External control arms: COVID-19 reveals the merits of using real world evidence in real-time for clinical and public health investigations

Randomized controlled trials are considered the 'gold standard' to reduce bias by randomizing patients to an experimental intervention, versus placebo or standard of care cohort. There are inherent challenges to enrolling a standard of care or cohorts: costs, site engagement logistics, socioeconomic variability, patient willingness, ethics of placebo interventions, cannibalizing the treatment arm population, and extending study duration. The COVID-19 pandemic has magnified aspects of constraints in trial recruitment and logistics, spurring innovative approaches to reducing trial sizes, accelerating trial accrual while preserving statistical rigor. Using data from medical records and databases allows for construction of external control arms that reduce the costs of an external control arm (ECA) randomized to standard of care. Simultaneously examining covariates of the clinical outcomes in ECAs that are being measured in the interventional arm can be particularly useful in phase 2 trials to better understand social and genetic determinants of clinical outcomes that might inform pivotal trial design. The FDA and EMA have promulgated a number of publicly available guidance documents and qualification reports that inform the use of this regulatory science tool to streamline clinical development, of phase 4 surveillance, and policy aspects of clinical outcomes research. Availability and quality of real-world data (RWD) are a prevalent impediment to the use of ECAs given such data is not collected with the rigor and deliberateness that characterizes prospective interventional control arm data. Conversely, in the case of contemporary control arms, a clinical trial outcome can be compared to a contemporary standard of care in cases where the standard of care is evolving at a fast pace, such as the use of checkpoint inhibitors in cancer care. Innovative statistical methods are an essential aspect of an ECA strategy and regulatory paths for these innovative approaches have been navigated, qualified, and in some cases published.

mGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite-Phenotype Associations

Metabolomics-based genome-wide association studies (mGWAS) are key to understanding the genetic regulations of metabolites in complex phenotypes. We previously developed mGWAS-Explorer 1.0 to link single-nucleotide polymorphisms (SNPs), metabolites, genes and phenotypes for hypothesis generation. It has become clear that identifying potential causal relationships between metabolites and phenotypes, as well as providing deep functional insights, are crucial for further downstream applications. Here, we introduce mGWAS-Explorer 2.0 to support the causal analysis between >4000 metabolites and various phenotypes. The results can be interpreted within the context of semantic triples and molecular quantitative trait loci (QTL) data. The underlying R package is released for reproducible analysis. Using two case studies, we demonstrate that mGWAS-Explorer 2.0 is able to detect potential causal relationships between arachidonic acid and Crohn's disease, as well as between glycine and coronary heart disease.

Biological and functional multimorbidity-from mechanisms to management

Globally, the number of people with multiple co-occurring diseases will increase substantially over the coming decades, with important consequences for patients, carers, healthcare systems and society. Addressing this challenge requires a shift in the prevailing clinical, educational and scientific thinking and organization-with a strong emphasis on the maintenance of generalist skills to balance the specialization trends of medical education and research. Multimorbidity is not a single entity but differs quantitively and qualitatively across life stages, ethnicities, sexes, socioeconomic groups and geographies. Data-driven science that quantifies the impact of disease co-occurrence-beyond the small number of currently well-studied long-term conditions (such as cardiometabolic diseases)-can help illuminate the pathological diversity of multimorbidity and identify common, mechanistically related, and prognostically relevant clusters. Broader access to data opportunities across modalities and disciplines will catalyze vertical and horizontal integration of multimorbidity research, to enable reconfiguring of medical services, clinical trials, guidelines and research in a way that accounts for the complexity of multimorbidity-and provides efficient, joined-up services for patients.

Cardiovascular risk factors and major recurrent coronary events: A genetic liability study in patients with coronary artery disease in the UK Biobank

BACKGROUND AND AIMS

Mendelian randomization confirmed multiple risk factors for primary events of coronary artery disease (CAD), but no such studies have been performed on recurrent major coronary events despite interesting insights derived from other designs. We examined the associations between genetically-influenced classical cardiovascular risk factors and the risk of recurrent major coronary events in a cohort of CAD patients.

METHODS

We included all first-time CAD cases (defined as angina pectoris, chronic ischemic heart disease or acute myocardial infarction) of European ancestry from the UK Biobank. Cases were followed till the end of follow-up, death or when they developed a recurrent major coronary event (chronic ischemic heart disease or acute myocardial infarction). Standardized weighted genetic risk scores were calculated for body mass index (BMI), systolic blood pressure, LDL cholesterol and triglycerides.

RESULTS

From a total of 22,949 CAD patients (mean age at first diagnosis 59.8 (SD 7.3) years, 71.1% men), 12,539 (54.6%) reported a recurrent major coronary event within a period of maximum 17.8 years. One standard deviation higher genetically-determined LDL cholesterol was associated with a higher risk of a recurrent major coronary event (odds ratio: 1.08 [95% confidence interval: 1.05, 1.11]). No associations were observed for genetically-influenced BMI (1.00 [0.98, 1.03]), systolic blood pressure (1.01 [0.98, 1.03]) and triglycerides (1.02 [0.995, 1.05]).

CONCLUSIONS

Despite the use risk-reducing medications following a first coronary event, this study provided genetic evidence that, of the classical risk factors, mainly high LDL cholesterol was associated with a higher risk of developing recurrent major coronary events.

Hereditary spastic paraplegias proteome: common pathways and pathogenetic mechanisms

INTRODUCTION

Hereditary spastic paraplegias (HSPs) are a group of inherited neurodegenerative disorders characterized by progressive spasticity and weakness of the lower limbs. These conditions are caused by lesions in the neuronal pyramidal tract and exhibit clinical and genetic variability. Ongoing research focuses on understanding the underlying mechanisms of HSP onset, which ultimately lead to neuronal degeneration. Key molecular mechanisms involved include axonal transport, cytoskeleton dynamics, myelination abnormalities, membrane trafficking, organelle morphogenesis, ER homeostasis, mitochondrial dysfunction, and autophagy deregulation.

AREAS COVERED

This review aims to provide an overview of the shared pathogenetic mechanisms in various forms of HSPs. By examining disease-causing gene products and their associated functional pathways, this understanding could lead to the discovery of new therapeutic targets and the development of treatments to modify the progression of the disease.

EXPERT OPINION

Investigating gene functionality is crucial for identifying shared pathogenetic pathways underlying different HSP subtypes. Categorizing protein function and identifying pathways aids in finding biomarkers, predicting early onset, and guiding treatment for a better quality of life. Targeting shared mechanisms enables efficient and cost-effective therapies. Prospects involve identifying new disease-causing genes, refining molecular processes, and implementing findings in diagnosis, key for advancing HSP understanding and developing effective treatments.

Lipidomics in pathogenesis, progression and treatment of nonalcoholic steatohepatitis (NASH): Recent advances

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease affecting up to 30% of the general adult population. NAFLD encompasses a histological spectrum ranging from pure steatosis to non-alcoholic steatohepatitis (NASH). NASH can progress to cirrhosis and is becoming the most common indication for liver transplantation, as a result of increasing disease prevalence and of the absence of approved treatments. Lipidomic readouts of liver blood and urine samples from experimental models and from NASH patients disclosed an abnormal lipid composition and metabolism. Collectively, these changes impair organelle function and promote cell damage, necro-inflammation and fibrosis, a condition termed lipotoxicity. We will discuss the lipid species and metabolic pathways leading to NASH development and progression to cirrhosis, as well as and those species that can contribute to inflammation resolution and fibrosis regression. We will also focus on emerging lipid-based therapeutic opportunities, including specialized proresolving lipid molecules and macrovesicles contributing to cell-to-cell communication and NASH pathophysiology.

