Choroid plexus enlargement in mild cognitive impairment on MRI: a large cohort study.

OBJECTIVES: Previous studies have shown possible choroid plexus (CP) dysfunction in Alzheimer's disease (AD) and highlighted CP enlargement on magnetic resonance imaging (MRI) as a predictive factor of AD. However, few studies have assessed the relationship between CP volume (CPV) and mild cognitive impairment (MCI). In this large elderly population study, we investigated the changes in CPV in patients with MCI using MRI above 65 years. METHODS: This cross-sectional study included 2144 participants (median age, 69 years; 60.9% females) who underwent 3T MRI; they were grouped as 218 MCI participants and 1904 cognitively healthy controls. The total intracranial volume (ICV), total brain volume (TBV), CPV, hippocampal volume (HV), and lateral ventricle volume (LVV) were calculated. RESULTS: CPV/ICV was a significant independent predictor of MCI (p < 0.01) after adjusting for potential confounders (age, sex, hypertension, hyperlipidemia, diabetes, and education level). The CPV/ICV ratio was also a significant independent predictor of MCI after adjusting for the TBV/ICV ratio (p = 0.022) or HV/ICV ratio (p = 0.017), in addition to potential confounders. The CPV was significantly correlated with the LVV (r = 0.97, p < 0.01). CONCLUSION: We identified a relationship between CPV and MCI, which could not be explained by the degree of brain atrophy. Our results support CP dysfunction in MCI. CLINICAL RELEVANCE STATEMENT: Choroid plexus volume measurement may serve as a valuable imaging biomarker for diagnosing and monitoring mild cognitive impairment. The enlargement of the choroid plexus, independent of brain atrophy, suggests its potential role in mild cognitive impairment pathology. KEY POINTS: • The study examines choroid plexus volume in relation to cognitive decline in elderly. • Enlarged choroid plexus volume independently indicates mild cognitive impairment presence. • Choroid plexus volume could be a specific biomarker for early mild cognitive impairment diagnosis.

Effects of rewarming therapies on outcomes in accidental hypothermia: A secondary analysis of a multicenter prospective study.

BACKGROUND: Rewarming therapies for accidental hypothermia (AH) include extracorporeal membrane oxygenation (ECMO) and non-ECMO related (conventional) therapies. However, there are limited data available to inform the selection of conventional rewarming therapy. The aim of the present study was to explore what patients' factors and which rewarming therapy predicted favorable prognosis. METHODS: This study is a secondary analysis of the Intensive Care with Extra Corporeal membrane oxygenation Rewarming in Accidentally Severe Hypothermia (ICE-CRASH) study, a multicenter prospective, observational study conducted in Japan. Enrolled in the ICE-CRASH study were patients aged ≥18 years with a core temperature of ≤32 °C who were transported to the emergency departments of 36 tertiary care hospitals in Japan between 1 December 2019 and 31 March 2022, among whom those who were rewarmed with conventional rewarming therapy were included in the present study. Logistic regression analysis was performed with 28-day survival as the objective variable; and seven factors including age, activities of daily living (ADL) independence, sequential organ failure assessment (SOFA) score, and each rewarming technique as explanatory variables. We performed linear regression analysis to identify whether each rewarming technique was associated with rewarming rate. RESULTS: Of the 499 patients enrolled in the ICE-CRASH study, 371 were eligible for this secondary analysis. The median age was 81 years, 50.9% were male, and the median initial body temperature was 28.8 °C. Age (odds ratio [OR]: 0.97, 95% confidence interval [CI]: 0.94-1.00) and SOFA score (OR: 0.73, 95% CI: 0.67-0.81) were associated with lower survival, whereas ADL independence (OR: 2.31, 95% CI: 1.15-4.63) was associated with higher survival. No conventional rewarming therapy was associated with 28-day survival. Hot bath was associated with a high rewarming rate (regression coefficient: 1.14, 95% CI: 0.75-1.53). CONCLUSION: No conventional rewarming therapy was associated with improved 28-day survival, which suggests that background factors such as age, ADL, and severity of condition contribute more to prognosis than does the selection of rewarming technique.

Inhibition of the bone morphogenetic protein pathway suppresses tumor growth through downregulation of epidermal growth factor receptor in MEK/ERK-dependent colorectal cancer.

