Rhode Island Research Articles

Rhode Island, Virginia pharmacists fight white bagging.

Rhode Island, Virginia pharmacists fight white bagging.

Learning health system linchpins: information exchange and a common data model.

To demonstrate the potential for a centrally managed health information exchange standardized to a common data model (HIE-CDM) to facilitate semantic data flow needed to support a learning health system (LHS). The Rhode Island Quality Institute operates the Rhode Island (RI) statewide HIE, which aggregates RI health data for more than half of the state's population from 47 data partners. We standardized HIE data to the Observational Medical Outcomes Partnership (OMOP) CDM. Atherosclerotic cardiovascular disease (ASCVD) risk and primary prevention practices were selected to demonstrate LHS semantic data flow from 2013 to 2023. We calculated longitudinal 10-year ASCVD risk on 62,999 individuals. Nearly two-thirds had ASCVD risk factors from more than one data partner. This enabled granular tracking of individual ASCVD risk, primary prevention (ie, statin therapy), and incident disease. The population was on statins for fewer than half of the guideline-recommended days. We also found that individuals receiving care at Federally Qualified Health Centers were more likely to have unfavorable ASCVD risk profiles and more likely to be on statins. CDM transformation reduced data heterogeneity through a unified health record that adheres to defined terminologies per OMOP domain. We demonstrated the potential for an HIE-CDM to enable observational population health research. We also showed how to leverage existing health information technology infrastructure and health data best practices to break down LHS barriers. HIE-CDM facilitates knowledge curation and health system intervention development at the individual, health system, and population levels.

Evaluation of sea surface temperature from ocean reanalysis products over the North Indian Ocean

Ocean and sea ice reanalyses (ORAs or ocean syntheses) are reconstructions of the ocean and sea ice states using an ocean model integration constrained by atmospheric surface forcing and ocean observations via a data assimilation method. Ocean reanalyses are a valuable tool for monitoring and understanding long-term ocean variability at depth, mainly because this part of the ocean is still largely unobserved. Sea surface temperature (SST) is the key variable that drives the air–sea interaction process on different time scales. Despite improvements in model and reanalysis schemes, ocean reanalyses show errors when evaluated with independent observations. The independent evaluation studies of SST from ocean reanalysis over the Indian Ocean are limited. In this study, we evaluated the SST from 10 reanalysis products (ECCO, BRAN, SODA, NCEP-GODAS, GODAS-MOM4p1, ORAS5, CGLORS, GLORYS2V4, GLOSEA, and GREP) and five synthetic observation products (COBE, ERSST, OISST, OSTIA, and HadISST) and from the pure observation-based product AMSR2 for 2012–2017 with 12 in-situ buoy observations (OMNI) over the Arabian Sea and Bay of Bengal. Even though the reanalysis and observational products perform very well in the open ocean, the performance is poorer near the coast and islands. The reanalysis products perform comparatively better than most of the observational products. COBE and OISST perform better among the synthetic observational products in the northern Indian Ocean. GODAS-MOM4p1 and GREP performs best among the reanalysis products, often surpassing the observational products. ECCO shows poorer performance and higher bias in the Bay of Bengal. Comparing the BRAN daily and monthly SST, the monthly SST performance of reanalysis is better than the daily time scale.

Abstract 4143250: Individualized Interactomes from Pulmonary Arterial Hypertension Biopsies Predict Therapeutic Response: an In Silico Clinical Study

