The melanocortin receptor pan-agonist PL9643, a potential therapy for ocular diseases, was investigated in a phase 2, 12-week study in patients with dry eye disease (DED).This was a placebo-controlled study evaluating efficacy and safety of thrice-daily PL9643. Placebo (vehicle) was similar to tears. Primary endpoints were intra-patient changes in inferior corneal fluorescein staining and ocular discomfort after 12 weeks. Secondary endpoints were changes in additional DED signs or symptoms. Multiple secondary endpoints were not adjusted for multiplicity. Patients with moderate or severe DED were analyzed in addition to the overall intent-to-treat (ITT) population.n = 160) the PL9643 group did not demonstrate significant treatment difference versus placebo at week 12/day 85 for the primary endpoints (P > 0.05). In patients with moderate or severe DED (n = 53), PL9643 treatment demonstrated either nominally significant (P < 0.05) or trending (P < 0.1) improvement over placebo in mean change from baseline at week 12/day 85 in several sign endpoints, including fluorescein staining in inferior, superior, corneal sum, and total sum regions; Lissamine Green staining in temporal, nasal, conjunctival sum, and total sum regions; and tear film breakup time. Conjunctival redness also showed (nonsignificant) improvement at week 12/day 85. There were no drug-related adverse events (AEs) and no drug-related discontinuations.In the ITT population (PL9643 showed no significant efficacy for the ITT population; however, efficacy results across several signs and symptoms in the subpopulation of moderate to severe DED patients, the low number of ocular AEs, and no tolerability issues suggest that PL9643 shows promise as a therapeutic for DED.Clinical Trial Registration number: NCT04268069. MC2R binds only ACTH.1The melanocortins are a family of hormone agonists that include α-β-γ-melanocyte-stimulating hormones (MSH) and adrenocorticotropin hormone (ACTH).7 For example, treatments that increase α-MSH levels either systemically or locally induce the resolution of inflammation in experimental models of uveitis.8–10 The melanocortin pathway is also involved in other biological roles within the ocular system such as maintaining corneal transparency, sustaining the integrity and protection of the corneal epithelium, potentially improving donor corneal graft survival, regulating aqueous tear secretion, maintaining blood-retinal barriers, and controlling abnormal new vessel growth in the choroid and retina.7The melanocortin system is important in regulating immune activity in the eye as α-MSH, by binding to MC1R, MC3R, and MC5R receptors and, through its effect on macrophages, antigen presenting cells, and antigen-specific T cells, suppresses inflammation and promotes inflammatory resolution.11 Synthetic melanocortin agonists, in particular those targeting MC1R and MC5R, have the potential to treat ocular pathologies with similar or better efficacy than glucocorticoids, but with a better safety profile since they may have greater potency, improved pharmacokinetics, and distinct receptor affinities.11The melanocortin pathway is therefore a potentially attractive target for new, nonsteroidal alternatives for the treatment of inflammatory eye diseases such as dry eye disease (DED) and uveitis, in addition to treating diabetic retinopathy and it has a role in aiding successful corneal transplantation.13 Many physicians and patients often regard existing dry eye therapies as inadequate owing to poor response, adverse side effects, poor ocular tolerability, and prolonged interval preceding therapeutic activity.14–16 PL9643  is a synthetic MCR pan-agonist (not active at MC2R) that is currently being investigated as a treatment for inflammatory ocular diseases. Here we describe the results of a phase 2 efficacy and tolerability clinical trial of PL9643 in adults with DED.Dry eye is a multifactorial disease of the ocular surface characterized by a loss of homeostasis of the tear film, and accompanied by ocular symptoms, in which tear film instability and hyperosmolarity, ocular surface inflammation and damage, and neurosensory abnormalities play etiological roles.The protocol, its amendments, and all relevant forms were reviewed and approved by a properly constituted independent ethics committee or institutional review board. The study was performed in accordance with the ethical principles of the Declaration of Helsinki and International Conference on Harmonisation Good Clinical Practice guidelines. All local, state, and federal requirements relevant to the use of investigational agents were followed. All patients provided written consent to participate, and informed consent was obtained before any study-related procedures.This was a phase 2, multicenter, randomized, placebo-controlled, double-masked study that evaluated the efficacy and safety of PL9643 in patients with DED. The study explored a range of signs and symptoms of DED using sign and symptom measures commonly used in clinical trials for DED in those patients who were classified as having mild, moderate, or severe DED.®) model was used to provide a consistent regulated environmental setting to exacerbate the signs and symptoms of DED. The CAE model is a controlled environment specifically developed to standardize the assessment of the signs and symptoms of DED. It consists of a chamber containing a standardized atmosphere in which subjects sit. This atmosphere has low humidity and increased airflow, and the subject undergoes various constant visual tasks. This environment consistently exacerbates dry eye signs and symptoms, which can then be measured. The dry eye measures are assessed immediately before and after the 90-min challenge. This model has been used for a number of clinical trials for both dry eye and other eye diseases.17 Assessments of signs and symptoms before, during, and after this challenge provided data on the extent of damage to the ocular surface, the extent and timing of recovery from that damage, and the effect of treatment on baseline response to adverse stimuli. During screening, two 90-min exposures to the CAE were conducted to ascertain eligibility to enter the study.The controlled adverse environment  used in the active formulation without the PL9643 peptide. Anything less optimal than this vehicle  would cause tolerability issues with the vehicle-treated population which would make the study drug look artificially good in comparison.in vitro than at human MC1R, so the 1 μg/mL dose for PL9643 was chosen for humans to be on the higher side of effective concentrations in view of the lower potency of PL9643 .The dose of 1 μg/mL was derived from preclinical studies with the MCR pan agonist PL8331  which has similar efficacy to PL9643 in dry eye models. PL8331 showed optimal behavior at 0.1 μg/mL followed closely by 1.0 μg/mL. Activity for both agonists was lower at 10 μg/mL. PL8331 is 10 times more potent at mouse MC1R n = 9 PL9643, n = 9 placebo). On clinic visit days, dosing was done in the clinic after the post-CAE assessments, but before discharging the patient.Patients received single-use blow-fill-seal containers and were instructed to self-administer the ophthalmic solution bilaterally. Randomization was performed by an interactive web response system in which each qualifying patient was given a 4-digit randomization number at the end of baseline (day 1) visit. Patients, sponsor, and the contract research organization were all masked to treatment assignment. A CAE occurred at all visits , with pre-CAE, during CAE (symptoms only), and post-CAE assessments of ocular signs and symptoms . For somEnrolled patients were adults with mild, moderate, or severe DED. Major selection criteria are shown in The coprimary endpoints were the degree of inferior corneal fluorescein staining and ocular discomfort after 12 weeks (day 85) versus that shown at baseline (day 0), pre- to post-CAE change.® Corneal and Conjunctival Staining Scale ,18 a 5-point scale from 0 (no staining) to 4 (severe staining) with 0.5-U increments. Ocular discomfort was measured by the Ora Calibra Ocular Discomfort Scale20 which ranges from 0 to 4, in which 0 = no discomfort, 1 = intermittent awareness, 2 = constant awareness, 3 = intermittent discomfort, and 4 = constant discomfort.Corneal fluorescein staining was measured by the Ora CalibraSecondary efficacy measures were changes in additional signs and symptoms of dry eye at all visits . Eyes weVisual acuity was assessed pre-CAE at all visits . Slit-lamp evaluation was assessed at all visits both pre- and post-CAE. Intraocular pressure and dilated fundus examination was performed post-CAE at screening and week 12. Adverse events (AEs) were recorded throughout the study at all visits.This study was expected to enroll 75 patients in each of the 2 treatment arms, for a total of 150 randomized patients. Assuming a 10% dropout rate, 67 patients per group were expected to complete the study. Assuming a common standard deviation (SD) in the change from baseline for the pre-CAE to post-CAE change in inferior corneal fluorescein staining of 0.80 U, a sample size of 67 patients per treatment group could detect a mean difference of 0.39 U between the active treatment group and the placebo group at a significance level of 0.05 with 80% power. A sample size of 67 patients per treatment group could detect a mean difference of 0.49 U in the change from baseline for the pre-CAE ocular discomfort as assessed by the Ora Calibra Ocular Discomfort Scale with 80% power, assuming an SD of 1.00 U. The power for both the sign and symptom endpoints was 64%, assuming independence between the endpoints. Although sample size calculations were based on completed patients, primary analysis for sign and symptom primary endpoints were conducted on the ITT population using Markov chain Monte Carlo imputation.