A Quantitative Computational Framework for Allopolyploid Single-Cell Data Integration and Core Gene Ranking in Development.

Polyploidization drives regulatory and phenotypic innovation. How the merger of different genomes contributes to polyploid development is a fundamental issue in evolutionary developmental biology and breeding research. Clarifying this issue is challenging because of genome complexity and the difficulty in tracking stochastic subgenome divergence during development. Recent single-cell sequencing techniques enabled probing subgenome-divergent regulation in the context of cellular differentiation. However, analyzing single-cell data suffers from high error rates due to high dimensionality, noise, and sparsity, and the errors stack up in polyploid analysis due to the increased dimensionality of comparisons between subgenomes of each cell, hindering deeper mechanistic understandings. In this study, we develop a quantitative computational framework, called "pseudo-genome divergence quantification" (pgDQ), for quantifying and tracking subgenome divergence directly at the cellular level. Further comparing with cellular differentiation trajectories derived from single-cell RNA sequencing data allows for an examination of the relationship between subgenome divergence and the progression of development. pgDQ produces robust results and is insensitive to data dropout and noise, avoiding high error rates due to multiple comparisons of genes, cells, and subgenomes. A statistical diagnostic approach is proposed to identify genes that are central to subgenome divergence during development, which facilitates the integration of different data modalities, enabling the identification of factors and pathways that mediate subgenome-divergent activity during development. Case studies have demonstrated that applying pgDQ to single-cell and bulk tissue transcriptomic data promotes a systematic and deeper understanding of how dynamic subgenome divergence contributes to developmental trajectories in polyploid evolution.

MR-BOIL: Causal inference in one-sample Mendelian randomization for binary outcome with integrated likelihood method.

Mendelian randomization is a statistical method for inferring the causal relationship between exposures and outcomes using an economics-derived instrumental variable approach. The research results are relatively complete when both exposures and outcomes are continuous variables. However, due to the noncollapsing nature of the logistic model, the existing methods inherited from the linear model for exploring binary outcome cannot take the effect of confounding factors into account, which leads to biased estimate of the causal effect. In this article, we propose an integrated likelihood method MR-BOIL to investigate causal relationships for binary outcomes by treating confounders as latent variables in one-sample Mendelian randomization. Under the assumption of a joint normal distribution of the confounders, we use expectation maximization algorithm to estimate the causal effect. Extensive simulations demonstrate that the estimator of MR-BOIL is asymptotically unbiased and that our method improves statistical power without inflating type I error rate. We then apply this method to analyze the data from Atherosclerosis Risk in Communications Study. The results show that MR-BOIL can better identify plausible causal relationships with high reliability, compared with the unreliable results of existing methods. MR-BOIL is implemented in R and the corresponding R code is provided for free download.

Cancer-associated dynamics and potential regulators of intronic polyadenylation revealed by IPAFinder using standard RNA-seq data.

Intronic polyadenylation (IpA) usually leads to changes in the coding region of an mRNA, and its implication in diseases has been recognized, although at its very beginning status. Conveniently and accurately identifying IpA is of great importance for further evaluating its biological significance. Here, we developed IPAFinder, a bioinformatic method for the de novo identification of intronic poly(A) sites and their dynamic changes from standard RNA-seq data. Applying IPAFinder to 256 pan-cancer tumor/normal pairs across six tumor types, we discovered 490 recurrent dynamically changed IpA events, some of which are novel and derived from cancer-associated genes such as TSC1, SPERD2, and CCND2 Furthermore, IPAFinder revealed that IpA could be regulated by factors related to splicing and m6A modification. In summary, IPAFinder enables the global discovery and characterization of biologically regulated IpA with standard RNA-seq data and should reveal the biological significance of IpA in various processes.

A weighted Bayesian integration method for predicting drug combination using heterogeneous data.

