Human brain connectomes include sets of densely connected hub regions. However, the consistency and reproducibility of functional connectome hubs have not been established to date and the genetic signatures underlying robust hubs remain unknown. Here, we conduct a worldwide harmonized meta-connectomic analysis by pooling resting-state functional MRI data of 5212 healthy young adults across 61 independent cohorts. We identify highly consistent and reproducible connectome hubs in heteromodal and unimodal regions both across cohorts and across individuals, with the greatest effects observed in lateral parietal cortex. These hubs show heterogeneous connectivity profiles and are critical for both intra- and inter-network communications. Using post-mortem transcriptome datasets, we show that as compared to non-hubs, connectome hubs have a spatiotemporally distinctive transcriptomic pattern dominated by genes involved in the neuropeptide signaling pathway, neurodevelopmental processes, and metabolic processes. These results highlight the robustness of macroscopic connectome hubs and their potential cellular and molecular underpinnings, which markedly furthers our understanding of how connectome hubs emerge in development, support complex cognition in health, and are involved in disease. A worldwide harmonized meta-connectomic analysis of 5212 healthy young adults across 61 independent cohorts provides consistent, reproducible, and transcriptionally relevant functional connectome hubs in the resting human brain. Connectome hubs play a crucial role in global brain communication2 and support a broad range of cognitive processing, such as working memory3 and semantic processing4. Growing evidence suggests that these highly connected brain hubs are preferentially targeted by many neuropsychiatric disorders8, which provides critical clues for understanding the biological mechanisms of disorders and establishing biomarkers for disease diagnosis9 and treatment evaluation10 (refs. 12 for reviews).Functional connectome mapping studies have identified sets of densely connected regions in large-scale human brain networks, which are known as hubs14, whereas others have reported midline structures of the DMN19. Several works have identified primary sensorimotor and visual regions as connectome hubs19, yet others did not replicate these findings15. Subcortical regions, such as the thalamus and amygdala, have also been inconsistently reported as hubs18 and non-hubs19. Thus, the consistency and reproducibility of functional connectome hubs have been difficult to establish to date, which can be attributed to inadequate sample size and differences in imaging scanner, imaging protocol, data processing, and connectome analysis strategies. Here, we aimed to establish a harmonized meta-analysis model to identify robust functional connectome hubs in healthy young adults by combining multiple cohorts with uniform protocols for data quality assurance, image processing, and connectome analyses.Despite such importance, there is considerable inconsistency in anatomical locations of functional connectome hubs among existing studies. For example, components of the default-mode network (DMN) have been frequently reported as connectome hubs, yet the spatial pattern is highly variable across studies. In particular, several studies have shown highly connected hubs in the lateral parietal regions of the DMN20 and the cost-efficiency optimization21. Moreover, the functional connectomes can be regulated by genotypic variation both during rest22 and in cognitive tasks23, especially involving the DMN23 and frontoparietal network (FPN)23. Growing evidence also suggests spatial correspondence between transcriptomic profiles and connectome architectures26 (ref. 27 for review). Thus, we reasoned that the robust macroscopic connectome hubs could be associated with microscopic genetic signatures. Elucidating these genetic signatures will substantially benefit our understanding of how connectome hubs emerge in development, function in complex cognition, and are involved in disease.Once the robust connectome hubs are identified, we will further examine their genetic signatures. It has been well demonstrated that the connectome architecture of the human brain is inheritable, such as functional connectivity of the DMNTo address these issues, we provided, to the best of our knowledge, the first worldwide harmonized meta-connectomic analysis of functional brain hubs by pooling a large-sample resting-state functional MRI (rsfMRI) dataset of 5212 healthy young adults  across 61 independent cohorts. We identified highly consistent and reproducible functional connectome hubs in multiple heteromodal and unimodal regions, with the most robust findings occurring in several lateral parietal regions. These connectome hubs showed unique and heterogeneous connectivity profiles to provide support for both intra- and inter-network communications. To uncover the genetic signatures underlying these connectome hubs, we conducted machine learning approaches to distinguish connectome hubs from non-hubs using transcriptomic data from the Allen Human Brain Atlas (AHBA), explored their developmental evolutions using the BrainSpan Atlas, and assessed their neural relevance by contextualizing them relative to established neuroimaging patterns. We demonstrated that these robust connectome hubs were associated with a spatiotemporal transcriptomic pattern dominated by genes enriched for the neuropeptide signaling pathway, neurodevelopmental processes, and metabolic processes.7. For each cohort, we performed a general linear model on these normalized FCS maps to reduce age and sex effects. As a result, we obtained a mean FCS map and its corresponding variance map for each cohort that were used for subsequent meta-analyses.Prior to the meta-analysis, we constructed a voxelwise functional connectome matrix for each individual by computing the Pearson’s correlation coefficient between preprocessed rsfMRI time series of all pairs of gray matter voxels . Then, the functional connectivity strength (FCS) of each voxel was computed as the sum of connection weights between the given voxel and all the other voxels. This resultant FCS map was further normalized with respect to its mean and standard deviation across voxelsp < 0.001, cluster size > 200 mm3) higher than the global mean  using a voxelwise Z value map computed by dividing the FCS map by the SE map. To determine the statistical significances of these observed Z values, a nonparametric permutation test28 with 10,000 iterations was performed. Finally, we estimated voxelwise effect sizes using Cohen’s d metric computed by dividing the Z value map by the square root of the cohort number  were spatially distributed in multiple brain networks, including the DMN (27.5%), dorsal attention network (DAN) (16.5%), FPN (15.9%), ventral attention network (VAN) (15.6%), somatomotor network (SMN) (14.4%), and visual network (VIS) (9.9%)  Fig. . Using aI2 (heterogeneity score) exceeding 50% . For hub peaks, leaving one cohort out resulted in very few displacements  that was trained using only the top ier Fig. . Becauseask Fig.  and alsoask Fig. . By contask Fig. .Validation analyses showed that the XGBoost and SVM classifiers trained using surrogate hub identification maps with the spatial autocorrelations being corrected performed no better than the chance level  = 8.9, uncorrected p = 1.2 × 10−5, Supplementary Data FE = 5.7, uncorrected p < 10−6, Supplementary Data FE = 1.2), cellular developmental process (FE = 1.3), anatomical structure development (FE = 1.3), and neuron projection arborization (FE = 13.7)  enrichment analysis using GOrilla37 and confirmed the mostly enriched GO term of the neuropeptide signaling pathway  and aerobic glycolysis (indicated by the glycolytic index), but also have more blood supply   and autism spectrum disorder  but positively correlated with the Cohen’s d of cortical thickness atrophy in bipolar disorder  and schizophrenia   Fig. . This suUsing a worldwide harmonized meta-connectomic analysis of 5212 healthy young adults across 61 cohorts, we provided, to the best of our knowledge, the first description of highly consistent and reproducible functional connectome hubs in the resting human brain. Using transcriptomic data from the AHBA and BrainSpan Atlas, we reported that these robust connectome hubs have a spatiotemporally distinctive transcriptomic pattern in contrast to non-hub regions. These results advanced our knowledge of the robustness of macroscopic functional connectome hubs and their potential cellular and molecular substrates.19, which may arise from high heterogeneity in the included subjects, data acquisition, and analysis strategies across studies. To diminish these potential confounding factors, we employed stringent participant inclusion criteria that included only healthy young adults aged 18–36 years and adopted harmonized data preprocessing and connectome analysis protocols across cohorts. Nevertheless, the random-effects meta-analysis revealed high heterogeneity among cohorts in almost all brain areas, which implied that heterogeneity of imaging scanners and/or imaging protocols could be an important cause for inconsistent and less reproducible results across prior studies. Thus, our study was indispensable by conducting a harmonized random-effects meta-analysis model in which both intracohort variation  and intercohort heterogeneity were considered51. In addition, our validation results showed that the spatial distribution of functional connectome hubs was relatively stable when using more than 510 subjects and 35 cohorts, demonstrating that 5212 subjects from 61 cohorts were adequate to minimize the effects of both sampling errors and heterogeneity among cohorts. Considering only dozens of subjects in most prior studies19, the low statistical power attributed to inadequate subjects could be another cause for prior inconsistent and less reproducible hub localizations. Finally, we used harmonized image processing and connectome analysis protocols across cohorts, which avoided methodological variation and reduced potential methodological defects that have not been resolved in prior studies. See an extension discussion in Supplementary Note Extant reports have shown largely inconsistent and less reproducible hub localizations52, VAN 52, and FPN (left