Microbiome function and neurodevelopment in Black infants: vitamin B12 emerges as a key factor.

The early life gut microbiome affects the developing brain, and therefore may serve as a target to support neurodevelopment of children living in stressful and under-resourced environments, such as Black youth living on the South Side of Chicago, for whom we observe racial disparities in health. Microbiome compositions/functions key to multiple neurodevelopmental facets have not been studied in Black children, a vulnerable population due to racial disparities in health; thus, a subsample of Black infants living in urban, low-income neighborhoods whose mothers participated in a prenatal nutrition study were recruited for testing associations between composition and function of the gut microbiome (16S rRNA gene sequencing, shotgun metagenomics, and targeted metabolomics of fecal samples) and neurodevelopment (developmental testing, maternal report of temperament, and observed stress regulation). Two microbiome community types, defined by high Lachnospiraceae or Enterobacteriaceae abundance, were discovered in this cohort from 16S rRNA gene sequencing analysis; the Enterobacteriaceae-dominant community type was significantly negatively associated with cognition and language scores, specifically in male children. Vitamin B12 biosynthesis emerged as a key microbiome function from shotgun metagenomics sequencing analysis, showing positive associations with all measured developmental skills (i.e., cognition, language, motor, surgency, effortful control, and observed stress regulation). Blautia spp. also were identified as substantial contributors of important microbiome functions, including vitamin B12 biosynthesis and related vitamin B12-dependent microbiome functions, anti-inflammatory microbial surface antigens, competitive mechanisms against pathobionts, and production of antioxidants. The results are promising with respect to the potential for exploring therapeutic candidates, such as vitamin B12 nutritional or Blautia spp. probiotic supplementation, to support the neurodevelopment of infants at risk for experiencing racial disparities in health.

Identifying novel candidate compounds for therapeutic strategies in retinopathy of prematurity via computational drug-gene association analysis.

Purpose: Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. Although interventions such as anti-VEGF and laser have high success rates in treating severe ROP, current treatment and preventative strategies still have their limitations. Thus, we aim to identify drugs and chemicals for ROP with comprehensive safety profiles and tolerability using a computational bioinformatics approach. Methods: We generated a list of genes associated with ROP to date by querying PubMed Gene which draws from animal models, human studies, and genomic studies in the NCBI database. Gene enrichment analysis was performed on the ROP gene list with the ToppGene program which draws from multiple drug-gene interaction databases to predict compounds with significant associations to the ROP gene list. Compounds with significant toxicities or without known clinical indications were filtered out from the final drug list. Results: The NCBI query identified 47 ROP genes with pharmacologic annotations present in ToppGene. Enrichment analysis revealed multiple drugs and chemical compounds related to the ROP gene list. The top ten most significant compounds associated with ROP include ascorbic acid, simvastatin, acetylcysteine, niacin, castor oil, penicillamine, curcumin, losartan, capsaicin, and metformin. Antioxidants, NSAIDs, antihypertensives, and anti-diabetics are the most common top drug classes derived from this analysis, and many of these compounds have potential to be readily repurposed for ROP as new prevention and treatment strategies. Conclusion: This bioinformatics analysis creates an unbiased approach for drug discovery by identifying compounds associated to the known genes and pathways of ROP. While predictions from bioinformatic studies require preclinical/clinical studies to validate their results, this technique could certainly guide future investigations for pathologies like ROP.

Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Proliferative Vitreoretinopathy.

Purpose: Proliferative vitreoretinopathy (PVR) is the dreaded cause of failure following retinal detachment repair; however, no cures or preventative therapies exist to date. The purpose of this study was to use bioinformatics tools to identify drugs or compounds that interact with biomarkers and pathways involved in PVR pathogenesis that could be eligible for further testing for the prevention and treatment of PVR. Methods: We queried PubMed to compile a comprehensive list of genes described in PVR to date from human studies, animal models, and genomic studies found in the National Center for Biotechnology Information database. Gene enrichment analysis was performed using ToppGene on PVR-related genes against drug-gene interaction databases to construct a pharmacome and estimate the statistical significance of overrepresented compounds. Compounds with no clinical indications were filtered out from the resulting drug lists. Results: Our query identified 34 unique genes associated with PVR. Out of 77,146 candidate drugs or compounds in the drug databases, our analysis revealed multiple drugs and compounds that have significant interactions with genes involved in PVR, including antiproliferatives, corticosteroids, cardiovascular agents, antioxidants, statins, and micronutrients. Top compounds, including curcumin, statins, and cardiovascular agents such as carvedilol and enalapril, have well-established safety profiles and potentially could be readily repurposed for PVR. Other significant compounds such as prednisone and methotrexate have shown promising results in ongoing clinical trials for PVR. Conclusions: This bioinformatics approach of studying drug-gene interactions can identify drugs that may affect genes and pathways implicated in PVR. Predicted bioinformatics studies require further validation by preclinical or clinical studies; however, this unbiased approach could identify potential candidates among existing drugs and compounds that could be repurposed for PVR and guide future investigations. Translational Relevance: Novel repurposable drug therapies for PVR can be found using advanced bioinformatics models.

Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Age-Related Macular Degeneration.

