Bidirectional modulation of TCA cycle metabolites and anaplerosis by metformin and its combination with SGLT2i.

BACKGROUND: Metformin and sodium-glucose-cotransporter-2 inhibitors (SGLT2i) are cornerstone therapies for managing hyperglycemia in diabetes. However, their detailed impacts on metabolic processes, particularly within the citric acid (TCA) cycle and its anaplerotic pathways, remain unclear. This study investigates the tissue-specific metabolic effects of metformin, both as a monotherapy and in combination with SGLT2i, on the TCA cycle and associated anaplerotic reactions in both mice and humans. METHODS: Metformin-specific metabolic changes were initially identified by comparing metformin-treated diabetic mice (MET) with vehicle-treated db/db mice (VG). These findings were then assessed in two human cohorts (KORA and QBB) and a longitudinal KORA study of metformin-naïve patients with Type 2 Diabetes (T2D). We also compared MET with db/db mice on combination therapy (SGLT2i + MET). Metabolic profiling analyzed 716 metabolites from plasma, liver, and kidney tissues post-treatment, using linear regression and Bonferroni correction for statistical analysis, complemented by pathway analyses to explore the pathophysiological implications. RESULTS: Metformin monotherapy significantly upregulated TCA cycle intermediates such as malate, fumarate, and α-ketoglutarate (α-KG) in plasma, and anaplerotic substrates including hepatic glutamate and renal 2-hydroxyglutarate (2-HG) in diabetic mice. Downregulated hepatic taurine was also observed. The addition of SGLT2i, however, reversed these effects, such as downregulating circulating malate and α-KG, and hepatic glutamate and renal 2-HG, but upregulated hepatic taurine. In human T2D patients on metformin therapy, significant systemic alterations in metabolites were observed, including increased malate but decreased citrulline. The bidirectional modulation of TCA cycle intermediates in mice influenced key anaplerotic pathways linked to glutaminolysis, tumorigenesis, immune regulation, and antioxidative responses. CONCLUSION: This study elucidates the specific metabolic consequences of metformin and SGLT2i on the TCA cycle, reflecting potential impacts on the immune system. Metformin shows promise for its anti-inflammatory properties, while the addition of SGLT2i may provide liver protection in conditions like metabolic dysfunction-associated steatotic liver disease (MASLD). These observations underscore the importance of personalized treatment strategies.

Metabolic effects of SGLT2i and metformin on 3-hydroxybutyric acid and lactate in db/db mice.

Combining a Sodium-Glucose-Cotransporter-2-inhibitor (SGLT2i) with metformin is recommended for managing hyperglycemia in patients with type 2 diabetes (T2D) who have cardio-renal complications. Our study aimed to investigate the metabolic effects of SGLT2i and metformin, both individually and synergistically. We treated leptin receptor-deficient (db/db) mice with these drugs for two weeks and conducted metabolite profiling, identifying 861 metabolites across kidney, liver, muscle, fat, and plasma. Using linear regression and mixed-effects models, we identified two SGLT2i-specific metabolites, X-12465 and 3-hydroxybutyric acid (3HBA), a ketone body, across all examined tissues. The levels of 3HBA were significantly higher under SGLT2i monotherapy compared to controls and were attenuated when combined with metformin. We observed similar modulatory effects on metabolites involved in protein catabolism (e.g., branched-chain amino acids) and gluconeogenesis. Moreover, combination therapy significantly raised pipecolate levels, which may enhance mTOR1 activity, while modulating GSK3, a common target of SGLT2i and 3HBA inhibition. The combination therapy also led to significant reductions in body weight and lactate levels, contrasted with monotherapies. Our findings advocate for the combined approach to better manage muscle loss, and the risks of DKA and lactic acidosis, presenting a more effective strategy for T2D treatment.

Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Moral distress among intensive care unit professions in the UK: a mixed-methods study.

