Integrating AI/ML Models for Patient Stratification Leveraging Omics Dataset and Clinical Biomarkers from COVID-19 Patients: A Promising Approach to Personalized Medicine.

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare system. Identifying the genomics and clinical biomarkers for effective patient stratification and management is critical to controlling the spread of the disease. Omics datasets provide a wealth of information that can aid in understanding the underlying molecular mechanisms of COVID-19 and identifying potential biomarkers for patient stratification. Artificial intelligence (AI) and machine learning (ML) algorithms have been increasingly used to analyze large-scale omics and clinical datasets for patient stratification. In this manuscript, we demonstrate the recent advances and predictive accuracies in AI- and ML-based patient stratification modeling linking omics and clinical biomarker datasets, focusing on COVID-19 patients. Our ML model not only demonstrates that clinical features are enough of an indicator of COVID-19 severity and survival, but also infers what clinical features are more impactful, which makes our approach a useful guide for clinicians for prioritization best-fit therapeutics for a given cohort of patients. Moreover, with weighted gene network analysis, we are able to provide insights into gene networks that have a significant association with COVID-19 severity and clinical features. Finally, we have demonstrated the importance of clinical biomarkers in identifying high-risk patients and predicting disease progression.

In Silico Development of Combinatorial Therapeutic Approaches Targeting Key Signaling Pathways in Metabolic Syndrome.

PURPOSE: Dysregulations of key signaling pathways in metabolic syndrome are multifactorial, eventually leading to cardiovascular events. Hyperglycemia in conjunction with dyslipidemia induces insulin resistance and provokes release of proinflammatory cytokines resulting in chronic inflammation, accelerated lipid peroxidation with further development of atherosclerotic alterations and diabetes. We have proposed a novel combinatorial approach using FDA approved compounds targeting IL-17a and DPP4 to ameliorate a significant portion of the clustered clinical risks in patients with metabolic syndrome. In our current research we have modeled the outcomes of metabolic syndrome treatment using two distinct drug classes. METHODS: Targets were chosen based on the clustered clinical risks in metabolic syndrome: dyslipidemia, insulin resistance, impaired glucose control, and chronic inflammation. Drug development platform, BIOiSIM™, was used to narrow down two different drug classes with distinct modes of action and modalities. Pharmacokinetic and pharmacodynamic profiles of the most promising drugs were modeling showing predicted outcomes of combinatorial therapeutic interventions. RESULTS: Preliminary studies demonstrated that the most promising drugs belong to DPP-4 inhibitors and IL-17A inhibitors. Evogliptin was chosen to be a candidate for regulating glucose control with long term collateral benefit of weight loss and improved lipid profiles. Secukinumab, an IL-17A sequestering agent used in treating psoriasis, was selected as a repurposed candidate to address the sequential inflammatory disorders that follow the first metabolic insult. CONCLUSIONS: Our analysis suggests this novel combinatorial therapeutic approach inducing DPP4 and Il-17a suppression has a high likelihood of ameliorating a significant portion of the clustered clinical risk in metabolic syndrome.

Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform.

The COVID-19 pandemic has reached over 100 million worldwide. Due to the multi-targeted nature of the virus, it is clear that drugs providing anti-COVID-19 effects need to be developed at an accelerated rate, and a combinatorial approach may stand to be more successful than a single drug therapy. Among several targets and pathways that are under investigation, the renin-angiotensin system (RAS) and specifically angiotensin-converting enzyme (ACE), and Ca2+-mediated SARS-CoV-2 cellular entry and replication are noteworthy. A combination of ACE inhibitors and calcium channel blockers (CCBs), a critical line of therapy for pulmonary hypertension, has shown therapeutic relevance in COVID-19 when investigated independently. To that end, we conducted in silico modeling using BIOiSIM, an AI-integrated mechanistic modeling platform by utilizing known preclinical in vitro and in vivo datasets to accurately simulate systemic therapy disposition and site-of-action penetration of the CCBs and ACEi compounds to tissues implicated in COVID-19 pathogenesis.

