Biological Hypotheses Research Articles

MoSBi: Automated signature mining for molecular stratification and subtyping

The improving access to increasing amounts of biomedical data provides completely new chances for advanced patient stratification and disease subtyping strategies. This requires computational tools that produce uniformly robust results across highly heterogeneous molecular data. Unsupervised machine learning methodologies are able to discover de novo patterns in such data. Biclustering is especially suited by simultaneously identifying sample groups and corresponding feature sets across heterogeneous omics data. The performance of available biclustering algorithms heavily depends on individual parameterization and varies with their application. Here, we developed MoSBi (molecular signature identification using biclustering), an automated multialgorithm ensemble approach that integrates results utilizing an error model-supported similarity network. We systematically evaluated the performance of 11 available and established biclustering algorithms together with MoSBi. For this, we used transcriptomics, proteomics, and metabolomics data, as well as synthetic datasets covering various data properties. Profiting from multialgorithm integration, MoSBi identified robust group and disease-specific signatures across all scenarios, overcoming single algorithm specificities. Furthermore, we developed a scalable network-based visualization of bicluster communities that supports biological hypothesis generation. MoSBi is available as an R package and web service to make automated biclustering analysis accessible for application in molecular sample stratification.

Efficacy of Caffeine in ADCY5-Related Dyskinesia: A Retrospective Study.

ADCY5-related dyskinesia is characterized by early-onset movement disorders. There is currently no validated treatment, but anecdotal clinical reports and biological hypotheses suggest efficacy of caffeine. The aim is to obtain further insight into the efficacy and safety of caffeine in patients with ADCY5-related dyskinesia. A retrospective study was conducted worldwide in 30 patients with a proven ADCY5 mutation who had tried or were taking caffeine for dyskinesia. Disease characteristics and treatment responses were assessed through a questionnaire. Caffeine was overall well tolerated, even in children, and 87% of patients reported a clear improvement. Caffeine reduced the frequency and duration of paroxysmal movement disorders but also improved baseline movement disorders and some other motor and nonmotor features, with consistent quality-of-life improvement. Three patients reported worsening. Our findings suggest that caffeine should be considered as a first-line therapeutic option in ADCY5-related dyskinesia. © 2022 International Parkinson and Movement Disorder Society.

Can classic biological invasion hypotheses be applied to reported cases of non-native terrestrial species in the Maritime Antarctic?

AbstractUnderstanding the success factors underlying each step in the process of biological invasion provides a robust foundation upon which to develop appropriate biosecurity measures. Insights into the processes occurring can be gained through clarifying the circumstances applying to non-native species that have arrived, established and, in some cases, successfully spread in terrestrial Antarctica. To date, examples include a small number of vascular plants and a greater diversity of invertebrates (including Diptera, Collembola, Acari and Oligochaeta), which share features of pre-adaptation to the environmental stresses experienced in Antarctica. In this synthesis, we examine multiple classic invasion science hypotheses that are widely considered to have relevance in invasion ecology and assess their utility in understanding the different invasion histories so far documented in the continent. All of these existing hypotheses appear relevant to some degree in explaining invasion processes in Antarctica. They are also relevant in understanding failed invasions and identifying barriers to invasion. However, the limited number of cases currently available constrains the possibility of establishing patterns and processes. To conclude, we discuss several new and emerging confirmatory methods as relevant tools to test and compare these hypotheses given the availability of appropriate sample sizes in the future.

It Ain't Over 'Til It's Over: SARS CoV-2 and Post-infectious Gastrointestinal Dysmotility.

The ongoing pandemic resulting from severe acute respiratory syndrome—caused by coronavirus 2 (SARS-CoV-2)—has posed a multitude of healthcare challenges of unprecedented proportions. Intestinal enterocytes have the highest expression of angiotensin-converting enzyme-2 (ACE2), which functions as the key receptor for SARS-CoV-2 entry into cells. As such, particular interest has been accorded to SARS-CoV-2 and how it manifests within the gastrointestinal system. The acute and chronic alimentary clinical implications of infection are yet to be fully elucidated, however, the gastrointestinal consequences from non-SARS-CoV-2 viral GI tract infections, coupled with the generalized nature of late sequelae following COVID-19 disease, would predict that motility disorders are likely to be seen in these patients. Determination of the chronic effects of COVID-19 disease, herein defined as GI disease which is persistent or recurrent more than 3 months following recovery from the acute respiratory illness, will require comprehensive investigations comprising combined endoscopic- and motility-based evaluation. It will be fascinating to ascertain whether the specific post-COVID-19 phenotype is hypotonic or hypertonic in nature and to identify the most vulnerable target portions of the gut. A specific biological hypothesis is that motility disorders may result from SARS-CoV-2-induced angiotensin-converting enzyme 2 (ACE2) depletion. Since SARS-CoV-2 is known to exhibit direct neuronal tropism, the potential also exists for the development of neurogenic motility disorders. This review aims to explore some of the potential pathophysiologic mechanisms underlying motility dysfunction as it relates to ACE2 and thereby aims to provide the foundation for mechanism-based potential therapeutic options.

