Ketamine and Esketamine in Clinical Trials: FDA-Approved and Emerging Indications, Trial Trends With Putative Mechanistic Explanations.

Ketamine has a long and very eventful pharmacological history. Its enantiomer, esketamine ((S)-ketamine), was approved by the US Food and Drug Administration (FDA) and EMA for patients with treatment-resistant depression (TRD) in 2019. The number of approved indications for ketamine and esketamine continues to increase, as well as the number of clinical trials. This analysis provides a quantitative overview of the use of ketamine and its enantiomers in clinical trials during 2014-2024. A total of 363 trials were manually assessed from clinicaltrial.gov with the search term "Ketamine." The highest number of trials were found for the FDA-approved indications: anesthesia (~22%) and pain management (~28%) for ketamine and TRD for esketamine (~29%). Clinical trials on TRD for both ketamine and esketamine also comprised a large proportion of these trials, and interestingly, have reached phase III and phase IV status. Combinatorial treatment of psychiatric disorders and non-psychiatric conditions with pharmacological and non-pharmacological combinations (electroconvulsive therapy, psychotherapeutic techniques, virtual reality, and transcranial magnetic stimulation) is prevalent. Sub-anesthetic doses of ketamine may represent novel therapeutic avenues in neuropsychiatric conditions, that is, major depression, schizophrenia, and bipolar disorder, where glutamate excitotoxicity and oxidative stress are likely to be involved. The study suggests that the number of ketamine studies will continue to grow and possible ketamine variants can be approved for treatment of additional indications.

Genomic Validation in the UK Biobank Cohort Suggests a Role of C8B and MFG-E8 in the Pathogenesis of Trigeminal Neuralgia.

Trigeminal neuralgia (TN) is a severe facial pain disease of uncertain pathophysiology and unclear genetic background. Although recent research has reported a more important role of genetic factors in TN pathogenesis, few candidate genes have been proposed to date. The present study aimed to identify independent genetic variants in the protein-coding genes associated with TN. We focused on genes previously linked to TN based on the results of four proteomic studies conducted by our research team. The goal was to validate these findings on the genetic level to enhance our understanding of the role of genetics in TN. The study is based on the participants from UK Biobank cohort. Following quality control, 175 independent single nucleotide polymorphisms (SNPs) in 17 genes were selected. The study sample comprised of diagnosed TN cases (N = 555) and randomly matched controls (N = 6245) based on specific criteria. Two SNPs corresponding to C8B rs706484 [odds ratio (OR) (95% confidence interval (CI)): 1.357 (1.158-1.590); p: 0.00016] and MFG-E8 rs2015495 [OR (95% CI): 1.313 (1.134-1.521); p: 0.00028] showed significant positive association with TN, indicating a positive effect of the SNP alleles on gene expression and disease risk. Interestingly, both SNPs are Expression Quantitative Trait Loci (eQTLs), and are associated with changes in the expression activity of their corresponding gene. Our findings suggest novel genetic associations between C8B, a key component of the complement system, and MFG-E8, which plays a role in regulating neuroinflammation, in relation to TN. The identified genetic variations may help explain why some individuals develop TN while others do not, indicating a potential genetic predisposition to the condition.

Recent developments of topoisomerase inhibitors: Clinical trials, emerging indications, novel molecules and global sales.

The nucleic acid topoisomerases (TOP) are an evolutionary conserved mechanism to solve topological problems within DNA and RNA that have been historically well-established as a chemotherapeutic target. During investigation of trends within clinical trials, we have identified a very high number of clinical trials involving TOP inhibitors, prompting us to further evaluate the current status of this class of therapeutic agents. In total, we have identified 233 unique molecules with TOP-inhibiting activity. In this review, we provide an overview of the clinical drug development highlighting advances in current clinical uses and discussing novel drugs and indications under development. A wide range of bacterial infections, along with solid and hematologic neoplasms, represent the bulk of clinically approved indications. Negative ADR profile and drug resistance among the antibacterial TOP inhibitors and anthracycline-mediated cardiotoxicity in the antineoplastic TOP inhibitors are major points of concern, subject to continuous research efforts. Ongoing development continues to focus on bacterial infections and cancer; however, there is a degree of diversification in terms of novel drug classes and previously uncovered indications, such as glioblastoma multiforme or Clostridium difficile infections. Preclinical studies show potential in viral, protozoal, parasitic and fungal infections as well and suggest the emergence of a novel target, TOP IIIß. We predict further growth and diversification of the field thanks to the large number of experimental TOP inhibitors emerging.