p9-46v and right IFSa)53. In addition, hub regions involved in the sensorimotor pathway 54 are also connected with the visual association cortex, acting as connectors between the VIS and the SMN, DAN, and VAN. Information flow along the primary visual, visual association, and higher-level sensorimotor cortices is undertaken by the four occipital hubs (Cluster II) left VMV1, right V4, and bilateral V3A that are all densely connected with the VIS and portions of the SMN, DAN, and VAN. This is supported by the report of their dense connections with both the visual system and SMN region the frontal eye field, DAN region the superior parietal cortex, and VAN region the parietal operculum and anterior insula55 and also aligns with the role of their homologous regions in the non-human primate cerebral cortex54. The remaining 10 hubs (Cluster III) are all located in canonical DMN regions56. One of them, the left 8Av hub, is robustly connected with both DMN and lateral prefrontal FPN regions, acting as a connector between the DMN and FPN. This can be supported by the recent finding of a control-default connector located in the posterior middle frontal gyrus32 and may also be a case of the hypothesis of parallel interdigitated subnetworks57 where the posterior middle frontal gyrus is connected with a subnetwork of the DMN and some regions of the FPN. This observation offers a crucial complementary interpretation to the conventional assumption that the DMN is anticorrelated with other networks56. Considering that communication between the DMN and other networks is of particular relevance to neuropsychiatric disorders58, such as autism spectrum disorders59, we speculated that the left 8Av hub may be a promising target region for therapeutic interventions.The present results demonstrated that the 35 highly consistent and reproducible connectome hubs show heterogeneous functional connectivity profiles, forming three clusters. Twenty-one hubs (Cluster I) are connected with extensive areas in the DAN, VAN, FPN, and SMN. Previous investigations indicated that they are core regions of the DAN 45, robust neuropeptide signaling pathways are indispensable for efficient synaptic signal transduction that sustains dense and flexible functional connections of hub regions. This is also supported by our observation of differences in neurotransmitter receptor and transporter density between hub and non-hub regions. In addition, hub regions have higher transcription levels for main neuronal metabolic pathways in contrast to non-hubs. This is reasonable because massive synaptic activities in hub regions demand high material and metabolic costs, which is in accordance with our observation of more blood supply and higher oxidative phosphorylation and aerobic glycolysis levels in hub regions. This is also consistent with prior observations of a tight coupling between FCS and blood supply49.We demonstrated that these robust brain hubs have a spatiotemporally distinctive transcriptomic pattern dominated by genes with the highest enrichment for the neuropeptide signaling pathway. Because neuropeptides are a main type of indirect neurotransmitter that is widely distributed in the human central nervous system44. Higher transcription levels for dendrite and synapse development in hub regions are necessary for the overproduction of synapses that will be selectively eliminated based on the demand of the environment and gradually stabilized before full maturation60, which has been proposed as the major mechanism of creating diverse neuronal connections beyond their genetic determination60. Lower transcription levels for axon development and myelination will prolong the myelination period in hub regions, which characterizes a delayed maturation phase61. Marked delay of anatomical maturation in human prefrontal and lateral parietal cortices has been frequently observed both in human development63 and in primate evolution61, which provides more opportunities for social learning to establish diverse neuronal circuits that contribute to our complex63 and species-specific61 cognitive capabilities. We also observed higher transcription levels for neuron migration in hub regions from mid-fetal period to early infancy. This is in agreement with the report of extensive migration of young neurons persisting for several months after birth in the human frontal cortex64. Meanwhile, the migration and final laminar positioning of postmitotic neurons are regulated by common transcription factors65, which suggests that a higher transcription level for neuron migration in hub regions facilitates the construction of more intricate interlaminar connectivity. These microscale divergences of key neurodevelopmental processes may result in a more intricate macroscale structural connectivity proflie in hub regions.We found that connectome hubs possess a spatiotemporally distinctive transcriptomic pattern of key neurodevelopmental processes in contrast to non-hubs. Specifically, connectome hubs have higher transcription levels for dendrite and synapse development and lower transcription levels for axon development and myelination during childhood, adolescence, and adulthood. These findings are compatible with previous observations of the prefrontal area having higher synapse density but lower myelination than primary somatosensory, auditory, and visual (V1/V2) cortices38. Thus, in addition to contributing to our complex cognitive capabilities, the spatiotemporal differences in transcriptomic pattern of neurodevelopment between hub and non-hub regions may also increase brain connectome’s susceptibility to neuropsychiatric disorders63, which means small disturbance in the magnitude or the timing of this transcriptomic pattern may have long-term consequences on brain anatomical topography or functional activation. This is in line with the result of several psychiatric disorders being the most significant disease associated with the top 150 key genes and is also supported by our observation of differences in susceptibility to cortical thickness atrophy in neuropsychiatric disorders between hub and non-hub regions. This implies that uncovering the intricate transcriptomic pattern, diverse neuronal circuits, anatomical topography, and functional activation of connectome hubs provide crucial and promising routes for understanding the pathophysiological mechanisms underlying neurodevelopmental disorders, such as autism spectrum disorders59 and schizophrenia63.Human neurodevelopment is an intricate and protracted process, during which the transcriptome of the human brain requires precise spatiotemporal regulation24, linear regression25, or partial least squares26. It has been argued that observations of transcriptome–connectome spatial association have a high false-positive rate through linear regression66 and linear correlation67 and may be largely shifted toward the first principal component axis of the dataset through partial least squares68. These investigations imply that prior transcriptome–connectome association results by linear mathematical operations may include high false-positive observations that are independent of connectome measurements, such as genes enriched for ion channels26. By contrast, high reproducibility across different machine learning models and across different GO enrichment analysis tools and convergent results from the AHBA and BrainSpan Atlas made it very unlikely that our findings were false-positive observations.Of note, we conducted transcriptome–connectome association analysis using machine learning approaches in which non-linear mathematical operations were implemented rather than linear operations, such as linear correlation69. Validation analysis demonstrated that hub distribution identified without global signal regression was more likely derived from physiological artifacts rather than by ongoing neuronal activity  hubs70. The effects of parcellation-based70 and surface-based71 analysis on hub localizations should be resolved in future studies. Third, the AHBA dataset only includes partial human genes, of which approximately half were excluded in data preprocessing34, which may have induced incomplete observations in our data-driven analysis. Finally, our transcriptomic signature results addressed only the association between connectome hubs and transcriptomic patterns and did not explore causation between them. Exploring more detailed mechanisms underlying this association is attractive and may be practicable for non-human primate brains in future studies.Some results of the present study should be interpreted cautiously because of methodological issues. First, we identified the robust connectome hubs using preprocessed rsfMRI data with global signal regression because of its great promise in minimizing physiological artifacts on functional connectomesN = 7202) from public data-sharing platforms and in-house cohorts, which consists of 73 cohorts from Asia, Europe, North America, and Australia. Data of each cohort were collected with participants’ written informed consent and with approval by the respective local institutional review boards.We collected a large-sample rsfMRI dataset  were excluded from the subsequent analyses. Then, all volumes were normalized to the 3-mm isotropic space of the Montreal Neurological Institute (MNI) using the EPI template provided by SPM12. The normalized volumes were spatially smoothed using a 6-mm full-width at half-maximum Gaussian kernel. After that, the time series of each voxel underwent the procedure of linear trend removal, nuisance signal regression , and temporal band-pass filtering (0.01–0.1 Hz). Finally, scrubbing was performed to minimize head motion effects73. Specifically, volumes with framewise displacement exceeding 0.5 mm and their adjacent volumes (1 back and 2 forward) were replaced with linearly interpolated data. We excluded participants with more than 25% interpolated volumes. Notably, slice-timing was not corrected in the Human Connectome Project cohort due to multiband acquisition74. For participants with more than one rsfMRI scan, we used only one of them. To reduce the potential effects of development and aging on our results, we restricted our analysis to healthy young adults aged 18 to 36 years. To ensure sufficient statistical power, twelve cohorts were discarded due to having fewer than 10 participants that passed quality