Mathematical analysis and numerical simulation of the Ebola epidemic disease in the sense of conformable derivative

The aim of this paper is to construct and analyze a mathematical model for the response of T-cytotoxic lymphocytes to the Ebola virus using the Herz-tuckwill model with nonlinear Conformable order differential equations which derive from real biological data, then study the global stability of the equilibria using an appropriate Lyapunov function and the LaSalle invariance principle. Furthermore, we demonstrate the impact of the non-integer order of the model compared with the integral order. Finally consider a numerical simulation that justifies the biological hypotheses and the theory results. The numerical results provided that, the non-integer order has a great impact on the treatments of Ebola virus in this model.

Intratarget Microdosing for Deep Phenotyping of Multiple Drug Effects in the Live Brain

A main impediment to effective development of new therapeutics for central nervous system disorders, and for the in vivo testing of biological hypotheses in the brain, is the ability to rapidly measure the effect of novel agents and treatment combinations on the pathophysiology of native brain tissue. We have developed a miniaturized implantable microdevice (IMD) platform, optimized for direct stereotactic insertion into the brain, which enables the simultaneous measurement of multiple drug effects on the native brain tissue in situ. The IMD contains individual reservoirs which release microdoses of single agents or combinations into confined regions of the brain, with subsequent spatial analysis of phenotypic, transcriptomic or metabolomic effects. Using murine models of Alzheimer’s disease (AD), we demonstrate that microdoses of various approved and investigational CNS drugs released from the IMD within a local brain region exhibit in situ phenotypes indicative of therapeutic responses, such as neuroprotection, reduction of hyperphosphorylation, immune cell modulation, and anti-inflammatory effects. We also show that local treatments with drugs affecting metabolism provide evidence for regulation of metabolite profiles and immune cell function in hMAPT AD mice. The platform should prove useful in facilitating the rapid testing of pharmacological or biological treatment hypotheses directly within native brain tissues (of various animal models and in patients) and help to confirm on-target effects, in situ pharmacodynamics and drug-induced microenvironment remodeling, much more efficiently than currently feasible.

Comparative invasion ecology ofCarpobrotusfrom four continents: responses to nutrients and competition

AbstractTwo key hypotheses in invasion biology are that certain traits underlie invasiveness in introduced species, and that these traits are selected for during or after introduction. We tested these hypotheses by focusing on two traits likely to confer invasiveness, high increase in growth in response to increase in nutrients and low decrease in growth in response to competition. We compared four species of Carpobrotus that differ in invasiveness, using species from four continents: Africa, Australia, Europe and North America. To test for selection for these traits in Carpobrotus edulis, a highly invasive species, we compared plants from its native range in South Africa to plants from the other three regions, where C. edulis has been introduced. Plants were propagated in a common garden. Offspring were then grown alone with or without added nutrients, and together with another species of Carpobrotus or with the grass Ammophila arenaria (a co-occurring native species in Europe) without added nutrients. Response to nutrients did not differ between species of Carpobrotus, nor was competitive response less negative in more invasive species. However, increase in growth in response to added nutrients was greater in introduced than in native C. edulis. Moreover, fresh mass per ramet at the start of treatments was higher in the two invasive species than in the two non-invasive ones. We provide new evidence that introduction can select for response to nutrient enrichment in invasive species and add to the evidence for an association between size and invasiveness in introduced plants.

Spray-Based Application of Matrix to Agar-Based Microbial Samples for Reproducible Sample Adherence in MALDI MSI.