Dual role of ANGPTL4 in inflammation

BACKGROUND

Angiopoietin-like 4 (ANGPTL4) belongs to the angiopoietin-like protein family and mediates the inhibition of lipoprotein lipase activity. Emerging evidence suggests that ANGPTL4 has pleiotropic functions with anti- and pro-inflammatory properties.

METHODS

A thorough search on PubMed related to ANGPTL4 and inflammation was performed.

RESULTS

Genetic inactivation of ANGPTL4 can significantly reduce the risk of developing coronary artery disease and diabetes. However, antibodies against ANGPTL4 result in several undesirable effects in mice or monkeys, such as lymphadenopathy and ascites. Based on the research progress on ANGPTL4, we systematically discussed the dual role of ANGPTL4 in inflammation and inflammatory diseases (lung injury, pancreatitis, heart diseases, gastrointestinal diseases, skin diseases, metabolism, periodontitis, and osteolytic diseases). This may be attributed to several factors, including post-translational modification, cleavage and oligomerization, and subcellular localization.

CONCLUSION

Understanding the potential underlying mechanisms of ANGPTL4 in inflammation in different tissues and diseases will aid in drug discovery and treatment development.

Unraveling White Adipose Tissue Heterogeneity and Obesity by Adipose Stem/Stromal Cell Biology and 3D Culture Models

The immune and endocrine dysfunctions of white adipose tissue are a hallmark of metabolic disorders such as obesity and type 2 diabetes. In humans, white adipose tissue comprises distinct depots broadly distributed under the skin (hypodermis) and as internal depots (visceral). Depot-specific ASCs could account for visceral and subcutaneous adipose tissue properties, by regulating adipogenesis and immunomodulation. More importantly, visceral and subcutaneous depots account for distinct contributions to obesity and its metabolic comorbidities. Recently, distinct ASCs subpopulations were also described in subcutaneous adipose tissue. Interestingly, the superficial layer closer to the dermis shows hyperplastic and angiogenic capacities, whereas the deep layer is considered as having inflammatory properties similar to visceral. The aim of this focus review is to bring the light of recent discoveries into white adipose tissue heterogeneity together with the biology of distinct ASCs subpopulations and to explore adipose tissue 3D models revealing their advantages, disadvantages, and contributions to elucidate the role of ASCs in obesity development. Recent advances in adipose tissue organoids opened an avenue of possibilities to recreate the main cellular and molecular events of obesity leading to a deep understanding of this inflammatory disease besides contributing to drug discovery. Furthermore, 3D organ-on-a-chip will add reproducibility to these adipose tissue models contributing to their translation to the pharmaceutical industry.

Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.

REEP1 Preserves Motor Function in SOD1G93A Mice by Improving Mitochondrial Function via Interaction with NDUFA4

A decline in the activities of oxidative phosphorylation (OXPHOS) complexes has been consistently reported in amyotrophic lateral sclerosis (ALS) patients and animal models of ALS, although the underlying molecular mechanisms are still elusive. Here, we report that receptor expression enhancing protein 1 (REEP1) acts as an important regulator of complex IV assembly, which is pivotal to preserving motor neurons in SOD1G93A mice. We found the expression of REEP1 was greatly reduced in transgenic SOD1G93A mice with ALS. Moreover, forced expression of REEP1 in the spinal cord extended the lifespan, decelerated symptom progression, and improved the motor performance of SOD1G93A mice. The neuromuscular synaptic loss, gliosis, and even motor neuron loss in SOD1G93A mice were alleviated by increased REEP1 through augmentation of mitochondrial function. Mechanistically, REEP1 associates with NDUFA4, and plays an important role in preserving the integrity of mitochondrial complex IV. Our findings offer insights into the pathogenic mechanism of REEP1 deficiency in neurodegenerative diseases and suggest a new therapeutic target for ALS.

Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations

Circulating metabolite levels may reflect the state of the human organism in health and disease, however, the genetic architecture of metabolites is not fully understood. We have performed a whole-genome sequencing association analysis of both common and rare variants in up to 11,840 multi-ethnic participants from five studies with up to 1666 circulating metabolites. We have discovered 1985 novel variant-metabolite associations, and validated 761 locus-metabolite associations reported previously. Seventy-nine novel variant-metabolite associations have been replicated, including three genetic loci located on the X chromosome that have demonstrated its involvement in metabolic regulation. Gene-based analysis have provided further support for seven metabolite-replicated loci pairs and their biologically plausible genes. Among those novel replicated variant-metabolite pairs, follow-up analyses have revealed that 26 metabolites have colocalized with 21 tissues, seven metabolite-disease outcome associations have been putatively causal, and 7 metabolites might be regulated by plasma protein levels. Our results have depicted the genetic contribution to circulating metabolite levels, providing additional insights into understanding human disease.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Glycerolipid Synthesis and Lipid Droplet Formation in the Endoplasmic Reticulum

More than 60 years ago, Eugene Kennedy and coworkers elucidated the endoplasmic reticulum (ER)-based pathways of glycerolipid synthesis, including the synthesis of phospholipids and triacylglycerols (TGs). The reactions of the Kennedy pathway were identified by studying the conversion of lipid intermediates and the isolation of biochemical enzymatic activities, but the molecular basis for most of these reactions was unknown. With recent progress in the cell biology, biochemistry, and structural biology in this area, we have a much more mechanistic understanding of this pathway and its reactions. In this review, we provide an overview of molecular aspects of glycerolipid synthesis, focusing on recent insights into the synthesis of TGs. Further, we go beyond the Kennedy pathway to describe the mechanisms for storage of TG in cytosolic lipid droplets and discuss how overwhelming these pathways leads to ER stress and cellular toxicity, as seen in diseases linked to lipid overload and obesity.

Inverse effects of APOC2 and ANGPTL4 on the conformational dynamics of lid-anchoring structures in lipoprotein lipase

The lipolytic processing of triglyceride-rich lipoproteins (TRLs) by lipoprotein lipase (LPL) is crucial for the delivery of dietary lipids to the heart, skeletal muscle, and adipose tissue. The processing of TRLs by LPL is regulated in a tissue-specific manner by a complex interplay between activators and inhibitors. Angiopoietin-like protein 4 (ANGPTL4) inhibits LPL by reducing its thermal stability and catalyzing the irreversible unfolding of LPL's α/β-hydrolase domain. We previously mapped the ANGPTL4 binding site on LPL and defined the downstream unfolding events resulting in LPL inactivation. The binding of LPL to glycosylphosphatidylinositol-anchored high-density lipoprotein-binding protein 1 protects against LPL unfolding. The binding site on LPL for an activating cofactor, apolipoprotein C2 (APOC2), and the mechanisms by which APOC2 activates LPL have been unclear and controversial. Using hydrogen-deuterium exchange/mass spectrometry, we now show that APOC2's C-terminal α-helix binds to regions of LPL surrounding the catalytic pocket. Remarkably, APOC2's binding site on LPL overlaps with that for ANGPTL4, but their effects on LPL conformation are distinct. In contrast to ANGPTL4, APOC2 increases the thermal stability of LPL and protects it from unfolding. Also, the regions of LPL that anchor the lid are stabilized by APOC2 but destabilized by ANGPTL4, providing a plausible explanation for why APOC2 is an activator of LPL, while ANGPTL4 is an inhibitor. Our studies provide fresh insights into the molecular mechanisms by which APOC2 binds and stabilizes LPL-and properties that we suspect are relevant to the conformational gating of LPL's active site.

Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges

Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.

ANGPTL4 is a potential driver of HCV-induced peripheral insulin resistance

Chronic hepatitis C (CHC) is associated with the development of metabolic disorders, including both hepatic and extra-hepatic insulin resistance (IR). Here, we aimed at identifying liver-derived factor(s) potentially inducing peripheral IR and uncovering the mechanisms whereby HCV can regulate the action of these factors. We found ANGPTL4 (Angiopoietin Like 4) mRNA expression levels to positively correlate with HCV RNA (r = 0.46, p < 0.03) and HOMA-IR score (r = 0.51, p = 0.01) in liver biopsies of lean CHC patients. Moreover, we observed an upregulation of ANGPTL4 expression in two models recapitulating HCV-induced peripheral IR, i.e. mice expressing core protein of HCV genotype 3a (HCV-3a core) in hepatocytes and hepatoma cells transduced with HCV-3a core. Treatment of differentiated myocytes with recombinant ANGPTL4 reduced insulin-induced Akt-Ser473 phosphorylation. In contrast, conditioned medium from ANGPTL4-KO hepatoma cells prevented muscle cells from HCV-3a core induced IR. Treatment of HCV-3a core expressing HepG2 cells with PPARγ antagonist resulted in a decrease of HCV-core induced ANGPTL4 upregulation. Together, our data identified ANGPTL4 as a potential driver of HCV-induced IR and may provide working hypotheses aimed at understanding the pathogenesis of IR in the setting of other chronic liver disorders.

Single-arm trials supporting the approval of anticancer medicinal products in the European Union: contextualization of trial results and observed clinical benefit

BACKGROUND

Single-arm trials (SATs) can sometimes be used to support marketing authorization of anticancer medicinal products in the European Union. The level and durability of antitumor activity of the product as well as context are important aspects to determine the relevance of trial results. The aim of this study is to provide details on the contextualization of trial results and to evaluate the magnitude of benefit of medicinal products approved based on SATs.

MATERIALS AND METHODS

We focused on anticancer medicinal products for solid tumors approved on the basis of SAT results (2012-2021). Data were retrieved from European public assessment reports and/or published literature. The benefit of these medicinal products was evaluated via the European Society for Medical Oncology (ESMO)-Magnitude of Clinical Benefit Scale (MCBS).

RESULTS

Eighteen medicinal products were approved based on 21 SATs-few medicinal products were supported by >1 SAT. For the majority of clinical trials, a clinically relevant treatment effect was (pre)specified (71.4%) and most often an accompanying sample size calculation was provided. For 10 studies, each testing a different medicinal product, a justification for the threshold for a clinically relevant treatment effect could be identified. At least 12 out of 18 applications included information to facilitate the contextualization of trial results, including six supportive studies. Of the pivotal SATs analyzed (n = 21), three were assigned an ESMO-MCBS score of 4, which corresponds to 'substantial' benefit.

CONCLUSIONS

The clinical relevance of the treatment effects shown by medicinal products for solid tumors tested in SATs is dependent on the effect size and context. To better facilitate regulatory decision making, prespecifying and motivating a clinically relevant effect and aligning the sample size to that effect is important. External controls may facilitate in the contextualization process, but the associated limitations must be addressed.

Diabetic vascular diseases: molecular mechanisms and therapeutic strategies

Vascular complications of diabetes pose a severe threat to human health. Prevention and treatment protocols based on a single vascular complication are no longer suitable for the long-term management of patients with diabetes. Diabetic panvascular disease (DPD) is a clinical syndrome in which vessels of various sizes, including macrovessels and microvessels in the cardiac, cerebral, renal, ophthalmic, and peripheral systems of patients with diabetes, develop atherosclerosis as a common pathology. Pathological manifestations of DPDs usually manifest macrovascular atherosclerosis, as well as microvascular endothelial function impairment, basement membrane thickening, and microthrombosis. Cardiac, cerebral, and peripheral microangiopathy coexist with microangiopathy, while renal and retinal are predominantly microangiopathic. The following associations exist between DPDs: numerous similar molecular mechanisms, and risk-predictive relationships between diseases. Aggressive glycemic control combined with early comprehensive vascular intervention is the key to prevention and treatment. In addition to the widely recommended metformin, glucagon-like peptide-1 agonist, and sodium-glucose cotransporter-2 inhibitors, for the latest molecular mechanisms, aldose reductase inhibitors, peroxisome proliferator-activated receptor-γ agonizts, glucokinases agonizts, mitochondrial energy modulators, etc. are under active development. DPDs are proposed for patients to obtain more systematic clinical care requires a comprehensive diabetes care center focusing on panvascular diseases. This would leverage the advantages of a cross-disciplinary approach to achieve better integration of the pathogenesis and therapeutic evidence. Such a strategy would confer more clinical benefits to patients and promote the comprehensive development of DPD as a discipline.

StocSum: stochastic summary statistics for whole genome sequencing studies

Genomic summary statistics, usually defined as single-variant test results from genome-wide association studies, have been widely used to advance the genetics field in a wide range of applications. Applications that involve multiple genetic variants also require their correlations or linkage disequilibrium (LD) information, often obtained from an external reference panel. In practice, it is usually difficult to find suitable external reference panels that represent the LD structure for underrepresented and admixed populations, or rare genetic variants from whole genome sequencing (WGS) studies, limiting the scope of applications for genomic summary statistics. Here we introduce StocSum, a novel reference-panel-free statistical framework for generating, managing, and analyzing stochastic summary statistics using random vectors. We develop various downstream applications using StocSum including single-variant tests, conditional association tests, gene-environment interaction tests, variant set tests, as well as meta-analysis and LD score regression tools. We demonstrate the accuracy and computational efficiency of StocSum using two cohorts from the Trans-Omics for Precision Medicine Program. StocSum will facilitate sharing and utilization of genomic summary statistics from WGS studies, especially for underrepresented and admixed populations.

Prevalence of combined metabolic health and weight status by various diagnosis criteria and association with cardiometabolic disease in Korean adults

The purpose of this study was to compare the cardiometabolic disease prevalence and risk factors between individuals categorized as metabolically unhealthy and healthy (MU vs. MH), with normal-weight and obesity (Nw vs. Ob), according to different established criteria for combined metabolic health and weight status; and to assess the optimal metabolic health diagnostic classifications to predict cardiometabolic disease risk factors. Data were obtained from the 2019 and 2020 Korean National Health and Nutrition Examination Surveys. We applied the nine accepted metabolic health diagnostic classification criteria. Statistical analysis was applied to frequency, multiple logistic regression, and ROC curve analysis. The prevalence of MHNw ranged from 24.6% to 53.9%, MUNw from 3.7% to 37.9%, MHOb from 3.4% to 25.9%, and MUOb from 16.3% to 39.1%. For hypertension, the MUNw had an increased risk ranging from 1.90 to 3.24 times compared with MHNw; MHOb ranged from 1.84 to 3.76 times; MUOb ranged from 4.18 to 6.97 times (all p < .05). For dyslipidemia, the MUNw had an increased risk ranging from 1.33 to 2.25 times compared with MHNw; MHOb ranged from 1.47 to 2.33 times; MUOb ranged from 2.31 to 2.67 times (all p < .05). For diabetes, the MUNw had an increased risk ranging from 2.27 to 11.93 times compared with MHNW; MHOb ranged from 1.36 to 1.95 times; MUOb ranged from 3.60 to 18.45 times (all p < .05). Our study findings revealed that AHA/NHLBI-02 and NCEP-02 can be the best diagnostic classifications criteria for cardiometabolic diseases risk factors.