BACKGROUND: In the management of complex diseases, the strategic adoption of combination therapy has gained considerable prominence. Combination therapy not only holds the potential to enhance treatment efficacy but also to alleviate the side effects caused by excessive use of a single drug. Presently, the exploration of combination therapy encounters significant challenges due to the vast spectrum of potential drug combinations, necessitating the development of efficient screening strategies. METHODS: In this study, we propose a prediction scoring method that integrates heterogeneous data using a weighted Bayesian method for drug combination prediction. Heterogeneous data refers to different types of data related to drugs, such as chemical, pharmacological, and target profiles. By constructing a multiplex drug similarity network, we formulate new features for drug pairs and propose a novel Bayesian-based integration scheme with the introduction of weights to integrate information from various sources. This method yields support strength scores for drug combinations to assess their potential effectiveness. RESULTS: Upon comprehensive comparison with other methods, our method shows superior performance across multiple metrics, including the Area Under the Receiver Operating Characteristic Curve, accuracy, precision, and recall. Furthermore, literature validation shows that many top-ranked drug combinations based on the support strength score, such as goserelin and letrozole, have been experimentally or clinically validated for their effectiveness. CONCLUSIONS: Our findings have significant clinical and practical implications. This new method enhances the performance of drug combination predictions, enabling effective pre-screening for trials and, thereby, benefiting clinical treatments. Future research should focus on developing new methods for application in various scenarios and for integrating diverse data sources.

Association between homocysteine and nonalcoholic fatty liver disease: Mendelian randomisation study.

BACKGROUND: Many observational studies explore the relationship between homocysteine (Hcy) and nonalcoholic fatty liver disease (NAFLD), whereas the causality of this association remains uncertain, especially in European populations. We performed a bidirectional Mendelian randomisation study to elucidate the causal association between Hcy and NAFLD. Furthermore, we explored the relationship of Hcy with liver enzymes, including alkaline phosphatase (ALP), alanine aminotransferase (ALT) and aspartate aminotransferase (AST). METHODS: Two-sample Mendelian randomisation study was conducted. Summary statistics for Hcy were obtained from a genome-wide association studies (GWAS) meta-analysis comprising 44,147 subjects. Summary-level data for NAFLD were acquired from a GWAS meta-analysis of 8434 cases and 770,180 noncases and another GWAS meta-analysis of 1483 cases and 17,781 noncases. Summary-level data for three liver enzymes were available from the UK Biobank. RESULTS: Genetic associations of Hcy concentrations with NAFLD and liver enzymes were observed. Genetically predicted higher Hcy concentrations were consistently associated with an increased NAFLD risk in two data sources. The combined odds ratio of NAFLD was 1.25 (95% confidence interval [CI], 1.05-1.45) per SD increase in Hcy concentrations. Genetically predicted higher Hcy concentrations showed significant association with ALP (Beta .69; 95% CI, 0.04-1.34), ALT (Beta 0.56; 95% CI, 0.15-0.97) and AST levels (Beta .57; 95% CI, 0.10-1.04). Genetic liability to NAFLD was not associated with Hcy concentrations. CONCLUSIONS: This study has clinical implications as it indicates that increased Hcy concentrations increase the relevant liver enzymes and may play a role in NAFLD risk in European populations.

Novel gene signatures for prognosis prediction in ovarian cancer.

Ovarian cancer (OV) is one of the leading causes of cancer deaths in women worldwide. Late diagnosis and heterogeneous treatment result to poor survival outcomes for patients with OV. Therefore, we aimed to develop novel biomarkers for prognosis prediction from the potential molecular mechanism of tumorigenesis. Eight eligible data sets related to OV in GEO database were integrated to identify differential expression genes (DEGs) between tumour tissues and normal. Enrichment analyses discovered DEGs were most significantly enriched in G2/M checkpoint signalling pathway. Subsequently, we constructed a multi-gene signature based on the LASSO Cox regression model in the TCGA database and time-dependent ROC curves showed good predictive accuracy for 1-, 3- and 5-year overall survival. Utility in various types of OV was validated through subgroup survival analysis. Risk scores formulated by the multi-gene signature stratified patients into high-risk and low-risk, and the former inclined worse overall survival than the latter. By incorporating this signature with age and pathological tumour stage, a visual predictive nomogram was established, which was useful for clinicians to predict survival outcome of patients. Furthermore, SNRPD1 and EFNA5 were selected from the multi-gene signature as simplified prognostic indicators. Higher EFNA5 expression or lower SNRPD1 indicated poorer outcome. The correlation between signature gene expression and clinical characteristics was observed through WGCNA. Drug-gene interaction was used to identify 16 potentially targeted drugs for OV treatment. In conclusion, we established novel gene signatures as independent prognostic factors to stratify the risk of OV patients and facilitate the implementation of personalized therapies.

Indirect effect inference and application to GAW20 data.

BACKGROUND: Association studies using a single type of omics data have been successful in identifying disease-associated genetic markers, but the underlying mechanisms are unaddressed. To provide a possible explanation of how these genetic factors affect the disease phenotype, integration of multiple omics data is needed. RESULTS: We propose a novel method, LIPID (likelihood inference proposal for indirect estimation), that uses both single nucleotide polymorphism (SNP) and DNA methylation data jointly to analyze the association between a trait and SNPs. The total effect of SNPs is decomposed into direct and indirect effects, where the indirect effects are the focus of our investigation. Simulation studies show that LIPID performs better in various scenarios than existing methods. Application to the GAW20 data also leads to encouraging results, as the genes identified appear to be biologically relevant to the phenotype studied. CONCLUSIONS: The proposed LIPID method is shown to be meritorious in extensive simulations and in real-data analyses.

Auxin Extraction and Purification Based on Recombinant Aux/IAA Proteins.

BACKGROUND: Indole-3-acetic acid (IAA) extraction and purification are of great importance in auxin research, which is a hot topic in the plant growth and development field. Solid-phase extraction (SPE) is frequently used for IAA extraction and purification. However, no IAA-specific SPE columns are commercially available at the moment. Therefore, the development of IAA-specific recognition materials and IAA extraction and purification methods will help researchers meet the need for more precise analytical methods for research on phytohormones. RESULTS: Since the AUXIN RESISTANT/INDOLE-3-ACETIC ACID INDUCIBLE (Aux/IAA) proteins show higher specific binding capability with auxin, recombinant IAA1, IAA7 and IAA28 proteins were used as sorbents to develop an IAA extraction and purification method. A GST tag was used to solidify the recombinant protein in a column. Aux/IAA proteins solidified in a column have successfully trapped trace IAA in aqueous solutions. The IAA7 protein showed higher IAA binding capability than the other proteins tested. In addition, expression of the IAA7 protein in Drosophila Schneider 2 (S2) cells produced better levels of binding than IAA7 expressed in E. coli. CONCLUSION: This work validated the potential of Aux/IAA proteins to extract and purify IAA from crude plant extracts once we refined the techniques for these processes.

Block-based association tests for rare variants using Kullback-Leibler divergence.

Although genome-wide association studies have successfully detected numerous associations between common variants and complex diseases, these variants typically can only explain a small part of the heritable component of a disease. With the advent of next-generation sequencing, attention has turned to rare variants. Recently, a variety of approaches for detecting associations of rare variants have been proposed, including the Kullback-Leibler divergence-based tests (KLTs) for detecting genotypic differences between cases and controls. However, few of these approaches consider linkage disequilibrium (LD) structure among rare variants and common variants. In this study, we propose two block-based association tests for testing the effects of rare variants on a disease. The main idea for this approach comes from the hypothesis that a region of interest may consist of two or more LD blocks such that single-nucleotide variants (SNVs) within each block are correlated, whereas SNVs in different blocks are independent or weakly correlated. Under this hypothesis, we propose two tests that are generalizations of the KLTs by taking the block structure into account. A simulation study under various scenarios shows that the proposed methods have well-controlled type I error rates and outperform some leading methods in the literature. Moreover, application to the Dallas Heart Study data demonstrates the feasibility and performance of the two proposed methods in a realistic setting.

Detecting multiple variants associated with disease based on sequencing data of case-parent trios.

With the advance of next-generation sequencing technology, the rare variants join the common ones in explaining more proportions of heritability. The coexistence of variants of common with rare, causal with neutral and deleterious with protective is a norm and should be appropriately addressed. Some existing methods suffer from low power when one or more forms of coexistence present, impeding their applications in practice. In this paper, for case-parent trios, pseudocontrols are constructed using the nontransmitted alleles of the parents. The Kullback-Leibler divergence is utilized to measure the difference between the distributions of variants in a genetic region for the affected children and pseudocontrols, and two nonparametric test statistics KLTT and cKLTT are proposed. Extensive simulations show that they are robust to the opposite directions of the causal variants and the amount of neutral variants, and have superiority over the existing methods when both rare and common variants are involved. Furthermore, their efficiency is demonstrated in the application to the data from Framingham Heart Study.

Kullback-Leibler distance methods for detecting disease association with rare variants from sequencing data.

