Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder.

Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed health problems, prior pharmacological treatments, and polygenic scores (PGS) has potential to inform risk stratification. We examined self-reported SB and ideation using the Columbia Suicide Severity Rating Scale (C-SSRS) among 3,942 SCZ and 5,414 BPI patients receiving care within the Veterans Health Administration (VHA). These cross-sectional data were integrated with electronic health records (EHRs), and compared across lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. PGS were constructed using available genomic data for related traits. Genome-wide association studies were performed to identify and prioritize specific loci. Only 20% of the veterans who reported SB had a corroborating ICD-9/10 EHR code. Among those without prior SB, more than 20% reported new-onset SB at follow-up. SB were associated with a range of additional clinical diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking initiation, suicide attempt, and major depressive disorder were associated with SB. The GWAS for SB yielded no significant loci. Among individuals with a diagnosed mental illness, self-reported SB were strongly associated with clinical variables across several EHR domains. Analyses point to sequelae of substance-related and psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in health records, underscoring the value of regular screening with direct, in-person assessments, especially among high-risk individuals.

Self-healing codes: How stable neural populations can track continually reconfiguring neural representations.

As an adaptive system, the brain must retain a faithful representation of the world while continuously integrating new information. Recent experiments have measured population activity in cortical and hippocampal circuits over many days and found that patterns of neural activity associated with fixed behavioral variables and percepts change dramatically over time. Such "representational drift" raises the question of how malleable population codes can interact coherently with stable long-term representations that are found in other circuits and with relatively rigid topographic mappings of peripheral sensory and motor signals. We explore how known plasticity mechanisms can allow single neurons to reliably read out an evolving population code without external error feedback. We find that interactions between Hebbian learning and single-cell homeostasis can exploit redundancy in a distributed population code to compensate for gradual changes in tuning. Recurrent feedback of partially stabilized readouts could allow a pool of readout cells to further correct inconsistencies introduced by representational drift. This shows how relatively simple, known mechanisms can stabilize neural tuning in the short term and provides a plausible explanation for how plastic neural codes remain integrated with consolidated, long-term representations.

Autoregulation of switching behavior by cellular compartment size.

SignificanceBiochemical reactions often occur in small volumes within a cell, restricting the number of molecules to the hundreds or even tens. At this scale, reactions are discrete and stochastic, making reliable signaling difficult. This paper shows that the transition between discrete, stochastic reactions and macroscopic reactions can be exploited to make a self-regulating switch. This constitutes a previously unidentified kind of reaction network that may be present in small structures, such as synapses.

Chemical editing of proteoglycan architecture.

Proteoglycans are heterogeneous macromolecular glycoconjugates that orchestrate many important cellular processes. While much attention has focused on the poly-sulfated glycosaminoglycan chains that decorate proteoglycans, other important elements of their architecture, such as core proteins and membrane localization, have garnered less emphasis. Hence, comprehensive structure-function relationships that consider the replete proteoglycan architecture as glycoconjugates are limited. Here we present an extensive approach to study proteoglycan structure and biology by fabricating defined semisynthetic modular proteoglycans that can be tailored for cell surface display. The expression of proteoglycan core proteins with unnatural amino acids permits bioorthogonal click chemistry with functionalized glycosaminoglycans for methodical dissection of the parameters required for optimal binding and function of various proteoglycan-binding proteins. We demonstrate that these sophisticated materials can recapitulate the functions of native proteoglycan ectodomains in mouse embryonic stem cell differentiation and cancer cell spreading while permitting the analysis of the contributing architectural elements toward function.

Variational log-Gaussian point-process methods for grid cells.

We present practical solutions to applying Gaussian-process (GP) methods to calculate spatial statistics for grid cells in large environments. GPs are a data efficient approach to inferring neural tuning as a function of time, space, and other variables. We discuss how to design appropriate kernels for grid cells, and show that a variational Bayesian approach to log-Gaussian Poisson models can be calculated quickly. This class of models has closed-form expressions for the evidence lower-bound, and can be estimated rapidly for certain parameterizations of the posterior covariance. We provide an implementation that operates in a low-rank spatial frequency subspace for further acceleration, and demonstrate these methods on experimental data.

Genotyping Array Design and Data Quality Control in the Million Veteran Program.

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect biosamples with consent from at least one million veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records, make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide a genome-wide scan of the entire cohort, in parallel with whole-genome sequencing, methylation, and other 'omics assays. Here, we present the design and performance of the MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality-control analysis was developed and conducted on an initial tranche of 485,856 individuals, leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high-quality genotypes not only on common variants but also on rare variants. We confirmed that, with non-European individuals making up nearly 30%, MVP's substantial ancestral diversity surpasses that of other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current dataset has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Hydrogen-Deuterium Exchange Epitope Mapping of Glycosylated Epitopes Enabled by Online Immobilized Glycosidase.

Hydrogen-deuterium exchange coupled with mass spectrometry (HDX-MS) is widely used for monoclonal antibody (mAb) epitope mapping, which aids in the development of therapeutic mAbs and vaccines, as well as enables the understanding of viral immune evasion. Numerous mAbs are known to recognize N-glycosylated epitopes and to bind in close proximity to an N-glycan site; however, glycosylated protein sites are typically obscured from HDX detection as a result of the inherent heterogeneity of glycans. To overcome this limitation, we covalently immobilized the glycosidase PNGase Dj on a solid resin and incorporated it into an online HDX-MS workflow for post-HDX deglycosylation. The resin-immobilized PNGase Dj exhibited robust tolerance to various buffer conditions and was employed in a column format that can be readily adapted into a typical HDX-MS platform. Using this system, we were able to obtain full sequence coverage of the SARS-CoV-2 receptor-binding domain (RBD) and map the glycosylated epitope of the glycan-binding mAb S309 to the RBD.

Returning Individual Research Results to Vulnerable Individuals.

Although issues associated with returning individual research results to study participants have been well explored, these issues have been less thoroughly investigated in vulnerable individuals and populations. Considerations regarding return of research results to these individuals and populations, including how best to ensure truly informed consent, how to minimize the risks and benefits of the return of research results, and how best to ensure justice may differ from those of the population at large. This article discusses the issues and challenges associated with the return of individual research results (such as genomic, proteomic, or other biomarker data) to potentially vulnerable individuals and populations, including those who may be vulnerable for cognitive, communicative, institutional, social, deferential, medical, economic, or social reasons. It explores factors that should be considered in the design, conduct, and oversight of ethically responsible research involving the return of research results to vulnerable individuals and populations and discuss recommendations for those engaged in this work.

Mapping glycan-mediated galectin-3 interactions by live cell proximity labeling.

Galectin-3 is a glycan-binding protein (GBP) that binds ß-galactoside glycan structures to orchestrate a variety of important biological events, including the activation of hepatic stellate cells and regulation of immune responses. While the requisite glycan epitopes needed to bind galectin-3 have long been elucidated, the cellular glycoproteins that bear these glycan signatures remain unknown. Given the importance of the three-dimensional (3D) arrangement of glycans in dictating GBP interactions, strategies that allow the identification of GBP receptors in live cells, where the native glycan presentation and glycoprotein expression are preserved, have significant advantages over static and artificial systems. Here we describe the integration of a proximity labeling method and quantitative mass spectrometry to map the glycan and glycoprotein interactors for galectin-3 in live human hepatic stellate cells and peripheral blood mononuclear cells. Understanding the identity of the glycoproteins and defining the structures of the glycans will empower efforts to design and develop selective therapeutics to mitigate galectin-3-mediated biological events.

FENS-Kavli Network of Excellence: Science needs strong European cohesion.

Decades of scientific collaboration have brought innovation, prosperity and wide societal benefit to Europe. However, recent political events have impacted pan-European research and collaborations, and solutions are yet to materialise. Here, we argue that a vibrant, united European Research community led by its members and independent from political bodies is needed for Europe to remain a successful, interconnected scientific hub and keep delivering globally competitive science. The Federation of European Neuroscience Societies (FENS) is in an ideal position to play a paramount role in this endeavour.

Neuromodulation of circuits with variable parameters: single neurons and small circuits reveal principles of state-dependent and robust neuromodulation.

