Proteomic Analysis of Idiopathic Nephrotic Syndrome Triggered by Primary Podocytopathies in Adults: Regulatory Mechanisms and Diagnostic Implications.

Idiopathic nephrotic syndrome (NS) is a heterogeneous group of glomerular disorders which includes two major phenotypes: minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS). MCD and FSGS are classic types of primary podocytopathies. We aimed to explore the molecular mechanisms in NS triggered by primary podocytopathies and evaluate diagnostic value of the selected proteomic signatures by analyzing blood proteome profiling. Totally, we recruited 90 participants in two cohorts. The first cohort was analyzed using label-free quantitative (LFQ) proteomics to discover differential expressed proteins and identify enriched biological process in NS which were further studied in relation to clinical markers of kidney injury. The second cohort was analyzed using parallel reaction monitoring-based quantitative proteomics to verify the data of LFQ proteomics and assess the diagnostic performance of the selected proteins using receiver-operating characteristic curve analysis. Several biological processes (such as immune response, cell adhesion, and response to hypoxia) were found to be associated with kidney injury during MCD and FSGS. Moreover, three proteins (CSF1, APOC3, and LDLR) had over 90% sensitivity and specificity in detecting adult NS triggered by primary podocytopathies. The identified biological processes may play a crucial role in MCD and FSGS pathogenesis. The three blood protein markers are promising for diagnosing adult NS triggered by primary podocytopathies.

Research progress on prediction of RNA-protein binding sites in the past five years.

Accurately predicting RNA-protein binding sites is essential to gain a deeper comprehension of the protein-RNA interactions and their regulatory mechanisms, which are fundamental in gene expression and regulation. However, conventional biological approaches to detect these sites are often costly and time-consuming. In contrast, computational methods for predicting RNA protein binding sites are both cost-effective and expeditious. This review synthesizes already existing computational methods, summarizing commonly used databases for predicting RNA protein binding sites. In addition, applications and innovations of computational methods using traditional machine learning and deep learning for RNA protein binding site prediction during 2018-2023 are presented. These methods cover a wide range of aspects such as effective database utilization, feature selection and encoding, innovative classification algorithms, and evaluation strategies. Exploring the limitations of existing computational methods, this paper delves into the potential directions for future development. DeepRKE, RDense, and DeepDW all employ convolutional neural networks and long and short-term memory networks to construct prediction models, yet their algorithm design and feature encoding differ, resulting in diverse prediction performances.

Machine learning in predicting T-score in the Oxford classification system of IgA nephropathy.

Background: Immunoglobulin A nephropathy (IgAN) is one of the leading causes of end-stage kidney disease (ESKD). Many studies have shown the significance of pathological manifestations in predicting the outcome of patients with IgAN, especially T-score of Oxford classification. Evaluating prognosis may be hampered in patients without renal biopsy. Methods: A baseline dataset of 690 patients with IgAN and an independent follow-up dataset of 1,168 patients were used as training and testing sets to develop the pathology T-score prediction (T pre) model based on the stacking algorithm, respectively. The 5-year ESKD prediction models using clinical variables (base model), clinical variables and real pathological T-score (base model plus T bio), and clinical variables and T pre (base model plus T pre) were developed separately in 1,168 patients with regular follow-up to evaluate whether T pre could assist in predicting ESKD. In addition, an external validation set consisting of 355 patients was used to evaluate the performance of the 5-year ESKD prediction model using T pre. Results: The features selected by AUCRF for the T pre model included age, systolic arterial pressure, diastolic arterial pressure, proteinuria, eGFR, serum IgA, and uric acid. The AUC of the T pre was 0.82 (95% CI: 0.80-0.85) in an independent testing set. For the 5-year ESKD prediction model, the AUC of the base model was 0.86 (95% CI: 0.75-0.97). When the T bio was added to the base model, there was an increase in AUC [from 0.86 (95% CI: 0.75-0.97) to 0.92 (95% CI: 0.85-0.98); P = 0.03]. There was no difference in AUC between the base model plus T pre and the base model plus T bio [0.90 (95% CI: 0.82-0.99) vs. 0.92 (95% CI: 0.85-0.98), P = 0.52]. The AUC of the 5-year ESKD prediction model using T pre was 0.93 (95% CI: 0.87-0.99) in the external validation set. Conclusion: A pathology T-score prediction (T pre) model using routine clinical characteristics was constructed, which could predict the pathological severity and assist clinicians to predict the prognosis of IgAN patients lacking kidney pathology scores.

