Genetic architecture of brain morphology and overlap with neuropsychiatric traits.

Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.

Multiplet-Assisted Peak Alignment for 1H NMR-Based Metabolomics.

NMR-based metabolomics aims at recovering biological information by comparing spectral data from samples of biological interest and appropriate controls. Any statistical analysis performed on the data matrix relies on the proper peak alignment to produce meaningful results. Through the last decades, several peak alignment algorithms have been proposed, as well as alternatives like spectral binning or strategies for annotation and quantification, the latter depending on reference databases. Most of the alignment algorithms, mainly based on segmentation of the spectra, present limitations for regions with peak overlap or cases of frequency order exchange. Here, we present our multiplet-assisted peak alignment algorithm, a new methodology that consists of aligning peaks by matching multiplet profiles of f1 traces from J-resolved spectra. A correspondence matrix with the linked f1 traces is built, and multivariate data analysis can be performed on it to obtain useful information from the data, overcoming the issues of peak overlap and frequency crossovers. Statistical total correlation spectroscopy can be applied on the matrix as well, toward a better identification of molecules of interest. The results can be queried on one-dimensional (1D) 1H databases or can be directly coupled to our previously published Chemical Shift Multiplet Database.

Bias correction for inverse variance weighting Mendelian randomization.

Inverse-variance weighted two-sample Mendelian randomization (IVW-MR) is the most widely used approach that utilizes genome-wide association studies (GWAS) summary statistics to infer the existence and the strength of the causal effect between an exposure and an outcome. Estimates from this approach can be subject to different biases due to the use of weak instruments and winner's curse, which can change as a function of the overlap between the exposure and outcome samples. We developed a method (MRlap) that simultaneously considers weak instrument bias and winner's curse while accounting for potential sample overlap. Assuming spike-and-slab genomic architecture and leveraging linkage disequilibrium score regression and other techniques, we could analytically derive, reliably estimate, and hence correct for the bias of IVW-MR using association summary statistics only. We tested our approach using simulated data for a wide range of realistic settings. In all the explored scenarios, our correction reduced the bias, in some situations by as much as 30-fold. In addition, our results are consistent with the fact that the strength of the biases will decrease as the sample size increases and we also showed that the overall bias is also dependent on the genetic architecture of the exposure, and traits with low heritability and/or high polygenicity are more strongly affected. Applying MRlap to obesity-related exposures revealed statistically significant differences between IVW-based and corrected effects, both for nonoverlapping and fully overlapping samples. Our method not only reduces bias in causal effect estimation but also enables the use of much larger GWAS sample sizes, by allowing for potentially overlapping samples.

Niche differentiation, reproductive interference, and range expansion.

Understanding species distributions and predicting future range shifts requires considering all relevant abiotic factors and biotic interactions. Resource competition has received the most attention, but reproductive interference is another widespread biotic interaction that could influence species ranges. Rubyspot damselflies (Hetaerina spp.) exhibit a biogeographic pattern consistent with the hypothesis that reproductive interference has limited range expansion. Here, we use ecological niche models to evaluate whether this pattern could have instead been caused by niche differentiation. We found evidence for climatic niche differentiation, but the species that encounters the least reproductive interference has one of the narrowest and most peripheral niches. These findings strengthen the case that reproductive interference has limited range expansion and also provide a counterexample to the idea that release from negative species interactions triggers niche expansion. We propose that release from reproductive interference enables species to expand in range while specializing on the habitats most suitable for breeding.

Can metformin prevent cancer relative to sulfonylureas? A target trial emulation accounting for competing risks and poor overlap via double/debiased machine learning estimators.

