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At least 199 records · Page 11

Data-driven causal model discovery and personalized prediction in Alzheimer's disease

Abstract With the explosive growth of biomarker data in Alzheimer’s disease (AD) clinical trials, numerous mathematical models have been developed to characterize disease-relevant biomarker trajectories over time. While some of these models are purely empiric, others are causal, built upon various hypotheses of AD pathophysiology, a complex and incompletely understood area of research. One of the most challenging problems in computational causal modeling is using a purely data-driven approach to derive the model’s parameters and the mathematical model itself, without any prior hypothesis bias. In this paper, we develop an innovative data-driven modeling approach to build and parameterize a causal model to characterize the trajectories of AD biomarkers. This approach integrates causal model learning, population parameterization, parameter sensitivity analysis, and personalized prediction. By applying this integrated approach to a large multicenter database of AD biomarkers, the Alzheimer’s Disease Neuroimaging Initiative, several causal models for different AD stages are revealed. In addition, personalized models for each subject are calibrated and provide accurate predictions of future cognitive status.

Zheng, Haoyang (ORCID:0000000168358242)↗

Integrating functional scoring and regulatory data to predict the effect of non-coding SNPs in a complex neurological disease

Abstract Most SNPs associated with complex diseases seem to lie in non-coding regions of the genome; however, their contribution to gene expression and disease phenotype remains poorly understood. Here, we established a workflow to provide assistance in prioritising the functional relevance of non-coding SNPs of candidate genes as susceptibility loci in polygenic neurological disorders. To illustrate the applicability of our workflow, we considered the multifactorial disorder migraine as a model to follow our step-by-step approach. We annotated the overlap of selected SNPs with regulatory elements and assessed their potential impact on gene expression based on publicly available prediction algorithms and functional genomics information. Some migraine risk loci have been hypothesised to reside in non-coding regions and to be implicated in the neurotransmission pathway. In this study, we used a set of 22 non-coding SNPs from neurotransmission and synaptic machinery-related genes previously suggested to be involved in migraine susceptibility based on our candidate gene association studies. After prioritising these SNPs, we focused on non-reported ones that demonstrated high regulatory potential: (1) VAMP2_rs1150 (3′ UTR) was predicted as a target of hsa-mir-5010-3p miRNA, possibly disrupting its own gene expression; (2) STX1A_rs6951030 (proximal enhancer) may affect the binding affinity of zinc-finger transcription factors (namely ZNF423) and disturb TBL2 gene expression; and (3) SNAP25_rs2327264 (distal enhancer) expected to be in a binding site of ONECUT2 transcription factor. This study demonstrated the applicability of our practical workflow to facilitate the prioritisation of potentially relevant non-coding SNPs and predict their functional impact in multifactorial neurological diseases.

Felício, Daniela↗

Plasma phosphorylated tau217 strongly associates with memory deficits in the Alzheimer’s disease spectrum

Abstract Plasma phosphorylated tau (p-tau) biomarkers open unprecedented opportunities for identifying carriers of Alzheimer’s disease pathophysiology in early disease stages using minimally invasive techniques. Plasma p-tau biomarkers are believed to reflect tau phosphorylation and secretion. However, it remains unclear to what extent the magnitude of plasma p-tau abnormalities reflects neuronal network disturbance in the form of cognitive impairment. To address this question, we included 103 cognitively unimpaired elderly and 40 cognitively impaired, amyloid-β-positive individuals from the TRIAD cohort, in addition to 336 cognitively unimpaired and 216 cognitively impaired, amyloid-β-positive older adults from the BioFINDER-2 cohort. Participants had tau PET scans, amyloid PET scans or amyloid CSF, p-tau217, p-tau181 and p-tau231 blood measures, structural T1-MRI and cognitive assessments. In this cross-sectional study, we used regression models and correlation analyses to assess the relationship between plasma biomarkers and cognitive scores. Furthermore, we applied receiver operating characteristic curves to assess cognitive impairment across plasma biomarkers. Finally, we categorized participants into amyloid (A), p-tau (T1) and tau PET (T2) positive (+) or negative (−) profiles and ran non-parametric comparisons to assess differences across cognitive domains. We found that plasma p-tau217 was more associated with cognitive performance than p-tau181 and p-tau231 and that this relationship was particularly strong for memory scores (TRIAD: βp-tau217 = −0.53, βp-tau181 = −0.35 and βp-tau231 = −0.24; BioFINDER-2: βp-tau217 = −0.52, βp-tau181 = −0.24 and βp-tau231 = −0.29). Associations in amyloid-β-positive participants resembled these results, but other cognitive scores also showed strong associations in cognitively impaired individuals. Moreover, plasma p-tau217 outperformed plasma p-tau181 and plasma p-tau231 in identifying memory impairment (area under the curve values for TRIAD: p-tau217 = 0.86, p-tau181 = 0.77 and p-tau231 = 0.75; and for BioFINDER-2: p-tau217 = 0.86, p-tau181 = 0.76 and p-tau231 = 0.81) and in identifying executive function impairment only in the BioFINDER-2 cohort (p-tau217 = 0.82, p-tau181 = 0.76 and p-tau231 = 0.76). Lastly, we showed that subtle memory deficits were present in A+T1+T2− participants for plasma p-tau217 (P = 0.007) and plasma p-tau181 (P = 0.01) in the TRIAD cohort and for all biomarkers across cognitive domains in A+T1+T2− and A+T1+T2− individuals (P < 0.001 in all) in the BioFINDER-2 cohort. The A+T1+T2− individuals showed cognitive deficits in both cohorts (P < 0.001 in all). Together, our results suggest that plasma p-tau217 stands out as a biomarker capable of identifying memory deficits attributable to Alzheimer’s disease and that memory impairment certainly occurs in amyloid-β- and plasma p-tau-positive individuals who have no significant amounts of tau in the neocortex.