Metabolic profiling of MRI-measured liver fat in the UK Biobank

OBJECTIVE

Liver fat associates with obesity-related metabolic disturbances and may precede incident diseases. Metabolomic profiles of liver fat in the UK Biobank were investigated.

METHODS

Regression models assessed the associations between 180 metabolites and proton density liver fat fraction (PDFF) measured 5 years later through magnetic resonance imaging, as the difference (in SD units) of each log metabolite measure with 1-SD higher PDFF among those without chronic disease and not taking statins, and by diabetes and cardiovascular diseases.

RESULTS

After accounting for confounders, multiple metabolites were associated positively with liver fat (p < 0.0001 for 152 traits), particularly extremely large and very large lipoprotein particle concentrations, very low-density lipoprotein triglycerides, small high-density lipoprotein particles, glycoprotein acetyls, monounsaturated and saturated fatty acids, and amino acids. Extremely large and large high-density lipoprotein concentrations had strong inverse associations with liver fat. Associations were broadly comparable among those with versus without vascular metabolic conditions, although negative, rather than positive, associations were observed between intermediate-density and large low-density lipoprotein particles among those with BMI ≥25 kg/m² , diabetes, or cardiovascular diseases. Metabolite principal components showed a 15% significant improvement in risk prediction for PDFF relative to BMI, which was twice as great (but nonsignificant) compared with conventional high-density lipoprotein cholesterol and triglycerides.

CONCLUSIONS

Hazardous metabolomic profiles are associated with ectopic hepatic fat and are relevant to risk of vascular-metabolic disease.

Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease

BACKGROUND

Some observational studies found that dyslipidaemia is a risk factor for non-alcoholic fatty liver disease (NAFLD), and lipid-lowering drugs may lower NAFLD risk. However, it remains unclear whether dyslipidaemia is causative for NAFLD. This Mendelian randomisation (MR) study aimed to explore the causal role of lipid traits in NAFLD and evaluate the potential effect of lipid-lowering drug targets on NAFLD.

METHODS

Genetic variants associated with lipid traits and variants of genes encoding lipid-lowering drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). Summary statistics for NAFLD were obtained from two independent GWAS datasets. Lipid-lowering drug targets that reached significance were further tested using expression quantitative trait loci data in relevant tissues. Colocalisation and mediation analyses were performed to validate the robustness of the results and explore potential mediators.

FINDINGS

No significant effect of lipid traits and eight lipid-lowering drug targets on NAFLD risk was found. Genetic mimicry of lipoprotein lipase (LPL) enhancement was associated with lower NAFLD risks in two independent datasets (OR₁ = 0.60 [95% CI 0.50-0.72], p₁ = 2.07 × 10^-8; OR₂ = 0.57 [95% CI 0.39-0.82], p₂ = 3.00 × 10^-3). A significant MR association (OR = 0.71 [95% CI, 0.58-0.87], p = 1.20 × 10^-3) and strong colocalisation association (PP.H₄ = 0.85) with NAFLD were observed for LPL expression in subcutaneous adipose tissue. Fasting insulin and type 2 diabetes mediated 7.40% and 9.15%, respectively, of the total effect of LPL on NAFLD risk.

INTERPRETATION

Our findings do not support dyslipidaemia as a causal factor for NAFLD. Among nine lipid-lowering drug targets, LPL is a promising candidate drug target in NAFLD. The mechanism of action of LPL in NAFLD may be independent of its lipid-lowering effects.

FUNDING

Capital's Funds for Health Improvement and Research (2022-4-4037). CAMS Innovation Fund for Medical Sciences (CIFMS, grant number: 2021-I2M-C&T-A-010).

How the Presence of a Doctor Known to Patients Impacts a Web-Based Intervention to Promote Physical Activity and Healthy Eating Behaviour in Individuals with an Overweight/Obesity–Hypertension Phenotype: A Randomised Clinical Trial

(1) Background: The ‘Living Better’ web-based programme has shown short- and long-term benefits for body composition and psychological variables in obese patients with hypertension by promoting a healthier lifestyle. To further explore the potential of this programme, in this work we aimed to explore the possible effect of the patient’s ‘own doctor’ appearing in the video content of the Living Better intervention. (2) Methods: A total of 132 patients were randomly assigned either to the experimental (EG, n = 70) or control (CG, n = 62) group (with a doctor the patient knew as ‘their own’ or an ‘unknown doctor’, respectively). The body mass index (BMI), motivation towards physical activity (PA), PA levels, motivation to change one’s eating habits, adherence to the Mediterranean diet, and eating behaviour were all assessed and compared at baseline and post-intervention (12 weeks). (3) Results: The results of this study confirmed the positive effects of the Living Better programme on BMI and external eating style, with significant improvements in these variables in both groups. In addition, in the EG there was higher intrinsic motivation to change eating behaviour (mean difference of 0.9, 95% CI [0.1, 1.6], p = 0.032) and lower amotivation (mean difference of −0.6, 95% CI [−1.2, −0.1], p = 0.027) compared to the CG. (4) Conclusions: This study suggests that the presence of the patients’ own doctor in the audiovisual content of the Living Better intervention did not have significant additional benefits in terms of BMI or external eating style. However, their presence did improve intrinsic motivation and amotivation related to eating habits.

Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results

Studies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights into our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.

Analysis of protein expression changes in patients with prediabetes using proteomics approaches

RATIONALE

Proteomics and metabolomics are widely used in the study of diabetes, but rarely in prediabetes research. This study aimed to explore the mechanisms of early-onset type 2 diabetes mellitus (T2DM) by analyzing proteomic changes at different stages of glucose metabolism.

METHODS

A total of 40 individuals undergoing routine physical health examinations between December 2016 and April 2017 were enrolled. Subjects were divided into four groups based on fasting blood glucose (FPG) levels: FPG < 5.6 mmol/L (group A); FPG ≥ 5.6 mmol/L and <6.1 mmol/L (group B); FPG ≥ 6.1 mmol/L and <7.0 mmol/L (group C); and FPG ≥ 7.0 mmol/L (group D). Each group had 10 cases. Sera from these 40 subjects were analyzed by label-free quantitative liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS). LC/MS/MS with selected reaction monitoring mode was also performed for qualitative and quantitative metabolomics analysis. Differentially expressed proteins were identified. Partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to analyze the differentially expressed metabolites.

RESULTS

A total of 202 differentially expressed proteins were screened and were identified as mainly secreted proteins. Comparing group A with group B, 32 proteins were up-regulated and 18 proteins were down-regulated. Comparing group A with group C, 24 proteins were up-regulated and 24 proteins were down-regulated. Comparing group A with group D, 19 proteins were up-regulated and 17 proteins were down-regulated. The fold change for up-regulated proteins was >1.2, p < 0.05, while the fold change for down-regulated proteins was <-1.2, p < 0.05. PLS-DA and OPLS-DA revealed 113 differentially expressed metabolites. Correlation analysis of differentially expressed metabolites of group A versus group B revealed that among the down-regulated differential proteins, transforming growth factor β-induced protein ig-h3 correlated negatively with metabolite L-saccharin, while among the up-regulated differential proteins, apolipoprotein C-IV correlated negatively with metabolite 3-methyloxindole. Among all differentially expressed proteins, 19 proteins were associated with early initiation of chronic inflammation, including CD14 and CSF-1R, which were newly identified in the early onset of T2DM.