There is mounting interest in the possibility that metformin, indicated for glycemic control in type 2 diabetes, has a range of additional beneficial effects. Randomized trials have shown that metformin prevents adverse cardiovascular events, and metformin use has also been associated with reduced cognitive decline and cancer incidence. In this paper, we dig more deeply into whether metformin prevents cancer by emulating target randomized trials comparing metformin to sulfonylureas as first line diabetes therapy using data from Clinical Practice Research Datalink, a U.K. primary care database (1987-2018). We included individuals with diabetes, no prior cancer diagnosis, no chronic kidney disease, and no prior diabetes therapy who initiated metformin (N=93353) or a sulfonylurea (N=13864). In our cohort, the estimated overlap weighted additive separable direct effect of metformin compared to sulfonylureas on cancer risk at 6 years was -1% (.95 CI=-2.2%, 0.1%), which is consistent with metformin providing no direct protection against cancer incidence or substantial protection. The analysis faced two methodological challenges-poor overlap, and pre-cancer death as a competing risk. To address these issues while minimizing nuisance model misspecification, we develop and apply double/debiased machine learning estimators of overlap weighted separable effects in addition to more traditional effect estimates.

The Evolution of Local Co-occurrence in Birds in Relation to Latitude, Degree of Sympatry, and Range Symmetry.

AbstractRecent speciation rates and the degree of range-wide sympatry are usually higher farther from the equator. Is there also a higher degree of secondary syntopy (coexistence in local assemblages in sympatry) at higher latitudes and, subsequently, an increase in local species richness? We studied the evolution of syntopy in passerine birds using worldwide species distribution data. We chose recently diverged species pairs from subclades not older than 5 or 7 million years, range-wide degree of sympatry not lower than 5% or 25%, and three definitions of the breeding season. We related their syntopy to latitude, the degree of sympatry (breeding range overlap), range symmetry, and the age of split. Syntopy was positively related to latitude, but it did not differ between tropical and temperate regions, instead increasing from the Southern to the Northern Hemisphere. Syntopy was also higher in species pairs with a higher degree of sympatry and more symmetric ranges, but it did not predict local species richness. Following speciation, species in the Northern Hemisphere presumably achieve positive local co-occurrence faster than elsewhere, which could facilitate their higher speciation rates. However, this does not seem to be linked to local species richness, which is probably governed by other processes.

Airway inflammation in a novel mouse model of asthma-COPD overlap induced by co-exposure to papain and tobacco smoke.

Asthma and chronic obstructive pulmonary disease (COPD) are respiratory diseases associated with airway inflammation, which is the main pathogenesis. Although their causes and characteristics differ, in some cases, asthma and COPD may coexist in the same patient in a condition called asthma-COPD overlap (ACO). The prognosis of ACO is more unfavourable than those of asthma or COPD alone, without any treatment strategies demonstrating efficacy. Owing to its intricate spectrum of features, the detailed pathogenesis of how ACO exacerbates respiratory features remains unclear. In this study, we exposed papain-induced asthma model mice to tobacco smoke to establish an ACO mouse model, in which features of airway inflammation observed in both asthma and COPD were incorporated. This model exhibited distinctive mixed and corticosteroid-resistant airway inflammation and emphysematous changes that are characteristic of ACO. The novel mouse model established here is expected to significantly contribute to elucidating the mechanisms of the broad pathologies of ACO and identifying potential therapeutic targets.

Identification of reliable QTLs and designed QTL breeding for grain shape and milling quality in the reciprocal introgression lines in rice.

Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers' final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.

Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis.

BACKGROUND: To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved. METHODS: Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations. RESULTS: Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL. CONCLUSIONS: Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.

Manipulated overlapping reactivation of multiple memories promotes explicit gist abstraction.

Sleep is considered to promote gist abstraction on the basis of spontaneous memory reactivation. As speculated in the theory of 'information overlap to abstract (iOtA)', 'overlap' between reactivated memories, beyond reactivation, is crucial to gist abstraction. Yet so far, empirical research has not tested this theory by manipulating the factor of 'overlap'. In the current study, 'overlap' itself was manipulated by targeted memory reactivation (TMR), through simultaneously reactivating multiple memories that either contain or do not contain spatially overlapped gist information, to investigate the effect of overlapping reactivation on gist abstraction. This study had a factorial design of 2 factors with 2 levels respectively (spatial overlap/no spatial overlap, TMR/no-TMR). Accordingly, 82 healthy college students (aged 19 âˆ¼ 25, 57 females) were randomized into four groups. After learning 16 pictures, paired with 4 auditory cues (4 pictures - 1 cue) according to the grouping, participants were given a 90-minute nap opportunity. Then TMR cueing was conducted during N2 and slow wave sleep of the nap. Performance in memory task was used to measure gist abstraction. The results showed a significant main effect of TMR on both implicit and explicit gist abstraction, and a marginally significant interaction effect on explicit gist abstraction. Further analyses showed that explicit gist abstraction in the spatial overlap & TMR group was significantly better than in the control group. Moreover, explicit gist abstraction was positively correlated with spindle density. The current study thus indicates that TMR facilitates gist abstraction, and explicit gist abstraction may benefit more from overlapping reactivation.

