Fluoxetine-induced hepatic lipid accumulation is mediated by prostaglandin endoperoxide synthase 1 and is linked to elevated 15-deoxy-Δ12,14PGJ2

Major depressive disorder and other neuropsychiatric disorders are often managed with long-term use of antidepressant medication. Fluoxetine, an SSRI antidepressant, is widely used as a first-line treatment for neuropsychiatric disorders. However, fluoxetine has also been shown to increase the risk of metabolic diseases such as non-alcoholic fatty liver disease. Fluoxetine has been shown to increase hepatic lipid accumulation in vivo and in vitro. In addition, fluoxetine has been shown to alter the production of prostaglandins which have also been implicated in the development of non-alcoholic fatty liver disease. The goal of this study was to assess the effect of fluoxetine exposure on the prostaglandin biosynthetic pathway and lipid accumulation in a hepatic cell line (H4-II-E-C3 cells). Fluoxetine treatment increased mRNA expression of prostaglandin biosynthetic enzymes (Ptgs1, Ptgs2, and Ptgds), PPAR gamma (Pparg), and PPAR gamma downstream targets involved in fatty acid uptake (Cd36, Fatp2, and Fatp5) as well as production of 15-deoxy-Δ^12,14PGJ₂ a PPAR gamma ligand. The effects of fluoxetine to induce lipid accumulation were attenuated with a PTGS1 specific inhibitor (SC-560), whereas inhibition of PTGS2 had no effect. Moreover, SC-560 attenuated 15-deoxy-Δ^12,14PGJ₂ production and expression of PPAR gamma downstream target genes. Taken together these results suggest that fluoxetine-induced lipid abnormalities appear to be mediated via PTGS1 and its downstream product 15d-PGJ₂ and suggest a novel therapeutic target to prevent some of the adverse effects of fluoxetine treatment.     

Human metabolism: pathways and clinical aspects

Metabolism describes the series of chemical reactions that are concerned with the provision of energy to biological systems. They may be divided into reactions involved in energy yield (catabolism: demand exceeds supply), and energy storage (anabolism: supply exceeds demand). Regulation of these pathways is critical for homeostasis, and derangements in metabolism are seen in a wide variety of pathological processes. Understanding metabolism is key to the treatment of many diseases, notably diabetes, as well as underpinning clinical nutritional support.     

Hepatic effects of repeated oral administration of diclofenac to hepatic cytochrome P450 reductase null (HRN™) and wild-type mice

Hepatic NADPH-cytochrome P450 oxidoreductase null (HRN?) mice exhibit normal hepatic and extrahepatic biotransformation enzyme activities when compared to wild-type (WT) mice, but express no functional hepatic cytochrome P450 activities. When incubated in vitro with [¹⁴C]-diclofenac, liver microsomes from WT mice exhibited extensive biotransformation to oxidative and glucuronide metabolites and covalent binding to proteins was also observed. In contrast, whereas glucuronide conjugates and a quinone-imine metabolite were formed when [¹⁴C]-diclofenac was incubated with HRN? mouse liver, only small quantities of P450-derived oxidative metabolites were produced in these samples and covalent binding to proteins was not observed. Livers from vehicle-treated HRN? mice exhibited enhanced lipid accumulation, bile duct proliferation, hepatocellular degeneration and necrosis and inflammatory cell infiltration, which were not present in livers from WT mice. Elevated liver-derived alanine aminotransferase, glutamate dehydrogenase and alkaline phosphatase activities were also observed in plasma from HRN? mice. When treated orally with diclofenac for 7 days, at 30 mg/kg/day, the severities of the abnormal liver histopathology and plasma liver enzyme findings in HRN? mice were reduced markedly. Oral diclofenac administration did not alter the liver histopathology or elevate plasma enzyme activities of WT mice. These findings indicate that HRN? mice are valuable for exploration of the role played by hepatic P450s in drug biotransformation, but poorly suited to investigations of drug-induced liver toxicity. Nevertheless, studies in HRN? mice could provide novel insights into the role played by inflammation in liver injury and may aid the evaluation of new strategies for its treatment.     

Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.     

Epithelial ovarian cancer risk: A review of the current genetic landscape

Ovarian cancer is the fourth most common cause of cancer-related death in women in the developed world, and one of the most heritable cancers. One of the most significant risk factors for epithelial ovarian cancer (EOC) is a family history of breast and/or ovarian cancer. Combined risk factors can be used in models to stratify risk of EOC, and aid in decisions regarding risk-reduction strategies. Germline pathogenic variants in EOC susceptibility genes including those involved in homologous recombination and mismatch repair pathways are present in approximately 22% to 25% of EOC. These genes are associated with an estimated lifetime risk of EOC of 13% to 60% for BRCA1 variants and 10% to 25% for BRCA2 variants, with lower risks associated with remaining genes. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) thought to explain an additional 6.4% of the familial risk of ovarian cancer, with 34 susceptibility loci identified to date. However, an unknown proportion of the genetic component of EOC risk remains unexplained. This review comprises an overview of individual genes and SNPs suspected to contribute to risk of EOC, and discusses use of a polygenic risk score to predict individual cancer risk more accurately.     

Embryonic skull development in the gecko,Tarentola annularis (Squamata: Gekkota: Phyllodactylidae)

Tarentola annularis is a climbing gecko with a wide distribution in Africa north of the equator. In the present paper, we describe the development of the osteocranium of this lizard, from the first appearance of the cranial elements up to the point of hatching. This is based on a combination of histology and cleared and stained specimens. This is the first comprehensive account of gekkotan pre-hatching skull development based on a comprehensive series of embryos, rather than a few selected stages. Given that Gekkota is now widely regarded as representing the sister group to other squamates, this account helps to fill a significant gap in the literature. Moreover, as many authors have considered features of the gekkotan skull and skeleton to be indicative of paedomorphosis, it is important to know whether this hypothesis is supported by delays in the onset of cranial ossification. In fact, we found the sequence of cranial bone ossification to be broadly comparable to that of other squamates studied to date, with no significant lags in development.