Because next generation sequencing technology that can rapidly genotype most genetic variations genome, there is considerable interest in investigating the effects of rare variants on complex diseases. In this paper, we propose four Kullback-Leibler distance-based Tests (KLTs) for detecting genotypic differences between cases and controls. There are several features that set the proposed tests apart from existing ones. First, by explicitly considering and comparing the distributions of genotypes, existence of variants with opposite directional effects does not compromise the power of KLTs. Second, it is not necessary to set a threshold for rare variants as the KL definition makes it reasonable to consider rare and common variants together without worrying about the contribution from one type overshadowing the other. Third, KLTs are robust to null variants thanks to a built-in noise fighting mechanism. Finally, correlation among variants is taken into account implicitly so the KLTs work well regardless of the underlying LD structure. Through extensive simulations, we demonstrated good performance of KLTs compared to the sum of squared score test (SSU) and optimal sequence kernel association test (SKAT-O). Moreover, application to the Dallas Heart Study data illustrates the feasibility and performance of KLTs in a realistic setting.

Higher prevalence of migraine in essential tremor: a case-control study.

BACKGROUND: The existence of an association between migraine and essential tremor has long been controversial. The prevalence of migraine in essential tremor patients was surveyed to explore the association between the two diseases. METHODS: A case-control clinical study was conducted to investigate the prevalence of migraine in 150 consecutive essential tremor patients and in 150 matched controls without tremor. Detailed information about essential tremor and migraine was obtained using a structured questionnaire at a face-to-face interview. Moreover, a functional variant of the dopamine receptor D3 gene (Ser9Gly, rs6280) was studied in 46 essential tremor patients with and without migraine using direct sequencing analysis. RESULTS: The prevalence of lifetime migraine in essential tremor patients was significantly higher than that in controls (22.0% vs. 12.7%; p=0.035; odds ratio=1.95; 95% confidence interval=1.05-3.60). No significant difference was found in the migraine features between the essential tremor and control groups and most tremor characteristics were no different in essential tremor patients with and without migraine. A higher male prevalence of essential tremor patients without migraine was observed. Moreover, 44 of 46 (95.7%) essential tremor patients had the dopamine receptor D3 Ser9Gly variant, but no significant difference was found in the frequencies of the variant between essential tremor patients with and without migraine (87.5% vs. 100.0%; p=0.22). CONCLUSION: Our data suggest that essential tremor patients have a higher risk of lifetime migraine than do controls and the dopamine receptor D3 Ser9Gly variant may be lower in essential tremor with migraine than the general essential tremor patients.

Exploring Causal Relationships Between Gut Microbiota and Alzheimer's Disease: A Bidirectional Mendelian Randomization Study.

Background: Many observational studies have investigated the link between the gut microbiota and Alzheimer's disease (AD), but the causality remains uncertain. Objective: This study aimed to evaluate the causal impact of gut microbiota on AD. Methods: A two-sample Mendelian randomization (MR) study was conducted employing summary data. Summary statistics for AD were from the latest genome-wide association study (cases and proxy cases: 85,934; controls: 401,577). Summary data for gut microbiota were acquired from MiBioGen consortium. Causal effect estimations primarily relied on the inverse variance weighting method along with the sensitivity analyses for testing for pleiotropy and heterogeneity. Additionally, reverse MR analyses were performed to examine potential reverse causality. Results: Seven gut microbiota were identified as associated with AD risk. Order Selenomonadales (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.03-1.24, p = 0.01), Family Pasteurellaceae (OR 1.07, 95% CI 1.01-1.13, p = 0.01), and Genus Methanobrevibacter (OR 1.07, 95% CI 1.00-1.13, p = 0.04) were correlated with an elevated likelihood of AD, while Class Mollicutes (OR 0.87, 95% CI 0.79-0.95, p = 0.00), Genus Ruminiclostridium9 (OR 0.87, 95% CI 0.78-0.97, p = 0.01), Genus Clostridiuminnocuumgroup (OR 0.94, 95% CI 0.89-0.99, p = 0.03), and Genus Eggerthella (OR 0.94, 95% CI 0.89-1.00, p = 0.04) exerted beneficial impact in mitigating AD. No statistically significant reverse causality was found between AD and each of these seven specific gut microbiota species. Conclusions: This study unveiled a causal link between certain gut microbiota and AD, offering new insights for advancing clinical treatments.

The change of intimate relationship between people with Alzheimer's disease and their adult child caregivers: An interpretative phenomenological analysis.

This study aims to explore the change of intimate relationship between people with Alzheimer's disease and their adult child caregivers as the disease progresses. Twelve adult child caregivers were recruited through purposive sampling. Explanatory phenomenological analysis was conducted to analyse data collected by semi-structured in-depth interviews. This study found a dynamically changing relationship between adult child caregivers and their parents with Alzheimer's disease during care giving that evolved with the progress of the disease. The relationship was the most intimate in the middle stage of the disease for most caregivers and a new reciprocal relationship developed due to caregiving. Caregivers experienced different degrees of self-growth when providing care, though caregiver burdens were common. The positive experience and perception of caregivers were important for improving the quality of life for adult child caregivers of people with Alzheimer's disease.

