Genetics of osteopontin in patients with chronic kidney disease: The German Chronic Kidney Disease study.

Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]≥1%) and aggregated variant testing (AVT, MAF<1%) of ELISA-quantified serum OPN, adjusted for age, sex, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) was conducted. In the project, GCKD participants had a mean age of 60 years (SD 12), median eGFR of 46 mL/min/1.73m2 (p25: 37, p75: 57) and median UACR of 50 mg/g (p25: 9, p75: 383). GWAS revealed 3 loci (p<5.0E-08), two of which replicated in the population-based Young Finns Study (YFS) cohort (p<1.67E-03): rs10011284, upstream of SPP1 encoding the OPN protein and related to OPN production, and rs4253311, mapping into KLKB1 encoding prekallikrein (PK), which is processed to kallikrein (KAL) implicated through the kinin-kallikrein system (KKS) in blood pressure control, inflammation, blood coagulation, cancer, and cardiovascular disease. The SPP1 gene was also identified by AVT (p = 2.5E-8), comprising 7 splice-site and missense variants. Among others, downstream analyses revealed colocalization of the OPN association signal at SPP1 with expression in pancreas tissue, and at KLKB1 with various plasma proteins in trans, and with phenotypes (bone disorder, deep venous thrombosis) in human tissue. In summary, this GWAS of OPN levels revealed two replicated associations. The KLKB1 locus connects the function of OPN with PK, suggestive of possible further post-translation processing of OPN. Further studies are needed to elucidate the complex role of OPN within human (patho)physiology.

Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission.

BACKGROUND: Timely diagnosis is crucial for sepsis treatment. Current machine learning (ML) models suffer from high complexity and limited applicability. We therefore created an ML model using only complete blood count (CBC) diagnostics. METHODS: We collected non-intensive care unit (non-ICU) data from a German tertiary care centre (January 2014 to December 2021). Using patient age, sex, and CBC parameters (haemoglobin, platelets, mean corpuscular volume, white and red blood cells), we trained a boosted random forest, which predicts sepsis with ICU admission. Two external validations were conducted using data from another German tertiary care centre and the Medical Information Mart for Intensive Care IV database (MIMIC-IV). Using the subset of laboratory orders also including procalcitonin (PCT), an analogous model was trained with PCT as an additional feature. RESULTS: After exclusion, 1 381 358 laboratory requests (2016 from sepsis cases) were available. The CBC model shows an area under the receiver operating characteristic (AUROC) of 0.872 (95% CI, 0.857-0.887). External validations show AUROCs of 0.805 (95% CI, 0.787-0.824) for University Medicine Greifswald and 0.845 (95% CI, 0.837-0.852) for MIMIC-IV. The model including PCT revealed a significantly higher AUROC (0.857; 95% CI, 0.836-0.877) than PCT alone (0.790; 95% CI, 0.759-0.821; P < 0.001). CONCLUSIONS: Our results demonstrate that routine CBC results could significantly improve diagnosis of sepsis when combined with ML. The CBC model can facilitate early sepsis prediction in non-ICU patients with high robustness in external validations. Its implementation in clinical decision support systems has strong potential to provide an essential time advantage and increase patient safety.

Sleep characteristics and parameters of bone turnover and strength in the adult population: results from the Study of Health in Pomerania-TREND.

Poor sleep quality or sleep deprivation may be related to decreased bone mineral density. We aimed to assess whether associations of sleep characteristics and bone turnover or strength are present in adults from the general population and whether these are independent of common risk factors such as sex, age, and obesity. A total of 1037 participants from the Study of Health in Pomerania-TREND underwent laboratory-based polysomnography and quantitative ultrasound measurements at the heel. Of these participants, 804 completed standardised questionnaires to assess daytime sleepiness, insomnia, and sleep quality. Serum concentrations of two bone turnover markers, intact amino-terminal propeptide of type 1 procollagen (P1NP) and carboxy-terminal telopeptide of type 1 collagen (CTX) were measured. Cross-sectional associations of polysomnography variables (total sleep time, sleep efficiency, time spent wake after sleep onset, oxygen desaturation index, apnea-hypopnea index, and obstructive sleep apnea [OSA]), as well as sleep questionnaire scores with the bone turnover markers and the ultrasound-based stiffness index were assessed in linear regression models. In adjusted models, higher insomnia scores and lower sleep quality scores were related to a higher bone turnover in women but not in men. However, associations between polysomnography variables or questionnaire scores and the stiffness index were absent. Our study provides limited evidence for relationships between sleep characteristics and bone turnover and strength independent of common risk factors for OSA and osteoporosis. Nevertheless, women reporting poor sleep or insomnia in combination with risk factors for osteoporosis might benefit from an evaluation of bone health.