α = 0.05, should be viewed as informative. P values in the text are labeled as “nominal” P values to indicate that they are not corrected for multiplicity. All statistical tests were 2-sided with a significance level of 0.05 unless otherwise specified. Confidence intervals (CIs) for differences between treatment groups were 2-sided at 95% confidence. Statistical programming and analyses were performed using Statistical Analysis Software®  version 9.4.For each endpoint, change from baseline was calculated for each patient as week 12 (day 85) − baseline (day 1), such that a positive difference indicated a worsening of the dry eye sign or symptom. In addition, comparisons between active treatment and placebo were calculated as active −placebo, such that a negative result indicated a better score for the active treatment. Pre- to post-CAE change was calculated as post-CAE − pre-CAE. For the analysis of the endpoints, patients without a recorded value at the final day 85 visit had their observations imputed using Markov chain Monte Carlo imputation under the assumption of a missing-at-random mechanism using the ITT population. Inferior corneal fluorescein staining was summarized at week 12 pre-CAE to post-CAE change by treatment groups using continuous descriptive statistics. Analysis of the change from baseline used an analysis of covariance model adjusted for baseline inferior corneal fluorescein staining pre-CAE to post-CAE change and with treatment group as the explanatory variable. Changes from baseline for each treatment group in inferior corneal fluorescein staining were compared between 1 μg/mL PL9643 ophthalmic solution and placebo. Ocular discomfort was summarized at week 12 pre-CAE by treatment groups using continuous descriptive statistics. The type I error for secondary endpoints was not adjusted for multiplicity. Therefore, statistical significance for these endpoints, which was determined based on a 2-sided The study was started on February 15, 2020, and completed on October 5, 2020. A total of 160 patients were randomized: 80 in the PL9643 group and 80 in the placebo group. A total of 156 patients (97.5%) completed the study: 79 (98.8%) in the PL9643 group and 77 (96.3%) in the placebo group. A total of 4 patients (2.5%) were discontinued from this study: 1 (1.3%) in the PL9643 group and 3 (3.8%) in the placebo group . A patien = 53) and also on those with mild DED (n = 107). Baseline demographics of the patients with moderate and severe disease were balanced across the 2 groups. Median age was 69  years for the placebo group and 69.5  years for the PL9643 group. All patients had the same eye color reported for both their right eye and left eye. Patients in the overall population were exposed to study drug for a mean (SD) of 82.9 (7.69) days and a median exposure of 84 days . Mean (SD) exposure to study drug was similar between the overall treatment groups: 82.6 (7.6) days in placebo group and 83.2 (7.8) days in PL9643 group.The demographic and baseline characteristics of the entire enrolled population are shown in P = 0.4363) (P = 0.8360). For the secondary endpoints, the PL9643 group did not demonstrate a significant difference in mean change from baseline at any visit or time point compared to the placebo group in the ITT population with observed data.For the overall population of patients with mild to severe DED, for inferior corneal fluorescein staining the PL9643 group showed better improvement than the placebo group, but did not demonstrate a statistically significant difference in mean change from baseline at week 12 compared to the placebo group (pre-CAE to post-CAE) with a PL9643 versus placebo least squares (LS) mean (95% CI) change of −0.11  . There wpost hoc analysis of the moderate or severe dry eye subpopulation, in contrast to the ITT population, showed nominal statistical significance (P < 0.05 vs. placebo) at week 2 and 12 for multiple signs and symptoms of DED compared with the ophthalmic solution placebo.The P = 0.0097). PL9643 treatment also demonstrated an improvement in total corneal  fluorescein staining at week 12 with an LS mean (SE) change of −1.41 (0.284) compared with −0.48 (0.278) for placebo, an LS mean (SE) treatment difference of −0.93   with a LS mean (standard error [SE]) change of −0.92 (0.144) versus −0.38 (0.142), respectively, an LS mean treatment difference of −0.55  .P = 0.0977) and total sum of all 5 regions .In addition, PL9643 treatment demonstrated some improvement over placebo in mean change from baseline at week 12 in superior corneal and conjunctival fluorescein staining . PL9643 treatment also demonstrated a significant improvement in conjunctival sum  staining at week 12 with an LS mean (SEM) change of −0.56 (0.204) compared with +0.25 (0.199) for placebo, an LS mean (SEM) treatment difference of −0.81 . PL9643 treatment also demonstrated an improvement in conjunctival sum  staining at week 2 with an LS mean (SEM) change of −0.89 (0.223) compared with −0.22 (0.196) for placebo, an LS mean (SEM) treatment difference of −0.67  (P = 0.0533).PL9643 treatment demonstrated an improvement over placebo in mean change from baseline in nasal staining at week 12 (change from pre-CAE to post-CAE) with an LS mean (SE) change of −0.36 (0.124) versus +0.09 (0.121), respectively, an LS mean treatment difference of −0.45  . In addiPL9643 treatment showed no significant improvement over placebo at either week 2 or 12 for conjunctival redness post-CAE as measured by the Ora Calibra Conjunctival Redness Scale .P = 0.0137)  treatment difference of +0.41 (0.158) seconds  .P = 0.1302) in the moderate or severe dry eye subpopulation although these differences were not significant (P < 0.05) or a trend toward improvement over placebo in mean change from baseline. The LS mean change  from baseline at 20 min during the CAE challenge showed less discomfort versus placebo as did the 25-min difference . However, at the other measured time points, PL9643 scored showed no differences with nominal P values >0.05 from placebo.As measured by the Ora Calibra Ocular Discomfort Scale, which is geared toward measuring of frequency of discomfort, PL9643 treatment showed mean improvement over placebo at week 12 pre-CAE of −0.4 , although there was no important difference at week 12. Burning at week 2 showed a larger treatment difference in favor of PL9643, with a mean difference from placebo of −0.6 . Other symptoms measured by the questionnaire  all showed a numerically superior (but nonsignificant) difference compared with placebo throughout the duration of the study, except for grittiness at week 12 ; nominal  week 12 .PL9643 treatment showed nonsignificant numerical improvement over placebo in LS mean change from baseline at week 2 for the VAS symptoms of itching (−1), foreign body sensation (−5.1), eye discomfort (−7.4), and eye dryness (−4.5). The treatment effect of PL9643 was generally maintained throughout the study for symptoms of eye discomfort, eye dryness, and itching from week 2 to 12. The greatest LS mean treatment differences at week 12 were observed for pain (−4.7) and itching (−3.0) .The subgroup with mild disease showed no significant differences in mean change from baseline compared to placebo. Inferior corneal staining, total corneal staining, conjunctival redness, ocular discomfort, and eye discomfort all showed improvement with PL9634 administration, but none was superior to placebo. Mean tear film breakup time stayed level over the duration of the study but was not better than placebo at any visit.Drop comfort was assessed for each eye immediately and at 1 and 2 min following initial dosing using the Ora Calibra Drop Comfort Scale at baseline. Descriptions of drop comfort using the Ora Calibra Drop Comfort Scale were assessed at 3 min after initial dosing. On this questionnaire, patients were asked to choose 3 words that best described how each eye drop felt in both of their eyes. The positive responses were comfortable, cool, refreshing, smooth, and soothing. The negative responses included burning, filmy, stinging, sticky, thick, gritty, and irritating. Patients may have also selected “other” and written in a different response, which may have been either positive or a negative.n = 41 each [51.3%]), compared with 44 (55.0%) and 36 (45.0%) patients in the placebo group, respectively. The most common negative response in the PL9643 group was “irritating,” (n = 14 [17.5%]), compared with 10 (12.5%) patients in the placebo group.Responses to the Ora Calibra Drop Comfort Scale at baseline between the treatment groups were comparable, with 67 (83.8%) patients in the PL9643 group and 66 (82.5%) patients in the placebo group reporting ≥1 positive response and 31 (38.8%) patients in the PL9643 group and 29 (36.6%) patients in the placebo group reporting ≥1 negative response. The most common positive responses in the PL9643 group were “cool” and “refreshing” . The most common ocular TEAE was instillation site pain in a total of 5 (3.8%) patients: all 5 (6.3%) patients were in the placebo group. These incidences of instillation site pain were considered to be treatment-related  and trended toward significance in favor of fewer patients having pain in the PL9643 arm (P = 0.0586). One ocular TEAE of chalazion was reported in the PL9643 group. Nonocular TEAEs were reported by a total of 24 (15.0%) patients, 12 (15.0%) patients in the PL9643 group and 12 (15.0%) patients in the placebo group. The most frequent nonocular TEAEs were in the infections and infestation system organ class, experienced by 6 (3.8%) of patients overall, 2 (2.5%) in the placebo and 4 (5.0%) in the PL9643 groups. All other nonocular TEAEs were reported in less than 3% of patients.In the overall ITT/safety population , more patients experienced more AEs and more treatment-emergent AEs (TEAEs) in the placebo group than in the PL9643 group  . For a cA total of 3 (1.9%) patients reported 3 treatment-emergent serious AEs: 1 (1.3%) patient in the PL9643 group and 2 (2.5%) patients in the placebo group. The 2 serious AEs in the placebo group were classified as severe , and the serious AE in the single patient in the PL9643 group was reported as moderate (lung adenocarcinoma). No treatment-emergent serious AEs were considered related to the study drug. No clinically significant effects on visual acuity, slit-lamp biomicroscopy, intraocular pressure, or dilated fundoscopy by PL9643 were observed.This study investigated the effect of an ophthalmic solution of the melanocortin MCR pan-agonist PL9643 on patients with DED over a 12-week period. The study explored a range of signs and symptoms of DED using commonly used measures, including the use of the CAE model. The prospective hypothesis that, in the ITT population of patients with mild to severe DED, PL9643 treatment would show statistically superior efficacy to placebo (pre-CAE to post-CAE) in inferior corneal fluorescein staining and ocular discomfort at week 12 was not supported. The ITT PL9643 group also did not demonstrate a significant difference from the placebo group for the secondary endpoints.post hoc analysis subgroup of patients with moderate or severe DED , ophthalmic PL9643 treatment demonstrated either nominally significant (P < 0.05) or trending (P < 0.1) improvement over the active control of artificial tears in mean change from baseline at week 12/day 85 in several sign endpoints, including fluorescein staining in inferior, superior, corneal sum, and total sum regions; Lissamine Green staining in temporal, nasal, conjunctival sum, and total sum regions; and tear film breakup time. Conjunctival redness also showed improvement at week 12/day 85, although not statistically significant, in favor of PL9643. In the subgroup of patients with mild disease, the magnitude of the effect against the artificial tears placebo was not discernible.In the Responses to the Ora Calibra Drop Comfort Scale in the overall ITT population were comparable for the PL9643 group compared with the placebo group, and PL9643-treated patients experienced no AEs of pain on instillation, in contrast to the 3.1% observed in the placebo group. PL9643 was well tolerated, with a safety profile trending toward superiority over placebo in the ITT population. No treatment-emergent serious AEs were considered related to the study drug, and no patients in the PL9643 group withdrew from the study due to AEs. PL9643 also showed no effects on other aspects of vision .A major limitation of this study is that the results of the secondary endpoints have not been adjusted for multiplicity, so that changes in these endpoints are hypothesis generating only. Further studies with larger sample sizes will be able to address the statistical significance of these changes. The absence of significant improvements in the mild subpopulation may be a consequence of the small sample size. In the future, tests evaluating ocular surface inflammation such as matrix metalloproteinase 9 concentration (or other pro-inflammatory markers) in the tear film offer the potential to aid the evaluation of efficacy.n = 53), PL9643 achieved nominal statistical significance (P < 0.05 vs. placebo) at week 2 and 12 for multiple signs and symptoms of DED compared with the ophthalmic solution placebo. PL9643 demonstrated good ocular safety and tolerability with no drug-related AEs, no drug-related discontinuations, and with high ocular comfort. These hypothesis-generating efficacy results and lack of tolerability issues suggest that PL9643 could be a valuable option as a novel therapeutic for treating DED and supports its continued development.The purpose of our initial clinical investigation was to identify patients that had the greatest response to PL9643. Although we did not see statistical significance for the overall ITT population, we were able to identify a responsive subpopulation which could be valuable for future clinical studies. In the subpopulation of moderate to severe patients (


