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PubMed2025

Novel approaches and applications in identifying DNA methylation markers of cardio-kidney-metabolic disease.

Cardio-kidney-metabolic (CKM) diseases represent a major public health challenge, accounting for a large proportion of global burden of morbidity and mortality. These conditions share risk factors, including genetic predisposition, environmental exposures, and lifestyle influences, which collectively drive disease development and progression. Epigenetic modifications, particularly DNA methylation (DNAm), serve as key mediators and biomarkers between these risk factors and disease phenotypes by regulating gene expression without altering the DNA sequence. Epigenome-wide association studies have identified DNAm markers associated with CKM diseases and related phenotypes, highlighting both shared pathways and disease-specific epigenetic signatures in inflammation, metabolic dysfunction, and aging-related processes. Longitudinal studies further demonstrate the dynamic nature of DNAm changes over time, offering insights into disease trajectories. Additionally, methylation risk scores integrating multiple epigenetic markers show promise in improving disease prediction and risk stratification beyond traditional clinical factors. To synthesize the current evidence, we conducted a targeted literature search in PubMed for English-language, peer-reviewed articles published between 2014 and the present. Future research leveraging large, well-phenotyped cohorts, advanced statistical methods, and innovative study designs will be critical for uncovering novel biomarkers, refining risk prediction models, and developing targeted epigenetic therapies to mitigate the global burden.

Humans↗
PubMed2026

Identifying Co-Expressed lncRNAs Correlated With Traits of Interest in an Animal Model for Metabolic Diseases in Humans.

Nutrigenomics investigates how nutrients modulate gene expression. Among them, fatty acids (FA) play important roles in regulating gene transcription, while long non-coding RNAs (lncRNAs) may be associated with gene regulation and metabolic diseases. This study aimed to analyze the hepatic transcriptome of pigs, a species frequently used as a model for nutrigenomic studies, to identify novel lncRNAs and their potential target genes in response to diets containing different sources of FA. Seventy-two pigs were fed four diets supplemented with 1.5% soybean oil (control), 3% canola oil, 3% fish oil, and 3% soybean oil. RNA sequencing of liver samples was performed to identify novel lncRNAs. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify modules associated with phenotypic traits related to lipid metabolism and inflammation. Functional enrichment analyses were then conducted to annotate genes within these modules using Gene Ontology (GO) terms and to assess overlap with Quantitative Trait Loci (QTL). The results revealed 106 novel lncRNAs potentially regulating genes associated with lipid metabolism and immune responses in pigs fed diets with different FA sources. These findings enhance understanding of the regulatory role of lncRNAs in pigs and reinforce their relevance as models for human metabolic diseases.

Animals↗
PubMed2026

SNP-derived CpG variation and DNA methylation linking genetic susceptibility to metabolic disease.

DNA methylation at CpG dinucleotides represents a key epigenetic mechanism linking genetic variation to gene regulation in complex human diseases. Single-nucleotide polymorphisms (SNPs) that create or disrupt CpG sites can alter local DNA methylation and transcriptional activity, thereby influencing disease susceptibility. These CpG-modifying variants provide a functional interface between inherited genetic variation and epigenetic regulation in complex metabolic disorders. This review summarizes current evidence on SNP-derived CpG variation and its role in allele-specific DNA methylation and gene regulation in metabolically relevant tissues. By integrating findings from genome-wide association studies, epigenome-wide association studies, and multi-omics research, this review provides a mechanistic framework explaining how CpG-modifying polymorphisms influence adipogenesis, pancreatic β-cell function, inflammation, and glucose metabolism. Special emphasis is placed on South Asian populations, who exhibit early β-cell dysfunction and increased visceral adiposity. Many CpG-modifying variants act as methylation quantitative trait loci (meQTLs), influencing allele-specific methylation and gene expression. Understanding SNP-CpG-methylation interactions may improve functional interpretation of disease-associated genetic variants, enhance biomarker discovery, and support precision medicine strategies for metabolic disease.

Humans↗
PubMed2026

Reduced R-loop abundance at proinflammatory loci: a shared epigenetic mechanism in inflammatory and metabolic diseases.

