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The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.

Women with uncomplicated urinary tract infection (UTI) symptoms are commonly treated with empirical antibiotics, resulting in overuse of antibiotics, which promotes antimicrobial resistance. Available diagnostic tools are either not cost-effective or diagnostically sub-optimal. Here, we identified clinical and urinary immunological predictors for UTI diagnosis. We explored 17 clinical and 42 immunological potential predictors for bacterial culture among women with uncomplicated UTI symptoms using random forest or support vector machine coupled with recursive feature elimination. Urine cloudiness was the best performing clinical predictor to rule out (negative likelihood ratio [LR−] = 0.4) and rule in (LR+ = 2.6) UTI. Using a more discriminatory scale to assess cloudiness (turbidity) increased the accuracy of UTI prediction further (LR+ = 4.4). Urinary levels of MMP9, NGAL, CXCL8 and IL-1β together had a higher LR+ (6.1) and similar LR− (0.4), compared to cloudiness. Varying the bacterial count thresholds for urine culture positivity did not alter best clinical predictor selection, but did affect the number of immunological predictors required for reaching an optimal prediction. We conclude that urine cloudiness is particularly helpful in ruling out negative UTI cases. The identified urinary biomarkers could be used to develop a point of care test for UTI but require further validation.

Background Autism spectrum disorder (ASD) is still diagnosed through behavioral observation, due to a lack of laboratory biomarkers, which could greatly aid clinicians in providing earlier and more reliable diagnoses. Metabolomics on human biofluids provides a sensitive tool to identify metabolite profiles potentially usable as biomarkers for ASD. Initial metabolomic studies, analyzing urines and plasma of ASD and control individuals, suggested that autistic patients may share some metabolic abnormalities, despite several inconsistencies stemming from differences in technology, ethnicity, age range, and definition of “control” status. Methods ASD-specific urinary metabolomic patterns were explored at an early age in 30 ASD children and 30 matched controls (age range 2–7, M:F = 22:8) using hydrophilic interaction chromatography (HILIC)-UHPLC and mass spectrometry, a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway. Results Urinary metabolites displaying the largest differences between young ASD and control children belonged to the tryptophan and purine metabolic pathways. Also, vitamin B 6 , riboflavin, phenylalanine-tyrosine-tryptophan biosynthesis, pantothenate and CoA, and pyrimidine metabolism differed significantly. ASD children preferentially transform tryptophan into xanthurenic acid and quinolinic acid (two catabolites of the kynurenine pathway), at the expense of kynurenic acid and especially of melatonin. Also, the gut microbiome contributes to altered tryptophan metabolism, yielding increased levels of indolyl 3-acetic acid and indolyl lactate. Conclusions The metabolic pathways most distinctive of young Italian autistic children largely overlap with those found in rodent models of ASD following maternal immune activation or genetic manipulations. These results are consistent with the proposal of a purine-driven cell danger response, accompanied by overproduction of epileptogenic and excitotoxic quinolinic acid, large reductions in melatonin synthesis, and gut dysbiosis. These metabolic abnormalities could underlie several comorbidities frequently associated to ASD, such as seizures, sleep disorders, and gastrointestinal symptoms, and could contribute to autism severity. Their diagnostic sensitivity, disease-specificity, and interethnic variability will merit further investigation.

To investigate the associations of serum α-Klotho and β-Klotho levels with type 2 diabetes mellitus (T2DM) progression. We evaluated 106 healthy controls and 261 cases of T2DM with or without diabetic complications (range: 45–84years). Serum α-Klotho and β-Klotho levels were analyzed using enzyme-linked immunosorbent assays. Compared to the healthy controls, α-Klotho and β-Klotho levels were significantly lower among patients with T2DM and with or without diabetic complications (P<0.05). Furthermore, α-Klotho levels were lower in the microalbuminuric and macroalbuminuric groups, compared to the normoalbuminuric group. However, β-Klotho levels were only lower in the macroalbuminuric group (P<0.05). Multiple linear regression analyses revealed that α-Klotho and β-Klotho levels were positively correlated with the creatinine clearance rate, and negatively correlated with the urinary albumin to creatinine ratio and randomly sampled serum levels of creatinine, blood urea nitrogen, and blood glucose. Moreover, α-Klotho and β-Klotho levels were positively correlated among patients with T2DM (r=0.693, P<0.001). Serum levels of α-Klotho and β-Klotho are down-regulated in patients with T2DM. Thus, these proteins may participate in the pathological mechanism of diabetes, and the positive correlation of α-Klotho and β-Klotho levels indicates that they might have similar mechanisms in T2DM.

To better understand the diagnostic and predictive performance of urinary biomarkers of kidney injury, we evaluated γ-glutamyltranspeptidase (GGT), alkaline phosphatase (AP), neutrophil-gelatinase-associated lipocalin (NGAL), cystatin C (CysC), kidney injury molecule-1 (KIM-1), and interleukin-18 (IL-18) in a prospective observational study of 529 patients in 2 general intensive care units (ICUs). Comparisons were made using the area under the receiver operator characteristic curve (AUC) for diagnosis or prediction of acute kidney injury (AKI), dialysis, or death, and reassessed after patient stratification by baseline renal function (estimated glomerular filtration rate, eGFR) and time after renal insult. On ICU entry, no biomarker had an AUC above 0.7 in the diagnosis or prediction of AKI. Several biomarkers (NGAL, CysC, and IL-18) predicted dialysis (AUC over 0.7), and all except KIM-1 predicted death at 7 days (AUC between 0.61 and 0.69). Performance was improved by stratification for eGFR or time or both. With eGFR <60ml/min, CysC and KIM-1 had AUCs of 0.69 and 0.73, respectively, within 6h of injury, and between 12 and 36h, CysC (0.88), NGAL (0.85), and IL-18 (0.94) had utility. With eGFR >60ml/min, GGT (0.73), CysC (0.68), and NGAL (0.68) had the highest AUCs within 6h of injury, and between 6 and 12h, all AUCs except AP were between 0.68 and 0.78. Beyond 12h, NGAL (0.71) and KIM-1 (0.66) performed best. Thus, the duration of injury and baseline renal function should be considered in evaluating biomarker performance to diagnose AKI.

Introduction: Major Depressive Disorder (MDD) is a common psychiatric disorder. Currently, there is no objective, cost-effective and non-invasive method to measure biological markers related to the pathogenesis of MDD. Previous studies primarily focused on urinary metabolite markers which are not proximal to the pathogenesis of MDD. Herein, we compare urinary monoamines, steroid hormones and the derived ratios amongst MDD when compared to healthy controls. Methods: Morning urine samples of medicated patients suffering from MDD (n = 47) and healthy controls (n = 41) were collected. Enzyme-linked immunosorbent assay (ELISA) was performed to measure five biomarkers: cortisol, dopamine, noradrenaline, serotonin and sulphate derivative of dehydroepiandrosterone (DHEAS). The mean urinary levels and derived ratios of monoamines and steroid hormones were compared between patients and controls to identify potential biomarkers. The receiver operative characteristic curve (ROC) analysis was conducted to evaluate the diagnostic performance of potential biomarkers. Results: Medicated patients with MDD showed significantly higher spot urine ratio of DHEAS/serotonin (1.56 vs. 1.19, p = 0.004) and lower ratio of serotonin/dopamine (599.71 vs. 888.60, p = 0.008) than healthy controls. A spot urine serotonin/dopamine ratio cut-off of >667.38 had a sensitivity of 73.2% and specificity of 51.1%. Conclusions: Our results suggest that spot urine serotonin/dopamine ratio can be used as an objective diagnostic method for adults with MDD.

Purpose Acute kidney injury (AKI) is a common and serious adverse effect of cisplatin-based chemotherapy. However, traditional markers of kidney function, such as serum creatinine, are suboptimal, because they are not sensitive measures of proximal tubular injury. We aimed to determine whether the new urinary biomarkers such as kidney injury molecule-1 (KIM-1), monocyte chemotactic protein-1 (MCP-1), and neutrophil gelatinase-associated lipocalin (NGAL) could detect cisplatin-induced AKI in lung cancer patients in comparison with the conventional urinary proteins such as N -acetyl- β - d -glucosaminidase (NAG) and β2-microglobulin. Methods We measured KIM-1, MCP-1, NGAL, NAG, and β2-microglobulin concentrations in urine samples from 11 lung cancer patients, which were collected the day before cisplatin administration and on days 3, 7, and 14. Subsequently, we evaluated these biomarkers by comparing their concentrations in 30 AKI positive (+) and 12 AKI negative (−) samples and performing receiver operating characteristic (ROC) curve analyses. Results The urinary levels normalized with urine creatinine of KIM-1 and MCP-1, but not NGAL, NAG, and β2-microglobulin in AKI (+) samples were significantly higher than those in AKI (−) samples. In addition, ROC curve analyses revealed that KIM-1 and MCP-1, but not NGAL, could detect AKI with high accuracy (area under the curve [AUC] = 0.858, 0.850, and 0.608, respectively). The combination of KIM-1 and MCP-1 outperformed either biomarker alone (AUC = 0.871). Conclusions Urinary KIM-1 and MCP-1, either alone or in combination, may represent biomarkers of cisplatin-induced AKI in lung cancer patients.

Estimation of dietary intake of polyphenols is difficult, due to limited availability of food composition data and bias inherent to dietary assessment methods. The aim of the present study was to evaluate the associations between the intake of polyphenol-rich foods and the urinary excretion of several phenolic compounds and therefore explore whether these phenolic compounds could be used as a biomarker of intake. Fifty-three participants of the SU.VI.MAX study (a randomised primary-prevention trial evaluating the effect of daily antioxidant supplementation on chronic diseases) collected a 24h urine and a spot urine sample and filled a dietary record during a 2d period. Thirteen polyphenols and metabolites, chlorogenic acid, caffeic acid, m-coumaric acid, gallic acid, 4-o-methylgallic acid, quercetin, isorhamnetin, kaempferol, hesperetin, naringenin, phloretin, enterolactone and enterodiol, were measured using HPLC–electrospray ionisation–MS–MS. In spot samples apple consumption was positively correlated to phloretin, grapefruit consumption to naringenin, orange to hesperetin, citrus fruit consumption to both naringenin and hesperetin, with r coefficients ranging from 0·31 to 0·57 (p<0·05). The combination of fruits and/or fruit juices was positively correlated to gallic acid and 4-o-methylgallic acid, isorhamnetin, kaempferol, hesperetin, naringenin and phloretin (r 0·24–0·44, p<0·05). Coffee consumption was positively correlated to caffeic and chlorogenic acids (r 0·29 and 0·63, p<0·05 respectively). Black tea and wine consumption were positively correlated with gallic and 4-o-methylgallic acids (r 0·37–0·54, p<0·001). The present results suggest that several polyphenols measured in a spot urine sample can be used as biomarkers of polyphenol-rich food intake.

Metabolomic profiles were used to characterise the effects of consuming a high-phytochemical diet compared with a diet devoid of fruits and vegetables (F&V) in a randomised trial and cross-sectional study. In the trial, 8 h fasting urine from healthy men (n 5) and women (n 5) was collected after a 2-week randomised, controlled trial of two diet periods: a diet rich in cruciferous vegetables, citrus and soya (F&V), and a fruit- and vegetable-free (basal) diet. Among the ions found to differentiate the diets, 176 were putatively annotated with compound identifications, with forty-six supported by MS/MS fragment evidence. Metabolites more abundant in the F&V diet included markers of the dietary intervention (e.g. crucifers, citrus and soya), fatty acids and niacin metabolites. Ions more abundant in the basal diet included riboflavin, several acylcarnitines and amino acid metabolites. In the cross-sectional study, we compared the participants based on the tertiles of crucifers, citrus and soya from 3 d food records (n 36) and FFQ (n 57); intake was separately divided into the tertiles of total fruit and vegetable intake for FFQ. As a group, ions individually differential between the experimental diets differentiated the observational study participants. However, only four ions were significant individually, differentiating the third v. first tertile of crucifer, citrus and soya intake based on 3 d food records. One of these ions was putatively annotated: proline betaine, a marker of citrus consumption. There were no ions significantly distinguishing tertiles by FFQ. The metabolomic assessment of controlled dietary interventions provides a more accurate and stronger characterisation of the diet than observational data.

In this trial in persons with chronic kidney disease and type 2 diabetes, combination therapy with finerenone and empagliflozin led to a greater reduction in the urinary albumin-to-creatinine ratio than either drug alone.