The bone morphogenetic protein (BMP) pathway promotes differentiation and induces apoptosis in normal colorectal epithelial cells. However, its role in colorectal cancer (CRC) is controversial, where it can act as context-dependent tumor promoter or tumor suppressor. Here we have found that CRC cells reside in a BMP-rich environment based on curation of two publicly available RNA-sequencing databases. Suppression of BMP using a specific BMP inhibitor, LDN193189, suppresses the growth of select CRC organoids. Colorectal cancer organoids treated with LDN193189 showed a decrease in epidermal growth factor receptor, which was mediated by protein degradation induced by leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1) expression. Among 18 molecularly characterized CRC organoids, suppression of growth by BMP inhibition correlated with induction of LRIG1 gene expression. Notably, knockdown of LRIG1 in organoids diminished the growth-suppressive effect of LDN193189. Furthermore, in CRC organoids, which are susceptible to growth suppression by LDN193189, simultaneous treatment with LDN193189 and trametinib, an FDA-approved MEK inhibitor, resulted in cooperative growth inhibition both in vitro and in vivo. Taken together, the simultaneous inhibition of BMP and MEK could be a novel treatment option in CRC cases, and evaluating in vitro growth suppression and LRIG1 induction by BMP inhibition using patient-derived organoids could offer functional biomarkers for predicting potential responders to this regimen.

CBNplot: Bayesian network plots for enrichment analysis.

SUMMARY: When investigating gene expression profiles, determining important directed edges between genes can provide valuable insights in addition to identifying differentially expressed genes. In the subsequent functional enrichment analysis (EA), understanding how enriched pathways or genes in the pathway interact with one another can help infer the gene regulatory network (GRN), important for studying the underlying molecular mechanisms. However, packages for easy inference of the GRN based on EA are scarce. Here, we developed an R package, CBNplot, which infers the Bayesian network (BN) from gene expression data, explicitly utilizing EA results obtained from curated biological pathway databases. The core features include convenient wrapping for structure learning, visualization of the BN from EA results, comparison with reference networks, and reflection of gene-related information on the plot. As an example, we demonstrate the analysis of bladder cancer-related datasets using CBNplot, including probabilistic reasoning, which is a unique aspect of BN analysis. We display the transformability of results obtained from one dataset to another, the validity of the analysis as assessed using established knowledge and literature, and the possibility of facilitating knowledge discovery from gene expression datasets. AVAILABILITY AND IMPLEMENTATION: The library, documentation and web server are available at https://github.com/noriakis/CBNplot. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Individual health-disease phase diagrams for disease prevention based on machine learning.

Early disease detection and prevention methods based on effective interventions are gaining attention worldwide. Progress in precision medicine has revealed that substantial heterogeneity exists in health data at the individual level and that complex health factors are involved in chronic disease development. Machine-learning techniques have enabled precise personal-level disease prediction by capturing individual differences in multivariate data. However, it is challenging to identify what aspects should be improved for disease prevention based on future disease-onset prediction because of the complex relationships among multiple biomarkers. Here, we present a health-disease phase diagram (HDPD) that represents an individual's health state by visualizing the future-onset boundary values of multiple biomarkers that fluctuate early in the disease progression process. In HDPDs, future-onset predictions are represented by perturbing multiple biomarker values while accounting for dependencies among variables. We constructed HDPDs for 11 diseases using longitudinal health checkup cohort data of 3,238 individuals, comprising 3,215 measurement items and genetic data. The improvement of biomarker values to the non-onset region in HDPD remarkably prevented future disease onset in 7 out of 11 diseases. HDPDs can represent individual physiological states in the onset process and be used as intervention goals for disease prevention.

Effect of gut microbial composition and diversity on major inhaled allergen sensitization and onset of allergic rhinitis.