Development of substituted N-[3-(3-methoxylphenyl)propyl] amides as MT(2)-selective melatonin agonists: improving metabolic stability.

A series of novel and selective N-[3-(6-benzyloxy-3-methoxyphenyl)propyl] amides has recently been shown to possess sub-nanomolar range binding affinity to the type 2 melatonin receptor (MT(2)). Pharmacokinetics studies suggested that these compounds were subject to vigorous CYP450-mediated metabolism, resulting in a series of metabolites with significantly decreased or diminished binding affinities toward MT(2) receptor. The ether bonds were found to be the major positions susceptible to metabolism. In this study, the benzyl ether bond was either removed or replaced with a carbon-carbon bond in an attempt to improve metabolic stability and enhance their resistance towards phase I oxidation. The synthesis, receptor binding affinity, intrinsic potency and metabolic stability of modified structures are reported in this article. By removal or replacement of metabolic labile ether linkerage with carbon linkers, a novel compound was identified with good potency and MT(2) selectivity, and with increased metabolic stability.

Design, synthesis and evaluation of novel heterodimers of donepezil and huperzine fragments as acetylcholinesterase inhibitors.

Four series of novel heterodimers comprised of donepezil and huperzine A (HupA) fragments were designed, synthesized, and evaluated in search of potent acetylcholinesterase (AChE) inhibitors as potential therapeutic treatment for Alzheimer's disease. Heterodimers comprised of dimethoxyindanone (from donepezil), hupyridone (from HupA), and connected with a multimethylene linker, were identified as potent and selective inhibitors of AChE. Diastereomeric heterodimers (RS,S)-17b (with a tetramethylene linker) exhibited the highest potency of inhibition towards AChE with an IC(50) value of 9 nM and no detectable inhibitory effect on butyrylcholinesterase at 1mM.

Bi-directional causal effect between vitamin B12 and non-alcoholic fatty liver disease: Inferring from large population data.

Objectives: Many observational studies evaluate the association between vitamin B12 and non-alcoholic fatty liver disease (NAFLD). However, the causality of this association remains uncertain, especially in European populations. We conducted a bidirectional Mendelian randomization study to explore the association between vitamin B12 and NAFLD. Methods: Two-sample Mendelian randomization study was conducted. Summary statistics for vitamin B12 were acquired from a genome-wide association studies (GWAS) meta-analysis including 45,576 subjects. Summary-level data for NAFLD was obtained from a GWAS meta-analysis of 8,434 cases and 770,180 non-cases and another GWAS meta-analysis of 1,483 cases and 17,781 non-cases. Summary-level data for 4 enzymes including alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma glutamyltransferase (GGT), was available from the UK Biobank. Inverse variance weighting (as main analysis), weighted median estimate, robust adjusted profile score, MR-Egger, and MR-PRESSO (sensitivity analyses) were performed to calculate causal estimates. Results: Genetically predicted higher vitamin B12 concentrations were consistently associated with an increased NAFLD in two sources. The combined odds ratio (OR) of NAFLD was 1.30 (95% confidence interval (CI), 1.13 to 1.48; p < 0.001) per SD-increase in vitamin B12 concentrations. Genetic liability to NAFLD was also positively associated with vitamin B12 concentrations (Beta 0.08, 95%CI, 0.01 to 0.16; p = 0.034). Sensitivity analyses also revealed consistent results. Genetically predicted vitamin B12 concentrations showed no significant association with liver enzymes. Conclusion: The present study indicates that increased serum vitamin B12 concentrations may play a role in NAFLD risk. NAFLD also has a causal impact on elevated vitamin B12 concentrations in the circulation. Notably, vitamin B12 concentrations imply the levels of vitamin B12 in the circulation, and higher intake of vitamin B12 may not directly lead to higher levels of serum vitamin B12, instead the higher levels of vitamin B12 in the circulation may be caused by the dysregulation of the metabolism of this vitamin in this study. There exist bidirectional causal effects between serum vitamin B12 concentrations and risk of NAFLD in European individuals.