Neurosciences & Neurology↗

Chromosome-Level Genome Assembly of Mentha longifolia L. Reveals Gene Organization Underlying Disease Resistance and Essential Oil Traits

Mentha longifolia (L.) Huds., a wild, diploid mint species, has been developed as a model for mint genetic and genomic research to aid breeding efforts that target Verticillium wilt disease resistance and essential oil monoterpene composition. Here, we present a near-complete, chromosome-scale mint genome assembly for M. longifolia USDA accession CMEN 585. This new assembly is an update of a previously published genome draft, with dramatic improvements. A total of 42,107 protein-coding genes were annotated and placed on 12 chromosomal scaffolds. One hundred fifty-three genes contained conserved sequence domains consistent with nucleotide binding site-leucine-rich-repeat (NBS-LRR) plant disease resistance genes. Homologs of genes implicated in Verticillium wilt resistance in other plant species were also identified. Multiple paralogs of genes putatively involved in p-menthane monoterpenoid biosynthesis were identified and several cases of gene clustering documented. Heterologous expression of candidate genes, purification of recombinant target proteins, and subsequent enzyme assays allowed us to identify the genes underlying the pathway that leads to the most abundant monoterpenoid volatiles. Here, the bioinformatic and functional analyses presented here are laying the groundwork for using marker-assisted selection in improving disease resistance and essential oil traits in mints.

59 BASIC BIOLOGICAL SCIENCES↗

ALD1 accumulation in Arabidopsis epidermal plastids confers local and non-autonomous disease resistance

The Arabidopsis plastid-localized ALD1 protein acts in the lysine catabolic pathway that produces infection-induced pipecolic acid (Pip), Pip derivatives, and basal non-Pip metabolite(s). ALD1 is indispensable for disease resistance associated with Pseudomonas syringae infections of naïve plants as well as those previously immunized by a local infection, a phenomenon called systemic acquired resistance (SAR). Pseudomonas syringae is known to associate with mesophyll as well as epidermal cells. To probe the importance of epidermal cells in conferring bacterial disease resistance, we studied plants in which ALD1 was only detectable in the epidermal cells of specific leaves. Local disease resistance and many features of SAR were restored when ALD1 preferentially accumulated in the epidermal plastids at immunization sites. Interestingly, SAR restoration occurred without appreciable accumulation of Pip or known Pip derivatives in secondary distal leaves. Our findings establish that ALD1 has a non-autonomous effect on pathogen growth and defense activation. We propose that ALD1 is sufficient in the epidermis of the immunized leaves to activate SAR, but basal ALD1 and possibly a non-Pip metabolite(s) are also needed at all infection sites to fully suppress bacterial growth. Thus, epidermal plastids that contain ALD1 play a key role in local and whole-plant immune signaling.

59 BASIC BIOLOGICAL SCIENCES↗

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species

Abstract Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI’s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.