controls. After these stringent quality controls, we included preprocessed rsfMRI data of 5212 healthy young adults  from 61 independent cohorts in the final analysis. The sample size and age ranges of each cohort were summarized in Fig. We first reviewed T1-weighted structural MRI data for all participants with the assistance of a neuroradiologist and a clinical neurologist to confirm no identifiable lesion or structural abnormality . All rsfMRI data for the remaining participants were preprocessed routinely using SPM12 v6470 and GRETNA29 and a subcortical network30. The cerebellum was not included due to largely incomplete coverage during rsfMRI scanning in most cohorts. Negative functional connections were excluded from our analysis due to neurobiologically ambiguous interpretations75. To further reduce the bias of signal noise and simultaneously avoid the effect of potential sharing signals between nearby voxels, both weak connections (Pearson’s r < 0.1) and connections terminating within 20 mm were set to zero76. We validated the threshold of weak connections using 0.05 and 0.2 . The gray matter mask was divided into seven large-scale cortical networksFor each cohort, we performed a general linear model on these normalized FCS maps to reduce age and sex effects. For each voxel, we constructed the general linear model as:FCSi, Agei, Sexi, and εi indicate the FCS, age, sex, and residual of the ith individual, respectively. MeanAge indicates the mean age of that cohort. β0 indicates the mean FCS of that cohort. The general linear model exported a mean FCS map and its corresponding variance map for each cohort.51 to address across-cohort heterogeneity of functional connectomes. A short summary of the random-effects meta-analysis was provided in the following section. The detailed computational procedures are described in the book51. This resulted in a consistent FCS pattern , we repeated the computation procedure of the random-effects meta-analysis for each voxel and extracted the maximum Z value of all voxels to construct a null distribution. A p value was assigned to each voxel by comparing the observed Z value to the null distribution. For a statistical significance level below 0.05, this p value closely tracks the Bonferroni threshold28.In line with a previous neuroimaging meta-analysis studyp value less than 0.001 and cluster size greater than 200 mm3 , we repeated the computation procedure of the random-effects meta-analysis for each voxel and extracted the maximum Z value of all voxels to construct a null distribution. Then, we assigned a p value to each voxel by comparing the observed Z value to the null distribution.We performed 10,000 one-sided nonparametric permutation testsp value less than 0.001 and cluster size greater than 200 mm3  and negative samples (non-hub samples) in the classifier training procedure to ensure that the optimal classifier was unbiased toward any type of sample. To balance the time complexity and the prediction accuracy, we trained the classifier with 300 randomly selected hub samples and 300 randomly selected non-hub samples and tested it with the remaining 82 hub samples and 476 non-hub samples , oxidative phosphorylation , and aerobic glycolysis (the glycolytic index) through one-sided Wilcoxon rank-sum test (Fig. The brain metabolism dataset provided by the positron emission tomography studyest Fig. .d value of cortical thickness atrophy in neuropsychiatric disorders was assigned to 68 cortical areas in a standard brain surface space50. We first resampled the unthresholded Cohen’s d map of connectome hub in Fig. 50 and computed the Cohen’s d value for each of the 68 cortical areas by averaging Cohen’s d value across vertices within each cortical area. Then, we computed Pearson’s correlation coefficient between the Cohen’s d value of connectome hub and the Cohen’s d value of cortical thickness atrophy across 68 cortical areas for each of the eight disorders (Fig. The Cohen’s ers Fig. . To reduZ values with their corresponding null distributions constructed by above mentioned 10,000 one-sided nonparametric permutation tests28. To determine the statistical significances of one-sided Wilcoxon rank-sum tests in Figs. 81 and repeated calculating rank-sum statistics using these surrogate hub identification maps to construct a null distribution. Then, p values of these rank-sum statistics were determined by comparing the observed values with their corresponding null distributions and were Bonferroni-corrected. Surrogate hub identification maps for Figs. d map in Fig. 81 and repeated calculating Pearson’s correlation coefficients using these surrogate Cohen’s d maps to construct a null distribution. Then, p values of these Pearson’s correlation coefficients were determined by comparing the observed values with their corresponding null distributions.We performed statistical analyses using MATLAB R2013a. The statistical significances of brain clusters in Figs. Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1-10Reporting Summary


Obesity is an increasingly recognized modifiable risk factor for Alzheimer’s disease (AD). Increased body mass index (BMI) is related to distinct changes in white matter (WM) fiber density and connectivity.We investigated whether sex differentially affects the relationship between BMI and WM structural connectivity.A cross-sectional sample of 231 cognitively normal participants were enrolled from the Knight Alzheimer Disease Research Center. Connectome analyses were done with diffusion data reconstructed using q-space diffeomorphic reconstruction to obtain the spin distribution function and tracts were selected using a deterministic fiber tracking algorithm.We identified an inverse relationship between higher BMI and lower connectivity in the associational fibers of the temporal lobe in overweight and obese men. Normal to overweight women showed a significant positive association between BMI and connectivity in a wide array of WM fibers, an association that reversed in obese and morbidly obese women. Interaction analyses revealed that with increasing BMI, women showed higher WM connectivity in the bilateral frontoparietal and parahippocampal parts of the cingulum, while men showed lower connectivity in right sided corticostriatal and corticopontine tracts. Subgroup analyses demonstrated comparable results in participants with and without positron emission tomography or cerebrospinal fluid evidence of brain amyloidosis, indicating that the relationship between BMI and structural connectivity in men and women is independent of AD biomarker status.BMI influences structural connectivity of WM differently in men and women across BMI categories and this relationship does not vary as a function of preclinical AD. Obesity is linked to microstructural white matter (WM) alterations . These eObesity is associated with neuroinflammation . High boWhile sexual dimorphisms in WM connectivity have been examined in prior work , there aWe therefore conducted a diffusion MRI correlational connectometry analysis in 231 healthy middle-age and older adults from the Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC). This study investigates: 1) whether biological sex differentially modifies the relationship between BMI and WM structural connectivity and how this relationship is affected in different BMI categories such as normal weight, overweight, obese and morbidly obese, 2) whether there is an interaction between biological sex and BMI in altering WM structural connectivity, and 3) how do the above relationships change in the context of preclinical AD as a modifier of WM structure in this population given the role of mid-life obesity in AD risk .APOE ɛ4) carrier status of the participants were entered separately as covariates in the models, as previous literature suggests a relationship between these variables and WM connectome in adults [2), normal weight (BMI: 18.5–24.9 kg/m2), overweight (BMI: 25–29.9 kg/m2), obese (BMI: 30–39.9 kg/m2), and morbidly obese (BMI≥40 kg/m2) categories [We selected 231 community dwelling individuals  from a larger cohort of participants enrolled in the ongoing longitudinal studies of memory and aging conducted at the Knight ADRC at Washington University School of Medicine in St. Louis. n adults . Particitegories , and then = 210). Among these, participants who had a positive amyloid PET uptake or, if not present, positive CSF AD biomarker, were considered as AD biomarker positive. Amyloid PET of CSF AD biomarker positivity were both determined based on established ADRC thresholds [biomarker negative. As cognitively normal individuals with positive AD biomarkers are characterized as having preclinical AD [Additionally, amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) AD biomarkers within 24 months of the dMRI scan were characterized for the majority of our sample  located at Washington University School of Medicine in Saint Louis. dMRI data were acquired through a 2D single-shot echo planar imaging (EPI) diffusion sequence, with TR = 14,500  ms, TE = 112 ms, maximal b-value = 1400 s/mmaccuracy . Preproc11C Pittsburgh Compound-B (PiB) or 18F-AV-45 (florbetapir). Details of acquisition and postprocessing for PiB and AV45 PET have been described elsewhere [Amyloid PET imaging was performed using either lsewhere . Particilsewhere .42) were measured with Elecsys® (Roche Diagnostics) assays [42 of > 0.0198 is highly concordant with established cut-off values for amyloid PET status and was used to define biomarker positive status [Twenty to thirty milliliters of cerebrospinal fluid was collected via lumbar puncture with a 22-gauge atraumatic spinal needle following overnight fasting. Samples were gently inverted to reduce possible gradient effects and then centrifuged at low speed and stored in 0.5 ml aliquots in polypropylene tubes at –84°C. The concentrations of CSF phosphorylated tau (pTau) and amyloid-β peptide 42 (Aβ) assays . A cut-oe status .Each dMRI scan was paired with the closest cognitive assessment with the maximum interval being 12 months. The mean interval between the dMRI and cognitive assessment was 84±54 days. The CDR and Mini-Mental State Exam (MMSE) were performed at the same cognitive assessment . The parConnectome analyses were performed using the DSI Studio Software . Diffusitracking the correlation paradigm, which is fundamentally different from the conventional