Neuromodulation underlies many behavioral states and has been extensively studied in small circuits. This has allowed the systematic exploration of how neuromodulatory substances and the neurons that release them can influence circuit function. The physiological state of a network and its level of activity can have profound effects on how the modulators act, a phenomenon known as state dependence. We provide insights from experiments and computational work that show how state dependence can arise and the consequences it can have for cellular and circuit function. These observations pose a general unsolved question that is relevant to all nervous systems: How is robust modulation achieved in spite of animal-to-animal variability and degenerate, nonlinear mechanisms for the production of neuronal and network activity?

Hippocampal neurogenesis promotes preference for future rewards.

Adult hippocampal neurogenesis has been implicated in a number of disorders where reward processing is disrupted but whether new neurons regulate specific aspects of reward-related decision making remains unclear. Given the role of the hippocampus in future-oriented cognition, here we tested whether adult neurogenesis regulates preference for future, advantageous rewards in a delay discounting paradigm for rats. Indeed, blocking neurogenesis caused a profound aversion for delayed rewards, and biased choice behavior toward immediately available, but smaller, rewards. Consistent with a role for the ventral hippocampus in impulsive decision making and future-thinking, neurogenesis-deficient animals displayed reduced activity in the ventral hippocampus. In intact animals, delay-based decision making restructured dendrites and spines in adult-born neurons and specifically activated adult-born neurons in the ventral dentate gyrus, relative to dorsal activation in rats that chose between immediately-available rewards. Putative developmentally-born cells, located in the superficial granule cell layer, did not display task-specific activity. These findings identify a novel and specific role for neurogenesis in decisions about future rewards, thereby implicating newborn neurons in disorders where short-sighted gains are preferred at the expense of long-term health.

Glycoengineering: scratching the surface.

At the surface of many cells is a compendium of glycoconjugates that form an interface between the cell and its surroundings; the glycocalyx. The glycocalyx serves several functions that have captivated the interest of many groups. Given its privileged residence, this meshwork of sugar-rich biomolecules is poised to transmit signals across the cellular membrane, facilitating communication with the extracellular matrix and mediating important signalling cascades. As a product of the glycan biosynthetic machinery, the glycocalyx can serve as a partial mirror that reports on the cell's glycosylation status. The glycocalyx can also serve as an information-rich barrier, withholding the entry of pathogens into the underlying plasma membrane through glycan-rich molecular messages. In this review, we provide an overview of the different approaches devised to engineer glycans at the cell surface, highlighting considerations of each, as well as illuminating the grand challenges that face the next era of 'glyco-engineers'. While we have learned much from these techniques, it is evident that much is left to be unearthed.

Fundamental bounds on learning performance in neural circuits.

How does the size of a neural circuit influence its learning performance? Larger brains tend to be found in species with higher cognitive function and learning ability. Intuitively, we expect the learning capacity of a neural circuit to grow with the number of neurons and synapses. We show how adding apparently redundant neurons and connections to a network can make a task more learnable. Consequently, large neural circuits can either devote connectivity to generating complex behaviors or exploit this connectivity to achieve faster and more precise learning of simpler behaviors. However, we show that in a biologically relevant setting where synapses introduce an unavoidable amount of noise, there is an optimal size of network for a given task. Above the optimal network size, the addition of neurons and synaptic connections starts to impede learning performance. This suggests that the size of brain circuits may be constrained by the need to learn efficiently with unreliable synapses and provides a hypothesis for why some neurological learning deficits are associated with hyperconnectivity. Our analysis is independent of specific learning rules and uncovers fundamental relationships between learning rate, task performance, network size, and intrinsic noise in neural circuits.

Neuronal oscillator robustness to multiple global perturbations.

Neuronal activity depends on ion channels and biophysical processes that are strongly and differentially sensitive to physical variables such as temperature and pH. Nonetheless, neuronal oscillators can be surprisingly resilient to perturbations in these variables. We study a three-neuron pacemaker ensemble that drives the pyloric rhythm of the crab, Cancer borealis. These crabs routinely experience a number of global perturbations, including changes in temperature and pH. Although pyloric oscillations are robust to such changes, for sufficiently large deviations the rhythm reversibly breaks down. As temperature increases beyond a tipping point, oscillators transition to silence. Acidic pH deviations also show tipping points, with a reliable transition first to tonic spiking, then to silence. Surprisingly, robustness to perturbations in pH only moderately affects temperature robustness. Consistent with high animal-to-animal variability in biophysical circuit parameters, tipping points in temperature and pH vary across animals. However, the ordering and discrete classes of transitions at critical points are conserved. This implies that qualitative oscillator dynamics are preserved across animals despite high quantitative parameter variability. A universal model of bursting dynamics predicts the existence of these transition types and the order in which they occur.