CONCLUSIONS

Many proteins are differentially expressed between prediabetes and after T2DM diagnosis, although the specific mechanism remains unclear. The expression level of CD14 was significantly up-regulated and that of CSF-1R was significantly down-regulated when FPG was ≥5.6 mmol/L, suggesting that CD14 and CSF-1R may be important markers for early-onset T2DM and may serve as new targets for T2DM treatment.

Exploiting the mediating role of the metabolome to unravel transcript-to-phenotype associations

Despite the success of genome-wide association studies (GWASs) in identifying genetic variants associated with complex traits, understanding the mechanisms behind these statistical associations remains challenging. Several methods that integrate methylation, gene expression, and protein quantitative trait loci (QTLs) with GWAS data to determine their causal role in the path from genotype to phenotype have been proposed. Here, we developed and applied a multi-omics Mendelian randomization (MR) framework to study how metabolites mediate the effect of gene expression on complex traits. We identified 216 transcript-metabolite-trait causal triplets involving 26 medically relevant phenotypes. Among these associations, 58% were missed by classical transcriptome-wide MR, which only uses gene expression and GWAS data. This allowed the identification of biologically relevant pathways, such as between ANKH and calcium levels mediated by citrate levels and SLC6A12 and serum creatinine through modulation of the levels of the renal osmolyte betaine. We show that the signals missed by transcriptome-wide MR are found, thanks to the increase in power conferred by integrating multiple omics layer. Simulation analyses show that with larger molecular QTL studies and in case of mediated effects, our multi-omics MR framework outperforms classical MR approaches designed to detect causal relationships between single molecular traits and complex phenotypes.

Ubiquitin-specific protease 28: the decipherment of its dual roles in cancer development

As significant posttranslational modifications, ubiquitination and deubiquitination, whose balance is modulated by ubiquitin-conjugating enzymes and deubiquitinating enzymes (DUBs), can regulate many biological processes, such as controlling cell cycle progression, signal transduction and transcriptional regulation. Belonging to DUBs, ubiquitin-specific protease 28 (USP28) plays an essential role in turning over ubiquitination and then contributing to the stabilization of quantities of substrates, including several cancer-related proteins. In previous studies, USP28 has been demonstrated to participate in the progression of various cancers. Nevertheless, several reports have recently shown that in addition to promoting cancers, USP28 can also play an oncostatic role in some cancers. In this review, we summarize the correlation between USP28 and tumor behaviors. We initially give a brief introduction of the structure and related biological functions of USP28, and we then introduce some concrete substrates of USP28 and the underlying molecular mechanisms. In addition, the regulation of the actions and expression of USP28 is also discussed. Moreover, we concentrate on the impacts of USP28 on diverse hallmarks of cancer and discuss whether USP28 can accelerate or inhibit tumor progression. Furthermore, clinical relevance, including impacting clinical prognosis, influencing therapy resistance and being the therapy target in some cancers, is depicted systematically. Thus, assistance may be given to future experimental designs by the information provided here, and the potential of targeting USP28 for cancer therapy is emphasized.

Identification of a weight loss-associated causal eQTL in MTIF3 and the effects of MTIF3 deficiency on human adipocyte function

Genetic variation at the MTIF3 (Mitochondrial Translational Initiation Factor 3) locus has been robustly associated with obesity in humans, but the functional basis behind this association is not known. Here, we applied luciferase reporter assay to map potential functional variants in the haplotype block tagged by rs1885988 and used CRISPR-Cas9 to edit the potential functional variants to confirm the regulatory effects on MTIF3 expression. We further conducted functional studies on MTIF3-deficient differentiated human white adipocyte cell line (hWAs-iCas9), generated through inducible expression of CRISPR-Cas9 combined with delivery of synthetic MTIF3-targeting guide RNA. We demonstrate that rs67785913-centered DNA fragment (in LD with rs1885988, r² > 0.8) enhances transcription in a luciferase reporter assay, and CRISPR-Cas9-edited rs67785913 CTCT cells show significantly higher MTIF3 expression than rs67785913 CT cells. Perturbed MTIF3 expression led to reduced mitochondrial respiration and endogenous fatty acid oxidation, as well as altered expression of mitochondrial DNA-encoded genes and proteins, and disturbed mitochondrial OXPHOS complex assembly. Furthermore, after glucose restriction, the MTIF3 knockout cells retained more triglycerides than control cells. This study demonstrates an adipocyte function-specific role of MTIF3, which originates in the maintenance of mitochondrial function, providing potential explanations for why MTIF3 genetic variation at rs67785913 is associated with body corpulence and response to weight loss interventions.

Relationship Between Regional Adiposity Distribution and Incident Heart Failure in General Populations without Cardiovascular Disease

BACKGROUND

Obesity is associated with a high risk of heart failure. However, the contribution of regional fat distribution evaluated using bioimpedance analysis toward heart failure risk in the general population without cardiovascular disease has rarely been studied.

METHODS

This study included 483,316 participants without heart failure and cardiovascular disease from the UK Biobank study. The regional fat mass was determined by bioimpedance analysis and calculated by dividing the square of height in meters (kg/m²). This study evaluated the association of regional fat mass (arm fat index [AFI], trunk fat index [TFI], and leg fat index [LFI]) with the risk of incident heart failure and whether regional fat mass adds a further prognostic value for heart failure besides body mass index (BMI) in a large prospective cohort study.

RESULTS

During the median 12.1 years, 3134 incident heart failure cases occurred. After adjustment for BMI and other confounding factors, each 1-standard deviation increase in LFI was associated with a 21% lower heart failure risk even after adjusting for BMI and other confounding factors (hazard ratio [HR] 0.79; 95% confidence interval [CI], 0.73-0.85). However, we did not observe heart failure-associated risks with AFI and TFI (HR 1.04; 95% CI, 0.99-1.09; HR 0.97, 95% CI, 0.91-1.04, respectively). Subgroup analysis demonstrated that the protective role of LFI was more prominent in the elderly and female participants (P < .01).

CONCLUSION

Regional fat measurement other than BMI can improve heart failure risk stratification; leg fat plays a protective role, yet arm and trunk fat do not, in the general population without cardiovascular disease.

Proteogenomic links to human metabolic diseases

Studying the plasma proteome as the intermediate layer between the genome and the phenome has the potential to identify new disease processes. Here, we conducted a cis-focused proteogenomic analysis of 2,923 plasma proteins measured in 1,180 individuals using antibody-based assays. We (1) identify 256 unreported protein quantitative trait loci (pQTL); (2) demonstrate shared genetic regulation of 224 cis-pQTLs with 575 specific health outcomes, revealing examples for notable metabolic diseases (such as gastrin-releasing peptide as a potential therapeutic target for type 2 diabetes); (3) improve causal gene assignment at 40% (n = 192) of overlapping risk loci; and (4) observe convergence of phenotypic consequences of cis-pQTLs and rare loss-of-function gene burden for 12 proteins, such as TIMD4 for lipoprotein metabolism. Our findings demonstrate the value of integrating complementary proteomic technologies with genomics even at moderate scale to identify new mediators of metabolic diseases with the potential for therapeutic interventions.

PPM1K-regulated impaired catabolism of branched-chain amino acids orchestrates polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is one of the most common diseases with the coexistence of reproductive malfunction and metabolic disorders. Previous studies have found increased branched chain amino acid (BCAA) levels in women with PCOS. However, it remains unclear whether BCAA metabolism is causally associated with the risk of PCOS.