Introduction: Pulmonary arterial hypertension (PAH) is a highly morbid cardiopulmonary disease characterized by substantial pathobiological and clinical heterogeneity, which is believed to underlie variable treatment-response observed in clinical trials and at point-of-care during real-world practice. Utilizing patient-specific pathogenetic information to inform drug selection for use in clinical practice is expected to improve clinical efficacy of PAH drugs, but such strategies are currently lacking. Methods: We conducted a retrospective analysis of 25 PAH patients (32 samples, receiving PAH therapies) undergoing right heart catheterization (RHC) for the routine clinical assessment of dyspnea at Rhode Island Hospital (Warren Alpert Medical School of Brown University) , along with 3 healthy controls. A minimally invasive "cell biopsy" approach was used to collect Pulmonary Arterial Endothelial Cells (PAECs) from the tips of pulmonary artery catheters. Transcriptomic RNA-seq was performed on mRNA isolated from cell passage 3 or 4 for all samples. We deployed an innovative network medicine method to construct sample-specific interactomes from the transcriptomic data and human protein-protein interactome. The individualized interactomes captured patient-specific molecular features, which could then be used to predict therapeutic response in PAH patients. Results: The individualized interactomes have a range of 5276 [4900, 7263] nodes and 7204 [6606, 12992] edges. We observed that an increase in 6MWD from baseline that was sustained at 12 months following treatment initiation was associated with higher fraction of drug targets in the individualized interactomes. By contrast, such a positive association was not observed in comparator drugs. Similarly, we observed a transition in BNP levels from elevated at baseline to within the normal range at 12 months that corresponded to an absolute decrease of ~250 pg/mL. Higher fraction of drug targets in the individualized interactomes was also associated with a significant improvement in REVEAL 2.0 Risk score at 6 months (p=0.004) and 12 months (p< 0.001). Conclusions: "Cell biopsies" taken at point-of-care for clinically indicated RHCs may be leveraged to predict therapeutic response and inform precision-based initiatives in pulmonary vascular disease through transcriptome-derived sample-specific interactomes and systems pharmacology tools.

An optimal transformation method for inferring ocean tracer sources and sinks

Abstract. The geography of changes in the fluxes of heat, carbon, freshwater and other tracers at the sea surface is highly uncertain and is critical to our understanding of climate change and its impacts. We present a state estimation framework wherein prior estimates of boundary fluxes can be adjusted to make them consistent with the evolving ocean state. In this framework, we define a discrete set of ocean water masses distinguished by their geographical, thermodynamic and chemical properties for specific time periods. Ocean circulation then moves these water masses in geographic space. In phase space, geographically adjacent water masses are able to mix together, representing a convergence, and air–sea property fluxes move the water masses over time. We define an optimisation problem whose solution is constrained by the physically permissible bounds of changes in ocean circulation, air–sea fluxes and mixing. As a proof-of-concept implementation, we use data from a historical numerical climate model simulation with a closed heat and salinity budget. An inverse model solution is found for the evolution of temperature and salinity that is consistent with “true” air–sea heat and freshwater fluxes which are introduced as model priors. When biases are introduced into the prior fluxes, the inverse model finds a solution closer to the true fluxes. This framework, which we call the optimal transformation method, represents a modular, relatively computationally cost-effective, open-source and transparent state estimation tool that complements existing approaches.

Dynamics of clustering rates in the rhode Island HIV-1 epidemic.

: Characterizing HIV clustering rates and their trends over time can improve understanding a local epidemic and enhance its control. Leveraging an academic-public health partnership in Rhode-Island, we explored longitudinal dynamics of statewide clustering rates among key populations from 1991 to 2023. Partial HIV-1 pol sequences were grouped by year of HIV-1 diagnosis. Molecular clusters were identified in cumulative annual phylogenies. Overall clustering rates, and clustering rates of newly-diagnosed and prevalent infections, and of specific socio-demographic characteristics of key populations over time were determined. Mann-Kendall statistics were used to estimate clustering rate trends and relationships among groups. By the end of 2023, 2,630 individuals with sequences represented the statewide epidemic in Rhode Island. Overall clustering rates increased from 7% in 1991 to 46% in 2023, correlating with cumulative sequence increase. Clustering rates of newly-diagnosed and prevalent infections significantly increased over time, higher in newly-diagnosed individuals since the early 2000 s. Increases were also observed among groups defined by gender, age, transmission risks, race, mental illness, HIV-1 subtypes, and country of birth, with some crossovers and divergence patterns over time. Exploring dynamics of HIV clustering rates over three decades in a statewide HIV-1 epidemic expanded its characterization and provided insight into its evolving changes. These dynamics may indicate a gradual shift towards a more concentrated and localized HIV-1 epidemic, highlighting important opportunities for targeted interventions to effectively prevent new HIV transmissions.

Burden of Kidney Disease in an Aging Population Living with HIV in the United States.