P < 0.05 in the univariate analysis were included in the multivariate regression analysis to investigate the relationship between different age groups and pCR.Breast cancer (BC) is currently the leading cause of death in women worldwide. Studies have confirmed that pregnancy is an independent factor affecting the survival of BC patients. BC found during pregnancy, lactation, or shortly after delivery is what we used to think of as pregnancy-associated breast cancer (PABC). The current expert definition of this concept is not uniform; however, there is growing evidence that postpartum breast cancer (PPBC) differs from other types of BC in terms of both biological features and prognosis, with a slightly different focus on diagnosis and treatment. With the increase of female reproductive age population and changes in fertility policies in China, patients with PPBC are receiving increasing attention. Here, we systematically analyzed the clinicopathological characteristics and chemotherapeutic response of patients with PPBC. We retrospectively analyzed the clinicopathological data, molecular subtypes, chemotherapy regimens, and pathological complete remission (pCR) rates of 1343 patients with non-metastatic BC at Harbin Medical University Cancer Hospital from January 1, 2012 to May 31, 2023. The categorical data were compared by chi-square test and Fisher exact test using logistic regression model. Predictor variables with (P < 0.05). In molecular typing, human epidermal growth factor receptor 2 (HER-2)-positive and triple-negative breast cancer (TNBC) were more frequent. In the entire cohort, HER-2 expression and delivery status were independent predictors of pCR rates in BC patients after neoadjuvant chemotherapy (NAC).A total of 714 patients were eligible for analysis in this study, and 667 patients had a history of pregnancy, 40 (5.6%) of whom were PPBC patients. When diagnosed with BC, patients with PPBC were younger, more likely to undergo breast-conserving surgery (BCS), and more likely to achieve pCR Our findings suggest that postpartum status is an independent predictor of pCR attainment in BC patients. PPBC is more sensitive to chemotherapy than other patients.We need to pay more attention to this group and achieve individualized treatment, which will help us treat BC better and provide new targets and blueprints for our clinical therapy. In recent years, the incidence of malignancies has been on the rise, and China has the highest annual incidence and mortality rate of malignancies in the world , and hollow needle biopsy of breast masses confirmed as BC, after communicating with the patients and their families and agreeing to NAC. Beforetreatment, the patients and their families were explained individual clinical and pathological information for clinical studies. The patient signed an informed consent regarding the medical history data and secondary use of the biospecimen. Patients underwent chemotherapy according to standard guidelines with a complete cycle of chemotherapy; surgical treatment was performed after completion of NAC, with mastectomy or breast-conserving surgery (BCS) depending on the patient's condition and wishes, and all patients underwent sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) if lymph nodes had metastasized.A total of 1343 patients were obtained for analysis, and detailed inclusion criteria included (1) female patients; (2) pathologically confirmed BC prior to chemotherapy; (3) all patients received NAC and completed treatment; (4) complete clinical and pathological data; (5) T1-T3 tumors as defined by the AJCC TNM staging system; and (6) patients underwent pathological IHC testing at the beginning and end of NAC. Exclusion criteria included (1) patients with incomplete data, (2) patients with multiple tumors, (3) patients with insufficient age at diagnosis and life status, (4) patients with occult BC, (5) male patients, and (6) patients with interrupted treatment or treatment at other hospitals. Finally, 714 patients who met this index were selected for analysis. This flow chart is shown in Fig. This research complies with the World Medical Association Declaration of Helsinki 1964 and subsequently amended versions. All of the patients signed an informed consent form before the treatment.Study variables included patient age, delivery history, surgical procedure, menopausal status, body mass index (BMI) value, lymphatic infiltration status, ER status, PR status, HER-2 status, KI67 expression, P53 expression, T-stage, N-stage, clinical stage, molecular subtype, chemotherapeutic drug type, pathological type, histological grade, and pCR status. Patient information and treatment details were recorded from the time of diagnosis. Patients were divided into three groups according to delivery: as follows: Nulliparous, PPBC, and Parous > 5 years. Patients with PPBC were diagnosed with BC within 5 years of pregnancy. Age was divided into two groups using 40 years as a cut-off. Surgical procedures were divided into mastectomy and BCS. Natural menopause was defined as patients with over 12 months of future menstruation or over 60 years of age. BMI values were stratified according to international health standards: thin, BMI < 18.5; normal, 18.5 ≤ BMI < 24; overweight, 24 ≤ BMI < 30, and obese BMI ≥ 30. IHC was used to detect the HR status of patients, and positive ER and PR expression was defined as 1% nuclear staining of tumor cells. HER-2 was positive when IHC stained 3 + and negative when IHC stained 0 or 1 + HER-2. When IHC stained 2 + , its status was detected by fluorescence in situ hybridization (FISH), and HER-2 was considered negative when Fish was negative. Otherwise, it is a positive one. KI67 refers to an anti-germin monoclonal antibody, a proliferating cell nuclear antigen associated with the tumor cell cycle, interpreted as the percentage of tumor cell nuclei between 400 and 500 cells. KI67 positive nuclear ≥ 15% was defined as high expression, < 15% as low expression. Clinical and imaging staging was performed in all patients. T-stage staging was determined by palpation and ancillary examinations. N-stage was defined as abnormal axillary lymph nodes or lymph nodes detected by ultrasound. Metastatic disease was assessed by imaging. We classify cancer molecular subtypes into four types: HR(+)/HER-2(+), HR(+)/HER-2(−), HR(−)/HER-2(+), and TNBC. Pathologists observe tumor sections and analyze pathological types, like IDC, ILC, etc. According to the pathological assessment after NAC of the Chinese Society of Clinical Oncology, the Miller & Payne system is currently used to evaluate primary lesions. This system mainly compares pre- and post-treatment surgical specimens.To assess the abundance of residual infiltrating tumor cells after NAC, specific interpretation criteria are divided into the following five levels: Grade 1 (G1): no change in infiltrating cancer cells or only a single cancer cell is changed, and there is no decrease in the number of tumor cells; Grade 2 (G2): mild decrease in infiltrating cancer cells, but the total number is still high, and the decrease does not exceed 30%; Grade 3 (G3): decrease in infiltrating cancer cells by 30–90%; Grade 4 (G4): decrease in infiltrating cancer cells by more than 90% and only small clusters or a few scattered single cancer cells remain; Grade 5 (G5): no infiltrating cancer cells at the original tumor bed site, but ductal carcinoma in situ (DCIS) may be present. G5 is used here as the study endpoint for this cohort.IHC is a globally accepted method for detecting ER and PR in BC. Pathologists or pathology assistants cut tumor and benign breast tissue samples. They were placed in the same container during the initial evaluation, thus ensuring that typical breast structures were used as subsequent controls. All study results were reviewed and confirmed by both pathologists. Pathological sections were 4 μm thick and specimens were embedded in paraffin and incubated with primary antibody, secondary antibody, and streptavidin in sequence.P < 0.05 was considered statistically significant. The nomogram was established based on clinicopathologic factors of BC patients. In addition, we analyzed the overall performance of the nomogram by plotting the receiver operating characteristic (ROC) curves and then calculating the AUC of the ROC curves with the aim of analyzing the overall performance of the nomogram, with the AUC exceeding 0.7 considered that the nomogram provided a reasonable estimation, and the above statistical analyses were performed by R4.1.0 software, including the car, rms, pROC, and rmda package.The data presented in this paper were analyzed using SPSS software version 26.0  and the data presented in this paper were stratified by pregnancy status. Categorical data were expressed as counts and percentages and continued to be compared and analyzed using chi-square tests and univariate logistic regression analysis for correlation of clinical case parameters with pCR rates within each subgroup. Statistically significant variables for univariate analysis were included in multivariate analysis. To determine which variables were independent predictors of pCR, P < 0.05). In this cohort, PPBC patients were younger than other types of patients. 33 patients (82.5%) were diagnosed with BC before the age of 40 years, so most patients were in premenopausal status, and menstrual status was strongly correlated with age. The probability of positive HER-2 expression was higher in PPBC patients (45%) than in controls, and 11 patients (27.5%) presented with TNBC, but it was not statistically significant. Among all known molecular subtypes of BC, TNBC had the worst prognosis. Most clinicopathological features did not differ significantly between groups regarding parity (P > 0.05). In the entire cohort, younger patients were more likely to undergo BCS, but the overall breast-conservation rate was not high, at 4.8%. This may be related to the prevailing treatment setting and patient mindset. 