Biology subjects

Harris, K. M.

Publications and source records attributed to Harris, K. M..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart

Resilience to cardiac stress is essential for health, yet the relationship between cardiomyocyte (CM) stress response and local microenvironment remains unclear. Here, we combined MERFISH spatial transcriptome profiling with Cellouette, an improved cell segmentation method, to determine CM-microenvironment relationships in a mouse model of ventricular pressure overload. We report the shape, transcription profile, spatial organization, and physical connectivity for >400,000 cells across stressed and healthy tissues. Under stress, CMs adopted a spectrum of emergent transcriptional states, with advanced states marked by a metabolic and pro-fibrotic shift. To discover CM-environment relationships, we performed a network analysis of physical cell connectivity combined with cell-type-specific profiling. We found that pro-fibrotic CM progression was tightly linked to distinct local microenvironments, and CM metabolic shifts could be inferred from transcriptional patterns in neighboring non-CM cells, revealing microenvironmental imprints of disease. We thus provide a resource for understanding the heterogeneity of outcome during cardiac pressure overload. HighlightsO_LICellouette provides accurate segmentation for single-cell spatial transcriptomics in cardiac tissue. C_LIO_LIPressure overload creates spatial gradients of cardiomyocyte pro-fibrotic states. C_LIO_LICardiomyocyte pro-fibrotic progression is linked to changes in local cell composition and gene expression. C_LIO_LITranscriptional states of non-muscle cells predict metabolic state of adjacent cardiomyocytes. C_LI

genomics↗

bioRxiv2025

Curvature-based machine learning method for automated segmentation of dendritic spines

AO_SCPLOWBSTRACTC_SCPLOWRecent advances in connectomics have been led by high-resolution reconstruction of large volumes of neural tissues using electron microscopy (EM), providing unprecedented insights into brain structure and function. Dendritic spines--dynamic protrusions on neuronal dendrites--play crucial roles in synaptic plasticity, influencing learning, memory, and various neurological disorders. However, current spine analysis methods often rely on manual annotation of subcellular features, limiting their ability to handle the complexity of spines in dense dendritic networks. This paper introduces a novel automated computational framework that integrates discrete differential geometry, machine learning, and 3D image processing to analyze dendritic spines in these intricate environments. By generating distributions of spine morphology from high resolution images including many thousands of spines, our approach captures subtle variations in spine shapes, offering a nuanced understanding of their roles in synaptic function. This framework is tested on multiple EM datasets, with the aim of enhancing our understanding of synaptic plasticity and its alterations in disease states. The proposed method is poised to accelerate neuroscience research by providing a scalable, objective, and comprehensive solution for spine analysis, uncovering insights into the role of spine geometry for neural function.

neuroscience↗

bioRxiv2025

Synaptopodin KO rat for assessing the dendritic spine apparatus and axonal cisternal organelle in synaptic plasticity, development, and behavior

The actin-binding protein synaptopodin (Synpo) regulates the cytoskeleton and organization of endoplasmic reticulum, thereby amplifying intracellular Ca2+ signaling. Knockout (KO) mouse models have been used to study the role of Synpo in kidney and brain functions, where it supports stress fiber formation, as well as long-term potentiation (LTP) and learning, respectively. Here, we generated Synpo KO rats using CRISPR-Cas9, and show they are viable but have reduced body weight after postnatal days 35-45, along with shorter limb bone length. Their basal kidney function is normal into early adulthood. Serial section electron microscopy from Synpo KO rat hippocampus reveals the absence of the spine apparatus in dendrites and cisternal organelle in the axon initial segment (AIS), two Synpo-dependent specializations of smooth endoplasmic reticulum. The AIS in KO was still innervated by inhibitory synapses despite the total loss of the cisternal organelle. Synpo KO rats also showed reduced LTP. Previously unknown KO effect of Synpo on body stature could have an inadvertent impact on behavioral outcomes. Furthermore, rats have a well-defined developmental onset of LTP, compared to the variable onset of LTP in mice. This, combined with known species differences in behavior, makes our KO rat model a valuable resource for assessing the role of Synpo in development, learning, synaptic plasticity, and a wide range of other biological functions.

neuroscience↗

bioRxiv2025

Perisynaptic astroglial response to in vivo long-term potentiation and concurrent long-term depression in the hippocampal dentate gyrus.

