Biology subjects

Laird, J.

Publications and source records attributed to Laird, J..

8 recordsLinked to original sources

bioRxiv2026

Perinatal exposure to individual and a metal mixture induces persistent and sex-specific alterations to the cardiac transcriptome of offspring

Exposure to heavy metals, such as lead, arsenic, cadmium, and chromium, has been individually linked to cardiac dysfunction during development and into adulthood. Although these metals are commonly encountered as a mixture, few studies have investigated the mixture effects of gestational exposure to these metals on the developing postnatal heart. To this end, we investigated the transcriptomic effects of individual heavy metals (arsenic, cadmium, chromium, and lead) and the combined mixture on female C57BI/6 mice prior to gestation through lactation. RNA was extracted from whole offspring hearts, and total RNA was sent for bulk RNA-sequencing. We found heavy metal exposure altered genes associated with circadian rhythm, cell division and DNA damage repair, and immune signaling. Moreover, we detected changes to the cellular composition of these hearts and an increase in Il2ra expression, indicating an increase in activated natural killer cells. When targeting postnatal heart development and maturation pathways, we found the mixture induced a general upregulation of almost all targeted pathways, which seemed to be driven by co-exposure to all metals instead of one metal driving the mixture phenotype, and revealed a potential functional-energetic mismatch. This study is one of the first to show that perinatal exposure to heavy metals altered circadian rhythm and immune signaling gene expression in a metal- and sex-specific manner, disrupted normal cardiac cellular composition, and upregulated genes associated with postnatal heart maturation.

pharmacology and toxicology↗

bioRxiv2025

Genetic Background and Sex Modulate Androgen Responses in Human Brain Microphysiological System

Sex steroids shape human brain development, yet the cellular and molecular consequences of androgen addition need further exploration. Here, we used a human neural organoid model - brain microphysiological system (bMPS), derived from nine induced pluripotent stem cell (iPSC) lines to model the impact of dihydrotestosterone (DHT), a potent non-aromatizable androgen. All lines differentiated reproducibly into electrically active, neuron-glia-oligodendrocyte organoids expressing robust androgen-signaling components. DHT was bioavailable, elicited nuclear androgen receptor (AR) translocation and increased organoid size in most cell lines, consistent with androgen-responsive mTOR and metabolic pathway activation. Bulk RNA-seq across nine lines revealed that transcriptional responses varied across donor backgrounds, but DHT-responsive genes converged on mitochondrial energetics, lysosomal function, glycoprotein processing, apoptosis, and mTOR signaling. Cell-type expression profiling showed an androgen-driven shift primarily in male lines toward astrocytic profiles with reductions in oligodendrocyte, oligodendrocyte progenitor (OPC), excitatory, and inhibitory neuronal signatures, supported by immunohistochemistry and AR enrichment in astrocytes and OPCs. DHT also altered neurodevelopmental pathways, increasing variation in synaptic pruning and decreasing variation in neuronal migration, with autism spectrum disorder (ASD) diagnosis and seizure status of donors moderating these effects more strongly than sex. Baseline transcriptional differences distinguished iPSC lines which responded more strongly to DHT from weak responders: responders displayed enhanced synaptic maturity and reduced ECM gene expression. Using isogenic XX/XY lines, we found that differences in sex-chromosome expression exceeded DHT-induced changes and that DHT decreased expression of inhibitory neuron genes in males and increased it in females. Finally, DHT induced extensive DNA methylation changes, targeting HOX genes, patterning, and synaptic genes. Collectively, these findings reveal that androgen signaling shapes transcription, cell populations, and epigenetic landscapes in a genetic background-dependent manner. This work contributes to understanding how androgens influence human brain development and highlights how in vitro models can contribute to representing inter-individual variability in neurodevelopment and neurodevelopmental disorders.

neuroscience↗

bioRxiv2024

Human Neural Organoid Microphysiological Systems Show the Building Blocks Necessary for Basic Learning and Memory