OBJECTIVE: To assess the experience of moral distress among intensive care unit (ICU) professionals in the UK. DESIGN: Mixed methods: validated quantitative measure of moral distress followed by purposive sample of respondents who underwent semistructured interviews. SETTING: Four ICUs of varying sizes and specialty facilities. PARTICIPANTS: Healthcare professionals working in ICU. RESULTS: 227 questionnaires were returned and 15 interviews performed. Moral distress occurred across all ICUs and professional demographics. It was most commonly related to providing care perceived as futile or against the patient's wishes/interests, followed by resource constraints compromising care. Moral distress score was independently influenced by profession (p=0.02) (nurses 117.0 vs doctors 78.0). A lack of agency was central to moral distress and its negative experience could lead to withdrawal from engaging with patients/families. One-third indicated their intention to leave their current post due to moral distress and this was greater among nurses than doctors (37.0% vs 15.0%). Moral distress was independently associated with an intention to leave their current post (p<0.0001) and a previous post (p=0.001). Participants described a range of individualised coping strategies tailored to the situations faced. The most common and highly valued strategies were informal and relied on working within a supportive environment along with a close-knit team, although participants acknowledged there was a role for structured and formalised intervention. CONCLUSIONS: Moral distress is widespread among UK ICU professionals and can have an important negative impact on patient care, professional wellbeing and staff retention, a particularly concerning finding as this study was performed prior to the COVID-19 pandemic. Moral distress due to resource-related issues is more severe than comparable studies in North America. Interventions to support professionals should recognise the individualistic nature of coping with moral distress. The value of close-knit teams and supportive environments has implications for how intensive care services are organised.

Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse.

Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.

Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes.

Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolite biomarkers and the best set of predictors of CKD in the longitudinal, population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort by targeted metabolomics and machine learning approaches. Out of 125 targeted metabolites, sphingomyelin C18:1 and phosphatidylcholine diacyl C38:0 were identified as candidate metabolite biomarkers of incident CKD specifically in hyperglycemic individuals followed during 6.5 years. Sets of predictors for incident CKD developed from 125 metabolites and 14 clinical variables showed highly stable performances in all three machine learning approaches and outperformed the currently established clinical algorithm for CKD. The two metabolites in combination with five clinical variables were identified as the best set of predictors, and their predictive performance yielded a mean area value under the receiver operating characteristic curve of 0.857. The inclusion of metabolite variables in the clinical prediction of future CKD may thus improve the risk prediction in people with prediabetes and T2D. The metabolite link with hyperglycemia-related early kidney dysfunction warrants further investigation.

Investigation of Adiposity Measures and Operational Taxonomic unit (OTU) Data Transformation Procedures in Stool Samples from a German Cohort Study Using Machine Learning Algorithms.

The analysis of the gut microbiome with respect to health care prevention and diagnostic purposes is increasingly the focus of current research. We analyzed around 2000 stool samples from the KORA (Cooperative Health Research in the Region of Augsburg) cohort using high-throughput 16S rRNA gene amplicon sequencing representing a total microbial diversity of 2089 operational taxonomic units (OTUs). We evaluated the combination of three different components to assess the reflection of obesity related to microbiota profiles: (i) four prediction methods (i.e., partial least squares (PLS), support vector machine regression (SVMReg), random forest (RF), and M5Rules); (ii) five OTU data transformation approaches (i.e., no transformation, relative abundance without and with log-transformation, as well as centered and isometric log-ratio transformations); and (iii) predictions from nine measurements of obesity (i.e., body mass index, three measures of body shape, and five measures of body composition). Our results showed a substantial impact of all three components. The applications of SVMReg and PLS in combination with logarithmic data transformations resulted in considerably predictive models for waist circumference-related endpoints. These combinations were at best able to explain almost 40% of the variance in obesity measurements based on stool microbiota data (i.e., OTUs) only. A reduced loss in predictive performance was seen after sex-stratification in waist-height ratio compared to other waist-related measurements. Moreover, our analysis showed that the contribution of OTUs less prevalent and abundant is minor concerning the predictive power of our models.

Establishment, optimisation and quantitation of a bioluminescent murine infection model of visceral leishmaniasis for systematic vaccine screening.