Purpose: Age-related macular degeneration (AMD) is the most common cause of aging-related blindness in the developing world. Although medications can slow progressive wet AMD, currently, no drugs to treat dry-AMD are available. We use a systems or in silico biology analysis to identify chemicals and drugs approved by the Food and Drug Administration for other indications that can be used to treat and prevent AMD. Methods: We queried National Center for Biotechnology Information to identify genes associated with AMD, wet AMD, dry AMD, intermediate AMD, and geographic atrophy to date. We combined genes from various AMD subtypes to reflect distinct stages of disease. Enrichment analysis using the ToppGene platform predicted molecules that can influence AMD genes. Compounds without clinical indications or with deleterious effects were manually filtered. Results: We identified several drug/chemical classes that can affect multiple genes involved in AMD. The drugs predicted from this analysis include antidiabetics, lipid-lowering agents, and antioxidants, which could theoretically be repurposed for AMD. Metformin was identified as the drug with the strongest association with wet AMD genes and is among the top candidates in all dry AMD subtypes. Curcumin, statins, and antioxidants are also among the top drugs correlating with AMD-risk genes. Conclusions: We use a systematic computational process to discover potential therapeutic targets for AMD. Our systematic and unbiased approach can be used to guide targeted preclinical/clinical studies for AMD and other ocular diseases. Translational Relevance: Advanced bioinformatics models identify novel chemicals and approved drug candidates that can be efficacious for different subtypes of AMD.

Effect of tea root-derived proanthocyanidin fractions on protection of dentin collagen.

OBJECTIVES: Proanthocyanidins (PAs) have been widely used as effective agents for dentin collagen cross-linking to enhance the biomechanics and biostability of dentin in vitro. However, the effects and protective mechanisms of various tea root-derived PA components on dentin remain undefined. This study evaluated the effects of these tea root-derived PA components on dentin biomechanics and biostability. METHODS: In this study, ethyl acetate and n-butyl alcohol were used to extract PAs with different degrees of polymerization from tea roots; the effects of these PA extracts on dentin were evaluated. RESULTS: Dentin was treated with glutaraldehyde, ethyl acetate, n-butyl alcohol, or water. PAs with a high degree of polymerization, extracted using n-butyl alcohol, were able to more effectively improve dentin collagen cross-linking, increase resistance to bacterial collagenase digestion, and enhance dentin elasticity, relative to treatment with glutaraldehyde or PAs with a low degree of polymerization (extracted using ethyl acetate). Additionally, treatment with aqueous extract of tea roots was detrimental to dentin stability and function. CONCLUSIONS: PAs with a high degree of polymerization were effective for dentin protection and restoration in vitro, suggesting clinical treatment potential for tea root-derived PAs.

Long-term functional maintenance of primary human hepatocytes in vitro.

The maintenance of terminally differentiated cells, especially hepatocytes, in vitro has proven challenging. Here we demonstrated the long-term in vitro maintenance of primary human hepatocytes (PHHs) by modulating cell signaling pathways with a combination of five chemicals (5C). 5C-cultured PHHs showed global gene expression profiles and hepatocyte-specific functions resembling those of freshly isolated counterparts. Furthermore, these cells efficiently recapitulated the entire course of hepatitis B virus (HBV) infection over 4 weeks with the production of infectious viral particles and formation of HBV covalently closed circular DNA. Our study demonstrates that, with a chemical approach, functional maintenance of PHHs supports long-term HBV infection in vitro, providing an efficient platform for investigating HBV cell biology and antiviral drug screening.

Lynx: a knowledge base and an analytical workbench for integrative medicine.

Lynx (http://lynx.ci.uchicago.edu) is a web-based database and a knowledge extraction engine. It supports annotation and analysis of high-throughput experimental data and generation of weighted hypotheses regarding genes and molecular mechanisms contributing to human phenotypes or conditions of interest. Since the last release, the Lynx knowledge base (LynxKB) has been periodically updated with the latest versions of the existing databases and supplemented with additional information from public databases. These additions have enriched the data annotations provided by Lynx and improved the performance of Lynx analytical tools. Moreover, the Lynx analytical workbench has been supplemented with new tools for reconstruction of co-expression networks and feature-and-network-based prioritization of genetic factors and molecular mechanisms. These developments facilitate the extraction of meaningful knowledge from experimental data and LynxKB. The Service Oriented Architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.

Effect of salt intake and potassium supplementation on urinary renalase and serum dopamine levels in Chinese adults.

OBJECTIVE: The aim of our study was to assess the effects of altered salt and potassium intake on urinary renalase and serum dopamine levels in humans. METHODS: Forty-two subjects (28­65 years of age) were selected from a rural community of northern China. All subjects were sequentially maintained on a low-salt diet for 7 days (3.0 g/day of NaCl), a high-salt diet for an additional 7 days (18.0 g/day of NaCl), and a high-salt diet with potassium supplementation for a final 7 days (18.0 g/day of NaCl + 4.5 g/day of KCl). RESULTS: Urinary renalase excretions were significantly higher during the high-salt diet intervention than during the low-salt diet. During high-potassium intake, urinary renalase excretions were not significantly different from the high-salt diet, whereas they were significantly higher than the low-salt levels. Serum dopamine levels exhibited similar trends across the interventions. Additionally, a significant positive relationship was observed between the urine renalase and serum dopamine among the different dietary interventions. Also, 24-hour urinary sodium excretion positively correlated with urine renalase and serum dopamine in the whole population. CONCLUSIONS: The present study indicates that dietary salt intake and potassium supplementation increase urinary renalase and serum dopamine levels in Chinese subjects.

An integrative computational approach for prioritization of genomic variants.

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.

Lynx: a database and knowledge extraction engine for integrative medicine.

We have developed Lynx (http://lynx.ci.uchicago.edu)--a web-based database and a knowledge extraction engine, supporting annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Its underlying knowledge base (LynxKB) integrates various classes of information from >35 public databases and private collections, as well as manually curated data from our group and collaborators. Lynx provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization to assist the user in extracting meaningful knowledge from LynxKB and experimental data, whereas its service-oriented architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.