Perisynaptic astroglia provide critical molecular and structural support to regulate synaptic transmission and plasticity in the nanodomain of the axon-spine interface. Three-dimensional reconstruction from serial section electron microscopy (3DEM) was used to investigate relationships between perisynaptic astroglia and dendritic spine synapses undergoing plasticity in the hippocampus of awake adult male rats. Delta-burst stimulation (DBS) of the medial perforant pathway induced long-term potentiation (LTP) in the middle molecular layer and concurrent long-term depression (cLTD) in the outer molecular layer of the dentate gyrus. The contralateral hippocampus received baseline stimulation as a within-animal control. Brains were obtained 30 minutes or 2 hours after DBS onset. An automated 3DEM pipeline was developed to enable unbiased quantification of astroglial coverage at the perimeter of the axon-spine interface. Under all conditions, >85% of synapses had perisynaptic astroglia processes within 120 nm of some portion of the perimeter. LTP broadened the distribution of spine sizes while reducing the presence and proximity of perisynaptic astroglia near the axon-spine interface of large spines. In contrast, cLTD transiently reduced the length of the axon-spine interface perimeter without substantially altering astroglial apposition. The postsynaptic density was discovered to be displaced from the center of the axon-spine interface, with this offset increasing during LTP and decreasing during cLTD. Astroglial access to the postsynaptic density was diminished during LTP and enhanced during cLTD, in parallel with changes in spine size. Thus, access of perisynaptic astroglia to synapses is dynamically modulated during LTP and cLTD alongside synaptic remodeling. Significance StatementPerisynaptic astroglia provide critical molecular and structural regulation of synaptic plasticity underlying learning and memory. The hippocampal dentate gyrus, a brain region crucial for learning and memory, was found to have perisynaptic astroglia at the axon-spine interface of >85% of excitatory synapses measured. Long-term potentiation triggered the retraction of perisynaptic astroglia processes selectively from large synapses. This retraction decreased access of perisynaptic astroglia to the postsynaptic density, which was discovered to be located off-center in the axon-spine interface. Concurrent long-term depression temporarily (< 2 h) decreased spine perimeter and thus increased access of synapses to perisynaptic astroglia. These findings provide new insights into how the structural dynamics of spines and synapses shape access to perisynaptic astroglia.

neuroscience↗

bioRxiv2025

Presynaptic vesicles supply membrane for axonal bouton enlargement during LTP

Long-term potentiation (LTP) induces presynaptic bouton enlargement and a reduction in the number of synaptic vesicles. To understand the relationship between these events, we performed 3D analysis of serial section electron micrographs in rat hippocampal area CA1, 2 hours after LTP induction. We observed a high vesicle packing density in control boutons, contrasting with a lower density in most LTP boutons. Notably, the summed membrane area of the vesicles lost in low-density LTP boutons is comparable to the surface membrane required for the observed bouton enlargement when compared to high-density control boutons. These novel findings suggest that presynaptic vesicle density provides a new structural indicator of LTP that supports a local mechanism of bouton enlargement.