INTRODUCTION: R-loops, RNA-DNA hybrid structures with a displaced single-stranded DNA loop, are key regulators of transcriptional control, chromatin architecture, and genome stability and have emerging roles in inflammatory signaling. However, the relationship between R-loop abundance and strongly modulated inflammatory effector genes in metabolic inflammation and influenza virus infection remains underexplored. METHODS: We performed a locus-centric integrative analysis combining robust differentially expressed genes (DEGs) from multiple inflammatory and infection-related murine and human transcriptomic disease models with experimentally validated multi-cell R-loop annotations from the reference atlas RLoopBase. Our correlation framework evaluated the directional relationship between R-loop abundance and inflammatory gene expression rather than assuming disease-sample-matched R-loop measurements. We further analyzed R-loop regulatory proteins, NRF2-associated R-loop regulators, and overlaps between R-loop regulators and CRISPRi-identified mitochondrial and cellular reactive oxygen species (ROS) regulators. RESULTS: In angiotensin II-infused apolipoprotein E-deficient (ApoE-/-) mice, a model of abdominal aortic aneurysm (AAA), genomic regions encoding the top significantly upregulated genes exhibited significantly fewer R-loops than those encoding downregulated genes at days 14 and 28. Similarly, in atherosclerotic ApoE-/- mice fed a high-fat diet for 32 and 78 weeks, upregulated genes were associated with fewer R-loops than downregulated genes. Reduced R-loop abundance was also observed in genomic regions encoding the top significantly upregulated genes in liver tissues from patients with non-alcoholic steatohepatitis (NASH), as well as in monosodium urate (MSU)-stimulated lymphatic endothelial cells (LECs) and influenza virus-infected human umbilical vein endothelial cells (HUVECs). R-loop regulatory proteins upregulated during metabolic inflammation were enriched in immune and inflammatory pathways. NRF2 was identified as a regulator of 27 R-loop regulatory proteins, including 10 positively and 17 negatively regulated proteins. Furthermore, 54 R-loop regulatory proteins overlapped with CRISPRi-identified mitochondrial and cellular ROS regulators, suggesting potential reciprocal regulation between R-loop homeostasis and ROS signaling. Disease-associated changes in pro-ROS and anti-ROS R-loop regulatory proteins further linked R-loop regulation to inflammatory and oxidative stress pathways. DISCUSSION: These findings identify reduced R-loop abundance at genomic regions encoding strongly upregulated inflammatory genes as a shared feature across multiple models of metabolic inflammation and influenza virus infection. The results further suggest that immune-associated R-loop regulatory proteins and the NRF2-ROS axis may contribute to R-loop remodeling during inflammatory disease. This integrative framework provides new insight into the potential role of R-loops and ROS-sensitive R-loop regulators in inflammatory and metabolic diseases and identifies candidate pathways for future mechanistic investigation and therapeutic targeting.

R-loop regulatory proteins↗
PubMed2026

Integrative pan-cancer analysis of transferrin reveals context-dependent prognostic associations and links to immune and metabolic disease-related programs.

BACKGROUND: Iron metabolism is closely linked to tumor biology, yet the pan-cancer significance of transferrin (TF), the major circulating iron-transport protein, remains insufficiently defined. Although TF has been implicated in cancer-related processes, its prognostic relevance, immune associations, and broader disease-related transcriptional context have not been systematically characterized across tumor types. OBJECTIVE: This study aimed to perform an integrative pan-cancer analysis of TF to characterize its expression patterns, clinical associations, immune context, pathway features, and pharmacogenomic correlations, and to explore whether TF-related signals extend to selected metabolic and chronic organ injury settings. METHODS: We used multiple public databases, including The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE), to integrate transcriptomic, proteomic, and clinical data across 33 tumor types and selected non-malignant conditions. TF expression was evaluated across normal tissues, tumors, and cell lines, followed by survival analysis, immune infiltration analysis, TMB/MSI and methylation assessment, pathway enrichment, and drug-response correlation. Independent GEO cohorts of non-alcoholic steatohepatitis (NASH), heart failure (HF), and liver cirrhosis (LC) were used for cross-disease extension. Selected findings were further explored in OA/PA-treated hepatocytes, 786-O renal carcinoma cells, and AC16 cardiomyocytes. RESULTS: TF showed pronounced tissue specificity and cancer-type-dependent dysregulation. Across pan-cancer cohorts, the most consistent adverse survival associations were observed in kidney renal clear cell carcinoma (KIRC) and stomach adenocarcinoma (STAD), where TF remained associated with overall survival (OS) in multivariable analyses. TF expression was also correlated with cancer-type-specific immune infiltration patterns and selected drug-response profiles. Across independent NASH, HF, and LC datasets, TF expression was elevated and TF-associated pathways partially overlapped with those observed in cancer. In vitro experiments provided preliminary support that TF modulation is associated with proliferative phenotypes in KIRC cells and stress- and metabolism-related phenotypes in hepatocyte and cardiomyocyte models. CONCLUSION: These findings support TF as a context-dependent biomarker candidate in cancer, with the most consistent prognostic relevance observed in KIRC and STAD. Rather than establishing a unified mechanism across diseases, this study provides an integrative framework suggesting that TF is associated with malignant behavior, immune context, and selected metabolic stress-related programs, and warrants further mechanistic investigation.