Effects of Magnesium, Calcium, and Aluminum Chelation on Fluoroquinolone Absorption Rate and Bioavailability: A Computational Study.

Fluoroquinolones (FQs) are a widespread class of broad-spectrum antibiotics prescribed as a first line of defense, and, in some cases, as the only treatment against bacterial infection. However, when administered orally, reduced absorption and bioavailability can occur due to chelation in the gastrointestinal tract (GIT) with multivalent metal cations acquired from diet, coadministered compounds (sucralfate, didanosine), or drug formulation. Predicting the extent to which this interaction reduces in vivo antibiotic absorption and systemic exposure remains desirable yet challenging. In this study, we focus on quinolone interactions with magnesium, calcium and aluminum as found in dietary supplements, antacids (Maalox) orally administered therapies (sucralfate, didanosine). The effect of FQ-metal complexation on absorption rate was investigated through a combined molecular and pharmacokinetic (PK) modeling study. Quantum mechanical calculations elucidated FQ-metal binding energies, which were leveraged to predict the magnitude of reduced bioavailability via a quantitative structure-property relationship (QSPR). This work will help inform clinical FQ formulation design, alert to possible dietary effects, and shed light on drug-drug interactions resulting from coadministration at an earlier stage in the drug development pipeline.

In Silico Simulation of the Systemic Drug Exposure Following the Topical Application of Opioid Analgesics in Patients with Cutaneous Lesions.

The use of opioid analgesics in treating severe pain is frequently associated with putative adverse effects in humans. Topical agents that are shown to have high efficacy with a favorable safety profile in clinical settings are great alternatives for pain management of multimodal analgesia. However, the risk of side effects induced by transdermal absorption and systemic exposure is of great concern as they are challenging to predict. The present study aimed to use "BIOiSIM" an artificial intelligence-integrated biosimulation platform to predict the transdermal disposition of opioid analgesics. The model successfully predicted their exposure following the topical application of central opioid agonist buprenorphine and peripheral agonist oxycodone in healthy human subjects with simulation of intra-skin exposure in subjects with burns and pressure wounds. The predicted plasma levels of analgesics were used to evaluate the safety of the therapeutic pain control in patients with the dermal structural impairments caused by acute (burns) or chronic cutaneous lesions (pressure wounds) with topical opioid analgesics.

Driving success in personalized medicine through AI-enabled computational modeling.

The development of successful drugs is expensive and time-consuming because of high clinical attrition rates. This is caused partially by the rupture seen in the translatability of the drug from the bench to the clinic in the context of personalized medicine. Artificial intelligence (AI)-driven platforms integrated with mechanistic modeling have become instrumental in accelerating the drug development process by leveraging data ubiquitously across the various phases. AI can counter the deficiencies and ambiguities that arise during the classical drug development process while reducing human intervention and bridging the translational gap in discovering the connections between drugs and diseases.

Molecular Simulation and Statistical Learning Methods toward Predicting Drug-Polymer Amorphous Solid Dispersion Miscibility, Stability, and Formulation Design.

Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API-carrier mixture and the principal API-carrier non-bonding interactions are critical factors for rational drug development and formulation decisions. Experimental determination of these interactions, solubility, and dissolution mechanisms is time-consuming, costly, and reliant on trial and error. To that end, molecular modeling has been applied to simulate ASD properties and mechanisms. Quantum mechanical methods elucidate the strength of API-carrier non-bonding interactions, while molecular dynamics simulations model and predict ASD physical stability, solubility, and dissolution mechanisms. Statistical learning models have been recently applied to the prediction of a variety of drug formulation properties and show immense potential for continued application in the understanding and prediction of ASD solubility. Continued theoretical progress and computational applications will accelerate lead compound development before clinical trials. This article reviews in silico research for the rational formulation design of low-solubility drugs. Pertinent theoretical groundwork is presented, modeling applications and limitations are discussed, and the prospective clinical benefits of accelerated ASD formulation are envisioned.