Brain Microphysiological Systems including neural organoids derived from human induced pluripotent stem cells offer a unique lens to study the intricate workings of the human brain. This paper investigates the foundational elements of learning and memory in neural organoids, also known as Organoid Intelligence by quantifying immediate early gene expression, synaptic plasticity, neuronal network dynamics, and criticality to demonstrate the utility of these organoids in basic science research. Neural organoids showed synapse formation, glutamatergic and GABAergic receptor expression, immediate early gene expression basally and evoked, functional connectivity, criticality, and synaptic plasticity in response to theta-burst stimulation. In addition, pharmacological interventions on GABAergic and glutamatergic receptors, and input specific theta-burst stimulation further shed light on the capacity of neural organoids to mirror synaptic modulation and short-term potentiation, demonstrating their potential as tools for studying neurophysiological and neurological processes and informing therapeutic strategies for diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/613333v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@50a256org.highwire.dtl.DTLVardef@1d1f8c9org.highwire.dtl.DTLVardef@24688borg.highwire.dtl.DTLVardef@4ba3b4_HPS_FORMAT_FIGEXP M_FIG C_FIG Overview of the main components of the experiments conducted. Figure created using BioRender.com.

neuroscience↗

bioRxiv2023

Transcriptomic network analysis of brain and bone reveals shared molecular mechanisms underlyingAlzheimer's Disease and related dementias and Osteoporosis

Alzheimers disease and related dementias (ADRD) and Osteoporosis (OP) are two prevalent diseases of aging with numerous epidemiological associations, but the underlying molecular mechanisms contributing to this association are unknown. We used WGCNA (weighted gene co-expression network analysis) to develop transcriptomic networks in bone and brain tissue using two different studies to discover common molecular mechanisms. We used RNA-sequencing data from the dorsolateral prefrontal cortex tissue of autopsied brains in 629 participants from ROSMAP (Religious Orders Study and the Memory and Aging Project), including a subset of 298 meeting criteria for inclusion in five ADRD categories and the full set in a secondary analysis, and RNA array data from transiliac bone in 84 participants from the Oslo study of postmenopausal women. After developing each network, we analyzed associations between modules (groups of co-expressed genes) with multiple bone and neurological traits, examined overlap in modules between networks, and performed pathway enrichment analysis to discover conserved mechanisms. We discovered three modules in ROSMAP that showed significant associations with ADRD and bone related traits and four modules in Oslo that showed significant associations with multiple bone outcomes. We found significant module overlap between the two networks, most notably among those modules linked to canonical Wnt signaling and skeletal tissue homeostasis and development. These results were preserved with a network from the full ROSMAP cohort (n=629), which included a broader spectrum of participants. Our results require validation in experimental studies but show support for Wnt signaling as an important driver of pathology in OP and ADRD. We additionally show a strong link between Dementia with Lewy bodies and bone outcomes. These results have translational significance in the development of novel treatments and biomarkers for both ADRD and OP.

neuroscience↗

bioRxiv2023

REVEILLE2 Thermosensitive Splicing: A Molecular Basis for the Integration of Nocturnal Temperature Information by the Arabidopsis Circadian Clock

O_LICold stress is one of the major environmental factors that limit growth and yield of plants. However, it is still not fully understood how plants account for daily temperature fluctuations, nor how these temperature changes are integrated with other regulatory systems such as the circadian clock. C_LIO_LIWe demonstrate that REVEILLE2, a MYB-like transcription factor, exhibits a cold-induced alternative splicing switch from a non-translatable isoform at ambient temperature to a translatable isoform upon cold exposure. We explore the biological function of REVEILLE2 using a combination of molecular genetics, transcriptomics, and physiology. C_LIO_LIDisruption of the REVEILLE2 cooling switch alters regulatory gene expression, impairs circadian timing, and improves photosynthetic capacity. Changes in nuclear gene expression are particularly apparent in the initial hours following chilling, with chloroplast gene expression subsequently up-regulated. C_LIO_LIThe REVEILLE2 cold switch extends our understanding of plants immediate response to cooling. We propose that the circadian component REVEILLE2 restricts plants responses to nocturnal reductions in temperature, thereby enabling appropriate responses to daily environmental changes. C_LI Plain language summaryPlants need to respond appropriately to temperature, accounting for the expected daily patterns of reduced temperatures that occur every night relative to the day. Here, we show that a gene expressed at night fulfils this function.