Iron metabolism↗
PubMed2025

Understanding disease-associated metabolic changes in human colonic epithelial cells using the iColonEpithelium metabolic reconstruction.

The colonic epithelium plays a key role in the host-microbiome interactions, allowing uptake of various nutrients and driving important metabolic processes. To unravel detailed metabolic activities in the human colonic epithelium, our present study focuses on the generation of the first cell-type-specific genome-scale metabolic model (GEM) of human colonic epithelial cells, named iColonEpithelium. GEMs are powerful tools for exploring reactions and metabolites at the systems level and predicting the flux distributions at steady state. Our cell-type-specific iColonEpithelium metabolic reconstruction captures genes specifically expressed in the human colonic epithelial cells. iColonEpithelium is also capable of performing metabolic tasks specific to the colonic epithelium. A unique transport reaction compartment has been included to allow for the simulation of metabolic interactions with the gut microbiome. We used iColonEpithelium to identify metabolic signatures associated with inflammatory bowel disease. We used single-cell RNA sequencing data from Crohn's Diseases (CD) and ulcerative colitis (UC) samples to build disease-specific iColonEpithelium metabolic networks in order to predict metabolic signatures of colonocytes in both healthy and disease states. We identified reactions in nucleotide interconversion, fatty acid synthesis and tryptophan metabolism were differentially regulated in CD and UC conditions, relative to healthy control, which were in accordance with experimental results. The iColonEpithelium metabolic network can be used to identify mechanisms at the cellular level, and we show an initial proof-of-concept for how our tool can be leveraged to explore the metabolic interactions between host and gut microbiota.

Humans↗
PubMed2025

The SELENOP Polymorphism rs7579 Predicts Hepatic Steatosis in Females With Insulin Resistance in the General Population.

CONTEXT: Selenoprotein P is a hepatokine associated with several metabolic processes. Rs7579 (C > T) is a SeP-related functional single nucleotide polymorphism. OBJECTIVE: In this study, we aimed to identify the environmental factors affecting the relationship between rs7579 and metabolic diseases, such as metabolic dysfunction-associated steatotic liver disease, in the general population. METHODS: This cross-sectional study was based on the Shika Study, a survey of residents in the Noto Peninsula of Ishikawa Prefecture. We analyzed a total of 900 adults, measuring full-length selenoprotein P (FL-SeP) serum levels using a sol-particle homogeneous immunoassay. RESULTS: We observed that selenium and FL-SeP serum levels were associated with dyslipidemia. In males, serum selenium was associated with dyslipidemia and hepatic steatosis. However, in females, FL-SeP tended to be associated with diabetes. Participants carrying the TT genotype and hepatic steatosis exhibited higher levels of liver enzymes, insulin, the homeostatic model assessment of insulin resistance (HOMA-IR), and the homeostasis model assessment of β-cell function than those without hepatic steatosis or with other genotypes. In females carrying the TT genotype of rs7579, hepatic steatosis, hypertension, diabetes, obesity, and metabolic syndrome were associated with higher HOMA-IR levels. CONCLUSION: In this study, we revealed that the association between metabolic diseases and HOMA-IR differed single nucleotide polymorphism genotype and sex dependently. In females carrying the TT genotype of rs7579, hepatic steatosis-associated metabolic disorders (diabetes, hypertension, obesity, and metabolic syndrome) were associated with higher HOMA-IR. The results of this study open the way to genetic signatures-based personalized preventive medicines.