The Concentration of Liver-Expressed Antimicrobial Peptide 2 in Human Milk and Infant Plasma Is Positively Associated with Adiposity and Body Weight in the First Year of Life.

BACKGROUND: The liver-expressed antimicrobial peptide 2 (LEAP2) is a recently recognized anorectic and glucose-regulating hormone with an unknown role in lactation. OBJECTIVES: The objectives of this study were as follows: 1) to assess LEAP2 presence in human milk and putative associations with infant body weight and adiposity in the first year of life, 2) to evaluate the impact of maternal weight status on LEAP2 concentration, and 3) to explore the relationship between infant plasma LEAP2 concentration and body weight and adiposity. METHODS: This prospective cohort observational study assessed LEAP2 concentration in plasma and milk from lactating women with normal weight (n = 26) or overweight or obesity (OW/OB, n = 26) at 6 mo postpartum and in 6-mo-old infant plasma, examining associations with metabolic and anthropometric variables at 6 mo and 1 y. Maternal plasma and milk leptin and insulin concentrations were also measured. LEAP2 expression in milk fat globules and single-cell-RNA-sequencing datasets was evaluated. RESULTS: LEAP2 was detected in all milk samples assessed (2.08 ± 0.65 ng/mL) and was positively associated with infant triceps (P = 0.022, Cohen f2 = 1.25) and subscapular (P = 0.008, f2 = 0.68) skinfolds at 1 y old. Maternal LEAP2 was positively associated with insulin (P = 0.005, f2 = 0.30) and prepregnancy body mass index (BMI) (P = 0.040, f2 = 0.17) and negatively associated with gestational weight gain (P = 0.008, f2 = 0.25) and postpartum weight retention (P = 0.036, f2 = 0.15). Maternal LEAP2 was higher in plasma (P = 0.039), but not milk of lactating women with OW/OB. Infant plasma LEAP2 (1.98 ± 0.28 ng/mL) was positively associated with weight (P = 0.004, f2 = 0.63), BMI (P = 0.049, f2 = 0.37), and weight-for-length (P = 0.024, f2 = 0.35) z-scores at 1 y old, predominantly in males. No evidence for LEAP2 mRNA expression was found in mammary cells. CONCLUSIONS: Milk LEAP2 is a bioactive component that plays a role in infant fat accretion in the first year of life. Although maternal LEAP2 responds to weight change in pregnancy and lactation, infant plasma LEAP2 might be involved in body weight regulation in early life. This trial was registered at clinicaltrials.gov as NCT05798676.

LEAP2 is associated with impulsivity and reward sensitivity depending on the nutritional status and decreases with protein intake in humans.

AIM: Liver-expressed antimicrobial peptide 2 (LEAP2) dynamics in human plasma and its association with feeding behaviour remain poorly understood. Therefore, this study aims: (a) to investigate fasting LEAP2 in participants with normal weight or with overweight or mild obesity (OW/OB); (b) to study the association between fasting LEAP2 and anthropometric and metabolic traits, feeding behaviour, LEAP2 genetic variants and blood cell DNA methylation status; and (c) to ascertain postprandial changes in LEAP2 after high protein intake and the association with feeding behaviour and food intake. METHODS: Anthropometric and behavioural measures, genotyping, methylation profiling, plasma glucose and LEAP2 concentrations were assessed in 327 females and males. A subgroup of 123 participants received an ad libitum high-protein meal, and postprandial LEAP2 concentration and behavioural measures were assessed. RESULTS: LEAP2 concentration was higher in participants with OW/OB (p < 0.001) and in females (p < 0.001), and was associated with LEAP2 single nucleotide polymorphisms rs765760 (p = 0.012) and rs803223 (p = 0.019), but not with LEAP2 methylation status. LEAP2 concentration was directly related to glycaemia (p = 0.001) and fullness (p = 0.003) in participants with normal weight, whereas it was associated with body mass index (p = 0.018), waist circumference (p = 0.014) and motor impulsivity in participants with OW/OB (p = 0.005). A negative association with reward responsiveness was observed in participants with OW/OB (p = 0.023). LEAP2 concentration was inversely associated with food intake (p = 0.034) and decreased after a high-protein meal (p < 0.001), particularly in women (p = 0.002). CONCLUSION: Increased LEAP2 in participants with OW/OB is associated with behavioural characteristics of obesity. Our results show sexual dimorphism in LEAP2 concentration before and after food intake and highlight the role of LEAP2 in feeding regulation.

