Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study

Biomarkers of frailty

Several biomarkers have been proposed to identify frailty, a multisystemic age-related syndrome. However, the complex pathophysiology and the absence of a consensus on a comprehensive and universal definition make it challenging to pinpoint a singular biomarker or set of biomarkers that conclusively characterize frailty. This review delves into the main laboratory biomarkers, placing special emphasis on those associated with various pathways closely tied to the frailty condition, such as inflammation, oxidative stress, mitochondrial dysfunction, metabolic and endocrine alterations and microRNA. Additionally, we provide a summary of different clinical biomarkers encompassing different tools that have been proposed to assess frailty. We further address various imaging biomarkers such as Dual Energy X-ray Absorptiometry, Bioelectrical Impedance analysis, Computed Tomography and Magnetic Resonance Imaging, Ultrasound and D3 Creatine dilution. Intervention to treat frailty, including non-pharmacological ones, especially those involving physical exercise and nutrition, and pharmacological interventions, that include those targeting specific mechanisms such as myostatin inhibitors, insulin sensitizer metformin and with special relevance for hormonal treatments are mentioned. We further address the levels of different biomarkers in monitoring the potential positive effects of some of these interventions. Despite the availability of numerous biomarkers, their performance and usefulness in the clinical arena are far from being satisfactory. Considering the multicausality of frailty, there is an increasing need to assess the role of sets of biomarkers and the combination between laboratory, clinical and image biomarkers, in terms of sensitivity, specificity and predictive values for the diagnosis and prognosis of the different outcomes of frailty to improve detection and monitoring of older people with frailty or at risk of developing it, being this a need in the everyday clinical practice.

Exploring the metabolomics profile of frailty- a systematic review

Background

Frailty is a multifaceted geriatric syndrome characterized by an increased vulnerability to stressful events. metabolomics studies are valuable tool for better understanding the underlying mechanisms of pathologic conditions. This review aimed to elucidate the metabolomics profile of frailty.

Method

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 statement. A comprehensive search was conducted across multiple databases. Initially, 5027 results were retrieved, and after removing duplicates, 1838 unique studies were subjected to screening. Subsequently, 248 studies underwent full-text screening, with 21 studies ultimately included in the analysis. Data extraction was performed meticulously by two authors, and the quality of the selected studies was assessed using the Critical Appraisal Skills Program (CASP) checklist.

Results

The findings revealed that certain Branched-chain amino acids (BCAAs) levels were lower in frail subjects compared to robust subjects, while levels of glutamate and glutamine were higher in frail individuals. Moreover, sphingomyelins and phosphatidylcholines (PC) displayed a decreasing trend as frailty advanced. Additionally, other metabolic derivatives, such as carnitine, exhibited significant associations with frailty. These metabolites were primarily interconnected through biochemical pathways related to the tricarboxylic acid and urea cycles. Notably, frailty was associated with a decrease in metabolic derivatives, including carnitine.

Conclusion

This study underscores the intricate relationship between essential metabolites, including amino acids and lipids, and their varying levels in frail individuals compared to their robust counterparts. It provides a comprehensive panel of metabolites, shedding light on their potential associations with frailty and expanding our understanding of this complex syndrome.

Plasma metabolites and physical function in patients undergoing hemodialysis

Impaired physical function contributes to falls, fractures, and mortality among patients undergoing dialysis. Using a metabolomic approach, we identified metabolite alterations and effect size-based composite scores for constructs of impaired gait speed and grip strength. 108 participants incident to dialysis had targeted plasma metabolomics via liquid chromatography-mass spectrometry and physical function assessed (i.e., 4 m walk, handgrip strength). Physical function measures were categorized as above/ below median, with grip utilizing sex-based medians. To develop composite scores, metabolites were identified via Wilcoxon uncorrected p < 0.05 and effect size > 0.40. Receiver operating characteristic analyses tested whether scores differentiated between above/below function groups. Participants were 54% male, 77% Black and 53 ± 14 y with dialysis vintage of 101 ± 50 days. Median (IQR) grip strength was 35.5 (11.1) kg (males) and 20 (8.4) kg (females); median gait speed was 0.82 (0.34) m/s. Of 246 measured metabolites, composite scores were composed of 22 and 12 metabolites for grip strength and gait speed, respectively. Area under the curve for metabolite composite was 0.88 (gait) and 0.911 (grip). Composite scores of physical function performed better than clinical parameters alone in patients on dialysis. These results provide potential pathways for interventions and needed validation in an independent cohort.

Prediagnostic plasma metabolite concentrations and liver cancer risk: a population-based study of Chinese men

BACKGROUND

Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites. In this study, we examined the association between the concentrations of 186 targeted metabolites and liver cancer risk using prediagnostic plasma samples collected up to 14 years prior to the clinical diagnosis of liver cancer.

