Impact of Affordable Care Act Provisions on the Racial Makeup of Patients Enrolled at a Deep South, High-Risk Breast Cancer Clinic.

PURPOSE: Black women are less likely to receive screening mammograms, are more likely to develop breast cancer at an earlier age, and more likely to die from breast cancer when compared to White women. Affordable Care Act (ACA) provisions decreased cost sharing for women's preventive screening, potentially mitigating screening disparities. We examined enrollment of a high-risk screening program before and after ACA implementation stratified by race. METHODS: This retrospective, quasi-experimental study examined the ACA's impact on patient demographics at a high-risk breast cancer screening clinic from 02/28/2003 to 02/28/2019. Patient demographic data were abstracted from electronic medical records and descriptively compared in the pre- and post-ACA time periods. Interrupted time series (ITS) analysis using Poisson regression assessed yearly clinic enrollment rates by race using incidence rate ratios (IRR) and 95% confidence intervals (CI). RESULTS: Two thousand seven hundred and sixty-seven patients enrolled in the clinic. On average, patients were 46 years old (SD, ± 12), 82% were commercially insured, and 8% lived in a highly disadvantaged neighborhood. In ITS models accounting for trends over time, prior to ACA implementation, White patient enrollment was stable (IRR 1.01, 95% CI 1.00-1.02) while Black patient enrollment increased at 13% per year (IRR 1.13, 95% CI 1.05-1.22). Compared to the pre-ACA enrollment period, the post-ACA enrollment rate remained unchanged for White patients (IRR 0.99, 95% CI 0.97-1.01) but decreased by 17% per year for Black patients (IRR 0.83, 95% CI 0.74-0.92). CONCLUSION: Black patient enrollment decreased at a high-risk breast cancer screening clinic post-ACA compared to the pre-ACA period, indicating a need to identify factors contributing to racial disparities in clinic enrollment.

Data-driven Cluster Analysis Reveals Increased Risk for Severe Insulin-Deficient Diabetes in Black/African Americans.

CONTEXT: Diabetes is a heterogenic disease and distinct clusters have emerged, but the implications for diverse populations have remained understudied. OBJECTIVE: Apply cluster analysis to a diverse diabetes cohort in the U.S. Deep South. DESIGN: Retrospective hierarchical cluster analysis of electronic health records from 89,875 patients diagnosed with diabetes between January 1, 2010, and December 31, 2019, at the Kirklin Clinic of the University of Alabama at Birmingham, an ambulatory referral center. PATIENTS: Adult patients with ICD diabetes codes were selected based on available data for 6 established clustering parameters (GAD-autoantibody; HbA1c; BMI; Diagnosis age; HOMA2-B; HOMA2-IR); ∼42% were Black/African American. MAIN OUTCOME MEASURE(S): Diabetes subtypes and their associated characteristics in a diverse adult population based on clustering analysis. We hypothesized that racial background would affect the distribution of subtypes. Outcome and hypothesis were formulated prior to data collection. RESULTS: Diabetes cluster distribution was significantly different in Black/African Americans compared to Whites (P<0.001). Black/African Americans were more likely to have severe insulin deficient diabetes (SIDD) (OR 1.83, CI 1.36-2.45, P<0.001), associated with more serious metabolic perturbations and a higher risk for complications (OR 1.42, 95% CI 1.06-1.90, P=0.020). Surprisingly, Black/African Americans specifically had more severe impairment of beta cell function (HOMA2-B, C-peptide) (P<0.001), while not being more obese or insulin resistant. CONCLUSIONS: Racial background greatly influences diabetes cluster distribution and Black/African Americans are more frequently and more severely affected by SIDD. This may further help explain the disparity in outcomes and have implications for treatment choice.

Impact of Affordable Care Act provisions on the racial makeup of patients enrolled at a Deep South, high-risk breast cancer clinic.