60 APPLIED LIFE SCIENCES↗

Distant-acting Enhancers in Development and Disease

Multiple converging lines of evidence from experimental and human genetic studies indicate that both common and rare sequence variants involving enhancers play major roles in Mendelian and complex human disease phenotypes. We use a combination of sequence-based molecular approaches including chromatin mapping and synthesis-enabled modification of enhancer sequences, large-scale transgenic mouse studies (http://enhancer.lbl.gov), and CRISPR genome editing in the mouse model to study the in vivofunction of enhancers in developmental, evolutionary, and disease-related processes. Using examples from our ongoing work, I will illustrate how these methods provide insight into the function and evolution of distant-acting regulatory sequences and offer a starting point for understanding their role in human disease. I will discuss how improved in vivo mouse assays can be used to study candidate pathogenic human mutations in enhancers at scale, revealing the extent to which human genetic studies alone can be insufficient to identify truly causal mutations in enhancers. I will also show how such assays can be used to explore the sensitivity of enhancers that are extremely conserved ("ultraconserved") in evolution to mutations, revealing a remarkable functional robustness to sequence changes that contrasts with apparent evolutionary constraints.

Visel, A↗

Spray-induced gene silencing for disease control is dependent on the efficiency of pathogen RNA uptake

Recent discoveries show that fungi can take up environmental RNA, which can then silence fungal genes through environmental RNA interference. This discovery prompted the development of Spray-Induced Gene Silencing (SIGS) for plant disease management. In this study, we aimed to determine the efficacy of SIGS across a variety of eukaryotic microbes. We first examined the efficiency of RNA uptake in multiple pathogenic and non-pathogenic fungi, and an oomycete pathogen. We observed efficient double-stranded RNA (dsRNA) uptake in the fungal plant pathogens Botrytis cinerea, Sclerotinia sclerotiorum, Rhizoctonia solani, Aspergillus niger and Verticillium dahliae, but no uptake in Colletotrichum gloeosporioides, and weak uptake in a beneficial fungus, Trichoderma virens. For the oomycete plant pathogen, Phytophthora infestans, RNA uptake was limited and varied across different cell types and developmental stages. Topical application of dsRNA targeting virulence-related genes in pathogens with high RNA uptake efficiency significantly inhibited plant disease symptoms, whereas the application of dsRNA in pathogens with low RNA uptake efficiency did not suppress infection. Our results have revealed that dsRNA uptake efficiencies vary across eukaryotic microbe species and cell types. The success of SIGS for plant disease management can largely be determined by the pathogen's RNA uptake efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

Vaccine-Associated Enhanced Respiratory Disease following Influenza Virus Infection in Ferrets Recapitulates the Model in Pigs

Influenza A virus (IAV) causes respiratory disease in swine and humans. Vaccines are used to prevent influenza illness in both populations but must be frequently updated due to rapidly evolving strains. Mismatch between the circulating strains and the strains contained in vaccines may cause loss of efficacy. Whole inactivated virus (WIV) vaccines with adjuvant, utilized by the swine industry, are effective against antigenically similar viruses; however, vaccine-associated enhanced respiratory disease (VAERD) may happen when the WIV is antigenically mismatched with the infecting virus. VAERD is a repeatable model in pigs, but had yet to be experimentally demonstrated in other mammalian species. We recapitulated VAERD in ferrets, a standard benchmark animal model for studying human influenza infection, in a direct comparison to VAERD in pigs. Both species were vaccinated with WIV with oil-in-water adjuvant containing a d -1 H1N2 (1B.2.2) derived from the pre-2009 human seasonal lineage, then challenged with a 2009 pandemic H1N1 (H1N1pdm09, 1A.3.3.2) 5 weeks after vaccination. Nonvaccinated and challenged groups showed typical signs of influenza disease, but the mismatched vaccinated and challenged pigs and ferrets showed elevated clinical signs, despite similar viral loads. VAERD-affected pigs exhibited a 2-fold increase in lung lesions, while VAERDaffected ferrets showed a 4-fold increase. Similar to pigs, antibodies from VAERD-affected ferrets preferentially bound to the HA2 domain of the H1N1pdm09 challenge strain. These results indicate that VAERD is not limited to pigs, as demonstrated here in ferrets, and the need to consider VAERD when evaluating new vaccine platforms and strategies.

