Understanding Toxoplasmosis in the United States Through "Large Data" Analyses.

BACKGROUND: Toxoplasma gondii infection causes substantial morbidity and mortality in the United States, and infects approximately one-third of persons globally. Clinical manifestations vary. Seropositivity is associated with neurologic diseases and malignancies. There are few objective data concerning US incidence and distribution of toxoplasmosis. METHODS: Truven Health MarketScan Database and International Classification of Diseases, Ninth Revision (ICD-9) codes, including treatment specific to toxoplasmosis, identified patients with this disease. Spatiotemporal distribution and patterns of disease manifestation were analyzed. Comorbidities between patients and matched controls were compared. RESULTS: Between 2003 and 2012, 9260 patients had ICD-9 codes for toxoplasmosis. This database of patients with ICD-9 codes includes 15% of those in the United States, excluding patients with no or public insurance. Thus, assuming that demographics do not change incidence, the calculated total is 61 700 or 6856 patients per year. Disease was more prevalent in the South. Mean age at diagnosis was 37.5 ± 15.5 years; 2.4% were children aged 0-2 years, likely congenitally infected. Forty-one percent were male, and 73% of women were of reproductive age. Of identified patients, 38% had eye disease and 12% presented with other serious manifestations, including central nervous system and visceral organ damage. Toxoplasmosis was statistically associated with substantial comorbidities, including human immunodeficiency virus, autoimmune diseases, and neurologic diseases. CONCLUSIONS: Toxoplasmosis causes morbidity and mortality in the United States. Our analysis of private insurance records missed certain at-risk populations and revealed fewer cases of retinal disease than previously estimated, suggesting undercoding, underreporting, undertreating, or differing demographics of those with eye disease. Mandatory reporting of infection to health departments and gestational screening could improve care and facilitate detection of epidemics and, thereby, public health interventions.

Quantifying the impact and extent of undocumented biomedical synonymy.

Synonymous relationships among biomedical terms are extensively annotated within specialized terminologies, implying that synonymy is important for practical computational applications within this field. It remains unclear, however, whether text mining actually benefits from documented synonymy and whether existing biomedical thesauri provide adequate coverage of these linguistic relationships. In this study, we examine the impact and extent of undocumented synonymy within a very large compendium of biomedical thesauri. First, we demonstrate that missing synonymy has a significant negative impact on named entity normalization, an important problem within the field of biomedical text mining. To estimate the amount synonymy currently missing from thesauri, we develop a probabilistic model for the construction of synonym terminologies that is capable of handling a wide range of potential biases, and we evaluate its performance using the broader domain of near-synonymy among general English words. Our model predicts that over 90% of these relationships are currently undocumented, a result that we support experimentally through "crowd-sourcing." Finally, we apply our model to biomedical terminologies and predict that they are missing the vast majority (>90%) of the synonymous relationships they intend to document. Overall, our results expose the dramatic incompleteness of current biomedical thesauri and suggest the need for "next-generation," high-coverage lexical terminologies.

Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability.

Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6×10(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], p = 0.02475 and 99% CI: [68%, 99.99%], p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).

Novel paradigm enables accurate monthly gestational screening to prevent congenital toxoplasmosis and more.

BACKGROUND: Congenital toxoplasmosis is a treatable, preventable disease, but untreated causes death, prematurity, loss of sight, cognition and motor function, and substantial costs worldwide. OBJECTIVES: We asked whether high performance of an Immunochromatographic-test (ICT) could enable accurate, rapid diagnosis/treatment, establishing new, improved care-paradigms at point-of-care and clinical laboratory. METHODS: Data were obtained in 12 studies/analyses addressing: 1-feasibility/efficacy; 2-false-positives; 3-acceptability; 4-pink/black-line/all studies; 5-time/cost; 6-Quick-Information/Limit-of-detection; 7, 8-acute;-chronic; 9-epidemiology; 10-ADBio; 11,12-Commentary/Cases/Chronology. FINDINGS: ICT was compared with gold-standard or predicate-tests. Overall, ICT performance for 1093 blood/4967 sera was 99.2%/97.5% sensitive and 99.0%/99.7% specific. However, in clinical trial, FDA-cleared-predicate tests initially caused practical, costly problems due to false-positive-IgM results. For 58 persons, 3/43 seronegative and 2/15 chronically infected persons had false positive IgM predicate tests. This caused substantial anxiety, concerns, and required costly, delayed confirmation in reference centers. Absence of false positive ICT results contributes to solutions: Lyon and Paris France and USA Reference laboratories frequently receive sera with erroneously positive local laboratory IgM results impeding patient care. Therefore, thirty-two such sera referred to Lyon's Reference laboratory were ICT-tested. We collated these with other earlier/ongoing results: 132 of 137 USA or French persons had false-positive local laboratory IgM results identified correctly as negative by ICT. Five false positive ICT results in Tunisia and Marseille, France, emphasize need to confirm positive ICT results with Sabin-Feldman-Dye-test or western blot. Separate studies demonstrated high performance in detecting acute infections, meeting FDA, CLIA, WHO REASSURED, CEMark criteria and patient and physician satisfaction with monthly-gestational-ICT-screening. CONCLUSIONS/SIGNIFICANCE: This novel paradigm using ICT identifies likely false positives or raises suspicion that a result is truly positive, rapidly needing prompt follow up and treatment. Thus, ICT enables well-accepted gestational screening programs that facilitate rapid treatment saving lives, sight, cognition and motor function. This reduces anxiety, delays, work, and cost at point-of-care and clinical laboratories. TRIAL REGISTRATION: NCT04474132, https://clinicaltrials.gov/study/NCT04474132 ClinicalTrials.gov.

