Systematic enhancement of protein crystallization efficiency by bulk lysine-to-arginine (KR) substitution.

Structural genomics consortia established that protein crystallization is the primary obstacle to structure determination using x-ray crystallography. We previously demonstrated that crystallization propensity is systematically related to primary sequence, and we subsequently performed computational analyses showing that arginine is the most overrepresented amino acid in crystal-packing interfaces in the Protein Data Bank. Given the similar physicochemical characteristics of arginine and lysine, we hypothesized that multiple lysine-to-arginine (KR) substitutions should improve crystallization. To test this hypothesis, we developed software that ranks lysine sites in a target protein based on the redundancy-corrected KR substitution frequency in homologs. This software can be run interactively on the worldwide web at https://www.pxengineering.org/. We demonstrate that three unrelated single-domain proteins can tolerate 5-11 KR substitutions with at most minor destabilization, and, for two of these three proteins, the construct with the largest number of KR substitutions exhibits significantly enhanced crystallization propensity. This approach rapidly produced a 1.9 Å crystal structure of a human protein domain refractory to crystallization with its native sequence. Structures from Bulk KR-substituted domains show the engineered arginine residues frequently make hydrogen-bonds across crystal-packing interfaces. We thus demonstrate that Bulk KR substitution represents a rational and efficient method for probabilistic engineering of protein surface properties to improve crystallization.

Knockout of murine Lyplal1 confers sex-specific protection against diet-induced obesity.

Human genome-wide association studies found single-nucleotide polymorphisms (SNPs) near LYPLAL1 (Lysophospholipase-like protein 1) that have sex-specific effects on fat distribution and metabolic traits. To determine whether altering LYPLAL1 affects obesity and metabolic disease, we created and characterized a mouse knockout (KO) of Lyplal1. We fed the experimental group of mice a high-fat, high-sucrose (HFHS) diet for 23 weeks, and the controls were fed regular chow diet. Here, we show that CRISPR-Cas9 whole-body Lyplal1 KO mice fed an HFHS diet showed sex-specific differences in weight gain and fat accumulation as compared to chow diet. Female, not male, KO mice weighed less than WT mice, had reduced body fat percentage, had white fat mass, and had adipocyte diameter not accounted for by changes in the metabolic rate. Female, but not male, KO mice had increased serum triglycerides, decreased aspartate, and decreased alanine aminotransferase. Lyplal1 KO mice of both sexes have reduced liver triglycerides and steatosis. These diet-specific effects resemble the effects of SNPs near LYPLAL1 in humans, suggesting that LYPLAL1 has an evolutionary conserved sex-specific effect on adiposity. This murine model can be used to study this novel gene-by-sex-by-diet interaction to elucidate the metabolic effects of LYPLAL1 on human obesity.

Polygenic Risk Prediction in Diverticulitis.

OBJECTIVE: To derive and validate a polygenic risk score (PRS) to predict the occurrence and severity of diverticulitis and to understand the potential for incorporation of a PRS in current decision-making. BACKGROUND: PRS quantifies genetic variation into a continuous measure of risk. There is a need for improved risk stratification to guide surgical decision-making that could be fulfilled by PRS. It is unknown how surgeons might integrate PRS in decision-making. METHODS: We derived a PRS with 44 single-nucleotide polymorphisms associated with diverticular disease in the UK Biobank and validated this score in the Michigan Genomics Initiative (MGI). We performed a discrete choice experiment of practicing colorectal surgeons. Surgeons rated the influence of clinical factors and a hypothetical polygenic risk prediction tool. RESULTS: Among 2812 MGI participants with diverticular disease, 1964 were asymptomatic, 574 had mild disease, and 274 had severe disease. PRS was associated with occurrence and severity. Patients in the highest PRS decile were more likely to have diverticulitis [odds ratio (OR)=1.84; 95% confidence interval (CI), 1.42-2.38)] and more likely to have severe diverticulitis (OR=1.61; 95% CI, 1.04-2.51) than the bottom 50%. Among 213 surveyed surgeons, extreme disease-specific factors had the largest utility (3 episodes in the last year, +74.4; percutaneous drain, + 69.4). Factors with strongest influence against surgery included 1 lifetime episode (-63.3), outpatient management (-54.9), and patient preference (-39.6). PRS was predicted to have high utility (+71). CONCLUSIONS: A PRS derived from a large national biobank was externally validated, and found to be associated with the incidence and severity of diverticulitis. Surgeons have clear guidance at clinical extremes, but demonstrate equipoise in intermediate scenarios. Surgeons are receptive to PRS, which may be most useful in marginal clinical situations. Given the current lack of accurate prognostication in recurrent diverticulitis, PRS may provide a novel approach for improving patient counseling and decision-making.

Investigating SH-SY5Y Neuroblastoma Cell Surfaceome as a Model for Neuronal-Targeted Novel Therapeutic Modalities.

The SH-SY5Y neuroblastoma cells are a widely used in vitro model approximating neurons for testing the target engagement of therapeutics designed for neurodegenerative diseases and pain disorders. However, their potential as a model for receptor-mediated delivery and uptake of novel modalities, such as antibody-drug conjugates, remains understudied. Investigation of the SH-SY5Y cell surfaceome will aid in greater in vitro to in vivo correlation of delivery and uptake, thereby accelerating drug discovery. So far, the majority of studies have focused on total cell proteomics from undifferentiated and differentiated SH-SY5Y cells. While some studies have investigated the expression of specific proteins in neuroblastoma tissue, a global approach for comparison of neuroblastoma cell surfaceome to the brain and dorsal root ganglion (DRG) neurons remains uninvestigated. Furthermore, an isoform-specific evaluation of cell surface proteins expressed on neuroblastoma cells remains unexplored. In this study, we define a bioinformatic workflow for the identification of high-confidence surface proteins expressed on brain and DRG neurons using tissue proteomic and transcriptomic data. We then delineate the SH-SY5Y cell surfaceome by surface proteomics and show that it significantly overlaps with the human brain and DRG neuronal surface proteome. We find that, for 32% of common surface proteins, SH-SY5Y-specific major isoforms are alternatively spliced, maintaining their protein-coding ability, and are predicted to localize to the cell surface. Validation of these isoforms using surface proteomics confirms a SH-SY5Y-specific alternative NRCAM (neuron-glia related cell adhesion molecule) isoform, which is absent in typical brain neurons, but present in neuroblastomas, making it a receptor of interest for neuroblastoma-specific therapeutics.

Population-based meta-analysis and gene-set enrichment identifies FXR/RXR pathway as common to fatty liver disease and serum lipids.

Nonalcoholic fatty liver disease (NAFLD) is prevalent worldwide. NAFLD is associated with elevated serum triglycerides (TG), low-density lipoprotein cholesterol (LDL), and reduced high-density lipoprotein cholesterol (HDL). Both NAFLD and blood lipid levels are genetically influenced and may share a common genetic etiology. We used genome-wide association studies (GWAS)-ranked genes and gene-set enrichment analysis to identify pathways that affect serum lipids and NAFLD. We identified credible genes in these pathways and characterized missense variants in these for effects on serum traits. We used MAGENTA to identify 58 enriched pathways from publicly available TG, LDL, and HDL GWAS (n = 99,000). Three of these pathways were also enriched for associations with European-ancestry NAFLD GWAS (n = 7176). One pathway, farnesoid X receptor (FXR)/retinoid X receptor (RXR) activation, was replicated for association in an African-ancestry NAFLD GWAS (n = 3214) and plays a role in serum lipids and NAFLD. Credible genes (proteins) in FXR/RXR activation include those associated with cholesterol/bile/bilirubin transport/absorption (ABCC2 (MRP2) [ATP binding cassette subfamily C member (multidrug resistance-associated protein 2)], ABCG5, ABCG8 [ATP-binding cassette (ABC) transporters G5 and G8], APOB (APOB) [apolipoprotein B], FABP6 (ILBP) [fatty acid binding protein 6 (ileal lipid-binding protein)], MTTP (MTP) [microsomal triglyceride transfer protein], SLC4A2 (AE2) [solute carrier family 4 member 2 (anion exchange protein 2)]), nuclear hormone-mediated control of metabolism (NR0B2 (SHP) [nuclear receptor subfamily 0 group B member 2 (small heterodimer partner)], NR1H4 (FXR) [nuclear receptor subfamily 1 group H member 4 (FXR)], PPARA (PPAR) [peroxisome proliferator activated receptor alpha], FOXO1 (FOXO1A) [forkhead box O1]), or other pathways (FETUB (FETUB) [fetuin B]). Missense variants in ABCC2 (MRP2), ABCG5 (ABCG5), ABCG8 (ABCG8), APOB (APOB), MTTP (MTP), NR0B2 (SHP), NR1H4 (FXR), and PPARA (PPAR) that associate with serum LDL levels also associate with serum liver function tests in UK Biobank. Conclusion: Genetic variants in NR1H4 (FXR) that protect against liver steatosis increase serum LDL cholesterol while variants in other members of the family have congruent effects on these traits. Human genetic pathway enrichment analysis can help guide therapeutic development by identifying effective targets for NAFLD/serum lipid manipulation while minimizing side effects. In addition, missense variants could be used in companion diagnostics to determine their influence on drug effectiveness.