Association between uric acid and risk of venous thromboembolism in East Asian populations: a cohort and Mendelian randomization study.

Background: Serum uric acid (SUA) levels have been associated with an increased risk and recurrence of venous thromboembolism (VTE) in European populations, but the potential causal relationship remains unclear. Large-scale studies on the association between SUA and VTE in East Asian populations are lacking, despite the high prevalence of hyperuricemia in this region. To address this, we conducted a cohort analysis and a two-sample Mendelian randomization (MR) study in East Asian populations. Methods: We collected data on VTE patients from the China Pulmonary Thromboembolism Registry Study (CURES) and compared them to controls obtained from the China Health and Retirement Longitudinal Survey (CHARLS). Propensity score matching (PSM) and cubic-spline models were applied to assess the effect of SUA on VTE risk while adjusting for multiple covariates. We also performed two-sample MR analyses to infer potential causality based on summary statistics from Genome-wide Association Studies (GWAS) of SUA and VTE in the East Asian population. Findings: We found that the SUA levels were higher in VTE patients (317.95 mmol/L) compared to the general population (295.75 mmol/L), and SUA ≥ 325 mmol/L was associated with an increased risk of VTE recurrence (P-value = 0.0001). The univariable MR suggested a causal relationship between elevated SUA and higher VTE risk (Pinverse variance weighted < 0.05), and multivariable MR showed that elevated SUA levels continued to promote the development of VTE after adjusting for multiple covariates (Pmultivariable residual < 0.05). Sensitivity analyses produced similar results for these estimations. Interpretation: Our study provides evidence supporting a robust positive association between SUA and VTE in the East Asian population, and MR analyses suggest that this association is likely to be causal. Our findings underscore the importance of monitoring SUA levels in VTE prevention and call for urgent action to address the growing burden of hyperuricemia in the Asia-Pacific region. Funding: This research was funded by Beijing Nova Program (No. Z211100002121057), National Natural Science Foundation of China (No. 82100065 and No. 62350004), CAMS Innovation Fund for Medical Sciences (No. 2021-I2M-1-061 and No. 2021-1-I2M-001), Elite Medical Professionals project of China-Japan Friendship Hospital (No. ZRJY2021-QM12), National Key Research and Development Project (No. 2021YFF1201200 and No. 2022YFC3341004).

Discrimination of Substandard and Falsified Formulations from Genuine Pharmaceuticals Using NIR Spectra and Machine Learning.

Near-infrared (NIR) spectroscopy is a promising technique for field identification of substandard and falsified drugs because it is portable, rapid, nondestructive, and can differentiate many formulated pharmaceutical products. Portable NIR spectrometers rely heavily on chemometric analyses based on libraries of NIR spectra from authentic pharmaceutical samples. However, it is difficult to build comprehensive product libraries in many low- and middle-income countries due to the large numbers of manufacturers who supply these markets, frequent unreported changes in materials sourcing and product formulation by the manufacturers, and general lack of cooperation in providing authentic samples. In this work, we show that a simple library of lab-formulated binary mixtures of an active pharmaceutical ingredient (API) with two diluents gave good performance on field screening tasks, such as discriminating substandard and falsified formulations of the API. Six data analysis models, including principal component analysis and support-vector machine classification and regression methods and convolutional neural networks, were trained on binary mixtures of acetaminophen with either lactose or ascorbic acid. While the models all performed strongly in cross-validation (on formulations similar to their training set), they individually showed poor robustness for formulations outside the training set. However, a predictive algorithm based on the six models, trained only on binary samples, accurately predicts whether the correct amount of acetaminophen is present in ternary mixtures, genuine acetaminophen formulations, adulterated acetaminophen formulations, and falsified formulations containing substitute APIs. This data analytics approach may extend the utility of NIR spectrometers for analysis of pharmaceuticals in low-resource settings.

Transcriptional Start Site Coverage Analysis in Plasma Cell-Free DNA Reveals Disease Severity and Tissue Specificity of COVID-19 Patients.

Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. A deep understanding of the variation of biological characteristics in severe COVID-19 patients is crucial for the detection of individuals at high risk of critical condition for the clinical management of the disease. Herein, by profiling the gene expression spectrum deduced from DNA coverage in regions surrounding transcriptional start site in plasma cell-free DNA (cfDNA) of COVID-19 patients, we deciphered the altered biological processes in the severe cases and demonstrated the feasibility of cfDNA in measuring the COVID-19 progression. The up- and downregulated genes in the plasma of severe patient were found to be closely related to the biological processes and functions affected by COVID-19 progression. More importantly, with the analysis of transcriptome data of blood cells and lung cells from control group and cases with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, we revealed that the upregulated genes were predominantly involved in the viral and antiviral activity in blood cells, reflecting the intense viral replication and the active reaction of immune system in the severe patients. Pathway analysis of downregulated genes in plasma DNA and lung cells also demonstrated the diminished adenosine triphosphate synthesis function in lung cells, which was evidenced to correlate with the severe COVID-19 symptoms, such as a cytokine storm and acute respiratory distress. Overall, this study revealed tissue involvement, provided insights into the mechanism of COVID-19 progression, and highlighted the utility of cfDNA as a noninvasive biomarker for disease severity inspections.

Deep sequencing of 1320 genes reveals the landscape of protein-truncating variants and their contribution to psoriasis in 19,973 Chinese individuals.

Protein-truncating variants (PTVs) have important impacts on phenotype diversity and disease. However, their population genetics characteristics in more globally diverse populations are not well defined. Here, we describe patterns of PTVs in 1320 genes sequenced in 10,539 healthy controls and 9434 patients with psoriasis, all of Han Chinese ancestry. We identify 8720 PTVs, of which 77% are novel, and estimate 88% of all PTVs are deleterious and subject to purifying selection. Furthermore, we show that individuals with psoriasis have a significantly higher burden of PTVs compared to controls (P = 0.02). Finally, we identified 18 PTVs in 14 genes with unusually high levels of population differentiation, consistent with the action of local adaptation. Our study provides insights into patterns and consequences of PTVs.

Preclinical Characterization of an Antibody-Drug Conjugate Targeting CS-1 and the Identification of Uncharacterized Populations of CS-1-Positive Cells.

Multiple myeloma is a hematologic cancer that disrupts normal bone marrow function and has multiple lines of therapeutic options, but is incurable as patients ultimately relapse. We developed a novel antibody-drug conjugate (ADC) targeting CS-1, a protein that is highly expressed on multiple myeloma tumor cells. The anti-CS-1 mAb specifically bound to cells expressing CS-1 and, when conjugated to a cytotoxic pyrrolobenzodiazepine payload, reduced the viability of multiple myeloma cell lines in vitro In mouse models of multiple myeloma, a single administration of the CS-1 ADC caused durable regressions in disseminated models and complete regression in a subcutaneous model. In an exploratory study in cynomolgus monkeys, the CS-1 ADC demonstrated a half-life of 3 to 6 days; however, no highest nonseverely toxic dose was achieved, as bone marrow toxicity was dose limiting. Bone marrow from dosed monkeys showed reductions in progenitor cells as compared with normal marrow. In vitro cell killing assays demonstrated that the CS-1 ADC substantially reduced the number of progenitor cells in healthy bone marrow, leading us to identify previously unreported CS-1 expression on a small population of progenitor cells in the myeloid-erythroid lineage. This finding suggests that bone marrow toxicity is the result of both on-target and off-target killing by the ADC.

Human Relaxin-2 Fusion Protein Treatment Prevents and Reverses Isoproterenol-Induced Hypertrophy and Fibrosis in Mouse Heart.

Background Heart failure is one of the leading causes of death in Western countries, and there is a need for new therapeutic approaches. Relaxin-2 is a peptide hormone that mediates pleiotropic cardiovascular effects, including antifibrotic, angiogenic, vasodilatory, antiapoptotic, and anti-inflammatory effects in vitro and in vivo. Methods and Results We developed RELAX10, a fusion protein composed of human relaxin-2 hormone and the Fc of a human antibody, to test the hypothesis that extended exposure of the relaxin-2 peptide could reduce cardiac hypertrophy and fibrosis. RELAX10 demonstrated the same specificity and similar in vitro activity as the relaxin-2 peptide. The terminal half-life of RELAX10 was 7 days in mouse and 3.75 days in rat after subcutaneous administration. We evaluated whether treatment with RELAX10 could prevent and reverse isoproterenol-induced cardiac hypertrophy and fibrosis in mice. Isoproterenol administration in mice resulted in increased cardiac hypertrophy and fibrosis compared with vehicle. Coadministration with RELAX10 significantly attenuated the cardiac hypertrophy and fibrosis compared with untreated animals. Isoproterenol administration significantly increased transforming growth factor ß1 (TGF-ß1)-induced fibrotic signaling, which was attenuated by RELAX10. We found that RELAX10 also significantly increased protein kinase B/endothelial NO synthase signaling and protein S-nitrosylation. In the reversal study, RELAX10-treated animals showed significantly reduced cardiac hypertrophy and collagen levels. Conclusions These findings support a potential role for RELAX10 in the treatment of heart failure.