DTI analysis paradigm of finding the correlation between variables of interest and tract parameters. Connectometry uses a nonparametric permutation test to first identify voxels that have strong association with the study variable and tracks along axonal fiber directions to identify the consecutive voxels that show a continuous strong positive or negative association. We performed correlational tractography between QA and BMI and between QA and BMI interaction with sex. In brief, a non-parametric approach was implemented through the Spearman rank-based correlation to consider the non-linear effect between BMI or BMI*Sex and QA. The model consisted of either a simple Spearman’s correlation  or a partial Spearman’s correlation considering age, cognitive status (MMSE score), or APOE ɛ4 allele carrier status as covariates in the model. Covariates were chosen based on literature demonstrating changes in WM connectome with age and the association of WM connectome with cognitive performance and APOE ɛ4 carrier status [We utilized a semi-automated atlas-based deterministic tracking algorithm to obtain correlational tractography based on Spearman rank-based correlation . Correlar status . Given tr status .p-value as it has a much higher true positive reporting rate and is less sensitive to sample size. The QA values were normalized prior to the analyses, and tracts were filtered by topology-informed pruning with 4 iterations [s between 0.1 and 0.29 is considered to represent a small association, while rs represent a medium and coefficients above 0.5 are considered to demonstrate a large association or relationship.Different T-score thresholds including 2, 2.5, and 3 were adopted. Models with T-score threshold of 2.5 yielded the strongest correlation while converging to reliably consistent results. As a result, a T-score threshold of 2.5 and a length threshold of 20 mm were assigned with a FDR threshold of 0.05 used to select tracks through a deterministic fiber tracking algorithm . FDR is erations . To estierations . ResultsDe-identified participant data including clinical and cognitive assessment, CSF biomarkers and dMRI images are available upon request through the Knight ADRC Leadership Committee (https://knightadrc.wustl.edu/research/resourcerequest.htm). The statistical and image analyses were all done through the DSI Studio (http://dsi-studio.labsolver.org) that is publicly available.APOE ɛ4 carrier status, self-reported race, systolic and diastolic blood pressure and MMSE score , overweight (BMI: 25–29.9 kg/m2), obese and morbidly obese (BMI≥30 kg/m2) categories are presented in We also investigated the association between BMI and white matter connectome in men and women from different BMI subcategories separately. Results of the correlational tractography in normal weight (BMI: 18.5–24.9 kg/mn = 210)  . This suWe performed correlational tractography separately in biomarker positive and negative men and women (Table 4). Biomarker positive and biomarker negative participants both showed a negative relationship between BMI and connectivity in the bilateral corticopontine tracts, bilateral ILF, bilateral frontoparietal cingulum, and the right dentatorubrothalamic and corticospinal tracts, in men (FDR < 0.01) (Table 4). Correlational tractography in biomarker positive and biomarker negative women revealed a positive relationship between BMI and connectivity in the left corticospinal and the right dentatorubrothalamic tracts . The pattern of BMI relationship with WM connectome in the biomarker positive and negative subgroups was similar to that of the entire study sample with a negative relationship between BMI and connectivity in men and a positive relationship between WM connectivity and BMI in women (Table 4). There was no statistically significant difference in WM connectivity between biomarker negative and positive participants in neither men nor women. Predictably, an interaction term between CSF biomarker status and BMI did not show any significant relationship with WM connectivity in neither men nor women.overweight and obese men and decreased structural connectivity in the associational fibers of the temporal lobe; namely the IFOF and ILF, 2) a statistically significant relationship between BMI in normal to overweight women and increased WM connectivity in the bilateral anterior thalamic radiations and the corticofugal motor pathways on the right, 3) an inverse relationship between BMI and WM connectome in obese and morbidly obese women in the bilateral IFOF, bilateral ILF and the corticofugal motor pathways on the right, and finally 5) a similar pattern in the association of WM connectivity in men and women with preclinical AD compared to their biomarker negative counterparts. Our findings collectively suggest that WM connectome is affected by a complex interplay of tissue adiposity and sex. While overweight, obese and morbidly obese men demonstrate detrimental effects of higher BMI in WM connectivity, these effect are not visible in women until they are obese or morbidly obese. Higher tissue adiposity conferred a protective effect on WM connectome in normal to overweight women and potentially due to the neuroprotective effects of estrogen on WM, as discussed later [Our analyses revealed distinct relationship patterns between BMI and WM connectivity in men and women. We demonstrated: 1) a statistically significant relationship between higher BMI in ed later .Mid-life overweight and obesity are well-demonstrated risk factors of late-life dementia . This efDespite its significant effects on both BMI  and cognWhile we did not collect data on hormonal therapy status of the postmenopausal women participants of our cohort, it is important to briefly address potential mechanisms by which hormone status in women can alter the obesity relationship to WM. Menopause is associated with reduced insulin sensitivity and a redistribution of visceral adipose tissue in favor of upper body and abdominal adiposity both of which are associated with reduced white and grey matter integrity . InverseSex difference in WM microstructure can be traced back to early childhood when boys and girls demonstrate tract-specific differences in WM development as early as two years of age . PubertyAs demonstrated in Our findings regarding the influence of BMI on connectivity in the IFOF differed significantly by sex. Where men demonstrated a significant negative association between connectivity in the right IFOF and BMI, women showed a significant positive influence that appeared after correction for age. Obese adolescent boys, but not girls, have shown to have increased WM integrity in the right IFOF demonstrated through higher along tracts FA and lower MD . As highIn contrast to the right IFOF, BMI had a significant negative relationship with left IFOF connectivity in both men and women. Decreased WM integrity in the left IFOF is seen in overweight/obese adolescent boys and in obese compared to normal weight young women . ImportaThe corticofugal motor pathways; namely the corticopontine tracts were also among fibers where connectivity negatively related to BMI in men but positively in women. A review of literature reveals a dimorphism among adolescent boys and girls in the association of lifestyle-related factors and microstructure of the corticospinal tracts. In adolescent boys, aerobic fitness is associated with decreased FA in the left corticospinal tract  and obesThe tapetum of the corpus callosum and the frontoparietal and parahippocampal divisions of the cingulum were another set of fibers with inverse relations to connectivity and BMI in men and positive association of connectivity with BMI in women. The tapetum of the corpus callosum connects the right and left temporal lobes and the parahippocampal and frontoparietal parts of the cingulum connect the anterior and posterior cingulate cortices to the medial temporal lobe . ComponeFinally, our analyses indicated a significant positive relationship between connectivity in bilateral SLF and BMI in women. This observation is in line with earlier reports demonstrating increasing axial diffusivity in the SLF with increased BMI in adult participants , but oppdiffusivity that is used by DTI, as the main function of interest. The QSDR outputs the SDF, which is an orientation distribution function of diffusing spins. SDF is then sampled at each peak orientation to yield a QA value for each fiber orientation [density that simplifies the separation of restricted and non-restricted diffusion and increases the performance in low signal-to-noise ratio conditions compared to DTI.The diffusion MRI connectometry analyses used in this research come with inherent strengths compared to conventional diffusion MRI analytic models, namely the diffusion tensor imaging (DTI). The QSDR is a generalization of the Generalized Q-sampling Imaging (GQI) model. GQI is a model-free diffusion reconstruction method that adopts the density of water diffusion in different directions, rather than entation . Unlike entation . As bothentation . FinallyThe heterogeneity of the study population in terms of their preclinical AD status, was a major limitation of this study. This was addressed by determining biomarker positivity through CSF and amyloid PET and subgroup analyses based on biomarker status. Nonetheless, the 24-month allowed interval between CSF or PET amyloid measurement might result in misclassification of participant in the biomarker positive or negative groups. Similarly, cognitive scores including MMSE and CDR were measured during a clinical visit within 12 months of the diffusion MR study and not on the same day as the diffusion MR studies. To address this, the absolute time difference between the dates of clinical assessment and dMRI acquisition was added as a covariate to all the models that included the MMSE score. Finally, we used BMI as a simple and accessible measurement of total body adiposity. However, BMI is not sufficient for optimal assessment of metabolic risk factors that are associated with obesity and their potential effect on brain health . TherefoIn summary, our results support the hypothesis that BMI affects WM structural connectivity differently in men and women, and that this relationship is not altered in the setting of preclinical AD. When viewed in the context of existing literature, our findings imply that sex differences in the reward and emotional arousal networks  give ris