RNAseq Analysis of Rodent Spaceflight Experiments Is Confounded by Sample Collection Techniques.

To understand the physiological changes that occur in response to spaceflight, mice are transported to the International Space Station (ISS) and housed for variable periods of time before euthanasia on-orbit or return to Earth. Sample collection under such difficult conditions introduces confounding factors that need to be identified and addressed. We found large changes in the transcriptome of mouse tissues dissected and preserved on-orbit compared with tissues from mice euthanized on-orbit, preserved, and dissected after return to Earth. Changes due to preservation method eclipsed those between flight and ground samples, making it difficult to identify spaceflight-specific changes. Follow-on experiments to interrogate the roles of euthanasia methods, tissue and carcass preservation protocols, and library preparation methods suggested that differences due to preservation protocols are exacerbated when coupled with polyA selection. This has important implications for the interpretation of existing datasets and the design of future experiments.

Author Correction: Multi-omics analysis of multiple missions to space reveal a theme of lipid dysregulation in mouse liver.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Multi-omics analysis of multiple missions to space reveal a theme of lipid dysregulation in mouse liver.

Spaceflight has several detrimental effects on the physiology of astronauts, many of which are recapitulated in rodent models. Mouse studies performed on the Space Shuttle showed disruption of lipid metabolism in liver. However, given that these animals were not sacrificed on-orbit and instead returned live to earth, it is unclear if these disruptions were solely induced by space stressors (e.g. microgravity, space radiation) or in part explained by the stress of return to Earth. In this work we analyzed three liver datasets from two different strains of mice (C57BL/6 (Jackson) & BALB/c (Taconic)) flown aboard the International Space Station (ISS). Notably, these animals were sacrificed on-orbit and exposed to varying spaceflight durations (i.e. 21, 37, and 42 days vs 13 days for the Shuttle mice). Oil Red O (ORO) staining showed abnormal lipid accumulation in all space-flown mice compared to ground controls regardless of strain or exposure duration. Similarly, transcriptomic analysis by RNA-sequencing revealed several pathways that were affected in both strains related to increased lipid metabolism, fatty acid metabolism, lipid and fatty acid processing, lipid catabolic processing, and lipid localization. In addition, key upstream regulators were predicted to be commonly regulated across all conditions including Glucagon (GCG) and Insulin (INS). Moreover, quantitative proteomic analysis showed that a number of lipid related proteins were changed in the livers during spaceflight. Taken together, these data indicate that activation of lipotoxic pathways are the result of space stressors alone and this activation occurs in various genetic backgrounds during spaceflight exposures of weeks to months. If similar responses occur in humans, a prolonged change of these pathways may result in the development of liver disease and should be investigated further.

Peripheral reduction of FGFR4 with antisense oligonucleotides increases metabolic rate and lowers adiposity in diet-induced obese mice.