neuroscience↗

bioRxiv2025

PyReconstruct: A fully opensource, collaborative successor to Reconstruct

As the serial section community transitions to volume electron microscopy, tools are needed to balance rapid segmentation efforts with documenting the fine detail of structures that support cell function. New annotation applications should be accessible to users and meet the needs of the neuroscience and connectomics communities while also being useful across other disciplines. Issues not currently addressed by a single, modern annotation application include: 1) built-in curation systems with utilities for expert intervention to provide quality assurance, 2) integrated alignment features that allow for image registration on-the-fly as image flaws are discovered during annotation, 3) simplicity for non-specialists within and beyond the neuroscience community, 5) a system to store experimental meta-data with annotation data in a way that researchers remain masked regarding condition to avoid potential biases, 6) local management of large datasets, 7) fully open-source codebase allowing development of new tools, and more. Here, we present PyReconstruct, a modern successor to the Reconstruct annotation tool. PyReconstruct operates in a field-agnostic manner, runs on all major operating systems, breaks through legacy RAM limitations, features an intuitive and collaborative curation system, and employs a flexible and dynamic approach to image registration. It can be used to analyze, display, and publish experimental or connectomics data. PyReconstruct is suited for generating ground truth to implement in automated segmentation, outcomes of which can be returned to PyReconstruct for proofreading and quality control. Significance statementIn neuroscience, the emerging field of connectomics has produced annotation tools for reconstruction that prioritize circuit connectivity across microns to centimeters and farther. Determining the strength of synapses forming the connections is crucial to understand function and requires quantification of their nanoscale dimensions and subcellular composition. PyReconstruct, successor to the early annotation tool Reconstruct, meets these requirements for synapses and other structures well beyond neuroscience. PyReconstruct lifts many restrictions of legacy Reconstruct and offers a user-friendly interface, integrated curation, dynamic alignment, nanoscale quantification, 3D visualization, and more. Extensive compatibility with third-party software provides access to the expanding tools from the connectomics and imaging communities.

cell biology↗

bioRxiv2024

The presynaptic vesicle cluster transitions from a compact to loose organization during long-term potentiation

Functional and structural elements of synaptic plasticity are tightly coupled, as has been extensively shown for dendritic spines. Here, we interrogated structural features of presynaptic terminals in 3DEM reconstructions from CA1 hippocampal axons that had undergone control stimulation or theta-burst stimulation (TBS) to produce long-term potentiation (LTP). We reveal that after LTP induction, the synaptic vesicle (SV) cluster is less dense, and SVs are more dispersed. The distances between neighboring SVs are greater in less dense terminals and have more SV-associated volume. We characterized the changes to the SV cluster by measuring distances between neighboring SVs, distances to the active zone, and the dispersion of the SV cluster. Furthermore, we compared the distribution of SVs with randomized ones and provided evidence that SVs gained mobility after LTP induction. With a computational model, we can predict the increment of the diffusion coefficient of the SVs in the cluster. Moreover, using a machine learning approach, we identify presynaptic terminals that were potentiated after LTP induction. Lastly, we show that the local SV density is a volume-independent property under strong regulation. Altogether, these results provide evidence that the SV cluster is undergoing a transition during LTP.

neuroscience↗

bioRxiv2024

A deep learning-based strategy for producing dense 3D segmentations from sparsely annotated 2D images

Analyzing volumetric microscopy data requires dense segmentation, yet training accurate machine learning models demands prohibitively expensive 3D ground-truth. To overcome this bottleneck, we present a lightweight framework that bootstraps dense 3D instance segmentations directly from sparse 2D annotations. A 2D network trained on sparse labels predicts complete boundaries on every section, and a 3D network pre-trained on synthetic data infers inter-section connectivity to build coherent 3D volumes. We validated this 2D[->]3D method across diverse datasets spanning electron, expansion, and live-cell microscopy. Strikingly, 3D models trained on these rapidly generated pseudo ground-truths achieve accuracy comparable to those trained on dense expert annotations, yielding up to a 1,000-fold reduction in human annotation time. Even accounting for downstream proofreading, total reconstruction costs drop by an order of magnitude. This approach democratizes the generation of dense 3D training data, seamlessly extending 2D foundation models into the third dimension.

neuroscience↗

bioRxiv2024

The Sociodemographic and Lifestyle Correlates of Epigenetic Aging in a Nationally Representative U.S. Study of Younger Adults

ImportanceEpigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most of this research is based on older adult samples who already have measurable chronic disease. ObjectiveTo investigate whether and how sociodemographic and lifestyle characteristics are related to biological aging in a younger adult sample across a wide array of epigenetic clock measures. DesignNationally representative prospective cohort study. SettingUnited States (U.S.). ParticipantsData come from the National Longitudinal Study of Adolescent to Adult Health, a national cohort of adolescents in grades 7-12 in U.S. in 1994 followed for 25 years over five interview waves. Our analytic sample includes participants followed-up through Wave V in 2016-18 who provided blood samples for DNA methylation (DNAm) testing (n=4237) at Wave V. ExposureSociodemographic (sex, race/ethnicity, immigrant status, socioeconomic status, geographic location) and lifestyle (obesity status, exercise, tobacco, and alcohol use) characteristics. Main OutcomeBiological aging assessed from blood DNAm using 16 epigenetic clocks when the cohort was aged 33-44 in Wave V. ResultsWhile there is considerable variation in the mean and distribution of epigenetic clock estimates and in the correlations among the clocks, we found sociodemographic and lifestyle factors are more often associated with biological aging in clocks trained to predict current or dynamic phenotypes (e.g., PhenoAge, GrimAge and DunedinPACE) as opposed to clocks trained to predict chronological age alone (e.g., Horvath). Consistent and strong associations of faster biological aging were found for those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use. Conclusions and RelevanceOur study found important social and lifestyle factors associated with biological aging in a nationally representative cohort of younger-aged adults. These findings indicate that molecular processes underlying disease risk can be identified in adults entering midlife before disease is manifest and represent useful targets for interventions to reduce social inequalities in heathy aging and longevity. Key PointsO_ST_ABSQuestionC_ST_ABSAre epigenetic clocks, measures of biological aging developed mainly on older-adult samples, meaningful for younger adults and associated with sociodemographic and lifestyle characteristics in expected patterns found in prior aging research? FindingsSociodemographic and lifestyle factors were associated with biological aging in clocks trained to predict morbidity and mortality showing accelerated aging among those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use. MeaningAge-related molecular processes can be identified in younger-aged adults before disease manifests and represent potential interventions to reduce social inequalities in heathy aging and longevity.

genomics↗

bioRxiv2024

Long-Term Potentiation Produces a Sustained Expansion of Synaptic Information Storage Capacity in Adult Rat Hippocampus

Long-term potentiation (LTP) has become a standard model for investigating synaptic mechanisms of learning and memory. Increasingly, it is of interest to understand how LTP affects the synaptic information storage capacity of the targeted population of synapses. Here, structural synaptic plasticity during LTP was explored using three-dimensional reconstruction from serial section electron microscopy. Storage capacity was assessed by applying a new analytical approach, Shannon information theory, to delineate the number of functionally distinguishable synaptic strengths. LTP was induced by delta-burst stimulation of perforant pathway inputs to the middle molecular layer of hippocampal dentate granule cells in adult rats. Spine head volumes were measured as predictors of synaptic strength and compared between LTP and control hemispheres at 30 min and 2 hr after the induction of LTP. Synapses from the same axon onto the same dendrite were used to determine the precision of synaptic plasticity based on the similarity of their physical dimensions. Shannon entropy was measured by exploiting the frequency of spine heads in functionally distinguishable sizes to assess the degree to which LTP altered the number of bits of information storage. Outcomes from these analyses reveal that LTP expanded storage capacity; the distribution of spine head volumes was increased from 2 bits in controls to 3 bits at 30 min and 2.7 bits at 2 hr after the induction of LTP. Furthermore, the distribution of spine head volumes was more uniform across the increased number of functionally distinguishable sizes following LTP, thus achieving more efficient use of coding space across the population of synapses. SignificanceEstablishing relationships between structure, function, and information storage capacity provides a new approach to assessing network strength from structural measurements. Long term potentiation (LTP) is a standard model for investigating synaptic mechanisms of learning and memory. Information is a retrievable quantity that is being stored in synapses as synaptic strength and is correlated with multiple structural components of synaptic strength. Structural synaptic plasticity was measured in 3D reconstructions from serial section electron microscopy of spine head volume, as a proxy for synapse strength, at 30 min and 2 hr after LTP induction. Outcomes indicate that LTP enhances information storage capacity for at least 2 hr by increasing the precision of the synaptic structure and expanding the range of synapse sizes.