Many viruses persisted for extended periods, as evidenced by ≥25% of IAVs remaining infectious in replicate samples for each treatment type through three sampling time points (144–155 days post-sample collection) and two viruses remaining viable in a single replicate sample each when tested upon collection at a fourth time point (361–377 days post-sample collection). The estimated probability of persistence of infectious IAVs in all five water types was estimated to be between 0.25 and 0.75 during days 50–200 post-sample collection as inferred through Kaplan-Meier survival analysis. Our results provide evidence that IAVs may remain infectious for extended periods, up to or even exceeding one year, when maintained in surface waters under ambient temperatures. Therefore, wetlands may represent an important medium in which infectious IAVs may reside outside of a biotic reservoir.Influenza A viruses (IAVs) deposited by wild birds into the environment may lead to sporadic mortality events and economically costly outbreaks among domestic birds. There is a paucity of information, however, regarding the persistence of infectious IAVs within the environment following deposition. In this investigation, we assessed the persistence of 12 IAVs that were present in cloacal and/or oropharyngeal swabs of naturally infected ducks. Infectivity of these IAVs was monitored over approximately one year with each virus tested in five water types: (1) distilled water held in the lab at 4 °C and (2–5) filtered surface water from each of four Alaska sites and maintained in the field at ambient temperature. By evaluating infectivity of IAVs   Though Until recently, information on the duration of IAV infectivity in water has been largely based upon temperature, pH, and salinity-controlled experiments conducted in laboratory settings using laboratory propagated virus . More reGiven evidence for the influence of physical and chemical factors on the persistence of infectious IAVs within water and the recent development of field-based approaches to assess the duration of viral infectivity, we aimed to evaluate viral persistence within waterfowl habitats exhibiting variable physical and chemical properties at a local scale. We focused our field efforts at Izembek National Wildlife Refuge (NWR), Alaska, a location globally recognized for its importance as wetland habitat to hundreds of thousands of migratory waterfowl , a well-2.2.1.To assess the duration that avian-origin IAVs remain viable in wetland surface waters exhibiting a range of physical and chemical properties when maintained under ambient temperatures, we set up an experiment at four sites within Izembek NWR, Alaska –2: Blueb2.2.Paired cloacal and oropharyngeal (CL/OP) swabs were collected from 206 hunter-harvested wild ducks. Paired swab samples from a single duck were immersed into 4 ml chilled, distilled water contained within an 8-ml screwcap tube. Contents were vortexed, and 0.2 ml were then aliquoted into each of 20 cryovials: four 4-ml cryovials containing 1.8 ml of 0.22-micron filtered surface water from each of the four field sites and four cryovials containing 1.8 ml of distilled water. Negative controls were incorporated by aliquoting 0.2 ml of distilled water into additional cryovials containing 1.8 ml of 0.22-micron filtered surface water from each of four sites or distilled water. One replicate cryovial per paired CL/OP swab sample and water type and one set of negative controls were sent to the lab upon collection  for IAV screening by real-time reverse transcriptase polymerase chain reaction (rRT-PCR) where a cycle threshold (Ct) value < 45 was considered ‘positive’  and via 2.3.At three subsequent time points during the ensuing year, submersed replicate vials and controls were retrieved from the field and sent to the lab chilled on ice packs (or recovered from the refrigerator for lab-held replicates in distilled water) for IAV testing via rRT-PCR and VI. Sample collection periods for time point two (T2), time point three (T3) and time point four (T4) were 4–12 December 2019, 20–27 February 2020, and 10–16 September 2020 (for replicates held in the field) or 8–16 October 2020 (for replicates held in the lab), respectively. Only replicate samples corresponding to those previously identified as VI positive through initial screening (of T1 replicates) and negative controls were tested. The physical and chemical attributes of unfiltered environmental surface waters from field sites were also measured in situ and through laboratory analyses at T2 and T3 as previously described for T0 ; however, we were unable to collect measures for surface waters of field sites at T4 due to logistical constraints.To confirm results of VI and to identify any potential artifacts resulting from sampling handling or processing procedures, we genomically characterized viral isolates and assessed genetic similarity among corresponding replicate samples. To do so, RNA was first extracted from amnioallantoic egg fluids for all putative VI-positive samples using the Qiagen viral RNA mini kit . Complementary DNA was synthesized and subsequently amplified, visualized, and purified per previously reported methods . Genomic2.4.Genomes of IAVs obtained from all T1 replicates derived from the same paired CL/OP swab sample were compared, and only those samples sharing >99% identity among all replicates (minimum of two) were used to assess persistence through time . Genomes of IAVs recovered from VI-positive T2, T3, and T4 replicate samples that shared >99% nucleotide identity at all gene segments with each other and corresponding viruses recovered from the T1 VI-positive distilled water replicate samples were inferred to remain infectious at the time point at which samples were retrieved. In the case of isolates representing mixed infections, we considered T2–T4 replicates to remain infectious if nucleotide sequences for either or both of two alleles for a given gene segment shared >99% nucleotide identify with corresponding gene segment sequences generated for the T1 distilled water isolate. T2–T4 replicates yielding IAV isolates with genomes sharing <99% nucleotide similarity at any gene segment as compared to the T1 distilled water isolate were considered negative to avoid deriving inference from field or laboratory artifacts as described above.To assess potential differences in viral persistence among replicates held in the field at four wetland sites and in the laboratory, we applied a Kaplan-Meier survival analysis to IAVs assessed for viral infectivity through time. To estimate the survival interval for viruses maintained under laboratory and field conditions, we considered T1 to be our start date which varied among samples. We considered the survival endpoint for any given replicate to be the mean date between the last time point from which we recovered an infectious IAV and the next subsequent time point at which the corresponding replicate was collected and tested negative . Survival curves and confidence intervals were calculated using the survival package  in R R .All data supporting conclusions in this product have been made publicly available in an associated data release  and via 3.3.1.From the initial (T1) screening of 206 paired CL/OP swabs from ducks aliquoted into distilled water, we identified IAV RNA in 58 samples (28.2%) via rRT-PCR and infectious IAV in 15 samples (7.3%) through VI. Through the testing of the T1paired swab samples aliquoted in filtered surface water from each of four Alaska study sites that corresponded to the 15 VI positive samples, and subsequent genomic characterization of resultant isolates, we identified 12 samples that met our criteria for assessing the duration of viral infectivity –S113. Th3.2.Through the testing of T2, T3, and T4 replicate samples for each of five treatments (distilled water held in the lab and filtered surface water from each of four Alaska study sites and held in the field), we observed successive declines in infectivity through time in the number of replicates testing VI-positive for viable IAVs per treatment with the single exception of T3 replicates held within, and containing surface waters from, Rescue Lake . Six T3 3.3.Our Kaplan-Meier survival analysis provided evidence for decreasing probability of infectivity through time for IAVs maintained under five different treatments . Estimat3.4.Water temperatures at four Izembek NWR field sites within which replicate samples were held were generally cool and consistent among sites with mean daily temperatures ranging between 0.0 and 18.7 °C . The ove4.In this investigation, we found evidence that IAVs from naturally infected ducks may remain infectious for extended periods of up to approximately one year, and potentially longer, when maintained in filtered surface water under ambient temperatures in southwestern Alaska wetlands at Izembek NWR or in temperature controlled distilled water in the laboratory. None of our negative controls containing filtered water from field sites inoculated with distilled water were identified as IAV-positive via rRT-PCR or VI, providing evidence that surface water used in this investigation was IAV-negative. Therefore, we have confidence that inference on the duration of infectivity was derived from IAVs present in CL/OP swabs from ducks. This study also provides field data that IAVs may commonly remain infectious for periods of months after deposition when maintained in water with cool temperature, near-neutral pH, and exhibiting relatively low to moderate specific conductivity, corroborating results reported for previous laboratory-based investigations . As suchThe finding that one IAV, maintained in filtered surface water from Bluebill Lake and held under ambient temperatures at this field site overwinter, remained infectious after approximately one full year extends the maximum duration for which viral infectivity has been confirmed through field experimentation by approximately five months . This reThough we did not estimate viral titers for duck swabs in filtered surface waters and distilled water at T1 in our experiment, which likely varied among samples and influenced the duration of infectivity, the finding that >25% of IAVs present on swabs collected from naturally infected ducks remained infectious in each water type under ambient temperature