90.2% of patients received anthracycline chemotherapy, the majority were IDC (69.3%), and the most common molecular subtype was HR(+)/HER-2(–) (44.3%).From January 1, 2012, to May 31, 2023, 1343 patients diagnosed with BC were studied at Harbin Medical University Cancer Hospital, 629 patients were excluded , and a total of 714 were included in the study. A total of 667 BC patients had a history of pregnancy, 40 patients with PPBC, 627 BC patients with Parous > 5 years, and 40 unproductive patients. The clinicopathological characteristics and treatment are shown in Table P < 0.05) (Table P > 0.05). Patients with younger age, lower T- and N-stage, ER-negative, PR-negative, HER2-positive, high KI67 expression, and lower BC histological grade were more likely to achieve pCR.Among patients who delivered, 111 (16.6%) achieved pCR and 556 (83.4%) did not. The univariate analysis determined the factors affecting the pCR rate after NAC. Age, T stage, N stage, ER expression, PR expression, HER-2 expression, KI67 expression, histological grade, molecular subtype, clinical stage, type of pathology, and time of delivery were all strongly associated with pCR rate (P = 0.040). HER-2 positive patients were more likely to achieve pCR than negative ones . These two factors were statistically significant. Delivery status and HER-2 expression were strongly associated with the performance of PCR in BC patients (P < 0.05) and were independent predictors of achieving postoperative PCR . Logistic regression analysis showed that patients with PPBC were more likely to achieve PCR compared with those who had been in labor for more than 5 years . In addition, this study also found that when clinical T or N staging was high, and ER or PR expression was positive, patients were less likely to achieve pCR, with probabilities of 56.4%, 57.9%, 64.5%, and 63.6%, respectively, with statistically significant differences (P < 0.05) (Table P > 0.05).We used the ROC to predict the probability of obtaining pCR in BC patients Figs. , 4. The A nomogram based on clinicopathologic characteristics of BC patients was designed to predict the probability of reaching pCR when BC patients are NAC. Clinical T and N staging had the greatest impact on pCR, and pregnancy status also had a large impact, with PPBC patients more likely to reach pCR Fig. . To asseP < 0.001)  Fig. . patientP < 0.05).Clinical efficacy was evaluated according to the efficacy evaluation criteria of the solid tumor criteria (RECIST) version 1.1 Table . PartialP > 0.05). Only 55 of this group did not breastfeed their infants, and patients were categorized according to the duration of breastfeeding. When BC patients were breastfed for 13–24 months, patients were more likely to achieve pCR, and this correlation was significant (P < 0.05). In addition, the sensitivity to chemotherapy was similar in singleton and multiplex patients (P > 0.05).In the present study, we continued to analyze the effect of other reproductive histories on the pCR of BC patients Table . A totalP < 0.001), these data confirm the importance of the time of the start of the last delivery as a biomarker of NAC outcome in BC patients. When dealing with patients with PPBC, we should strongly recommend chemotherapy to patients and also need to study PPBC as a high-risk subset. By evaluating these factors, physicians can change the treatment decisions of BC patients and achieve appropriate individualized treatment.A total of 714 female patients with BC were selected for this study, of whom approximately 5.6% were patients with PPBC, similar to the epidemiological findings in China. This retrospective study analyzed the response of BC patients to NAC. We found that delivery status was an independent predictor of pCR rates after NAC in BC patients, that PPBC patients were younger at the time of BC diagnosis, that most patients were in an unmenopausal state, had a more significant proportion of the TNBC phenotype, and were more sensitive to chemotherapy than other groups (37.5% vs. 15.3%, Globally, cancer is a growing pregnancy complication, mainly due to the increasing age of women at childbirth (Eastwood-Wilshere et al. PPBC remains an under-recognized high-risk BC group, and the age of BC diagnosis is now gradually becoming younger, with a large proportion of patients diagnosed with BC under 45 years of age being PPBC, probably because younger BC patients are more likely to accept becoming mothers after cancer treatment (Colleoni et al. PPBC is an aggressive subtype characterized by a unique genetic profile, and PPBC affects women far beyond their last pregnancy. There are many potential mechanisms for the poor survival of PPBC patients, most notably the degenerative process of the mammary gland after delivery. Martinson found that changes in the mammary gland after weaning in mice increased tumor growth, invasion, and metastasis persisted for a long time. These changes persisted for a long time (Martinson et al. It has also been shown that most PPBC is in an intermediate to advanced stage due to a delay in diagnosis (Ishida et al. However, some experts have suggested otherwise, and Amant found that patients diagnosed with BC during pregnancy do not have an increased risk of metastasis and death. Patients with PABC have similar OS to non-pregnant patients (Amant et al. In this study, we continued to analyze the effect of breastfeeding and miscarriage on pCR in BC patients. Miscarriage does not affect the sensitivity of chemotherapy in BC patients. In 1980, experts concluded that there was a close association between miscarriage and BC, with undifferentiated mammary cells and fully differentiated cells in menstruating women, and that women who experienced miscarriage were likely to be partially differentiated and more susceptible to carcinogens (Braüner et al. Our study still has many limitations. First, this is a single-center study with inevitable selection bias, which may not fully represent the entire Chinese population, and subtle differences may not be detected due to the limited number of cases.Secondly, there is no survival analysis in this study. The prognosis of patients is still the most critical endpoint of the study. In the subsequent study, we need continuous postoperative follow-up. Nevertheless, this study is also a rare study of the NAC response to pregnancy in BC patients in Asian countries. It allows us to better focus on this category of patients and make treatment choices, but we also need further research to confirm our findings and explore the biological background behind it.In conclusion, different pregnancy statuses were independent predictors of achieving pCR after BC patients received NAC, and PPBC patients were likelier to achieve pCR than other patients. In previous studies, PPBC was often classified as PABC, hiding its biological characteristics. As a specific group, doctors need to analyze the biological factors of PPBC in more detail, and governments should develop additional policies to help patients achieve precise individualized treatment.


Ka/Ks values of most protein-coding genes were far smaller than 1, indicating that these genes were evolving under purifying selection. Phylogenetic relationships between the family Chironomidae were reconstructed using 23 species representing six subfamilies, based on protein-coding genes and rRNAs using Bayesian Inference and Maximum Likelihood. Our results suggested the following relationship within the Chironomidae: (Podonominae + Tanypodinae) + (Diamesinae + (Prodiamesinae + (Orthocladiinae + Chironominae))). This study contributes to the mitogenomic database of Chironomidae, which will be significant for studing the mitogenome evolution of Chironomidae.The family Chironomidae is represented by seven subfamilies in China, among which Chironominae and Orthocladiinae are the most diverse. To gain a better understanding of the architecture and evolution of the mitogenomes of Chironomidae, we sequenced mitogenomes of twelve species (including two published species) of the two subfamilies Chironominae and Orthocladiinae, and comparative mitogenomic analyses were performed. Thus, we identified highly conserved genome organization of twelve species with regard to genome content, nucleotide and amino acid composition, codon usage, and gene characteristics. The  Unlike the nuclear genome, mitogenomes are typically inherited maternally, they occur at hundreds to thousands of copies per cell5, and they exhibit very little recombination in animals7. Furthermore, the comparison of animal mitochondrial gene arrangements has become a powerful means for inferring long-term evolutionary relationships as rearrangements appear to be unique and generally rare events that are unlikely to arise independently in separate evolutionary lineages1.The mitochondrial genome of animals is generally a small (15–20 kb) and comprises 37 genes, i.e., 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), the large and small ribosomal RNA unit genes . There is typically also a single large non-coding region which contains controlling elements for replication and transcription, and various spacer and overlapping regions occur in the mitochondrial genome8. The study of the systematic evolution of Chironomidae was initially based on morphology10, however, modern molecular genetics has further resolved taxonomic diversity and phylogenetics, mainly through genetic markers including mitochondrial sequences16. In addition, the Chironomidae are a large group of Diptera insects, with more than 6300 known species, however, only few complete Chironomidae mitogenomes have been published so far26. Previous studies primarily provide descriptions of single mitochondrial genomes or comparative analyses of mitogenomes within genera or among subfamilies. However, there are few mitogenomes and comparative studies of the most diverse subfamilies Orthocladiinae and Chironominae. In addition, some controversies remain with regard to the phylogenetic relationships within the Chironomidae.Chironomids (Diptera: Chironomidae) are important aquatic insects, and they are widely distributed in all biogeographic regions of the world. Further, chironomid larvae are commonly used bioindicators of freshwater ecosystemsPropsilocerus from Orthocladiinae to Prodiamesinae.In this study, we present novel insights into the phylogenetic relationships between different Chironomidae subfamilies. Furthermore, we performed comparative analyses of mitogenome structure, base composition, and evolutionary rates among twelve species representing the subfamilies Orthocladiinae and Chironominae. Using previously published mitogenomes of the subfamilies Prodiamesinae, Podonominae, Tanypodinae, and Diamesinae, we employed mitochondrial genes isolated from complete mitogenomes to explore the