Biology subjects

Adams, H.

Publications and source records attributed to Adams, H..

12 recordsLinked to original sources

bioRxiv2026

Investigating biotic, chemical, and physical drivers of periphyton and invertebrate biomass in boreal streams supporting juvenile Atlantic salmon

1. Atlantic salmon (Salmo salar) are an anadromous fish with a broad distribution from eastern North America to western Europe, with ecological, economic, and cultural significance. Despite their expansive range, wild populations across the North Atlantic have experienced decline. Survival to reproductive age is a management concern, with a focus on identifying factors affecting the juvenile freshwater life stage. Specifically, research is needed to identify potential bottlenecks limiting freshwater productivity. 2. We addressed this research gap with a case study on the Exploits River, Newfoundland - a watershed that receives one of the largest anadromous Atlantic salmon returns in North America. We aimed to identify biotic, chemical, and physical predictors of food resources for juvenile salmon (i.e., invertebrates) and food resources for invertebrates (i.e., periphyton). To test our hypotheses, we collected data on a suite of biotic (e.g., invertebrates and periphyton), chemical (e.g., total dissolved N), and physical (e.g., wetted width) variables at 42 sites within and around this watershed. 3. We observed evidence for relationships between invertebrate biomass and biotic and temporal variables. Specifically, invertebrate biomass was higher at sites with high periphyton biomass that were sampled later in the season. In addition, we observed that periphyton biomass was related to biotic, chemical, and physical variables. Here, we present evidence for bottom-up control, with increased periphyton biomass supporting increased invertebrate biomass. 4. We expect knock-on effects where increased invertebrate biomass results in increased juvenile Atlantic salmon biomass. Our large sample size revealed some predictors of invertebrate biomass and periphyton biomass. However, we found no evidence of correlation between invertebrate biomass and chemical or physical variables. The low productivity of our maritime boreal forest system could be an outlier in expected biotic, chemical, and physical relationships in streams. 5. Our findings provide an important step forward in furthering boreal stream ecology, producing novel invertebrate and periphyton knowledge for watershed managers.

ecology↗

bioRxiv2026

Global identification of neuronal and astrocytic integral membrane proteins that require Retromer for their endosomal recycling.

Efficient transport of membrane proteins through the endosomal network is essential for brain development and function, with perturbation implicated in disease. Deficiencies in Retromer, a key regulator of endosomal transport, have been linked to aging-related neurodegenerative disorders including Alzheimers and Parkinsons disease. To better define the neuroprotective role of Retromer, we have applied cell surface restricted proteomics to identify those integral membrane proteins whose recycling to the plasma membrane is mediated by Retromer and associated cargo adaptors, sorting nexin 3 (SNX3), its paralogue sorting nexin 12 (SNX12), and sorting nexin 27 (SNX27) (data available via ProteomeXchange: PXD078277). By comparing primary rat cortical neurons and astrocytes we have identified several cargoes that require either SNX3/SNX12- or SNX27-Retromer complexes for endosomal recycling, including proteins involved in synapse organisation, synaptic signalling and Alzheimers disease pathology. We highlight that perturbed Retromer function leads to endosomal enlargement, and we establish a key role of SNX27-Retromer in modulating transport of glutamate across both neuronal and astrocytic membranes via recycling of glutamate transporters EAAT3 (SLC1A1) and EAAT1 (SLC1A3) respectively. Our study provides further mechanistic insight into the consequences of Retromer deficiency for neuronal and astrocytic function, offering new avenues of research in the treatment of neurodegenerative disease. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/724903v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@1225eedorg.highwire.dtl.DTLVardef@1863f1dorg.highwire.dtl.DTLVardef@99c21eorg.highwire.dtl.DTLVardef@976bfd_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO Suppression of Retromer and the sorting nexins (SNX27, SNX3/SNX12) leads to a significant change in the surface proteome of rat cortical neurons and astrocytes. Focusing on the glutamate transporters, SLC1A1 and SLC1A3, we have validated that SNX27-Retromer is required for their trafficking, with SNX27-Retromer suppression in astrocytes leading to a loss of glutamate uptake. C_FIG

molecular biology↗

bioRxiv2024

Impacts of urbanization on the health of American Robins (Turdus migratorus) in Chicagoland