The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci.

Human diseases are traditionally studied as singular, independent entities, limiting researchers' capacity to view human illnesses as dependent states in a complex, homeostatic system. Here, using time-stamped clinical records of over 151 million unique Americans, we construct a disease representation as points in a continuous, high-dimensional space, where diseases with similar etiology and manifestations lie near one another. We use the UK Biobank cohort, with half a million participants, to perform a genome-wide association study of newly defined human quantitative traits reflecting individuals' health states, corresponding to patient positions in our disease space. We discover 116 genetic associations involving 108 genetic loci and then use ten disease constellations resulting from clustering analysis of diseases in the embedding space, as well as 30 common diseases, to demonstrate that these genetic associations can be used to robustly predict various morbidities.

A High-Fidelity Model to Predict Length-of-Stay in the Neonatal Intensive Care Unit (NICU).

Having an interpretable dynamic length-of-stay (LOS) model can help hospital administrators and clinicians make better decisions and improve the quality of care. The widespread implementation of electronic medical record (EMR) systems has enabled hospitals to collect massive amounts of health data. However, how to integrate this deluge of data into healthcare operations remains unclear. We propose a framework grounded in established clinical knowledge to model patients' lengths-of-stay. In particular, we impose expert knowledge when grouping raw clinical data into medically meaningful variables, which summarize patients' health trajectories. We use dynamic predictive models to output patients' remaining lengths-of-stay (RLOS), future discharges, and census probability distributions based on their health trajectories up to the current stay. Evaluated with large-scale EMR data, the dynamic model significantly improves predictive power over the performance of any model in previous literature and remains medically interpretable.

Building Programs to Eradicate Toxoplasmosis Part II: Education.

Purpose of Review: Review work to create and evaluate educational materials that could serve as a primary prevention strategy to help both providers and patients in Panama, Colombia, and the USA reduce disease burden of Toxoplasma infections. Recent Findings: Educational programs had not been evaluated for efficacy in Panama, USA, or Colombia. Summary: Educational programs for high school students, pregnant women, medical students and professionals, scientists, and lay personnel were created. In most settings, short-term effects were evaluated. In Panama, Colombia, and USA, all materials showed short-term utility in transmitting information to learners. These educational materials can serve as a component of larger public health programs to lower disease burden from congenital toxoplasmosis. Future priorities include conducting robust longitudinal studies of whether education correlates with reduced adverse disease outcomes, modifying educational materials as new information regarding region-specific risk factors is discovered, and ensuring materials are widely accessible.

Building Programs to Eradicate Toxoplasmosis Part I: Introduction and Overview.

Purpose of Review: Review building of programs to eliminate Toxoplasma infections. Recent Findings: Morbidity and mortality from toxoplasmosis led to programs in USA, Panama, and Colombia to facilitate understanding, treatment, prevention, and regional resources, incorporating student work. Summary: Studies foundational for building recent, regional approaches/programs are reviewed. Introduction provides an overview/review of programs in Panamá, the United States, and other countries. High prevalence/risk of exposure led to laws mandating testing in gestation, reporting, and development of broad-based teaching materials about Toxoplasma. These were tested for efficacy as learning tools for high-school students, pregnant women, medical students, physicians, scientists, public health officials and general public. Digitized, free, smart phone application effectively taught pregnant women about toxoplasmosis prevention. Perinatal infection care programs, identifying true regional risk factors, and point-of-care gestational screening facilitate prevention and care. When implemented fully across all demographics, such programs present opportunities to save lives, sight, and cognition with considerable spillover benefits for individuals and societies. Supplementary Information: The online version contains supplementary material available at 10.1007/s40124-022-00269-w.