conditions for >144 days, or the equivalent of nearly five months, suggests that a considerable proportion of wild bird origin IAVs have the capacity to persist in diverse wetland surface waters for long durations, and potentially over winter, at high latitude locations. We recognize that viral strain, viral titer, water chemistry, and numerous other factors likely influenced temporal viral viability in our study. Solar ultraviolet radiation and biotic components of surface water are other factors that likely affect the viability of IAVs, though we attempted to control for these influences in our investigation. That is, steel perforated drums were sealed on the ends to minimize the entry of ambient light and filtering of surface waters was intended to minimize algae, bacteria, biofilms, invertebrates, and other biologics that could have inhibited, or in some cases promoted, the duration of viral infectivity.In this study, we attempted to incorporate a diversity of field sites and temperature regimes to provide inference on variability of viral persistence in surface waters with diverse chemical properties at a local scale. Surface water from three of our sites consistently shared similar physical and chemical properties  while only one site showed evidence for marked differences in chemical attributes (Proxy Pond), likely a function of tidal influence to this latter site. As such, we acknowledge that the water in which IAVs were maintained in this study may have represented a relatively narrow diversity of physical and chemical properties. We also recognize that our measures of surface waters at field sites do not necessarily reflect the same physical and chemical attributes of sample replicates  physically isolated from the environment throughout our experiment. Thus, we were unable to draw any rigorous inference from this study regarding how variability of physical and chemical properties of surface water among field sites influenced the duration of viral infectivity.Additional evaluations incorporating ecologically relevant context are necessary to better understand the viability of IAVs in globally diverse wetlands. Such evaluations are particularly important for high consequence IAVs such as highly pathogenic clade 2.3.4.4 Goose/Guangdong lineage H5 viruses. By better understanding the persistence of IAVs in diverse environmental surface waters, agencies managing wild water birds and their aquatic habitats may be able to better mitigate damages from outbreaks of highly pathogenic avian influenza involving wild birds through the development of science-based management actions. For example, agencies could explore: (i) limiting access to potentially virally contaminated wetlands for a defined period following outbreak events to avoid/reduce spread via fomites; (ii) regulating the disinfection of boats, hunting/fishing gear, and/or equipment following use in potentially virally contaminated wetlands for a defined period following outbreak events; (iii) instituting or increasing surveillance effort for high consequence IAVs in wild birds or wetlands affected by outbreaks for a defined period following detection events; and (iv) managing water levels or altering the pH/temperature of small ponds affected by outbreak events to facilitate more rapid viral deactivation and/or to mitigate further viral dissemination via water. Ideally, the potential development and implementation of management activities aimed at mitigating viral dissemination via water would incorporate ecologically relevant information on the duration of IAV infectivity as well as empirical evaluation of how infectivity may be altered or mitigated for through science-based actions.5.Through a combination of laboratory and field-based experimental approaches, we assessed the persistence of 12 IAVs obtained from the cloaca and/or oropharynx of naturally infected ducks in filtered surface water over approximately one year. Our results provide evidence that most IAVs remained viable for extended periods that may exceed one year when maintained in cool water, with near-neutral pH, and exhibiting relatively low to moderate salinity/specific conductivity. Therefore, wetlands exhibiting these conditions may represent an important medium in which infectious IAVs may reside outside of a biotic reservoir.Supp Figure S1Supp FiguresSupp Tables


Bile acids are critical for the digestion and absorption of lipids and fat-soluble vitamins; however, evidence continues to emerge supporting additional roles for bile acids as signaling molecules. After they are synthesized from cholesterol in the liver, primary bile acids are modified into secondary bile acids by gut flora contributing to a diverse pool and making the composition of bile acids highly sensitive to alterations in gut microbiota. Disturbances in bile acid homeostasis have been observed in patients with Inflammatory Bowel Diseases (IBD). In fact, a decrease in secondary bile acids was shown to occur because of IBD-associated dysbiosis. Further, the increase in luminal bile acids due to malabsorption in Crohn’s ileitis and ileal resection has been implicated in the induction of diarrhea and the exacerbation of inflammation. A causal link between bile acid signaling and intestinal inflammation has been recently suggested. With respect to potential mechanisms related to bile acids and IBD, several studies have provided strong evidence for direct effects of bile acids on intestinal permeability in porcine and rodent models as well as in humans. Interestingly, different bile acids were shown to exert distinct effects on the inflammatory response and intestinal permeability that require careful consideration. Such findings revealed a potential effect for changes in the relative abundance of different bile acids on the induction of inflammation by bile acids and the development of IBD. This review summarizes current knowledge about the roles for bile acids as inflammatory mediators and modulators of intestinal permeability mainly in the context of inflammatory bowel diseases. Bile acids are synthesized in the liver from cholesterol and secreted into the intestine where they serve to emulsify and facilitate the absorption of dietary lipids. Approximately 5% of the bile acid pool is eliminated in the stool and serves as a major pathway for eliminating cholesterol from the body . Most biThe bile acid pool is highly conserved and is composed of different types of bile acids, each having a specific affinity to certain bile acid receptors. Interestingly, secondary bile acids are generated in the intestine and therefore the gut microbiota is crucial for expanding the metabolic profile of the bile acid pool . The abuPetromyzon marrinus) where bile acid synthesis occurs in the liver and intestine  plays a key role in bile acid homeostasis by serving as a negative regulator of bile acid synthesis. Following active absorption in the ileum, bile acids activate the intestinal farnesoid X receptor (FXR), leading to the induction of FGF19 expression. FGF19 is then secreted into the portal blood stream and eventually suppresses CYP7A1 and bile acid synthesis in the liver . InteresWhile bile acids are preserved in the enterohepatic circulation, a small percentage enter the systemic circulation where they modulate the function of different organ systems, including the central nervous system (CNS) . Indeed,via CYP2c70  before circulating back to the liver  and then exit the enterocytes by the organic solute transporters OSTα and OSTβ.Both primary and secondary bile acids are actively reabsorbed in the distal ileum he liver . ASBT fuThe hepatic secretion of bile acids is controlled by the ATP-binding cassette transporters bile salt export pump (BSEP) and multidrug resistance-associated protein (MRP2). While humans mainly use BSEP to efflux bile acids into the bile, mice use both BSEP and MRP2 . Bile acbai) operon are involved in 7α -dehydroxylation of bile acids (baiG gene) is responsible for the entry of primary bile acids into the bacterium, and the rate limiting step of 7α-dehydroxylation (baiE). Gut bacteria possess several other enzymes, such as the bacterial hydroxysteroid dehydrogenases (HSDs): α-HSD and β-HSD  has been discovered . Unlike fibrosis . HoweverInflammatory bowel diseases (IBD) are multifactorial disorders of chronic intestinal inflammation consisting of two subtypes, Ulcerative Colitis (UC) and Crohn’s Disease (CD) . UlceratBile acids are known to activate different receptors that were recently shown to affect immune responses as they relate to IBD Table 1.FXR is expressed in cells of myeloid lineage including monocytes, macrophages, dendritic cells (DCs), and natural killer T-cells (NKTs) with different effects upon activation . FXR sigThese findings have been corroborated in various models of intestinal inflammation. A previous study utilized DSS and TNBS induced colitis in wild type and mice lacking FXR and showed that mice were treated with FXR agonist INT-747 exhibited decreased severity of colitis . This stG-protein bile acid receptor 1 (GPBAR1), also known as transmembrane G-protein-coupled receptor 5 (TGR5) is broadly expressed in various tissues and is also expressed in monocytes, macrophages, dendritic cells (DCs), and natural killer T-cells (NKTs) . TGR5 acOne recent study has shown that administration of TGR5 agonists during inflammatory stress protected against inflammasome activation. Treatment with Genistein, a compound known to protect against DSS colitis, increased intracellular cAMP levels in LPS treated macrophage cell lines (THP and U937 cells) . Furtherin vitro studies where they used these antagonists in the presence of LPS and found that blocking S1PR2 and ROCK1 prevented increases in CD86, MCP-1, TNF-α, and iNOS mRNA expression in primary mouse macrophages providing further evidence that S1PR2 signaling in macrophages leads to a pro-inflammatory phenotype (Bile acids are known to activate the sphingosine 1 phosphate receptor 2 (S1PR2). Many studies indeed, have shown the roles of S1PR2 in the modulation of immune responses. In this regard, Wang X et al. examined the effects of S1PR2 activation through LPS in primary murine macrophages . S1PR2 whenotype .Additionally studies have shown that activation of S1PR2 results in a pro-inflammatory M1-like phenotype in human macrophages . Their din vitro prevented an increase in the