Biology subjects

Patterson, C.

Publications and source records attributed to Patterson, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Predation by migratory birds shapes seasonally fluctuating selection on a sexually selected signal

Sexually selected traits often impose fitness costs on their bearers. Yet, the relative costs and benefits of conspicuous traits can vary through space and time, driving variation in selection acting on those traits. For insects, an important but overlooked source of such variation is seasonal shifts in the local abundance of migratory insectivorous birds. Smoky rubyspot damselflies (Hetaerina titia) exhibit a marked seasonal polyphenism in wing pigmentation throughout much of North America, with individuals emerging in the summer exhibiting conspicuous dark wings. Here, we test the hypothesis that this variation is an adaptive response to seasonal and geographical variation in predation risk. First, we find evidence for strong constraints acting on wing phenotypes outside of the summer season, consistent with a seasonal shift in the relative costs and benefits of pigmentation. Second, using a continentally distributed predation experiment, we find that predation risk covaries with spatiotemporal variation in wing pigmentation and is linked to shifts in the local abundance of migratory birds. Overall, our analyses establish an eco-evolutionary link between tropical and temperate regions, underscoring the importance of considering both the evolutionary and ecological consequences of spatiotemporal variation in biotic interactions as species assemblages shift in response to global change.

evolutionary biology↗

bioRxiv2026

Immune variation and host ontogeny constrain pathogen virulence and transmission in a helminth parasite

Host immune strategies vary widely, yet how this variation shapes parasite virulence and transmission in natural systems remains unresolved. We tested whether host immune strategy governs macroparasite transmission timing and magnitude in Schistocephalus solidus, a cestode with a three-host life cycle. Over 13 months, we surveyed infection and immune activation (fibrosis) in second-intermediate host populations (threespine stickleback) from eight lakes. Host immune strategy (ranging from resistance to tolerance) strongly influenced whether and when parasites reached transmissible sizes, and shifted the synchrony between transmissible-stage peaks and definitive host availability. Across populations, transmission potential peaked at intermediate parasite burdens, consistent with virulence-transmission trade-off theory. These findings demonstrate that host immune phenotype alters epidemiological outcomes in complex life cycle parasites, by shifting both the magnitude and phenology of parasite growth to structure the effective transmission window.

ecology↗

bioRxiv2026

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimers disease and related dementias (ADRDs). As many individuals with ADRDs have mixed pathologies ({beta}-amyloid, pathologic tau, cerebrovascular disease, vascular brain injury, pathologic TDP-43, hippocampal sclerosis, Lewy bodies), there is interest in determining how accurately we can infer these pathologic changes from clinical data, biofluid assays (e.g., CSF), and neuroimaging. Here we evaluated automated machine learning models trained on data curated by the AD Sequencing Project Phenotype Harmonization Consortium (N=7,894 individuals), to predict 26 autopsy-confirmed neuropathological outcomes. Predictors included in vivo clinical and cognitive composite scores, brain measures from 3D structural MRI and diffusion tensor imaging, image-derived measures of white matter hyperintensities (WMH), and CSF biomarkers. Predictive models were trained using ensemble learning with stratified cross-validation. We assessed performance using Spearmans rank correlation and Matthews correlation coefficient, to accommodate co-occurring pathologic changes. The added value of neuroimaging and CSF versus clinical features alone was quantified. Braak stage was among the most consistently predicted outcomes. CSF biomarkers best predicted {beta}-amyloid and tau pathology, but diffusion MRI metrics best captured vascular brain injury and white matter injury, and outperformed clinical and cognitive measures and anatomical MRI in predicting Lewy body disease. Anatomical measures from structural MRI outperformed standard clinical assessments in assessing neurodegeneration and hippocampal sclerosis, and WMH complemented cognitive measures in predicting TDP-43 pathology. These results establish a baseline for comparing modalities for inferring neuropathology.

neuroscience↗

bioRxiv2026

Linking land-use change, water quality, and host-parasite dynamics with droplet digital PCR and Bayesian path analyses