Off-target effects of statins: molecular mechanisms, side effects and the emerging role of kinases.

Statins are one of the most important classes of drugs. In this analytical review, we elucidate the intricate molecular mechanisms and toxicological rationale regarding both the on- (targeting 3-hydroxy-3-methylglutaryl-coenzyme A reductase [HMGCR]) and off-target effects of statins. Statins interact with a number of membrane kinases, such as epidermal growth factor receptor (EGFR), erb-b2 receptor tyrosine kinase 2 (HER2) and MET proto-oncogene, receptor tyrosine kinase (MET), as well as cytosolic kinases, such as SRC proto-oncogene, non-receptor tyrosine kinase (Src) and show inhibitory activity at nanomolar concentrations. In addition, they interact with calcium ATPases and peroxisome proliferator-activated receptor α (PPARα/NR1C1) at higher concentrations. Statins interact with mitochondrial complexes III and IV, and their inhibition of coenzyme Q10 synthesis also impairs the functioning of complexes I and II. Statins act as inhibitors of kinases, calcium ATPases and mitochondrial complexes, while activating PPARα. These off-target effects likely contribute to the side effects observed in patients undergoing statin therapy, including musculoskeletal symptoms and hepatic effects. Interestingly, some off-target effects of statins could also be the cause of favourable outcomes, relating to repurposing statins in conditions such as inflammatory disorders and cancer.

Oxytocin pathway gene variation and corticostriatal resting-state functional connectivity.

Genetic variations in single nucleotide polymorphisms (SNPs) within oxytocin pathway genes have been linked to social behavior and neurodevelopmental conditions. However, the neurobiological mechanisms underlying these associations remain elusive. In this study, we investigated the relationship between variations of 10 SNPs in oxytocin pathway genes and resting-state functional connectivity among 55 independent components using a large sample from the UK Biobank (N ≈ 30,000). Our findings revealed that individuals with the GG genotype at rs4813627 within the oxytocin structural gene (OXT) exhibited weaker resting-state functional connectivity in the corticostriatal circuit compared to those with the GA/AA genotypes. Empirical evidence has linked the GG genotype at OXT rs4813627 with a behavioral tendency of insensitivity to others. These results inform the neural mechanisms by which oxytocin-related genetic factors can influence social behavior.

Association of polygenic scores for autism with volumetric MRI phenotypes in cerebellum and brainstem in adults.

Previous research on autism spectrum disorders (ASD) have showed important volumetric alterations in the cerebellum and brainstem. Most of these studies are however limited to case-control studies with small clinical samples and including mainly children or adolescents. Herein, we aimed to explore the association between the cumulative genetic load (polygenic risk score, PRS) for ASD and volumetric alterations in the cerebellum and brainstem, as well as global brain tissue volumes of the brain among adults at the population level. We utilized the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and constructed the ASD PRS in an independent cohort, the UK Biobank. Regression analyses controlled for multiple comparisons with the false-discovery rate (FDR) at 5% were performed to investigate the association between ASD PRS and forty-four brain magnetic resonance imaging (MRI) phenotypes among ~ 31,000 participants. Primary analyses included sixteen MRI phenotypes: total volumes of the brain, cerebrospinal fluid (CSF), grey matter (GM), white matter (WM), GM of whole cerebellum, brainstem, and ten regions of the cerebellum (I_IV, V, VI, VIIb, VIIIa, VIIIb, IX, X, CrusI and CrusII). Secondary analyses included twenty-eight MRI phenotypes: the sub-regional volumes of cerebellum including the GM of the vermis and both left and right lobules of each cerebellar region. ASD PRS were significantly associated with the volumes of seven brain areas, whereby higher PRS were associated to reduced volumes of the whole brain, WM, brainstem, and cerebellar regions I-IV, IX, and X, and an increased volume of the CSF. Three sub-regional volumes including the left cerebellar lobule I-IV, cerebellar vermes VIIIb, and X were significantly and negatively associated with ASD PRS. The study highlights a substantial connection between susceptibility to ASD, its underlying genetic etiology, and neuroanatomical alterations of the adult brain.