A new framework for host-pathogen interaction research.

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

Morphological cell profiling of SARS-CoV-2 infection identifies drug repurposing candidates for COVID-19.

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10 to 15 y from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 US Food and Drug Administration (FDA)-approved compounds and clinical candidates, we identified 17 hits that inhibited SARS-CoV-2 infection and analyzed their antiviral activity across multiple cell lines, including lymph node carcinoma of the prostate (LNCaP) cells and a physiologically relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein found in secretory fluids including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.

BET Bromodomain Inhibition Blocks an AR-Repressed, E2F1-Activated Treatment-Emergent Neuroendocrine Prostate Cancer Lineage Plasticity Program.

PURPOSE: Lineage plasticity in prostate cancer-most commonly exemplified by loss of androgen receptor (AR) signaling and a switch from a luminal to alternate differentiation program-is now recognized as a treatment resistance mechanism. Lineage plasticity is a spectrum, but neuroendocrine prostate cancer (NEPC) is the most virulent example. Currently, there are limited treatments for NEPC. Moreover, the incidence of treatment-emergent NEPC (t-NEPC) is increasing in the era of novel AR inhibitors. In contradistinction to de novo NEPC, t-NEPC tumors often express the AR, but AR's functional role in t-NEPC is unknown. Furthermore, targetable factors that promote t-NEPC lineage plasticity are also unclear. EXPERIMENTAL DESIGN: Using an integrative systems biology approach, we investigated enzalutamide-resistant t-NEPC cell lines and their parental, enzalutamide-sensitive adenocarcinoma cell lines. The AR is still expressed in these t-NEPC cells, enabling us to determine the role of the AR and other key factors in regulating t-NEPC lineage plasticity. RESULTS: AR inhibition accentuates lineage plasticity in t-NEPC cells-an effect not observed in parental, enzalutamide-sensitive adenocarcinoma cells. Induction of an AR-repressed, lineage plasticity program is dependent on activation of the transcription factor E2F1 in concert with the BET bromodomain chromatin reader BRD4. BET inhibition (BETi) blocks this E2F1/BRD4-regulated program and decreases growth of t-NEPC tumor models and a subset of t-NEPC patient tumors with high activity of this program in a BETi clinical trial. CONCLUSIONS: E2F1 and BRD4 are critical for activating an AR-repressed, t-NEPC lineage plasticity program. BETi is a promising approach to block this program.

Standing Variations Modeling Captures Inter-Individual Heterogeneity in a Deterministic Model of Prostate Cancer Response to Combination Therapy.

Sipuleucel-T (Provenge) is the first live cell vaccine approved for advanced, hormonally refractive prostate cancer. However, survival benefit is modest and the optimal combination or schedule of sipuleucel-T with androgen depletion remains unknown. We employ a nonlinear dynamical systems approach to modeling the response of hormonally refractive prostate cancer to sipuleucel-T. Our mechanistic model incorporates the immune response to the cancer elicited by vaccination, and the effect of androgen depletion therapy. Because only a fraction of patients benefit from sipuleucel-T treatment, inter-individual heterogeneity is clearly crucial. Therefore, we introduce our novel approach, Standing Variations Modeling, which exploits inestimability of model parameters to capture heterogeneity in a deterministic model. We use data from mouse xenograft experiments to infer distributions on parameters critical to tumor growth and to the resultant immune response. Sampling model parameters from these distributions allows us to represent heterogeneity, both at the level of the tumor cells and the individual (mouse) being treated. Our model simulations explain the limited success of sipuleucel-T observed in practice, and predict an optimal combination regime that maximizes predicted efficacy. This approach will generalize to a range of emerging cancer immunotherapies.

