Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning

Osteoarthritis (OA) is increasing in prevalence and has a severe impact on patients' lives. However, our understanding of biomarkers driving OA risk remains limited. We developed a model predicting the five-year risk of OA diagnosis, integrating retrospective clinical, lifestyle and biomarker data from the UK Biobank (19,120 patients with OA, ROC-AUC: 0.72, 95%CI (0.71-0.73)). Higher age, BMI and prescription of non-steroidal anti-inflammatory drugs contributed most to increased OA risk prediction ahead of diagnosis. We identified 14 subgroups of OA risk profiles. These subgroups were validated in an independent set of patients evaluating the 11-year OA risk, with 88% of patients being uniquely assigned to one of the 14 subgroups. Individual OA risk profiles were characterised by personalised biomarkers. Omics integration demonstrated the predictive importance of key OA genes and pathways (e.g., GDF5 and TGF-β signalling) and OA-specific biomarkers (e.g., CRTAC1 and COL9A1). In summary, this work identifies opportunities for personalised OA prevention and insights into its underlying pathogenesis.

Evaluation of long acting GLP1R/GCGR agonist in a DIO and biopsy-confirmed mouse model of NASH suggest a beneficial role of GLP-1/glucagon agonism in NASH patients

OBJECTIVE

The metabolic benefits of GLP-1 receptor (GLP-1R) agonists on glycemic and weight control are well established as therapy for type 2 diabetes and obesity. Glucagon's ability to increase energy expenditure is well described, and the combination of these mechanisms-of-actions has the potential to further lower hepatic steatosis in metabolic disorders and could therefore be attractive for the treatment for non-alcoholic steatohepatitis (NASH). Here, we have investigated the effects of a dual GLP-1/glucagon receptor agonist NN1177 on hepatic steatosis, fibrosis, and inflammation in a preclinical mouse model of NASH. Having observed strong effects on body weight loss in a pilot study with NN1177, we hypothesized that direct engagement of the hepatic glucagon receptor (GCGR) would result in a superior effect on steatosis and other liver related parameters as compared to the GLP-1R agonist semaglutide at equal body weight.

METHODS

Male C57Bl/6 mice were fed a diet high in trans-fat, fructose, and cholesterol (Diet-Induced Obese (DIO)-NASH) for 36 weeks. Following randomization based on the degree of fibrosis at baseline, mice were treated once daily with subcutaneous administration of a vehicle or three different doses of NN1177 or semaglutide for 8 weeks. Hepatic steatosis, inflammation and fibrosis were assessed by immunohistochemistry and morphometric analyses. Plasma levels of lipids and liver enzymes were determined, and hepatic gene expression was analyzed by RNA sequencing.

RESULTS

NN1177 dose-dependently reduced body weight up to 22% compared to vehicle treatment. Plasma levels of ALT, a measure of liver injury, were reduced in all treatment groups with body weight loss. The dual agonist reduced hepatic steatosis to a greater extent than semaglutide at equal body weight loss, as demonstrated by three independent methods. Both the co-agonist and semaglutide significantly decreased histological markers of inflammation such as CD11b and Galectin-3, in addition to markers of hepatic stellate activation (αSMA) and fibrosis (Collagen I). Interestingly, the maximal beneficial effects on above mentioned clinically relevant endpoints of NN1177 treatment on hepatic health appear to be achieved with the middle dose tested. Administering the highest dose resulted in a further reduction of liver fat and accompanied by a massive induction in genes involved in oxidative phosphorylation and resulted in exaggerated body weight loss and a downregulation of a module of co-expressed genes involved in steroid hormone biology, bile secretion, and retinol and linoleic acid metabolism that are also downregulated due to NASH itself.

CONCLUSIONS

These results indicate that, in a setting of overnutrition, the liver health benefits of activating the fasting-related metabolic pathways controlled by the glucagon receptor displays a bell-shaped curve. This observation is of interest to the scientific community, due to the high number of ongoing clinical trials attempting to leverage the positive effects of glucagon biology to improve metabolic health.

Profiling the genome and proteome of metabolic dysfunction-associated steatotic liver disease identifies potential therapeutic targets

BACKGROUND & AIMS

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over 25% of the population and currently has no effective treatments. Plasma proteins with causal evidence may represent promising drug targets. We aimed to identify plasma proteins in the causal pathway of MASLD and explore their interaction with obesity.

