Biology subjects

Gunter, C.

Publications and source records attributed to Gunter, C..

8 recordsLinked to original sources

bioRxiv2026

Psychometric Validation of the Education and Assessment of Genetic Literacy (EAGL) Measure

Genetic literacy is an integral measure for examining societys interaction with genetics, but widely-used "genetic literacy" measures lack both knowledge comprehension measures and psychometric validation. To address these issues, we validated the Education and Assessment of Genetic Literacy measure (EAGL) in a sample of 2708 US participants, using both exploratory and confirmatory factor analysis. In addition to standard subjective and objective knowledge subscales, our measures distinct knowledge comprehension subscale focuses on autism as an example of a complex condition. Regression analyses showed a statistically significant interaction when looking at education and personal connection to autism in relation to knowledge comprehension (F=3.68, p=0.003). Separately, those in our sample with a connection to autism scored higher on the subjective knowledge section (F=19.52, p<0.001) only, concurring with previous demonstrations of a subjective-objective knowledge gap in science literacy. We explored geographic location as one potential factor in genetic literacy and found that metropolitan vs non-metropolitan status had no significant main effects on overall levels. After the validation process, we have two multi-domain measures which accurately capture the construct of genetic literacy and are available for wide use: the multi-faceted EAGL-long, which has previously been tested in thousands of participants, or the validated three-factor EAGL-short.

genetics↗

bioRxiv2024

BioMapAI: Artificial Intelligence Multi-Omics Framework Modeling of Myalgic Encephalomyelitis / Chronic Fatigue Syndrome

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic illness with a multifactorial etiology and heterogeneous symptomatology, posing major challenges for diagnosis and treatment. Here, we present BioMapAI, a supervised deep neural network trained on a four-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data, and detailed clinical symptoms. By simultaneously modeling these diverse data types to predict clinical severity, BioMapAI identifies disease- and symptom-specific biomarkers and robustly classifies ME/CFS in both held-out and independent external cohorts. Using an explainable AI approach, we construct the first connectivity map spanning the microbiome, immune system, and plasma metabolome in health and ME/CFS, adjusted for age, gender, and additional clinical factors. This map uncovers disrupted associations between microbial metabolism (e.g., short-chain fatty acids, branched-chain amino acids, tryptophan, benzoate), plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, {gamma}{delta}T) secreting IFN{gamma} and GzA. Overall, BioMapAI provides unprecedented systems-level insights into ME/CFS, refining existing hypotheses and hypothesizing new pathways associated to the diseases heterogeneous symptoms.

bioinformatics↗

bioRxiv2024

Survey-Based Analysis of a Science of Science Communication Scientific Interest Group: Member Feedback and Perspectives on Science Communication

Coordinated attempts to promote systematic approaches to the design and evaluation of science communication efforts have generally lagged behind the proliferation and diversification of those efforts. To address this, we founded the US National Institutes of Health (NIH) Science of Science Communication Scientific Interest Group (SciOSciComm-SIG) and undertook a mixed-methods survey-based evaluation of the group one year after its founding. Respondents indicated ongoing interest and some participation in public-facing science communication while identifying specific barriers, and praised the role of the SIG in expanding access to information about evidence-based practices.

scientific communication and education↗

bioRxiv2022

Understanding changes in genetic literacy over time and in genetic research participants

As genomic and personalized medicine becomes mainstream, assessing and understanding the publics genetic literacy is paramount. Because genetic research drives innovation in this area and involves much of the public, it is equally important to assess its impact on genetic literacy. We designed a survey to assess genetic literacy in three ways (familiarity, knowledge, and skills) and distributed it to two distinct samples: 2050 members of the general population, and 2023 individuals currently enrolled in a large-scale genetic research study. We compared these data to a similar survey implemented in 2013. The results indicate that familiarity with basic genetic terms in 2021 (M = 5.36, p<.001) and knowledge of genetic concepts in 2021 (M = 9.06, p = 0.002) is significantly higher compared to 2013 (M = 5.08; M = 8.72). Those currently enrolled in a genetic study were also significantly more familiar with genetic terms (M = 5.79, p<.001), more knowledgeable of genetic concepts (M = 10.27, p<.001), and scored higher in skills (M = 3.57, p<.001) than the general population (M = 4.98; M = 9.06; M = 2.65).The results suggest that genetic literacy is improving over time, though there is room for improvement. The data also suggest that participating in genetic research is one avenue for improving genetic literacy. We conclude that educational interventions are needed to ensure familiarity with and comprehension of basic genetic concepts. We also suggest further exploration of the impact of genetic research participation on genetic literacy to determine mechanisms for potential interventions.