Anti-Ku + myositis: an acquired inflammatory protein-aggregate myopathy.

Myositis with anti-Ku-autoantibodies is a rare inflammatory myopathy associated with various connective tissue diseases. Histopathological studies have identified inflammatory and necrotizing aspects, but a precise morphological analysis and pathomechanistic disease model are lacking. We therefore aimed to carry out an in-depth morpho-molecular analysis to uncover possible pathomechanisms. Muscle biopsy specimens from 26 patients with anti-Ku-antibodies and unequivocal myositis were analyzed by immunohistochemistry, immunofluorescence, transcriptomics, and proteomics and compared to biopsy specimens of non-disease controls, immune-mediated necrotizing myopathy (IMNM), and inclusion body myositis (IBM). Clinical findings and laboratory parameters were evaluated retrospectively and correlated with morphological and molecular features. Patients were mainly female (92%) with a median age of 56.5 years. Isolated myositis and overlap with systemic sclerosis were reported in 31%, respectively. Isolated myositis presented with higher creatine kinase levels and cardiac involvement (83%), whereas systemic sclerosis-overlap patients often had interstitial lung disease (57%). Histopathology showed a wide spectrum from mild to pronounced myositis with diffuse sarcolemmal MHC-class I (100%) and -II (69%) immunoreactivity, myofiber necrosis (88%), endomysial inflammation (85%), thickened capillaries (84%), and vacuoles (60%). Conspicuous sarcoplasmic protein aggregates were p62, BAG3, myotilin, or immunoproteasomal beta5i-positive. Proteomic and transcriptomic analysis identified prominent up-regulation of autophagy, proteasome, and hnRNP-related cell stress. To conclude, Ku + myositis is morphologically characterized by myofiber necrosis, MHC-class I and II positivity, variable endomysial inflammation, and distinct protein aggregation varying from IBM and IMNM, and it can be placed in the spectrum of scleromyositis and overlap myositis. It features characteristic sarcoplasmic protein aggregation on an acquired basis being functionally associated with altered chaperone, proteasome, and autophagy function indicating that Ku + myositis exhibit aspects of an acquired inflammatory protein-aggregate myopathy.

Neopterin in patients with COPD, asthma, and ACO: association with endothelial and lung functions.

BACKGROUND AND OBJECTIVE: Endothelial dysfunction has been widely recognized in chronic airway diseases, including chronic obstructive pulmonary disease (COPD) and asthma; however, it remains unclear in asthma-COPD overlap (ACO). Neopterin (NP), a metabolite of guanosine triphosphate, is a novel biomarker for identifying the increased risk of adverse cardiovascular events. This study aims to investigate the association of NP with endothelial dysfunction and impaired lung function in COPD, asthma, and ACO patients. METHODS: A total of 77 subjects were prospectively recruited. All the participants underwent lung function test, endothelial function evaluation, including pulse wave velocity (PWV) and flow-mediated dilation (FMD), and blood sample detection. Moreover, the effect of NP on endothelial cells (ECs) in anoxic environments was assessed in vitro. RESULTS: Endothelial function was significantly decreased in the COPD and ACO patients compared with that in the healthy controls (P < 0.05). Forced expiratory volume in 1 s (FEV1) was negatively correlated with PWV and positively correlated with FMD (P < 0.05). NP was significantly increased in patients with chronic respiratory diseases compared with that in the control group, with COPD being the highest, followed by asthma, and ACO as the last (P < 0.05). The plasma level of NP exhibited negative correlations with FEV1 and positive correlations with PWV (P < 0.05). In vitro, a high level of NP increased the reactive oxygen species (ROS) and decreased the mitochondrial membrane potential (ΔΨm) of ECs dose-dependently in a hypoxic environment (P < 0.05). CONCLUSION: NP was related to disease severity of chronic airway diseases and involved in the pathogenesis of endothelial dysfunction. A high NP level may contribute to endothelial dysfunction by increasing the oxidative stress of ECs dose-dependently in a hypoxic environment. Our findings may provide a novel evaluation and therapeutic target for endothelial dysfunction related to chronic airway diseases.