Antiretroviral therapy (ART) has significantly improved mortality rates for individuals living with HIV, but kidney disease remains prevalent, especially among older adults. Our study analyzed the burden of kidney disease in individuals aged 65 and older at The Miriam Hospital Immunology Center in Rhode Island. We calculated estimated glomerular filtration rates using the last creatinine values from 2019 and identified chronic kidney disease (CKD) stages. Results showed a 19% prevalence of moderate or severe CKD among adults living with HIV, rising to 39% for those aged 75 and older. Particularly striking was the increased prevalence among African American adults aged 65+, at 30.4%, rising to 50% for those over 75. In comparison, the National Institute of Diabetes and Digestive and Kidney Diseases reports that CKD stage 3 affects 20.1% of adults aged 65+, compared with just 1.2% in those younger than 65. Gender and racial disparities are evident; CKD stage 3 is more prevalent in females (5.8%) than males (4.4%). Our findings indicate that 32% of HIV-positive females have moderate-to-severe kidney disease, compared with 14% of males. Importantly, we did not account for hypertension, diabetes, and hepatitis C virus infection, which may influence renal outcomes. Our study shows that ART has reduced mortality, as more people with HIV now live longer, while also revealing the disproportionate burden of kidney disease among older adults and racial minorities, as well as a concerning trend among women; therefore, emphasizing the need for targeted health care strategies for high-risk groups.

Randomised clinical trial of a 16 mg vs 24 mg maintenance daily dose of buprenorphine to increase retention in treatment among people with an opioid use disorder in Rhode Island: study protocol paper

IntroductionBuprenorphine is a highly effective treatment for opioid use disorder (OUD). However, provider observations and preliminary research suggest that the current standard maintenance dose may be insufficient for suppressing withdrawal...

Child and adolescent behavioral health in the juvenile legal system: Inside the walls and beyond

Jason, a 15‐year‐old adolescent, was recently adjudicated and placed at the Rhode Island Training School (RITS), the state's only secure carceral facility for detained and adjudicated youth. Like many of the youth entering the facility, Jason arrived at the RITS with a complex history of trauma, substance use, and behavioral issues. As a child, his father was incarcerated and his mother struggled with substance use, leaving Jason without a consistent caregiver. His early life was marked by frequent moves between foster homes, unstable housing, and exposure to violence. This instability in his childhood led to feelings of anger and frustration, which often manifested in school through defiant behavior, truancy, and eventually, physical altercations that led to his involvement with the juvenile legal system.

Future directions for deep ocean climate science and evidence-based decision making

IntroductionA defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view.MethodsHere we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts.ResultsHalf of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results.DiscussionKey areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key “known unknowns” includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system.

Impacts of Langmuir turbulence derived from a statistical wave model on the oceanic mean state in the North Atlantic

Impacts of Langmuir turbulence derived from a statistical wave model on the oceanic mean state in the North Atlantic

Connections and choice for high schoolers

Chronic absenteeism is a symptom of a lack of student engagement. Many students feel that schools are not welcoming places and that what they learn in the classroom is not applicable in the real world. Schools like Metropolitan Regional Career and Technical Center (the Met) in Rhode Island offer an alternative to educating high school students that taps into their need for connection to adults and the world outside the classroom. The Met is the first school founded by Big Picture Learning, which has grown into a network of public schools across the country and internationally. Its interest-based learning approach gives students opportunities to explore internships and projects based on their interests and passions. The students devote two days a week to internships during the school year.

Modeling nonstationary surface‐level ozone extremes through the lens of US air quality standards: A Bayesian hierarchical approach