Detecting Small Inversions Using SRinversion.

Rapid development of next generation sequencing (NGS) technology has substantially improved our ability to detect genomic variations. However, unlike other variations, such as point mutations, insertions, and deletions, which can be identified in high sensitivities and specificities based on NGS reads, most of inversions, especially those shorter than 1 kb, remain difficult to detect. Here we introduce a new framework, SRinversion, which was developed specifically for detection of inversions shorter than 1 kb by splitting and realigning poorly mapped or unmapped reads of the NGS data.

Novel identified associations of RGS1 and RASGRP1 variants in IgA Nephropathy.

Known susceptibility loci together can only explain about 6-8% of the disease heritability of IgA nephropathy (IgAN), suggesting that there are still a large number of genetic variants remained to be discovered. We previously identified IgAN and systemic lupus erythematosus (SLE)/lupus nephritis (LN) shared many loci based on GWAS on Chinese populations. The more recent study with high-density genotyping of immune-related loci in individuals with Asian ancestry identified 10 new and 6 suggestive loci in SLE. In the current study, we thus included all the lead SNPs from these 16 loci reported, and firstly tested their associations in 1,248 patients with sporadic IgAN, 737 patients with LN and 1,187 controls. Significant associations identified in IgAN were replicated in additional 500 patients and 2372 controls. rs12022418 in RGS1 (p = 3.0 × 10-6) and rs7170151 in RASGRP1 (p = 1.9 × 10-5) showed novel associations in IgAN. Compared to SNPs that were in LD with them, the associated variants showed higher potential of regulatory features by affecting gene expression. And systemic evaluation of GWAS data supported the pleiotropic effects of RGS1 and RASGRP1 variants in mediating human complex diseases. In conclusion, novel risk loci shared between IgAN and SLE/LN were identified, which may shed new light to exploit the potential pathogenesis for those two diseases.

SRinversion: a tool for detecting short inversions by splitting and re-aligning poorly mapped and unmapped sequencing reads.

MOTIVATION: Rapid development in sequencing technologies has dramatically improved our ability to detect genetic variants in human genome. However, current methods have variable sensitivities in detecting different types of genetic variants. One type of such genetic variants that is especially hard to detect is inversions. Analysis of public databases showed that few short inversions have been reported so far. Unlike reads that contain small insertions or deletions, which will be considered through gap alignment, reads carrying short inversions often have poor mapping quality or are unmapped, thus are often not further considered. As a result, the majority of short inversions might have been overlooked and require special algorithms for their detection. RESULTS: Here, we introduce SRinversion, a framework to analyze poorly mapped or unmapped reads by splitting and re-aligning them for the purpose of inversion detection. SRinversion is very sensitive to small inversions and can detect those less than 10 bp in size. We applied SRinversion to both simulated data and high-coverage sequencing data from the 1000 Genomes Project and compared the results with those from Pindel, BreakDancer, DELLY, Gustaf and MID. A better performance of SRinversion was achieved for both datasets for the detection of small inversions. AVAILABILITY AND IMPLEMENTATION: SRinversion is implemented in Perl and is publicly available at http://paed.hku.hk/genome/software/SRinversion/index.html CONTACT: yangwl@hku.hkSupplementary information: Supplementary data are available at Bioinformatics online.

Genome-wide association meta-analysis in Chinese and European individuals identifies ten new loci associated with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE; OMIM 152700) is a genetically complex autoimmune disease. Genome-wide association studies (GWASs) have identified more than 50 loci as robustly associated with the disease in single ancestries, but genome-wide transancestral studies have not been conducted. We combined three GWAS data sets from Chinese (1,659 cases and 3,398 controls) and European (4,036 cases and 6,959 controls) populations. A meta-analysis of these studies showed that over half of the published SLE genetic associations are present in both populations. A replication study in Chinese (3,043 cases and 5,074 controls) and European (2,643 cases and 9,032 controls) subjects found ten previously unreported SLE loci. Our study provides further evidence that the majority of genetic risk polymorphisms for SLE are contained within the same regions across both populations. Furthermore, a comparison of risk allele frequencies and genetic risk scores suggested that the increased prevalence of SLE in non-Europeans (including Asians) has a genetic basis.

