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BackgroundDeep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.MethodsThe c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.FindingsThe application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).InterpretationOur results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.FundingThe specific funding of this article is provided in the acknowledgements section.

ObjectiveTo investigate the differences in postoperative short-term complications and long-term prognosis of pancreatic cancer(PC) patients after total pancreatectomy(TP) and pancreaticoduodenectomy(PD).MethodsClinical data of PC patients who underwent TP from January 2016 to December 2021(TP group) and PD from January 2019 to December 2021(PD group) at Peking Union Medical College Hospital were retrospectively collected. Patients in the PD group were divided into the pancreatic fistula(PF) high-risk PD group and the recurrence high-risk PD group according to risk factors. After propensity score matching, the differences in postoperative short-term surgical efficacy indicators(postoperative complication rate, 30 d mortality rate, length of hospital stay, etc.), long-term surgical efficacy indicators(overall survival), and quality of life were compared between the TP group and the PF high-risk PD group or the recurrence high-risk PD group.ResultsA total of 32 patients in the TP group and 114 patients in the PD group(99 patients in the PF high-risk PD group and 15 patients in the recurrence high-risk PD group) meeting the inclusion and exclusion criteria were enrolled.(1)TP group and PF high-risk PD group: after propensity score matching, 29 patients in the TP group and 56 patients in the PF high-risk PD group were finally included. There was no PF in the TP group, and the rate of PF in the PF high-risk PD group was 19.64%(P=0.027).There were no statistical differences in short-term surgical efficacy indicators such as other postoperative complication rates, Clavien-Dindo grading, length of stay, ICU stay, and 30 d mortality between the two groups(all P > 0.05). At the median follow-up time of 36 months, there was no significant difference in the quality of life questionnaire-core 30(QLQ-C30) scores between the two groups(P > 0.05).(2)TP group and recurrent high-risk PD group: Since there were no statistically significant differences between the baseline data of the two groups(P > 0.05), 32 patients in the TP group and 15 patients in the recurrent high-risk PD group were both included in the analysis. There was no PF in the TP group, and the rate of PF in the recurrent high-risk PD group was 20.00%(P=0.028).The other postoperative complication rates, Clavien- Dindo grading, length of hospital stay, ICU stay, 30 d mortality and other short-term surgical efficacy indicators were also not statistically different between the two groups(all P > 0.05). By the final follow-up, the median overall survival was longer in the TP group than the recurrent high-risk PD group(37.68 months vs. 15.24 months, HR=2.551, 95% CI: 1.144-5.689, P=0.018). Multifactorial Cox regression showed that recurrent high-risk PD and preoperative obstructive jaundice were independent risk factors in the poor long-term prognosis of patients with PC.ConclusionsFor PC patients at high risk of PF, TP can achieve short-term surgical outcomes and long-term quality of life comparable to PD with no burden of postoperative pancreatic fistula. For patients with high-risk recurrence, TP can significantly prolong the survival of PC patients while ensuring surgical safety.

The 2nd CASMS conference was held virtually through Gather. Town platform from October 17 to 21, 2022, with a total of 363 registrants including an outstanding and diverse group of scientists at the forefront of their research fields from both academia and industry worldwide, especially in the United States and China. The conference offered a 5-day agenda with an exciting scientific program consisting of two plenary lectures, 14 parallel symposia, and 4 special sessions in which a total of 97 invited speakers presented technological innovations and their applications in proteomics & biological mass spectrometry and metabo-lipidomics & pharmaceutical mass spectrometry. In addition, 18 invited speakers/panelists presented at 3 research-focused and 2 career development workshops. Moreover, 144 posters, 54 lightning talks, 5 sponsored workshops, and 14 exhibitions were presented, from which 20 posters and 8 lightning talks received presentation awards. Furthermore, the conference featured 1 MCP lectureship and 5 young investigator awardees for the first time to highlight outstanding mid-career and early-career rising stars in mass spectrometry from our society. The conference provided a unique scientific platform for young scientists (i.e., graduate students, postdocs and junior faculty/investigators) to present their research, meet with prominent scientists, and learn about career development and job opportunities (http://casms.org).

