Targeted metabolomics kit-based assays are widely used for quantitative metabolic profiling in clinical research. However, they are primarily validated for conventional matrices such as plasma and serum. Their direct application to dried blood spots (DBS) cannot be assumed and requires specific optimization due to intrinsic matrix-specific differences. This study aims to optimize the TMIC MTX MEGA assay for DBS analysis and matrix comparison. Validation was then conducted using paired longitudinal DBS and serum samples from 11 participants in a clinical study undergoing cardiac rehabilitation. A total of 323 compounds were quantitatively measured in DBS and 496 in serum. Principal component analysis revealed matrix-driven separation, highlighting clear distinctions of plasma/serum from DBS and confirming intrinsic matrix differences. Despite global differences, longitudinal trends across metabolite classes and at individual metabolite levels were largely concordant between DBS and serum. Class-specific differences were observed, particularly among lipid species and metabolites influenced by intracellular contributions, consistent with known biological factors. Although absolute concentrations differed for several metabolites, relative temporal changes were preserved. This proof-of-concept study demonstrates the feasibility of applying targeted metabolomics kit-based assays to DBS following workflow optimization. Overall, the optimized DBS workflow shows promise for longitudinal metabolic profiling in clinical contexts. These preliminary findings support further evaluation of DBS as a minimally invasive sampling alternative for targeted metabolomics applications in larger cohorts.

Sodium-glucose co-transporter 2 inhibitors (SGLT2i), when combined with metformin (COMBI), offer multi-organ protective effects in patients with type 2 diabetes (T2D), particularly those at high risk of cardiovascular or renal complications. However, the underlying molecular mechanisms remain poorly understood. We profiled 303 targeted serum metabolites in 1494 participants of the KORA study, including T2D patients treated with COMBI therapy, metformin monotherapy, or no glucose-lowering medication. Additionally, metabolomic profiling was quantified on seven tissues (plasma, liver, adrenal glands, adipose tissue, testis, lung, and cerebellum), and related hepatic transcripts were evaluated in 40 mice. Multivariable linear regression analyses, adjusted for age, sex, BMI, lifestyle, glycemic, and cardiovascular risk factors, were applied to human data; tissue-specific regression analyses were conducted for murine samples. Identified metabolites were further investigated using biochemical pathway analyses and literature review. COMBI therapy was associated with significant changes in metabolite profiles. In humans, 10 metabolites were significantly altered compared to metformin monotherapy. In mice, 82 altered metabolites were identified in plasma, 52 in liver, 30 in adrenal glands, 12 in adipose tissue, seven in testis, seven in lung, and six in cerebellum. COMBI therapy lowered threonine concentrations in both human serum and murine plasma but raised threonine, glycine, and urea cycle metabolites (citrulline, asymmetric dimethyl arginine (ADMA), and ornithine) in murine liver. This was accompanied by enhanced hepatic expression of Slc38a2, a threonine transporter gene. In humans, urea cycle metabolites correlated strongly with the fibrosis-4 index, a marker of liver fibrosis. Additionally, COMBI therapy elevated ketone body markers, such as hydroxybutyrylcarnitine, across murine liver, plasma, adrenal glands, adipose tissue, and testis. COMBI therapy modulates amino acid metabolism, the urea cycle, and ketone body production, suggesting potential mechanisms underlying its protective effects against liver fibrosis and male subfertility. These findings provide novel insights into the systemic metabolic actions of COMBI therapy and highlight its translational potential to improve clinical outcomes in T2D patients.

The mitochondrial selenoenzyme thioredoxin reductase 2 (TXNRD2) plays a critical role in redox homeostasis and reactive oxygen species (ROS) scavenging. While heart-specific deletion of Txnrd2 in mice resulted in cardiac dysfunction, TXNRD2 function in skeletal muscle, the major component of lean body mass, remains unclear. In human GWAS the TXNRD2 locus is associated with total lean mass. Here, we show that Txnrd2 muscle-specific knockout (mTKO) induces a lean phenotype characterized by muscle atrophy and diminished adipose tissues. mTKO mice were resistant to weight gain on standard and high-fat diet. Whole body glucose clearance was increased, and ATP levels in muscle were decreased, suggesting impaired mitochondrial energy production. Transcriptomic and metabolomic analyses revealed alterations in one-carbon metabolism and related pathways. Despite elevated glutathione levels, changes in key factors of cellular detoxification were consistent with compromised antioxidant defence system. In sum, we unravel that Txnrd2 deficiency in skeletal muscle rewires whole-body energy metabolism through mitochondrial dysfunction and impaired redox capacity.

Introduction We comprehensively investigated whether serum acylcarnitine levels are associated with and predict the decline of glomerular filtration rate (GFR) in type 2 diabetes.Research design and methods Two cohorts of patients with type 2 diabetes were investigated: a subset of the aggregate Gargano Mortality Study (aGMS, n=575; 9 years of median follow-up; mean age=60.9±9.8; mean diabetes duration=11.6±9.3) as a discovery set from Italy. A sample from the Joslin Kidney Study (JKS, n=252; 10 years of median follow-up; mean age=57.8±5.6; mean diabetes duration=14.2±7.6) was used as an independent validation set with different environmental and ethnic background for some associated metabolites in the aGMS.Main outcome estimated GFR (eGFR) change over time (mL/min/1.73 m2/year).Results Eleven out of the 40 acylcarnitines (by the AbsoluteIDQTM p180 Kit, BIOCRATES) were significantly associated with the rate of eGFR decline after Bonferroni correction. All 11 molecules were internally validated (p<0.05). Most of these associations survived the adjustment for several confounders, including age, sex, smoking habit, body mass index, glycated hemoglobin, disease duration, albumin excretion rate, triglycerides, low-density lipoprotein and statins treatment (p<0.05). Tiglylcarnitine and methylglutarylcarnitine, but not tetradecenoylcarnitine and hexadecenoylcarnitine, were also associated with eGFR decline in the JKS (p<0.05). Using multivariable least absolute shrinkage and selection operator regression analysis, methylglutarylcarnitine, hydroxyvalerylcarnitine, hexenoylcarnitine, decadienylcarnitine, dodecanedioylcarnitine, tetradecadienylcarnitine were independently associated with kidney function decline. The pairwise correlation among these ranged from −0.02 to 0.55. An acylcarnitine score comprising these six molecules improved discrimination (p<0.01) and reclassification (p<0.001) of two clinical prediction models of GFR decline in diabetes.Conclusions In patients with type 2 diabetes, four short, three medium and four long-chain acylcarnitines are associated with the rate of kidney function decline. Adding the acylcarnitine score to clinical prediction models improves the identification of individuals who are at greater risk of progression to kidney failure.

Objective This study aimed to identify metabolites characterizing the progression from normal glucose metabolism (NORM) to prediabetes (PreT2D) and type 2 diabetes (T2D), focusing on stage-specific metabolic shifts (early: NORM to PreT2D; late: PreT2D to T2D) and mechanistic relevance. Research Design and Methods We analyzed 8,240 observations from the KORA cohort, profiling 104 targeted and 312 non-targeted metabolites across three time points: baseline (S4) and follow-ups (F4 and FF4) spanning 14 years. Trajectory analyses of 1,050 individuals identified 211 incident PreT2D and 112 incident T2D cases. Linear mixed-effects models (basic: adjusted for age, sex, BMI, lifestyle; sensitivity: additionally adjusted for glycemic factors like fasting glucose, and cardiovascular factors such as systolic blood pressure (BP) were used to evaluate metabolic differences across glycemic states. Mediation and Mendelian randomization (MR) analyses examined mechanistic and causal relationships. Results We identified 140 Bonferroni-significant metabolites (45 targeted, 109 non-targeted, 14 overlapping), including 68 early-stage metabolites (significant in PreT2D/T2D vs. NORM), primarily energy metabolism markers such as fatty acid oxidation metabolites (e.g., 37 lipids) and TCA cycle metabolites (e.g., citrate). Twenty late-stage metabolites (significant in T2D vs. PreT2D/NORM) included amino acids like BCAAs and γ-glutamyl derivatives. Fewer significant associations were observed in incident cases. Sensitivity models validated 50% of early-stage but not late-stage metabolites. Fasting glucose mediated 35.1% of the γ-glutamyl-valine-T2D association, while MR analysis found no causal roles for C2, BCAAs, or γ-glutamyl-valine. Conclusions Energy metabolism shifts occur early, while amino acid alterations emerge later stages. These stage-specific signatures may guide diabetes prevention strategies.