Wild animals in urbanized environments face several unique challenges, including increased anthropogenic stressors, decreased natural food availability and quality, and increased pollutant exposure. While some work has shown that individual urbanization stressors can have negative impacts on aspects of wild bird physiology, other studies have demonstrated ambiguous or sometimes positive interactions. As such, the impact of multiple, coincident urban stressors on avian health still needs to be fully understood. Here, we addressed this knowledge gap by holistically measuring multiple physiological markers of American robin (Turdus migratorius) health across a gradient of urbanization throughout Chicagoland. We predicted that birds using highly urbanized habitats would experience higher heavy metal contamination, higher oxidative stress, lower body condition, higher avian malaria burden, and decreased measures of immune response compared to exurban birds in the Chicagoland area. Multiple linear models revealed that robins in more urbanized areas exhibited higher levels of heavy metal contamination and slightly elevated levels of associated physiological impairments compared to their counterparts in exurban sites. Additionally, noise and light pollution were significantly associated with oxidative stress and infection status, respectively, albeit in different directions. Overall, our findings underscore how the complex environmental changes that accompany urbanization can impact the health of urban bird populations.

ecology↗

bioRxiv2023

Geographic risk assessment of Batrachochytrium salamandrivorans invasion in Costa Rica as a means of informing emergence management and mitigation

Remotely-sensed risk assessments of emerging, invasive pathogens are key to targeted surveillance and outbreak responses. The recent emergence and spread of the fungal pathogen, Batrachochytrium salamandrivorans (Bsal), in Europe has negatively impacted multiple salamander species. Scholars and practitioners are increasingly concerned about the potential consequences of this lethal pathogen in the Americas, where salamander biodiversity is higher than anywhere else in the world. Although Bsal has not yet been detected in the Americas, certain countries have already proactively implemented monitoring and detection plans in order to identify areas of greatest concern and enable efficient contingency planning in the event of pathogen detection. To predict areas in Costa Rica with a high Bsal transmission risk, we employed ecological niche modeling combined with biodiversity and tourist visitation data to ascertain the specific risk to a country with world renowned biodiversity. Our findings indicate that approximately 23% of Costa Ricas landmass provides suitable conditions for Bsal, posing a threat to 37 salamander species. The Central and Talamanca mountain ranges, in particular, have habitats predicted to be highly suitable for the pathogen. To facilitate monitoring and mitigation efforts, we identified eight specific protected areas that we believe are at the greatest risk due to a combination of high biodiversity, tourist visitation, and suitable habitat for Bsal. We advise regular monitoring utilizing remotely-sensed data and ecological niche modeling to effectively target in-situ surveillance and as places begin implementing educational efforts.

ecology↗

bioRxiv2021

Investigating the genetic and environmental basis of head micromovements during MRI

IntroductionHead motion during magnetic resonance imaging is heritable. Further, it shares phenotypical and genetic variance with body mass index (BMI) and impulsivity. Yet, to what extent this trait is related to single genetic variants and physiological or behavioral features is unknown. We investigated the genetic basis of head motion in a meta-analysis of genome-wide association studies. Further, we tested whether physiological or psychological measures, such as respiratory rate or impulsivity, mediated the relationship between BMI and head motion. MethodsWe conducted a genome-wide association meta-analysis for mean and maximal framewise head displacement (FD) in seven population neuroimaging cohorts (UK Biobank, LIFE-Adult, Rotterdam Study cohort 1-3, Austrian Stroke Prevention Family Study, Study of Health in Pomerania; total N = 35.109). We performed a pre-registered analysis to test whether respiratory rate, respiratory volume, self-reported impulsivity and heart rate mediated the relationship between BMI and mean FD in LIFE-Adult. ResultsNo variant reached genome-wide significance for neither mean nor maximal FD. Neither physiological nor psychological measures mediated the relationship between BMI and head motion. ConclusionBased on these findings from a large meta-GWAS and pre-registered follow-up study, we conclude that the previously reported genetic correlation between BMI and head motion relies on polygenic variation, and that neither psychological nor simple physiological parameters explain a substantial amount of variance in the association of BMI and head motion. Future imaging studies should thus rigorously control for head motion at acquisition and during preprocessing.

neuroscience↗

bioRxiv2021

Neural correlates of orbital telorism

Orbital telorism, the interocular distance, is a clinically informative and in extremes is considered a minor physical anomaly. While its extremes, hypo- and hypertelorism, have been linked to disorders often related to cognitive ability, little is known about the neural correlates of normal variation of telorism within the general population. We derived measures of orbital telorism from cranial magnetic resonance imaging (MRI) by calculating the distance between the eyeball center of gravity in two population-based datasets (N=5,653, N=29,824, Mean age 64.66, 63.75 years). This measure was found to be related grey matter tissue density within numerous regions of the brain, including, but surprisingly not limited to, the frontal regions, in both positive and negative directions. Additionally, telorism was related to several cognitive functions, such as Perdue Pegboard test (Beta, P-value, (CI95%) -0.02, 1.63x10-7(-0.03;-0.01)) and fluid intelligence (0.02, 4.75x10-06 (0.01:0.02)), with some relationships driven by individuals with a smaller orbital telorism. This is reflective of the higher prevalence of hypo-telorism in developmental disorders, specifically those that accompany lower cognitive lower functioning. This study suggests, despite previous links only made in clinical extremes, that orbital telorism holds some relation to structural brain development and cognitive function in the general population. This relationship is likely driven by shared developmental periods.

