bioRxiv Science⌕ Search

Biology subjects

Nguyen, T.

Publications and source records attributed to Nguyen, T..

At least 217 records · Page 12Linked to original sources

Learning from unexpected events in the neocortical microcircuit

Scientists have long conjectured that the neocortex learns the structure of the environment in a predictive, hierarchical manner. According to this conjecture, expected, predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of information. It is theorized that the neocortex then changes the representation of incoming stimuli, guided by differences in the responses to expected and unexpected events. In line with this conjecture, different responses to expected and unexpected sensory features have been observed in spiking and somatic calcium events. However, it remains unknown whether these unexpected event signals occur in the distal apical dendrites where many top-down signals are received, and whether these signals govern subsequent changes in the brains stimulus representations. Here, we show that both somata and distal apical dendrites of cortical pyramidal neurons exhibit distinct unexpected event signals that systematically change over days. These findings were obtained by tracking the responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons over multiple days in primary visual cortex of awake, behaving mice using two-photon calcium imaging. Many neurons in both layers 2/3 and 5 showed large differences between their responses to expected and unexpected events. Interestingly, these responses evolved in opposite directions in the somata and distal apical dendrites. These differences between the somata and distal apical dendrites may be important for hierarchical computation, given that these two compartments tend to receive bottom-up and top-down information, respectively.

neuroscience↗

A standardized behavioral event equally impacts the activity of cortical visual areas and layers

Multiple recent studies have shown that motor activity greatly impacts the activity of primary sensory areas like V1. Yet, the role of this motor related activity in sensory processing is still unclear. Here we dissect how these behavior signals are broadcast to different layers and areas of the visual cortex. To do so, we leveraged a standardized and spontaneous behavioral fidget event in passively viewing mice. Importantly, this behavior event had no relevance to any ongoing task allowing us to compare its neuronal correlate with visually relevant behavior like running. A large two-photon Ca2+ imaging database of neuronal responses uncovered four neural response types during fidgets that were surprisingly consistent in their proportion and response patterns across all visual areas and layers of the visual cortex. Indeed, the layer and area identity could not be decoded above chance level based only on neuronal recordings. In contrast to running behavior, fidget evoked neural responses were independent to visual processing. The broad availability of visually orthogonal standardized behavior signals could be a key component in how the cortex selects, learns and binds local sensory information with motor outputs. Contrary to relevant motor outputs, irrelevant motor signals would use a separate neural subspaces. Significance StatementRecent studies have shown contextual and behavioral variables to dominate brain-wide activity, but yet it is unknown how this information is broadcast across cortical layers and areas. Using a large two-photon dataset collected in mice passively viewing a battery of visual stimuli, we characterized the neuronal response of neurons of the visual cortex to a standardized fidget behavior. We found that as much as 47% of excitatory neurons show significant co-activity with fidgets. Throughout all areas and layers we recorded from, those responses were distributed across surprisingly consistent three neural response types. Further analysis showed no interaction between fidget neural events and cells visual stimulus responses, contrasting with feedback neural signals induced by running. These contrasting response distribution patterns suggest that behavioral neuronal correlates are broadly available but will modulate sensory responses depending on their relevance to local sensory inputs.

neuroscience↗

A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs

One often observes small but measurable differences in diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and potentially reflect the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step to extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). State changes may be expressed as changes in morphology, so that a subset of the polystates may be observed as polymorphs. After mixed-state data are deliberately or inadvertently measured, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here we address this problem using a simple multi-factor clustering approach that classifies each data set using independent observables in order to assign each data set to the correct location in conformation space. We illustrate this method using two independent observables (unit cell constants and intensities) to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. We observe that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin.

molecular biology↗

BBrowser: Making single-cell data easily accessible

BioTurings BBrowser is a software solution that helps scientists effectively analyze single-cell omics data. It combines big data with big computation and modern data visualization to create a unique platform where scientists can interact and obtain important biological insights from the massive amounts of single-cell data. BBrowser has three main components: a curated single-cell database, a big-data analytics layer, and a data visualization module. BBrowser is available for download at: https://bioturing.com/bbrowser/download.