METHODS

The changes of BCAA levels in the plasma and follicular fluids of PCOS women were detected. Mendelian randomization (MR) approaches were used to explore the potential causal association between BCAA levels and the risk of PCOS. The function of the gene coding the protein phosphatase Mg2+/Mn2+-dependent 1K (PPM1K) was further explored by using Ppm1k-deficient mouse model and PPM1K down-regulated human ovarian granulosa cells.

FINDINGS

BCAA levels were significantly elevated in both plasma and follicular fluids of PCOS women. Based on MR, a potential direct, causal role for BCAA metabolism was revealed in the pathogenesis of PCOS, and PPM1K was detected as a vital driver. Ppm1k-deficient female mice had increased BCAA levels and exhibited PCOS-like traits, including hyperandrogenemia and abnormal follicle development. A reduction in dietary BCAA intake significantly improved the endocrine and ovarian dysfunction of Ppm1k-/- female mice. Knockdown of PPM1K promoted the conversion of glycolysis to pentose phosphate pathway and inhibited mitochondrial oxidative phosphorylation in human granulosa cells.

INTERPRETATION

Ppm1k deficiency-impaired BCAA catabolism causes the occurrence and development of PCOS. PPM1K suppression disturbed energy metabolism homeostasis in the follicular microenvironment, which provided an underlying mechanism of abnormal follicle development.

FUNDING

This study was supported by the National Key Research and Development Program of China (2021YFC2700402, 2019YFA0802503), the National Natural Science Foundation of China (81871139, 82001503, 92057107), the CAMS Innovation Fund for Medical Sciences (2019-I2M-5-001), Key Clinical Projects of Peking University Third Hospital (BYSY2022043), the China Postdoctoral Science Foundation (2021T140600), and the Collaborative Innovation Program of Shanghai Municipal Health Commission (2020CXJQ01).

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

A New In Vivo Zebrafish Bioassay Evaluating Liver Steatosis Identifies DDE as a Steatogenic Endocrine Disruptor, Partly through SCD1 Regulation

Non-alcoholic fatty liver disease (NAFLD), which starts with liver steatosis, is a growing worldwide epidemic responsible for chronic liver diseases. Among its risk factors, exposure to environmental contaminants, such as endocrine disrupting compounds (EDC), has been recently emphasized. Given this important public health concern, regulation agencies need novel simple and fast biological tests to evaluate chemical risks. In this context, we developed a new in vivo bioassay called StAZ (Steatogenic Assay on Zebrafish) using an alternative model to animal experimentation, the zebrafish larva, to screen EDCs for their steatogenic properties. Taking advantage of the transparency of zebrafish larvae, we established a method based on fluorescent staining with Nile red to estimate liver lipid content. Following testing of known steatogenic molecules, 10 EDCs suspected to induce metabolic disorders were screened and DDE, the main metabolite of the insecticide DDT, was identified as a potent inducer of steatosis. To confirm this and optimize the assay, we used it in a transgenic zebrafish line expressing a blue fluorescent liver protein reporter. To obtain insight into DDE's effect, the expression of several genes related to steatosis was analyzed; an up-regulation of scd1 expression, probably relying on PXR activation, was found, partly responsible for both membrane remodeling and steatosis.

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Genetically determined serum serine level has a novel causal effect on multiple sclerosis risk and predicts disability progression

BACKGROUND

There are currently no specific biomarkers for multiple sclerosis (MS). Identifying robust biomarkers for MS is crucial to improve disease diagnosis and management.

METHODS

This study first used six Mendelian randomisation methods to assess causal relationship of 174 metabolites with MS, incorporating data from European-ancestry metabolomics (n=8569-86 507) and MS (n=14 802 MS cases, 26 703 controls) genomewide association studies. Genetic scores for identified causal metabolite(s) were then computed to predict MS disability progression in an independent longitudinal cohort (AusLong study) of 203 MS cases with up to 15-year follow-up.

RESULTS

We found a novel genetic causal effect of serine on MS onset (OR=1.67, 95% CI 1.51 to 1.84, p=1.73×10^-20), such that individuals whose serine level is 1 SD above the population mean will have 1.67 times the risk of developing MS. This is robust across all sensitivity methods (OR ranges from 1.49 to 1.67). In an independent longitudinal MS cohort, we then constructed time-dynamic and time-fixed genetic scores based on serine genetic instrument single-nucleotide polymorphisms, where higher scores for raised serum serine level were associated with increased risk of disability worsening, especially in the time-dynamic model (RR=1.25, 95% CI 1.10 to 1.42, p=7.52×10^-4).

CONCLUSIONS

These findings support investigating serine as an important candidate biomarker for MS onset and disability progression.

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. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

From 'Omics to Multi-omics Technologies: the Discovery of Novel Causal Mediators

PURPOSE OF REVIEW

'Omics studies provide a comprehensive characterisation of a biological entity, such as the genome, epigenome, transcriptome, proteome, metabolome, or microbiome. This review covers the unique properties of these types of 'omics and their roles as causal mediators in cardiovascular disease. Moreover, applications and challenges of integrating multiple types of 'omics data to increase predictive power, improve causal inference, and elucidate biological mechanisms are discussed.

RECENT FINDINGS

Multi-omics approaches are growing in adoption as they provide orthogonal evidence and overcome the limitations of individual types of 'omics data. Studies with multiple types of 'omics data have improved the diagnosis and prediction of disease states and afforded a deeper understanding of underlying pathophysiological mechanisms, beyond any single type of 'omics data. For instance, disease-associated loci in the genome can be supplemented with other 'omics to prioritise causal genes and understand the function of non-coding variants. Alternatively, techniques, such as Mendelian randomisation, can leverage genetics to provide evidence supporting a causal role for disease-associated molecules, and elucidate their role in disease pathogenesis. As technologies improve, costs for 'omics studies will continue to fall and datasets will become increasingly accessible to researchers. The intrinsically unbiased nature of 'omics data is well-suited to exploratory analyses that discover causal mediators of disease, and multi-omics is an emerging discipline that leverages the strengths of each type of 'omics data to provide insights greater than the sum of its parts.

A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.

Causal effects of maternal circulating amino acids on offspring birthweight: a Mendelian randomisation study

BACKGROUND

Amino acids are key to protein synthesis, energy metabolism, cell signaling and gene expression; however, the contribution of specific maternal amino acids to fetal growth is unclear.

METHODS

We explored the effect of maternal circulating amino acids on fetal growth, proxied by birthweight, using two-sample Mendelian randomisation (MR) and summary data from a genome-wide association study (GWAS) of serum amino acids levels (sample 1, n = 86,507) and a maternal GWAS of offspring birthweight in UK Biobank and Early Growth Genetics Consortium, adjusting for fetal genotype effects (sample 2, n = 406,063 with maternal and/or fetal genotype effect estimates). A total of 106 independent single nucleotide polymorphisms robustly associated with 19 amino acids (p < 4.9 × 10-10) were used as genetic instrumental variables (IV). Wald ratio and inverse variance weighted methods were used in MR main analysis. A series of sensitivity analyses were performed to explore IV assumption violations.

FINDINGS

Our results provide evidence that maternal circulating glutamine (59 g offspring birthweight increase per standard deviation increase in maternal amino acid level, 95% CI: 7, 110) and serine (27 g, 95% CI: 9, 46) raise, while leucine (-59 g, 95% CI: -106, -11) and phenylalanine (-25 g, 95% CI: -47, -4) lower offspring birthweight. These findings are supported by sensitivity analyses.