BACKGROUND: Decreased gut microbiota diversity is associated with gut dysbiosis and causes various diseases, including allergic diseases. We investigated the relationship between gut microbial diversity and sensitization to major inhaled allergens. Furthermore, the relationship of allergic symptom onset with bacterial composition in sensitized individuals was investigated. METHODS: This study included 1092 local residents who had participated in the Iwaki Health Promotion Project in 2016. Blood samples were analyzed to ascertain specific IgE levels against major inhaled allergens (JCP, HD1, Grass-mix, Weed-mix). Nasal symptoms were estimated by questionnaires. Fecal samples were analyzed for bacterial 16S rRNA using next generation sequencing. The diversity index (α-diversity, ß-diversity) and the composition of gut microbes in phylum/order levels were compared between patients sensitized or unsensitized to allergen, and symptomatic and asymptomatic groups. RESULTS: Some α-diversity metrics were significantly decreased in patients who were sensitized to any/all four allergens compared with the unsensitized group. ß-diversity differed significantly between those unsensitized and sensitized to all allergens (aged 20-49 years), and between those unsensitized and sensitized to any/all four allergens (aged ≥50 years). The relative abundance of Bacteroidales was significantly lower in the unsensitized than in the sensitized group. The composition and diversity of gut microbiota were similar between the symptomatic and asymptomatic groups. CONCLUSIONS: Our results suggest that lack of diversity in gut microbiota has an effect on sensitization to allergens. Bacteroidales in order level may affect sensitization; however, the onset of allergy symptoms was not significantly associated with bacterial composition and diversity.

Lung adenocarcinoma subtypes definable by lung development-related miRNA expression profiles in association with clinicopathologic features.

Accumulation of genetic and epigenetic changes alters regulation of a web of interconnected genes including microRNAs (miRNAs), which confer hallmark capabilities and characteristic cancer features. In this study, the miRNA and messenger RNA expression profiles of 126 non-small cell lung cancer specimens were analyzed, with special attention given to the diversity of lung adenocarcinomas. Of those, 76 adenocarcinomas were classified into two major subtypes, developing lung-like and adult lung-like, based on their distinctive miRNA expression profiles resembling those of either developing or adult lungs, respectively. A systems biology-based approach using a Bayesian network and non-parametric regression was employed to estimate the gene regulatory circuitry functioning in patient tumors in order to identify subnetworks enriched for genes with differential expression between the two major subtypes. miR-30d and miR-195, identified as hub genes in such subnetworks, had lower levels of expression in the developing lung-like subtype, whereas introduction of miR-30d or miR-195 into the lung cancer cell lines evoked shifts of messenger RNA expression profiles toward the adult lung-like subtype. Conversely, the influence of miR-30d and miR-195 was significantly different between the developing lung-like and adult lung-like subtypes in our analysis of the patient data set. In addition, RRM2, a child gene of the miR-30d-centered subnetwork, was found to be a direct target of miR-30d. Together, our findings reveal the existence of two miRNA expression profile-defined lung adenocarcinoma subtypes with distinctive clinicopathologic features and also suggest the usefulness of a systems biology-based approach to gain insight into the altered regulatory circuitry involved in cancer development.

The effect of ligands on FePt-Fe3O4 core-shell magnetic nanoparticles.

FePt-Fe3O4 core-shell nanoparticles functionalized with 3,4-dihydroxyphenylacetic acid (DOPAC) and dimercaptosuccinic acid (DMSA) ligands were synthesized and characterized. We found that the DOPAC ligand enhances the magnetic properties of the FePt-Fe3O4 particles, in comparison with the DMSA ligand, which induces the oxidation of the shell layer that causes a significant reduction of the saturation magnetization. The synthesized magnetic nanoparticles were evaluated for applications in magnetic hyperthermia and magnetic resonance imaging contrast enhancement.

Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.

Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.

Association between Gut Microbiota and Muscle Strength in Japanese General Population of the Iwaki Health Promotion Project.