Global changes in land use and nutrient cycling are transforming ecosystems at unprecedented rates, with significant consequences for infectious disease dynamics. Aquatic environments are particularly vulnerable because the interplay of habitat modification, nutrient enrichment, and biodiversity loss can drive pronounced changes in the community composition of food webs, including hosts and parasites. Yet, despite well-documented effects of habitat modification on aquatic communities and food webs, the mechanisms through which these changes influence infectious disease dynamics remain poorly resolved. This gap arises, in part, because it remains challenging to disentangle how multiple stressors interact to shape disease outcomes and quantify parasite levels and host densities from field-collected samples. Here, we illustrate two tools that might help address these challenges. First, highly sensitive droplet digital PCR can quantify infection loads even when the signal:noise ratio is low. Second, stepwise Bayesian path analyses can identify the direct and indirect pathways connecting land-use changes to infectious disease dynamics. As a case study, we examined cyclopoid copepods and their helminth parasite, Schistocephalus solidus, across 47 freshwater lakes on Vancouver Island, a region strongly shaped by commercial logging, including widespread clear-cutting of old-growth forests. Our results reveal a positive correlation between copepod density and deforestation, potentially mediated by associated changes in water quality and calanoid copepods, key competitors of the focal host. ddPCR enabled sensitive detection of extremely low parasite signals in field-collected copepods. We detected positive infections in only 19.5% of the lakes surveyed, highlighting the difficulty of assessing disease dynamics in natural populations. Nonetheless, this study highlights the challenges of linking land-use change to disease outcomes, while also demonstrating that sensitive molecular and statistical tools offer new ways to reveal these hidden connections.

ecology↗

bioRxiv2026

A Multi-Scale Ecological Approach to Assessing Antimicrobial Resistance in a Freshwater Fish

Antimicrobial resistance (AMR) genes are increasingly recognized as an emerging environmental contaminant. Yet, the ecological mechanisms shaping their distribution across natural landscapes remain poorly understood. Here, we quantified AMR gene abundances in microbial communities sampled from wild fish from eight freshwater lakes on Vancouver Island and paired these gene-level measurements with fine-scale limnological and land-use data. Using droplet digital PCR, field surveys, and an iterative spatial forecasting framework that integrates Random Forest models with regression kriging, we explored how watershed-scale processes relate to variation in AMR genes across lakes. Our analyses reveal potential associations between elevated AMR gene levels, changes in water quality, deforestation, and geographic proximity to salmon aquaculture. By integrating data across biological and spatial scales, from genes within microbial communities to lake-level conditions and landscape patterns, this study illustrates the value of combining quantitative molecular measurements with geospatial modeling to identify environmental factors that may promote antimicrobial resistance in natural systems. Our approach provides a proof-of-concept and a general predictive framework for generating hypotheses and informing future monitoring efforts aimed at understanding, managing, and forecasting environmental reservoirs of resistance. SignificanceAntimicrobial resistance (AMR) genes are ancient components of environmental microbiomes. Yet, the mechanisms that generate modern hotspots of resistance across natural landscapes remain unclear. Here, we reveal how watershed-scale environmental change, including water quality metrics linked with deforestation and proximity to salmon aquaculture, predicts elevated AMR gene levels in the microbiomes of wild fish populations. By combining quantitative droplet digital PCR with ecological data and geospatial modeling, we move beyond isolated surveillance data to identify ecological mechanisms that promote antimicrobial resistance in freshwater ecosystems. This integrative approach provides mechanistic insight into why certain habitats, and the organisms within them, become reservoirs of resistance while others do not. Our findings highlight the importance of ecological context in understanding resistance evolution and offer a predictive tool for informing proactive monitoring and management strategies.

ecology↗

bioRxiv2026

Constitutive and inducible fibrosis explain immune variation among threespine stickleback populations