mRNA expression of NLRP3, pro-Il-1β, pro-IL-18, as well as IL-1β and IL-18 secretion. This was further supported by additional work by Hou L. et al  administration of JTE-013, an S1PR2 antagonist, reduced neutrophil chemotaxis to the liver as measured through Lys6G mRNA expression and flow cytometry. Further work by Zhao X. et al. also found neutrophils can form neutrophil extracellular traps (NETs) in response to S1PR2 activation , and myeloperoxidase (MPO). Furthermore, they applied S1P treatment in the presence of S1PR2 antagonist JTE-013 and found that the formation of NETs was blunted. In vivo, they administered S1PR2 siRNA in MCDHF (methionine and choline deficient high fat)-fed mice and found that blocking S1PR2 led to decreased levels of MPO-DNA complexes in the serum of these mice along with decreased protein expression of Cit-H3 in those livers, providing evidence for decreased neutrophil activation that was accompanied by decreased severity of liver injury. It was also found that S1PR2 was responsible for preventing spontaneous neutrophil apoptosis by administering S1PR2 antagonist JTE-013 and measuring the proportion of Annexin V positive cells  isolated from WT and S1PR2 KO mice both with and without acute DSS colitis . Co-cultammation , 64.Pregnane X receptor (PXR) has also been shown to activated by bile acids and the roles of this receptor in altering immune responses was investigated. Hudson et al., studied the effect of PXR activation in LPS-primed macrophages by treating both murine peritoneal macrophages and THP-1 derived macrophages . Both moThe Vitamin D Receptor (VDR) is not only highly expressed in the intestine but also in immune cells. Bile acids were shown to activate VDR, and this receptor is highly expressed in monocytes, macrophages, dendritic cells, and T cells. VDR activation in monocytes and macrophages generally results in anti-inflammatory effects with decreases in IL-1, IL-6, IL-8, IL-12, and TNF-α , 37. DC via VDR siRNA silencing. Furthermore, VitD3 mediated VDR signaling reduced the severity of DSS colitis and found that it increased the ratio of M2 to M1 macrophages as well as inhibiting the differentiation of CD4+ T-cells into Th1 and Th17 T-helper cell subtypes. Wang et al. has also shown that VDR signaling protected from DSS colitis, providing additional evidence for VDR in immune signaling by shifting macrophages towards the M2 phenotype. He L., et al., utilized a TNBS model of colitis and found that mice lacking VDR in intestinal epithelial cells and specifically in colonic epithelial cells exhibited increased severity of colitis with increased Th1 and Th17 responses, and increased epithelial cell apoptosis with impaired gut permeability . In innate lymphoid cells (ILCs), RORyt activation leads to increased differentiation and function of ILC3 subtypes, which play an important role in mucosal homeostasis . In T-ceA study with CD subjects showed that BI119, an RORyt antagonist inhibited the expression of Th17 genes in PBMCs challenged with bacterial antigens while simultaneously favoring expression of Treg genes . FurtherSeveral studies have extensively reported on alterations in bile acid signaling and bile acid levels in IBD. These studies are summarized in Another key aspect of bile acid homeostasis is the diversity of the bile aicd pool which is heavily influenced by bacterial transformation. Das P. et al. performed shotgun metagenomics to study bile salt transformation genes on the phyla level in the gut microbiota of healthy subjects and those with IBD . SubsequAnother study examined bile acid metabolism directly related to the gut microbiota by applying pure bile acid solutions to stool homogenates followed by direct measurement of chemically modified bile acids. The microbiota of healthy subjects was able to perform deconjugation, transformation, and desulphation on bile acids, whereas those capabilities were diminished in the IBD samples. These findings demonstrate how IBD induced gut microbial dysbiosis directly affects bile acid composition .RutgeertAnother important area of study has been measuring changes in metabolism of bile acids in IBD. Tougaard L. et al., examined the turnover rate of orally administered [14]-C labeled TC by measuring fecal excretion of CA, CDCA, DCA, and LCA in order to study bile acid metabolism in CD subjects with terminal ileal involvement . There wFurthermore, most patients with IBD are on medical treatment, a variable that is often confounding, but Roda G. et al., specifically looked at serum bile acid levels in IBD subjects who were treated with anti-TNF agents . Based oThere are additional variables which need to be considered in the study of bile acid homeostasis disruptions in IBD such as age. Jacobs J.P. et al., recruited families with pediatric IBD cases to study gut microbial structure and associated metabolic changes . The bilAs previously mentioned, a key aspect in bile acid homeostasis involves the conjugation of bile acids and several changes in conjugation have been reported in IBD. Gnewuch C. et al. found decreases in total serum unconjugated bile acid levels in UC . Those wSeveral studies have measured the levels of unconjugated bile acids in the serum of subjects with IBD under various states Table 2.In order to explore why patients with IBD typically have less PXR and FXR activity, Wilson A. et al., examined their changes in serum bile acid composition . They foIn a study of pediatric IBD, Ejderhamm J. et al. found that subjects with active UC exhibited significantly higher levels of CA and CDCA in their serum, four hours after food consumption when compared to healthy, age-matched subjects . These fOverall, these studies demonstrate how changes in bile acid during IBD are context specific. While conducting such studies would be challenging, further clinical investigations with larger sample sizes and granular stratifications based upon age, severity of disease, surgical history, and intestinal region affected, are warranted to allow for better understanding of how unconjugated bile acids specifically are being altered in both UC and CD.While there are a few studies looking at serum levels of unconjugated bile acids in IBD, there are several more doing so in the feces. Yang, Z.H., et al. found an increase in fecal CA with decreases in DCA, LCA, and 12-ketoLCA, in UC subjects compared to healthy controls, while also reporting trends towards increases in CDCA . AdditioAn understudied area in the measurement of fecal bile acids involves colon fluid. Vertzoni M. et al. collected colon fluid endoscopically in UC subjects with UC in relapse and in remissions and analyzed the composition of the fluid . There wJansson et al., performed non-targeted metabolic profiling in identical twin pairs including healthy subjects and subjects with CD and in the case of ileal CD, found increases in fecal 3α, 7α, and 12α-trihydroxy-5β -cholanate . Fiasse Studies by Das P. et al. found that subjects with IBD had reduced levels of BSBGs and proceeded to examine fecal bile acid compositions in these subjects and found that CA was increased while LCA was decreased in IBD subjects (encompassing both UC and CD) . EjderhaA less investigated compartment for the measurement of bile acids in IBD is in the bile itself, due to the practical challenges of more invasive techniques needed for samples. Due to procedural challenges, these studies are not as common and are less current, but they offer an important insight, nevertheless. Many of these studies were performed by Dr. Rutgeerts and most were performed in subjects with CD.In one study by Rutgeerts, studying cholic acid metabolism it was found that the metabolism of CA and CDCA was significantly increased in subjects with ileal CD when measured directly from the bile, and to those with both ileal and colonic involvement when compared to healthy subjects .Nishida, T. et al., orally administered deuterated CDCA in subjects with CD and healthy volunteers . Using dRutgeerts P. et al. examined duodenal bile in subjects with CD localized to the colon and found significantly decreased concentrations of DCA in subjects with CD compared to healthy controls . AnotherLapidus A. et al. found that bile acid composition in the duodenal bile of subjects with CD exhibited a significant decrease in the abundance of DCA and UDCA . In anotThese studies highlight an exciting avenue for further investigation in pre-clinical models where the invasiveness of sampling bile does not pose the same concerns it does in humans even if it poses additional technical challenges. Few physiological studies have explored the changes in bile acid composition specifically in the bile in models of IBD. Such studies could provide important mechanistic insight into these clinical observations that have already been made.Overall, there are few studies examining the levels of taurine conjugated bile acids in the serum of IBD cohorts. Gnewuch C. et al. (2009) found a decrease in serum total bile acid tauroconjugates in a CD cohort, along with a general decrease in total bile acids . They alThere are also few studies looking at fecal levels of taurine conjugated bile acids in IBD. Yang, Z.H., et al. found an increase in fecal TCA, but a decrease in TCDCA and TLCA in UC subjects compared to healthy controls . FurtherThere are also limited studies on serum glycine conjugated bile acids in IBD. Gnewuch C. et al. (2009) found a decrease in serum total bile acid glycoconjugates in their CD cohort . In UC sIn the feces, Yang, Z.H., et al. found an increase and decrease in GCDCA and GLCA respectively in UC subjects compared to healthy controls . FurtherAnother key variable to consider when examining alterations in bile acids during IBD is the difference in abundance between primary and secondary bile acids because of the gut microbial dysbiosis that is known to occur in IBD. Yang, Z.H., studied the gut microbial profiles in patients with UC and fecal bile acid levels . BrieflyKruis W. et al. found that the daily fecal bile acid excretion rate was increased in subjects with CD and decreased in UC compared to healthy controls . CD and Duboc, et al., studied the effects of IBD induced gut microbial dysbiosis on bile acid metabolism by measuring the levels of bile acids in both feces and serum in healthy subjects, active IBD, and IBD in remission . There win vivo but not captured with less