bioinformatics↗

Betulonic acid derivatives inhibiting coronavirus replication in cell culture via the nsp15 endoribonuclease

The lack of medication to suppress coronavirus infections is a main reason for the dramatic course of the COVID-19 pandemic. There is an urgent need to identify suitable coronavirus drug targets and corresponding lead molecules. Here we describe the discovery of a class of coronavirus inhibitors acting on nsp15, a hexameric protein component of the viral replication-transcription complexes, endowed with immune evasion-associated endoribonuclease activity. SAR exploration of these 1,2,3-triazolo fused betulonic acid derivatives yielded lead molecule 5h as a strong inhibitor (antiviral EC50: 0.6 M) of human coronavirus 229E replication. An nsp15 endoribonuclease active site mutant virus was markedly less sensitive to 5h, and selected resistance to the compound mapped to mutations in the N-terminal part of nsp15, at an interface between two nsp15 monomers. The biological findings were substantiated by the nsp15 binding mode for 5h, predicted by docking. Hence, besides delivering a distinct class of inhibitors, our study revealed a druggable pocket in the nsp15 hexamer with relevance for anti-coronavirus drug development.

microbiology↗

Zika Virus Infection Prevents Host mRNA Nuclear Export by Disrupting UPF1 Function

Zika virus (ZIKV) is a mosquito-borne RNA virus that can infect fetuses in utero causing characteristic neurodevelopmental disorders including microcephaly. We previously showed that ZIKV infection downregulates expression of up-frameshift protein 1 (UPF1), a helicase/ATPase and central regulator of the nonsense-mediated mRNA decay pathway. Here, we identify a novel function of nuclear UPF1 in mRNA export. Using crosslinking immunoprecipitation of UPF1 followed by sequencing of associated transcripts as well as fluorescence in situ hybridization experiments, we find widespread mRNA accumulation in the nucleus of human neural progenitor cells (NPCs) upon ZIKV infection or UPF1 knockdown. Knockdown of FREM2, a top UPF1 target transcript encoding an extra-cellular matrix protein critical in fetal development, decreased expression of pluripotency markers and increased expressed neuronal differentiation in NPCs, consistent with the model that trapping FREM2 mRNA in the nucleus perturbs proper NPC function. Collectively, our data uncover a new posttranscriptional mechanism by which ZIKV "shuts off" host mRNA export via UPF1. As we find UPF1 linked to many neurodevelopment pathways, we propose that the lack of host mRNA export contributes to the neurodevelopmental defects associated with ZIKV infection.

microbiology↗

Exchange of molecular and cellular information: a hybrid model that integrates stem cell divisions and key regulatory interactions

Stem cells give rise to the entirety of cells within an organ. Maintaining stem cell identity and coordinately regulating stem cell divisions is crucial for proper development. In plants, mobile proteins, such as WOX5 and SHR, regulate divisions in the root stem cell niche (SCN). However, how these proteins coordinately function to establish systemic behavior is not well understood. We propose a non-cell autonomous role for WOX5 in the CEI and identify a regulator, AN3/GIF1, that coordinates CEI divisions. Here we show with a multiscale hybrid model integrating ODEs and agent-based modeling that QC and CEI divisions have different dynamics. Specifically, by combining continuous models to describe regulatory networks and agent-based rules, we model systemic behavior, which led us to predict cell-type-specific expression dynamics of SHR, SCR, WOX5, AN3, and CYCD6;1, and experimentally validate CEI cell divisions. Conclusively, our results show an interdependency between CEI and QC divisions. Thumbnail image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/404426v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@abcd10org.highwire.dtl.DTLVardef@123e110org.highwire.dtl.DTLVardef@8d175dorg.highwire.dtl.DTLVardef@f8f498_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Fine Molecular Tuning of Chimeric Antigen Receptors through Hinge Length Optimization