Understanding how immune variation arises in natural populations requires disentangling the relative contributions of host genetic differences, environmental variation, and parasite effects, which is rarely possible in wild systems. Threespine stickleback populations vary in their use of intraperitoneal fibrosis as a defense against the helminth parasite Schistocephalus solidus, providing a natural system to study the genetic and ecological drivers of immune variation. We combined a 46-lake field survey with common garden experiments on 20 representative populations exposed to multiple parasite genotypes to test whether population differences in fibrosis persist under controlled conditions and whether they depend on parasite genotype or lake ecology. Fibrosis variation was strongly heritable, with both constitutive and inducible components persisting under common garden conditions. In contrast, parasite genotype had only a weak effect on fibrosis responses. Moreover, inducible fibrosis covaried with lake environmental conditions, with populations from more eutrophic-like lakes exhibiting stronger responses than those from more oligotrophic-like lakes. Together, these results reveal ecologically structured divergence in heritable immune responses among natural populations.

evolutionary biology↗

bioRxiv2025

Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic Data

Alzheimers disease and related dementias (ADRD) involve overlapping neurodegenerative and vascular pathologies--such as amyloid-{beta} (A{beta}), tau, cerebral amyloid angiopathy (CAA), TDP-43, and alpha-synuclein--that complicate diagnosis and treatment. While PET and CSF biomarkers are useful for detecting A{beta} and tau, they are invasive, expensive, and not widely available. In contrast, magnetic resonance imaging (MRI) is non-invasive and widely accessible, offering an opportunity for pathology prediction when combined with deep learning. Most prior studies have focused on single-pathology detection, but there remains a need for models that can jointly predict multiple co-occurring pathologies. In this work, we evaluate deep learning models that integrate structural MRI with demographic, clinical, and genetic data to classify six autopsy-confirmed neuropathologies: A{beta}, tau, CAA, TDP-43, hippocampal sclerosis, and dementia with Lewy bodies. We compare our hybrid deep learning model to AutoGluon, an automated machine learning framework. Our findings support the potential of multimodal AI to enable non-invasive, comprehensive neuropathological profiling in ADRD.

neuroscience↗

bioRxiv2025

Deep Learning to Predict Future Cognitive Decline: A Multimodal Approach Using Brain MRI and Clinical Data

Predicting the trajectory of clinical decline in aging individuals is a pressing challenge, especially for people with mild cognitive impairment, Alzheimers disease, Parkinsons disease, or vascular dementia. Accurate predictions can guide treatment decisions, identify risk factors, and optimize clinical trials. In this study, we compared two deep learning approaches for forecasting changes, over a 2-year interval, in the Clinical Dementia Rating scale sum of boxes score (sobCDR). This is a key metric in dementia research, and scores range from 0 (no impairment) to 18 (severe impairment). To predict decline, we trained a hybrid convolutional neural network that integrates 3D T1-weighted brain MRI scans with tabular clinical and demographic features (including age, sex, body mass index (BMI), and baseline sobCDR). We benchmarked its performance against AutoGluon, an automated multimodal machine learning framework that selects an appropriate neural network architecture. Our results demonstrate the importance of combining image and tabular data in predictive modeling for clinical applications. Deep learning algorithms can fuse image-based brain signatures and tabular clinical data, with potential for personalized prognostics in aging and dementia.

neuroscience↗

bioRxiv2024

Spatiotemporal dynamics of non-ecological speciation in rubyspot damselflies (Hetaerina spp.)

Non-ecological speciation is a common mode of speciation which occurs when allopatric lineages diverge in the absence of pronounced ecological differences. Yet, relative to other speciation mechanisms, non-ecological speciation remains understudied. Numerous damselfly clades are characterized as non-adaptive radiations (the result of several rounds of non-ecological speciation), but there are few damselfly lineages for which we have a detailed understanding of the spatiotemporal dynamics of divergence. Recent phylogeographic analyses demonstrate that American rubyspot damselflies (Hetaerina americana sensu lato) actually comprise at least two cryptic lineages that coexist sympatrically across most of Mexico. To broaden our understanding of the dynamics of diversification to other rubyspot lineages, we investigated the phylogeographic history of smoky rubyspot damselflies (Hetaerina titia) using genomic data collected across Central and North America. Unexpectedly, we found evidence of reproductive isolation between the highly genetically differentiated Pacific and Atlantic lineages of H. titia in a narrow secondary contact zone on the Isthmus of Tehuantepec, Mexico. We then fit models of historical demography to both H. americana sensu lato and H. titia to place these comparisons in a temporal context. Our findings indicate that Pacific and Atlantic lineages of H. titia split more recently than the broadly sympatric lineages within H. americana sensu lato, supporting key assumptions of the non-ecological speciation model and demonstrating that these two pairs of sister lineages are at different stages of the speciation cycle.

