論文

Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer-Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target-capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third-degree relatives), triple-negative breast cancer patients under the age of 60, and ovarian cancer history (all P <.0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69-0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high-risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.

Parental experience of initiation of alcohol drinking has been identified as one of the early causes of alcohol drinking in preadolescents in many countries, including Japan. This study identified the association between parental alcohol-related knowledge and the initiation of alcohol use among preadolescent students in an urban area in Japan. Self-administrated questionnaires were distributed to 420 parents of kindergarteners and elementary school students, of which 339 were filled and returned (response rate: 81%). The parents’ experience in initiating alcohol drinking in their children and their knowledge about the effects of alcohol on youth were explored. The requirements for drinking prevention programs for youth were also investigated. The result showed that a significantly higher proportion of parents of elementary school students had experiences of initiating alcohol use in their children compared to parents of kindergarten children. The parents’ knowledge regarding the effects of alcohol on youth showed no significant difference between the two parent groups. These data indicate that the age of children is the only factor as opposed to parents’ knowledge. We also found significant differences in the requirements of prevention programs between the two parent groups. The results of this study can contribute to the design of alcohol prevention programs for these parents, which could reduce the onset of children’s drinking.

Increasing evidence suggests the involvement of peripheral amino acid metabolism in the pathophysiology of neuropsychiatric disorders, whereas the molecular mechanisms are largely unknown. Tetrahydrobiopterin (BH4) is a cofactor for enzymes that catalyze phenylalanine metabolism, monoamine synthesis, nitric oxide production, and lipid metabolism. BH4 is synthesized from guanosine triphosphate and regenerated by quinonoid dihydropteridine reductase (QDPR), which catalyzes the reduction of quinonoid dihydrobiopterin. We analyzed Qdpr−/− mice to elucidate the physiological significance of the regeneration of BH4. We found that the Qdpr−/− mice exhibited mild hyperphenylalaninemia and monoamine deficiency in the brain, despite the presence of substantial amounts of BH4 in the liver and brain. Hyperphenylalaninemia was ameliorated by exogenously administered BH4, and dietary phenylalanine restriction was effective for restoring the decreased monoamine contents in the brain of the Qdpr−/− mice, suggesting that monoamine deficiency was caused by the secondary effect of hyperphenylalaninemia. Immunohistochemical analysis showed that QDPR was primarily distributed in oligodendrocytes but hardly detectable in monoaminergic neurons in the brain. Finally, we performed a behavioral assessment using a test battery. The Qdpr−/− mice exhibited enhanced fear responses after electrical foot shock. Taken together, our data suggest that the perturbation of BH4 metabolism should affect brain monoamine levels through alterations in peripheral amino acid metabolism, and might contribute to the development of anxiety-related psychiatric disorders. (Figure presented.). Cover Image for this issue: https://doi.org/10.1111/jnc.15398.

Arg (R)-rich dipeptide repeat proteins (DPRs; poly(PR): Pro-Arg and poly(GR): Gly-Arg), encoded by a hexanucleotide expansion in the C9ORF72 gene, induce neurodegeneration in amyotrophic lateral sclerosis (ALS). Although R-rich DPRs undergo liquid–liquid phase separation (LLPS), which affects multiple biological processes, mechanisms underlying LLPS of DPRs remain elusive. Here, using in silico, in vitro, and in cellulo methods, we determined that the distribution of charged Arg residues regulates the complex coacervation with anionic peptides and nucleic acids. Proteomic analyses revealed that alternate Arg distribution in poly(PR) facilitates entrapment of proteins with acidic motifs via LLPS. Transcription, translation, and diffusion of nucleolar nucleophosmin (NPM1) were impaired by poly(PR) with an alternate charge distribution but not by poly(PR) variants with a consecutive charge distribution. We propose that the pathogenicity of R-rich DPRs is mediated by disturbance of proteins through entrapment in the phase-separated droplets via sequence-controlled multivalent protein–protein interactions.

The aim of this study was to determine the impact of postoperative delirium (POD) on 2-year survival and identify perioperative risk factors contributing to POD in patients undergoing oral and maxillofacial reconstructive surgery. A retrospective observational study was conducted at Hokkaido University Hospital. The cohort included 65 patients who underwent oral and maxillofacial reconstructive surgery between January 2016 and May 2022. Patients were categorized into POD ( n = 20) and non-POD ( n = 45) groups. POD diagnosis was based on clinical criteria assessed by psychiatrists. Survival was analysed using Kaplan–Meier curves and a Cox proportional hazards model adjusted for age, American Society of Anesthesiologists (ASA) physical status, malignancy, and disease classification. POD occurred in 30.8% of patients. Two-year survival estimated by Kaplan–Meier analysis was significantly lower in POD group (60%) than in non-POD group (87%) ( P = 0.009). POD was an independent risk factor for decreased survival (hazard ratio 3.40, 95% confidence interval 1.10–10.57; P = 0.034). No significant perioperative predictors of POD were identified. POD was associated with a substantial decrease in long-term survival following oral and maxillofacial reconstructive surgery. Early recognition and management of POD are critical to improving outcomes in this high-risk population.