Obesity is a primary risk factor for multiple metabolic disorders. Many drugs for the treatment of obesity, which mainly act through CNS as appetite suppressants, have failed during development or been removed from the market due to unacceptable adverse effects. Thus, there are very few efficacious drugs available and remains a great unmet medical need for anti-obesity drugs that increase energy expenditure by acting on peripheral tissues without severe side effects. Here, we report a novel approach involving antisense inhibition of fibroblast growth factor receptor 4 (FGFR4) in peripheral tissues. Treatment of diet-induce obese (DIO) mice with FGFR4 antisense oligonucleotides (ASO) specifically reduced liver FGFR4 expression that not only resulted in decrease in body weight (BW) and adiposity in free-feeding conditions, but also lowered BW and adiposity under caloric restriction. In addition, combination treatment with FGFR4 ASO and rimonabant showed additive reduction in BW and adiposity. FGFR4 ASO treatment increased basal metabolic rate during free-feeding conditions and, more importantly, prevented adaptive decreases of metabolic rate induced by caloric restriction. The treatment increased fatty acid oxidation while decreased lipogenesis in both liver and fat. Mechanistic studies indicated that anti-obesity effect of FGFR4 ASO was mediated at least in part through an induction of plasma FGF15 level resulted from reduction of hepatic FGFR4 expression. The anti-obesity effect was accompanied by improvement in plasma glycemia, whole body insulin sensitivity, plasma lipid levels and liver steatosis. Therefore, FGFR4 could be a potential novel target and antisense reduction of hepatic FGFR4 expression could be an efficacious therapy as an adjunct to diet restriction or to an appetite suppressant for the treatment of obesity and related metabolic disorders.

Pharmacodynamics and subchronic toxicity in mice and monkeys of ISIS 388626, a second-generation antisense oligonucleotide that targets human sodium glucose cotransporter 2.

ISIS 388626, a 2'-methoxyethyl (MOE)-modified antisense oligonucleotide (ASO) that targets human sodium glucose cotransporter 2 (SGLT2) mRNA, is in clinical trials for the management of diabetes. SGLT2 plays a pivotal role in renal glucose reabsorption, and inhibition of SGLT2 is anticipated to reduce hyperglycemia in diabetic subjects by increasing urinary glucose elimination. To selectively inhibit SGLT2 in the kidney, ISIS 388626 was designed as a "shortmer" ASO, consisting of only 12 nucleotides with two 2'-MOE-modified nucleotides at the termini. Mice and monkeys received up to 30 mg/kg/week ISIS 388626 via subcutaneous injection for 6 or 13 weeks. Dose-dependent decreases in renal SGLT2 mRNA expression were observed, which correlated with dose-related increases in glucosuria without concomitant hypoglycemia. There were no histologic changes in the kidney attributed to SGLT2 inhibition after 6 or 13 weeks of treatment. The remaining changes observed in these studies were typical of those produced in these species by the administration of oligonucleotides, correlated with high doses of ISIS 388626, and were unrelated to the inhibition of SGLT2 expression. The kidney contained the highest concentration of ISIS 388626, and dose-dependent basophilic granule accumulation in tubular epithelial cells of the kidney, which is evidence of oligonucleotide accumulation in these cells, was the only histologic change identified. No changes in kidney function were observed. These results revealed only readily reversible changes after the administration of ISIS 388626 and support the continued investigation of the safety and efficacy of ISIS 388626 in human trials.

Insulin regulation of phosphoenolpyruvate carboxykinase-c gene transcription: the role of sterol regulatory element-binding protein 1c.

The effect of insulin on the regulation of phosphoenolpyruvate carboxykinase C (PEPCK-C) gene transcription, while pivotal for control of carbohydrate metabolism, constitutes only a small part of its overall action in cellular processes. Transcription of the PEPCK-C gene is the target for a number of pathways involved in the signal transduction initiated by insulin, and these processes involve an array of transcription factors and co-regulatory proteins that either alone or in concert bind to a subset of sites in the gene promoter to regulate its expression. This review will focus on a specific transcription factor, sterol regulatory element-binding protein 1c (SREBP-1c), and its role in the control of PEPCK-C gene transcription.

Several transcription factors are recruited to the glucose-6-phosphatase gene promoter in response to palmitate in rat hepatocytes and H4IIE cells.