Upregulated microRNA-125b-5p in patients with asthma-COPD overlap mediates oxidative stress and late apoptosis via targeting IL6R/TRIAP1 signaling.

BACKGROUND: Among patients with chronic obstructive pulmonary disease (COPD), some have features of both asthma and COPD-a condition categorized as asthma-COPD overlap (ACO). Our aim was to determine whether asthma- or COPD-related microRNAs (miRNAs) play a role in the pathogenesis of ACO. METHODS: A total of 22 healthy subjects and 27 patients with ACO were enrolled. We selected 6 miRNAs that were found to correlate with COPD and asthma. The expression of miRNAs and target genes was analyzed using quantitative reverse-transcriptase polymerase chain reaction. Cell apoptosis and intracellular reactive oxygen species production were evaluated using flow cytometry. In vitro human monocytic THP-1 cells and primary normal human bronchial epithelial (NHBE) cells under stimuli with cigarette smoke extract (CSE) or ovalbumin (OVA) allergen or both were used to verify the clinical findings. RESULTS: We identified the upregulation of miR-125b-5p in patients with ACO and in THP-1 cells stimulated with CSE plus OVA allergen. We selected 16 genes related to the miR-125b-5p pathway and found that IL6R and TRIAP1 were both downregulated in patients with ACO and in THP-1 cells stimulated with CSE plus OVA. The percentage of late apoptotic cells increased in the THP-1 cell culture model when stimulated with CSE plus OVA, and the effect was reversed by transfection with miR-125b-5p small interfering RNA (siRNA). The percentage of reactive oxygen species-producing cells increased in the NHBE cell culture model when stimulated with CSE plus OVA, and the effect was reversed by transfection with miR-125b-5p siRNA. In NHBE cells, siRNA transfection reversed the upregulation of STAT3 under CSE+OVA stimulation. CONCLUSIONS: Our study revealed that upregulation of miR-125b-5p in patients with ACO mediated late apoptosis in THP-1 cells and oxidative stress in NHBE cells via targeting IL6R and TRIAP1. STAT3 expression was also regulated by miR-125b-5p.

Shared familial risk for type 2 diabetes mellitus and psychiatric disorders: a nationwide multigenerational genetics study.

BACKGROUND: Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM. METHODS: We linked 659 906 individuals born in Denmark 1990-2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981-2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders. RESULTS: Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35-1.42; grandparents: 1.14, 1.13-1.15; and aunts/uncles: 1.19, 1.16-1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08-1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa. CONCLUSIONS: Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation.

Cusp overlap method for self-expanding transcatheter aortic valve replacement.