Visceral leishmaniasis is an infectious parasitic disease caused by the protozoan parasites Leishmania donovani and Leishmania infantum. The drugs currently used to treat visceral leishmaniasis suffer from toxicity and the emergence of parasite resistance, and so a better solution would be the development of an effective subunit vaccine; however, no approved vaccine currently exists. The comparative testing of a large number of vaccine candidates requires a quantitative and reproducible experimental murine infection model, but the parameters that influence infection pathology have not been systematically determined. To address this, we have established an infection model using a transgenic luciferase-expressing L. donovani parasite and longitudinally quantified the infections using in vivo bioluminescent imaging within individual mice. We examined the effects of varying the infection route, the site of adjuvant formulation administration, and standardised the parasite preparation and dose. We observed that the increase in parasite load within the liver during the first few weeks of infection was directly proportional to the parasite number in the initial inoculum. Finally, we show that immunity can be induced in pre-exposed animals that have resolved an initial infection. This murine infection model provides a platform for systematic subunit vaccine testing against visceral leishmaniasis.

The use of triclosan-coated sutures to prevent surgical site infections: a systematic review and meta-analysis of the literature.

INTRODUCTION AND OBJECTIVES: Surgical site infections (SSIs) represent a common and serious complication of all surgical interventions. Microorganisms are able to colonise sutures that are implanted in the skin, which is a causative factor of SSIs. Triclosan-coated sutures are antibacterial sutures aimed at reducing SSIs. Our objective is to update the existing literature by systematically reviewing available evidence to assess the effectiveness of triclosan-coated sutures in the prevention of SSIs. METHODS: A systematic review of EMBASE, MEDLINE, AMED (Allied and complementary medicine database) and CENTRAL was performed to identify full text randomised controlled trials (RCTs) on 31 May 2019. INTERVENTION: Triclosan-coated sutures versus non-triclosan-coated sutures. PRIMARY OUTCOME: Our primary outcome was the development of SSIs at 30 days postoperatively. A meta-analysis was performed using a fixed-effects model. RESULTS: Twenty-five RCTs were included involving 11 957 participants. Triclosan-coated sutures were used in 6008 participants and non triclosan-coated sutures were used in 5949. Triclosan-coated sutures significantly reduced the risk of SSIs at 30 days (relative risk 0.73, 95% CI 0.65 to 0.82). Further sensitivity analysis demonstrated that triclosan-coated sutures significantly reduced the risk of SSIs in both clean and contaminated surgery. CONCLUSION: Triclosan-coated sutures have been shown to significantly reduced the risk of SSIs when compared with standard sutures. This is in agreement with previous work in this area. This study represented the largest review to date in this area. This moderate quality evidence recommends the use of triclosan-coated sutures in order to reduce the risk of SSIs particularly in clean and contaminated surgical procedures. PROSPERO REGISTRATION NUMBER: CRD42014014856.

Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies.

Ageing, one of the largest risk factors for many complex diseases, is highly interconnected to metabolic processes. Investigating the changes in metabolite concentration during ageing among healthy individuals offers us unique insights to healthy ageing. We aim to identify ageing-associated metabolites that are independent from chronological age to deepen our understanding of the long-term changes in metabolites upon ageing. Sex-stratified longitudinal analyses were performed using fasting serum samples of 590 healthy KORA individuals (317 women and 273 men) who participated in both baseline (KORA S4) and seven-year follow-up (KORA F4) studies. Replication was conducted using serum samples of 386 healthy CARLA participants (195 women and 191 men) in both baseline (CARLA-0) and four-year follow-up (CARLA-1) studies. Generalized estimation equation models were performed on each metabolite to identify ageing-associated metabolites after adjusting for baseline chronological age, body mass index, physical activity, smoking status, alcohol intake and systolic blood pressure. Literature researches were conducted to understand their biochemical relevance. Out of 122 metabolites analysed, we identified and replicated five (C18, arginine, ornithine, serine and tyrosine) and four (arginine, ornithine, PC aa C36:3 and PC ae C40:5) significant metabolites in women and men respectively. Arginine decreased, while ornithine increased in both sexes. These metabolites are involved in several ageing processes: apoptosis, mitochondrial dysfunction, inflammation, lipid metabolism, autophagy and oxidative stress resistance. The study reveals several significant ageing-associated metabolite changes with two-time-point measurements on healthy individuals. Larger studies are required to confirm our findings.

Night Shift Work Affects Urine Metabolite Profiles of Nurses with Early Chronotype.

Night shift work can have a serious impact on health. Here, we assess whether and how night shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424 waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate <0.05) affected in nurses working in night shifts. One metabolite, acylcarnitine C10:2, was consistently identified with all three normalization methods. We further observed 11 and 4 metabolites significantly associated with night shift in early and late chronotype classes, respectively. Increased levels of medium- and long chain acylcarnitines indicate a strong impairment of the fatty acid oxidation. Our results show that night shift work influences acylcarnitines and BCAAs, particularly in nurses in the early chronotype class. Women with intermediate and late chronotypes appear to be less affected by night shift work.

Revealing Electron-Electron Interactions within Lewis Pairs in Chemical Systems.

The so-called "Lewis pair" is a ubiquitous phenomenon in chemistry and is often used as an intuitive construct to predict and rationalize chemical structure and behavior. Concepts from the very general Valence Shell Electron Pair Repulsion (VSEPR) model to the most esoteric reaction mechanism routinely rely on the notion that electrons tend to exist in pairs and that these pairs can be thought of as being localized to a particular region of space. It is precisely this localization that allows one to intuit how these pairs might behave, generally speaking, so that reasonable predictions may be made regarding molecular structure, intermolecular interactions, property trends, and reaction mechanisms, etc. Of course, it is rather unfortunate that the Lewis model is entirely qualitative and yields no information regarding how any specific electron pair is distributed. Here we demonstrate a novel electronic structure analysis technique that predicts and analyzes precise quantitative details about the relative and absolute distribution of individual electron pairs. This Single Electron Pair Distribution Analysis (SEPDA) reveals quantitative details about the distribution of the well-known Lewis pairs, such as how they are distributed in space and how their relative velocities change in various chemical contexts. We show that these distributions allow one to image the explicitly pairwise electronic behavior of bonds and lone pairs. We further demonstrate how this electronic behavior changes with several conditions to explore the nature of the covalent chemical bond, non-covalent interactions, bond formation, and exotic 3-center-2-electron species. It is shown that indications of the strength of bonded and non-bonded interactions may also be gleaned from such distributions and SEPDA can be used as a tool to differentiate between interaction types. We anticipate that SEPDA will be of broad utility in a wide variety of chemical contexts because it affords a very detailed, visual and intuitive analysis technique that is generally applicable.

Plasma and Serum Metabolite Association Networks: Comparability within and between Studies Using NMR and MS Profiling.

Blood is one of the most used biofluids in metabolomics studies, and the serum and plasma fractions are routinely used as a proxy for blood itself. Here we investigated the association networks of an array of 29 metabolites identified and quantified via NMR in the plasma and serum samples of two cohorts of ∼1000 healthy blood donors each. A second study of 377 individuals was used to extract plasma and serum samples from the same individual on which a set of 122 metabolites were detected and quantified using FIA-MS/MS. Four different inference algorithms (ARANCE, CLR, CORR, and PCLRC) were used to obtain consensus networks. The plasma and serum networks obtained from different studies showed different topological properties with the serum network being more connected than the plasma network. On a global level, metabolite association networks from plasma and serum fractions obtained from the same blood sample of healthy people show similar topologies, and at a local level, some differences arise like in the case of amino acids.

Impact of a multifaceted antimicrobial stewardship program: A front-line ownership driven quality improvement project in a large urban emergency department.

BACKGROUND: Antibiotic overuse has promoted growing rates of antimicrobial resistance and secondary antibiotic-associated infections such as Clostridium difficile (C. difficile). Antimicrobial stewardship programs (ASPs) are effective in reducing antimicrobial use in the inpatient setting; however, the unique environment of the emergency department (ED) lends itself to challenges for successful implementation. Front-line ownership (FLO) methodology has been shown to be a potentially effective strategy for the implementation of inpatient ASPs through an iterative multi-pronged approach driven by front-line providers. OBJECTIVE: To determine whether a FLO approach to antimicrobial stewardship in the ED can alter antimicrobial usage. METHODS: Interventions were driven by ED physicians and facilitated by Infectious Diseases Division physicians from the hospital's ASP using FLO principles. Measured end points included antibiotic usage in the ED as measured by defined daily doses, and rates of urine culture sent from the ED. RESULTS: There was a step-wise significant reduction in the use of azithromycin (p=0.006), ceftriaxone (p=0.045), ciprofloxacin (p=0.034), and moxifloxacin (p=0.008). There was also a significant reduction in rates of urine cultures (p<0.001) by 2.26 urine cultures per 100 ED patient visits. CONCLUSIONS: FLO offers a promising approach to successful implementation of an ASP in the ED. Future studies would be important to evaluate the generalizability of the FLO approach to ASP development in other EDs and to determine strategies to improve the sustainability of reductions in antimicrobial use.

Midterm Radiographic and Functional Outcomes of the Anterior Subcutaneous Internal Pelvic Fixator (INFIX) for Pelvic Ring Injuries.

OBJECTIVE: To describe our experience using the anterior internal pelvic fixator (INFIX) for treating pelvic ring injuries. DESIGN: Case Series. SETTING: Level 1 Trauma Center. PATIENTS: Eighty-three patients with pelvic ring injuries were treated with INFIX. Follow-up average was 35 months (range 12-80.33). INTERVENTION: Surgical treatment of pelvic ring injuries included reduction, appropriate posterior fixation, and INFIX placement. OUTCOME MEASUREMENTS: Reduction using the pelvic deformity index and pubic symphysis widening, Majeed functional scores, complications; infection, implant failure, heterotopic ossification (HO), nerve injury, and pain. RESULTS: All patients healed in an appropriate time frame (full weight bearing 12 weeks postoperation). The average pelvic deformity index reduction (injury = 0.0420 ± 0.0412, latest FU = 0.0254 ± 0.0243) was 39.58%. The average reduction of pubic symphysis injuries was 56.92%. The average Majeed score of patients at latest follow-up was 78.77 (range 47-100). Complications were 3 infections, 1 case of implant failure, 2 cases implantation too deep, 7 cases of lateral femoral cutaneous nerve irritation, and 3 cases of pain associated with the device. HO was seen in >50% of the patients, correlated with increased age (P < 0.007), injury severity score (P < 0.05) but only 1 case was symptomatic. CONCLUSIONS: The pelvic injuries had good functional and radiological outcomes with INFIX and the appropriate posterior fixation. The downside is removal requiring a second anesthetic, there is a learning curve, HO often occurs, the lateral femoral cutaneous nerve may get irritated which often resolves once the implants are removed. Surgery-specific implants need to be developed. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

INFIX versus plating for pelvic fractures with disruption of the symphysis pubis.

PURPOSE: The purpose of this study is to compare INFIX to plating in the treatment of unstable pelvic ring injuries with disruption of the symphysis. METHODS: Twenty-four patients treated with INFIX were compared to 28 patients fixed by plating. All patients had anterior and posterior fixation. Injuries were classified using the Young and Burgess and AO/OTA classification systems. Reductions of the pelvic ring were assessed using the pelvic deformity index (PDI) and symphyseal widening. Patients were contacted to get functional outcomes using the Majeed scoring system and complications were tabulated . RESULTS: INFIX was inferior to plating at reducing symphyseal widening (INFIX 10.72± 5.0 Plates 6.97 ± 3.39 P = 0.012) but similar in reducing the pelvic deformity index. (INFIX 0.0221± .015 Plates 0.0190 ± .0105 P = 0 .38). Majeed scores were similar 83.95 ± 15.2 (median 89, range 51-100) for INFIX and 77.67± 16.7 (median 79, range 54-100) for plating. Complications included infection (1 (4%) INFIX , 4 (14%) plates), improper hardware placement or failure (2 (8%) INFIX, 3 (11%) plates), and heterotopic ossification (11 (46%) INFIX, 16 (57.1%) plates). Infection in the plated patients was related to urological injury in 3/4 cases. CONCLUSIONS: Plating provides better reduction of the pubic symphysis and requires only one surgery. Outcomes scores were similar. INFIX may be preferable in obese patients, young women of childbearing age or those with urological injury.