evolutionary biology↗

bioRxiv2024

Cross-sectional and longitudinal changes in category-selectivity in visual cortex following pediatric cortical resection

The topographic organization of category-selective responses in human ventral occipitotemporal cortex (VOTC) and its relationship to regions subserving language functions is remarkably uniform across individuals. This arrangement is thought to result from the clustering of neurons responding to similar inputs, constrained by intrinsic architecture and tuned by experience. We examined the malleability of this organization in individuals with unilateral resection of VOTC during childhood for the management of drug-resistant epilepsy. In cross-sectional and longitudinal functional imaging studies, we compared the topography and neural representations of 17 category-selective regions in individuals with a VOTC resection, a control patient with resection outside VOTC, and typically developing matched controls. We demonstrated both adherence to and deviation from the standard topography and uncovered fine-grained competitive dynamics between word- and face-selectivity over time in the single, preserved VOTC. The findings elucidate the nature and extent of cortical plasticity and highlight the potential for remodeling of extrastriate architecture and function. TeaserAfter pediatric cortical resection, deviations from the constraints of standard topography in visual cortex reflect plasticity.

neuroscience↗

bioRxiv2024

Functional resilience of the neural visual recognition system post-pediatric occipitotemporal resection

In the typically developing (TD) brain, neural representations for visual stimulus categories (e.g., faces, objects, and words) emerge in bilateral occipitotemporal cortex (OTC), albeit with weighted asymmetry; in parallel, recognition behavior continues to be refined. A fundamental question is whether two hemispheres are necessary or redundant for the emergence of neural representations and recognition behavior typically distributed across both hemispheres. The rare population of patients undergoing unilateral OTC resection in childhood offers a unique opportunity to evaluate whether neural computations for visual stimulus individuation suffice for recognition with only a single developing OTC. Here, using functional magnetic resonance imaging, we mapped category selectivity (CS) and neural representations for individual stimulus exemplars using repetition suppression (RS) in the non-resected hemisphere of pediatric OTC resection patients (n = 9) and control patients with resection outside of OTC (n = 12), as well as in both hemispheres of TD controls (n = 21). There were no univariate group differences in the magnitude of CS or RS or any multivariate differences (per representational similarity analysis) in neural activation to faces, objects, or words across groups. Notwithstanding their comparable neural profiles, accuracy of OTC resection patients on face and object recognition, but not word recognition, was statistically inferior to that of controls. The comparable neural signature of the OTC resection patients preserved hemisphere and the other two groups highlights the resilience of the system following damage to the contralateral homologue. Critically, however, a single OTC does not suffice for normal behavior, and, thereby, implicates the necessity for two hemispheres.

neuroscience↗

bioRxiv2023

Morphometrics of the preserved post-surgical hemisphere in paediatric drug-resistant epilepsy

Characterization of the structural integrity of cortex in adults who have undergone resection for epilepsy treatment has, in some cases, revealed persistent or even accelerated cortical atrophy but, in others, the converse is evident, and atrophy decelerates or even reverses. Whether this variability applies to a pediatric population, for whom postoperative plasticity may be greater than in adulthood, remains to be determined. Furthermore, understanding the morphometrics of this patient population is important, as cognitive gains have been associated with the anatomical status of preserved cortex post-resection. Here, we used high-resolution structural T1 magnetic resonance imaging data to compare the (1) gross anatomy, (2) cortical thickness, volume, and surface area for 34 cortical regions, and (3) volume for nine subcortical regions of 32 pediatric post-surgical cases and 51 healthy controls. Patients with either a preserved right hemisphere (RH) or left hemisphere (LH) had lower total white matter volume and select subcortical structures volumes, relative to controls; lateral ventricle size of both preserved RH and LH patients was also significantly larger than that of controls. However, relative to controls, only patients with a preserved RH had significantly lower total gray matter volume and lower thickness, volume, and surface area in multiple cortical regions, primarily in frontal and temporal cortex. The differences in preserved RH cortex of LH resection patients may relate to transfer of language function from the resected LH. Our findings lay the foundation for future studies probing associations of the morphometric differences in pediatric epilepsy surgery patients with neuropsychological outcomes.