phylogeny of Chironomidae. Further, we evaluate the monophyly of Orthocladiinae and propose to transfer the genus Chironomus nipponensis23 and Polypedilum nubifer24). Furthermore, 11 previously published Chironomidae mitochondrial genome sequences were retrieved from NCBI Genbank. In total, 23 Chironomidae species were used as ingroups, including 12 of which were Chironominae, 5 Orthocladiinae, 3 Prodiamesinae, 1 Podonominae, 1 Tanypodinae, and 1 Diamesinae. Collection information and accession numbers of all specimens are shown in Appendix 28. All specimens sequenced for this study were deposited in College of Biology and Agricultural Resources, Huanggang Normal University, Hubei Province, China. Genomic DNA was extracted from three to five adult specimens pooled in one centrifuge tube using the TIANamp Micro DNA Kit , according to the manufacturer’s instructions.We included ten previously unpublished Chironomidae mitogenomes and two published completed mitogenomes . Adapter sequences were removed using Trimmomatic v0.3029, and approximately 2 Gb clean data were retained per library after trimming. The original sequences were filtered to obtain high-quality clean sequences which were then assembled using spades v.3.11.130 and Getorganells31.Paired-end sequencing libraries with an insert size of 350 bp were constructed from purified DNA extracts according to a standard protocol for Illumina DNA library construction. Sequencing was carried out using an Illumina NovaSeq 6000 platform  by a commercial service provider . A quality assessment of raw FASTQ files of the two libraries was carried using FastQC v0.11.8 (32 and ORF finder (https://www.ncbi.nlm.nih.gov/orffinder/) were used for annotation of PCGs and ribosomal RNA (rRNA) genes. Then, NCBI Blastp and Blastn  were applied to compare PCGs and rRNA genes of mitogenomes of related species reported previously. ARWEN1.233 (http://mbio-serv2.mbioekol.lu.se/ARWEN/) and tRNAscan-SE 2.034 were used to annotate tRNAs.After assembly, MITOS35. MEGA X36 and Codonw 1.4.4 were used for statistical analyses of base composition, codon usage, and relative synonymous codon usage (RSCU). MISA38 was used for the detection of simple sequence repeats (SSRs) throughout the genomes. DnaSP 6.12.0339 was used for the analysis of non-synonymous substitution rates (Ka) and synonymous substitution rates (Ks). Nucleotide composition bias was calculated according to the AT-skew = (A−T)/(A+T) and GC-skew = (G−C)/(G+C), as previously reported40. The AT-Skew and GC-Skew data were normalized for visualization using R (package pheatmap).Mitogenome maps were produced using CG View server 1.041 with several plug-in programs: the first procedure is to standardize synonymous gene names and identify problematic annotation features, followed by sequence extraction; thereafter, nucleotide and amino acid sequences of genes were individually aligned using Mafft v7.40742 with the normal alignment mode and trimmed using Gblocks v0.9143 with default settings to remove ambiguously aligned regions. Alignments of 13 PCGs and 2 rRNAs were then concatenated into a supermatrix with the function ‘concatenate sequences’, additionally, this function can record the index of each gene during concatenation and generate a partition file, which can be used in the PartitionFinder software. Then, PartitionFinder244 selected best-fit partitioning schemes and models for the concatenated sequences based on the AICc criterion. Maximum likelihood (ML) analyses using partition mode were performed using IQ-TREE 1.6.845, bootstrapping using ultrafast46, and the nodal support values were calculated with 5000 bootstrap replicates. Bayesian inference (BI) analysis was performed using MrBayes 3.2.647 with the partition models. Markov chain Monte Carlo runs of 200,000 generations were conducted, and trees were sampled every 1000 generations with the first 25% of the trees discarded as burn-in. Anopheles quadrimaculatus (NCBI accession NC000875), Wyeomyia confusa (MK575492), Simulium variegatum (NC033348), Simulium maculatum (NC040120), Forcipomyia sp. (MK000395), and Culicoides arakawae (NC009809) were used as outgroups. Tree topology was visualized using iTOL48.Phylogenetic analyses were performed in Bayesian Inference and Maximum Likelihood using all PCGs and rRNA genes in PhyloSuiteChironomus kiiensis, Chironomus nipponensis, Chironomus plumosus, Dicrotendipes pelochloris, Dicrotendipes sp., Einfeldia sp., Glyptotendipes tokunagai, Limnophyes sp., Nilodorum tainanus, Polypedilum nubifer, Smittia aterrima, and Tanytarsus formosanus) were similar to those of other chironomids reported previously  to 99.14% (Einfeldia sp.), whereas the first and the second codon positions of PCGs had the lowest A + T content, varying from 66.77 to 71.01%. With regard to complete mitogenomes, the AT-skew values were positive, varying from 0.010 (Einfeldia sp.) to 0.057 (Polypedilum nubifer), whereas GC-skew values were negative in all species, varying from − 0.257 (Polypedilum nubifer) to − 0.147 (Limnophyes sp.) . Trinucleotide repeats occurred only in Nilodorum tainanus and Smittia aterrima. The single nucleotide was repetitive for A/T, and the dinucleotide repeated only AT/TA types. Trinucleotide repeats showed only ATT repeated, and no CG/GC types were detected. All SSRs contained high ratios of A or T bases.Analysis using MISAnad), 3 were cytochrome c oxidase subunit genes (cox), 2 were ATP synthase subunit genes (atp), and 1 was a cytochrome b gene (cytb). The total length of PCGs ranged from 11,106 to 11,220 bp, and the A + T content in this region ranged from 72.55 to 76.54%. The A + T content of the third codon position (82.32–91.98%) was higher compared to that of the first (67.58–71.01%) and second codons (66.77–68.33%)  were observed Fig. . Among snad4 gene terminated with TAA or TAG, other genes terminated with TAA (Appendix nad5 gene was the longest (1600–1800 bp), followed by the coxI gene (1500–1600 bp), and the ATP8 gene was the shortest (< 200 bp).Additionally, there were two types of stop codon: TAA and TAG. The Appendix . The lenAppendix , of whicThe total number of codons ranged from 3702 to 3740 in the 13 protein-coding genes excluding the stop codons Table . The 12 a/Ks (ω) was used to investigate the evolutionary rates of mitochondrial PCGs  were all below 1.0, indicating a strong repair mechanism against deleterious mutations in most PCGs. However, the Ka/Ks ratio differed significantly among individual genes, implying that the region comprised varying functional constraints. The Ka/Ks value of nad5 was the highest, implying the least purifying selective pressure. coxI exhibited the lowest Ka/Ks value, indicating the strongest purifying selective pressure.The ratio of KCGs Fig. . The resLimnophyes sp.) to 81.11% (Polypedilum nubifer). All tRNAs exhibited positive AT-skew and positive GC-skew  Appendix . The AT trnV and the control region and between trnL1 and trnV, respectively. The length of the rrnL genes ranged from 1299 to 1430 bp, and that of the rrnS genes ranged from 785 to 837 bp (Appendix Smittia aterrima) to 84.32% (Polypedilum nubifer), and that of the 16S rRNA genes ranged from 83.76% (Smittia aterrima) to 85.67% (Polypedilum nubifer). The 12S rRNA genes exhibited negative a AT-skew in Dicrotendipes sp., Limnophyes sp., Polypedilum nubifer, and Tanytarsus formosanus and a positive AT-skew in the other species. The 16S rRNA genes showed a positive AT-skew in Einfeldia sp., Nilodorum tainanus, and Tanytarsus formosanus and a negative AT-skew in the other species. The 12S rRNA genes exhibited a positive GC-skew in all 12 mitogenomes. The 16S rRNA genes showed a negative GC-skew in Tanytarsus formosanus and a positive GC-skew in the other mitogenomes  to 682 bp (Dicrotendipes pelochloris), and it was located between rrnS and trnI. Its size can impact replication efficiency, and in some cases, smaller control regions may enhance replication efficiency by reducing the time required for the replication machinery to unwind the DNA and initiate replication. Analyses of the control region showed that the proportions of A, T, G, and C were 36.76–48.80%, 47.79–60.29%, 0.48–2.63%, and 0–2.67%, respectively. The control region showed a positive AT-skew in Nilodorum tainanus, Polypedilum nubifer and Tanytarsus formosanus and a negative AT-skew in the other species. The control region exhibited a negative GC-skew in Dicrotendipes sp., Glyptotendipes tokunagai, Limnophyes sp., Nilodorum tainanus, Smittia aterrima, and Tanytarsus formosanus and a positive GC-skew in the other species  as sister groups to the remaining taxa. Diamesinae  was a sister clade to Prodiamesinae + (Orthocladiinae + Chironominae). Prodiamesinae  was a sister group to Orthocladiinae + Chironominae. In the present study, the mitogenomic data used to explore the phylogenetic relationships of six subfamilies within the Chironomidae generally showed consistent trends with traditional morphology-based systematicsAT-skew values were positive, while the GC-skew values were negative in all species, which is in line with the mitochondrial genomes of most insects contained more A than T, while G content was lower than that of C. SSRs mainly comprised mono-, di-, and trinucleotide repeats, with a high proportion of A or T bases. In terms of codon usage in this study, the relative frequency of synonymous codon usage showed that codons ending in A/U were more frequent than those ending in G/C, which was consistent with the high AT characteristics of insect mitochondrial genomes.In the PCGs of 12 mitogenomes, the A + T content of the third codon position was markedly higher than those of the first and second positions, as in the published mitogenomes of other Chironomidae. For the whole mitogenomes, the a/Ks ratio of all genes (except nad5) was < 1, indicating mainly the purification selection of PCGs. The nad5 was the largest among the 13 PCGs, but it is rarely used in the phylogeny of Chironomidae, likely owing to its rapid rate of evolution. The coxI gene was the second-longest, and its Ka/Ks value was the lowest; therefore, it provides the strongest and the most conserved effective phylogenetic and evolutionary signals among all genes, and it is frequently used as a key barcode marker to identify species and determine inter-species differences. In general, different Ka/Ks values reflected that genes were subjected to different degrees of purification selection.In the mitochondrial evolution rate analysis of the current study, the KPropsilocerus is transferred to the Prodiamesinae subfamily, all six subfamilies are monophyletic. The phylogenetic relationship of the six subfamilies is thus (Podonominae + Tanypodinae) + (Diamesinae + (Prodiamesinae + (Orthocladiinae + Chironominae))). Obtaining more data on the mitochondrial genome of Chironomidae will provide important support for research on the phylogenetic relationship of Chironomidae.According to the phylogenetic results, the basic branches of Chironomidae included the subfamilies Podonominae and Tanypodinae. When Supplementary Information 1.Supplementary Information 2.Supplementary Figure S1.Supplementary Figure Legend.