genetics↗

bioRxiv2021

Multi-omics of host-microbiome interactions in short- and long-term Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system, debilitating disability manifesting as severe fatigue and post-exertional malaise. The chronic dysfunctions in ME/CFS are increasingly recognized as significant health factors with potential parallels with long COVID. However, the etiology of ME/CFS remains elusive with limited high-resolution human studies. In addition, reliable biomarker-based diagnostics have not been well-established, but may assist in disease classification, particularly during different temporal phases of the disease. Here, we performed deep multi- omics (shotgun metagenomics of gut microbiota and plasma metabolomics) and clinical phenotyping of healthy controls (n=79) vs. two cohorts of ME/CFS patients - those with short-term disease (<4 years, n=75), and patients with long-term disease (>10y, n=79). Overall, ME/CFS was characterized by reduced gut microbiome diversity and richness with high heterogeneity, and depletion of sphingomyelins and short-chain fatty acids in the plasma. We found significant differences when stratifying by cohort; short-term ME/CFS was associated with more microbial dysbiosis, but long-term ME/CFS was associated with markedly more severe phenotypic and metabolic abnormalities. We identified a reduction in the gene-coding capacity (and relative abundance of butyrate producers) of microbial butyrate biosynthesis together with a reduction in the plasma concentration of butyrate, especially in the short-term group. Global co-association and detailed gene pathway correlation analyses linking the microbiome and metabolome identified additional potential biological mechanisms underlying host-microbiome interactions in ME/CFS, including bile acids and benzoate pathways. Finally, we built multiple state-of-the-art classifiers to identify microbes, microbial gene pathways, metabolites, and clinical features that individually or together, were most able to differentiate short or long-term MECFS, or MECFS vs. healthy controls. Taken together, our study presents the highest resolution, multi-cohort and multi- omics analysis to date, providing an important resource to facilitate mechanistic hypotheses of host-microbiome interactions in ME/CFS.

microbiology↗

bioRxiv2021

Participation in a Science Festival Promotes Inclusive Science Communication around Autism Spectrum Disorder

As a high prevalence disorder with limited information about etiology, autism spectrum disorder (ASD) has been marked by confusion and miscommunication around its causes and treatments. To promote high-quality science communication, we participated in a local science festival, both providing information about the brain and ASD and asking passersby questions about their knowledge of ASD. We then asked the booth staffers to evaluate the program and conducted qualitative analyses of public and staffer responses. Public responses to the question "what would you like to know about autism?" most often concerned how the disorder was diagnosed or defined. In contrast, public responses to the question "what would you like others to know about autism?" centered around educating those unaffected by ASD on how to improve interactions and awareness, mentioning inclusivity and intersectionality, and dispelling negative stereotypes. The staffers overwhelmingly reported that in future years, they would include even more science and allow for more in-depth conversations with interested parties, as well as bringing materials in other languages. These responses are in keeping with a trend for more inclusive science communication, particularly in the field of behavioral health and ASD, and a desire to challenge myths around the condition. We conclude that our science festival interactions brought multiple benefits to public and staff.

scientific communication and education↗

bioRxiv2020

Validation of the Social Responsiveness Scale (SRS) to screen for atypical social behaviors in juvenile macaques

Primates form strong social bonds and depend on social relationships and networks that provide shared resources and protection critical for survival. Social deficits such as those present in autism spectrum disorder (ASD) and other psychiatric disorders hinder the individual’s functioning in communities. Given that early diagnosis and intervention can improve outcomes and trajectories of ASD, there is a great need for tools to identify early markers for screening/diagnosis, and for translational animal models to uncover biological mechanisms and develop treatments. One of the most widely used screening tools for ASD in children is the Social Responsiveness Scale (SRS), a quantitative measure used to identify individuals with atypical social behaviors. The SRS has been adapted for use in adult rhesus monkeys (Macaca mulatta) –a species very close to humans in terms of social behavior, brain anatomy/connectivity and development– but has not yet been validated or adapted for a necessary downward extension to younger ages matching those for ASD diagnosis in children. The goal of the present study was to adapt and validate the adult macaque SRS (mSRS) in juvenile macaques with age equivalent to 4-6 yr old human children. Expert primate coders modified the mSRS to adapt it to rate atypical social behaviors in juvenile macaques living in complex social groups at the Yerkes National Primate Research Center. Construct and face validity of this juvenile mSRS (jmSRS) was determined based on well-established and operationalized measures of social and non-social behaviors in this species using traditional behavioral observations. We found that the jmSRS identifies variability in social responsiveness of juvenile rhesus monkeys and shows strong construct/predictive validity, as well as sensitivity to detect atypical social behaviors in young male and female macaques across social status. Thus, the jmSRS provides a promising tool for translational research on macaque models of children social disorders.View Full Text

animal behavior and cognition↗

bioRxiv2019

Perturbation of effector and regulatory T cell subsets in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disorder of unknown etiology, and diagnosis of the disease is largely based on clinical symptoms. We hypothesized that immunological disruption is the major driver of this disease and analyzed a large cohort of ME/CFS patient or control blood samples for differences in T cell subset frequencies and functions. We found that the ratio of CD4+ to CD8+ T cells and the proportion of CD8+ effector memory T cells were increased, whereas NK cells were reduced in ME/CFS patients younger than 50 years old compared to a healthy control group. Remarkably, major differences were observed in Th1, Th2, Th17 and mucosal-associated invariant T (MAIT) T cell subset functions across all ages of patients compared to healthy subjects. While CCR6+ Th17 cells in ME/CFS secreted less IL-17 compared to controls, their overall frequency was higher. Similarly, MAIT cells from patients secreted lower IFN{gamma}, GranzymeA and IL-17 upon activation. Together, these findings suggest chronic stimulation of these T cell populations in ME/CFS patients. In contrast, the frequency of regulatory T cells (Tregs), which control excessive immune activation, was higher in ME/CFS patients. Finally, using a machine learning algorithm called random forest, we determined that the set of T cell parameters analyzed could identify more than 90% of the subjects in the ME/CFS cohort as patients (93% true positive rate or sensitivity). In conclusion, these multiple and major perturbations or dysfunctions in T cell subsets in ME/CFS patients suggest potential chronic infections or microbiome dysbiosis. These findings also have implications for development of ME/CFS specific immune biomarkers and reveal potential targets for novel therapeutic interventions.

immunology↗