METHODS

We analysed 2,941 plasma proteins in 43,978 European participants from UK Biobank. We performed genome-wide association study (GWAS) for all MASLD-associated proteins and created the largest MASLD GWAS (109,885 cases/1,014,923 controls). We performed Mendelian Randomization (MR) and integrated proteins and their encoding genes in MASLD ranges to identify candidate causal proteins. We then validated them through independent replication, exome sequencing, liver imaging, bulk and single-cell gene expression, liver biopsies, pathway, and phenome-wide data. We explored the role of obesity by MR and multivariable MR across proteins, body mass index, and MASLD.

RESULTS

We found 929 proteins associated with MASLD, reported five novel genetic loci associated with MASLD, and identified 17 candidate MASLD protein targets. We identified four novel targets for MASLD (CD33, GRHPR, HMOX2, and SCG3), provided protein evidence supporting roles of AHCY, FCGR2B, ORM1, and RBKS in MASLD, and validated nine previously known targets. We found that CD33, FCGR2B, ORM1, RBKS, and SCG3 mediated the association of obesity and MASLD, and HMOX2, ORM1, and RBKS had effect on MASLD independent of obesity.

CONCLUSIONS

This study identified new protein targets in the causal pathway of MASLD, providing new insights into the multi-omics architecture and pathophysiology of MASLD. These findings advise further therapeutic interventions for MASLD.

MLX plays a key role in lipid and glucose metabolism in humans: Evidence from in vitro and in vivo studies

BACKGROUND AND AIM

Enhanced hepatic de novo lipogenesis (DNL) has been proposed as an underlying mechanism for the development of NAFLD and insulin resistance. Max-like protein factor X (MLX) acts as a heterodimer binding partner for glucose sensing transcription factors and inhibition of MLX or downstream targets has been shown to alleviate intrahepatic triglyceride (IHTG) accumulation in mice. However, its effect on insulin sensitivity remains unclear. As human data is lacking, the aim of the present work was to investigate the role of MLX in regulating lipid and glucose metabolism in primary human hepatocytes (PHH) and in healthy participants with and without MLX polymorphisms.

METHODS

PHH were transfected with non-targeting or MLX siRNA to assess the effect of MLX knockdown on lipid and glucose metabolism, insulin signalling and the hepatocellular transcriptome. A targeted association analysis on imputed genotype data for MLX on healthy individuals was undertaken to assess associations between specific MLX SNPs (rs665268, rs632758 and rs1474040), plasma biochemistry, IHTG content, DNL and gluconeogenesis.

RESULTS

MLX knockdown in PHH altered lipid metabolism (decreased DNL (p < 0.05), increased fatty acid oxidation and ketogenesis (p < 0.05), and reduced lipid accumulation (p < 0.001)). Additionally, MLX knockdown increased glycolysis, lactate secretion and glucose production (p < 0.001) and insulin-stimulated pAKT levels (p < 0.01) as assessed by transcriptomic, steady-state and dynamic measurements. Consistent with the in vitro data, individuals with the rs1474040-A and rs632758-C variants had lower fasting plasma insulin (p < 0.05 and p < 0.01, respectively) and TG (p < 0.05 and p < 0.01, respectively). Although there was no difference in IHTG or gluconeogenesis, individuals with rs632758 SNP had notably lower hepatic DNL (p < 0.01).

CONCLUSION

We have demonstrated using human in vitro and in vivo models that MLX inhibition favored lipid catabolism over anabolism and increased glucose production, despite increased glycolysis and phosphorylation of Akt, suggesting a metabolic mechanism that involves futile cycling.

Central androgen action reverses hypothalamic astrogliosis and atherogenic risk factors induced by orchiectomy and high-fat diet feeding in male mice

Hypogonadism in males confers elevated cardiovascular disease (CVD) risk by unknown mechanisms. Recent radiological evidence suggests that low testosterone (T) is associated with mediobasal hypothalamic (MBH) gliosis, a central nervous system (CNS) cellular response linked to metabolic dysfunction. To address mechanisms linking CNS androgen action to CVD risk, we generated a hypogonadal, hyperlipidemic mouse model with orchiectomy (ORX) combined with hepatic PCSK9 overexpression. After 4 wk of high-fat, high-sucrose diet (HFHS) consumption, despite equal body weights and glucose tolerance, androgen-deficient ORX mice had a more atherogenic lipid profile and increased liver and leukocyte inflammatory signaling compared with sham-operated control mice. Along with these early CVD risk indicators, ORX markedly amplified HFHS-induced astrogliosis in the MBH. Transcriptomic analysis further revealed that ORX and high-fat diet feeding induced upregulation of inflammatory pathways and downregulation of metabolic pathways in hypothalamic astrocytes. To interrogate the role of sex steroid signaling in the CNS in cardiometabolic risk and MBH inflammation, central infusion of T and dihydrotestosterone (DHT) was performed on ORX mice. Central DHT prevented MBH astrogliosis and reduced the liver inflammatory signaling and monocytosis induced by HFHS and ORX; T had a partial protective effect. Finally, a cross-sectional study in 41 adult men demonstrated a positive correlation between radiological evidence of MBH gliosis and plasma lipids. These findings demonstrate that T deficiency in combination with a Western-style diet promotes hypothalamic gliosis concomitant with increased atherogenic risk factors and provide supportive evidence for regulation of lipid metabolism and cardiometabolic risk determinants by the CNS action of sex steroids.NEW & NOTEWORTHY This study provides evidence that hypothalamic gliosis is a key early event through which androgen deficiency in combination with a Western-style diet might lead to cardiometabolic dysregulation in males. Furthermore, this work provides the first evidence in humans of a positive association between hypothalamic gliosis and LDL-cholesterol, advancing our knowledge of CNS influences on CVD risk progression.