A multi-class classification model for acute coronary syndrome (ACS) remains to be constructed based on multi-fluid metabolomics. Major confounders may exert spurious effects on the relationship between metabolism and ACS. The study aims to identify an independent biomarker panel for the multiclassification of HC, UA, and AMI by integrating serum and urinary metabolomics. We performed a liquid chromatography-tandem mass spectrometry (LC–MS/MS)-based metabolomics study on 300 serum and urine samples from 44 patients with unstable angina (UA), 77 with acute myocardial infarction (AMI), and 29 healthy controls (HC). Multinomial machine learning approaches, including multinomial adaptive least absolute shrinkage and selection operator (LASSO) regression and random forest (RF), and assessment of the confounders were applied to integrate a multi-class classification biomarker panel for HC, UA and AMI. Different metabolic landscapes were portrayed during the transition from HC to UA and then to AMI. Glycerophospholipid metabolism and arginine biosynthesis were predominant during the progression from HC to UA and then to AMI. The multiclass metabolic diagnostic model (MDM) dependent on ACS, including 2-ketobutyric acid, LysoPC), argininosuccinic acid, and cyclic GMP, demarcated HC, UA, and AMI, providing a C-index of 0.84 (HC vs. UA), 0.98 (HC vs. AMI), and 0.89 (UA vs. AMI). The diagnostic value of MDM largely derives from the contribution of 2-ketobutyric acid, and LysoPC) in serum. Higher 2-ketobutyric acid and cyclic GMP levels were positively correlated with ACS risk and atherosclerosis plaque burden, while LysoPC) and argininosuccinic acid showed the reverse relationship. An independent multiclass biomarker panel for HC, UA, and AMI was constructed using the multinomial machine learning methods based on serum and urinary metabolite signatures. The thrombus is usually incomplete and dynamic or even absent in UA, whereas it is primarily occlusive and sustained in AMI, mainly caused by plaque rupture3. The formation and progression of atherosclerotic plaque is a complex process associated with atherosclerotic cardiovascular disease (ASCVD) events4. Perturbations in cardiac glucose, amino acid, and fatty acid metabolism are contributors to coronary atherosclerotic plaque and ACS pathologies5. Based on the different characteristics of plaque and clinical outcomes in different types of ACS, we speculate that UA and AMI exhibit specific small-molecule metabolite variations.ACS, including UA and AMI, will occur as a result of a luminal thrombus or a sudden hemorrhage imposed on an atherosclerotic plaque6. Metabolic phenotypes could be widely varied by gender, age, diet, physical activities, and other multifaceted factors9. Furthermore, these exogenous or endogenous confounders might exert some of their pathogenic effect on ACS via modification of the small metabolites10. Ultimately, the genuine disease signatures might be obscured or even masked by these confounders11. Therefore, in order to explore the genuine relationship between metabolites and ACS, some researchers call for adjustments for confounders that influence the host metabolome12. However, in the real-world recognition and classification problems, it is a tremendous challenge or even impossible to completely isolate confounders and disease-related metabolic features under the complex context of the human body.As a metabolism-related and multifactorial disease, ACS involves a complex interplay among aging, sex, weight, lifestyle, comorbidities, and adverse environmental exposures16. For recapitulating plaque formation, growth and rupture, researchers explored the plasma metabolomes of individuals with normal coronary artery (NCA), nonobstructive coronary atherosclerosis (NOCA), stable angina (SA), UA, and AMI15. Using a similar study design, the later report showed that N-acetyl-L-neuraminic acid (Neu5Ac) acted as a trigger for myocardial injury and accumulated progressively as CAD progressed13. Another two studies revealed that both the gut microbiota and metabolites changed significantly as CAD progressed, and a combined biomarker set may distinguish stable coronary artery disease (SCAD) from ACS16. These metabolome analyses paid scant attention to major confounders of study outcomes, such as age, gender, and co-morbid conditions18. In order to identify genuine disease-specific metabolome variance, the assessment and adjustment of the confounders are crucial for eliminating possible spurious effects on metabolism20.The detailed small-molecule mechanism of the formation and progression of coronary atherosclerotic plaques in different types of ACS has not been uniformly concluded yet. The present studies are focused on the underlying small molecular activities and novel metabolic biomarkers related to the progression and severity of coronary artery disease (CAD)16. Compared with binary classification (N = 2), multiclass omics is more intrinsically challenging in obtaining stable biomarkers22. Although machine learning (ML) is widely used in metabolome classification, few ML algorithms are applied to construct multiclassification metabolomics models23. In order to convert the multiclassification into a binary classification, previous metabolomics studies on multiclassification of CAD usually conducted the multiple cross-comparisons based on hypothesis testing and then used binary classification ML approaches to obtain a classification model16. For instance, LASSO regression usually failed to be used as a multinomial classifier in previous ACS metabolomic investigations25. The multiclass metabolomics model for ACS and multinomial ML is lacking. A novel multiclass classification model for UA, AMI, and healthy controls using multinomial ML techniques is necessary.Additionally, the studies mentioned above are multiclassification (N > 2) metabolomics studies that require us to map subjects into multiple categoriesIn this study, we analyzed the serum and urine metabolic profiles from the 300 samples of the 150 participants through ultra-high liquid chromatography-tandem mass spectrometry (LC–MS/MS). Then, by performing the multinomial adaptive LASSO regression and RF classifier for multiclassification and adjusting for confounding factors, we developed a multiclass metabolite-based model that demarcated individuals with HC, UA or AMI. Our work may provide a power assist for metabolites to achieve early clinical translational applications for ACS.26. The diagnostic criteria for AMI need to be met by detecting the increase and/or decrease of cardiac biomarkers, preferably high sensitivity cardiac troponin (hs-cTn) T or I, with at least one value higher than the 99th percentile of the reference upper limit, and at least one of the following must be met: a. Symptoms of myocardial ischaemia; b. New ischemic ECG changes; c. Development of pathological Q waves on ECG; d. Imaging evidence of loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology; e. Intracoronary thrombus detected on angiography or autopsy26. Subjects who showed no stenosis were regarded as healthy controls. Those with malignant tumors, autoimmune disorders, infectious diseases, and severe renal dysfunction with creatinine > 3.0 mg/dl were excluded. The Ethics Review Committee of the General Hospital of Ningxia Medical University authorized this study, which followed the Declaration of Helsinki’s guidelines. Written informed consent was received from all the participants before the study launched.The graphical abstract of this study is illustrated in Supplemental Fig. We performed power analysis using MetaboAnalyst 5.0. The power reaches an acceptable level (0.8) at a sample size of approximately 120 . The SYNTAX score II  was computed by the SYNTAX score I, unprotected left main CAD; other clinical variables included age, sex, left ventricular ejection fraction, creatinine clearance, chronic obstructive pulmonary disease, and peripheral vascular disease. The modified Gensini scores take the severity score, the region multiplying factor, and the collaterals with the severity score adjustment factor into consideration28.The SYNTAX score and modified Gensini score were applied to evaluate the severity of ACS. The SYNTAX score was used to grade the complexity of coronary lesions31. Paired morning whole blood and urine samples were collected from all subjects before CAG and centrifuged at 3000 rpm for 10 min at 4 °C. Serum and the urine supernatant were kept and aliquoted, respectively, and then stored at − 80 °C immediately for metabolic analysis. For the metabolite extraction, 50 μL of the samples were transferred to an Eppendorf tube. After the addition of 200 μL extract solution , the samples were vortexed for 30 s, sonicated for 10 min in an ice-water bath, and incubated for 1 h at − 40 °C to precipitate proteins. Then the samples were centrifuged at 12,000 rpm  for 15 min at 4 °C. The resulting supernatants were transferred to a fresh glass vial for analysis. The quality control (QC) samples were prepared by mixing an equal aliquot of the supernatants from all of the samples. One QC sample was inserted in every 10 test samples to monitor the repeatability of the analysis process.The metabolomics workflow complies with the published guidelinesA UHPLC system  with a UHPLC BEH Amide column  coupled to QE HFX MS  was performed in both positive and negative ionization modes. A mixture of 25 mmol/L ammonium acetate and 25 mmol/L ammonia hydroxide in water (pH = 9.75) (A) and acetonitrile (B) made up the mobile phase. The auto-sampler temperature was 4 °C, and the injection volume was 2 μL. For its capacity to acquire MS/MS spectra in information-dependent acquisition (IDA) mode under the supervision of the acquisition software , the QE HFX mass spectrometer was utilized. The acquisition software continuously assessed the full scan MS spectrum in this mode. The ESI source criteria were established: the capillary temperature was 350 °C, the sheath gas flow rate was 30 Arb, the auxiliary gas flow rate was 25 Arb, the full MS resolution was 60,000, the MS/MS resolution was 7500, the collision energy was 10/30/60 in NCE mode, and the spray voltage was either 3.6 kV (positive) or − 3.2 kV (negative), as appropriate.31. In this study, the internal standard of relative standard deviation (RSD) in QC samples was ≤ 15% (median), which represents high data quality. The raw data were imported to ProteoWizard and processed with R and XCMS for peak detection, extraction, alignment, and integration. Then, after obtaining the ion intensities for each peak, we created a matrix with the names of the samples, retention time-m/z pairings, and peak intensities.The criteria for assessing the quality of metabolomics data, the stability and reproducibility of the experimental method are as follows: the tolerance limits are set such that the measured response detected in two-thirds of QC samples is within 30% coefficient of variation31. By eliminating peaks with missing values in more than 50% of samples, the matrix was further condensed31. The residual missing value was filled up by one-half of the minimum value. Each retained peak was normalized using an internal standard.The deviation value is filtered based on the RSD ≥ 30%http://www.genome.jp/kegg/), Human Metabolome Database (HMDB) (http://www.hmdb.ca), and Metabolite Link (METLIN) (https://metlin.scripps.edu). The compound matching in this study is qualitative based on the dual-core algorithm (the dot-product function and the Euclidean distance)32. The authentication accuracy of the algorithms exceeds 70%32. Known metabolites reported in this study conformed to confidence level 1 (the highest confidence level of identification) of the Metabolomics Standards Initiative34.The molecular mass data (m/z) were aligned to identify metabolites using our in-house metabolite library, and public databases including the Kyoto Encyclopedia of Genes and Genomes databases (KEGG)  to perform pathway topology analysis based on KEGG databases. The statistical significance of the changes in pathways was evaluated by the Hypergeometric test, the default method used by MetaboAnalyst 5.0. The topological pathway impacts were quantified using the published method35. Using the K-means cluster method to observe the change trend of metabolites.We used MetaboAnalyst 5.0 , another ensemble machine-learning approach for classification, was applied. The ‘createDataPartition’ function in the ‘caret’ package was applied to randomly divide the data into a 75% traininging set and a 25% test set. The ‘randomForest’ package yielded lists of metabolites sorted by feature importance. The optimal number of discriminant metabolites was identified using tenfold cross-validation implemented with the “rfcv” function in the R package ‘randomForest’ with five repeats. The effectiveness of machine learning algorithms was displayed by confusion matrices and multi-group receiver operating characteristic (ROC) curves. Multi-group ROC curves were displayed by ‘multiclass. Roc’ in the ‘pROC’ package. To improve reproducibility and model robustness, the 28 shared metabolic features (15 in serum and 13 in urine) with the two algorithms were selected as candidate metabolic biomarkers. The intersection of variables in the two machine learning approaches was visualized as a Venn diagram by the ‘VennDiagram’ package.In order to explore the genuine relationship between metabolites and ACS, the multivariable-adjusted model and subgroup interaction test were used to recognize metabolites that were not roiled by confounders among the 28 candidate metabolites. The ‘mgcv’ package was used to conduct stratified and interaction analyses for exploring the associations between the metabolic signatures and ACS risk in different subgroups, such as different age, sex, BMI, smoking status, history of hypertension or diabetes, or levels of TG, TC, HDL-C, and LDL-C. The forest plot of univariable and multivariable-adjusted models was visualized by the ‘ggforestplot’ package, and the forest plot of subgroup interaction was depicted by the ‘forestploter’ package.The multiclass metabolic diagnostic model (MDM) was developed via multivariate generalized linear regression (R package ‘glm’). The contribution of each metabolite to the MDM is calculated by the ‘calc.relimp’ function in the ‘relaimpo’ package. The jitter plot of the cutoff is using the ‘ggsignif’ and ‘ggplot2’ packages. Consistency between actual and integrated model-predicted probabilities and the overfitting risk of MDM was assessed using the calibration curve (1000 resampling bootstraps) in the internal validation set. Hosmer–Lemeshow p > 0.05 reveals good consistency between actual and predicted probabilities, and MDM is not overfitted. The clinical application of alternative diagnostic strategies was determined with decision curve analysis (DCA) by quantifying the net benefits at various threshold probabilities.The discrimination ability of the integrated model was measured using the Harrell concordance index (C-index) with 1000 resampling bootstraps in internal validation. The Net Reclassification Index (NRI) was employed to compare the diagnostic value of a single metabolite with the combined metabolic panel.t-test. The Mann–Whitney U test was applied to data that was not normally distributed. (3) Categorical variables were compared by the χ2 test. The Kruskal–Wallis H-test was used to compare the metabolites' intensity between the three groups. The relationship between metabolites and the ACS phenotype, as well as the relationship between serum and urine metabolites were expressed by the Spearman correlation analysis. All the tests were two-sided, and p < 0.05 indicates significance unless otherwise stated. The Benjamin-Hochberg correction based on false discovery rate (FDR) was utilized in multiple tests to decrease false-positive rates, and adjusted p < 0.05 indicates significance.R 4.2.1 was used for data analysis and visualization. The workflow of statistical analysis is presented in Fig. The study was approved by the Ethics Committee for the Conduct of Human Research at the General Hospital of Ningxia Medical University (2020-763). All participants were informed of the possible risks of the study and gave written informed consent. All methods were carried out in accordance with relevant guidelines and regulations.p ˂ 0.05; HC vs. AMI, adjusted p ˂ 0.05), and traditional cardiovascular risk factors, such as smoking, hypertension, diabetes mellitus, and hyperlipidemia, are much more frequently presented compared with the HC (adjusted p ˂ 0.05). The AMI has higher levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) than the UA with disease shifting (adjusted p ˂ 0.05). The UA and AMI display lower red blood cell (RBC) counts and hemoglobin (HGB) levels compared with the HC group (adjusted p ˂ 0.05). The white blood cell (WBC) and neutrophil (NEUT) counts and hypersensitive C-reactive protein (hs-CRP) levels in the AMI group are significantly increased compared with the HC and the UA (adjusted p ˂ 0.05). With the progress of the disease, levels of aspartate transaminase (AST), alanine aminotransferase (ALT), and Recombinant N-terminal Pro-Brain Natriuretic peptide (NT-proBNP) are increased (adjusted p ˂ 0.05). The AMI exhibits higher SYNTAX I, Gensini scores, number of stenosed vessels (No. of SV), and cTnI levels, as well as lower LVEF compared with the UA (adjusted p ˂ 0.05). Based on the above, subjects suffering from AMI experienced the most stressful inflammation, metabolomic disorders, the most severe coronary artery lesion, and left ventricular dysfunction.As shown in Table + and ESI−) modes. Based on KEGG and HMDB analyses, 651 metabolites were identified after peak alignment and data preprocessing  to fit the LASSO regression . Eight urine metabolites remained statistically significant after adjusting for various variables (p < 0.05). Each SD of LysoPC), 2-ketobutyric acid, N6-Acetyl-l-lysine, and cyclic GMP was associated with a 3.89-fold (95% CI 1.57–15.23), 12.44-fold (95% CI 2.56–70.69), 8.77-fold (95% CI 1.19–80.26), and 11.22-fold (95% CI 2.00–74.71) increment in the OR for incident ACS. The risk of suffering from ACS was reduced by 0.89-fold (95% CI 0.03–0.45), 0.79-fold (95% CI 0.08–0.57), 0.89-fold (95% CI 0.03–0.42), 0.64-fold (95% CI 0.16–0.80), 0.79-fold (95% CI 0.07–0.59), 0.95-fold (95% CI 0.01–0.31), 0.73-fold (95% CI 0.10–0.76), 0.59-fold (95% CI 0.21–0.81), and 0.69-fold (95% CI 0.13–0.74) for each SD increase of metabolites in LysoPC), LysoPC(22:0), PE(P-18:1(9Z)/18:1(9Z)), corticosterone, erythronic acid, uracil, argininosuccinic acid, xanthurenic acid, and N4-Acetylcytidine, respectively.In order to discover robust biomarkers that are independent of conventional cardiovascular risk factors, we conducted logistic regression analyses and interaction tests. The odds ratio (OR) per standard deviation (SD) of the 15 candidates in serum and the 13 candidates in urine are depicted in Fig. p for interaction > 0.05, Fig. p for interaction > 0.05, Fig. p for interaction > 0.05, Fig. Then subgroup analysis and interaction tests were carried out for the selected thirteen metabolites Fig. –S6. Subgp < 0.05; rho = 0.29, p < 0.05). LysoPC), argininosuccinic acid, and xanthurenic acid showed a progressive decline as the disease progressed ), argininosuccinic acid, and cyclic GMP as candidate biomarkers of ACS and applied them to develop MDM. A ROC analysis was conducted to observe the diagnostic value of the four molecules. The area under the curve (AUC) of 2-ketobutyric acid, LysoPC), argininosuccinic acid, and Cyclic GMP was 0.64, 0.80, 0.66, and 0.56, for distinguishing UA from HC Fig. a. Encourp = 0.413, Fig. p = 0.998; Hosmer–Lemeshow p = 0.953; Fig. To assess the consistency of the MDM, we performed the calibration curve by bootstrapping with 1000 resamplings in the internal validation. For the UA discrimination, the calibration curve presented excellent consistency between the actual and predicted probabilities of the MDM ), argininosuccinic acid, cyclic GMP, and MDM for HC vs. UA, HC vs. AMI, and UA vs. AMI are presented in Fig. We performed the bootstrapping with 1000 resamplings in the internal validation. The C-index with 1000 resampling was 0.83 (95% CI 0.73–0.91), 0.97 (95% CI 0.92–0.99), and 0.89 (95% CI 0.83–0.94) for HC vs. UA, HC vs. AMI, and UA vs. AMI ), argininosuccinic acid, and cyclic GMP, we established the multiclassification model MDM that approached a strong C-index, outperforming single metabolite alone. Furthermore, we discovered that the four metabolites changed dynamically as plaque burden increased. In addition, 2-ketobutyric acid is identified both in serum and urine, but they are not correlated. These results lend credence to the idea that the combination of serum and urine metabolites exhibits powerful efficiency in classifying subjects into HC, UA, or AMI, which may have the clinical effect of improving risk stratification relatively noninvasively.38. The aim of this study is to establish a multiclassification metabolic model to classify subjects into HC, UA, or AMI. Obviously, this is a multiclassification problem (N > 2) rather than a simple binary classification problem. Multiclass metabolic models are scarce in the field of CAD. As the complexity of determining accurate class decision boundaries increases, it is more difficult to obtain stable and reliable classification models for multiclassification22. Therefore, compared with binary classification, machine learning algorithms suitable for multiclassification are greatly reduced23. A report claimed that fewer than fourteen ML methods can be applied to multiclass metabolomics23. The premise of applying machine learning algorithms in the past multiclassification metabolic research of CAD is to convert the multiclassification into a dichotomous problem through cross comparison and traditional hypothesis testing, such as the Student's t-test24. These studies used RF, binominal LASSO, and support vector machine (SVM) to construct binary classification so as to overlook the establishment of multiclassification models24. Traditional hypothesis testing will narrow the prior range of differential metabolites, and multiple pairwise comparisons will increase the risk of type I error39. In view of this, this study does not use traditional hypothesis testing and multiple pairwise comparisons in the modeling process. Adaptive LASSO is an upgraded version of LASSO that can overcome the shortcomings of LASSO, as it obtains initial weights using ordinary least squares estimation, which results in higher penalties for zero coefficients and lower penalties for nonzero coefficients40. We ameliorated adaptive LASSO into multinomial adaptive LASSO, and combined it with RF to build a multiclass metabolic model to classify HC, UA, and AMI. We plugged all identified metabolites into the multinomial classifiers for feature selection, which was conducive to making comprehensive use of metabolites and eliminating type I error. Finally, 2-ketobutyric acid, LysoPC), argininosuccinic acid, and cyclic GMP stood out as representatives of ACS after controlling confounders and the interaction test, potentially mirroring ACS severity.The multinomial classifiers named adaptive LASSO multinomial regression and RF for feature selection employed in our research are differentiated from previous research41. The reproducibility of biomarkers in different populations, subgroups, or subsets is the fundamental criterion for measuring the performance of machine learning algorithms used43. Based on the reproducibility criteria, this study obtained candidate diagnostic metabolic small molecules by taking intersections based on multinomial adaptive LASSO regression and RF and then conducting confounding factor evaluation and interaction testing. In a real-world setting, it is almost impossible to completely remove the