Are we prepared to deliver gene-targeted therapies for rare diseases?

The cost and time needed to conduct whole-genome sequencing (WGS) have decreased significantly in the last 20 years. At the same time, the number of conditions with a known molecular basis has steadily increased, as has the number of investigational new drug applications for novel gene-based therapeutics. The prospect of precision gene-targeted therapy for all seems in reach… or is it? Here we consider practical and strategic considerations that need to be addressed to establish a foundation for the early, effective, and equitable delivery of these treatments.

Medical and psychosocial outcomes of state-funded population genomic screening.

As the uptake of population screening expands, assessment of medical and psychosocial outcomes is needed. Through the Alabama Genomic Health Initiative (AGHI), a state-funded genomic research program, individuals received screening for pathogenic or likely pathogenic variants in 59 actionable genes via genotyping. Of the 3874 eligible participants that received screening results, 858 (22%) responded to an outcomes survey. The most commonly reported motivation for seeking testing through AGHI was contribution to genetic research (64%). Participants with positive results reported a higher median number of planned actions (median = 5) due to AGHI results as compared to negative results (median = 3). Interviews were conducted with survey participants with positive screening results. As determined by certified genetic counselors, 50% of interviewees took appropriate medical action based on their result. There were no negative or harmful actions taken. These findings indicate population genomic screening of an unselected adult population is feasible, is not harmful, and may have positive outcomes on participants now and in the future; however, further research is needed in order to assess clinical utility.

COVID-19 bacteremic co-infection is a major risk factor for mortality, ICU admission, and mechanical ventilation.

BACKGROUND: Recent single-center reports have suggested that community-acquired bacteremic co-infection in the context of Coronavirus disease 2019 (COVID-19) may be an important driver of mortality; however, these reports have not been validated with a multicenter, demographically diverse, cohort study with data spanning the pandemic. METHODS: In this multicenter, retrospective cohort study, inpatient encounters were assessed for COVID-19 with community-acquired bacteremic co-infection using 48-h post-admission blood cultures and grouped by: (1) confirmed co-infection [recovery of bacterial pathogen], (2) suspected co-infection [negative culture with ≥ 2 antimicrobials administered], and (3) no evidence of co-infection [no culture]. The primary outcomes were in-hospital mortality, ICU admission, and mechanical ventilation. COVID-19 bacterial co-infection risk factors and impact on primary outcomes were determined using multivariate logistic regressions and expressed as adjusted odds ratios with 95% confidence intervals (Cohort, OR 95% CI, Wald test p value). RESULTS: The studied cohorts included 13,781 COVID-19 inpatient encounters from 2020 to 2022 in the University of Alabama at Birmingham (UAB, n = 4075) and Ochsner Louisiana State University Health-Shreveport (OLHS, n = 9706) cohorts with confirmed (2.5%), suspected (46%), or no community-acquired bacterial co-infection (51.5%) and a comparison cohort consisting of 99,170 inpatient encounters from 2010 to 2019 (UAB pre-COVID-19 pandemic cohort). Significantly increased likelihood of COVID-19 bacterial co-infection was observed in patients with elevated ≥ 15 neutrophil-to-lymphocyte ratio (UAB: 1.95 [1.21-3.07]; OLHS: 3.65 [2.66-5.05], p < 0.001 for both) within 48-h of hospital admission. Bacterial co-infection was found to confer the greatest increased risk for in-hospital mortality (UAB: 3.07 [2.42-5.46]; OLHS: 4.05 [2.29-6.97], p < 0.001 for both), ICU admission (UAB: 4.47 [2.87-7.09], OLHS: 2.65 [2.00-3.48], p < 0.001 for both), and mechanical ventilation (UAB: 3.84 [2.21-6.12]; OLHS: 2.75 [1.87-3.92], p < 0.001 for both) across both cohorts, as compared to other risk factors for severe disease. Observed mortality in COVID-19 bacterial co-infection (24%) dramatically exceeds the mortality rate associated with community-acquired bacteremia in pre-COVID-19 pandemic inpatients (5.9%) and was consistent across alpha, delta, and omicron SARS-CoV-2 variants. CONCLUSIONS: Elevated neutrophil-to-lymphocyte ratio is a prognostic indicator of COVID-19 bacterial co-infection within 48-h of admission. Community-acquired bacterial co-infection, as defined by blood culture-positive results, confers greater increased risk of in-hospital mortality, ICU admission, and mechanical ventilation than previously described risk factors (advanced age, select comorbidities, male sex) for COVID-19 mortality, and is independent of SARS-CoV-2 variant.

Cardioinformatics: the nexus of bioinformatics and precision cardiology.

Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17 million deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, most bioinformatics and computational biology research and funding to date has been concentrated predominantly on cancer research, with a relatively modest footprint in CVD. In this paper, we review the existing literary landscape and critically assess the unmet need to further develop an emerging field at the multidisciplinary interface of bioinformatics and precision cardiovascular medicine, which we refer to as 'cardioinformatics'.

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.

A state-based approach to genomics for rare disease and population screening.

PURPOSE: The Alabama Genomic Health Initiative (AGHI) is a state-funded effort to provide genomic testing. AGHI engages two distinct cohorts across the state of Alabama. One cohort includes children and adults with undiagnosed rare disease; a second includes an unselected adult population. Here we describe findings from the first 176 rare disease and 5369 population cohort AGHI participants. METHODS: AGHI participants enroll in one of two arms of a research protocol that provides access to genomic testing results and biobank participation. Rare disease cohort participants receive genome sequencing to identify primary and secondary findings. Population cohort participants receive genotyping to identify pathogenic and likely pathogenic variants for actionable conditions. RESULTS: Within the rare disease cohort, genome sequencing identified likely pathogenic or pathogenic variation in 20% of affected individuals. Within the population cohort, 1.5% of individuals received a positive genotyping result. The rate of genotyping results corroborated by reported personal or family history varied by gene. CONCLUSIONS: AGHI demonstrates the ability to provide useful health information in two contexts: rare undiagnosed disease and population screening. This utility should motivate continued exploration of ways in which emerging genomic technologies might benefit broad populations.

Transcriptome and functional analysis in a Drosophila model of NGLY1 deficiency provides insight into therapeutic approaches.

Autosomal recessive loss-of-function mutations in N-glycanase 1 (NGLY1) cause NGLY1 deficiency, the only known human disease of deglycosylation. Patients present with developmental delay, movement disorder, seizures, liver dysfunction and alacrima. NGLY1 is a conserved cytoplasmic component of the Endoplasmic Reticulum Associated Degradation (ERAD) pathway. ERAD clears misfolded proteins from the ER lumen. However, it is unclear how loss of NGLY1 function impacts ERAD and other cellular processes and results in the constellation of problems associated with NGLY1 deficiency. To understand how loss of NGLY1 contributes to disease, we developed a Drosophila model of NGLY1 deficiency. Loss of NGLY1 function resulted in developmental delay and lethality. We used RNAseq to determine which processes are misregulated in the absence of NGLY1. Transcriptome analysis showed no evidence of ER stress upon NGLY1 knockdown. However, loss of NGLY1 resulted in a strong signature of NRF1 dysfunction among downregulated genes, as evidenced by an enrichment of genes encoding proteasome components and proteins involved in oxidation-reduction. A number of transcriptome changes also suggested potential therapeutic interventions, including dysregulation of GlcNAc synthesis and upregulation of the heat shock response. We show that increasing the function of both pathways rescues lethality. Together, transcriptome analysis in a Drosophila model of NGLY1 deficiency provides insight into potential therapeutic approaches.

anexVis: visual analytics framework for analysis of RNA expression.

Summary: Although RNA expression data are accumulating at a remarkable speed, gaining insights from them still requires laborious analyses, which hinder many biological and biomedical researchers. This report introduces a visual analytics framework that applies several well-known visualization techniques to leverage understanding of an RNA expression dataset. Our analyses on glycosaminoglycan-related genes have demonstrated the broad application of this tool, anexVis (analysis of RNA expression), to advance the understanding of tissue-specific glycosaminoglycan regulation and functions, and potentially other biological pathways. Availability and implementation: The application is accessible at https://anexvis.chpc.utah.edu/, source codes deposited on GitHub. Supplementary information: Supplementary data are available at Bioinformatics online.

A comprehensive approach to identifying repurposed drugs to treat SCN8A epilepsy.

OBJECTIVE: Many previous studies of drug repurposing have relied on literature review followed by evaluation of a limited number of candidate compounds. Here, we demonstrate the feasibility of a more comprehensive approach using high-throughput screening to identify inhibitors of a gain-of-function mutation in the SCN8A gene associated with severe pediatric epilepsy. METHODS: We developed cellular models expressing wild-type or an R1872Q mutation in the Nav 1.6 sodium channel encoded by SCN8A. Voltage clamp experiments in HEK-293 cells expressing the SCN8A R1872Q mutation demonstrated a leftward shift in sodium channel activation as well as delayed inactivation; both changes are consistent with a gain-of-function mutation. We next developed a fluorescence-based, sodium flux assay and used it to assess an extensive library of approved drugs, including a panel of antiepileptic drugs, for inhibitory activity in the mutated cell line. Lead candidates were evaluated in follow-on studies to generate concentration-response curves for inhibiting sodium influx. Select compounds of clinical interest were evaluated by electrophysiology to further characterize drug effects on wild-type and mutant sodium channel functions. RESULTS: The screen identified 90 drugs that significantly inhibited sodium influx in the R1872Q cell line. Four drugs of potential clinical interest-amitriptyline, carvedilol, nilvadipine, and carbamazepine-were further investigated and demonstrated concentration-dependent inhibition of sodium channel currents. SIGNIFICANCE: A comprehensive drug repurposing screen identified potential new candidates for the treatment of epilepsy caused by the R1872Q mutation in the SCN8A gene.

Repurposing of Proton Pump Inhibitors as first identified small molecule inhibitors of endo-ß-N-acetylglucosaminidase (ENGase) for the treatment of NGLY1 deficiency, a rare genetic disease.

N-Glycanase deficiency, or NGLY1 deficiency, is an extremely rare human genetic disease. N-Glycanase, encoded by the gene NGLY1, is an important enzyme involved in protein deglycosylation of misfolded proteins. Deglycosylation of misfolded proteins precedes the endoplasmic reticulum (ER)-associated degradation (ERAD) process. NGLY1 patients produce little or no N-glycanase (Ngly1), and the symptoms include global developmental delay, frequent seizures, complex hyperkinetic movement disorder, difficulty in swallowing/aspiration, liver dysfunction, and a lack of tears. Unfortunately, there has not been any therapeutic option available for this rare disease so far. Recently, a proposed molecular mechanism for NGLY1 deficiency suggested that endo-ß-N-acetylglucosaminidase (ENGase) inhibitors may be promising therapeutics for NGLY1 patients. Herein, we performed structure-based virtual screening utilizing FDA-approved drug database on this ENGase target to enable repurposing of existing drugs. Several Proton Pump Inhibitors (PPIs), a series of substituted 1H-benzo [d] imidazole, and 1H-imidazo [4,5-b] pyridines, among other scaffolds, have been identified as potent ENGase inhibitors. An electrophoretic mobility shift assay was employed to assess the inhibition of ENGase activity by these PPIs. Our efforts led to the discovery of Rabeprazole Sodium as the most promising hit with an IC50 of 4.47±0.44µM. This is the first report that describes the discovery of small molecule ENGase inhibitors, which can potentially be used for the treatment of human NGLY1 deficiency.

What happens when N = 1 and you want plus 1?

We present a personal case study of what happens when a family has a child with an undiagnosed genetic disorder yet wishes to have more children free of the disease. After an intractable diagnostic odyssey for our oldest son, our family turned to exome sequencing. Exome sequencing found likely pathogenic variants of uncertain significance in the gene NGLY1. We used social media to uncover more cases for the newly discovered disorder and confirm the diagnosis in the process. With a diagnosis, we then explored and experienced a broad range of options for conceiving a child free of the disorder. Our success in having another child free of the disorder created a pathway for other families in our newly discovered disease community to do the same. © 2016 John Wiley & Sons, Ltd.

Participant-driven matchmaking in the genomic era.

Whole-genome and whole-exome sequencing are increasingly useful diagnostic tools for novel monogenic conditions. In order to confirm diagnoses made using these technologies, genomic matchmaking-the matching of cases with similar phenotypic and/or genotypic profiles, to narrow the number of candidate genes or ascertain a condition's etiology with greater certainty-is essential. Yet, due to current limitations on the size of matchmaking networks and data sets available to support them, identifying a match can be difficult. We argue that matchmaking efforts led by affected individuals and their families-participant-led efforts-offer a twofold solution to this need, in that participants both have the capacity to access larger networks and to provide more detailed sets of phenotypic and genotypic data. These features of participant-led efforts have the potential to increase the value of matchmaking networks, both in terms of number of matches and in terms of the overall energy of the network. We provide two examples of participant-led matchmaking, and propose a model for scaling these efforts.

Characteristics and Determinants of Pulmonary Long COVID.