Long-term changes in adiposity markers during and after antidepressant therapy in a community cohort.

Research on antidepressant-related weight changes over more than 12 months is scarce and adjustment for the effects of depressive episodes has rarely been applied. Accordingly, our aim was to assess the associations of the use of any antidepressants, subclasses of antidepressant and specific compounds prior to baseline and during a 5.5-year follow-up with changes in adiposity markers, and the effect of sex on these associations, with adjustment for multiple confounders including the effects of depressive episodes and their severity. Data stemmed from a prospective cohort study including 2479 randomly selected 35-66 year-old residents of an urban area (mean age 49.9 years, 53.3% women) who underwent physical and psychiatric evaluations at baseline and follow-up. Weight, height, waist circumference, and body fat were measured by trained nurses and information on diagnosis and antidepressant use prior to baseline and during follow-up was collected through standardized interviews. In the fully adjusted models, the number of antidepressants, mainly SSRIs and TCAs, used prior to baseline, was associated with a lower increase of body-mass index (BMI, ß (95%CI) = -0.12 (-0.19, -0.05)) and waist circumference (ß = -0.28 (-0.56, -0.01)), whereas participants treated with antidepressants during the follow-up had a steeper increase in BMI (ß = 0.32 (0.13, 0.50)) and waist circumference (ß = 1.23 (0.44, 2.01)). Within the class of SSRIs, the use of fluoxetine, sertraline or escitalopram during follow-up was associated with a steeper increase in adiposity markers. The associations of SSRIs with BMI and waist circumference were only observed when the SSRIs were used during the second period of the follow-up. Sex did not moderate these associations. Our findings suggest an increase of adiposity markers during sustained treatment with TCAs and SSRIs, which however return to normal levels after cessation of treatment. Hence, the benefit of long-term administration of these antidepressants should be carefully weighed against the potential risk of weight gain.

Blockade of the lncRNA-PART1-PHB2 axis confers resistance to PARP inhibitor and promotes cellular senescence in ovarian cancer.

PARPi is currently the most important breakthrough in the treatment of ovarian cancer in decades, and it has been integrated into the initial maintenance therapy for ovarian cancer. However, the mechanism leading to PARPi resistance remains unelucidated. Our study aims to screen novel targets to better predict and reverse resistance to PARPi and explore the potential mechanism. Here, we conducted a comparative analysis of differentially expressed genes between platinum-sensitive and platinum-resistant groups within the TCGA ovarian cancer cohort. The analysis indicated that lncRNA PART1 was significantly highly expressed in platinum-sensitive patients compared to platinum-resistant individuals in TCGA-OV cohort and further validated in the GEO dataset and Qilu hospital cohort. Moreover, the upregulation of PART1 was positively correlated with a favorable prognosis in ovarian cancer. Furthermore, in vitro and in vivo experiments showed that inhibition of PART1 conferred resistance to both cisplatin and PARP inhibitor and promoted cellular senescence. Senescent cells are more resistant to chemotherapeutics. RNA antisense purification and RNA immunoprecipitation assays revealed an interaction between PART1 and PHB2, a crucial mitophagy receptor. Knockdown of PART1 could promote the degradation of PHB2, impairing mitophagy and leading to cellular senescence. Rescue assays indicated that overexpression of PHB2 remarkably diminished the resistance to PARPi and cellular senescence caused by PART1 knockdown. PDX models were utilized to further confirm the findings. Altogether, our study demonstrated that lncRNA PART1 has the potential to serve as a novel promising target to reverse resistance to PARPi and improve prognosis in ovarian cancer.

Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression signatures in six different populations using six public and two domestic cohorts (n = 1942) conducting mega-analysis and meta-analysis of the individual studies. We evaluated 12 machine learning and deep learning strategies for depression classification both in cross-validation (CV) and in hold-out tests using merged data from 8 separate batches, constructing models with both biased and unbiased feature selection. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level, and the associated genes were nominally related to axon guidance and immune pathways based on enrichment analysis and eQTM data. Random forest classifiers achieved the highest performance (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data. In contrast, the methylation showed low predictive power (all AUCs < 0.57) for all classifiers in CV and no predictive power in hold-out tests when used with harmonized data. All models achieved significantly better performance (>14% gain in AUCs) with pre-selected features (selection bias), with some of the models (joint autoencoder-classifier) reaching AUCs of up to 0.91 in the final testing regardless of data preparation. Different algorithmic feature selection approaches may outperform limma, however, random forest models perform well regardless of the strategy. The results provide an overview over potential future biomarkers for depression and highlight many important methodological aspects for DNA methylation-based depression profiling including the use of machine learning strategies.

Advances in development of biomarkers for brain damage and ischemia.

Acquired brain injury is an urgent situation that requires rapid diagnosis and treatment. Magnetic resonance imaging (MRI) and computed tomography (CT) are required for accurate diagnosis. However, these methods are costly and require substantial infrastructure and specialized staff. Circulatory biomarkers of acute brain injury may help in the management of patients with acute cerebrovascular events and prevent poor outcome and mortality. The purpose of this review is to provide an overview of the development of potential biomarkers of brain damage to increase diagnostic possibilities. For this purpose, we searched the PubMed database of studies on the diagnostic potential of brain injury biomarkers. We also accessed information from Clinicaltrials.gov to identify any clinical trials of biomarker measurements for the diagnosis of brain damage. In total, we present 41 proteins, enzymes and hormones that have been considered as biomarkers for brain injury, of which 20 have been studied in clinical trials. Several microRNAs have also emerged as potential clinical biomarkers for early diagnosis. Combining multiple biomarkers in a panel, along with other parameters, is yielding promising outcomes.

Depression clinical trials worldwide: a systematic analysis of the ICTRP and comparison with ClinicalTrials.gov.

Major depressive disorder (MDD), commonly known as depression, affects over 300 million people worldwide as of 2018 and presents a wide range of clinical symptoms. The international clinical trials registry platform (ICTRP) introduced by WHO includes aggregated data from ClinicalTrials.gov and 17 other national registers, making it the largest clinical trial platform. Here we analysed data in ICTRP with the aim of providing comprehensive insights into clinical trials on depression. Applying a novel hidden duplicate identification method, 10,606 depression trials were identified in ICTRP, with ANZCTR being the largest non- ClinicalTrials.gov database at 1031 trials, followed by IRCT with 576 trials, ISRCTN with 501 trials, CHiCTR with 489 trials, and EUCTR with 351 trials. The top four most studied drugs, ketamine, sertraline, duloxetine, and fluoxetine, were consistent in both groups, but ClinicalTrials.gov had more trials for each drug compared to the non-ClinicalTrials.gov group. Out of 9229 interventional trials, 663 unique agents were identified, including approved drugs (74.5%), investigational drugs (23.2%), withdrawn drugs (1.8%), nutraceuticals (0.3%), and illicit substances (0.2%). Both ClinicalTrials.gov and non-ClinicalTrials.gov databases revealed that the largest categories were antidepressive agents (1172 in ClinicalTrials.gov and 659 in non-ClinicalTrials.gov) and nutrients, amino acids, and chemical elements (250 in ClinicalTrials.gov and 659 in non-ClinicalTrials.gov), indicating a focus on alternative treatments involving dietary supplements and nutrients. Additionally, 26 investigational antidepressive agents targeting 16 different drug targets were identified, with buprenorphine (opioid agonist), saredutant (NK2 antagonist), and seltorexant (OX2 antagonist) being the most frequently studied. This analysis addresses 40 approved drugs for depression treatment including new drug classes like GABA modulators and NMDA antagonists that are offering new prospects for treating MDD, including drug-resistant depression and postpartum depression subtypes.