INTERPRETATION

Our findings strengthen evidence for key roles of maternal circulating amino acids during pregnancy in healthy fetal growth.

FUNDING

A full list of funding bodies that contributed to this study can be found under Acknowledgments.

Impact of the gut microbiota and associated metabolites on cardiometabolic traits, chronic diseases and human longevity: a Mendelian randomization study

Features of the gut microbiota have been associated with several chronic diseases and longevity in preclinical models as well as in observational studies. Whether these relations underlie causal effects in humans remains to be established. We aimed to determine whether the gut microbiota influences cardiometabolic traits as well as the risk of chronic diseases and human longevity using a comprehensive 2-Sample Mendelian randomization approach. We included as exposures 10 gut-associated metabolites and pathways and 57 microbial taxa abundance. We included as outcomes nine cardiometabolic traits (fasting glucose, fasting insulin, systolic blood pressure, diastolic blood pressure, HDL cholesterol, LDL cholesterol, triglycerides, estimated glomerular filtration rate, body mass index [BMI]), eight chronic diseases previously linked with the gut microbiota in observational studies (Alzheimer's disease, depression, type 2 diabetes, non-alcoholic fatty liver disease, coronary artery disease (CAD), stroke, osteoporosis and chronic kidney disease), as well as parental lifespan and longevity. We found 7 associations with evidence of causality before and after sensitivity analyses, but not after multiple testing correction (1198 tests). Most effect sizes (4/7) were small. The two largest exposure-outcome effects were markedly attenuated towards the null upon inclusion of BMI or alcohol intake frequency in multivariable MR analyses. While finding robust genetic instruments for microbiota features is challenging hence potentially inflating type 2 errors, these results do not support a large causal impact of human gut microbita features on cardiometabolic traits, chronic diseases or longevity. These results also suggest that the previously documented associations between gut microbiota and human health outcomes may not always underly causal relations.

Genetic influences on human blood metabolites in the Japanese population

An increase in ethnic diversity in genetic studies has the potential to provide unprecedented insights into how genetic variations influence human phenotypes. In this study, we conducted a quantitative trait locus (QTL) analysis of 121 metabolites measured using gas chromatography-mass spectrometry with plasma samples from 4,888 Japanese individuals. We found 60 metabolite-gene associations, of which 13 have not been previously reported. Meta-analyses with another Japanese and a European study identified six and two additional unreported loci, respectively. Genetic variants influencing metabolite levels were more enriched in protein-coding regions than in the regulatory regions while being associated with the risk of various diseases. Finally, we identified a signature of strong negative selection for uric acid ( S ˆ  = -1.53, p = 6.2 × 10^-18). Our study expanded the knowledge of genetic influences on human blood metabolites, providing valuable insights into their physiological, pathological, and selective properties.

Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data

BACKGROUND

Global or untargeted metabolomics is widely used to comprehensively investigate metabolic profiles under various pathophysiological conditions such as inflammations, infections, responses to exposures or interactions with microbial communities. However, biological interpretation of global metabolomics data remains a daunting task. Recent years have seen growing applications of pathway enrichment analysis based on putative annotations of liquid chromatography coupled with mass spectrometry (LC-MS) peaks for functional interpretation of LC-MS-based global metabolomics data. However, due to intricate peak-metabolite and metabolite-pathway relationships, considerable variations are observed among results obtained using different approaches. There is an urgent need to benchmark these approaches to inform the best practices.

RESULTS

We have conducted a benchmark study of common peak annotation approaches and pathway enrichment methods in current metabolomics studies. Representative approaches, including three peak annotation methods and four enrichment methods, were selected and benchmarked under different scenarios. Based on the results, we have provided a set of recommendations regarding peak annotation, ranking metrics and feature selection. The overall better performance was obtained for the mummichog approach. We have observed that a ~30% annotation rate is sufficient to achieve high recall (~90% based on mummichog), and using semi-annotated data improves functional interpretation. Based on the current platforms and enrichment methods, we further propose an identifiability index to indicate the possibility of a pathway being reliably identified. Finally, we evaluated all methods using 11 COVID-19 and 8 inflammatory bowel diseases (IBD) global metabolomics datasets.

Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene

Obesity remains an unmet global health burden. Detrimental anatomical distribution of body fat is a major driver of obesity-mediated mortality risk and is demonstrably heritable. However, our understanding of the full genetic contribution to human adiposity is incomplete, as few studies measure adiposity directly. To address this, we impute whole-body imaging adiposity phenotypes in UK Biobank from the 4,366 directly measured participants onto the rest of the cohort, greatly increasing our discovery power. Using these imputed phenotypes in 392,535 participants yielded hundreds of genome-wide significant associations, six of which replicate in independent cohorts. The leading causal gene candidate, ADAMTS14, is further investigated in a mouse knockout model. Concordant with the human association data, the Adamts14-/- mice exhibit reduced adiposity and weight-gain under obesogenic conditions, alongside an improved metabolic rate and health. Thus, we show that phenotypic imputation at scale offers deeper biological insights into the genetics of human adiposity that could lead to therapeutic targets.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P_FDR = 3.40 × 10^-5), CCR5 rs333 (OR = 1.99, P_FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P_FDR = 2.64 × 10^-4), TCF7L2 rs114758349 (OR = 1.77, P_FDR = 9.37 × 10^-5), and CCL2 rs1024611 (OR = 1.38, P_FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10^-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

The I148M PNPLA3 variant mitigates niacin beneficial effects: How the genetic screening in non-alcoholic fatty liver disease patients gains value

Background

The PNPLA3 p.I148M impact on fat accumulation can be modulated by nutrients. Niacin (Vitamin B3) reduced triglycerides synthesis in in vitro and in vivo NAFLD models.

Objectives

In this study, we aimed to investigate the niacin-I148M polymorphism crosstalk in NAFLD patients and examine niacin's beneficial effect in reducing fat by exploiting hepatoma cells with different PNPLA3 genotype.

Design

We enrolled 172 (Discovery cohort) and 358 (Validation cohort) patients with non-invasive and histological diagnosis of NAFLD, respectively. Dietary niacin was collected from food diary, while its serum levels were quantified by ELISA. Hepatic expression of genes related to NAD metabolism was evaluated by RNAseq in bariatric NAFLD patients (n = 183; Transcriptomic cohort). Hep3B (148I/I) and HepG2 (148M/M) cells were silenced (siHep3B) or overexpressed (HepG2^I148+ ) for PNPLA3, respectively.

Results

In the Discovery cohort, dietary niacin was significantly reduced in patients with steatosis ≥ 2 and in I148M carriers. Serum niacin was lower in subjects carrying the G at risk allele and negatively correlated with obesity. The latter result was confirmed in the Validation cohort. At multivariate analysis, the I148M polymorphism was independently associated with serum niacin, supporting that it may be directly involved in the modulation of its availability. siHep3B cells showed an impaired NAD biosynthesis comparable to HepG2 cells which led to lower niacin efficacy in clearing fat, supporting a required functional protein to guarantee its effectiveness. Conversely, the restoration of PNPLA3 Wt protein in HepG2^I148+ cells recovered the NAD pathway and improved niacin efficacy. Finally, niacin inhibited de novo lipogenesis through the ERK1/2/AMPK/SIRT1 pathway, with the consequent SREBP1-driven PNPLA3 reduction only in Hep3B and HepG2^I148M+ cells.