NMDA Receptor Antagonists Increase the Release of GLP-1 From Gut Endocrine Cells

Type 2 diabetes mellitus (T2DM) remains one of the most pressing health issues facing modern society. Several antidiabetic drugs are currently in clinical use to treat hyperglycaemia, but there is a need for new treatments that effectively restore pancreatic islet function in patients. Recent studies reported that both murine and human pancreatic islets exhibit enhanced insulin release and β-cell viability in response to N-methyl-D-aspartate (NMDA) receptor antagonists. Furthermore, oral administration of dextromethorphan, an over-the-counter NMDA receptor antagonist, to diabetic patients in a small clinical trial showed improved glucose tolerance and increased insulin release. However, the effects of NMDA receptor antagonists on the secretion of the incretin hormone GLP-1 was not tested, and nothing is known regarding how NMDA receptor antagonists may alter the secretion of gut hormones. This study demonstrates for the first time that, similar to β-cells, the NMDA receptor antagonist MK-801 increases the release of GLP-1 from a murine L-cell enteroendocrine model cell line, GLUTag cells. Furthermore, we report the 3′ mRNA expression profiling of GLUTag cells, with a specific focus on glutamate-activated receptors. We conclude that if NMDA receptor antagonists are to be pursued as an alternative, orally administered treatment for T2DM, it is essential that the effects of these drugs on the release of gut hormones, and specifically the incretin hormones, are fully investigated.

Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10-6). Novel reciprocal case-control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

Using common genetic variation to examine phenotypic expression and risk prediction in 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11DS) is associated with a 20-25% risk of schizophrenia. In a cohort of 962 individuals with 22q11DS, we examined the shared genetic basis between schizophrenia and schizophrenia-related early trajectory phenotypes: sub-threshold symptoms of psychosis, low baseline intellectual functioning and cognitive decline. We studied the association of these phenotypes with two polygenic scores, derived for schizophrenia and intelligence, and evaluated their use for individual risk prediction in 22q11DS. Polygenic scores were not only associated with schizophrenia and baseline intelligence quotient (IQ), respectively, but schizophrenia polygenic score was also significantly associated with cognitive (verbal IQ) decline and nominally associated with sub-threshold psychosis. Furthermore, in comparing the tail-end deciles of the schizophrenia and IQ polygenic score distributions, 33% versus 9% of individuals with 22q11DS had schizophrenia, and 63% versus 24% of individuals had intellectual disability. Collectively, these data show a shared genetic basis for schizophrenia and schizophrenia-related phenotypes and also highlight the future potential of polygenic scores for risk stratification among individuals with highly, but incompletely, penetrant genetic variants.

Functional module detection through integration of single-cell RNA sequencing data with protein-protein interaction networks

Background

Recent advances in single-cell RNA sequencing have allowed researchers to explore transcriptional function at a cellular level. In particular, single-cell RNA sequencing reveals that there exist clusters of cells with similar gene expression profiles, representing different transcriptional states.

Results

In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted protein–protein interaction networks, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As case studies, we investigate two RNA-sequencing data sets from human liver spheroids and human adipose tissue, respectively. With scPPIN we expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the protein–protein interaction networks significantly enriched which represent biological pathways. In these pathways, scPPIN identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differential expressed gene analysis.

Conclusions

The introduced scPPIN method can be used to systematically analyse differentially expressed genes in single-cell RNA sequencing data by integrating it with protein interaction data. The detected modules that characterise each cluster help to identify and hypothesise a biological function associated to those cells. Our analysis suggests the participation of unexpected proteins in these pathways that are undetectable from the single-cell RNA sequencing data alone. The techniques described here are applicable to other organisms and tissues.

Supplementary Information

The online version contains supplementary material available at (doi:10.1186/s12864-020-07144-2).