plant biology↗

bioRxiv2022

Continuous Fish Muscle Cell Line with Capacity for Myogenic and Adipogenic-like Phenotypes

Cell-cultivated fish offers the potential for a more ethical, sustainable, and safe seafood system. However, fish cell culture is relatively understudied in comparison to mammalian cells. Here, we established and characterized a continuous Atlantic mackerel (Scomber scombrus) skeletal muscle cell line ("Mack" cells). The cells were isolated from muscle biopsies of fresh-caught fish, with separate isolations performed from two distinct fish. Mack1 cells (cells from the first isolation) were cultured for over a year and subcultured over 130 times. The cells proliferated at initial doubling times of 63.9 hr ({+/-} 19.1 SD). After a spontaneous immortalization crisis from passages 37-43, the cells proliferated at doubling times of 24.3 hr ({+/-} 4.91 SD). A muscle phenotype was confirmed through characterization of muscle stemness and differentiation via paired-box protein 7 (PAX7) and myosin heavy chain (MHC) immunostaining, respectively. An adipocyte-like phenotype was also demonstrated for the cells through lipid accumulation, confirmed via Oil Red O (ORO) staining and quantification of neutral lipids. New qPCR primers (HPRT, PAX3B, MYOD1, MYOG, TNNT3A, and PPARG) were tailored to the mackerel genome and used to characterize mackerel cell genotypes. This work provides the first spontaneously immortalized fish muscle cell line for research, ideally serving as a reference for subsequent investigation.

bioengineering↗

bioRxiv2021

Personalized Perturbation Profiles Reveal Concordance between Autism Blood Transcriptome Datasets

The complex heterogeneity of Autism Spectrum Disorder (ASD) has made quantifying disease specific molecular changes a challenge. Blood based transcriptomic assays have been performed to isolate these molecular changes and provide biomarkers to aid in ASD diagnoses, etiological understanding, and potential treatment1-6. However, establishing concordance amongst these studies is made difficult in part by the variation in methods used to call putative biomarkers. Here we use personal perturbation profiles to establish concordance amongst these datasets and reveal a pool of 1,189 commonly perturbed genes and new insights into poorly characterized genes that are perturbed in ASD subjects. We find the resultant perturbed gene pools to include the following unnamed genes: C18orf25, C15orf39, C1orf109, C1orf43, C19orf12, C6orf106, C3orf58, C19orf53, C17orf80, C4orf33, C21orf2, C10orf2, C1orf162, C10orf25 and C10orf90. Investigation into these genes using differential correlation analysis and the text mining tool Chilibot reveal interesting connections to DNA damage, ubiquitination, R-loops, autophagy, and mitochondrial damage. Our results support evidence that these cellular events are relevant to ASD molecular mechanisms. The personalized perturbation profile analysis scheme, as described in this work, offers a promising way to establish concordance between seemingly discordant expression datasets and expose the relevance of new genes in disease.

bioinformatics↗

bioRxiv2019

A Common Architecture for Human and Artificial Cognition Explains Brain Activity Across Domains

The Common Model of Cognition (CMC) is a recently proposed, consensus architecture intended to capture decades of progress in cognitive science on modeling human and human-like intelligence. Because of the broad agreement around it and preliminary mappings of its components to specific brain areas, we hypothesized that the CMC could be a candidate model of the large-scale functional architecture of the human brain. To test this hypothesis, we analyzed functional MRI data from 200 participants and seven different tasks that cover a broad range of cognitive domains. The CMC components were identified with functionally homologous brain regions through canonical fMRI analysis, and their communication pathways were translated into predicted patterns of effective connectivity between regions. The resulting dynamic linear model was implemented and fitted using Dynamic Causal Modeling, and compared against six alternative brain architectures that had been previously proposed in the field of neuroscience (three hierarchical architectures and three hub-and-spoke architectures) using a Bayesian approach. The results show that, in all cases, the CMC vastly outperforms all other architectures, both within each domain and across all tasks. These findings suggest that a common set of architectural principles that could be used for artificial intelligence also underpins human brain function across multiple cognitive domains.

neuroscience↗