AbstractSurface‐level ozone (O) is a harmful air pollutant whose effects may be more deleterious when at its most extreme levels. Current US air quality standards are written in terms of the 3‐year average of the 4th highest annual daily maximum 8‐h O values; therefore, developing approaches based on extreme value theory may be useful. We develop a Bayesian hierarchical approach, where the ‐largest order statistics are parametrized by the generalized extreme value (GEV) distribution, while a Gaussian process is employed to characterize how the GEV parameters depend on the O precursors, namely nitrous oxides (NO) and volatile organic compounds (VOCs). The fitted model is then used to characterize the upper tail of the distribution of O and estimate O noncompliance probabilities. We illustrate the proposed method using data from an air quality station in Providence, Rhode Island (RI). The results suggest that the far upper tail of extreme O values is likely bounded, and the dependence of the upper tail distribution on NO and O is highly nonlinear, consistent with the known relationship, albeit not specifically for extreme values, in the existing scientific literature. A convolution‐based approach is used to estimate noncompliance probabilities for several covariate scenarios. Our results indicate that estimated noncompliance probabilities in recent years are much lower than in the mid‐1990s, primarily due to lower O precursor levels. However, the estimated noncompliance probabilities appear to rise sharply for hypothetical stricter O standards, even for the conditions observed in recent years.

Identification of quantitative trait locus and positional candidate loci influencing chicken egg quality under tropical conditions.

Egg quality is a vital factor in the poultry industry. High-quality eggs not only meet consumer expectations for appearance, taste, and nutritional value but also have high marketability, profitability, and consumer satisfaction. Accordingly, we executed our research with the purpose of determining chromosomal regions and genetic markers associated with egg quality in an F2 cross-bred chicken population under tropical conditions; we determined these through a genome-wide association study and quantitative trait locus (QTL) mapping. This population was created by cross-breeding the L2 line of Taiwan Country chickens, which is adapted to local conditions in Taiwan, with an experimental line (R-line) of Rhode Island Red layer chickens, which was developed by the French National Research Institute for Agriculture, Food and the Environment. A 60K single nucleotide polymorphism (SNP) genotyping array for chickens was employed to execute the analysis. Our analysis revealed 40 QTLs associated with egg quality under tropical conditions, namely 20 QTLs with genome-wide statistical significance and 20 QTLs with chromosome-wide statistical significance. Furthermore, we identified 93 SNPs exerting discernible effects on egg quality, with 10 of these effects exhibiting genome-wide significance and 83 exhibiting potential significance. The majority of the detected QTL regions and SNPs agreed with those identified as having an association with egg quality or production traits in previous studies, thus supporting the interrelationships determined between the studied characteristics. The findings of this study enhance the understanding regarding the genetic regulation governing chicken egg quality, thereby serving as a valuable reference for future functional investigations.

Early, Individualized Recommendations for Hospitalized Patients With Acute Kidney Injury

Acute kidney injury (AKI) is a common complication during hospitalization and is associated with adverse outcomes. To evaluate whether diagnostic and therapeutic recommendations sent by a kidney action team through the electronic health record improve outcomes among patients hospitalized with AKI compared with usual care. Randomized clinical trial conducted at 7 hospitals in 2 health systems: in New Haven, Bridgeport, New London, and Waterbury, Connecticut, and Westerly, Rhode Island; and in Baltimore, Maryland. Hospitalized patients with AKI were randomized between October 29, 2021, and February 8, 2024. Final follow-up occurred February 22, 2024. An alert about AKI was sent to the kidney action team, consisting of a study physician and study pharmacist, which sent personalized recommendations through the electronic health record in 5 major categories (diagnostic testing, volume, potassium, acid base, and medications) within 1 hour of AKI detection. The note was immediately visible to anyone with access to the electronic health record. Randomization to the intervention or usual care occurred after the recommendations were generated, but the note was only delivered to clinicians of patients randomized to the intervention group. The primary outcome was a composite outcome consisting of AKI progression to a higher stage of AKI, dialysis, or mortality occurring while the patient remained hospitalized and within 14 days from randomization. Of the 4003 patients randomized (median age, 72 years [IQR, 61-81 years), 1874 (47%) were female and 931 (23%) were Black patients. The kidney action team made 14 539 recommendations, with a median of 3 (IQR, 2-5) per patient. The primary outcome occurred in 19.8% of the intervention group and in 18.4% in the usual care group (difference, 1.4%, 95% CI, -1.1% to 3.8,% P = .28). Of 6 secondary outcomes, only 1 secondary outcome, rates of recommendation implementation, significantly differed between the 2 groups: 2459 of 7270 recommendations (33.8%) were implemented in the intervention group and 1766 of 7269 undelivered recommendations (24.3%) were implemented in the usual care group within 24 hours (difference, 9.5%; 95% CI, 8.1% to 11.0%). Among patients hospitalized with AKI, recommendations from a kidney action team did not significantly reduce the composite outcome of worsening AKI stage, dialysis, or mortality, despite a higher rate of recommendation implementation in the intervention group than in the usual care group. ClinicalTrials.gov Identifier: NCT04040296.