BackgroundChimeric antigen receptor (CAR) technology has revolutionized the treatment of B-cell malignancies and steady progress is being made towards CAR-immunotherapies for solid tumours. Epidermal growth factor family receptors EGFR or HER2 are commonly overexpressed in cancer and represent proven targets for CAR-T therapy; given their expression in healthy tissues it is imperative that any targeting strategy consider the potential for on-target off-tumour toxicity. MethodsHerein, we utilize high-throughput CAR screening to identify novel camelid single-domain antibody CARs (sdCARs) with high EGFR-specific CAR-T response. To optimize antigenic sensitivity of this EGFR-sdCAR, we performed progressive N-terminal truncation of the human CD8 hinge domain used as a spacer in many CAR constructs. Hinge truncation resulted in decreased CAR sensitivity to EGFR and improved selectivity for EGFR-overexpressing cells over EGFR-low target cells or healthy donor derived EGFR-positive fibroblasts. To investigate the molecular mechanism of hinge truncation, we test hinge-truncated scFv-based CARs targeting membrane proximal or membrane distal domains of EGFR-family proteins, HER2 and EGFRvIII. Finally, we proceed to test hinge variant EGFR-sdCAR functionality through in vitro and in vivo assessments in primary T cells derived from multiple donors. ResultsFor CARs targeting membrane-proximal epitopes, hinge truncation by even a single amino acid provided fine control of the antigenic sensitivity, whereas CARs targeting membrane distal domains were not sensitive to even complete hinge domain removal. Hinge-modified EGFR-sdCARs showed consistent and predictable responses in Jurkat-CAR cells and primary human CAR-T cells in vitro and in vivo. ConclusionsOverall, these results indicate that membrane-proximal epitope targeting CARs can be modified through hinge length tuning for programmable antigenic sensitivity and improved tumour selectivity. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/360925v2_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1f0db64org.highwire.dtl.DTLVardef@1d3ac43org.highwire.dtl.DTLVardef@1d270faorg.highwire.dtl.DTLVardef@f7614f_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LISingle amino acid truncations of CD8-hinge domain provide precise control of CAR antigen sensitivity C_LIO_LITruncated hinge CARs show enhanced selectivity for antigen overexpressing tumour cells and decreased activity towards healthy antigen-expressing cells C_LIO_LIEpitope location is a critical factor in determining hinge sensitivity for a CAR C_LIO_LIHinge tuning can modulate CAR-T antigenic sensivity in vitro and in vivo C_LI

immunology↗

Unbiased identification of nanoparticle cell uptake mechanism via a genome-wide CRISPR/Cas9 knockout screen

A major bottleneck in nanocarrier and macromolecule development for therapeutic delivery is our limited understanding of the processes involved in their uptake into target cells. This includes their active interactions with membrane transporters that co-ordinate cellular uptake and processing. Current strategies to elucidate the mechanism of uptake, such as painstaking manipulation of individual effectors with pharmacological inhibitors or specific genetic knockdowns, are limited in scope and biased towards previously studied pathways or the intuition of the investigators. Furthermore, each of these approaches present significant off-target effects, clouding the outcomes. We set out to develop and examine an unbiased whole-genome screening approach using pooled CRISPR/Cas9 libraries for its ability to provide a robust and rapid approach to identify novel effectors of material uptake. Enabling this, we developed a methodology termed fast-library of inserts (FLI)-seq for library preparation and quantitative readout of pooled screens that shows improved technical reproducibility and is easier to perform than existing methods. In this proof-of-concept study we use FLI-seq to identify a solute carrier protein family member, SLC18B1, as a transporter for polymeric micellar nanoparticles, confirming the viability for this approach to yield novel insights into uptake mechanisms.

genomics↗

Smad3 Regulates Smooth Muscle Cell Fate and Governs Adverse Remodeling and Calcification of Atherosclerotic Plaque