complex in vitro models. There have been several studies examining the effects of individual unconjugated bile acids on intestinal epithelial cell TEER, apoptotic signaling, and cytokine secretion.Most studies of bile acids and intestinal epithelial cells utilized cell lines which lack other cell types found in the intestines while also lacking some physiological aspects that are present in newer primary enteroid cell culture systems and thus the findings of such studies need to be carefully interpreted. Overall, studies examining the effects of bile acids on intestinal epithelial cells would be greatly improved with the utilization of more complex models such as primary intestinal cultures and primary intestinal cultures co-cultured with immune cells to help delineate cell specific mechanisms that are often obscured in vitro scratch model. Ultimately, CA, CDCA and LCA had no effect intestinal epithelial cell growth in response to the in vitro wound in the form of a scratch  knockout mice treated with DSS, it was found that the bile acid UDCA reduced the severity of colitis and downregulated colitis susceptibility protein mucosal addressin-cell adhesion molecule 1(MAdCAM-1) . Furtherty index . SimilarThe role of bile acid conjugation has also been studied specifically in the cases of taurine conjugated bile acids. Taurocholic acid (TCA), a conjugated primary bile acid has been shown to exert anti-inflammatory effects in chemically induced colitis. Yang Y., showed that oral gavage of TCA prevented TNBS weight loss and improved mortality . TCA alsARE mice shifted closer towards wild type mice than TNFARE mice who did not receive TUDCA. TUDCA treated mice demonstrated continued weight gain through 13 weeks of age as compared to TNFARE mice which began to exhibit weight loss at 11 weeks of age. The histological score and leukocyte infiltration scores were also significantly decreased in TNFARE mice treated with TUDCA. This study provides strong evidence that TUDCA provides some anti-inflammatory effects in a mouse model for Crohn’s ileal inflammation while also restoring some aspects of bile acid homeostasis that are impaired in ileitis.While there is evidence that taurine conjugated bile acids are protective against DSS colitis, there is additional evidence in other models for intestinal inflammation. TNF-α overexpressing mice given TUDCA in their water for eleven weeks showed benefits in their bile acid homeostasis . TUDCA tIn a model of acute DSS colitis (7-day DSS treatment followed by 7-day recovery period) with Tollip (Toll-interacting protein) deficient neutrophils, Diao N., et al. showed that DSS colitis was more severe in mice with neutrophils lacking Tollip (toll-interacting protein) . They exThe effects of TUDCA have also been studied in other models of colitis. Yang Y., et al., studied the effects of TUDCA on TNBS colitis and found that it protected against colitis during a seven-day treatment beginning 24 hours after rectal TNBS administration . Adminisin vitro to show that ER stress can promote an inflammatory response through the activation of the p38 MAPK pathway, but they did not directly test the effects of TUDCA during those experiments.More recently, Long Y., et al., showed that treatment of TNBS colitis mice with TUDCA demonstrated improved colon length, and decreased histological score . To explTaurohyodeoxycholic acid (THDCA) was investigated by He J. et al. in a model of TNBS colitis . They usWhile there have been extensive studies on bile acids as potential therapeutics for IBD in preclinical models, there are limited studies examining these effects in human IBD. Wang, Z. et al., has examined the roles of UDCA in conjunction with Mesalazine on patients with ulcerative colitis. In this prospective, single center study, participants with UC were randomly assigned to two arms: treatment with Mesalazine or treatment with Mesalazine and UDCA . SubjectWhile there is evidence for benefits in UDCA as an adjunct treatment for IBD, those benefits may come with unintended consequences. Matsui H., et al. reported on a case of a Crohn’s disease patient who developed an enterolith after UDCA administration . This paIn vitro studies modeling intestinal epithelial cells have shown that CDCA increased IL-8 secretion while LCA diminished IL-8 in two distinct human intestinal epithelial cell lines. However, to the best of our knowledge, CDCA alone was not explored in animal models and thus conclusions about CDCA remain limited. On the other hand, LCA appeared to improve intestinal barrier function and reduce apoptotic signaling in a chemical colitis model which coincides well with in vitro data. This was also the case with UDCA where there was strong evidence for anti-inflammatory properties when considering studies performed in vitro, in preclinical animal models, and in humans  cells . DCA ledZeng H. et al. (2022) found similar findings with DCA on Caco-2 cells . DCA ledBernardes-Silva et al. studied the effects of UDCA on intestinal permeability in a rat model of indomethacin induced intestinal inflammation . Intestiin vitro studies with models of intestinal epithelial cells and explants, and in vivo models of intestinal inflammation.With the exception of LCA, most of the available literature points to unconjugated bile acids as being disruptors or having no effect on intestinal barrier function in both Lowes S. et al. studied the effects of TCA and TDCA on human intestinal epithelial Caco-2 and T84 cells . Basal aLiu H. et al. studied the effects of CA supplementation on intestinal barrier integrity in rats . There wThere have also been important studies that have occurred in porcine models. Song M., et al. examined the effects of TUDCA specifically on the intestinal barrier function of weaned piglets . They adin vitro in porcine intestinal columnal epithelial IPEC-J2 cells challenged with K88 E. coli to induce epithelial barrier dysfunction (E. coli induced decreased in ZO-1, Claudin-1, and Occludin protein expression while also reducing LDH activity in the cell culture supernatant. Additionally, TUDCA treatment with and without E. coli led to significant increases in the expression of bile acid receptor TGR5, but not in FXR. Subsequently, the beneficial TUDCA effects were mediated through TGR5 signaling by knocking down TGR5 and showing that without TGR5, TUDCA did not improve E. coli disruption of epithelial barrier function in vitro. This was also supported by their data showing that during the TGR5 knockdown, TUDCA did not lead to increased levels of cAMP. This was further explored by looking at the MLCK pathway. Intestinal epithelial cells challenged with E. coli had increased MLCK expression along with an increase in the ratio of phosphorylated to unphosphorylated MLC. TUDCA treatment prevented this MLCK pathway activation, but when TGR5 was knocked down, this did not occur further providing evidence that the beneficial effects of TUDCA on intestinal permeability are mediated by TGR5. This was further supported with a MLCK inhibitor and observed similar effects compared to TUDCA.Song M., et al. also examined the effects of TUDCA function . TreatmeThere is an interesting juxtaposition between the effects of taurine conjugated bile acids on intestinal barrier function and their effects on IBD or models of IBD. Most taurine conjugated bile acids showed beneficial effects towards intestinal inflammation. However, when relating to barrier function, the data suggests that taurine conjugated bile acids mostly impair intestinal barrier function. This is counterintuitive as intestinal permeability is thought of as a hallmark of IBD and as a marker of disease severity especially in pre-clinical models. These contradictions warrant further investigation and possibly even suggest that perhaps the field needs to rethink the way that intestinal permeability is linked to disease activity in IBD.The roles of bile acids in modulating the immune responses are emerging. There is collective evidence from multiple studies and experimental approaches to support their disturbances in cases of intestinal inflammation. Unique alterations in the composition of bile acid pool are attributed to dysbiosis associated with IBD. Yet, the mechanisms by which bile acids contribute to the pathophysiology and/or the severity of intestinal inflammation are not fully understood. The complex nature of bile acid homeostasis and presence of several receptors expressed in different cell types that could be activated by bile acids make it challenging to delineate the causal link between bile acids and the inflammatory response in IBD. Future research in this field should leverage advanced bioinformatic and systems biology approaches to gain novel insights about their potential roles in the pathophysiology of IBD. Also, the profound differences in the composition of bile acid pool between humans and rodents raise serious concerns about the extent to which data obtained from these models could be extrapolated to humans. The generation of transgenic mouse models with bile acid pool similar to that of humans should offer excellent preclinical models to facilitate new discoveries related to bile acids and IBD. Further, better understanding of how gut microbiota shapes the response to a changing pool of bile acids remains a major interest of investigations. Since data suggest that a single bacterial modification of bile acids may rather involve communities of different bacteria from distinct species, future studies should focus on investigating the changes in specific microbial consortia in IBD and their effects on bile acid homeostasis. Additionally, investigating the novel roles of the newly discovered microbially conjugated bile acids will likely yield to novel findings that could further explain the potential roles of gut microbiota/bile acids axis in the development of intestinal inflammation. Overall, the increase in our knowledge about bile acids as inflammatory mediators will enhance our understanding of IBD and will define novel targets for improved therapeutic modalities for treatment of these debilitating gut disorders.NC and SC performed initial literature screening. NC, SC, RKG, and WAA finalized the first draft. NC created tables and Figure. NC, SC, PKD, SS, RKG and WAA edited and approved final version. All authors contributed to the article and approved the submitted version.