tissues indicate a limited pro-inflammatory baseline immune profile outside the pancreas. As Type-2 diabetes is frequently associated with obesity and adipocyte-released inflammatory mediators, the pro-inflammatory milieu seems not due to Type-2 diabetes per se; although this overall reduction of immune markers suggests marked immune dysfunction in Goto-Kakizaki rats.

The 'Jekyll and Hyde' of Gluconeogenesis: Early Life Adversity, Later Life Stress, and Metabolic Disturbances.

The physiological response to a psychological stressor broadly impacts energy metabolism. Inversely, changes in energy availability affect the physiological response to the stressor in terms of hypothalamus, pituitary adrenal axis (HPA), and sympathetic nervous system activation. Glucocorticoids, the endpoint of the HPA axis, are critical checkpoints in endocrine control of energy homeostasis and have been linked to metabolic diseases including obesity, insulin resistance, and type 2 diabetes. Glucocorticoids, through the glucocorticoid receptor, activate transcription of genes associated with glucose and lipid regulatory pathways and thereby control both physiological and pathophysiological systemic energy homeostasis. Here, we summarize the current knowledge of glucocorticoid functions in energy metabolism and systemic metabolic dysfunction, particularly focusing on glucose and lipid metabolism. There are elements in the external environment that induce lifelong changes in the HPA axis stress response and glucocorticoid levels, and the most prominent are early life adversity, or exposure to traumatic stress. We hypothesise that when the HPA axis is so disturbed after early life adversity, it will fundamentally alter hepatic gluconeogenesis, inducing hyperglycaemia, and hence crystalise the significant lifelong risk of developing either the metabolic syndrome, or type 2 diabetes. This gives a "Jekyll and Hyde" role to gluconeogenesis, providing the necessary energy in situations of acute stress, but driving towards pathophysiological consequences when the HPA axis has been altered.

The COVID-19 Pandemic: Does Our Early Life Environment, Life Trajectory and Socioeconomic Status Determine Disease Susceptibility and Severity?

A poor socioeconomic environment and social adversity are fundamental determinants of human life span, well-being and health. Previous influenza pandemics showed that socioeconomic factors may determine both disease detection rates and overall outcomes, and preliminary data from the ongoing coronavirus disease (COVID-19) pandemic suggests that this is still true. Over the past years it has become clear that early-life adversity (ELA) plays a critical role biasing the immune system towards a pro-inflammatory and senescent phenotype many years later. Cytotoxic T-lymphocytes (CTL) appear to be particularly sensitive to the early life social environment. As we understand more about the immune response to SARS-CoV-2 it appears that a functional CTL (CD8+) response is required to clear the infection and COVID-19 severity is increased as the CD8+ response becomes somehow diminished or exhausted. This raises the hypothesis that the ELA-induced pro-inflammatory and senescent phenotype may play a role in determining the clinical course of COVID-19, and the convergence of ELA-induced senescence and COVID-19 induced exhaustion represents the worst-case scenario with the least effective T-cell response. If the correct data is collected, it may be possible to separate the early life elements that have made people particularly vulnerable to COVID-19 many years later. This will, naturally, then help us identify those that are most at risk from developing the severest forms of COVID-19. In order to do this, we need to recognize socioeconomic and early-life factors as genuine medically and clinically relevant data that urgently need to be collected. Finally, many biological samples have been collected in the ongoing studies. The mechanisms linking the early life environment with a defined later-life phenotype are starting to be elucidated, and perhaps hold the key to understanding inequalities and differences in the severity of COVID-19.