CCDC152↗
PubMed2026

The association between GLP-1R expression and cardiovascular-kidney-metabolic-related diseases in non-diabetic and non-obese population: evidence triangulation using Mendelian randomization, observational and polygenic score association analysis.

BACKGROUND: Glucagon-like peptide-1 receptor (GLP-1R) agonists are emerging as promising therapies for cardiovascular-kidney-metabolic (CKM) related diseases in individuals with type 2 diabetes mellitus (T2DM) or obesity. But their effects in non-obese and non-diabetic individuals are unclear. This study triangulates evidence using Mendelian randomization (MR), polygenic scores (PGS) and observational analyses to estimate the associations of GLP-1R expression with chronic kidney disease (CKD), heart failure (HF) and metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: For the MR analysis, instruments mimicking GLP-1R expression were identified using pancreas-specific cis-expression quantitative trait loci from GTEx (N ≤ 305). MR-Robust method was used as the primary MR approach. PGS and observational analyses were performed both in non-diabetic and non-obese individuals separately. A genome-wide association study (GWAS) for MASLD (14,231 cases and 348,091 controls) was performed in the general population using data from UK Biobank. RESULTS: GLP-1R expression showed robust effects on CKD (odds ratio [OR] 0.96, 95%CI 0.95 to 0.97, q = 1.7 × 10- 10 ), HF (OR = 0.96, 95%CI 0.94 to 0.97, q = 2.5 × 10- 8) and MASLD (OR = 0.96, 95%CI 0.93 to 0.98, q = 1.3 × 10- 3) in the general population. Consistent results were observed in validation analyses. Furthermore, PGS and observational analyses among non-T2DM and non-obese individuals found little evidence to support its association with CKD, HF or MASLD. GWAS analysis identified eight conditionally independent variants associated with MASLD, in which rs563199662 was a new signal located at TFPI region. CONCLUSIONS: This study provides multilayered evidence for GLP-1R expression in mitigating CKD, HF and MASLD risks in the general population, while de-prioritized its effect on CKM-related diseases in non-obese and non-diabetic individuals. Further clinical trials are needed to validate the effects of GLP-1R agonists in relative health population.

Humans↗
PubMed2022

Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children.

BACKGROUND: Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion. OBJECTIVES: We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort. METHODS: We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members. RESULTS: All 3 parameters were significantly heritable (h2&#xa0;=&#xa0;0.22-0.78; P&#xa0;<&#xa0;0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P&#xa0;<&#xa0;3.5&#xa0;&#xd7;&#xa0;10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (&#x3b2; = 0.68; SE, 0.25; P&#xa0;=&#xa0;0.006) and rs3796191 (&#x3b2; = 0.25; SE, 0.08; P&#xa0;=&#xa0;0.003) and between glycine and rs3796191 (&#x3b2; = -0.08; SE, 0.02; P&#xa0;=&#xa0;0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P&#xa0;<&#xa0;0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P&#xa0;<&#xa0;0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P&#xa0;<&#xa0;0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes. CONCLUSIONS: Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.

Child↗
PubMed2026

Effect of semaglutide on kidney outcomes in the SELECT, FLOW, and SOUL trials: a prespecified pooled analysis.