59 BASIC BIOLOGICAL SCIENCES↗

Defective Interfering Viral Particle Treatment Reduces Clinical Signs and Protects Hamsters from Lethal Nipah Virus Disease

Defective interfering particles (DIs) contain a considerably smaller genome than the parental virus but retain replication competency. As DIs can directly or indirectly alter propagation kinetics of the parental virus, they offer a novel approach to antiviral therapy, capitalizing on knowledge from natural infection. However, efforts to translate in vitro inhibition to in vivo screening models remain limited. We investigated the efficacy of virus-like particles containing DI genomes (therapeutic infectious particles [TIPs]) in the Syrian hamster model of lethal Nipah virus (NiV) disease. We found that coadministering a high dose of TIPs intraperitoneally with virus challenge improved clinical course and reduced lethality. To mimic natural exposure, we also evaluated lower-dose TIP delivery and virus challenge intranasally, finding equally efficacious reduction in disease severity and overall lethality. Eliminating TIP replicative capacity decreased efficacy, suggesting protection via direct inhibition. These data provide evidence that TIP-mediated treatment can confer protection against disease and lethal outcome in a robust animal NiV model, supporting further development of TIP treatment for NiV and other high-consequence pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

EMC3 regulates trafficking and pulmonary toxicity of the SFTPC I73T mutation associated with interstitial lung disease

The most common mutation in surfactant protein C gene (SFTPC), SFTPC I73T , causes interstitial lung disease with few therapeutic options. We previously demonstrated that EMC3, an important component of the multiprotein endoplasmic reticulum membrane complex (EMC), is required for surfactant homeostasis in alveolar type 2 epithelial (AT2) cells at birth. In the present study, we investigated the role of EMC3 in the control of SFTPC I73T metabolism and its associated alveolar dysfunction. Using a knock-in mouse model phenocopying the I73T mutation, we demonstrated that conditional deletion of Emc3 in AT2 cells rescued alveolar remodeling/simplification defects in neonatal and adult mice. Proteomic analysis revealed that Emc3 depletion reversed the disruption of vesicle trafficking pathways and rescued the mitochondrial dysfunction associated with I73T mutation. Affinity mass spectrometry analysis identified potential EMC3 interacting proteins in lung AT2 cells, including Valosin Containing Protein (VCP) and its interactors. Treatment of Sftpc I73T knock-in mice and SFTPC I73T expressing iAT2 cells derived from SFTPC I73T patient-specific iPSCs with the specific VCP inhibitor CB5083 restored alveolar structure and SFTPC I73T trafficking respectively. Taken together, the present work identifies the EMC complex and VCP in the metabolism of the disease-associated SFTPC I73T mutant, providing novel therapeutical targets for SFTPC I73T -associated interstitial lung disease.

60 APPLIED LIFE SCIENCES↗

Psychological Distress and Alzheimer’s Disease Mortality in the United States: Results from the 1997–2014 National Health Interview Survey-National Death Index Record Linkage Study

Objective: This study examines the association between psychological distress and Alzheimer’s disease mortality among US adults aged ≥45. Methods: We analyzed the Kessler 6-item psychological distress scale as a risk factor for Alzheimer’s mortality using the pooled 1997–2014 National Health Interview Survey (NHIS)- National Death Index (NDI) database ( N = 265,089). Cox regression was used to model mortality as a function of psychological distress and sociodemographic and behavioral covariates. Results: The Alzheimer’s mortality risk was 97% higher (HR = 1.97; 95% confidence interval [CI] = 1.37, 2.84) in adults with serious psychological distress compared with those without psychological distress, controlling for sociodemographic covariates. The relative mortality risk remained statistically significant (HR = 1.49; 95% CI = 1.04, 2.13) after additional adjustment for smoking, alcohol consumption, health status, activity limitation, and body mass index. Discussion: US adults had significantly higher risks of Alzheimer’s disease mortality at higher psychological distress levels. These findings underscore the significance of addressing psychological well-being as a strategy for reducing Alzheimer’s disease mortality.

Singh, Gopal K.↗

Assessment of Knowledge, Attitudes, and Practices Toward Ticks and Tickborne Disease among Healthcare Professionals Working in Schools in New York and Maryland

Healthcare Professionals Working in Schools (HPWS) are responsible for providing health services to students and play a role in providing education to prevent illnesses, including tickborne diseases (TBD). Providing TBD education to children has been shown to increase prevention behaviors and knowledge of TBD symptoms, but little is known regarding the current state of TBD awareness among HPWS. In spring 2019 we conducted a cross-sectional knowledge, attitudes, and practices (KAP) survey of HPWS in two states with a high incidence of Lyme disease (LD) to inform design of TBD prevention programs. The survey queried general knowledge of TBDs, school practices regarding TBDs, and availability of TBD resources. Overall, higher confidence, experience, risk perception, prior training on TBD, and more years employed as a HPWS were independently associated with knowledge of LD transmission, symptoms, and correct tick removal practices. State and local health departments should consider prioritizing engagement with HPWS to provide educational opportunities about tickborne diseases.