Microbial mass spectrometry imaging (MSI) is a powerful tool used to generate biological hypotheses about the roles of metabolites in microbial competition based upon their two-dimensional spatial distribution. The most commonly used ionization method for microbial MSI is matrix-assisted laser desorption ionization (MALDI). However, medium components and microbial metabolites influence the adhesion of agar samples to the MALDI target, limiting the applicability of MALDI MSI to microbes grown on specific media. Here, we describe a three-step process using a robotic sprayer for a matrix application that improves the adherence of agar samples to the MALDI target, enabling the use of different media for microbial growth and an MSI analysis of larger sample surface areas.

Morphological Evolution: Bioinspired Methods for Analyzing Bioinspired Robots.

To fully understand the evolution of complex morphologies, analyses cannot stop at selection: It is essential to investigate the roles and interactions of multiple processes that drive evolutionary outcomes. The challenges of undertaking such analyses have affected both evolutionary biologists and evolutionary roboticists, with their common interests in complex morphologies. In this paper, we present analytical techniques from evolutionary biology, selection gradient analysis and morphospace walks, and we demonstrate their applicability to robot morphologies in analyses of three evolutionary mechanisms: randomness (genetic mutation), development (an explicitly implemented genotype-to-phenotype map), and selection. In particular, we applied these analytical techniques to evolved populations of simulated biorobots—embodied robots designed specifically as models of biological systems, for the testing of biological hypotheses—and we present a variety of results, including analyses that do all of the following: illuminate different evolutionary dynamics for different classes of morphological traits; illustrate how the traits targeted by selection can vary based on the likelihood of random genetic mutation; demonstrate that selection on two selected sets of morphological traits only partially explains the variance in fitness in our biorobots; and suggest that biases in developmental processes could partially explain evolutionary dynamics of morphology. When combined, the complementary analytical approaches discussed in this paper can enable insight into evolutionary processes beyond selection and thereby deepen our understanding of the evolution of robotic morphologies.

BoomBox: An Automated Behavioural Response (ABR) camera trap module for wildlife playback experiments

Abstract Camera traps (CTs) are a valuable tool in ecological research, amassing large quantities of information on the behaviour of diverse wildlife communities. CTs are predominantly used as passive data loggers to gather observational data for correlational analyses. Integrating CTs into experimental studies, however, can enable rigorous testing of key hypotheses in animal behaviour and conservation biology that are otherwise difficult or impossible to evaluate. We developed the 'BoomBox', an open‐source Arduino‐compatible board that attaches to commercially available CTs to form an Automated Behavioural Response (ABR) system. The modular unit connects directly to the CT’s passive infrared (PIR) motion sensor, playing audio files over external speakers when the sensor is triggered. This creates a remote playback system that captures animal responses to specific cues, combining the benefits of camera trapping (e.g. continuous monitoring in remote locations, lack of human observers, large data volume) with the power of experimental manipulations (e.g. controlled perturbations for strong mechanistic inference). Our system builds on previous ABR designs to provide a cheap (~100USD) and customizable field tool. We provide a practical guide detailing how to build and operate the BoomBox ABR system with suggestions for potential experimental designs that address a variety of questions in wildlife ecology. As proof‐of‐concept, we successfully field tested the BoomBox in two distinct field settings to study species interactions (predator–prey and predator–predator) and wildlife responses to conservation interventions. This new tool allows researchers to conduct a unique suite of manipulative experiments on free‐living species in complex environments, enhancing the ability to identify mechanistic drivers of species' behaviours and interactions in natural systems.

A Short History of Bernard Fisher's Contributions to Randomized Clinical Trials.

Dr. Bernard Fisher (1918-2019) was an early proponent of evidence-based medicine using the mechanism of prospective, multicenter, randomized clinical trials to test biological and clinical hypotheses. In this article, I trace how his early scientific work in striving to understand the nature of cancer metastasis through animal experiments led to a new, testable, clinical hypothesis: that surgery to remove only the tumor and a small amount of tissue around it was as effective as the more disfiguring operations that were then the standard treatment. Fisher's work with the National Surgical Adjuvant Breast and Bowel Project (NSABP) using large, randomized clinical trials to demonstrate the veracity of this hypothesis led to a new paradigm in which the emphasis was placed on how systemic therapies used at an early stage of disease could effectively eradicate breast cancer for many patients. This new therapeutic approach led to the successful development of new treatments, many of which are widely used today. Ultimately, the new paradigm led to successfully preventing breast cancer in women who were at high risk for the disease but who had not yet been diagnosed with the disease. Throughout his entire career, Fisher championed the use of large prospective, randomized clinical trials despite criticism from many in the medical community who strongly criticized his use of randomization as a mechanism for testing clinical hypotheses. The approach he and the NSABP employed is still considered to be the highest standard of evidence in conducting clinical studies.