neuroscience↗

bioRxiv2023

Differential functional reorganization of ventral and dorsal visual pathways following childhood hemispherectomy

Hemispherectomy is a surgical procedure in which an entire hemisphere of a patients brain is resected or functionally disconnected to manage seizures in individuals with drug-resistant epilepsy. Despite the extensive loss of input from both ventral and dorsal visual pathways of one hemisphere, pediatric patients who have undergone hemispherectomy show a remarkably high degree of perceptual function across many domains. In the current study, we sought to understand the extent to which functions of the ventral and dorsal visual pathways reorganize to the contralateral hemisphere following childhood hemispherectomy. To this end, we collected fMRI data from an equal number of left and right hemispherectomy patients who completed tasks that typically elicit lateralized responses from the ventral or the dorsal pathway, namely, word (left ventral), face (right ventral), tool (left dorsal), and global form (right dorsal) perception. Overall, there was greater evidence of functional reorganization in the ventral pathway than in the dorsal pathway. Importantly, because ventral and dorsal reorganization was tested in the very same patients, these results cannot be explained by idiosyncratic factors such as disease etiology, age at the time of surgery, or age at testing. These findings suggest that because the dorsal pathway may mature earlier, it may have a shorter developmental window of plasticity than the ventral pathway and, hence, be less malleable.

neuroscience↗

bioRxiv2021

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)

The traditional model of genomic data analysis - downloading data from centralized warehouses for analysis with local computing resources - is increasingly unsustainable. Not only are transfers slow and cost prohibitive, but this approach also leads to redundant and siloed compute infrastructure that makes it difficult to ensure security and compliance of protected data. The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) inverts this model, providing a unified cloud computing environment for data storage, management, and analysis. AnVIL eliminates the need for data movement, allows for active threat detection and monitoring, and provides scalable, shared computing resources that can be acquired by researchers as needed. This presents many new opportunities for collaboration and data sharing that will ultimately lead to scientific discoveries at scales not previously possible.

bioinformatics↗

bioRxiv2020

All hands on deck: Large-scale (re)sculpting of cortical circuits in post-resection children

Despite the relative successes in the surgical treatment of pharmacoresistant epilepsy, there is rather little research on the neural (re)organization that potentially subserves behavioral compensation. Here, we examined the post-surgical functional connectivity (FC) in children and adolescents who have undergone unilateral cortical resection and, yet, display remarkably normal behavior. Conventionally, FC has been investigated in terms of the mean correlation of the BOLD time courses extracted from different brain regions. Here, we demonstrated the value of segregating the voxel-wise relationships into mutually exclusive populations that were either positively or negatively correlated. While, relative to controls, the positive correlations were largely normal, negative correlations among networks were increased. Together, our results point to reorganization in the contralesional hemisphere, possibly suggesting competition for cortical territory due to the demand for representation of function. Conceivably, the ubiquitous negative correlations enable the differentiation of function in the reduced cortical volume following a unilateral resection.

neuroscience↗

bioRxiv2019

Effects of unilateral cortical resection of the visual cortex on bilateral human white matter