Meta-analysis of GWAS on two Chinese populations followed by replication identifies novel genetic variants on the X chromosome associated with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease that affects mainly females. What role the X chromosome plays in the disease has always been an intriguing question. In this study, we examined the genetic variants on the X chromosome through meta-analysis of two genome-wide association studies (GWAS) on SLE on Chinese Han populations. Prominent association signals from the meta-analysis were replicated in 4 additional Asian cohorts, with a total of 5373 cases and 9166 matched controls. We identified a novel variant in PRPS2 on Xp22.3 as associated with SLE with genome-wide significance (rs7062536, OR = 0.84, P = 1.00E-08). Association of the L1CAM-MECP2 region with SLE was reported previously. In this study, we identified independent contributors in this region in NAA10 (rs2071128, OR = 0.81, P = 2.19E-13) and TMEM187 (rs17422, OR = 0.75, P = 1.47E-15), in addition to replicating the association from IRAK1-MECP2 region (rs1059702, OR = 0.71, P = 2.40E-18) in Asian cohorts. The X-linked susceptibility variants showed higher effect size in males than that in females, similar to results from a genome-wide survey of associated SNPs on the autosomes. These results suggest that susceptibility genes identified on the X chromosome, while contributing to disease predisposition, might not contribute significantly to the female predominance of this prototype autoimmune disease.

Discovery of biclonal origin and a novel oncogene SLC12A5 in colon cancer by single-cell sequencing.

Single-cell sequencing is a powerful tool for delineating clonal relationship and identifying key driver genes for personalized cancer management. Here we performed single-cell sequencing analysis of a case of colon cancer. Population genetics analyses identified two independent clones in tumor cell population. The major tumor clone harbored APC and TP53 mutations as early oncogenic events, whereas the minor clone contained preponderant CDC27 and PABPC1 mutations. The absence of APC and TP53 mutations in the minor clone supports that these two clones were derived from two cellular origins. Examination of somatic mutation allele frequency spectra of additional 21 whole-tissue exome-sequenced cases revealed the heterogeneity of clonal origins in colon cancer. Next, we identified a mutated gene SLC12A5 that showed a high frequency of mutation at the single-cell level but exhibited low prevalence at the population level. Functional characterization of mutant SLC12A5 revealed its potential oncogenic effect in colon cancer. Our study provides the first exome-wide evidence at single-cell level supporting that colon cancer could be of a biclonal origin, and suggests that low-prevalence mutations in a cohort may also play important protumorigenic roles at the individual level.

The Genome of the Netherlands: design, and project goals.

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project.

YHap: a population model for probabilistic assignment of Y haplogroups from re-sequencing data.

BACKGROUND: Y haplogroup analyses are an important component of genealogical reconstruction, population genetic analyses, medical genetics and forensics. These fields are increasingly moving towards use of low-coverage, high throughput sequencing. While there have been methods recently proposed for assignment of Y haplogroups on the basis of high-coverage sequence data, assignment on the basis of low-coverage data remains challenging. RESULTS: We developed a new algorithm, YHap, which uses an imputation framework to jointly predict Y chromosome genotypes and assign Y haplogroups using low coverage population sequence data. We use data from the 1000 genomes project to demonstrate that YHap provides accurate Y haplogroup assignment with less than 2x coverage. CONCLUSIONS: Borrowing information across multiple samples within a population using an imputation framework enables accurate Y haplogroup assignment.

Interaction of the novel antipsychotic aripiprazole with 5-HT1A and 5-HT 2A receptors: functional receptor-binding and in vivo electrophysiological studies.