Path-level interpretation of Gaussian graphical models using the pair-path subscore

Background Construction of networks from cross-sectional biological data is increasingly common. Many recent methods have been based on Gaussian graphical modeling, and prioritize estimation of conditional pairwise dependencies among nodes in the network. However, challenges remain on how specific paths through the resultant network contribute to overall ‘network-level’ correlations. For biological applications, understanding these relationships is particularly relevant for parsing structural information contained in complex subnetworks.ResultsWe propose the pair-path subscore (PPS), a method for interpreting Gaussian graphical models at the level of individual network paths. The scoring is based on the relative importance of such paths in determining the Pearson correlation between their terminal nodes. PPS is validated using human metabolomics data from the Hyperglycemia and adverse pregnancy outcome (HAPO) study, with observations confirming well-documented biological relationships among the metabolites. We also highlight how the PPS can be used in an exploratory fashion to generate new biological hypotheses. Our method is implemented in the R package pps, available at https://github.com/nathan-gill/pps.ConclusionsThe PPS can be used to probe network structure on a finer scale by investigating which paths in a potentially intricate topology contribute most substantially to marginal behavior. Adding PPS to the network analysis toolkit may enable researchers to ask new questions about the relationships among nodes in network data.

Sex hormone-related polymorphisms in endometriosis and migraine: A narrative review

Some evidence indicates endometriosis and migraine have a common genetic predisposition in sex-hormone genes, which could have important implications for the treatment of these two heterogenous conditions. To date, the genes responsibility remains unknown. Based on the biological hypothesis that polymorphisms of genes involved in sex-hormone pathways may influence estrogen levels and phenotypes of both disorders, we did a literature search for candidate sex-hormone genes and genes involved in the metabolism of estradiol. The aim was to review the evidence for shared sex-hormone-related polymorphisms between endometriosis and migraine and provide an exhaustive overview of the current literature. We included case-control studies investigating associations between candidate sex-hormone-related genes and the disorders endometriosis and migraine, respectively. Results showed three overlapping sex-hormone-associated polymorphisms in estrogen receptor genes that are associated with both conditions. To confirm possible associations with other sex-hormone genes, larger studies are needed.

Nonparametric k-Sample Test on Shape Spaces with Applications to Mitochondrial Shape Analysis

Abstract An important hypothesis in animal cell biology is that an animal’s acute exercise regimen affects some subcellular structures, for example mitochondrial morphology, in its muscle tissue. This paper investigates that hypothesis using a nonparametric metric-based energy test for comparing mitochondrial populations. It explores two shape spaces—the elastic shape space and Kendall shape space—and five corresponding shape metrics on these spaces. The results overwhelmingly point to the statistical significance of the effect of an acute exercise regimen on the shape of SS-type mitochondria. Although past studies based on specific morphological features derived from mitochondria failed to detect this significance. In this analysis, a potentially significant factor is cell membership and a k-sample generalization of the energy test—the DISCO test shows that the cell effect is indeed significant. The energy test cannot be applied directly due to the hierarchical structure of the distance matrix. We propose a compression method to remove the significant cell effect while testing for the exercise effect. With this compression, only the elastic scaled metric shows statistical significance of the exercise factor in this more complicated scenario. This result is because the elastic-scaled metric is more sensitive to subtle changes in mitochondrial shapes caused by acute exercise.

Sex and gender differences in autoimmune demyelinating CNS disorders: Multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD) and myelin-oligodendrocyte-glycoprotein antibody associated disorder (MOGAD).

Multiple sclerosis (MS), Neuromyelitis optica spectrum disorder (NMOSD) and Myelin-Oligodendrocyte-Glycoprotein antibody associated disorder (MOGAD) are demyelinating disorders of the central nervous system (CNS) of autoimmune origin. Here, we summarize general considerations on sex-specific differences in the immunopathogenesis and hormonal influences as well as key clinical and epidemiological elements. Gender-specific issues are widely neglected starting with the lacking separation of sex as a biological variable and gender comprising the sociocultural components. As for other autoimmune diseases, female preponderance is common in MS and NMOSD. However, sex distribution in MOGAD seems equal. As in MS, immunotherapy in NMOSD and MOGAD is crucial to prevent further disease activity. Therefore, we assessed data on sex differences of the currently licensed disease-modifying treatments for efficacy and safety. This topic seems widely neglected with only fragmented information resulting from post-hoc analyses of clinical trials or real-world post-marketing studies afflicted with lacking power and/or inherent sources of bias. In summary, biological hypotheses of sex differences including genetic factors, the constitution of the immune system and hormonal influences are based upon human and preclinical data, especially for the paradigmatic disease of MS whereas specific data for NMOSD and MOGAD are widely lacking. Epidemiological and clinical differences between men and women are well described for MS and to some extent for NMOSD, yet, with remaining contradictory findings. MOGAD needs further detailed investigation. Sex-specific analyses of safety and efficacy of long-term immunotherapies need to be addressed in future studies designed and powered to answer the pressing questions and to optimize and individualize treatment.