Dysregulation of sphingomyelin and ceramide metabolism have been implicated in Alzheimer's disease. Genome-wide and transcriptome-wide association studies have identified various genes and genetic variants in lipid metabolism that are associated with Alzheimer's disease. However, the molecular mechanisms of sphingomyelin and ceramide disruption remain to be determined. We focus on the sphingolipid pathway and carry out multi-omics analyses to identify central and peripheral metabolic changes in Alzheimer's patients, correlating them to imaging features. Our multi-omics approach is based on (a) 2114 human post-mortem brain transcriptomics to identify differentially expressed genes; (b) in silico metabolic flux analysis on context-specific metabolic networks identified differential reaction fluxes; (c) multimodal neuroimaging analysis on 1576 participants to associate genetic variants in sphingomyelin pathway with Alzheimer's disease pathogenesis; (d) plasma metabolomic and lipidomic analysis to identify associations of lipid species with dysregulation in Alzheimer's; and (e) metabolite genome-wide association studies to define receptors within the pathway as a potential drug target. We validate our hypothesis in amyloidogenic APP/PS1 mice and show prolonged exposure to fingolimod alleviated synaptic plasticity and cognitive impairment in mice. Our integrative multi-omics approach identifies potential targets in the sphingomyelin pathway and suggests modulators of S1P metabolism as possible candidates for Alzheimer's disease treatment.

BackgroundMajor depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions.MethodsUsing three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism.ResultsThe IMD clinical dimension and the inflammatory index were positively correlated (r = 0.19, p = 0.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids.ConclusionThe IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines-including arginine, proline, and methionine sulfoxide-were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (

We previously reported preliminary characterization of adipose tissue (AT) dysfunction through the adiponectin/leptin ratio (ALR) and fasting/postprandial (F/P) gene expression in subcutaneous (SQ) adipose tissue (AT) biopsies obtained from participants in the GEMM study, a precision medicine research project. Here we present integrative data replication of previous findings from an increased number of GEMM symptom-free (SF) adults (N = 124) to improve characterization of early biomarkers for cardiovascular (CV)/immunometabolic risk in SF adults with AT dysfunction. We achieved this goal by taking advantage of the rich set of GEMM F/P 5 h time course data and three tissue samples collected at the same time and frequency on each adult participant (F/P blood, biopsies of SQAT and skeletal muscle (SKM)). We classified them with the presence/absence of AT dysfunction: low (1) ALR. We also examined the presence of metabolically healthy (MH)/unhealthy (MUH) individuals through low-grade chronic subclinical inflammation (high sensitivity C-reactive protein (hsCRP)), whole body insulin sensitivity (Matsuda Index) and Metabolic Syndrome criteria in people with/without AT dysfunction. Molecular data directly measured from three tissues in a subset of participants allowed fine-scale multi-OMIC profiling of individual postprandial responses (RNA-seq in SKM and SQAT, miRNA from plasma exosomes and shotgun lipidomics in blood). Dynamic postprandial immunometabolic molecular endophenotypes were obtained to move towards a personalized, patient-defined medicine. This study offers an example of integrative translational research, which applies bench-to-bedside research to clinical medicine. Our F/P study design has the potential to characterize CV/immunometabolic early risk detection in support of precision medicine and discovery in SF individuals.

Objective To explore the role of establishing general surgical emergency team in improving the efficiency of emergency surgical treatment. Methods All patients attending emergency surgery from August1, 2019 to July 31, 2021 were retrospectively analysed. The number of flow, observation and their ratio before and after the establishment of general surgical emergency team were compared. The clinical data, including age, gender, complication, diagnoses, the number of surgery, the grading of disease, preoperative preparation time, the ratio of transfer to ICU, the ratio of patients staying more than 30 days, and complication rate before and after the establishment were analysed. Length of stay and hospitalization costs were compared by surgical grading and disease severity grading. The factors affecting hospitalization costs in emergency surgery patients were analysed using univariate and multiple linear regression. Results A total of 37 945 flow patients were included. Before and after the establishment of the surgical team, the number of flow was 15 745 and 22 200, respectively (1312 and 1850 monthly), the number of observation was 1814 and 1622, respectively (151 and 135 monthly), and the ratio of observation to flow decreased from 11.6% to 7.3% (P=0.000), preoperative preparation time decreased from (1.5±0.7) days to (0.7±0.9) days (P=0.000), the ratio of transfer to ICU decreased from 37.9% to 23.7% (P=0.000), the ratio of patients staying more than 30 days decreased from 5.7% to 0.5% (P=0.000), the average length of stay (5 d vs. 3 d, P=0.028) and cost (34 000 vs. 13 000, P=0.000) were significantly reduced, and the total operation number were 317 and 919, respectively(26 vs. 77 monthly, P=0.000).There was no significant change in complication rate (P=0.548). Multiple linear regression showed that establishing emergency surgery team reduced the hospitalization cost, while high surgical grading, long hospitalization time and transfer to ICU increased the hospitalization cost. Conclusion The establishment of emergency surgery team can solve the current problem of emergency to some degree, such as evacuating emergency congestion, increasing emergency surgery turnover rate, reducing the medical burden, and improving the efficiency of emergency treatment.

Late-onset Alzheimer's disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.

Interactions between macrophages and adipocytes are early molecular factors influencing adipose tissue (AT) dysfunction, resulting in high leptin, low adiponectin circulating levels and low-grade metaflammation, leading to insulin resistance (IR) with increased cardiovascular risk. We report the characterization of AT dysfunction through measurements of the adiponectin/leptin ratio (ALR), the adipo-insulin resistance index (Adipo-IRi), fasting/postprandial (F/P) immunometabolic phenotyping and direct F/P differential gene expression in AT biopsies obtained from symptom-free adults from the GEMM family study. AT dysfunction was evaluated through associations of the ALR with F/P insulin-glucose axis, lipid-lipoprotein metabolism, and inflammatory markers. A relevant pattern of negative associations between decreased ALR and markers of systemic low-grade metaflammation, HOMA, and postprandial cardiovascular risk hyperinsulinemic, triglyceride and GLP-1 curves was found. We also analysed their plasma non-coding microRNAs and shotgun lipidomics profiles finding trends that may reflect a pattern of adipose tissue dysfunction in the fed and fasted state. Direct gene differential expression data showed initial patterns of AT molecular signatures of key immunometabolic genes involved in AT expansion, angiogenic remodelling and immune cell migration. These data reinforce the central, early role of AT dysfunction at the molecular and systemic level in the pathogenesis of IR and immunometabolic disorders.

High-fat diet (HFD) causes renal lipotoxicity that is ameliorated with AMP-activated protein kinase (AMPK) activation. Although bioactive eicosanoids increase with HFD and are essential in regulation of renal disease, their role in the inflammatory response to HFD-induced kidney disease and their modulation by AMPK activation remain unexplored. In a mouse model, we explored the effects of HFD on eicosanoid synthesis and the role of AMPK activation in ameliorating these changes. We used targeted lipidomic profiling with quantitative MS to determine PUFA and eicosanoid content in kidneys, urine, and renal arterial and venous circulation. HFD increased phospholipase expression as well as the total and free pro-inflammatory arachidonic acid (AA) and anti-inflammatory DHA in kidneys. Consistent with the parent PUFA levels, the AA- and DHA-derived lipoxygenase (LOX), cytochrome P450, and nonenzymatic degradation (NE) metabolites increased in kidneys with HFD, while EPA-derived LOX and NE metabolites decreased. Conversely, treatment with 5-aminoimidazole-4-carboxamide-1-β-D-furanosyl 5'-monophosphate (AICAR), an AMPK activator, reduced the free AA and DHA content and the DHA-derived metabolites in kidney. Interestingly, kidney and circulating AA, AA metabolites, EPA-derived LOX, and NE metabolites are increased with HFD; whereas, DHA metabolites are increased in kidney in contrast to their decreased circulating levels with HFD. Together, these changes showcase HFD-induced pro- and anti-inflammatory eicosanoid dysregulation and highlight the role of AMPK in correcting HFD-induced dysregulated eicosanoid pathways.

IntroductionBile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer's disease (AD) including neuroinflammation and amyloid-β deposition.MethodSerum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n = 1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF) biomarkers, atrophy (magnetic resonance imaging), and brain glucose metabolism ([18F]FDG PET).ResultsOf 23 BAs and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1-42 ("A") and three with CSF p-tau181 ("T") (corrected P

IntroductionIncreasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut-brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD).MethodsSerum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for confounders and multiple testing.ResultsIn AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response-related genes implicated in AD showed associations with BA profiles.DiscussionWe report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut-liver-brain axis in the pathogenesis of AD.

Human blood is a self-regenerating lipid-rich biological fluid that is routinely collected in hospital settings. The inventory of lipid molecules found in blood plasma (plasma lipidome) offers insights into individual metabolism and physiology in health and disease. Disturbances in the plasma lipidome also occur in conditions that are not directly linked to lipid metabolism; therefore, plasma lipidomics based on MS is an emerging tool in an array of clinical diagnostics and disease management. However, challenges exist in the translation of such lipidomic data to clinical applications. These relate to the reproducibility, accuracy, and precision of lipid quantitation, study design, sample handling, and data sharing. This position paper emerged from a workshop that initiated a community-led process to elaborate and define a set of generally accepted guidelines for quantitative MS-based lipidomics of blood plasma or serum, with harmonization of data acquired on different instrumentation platforms across independent laboratories as an ultimate goal. We hope that other fields may benefit from and follow such a precedent.