BACKGROUND: The GLP-1 receptor agonist semaglutide reduces clinically important kidney outcomes in people with type 2 diabetes and chronic kidney disease (CKD). We aimed to assess the pooled effects of semaglutide on kidney outcomes in prespecified analyses of participant-level data from the diverse populations of the SELECT, FLOW, and SOUL randomised placebo-controlled trials. METHODS: Participants with CKD (FLOW) or atherosclerotic cardiovascular disease (SELECT and SOUL) were randomly assigned semaglutide (once-weekly subcutaneous 1&#xb7;0 mg [FLOW], once-weekly subcutaneous 2&#xb7;4 mg [SELECT], or once-daily oral 14 mg [SOUL]) or matching placebo, added to standard of care. The primary outcome in this pooled analysis was time to first occurrence of a kidney composite, defined as onset of persistent 50% or greater reduction in estimated glomerular filtration rate (eGFR), kidney failure (persistent eGFR <15 mL/min per 1&#xb7;73 m2, or initiation of kidney replacement therapy), kidney-related death, or cardiovascular-related death. Safety was also assessed. FINDINGS: The pooled participants from the trials (N=30&#x2008;787) had a mean follow-up of 39&#xb7;5-47&#xb7;5 months. Among participants assigned to semaglutide, 973 first events of the primary kidney composite occurred compared with 1134 first events for placebo (hazard ratio [HR] 0&#xb7;84 [95% CI 0&#xb7;77-0&#xb7;91]). First events of a narrower secondary kidney composite (excluding cardiovascular-related death from the primary outcome) were also reduced with semaglutide versus placebo (347 and 416, respectively; 0&#xb7;80 [0&#xb7;69-0&#xb7;92]). Safety outcomes were overall similar between groups, and in line with other GLP-1 receptor agonist trials. Serious adverse events were numberically lower with semaglutide than with placebo. INTERPRETATION: Data pooled from three large phase 3 trials suggest that semaglutide reduces the risk of major kidney outcomes in a broad population with cardio-kidney-metabolic disease while having a favourable risk-benefit profile. In people with cardio-kidney-metabolic disease, with and without diabetes, semaglutide (oral or injected) prevents kidney-related and cardiovascular complications and induces adverse events in line with GLP-1 receptor agonist studies, regardless of baseline characteristics within the cardio-kidney-metabolic spectrum. This was a participant-level analysis conducted in a large database of three randomised controlled trials of similar design and examining the same treatment, but there were some differences in participants' baseline characteristics, and in the dose and route of administration of treatment. This pooled analysis adds evidence for the benefit of GLP-1 receptor agonists in general, and semaglutide in particular, in a broad population of people with cardio-kidney-metabolic disease, suggesting that the benefit of semaglutide might not be explained only by its glycaemic effects, weight-management effects, or both. FUNDING: Novo Nordisk.

Humans↗
PubMed2022

Insights on the pathogenesis of type 2 diabetes as revealed by signature genomic classifiers in an African American population in the Washington, DC area.

AIMS: African Americans (AA) in the United States have a high risk of type 2 diabetes mellitus (T2DM) and suffer from disparities in the prevalence, mortality, and comorbidities of the disease compared to other Americans. The present study aimed to shed light on the molecular mechanisms of disease pathogenesis of T2DM among AA in the Washington, DC region. METHODS: We performed TaqMan Low Density Arrays (TLDA) on 24 genes of interest that belong to three categories: metabolic disease and disorders, cancer-related genes, and neurobehavioural disorders genes. The 18 genes, viz. ARNT, CYP2D6, IL6, INSR, RRAD, SLC2A2 (metabolic disease and disorders), APC, BCL2, CSNK1D, MYC, SOD2, TP53 (Cancer-related), APBA1, APBB2, APOC1, APOE, GSK3B, and NAE1 (neurobehavioural disorders), were differentially expressed in T2DM participants compared to controls. RESULTS: Our results suggest that factors including gender, smoking habits, and the severity or lack of control of T2DM (as indicated by HbA1c levels) were significantly associated with differential gene expression. APBA1 was significantly (p-value <0.05) downregulated in all diabetes participants. Upregulation of APOE and CYP2D6 genes and downregulation of the INSR gene were observed in the majority of diabetes patients. CONCLUSIONS: Tobacco smoking and gender were significantly associated with case-control differences in expression of the APBA1 and APOE genes (connected with Alzheimer's disease) and the INSR and CYP2D6 (associated with metabolic disorders). The results highlight the need for more effective management of T2DM and for tobacco smoking cessation interventions in this community, and further research on the associations of T2DM with other disease processes, including cancer and neurobehavioral pathways.

Humans↗
PubMed2024

Association of urinary levels of trace metals with type 2 diabetes and obesity in postmenopausal women in Korea: A community-based cohort study.

Several toxic metals have been associated with metabolic diseases like obesity and diabetes mellitus (DM) in humans. However, knowledge regarding the influence of many trace elements, especially in combination with essential elements is limited. This study aims to address this research gap by investigating the associations of both non-essential and essential inorganic trace elements in urine with DM and obesity, employing a group of postmenopausal women (n&#xa0;=&#xa0;851) from the Korean Genome and Epidemiology Study (KoGES) cohort. Urine samples were collected during 2017-2018, and were analyzed for 19 trace elements using inductively coupled plasma-mass spectrometry and an automatic mercury analyzer. Outcomes of interest were metabolic diseases (DM and obesity) and DM-related traits (insulin resistance and &#x3b2;-cell function). After adjustment of covariates, such as age, alcohol consumption, smoking status, educational level, and daily energy intake, urinary Zn, Ni, Tl, and U levels were associated with the prevalence of DM and homeostatic model assessment (HOMA) for insulin resistance (IR) in the postmenopausal women. In the whole mixture model, however, no significant association was observed for the prevalence of DM. Urinary levels of Zn were negatively associated with HOMA of &#x3b2;-cell function (HOMA-&#x3b2;), positively correlated with HbA1c levels, HOMA-IR, and prevalent DM. In addition, urinary Zn, Co, Tl, and Cs were positively associated with obesity (body mass index &#x2265;25&#xa0;kg/m2). The present observation shows that several individual elements and their mixtures may be associated with the prevalence of DM, IR, or obesity.

