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.

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.

Plasma Proteomics to Identify Drug Targets for Ischemic Heart Disease.

Background: Integrated analyses of plasma proteomic and genetic markers in prospective studies can clarify the causal relevance of proteins and discover novel targets for ischemic heart disease (IHD) and other diseases.

Objectives: The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments.

Methods: We conducted a nested case-cohort study in the China Kadoorie Biobank (CKB) involving 1,971 incident IHD cases and 2,001 subcohort participants who were genotyped and free of prior cardiovascular disease.

Weight-loss Independent Clinical and Metabolic Biomarkers Associated with Type 2 Diabetes Remission Post-bariatric/metabolic Surgery.

Purpose: Remission of type 2 diabetes (T2D) can be achieved by many, but not all, people following bariatric/metabolic surgery. The mechanisms underlying T2D remission remain incompletely understood. This observational study aimed to identify novel weight-loss independent clinical, metabolic and genetic factors that associate with T2D remission using comprehensive phenotyping.

Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study.

Background: Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR).

Denture use and risk for cardiometabolic disease: observational and Mendelian randomization analyses.

Aims: Denture use may potentially increase the risk of cardiometabolic diseases (CMDs), but the casual relevance and strength of the associations are currently unknown.

Methods And Results: A total of 495 938 participants from the UK Biobank were included in the observational analyses. Linkage disequilibrium score (LDSC) regression and Mendelian randomization analyses were employed to estimate genetic correlation and the associations between the genetic liability for denture use with coronary artery disease, myocardial infarction, heart failure (HF), any stroke (AS), ischaemic stroke, haemorrhagic stroke, type 2 diabetes (T2D), and related clinical risk factors.

Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia.

With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers.

Predicting Hearing Loss in Testicular Cancer Patients after Cisplatin-Based Chemotherapy.

Testicular cancer is predominantly curable, but the long-term side effects of chemotherapy have a severe impact on life quality. In this research study, we focus on hearing loss as a part of overall chemotherapy-induced ototoxicity. This is a unique approach where we combine clinical data from the acclaimed nationwide Danish Testicular Cancer (DaTeCa)-Late database.

Proteomics analysis of plasma from middle-aged adults identifies protein markers of dementia risk in later life.

A diverse set of biological processes have been implicated in the pathophysiology of Alzheimer's disease (AD) and related dementias. However, there is limited understanding of the peripheral biological mechanisms relevant in the earliest phases of the disease. Here, we used a large-scale proteomics platform to examine the association of 4877 plasma proteins with 25-year dementia risk in 10,981 middle-aged adults.

Computational design of N-linked glycans for high throughput epitope profiling.

Efficient identification of epitopes is crucial for drug discovery and design as it enables the selection of optimal epitopes, expansion of lead antibody diversity, and verification of binding interface. Although high-resolution low throughput methods like x-ray crystallography can determine epitopes or protein-protein interactions accurately, they are time-consuming and can only be applied to a limited number of complexes. To overcome these limitations, we have developed a rapid computational method that incorporates N-linked glycans to mask epitopes or protein interaction surfaces, thereby providing a mapping of these regions.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance.

Background And Aims: The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping.

Hepatocyte mARC1 promotes fatty liver disease.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) has a prevalence of ∼25% worldwide, with significant public health consequences yet few effective treatments. Human genetics can help elucidate novel biology and identify targets for new therapeutics. Genetic variants in mitochondrial amidoxime-reducing component 1 () have been associated with NAFLD and liver-related mortality; however, its pathophysiological role and the cell type(s) mediating these effects remain unclear.

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.

Sparse dimensionality reduction approaches in Mendelian randomisation with highly correlated exposures.

Multivariable Mendelian randomisation (MVMR) is an instrumental variable technique that generalises the MR framework for multiple exposures. Framed as a regression problem, it is subject to the pitfall of multicollinearity. The bias and efficiency of MVMR estimates thus depends heavily on the correlation of exposures.

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.

Compromised autophagy and mitophagy in brain ageing and Alzheimer's diseases.

Alzheimer's disease (AD) is one of the most persistent and devastating neurodegenerative disorders of old age, and is characterized clinically by an insidious onset and a gradual, progressive deterioration of cognitive abilities, ranging from loss of memory to impairment of judgement and reasoning. Despite years of research, an effective cure is still not available. Autophagy is the cellular 'garbage' clearance system which plays fundamental roles in neurogenesis, neuronal development and activity, and brain health, including memory and learning.

TIS Transformer: remapping the human proteome using deep learning.

The correct mapping of the proteome is an important step towards advancing our understanding of biological systems and cellular mechanisms. Methods that provide better mappings can fuel important processes such as drug discovery and disease understanding. Currently, true determination of translation initiation sites is primarily achieved by experiments.

Prognostic modelling of clinical outcomes after first-time acute coronary syndrome in New Zealand.

Objective: The Multi-Ethnic New Zealand Study of Acute Coronary Syndromes (MENZACS) was established to investigate the drivers of secondary events after first-time acute coronary syndrome (ACS), including addressing inequitable outcomes by ethnicity. Herein, the first clinical outcomes and prognostic modelling approach are reported.

Methods: First, in 28 176 New Zealanders with first-time ACS from a national registry, a clinical summary score for predicting 1-year death/cardiovascular readmission was created using Cox regression of 20 clinical variables.

Using genetic association data to guide drug discovery and development: Review of methods and applications.

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants.

Rare and common genetic determinants of metabolic individuality and their effects on human health.

Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.

Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups.