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JAMA Network Open Sep 2023Body mass index (BMI) is an easily obtained adiposity surrogate. However, there is variability in body composition and adipose tissue distribution between individuals...
IMPORTANCE
Body mass index (BMI) is an easily obtained adiposity surrogate. However, there is variability in body composition and adipose tissue distribution between individuals with the same BMI, and there is controversy regarding the BMI associated with the lowest mortality risk.
OBJECTIVE
To evaluate which of BMI, fat mass index (FMI), and waist-to-hip (WHR) has the strongest and most consistent association with mortality.
DESIGN, SETTING, AND PARTICIPANT
This cohort study used incident deaths from the UK Biobank (UKB; 2006-2022), which includes data from 22 clinical assessment centers across the United Kingdom. UKB British participants of British White ancestry (N = 387 672) were partitioned into a discovery cohort (n = 337 078) and validation cohort (n = 50 594), with the latter consisting of 25 297 deaths and 25 297 controls. The discovery cohort was used to derive genetically determined adiposity measures while the validation cohort was used for analyses. Exposure-outcome associations were analyzed through observational and mendelian randomization (MR) analyses.
EXPOSURES
BMI, FMI, and WHR.
MAIN OUTCOMES AND MEASURES
All-cause and cause-specific (cancer, cardiovascular disease [CVD], respiratory disease, or other causes) mortality.
RESULTS
There were 387 672 and 50 594 participants in our observational (mean [SD] age, 56.9 [8.0] years; 177 340 [45.9%] male, 210 332 [54.2%], female), and MR (mean [SD] age, 61.6 [6.2] years; 30 031 [59.3%] male, 20 563 [40.6%], female) analyses, respectively. Associations between measured BMI and FMI with all-cause mortality were J-shaped, whereas the association of WHR with all-cause mortality was linear using the hazard ratio (HR) scale (HR per SD increase of WHR, 1.41 [95% CI, 1.38-1.43]). Genetically determined WHR had a stronger association with all-cause mortality than BMI (odds ratio [OR] per SD increase of WHR, 1.51 [95% CI, 1.32-1.72]; OR per SD increase of BMI, 1.29 [95% CI, 1.20-1.38]; P for heterogeneity = .02). This association was stronger in male than female participants (OR, 1.89 [95% CI, 1.54-2.32]; P for heterogeneity = .01). Unlike BMI or FMI, the genetically determined WHR-all-cause mortality association was consistent irrespective of observed BMI.
CONCLUSIONS AND RELEVANCE
In this cohort study, WHR had the strongest and most consistent association with mortality irrespective of BMI. Clinical recommendations should consider focusing on adiposity distribution compared with mass.
Topics: Humans; Female; Male; Middle Aged; Adiposity; Cohort Studies; Obesity; Body Fat Distribution; Biomarkers
PubMed: 37728925
DOI: 10.1001/jamanetworkopen.2023.34836 -
Nature Communications Nov 2023The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings...
The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings across studies impede a comprehensive understanding of their roles in IBD and their potential as reliable diagnostic biomarkers. To address this challenge, here we comprehensively analyze 9 metagenomic and 4 metabolomics cohorts of IBD from different populations. Through cross-cohort integrative analysis (CCIA), we identify a consistent characteristic of commensal gut microbiota. Especially, three bacteria, namely Asaccharobacter celatus, Gemmiger formicilis, and Erysipelatoclostridium ramosum, which are rarely reported in IBD. Metagenomic functional analysis reveals that essential gene of Two-component system pathway, linked to fecal calprotectin, are implicated in IBD. Metabolomics analysis shows 36 identified metabolites with significant differences, while the roles of these metabolites in IBD are still unknown. To further elucidate the relationship between gut microbiota and metabolites, we construct multi-omics biological correlation (MOBC) maps, which highlights gut microbial biotransformation deficiencies and significant alterations in aminoacyl-tRNA synthetases. Finally, we identify multi-omics biomarkers for IBD diagnosis, validated across multiple global cohorts (AUROC values ranging from 0.92 to 0.98). Our results offer valuable insights and a significant resource for developing mechanistic hypotheses on host-microbiome interactions in IBD.
Topics: Humans; Multiomics; Inflammatory Bowel Diseases; Metabolome; Microbiota; Biomarkers
PubMed: 37932270
DOI: 10.1038/s41467-023-42788-0 -
Molecular & Cellular Proteomics : MCP Jul 2023Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the...
Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification, and quantification, making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In in a previous review in 2017, we described technological and conceptual limitations that had held back success. We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification, and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. Shorter gradients, new scan modes, and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multiprotein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.
Topics: Humans; Proteomics; Mass Spectrometry; Biomarkers; Proteome; Body Fluids
PubMed: 37209816
DOI: 10.1016/j.mcpro.2023.100577 -
EBioMedicine Jul 2023Individual plasma proteins have been identified as minimally invasive biomarkers for lung cancer diagnosis with potential utility in early detection. Plasma proteomes...
BACKGROUND
Individual plasma proteins have been identified as minimally invasive biomarkers for lung cancer diagnosis with potential utility in early detection. Plasma proteomes provide insight into contributing biological factors; we investigated their potential for future lung cancer prediction.
METHODS
The Olink® Explore-3072 platform quantitated 2941 proteins in 496 Liverpool Lung Project plasma samples, including 131 cases taken 1-10 years prior to diagnosis, 237 controls, and 90 subjects at multiple times. 1112 proteins significantly associated with haemolysis were excluded. Feature selection with bootstrapping identified differentially expressed proteins, subsequently modelled for lung cancer prediction and validated in UK Biobank data.
FINDINGS
For samples 1-3 years pre-diagnosis, 240 proteins were significantly different in cases; for 1-5 year samples, 117 of these and 150 further proteins were identified, mapping to significantly different pathways. Four machine learning algorithms gave median AUCs of 0.76-0.90 and 0.73-0.83 for the 1-3 year and 1-5 year proteins respectively. External validation gave AUCs of 0.75 (1-3 year) and 0.69 (1-5 year), with AUC 0.7 up to 12 years prior to diagnosis. The models were independent of age, smoking duration, cancer histology and the presence of COPD.
INTERPRETATION
The plasma proteome provides biomarkers which may be used to identify those at greatest risk of lung cancer. The proteins and the pathways are different when lung cancer is more imminent, indicating that both biomarkers of inherent risk and biomarkers associated with presence of early lung cancer may be identified.
FUNDING
Janssen Pharmaceuticals Research Collaboration Award; Roy Castle Lung Cancer Foundation.
Topics: Humans; Biomarkers, Tumor; Early Detection of Cancer; Lung Neoplasms; Biomarkers; Blood Proteins; Smoking; Proteome
PubMed: 37379654
DOI: 10.1016/j.ebiom.2023.104686 -
Frontiers in Endocrinology 2023
Topics: Humans; Prediabetic State; Endocrine System
PubMed: 37664837
DOI: 10.3389/fendo.2023.1268552 -
Nature Communications Dec 2023Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based...
Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.
Topics: Humans; Carcinoma, Hepatocellular; Liver Neoplasms; Biomarkers, Tumor; Proteomics; Prospective Studies; alpha-Fetoproteins; Biomarkers; Early Detection of Cancer
PubMed: 38110372
DOI: 10.1038/s41467-023-44255-2 -
Ageing Research Reviews Nov 2023According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age... (Review)
Review
According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.
Topics: Humans; Frailty; Artificial Intelligence; Aging; Biomarkers; Inflammation
PubMed: 37647997
DOI: 10.1016/j.arr.2023.102044 -
Nutrients Jul 2023Dietary vitamin B3 components, such as nicotinamide and nicotinic acid, are precursors to the ubiquitous redox cofactor nicotinamide adenine dinucleotide (NAD). NAD... (Review)
Review
Dietary vitamin B3 components, such as nicotinamide and nicotinic acid, are precursors to the ubiquitous redox cofactor nicotinamide adenine dinucleotide (NAD). NAD levels are thought to decline with age and disease. While the drivers of this decline remain under intense investigation, strategies have emerged seeking to functionally maintain NAD levels through supplementation with NAD biosynthetic intermediates. These include marketed products, such as nicotinamide riboside (NR) and its phosphorylated form (NMN). More recent developments have shown that NRH (the reduced form of NR) and its phosphorylated form NMNH also increases NAD levels upon administration, although they initially generate NADH (the reduced form of NAD). Other means to increase the combined levels of NAD and NADH, NAD(H), include the inhibition of NAD-consuming enzymes or activation of biosynthetic pathways. Multiple studies have shown that supplementation with an NAD(H) precursor changes the profile of NAD(H) catabolism. Yet, the pharmacological significance of NAD(H) catabolites is rarely considered although the distribution and abundance of these catabolites differ depending on the NAD(H) precursor used, the species in which the study is conducted, and the tissues used for the quantification. Significantly, some of these metabolites have emerged as biomarkers in physiological disorders and might not be innocuous. Herein, we review the known and emerging catabolites of the NAD(H) metabolome and highlight their biochemical and physiological function as well as key chemical and biochemical reactions leading to their formation. Furthermore, we emphasize the need for analytical methods that inform on the full NAD(H) metabolome since the relative abundance of NAD(H) catabolites informs how NAD(H) precursors are used, recycled, and eliminated.
Topics: NAD; Niacinamide; Niacin; Metabolome; Oxidation-Reduction; Biomarkers
PubMed: 37447389
DOI: 10.3390/nu15133064 -
Proceedings of the National Academy of... Jul 2023Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of...
Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the supervised tissue deconvolution approach, a deep-learning-powered model, , for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.
Topics: Humans; Cell-Free Nucleic Acids; Deep Learning; DNA Methylation; Biomarkers; Promoter Regions, Genetic; Biomarkers, Tumor
PubMed: 37399400
DOI: 10.1073/pnas.2305236120 -
Bioanalysis Jul 2023The 2022 16th Workshop on Recent Issues in Bioanalysis (WRIB) took place in Atlanta, GA, USA on September 26-30, 2022. Over 1000 professionals representing...
2022 White Paper on Recent Issues in Bioanalysis: FDA Draft Guidance on Immunogenicity Information in Prescription Drug Labeling, LNP & Viral Vectors Therapeutics/Vaccines Immunogenicity, Prolongation Effect, ADA Affinity, Risk-based Approaches, NGS, qPCR, ddPCR Assays ( - Recommendations on Gene...
The 2022 16th Workshop on Recent Issues in Bioanalysis (WRIB) took place in Atlanta, GA, USA on September 26-30, 2022. Over 1000 professionals representing pharma/biotech companies, CROs, and multiple regulatory agencies convened to actively discuss the most current topics of interest in bioanalysis. The 16th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on ICH M10 BMV final guideline (focused on this guideline training, interpretation, adoption and transition); mass spectrometry innovation (focused on novel technologies, novel modalities, and novel challenges); and flow cytometry bioanalysis (rising of the 3rd most common/important technology in bioanalytical labs) were the special features of the 16th edition. As in previous years, WRIB continued to gather a wide diversity of international, industry opinion leaders and regulatory authority experts working on both small and large molecules as well as gene, cell therapies and vaccines to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance, and achieving scientific excellence on bioanalytical issues. This 2022 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2022 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 3) covers the recommendations on Gene Therapy, Cell therapy, Vaccines and Biotherapeutics Immunogenicity. Part 1 (Mass Spectrometry and ICH M10) and Part 2 (LBA, Biomarkers/CDx and Cytometry) are published in volume 15 of Bioanalysis, issues 16 and 15 (2023), respectively.
Topics: Prescription Drugs; Technology; Biological Assay; Biomarkers; Cell- and Tissue-Based Therapy
PubMed: 37526071
DOI: 10.4155/bio-2023-0135