Purpose: Black women are less likely to receive screening mammograms and are at a higher lifetime risk for developing breast cancer compared to their White counterparts. Affordable Care Act (ACA) provisions decreased cost sharing for women's preventive screening, potentially mitigating screening disparities. We examined enrollment of a high-risk screening program before and after ACA implementation stratified by race. Methods: This retrospective, quasi-experimental study examined the ACA's impact on patient demographics at a high-risk breast cancer screening clinic from 02/28/2003-02/28/2019. Patient demographic data were abstracted from electronic medical records and descriptively compared in the pre- and post-ACA time periods. Interrupted time series (ITS) analysis using Poisson regression assessed yearly clinic enrollment rates by race using incidence rate ratios (IRR) and 95% confidence intervals (CI). Results: 2,767 patients enrolled in the clinic. On average, patients were 46 years old (SD, ± 12), 82% were commercially insured, and 8% lived in a highly disadvantaged neighborhood. In ITS models accounting for trends over time, Prior to ACA implementation, White patient enrollment was stable (IRR 1.01, 95% CI 1.00-1.02) while Black patient enrollment increased at 13% per year (IRR 1.13, 95% CI 1.05-1.22). Compared to the pre-ACA enrollment period, the post-ACA enrollment rate remained unchanged for White patients (IRR 0.99, 95% CI 0.97-1.01) but decreased by 17% for Black patients (IRR 0.83, 95% CI 0.74-0.92). Conclusion: Black patient enrollment decreased at a high-risk breast cancer screening clinic post-ACA compared to the pre-ACA period, indicating a need to identify factors contributing to racial disparities in clinic enrollment.

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

A Primer in Precision Nephrology: Optimizing Outcomes in Kidney Health and Disease through Data-Driven Medicine.

This year marks the 63rd anniversary of the International Society of Nephrology, which signaled nephrology's emergence as a modern medical discipline. In this article, we briefly trace the course of nephrology's history to show a clear arc in its evolution-of increasing resolution in nephrological data-an arc that is converging with computational capabilities to enable precision nephrology. In general, precision medicine refers to tailoring treatment to the individual characteristics of patients. For an operational definition, this tailoring takes the form of an optimization, in which treatments are selected to maximize a patient's expected health with respect to all available data. Because modern health data are large and high resolution, this optimization process requires computational intervention, and it must be tuned to the contours of specific medical disciplines. An advantage of this operational definition for precision medicine is that it allows us to better understand what precision medicine means in the context of a specific medical discipline. The goal of this article was to demonstrate how to instantiate this definition of precision medicine for the field of nephrology. Correspondingly, the goal of precision nephrology was to answer two related questions: ( 1 ) How do we optimize kidney health with respect to all available data? and ( 2 ) How do we optimize general health with respect to kidney data?

Circulating SARS-CoV-2+ megakaryocytes are associated with severe viral infection in COVID-19.

Several independent lines of evidence suggest that megakaryocytes are dysfunctional in severe COVID-19. Herein, we characterized peripheral circulating megakaryocytes in a large cohort of inpatients with COVID-19 and correlated the subpopulation frequencies with clinical outcomes. Using peripheral blood, we show that megakaryocytes are increased in the systemic circulation in COVID-19, and we identify and validate S100A8/A9 as a defining marker of megakaryocyte dysfunction. We further reveal a subpopulation of S100A8/A9+ megakaryocytes that contain severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protein and RNA. Using flow cytometry of peripheral blood and in vitro studies on SARS-CoV-2-infected primary human megakaryocytes, we demonstrate that megakaryocytes can transfer viral antigens to emerging platelets. Mechanistically, we show that SARS-CoV-2-containing megakaryocytes are nuclear factor κB (NF-κB)-activated, via p65 and p52; express the NF-κB-mediated cytokines interleukin-6 (IL-6) and IL-1ß; and display high surface expression of Toll-like receptor 2 (TLR2) and TLR4, canonical drivers of NF-κB. In a cohort of 218 inpatients with COVID-19, we correlate frequencies of megakaryocyte subpopulations with clinical outcomes and show that SARS-CoV-2-containing megakaryocytes are a strong risk factor for mortality and multiorgan injury, including respiratory failure, mechanical ventilation, acute kidney injury, thrombotic events, and intensive care unit admission. Furthermore, we show that SARS-CoV-2+ megakaryocytes are present in lung and brain autopsy tissues from deceased donors who had COVID-19. To our knowledge, this study offers the first evidence implicating SARS-CoV-2+ peripheral megakaryocytes in severe disease and suggests that circulating megakaryocytes warrant investigation in inflammatory disorders beyond COVID-19.