RNA binding proteins have multiple diverse cellular functions and are often mis-regulated in disease. Despite their many cellular functions and implications in disease, very little is known about their physiological functions. Here we describe a novel zebrafish knockout model of the RNA binding proteins Hnrnpa1 and Hnrnpa3. Loss of Hnrnpa3 in zebrafish has no obvious morphological phenotype. Similarly, single mutants of the duplicated zebrafish hnrnpa1 genes, hnrnpa1a and hnrnpa1b, have no discernible phenotype, whereas the hnrnpa1a; hnrnpa1b double mutants are embryonic lethal. They display muscle, vascular and developmental defects with a reduced volume of the yolk extension. Metabolic profiling revealed severe changes in lipid metabolism in the hnrnpa1a; hnrnpa1b double mutants. Our analysis identified the involvement of Hnrnpa1 in many cellular pathways including the regulation of lipid metabolism and opens the door for future therapeutic studies in HNRNPA-associated diseases.

Background: Endometriosis, a benign gynaecological disease, includes three distinct entities: ovarian, peritoneal, and deep endometriosis. It affects up to 10% of reproductive age women and is associated with severe pain and infertility. Present diagnosis requires laparoscopy; thus non-invasive diagnostic options are needed as replacement or triage tests. So far, none of the published metabolite biomarker candidates have been validated in an independent population, none of the studies have focused on peritoneal endometriosis, and no models combining metabolites and proteins have been reported. Methods: This study included 513 participants, 316 with different types of endometriosis and 197 controls in the discovery and validation phase. 163 metabolites were measured in plasma by LC-MS/MS. TGFBI was measured by ELISA. Logistic regression was used to develop classification models. Findings: Five models, including two metabolite ratios and TGFBI, predicted peritoneal endometriosis with an AUC of 0·889 to 0·914 in the discovery phase and an AUC of 0·867 to 0·888 in the validation phase. The validated model with a ratio of lysoPC a C16:0/Hexoses, lysoPC a C18:2/PC aa C38:3, and TGFBI, met the criteria for a rule out triage test, while three out of the five models met the criteria for a rule in triage test. Interpretation: The validated models show excellent characteristics for diagnosing peritoneal endometriosis and fulfil the requirements for translation into clinical application if successfully validated in international multicentre studies.

Context The role of inflammation in shaping death risk in diabetes is still unclear. Objective To study whether inflammation is associated with and helps predict mortality risk in patients with type 2 diabetes. To explore the intertwined link between inflammation and tryptophan metabolism on death risk. Methods There were 2 prospective cohorts: the aggregate Gargano Mortality Study (1731 individuals; 872 all-cause deaths) as the discovery sample, and the Foggia Mortality Study (490 individuals; 256 deaths) as validation sample. Twenty-seven inflammatory markers were measured. Causal mediation analysis and in vitro studies were carried out to explore the link between inflammatory markers and the kynurenine to tryptophan ratio (KTR) in shaping mortality risk. Results Using multivariable stepwise Cox regression analysis, interleukin (IL)-4, IL-6, IL-8, IL-13, RANTES, and interferon gamma-induced protein-10 (IP-10) were independently associated with death. An inflammation score (I score) comprising these 6 molecules is strongly associated with death in both the discovery and the validation cohorts HR (95% CI) 2.13 (1.91-2.37) and 2.20 (1.79-2.72), respectively. The I score improved discrimination and reclassification measures (all P < .01) of 2 mortality prediction models based on clinical variables. The causal mediation analysis showed that 28% of the KTR effect on mortality was mediated by IP-10. Studies in cultured endothelial cells showed that 5-methoxy-tryptophan, an anti-inflammatory metabolite derived from tryptophan, reduces the expression of IP-10, thus providing a functional basis for the observed causal mediation. Conclusion Adding the I score to clinical prediction models may help identify individuals who are at greater risk of death. Deeply addressing the intertwined relationship between low-grade inflammation and imbalanced tryptophan metabolism in shaping mortality risk may help discover new therapies targeting patients characterized by these abnormalities.