Paradoxical relationships between active transport and global protein distributions in neurons.

Neural function depends on continual synthesis and targeted trafficking of intracellular components, including ion channel proteins. Many kinds of ion channels are trafficked over long distances to specific cellular compartments. This raises the question of whether cargo is directed with high specificity during transit or whether cargo is distributed widely and sequestered at specific sites. We addressed this question by experimentally measuring transport and expression densities of Kv4.2, a voltage-gated transient potassium channel that exhibits a specific dendritic expression that increases with distance from the soma and little or no functional expression in axons. In over 500 h of quantitative live imaging, we found substantially higher densities of actively transported Kv4.2 subunits in axons as opposed to dendrites. This paradoxical relationship between functional expression and traffic density supports a model-commonly known as the sushi belt model-in which trafficking specificity is relatively low and active sequestration occurs in compartments where cargo is expressed. In further support of this model, we find that kinetics of active transport differs qualitatively between axons and dendrites, with axons exhibiting strong superdiffusivity, whereas dendritic transport resembles a weakly directed random walk, promoting mixing and opportunity for sequestration. Finally, we use our data to constrain a compartmental reaction-diffusion model that can recapitulate the known Kv4.2 density profile. Together, our results show how nontrivial expression patterns can be maintained over long distances with a relatively simple trafficking mechanism and how the hallmarks of a global trafficking mechanism can be revealed in the kinetics and density of cargo.

Adult-Born Hippocampal Neurons Undergo Extended Development and Are Morphologically Distinct from Neonatally-Born Neurons.

During immature stages, adult-born neurons pass through critical periods for survival and plasticity. It is generally assumed that by 2 months of age adult-born neurons are mature and equivalent to the broader neuronal population, raising questions of how they might contribute to hippocampal function in old age when neurogenesis has declined. However, few have examined adult-born neurons beyond the critical period or directly compared them to neurons born in infancy. Here, we used a retrovirus to visualize functionally relevant morphological features of 2- to 24-week-old adult-born neurons in male rats. From 2 to 7 weeks, neurons grew and attained a relatively mature phenotype. However, several features of 7-week-old neurons suggested a later wave of growth: these neurons had larger nuclei, thicker dendrites, and more dendritic filopodia than all other groups. Indeed, between 7 and 24 weeks, adult-born neurons gained additional dendritic branches, formed a second primary dendrite, acquired more mushroom spines, and had enlarged mossy fiber presynaptic terminals. Compared with neonatal-born neurons, old adult-born neurons had greater spine density, larger presynaptic terminals, and more putative efferent filopodial contacts onto inhibitory neurons. By integrating rates of cell birth and growth across the life span, we estimate that adult neurogenesis ultimately produces half of the cells and the majority of spines in the dentate gyrus. Critically, protracted development contributes to the plasticity of the hippocampus through to the end of life, even after cell production declines. Persistent differences from neonatal-born neurons may additionally endow adult-born neurons with unique functions even after they have matured.SIGNIFICANCE STATEMENT Neurogenesis occurs in the hippocampus throughout adult life and contributes to memory and emotion. It is generally assumed that new neurons have the greatest impact on behavior when they are immature and plastic. However, since neurogenesis declines dramatically with age, it is unclear how they might contribute to behavior later in life when cell proliferation has slowed. Here we find that newborn neurons mature over many months in rats and may end up with distinct morphological features compared with neurons born in infancy. Using a mathematical model, we estimate that a large fraction of neurons is added in adulthood. Moreover, their extended growth produces a reserve of plasticity that persists even after neurogenesis has declined to low rates.

Return of Individual Research Results: A Guide for Biomedical Researchers Utilizing Human Biospecimens.