Stability of targeted metabolite profiles of urine samples under different storage conditions.

INTRODUCTION: Few studies have investigated the influence of storage conditions on urine samples and none of them used targeted mass spectrometry (MS). OBJECTIVES: We investigated the stability of metabolite profiles in urine samples under different storage conditions using targeted metabolomics. METHODS: Pooled, fasting urine samples were collected and stored at -80 °C (biobank standard), -20 °C (freezer), 4 °C (fridge), ~9 °C (cool pack), and ~20 °C (room temperature) for 0, 2, 8 and 24 h. Metabolite concentrations were quantified with MS using the AbsoluteIDQ™ p150 assay. We used the Welch-Satterthwaite-test to compare the concentrations of each metabolite. Mixed effects linear regression was used to assess the influence of the interaction of storage time and temperature. RESULTS: The concentrations of 63 investigated metabolites were stable at -20 and 4 °C for up to 24 h when compared to samples immediately stored at -80 °C. When stored at ~9 °C for 24 h, few amino acids (Arg, Val and Leu/Ile) significantly decreased by 40% in concentration (P < 7.9E-04); for an additional three metabolites (Ser, Met, Hexose H1) when stored at ~20 °C reduced up to 60% in concentrations. The concentrations of four more metabolites (Glu, Phe, Pro, and Thr) were found to be significantly influenced when considering the interaction between exposure time and temperature. CONCLUSION: Our findings indicate that 78% of quantified metabolites were stable for all examined storage conditions. Particularly, some amino acid concentrations were sensitive to changes after prolonged storage at room temperature. Shipping or storing urine samples on cool packs or at room temperature for more than 8 h and multiple numbers of freeze and thaw cycles should be avoided.

Metformin Effect on Nontargeted Metabolite Profiles in Patients With Type 2 Diabetes and in Multiple Murine Tissues.

Metformin is the first-line oral medication to increase insulin sensitivity in patients with type 2 diabetes (T2D). Our aim was to investigate the pleiotropic effect of metformin using a nontargeted metabolomics approach. We analyzed 353 metabolites in fasting serum samples of the population-based human KORA (Cooperative Health Research in the Region of Augsburg) follow-up survey 4 cohort. To compare T2D patients treated with metformin (mt-T2D, n = 74) and those without antidiabetes medication (ndt-T2D, n = 115), we used multivariable linear regression models in a cross-sectional study. We applied a generalized estimating equation to confirm the initial findings in longitudinal samples of 683 KORA participants. In a translational approach, we used murine plasma, liver, skeletal muscle, and epididymal adipose tissue samples from metformin-treated db/db mice to further corroborate our findings from the human study. We identified two metabolites significantly (P < 1.42E-04) associated with metformin treatment. Citrulline showed lower relative concentrations and an unknown metabolite X-21365 showed higher relative concentrations in human serum when comparing mt-T2D with ndt-T2D. Citrulline was confirmed to be significantly (P < 2.96E-04) decreased at 7-year follow-up in patients who started metformin treatment. In mice, we validated significantly (P < 4.52E-07) lower citrulline values in plasma, skeletal muscle, and adipose tissue of metformin-treated animals but not in their liver. The lowered values of citrulline we observed by using a nontargeted approach most likely resulted from the pleiotropic effect of metformin on the interlocked urea and nitric oxide cycle. The translational data derived from multiple murine tissues corroborated and complemented the findings from the human cohort.