The precision medicine process for treating rare disease using the artificial intelligence tool mediKanren.

There are over 6,000 different rare diseases estimated to impact 300 million people worldwide. As genetic testing becomes more common practice in the clinical setting, the number of rare disease diagnoses will continue to increase, resulting in the need for novel treatment options. Identifying treatments for these disorders is challenging due to a limited understanding of disease mechanisms, small cohort sizes, interindividual symptom variability, and little commercial incentive to develop new treatments. A promising avenue for treatment is drug repurposing, where FDA-approved drugs are repositioned as novel treatments. However, linking disease mechanisms to drug action can be extraordinarily difficult and requires a depth of knowledge across multiple fields, which is complicated by the rapid pace of biomedical knowledge discovery. To address these challenges, The Hugh Kaul Precision Medicine Institute developed an artificial intelligence tool, mediKanren, that leverages the mechanistic insight of genetic disorders to identify therapeutic options. Using knowledge graphs, mediKanren enables an efficient way to link all relevant literature and databases. This tool has allowed for a scalable process that has been used to help over 500 rare disease families. Here, we provide a description of our process, the advantages of mediKanren, and its impact on rare disease patients.

Why rare disease needs precision medicine-and precision medicine needs rare disease.

With one in ten suffering from one of 10,000 rare diseases, precision medicine opens a path toward identifying therapies for rare patients. Conversely, it is rare patients-through their collective experience and the knowledge captured in their genetics-who open the path toward identifying therapies for common patients.

Functional characterization and potential therapeutic avenues for variants in the NTRK2 gene causing developmental and epileptic encephalopathies.

Variants within the Neurotrophic Tyrosine Kinase Receptor Type 2 (NTRK2) gene have been discovered to play a role in developmental and epileptic encephalopathies, a group of debilitating conditions for which little is known about cause or treatment. Here, we determine the functional consequences of two variants: p.Tyr434Cys (Y434C) (located in the transmembrane domain) and p.Thr720Ile (T720I) (located in the catalytic domain). Wild-type and variant cDNAs were constructed and transfected into HEK293 cells. In cell culture, variant Y434C exhibited ligand-independent activation of tropomyosin-related kinase B (TRKB) signaling with an associated abnormal response to brain-derived neurotrophic factor (BDNF) stimulation and increased levels of phosphorylated extracellular signal-regulated kinase (ERK) and ETS like-1 protein (ELK1) activity. Expression of variant T720I resulted in decreased TRKB signaling with reduced mTor activity as determined by decreased levels of phosphorylated S6. With the deleterious mechanisms characterized, we utilized mediKanren (a novel artificial intelligence tool) to identify therapeutics to compensate for the pathological effects. Downregulation of TRKB through inhibition with mediKanren-predicted compound 1NM-PP1 led to decreased MEK activity. Upregulation of TRKB signaling by mediKanren-predicted valproic acid led to subsequent increase of mTor activity. Overall, our results provide further characterization of the pathogenicity of these two variants in the NTRK2 gene. Indeed, Y434C is the first patient-specific NTRK2 variant with demonstrated hypermorphic activity. Furthermore, we observed that variants Y434C and T720I result in distinct functional consequences that require distinct therapeutic strategies. These data suggest the possibility that unique mutations within different regions of the NTRK2 gene results in separate clinical presentations, representing distinct genetic disorders requiring unique therapeutics.

Water-soluble tocopherol derivatives inhibit SARS-CoV-2 RNA-dependent RNA polymerase.