BACKGROUND: Aripiprazole (7-{4-[4-(2,3-dichlorophenyl)-1-piperazinyl]butoxy}-3,4-dihydro-2(1H)-quinolinone) is a novel antipsychotic with a mechanism of action that differs from current typical and atypical antipsychotics. Aripiprazole interacts with a range of receptors, including serotonin [5-hydroxytryptamine (5-HT)] and dopamine receptors. MATERIALS AND METHODS: This study examined aripiprazole's interactions with 5-HT systems in vitro and in vivo to further clarify its pharmacologic properties. RESULTS: Aripiprazole produced increases in [(35)S]GTPgammaS binding to rat hippocampal membranes. Its potency (pEC(50) = 7.2) was similar to that of ziprasidone (7.1) and greater than that of 5-HT (6.7) and buspirone (6.4), a 5-HT(1A)-receptor partial agonist, whereas its intrinsic activity was similar to that of ziprasidone and buspirone. The stimulatory effect of aripiprazole was blocked by WAY-100635, a 5-HT(1A)-receptor antagonist. In in vivo electrophysiology studies, aripiprazole produced a dose-related reduction in the firing rate of 5-HT-containing dorsal raphe neurons in rats, which was both prevented and reversed by WAY-100635 administration. Aripiprazole showed a high affinity for human 5-HT(1A) receptors (K (i) = 4.2 nM) using parietal cortex membrane preparations. In membranes from cells expressing human recombinant receptors, aripiprazole bound with high affinity to 5-HT(2A) receptors (K (i) = 3.4 nM), moderate affinity to 5-HT(2C) (K (i) = 15 nM) and 5-HT(7) (K (i) = 39 nM) receptors, and low affinity to 5-HT(6) receptors (K (i) = 214 nM) and 5-HT transporter (K (i) = 98 nM). In addition, aripiprazole potently blocked 5-HT(2A)-receptor-mediated increases in intracellular Ca(2+) levels in a rat pituitary cell line (IC(50) = 11 nM). DISCUSSION: These results support a partial agonist activity for aripiprazole at 5-HT(1A) receptors in vitro and in vivo, and suggest important interactions with other 5-HT-receptor subtypes. This receptor activity profile may contribute to the antipsychotic activity of aripiprazole in humans.

Dopamine D2 receptor partial agonists display differential or contrasting characteristics in membrane and cell-based assays of dopamine D2 receptor signaling.

Clinical evidence suggests that dopamine D(2) receptor partial agonists must have a sufficiently low intrinsic activity to be effective as antipsychotics. Here, we used dopamine D(2) receptor signaling assays to compare the in vitro functional characteristics of the antipsychotic aripiprazole with other dopamine D(2) receptor partial agonists (7-{3-[4-(2,3-dimethylphenyl)-piperazinyl]propoxy}-2(1H)-quinolinone [OPC-4392], (-)-3-(3-hydroxy-phenyl)-N-n-propylpiperidine [(-)3-PPP] and (+)terguride) and dopamine D(2) receptor antagonists. Aripiprazole and OPC-4392 were inactive in a guanosine-5'-O-(3-[(35)S]thio)-triphosphate ([(35)S]GTPgammaS) binding assay using Chinese Hamster Ovary (CHO) cell membranes expressing cloned human dopamine D(2Long) (hD(2L)) receptors, whereas (-)3-PPP and (+)terguride displayed low intrinsic activity. Aripiprazole also had no effect on [(35)S]GTPgammaS binding to CHO-hD(2L) cells, while OPC-4392, (-)3-PPP and (+)terguride were partial agonists. In contrast, aripiprazole, OPC-4392, (-)3-PPP, and (+)terguride were inactive in a [(35)S]GTPgammaS binding assay using rat striatal membranes. However, at a more downstream level of CHO-hD(2L) cell signalling, these drugs all behaved as dopamine hD(2L) receptor partial agonists, with aripiprazole displaying an intrinsic activity 2 to 3-fold lower (inhibition of forskolin-induced adenosine 3',5'-cyclic monophosphate accumulation) and almost half as high (enhancement of adenosine triphosphate-stimulated [(3)H]arachidonic acid release) as OPC-4392, (-)3-PPP and (+)terguride. Dopamine activity was blocked in each case by (-)raclopride, which was inactive on its own in every assay, as were the antipsychotics haloperidol, olanzapine, ziprasidone and clozapine. Together, these data, whilst preclinical in nature, are consistent with clinical evidence suggesting the favorable antipsychotic profile of aripiprazole, compared with the other clinically ineffective partial agonists, is dependent on its low intrinsic activity at dopamine D(2) receptors. This study also highlights the limitations of using [(35)S]GTPgammaS binding assays to identify dopamine D(2) receptor partial agonists.