Fatty acids and glucose are strong modulators of the expression of glucose-6-phosphatase (Glc-6-Pase), an enzyme that plays a key role in glucose homeostasis. PUFA inhibit, whereas SFA and monounsaturated fatty acids induce the expression of the Glc-6-Pase gene. Palmitate and oleate are the most abundant fatty acid species in circulation during food deprivation in mammals. Although dietary fats have been shown to modulate the expression of genes involved in both lipid and carbohydrate metabolism in liver, little is known regarding the molecular mechanism of transcriptional response of the Glc-6-Pase gene to long-chain fatty acids. Using H4IIE hepatoma cells and hepatocytes from adult rats, we investigated the mechanism of the induction of this gene by palmitate and oleate. Both of these fatty acids stimulated Glc-6-Pase gene transcription but did not affect the stability of its mRNA. In transient transfection assays, transcription from the Glc-6-Pase gene promoter was markedly enhanced by both palmitate and oleate but not by arachidonate. Chromatin immunoprecipitation analysis was used to show that palmitate induced the recruitment of an array of transcription factors viz hepatic nuclear factor(NF)-4alpha, CAAT/enhancer binding proteinbeta, PPARalpha, chicken ovalbumin upstream promoter transcription factor (COUP-TF), cAMP regulatory element binding protein, and NF-kappaB to this gene promoter. Although it is presently unclear how these various transcription factors interact at this promoter, the data are consistent with the view that multiple regulatory elements in the Glc-6-Pase gene promoter are responsible for the modulation of gene transcription by fatty acids.

A feedback transcriptional mechanism controls the level of the arginine/lysine transporter cat-1 during amino acid starvation.

The adaptive response to amino acid limitation in mammalian cells inhibits global protein synthesis and promotes the expression of proteins that protect cells from stress. The arginine/lysine transporter, cat-1, is induced during amino acid starvation by transcriptional and post-transcriptional mechanisms. It is shown in the present study that the transient induction of cat-1 transcription is regulated by the stress response pathway that involves phosphorylation of the translation initiation factor, eIF2 (eukaryotic initiation factor-2). This phosphorylation induces expression of the bZIP (basic leucine zipper protein) transcription factors C/EBP (CCAAT/enhancer-binding protein)-beta and ATF (activating transcription factor) 4, which in turn induces ATF3. Transfection experiments in control and mutant cells, and chromatin immunoprecipitations showed that ATF4 activates, whereas ATF3 represses cat-1 transcription, via an AARE (amino acid response element), TGATGAAAC, in the first exon of the cat-1 gene, which functions both in the endogenous and in a heterologous promoter. ATF4 and C/EBPbeta activated transcription when expressed in transfected cells and they bound as heterodimers to the AARE in vitro. The induction of transcription by ATF4 was inhibited by ATF3, which also bound to the AARE as a heterodimer with C/EBPbeta. These results suggest that the transient increase in cat-1 transcription is due to transcriptional activation caused by ATF4 followed by transcriptional repression by ATF3 via a feedback mechanism.

Glucocorticoids regulate transcription of the gene for phosphoenolpyruvate carboxykinase in the liver via an extended glucocorticoid regulatory unit.

The hepatic transcriptional regulation by glucocorticoids of the cytosolic form of phosphoenolpyruvate carboxykinase (PEPCK-C) gene is coordinated by interactions of specific transcription factors at the glucocorticoid regulatory unit (GRU). We propose an extended GRU that consists of four accessory sites, two proximal AF1 and AF2 sites and their distal counterpart dAF1 (-993) and a new site, dAF2 (-1365); together, these four sites form a palindrome. Sequencing and gel shift binding assays of hepatic nuclear proteins interacting with these sites indicated similarity of dAF1 and dAF2 sites to the GRU proximal AF1 and AF2 sites. Chromatin immunoprecipitation assays demonstrated that glucocorticoids enhanced the binding of FOXO1 and peroxisome proliferator-activated receptor-alpha to AF2 and dAF2 sites and not to dAF1 site but enhanced the binding of hepatic nuclear transcription factor-4alpha only to the dAF1 site. Insulin inhibited the binding of these factors to their respective sites but intensified the binding of phosphorylated FOXO1. Transient transfections in HepG2 human hepatoma cells showed that glucocorticoid receptor interacts with several non-steroid nuclear receptors, yielding a synergistic response of the PEPCK-C gene promoter to glucocorticoids. The synergistic stimulation by glucocorticoid receptor together with peroxisome proliferator-activated receptor-alpha or hepatic nuclear transcription factor-4alpha requires all four accessory sites, i.e. a mutation of each of these markedly affects the synergistic response. Mice with a targeted mutation of the dAF1 site confirmed this requirement. This mutation inhibited the full response of hepatic PEPCK-C gene to diabetes by reducing PEPCK-C mRNA level by 3.5-fold and the level of circulating glucose by 25%.