The association between the gut microbiota and muscle strength has garnered attention in the context of mitigating muscle decline. However, many study subjects have been individuals with existing illnesses or the elderly only. This study aims to elucidate the association between the gut microbiota and muscle strength indicators using grip strength/BMI in a large-scale study of community residents. The mean age of men (n = 442) and women (n = 588) was 50.5 (15.3) and 51.2 (15.9) years, respectively. The muscle strength indicator used was grip/BMI. The association between total read count and genus-level gut microbiota and muscle strength was analyzed. The mean grip/BMI was 1.8 (0.3) for men and 1.2 (0.2) for women. The genus of the gut microbiota that showed an association in both sexes was Eggerthella (men: ß = 0.18, CI: 0.04-0.31, p = 0.009; women: ß = 0.07, CI: 0.00-0.12, p = 0.028). Blautia, Eggerthella and Faecalibacterium were found to be significantly associated with grip/BMI in both the multiple regression analysis and Spearman's correlation analysis after the multiple comparison adjustment. These results suggest that an increase in Blautia and Eggerthella, coupled with a decrease in Faecalibacterium, may contribute to muscle strengthening or the suppression of muscle weakness.

Dairy consumption, bone turnover biomarkers, and osteo sono assessment index in Japanese adults: A cross-sectional analysis of data from the Iwaki Health Promotion Project.

Purpose: Dairy foods are nutritional sources of calcium, phosphorus, protein, and other nutrients that improve bone health. However, the effects of dairy consumption on bone biomarkers in the Japanese population remain unclear. This study explored the association between dairy consumption and bone biomarkers in Japanese adults. Methods: This cross-sectional study was conducted as part of the Iwaki Health Promotion Project in Aomori, Japan. In total, 1063 adults were included in the analysis. Bone turnover marker levels were measured in local citizens during their annual medical checkups. The calcaneus osteo sono assessment index (OSI) was calculated using a quantitative ultrasound technique. The dietary intake of foods and nutrients was estimated using a food frequency questionnaire. Linear regression models were established using dairy consumption and bone biomarkers with adjustments. Statistic significance was considered by P < 0.05. Results: In multivariate models, the tartrate-resistant acid phosphatase 5b and parathyroid hormone concentrations were inversely associated with dietary dairy consumption after adjusting for age and sex. The undercarboxylated osteocalcin, a procollagen type I N-terminal peptide to bone alkaline phosphatase ratio, and OSI were the directly associated with dairy consumption in multivariate models with adjustment. Conclusions: Dairy consumption is partially associated with bone turnover biomarkers and OSI in adult Japanese participants. Habitual consumption of dairy foods may contribute to the nutritional supplementation for maintaining bone health, including turnover and structure. Clinical trial registry number and website where it was obtained: The Japanese Clinical Trials Registry (UMIN000040459), https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000046175.

FLAIR Hyperintensities in the Anterior Part of the Callosal Splenium in the Elderly Population: A Large Cohort Study.

RATIONALE AND OBJECTIVES: Although hyperintensity in the anterior portion of the callosal splenium on FLAIR (aCS-hyperintensity) is a common finding in elderly adults, no previous studies have examined the clinical significance. In this large elderly population study, we aimed to investigate the associations of aCS-hyperintensity with vascular risk factors, cognitive decline, and other MRI measurements. MATERIALS AND METHODS: This cross-sectional study included 2110 participants (median age, 69 years; 61.1% females) who underwent 3 T MRI. The participants were grouped as 215 with mild cognitive impairment (MCI) and 1895 cognitively normal older adults (NOAs). Two neuroradiologists evaluated aCS-hyperintensity by using a four-point scale (none, mild, moderate, and severe). Periventricular hyperintensities (PVHs) were also rated on a four-point scale according to the Fazekas scale. The total intracranial volume (ICV), total brain volume, choroid plexus volume (CPV), and lateral ventricle volume (LVV) were calculated. RESULTS: Logistic regression analysis showed diabetes was the main predictor of aCS-hyperintensity after adjusting for potential confounders (age, sex, hypertension, and hyperlipidemia) (p < 0.01), whereas PVH was associated with hypertension (p < 0.01). aCS-hyperintensity rated as "severe" was associated with a presence of MCI (p < 0.01). For the imaging factors, LVV was an independent predictor of aCS-hyperintensity when brain volume and PVH grade were added to the analysis (p < 0.01). CONCLUSION: Cerebral small vessel disease due to diabetes is a major contributor to the development of aCS-hyperintensity. Cerebrospinal fluid clearance failure may also relate to aCS-hyperintensity, which may offer new insights into the pathologic processes underlying MCI.

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-ß signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.

Vasohibin-1 is identified as a master-regulator of endothelial cell apoptosis using gene network analysis.