ABCB5 is a member of the ATP-binding cassette transporter superfamily that is expressed as a full transporter (ABCB5FL) and half transporter (ABCB5β). The ABCB5FL transporter mediates low-level multidrug resistance in cancer and is normally expressed in the prostate and testis, while ABCB5β has been found to be a marker of melanoma and limbal stem cells and is expressed in pigmented cells. To explore ABCB5's role in normal physiology, we generated Abcb5-deficient C57BL/6J mice by the deletion of Abcb5 exon 2, knocking out both forms of ABCB5, which were completely phenotyped. The mice were fertile and demonstrated altered bioenergetics and fat metabolism, along with alterations in their blood composition, including anisocytosis and decreased white blood cells and platelet counts. This study uncovers further avenues of investigation into the role of Abcb5 in intermediary metabolism, particularly in relation to atherogenesis.

OBJECTIVE:Villus growth in the small bowel by Glucagon-like peptide-2 (GLP-2) pharmacotherapy improves intestinal absorption capacity and is now used clinically for the treatment of short bowel syndrome and intestinal failure occurring after extensive intestinal resection. Another recently acknowledged effect of GLP-2 treatment is the inhibition of gallbladder motility and increased gallbladder refilling. However, the impact of these two GLP-2-characteristic effects on bile acid metabolism in health and after intestinal resection is not understood. METHODS:Mice were injected with the GLP-2-analogue teduglutide or vehicle. We combined the selenium-75-homocholic acid taurine (SeHCAT) assay with novel spatial imaging in healthy mice and after ileocecal resection (ICR mice) and associated the results with clinical stage targeted bile acid metabolomics as well as gene expression analyses. RESULTS:ICR mice had virtual complete intestinal loss of secondary bile acids, and an increased ratio of 12α-hydroxylated vs. non-12α-hydroxylated bile acids, which was attenuated by teduglutide. Teduglutide promoted SeHCAT retention in healthy and in ICR mice. Acute concentration of the SeHCAT-signal into the hepatobiliary system was observed. Teduglutide induced significant repression of hepatic cyp8b1 expression, likely by induction of MAF BZIP Transcription Factor G. CONCLUSIONS:The data suggest that GLP-2-pharmacotherapy in mice significantly slows bile acid circulation primarily via hepatic Farnesoid X receptor-signaling.

Introduction and Objective: The role that circulating acylcarnitines exert on renal failure in individuals with type 2 diabetes is still vague. Therefore, we comprehensively studied the association between 40 acylcarnitines and the decline of glomerular filtration rate (GFR) in type 2 diabetes Methods: We traced the decline of eGFR in 575 patients with type 2 diabetes from the aggregate Gargano Mortality Study and measured 40 acylcarnitines by targeted metabolomics. Results: The annual eGFR change (mL/min/1.73 m2) was 1.32 (-2.20, -0.60). Eleven acylcarnitines were associated with eGFR decline adjusting for multiple comparisons (P value threshold = 1.2E-3, 0.05/40). Three short-chain C3:1, C5:1, C5-OH (C3-DC-M), 2 medium-chain C10:2, C12-DC (the only inversely associated) and 2 long-chain C14:2, and C16:2-OH acylcarnitines] remained associated in a model including sex, age at recruitment, smoking habit, BMI, HbA1c, diabetes duration, eGFR, and ongoing treatments at baseline (P from 0.001 to 0.03). All 7 associations were internally validated by subgroup analyses (created using sex or median values ​​of age at recruitment, BMI, HbA1c, duration of the disease) in which no heterogeneity was observed. After a forward-backward stepwise analysis in the fully adjusted model that included all 7 independently associated acylcarnitines, C5-OH (C3-DC-M) remained significantly (P = 4.4E-5) linked to the decline of eGFR and captured the information of all the other 6 markers. Conclusion: Several acylcarnitines, are independently associated with eGFR decline, suggesting that their dysregulation affects renal failure in type 2 diabetes. Further work is currently underway to validate our associations in an independent sample and study whether the more strongly associated acylcarnitines improve the prediction of renal failure provided by clinical models, thus paving the way to a precision medicine approach aimed at preventing kidney failure in patients most at risk. C. Menzaghi: None. M. Mastroianno: None. C. Prehn: None. L. Salvemini: None. G. Fini: None. J. Adamski: None. S. de Cosmo: Speaker's Bureau; Abbott Diagnostics, Lilly Diabetes, Boehringer-Ingelheim. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk, MSD Life Science Foundation. Advisory Panel; Sanofi. Speaker's Bureau; Sanofi, Daiichi Sankyo, AstraZeneca, Bayer Pharmaceuticals, Inc. V. Trischitta: None. European Union - Next Generation EU - NRRP M6C2 - Investment 2.1 Enhancement and strengthening of biomedical research in the NHS (PNRR-MAD-2022-12375970)

Despite recent progress in the diagnosis and treatment of advanced cancers, the overall patient treatment outcome did not substantially improve over the last years. Therefore, developing novel therapies, which may also work synergistically in combination with the conventional therapies is crucial. One promising new therapeutic approach is bacterium-mediated cancer therapy. In the current work, we describe the influence of the gut microbiome and intranasal E. coli Nissle applications on the metabolism in cancer tissues of 4T1 syngeneic tumor bearing mice. Here we found that after gut microbiome depletion and/or E. coli Nissle treatment the ratios of ADMA/Arginine, Putrescine/Ornithine and Kynurenine/Tryptophan as well as the total concentration of Carnosine, Kynurenine and H1 (synonymus for all sugars detectable) are significantly altered in tumor tissues of as the result of treatment. In conclusion, our current data show that E. coli Nissle bacteria facilitating metabolic modulation of tumors, a finding could be important for improved cancer therapy in patients.

Longitudinal multi-view omics data offer unique insights into the temporal dynamics of individual-level physiology, which provides opportunities to advance personalized healthcare. However, the common occurrence of incomplete views makes extrapolation tasks difficult, and there is a lack of tailored methods for this critical issue. Here, we introduce LEOPARD, an innovative approach specifically designed to complete missing views in multi-timepoint omics data. By disentangling longitudinal omics data into content and temporal representations, LEOPARD transfers the temporal knowledge to the omics-specific content, thereby completing missing views. The effectiveness of LEOPARD is validated on four real-world omics datasets constructed with data from the MGH COVID study and the KORA cohort, spanning periods from 3 days to 14 years. Compared to conventional imputation methods, such as missForest, PMM, GLMM, and cGAN, LEOPARD yields the most robust results across the benchmark datasets. LEOPARD-imputed data also achieve the highest agreement with observed data in our analyses for age-associated metabolites detection, estimated glomerular filtration rate-associated proteins identification, and chronic kidney disease prediction. Our work takes the first step toward a generalized treatment of missing views in longitudinal omics data, enabling comprehensive exploration of temporal dynamics and providing valuable insights into personalized healthcare.

BACKGROUND AND AIMS:Fasting hypoglycemia has clinical implications for children with growth hormone (GH)-insensitivity syndrome. This study investigates the pathophysiology of juvenile hypoglycemia in a large animal model for GH receptor (GHR) deficiency (the GHR-KO pig) and elucidates mechanisms underlying the transition to normoglycemia in adulthood. METHODS:Insulin sensitivity was assessed in juvenile and adult GHR-KO pigs and wild-type (WT) controls via hyperinsulinemic-euglycemic clamp (HEC) tests. Glucose turnover was measured using D-[6,6-2H2] glucose and 2H2O. Clinical chemical and targeted metabolomics parameters in blood serum were correlated with qPCR and western blot analyses of liver and adipose tissue. RESULTS:GHR-KO pigs showed increased insulin sensitivity (p = 0.0019), especially at young age (M-value +34% vs. WT), insignificantly reduced insulin levels, and reduced endogenous glucose production (p = 0.0007), leading to fasting hypoglycemia with depleted liver glycogen, elevated β-hydroxybutyrate, but no increase in NEFA levels. Low hormone-sensitive lipase phosphorylation in adipose tissue suggested impaired lipolysis in young GHR-KO pigs. Metabolomics indicated enhanced fatty acid beta-oxidation and use of glucogenic amino acids, likely serving as compensatory pathways to maintain energy homeostasis. In adulthood, insulin sensitivity remained elevated but less pronounced (M-value +20%), while insulin levels were significantly reduced, enabling normoglycemia and improved NEFA availability. Increased fat mass, but not sex hormones, appeared key to this metabolic transition, as early castration had no effect. CONCLUSIONS:Juvenile hypoglycemia in GH insensitivity results from excessive insulin sensitivity, reduced glucose production, and impaired lipolysis. Normoglycemia in adulthood emerges through increased adiposity and moderated insulin sensitivity, independently of sex hormones. These findings elucidate the age-dependent metabolic adaptations in GH insensitivity.