Atherosclerotic plaques consist mostly of smooth muscle cells (SMC), and genes that influence SMC biology can modulate coronary artery disease (CAD) risk. Allelic variation at 15q22.33 has been identified by genome-wide association studies to modify the risk of CAD, and is associated with expression of SMAD3 in SMC, but the mechanism by which this gene modifies CAD risk remains poorly understood. SMC-specific deletion of Smad3 in a murine atherosclerosis model resulted in greater plaque burden, positive remodeling, and increased vascular calcification. Single-cell transcriptomic analyses revealed that loss of Smad3 altered SMC progeny phenotype toward the previously described chondromyocyte fate, but importantly also promoted transition to a novel cell-state that governs remodeling and recruitment of inflammatory cells. This new remodeling population was marked by uniquely high Mmp3 and Cxcl12 expression, and its appearance correlated with higher-risk plaque features such as increased positive remodeling and macrophage content. Further, investigation of transcriptional mechanisms by which Smad3 alters SMC cell-fate revealed novel roles for Hox and Sox transcription factors whose direct interaction with Smad3 regulate an extensive transcriptional program balancing remodeling and vascular ECM with significant implications for human Mendelian aortic aneurysmal diseases. Together, these data suggest that Smad3 expression in SMC inhibits the emergence of specific SMC phenotypic transition cells that mediate adverse plaque features, including positive remodeling, monocyte recruitment, and vascular calcification.

cell biology↗

St. Jude Cloud a Pediatric Cancer Genomic Data Sharing Ecosystem

Effective data sharing is key to accelerating research that will improve the precision of diagnoses, efficacy of treatments and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem developed via collaboration between St. Jude Childrens Research Hospital, DNAnexus, and Microsoft, for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients, long-term survivors of pediatric cancer and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabyes on St. Jude Cloud include 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes, which are freely available to researchers worldwide. The resource is expanding rapidly with regular data uploads from St. Judes prospective clinical genomics programs, providing public access as soon as possible rather than holding data back until publication. Three interconnected apps within the St. Jude Cloud ecosystem--Genomics Platform, Pediatric Cancer Knowledgebase (PeCan) and Visualization Community--provide a unique experience for simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the St. Jude Cloud ecosystem through use cases that classify 48 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 subtypes of pediatric cancer.

cancer biology↗

In vivo contactless brain stimulation via non-invasive and targeted delivery of magnetoelectric nanoparticles

Non-invasive brain stimulation is valuable for studying neural circuits and treating various neurological disorders in humans. However, the current technologies usually have low spatial and temporal precision and poor brain penetration, which greatly limit their application. A new class of nanoparticles known as magneto-electric nanoparticles (MENs) can be navigated to a targeted brain region with a magnetic field and is highly efficient in converting an externally applied magnetic wave into local electric fields for neuronal activity modulation. Here we developed a new method to fabricate MENs of CoFe2O4-BaTiO3 core-shell structure that had excellent magneto-electrical coupling properties. Using calcium imaging of organotypic and acute cortical slices from GCaMP6s transgenic mice, we demonstrated their efficacy in reliably evoking neuronal responses with a short latency period. For in vivo non-invasive delivery of MENs to brain, fluorescently labeled MENs were intravenously injected and guided to pass through the blood brain barrier to a targeted brain region by applying a magnetic field gradient. A magnetic field ([~]450 Oe at 10 Hz) applied to mouse brain was able to reliably evoke cortical activities, as revealed by in vivo two-photon and mesoscopic imaging of calcium signals at both cellular and global network levels. The effect was further confirmed by the increased number of c-Fos expressing cells after stimulation. Neither brain delivery of MENs nor the subsequent magnetic stimulation caused any significant increases in the numbers of GFAP and IBA1 positive astrocytes and microglia in the brain. This study demonstrates the feasibility of using MENs as a novel efficient and non-invasive technique of contactless deep brain stimulation that may have great potential for translation.

neuroscience↗

Platelet Derived Growth Factor Receptor β (PDGFRβ) is a Host Receptor for the human malaria parasite adhesin TRAP

Following their inoculation by the bite of an infected Anopheles mosquito, the malaria parasite sporozoite forms travel from the bite site in the skin into the bloodstream, which transports them to the liver. The thrombospondin-related anonymous protein (TRAP) is a type 1 transmembrane protein that is released from secretory organelles and relocalized on the sporozoite plasma membrane. TRAP is required for sporozoite motility and host infection, and its extracellular portion contains adhesive domains that are predicted to engage host receptors. Here, we identified the human platelet-derived growth factor receptor {beta} (hPDGFR{beta}) as one such protein receptor. Deletion mutants showed that the von Willebrand factor type A and thrombospondin repeat domains of TRAP are both required for optimal binding to hPDGFR{beta}-expressing cells. We also demonstrate that this interaction is conserved in the human-infective parasite Plasmodium vivax, but not the rodent-infective parasite Plasmodium yoelii. We observed expression of hPDGFR{beta} mainly in cells associated with the vasculature suggesting that TRAP:hPDGFR{beta} interaction may play a role in the recognition of blood vessels by invading sporozoites.

microbiology↗

The winning methods for predicting cellular position in the DREAM single cell transcriptomics challenge

MotivationPredicting cell locations is important since with the understanding of cell locations, we may estimate the function of cells and their integration with the spatial environment. Thus, the DREAM Challenge on Single Cell Transcriptomics required participants to predict the locations of single cells in the Drosophila embryo using single cell transcriptomic data. ResultsWe have developed over 50 pipelines by combining different ways of pre-processing the RNA-seq data, selecting the genes, predicting the cell locations, and validating predicted cell locations, resulting in the winning methods for two out of three sub-challenges in the competition. In this paper, we present an R package, SCTCwhatateam, which includes all the methods we developed and the Shiny web-application to facilitate the research on single cell spatial reconstruction. All the data and the example use cases are available in the Supplementary material. AvailabilityThe scripts of the package are available at https://github.com/thanhbuu04/SCTCwhatateam and the Shiny application is available at https://github.com/pvvhoang/SCTCwhatateam-ShinyApp ContactThuc.Le@unisa.edu.au Supplementary informationSupplementary data are available at Briefings in Bioinformatics online.

systems biology↗

pDriver: A novel method for unravelling personalised coding and miRNA cancer drivers

MotivationUnravelling cancer driver genes is important in cancer research. Although computational methods have been developed to identify cancer drivers, most of them detect cancer drivers at population level. However, two patients who have the same cancer type and receive the same treatment may have different outcomes because each patient has a different genome and their disease might be driven by different driver genes. Therefore new methods are being developed for discovering cancer drivers at individual level, but existing personalised methods only focus on coding drivers while microRNAs (miRNAs) have been shown to drive cancer progression as well. Thus, novel methods are required to discover both coding and miRNA cancer drivers at individual level. ResultsWe propose the novel method, pDriver, to discover personalised cancer drivers. pDriver includes two stages: (1) Constructing gene networks for each cancer patient and (2) Discovering cancer drivers for each patient based on the constructed gene networks. To demonstrate the effectiveness of pDriver, we have applied it to five TCGA cancer datasets and compared it with the state-of-the-art methods. The result indicates that pDriver is more effective than other methods. Furthermore, pDriver can also detect miRNA cancer drivers and most of them have been confirmed to be associated with cancer by literature. We further analyse the predicted personalised drivers for breast cancer patients and the result shows that they are significantly enriched in many GO processes and KEGG pathways involved in breast cancer. Availability and implementationpDriver is available at https://github.com/pvvhoang/pDriver ContactThuc.Le@unisa.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

The environment-sensing aryl-hydrocarbon receptor inhibits the chondrogenic fate of modulated smooth muscle cells in atherosclerotic lesions