neuroscience↗

bioRxiv2020

GenNet framework: interpretable neural networks for phenotype prediction

Deep learning is rarely used in population genomics because of the computational burden and challenges in interpreting neural networks. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biological knowledge from public databases, resulting in neural networks that contain only biological plausible connections. We applied the framework to seventeen phenotypes from a case-control study, a population-based study and the UK Biobank. Interpreting the networks revealed well-replicated genes such as HERC2 and OCA2 for hair and eye color and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework obtained an AUC of 0.74 in the held-out test set and identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases.

bioinformatics↗

bioRxiv2019

Seroprevalence of viral and vector-borne bacterial pathogens in domestic dogs (Canis familiaris) in northern Botswana

BackgroundDomestic dogs (Canis familiaris) have the potential to act as disease reservoirs for wildlife and are important sentinels for common circulating pathogens. Therefore, the infectious disease seroprevalence among domestic dogs in northern Botswana may be indicative of pathogen exposure of various wildlife species. The objective of this study was to assess the seroprevalence of Ehrlichia spp., Borrelia burgdorferi, Anaplasma spp., Dirofilaria immitis, canine adenovirus, canine parvovirus, and canine distemper virus in domestic dogs as proxies of disease prevalence in the local wildlife in the Okavango Delta region of Botswana. Statistical analysis assessed crude and factor-specific seroprevalence proportions and assessed the factors age, sex, and geographical location as predictors of seropositivity. Logistic regression was used to identify adjusted predictors of seropositivity for each of the pathogens of interest.\n\nResultsSamples from 233 dogs in a total of 7 locations in Maun, Botswana, and surrounding villages were collected and serologically analyzed. No dogs were seropositive for B. burgdorferi, while low seroprevalence proportions were observed for Anaplasma spp. (2.2%) and D. immitis (0.9%). Higher seroprevalence proportions were observed for the tick-borne pathogen, Ehrlichia spp. (21.0%), and 19.7% were seropositive for canine adenovirus (hepatitis). The highest seroprevalence proportions were for canine parvovirus (70.0%) and canine distemper virus (44.8%). The predictors of seropositivity revealed that adults were more likely to be seropositive for canine adenovirus, canine distemper virus, and canine parvovirus than juveniles, and location was a risk factor for canine adenovirus, canine distemper virus, canine parvovirus, and Ehrlichia spp.\n\nConclusionsResults indicate that increasing tick control and vaccination campaigns for domestic dogs may improve the health of domestic animals, and potentially wildlife and humans in the Okavango Delta since viral and vector-borne bacterial pathogens can be transmitted between them.