influence of confounding factors on host metabolism. Our study identified independent metabolites that are not modified by age, sex, BMI, smoking status, history of hypertension or diabetes, or levels of TG, TC, HDL-C, and LDL-C to the maximum extent. Whether these metabolites are affected by other potential confounders was not evaluated in this study. The representativeness of the study population is another important factor affecting reproducibility. The importance of sample size for the generalizability of results to a broader population is widely acknowledged. The sample size of this study meets the sample size requirement for identifying differences in metabolites between groups. This indicates that the study population is representative at the sample size level. In addition, the baseline characteristics of the population in this study are consistent with the epidemiological characteristics of ACS, which proves that the study population is representative to some extent44. Meanwhile, model overfitting is one of the difficulties in applying machine learning to small datasets45. Although this multiclassification model did not undergo external dataset validation for reproducibility, internal validation, including cross-validation and 1,000 resampling bootstraps, demonstrated that it has considerable reproducibility and there is no overfitting of the model.The selected metabolic small molecules based on different machine learning algorithms require reproducibility. Previous studies have found that one of the reasons for the low reproducibility of biomarkers is due to the inappropriate methods of identifying biomarkers47. These previous studies showed that glycerophospholipid metabolism was found to be the most significantly altered metabolic pathway in all paired comparisons, such as UA versus SA, AMI versus UA48. Consistent with our results, glycerophospholipids in SA and AMI patients were significantly lower than those in healthy individuals49. Glycerophospholipid metabolism is closely related to the inflammatory response of CAD, and glycerophospholipids may act as potential inflammatory mediators50. The arginine biosynthesis pathway represents the source of nitric oxide (NO) production51. Reduced arginine uptake can cause a decrease in NO bioavailability51. NO exerts anti atherosclerotic cardioprotective effects by vasodilation, inhibiting platelet aggregation, and adhesion, inhibiting inflammation produced by leukocyte adhesion to blood vessels, and inhibiting vascular smooth muscle proliferation52. Previous studies have confirmed that the arginine metabolic pathway in CAD is impaired, which supports our findings47. Some scholars claim that exogenous arginine supplementation can restore NO bioavailability, increase coronary blood flow, dilate blood vessels, and relieve angina pectoris in patients with CAD, while others hold negative results53. Therefore, the benefit of arginine for CAD is controversial.We mapped biochemical metabolic pathways based on the four metabolic signatures Fig. . Glycero54. A magnitude of studies identified the impaired TCA cycle in myocardial ischaemia, which is similar to our results56. Previous studies reported a decrease in intermediate metabolites of the TCA cycle during AMI, such as fumaric acid, succinate, and oxaloacetic acid58. However, some scholars are opposed to this. They believe that succinate is elevated during myocardial ischaemia and drives reactive oxygen species (ROS) to cause ischaemia–reperfusion injury60. In line with the previous study, our result demonstrated that the levels of 2-ketobutyric acid were upregulated in ACS13. Researchers speculated that accumulations of 2-ketobutyric acid, the TCA cycle intermediate, signified perturbations of oxidative phosphorylation61. Activating 2-ketobutyric acid production was sufficient to promote glucose oxidation and mitochondrial respiration62. The accumulation of 2-ketobutyric acid in ACS, especially in AMI, may be due to the feedback increases caused by the impaired TCA cycle activity.As Fig. 63. It was reported that a supplement of L-citrulline, a precursor of argininosuccinic acid, showed benefits for cardiovascular and metabolic health outcomes64. This report supports our findings. As a precursor of fumarate, the downregulation of argininosuccinic acid in the ACS might indirectly affect fumarate production and further signify abnormal activities of the TCA cycle.In this work, higher levels of argininosuccinic acid were associated with a lower risk of ACS. We showed that argininosuccinic acid was negatively correlated with ACS phenotype indices. This indicates that the deficiency of argininosuccinic acid might have a deleterious effect on ACS. Thus, our findings suggest that argininosuccinic acid is beneficial for ACS and it may contribute to the etiology of ACS as part of the cause or a consequence. The specific causality needs further verification. Arginosuccinic acid can be synthesized from citrulline and is used as a precursor of arginine in arginine biosynthesis. This study clarifies that arginosuccinic acid is involved in the progression of HC → UA → AMI via dysregulated arginine biosynthesis. The previous study supported our view by showing that a higher arginine/asymmetric dimethylarginine ratio was associated with lower CVD incidence46. We find that LysoPC) contributes the greatest diagnostic value in distinguishing whether an individual suffers from ACS or not with the maximum contribution ratio. Interestingly, we observed that LysoPC) was in low abundance in AMI and was negatively associated with atherosclerosis plaque burden and hs-CRP. This analysis provides insight into the anti-atherosclerotic and anti-inflammatory properties of LysoPC) in the setting of ACS65. Consistent with our findings, previous studies showed that LysoPC(18:2) was downregulated in the ACS or in the AMI66. Large-scale cohort studies suggested a negative association between LysoPC(18:2) and MACE risk or hs-CRP, which supported our findings67. A previous study demonstrated that LPC can bind C-reactive protein (CRP), thereby inhibiting its pro-atherogenic effect on macrophages and delaying the progression of atherosclerosis68. These discoveries demonstrate that LysoPC(18:2) could stabilize atherosclerotic plaque. This contradicts LPC could significantly induce the uptake of oxLDL by macrophages, thereby transforming into foam cells and aggravate the deterioration of atherosclerotic plaques69. The following reasons can explain: LPC may play an antiatherosclerosis role by inhibiting cholesterol biosynthesis and reducing cellular cholesterol accumulation in liver cells70 and macrophages71. Another explanation for this discrepancy result is attributed to that the acyl chain length and saturation of different LPC species affect their activity and function73. Saturated LPC, such as LPC (16:0), can promote the release of inflammatory cytokines74. Unsaturated LPC, such as LPC (20:4), can inhibit the production of inflammatory mediators and exert anti-inflammatory effects, which supports our findings74. Recent evidence elucidates that the more the number of double bonds of phosphatidylcholine, the lower the risk of death from CAD46. This supports the view of this study that polyunsaturated LPC, such as LysoPC), have beneficial effects on ACS.LysoPC), an unsaturated LPC (lysophosphatidylcholine), participates in the progression of HC → UA → AMI via the dysregulated glycerophospholipid metabolism, which is supported by the previous research75. Activating the NO/cGMP/cGMP-dependent protein kinase type I (cGKI)-signaling pathway can facilitate thrombus dissolution76. Elevating cGMP provides protection against ischaemia and reperfusion injury by increasing Ca2+-activated K+ channels of the BK-type activity (BK)77. These protective effects of cGMP seem to contradict the positive association between urinary cGMP and CVD risk. Some reasons can explain this relationship. Direct activation of the respective guanylate cyclase by nitric oxide (NO) or natriuretic peptide (NP)-triggered pathways can upregulate cGMP78. The increase of cGMP in urine was largely triggered by the NP pathway rather than NO pools79. We observed that cGMP was positively correlated with NT-proBNP, a natural ligand for membrane-bound guanylate cyclase receptors to stimulate the synthesis of cGMP. This result supports the idea that urinary upregulated cGMP in ACS is more likely to originate from the NP pathway. Although the cardioprotective effects of cGMP, cGMP levels are upregulated in ACS pathological conditions, like NT-proBNP. The elevated urinary cGMP reflects inadequate compensatory mechanisms of ACS. In addition, by analyzing the relationship between serum and urine metabolites, we found that cGMP was detected only in urine and not in serum. This is due to the fact that cGMP produced by the NO pathway is intracellular compartmentalized and difficult to measure in blood, while cGMP produced by the NP pathway resides at the membrane and is secreted to the extracellular80. This is another explanation for our detection of elevated urine cGMP levels in ACS. This paradox highlights the complexity of the relationship between cGMP and ACS.Another intriguing discovery is that higher urinary cyclic GMP (cGMP) levels were associated with an increased risk of incident ACS and positively related to atherosclerosis plaque burden. Consistent with our result, a case-cohort analysis nested study with 875 participants showed that higher levels of cGMP were independent risk factors for heart failure, cardiovascular events, and coronary heart disease after 9.9 years of follow-upOne of the strengths of the study is that the detailed contribution proportions of the four metabolites to MDM are helpful for clinical decision-making. These metabolites have the potential to be made into reagents to monitor the occurrence of ACS. Their clinical application value is reflected in that when an individual's 2-ketobutyric acid is the most significantly upregulated among the four signatures, they are at high risk of AMI rather than UA, and when LysoPC) is most significantly downregulated, they are more inclined to UA or AMI diagnosis rather than healthy status. Our results fill a gap in the establishment of a multiclassification metabolomics model with multinomial ML approaches, especially multinomial adaptive LASSO regression. Furthermore, the MDM is a robust independent biomarker panel of ACS and atherosclerosis plaque burden, as the spurious effects of some confounding factors were dismissed.7. This study serves as an exploratory analysis, a larger-scale cohort study for external validation in real-world medicine is essential to proving the generalizability and reproducibility of our findings.Further investigations are essential. This is a cross-sectional study, and only the metabolites at a certain moment were observed. Long-term dynamic metabolite changes or metabolic flux using tracer technology is needed to determine whether there is a causal relationship between the four metabolic signatures and ACS. Besides, a large number of metabolites used to prepare diagnostic test reagents do not have reference material. At present, one of the biggest challenges and limitations of metabolome disease diagnostics is the generalizability of target metabolites, which can be affected by the diversity of the population, genetics, environment, and various potential confoundersIn conclusion, glycerophospholipid metabolism and arginine biosynthesis act on predominant roles as ACS and atherosclerosis plaque progression. This study provides a new metabolic multiclassification model and multinomial machine learning algorithm for ACS. The MDM integrated by 2-ketobutyric acid, LysoPC), argininosuccinic acid, and cyclic GMP have emerged as robust, independent hallmarks of ACS and atherosclerosis plaque. Our finding provides new insights for revealing novel potential etiologies for ACS.Supplementary Figures.Supplementary Tables.