Genome-wide association study of serum liver enzymes implicates diverse metabolic and liver pathology.

Serum liver enzyme concentrations are the most frequently-used laboratory markers of liver disease, a major cause of mortality. We conduct a meta-analysis of genome-wide association studies of liver enzymes from UK BioBank and BioBank Japan. We identified 160 previously-unreported independent alanine aminotransferase, 190 aspartate aminotransferase, and 199 alkaline phosphatase genome-wide significant associations, with some affecting multiple different enzymes. Associated variants implicate genes that demonstrate diverse liver cell type expression and promote a range of metabolic and liver diseases. These findings provide insight into the pathophysiology of liver and other metabolic diseases that are associated with serum liver enzyme concentrations.

Causal Relationship and Shared Genetic Loci between Psoriasis and Type 2 Diabetes through Trans-Disease Meta-Analysis.

Psoriasis and type 2 diabetes (T2D) are complex conditions with significant impacts on health. Patients with psoriasis have a higher risk of T2D (∼1.5 OR) and vice versa, controlling for body mass index; yet, there has been a limited study comparing their genetic architecture. We hypothesized that there are shared genetic components between psoriasis and T2D. Trans-disease meta-analysis was applied to 8,016,731 well-imputed genetic markers from large-scale meta-analyses of psoriasis (11,024 cases and 16,336 controls) and T2D (74,124 cases and 824,006 controls), adjusted for body mass index. We confirmed our findings in a hospital-based study (42,112 patients) and tested for causal relationships with multivariable Mendelian randomization. Mendelian randomization identified a causal relationship between psoriasis and T2D (P = 1.6 × 10‒4, OR = 1.01) and highlighted the impact of body mass index. Trans-disease meta-analysis further revealed four genome-wide significant loci (P < 5 × 10‒8) with evidence of colocalization and shared directions of effect between psoriasis and T2D not present in body mass index. The proteins coded by genes in these loci (ACTR2, ERLIN1, TRMT112, and BECN1) are connected through NF-κB signaling. Our results provide insight into the immunological components that connect immune-mediated skin conditions and metabolic diseases, independent of confounding factors.

Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection.

Our systematic literature collection and annotation identified 106 chemical drugs and 31 antibodies effective against the infection of at least one human coronavirus (including SARS-CoV, SAR-CoV-2, and MERS-CoV) in vitro or in vivo in an experimental or clinical setting. A total of 163 drug protein targets were identified, and 125 biological processes involving the drug targets were significantly enriched based on a Gene Ontology (GO) enrichment analysis. The Coronavirus Infectious Disease Ontology (CIDO) was used as an ontological platform to represent the anti-coronaviral drugs, chemical compounds, drug targets, biological processes, viruses, and the relations among these entities. In addition to new term generation, CIDO also adopted various terms from existing ontologies and developed new relations and axioms to semantically represent our annotated knowledge. The CIDO knowledgebase was systematically analyzed for scientific insights. To support rational drug design, a "Host-coronavirus interaction (HCI) checkpoint cocktail" strategy was proposed to interrupt the important checkpoints in the dynamic HCI network, and ontologies would greatly support the design process with interoperable knowledge representation and reasoning.

Loci identified by a genome-wide association study of carotid artery stenosis in the eMERGE network.