Results of a randomized controlled superiority trial of the effect of modified collaborative assessment vs. standard assessment on patients’ readiness for psychotherapy (CO-ASSM-RCT)

BackgroundAvoidant personality disorder (AvPD) and social phobia (SP) are associated with high personal and societal costs. While psychotherapy can be efficient, many patients drop out during treatment. Little is known about what can be done to increase a patient’s readiness for psychotherapy. However, research highlights the fields of collaborative and therapeutic assessment as a possible means to enhance readiness for psychotherapy.MethodsWe conducted a randomized controlled feasibility and superiority trial on patients with SP or AvPD who were to initiate psychotherapeutic treatment in outpatient mental health services. Patients were randomized 1:1 to either assessment as usual or modified collaborative assessment (MCA), provided as a pre-treatment intervention before psychotherapy initiation. MCA included the collaborative administration of a battery of psychological tests designed to assess the patient’s psychopathology more systematically. The tests were administered in collaboration with the patient, and detailed oral and written feedback was provided. We investigated the feasibility of the MCA intervention regarding acceptability, patient satisfaction, and adherence. We also investigated MCA’s effect on readiness for psychotherapy, as assessed with the University of Rhode Island Change Assessment Scale (URICA), and outcomes relating to symptomatology and dropout rates.ResultsAll three prespecified feasibility outcomes were met. At the end of treatment, no significant difference was observed in any other outcome, except client satisfaction, which favored MCA (− 7.42 (95% CI − 11.75; − 3.09; p = 0.002)).DiscussionWe found that MCA was feasible, and patients were highly satisfied with the intervention. It is relevant to investigate another implementation of MCA.Trial registrationClinicalTrials.gov NCT05018312. Registered on August 24, 2021.

Assessing impacts of observations on ocean circulation models with examples from coastal, shelf, and marginal seas

Ocean observing systems in coastal, shelf and marginal seas collect diverse oceanographic information supporting a wide range of socioeconomic needs, but observations are necessarily sparse in space and/or time due to practical limitations. Ocean analysis and forecast systems capitalize on such observations, producing data-constrained, four-dimensional oceanographic fields. Here we review efforts to quantify the impact of ocean observations, observing platforms, and networks of platforms on model products of the physical ocean state in coastal regions. Quantitative assessment must consider a variety of issues including observation operators that sample models, error of representativeness, and correlated uncertainty in observations. Observing System Experiments, Observing System Simulation Experiments, representer functions and array modes, observation impacts, and algorithms based on artificial intelligence all offer methods to evaluate data-based model performance improvements according to metrics that characterize oceanographic features of local interest. Applications from globally distributed coastal ocean modeling systems document broad adoption of quantitative methods, generally meaningful reductions in model-data discrepancies from observation assimilation, and support for assimilation of complementary data sets, including subsurface in situ observation platforms, across diverse coastal environments.

Identifying Barriers to Implementing Complementary and Integrative Health Therapies in Rhode Island Health Care Systems: A Qualitative Approach.

Introduction: Complementary and integrative health (CIH) therapies are widely used and make up billions of dollars in out-of-pocket expenditures. This quality improvement project aimed to identify stakeholders' perceptions of implementing CIH therapies in health care systems to examine the barriers and facilitators to CIH implementation in Rhode Island (RI). Methods: A qualitative approach guided by the Consolidated Framework for Implementation Research (CFIR) was used to conduct interviews with key stakeholder groups: health care administrators, health insurance administrators, physicians, and CIH practitioners. Interviews were analyzed by directed content analysis of transcripts with CFIR as the a priori coding framework. Results: Eleven subconstructs within four major domains were most prominent in interviews across all stakeholder groups. Key barriers in the "innovation" domain include a perceived lack of evidence and credibility of CIH therapies, logistical and administrative complexity of implementation, high costs to patients, and little financial incentive for hospitals and insurance companies. The "outer setting" domain highlights the utility of market pressure in decision making to implement CIH and the role of health policy. The "inner setting" domain demonstrates the varied personal beliefs about CIH, credentialing challenges, and the dissonance between medical system priorities and patient needs. Positive facilitation of implementation is marked by personal exposure to CIH and provider satisfaction in the "implementation process" domain. Conclusion: CIH therapies offer the medical system low risk and effective interventions that meet patient needs not currently met by Western medicine. However, implementation is difficult due to poor perception of evidence and lack of financial gain for the medical system. Acupuncture and massage may be modalities better situated for implementation in the RI medical system. Further education, awareness, and advocacy for CIH therapies would help meet patients' needs for CIH availability.