Purpose: Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to neoadjuvant chemotherapy in breast cancer patients utilizing a metabolomic approach. Methods: Plasma samples were obtained from 87 breast cancer patients undergoing neoadjuvant chemotherapy at our facility, collected both before the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC–MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles. Results: Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second neoadjuvant chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points. Conclusion: The application of plasma metabolomics, utilizing CE-MS and LC–MS, may serve as a tool for predicting the efficacy of neoadjuvant chemotherapy in breast cancer in the future after all necessary validations have been completed.

Ovarian cancer (OC) is the most lethal gynecologic cancer, mainly due to late diagnosis with widespread peritoneal spread at first presentation. We performed metabolomic analyses of ovarian and paired control tissues using capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry to understand its metabolomic dysregulation. Of the 130 quantified metabolites, 96 metabolites of glycometabolism, including glycolysis, tricarboxylic acid cycles, urea cycles, and one-carbon metabolites, showed significant differences between the samples. To evaluate the local and systemic metabolomic differences in OC, we also analyzed low or non-invasively available biofluids, including plasma, urine, and saliva collected from patients with OC and benign gynecological diseases. All biofluids and tissue samples showed consistently elevated concentrations of N1,N12-diacetylspermine compared to controls. Four metabolites, polyamines, and betaine, were significantly and consistently elevated in both plasma and tissue samples. These data indicate that plasma metabolic dysregulation, which the most reflected by those of OC tissues. Our metabolomic profiles contribute to our understanding of metabolomic abnormalities in OC and their effects on biofluids.

Background/Aim: 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is reportedly associated with the malignant potential of cancer. This study aimed to evaluate the association between FDG accumulation and tumor metabolism in pancreatic ductal adenocarcinoma (PDAC). Patients and Methods: A prognostic analysis of data from 131 patients with PDAC who underwent FDG-PET/CT before curative-intent pancreatic surgery was performed. Capillary electrophoresis-mass spectrometry (CE-MS) was used to analyze the metabolome of tumor and non-neoplastic pancreas from 80 patients. These patients were divided into two groups: low SUVmax group (SUVmax <6.09) and high SUVmax group (SUVmax ≥6.09). Results: Carbohydrate antigen 19-9 (CA19-9), maximum standardized uptake value (SUVmax) of PET, N stage, and postoperative chemotherapy were identified as significant prognostic factors by univariate analysis. SUVmax emerged as an independent prognostic factor for overall survival [hazard ratio (HR)=1.88, p<0.05] and disease-free survival (HR=2.01, p<0.05) in multivariate analysis. Metabolic analyses confirmed that 43 metabolites significantly differed depending on the accumulation of SUV in tumors. Metabolites involved in the removal of reactive oxygen species (e.g., hypotaurine, glutathione, Met), treatment resistance (UDP-N-acetylglucosamine), and proliferation (e.g., choline, leucine, isoleucine) were increased in the high SUVmax group. Conclusion: FDG accumulation is an important independent prognostic factor reflecting tumor activity associated with metabolic changes in cancer cells.

Background Acute retinal necrosis (ARN) is a rare but vision-threatening viral retinitis that can lead to severe visual impairment or blindness if not diagnosed and treated promptly. However, due to its rarity, there are limited large-scale data on the clinical characteristics, treatment approaches, and outcomes of ARN in Japan. A nationwide registry is needed to systematically collect data on ARN cases across Japan to improve understanding of this condition and optimize patient care. We have designed a national registry that collects data of patient characteristics, diagnosis, treatment, and visual outcome to generate evidence for the management of ARN. Methods and design This research is a combined retrospective and prospective, multicenter cohort study of ARN in Japan from 1 April 2014–31 March 2029 (UMIN000056246). The registry has received Japan-wide approval from a national human research ethics committee. The following data will be collected: patient demographics, visual function at the initial visit and 6, 12, 24, and 36 months later, image data, diagnostic methods, virus analysis, indications and timing of vitrectomy, and complications. Customized software and platforms have been designed to permit data collection for a single baseline and multiple follow-up forms. Discussion By analyzing the accumulated patient information, the results of this study will generate real-world evidence that will contribute to solve various important clinical issues in ARN. The results will be presented after data collection and analysis are completed.