METHODS

We conducted a nested case-control study (n = 322 liver cancer cases, n = 322 matched controls) within the Shanghai Men's Health Study. Conditional logistic regression models adjusted for demographics, lifestyle factors, dietary habits, and related medical histories were used to estimate the odds ratios. Restricted cubic spline functions were used to characterise the dose-response relationships between metabolite concentrations and liver cancer risk.

FINDINGS

After adjusting for potential confounders and correcting for multiple testing, 28 metabolites were associated with liver cancer risk. Significant non-linear relationships were observed for 22 metabolites. The primary bile acid biosynthesis and phenylalanine, tyrosine and tryptophan biosynthesis were found to be important pathways involved in the aetiology of liver cancer. A metabolic score consisting of 10 metabolites significantly improved the predictive ability of traditional epidemiological risk factors for liver cancer, with an optimism-corrected AUC increased from 0.84 (95% CI: 0.81-0.87) to 0.89 (95% CI: 0.86-0.91).

INTERPRETATION

This study characterised the dose-response relationships between metabolites and liver cancer risk, providing insights into the complex metabolic perturbations prior to the clinical diagnosis of liver cancer. The metabolic score may serve as a candidate risk predictor for liver cancer.

FUNDING

National Key Project of Research and Development Program of China [2021YFC2500404, 2021YFC2500405]; US National Institutes of Health [subcontract of UM1 CA173640].

Goat Milk Improves Glucose Metabolism in Type 2 Diabetic Mice and Protects Pancreatic β-Cell Functions

SCOPE

Consuming goat milk is known to benefit high-fat diet-fed and streptozocin (STZ)-induced diabetic rats, but the underlying mechanisms are unknown. This study is conducted to investigate the metabolic effects of a goat milk diet (a form of goat milk powder) on glucose homeostasis and pancreatic conditions in a mouse model of Type 2 diabetes mellitus (T2DM) induced by STZ.

METHODS AND RESULTS

T2DM mice are fed with a goat-milk-based diet containing 10.3% w/w goat milk powder for 10 weeks for investigating the in vivo effects; a β-cell line MIN6 cells are used to test the in vitro effects of digested goat milk (DGM). Goat milk diet improves the deleterious effects of STZ on fasting glucose levels and glucose tolerance, accelerates pancreatic structure recovery, and alters blood metabolites in mice. Based on the significant differences observed in metabolites, the key pathways, metabolite regulatory enzymes, metabolite molecular modules, and biochemical reactions are identified as critical integrated pathways. DGM promotes the cell activity, glucose transportation, and AKT activation in cultured STZ-treated MIN6 cells in vitro.

CONCLUSIONS

Goat milk diet improves glucose homeostasis and pancreatic conditions of T2DM mice, in association with improved blood metabolite profiles and activation of pancreatic AKT pathway.

Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment

Diabetes is a major global public health problem with high incidence and case fatality rates. Traditional Chinese medicine (TCM) is used to help manage Type 2 Diabetes Mellitus (T2DM) and has steadily gained international acceptance. Despite being generally accepted in daily practice, the TCM methods and hypotheses for understanding diseases lack applicability in the current scientific characterization systems. To date, there is no systematic evaluation system for TCM in preventing and treating T2DM. Metabonomics is a powerful tool to predict the level of metabolites in vivo, reveal the potential mechanism, and diagnose the physiological state of patients in time to guide the follow-up intervention of T2DM. Notably, metabolomics is also effective in promoting TCM modernization and advancement in personalized medicine. This review provides updated knowledge on applying metabolomics to TCM syndrome differentiation, diagnosis, biomarker discovery, and treatment of T2DM by TCM. Its application in diabetic complications is discussed. The combination of multi-omics and microbiome to fully elucidate the use of TCM to treat T2DM is further envisioned.

Normative Data on Serum and Plasma Tryptophan and Kynurenine Concentrations from 8089 Individuals Across 120 Studies: A Systematic Review and Meta-Analysis

In this systematic review and meta-analysis, a normative dataset is generated from the published literature on the kynurenine pathway in control participants extracted from case-control and methodological validation studies. Study characteristics were mapped, and studies were evaluated in terms of analytical rigour and methodological validation. Meta-analyses of variance between types of instruments, sample matrices and metabolites were conducted. Regression analyses were applied to determine the relationship between metabolite, sample matrix, biological sex, participant age and study age. The grand mean concentrations of tryptophan in the serum and plasma were 60.52 ± 15.38 μM and 51.45 ± 10.47 μM, respectively. The grand mean concentrations of kynurenine in the serum and plasma were 1.96 ± 0.51 μM and 1.82 ± 0.54 μM, respectively. Regional differences in metabolite concentrations were observed across America, Asia, Australia, Europe and the Middle East. Of the total variance within the data, mode of detection (MOD) accounted for up to 2.96%, sample matrix up to 3.23%, and their interaction explained up to 1.53%; the latter of which was determined to be negligible. This review was intended to inform future empirical research and method development studies and successfully synthesised pilot data. The pilot data reported in this study will inform future precision medicine initiatives aimed at targeting the kynurenine pathway by improving the availability and quality of normative data.

Abnormal tryptophan catabolism in diabetes mellitus and its complications: Opportunities and challenges

In recent years, the incidence rate of diabetes mellitus (DM), including type 1 diabetes mellitus(T1DM), type 2 diabetes mellitus(T2DM), and gestational diabetes mellitus (GDM), has increased year by year and has become a major global health problem. DM can lead to serious complications of macrovascular and microvascular. Tryptophan (Trp) is an essential amino acid for the human body. Trp is metabolized in the body through the indole pathway, kynurenine (Kyn) pathway and serotonin (5-HT) pathway, and is regulated by intestinal microorganisms to varying degrees. These three metabolic pathways have extensive regulatory effects on the immune, endocrine, neural, and energy metabolism systems of the body, and are related to the physiological and pathological processes of various diseases. The key enzymes and metabolites in the Trp metabolic pathway are also deeply involved in the pathogenesis of DM, playing an important role in pancreatic function, insulin resistance (IR), intestinal barrier, and angiogenesis. In DM and its complications, there is a disruption of Trp metabolic balance. Several therapy approaches for DM and complications have been proven to modify tryptophan metabolism. The metabolism of Trp is becoming a new area of focus for DM prevention and care. This paper reviews the impact of the three metabolic pathways of Trp on the pathogenesis of DM and the alterations in Trp metabolism in these diseases, expecting to provide entry points for the treatment of DM and its complications.

An early prediction model for gestational diabetes mellitus based on metabolomic biomarkers

BACKGROUND

Gestational diabetes mellitus (GDM) represents the main metabolic alteration during pregnancy. The available methods for diagnosing GDM identify women when the disease is established, and pancreatic beta-cell insufficiency has occurred.The present study aimed to generate an early prediction model (under 18 weeks of gestation) to identify those women who will later be diagnosed with GDM.

METHODS

A cohort of 75 pregnant women was followed during gestation, of which 62 underwent normal term pregnancy and 13 were diagnosed with GDM. Targeted metabolomics was used to select serum biomarkers with predictive power to identify women who will later be diagnosed with GDM.

RESULTS

Candidate metabolites were selected to generate an early identification model employing a criterion used when performing Random Forest decision tree analysis. A model composed of two short-chain acylcarnitines was generated: isovalerylcarnitine (C5) and tiglylcarnitine (C5:1). An analysis by ROC curves was performed to determine the classification performance of the acylcarnitines identified in the study, obtaining an area under the curve (AUC) of 0.934 (0.873-0.995, 95% CI). The model correctly classified all cases with GDM, while it misclassified ten controls as in the GDM group. An analysis was also carried out to establish the concentrations of the acylcarnitines for the identification of the GDM group, obtaining concentrations of C5 in a range of 0.015-0.25 μmol/L and of C5:1 with a range of 0.015-0.19 μmol/L.

CONCLUSION

Early pregnancy maternal metabolites can be used to screen and identify pregnant women who will later develop GDM. Regardless of their gestational body mass index, lipid metabolism is impaired even in the early stages of pregnancy in women who develop GDM.

Plasma metabolomics of oral squamous cell carcinomas based on NMR and MS approaches provides biomarker identification and survival prediction

Metabolomics has proven to be an important omics approach to understand the molecular pathways underlying the tumour phenotype and to identify new clinically useful markers. The literature on cancer has illustrated the potential of this approach as a diagnostic and prognostic tool. The present study aimed to analyse the plasma metabolic profile of patients with oral squamous cell carcinoma (OSCC) and controls and to compare patients with metastatic and primary tumours at different stages and subsites using nuclear magnetic resonance and mass spectrometry. To our knowledge, this is the only report that compared patients at different stages and subsites and replicates collected in diverse institutions at different times using these methodologies. Our results showed a plasma metabolic OSCC profile suggestive of abnormal ketogenesis, lipogenesis and energy metabolism, which is already present in early phases but is more evident in advanced stages of the disease. Reduced levels of several metabolites were also associated with an unfavorable prognosis. The observed metabolomic alterations may contribute to inflammation, immune response inhibition and tumour growth, and may be explained by four nonexclusive views-differential synthesis, uptake, release, and degradation of metabolites. The interpretation that assimilates these views is the cross talk between neoplastic and normal cells in the tumour microenvironment or in more distant anatomical sites, connected by biofluids, signalling molecules and vesicles. Additional population samples to evaluate the details of these molecular processes may lead to the discovery of new biomarkers and novel strategies for OSCC prevention and treatment.

Amino Acid Profiles in Older Adults with Frailty: Secondary Analysis from MetaboFrail and BIOSPHERE Studies

An altered amino acid metabolism has been described in frail older adults which may contribute to muscle loss and functional decline associated with frailty. In the present investigation, we compared circulating amino acid profiles of older adults with physical frailty and sarcopenia (PF&S, n = 94), frail/pre-frail older adults with type 2 diabetes mellitus (F-T2DM, n = 66), and robust non-diabetic controls (n = 40). Partial least squares discriminant analysis (PLS-DA) models were built to define the amino acid signatures associated with the different frailty phenotypes. PLS-DA allowed correct classification of participants with 78.2 ± 1.9% accuracy. Older adults with F-T2DM showed an amino acid profile characterized by higher levels of 3-methylhistidine, alanine, arginine, ethanolamine, and glutamic acid. PF&S and control participants were discriminated based on serum concentrations of aminoadipic acid, aspartate, citrulline, cystine, taurine, and tryptophan. These findings suggest that different types of frailty may be characterized by distinct metabolic perturbations. Amino acid profiling may therefore serve as a valuable tool for frailty biomarker discovery.

The acute postprandial response of homocysteine to multivitamin and mineral supplementation with a standard meal is not impaired in older compared to younger adults

PURPOSE

B vitamins are required for the complex regulation of homocysteine and one-carbon (1C) metabolism. Nutritional supplements are frequently used by older adults to counter nutritional inadequacies. However, the postprandial use of B vitamins from supplements in 1C metabolism may be altered with age owing to impaired nutrient absorption and metabolic regulation. Despite implications for health and nutritional status, postprandial 1C metabolite responses have not been characterised in older adults.

METHODS

Healthy older (n = 20, 65-76 years) and younger (n = 20, 19-30 years) participants were recruited through online and printed advertisements in Auckland, New Zealand. Participants consumed a multivitamin and mineral supplement with a standard breakfast meal. Blood samples were collected at baseline and hourly for 4 h following ingestion. Plasma 1C metabolites (betaine, choline, cysteine, dimethylglycine, glycine, methionine, serine) were quantified using liquid chromatography coupled with mass spectrometry. Serum homocysteine, folate and vitamin B₁₂ were quantified on a Cobas e411 autoanalyzer.

RESULTS

Older adults had higher fasting homocysteine concentrations (older: 14.0 ± 2.9 µmol/L; younger: 12.2 ± 2.5 µmol/L; p = 0.036) despite higher folate (older: 36.7 ± 17.4 nmol/L; younger: 21.6 ± 7.6 nmol/L; p < 0.001) and similar vitamin B₁₂ concentrations (p = 0.143) to younger adults. However, a similar postprandial decline in homocysteine was found in older and younger subjects in response to the combined meal and supplement. Except for a faster decline of cystathionine in older adults (p = 0.003), the postprandial response of other 1C metabolites was similar between young and older adults.

CONCLUSION

Healthy older adults appear to maintain postprandial responsiveness of 1C metabolism to younger adults, supported by a similar postprandial decline in homocysteine concentrations.

A Metabolic Signature of Hereditary Transthyretin Amyloidosis: A Pilot Study

Hereditary transthyretin amyloidosis is the most common form of hereditary amyloidosis, with an autosomal dominant inheritance and a variable penetrance. ATTRv amyloidosis can present as a progressive, axonal sensory autonomic and motor neuropathy or as an infiltrative cardiomyopathy. The definition of biomarkers for the early diagnosis of ATTRv is particularly important in the current era of emerging treatments. In this sense, metabolomics could be an instrument able to provide metabolic profiles with their related metabolic pathways, and we would propose them as possible fluid biomarkers. The aim of this study is to identify altered metabolites (free fatty acids and amino acids) in subjects with a confirmed pathogenic TTR variant. Out of the studied total free fatty acids and amino acids, the serum values of palmitic acid are significantly lower in the ATTRv patients compared to the recruited healthy subjects. The metabolic remodeling identified in this neurogenetic disorder could be the manifestation of pathophysiological processes of the disease, such as mitochondrial dysfunction and neuroinflammation, and contribute to explaining some of its clinical manifestations.

The Effect of Dietary Carbohydrate and Fat Manipulation on the Metabolome and Markers of Glucose and Insulin Metabolism: A Randomised Parallel Trial

High carbohydrate, lower fat (HCLF) diets are recommended to reduce cardiometabolic disease (CMD) but low carbohydrate high fat (LCHF) diets can be just as effective. The effect of LCHF on novel insulin resistance biomarkers and the metabolome has not been fully explored. The aim of this study was to investigate the impact of an ad libitum 8-week LCHF diet compared with a HCLF diet on CMD markers, the metabolome, and insulin resistance markers. n = 16 adults were randomly assigned to either LCHF (n = 8, <50 g CHO p/day) or HCLF diet (n = 8) for 8 weeks. At weeks 0, 4 and 8, participants provided fasted blood samples, measures of body composition, blood pressure and dietary intake. Samples were analysed for markers of cardiometabolic disease and underwent non-targeted metabolomic profiling. Both a LCHF and HCLF diet significantly (p < 0.01) improved fasting insulin, HOMA IR, rQUICKI and leptin/adiponectin ratio (p < 0.05) levels. Metabolomic profiling detected 3489 metabolites with 78 metabolites being differentially regulated, for example, an upregulation in lipid metabolites following the LCHF diet may indicate an increase in lipid transport and oxidation, improving insulin sensitivity. In conclusion, both diets may reduce type 2 diabetes risk albeit, a LCHF diet may enhance insulin sensitivity by increasing lipid oxidation.

Therapeutic mechanisms of mulberry leaves in type 2 diabetes based on metabolomics

Background: Type 2 diabetes (T2D) is considered as one of the most significant metabolic syndromes worldwide, and the long-term use of the drugs already on the market for T2D often gives rise to some side effects. The mulberry leaf (ML), Morus alba L., has advantages in terms of its comprehensive therapeutic efficacy, which are characterized as multicomponent, multitarget, multipathway, and matching with the complex pathological mechanisms of diabetes.

Methods: T2D rats were established by a high-fat diet combined with an intraperitoneal injection of streptozotocin; an evaluation of the hypoglycemic effects of the ML in combination with fasting blood glucose and other indicators, in addition to the utilization of metabolomics technology, was performed to analysis the metabolite changes in serum of rats.

Results: MLs significantly reduced the fasting blood glucose of T2D rats, while improving the symptoms of polyphagia and polyuria. ML treatment altered the levels of various metabolites in the serum of T2D rats, which are involved in multiple metabolic pathways (amino acid metabolism, carbohydrate metabolism, and lipid metabolism), played a role in antioxidative stress and anti-inflammation, modulated immune and gluconeogenesis processes, and improved obesity as well as insulin resistance (IR).

Conclusion: The ML contains a variety of chemical components, and metabolomic results have shown that MLs regulate multiple metabolic pathways to exert hypoglycemic effects, suggesting that MLs may have great promise in the development of new hypoglycemic drugs.

Amino acid profile of skeletal muscle loss in type 2 diabetes: Results from a 7-year longitudinal study in asians

AIMS

Little is known about pathophysiology of sarcopenia in diabetes. We aimed to study amino acid profile associated with skeletal muscle mass loss longitudinally in Type 2 Diabetes Mellitus (T2DM).

METHODS

This is a prospective study of 1140 patients aged 56.6 ± 10.6 years from the SMART2D cohort. Skeletal muscle mass was measured using bio-impedance analysis at baseline and follow-up. Amino acids were measured by mass spectrometry.

RESULTS

Over a period of up to 7.9 years, 43.9% experienced skeletal muscle mass loss. Lower baseline valine, leucine and isoleucine levels were associated with decreased skeletal muscle mass index (SMI) with corresponding coefficient 0.251(95 %CI 0.009 to 0.493), 0.298(95 %CI 0.051 to 0.544)) and 0.366(95 %CI 0.131 to 0.600). Higher baseline valine, leucine, isoleucine, alanine and tryptophan levels were associated with reduced odds of muscle mass loss with corresponding odds ratio (OR)0.797 (95 %CI 0.690 to 0.921), 0.825 (95 %CI 0.713 to 0.955), 0.826 (95 %CI 0.718-0.950), 0.847 (95 %CI 0.739-0.969) and 0.835 (95 %CI 0.720-0.979).

CONCLUSION

The branched-chain amino acids valine, leucine and isoleucine were positively associated with change in SMI and reduced odds of muscle mass loss longitudinally. Further studies should be conducted to elucidate the pathophysiological mechanisms underlying the relationship between these amino acids and muscle mass loss in T2DM.

Specific lysophosphatidylcholine and acylcarnitine related to sarcopenia and its components in older men

Background

Metabolic profiling may provide insights into the pathogenesis and identification of sarcopenia; however, data on the metabolic basis of sarcopenia and muscle-related parameters among older adults remain incompletely understood. This study aimed to identify the associations of metabolites with sarcopenia and its components, and to explore metabolic perturbations in older men, who have a higher prevalence of sarcopenia than women.

Methods

We simultaneously measured the concentrations of amino acids, carnitine, acylcarnitines, and lysophosphatidylcholines (LPCs) in serum samples from a cross-sectional study of 246 Chinese older men, using targeted metabolomics. Sarcopenia and its components, including skeletal muscle index (SMI), 6-m gait speed, and handgrip strength were assessed according to the algorithm of the Asian Working Group for Sarcopenia criteria. Associations were determined by univariate and multivariate analyses.

Results

Sixty-five (26.4%) older men with sarcopenia and 181 (73.6%) without sarcopenia were included in the study. The level of isovalerylcarnitine (C5) was associated with the presence of sarcopenia and SMI. Regarding the overlapped metabolites for muscle parameters, among ten metabolites associated with muscle mass, six metabolites including leucine, octanoyl-L-carnitine (C8), decanoyl-L-carnitine (C10), dodecanoyl-L-carnitine (C12) and tetradecanoyl-L-carnitine (C14), and LPC18:2 were associated with handgrip strength, and three of which (C12, C14, and LPC18:2) were also associated with gait speed. Specifically, tryptophan was positively associated and glycine was negatively associated with handgrip strength, while glutamate was positively correlated with gait speed. Isoleucine, branched chain amino acids, and LPC16:0 were positively associated with SMI. Moreover, the levels of LPC 16:0,18:2 and 18:0 contributed significantly to the model discriminating between older men with and without sarcopenia, whereas there were no significant associations for other amino acids, acylcarnitines, and LPC lipids.

Conclusions

These results showed that specific and overlapped metabolites are associated with sarcopenic parameters in older men. This study highlights the potential roles of acylcarnitines and LPCs in sarcopenia and its components, which may provide valuable information regarding the pathogenesis and management of sarcopenia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02953-4.

Specific Metabolites Involved in Antioxidation and Mitochondrial Function Are Correlated With Frailty in Elderly Men

Background

As an age-related syndrome, frailty may play a central role in poor health among older adults. Sarcopenia overlaps with the physical domain of frailty, and most existing studies have analyzed the associated factors of frailty and sarcopenia as an isolated state. Perturbations in metabolism may play an important role in the presence of frailty or sarcopenia; however, the metabolites associated with frailty, especially overlapping with sarcopenia remain unclear. In this study, we aimed to explore whether amino acids, carnitines, acylcarnitines and lysophosphatidylcholines, as specific panels, are significantly correlated with frailty, especially overlapping with sarcopenia, to gain insight into potential biomarkers and possible biological mechanisms and to facilitate their management.

Methods

We applied a targeted high-performance liquid chromatography-tandem mass spectrometry approach in serum samples from 246 Chinese older men (age 79.2 ± 7.8 years) with frailty (n = 150), non-frailty (n = 96), frailty and sarcopenia (n = 52), non-frail and non-sarcopenic control (n = 85). Frailty was evaluated using Freid phenotype criteria, sarcopenia was defined by diagnostic algorithm of Asian Working Group on Sarcopenia, and the participants were diagnosed as frailty and sarcopenia when they met the evaluation criteria of both frailty and sarcopenia. A panel of 29 metabolomic profiles was assayed and included different classes of amino acids, carnitines, acylcarnitines, and lysophosphatidylcholines (LPCs). Multivariate logistic regression was used to screen the metabolic factors contributing to frailty status, and orthogonal partial least squares discriminant analysis was used to explore important factors and distinguish different groups.

Results

In older men demonstrating the frail phenotype, amino acid perturbations included lower tryptophan and higher glycine levels. With regard to lipid metabolism, the frailty phenotype was characterized by lower concentrations of isovalerylcarnitine (C5), LPC16:0 and LPC18:2, while higher levels of octanoyl-L-carnitine (C8), decanoyl-L-carnitine (C10), dodecanoyl-L-carnitine (C12) and tetradecanoyl-L-carnitine (C14). After adjusting for several clinical confounders, tryptophan, LPC18:2, LPC 16:0 and C5 were negatively correlated with frailty, and C8 and C12 were positively related to frailty. We preliminarily identified metabolic profiles (LPC16:0, LPC18:2, glycine and tryptophan) that may distinguish older men with frailty from those without frailty. Importantly, a set of serum amino acids and LPCs (LPC16:0, LPC18:2, and tryptophan) was characterized in the metabotype of older adults with an overlap of frailty and sarcopenia. The metabolites that were most discriminating of frailty status implied that the underlying mechanism might be involved in antioxidation and mitochondrial dysfunction.

Conclusions

These present metabolic analyses may provide valuable information on the potential biomarkers and possible biological mechanisms of frailty, and overlapping sarcopenia. The findings obtained may offer insight into their management in older adults.

Combined effect of diabetes and frailty on mortality among Chinese older adults: A follow-up study

BACKGROUND

Frailty and diabetes are two important health problems associated with aging in older individuals. This paper seeks to analyze the frailty in older adults suffering from diabetes and the combined effect of diabetes and frailty on mortality risk.

METHODS

The frailty index (FI) model was employed when evaluating frailty among the older adults based on the baseline data conducted in 2009; and death as outcome variables collected in 2020 were analyzed. The influence of diabetes on age-related changes in frailty in the older adults and resulting mortality rates was analyzed. Cox regression and Kaplan-Meier curves were applied to evaluate the influence on the risk of death and the 11-year survival of the older adults with varying diabetes and frailty statuses.

RESULTS

Ultimately, 1,213 older people aged between 60 and 101, with an average age of (74.79 ± 8.58) at baseline, were included in the analysis. By 2020, there had been 447 deaths with mortality at 36.9% (447/1,213); there were 271 cases of diabetes, with a prevalence of 22.3% (271/1,213). The mean FI value for older adults with diabetes was higher than that of those without regardless of age, and the average annual relative growth rate of the FI value for older adults with diabetes was higher than that of those without diabetes (β = 0.039 vs. β = 0.035, t = 8.367, P < 0.001). For all FI value levels, the mortality rate among older adults with diabetes was higher than that of those without. The Cox Regression analysis showed that, compared with those suffering from neither diabetes nor frailty, older adults with both had the higher mortality risk (HR = 1.760. P < 0.001), followed by older adults suffering from frailty alone (HR = 1.594, P = 0.006), and then by older adults suffering from only diabetes (HR = 1.475, P = 0.033). The survival analysis showed that the median survival of those suffering from diabetes and frailty to be the shortest at just 57.23 (95% CI: 54.05 to 60.41) months, lower than the 83.78 (95% CI: 79.33 to 88.23) months in those suffering from frailty alone, and 119.93 (95% CI: 113.84 to 126.02) months in those with only diabetes, and 124.39 (95% CI: 119.76 to 129.02) months in older adults with neither diabetes nor frailty (P < 0.001).

CONCLUSION

Frailty is common among older adults suffering from diabetes, and there is an increased risk of poor health outcomes, such as death, among older adults suffering from diabetes and frailty. When diagnosing, treating, and dealing with older adults with diabetes, attention should be paid to screening and assessing frailty in hopes of identifying it early so that appropriate measures of intervention can be taken to avoid or delay the resulting adverse effects.

Circulating Mitochondrial-Derived Vesicles, Inflammatory Biomarkers and Amino Acids in Older Adults With Physical Frailty and Sarcopenia: A Preliminary BIOSPHERE Multi-Marker Study Using Sequential and Orthogonalized Covariance Selection - Linear Discriminant Analysis

Physical frailty and sarcopenia (PF&S) is a prototypical geriatric condition characterized by reduced physical function and low muscle mass. The multifaceted pathophysiology of this condition recapitulates all hallmarks of aging making the identification of specific biomarkers challenging. In the present study, we explored the relationship among three processes that are thought to be involved in PF&S (i.e., systemic inflammation, amino acid dysmetabolism, and mitochondrial dysfunction). We took advantage of the well-characterized cohort of older adults recruited in the “BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons” (BIOSPHERE) study to preliminarily combine in a multi-platform analytical approach inflammatory biomolecules, amino acids and derivatives, and mitochondrial-derived vesicle (MDV) cargo molecules to evaluate their performance as possible biomarkers for PF&S. Eleven older adults aged 70 years and older with PF&S and 10 non-sarcopenic non-frail controls were included in the analysis based on the availability of the three categories of biomolecules. A sequential and orthogonalized covariance selection—linear discriminant analysis (SO-CovSel–LDA) approach was used for biomarkers selection. Of the 75 analytes assayed, 16 had concentrations below the detection limit. Within the remaining 59 biomolecules, So-CovSel–LDA selected a set comprising two amino acids (phosphoethanolamine and tryptophan), two cytokines (interleukin 1 receptor antagonist and macrophage inflammatory protein 1β), and MDV-derived nicotinamide adenine dinucleotide reduced form:ubiquinone oxidoreductase subunit S3 as the best predictors for discriminating older people with and without PF&S. The evaluation of these biomarkers in larger cohorts and their changes over time or in response to interventions may unveil specific pathogenetic pathways of PF&S and identify new biological targets for drug development.

Biomarkers of Physical Frailty and Sarcopenia: Coming up to the Place?

Physical frailty and sarcopenia (PF&S) recapitulates all the hallmarks of aging and has become a focus in geroscience. Factors spanning muscle-specific processes (e.g., mitochondrial dysfunction in skeletal myocytes) to systemic changes (e.g., inflammation and amino acid dysmetabolism) have been pinpointed as possible contributors to PF&S pathophysiology. However, the search for PF&S biomarkers allowing the early identification and tracking of the condition over time is ongoing. This is mainly due to the phenotypic heterogeneity of PF&S, its unclear pathophysiology, and the frequent superimposition of other age-related conditions. Hence, presently, the identification of PF&S relies upon clinical, functional, and imaging parameters. The adoption of multi-marker approaches (combined with multivariate modeling) has shown great potential for addressing the complexity of PF&S pathophysiology and identifying candidate biological markers. Well-designed longitudinal studies are necessary for the incorporation of reliable biomarkers into clinical practice and for unveiling novel targets that are amenable to interventions.

Omics biomarkers for frailty in older adults

Frailty is a clinical state characterized by an age-related unsteady state of the body, a decline in physiological function, and an increased vulnerability to adverse outcomes. Early diagnosis of frailty is important for improving the quality of life in older adults and promoting healthy aging. The biological mechanisms underlying frailty have been extensively studied in recent years. Combining assessment tools and biomarkers can facilitate the early diagnosis of frailty. However, there is a lack of stable and reliable frailty-related biomarkers for use in clinical practice. Advances in the multi-omics platforms have provided new information on the molecular mechanisms underlying frailty. Thus, identifying biomarkers using omics-based approaches helps explore the physiological mechanisms underlying frailty, and aids the evaluation of the risk of frailty development and progression. This article reviews the current status of frailty biomarkers from the genomics, transcriptomics, proteomics, and metabolomics perspectives.

Identification of biomarkers for physical frailty and sarcopenia through a new multi-marker approach: results from the BIOSPHERE study

Physical frailty and sarcopenia (PF&S) is a prototypical geriatric condition characterized by reduced physical function and low muscle mass. The aim of the present study was to provide an initial selection of biomarkers for PF&S using a novel multivariate analytic strategy. Two-hundred community-dwellers, 100 with PF&S and 100 non-physically frail, non-sarcopenic (nonPF&S) controls aged 70 and older were enrolled as part of the BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons (BIOSPHERE) study. A panel of 74 serum analytes involved in inflammation, muscle growth and remodeling, neuromuscular junction damage, and amino acid metabolism was assayed. Biomarker selection was accomplished through sequential and orthogonalized covariance selection (SO-CovSel) analysis. Separate SO-CovSel models were constructed for the whole study population and for the two genders. The model with the best prediction ability obtained with the smallest number of variables was built using seven biomolecules. This model allowed correct classification of 80.6 ± 5.3% PF&S participants and 79.9 ± 5.1% nonPF&S controls. The PF&S biomarker profile was characterized by higher serum levels of asparagine, aspartic acid, and citrulline. Higher serum concentrations of platelet-derived growth factor BB, heat shock protein 72 (Hsp72), myeloperoxidase, and α-aminobutyric acid defined the profile of nonPF&S participants. Gender-specific SO-CovSel models identified a "core" biomarker profile of PF&S, characterized by higher serum levels of aspartic acid and Hsp72 and lower concentrations of macrophage inflammatory protein 1β, with peculiar signatures in men and women.SO-CovSel analysis allowed identifying a set of potential biomarkers for PF&S. The adoption of such an innovative multivariate approach could help address the complex pathophysiology of PF&S, translate biomarker discovery from bench to bedside, and unveil novel targets for interventions.

The "develOpment of metabolic and functional markers of Dementia IN Older people" (ODINO) Study: Rationale, Design and Methods

Mild cognitive impairment (MCI), also termed mild neurocognitive disorder, includes a heterogeneous group of conditions characterized by declines in one or more cognitive domains greater than that expected during "normal" aging but not severe enough to impair functional abilities. MCI has been associated with an increased risk of developing dementia and even considered an early stage of it. Therefore, noninvasively accessible biomarkers of MCI are highly sought after for early identification of the condition. Systemic inflammation, metabolic perturbations, and declining physical performance have been described in people with MCI. However, whether biological and functional parameters differ across MCI neuropsychological subtypes is presently debated. Likewise, the predictive value of existing biomarkers toward MCI conversion into dementia is unclear. The "develOpment of metabolic and functional markers of Dementia IN Older people" (ODINO) study was conceived as a multi-dimensional investigation in which multi-marker discovery will be coupled with innovative statistical approaches to characterize patterns of systemic inflammation, metabolic perturbations, and physical performance in older adults with MCI. The ultimate aim of ODINO is to identify potential biomarkers specific for MCI subtypes and predictive of MCI conversion into Alzheimer's disease or other forms of dementia over a three-year follow-up. Here, we describe the rationale, design, and methods of ODINO.