IntroductionSmooth muscle cells (SMC) play a critical role in atherosclerosis. The Aryl hydrocarbon receptor (AHR) is an environment-sensing transcription factor that contributes to vascular development, and has been implicated in coronary artery disease (CAD) risk. We hypothesized that AHR can affect atherosclerosis by regulating phenotypic modulation of SMC. MethodsWe combined RNA-Seq, ChIP-Seq, ATAC-Seq and in-vitro assays in human coronary artery SMC (HCASMC), with single-cell RNA-Seq (scRNA-Seq), histology, and RNAscope in an SMC-specific lineage-tracing Ahr knockout mouse model of atherosclerosis to better understand the role of AHR in vascular disease. ResultsGenomic studies coupled with functional assays in cultured HCASMC revealed that AHR modulates HCASMC phenotype and suppresses ossification in these cells. Lineage tracing and activity tracing studies in the mouse aortic sinus showed that the Ahr pathway is active in modulated SMC in the atherosclerotic lesion cap. Furthermore, scRNA-Seq studies of the SMC-specific Ahr knockout mice showed a significant increase in the proportion of modulated SMC expressing chondrocyte markers such as Col2a1 and Alpl, which localized to the lesion neointima. These cells, which we term "chondromyocytes" (CMC), were also identified in the neointima of human coronary arteries. In histological analyses, these changes manifested as larger lesion size, increased lineage-traced SMC participation in the lesion, decreased lineage-traced SMC in the lesion cap, and increased alkaline phosphatase activity in lesions in the Ahr knockout compared to wild-type mice. We propose that AHR is likely protective based on these data and inference from human genetic analyses. ConclusionOverall, we conclude that AHR promotes maintenance of lesion cap integrity and diminishes the disease related SMC-to-CMC transition in atherosclerotic tissues.

genomics↗

Graph convolutional networks for drug response prediction

BackgroundDrug response prediction is an important problem in computational personalized medicine. Many machine-learning-based methods, especially deep learning-based ones, have been proposed for this task. However, these methods often represent the drugs as strings, which are not a natural way to depict molecules. Also, interpretation (e.g., what are the mutation or copy number aberration contributing to the drug response) has not been considered thoroughly. MethodsIn this study, we propose a novel method, GraphDRP, based on graph convolutional network for the problem. In GraphDRP, drugs were represented in molecular graphs directly capturing the bonds among atoms, meanwhile cell lines were depicted as binary vectors of genomic aberrations. Representative features of drugs and cell lines were learned by convolution layers, then combined to represent for each drug-cell line pair. Finally, the response value of each drug-cell line pair was predicted by a fully-connected neural network. Four variants of graph convolutional networks were used for learning the features of drugs. ResultsWe found that GraphDRP outperforms tCNNS in all performance measures for all experiments. Also, through saliency maps of the resulting GraphDRP models, we discovered the contribution of the genomic aberrations to the responses. ConclusionRepresenting drugs as graphs can improve the performance of drug response prediction. Availability of data and materialsData and source code can be downloaded at https://github.com/hauldhut/GraphDRP.

bioinformatics↗

Physical and mental health characteristics of adults with subjective cognitive decline: A study of 3,407 people aged 18-81 years from an MTurk-based U.S. national sample

Subjective cognitive decline (SCD), or internal feelings of reduced mental capacity, is of increasing interest in the scientific, clinical, and lay community. Much of the extant literature is focused on SCD as a risk factor for Alzheimers disease in older adults, while less attention has been paid to non-cognitive health correlates of SCD across adulthood. Consequently, we investigated physical and mental health correlates of SCD in younger, middle-aged, and older adults. We recruited 3,407 U.S. residents through Amazons Mechanical Turk, an online labor market. Participants completed a 90-item self-report survey questionnaire assessing sociodemographic characteristics, physical health, sleep, depression, anxiety, loneliness, wisdom, self-efficacy, and happiness. Overall, 493/1930 (25.5%) of younger adults (18-49) and 278/1032 (26.9%) of older adults (50 or older) endorsed the SCD item. Multivariate analysis of variance and follow-up t-tests revealed worse physical and mental health characteristics in people endorsing SCD compared to those who did not, with effect sizes primarily in the medium to large range. Additionally, age did not moderate relationships between SCD and physical and mental health. Results suggest that SCD is associated with a diverse set of negative health characteristics such as poor sleep and high body mass index, and lower levels of positive factors including happiness and wisdom. Effect sizes of psychological correlates of SCD were as large as (or larger than) those of physical correlates, indicating that mental health and affective symptoms may be critical to consider when evaluating SCD. Overall, findings from this large, national U.S. sample suggest the presence of relationships between SCD and multiple psychological and perceived health factors; our results also show that SCD may be highly prevalent in both younger and older adults, suggesting that it be assessed across the adult lifespan.

neuroscience↗