Conclusions

We demonstrated a niacin-PNPLA3 I148M interaction in NAFLD patients which possibly pave the way to vitamin B3 supplementation in those with a predisposing genetic background.

Inhibition of Diacylglycerol Acyltransferase 2 Versus Diacylglycerol Acyltransferase 1: Potential Therapeutic Implications of Pharmacology

PURPOSE

Hepatic steatosis due to altered lipid metabolism and accumulation of hepatic triglycerides is a hallmark of nonalcoholic fatty liver disease (NAFLD). Diacylglycerol acyltransferase (DGAT) enzymes, DGAT1 and DGAT2, catalyze the terminal reaction in triglyceride synthesis, making them attractive targets for pharmacologic intervention. There is a common misconception that these enzymes are related; however, despite their similar names, DGAT1 and DGAT2 differ significantly on multiple levels. As we look ahead to future clinical studies of DGAT2 inhibitors in patients with NAFLD and nonalcoholic steatohepatitis (NASH), we review key differences and include evidence to highlight and support DGAT2 inhibitor (DGAT2i) pharmacology.

METHODS

Three Phase I, randomized, double-blind, placebo-controlled trials assessed the safety, tolerability, and pharmacokinetic properties of the DGAT2i ervogastat (PF-06865571) in healthy adult participants (Single Dose Study to Assess the Safety, Tolerability and Pharmacokinetics of PF-06865571 [study C2541001] and Study to Assess the Safety, Tolerability, and Pharmacokinetics of Multiple Doses of PF-06865571 in Healthy, Including Overweight and Obese, Adult Subjects [study C2541002]) or participants with NAFLD (2-Week Study in People With Nonalcoholic Fatty Liver Disease [study C2541005]). Data from 2 Phase I, randomized, double-blind, placebo-controlled trials of the DGAT1i PF-04620110 in healthy participants (A Single Dose Study of PF-04620110 in Overweight and Obese, Otherwise Healthy Volunteers [study B0961001] and A Multiple Dose Study of PF-04620110 in Overweight and Obese, Otherwise Healthy Volunteers [study B0961002]) were included for comparison. Safety outcomes were the primary end point in all studies, except in study C2541005, in which safety was the secondary end point, with relative change from baseline in whole liver fat at day 15 assessed as the primary end point. Safety data were analyzed across studies by total daily dose of ervogastat (5, 15, 50, 100, 150, 500, 600, 1000, and 1500 mg) or PF-04620110 (0.3, 1, 3, 5, 7, 10, 14, and 21 mg), with placebo data pooled separately across ervogastat and PF-04620110 studies.

FINDINGS

Published data indicate that DGAT1 and DGAT2 differ in multiple dimensions, including gene family, subcellular localization, substrate preference, and specificity, with unrelated pharmacologic inhibition properties and differing safety profiles. Although initial nonclinical studies suggested a potentially attractive therapeutic profile with DGAT1 inhibition, genetic and pharmacologic data suggest otherwise, with common gastrointestinal adverse events, including nausea, vomiting, and diarrhea, limiting further clinical development. Conversely, DGAT2 inhibition, although initially not pursued as aggressively as a potential target for pharmacologic intervention, has consistent efficacy in nonclinical studies, with reduced triglyceride synthesis accompanied by reduced expression of genes essential for de novo lipogenesis. In addition, early clinical data indicate antisteatotic effects with DGAT2i ervogastat, in participants with NAFLD, accompanied by a well-tolerated safety profile.

IMPLICATIONS

Although pharmacologic DGAT1is are limited by an adverse safety profile, data support use of DGAT2i as an effective and well-tolerated therapeutic strategy for patients with NAFLD, NASH, and NASH with liver fibrosis.

CLINICALTRIALS

gov identifiers: NCT03092232, NCT03230383, NCT03513588, NCT00799006, and NCT00959426.

Genetic Mimicry Analysis Reveals the Specific Lipases Targeted by the ANGPTL3-ANGPTL8 Complex and ANGPTL4

Angiopoietin-like proteins, ANGPTL3, ANGPTL4, and ANGPTL8, are involved in regulating plasma lipids. In vitro and animal-based studies point to LPL and endothelial lipase (EL, LIPG) as key targets of ANGPTLs. To examine the ANGPTL mechanisms for plasma lipid modulation in humans, we pursued a genetic mimicry analysis of enhancing or suppressing variants in the LPL, LIPG, lipase C hepatic type (LIPC), ANGPTL3, ANGPTL4, and ANGPTL8 genes using data on 248 metabolic parameters derived from over 110,000 nonfasted individuals in the UK Biobank and validated in over 13,000 overnight fasted individuals from 11 other European populations. ANGPTL4 suppression was highly concordant with LPL enhancement but not HL or EL, suggesting ANGPTL4 impacts plasma metabolic parameters exclusively via LPL. The LPL-independent effects of ANGPTL3 suppression on plasma metabolic parameters showed a striking inverse resemblance with EL suppression, suggesting ANGPTL3 not only targets LPL but also targets EL. Investigation of the impact of the ANGPTL3-ANGPTL8 complex on plasma metabolite traits via the ANGPTL8 R59W substitution as an instrumental variable showed a much higher concordance between R59W and EL activity than between R59W and LPL activity, suggesting the R59W substitution more strongly affects EL inhibition than LPL inhibition. Meanwhile, when using a rare and deleterious protein-truncating ANGPTL8 variant as an instrumental variable, the ANGPTL3-ANGPTL8 complex was very LPL specific. In conclusion, our analysis provides strong human genetic evidence that the ANGPTL3-ANGPTL8 complex regulates plasma metabolic parameters, which is achieved by impacting LPL and EL. By contrast, ANGPTL4 influences plasma metabolic parameters exclusively via LPL.

Immune Checkpoint Inhibitor-Based Combination Therapy for Colorectal Cancer: An Overview

Colorectal cancer (CRC) is one of the most common diseases in the world. Tumor immunotherapy is an innovative cancer treatment that acts by activating the human body's autoimmune system. Immune checkpoint block has been shown to be effective in DNA deficient mismatch repair/microsatellite instability-high CRC. However, the therapeutic effect for proficient mismatch repair/microsatellite stability patients still requires further study and optimization. At present, the main CRC strategy is to combine other therapeutic methods, such as chemotherapy, targeted therapy, and radiotherapy. Here, we review the current status and the latest progress of immune checkpoint inhibitors in the treatment of CRC. At the same time, we consider therapeutic opportunities for transforming cold to hot, as well as perspectives on possible future therapies, which may be in great demand for drug-resistant patients.

Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases

Metabolic processes can influence disease risk and provide therapeutic targets. By conducting genome-wide association studies of 1,091 blood metabolites and 309 metabolite ratios, we identified associations with 690 metabolites at 248 loci and associations with 143 metabolite ratios at 69 loci. Integrating metabolite-gene and gene expression information identified 94 effector genes for 109 metabolites and 48 metabolite ratios. Using Mendelian randomization (MR), we identified 22 metabolites and 20 metabolite ratios having estimated causal effect on 12 traits and diseases, including orotate for estimated bone mineral density, α-hydroxyisovalerate for body mass index and ergothioneine for inflammatory bowel disease and asthma. We further measured the orotate level in a separate cohort and demonstrated that, consistent with MR, orotate levels were positively associated with incident hip fractures. This study provides a valuable resource describing the genetic architecture of metabolites and delivers insights into their roles in common diseases, thereby offering opportunities for therapeutic targets.