neuroscience↗

bioRxiv2022

Violation of the ultrastructural size principle in the dorsolateral prefrontal cortex underlies working memory impairment in the aged common marmoset (Callithrix jacchus)

Working memory relies critically on the dorsolateral prefrontal cortex (dlPFC). Morphology and function of the dlPFC, and corresponding working memory performance, are affected early in the aging process. However, these effects are heterogeneous, with nearly half of aged individuals spared of working memory deficits. Translationally relevant model systems are critical for investigating the neurobiological drivers of this variability and identifying why some people experience age-related working memory impairment while others do not. The common marmoset (Callithrix jacchus) is advantageous as a model in which to investigate the biological underpinnings of aging because, as a nonhuman primate, marmosets have a clearly defined dlPFC facilitating investigations of prefrontal-dependent cognitive functions, including working memory, and their short (~10 year) lifespan facilitates longitudinal studies of aging. Here, we conduct the first investigation of synaptic ultrastructure in the dlPFC of the marmoset and investigate whether there are changes to synaptic ultrastructure that are unique to aging with and without working memory impairment. To do this, we characterized working memory capacity in a cohort of marmosets that collectively covered their short lifespan, and found age-related working memory impairment. We also found a remarkable degree of heterogeneity in performance, similar to that found in humans. Utilizing three dimensional reconstruction from serial section electron microscopy, we visualized structural correlates of synaptic efficacy including boutons, mitochondria, and synapses in layer III of the dlPFC of three marmosets: one young adult (YA), one aged cognitively unimpaired (AU), and one aged cognitively impaired (AI). We find that aged marmosets have fewer synapses in dlPFC than young, and this is due to selective vulnerability of small synapses. Next, we tested the hypothesis that violation of the ultrastructural size principle underlies age-related working memory impairment. The ultrastructural size principle states that synaptic efficacy relies on coordinated scaling of synaptic components (e.g., synapses, mitochondria) with presynaptic boutons. While synapses and mitochondria scaled proportionally and were strongly correlated with presynaptic boutons in the YA and AU marmosets, the ultrastructural characteristics of the AI marmoset were alarmingly different. We found that age-related working memory impairment was associated with disproportionately large synapses compared to presynaptic boutons, specifically in those with mitochondria. Remarkably, presynaptic mitochondria and these boutons were completely decorrelated. We posit that this decorrelation results in mismatched energy supply and demand, leading to impaired synaptic transmission. This is the first report of age-related synapse loss in the marmoset, and the first demonstration that violation of the ultrastructural size principle underlies age-related working memory impairment.

neuroscience↗

bioRxiv2022

Regional and LTP-Dependent Variation of Synaptic Information Storage Capacity in Rat Hippocampus