The recent emergence of a novel coronavirus, SARS-CoV-2, has led to the global pandemic of the severe disease COVID-19 in humans. While efforts to quickly identify effective antiviral therapies have focused largely on repurposing existing drugs 1-4 , the current standard of care, remdesivir, remains the only authorized antiviral intervention of COVID-19 and provides only modest clinical benefits 5 . Here we show that water-soluble derivatives of α-tocopherol have potent antiviral activity and synergize with remdesivir as inhibitors of the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). Through an artificial-intelligence-driven in silico screen and in vitro viral inhibition assay, we identified D-α-tocopherol polyethylene glycol succinate (TPGS) as an effective antiviral against SARS-CoV-2 and ß-coronaviruses more broadly that also displays strong synergy with remdesivir. We subsequently determined that TPGS and other water-soluble derivatives of α-tocopherol inhibit the transcriptional activity of purified SARS-CoV-2 RdRp and identified affinity binding sites for these compounds within a conserved, hydrophobic interface between SARS-CoV-2 nonstructural protein 7 and nonstructural protein 8 that is functionally implicated in the assembly of the SARS-CoV-2 RdRp 6 . In summary, we conclude that solubilizing modifications to α-tocopherol allow it to interact with the SARS-CoV-2 RdRp, making it an effective antiviral molecule alone and even more so in combination with remdesivir. These findings are significant given that many tocopherol derivatives, including TPGS, are considered safe for humans, orally bioavailable, and dramatically enhance the activity of the only approved antiviral for SARS-CoV-2 infection 7-9 .

METFORMIN USE IS ASSOCIATED WITH REDUCED MORTALITY IN A DIVERSE POPULATION WITH COVID-19 AND DIABETES.

BACKGROUND: Coronavirus disease-2019 (COVID-19) is a growing pandemic with an increasing death toll that has been linked to various comorbidities as well as racial disparity. However, the specific characteristics of these at-risk populations are still not known and approaches to lower mortality are lacking. METHODS: We conducted a retrospective electronic health record data analysis of 25,326 subjects tested for COVID-19 between 2/25/20 and 6/22/20 at the University of Alabama at Birmingham Hospital, a tertiary health care center in the racially diverse Southern U.S. The primary outcome was mortality in COVID-19-positive subjects and the association with subject characteristics and comorbidities was analyzed using simple and multiple linear logistic regression. RESULTS: The odds ratio of contracting COVID-19 was disproportionately high in Blacks/African-Americans (OR 2.6; 95%CI 2.19-3.10; p<0.0001) and in subjects with obesity (OR 1.93; 95%CI 1.64-2.28; p<0.0001), hypertension (OR 2.46; 95%CI 2.07-2.93; p<0.0001), and diabetes (OR 2.11; 95%CI 1.78-2.48; p<0.0001). Diabetes was also associated with a dramatic increase in mortality (OR 3.62; 95%CI 2.11-6.2; p<0.0001) and emerged as an independent risk factor in this diverse population even after correcting for age, race, sex, obesity and hypertension. Interestingly, we found that metformin treatment was independently associated with a significant reduction in mortality in subjects with diabetes and COVID-19 (OR 0.33; 95%CI 0.13-0.84; p=0.0210). CONCLUSION: Thus, these results suggest that while diabetes is an independent risk factor for COVID-19-related mortality, this risk is dramatically reduced in subjects taking metformin, raising the possibility that metformin may provide a protective approach in this high risk population.

Metformin Use Is Associated With Reduced Mortality in a Diverse Population With COVID-19 and Diabetes.

Background: Coronavirus disease-2019 (COVID-19) is a growing pandemic with an increasing death toll that has been linked to various comorbidities as well as racial disparity. However, the specific characteristics of these at-risk populations are still not known and approaches to lower mortality are lacking. Methods: We conducted a retrospective electronic health record data analysis of 25,326 subjects tested for COVID-19 between 2/25/20 and 6/22/20 at the University of Alabama at Birmingham Hospital, a tertiary health care center in the racially diverse Southern U.S. The primary outcome was mortality in COVID-19-positive subjects and the association with subject characteristics and comorbidities was analyzed using simple and multiple linear logistic regression. Results: The odds ratio of contracting COVID-19 was disproportionately high in Blacks/African-Americans (OR 2.6; 95% CI 2.19-3.10; p<0.0001) and in subjects with obesity (OR 1.93; 95% CI 1.64-2.28; p<0.0001), hypertension (OR 2.46; 95% CI 2.07-2.93; p<0.0001), and diabetes (OR 2.11; 95% CI 1.78-2.48; p<0.0001). Diabetes was also associated with a dramatic increase in mortality (OR 3.62; 95% CI 2.11-6.2; p<0.0001) and emerged as an independent risk factor in this diverse population even after correcting for age, race, sex, obesity, and hypertension. Interestingly, we found that metformin treatment prior to diagnosis of COVID-19 was independently associated with a significant reduction in mortality in subjects with diabetes and COVID-19 (OR 0.33; 95% CI 0.13-0.84; p=0.0210). Conclusion: Thus, these results suggest that while diabetes is an independent risk factor for COVID-19-related mortality, this risk is dramatically reduced in subjects taking metformin prior to diagnosis of COVID-19, raising the possibility that metformin may provide a protective approach in this high risk population.