Large-scale metabolomic studies have become common, and the reliability of the peak data produced by the various instruments is an important issue. However, less attention has been paid to the large number of uncharacterized peaks in untargeted metabolomics data. In this study, we tested various criteria to assess the reliability of 276 and 202 uncharacterized peaks that were detected in a gathered set of 30 plasma and urine quality control samples, respectively, using capillary electrophoresis-time-of-flight mass spectrometry (CE-TOFMS). The linear relationship between the amounts of pooled samples and the corresponding peak areas was one of the criteria used to select reliable peaks. We used samples from approximately 3000 participants in the Tsuruoka Metabolome Cohort Study to investigate patterns of the areas of these uncharacterized peaks among the samples and clustered the peaks by combining the patterns and differences in the migration times. Our assessment pipeline removed substantial numbers of unreliable or redundant peaks and detected 35 and 74 reliable uncharacterized peaks in plasma and urine, respectively, some of which may correspond to metabolites involved in important physiological processes such as disease progression. We propose that our assessment pipeline can be used to help establish large-scale untargeted clinical metabolomic studies.

High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography–mass spectrometry was used to analyze 10,833 samples in 279 batch measurements. The quantified profile included 147 lipids including acylcarnitine, fatty acids, glucosylceramide, lactosylceramide, lysophosphatidic acid, and progesterone. Each batch included 40 samples, and 5 QC samples were measured for 10 samples of each. The quantified data from the QC samples were used to normalize the quantified profiles of the sample data. The intra- and inter-batch median coefficients of variation (CV) among the 147 lipids were 44.3% and 20.8%, respectively. After normalization, the CV values decreased by 42.0% and 14.7%, respectively. The effect of this normalization on the subsequent analyses was also evaluated. The demonstrated analyses will contribute to obtaining unbiased, quantified data for large-scale metabolomics.

Background: Nutritional assessment during the perioperative period is critical, particularly for older patients at high risk for complications. Bioelectrical impedance analysis (e.g., InBody) is commonly used to assess skeletal muscle mass via the skeletal muscle index (SMI). However, its use is limited in patients with contraindications, including implantable cardiac devices. Objective: Therefore, this study explored a noninvasive alternative: assessing the relationship between salivary metabolites and SMI to identify potential biomarkers associated with muscle mass. Methods: This retrospective study analyzed data from male preoperative patients who had both InBody analysis and salivary metabolomics data collected between January 2021 and March 2024. Salivary metabolites, including butyrate and hexanoate, were quantified using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF MS). Body composition parameters, including SMI, and blood nutritional indicators, were obtained. Volcano plot analysis identified metabolites significantly differing between patients with SMI ≥ 7.0 and < 7.0 kg/m2. Receiver operating characteristic (ROC) curve analysis evaluated the discriminatory ability of individual variables. Univariate and multivariate logistic regression analyses identified factors associated with SMI status. Results: Patients with low SMI were significantly older than those with high SMI. While body composition indices differed significantly, general nutritional blood markers remained comparable. Volcano plot analysis showed significantly higher salivary butyrate and hexanoate levels in patients with SMI ≥ 7.0 kg/m2 compared to those with SMI < 7.0 kg/m2. ROC curve analysis demonstrated significant discriminatory ability for butyrate, hexanoate, and age. Univariate analysis identified age as significantly associated with SMI status based on odds ratio. Multivariate analysis using stepwise variable selection retained age (OR: 1.155, p-value = 0.070) and hexanoate (OR: 0.980, p-value = 0.269) in the final model. Conclusions: This exploratory study suggests that salivary metabolites, particularly butyrate and hexanoate, along with age, may serve as potential indicators for discriminating SMI status. These findings suggest the potential utility of salivary metabolites as noninvasive biomarkers for assessing muscle mass in the perioperative setting. This could enable early sarcopenia detection and enhanced nutritional management in older patients, particularly those with contraindications. Trial Registration: UMIN Clinical Trials Registry: UMIN000057185.

Antarctic expeditions have a high risk of participant depression owing to long stays and isolated environments. By quantifying the stress state and changes in biomolecules over time before the onset of depressive symptoms, predictive markers of depression can be explored. Here, we evaluated the psychological changes in 30 participants in the Japanese Antarctic Research Expedition using the Patient Health Questionnaire-9 (PHQ-9). Urinary samples were collected every three months for a year, and comprehensive urinary metabolomic profiles were quantified using liquid chromatography time-of-flight mass spectrometry. Five participants showed major depressive episodes (PHQ-9 ≥ 10) at 12 months. The urinary metabolites between these participants and the 25 unaffected participants were compared at individual metabolite and pathway levels. The individual comparisons showed the most significant differences at 12 months in 14 metabolites, including ornithine and beta-alanine. Data from shorter stays showed less significant differences. In contrast, pathway and enrichment analyses showed the most significant difference at three months and a less significant difference at longer stays. These time transitions of urinary metabolites could help in the development of urinary biomarkers to detect subjects with depressive episodes at an early stage.

Background: The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies. Method: We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure. Result: Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle). Conclusion: These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Early detection of oral candidiasis is essential. However, most currently available methods are time-consuming and useful only for screening patients. Previous studies on the relationship between oral candidiasis and saliva have focused on saliva volume and not on its components. Therefore, to clarify the effects of oral candidiasis on salivary metabolites, the relationship between salivary components and oral candidiasis was investigated by comparing the salivary metabolites of oral candidiasis patients and those not previously diagnosed with candidiasis. Forty-five participants visiting our university hospital were included and classified into two groups, the Candida group and the control group, based on the Candida detection test results. The unstimulated saliva was collected using the spitting method over 15 min, and the stimulated saliva was collected using the gum-chewing method over 10 min. The saliva volume was measured, and the saliva samples were frozen and analyzed metabolomically. Metabolome analysis revealed 51 metabolites with peak detection rates exceeding 50%. There was no significant difference in age and sex between the Candida and control groups. In the Candida group, five metabolites (tyrosine, choline, phosphoenolpyruvate, histidine, and 6-phosphogluconate) were significantly elevated in the unstimulated, two (octanoic acid and uridine monophosphate(UMP)) were significantly increased, and four (ornithine, butyrate, aminovalerate and aminolevulinate) were significantly decreased in the stimulated saliva. This study suggests the possibility of identifying metabolites specific to patients with oral candidiasis, which could aid prompt diagnosis.

Background/Aim: This study explored the relationship between salivary metabolomic profiles, periodontal diseases, and age. Patients and Methods: Resting whole saliva samples were collected from a cohort comprising 21 women and 30 men aged 20 to 70 years, including healthy volunteers and patients with different stages of periodontal diseases. Hydrophilic metabolites were analyzed using capillary electrophoresis‑mass spectrometry. The concentrations were quantified and analyzed using multivariable analysis with or without normalization to eliminate overall differences in salivary concentrations across the samples. Results: Metabolomic analysis quantified the absolute concentration of 248 metabolites in saliva samples. The unnormalized metabolomic profiles formed large clusters, with more than half of the detected metabolites showing positive correlations with each other. The absence of such clusters in the normalized data suggests the presence of individual differences in the processed data. The presence of urea, whose concentration increased gradually with the degree of progression of periodontal disease, and leucine, whose concentration decreased gradually, was identified. Highly positive correlations were observed between proline and glycine, which remained consistent regardless of normalization, age, or disease progression. Conclusion: The metabolomic profiles of salivary samples revealed unique correlations between amino acids that were independent of age and periodontal disease.

PURPOSE. This study aimed to elucidate whether machine learning algorithms applied to vitreous levels of immune mediators predict the diagnosis of 12 representative intraocular diseases, and identify immune mediators driving the predictive power of machine learning model. METHODS. Vitreous samples in 522 eyes diagnosed with 12 intraocular diseases were collected, and 28 immune mediators were measured using a cytometric bead array. The significance of each immune mediator was determined by employing five machine learning algorithms. Stratified k-fold cross-validation was performed to divide the dataset into training and test sets. The algorithms were assessed by analyzing precision, recall, accuracy, F-score, area under the receiver operating characteristics curve, area under the precision–recall curve, and feature importance. RESULTS. Of the five machine learning models, random forest attained the maximum accuracy in the classification of 12 intraocular diseases in a multi-class setting. The random forest prediction models for vitreoretinal lymphoma, endophthalmitis, uveal melanoma, rhegmatogenous retinal detachment, and acute retinal necrosis demonstrated superior classification accuracy, precision, and recall. The top three important immune mediators for predicting vitreoretinal lymphoma were IL-10, granzyme A, and IL-6; those for endophthalmitis were IL-6, G-CSF, and IL-8; and those for uveal melanoma were RANTES, IL-8 and bFGF. CONCLUSIONS. The random forest algorithm effectively classified 28 immune mediators in the vitreous to accurately predict the diagnosis of vitreoretinal lymphoma, endophthalmitis, and uveal melanoma among 12 representative intraocular diseases. In summary, the results of this study enhance our understanding of potential new biomarkers that may contribute to elucidating the pathophysiology of intraocular diseases in the future.

Nurses are expected to depend on a wide variety of visually available pieces of patient information to understand situations. Thus, we assumed a relationship between nurses’ skills and their gaze trajectories. An observational study using a simulator was conducted to analyze gaze during neonatal care practice using eye tracking. We defined the face, thorax, and abdomen of the neonate, the timer, and the pulse oximeter as areas of interest (AOIs). We compared the eye trajectories for respiration and heart rate assessment between 7 experienced and 13 novice nurses. There were no statistically significant differences in the time spent on each AOI for breathing or heart rate confirmation. However, in novice nurses, we observed a significantly higher number of instances of gazing at the thorax and abdomen. The deviation in the number of instances of gazing at the face was also significantly higher among novice nurses. These results indicate that experienced and novice nurses differ in their gaze movements during situational awareness. These objective and quantitative differences in gaze trajectories may help to establish new educational tools for less experienced nurses.

Aims: Nonalcoholic fatty liver disease (NAFLD) is known to be associated with atherosclerosis. This study focused on upstream changes in the process by which NAFLD leads to atherosclerosis. The study aimed to confirm the association between NAFLD and the cardio-ankle vascular index (CAVI), an indicator of subclinical atherosclerosis, and explore metabolites involved in both by assessing 94 plasma polar metabolites.Methods: A total of 928 Japanese community-dwellers (306 men and 622 women) were included in this study. The association between NAFLD and CAVI was examined using a multivariable regression model adjusted for confounders. Metabolites commonly associated with NAFLD and CAVI were investigated using linear mixed-effects models in which batch numbers of metabolite measurements were used as a random-effects variable, and false discovery rate-adjusted p-values were calculated. To determine the extent to which these metabolites mediated the association between NAFLD and CAVI, mediation analysis was conducted.Results: NAFLD was positively associated with CAVI (coefficients [95% Confidence intervals (CI)]=0.23 [0.09–0.37]; p=0.001). A total of 10 metabolites were involved in NAFLD and CAVI, namely, branched-chain amino acids (BCAAs; valine, leucine, and isoleucine), aromatic amino acids (AAAs; tyrosine and tryptophan), alanine, proline, glutamic acid, glycerophosphorylcholine, and 4-methyl-2-oxopentanoate. Mediation analysis showed that BCAAs mediated more than 20% of the total effect in the association between NAFLD and CAVI.Conclusions: NAFLD was associated with a marker of atherosclerosis, and several metabolites related to insulin resistance, including BCAAs and AAAs, could be involved in the process by which NAFLD leads to atherosclerosis.

Highlights: What are the main findings? Attachment insecurity was associated with elevated depressive symptoms across the perinatal period. Higher psychological stress responses were consistently linked to EPDS positivity. Salivary cortisol showed no consistent association with depressive symptoms. What is the implication of the main findings? Brief psychosocial screening during pregnancy may help identify women at risk for perinatal depression. Background/Objectives: Perinatal depressive symptoms are influenced by psychosocial and relational factors. This study examined stage-specific associations between adult attachment style, psychological stress responses, satisfaction with the childcare environment, and depressive symptoms across five perinatal stages in Japan. Methods: This repeated cross-sectional study included 417 independent assessment datasets collected during the first, second, and third trimesters, and at two weeks and one month postpartum. Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS). Adult attachment was measured using the Relationship Questionnaire, and psychological stress responses were measured using the Stress Response Scale-18 (SRS-18). Salivary cortisol was analyzed in a subset of participants. Results: Elevated depressive symptoms (EPDS+) were observed in approximately 10–15% of participants across stages. Attachment insecurity was associated with higher odds of EPDS+ at one month postpartum (OR 12.1, 95% CI 1.35–109). Higher SRS-18 scores were consistently associated with increased odds of EPDS+ across stages (e.g., OR 20.9, 95% CI 5.46–80.0 in the second trimester). Lower satisfaction with the childcare environment was associated with elevated depressive symptoms during pregnancy. No consistent association was observed between salivary cortisol and EPDS+. Conclusions: Adult attachment insecurity and psychological stress responses were associated with perinatal depressive symptoms across stages. By clarifying stage-specific psychosocial patterns, these findings support stress–attachment frameworks, suggesting that attachment insecurity may heighten vulnerability during the perinatal transition, provide culturally specific evidence from Japan, and underscore the potential value of brief psychosocial screening in routine perinatal care.