BACKGROUND: Apoptosis is a critical process in endothelial cell (EC) biology and pathology, which has been extensively studied at protein level. Numerous gene expression studies of EC apoptosis have also been performed, however few attempts have been made to use gene expression data to identify the molecular relationships and master regulators that underlie EC apoptosis. Therefore, we sought to understand these relationships by generating a Bayesian gene regulatory network (GRN) model. RESULTS: ECs were induced to undergo apoptosis using serum withdrawal and followed over a time course in triplicate, using microarrays. When generating the GRN, this EC time course data was supplemented by a library of microarray data from EC treated with siRNAs targeting over 350 signalling molecules.The GRN model proposed Vasohibin-1 (VASH1) as one of the candidate master-regulators of EC apoptosis with numerous downstream mRNAs. To evaluate the role played by VASH1 in EC, we used siRNA to reduce the expression of VASH1. Of 10 mRNAs downstream of VASH1 in the GRN that were examined, 7 were significantly up- or down-regulated in the direction predicted by the GRN.Further supporting an important biological role of VASH1 in EC, targeted reduction of VASH1 mRNA abundance conferred resistance to serum withdrawal-induced EC death. CONCLUSION: We have utilised Bayesian GRN modelling to identify a novel candidate master regulator of EC apoptosis. This study demonstrates how GRN technology can complement traditional methods to hypothesise the regulatory relationships that underlie important biological processes.

Definition of a Dietary Pattern Expressing the Intake of Vegetables and Fruits and Its Association with Intestinal Microbiota.

Daily dietary habits directly or indirectly influence the intestinal microbiota, and the resulting changes in its composition and metabolic activity alter the health conditions of the host. Although many studies have analyzed the association between individual nutrients/food items and intestinal microbiota, the assessment of the diet and intestinal microbiota from a macroscopic perspective has not yet been performed in Japan. Therefore, we focused on vegetables and fruits and aimed to identify dietary patterns of high intake of these foods and to examine their relationship with the intestinal microbiota. This cross-sectional study included 1019 healthy individuals aged ≥20 years in a rural area in northern Japan. Six dietary patterns were detected by factor analysis using the brief-type self-administered diet history questionnaire (BDHQ) data to identify the "vege pattern", which was the dietary pattern rich in vegetables and fruits. Permutational multivariate analysis of variance revealed changes in ß-diversity according to dietary patterns. In multivariable-adjusted models, the adherence to the vege pattern was positively correlated with α-diversity. This is the first study to reveal a correlation between intestinal microbiota and dietary habits rich in vegetables and fruits in a rural area of Japan.

Altered structural hippocampal intra-networks in a general elderly Japanese population with mild cognitive impairment.

Although altered networks inside the hippocampus (hippocampal intra-networks) have been observed in dementia, the evaluation of hippocampal intra-networks using magnetic resonance imaging (MRI) is challenging. We employed conventional structural imaging and incident component analysis (ICA) to investigate the structural covariance of the hippocampal intra-networks. We aimed to assess altered hippocampal intra-networks in patients with mild cognitive impairment (MCI). A cross-sectional study of 2122 participants with 3T MRI (median age 69 years, 60.9% female) were divided into 218 patients with MCI and 1904 cognitively normal older adults (CNOA). By employing 3D T1-weighted imaging, voxels within the hippocampus were entered into the ICA analysis to extract the structural covariance intra-networks within the hippocampus. The ICA extracted 16 intra-networks from the hippocampal structural images, which were divided into two bilateral networks and 14 ipsilateral networks. Of the 16 intra-networks, two (one bilateral network and one ipsilateral networks) were significant predictors of MCI from the CNOA after adjusting for age, sex, education, disease history, and hippocampal volume/total intracranial volume ratio. In conclusion, we found that the relationship between hippocampal intra-networks and MCI was independent from the hippocampal volume. Our results suggest that altered hippocampal intra-networks may reflect a different pathology in MCI from that of brain atrophy.

Multiomics and artificial intelligence enabled peripheral blood-based prediction of amnestic mild cognitive impairment.