CONTEXT:The independent role of glomerular filtration rate (GFR) decline in shaping the risk of mortality in people with type 2 diabetes has only been partially addressed. OBJECTIVE:The objective of the study was 2-fold: (1) to investigate the association between all-cause mortality and eGFR changes over time; (2) to understand whether renal dysfunction mediates the effect of tryptophan metabolism on death risk. METHODS:Prospective study with an average follow-up of 14.8 years at a research hospital. The aggregate Gargano Mortality Study included 962 patients with type 2 diabetes who had at least 3 eGFR recordings and at least 1.5 years of follow-up. This was an observational study, with no interventions. Rate of all-cause mortality was measured. RESULTS:Age- and sex-adjusted annual incident rate of mortality was 2.75 events per 100 person-years. The median annual rate of decline of eGFR was 1.3 mL/min per 1.73 m2 per year (range -3.7; 7.8). The decline of kidney function was strongly and independently associated with the risk of death. Serum kynurenine to tryptophan ratio (KTR) was associated with both eGFR decline and all-cause mortality. Causal mediation analysis showed that 24.3% of the association between KTR and mortality was mediated by eGFR decline. CONCLUSION:In patients with type 2 diabetes, eGFR decline is independently associated with the risk of all-cause mortality and mediates a significant proportion of the association between tryptophan metabolism and death.

Previous case–control studies have reported aberrations of the gut microbiota in individuals with prediabetes. The primary objective of the present study was to explore the dynamics of the gut microbiota of individuals with prediabetes over 4 years with a secondary aim of relating microbiota dynamics to temporal changes of metabolic phenotypes. The study included 486 European patients with prediabetes. Gut microbiota profiling was conducted using shotgun metagenomic sequencing and the same bioinformatics pipelines at study baseline and after 4 years. The same phenotyping protocols and core laboratory analyses were applied at the two timepoints. Phenotyping included anthropometrics and measurement of fasting plasma glucose and insulin levels, mean plasma glucose and insulin under an oral glucose tolerance test (OGTT), 2-h plasma glucose after an OGTT, oral glucose insulin sensitivity index, Matsuda insulin sensitivity index, body mass index, waist circumference, and systolic and diastolic blood pressure. Measures of the dynamics of bacterial microbiota were related to concomitant changes in markers of host metabolism. Over 4 years, significant declines in richness were observed in gut bacterial and viral species and microbial pathways accompanied by significant changes in the relative abundance and the genetic composition of multiple bacterial species. Additionally, bacterial-viral interactions diminished over time. Despite the overall reduction in bacterial richness and microbial pathway richness, 80 dominant core bacterial species and 78 core microbial pathways were identified at both timepoints in 99

This study investigates impaired awareness of hypoglycaemia (IAH), a complication of insulin therapy affecting 20–40% of individuals with type 1 diabetes. The exact pathophysiology is unclear, therefore we sought to identify metabolic signatures in IAH to elucidate potential pathophysiological pathways. Plasma samples from 578 individuals of the Dutch type 1 diabetes biomarker cohort, 67 with IAH and 108 without IAH (NAH) were analysed using the targeted metabolomics Biocrates AbsoluteIDQ p180 assay. Eleven metabolites were significantly associated with IAH. Genome-wide association studies of these 11 metabolites identified significant single nucleotide polymorphisms (SNPs) in C22:1-OH and phosphatidylcholine diacyl C36:6. After adjusting for the SNPs, 11 sphingomyelins and phosphatidylcholines were significantly higher in the IAH group in comparison to NAH. These metabolites are important components of the cell membrane and have been implicated to play a role in cell signalling in diabetes. These findings demonstrate the potential role of phosphatidylcholine and sphingomyelins in IAH.