Genetic variants of LEAP2 are associated with anthropometric traits and circulating insulin-like growth factor-1 concentration: A UK Biobank study.

AIM: To test the hypothesis that liver-expressed antimicrobial peptide 2 (LEAP2) genetic variants might influence the susceptibility to human obesity. METHODS: Using data from the UK Biobank, we identified independent LEAP2 gene single nucleotide polymorphisms (SNPs) and examined their associations with obesity traits and serum insulin-like growth factor-1 (IGF-1) concentration. These associations were evaluated for both individual SNPs and after combining them into a genetic risk score (GRSLEAP2) using linear and logistic regression models. Sex-stratified analyses were also conducted. RESULTS: Five SNPs showed positive associations with obesity-related traits. rs57880964 was associated with body mass index (BMI) and waist-to-hip ratio adjusted for BMI (WHRadjBMI), in the total population and among women. Four independent SNPs were positively associated with higher serum IGF-1 concentrations in both men and women. GRSLEAP2 was associated with BMI and WHRadjBMI only in women and with serum IGF-1 concentration in both sexes. CONCLUSIONS: These findings reveal sex-specific associations between key LEAP2 gene variants and several obesity traits, while also indicating a strong independent association of LEAP2 variants with serum IGF-1 concentration.

Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics.

BACKGROUND: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. METHODS: We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. FINDINGS: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. INTERPRETATION: Our findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer. FUNDING: This work was supported by Cancer Research UK (grant no. C8221/A29017).

Depression proteomic profiling in adolescents with transcriptome analyses in independent cohorts.

Introduction: Depression is a major global burden with unclear pathophysiology and poor treatment outcomes. Diagnosis of depression continues to rely primarily on behavioral rather than biological methods. Investigating tools that might aid in diagnosing and treating early-onset depression is essential for improving the prognosis of the disease course. While there is increasing evidence of possible biomarkers in adult depression, studies investigating this subject in adolescents are lacking. Methods: In the current study, we analyzed protein levels in 461 adolescents assessed for depression using the Development and Well-Being Assessment (DAWBA) questionnaire as part of the domestic Psychiatric Health in Adolescent Study conducted in Uppsala, Sweden. We used the Proseek Multiplex Neuro Exploratory panel with Proximity Extension Assay technology provided by Olink Bioscience, followed by transcriptome analyses for the genes corresponding to the significant proteins, using four publicly available cohorts. Results: We identified a total of seven proteins showing different levels between DAWBA risk groups at nominal significance, including RBKS, CRADD, ASGR1, HMOX2, PPP3R1, CD63, and PMVK. Transcriptomic analyses for these genes showed nominally significant replication of PPP3R1 in two of four cohorts including whole blood and prefrontal cortex, while ASGR1 and CD63 were replicated in only one cohort. Discussion: Our study on adolescent depression revealed protein-level and transcriptomic differences, particularly in PPP3R1, pointing to the involvement of the calcineurin pathway in depression. Our findings regarding PPP3R1 also support the role of the prefrontal cortex in depression and reinforce the significance of investigating prefrontal cortex-related mechanisms in depression.

Hydroxymethylglutaryl-CoA reductase activity is essential for mitochondrial ß-oxidation of fatty acids to prevent lethal accumulation of long-chain acylcarnitines in the mouse liver.