Identification of a coagulation-related signature correlated with immune infiltration and their prognostic implications in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a fatal form of lung cancer with a poor prognosis. Coagulation system had been confirmed closely related to tumor progression and the hypercoagulable state encouraged the immune infiltration and development of tumor cells, leading to a poor prognosis in cancer patients. However, the use of the coagulation-related genes (CRGs) for prognosis in LUAD has yet to be determined. In this study, we constructed an immune-related signature (CRRS) and identified a potential coagulation-related biomarker (P2RX1). METHODS: We obtained a total of 209 CRGs based on two coagulation-related KEGG pathways, then developed the CRRS signature by using the TCGA-LUAD RNA-seq data via the procedure of LASSO-Cox regression, stepwise-Cox regression, univariate and multivariate Cox regression. Grouped by the CRRS, Kaplan-Meier survival curves and receiver operating characteristic curves were drawn for the training and validation sets, respectively. In addition, single-sample gene set enrichment analysis was exploited to explore immune infiltration level. Moreover, immunophenotypes and immunotherapy grouped by CRRS were further analyzed. RESULTS: We developed an immune-related signature (CRRS) composed of COL1A2, F2, PLAUR, C4BPA, and P2RX1 in LUAD. CRRS was an independent risk factor for overall survival and displayed stable and powerful performance. Additionally, CRRS possessed distinctly superior accuracy than traditional clinical variables and molecular features. Functional analysis indicated that the differentially high expressed genes in the low-risk group significantly enriched in T cell and B cell receptor signaling pathways. The low-risk group was sensitive to anti-PD-1/PD-L1 immunotherapy and displayed abundant immune infiltration and immune checkpoint gene expression. Finally, we identified an independent prognostic gene P2RX1. Low expression of P2RX1 associated with poor overall survival and decreased immune infiltration. CONCLUSIONS: Our study revealed a significant correlation between CRRS and immune infiltration. CRRS could serve as a promising tool to improve the clinical outcomes for individual LUAD patients.

A powerful parent-of-origin effects test for qualitative traits incorporating control children in nuclear families.

Genomic imprinting is an important epigenetic phenomenon in studying complex traits and has generally been examined by detecting parent-of-origin effects of alleles. The parental-asymmetry test (PAT) based on nuclear families with both parents and its extensions to deal with missing parental genotypes is simple and powerful for such a task. However, these methods only use case (affected) children in nuclear families and thus do not make full use of information on control (unaffected) children, if available, in these families. In this article, we propose a novel parent-of-origin effects test C-PATu (the combined test of PATu and 1-PATu) by using both the control and case children in nuclear families with one or both parents. C-PATu is essentially a weighted framework, in which the test based on all the control children and their parents and that based on all the case children and their parents are weighted according to the population disease prevalence. Simulation results demonstrate that the proposed tests control the size well under no parent-of-origin effects and using additional information from control children improves the power of the tests under the imprinting alternative. Application of C-PATu to a Framingham Heart Study data set further shows the feasibility in practical application of the test.

Pharmacokinetics, oral bioavailability and metabolism of a novel isoquinolinone-based melatonin receptor agonist in rats.

7-Methoxy-6-(3-methoxy-benzyloxy)-2-methylisoquinolin-1(2H)-one (named as IS0042) is a newly identified melatoninergic agonist which exhibits selectivity to the type 2 melatonin receptor. Here, we examined the in vitro and in vivo pharmacokinetics properties of IS0042 in rats. IS0042 was considerably lipophilic with a modest aqueous solubility of 27.3 µg/mL. It was stable in simulated gastrointestinal fluid, and readily penetrated across differentiated Caco-2 cell model of intestinal barrier, suggesting good oral absorption. IS0042 underwent metabolism in rat intestinal and liver microsomes with an in vitro half-life of 367.5 ± 36.6 and 17.5 ± 2.7 min, respectively. Metabolite identification suggested that the major biotransformation pathways included the cleavage of ether bond, hydroxylation and demethylation. The same metabolites were also present in blood circulation following oral administration, indicating a good correlation between in vitro and in vivo metabolism. The pharmacokinetics parameters of IS0042 were evaluated after intravenous administration (10 or 25 mg/kg) and oral administration (100 mg/kg) of the drug to rats. IS0042 showed moderate clearance (0.73-1.02 L/h/kg), large volume of distribution (1.76-3.16 L/kg) and long elimination half-life (3.11-6.04 h) after intravenous administration. The absolute oral bioavailability of IS0042 was relatively low (9.8-18.6%). Overall, these results provide important parameters for the further development of this novel class of melatoninergic ligands.