Reconstructing the Ocean State Using Argo Data and a Data-Driven Method

Abstract Over the past two decades, Argo profiles have provided unprecedented insight into the global patterns of space and time variability of ocean temperature and salinity, significantly reducing associated uncertainties. However, analyzing such assessments during the pre-Argo period remains challenging due to the scarcity of observations in many regions. From the Argo period, a set of dominant three-dimensional patterns can be estimated using Empirical Orthogonal Function (EOF) analysis, which helps to fill in observational gaps. From the associated principal components, temporal fluctuations can be observed, aiming to build a catalog of possible ocean state trajectories. To map pre-Argo observations, EOFs are used in a data assimilation framework that uses this catalog to feed an analog prediction and provide reanalysis. In this study, a new data-driven interpolation method called RedAnDA (Reduced-space Analog Data Assimilation) was tested in the tropical Pacific Ocean. RedAnDA was first validated through an Observing System Simulation Experiment (OSSE) approach, using synthetic observations extracted from a model simulation. It was subsequently applied to a real historical dataset and compared with other available reanalysis products. Overall, the reconstructed temperature field showed variability consistent with the OSSE true field and other reanalysis products in the real data application. Further improvements are needed to optimally estimate uncertainty, but RedAnDA already combines valuable information about state predictability, observational sampling, and unresolved scale issues.

Analysis of Mannose-Binding Lectin Protein and mRNA Levels on Selected Chicken Breeds in South Africa.

Mannose-binding lectin (MBL) is a key component of the innate immune system that plays a crucial role in binding to the microbial sugar surface to recognize and eliminate pathogens by activating the complement system. To detect and quantify the MBL protein concentration and chicken MBL expression in selected chicken breeds in South Africa. Forty-five blood samples from three indigenous chicken breeds, Ovambo (OV=9), Venda (VD=9) and Potchefstroom Koekoek (PK=9), and two exotic chicken breeds, Rhode Island Red (RIR=9) and Lohmann Brown (LB=9), were used for MBL protein concentration using enzyme-linked immunosorbent assay (ELISA) techniques. Also 20 liver samples from symptomatic two indigenous chicken breeds, OV (5) and PK (5), and two exotic chicken breeds, RIR (5) and LB (5), were used for MBL expression using quantitative polymerase chain reaction (qPCR) techniques. A general linear model was done using Tukey's multiple comparison post hoc test. The findings revealed MBL protein concentration from 5.26 to 18.56µg/mL. The LB breed had the lowest mean 6.40±0.80µg/mL, whereas the PK breed had the highest mean MBL concentration of 17.70±0.24µg/mL of MBL protein concentration. At 12, 25 and 35 weeks, the MBL proteins of OV, VD, PK, RIR and LB varied significantly at p≤0.05. The mRNA MBL expression of OV and LB breeds showed a 1-fold decrease in MBL expression, while RIR showed a 2-fold increase in MBL expression, and the PK showed more than a 3-fold increase in MBL expression relative to the control. The least-squares means for OV, LB, PK and RIR mRNA MBL expression were 0.54±0.19, 0.68±0.30, 4.46±2.76 and 2.89±0.19µg/mL, respectively. MBL protein was detected and quantified with distinct differences in concentration and expression levels at the presence of mycoplasma gallisepticum among the sampled South African chicken breeds. This highlights the genetic diversity of MBL as a tool for disease prevention in South African chicken breeds.