Nursing↗

Calibration verification for stochastic agent-based disease spread models

Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.

60 APPLIED LIFE SCIENCES↗

COVID-19 through Adverse Outcome Pathways: Building networks to better understand the disease – 3rd CIAO AOP Design Workshop

On April 28-29, 2021, 50 scientists from different fields of expertise met for the 3rd online CIAO workshop. The CIAO project “Modelling the Pathogenesis of COVID-19 using the Adverse Outcome Pathway (AOP) framework” aims at building a holistic assembly of the available scientific knowledge on COVID-19 using the AOP framework. An individual AOP depicts the disease progression from the initial contact with the SARS-CoV-2 virus through biological key events (KE) toward an adverse outcome such as respiratory distress, anosmia or multiorgan failure. Assembling the individual AOPs into a network highlights shared KEs as central biological nodes involved in multiple outcomes observed in COVID-19 patients. During the workshop, the KEs and AOPs established so far by the CIAO members were presented and posi­tioned on a timeline of the disease course. Modulating factors influencing the progression and severity of the disease were also addressed as well as factors beyond purely biological phenomena. CIAO relies on an interdisciplinary crowd­sourcing effort, therefore, approaches to expand the CIAO network by widening the crowd and reaching stakeholders were also discussed. To conclude the workshop, it was decided that the AOPs/KEs will be further consolidated, inte­grating virus variants and long COVID when relevant, while an outreach campaign will be launched to broaden the CIAO scientific crowd.

60 APPLIED LIFE SCIENCES↗

Chimeric Protein Treatment of Pierce Disease

Pierce disease is an economically costly disease for several agricultural crops, including grapes, citrus, and olives. An invasive insect species, the glassy-winged sharpshooter, harbors a gut bacteria that kills grape vines. The bacteria destroys the xylem, the water transport tissue in plants. Los Alamos researchers have designed a technology to target and kill the source of Pierce disease. The treatment does not require the use of pesticides or the removal and replacement of the effected vines.

59 BASIC BIOLOGICAL SCIENCES↗

Engineered human vascular models to study endothelial dysfunction in infectious disease

Vascular involvement plays a pivotal role in the pathogenesis of numerous emerging viral threats, with climate changes amplifying the likelihood of these diseases evolving into pandemics. Establishing an infectable and physiologically relevant human in vitro model holds immense importance in comprehending the pathogenesis of these threats and devising effective countermeasures. Although in vivo models provide valuable insight into disease, their application is restricted by interspecies variations, particularly concerning pathogens exclusive to humans. Moreover, animal models often fail to replicate comorbidities prevalent in patient populations, thus limiting our understanding of disease behavior in humans. In this study, we have devised a testing platform aimed at exploring pathogen interactions with innate immunity within the vasculature, encompassing both healthy and dysfunctional endothelial conditions.

42 ENGINEERING↗

The key role of the ferroptosis mechanism in neurological diseases and prospects for targeted therapy

Neurological disorders represent a major global health concern owing to their intricate pathological processes. Ferroptosis, defined as a form of cell death that is reliant on iron, has been closely linked to various neurological conditions. The fundamental process underlying ferroptosis is defined by the excessive buildup of iron ions, which initiates lipid peroxidation processes leading to cellular demise. Neurons, as highly metabolically active cells, are susceptible to oxidative stress, and imbalances in iron metabolism can directly initiate the ferroptosis process. In neurodegenerative disorders like Alzheimer’s disease and Parkinson’s disease, ferroptosis driven by iron accumulation represents a fundamental pathological connection. Although the connection between ferroptosis and neurological diseases is clear, clinical application still faces challenges, such as precise regulation of iron metabolism, development of specific drugs, and assessment of efficacy. The limited comprehension of the ferroptosis mechanism hinders the development of personalized treatment approaches. Consequently, subsequent investigations must tackle these obstacles to facilitate the clinical application of ferroptosis-associated therapies in neurological disorders. This article provides a comprehensive overview of the most recent advancements regarding the underlying mechanisms of ferroptosis. Subsequently, the study investigates the mechanistic contributions of ferroptosis within the nervous system. In conclusion, we evaluate and deliberate on targeted therapeutic strategies associated with ferroptosis and neurological disorders.

Xie, Chenyu↗