Factors that control the tissue-specific transcription of the gene for phosphoenolpyruvate carboxykinase-C.

Transcription of the gene for PEPCK-C occurs in a number of mammalian tissues, with highest expression occurring in the liver, kidney cortex, and white and brown adipose tissue. Several hormones and other factors, including glucagon, epinephrine, insulin, glucocorticoids and metabolic acidosis, control this process in three responsive tissues, liver, adipose tissue, and kidney cortex. Expression of the gene in these three tissues in regulated in a different manner, responding to the specific physiological role of the tissue. The PEPCK-C gene promoter has been extensively studied and a number of regulatory regions identified that bind key transcription factors and render the gene responsive to hormonal and dietary stimuli. This review will focus on the control of transcription for the gene, with special emphasis on our current understanding of the transcription factors that are involved in the response of PEPCK-C gene in specific tissues. We have also reviewed the biological function of PEPCK-C in each of the tissues discussed in this review, in order to place the control of PEPCK-C gene transcription in the appropriate physiological context. Because of its extraordinary importance in mammalian metabolism and its broad pattern of tissue-specific expression, the PEPCK-C gene has become a model for studying the biological basis of the control of gene transcription.

SREBP-1c and Sp1 interact to regulate transcription of the gene for phosphoenolpyruvate carboxykinase (GTP) in the liver.

The sterol regulatory element-binding protein-1c (SREBP-1c), as well as SREBP-1a and SREBP-2, inhibit transcription of the gene encoding the cytosolic form of phosphoenolpyruvate carboxykinase (GTP) (PEPCK-C). There are two SREBP regulatory elements (SREs) in the PEPCK-C gene promoter (-322 to -313 and -590 to -581). The SRE at -590 overlaps an Sp1 site on the opposite strand of the DNA. These SREs bound SREBP-1a and SREBP-1c with low affinity but the addition of purified upstream stimulatory activity enhanced the binding of SREBP-1 to both of these sites. Mutating these SREs increased both unstimulated (5-fold) and protein kinase A-stimulated transcription (8-27-fold) from the PEPCK-C gene promoter; this was lost when both SREs were mutated. The SRE at -590 differs by a single base pair from the SRE in the low density lipoprotein (LDL) receptor gene (T in the PEPCK-C gene promoter at -582, compared with an A in the SRE of the gene for the LDL receptor promoter). Introduction of the LDL receptor SRE into the PEPCK-C gene promoter increased SREBP-1c binding and caused a 10-fold enhancement of basal transcription from the promoter, rather than an inhibition as observed with the SRE in the PEPCK-C gene promoter. The T/A change does not alter the binding of Sp1 to its site on the opposite strand of the DNA. Sp1 bound to the promoter independently of SREBP-1c but competed with SREBP-1c for binding. Sp1 does not bind to the SRE at -322. Chromatin immunoprecipitation analysis, using rat hepatocytes, demonstrated that SREBP-1 and Sp1 were associated in vivo with putative regulatory regions corresponding to the SREs in the PEPCK-C gene promoter. We propose that insulin represses transcription of the gene for PEPCK-C by inducing SREBP-1c production in the liver, which interferes with the stimulatory effect of Sp1 at -590 of the PEPCK-C gene promoter.