BACKGROUND AND PURPOSE: Statins are competitive inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (HMGCR), and exert adverse effects on mitochondrial function, although the mechanisms underlying these effects remain unclear. We used a tamoxifen-induced Hmgcr-knockout (KO) mouse model, a multi-omics approach and mitochondrial function assessments to investigate whether decreased HMGCR activity impacts key liver energy metabolism pathways. EXPERIMENTAL APPROACH: We established a new mouse strain using the Cre/loxP system, which enabled whole-body deletion of Hmgcr expression. These mice were crossed with Rosa26Cre mice and treated with tamoxifen to delete Hmgcr in all cells. We performed transcriptomic and metabolomic analyses and thus evaluated time-dependent changes in metabolic functions to identify the pathways leading to cell death in Hmgcr-KO mice. KEY RESULTS: Lack of Hmgcr expression resulted in lethality, due to acute liver damage caused by rapid disruption of mitochondrial fatty acid ß-oxidation and very high accumulation of long-chain (LC) acylcarnitines in both male and female mice. Gene expression and KO-related phenotype changes were not observed in other tissues. The progression to liver failure was driven by diminished peroxisome formation, which resulted in impaired mitochondrial and peroxisomal fatty acid metabolism, enhanced glucose utilization and whole-body hypoglycaemia. CONCLUSION AND IMPLICATIONS: Our findings suggest that HMGCR is crucial for maintaining energy metabolism balance, and its activity is necessary for functional mitochondrial ß-oxidation. Moreover, statin-induced adverse reactions might be rescued by the prevention of LC acylcarnitine accumulation.

Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers.

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Social support predicted subsequent subjective well-being during the COVID-19 pandemic: a prospective study.

BACKGROUND: Subjective well-being (SWB) is associated with social support in cross-sectional studies. However, it remains unclear whether and how social support predicts SWB longitudinally, especially during the COVID-19 contingency. METHODS: By adopting a prospective design, the current work addressed this research question in a sample of 594 participants from the U.K. The data were collected via the online platform, Prolific, at two time points (June, 2020 and August, 2021) with a 14-month interval. Descriptive analysis and a moderated mediation model were conducted to test the proposed hypotheses. RESULTS: Baseline social support was a significant predictor of subjective well-being (SWB) 14 months later, even after controlling for baseline SWB and other covariates such as personality traits. Additionally, affect balance (i.e., the affective component of SWB) fully mediated the link between baseline social support and subsequent life satisfaction (i.e., the cognitive component of SWB). Moreover, household income moderated this relationship, indicating a stronger mediation for individuals with lower monthly household income. CONCLUSION: The present work sheds light on the underlying mechanism and boundary condition of the association between social support and different components of SWB during the COVID-19 pandemic.

Differential change in alcohol consumption during the COVID-19 pandemic: the role of loneliness, socialization, and mental well-being.

Introduction: The COVID-19 pandemic led to a surge in mental health issues and psychological distress, disruption to work/studying conditions, and social isolation particularly among young adults. Changes in these factors are differentially associated with alcohol use. Moreover, the relationship between these factors are bidirectional and may have fluctuated throughout the different phases of the pandemic. However, studies focusing on young adults had conflicting results, short follow-up periods, and lacked comprehensive data to describe underlying mechanisms. Methods: 1067 young adults participated in repetitive measures termed wave 4 (2021) of the Survey of Adolescent Life in Västmanland Cohort "SALVe" Cohort. Of these, 889 also completed pre-pandemic measurements termed wave 3 (2018). Participants completed the Alcohol Use Disorders Identification Test (AUDIT) to evaluate alcohol consumption and harmful use. Cross-sectional associations between perceived changes in alcohol use and shift in individual, mental health, and work environment factors were examined using Chi-square tests. Logistic regression was utilized to identify pre-pandemic predictors of harmful consumption during the pandemic. Results: Harmful consumption decreased only in females following the COVID-19 pandemic. Participants who reported increased feelings of depression, anxiety, and loneliness were more likely to increase their alcohol use. Interestingly, the subgroup who felt less lonely and met their friends more often, as well as those who continued working/studying from their regular workplace also had an increased likelihood of higher consumption. Only pre-pandemic ADHD and delinquency symptoms predicted harmful alcohol consumption following the pandemic. Conclusion: Females reduced harmful alcohol consumption during the COVID-19 pandemic. While those who suffered the burden of social isolation and distress were more likely to increase their alcohol use, young adults who felt less lonely and met their friends more often also had a similar outcome. The relationship between loneliness and alcohol consumption among young adults is influenced by the social factors that may be facilitated by drinking.