Building Programs to Eradicate Toxoplasmosis Part IV: Understanding and Development of Public Health Strategies and Advances "Take a Village".

Purpose of Review: Review international efforts to build a global public health initiative focused on toxoplasmosis with spillover benefits to save lives, sight, cognition and motor function benefiting maternal and child health. Recent Findings: Multiple countries' efforts to eliminate toxoplasmosis demonstrate progress and context for this review and new work. Summary: Problems with potential solutions proposed include accessibility of accurate, inexpensive diagnostic testing, pre-natal screening and facilitating tools, missed and delayed neonatal diagnosis, restricted access, high costs, delays in obtaining medicines emergently, delayed insurance pre-approvals and high medicare copays taking considerable physician time and effort, harmful shortcuts being taken in methods to prepare medicines in settings where access is restricted, reluctance to perform ventriculoperitoneal shunts promptly when needed without recognition of potential benefit, access to resources for care, especially for marginalized populations, and limited use of recent advances in management of neurologic and retinal disease which can lead to good outcomes. Supplementary Information: The online version contains supplementary material available at 10.1007/s40124-022-00268-x.

Building Programs to Eradicate Toxoplasmosis Part III: Epidemiology and Risk Factors.

Purpose of Review: Review comprehensive data on rates of toxoplasmosis in Panama and Colombia. Recent Findings: Samples and data sets from Panama and Colombia, that facilitated estimates regarding seroprevalence of antibodies to Toxoplasma and risk factors, were reviewed. Summary: Screening maps, seroprevalence maps, and risk factor mathematical models were devised based on these data. Studies in Ciudad de Panamá estimated seroprevalence at between 22 and 44%. Consistent relationships were found between higher prevalence rates and factors such as poverty and proximity to water sources. Prenatal screening rates for anti-Toxoplasma antibodies were variable, despite existence of a screening law. Heat maps showed a correlation between proximity to bodies of water and overall Toxoplasma seroprevalence. Spatial epidemiological maps and mathematical models identify specific regions that could most benefit from comprehensive, preventive healthcare campaigns related to congenital toxoplasmosis and Toxoplasma infection.

NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding.

Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing biomedical documents. Over the last two decades1,2, the most dramatic advances in MR have followed in the wake of critical corpus development3. Large, well-annotated corpora have been associated with punctuated advances in MR methodology and automated knowledge extraction systems in the same way that ImageNet4 was fundamental for developing machine vision techniques. This study contributes six components to an advanced, named entity analysis tool for biomedicine: (a) a new, Named Entity Recognition Ontology (NERO) developed specifically for describing textual entities in biomedical texts, which accounts for diverse levels of ambiguity, bridging the scientific sublanguages of molecular biology, genetics, biochemistry, and medicine; (b) detailed guidelines for human experts annotating hundreds of named entity classes; (c) pictographs for all named entities, to simplify the burden of annotation for curators; (d) an original, annotated corpus comprising 35,865 sentences, which encapsulate 190,679 named entities and 43,438 events connecting two or more entities; (e) validated, off-the-shelf, named entity recognition (NER) automated extraction, and; (f) embedding models that demonstrate the promise of biomedical associations embedded within this corpus.

Classification of common human diseases derived from shared genetic and environmental determinants.

In this study, we used insurance claims for over one-third of the entire US population to create a subset of 128,989 families (481,657 unique individuals). We then used these data to (i) estimate the heritability and familial environmental patterns of 149 diseases and (ii) infer the genetic and environmental correlations for disease pairs from a set of 29 complex diseases. The majority (52 of 65) of our study's heritability estimates matched earlier reports, and 84 of our estimates appear to have been obtained for the first time. We used correlation matrices to compute environmental and genetic disease classifications and corresponding reliability measures. Among unexpected observations, we found that migraine, typically classified as a disease of the central nervous system, appeared to be most genetically similar to irritable bowel syndrome and most environmentally similar to cystitis and urethritis, all of which are inflammatory diseases.

Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants.

OBJECTIVE: Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. MATERIALS AND METHODS: An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. RESULTS: Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). DISCUSSION: The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein-protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). CONCLUSION: These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as 'unique personal variants'. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics.