Plasma metabolomic profiling of patients with diabetes-associated cognitive decline

Non-invasive metabolic biomarkers in initial cognitive impairment in patients with diabetes: A systematic review and meta-analysis

AIM

Diabetic cognitive impairment (DCI), considered one of the most severe and commonly overlooked complications of diabetes, has shown inconsistent findings regarding the metabolic profiles in DCI patients. This systematic review and meta-analysis aimed to identify dysregulated metabolites as potential biomarkers for early DCI, providing valuable insights into the underlying pathophysiological mechanisms.

MATERIALS AND METHODS

A systematic search of four databases, namely PubMed, Embase, Web of Science and Cochrane, was conducted up to March 2024. Subsequently, a qualitative review of clinical studies was performed followed by a meta-analysis of metabolite markers. Finally, the sources of heterogeneity were explored through subgroup and sensitivity analyses.

RESULTS

A total of 774 unique publications involving 4357 participants and the identification of multiple metabolites were retrieved. Of these, 13 clinical studies reported metabolite differences between the DCI and control groups. Meta-analysis was conducted for six brain metabolites and two metabolite ratios. The results revealed a significant increase in myo-inositol (MI) concentration and decreases in glutamate (Glu), Glx (glutamate and glutamine) and N-acetylaspartate/creatine (NAA/Cr) ratios in DCI, which have been identified as the most sensitive metabolic biomarkers for evaluating DCI progression. Notably, brain metabolic changes associated with cognitive impairment are more pronounced in type 2 diabetes mellitus than in type 1 diabetes mellitus, and the hippocampus emerged as the most sensitive brain region regarding metabolic changes associated with DCI.

CONCLUSIONS

Our results suggest that MI, Glu, and Glx concentrations and NAA/Cr ratios within the hippocampus may serve as metabolic biomarkers for patients with early-stage DCI.

Bile acid modulation by gut microbiota: a bridge to understanding cognitive health

The gut microbiota plays an important role in regulating the body's physiological system, and more recently its impact on bile acid metabolism and cognitive function has been investigated by many studies. In addition to their conventional function in fat digestion and absorption, bile acids are now considered crucial signaling molecules that control several metabolic processes and immunological responses. For this purpose, the authors conducted comprehensive research using relevant terms in an attempt to understand more about the gut microbiota and its impact on bile acid metabolism and cognitive health. The gut-brain axis refers to the network of routes through which gut bacteria communicate with the brain. Through its capacity to bio-transform primary bile acids into secondary bile acids, the gut microbiota plays a significant role in bile acid metabolism. Bile acids function as signaling molecules and act on the brain through nuclear and membrane-bound receptors, influencing neurotransmitter production, neuroinflammation, and neuroplasticity to modify this communication. Any dysregulation in this axis can result in cognitive dysfunction. The link between gut microbiota, bile acids, and cognitive health cannot be ignored. It is imperative to explore this link further by conducting large-scale trials to improve the cognitive health of patients with multiple comorbidities, especially those involving the gastrointestinal tract and nervous system.

Modulating the Gut Microbiota and Metabolites with Traditional Chinese Medicines: An Emerging Therapy for Type 2 Diabetes Mellitus and Its Complications

Currently, an estimated 537 million individuals are affected by type 2 diabetes mellitus (T2DM), the occurrence of which is invariably associated with complications. Glucose-lowering therapy remains the main treatment for alleviating T2DM. However, conventional antidiabetic agents are fraught with numerous adverse effects, notably elevations in blood pressure and lipid levels. Recently, the use of traditional Chinese medicines (TCMs) and their constituents has emerged as a preferred management strategy aimed at curtailing the progression of diabetes and its associated complications with fewer adverse effects. Increasing evidence indicates that gut microbiome disturbances are involved in the development of T2DM and its complications. This regulation depends on various metabolites produced by gut microbes and their interactions with host organs. TCMs' interventions have demonstrated the ability to modulate the intestinal bacterial microbiota, thereby restoring host homeostasis and ameliorating metabolic disorders. This review delves into the alterations in the gut microbiota and metabolites in T2DM patients and how TCMs treatment regulates the gut microbiota, facilitating the management of T2DM and its complications. Additionally, we also discuss prospective avenues for research on natural products to advance diabetes therapy.

Untargeted Metabolomic Profiling Reveals Differentially Expressed Serum Metabolites and Pathways in Type 2 Diabetes Patients with and without Cognitive Decline: A Cross-Sectional Study

Diabetes is recognized as a risk factor for cognitive decline, but the underlying mechanisms remain elusive. We aimed to identify the metabolic pathways altered in diabetes-associated cognitive decline (DACD) using untargeted metabolomics. We conducted liquid chromatography-mass spectrometry-based untargeted metabolomics to profile serum metabolite levels in 100 patients with type 2 diabetes (T2D) (54 without and 46 with DACD). Multivariate statistical tools were used to identify the differentially expressed metabolites (DEMs), and enrichment and pathways analyses were used to identify the signaling pathways associated with the DEMs. The receiver operating characteristic (ROC) analysis was employed to assess the diagnostic accuracy of a set of metabolites. We identified twenty DEMs, seven up- and thirteen downregulated in the DACD vs. DM group. Chemometric analysis revealed distinct clustering between the two groups. Metabolite set enrichment analysis found significant enrichment in various metabolite sets, including galactose metabolism, arginine and unsaturated fatty acid biosynthesis, citrate cycle, fructose and mannose, alanine, aspartate, and glutamate metabolism. Pathway analysis identified six significantly altered pathways, including arginine and unsaturated fatty acid biosynthesis, and the metabolism of the citrate cycle, alanine, aspartate, glutamate, a-linolenic acid, and glycerophospholipids. Classifier models with AUC-ROC > 90% were developed using individual metabolites or a combination of individual metabolites and metabolite ratios. Our study provides evidence of perturbations in multiple metabolic pathways in patients with DACD. The distinct DEMs identified in this study hold promise as diagnostic biomarkers for DACD patients.

Differences of serum glucose and lipid metabolism and immune parameters and blood metabolomics regarding the transition cows in the antepartum and postpartum period

This study aims to investigate differences in metabolism regarding the transition cows. Eight cows were selected for the test. Serum was collected on antepartum days 14th (ap14) and 7th (ap7) and postpartum days 1st (pp1), 7th (pp7), and 14th (pp14) to detect biochemical parameters. The experiment screened out differential metabolites in the antepartum (ap) and postpartum (pp) periods and combined with metabolic pathway analysis to study the relationship and role between metabolites and metabolic abnormalities. Results: (1) The glucose (Glu) levels in ap7 were significantly higher than the other groups (p < 0.01). The insulin (Ins) levels of ap7 were significantly higher than pp7 (p = 0.028) and pp14 (p < 0.01), and pp1 was also significantly higher than pp14 (p = 0.016). The insulin resistance (HOMA-IR) levels of ap7 were significantly higher than ap14, pp7, and pp14 (p < 0.01). The cholestenone (CHO) levels of ap14 and pp14 were significantly higher than pp1 (p < 0.01). The CHO levels of pp14 were significantly higher than pp7 (p < 0.01). The high density lipoprotein cholesterol (DHDL) levels of pp1 were significantly lower than ap14 (p = 0.04), pp7 (p < 0.01), and pp14 (p < 0.01), and pp14 was also significantly higher than ap14 and ap7 (p < 0.01). (2) The interferon-gamma (IFN-γ) and tumor necrosis factor α (TNF-α) levels of ap7 were significantly higher than pp1 and pp7 (p < 0.01); the immunoglobulin A (IgA) levels of pp1 were significantly higher than ap7 and pp7 (p < 0.01); the interleukin-4 (IL-4) levels of pp7 were significantly higher than ap7 and pp1 (p < 0.01), the interleukin-6 (IL-6) levels of ap7 and pp1 were significantly higher than pp7 (p < 0.01). (3) Metabolomics identified differential metabolites mainly involved in metabolic pathways, such as tryptophan metabolism, alpha-linolenic acid metabolism, tyrosine metabolism, and lysine degradation. The main relevant metabolism was concentrated in lipid and lipid-like molecules, organic heterocyclic compounds, organic acids, and their derivatives. The results displayed the metabolic changes in the transition period, which laid a foundation for further exploring the mechanism of metabolic abnormalities in dairy cows in the transition period.

A Review of Bile Acid Metabolism and Signaling in Cognitive Dysfunction-Related Diseases

Bile acids are commonly known as one of the vital metabolites derived from cholesterol. The role of bile acids in glycolipid metabolism and their mechanisms in liver and cholestatic diseases have been well studied. In addition, bile acids also serve as ligands of signal molecules such as FXR, TGR5, and S1PR2 to regulate some physiological processes in vivo. Recent studies have found that bile acids signaling may also play a critical role in the central nervous system. Evidence showed that some bile acids have exhibited neuroprotective effects in experimental animal models and clinical trials of many cognitive dysfunction-related diseases. Besides, alterations in bile acid metabolisms well as the expression of different bile acid receptors have been discovered as possible biomarkers for prognosis tools in multiple cognitive dysfunction-related diseases. This review summarizes biosynthesis and regulation of bile acids, receptor classification and characteristics, receptor agonists and signaling transduction, and recent findings in cognitive dysfunction-related diseases.

LC-MS-Based Untargeted Metabolomics Reveals Early Biomarkers in STZ-Induced Diabetic Rats With Cognitive Impairment

Diabetes in the elderly increases cognitive impairment, but the underlying mechanisms are still far from fully understood. A non-targeted metabolomics approach based on liquid chromatography-mass spectrometry (LC-MS) was performed to screen out the serum biomarkers of diabetic mild cognitive impairment (DMMCI) in rats. Total 48 SD rats were divided into three groups, Normal control (NC) group, high-fat diet (HFD) fed group and type 2 diabetes mellitus (T2DM) group. The T2DM rat model was induced by intraperitoneal administration of streptozotocin (STZ, 35 mg/kg) after 6 weeks of high-fat diet (HFD) feeding. Then each group was further divided into 4-week and 8-week subgroups, which were calculated from the time point of T2DM rat model establishment. The novel object recognition test (NORT) and the Morris water maze (MWM) method were used to evaluate the cognitive deficits in all groups. Compared to the NC-8w and HFD-8w groups, both NOR and MWM tests indicated significant cognitive dysfunction in the T2DM-8w group, which could be used as an animal model of DMMCI. Serum was ultimately collected from the inferior vena cava after laparotomy. Metabolic profiling analysis was conducted using ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) technology. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to verify the stability of the model. According to variable importance in the project (VIP > 1) and the p-value of t-test (P < 0.05) obtained by the OPLS-DA model, the metabolites with significant differences were screened out as potential biomarkers. In total, we identified 94 differentially expressed (44 up-regulated and 50 down-regulated) endogenous metabolites. The 10 top up-regulated and 10 top down-regulated potential biomarkers were screened according to the FDR significance. These biomarkers by pathway topology analysis were primarily involved in the metabolism of sphingolipid (SP) metabolism, tryptophan (Trp) metabolism, Glycerophospholipid (GP) metabolism, etc. Besides, SP metabolism, Trp metabolism and GP metabolism mainly belonging to the lipid metabolism showed marked perturbations over DMMCI and may contribute to the development of disease. Taken collectively, our results revealed that T2DM could cause cognitive impairment by affecting a variety of metabolic pathways especially lipid metabolism. Besides, serum PE, PC, L-Trp, and S1P may be used as the most critical biomarkers for the early diagnosis of DMMCI.

Diabetic Cognitive Dysfunction: From Bench to Clinic

Type 2 diabetes increases the risk of developing cognitive dysfunction in the elderly in the form of short-term memory and executive function impairment. Genetic and diet-induced models of type 2 diabetes further support this link, displaying deficits in working memory, learning, and memory performance. The risk factors for diabetic cognitive dysfunction include vascular disease, hypoglycaemia, hyperlipidaemia, adiposity, insulin resistance, lifestyle factors, and genetic factors. Using neuronal imaging technologies, diabetic patients with cognitive dysfunction show atrophy of the whole brain, particularly the grey matter, hippocampus and amygdala; increased volume of the ventricular and white matter; brain infarcts; impaired network integrity; abnormal microstructure; and reduced cerebral blood flow and amplitude of low-frequency fluctuations. The pathogenesis of type 2 diabetes with cognitive dysfunction involves hyperglycaemia, macrovascular and microvascular diseases, insulin resistance, inflammation, apoptosis, and disorders of neurotransmitters. Large clinical trials may offer further proof of biomarkers and risk factors for diabetic cognitive dysfunction. Advanced neuronal imaging technologies and novel disease animal models will assist in elucidating the precise pathogenesis and to provide better therapeutic interventions and treatment.

Parallel validation of a green-solvent extraction method and quantitative estimation of multi-mycotoxins in staple cereals using LC-MS/MS

In this study, 15 different mycotoxins were estimated in three staple cereals from selected agro-ecological regions in Nigeria using a 'novel' green extraction method, pressurized hot water extraction (PHWE) in comparison to a conventional solvent extraction method. Discrimination of the results of PHWE and solvent extraction using principal component analysis (PCA) and orthogonal projection to latent structures discriminate analysis (OPLS-DA) did not yield any differential clustering patterns. All maize samples (n = 16), 32% (n = 38) of sorghum and 35% (n = 37) of millet samples were positive for at least one of the 15 tested mycotoxins. Contamination levels for the cereals were higher in the warm humid rain forest region and gradually decreased towards the hot and arid region in the north of the country. The results demonstrate the applicability of PHWE as a possible alternative extraction method to conventional methods of extraction, which are solvent based.

Metabolomics-driven identification of perturbations in amino acid and sphingolipid metabolism as therapeutic targets in a rat model of anorexia nervosa disease using chemometric analysis and a multivariate analysis platform

It is important to explore novel therapeutic targets and develop an effective strategy for the treatment of anorexia nervosa. In this work, serum samples were analyzed using ultra-performance liquid chromatography coupled with quadrupole time-of flight mass spectrometry (UPLC/Q-TOF MS) coupled with chemometric analysis and multivariate analysis to obtain the metabolites and their corresponding pathways. In addition, knock-in and knock-down of the key enzyme in vivo was performed to verify the reliability of the obtained metabolic pathway, which is closely associated with the anorexia nervosa pathomechanism and the potential targets. There were significant differences in the biochemical parameters between the model group and the control group. A total of 26 potential biomarkers were identified to resolve the difference between the control and model rats, which were closely related to amino acid metabolism, sphingolipid metabolism, arachidonic acid metabolism, the citrate cycle, and so forth. According to the ingenuity pathway analysis, we further elucidated the relationship between the gene, protein, and metabolite alteration in anorexia nervosa, which are involved in cellular compromise, lipid metabolism, small molecule biochemistry, cell signaling, molecular transport, nucleic acid metabolism, cell morphology, cellular function and maintenance. Arginosuccinate synthetase (ASS) deficiency was accompanied by a significant downregulation of the β-endorphin and ghrelin in the animal models. The metabolites and pathways obtained using the metabolomics strategy may provide valuable information for the early treatment for anorexia nervosa.

It is important to explore novel therapeutic targets and develop an effective strategy for the treatment of anorexia nervosa.

Identification of disordered metabolic networks in postpartum dairy cows with left displacement of the abomasum through integrated metabolomics and pathway analyses

High-producing dairy cows are easily affected by left displacement of the abomasum (LDA) within 4 weeks postpartum. Although LDA is highly associated with metabolic disturbances, the related information on comprehensive metabolic changes, with the exception of some blood biochemical parameters, remains limited. In this study, the changes in plasma metabolites and in the metabolic profile of postpartum dairy cows with LDA were investigated through liquid chromatography coupled with quadrupole time of flight mass spectrometry (LC-Q/TOF-MS)-based metabolomics, and the metabolic networks related to LDA were constructed through metabolomics pathway analysis (MetPA). An obvious change in the metabolic profile was reflected by significant variations in 68 plasma metabolites in postpartum dairy cows with LDA, and these variations consequently altered 13 metabolic pathways (histidine metabolism, tyrosine metabolism, valine, leucine and isoleucine biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, arginine and proline metabolism, tryptophan metabolism, synthesis and degradation of ketone bodies, linoleic acid metabolism, arachidonic acid metabolism, citrate cycle, butanoate metabolism, vitamin B₆ metabolism and pyrimidine metabolism). This study shows that the more detailed information obtained by LC-Q/TOF-MS-based metabolomics and MetPA might contribute to a better understanding of the disordered metabolic networks in postpartum dairy cows with LDA.

Dysregulation of Δ4-3-oxosteroid 5β-reductase in diabetic patients: Implications and mechanisms

Aldo-keto reductase family 1 member D1 (AKR1D1) is a Δ⁴-3-oxosteroid 5β-reductase required for bile acid synthesis and steroid hormone metabolism. Both bile acids and steroid hormones, especially glucocorticoids, play important roles in regulating body metabolism and energy expenditure. Currently, our understanding on AKR1D1 regulation and its roles in metabolic diseases is limited. We found that AKR1D1 expression was markedly repressed in diabetic patients. Consistent with repressed AKR1D1 expression, hepatic bile acids were significantly reduced in diabetic patients. Mechanistic studies showed that activation of peroxisome proliferator-activated receptor-α (PPARα) transcriptionally down-regulated AKR1D1 expression in vitro in HepG2 cells and in vivo in mice. Consistently, PPARα signaling was enhanced in diabetic patients. In summary, dysregulation of AKR1D1 disrupted bile acid and steroid hormone homeostasis, which may contribute to the pathogenesis of diabetes. Restoring bile acid and steroid hormone homeostasis by modulating AKR1D1 expression may represent a new approach to develop therapies for diabetes.

Metabolomics and pathway analyses to characterize metabolic alterations in pregnant dairy cows on D 17 and D 45 after AI

Nutrient flow to the embryo and placenta is crucial for proper development and growth during pregnancy. In this study, a metabonomic analysis was undertaken to better understand global changes in pregnant dairy cows on D 17 and D 45 after timed artificial insemination (AI). Metabolic changes in the blood plasma of pregnant dairy cows were investigated using HPLC-MS and a multivariate statistical analysis. Changes in metabolic networks were established using the MetPA method. Alterations in six metabolic pathways were found on D 17 and D 45, including variations in the level of alpha-linolenic acid metabolism, glycerophospholipid metabolism, pentose and glucuronate interconversions, glycerolipid metabolism, folate biosynthesis, and tyrosine metabolism. In addition to these pathways, 9 metabolic pathways were markedly altered on D 45. These pathways included changes in the one-carbon pool caused by folate; phenylalanine, tyrosine and tryptophan biosynthesis; thiamine metabolism; pantothenate and CoA biosynthesis; purine metabolism; inositol phosphate metabolism; amino sugar and nucleotide sugar metabolism; pentose phosphate; and the TCA pathway. The combination of metabonomics and network methods used in this study generated rich biochemical insight into possible biological modules related to early pregnancy in dairy cows.

Impact of a cafeteria diet and daily physical training on the rat serum metabolome

Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS), which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST) or cafeteria diet (CAF) and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which moderate-intensity seems more effective than high-intensity training. Our results indicate that CAF has a strong negative impact on the metabolome of animals that is difficult to reverse by daily exercise.