BACKGROUND: Conduction disturbances and the need for permanent pacemaker (PPM) implantation remains a common complication for transcatheter aortic valve replacement (TAVR), particularly when self-expanding (SE) valves are used. AIMS: We compared in-hospital and 30-day rates of new PPM implantation between patients undergoing TAVR with SE valves using the conventional three-cusp coplanar implantation technique and the cusp-overlap technique. METHODS: We retrospectively compared patients without a pre-existing PPM who underwent a TAVR procedure with SE Evolut R or PRO valves using the cusp-overlap technique from July 2018 to September 2020 (n = 519) to patients who underwent TAVR using standard three-cusp technique from April 2016 to March 2017 (n = 128) in two high volume Canadian centers. RESULTS: There was no significant difference in baseline RBBB between the groups (10.4% vs. 13.2; p = 0.35). The rate of in-hospital new complete heart block (9.4% vs. 23.4%; p ≤ 0.001) and PPM implantation (8% vs. 21%; p ≤ 0.001) were significantly reduced when using the cusp-overlap technique. The incidence of new LBBB (30.4% vs. 29%; p = 0.73) was similar. At 30 days, the rates of new complete heart block (11% vs. 23%; p ≤ 0.001) and PPM implantation (10% vs. 21%, p ≤ 0.001) remained significantly lower in the cusp-overlap group, while the rate of new LBBB (35% vs. 30%; p = 0.73) was similar. CONCLUSION: Cusp-overlap approach offers several potential technical advantages compared to standard three-cusp view, and may result in lower PPM rates in TAVR with SE Evolut valve.

Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute-Lipid Interactions.

This study explores the research area of drug solubility in lipid excipients, an area persistently complex despite recent advancements in understanding and predicting solubility based on molecular structure. To this end, this research investigated novel descriptor sets, employing machine learning techniques to understand the determinants governing interactions between solutes and medium-chain triglycerides (MCTs). Quantitative structure-property relationships (QSPR) were constructed on an extended solubility data set comprising 182 experimental values of structurally diverse drug molecules, including both development and marketed drugs to extract meaningful property relationships. Four classes of molecular descriptors, ranging from traditional representations to complex geometrical descriptions, were assessed and compared in terms of their predictive accuracy and interpretability. These include two-dimensional (2D) and three-dimensional (3D) descriptors, Abraham solvation parameters, extended connectivity fingerprints (ECFPs), and the smooth overlap of atomic position (SOAP) descriptor. Through testing three distinct regularized regression algorithms alongside various preprocessing schemes, the SOAP descriptor enabled the construction of a superior performing model in terms of interpretability and accuracy. Its atom-centered characteristics allowed contributions to be estimated at the atomic level, thereby enabling the ranking of prevalent molecular motifs and their influence on drug solubility in MCTs. The performance on a separate test set demonstrated high predictive accuracy (RMSE = 0.50) for 2D and 3D, SOAP, and Abraham Solvation descriptors. The model trained on ECFP4 descriptors resulted in inferior predictive accuracy. Lastly, uncertainty estimations for each model were introduced to assess their applicability domains and provide information on where the models may extrapolate in chemical space and, thus, where more data may be necessary to refine a data-driven approach to predict solubility in MCTs. Overall, the presented approaches further enable computationally informed formulation development by introducing a novel in silico approach for rational drug development and prediction of dose loading in lipids.

On variance estimation of the inverse probability-of-treatment weighting estimator: A tutorial for different types of propensity score weights.

Propensity score methods, such as inverse probability-of-treatment weighting (IPTW), have been increasingly used for covariate balancing in both observational studies and randomized trials, allowing the control of both systematic and chance imbalances. Approaches using IPTW are based on two steps: (i) estimation of the individual propensity scores (PS), and (ii) estimation of the treatment effect by applying PS weights. Thus, a variance estimator that accounts for both steps is crucial for correct inference. Using a variance estimator which ignores the first step leads to overestimated variance when the estimand is the average treatment effect (ATE), and to under or overestimated estimates when targeting the average treatment effect on the treated (ATT). In this article, we emphasize the importance of using an IPTW variance estimator that correctly considers the uncertainty in PS estimation. We present a comprehensive tutorial to obtain unbiased variance estimates, by proposing and applying a unifying formula for different types of PS weights (ATE, ATT, matching and overlap weights). This can be derived either via the linearization approach or M-estimation. Extensive R code is provided along with the corresponding large-sample theory. We perform simulation studies to illustrate the behavior of the estimators under different treatment and outcome prevalences and demonstrate appropriate behavior of the analytical variance estimator. We also use a reproducible analysis of observational lung cancer data as an illustrative example, estimating the effect of receiving a PET-CT scan on the receipt of surgery.

Balancing versus modelling in weighted analysis of non-randomised studies with survival outcomes: A simulation study.