RATIONALE: Persistent cough and dyspnea are prominent features of post-acute sequelae of SARS-CoV-2 (termed 'Long COVID'); however, physiologic measures and clinical features associated with these pulmonary symptoms remain poorly defined. OBJECTIVES: Using longitudinal pulmonary function testing (PFTs) and CT imaging, this study aimed to identify the characteristics and determinants of pulmonary Long COVID. METHODS: The University of Alabama at Birmingham Pulmonary Long COVID cohort was utilized to characterize lung defects in patients with persistent pulmonary symptoms after resolution primary COVID infection. Longitudinal PFTs including total lung capacity (TLC) and diffusion limitation of carbon monoxide (DLCO) were used to evaluate restriction and diffusion impairment over time in this cohort. Analysis of chest CT imaging was used to phenotype the pulmonary Long COVID pathology. Risk factors linked to development of pulmonary Long COVID were estimated using univariate and multivariate logistic regression models. MEASUREMENTS AND MAIN RESULTS: Longitudinal evaluation 929 patients with post-COVID pulmonary symptoms revealed diffusion impairment (DLCO ≤80%) and restriction (TLC ≤80%) in 51% of the cohort (n=479). In multivariable logistic regression analysis (adjusted odds ratio; aOR, 95% confidence interval [CI]), invasive mechanical ventilation during primary infection conferred the greatest increased odds of developing pulmonary Long COVID with diffusion impaired restriction (aOR=10.9 [4.09-28.6]). Finally, a sub-analysis of CT imaging identified evidence of fibrosis in this population. CONCLUSIONS: Persistent diffusion impaired restriction was identified as a key feature of pulmonary Long COVID. Subsequent clinical trials should leverage combined symptomatic and quantitative PFT measurements for more targeted enrollment of pulmonary Long COVID patients.

Characteristics and determinants of pulmonary long COVID.

BACKGROUNDPersistent cough and dyspnea are prominent features of postacute sequelae of SARS-CoV-2 (also termed "long COVID"); however, physiologic measures and clinical features associated with these pulmonary symptoms remain poorly defined. Using longitudinal pulmonary function testing (PFT) and CT imaging, this study aimed to identify the characteristics and determinants of pulmonary long COVID.METHODSThis single-center retrospective study included 1,097 patients with clinically defined long COVID characterized by persistent pulmonary symptoms (dyspnea, cough, and chest discomfort) lasting for 1 or more months after resolution of primary COVID infection.RESULTSAfter exclusion, a total of 929 patients with post-COVID pulmonary symptoms and PFTs were stratified as diffusion impairment and pulmonary restriction, as measured by percentage predicted diffusion capacity for carbon monoxide (DLCO) and total lung capacity (TLC). Longitudinal evaluation revealed diffusion impairment (DLCO ≤ 80%) and pulmonary restriction (TLC ≤ 80%) in 51% of the cohort overall (n = 479). In multivariable modeling regression analysis, invasive mechanical ventilation during primary infection conferred the greatest increased odds of developing pulmonary long COVID with diffusion impairment and restriction (adjusted odds ratio [aOR] = 9.89, 95% CI 3.62-26.9]). Finally, a subanalysis of CT imaging identified radiographic evidence of fibrosis in this patient population.CONCLUSIONLongitudinal PFTs revealed persistent diffusion-impaired restriction as a key feature of pulmonary long COVID. These results emphasize the importance of incorporating PFTs into routine clinical practice for evaluation of long COVID patients with prolonged pulmonary symptoms. Subsequent clinical trials should leverage combined symptomatic and quantitative PFT measurements for more targeted enrollment of pulmonary long COVID patients.FUNDINGNational Institute of Allergy and Infectious Diseases (AI156898, K08AI129705), National Heart, Lung, and Blood Institute (HL153113, OTA21-015E, HL149944), and the COVID-19 Urgent Research Response Fund at the University of Alabama at Birmingham.

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?

Generation and characterization of NGLY1 patient-derived midbrain organoids.

NGLY1 deficiency is an ultra-rare, autosomal recessive genetic disease caused by mutations in the NGLY1 gene encoding N-glycanase one that removes N-linked glycan. Patients with pathogenic mutations in NGLY1 have complex clinical symptoms including global developmental delay, motor disorder and liver dysfunction. To better understand the disease pathogenesis and the neurological symptoms of the NGLY1 deficiency we generated and characterized midbrain organoids using patient-derived iPSCs from two patients with distinct disease-causing mutations-one homozygous for p. Q208X, the other compound heterozygous for p. L318P and p. R390P and CRISPR generated NGLY1 knockout iPSCs. We demonstrate that NGLY1 deficient midbrain organoids show altered neuronal development compared to one wild type (WT) organoid. Both neuronal (TUJ1) and astrocytic glial fibrillary acid protein markers were reduced in NGLY1 patient-derived midbrain organoids along with neurotransmitter GABA. Interestingly, staining for dopaminergic neuronal marker, tyrosine hydroxylase, revealed a significant reduction in patient iPSC derived organoids. These results provide a relevant NGLY1 disease model to investigate disease mechanisms and evaluate therapeutics for treatments of NGLY1 deficiency.

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.

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.

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.