Connectomics is generating an ever-increasing deluge of data, which challenges us to develop new methods for analyzing and extracting insights from these data. We introduce here a powerful method for analyzing three-dimensional reconstruction from serial section electron microscopy (3DEM) to measure synaptic information storage capacity (SISC) and apply it to data following in vivo long-term potentiation (LTP). Connectomic researchers have focused on the pattern of connectivity between neurons. The strengths of synapses have also been studied by quantifying the sizes of synapses. Importantly, synapses from the same axon onto the same dendrite have a common history of coactivation, making them a candidate for measuring the precision of synaptic plasticity based on the similarity of their dimensions. Quantifying precision is fundamental to understanding information storage and retrieval in neural circuits. We quantify this precision with Shannon information theory, which is a more reliable estimate than prior analyses based on signal detection theory because there is no overlap between states, and outliers do not artificially bias the outcome. Spine head volumes are well correlated with other measures of synaptic weight, thus SISC can be determined by identifying the non-overlapping clusters of dendritic spine head volumes to determine the number of distinguishable synaptic weights. SISC analysis of spine head volumes in the stratum radiatum of hippocampal area CA1 revealed 24 distinguishable states (4.1 bits). In contrast, spine head volumes in the middle molecular layer of control dentate gyrus occupied only 5 distinguishable states (2 bits). Thus, synapses in different hippocampal regions had significantly different SISCs. Moreover, these were not fixed properties but increased by 30 min following induction of LTP in the dentate gyrus to occupy 10 distinguishable states (3 bits), and this increase lasted for at least 2 hours. We also observed a broader and nearly uniform distribution of spine head volumes across the increased number of states, suggesting the distribution evolved towards the theoretical upper bound of SISC following LTP. For dentate granule cells these findings show that the spine size range was broadened by the interplay among synaptic plasticity mechanisms. SISC provides a new analytical measure to probe these mechanisms in normal and diseased brains.

neuroscience↗

bioRxiv2021

Social mobility and biological aging among older adults in the United States

Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may therefore extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We analyzed blood-chemistry and DNA methylation (DNAm) data from n=9286 participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study to test associations of life-course social mobility with biological aging. We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using three DNA methylation "clocks" and three blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ~0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility revealed differential effects by racial identity, suggesting that mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging. Significance StatementUpward social mobility may disrupt effects of early-life disadvantage on aging-related health decline. However, the stresses of crossing social boundaries can have biological costs. To investigate the balance of these forces, we analyzed social mobility from reports of childhood circumstances, education, and later-life wealth in 9,286 older adults in the US Health and Retirement Study. We quantified life-course health impacts of social mobility from blood-chemistry and DNA-methylation analysis of biological aging. We found that educational mobility alone benefited Black Americans less than White Americans, whereas mobility that produced accumulation of wealth into later-life was associated with delayed biological aging across social categories. Black-White disparities in healthy-aging outcomes of educational mobility may reflect inequalities in social gains realized from education.

physiology↗

bioRxiv2021

Uncovering the Genetic Architecture of Broad Antisocial Behavior through a Genome-Wide Association Study Meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8,058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, P = 6.32 x 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). The SNP-based heritability of ASB was 8.4% (s.e.= 1.2%). Polygenic-risk-score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg{square}={square}0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg{square}={square}0.54), cognitive ability (intelligence rg= -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg={square}- 0.58, fathers age at death rg= -0.54). Our findings provide a starting point towards identifying critical biosocial risk mechanisms for the development of ASB.

genetics↗

bioRxiv2021

Resource Profile and User Guide of the Polygenic Index Repository

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs prediction accuracies, we constructed them using genome-wide association studies--some of which are novel--from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the "additive SNP factor." Regressions in which the true regressor is the additive SNP factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

genomics↗

bioRxiv2020

Investigating the Genetic Architecture of Non-Cognitive Skills Using GWAS-by-Subtraction

Educational attainment (EA) is influenced by cognitive abilities and by other characteristics and traits. However little is known about the genetic architecture of these "non-cognitive" contributions to EA. Here, we use Genomic Structural Equation Modelling and results of prior genome-wide association studies (GWASs) of EA (N = 1,131,881) and cognitive test performance (N = 257,841) to estimate SNP associations with variation in EA that is independent of cognitive ability. We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in EA. Phenotypic and biological annotation revealed that (1) both cognitive and non-cognitive contributions to EA were genetically correlated with socioeconomic success and longevity; and (2) non-cognitive contributions to EA were related to personality, decision making, risk-behavior, and increased risk for psychiatric disorders; (3) non-cognitive and cognitive contributions to EA were enriched in the same tissues and cell types, but (4) showed different associations with gray-matter neuroimaging phenotypes.