Weighting methods are widely used for causal effect estimation in non-randomised studies. In general, these methods use the propensity score (PS), the probability of receiving the treatment given the covariates, to arrive at the respective weights. All of these "modelling" methods actually optimize prediction of the respective outcome, which is, in the PS model, treatment assignment. However, this does not match with the actual aim of weighting, which is eliminating the association between covariates and treatment assignment. In the "balancing" approach, covariates are thus balanced directly by solving systems of numerical equations, explicitly without fitting a PS model. To compare modelling, balancing and hybrid approaches to weighting we performed a large simulation study for a binary treatment and a survival outcome. For maximal practical relevance all simulation parameters were selected after a systematic review of medical studies that used PS methods for analysis. We also introduce a new hybrid method that uses the idea of the covariate balancing propensity score and matching weights, thus avoiding extreme weights. In addition, we present a corrected robust variance estimator for some of the methods. Overall, our simulations results indicate that balancing approach methods work worse than expected. However, among the considered balancing methods, entropy balancing consistently outperforms the variance balancing approach. All methods estimating the average treatment effect in the overlap population perform well with very little bias and small standard errors even in settings with misspecified propensity score models. Finally, the coverage using the standard robust variance estimator was too high for all methods, with the proposed corrected robust variance estimator improving coverage in a variety of settings.

Effects of food supplementation and helminth removal on space use and spatial overlap in wild rodent populations.

Animal space use and spatial overlap can have important consequences for population-level processes such as social interactions and pathogen transmission. Identifying how environmental variability and inter-individual variation affect spatial patterns and in turn influence interactions in animal populations is a priority for the study of animal behaviour and disease ecology. Environmental food availability and macroparasite infection are common drivers of variation, but there are few experimental studies investigating how they affect spatial patterns of wildlife. Bank voles (Clethrionomys glareolus) are a tractable study system to investigate spatial patterns of wildlife and are amenable to experimental manipulations. We conducted a replicated, factorial field experiment in which we provided supplementary food and removed helminths in vole populations in natural forest habitat and monitored vole space use and spatial overlap using capture-mark-recapture methods. Using network analysis, we quantified vole space use and spatial overlap. We compared the effects of food supplementation and helminth removal and investigated the impacts of season, sex and reproductive status on space use and spatial overlap. We found that food supplementation decreased vole space use while helminth removal increased space use. Space use also varied by sex, reproductive status and season. Spatial overlap was similar between treatments despite up to threefold differences in population size. By quantifying the spatial effects of food availability and macroparasite infection on wildlife populations, we demonstrate the potential for space use and population density to trade-off and maintain consistent spatial overlap in wildlife populations. This has important implications for spatial processes in wildlife including pathogen transmission.

Experimental manipulation of food availability and macroparasite prevalence reveal differential effects on space use in wild rodents.

Research Highlight: Mistrick, J., Veitch, J. S. M., Kitchen, S. M., Clague, S., Newman, B. C., Hall, R. J., Budischak, S. A., Forbes, K. M., & Craft, M. E. (2024). Effects of food supplementation and helminth removal on space use and spatial overlap in wild rodent populations. Journal of Animal Ecology. http://doi.org/10.1111/1365-2656.14067. The spread of pathogens has been of long-standing interest, even before dramatic outbreaks of avian influenza and the coronavirus pandemic spiked broad public interest. However, the dynamics of pathogen spread in wild populations are complex, with multiple effects shaping where animals go (their space use), population density and, more fundamentally, the resultant patterns of contacts (direct or indirect) among individuals. Thus, experimental studies exploring the dynamics of contact under different sets of conditions are needed. In the current field study, Mistrick et al. (2024) used a multifactorial experimental design, manipulating food availability and individual pathogen infection state in wild bank voles (Clethrionomys glareolus). They found that while food availability, individual traits and seasonality can affect how far individual voles moved, the degree of overlap between individual voles remained largely the same despite a high variation in population density-which itself was affected by food availability. These results highlight how biotic and abiotic factors can shape patterns of space use and balance the level of spatial overlap through multiple pathways.