Carotid artery atherosclerotic disease (CAAD) is a risk factor for stroke. We used a genome-wide association (GWAS) approach to discover genetic variants associated with CAAD in participants in the electronic Medical Records and Genomics (eMERGE) Network. We identified adult CAAD cases with unilateral or bilateral carotid artery stenosis and controls without evidence of stenosis from electronic health records at eight eMERGE sites. We performed GWAS with a model adjusting for age, sex, study site, and genetic principal components of ancestry. In eMERGE we found 1793 CAAD cases and 17,958 controls. Two loci reached genome-wide significance, on chr6 in LPA (rs10455872, odds ratio [OR] (95% confidence interval [CI]) = 1.50 (1.30-1.73), p = 2.1 × 10-8 ) and on chr7, an intergenic single nucleotide variant (SNV; rs6952610, OR (95% CI) = 1.25 (1.16-1.36), p = 4.3 × 10-8 ). The chr7 association remained significant in the presence of the LPA SNV as a covariate. The LPA SNV was also associated with coronary heart disease (CHD; 4199 cases and 11,679 controls) in this study (OR (95% CI) = 1.27 (1.13-1.43), p = 5 × 10-5 ) but the chr7 SNV was not (OR (95% CI) = 1.03 (0.97-1.09), p = .37). Both variants replicated in UK Biobank. Elevated lipoprotein(a) concentrations ([Lp(a)]) and LPA variants associated with elevated [Lp(a)] have previously been associated with CAAD and CHD, including rs10455872. With electronic health record phenotypes in eMERGE and UKB, we replicated a previously known association and identified a novel locus associated with CAAD.

A Meta-Analysis of the Transferability of Bone Mineral Density Genetic Loci Associations From European to African Ancestry Populations.

Genetic studies of bone mineral density (BMD) largely have been conducted in European populations. We therefore conducted a meta-analysis of six independent African ancestry cohorts to determine whether previously reported BMD loci identified in European populations were transferable to African ancestry populations. We included nearly 5000 individuals with both genetic data and assessments of BMD. Genotype imputation was conducted using the 1000G reference panel. We assessed single-nucleotide polymorphism (SNP) associations with femoral neck and lumbar spine BMD in each cohort separately, then combined results in fixed effects (or random effects if study heterogeneity was high, I2 index >60) inverse variance weighted meta-analyses. In secondary analyses, we conducted locus-based analyses of rare variants using SKAT-O. Mean age ranged from 12 to 68 years. One cohort included only men and another cohort included only women; the proportion of women in the other four cohorts ranged from 52% to 63%. Of 56 BMD loci tested, one locus, 6q25 (C6orf97, p = 8.87 × 10-4 ), was associated with lumbar spine BMD and two loci, 7q21 (SLC25A13, p = 2.84 × 10-4 ) and 7q31 (WNT16, p = 2.96 × 10-5 ), were associated with femoral neck BMD. Effects were in the same direction as previously reported in European ancestry studies and met a Bonferroni-adjusted p value threshold, the criteria for transferability to African ancestry populations. We also found associations that met locus-specific Bonferroni-adjusted p value thresholds in 11q13 (LRP5, p < 2.23 × 10-4 ), 11q14 (DCDC5, p < 5.35 × 10-5 ), and 17p13 (SMG6, p < 6.78 × 10-5 ) that were not tagged by European ancestry index SNPs. Rare single-nucleotide variants in AKAP11 (p = 2.32 × 10-2 ), MBL2 (p = 4.09 × 10-2 ), MEPE (p = 3.15 × 10-2 ), SLC25A13 (p = 3.03 × 10-2 ), STARD3NL (p = 3.35 × 10-2 ), and TNFRSF11A (p = 3.18 × 10-3 ) were also associated with BMD. The majority of known BMD loci were not transferable. Larger genetic studies of BMD in African ancestry populations will be needed to overcome limitations in statistical power and to identify both other loci that are transferable across populations and novel population-specific variants. © 2020 American Society for Bone and Mineral Research (ASBMR).

A Noncoding Variant Near PPP1R3B Promotes Liver Glycogen Storage and MetS, but Protects Against Myocardial Infarction.