BACKGROUND: Since dementia is preventable with early interventions, biomarkers that assist in diagnosing early stages of dementia, such as mild cognitive impairment (MCI), are urgently needed. METHODS: Multiomics analysis of amnestic MCI (aMCI) peripheral blood (n = 25) was performed covering the transcriptome, microRNA, proteome, and metabolome. Validation analysis for microRNAs was conducted in an independent cohort (n = 12). Artificial intelligence was used to identify the most important features for predicting aMCI. FINDINGS: We found that hsa-miR-4455 is the best biomarker in all omics analyses. The diagnostic index taking a ratio of hsa-miR-4455 to hsa-let-7b-3p predicted aMCI patients against healthy subjects with 97% overall accuracy. An integrated review of multiomics data suggested that a subset of T cells and the GCN (general control nonderepressible) pathway are associated with aMCI. INTERPRETATION: The multiomics approach has enabled aMCI biomarkers with high specificity and illuminated the accompanying changes in peripheral blood. Future large-scale studies are necessary to validate candidate biomarkers for clinical use.

SiGN-SSM: open source parallel software for estimating gene networks with state space models.

UNLABELLED: SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles. AVAILABILITY: SiGN-SSM is distributed under GNU Affero General Public Licence (GNU AGPL) version 3 and can be downloaded at http://sign.hgc.jp/signssm/. The pre-compiled binaries for some architectures are available in addition to the source code. The pre-installed binaries are also available on the Human Genome Center supercomputer system. The online manual and the supplementary information of SiGN-SSM is available on our web site. CONTACT: tamada@ims.u-tokyo.ac.jp.

Factors Associated with Reduced Heart Rate Variability in the General Japanese Population: The Iwaki Cross-Sectional Research Study.

Although many studies have reported factors associated with reduced heart rate variability (HRV) in Western populations, evidence is limited among Asian populations. Therefore, we investigated the factors associated with reduced HRV values in a general Japanese population by measuring HRV among the participants of the Iwaki Health Promotion Project who underwent medical examination in 2019. We performed 90-s HRV measurements in 1065 participants. Of these, we evaluated the coefficient of variation in R-R intervals (CVRR) and standard deviation in R-R intervals (SDNN). Blood was collected under a fasting condition, and investigations of glucose metabolism, lipid metabolism, renal function, liver function, advanced glycation end products, and blood pressure were performed. A multivariate regression analysis of the association between CVRR or SDNN and blood test parameters and blood pressure in 987 participants with adequately completed HRV assessments showed that reduced CVRR or SDNN was associated with higher levels of glycated hemoglobin (HbA1c), glycoalbumin, blood glucose, triglycerides, creatinine, plasma pentosidine, and diastolic blood pressure. In the general Japanese population, higher levels of HbA1c, glycoalbumin, blood glucose, triglycerides, creatinine, plasma pentosidine, and diastolic blood pressure are associated with reduced CVRR or SDNN, which are typical HRV parameters.

Correlation between Glycation-Related Biomarkers and Quality of Life in the General Japanese Population: The Iwaki Cross-Sectional Research Study.

The correlation between diabetes-related biomarkers and quality of life (QOL) remains unclear. In this cross-sectional study, we investigated the correlation between diabetes-related biomarkers and QOL in a general Japanese population who underwent health checkups as a part of the Iwaki Health Promotion Project. Male and female participants aged ≥ 20 years from Iwaki District, Hirosaki City, Aomori Prefecture who participated in the 2019 medical evaluation were recruited. QOL was evaluated using the Short Form Health Survey 36 (SF-36). Fasting blood glucose, homeostatic model assessment-estimated insulin resistance (HOMA-IR), hemoglobin A1c (HbA1c), glycoalbumin, and plasma pentosidine were also evaluated as diabetes-related markers. Of the 1065 recruited participants, 1053 completed the clinical and QOL evaluations. Multivariate regression analysis revealed that upregulated diabetes-related markers levels were correlated with decreased SF-36 scores. Blood glucose, HOMA-IR, HbA1c, glycoalbumin, and plasma pentosidine levels were correlated with general health. Moreover, plasma pentosidine levels were correlated with role physical, social functioning, and role emotional in addition to general health. These results indicated that the levels of diabetes-related biomarkers, particularly the levels of plasma pentosidine, a glycation marker, were associated with QOL in our cohort.