Children with unilateral resections of ventral occipito-temporal cortex (VOTC) typically do not evince visual perceptual impairments, even when relatively large swathes of VOTC are resected. In search of possible explanations for this behavioral competence, we evaluated white matter microstructure and connectivity in eight pediatric epilepsy patients following unilateral cortical resection and 15 age-matched controls. To uncover both local and broader resection-induced effects, we analyzed tractography data using two complementary approaches. First, the microstructural properties were measured in the inferior longitudinal and the inferior fronto-occipital fasciculi, the major VOTC association tracts. Group differences were only evident in the ipsilesional, and not in the contralesional, hemisphere, and single-subject analyses revealed that these differences were limited to the site of the resection. Second, graph theory was used to characterize the connectivity of the contralesional occipito-temporal regions. There were no changes to the network properties in patients with left VOTC resections nor in patients with resections outside the VOTC, but altered network efficiency was observed in two cases with right VOTC resections. These results suggest that, in many, although perhaps not all, cases of unilateral VOTC resections in childhood, the white matter integrity in the preserved contralesional hemisphere along with residual neural activity might be sufficient for normal visual perception.\n\nHighlightsO_LIThere is well-circumscribed white matter damage in pediatric epilepsy after surgery\nC_LIO_LIWhite matter pathways are normal distal as well as contralesional to the resection\nC_LIO_LIContralesional network properties differ after left or right hemisphere resection\nC_LIO_LIPreserved cortex and white matter may be sufficient for normal perception\nC_LI

neuroscience↗

bioRxiv2019

Mitonuclear interactions influence Alzheimer’s disease risk

We examined the associations between mitochondrial DNA haplogroups (MT-hg) and their interactions with a polygenic risk score based on nuclear-encoded mitochondrial genes (nMT-PRS) with risk of dementia and age of onset of dementia (AOO). Logistic regression was used to determine the effect of MT-hgs and nMT-PRS on dementia at baseline (332 controls / 204 cases). Cox proportional hazards models were used to model dementia AOO (n=1047; 433 incident cases). Additionally, we tested for interactions between MT-hg and nMT-PRS in the logistic and Cox models. MT-hg K and a one SD larger nMT-PRS were associated with elevated odds of dementia. Significant antagonistic interactions between the nMT-PRS and MT-hg K and T were observed. Individual MT-hg were not associated with AOO; however, a significant antagonistic interactions was observed between the nMT-PRS and MT-hg T and a synergistic interaction between the nMT-PRS and MT-hg V. These results suggest that MT-hgs influence dementia risk, and that variants in the nuclear and mitochondrial genome interact to influence the age of onset of dementia.\n\nHighlightsO_LIMitochondrial dysfunction has been proposed to influence dementia risk\nC_LIO_LIMT-hg K and T interacted with a genetic risk score to reduce dementia risk\nC_LIO_LIMT-hg T and V interacted with a genetic risk score to influence dementia age of onset\nC_LI

genetics↗

bioRxiv2019

MitoImpute: A Snakemake pipeline for imputation of mitochondrial genetic variants

BackgroundVariation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes to phylogenetic lineages or haplogroups. This lack of resolution can limit functional and clinical interpretation of a substantial body of existing mtDNA data. To address this limitation, we developed and evaluated a method for imputing missing mtDNA single nucleotide variants (mtSNVs) that uses a large reference alignment of complete mtDNA sequences. The method and reference alignment are combined into a pipeline, which we call MitoImpute. ResultsWe aligned the sequences of 36,960 complete human mitochondrial genomes downloaded from GenBank, filtered and controlled for quality. These sequences were reformatted for use in imputation software, IMPUTE2. We assessed the imputation accuracy of MitoImpute by measuring haplogroup and genotype concordance in data from the 1,000 Genomes Project and the Alzheimers Disease Neuroimaging Initiative (ADNI). The mean improvement of haplogroup assignment in the 1,000 Genomes samples was 42.7% (Matthews correlation coefficient = 0.64). In the ADNI cohort, we imputed missing single nucleotide variants. ConclusionsThese results show that our reference alignment and panel can be used to impute missing mtSNVs in exiting data obtained from using microarrays, thereby broadening the scope of functional and clinical investigation of mtDNA. This improvement may be particularly useful in studies where participants have been recruited over time and mtDNA data obtained using different methods, enabling better integration of early data collected using less accurate methods with more recent sequence data.

genomics↗