Morphological correlates of pyramidal cell axonal myelination in mouse and human neocortex.

The axons of neocortical pyramidal neurons are frequently myelinated. Heterogeneity in the topography of axonal myelination in the cerebral cortex has been attributed to a combination of electrophysiological activity, axonal morphology, and neuronal-glial interactions. Previously, we showed that axonal segment length and caliber are critical local determinants of fast-spiking interneuron myelination. However, the factors that determine the myelination of individual axonal segments along neocortical pyramidal neurons remain largely unexplored. Here, we used structured illumination microscopy to examine the extent to which axonal morphology is predictive of the topography of myelination along neocortical pyramidal neurons. We identified critical thresholds for axonal caliber and interbranch distance that are necessary, but not sufficient, for myelination of pyramidal cell axons in mouse primary somatosensory cortex (S1). Specifically, we found that pyramidal neuron axonal segments with a caliber < 0.24 µm or interbranch distance < 18.10 µm are rarely myelinated. Moreover, we further confirmed that these findings in mice are similar for human neocortical pyramidal cell myelination (caliber < 0.25 µm, interbranch distance < 19.00 µm), suggesting that this mechanism is evolutionarily conserved. Taken together, our findings suggest that axonal morphology is a critical correlate of the topography and cell-type specificity of neocortical myelination.

iPSC-derived healthy human astrocytes selectively load miRNAs targeting neuronal genes into extracellular vesicles.

Astrocytes are in constant communication with neurons during the establishment and maturation of functional networks in the developing brain. Astrocytes release extracellular vesicles (EVs) containing microRNA (miRNA) cargo that regulates transcript stability in recipient cells. Astrocyte released factors are thought to be involved in neurodevelopmental disorders. Healthy astrocytes partially rescue Rett Syndrome (RTT) neuron function. EVs isolated from stem cell progeny also correct aspects of RTT. EVs cross the blood-brain barrier (BBB) and their cargo is found in peripheral blood which may allow non-invasive detection of EV cargo as biomarkers produced by healthy astrocytes. Here we characterize miRNA cargo and sequence motifs in healthy human astrocyte derived EVs (ADEVs). First, human induced Pluripotent Stem Cells (iPSC) were differentiated into Neural Progenitor Cells (NPCs) and subsequently into astrocytes using a rapid differentiation protocol. iPSC derived astrocytes expressed specific markers, displayed intracellular calcium transients and secreted ADEVs. miRNAs were identified by RNA-Seq on astrocytes and ADEVs and target gene pathway analysis detected brain and immune related terms. The miRNA profile was consistent with astrocyte identity, and included approximately 80 miRNAs found in astrocytes that were relatively depleted in ADEVs suggestive of passive loading. About 120 miRNAs were relatively enriched in ADEVs and motif analysis discovered binding sites for RNA binding proteins FUS, SRSF7 and CELF5. miR-483-5p was the most significantly enriched in ADEVs. This miRNA regulates MECP2 expression in neurons and has been found differentially expressed in blood samples from RTT patients. Our results identify potential miRNA biomarkers selectively sorted into ADEVs and implicate RNA binding protein sequence dependent mechanisms for miRNA cargo loading.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness.

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Prevalence and incidence measures for schizophrenia among commercial health insurance and medicaid enrollees.

Given the chronic nature of schizophrenia, it is important to examine age-specific prevalence and incidence to understand the scope of the burden of schizophrenia across the lifespan. Estimates of lifetime prevalence of schizophrenia have varied widely and have often relied upon community-based data estimates from over two decades ago, while more recent studies have shown considerable promise by leveraging pooled datasets. However, the validity of measures of schizophrenia, particularly new onset schizophrenia, has not been well studied in these large health databases. The current study examines prevalence and validity of incidence measures of new diagnoses of schizophrenia in 2019 using two U.S. administrative health databases: MarketScan, a national database of individuals receiving employer-sponsored commercial insurance (N = 16,365,997), and NYS Medicaid, a large state public insurance program (N = 4,414,153). Our results indicate that the prevalence of schizophrenia is over 10-fold higher, and the incidence two-fold higher, in the NYS Medicaid population compared to the MarketScan database. In addition, prevalence increased over the lifespan in the Medicaid population, but decreased in the employment based MarketScan database beginning in early adulthood. Incident measures of new diagnoses of schizophrenia had excellent validity, with positive predictive values and specificity exceeding 95%, but required a longer lookback period for Medicaid compared to MarketScan. Further work is needed to leverage these findings to develop robust clinical outcome predictors for new onset of schizophrenia within large administrative health data systems.