CONTEXT: Glycogen storage diseases are rare. Increased glycogen in the liver results in increased attenuation. OBJECTIVE: Investigate the association and function of a noncoding region associated with liver attenuation but not histologic nonalcoholic fatty liver disease. DESIGN: Genetics of Obesity-associated Liver Disease Consortium. SETTING: Population-based. MAIN OUTCOME: Computed tomography measured liver attenuation. RESULTS: Carriers of rs4841132-A (frequency 2%-19%) do not show increased hepatic steatosis; they have increased liver attenuation indicative of increased glycogen deposition. rs4841132 falls in a noncoding RNA LOC157273 ~190 kb upstream of PPP1R3B. We demonstrate that rs4841132-A increases PPP1R3B through a cis genetic effect. Using CRISPR/Cas9 we engineered a 105-bp deletion including rs4841132-A in human hepatocarcinoma cells that increases PPP1R3B, decreases LOC157273, and increases glycogen perfectly mirroring the human disease. Overexpression of PPP1R3B or knockdown of LOC157273 increased glycogen but did not result in decreased LOC157273 or increased PPP1R3B, respectively, suggesting that the effects may not all occur via affecting RNA levels. Based on electronic health record (EHR) data, rs4841132-A associates with all components of the metabolic syndrome (MetS). However, rs4841132-A associated with decreased low-density lipoprotein (LDL) cholesterol and risk for myocardial infarction (MI). A metabolic signature for rs4841132-A includes increased glycine, lactate, triglycerides, and decreased acetoacetate and beta-hydroxybutyrate. CONCLUSIONS: These results show that rs4841132-A promotes a hepatic glycogen storage disease by increasing PPP1R3B and decreasing LOC157273. rs4841132-A promotes glycogen accumulation and development of MetS but lowers LDL cholesterol and risk for MI. These results suggest that elevated hepatic glycogen is one cause of MetS that does not invariably promote MI.

Mitochondrial GWAS and association of nuclear - mitochondrial epistasis with BMI in T1DM patients.

BACKGROUND: BMI is a strong indicator of complications from type I diabetes, especially under intensive treatment. METHODS: We have genotyped 435 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays and performed mitoGWAS on BMI. We identified additive interactions between mitochondrial and nuclear variants in genes associated with mitochondrial functioning MitoCarta2.0 and confirmed and refined the results on external cohorts: the Framingham Heart Study (FHS) and GTEx data. Linear mixed model analysis was performed using the GENESIS package in R/Bioconductor. RESULTS: We find a borderline significant association between the mitochondrial variant rs28357980, localized to MT-ND2, and BMI (ß = - 0.69, p = 0.056). This BMI association was confirmed on 1889 patients from FHS cohort (ß = - 0.312, p = 0.047). Next, we searched for additive interactions between mitochondrial and nuclear variants. MT-ND2 variants interacted with variants in the genes SIRT3, ATP5B, CYCS, TFB2M and POLRMT. TFB2M is a mitochondrial transcription factor and together with TFAM creates a transcription promoter complex for the mitochondrial polymerase POLRMT. We have found an interaction between rs3021088 in MT-ND2 and rs6701836 in TFB2M leading to BMI decrease (inter_pval = 0.0241), while interaction of rs3021088 in MT-ND2 and rs41542013 in POLRMT led to BMI increase (inter_pval = 0.0004). The influence of these interactions on BMI was confirmed in external cohorts. CONCLUSIONS: Here, we have shown that variants in the mitochondrial genome as well as additive interactions between mitochondrial and nuclear SNPs influence BMI in T1DM and general cohorts.

Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19.

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 17 dose-responsive compounds with in vitro antiviral efficacy in human liver Huh7 cells and confirmed antiviral efficacy in human colon carcinoma Caco-2, human prostate adenocarcinoma LNCaP, and in a physiologic relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein classically found in secretory fluids, including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.

Mitigating temozolomide resistance in glioblastoma via DNA damage-repair inhibition.

Glioblastomas are among the most lethal cancers, with a 5 year survival rate below 25%. Temozolomide is typically used in glioblastoma treatment; however, the enzymes alkylpurine-DNA-N-glycosylase (APNG) and methylguanine-DNA-methyltransferase (MGMT) efficiently mediate the repair of DNA damage caused by temozolomide, reducing treatment efficacy. Consequently, APNG and MGMT inhibition has been proposed as a way of overcoming chemotherapy resistance. Here, we develop a mechanistic mathematical model that explicitly incorporates the effects of chemotherapy on tumour cells, including the processes of DNA damage induction, cell arrest and DNA repair. Our model is carefully parametrized and validated, and then used to virtually recreate the response of heteroclonal glioblastomas to dual treatment with temozolomide and inhibitors of APNG/MGMT. Using our mechanistic model, we identify four combination treatment strategies optimized by tumour cell phenotype, and isolate the strategy most likely to succeed in a pre-clinical and clinical setting. If confirmed in clinical trials, these strategies have the potential to offset chemotherapy resistance in patients with glioblastoma and improve overall survival.