Multiple Chemical Sensitivity.

Multiple Chemical Sensitivity (MCS), a condition also known as Chemical Sensitivity (CS), Chemical Intolerance (CI), Idiopathic Environmental Illness (IEI) and Toxicant Induced Loss of Tolerance (TILT), is an acquired multifactorial syndrome characterized by a recurrent set of debilitating symptoms. The symptoms of this controversial disorder are reported to be induced by environmental chemicals at doses far below those usually harmful to most persons. They involve a large spectrum of organ systems and typically disappear when the environmental chemicals are removed. However, no clear link has emerged among self-reported MCS symptoms and widely accepted objective measures of physiological dysfunction, and no clear dose-response relationship between exposure and symptom reactions has been observed. In addition, the underlying etiology and pathogenic processes of the disorder remain unknown and disputed, although biologic and psychologic hypotheses abound. It is currently debated whether MCS should be considered a clinical entity at all. Nevertheless, in the last few decades MCS has received considerable scientific and governmental attention in light of the many persons reporting this illness. In this review, we provide a general overview of the history, definition, demographics, prevalence, and etiologic challenges in defining and understanding MCS.

Patterned photocrosslinking to establish stiffness anisotropies in fibrous 3D hydrogels

Cells are known to constantly interact with their local extracellular matrix (ECM) and respond to a variety of biochemical and mechanical cues received from the ECM. Nonetheless, comprehensive understanding of cell-ECM interactions has been elusive. Many studies rely on analysis of cell behavior on 2D substrates, which do not reflect a natural cell environment. Further, lack of dynamic control over local stiffness anisotropies and fiber alignment hinders progress in studies in naturally derived fibrous 3D cultures. Here, we present a cell-safe method of patterned photocrosslinking, which can aid in studying biological hypotheses related to mechanotransduction in 3D hydrogels. As previously described by our group, ruthenium-catalyzed photocrosslinking (RCP) of selected ECM regions promotes localized increase in stiffness mediated by focused blue laser light in a confocal microscope. In this study, we further demonstrate that RCP can induce localized strain stiffening and fiber alignment outside of the selected crosslinked region and induce stiffness anisotropy biased towards the direction of fiber alignment. MDA-MB-231 cells are shown to respond to RCP-induced changes in local ECM architecture and display directional bias towards the direction of fiber alignment, as compared to control cells. Further, the effect of patterned crosslinking on a stiffness landscape is measured using multi-axes optical tweezers active microrheology (AMR) with backscattered laser beam illumination. AMR validates RCP as a suitable tool for creating distinct stiffness anisotropies which promote directed migration of cells, further underscoring the usefulness of RCP in cell-ECM studies. Statement of significanceStudies on cell-ECM interactions in 3D cultures have often been hindered by the lack of available tools to dynamically alter local ECM stiffness and fiber alignment. Here, we present a non-invasive, cell-safe and easily applicable method of patterned photocrosslinking, which can aid in studying biological hypotheses in fibrous 3D hydrogels. Ruthenium-catalyzed crosslinking (RCP) of selected fibrin ECM regions promotes localized increase in stiffness and creates distinct stiffness anisotropies in the presence of the focused blue laser light. Outside of the crosslinked region, RCP causes fiber alignment and strain stiffening in the ECM, verified using multi-axes optical tweezers active microrheology (AMR). Following RCP, human breast cancer MDA-MB-231 exhibit directed cell migration, validating usefulness of this method in cell-ECM studies.

BioProfiling.jl: profiling biological perturbations with high-content imaging in single cells and heterogeneous populations.