microbiology↗

bioRxiv2019

Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study

Key PointsO_ST_ABSQuestionC_ST_ABSIs the gap between brain age predicted from MRI and chronological age associated with incident dementia in a general population of Dutch adults?\n\nFindingsBrain age was predicted using a deep learning model, using MRI-derived grey matter density maps. In a population based study including 5496 participants, the observed gap was significantly associated with the risk of dementia.\n\nMeaningThe gap between MRI-brain predicted and chronological age is potentially a biomarker for dementia risk screening.\n\nAbstractO_ST_ABSImportanceC_ST_ABSThe gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as biomarker for early-stage neurodegeneration and potentially as a risk indicator for dementia. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link.\n\nObjectiveWe aimed to investigate the utility of such a gap as a risk biomarker for incident dementia in a general Dutch population, using a deep learning approach for predicting brain age based on MRI-derived grey matter maps.\n\nDesignData was collected from participants of the cohort-based Rotterdam Study who underwent brain magnetic resonance imaging between 2006 and 2015. This study was performed in a longitudinal setting and all participant were followed up for incident dementia until 2016.\n\nSettingThe Rotterdam Study is a prospective population-based study, initiated in 1990 in the suburb Ommoord of in Rotterdam, the Netherlands.\n\nParticipantsAt baseline, 5496 dementia- and stroke-free participants (mean age 64.67{+/-}9.82, 54.73% women) were scanned and screened for incident dementia. During 6.66{+/-}2.46 years of follow-up, 159 people developed dementia.\n\nMain outcomes and measuresWe built a convolutional neural network (CNN) model to predict brain age based on its MRI. Model prediction performance was measured in mean absolute error (MAE). Reproducibility of prediction was tested using the intraclass correlation coefficient (ICC) computed on a subset of 80 subjects. Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for years of education, ApoE{varepsilon}4 allele carriership, grey matter volume and intracranial volume. Additionally, we computed the attention maps of CNN, which shows which brain regions are important for age prediction.\n\nResultsMAE of brain age prediction was 4.45{+/-}3.59 years and ICC was 0.97 (95% confidence interval CI=0.96-0.98). Logistic regression and Cox proportional hazards models showed that the age gap was significantly related to incident dementia (odds ratio OR=1.11 and 95% confidence intervals CI=1.05-1.16; hazard ratio HR=1.11 and 95% CI=1.06-1.15, respectively). Attention maps indicated that grey matter density around the amygdalae and hippocampi primarily drive the age estimation.\n\nConclusion and relevanceWe show that the gap between predicted and chronological brain age is a biomarker associated with risk of dementia development. This suggests that it can be used as a biomarker, complimentary to those that are known, for dementia risk screening.

epidemiology↗

bioRxiv2018

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,822 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 161 genome-wide significant associations pointing to wnt/{beta}-catenin, TGF-{beta} and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

genetics↗

bioRxiv2017

Genome-wide Association Study Links APOEϵ4 and BACE1 Variants with Plasma Amyloid β Levels

INTRODUCTIONThere is increasing interest in plasma A{beta} as an endophenotype and biomarker of Alzheimers disease (AD). Identifying the genetic determinants of plasma A{beta} levels may elucidate important processes that determine plasma A{beta} measures. METHODSWe included 12,369 non-demented participants derived from eight population-based studies. Imputed genetic data and plasma A{beta}1-40, A{beta}1-42 levels and A{beta}1-42/A{beta}1-40 ratio were used to perform genome-wide association studies, gene-based and pathway analyses. Significant variants and genes were followed-up for the association with PET A{beta} deposition and AD risk. RESULTSSingle-variant analysis identified associations across APOE for A{beta}1-42 and A{beta}1-42/A{beta}1-40 ratio, and BACE1 for A{beta}1-40. Gene-based analysis of A{beta}1-40 additionally identified associations for APP, PSEN2, CCK and ZNF397. There was suggestive interaction between a BACE1 variant and APOE{varepsilon}4 on brain A{beta} deposition. DISCUSSIONIdentification of variants near/in known major A{beta}-processing genes strengthens the relevance of plasma-A{beta} levels both as an endophenotype and a biomarker of AD.

genetics↗

bioRxiv2017

A common haplotype lowers SPI1 (PU.1) expression in myeloid cells and delays age at onset for Alzheimer’s disease

In this study we used age at onset of Alzheimers disease (AD), cerebrospinal fluid (CSF) biomarkers, and cis-expression quantitative trait loci (cis-eQTL) datasets to identify candidate causal genes and mechanisms underlying AD GWAS loci. In a genome-wide survival analysis of 40,255 samples, eight of the previously reported AD risk loci are significantly (P < 5x10-8) or suggestively (P < 1x10-5) associated with age at onset-defined survival (AAOS) and a further fourteen novel loci reached suggestive significance. Using stratified LD score regression we demonstrated a significant enrichment of AD heritability in hematopoietic cells of the myeloid and B-lymphoid lineage. We then investigated the impact of these 22 AAOS-associated variants on CSF biomarkers and gene expression in cells of the myeloid lineage. In particular, the minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, shows association with higher age at onset of AD (P=8.40x10-6), higher CSF levels of A{beta}42 (P=1.2x10-4), and lower expression of SPI1 in monocytes (P=1.50x10-105) and macrophages (P=6.41x10-87). SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability is enriched within the SPI1 cistromes of monocytes and macrophages, implicating a myeloid PU.1 target gene network in the etiology of AD. Finally, experimentally altered PU.1 levels are correlated with phagocytic activity of BV2 mouse microglial cells and specific changes in the expression of multiple myeloid-expressed genes, including the mouse orthologs of AD-associated genes, APOE, CLU/APOJ, CD33, MS4A4A/MS4A6A, and TYROBP. Our results collectively suggest that lower SPI1 expression reduces AD risk by modulating myeloid cell gene expression and function.

neuroscience↗