Allele-specific conditional destabilization of glutamine repeat mRNAs.

Several late-onset neurological diseases are caused by the inheritance of an expanded CAG repeat coding for polyglutamine. To date there is no effective means of halting the progression of these diseases, and their underlying molecular mechanisms remain a mystery. Strategies designed to specifically reduce the levels of long repeat mRNA might provide an effective therapy for these diseases. An emphasis on allele specificity is necessary to avoid the potential toxicities associated with reduction of expression. The experiments described here are based on the relationship between translation and mRNA stability and the idea that translation of a repeated codon might be extremely sensitive to reductions in levels of cognate aminoacylated tRNA. Consistent with this hypothesis, we have discovered that reduced glutamine concentration destabilizes mRNAs coding for long glutamine repeats while sparing short repeat versions of the same mRNAs. These results suggest therapy might be attained with existing compounds or environmental conditions known to decrease free glutamine levels.

Verification of somatic CAG repeat expansion by pre-PCR fractionation.

The inheritance of a long CAG repeat causes several late onset neurological disorders including Huntington's disease (HD). Longer CAG repeats correlate with earlier onset of HD suggesting an increased toxicity for the products of long repeat alleles. PCR based data has been used to show that HD CAG repeat expansion beyond the inherited length occurs in affected tissues indicating a possible role for somatic instability in the disease process. PCR, however, is prone to artifacts resulting from expansion of repeat sequences during amplification. We describe a method to distinguish between CAG repeat expansions that exist in vivo and those that potentially occur during PCR. The method involves size fractionation of genomic restriction fragments containing the expanded repeats followed by PCR amplification. The application of this method confirms the presence of somatic expansions in the brains of a knock-in mouse model of HD.

Hprt(CAG)146 mice: age of onset of behavioral abnormalities, time course of neuronal intranuclear inclusion accumulation, neurotransmitter marker alterations, mitochondrial function markers, and susceptibility to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine.

We reported previously a model of polyglutamine repeat disorders with insertion of 146 CAG repeats into the murine hypoxanthine phosphoribosyl transferase locus (Hprt(CAG)146; Ordway et al. [1997] Cell 91:753-763), which does not normally contain polyglutamine repeats. These mice develop an adult-onset neurologic phenotype of incoordination, involuntary limb clasping, seizures, and premature death. Histologic analysis demonstrates widespread ubiquinated neuronal intranuclear inclusions (NIIs). We now report characterization of the age of onset of behavioral abnormalities, correlated with the time course of occurrence of NIIs in several brain regions, and the occurrence of NIIs in non-neuronal tissues. Onset of behavioral abnormalities occurred at approximately 22 weeks of age. There was variable time course of expression of NIIs in several brain regions. Assessment of several non-neuronal tissues revealed nuclear inclusions in hepatocytes and choroid plexus epithelium. Gamma-aminobutyric acid (GABA)/benzodiazepine receptors, dopamine D1-like and D2-like receptors, and type 2 vesicular monoamine transporter (VMAT2) binding sites were assayed before and after the onset of behavioral abnormalities. GABA/benzodiazepine receptors were unchanged either before or after the onset of behavioral abnormalities in any region analyzed, whereas striatal D1-like and D2-like receptors were diminished after but not before the onset of symptoms. Dorsal striatal VMAT2 binding sites were decreased before the onset of behavioral changes. Mitochondrial electron transport chain components were assayed with histochemical methods before and after the onset of behavioral changes. There was no change in behaviorally presymptomatic or symptomatic animals. Hprt(CAG)146 mice did not exhibit increased susceptibility to the mitochondrial toxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. Hprt(CAG)146 mice are a useful model for studying polyglutamine repeat disorders.