MotivationHigh-content imaging screens provide a cost-effective and scalable way to assess cell states across diverse experimental conditions. The analysis of the acquired microscopy images involves assembling and curating raw cellular measurements into morphological profiles suitable for testing biological hypotheses. Despite being a critical step, general-purpose and adaptable tools for morphological profiling are lacking and no solution is available for the high-performance Julia programming language.ResultsHere, we introduce BioProfiling.jl, an efficient end-to-end solution for compiling and filtering informative morphological profiles in Julia. The package contains all the necessary data structures to curate morphological measurements and helper functions to transform, normalize and visualize profiles. Robust statistical distances and permutation tests enable quantification of the significance of the observed changes despite the high fraction of outliers inherent to high-content screens. This package also simplifies visual artifact diagnostics, thus streamlining a bottleneck of morphological analyses. We showcase the features of the package by analyzing a chemical imaging screen, in which the morphological profiles prove to be informative about the compounds' mechanisms of action and can be conveniently integrated with the network localization of molecular targets.Availability and implementationThe Julia package is available on GitHub: https://github.com/menchelab/BioProfiling.jl. We also provide Jupyter notebooks reproducing our analyses: https://github.com/menchelab/BioProfilingNotebooks. The data underlying this article are available from FigShare, at https://doi.org/10.6084/m9.figshare.14784678.v2.Supplementary information Supplementary data are available at Bioinformatics online.

GraphOmics: an interactive platform to explore and integrate multi-omics data

BackgroundAn increasing number of studies now produce multiple omics measurements that require using sophisticated computational methods for analysis. While each omics data can be examined separately, jointly integrating multiple omics data allows for deeper understanding and insights to be gained from the study. In particular, data integration can be performed horizontally, where biological entities from multiple omics measurements are mapped to common reactions and pathways. However, data integration remains a challenge due to the complexity of the data and the difficulty in interpreting analysis results.ResultsHere we present GraphOmics, a user-friendly platform to explore and integrate multiple omics datasets and support hypothesis generation. Users can upload transcriptomics, proteomics and metabolomics data to GraphOmics. Relevant entities are connected based on their biochemical relationships, and mapped to reactions and pathways from Reactome. From the Data Browser in GraphOmics, mapped entities and pathways can be ranked, sorted and filtered according to their statistical significance (p values) and fold changes. Context-sensitive panels provide information on the currently selected entities, while interactive heatmaps and clustering functionalities are also available. As a case study, we demonstrated how GraphOmics was used to interactively explore multi-omics data and support hypothesis generation using two complex datasets from existing Zebrafish regeneration and Covid-19 human studies.ConclusionsGraphOmics is fully open-sourced and freely accessible from https://graphomics.glasgowcompbio.org/. It can be used to integrate multiple omics data horizontally by mapping entities across omics to reactions and pathways. Our demonstration showed that by using interactive explorations from GraphOmics, interesting insights and biological hypotheses could be rapidly revealed.

Pathway modeling applied to TREAT-AD proteomic targets demonstrates linkages between AD endophenotypes.

The poor success rate of therapeutic targeting in Alzheimer's disease necessitates the explorations of new biological areas and hypotheses of disease mechanism. The TREAT-AD Consortium is an international group of academic researchers dedicated to identifying novel targets for AD from under-explored areas of disease-linked pathology. However, target identification from genomic and proteomic studies is extremely challenging. Toward that end, we identified 13 core biological domains associated with AD, and created a gene ontology (GO) mapping to each in order to automatically identify genes associated with each endophenotype. The TREAT-AD hits coming from large scale brain proteomic studies were then mapped onto the core biological domains. A novel system of dynamic data driven pathway reconstruction was applied that draws binary relationships from the Pathway Commons data store and builds AD-weighted pathways around the proteomic targets linked to the 13 core biological domains of AD. The dynamic data-driven pathway reconstruction application developed large network objects around the submitted proteomic targets that create hypothetical linkage points across discrete areas of disease biology. The network objects represent a holistic pathway linking the submitted TREAT-AD proteomic hits to each other, through missing elements and disease sentinel genes, to create an interlinked pathway model. This model can be shared and community-mined for significant AD-linked hypotheses. Using this approach, we identified numerous interactions between AD endophenotypes, such as neuroinflammation and endocytosis. One of the primary difficulties with therapeutic target identification is understanding the biological network within which any particular gene resides. The tools we have developed may help examine the biological neighborhood more robustly, as well as assess specific hypothetical mechanist connections between genes that may help identify and optimized AD-drug targets in the future.