genetics↗

bioRxiv2019

Ultrastructure of light-activated axons following optogenetic stimulation to produce late-phase long-term potentiation

Analysis of neuronal compartments has revealed many state-dependent changes in geometry but establishing synapse-specific mechanisms at the nanoscale has proven elusive. We co-expressed channelrhodopsin2-GFP and mAPEX2 in a subset of hippocampal CA3 neurons and used trains of light to induce late-phase long-term potentiation (L-LTP) in area CA1. L-LTP was shown to be specific to the labeled axons by severing CA3 inputs, which prevented back-propagating recruitment of unlabeled axons. Membrane-associated mAPEX2 tolerated microwave-enhanced chemical fixation and drove tyramide signal amplification to deposit Alexa Fluor dyes in the light-activated axons. Subsequent post-embedding immunogold labeling resulted in outstanding ultrastructure and clear distinctions between labeled (activated), and unlabeled axons without obscuring subcellular organelles. The gold-labeled axons in potentiated slices were reconstructed through serial section electron microscopy; presynaptic vesicles and other constituents could be quantified unambiguously. The genetic specification, reliable physiology, and compatibility with established methods for ultrastructural preservation make this an ideal approach to link synapse ultrastructure and function in intact circuits.

neuroscience↗

bioRxiv2019

Developmental onset of enduring long-term potentiation in mouse hippocampus

Analysis of long-term potentiation (LTP) provides a powerful window into cellular mechanisms of learning and memory. Prior work shows late LTP (L-LTP), lasting >3 hours, occurs abruptly at postnatal day 12 (P12) in rat hippocampus. The goal here was to determine the developmental profile of synaptic plasticity leading to L-LTP in the mouse hippocampus. Two mouse strains and two mutations known to affect synaptic plasticity were chosen: C57BL/6 and Fmr1-/y on the C57BL/6 background, and 129SVE and Hevin-/- (Sparcl1-/-) on the 129SVE background. Like rats, hippocampal slices from all of the mice showed test pulse-induced depression early during development that was gradually resolved with maturation by 5 weeks. All the mouse strains showed a gradual progression between P10-P35 in the expression of short-term potentiation (STP), lasting [≤] one hour. In the 129SVE mice, L-LTP onset (>25% of slices) occurred by 3 weeks, reliable L-LTP (>50% slices) was achieved by 4 weeks, and Hevin-/- advanced this profile by one week. In the C57BL/6 mice, L-LTP onset occurred significantly later, over 3-4 weeks, and reliability was not achieved until 5 weeks. Although some of the Fmr1-/y mice showed L-LTP before 3 weeks, reliable L-LTP also was not achieved until 5 weeks. Two bouts of TBS separated by [≥]90 minutes advanced the onset age of L-LTP in rats from P12 to P10. In contrast, L-LTP onset was not advanced in any of the mouse genotypes by multiple bouts of TBS at 90 or 180 minute intervals. These findings show important species differences in the onset of STP and L-LTP, which occur at the same age in rats but are sequentially acquired in mice. SIGNIFICANCE STATEMENTLong-term potentiation (LTP) is a cellular mechanism of learning and memory. Knowing the developmental profile for LTP provides a basis for investigating developmental abnormalities leading to intellectual disabilities and other neurodevelopmental disorders. Here we explore the developmental profile of LTP onset in two wild type mouse strains, C57BL/6 and 129SVE, together with Fmr1-/y and Hevin-/- (Sparcl1-/-) mutations that produce abnormalities in synaptic structure, plasticity, and development. Our data provide a foundation for future investigations into connections between structural and functional plasticity leading to developmental anomalies in the brain.

neuroscience↗