Humans↗
PubMed2025

Decreased intestinal abundance of Akkermansia muciniphila is associated with metabolic disorders among people living with HIV.

BACKGROUND: Previous studies have shown changes in gut microbiota after human immunodeficiency virus (HIV) infection, but there is limited research linking the gut microbiota of people living with HIV (PLWHIV) to metabolic diseases. METHODS: A total of 103 PLWHIV were followed for 48&#x2009;weeks of anti-retroviral therapy (ART), with demographic and clinical data collected. Gut microbiome analysis was conducted using metagenomic sequencing of fecal samples from 12 individuals. Nonalcoholic fatty liver disease (NAFLD) was diagnosed based on controlled attenuation parameter (CAP) values of 238&#x2009;dB/m from liver fibro-scans. Participants were divided based on the presence of metabolic disorders, including NAFLD, overweight, and hyperlipidemia. Akkermansia abundance in stool samples was measured using RT-qPCR, and Pearson correlation and logistic regression were applied for analysis. RESULTS: Metagenomic sequencing revealed a significant decline in gut Akkermansia abundance in PLWHIV with NAFLD. STAMP analysis of public datasets confirmed this decline after HIV infection, while KEGG pathway analysis identified enrichment of metabolism-related genes. A prospective cohort study with 103 PLWHIV followed for 48&#x2009;weeks validated these findings. Akkermansia abundance was significantly lower in participants with NAFLD, overweight, and hyperlipidemia at baseline, and it emerged as an independent predictor of NAFLD and overweight. Negative correlations were observed between Akkermansia abundance and both CAP values and body mass index (BMI) at baseline and at week 48. At the 48-week follow-up, Akkermansia remained a predictive marker for NAFLD. CONCLUSIONS: Akkermansia abundance was reduced in PLWHIV with metabolic disorders and served as a predictive biomarker for NAFLD progression over 48&#x2009;weeks of ART.

Humans↗
PubMed2026

Proteomics profiling of serum and liver in GSD Ia and Ib patients: insights into complication mechanisms and circulation biomarkers.

BACKGROUND: Glycogen Storage Disease (GSD) Types Ia and Ib are rare metabolic diseases caused by gene variants in G6PC1 and SLC37A4, respectively. Although life-threatening fasting hypoglycemia can be controlled by a strict diet, patients often suffer from multiple metabolic abnormalities and severe long-term complications. However, the underlying mechanisms remain incompletely understood, and there is a lack of effective monitoring biomarkers. Therefore, the aims of this study are to investigate the pathological mechanisms of the disease and disease complications in GSD I and identify potential protein biomarkers. METHODS: Comprehensive untargeted proteomics was performed on 18 GSD Ia and 8 GSD Ib sera samples from patients with 21 matched control sera, complemented by liver 3 GSD Ia samples and 1 GSD Ib sample from patient liver tissues, compared to 10 donor liver samples. RESULTS: We identified 415 proteins in total. Significantly changed (FDR&#x2009;<&#x2009;0.05) were observed in 158 (38%) proteins for GSD Ia vs Control, 116 (28%) for GSD Ib vs. Control, and 151 (36%) for GSD Ia vs. Ib. Pathway analysis revealed distinct alterations in serum/plasma, with 58, 32, and 29 significantly changed biological processes (FDR&#x2009;<&#x2009;0.05) in these three comparisons, respectively. The coagulation pathway was the most significantly changed one in the GSD Ia patients. Immune response-associated proteins, especially immunoglobulins, were increased in GSD Ib specifically. Proteins related to liver injury, cholesterol, and amyloidosis were altered in two subtypes, though more pronounced in GSD Ia. Potential biomarkers with significant alterations both in the circulation and in the liver tissue were identified specifically for monitoring GSD I subtypes and prognosing liver deterioration, namely APOC1 and CD5L to distinguish between GSD Ia and Ib and ALDOB for the presence of hepatocellular carcinoma (HCC) in GSD Ia patients. CONCLUSIONS: These findings provide new insights into the differences between the two GSD I subtypes and the pathogenesis of GSD I-related complications, as well as highlighting the potential of protein circulating biomarkers for monitoring complication progression in GSD I and assessing HCC risk in GSD Ia patients.