The recent movement toward returning individual research results to study subjects/participants generates ethical and legal challenges for laboratories performing research on human biospecimens. The concept of an individual's interest in knowing the results of testing on their tissue is pitted against individual and systemic risks and an established legal framework regulating the performance of laboratory testing for medical care purposes. This article discusses the rationale for returning individual research results to subjects, the potential risks associated with returning these results, and the legal framework in the United States that governs testing of identifiable human biospecimens. On the basis of these considerations, this article provides recommendations for investigators to consider when planning and executing human biospecimen research, with the objective of appropriately balancing the interests of research subjects, the need for ensuring integrity of the research process, and compliance with US laws and regulations.

Testing for Severe Acute Respiratory Syndrome-Coronavirus 2: Challenges in Getting Good Specimens, Choosing the Right Test, and Interpreting the Results.

OBJECTIVES: We explore ways to reduce errors in laboratory diagnosis of severe acute respiratory syndrome-coronavirus 2 infection by considering preanalytic, analytic, and postanalytic sources. To address preanalytic challenges, we first consider alternative anatomic sites for specimen collection, then discuss self-collection, alternative sampling devices, and transport media. Strengths and limitations of various analytic test systems are considered in the context of postanalytic challenges associated with making test results meaningful, specifically considering the complex relationship between "positive" test results and reproduction and shedding of intact virus. Finally, we provide recommendations regarding healthcare worker surveillance and release of patients with coronavirus disease 2019 from isolation. DATA SOURCES: Material was derived from a Webinar available to the public, manufacturer's websites, U.S. Food and Drug Administration, and Centers for Disease Control and Prevention websites and from both peer-reviewed papers identified by PubMed search and nonpeer-reviewed papers posted on Biorxiv and Medrxiv. Unpublished data came from the Washington State Department of Health. STUDY SELECTION: We included studies that compared diagnostic performance strategies without introducing bias due to use of an imperfect gold standard. Case series and case reports were included as necessary to illuminate the significance of results. DATA EXTRACTION: Data were extracted manually. DATA SYNTHESIS: Sensitivity, specificity, and CIs were computed from article data using a composite reference standard. Nucleic acid-based tests were assumed to perform at 100% specificity. CONCLUSIONS: Although sputum and bronchoalveolar lavage samples provide the highest diagnostic sensitivity for severe acute respiratory syndrome-coronavirus 2, nasopharyngeal, mid turbinate, and nasal specimens are suitable in most cases and require less use of personal protective equipment. When desired sampling materials are unavailable, alternatives may be substituted with no loss of performance. Both reverse transcriptase polymerase chain reaction tests and rapid nucleic acid-based tests offer good performance in most circumstances. Testing is not required to release most patients from isolation.

Genome-wide association study of cognitive performance in U.S. veterans with schizophrenia or bipolar disorder.

Cognitive impairment is a frequent and serious problem in patients with various forms of severe mental illnesses (SMI), including schizophrenia (SZ) and bipolar disorder (BP). Recent research suggests genetic links to several cognitive phenotypes in both SMI and in the general population. Our goal in this study was to identify potential genomic signatures of cognitive functioning in veterans with severe mental illness and compare them to previous findings for cognition across different populations. Veterans Affairs (VA) Cooperative Studies Program (CSP) Study #572 evaluated cognitive and functional capacity measures among SZ and BP patients. In conjunction with the VA Million Veteran Program, 3,959 European American (1,095 SZ, 2,864 BP) and 2,601 African American (1,095 SZ, 2,864 BP) patients were genotyped using a custom Affymetrix Axiom Biobank array. We performed a genome-wide association study of global cognitive functioning, constructed polygenic scores for SZ and cognition in the general population, and examined genetic correlations with 2,626 UK Biobank traits. Although no single locus attained genome-wide significance, observed allelic effects were strongly consistent with previous studies. We observed robust associations between global cognitive functioning and polygenic scores for cognitive performance, intelligence, and SZ risk. We also identified significant genetic correlations with several cognition-related traits in UK Biobank. In a diverse cohort of U.S. veterans with SZ or BP, we demonstrate broad overlap of common genetic effects on cognition in the general population, and find that greater polygenic loading for SZ risk is associated with poorer cognitive performance.