Humans↗
PubMed2026

Clinical and biochemical footprints of inherited disorders of autophagy.

Autophagy is an evolutionarily conserved lysosomal recycling system that integrates nutrient sensing, organelle quality control, proteostasis, cellular stress responses and metabolic adaptation. Autophagy is particularly relevant for post-mitotic tissue such as neurons, skin, and immune cells. Monogenic disorders disrupting autophagy or closely coupled endolysosomal trafficking pathways have recently emerged as a recognizable group of inherited metabolic diseases. These conditions are individually rare inborn errors of metabolism and collectively important because they bridge neurodevelopmental, neuromuscular and neurodegenerative disorders, including hereditary forms of Parkinson's disease, spastic paraplegias and neurodegeneration with brain iron accumulation. Multisystem involvement is common but variable. The prototypic disorder is EPG5-related Vici syndrome, in which defective autophagosome-lysosome fusion causes severe neurodevelopmental and multisystem disease. Other disorders may affect any step of the pathway, from phosphatidylinositol 3-phosphate effector biology and ATG conjugation/lipidation to autophagosome maturation, ATG9 trafficking, HOPS/CORVET-related vesicle trafficking (including VPS16 and VPS33A), autophagosome-lysosome fusion, autolysosome reformation and lysosome-mTOR signaling. Clinically, affected individuals commonly present with global developmental delay and/or intellectual disability, epilepsy, movement disorders including dystonia, parkinsonism, ataxia and spasticity, and both neuropathic and myopathic neuromuscular manifestations. A biphasic course with progressive neurodegeneration and variable multisystem (including ocular, cardiac, immunological, cutaneous and growth) involvement are important clinical clues. Diagnosis relies on careful phenotyping, brain MRI, targeted metabolic exclusion of mimics, genomic sequencing and functional assays in patient-derived cells as required. Supportive multidisciplinary management is essential. No disease-modifying therapy is currently established in humans, but pathway-based cellular assays, model systems and small-molecule or gene-replacement strategies are creating a rational therapeutic pipeline. Importantly, IEMbase dyadic nomenclature with system-level clinical annotations provides a standardized framework for quantifying shared phenotypic signatures across these ultra-rare conditions. This review summarizes pathobiochemistry, genetics, clinical presentation, diagnosis and treatment prospects for inherited disorders of autophagy.

Autophagosome↗
PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans↗
PubMed2024

Estimating the sensitivity of genomic newborn screening for treatable inherited metabolic disorders.

PURPOSE: Over 30 research groups and companies are exploring newborn screening using genomic sequencing (NBSeq), but the sensitivity of this approach is not well understood. METHODS: We identified individuals with treatable inherited metabolic disorders (IMDs) and ascertained the proportion whose DNA analysis revealed explanatory deleterious variants (EDVs). We examined variables associated with EDV detection and estimated the sensitivity of DNA-first NBSeq. We further predicted the annual rate of true-positive and false-negative NBSeq results in the United States for several conditions on the Recommended Uniform Screening Panel. RESULTS: We identified 635 individuals with 80 unique IMDs. In univariate analyses, Black race (OR&#xa0;= 0.37, 95% CI: 0.16-0.89, P&#xa0;= .02) and public insurance (OR&#xa0;= 0.60, 95% CI: 0.39-0.91, P&#xa0;= .02) were less likely to be associated with finding EDVs. Had all individuals been screened with NBSeq, the sensitivity would have been 80.3%. We estimated that between 0 and 649.9 cases of Recommended Uniform Screening Panel IMDs would be missed annually by NBSeq in the United States. CONCLUSION: The overall sensitivity of NBSeq for treatable IMDs is estimated at 80.3%. That sensitivity will likely be lower for Black infants and those who are on public insurance.

Humans↗