Estimates of protection levels against SARS-CoV-2 infection and severe COVID-19 in Germany before the 2022/2023 winter season: the IMMUNEBRIDGE project.

PURPOSE: Despite the need to generate valid and reliable estimates of protection levels against SARS-CoV-2 infection and severe course of COVID-19 for the German population in summer 2022, there was a lack of systematically collected population-based data allowing for the assessment of the protection level in real time. METHODS: In the IMMUNEBRIDGE project, we harmonised data and biosamples for nine population-/hospital-based studies (total number of participants n = 33,637) to provide estimates for protection levels against SARS-CoV-2 infection and severe COVID-19 between June and November 2022. Based on evidence synthesis, we formed a combined endpoint of protection levels based on the number of self-reported infections/vaccinations in combination with nucleocapsid/spike antibody responses ("confirmed exposures"). Four confirmed exposures represented the highest protection level, and no exposure represented the lowest. RESULTS: Most participants were seropositive against the spike antigen; 37% of the participants ≥ 79 years had less than four confirmed exposures (highest level of protection) and 5% less than three. In the subgroup of participants with comorbidities, 46-56% had less than four confirmed exposures. We found major heterogeneity across federal states, with 4-28% of participants having less than three confirmed exposures. CONCLUSION: Using serological analyses, literature synthesis and infection dynamics during the survey period, we observed moderate to high levels of protection against severe COVID-19, whereas the protection against SARS-CoV-2 infection was low across all age groups. We found relevant protection gaps in the oldest age group and amongst individuals with comorbidities, indicating a need for additional protective measures in these groups.

Diagnostic sample transport via pneumatic tube systems: data logger and their algorithms are sensitive to transport effects.

OBJECTIVES: Many hospitals use pneumatic tube systems (PTS) for transport of diagnostic samples. Continuous monitoring of PTS and evaluation prior to clinical use is recommended. Data loggers with specifically developed algorithms have been suggested as an additional tool in PTS evaluation. We compared two different data loggers. METHODS: Transport types - courier, conventional (cPTS) and innovative PTS (iPTS) - were monitored using two data loggers (MSR145® logger, CiK Solutions GmbH, Karlsruhe, Germany, and a prototype developed at the University Medicine Greifswald). Data loggers differ in algorithm, recording frequencies and limit of acceleration detection. Samples from apparently healthy volunteers were split among the transport types and results for 37 laboratory measurands were compared. RESULTS: For each logger specific arbitrary units were calculated. Area-under-the-curve (AUC)-values (MSR145®) were lowest for courier and highest for iPTS and increased with increasing recording frequencies. Stress (St)-values (prototype logger) were obtained in kmsu (1,000*mechanical stress unit) and were highest for iPTS as well. Statistical differences between laboratory measurement results of transport types were observed for three measurands sensitive for hemolysis. CONCLUSIONS: The statistical, but not clinical, differences in the results for hemolysis sensitive measurands may be regarded as an early sign of preanalytical impairment. Both data loggers record this important interval of beginning mechanical stress with a high resolution indicating their potential to facilitate early detection of preanalytical impairment. Further studies should identify suitable recording frequencies. Currently, evaluation and monitoring of diagnostic sample transport should not only rely on data loggers but also include diagnostic samples.

Implications of monoclonal gammopathy and isoelectric focusing pattern 5 on the free light chain kappa diagnostics in cerebrospinal fluid.

OBJECTIVES: Oligoclonal bands (OCB) analysis is the reference standard for detecting an intrathecal IgG synthesis. Alongside OCB, free light chains kappa (FLCκ) are considered an additional sensitive biomarker for determining patterns 2 or 3, indicating intrathecal Ig synthesis. However, kFLC IF is not suitable for detecting a monoclonal pattern 5. The primary aim of this study was to evaluate the impact of incorporating FLCκ analysis into routine cerebrospinal fluid (CSF) diagnostics instead of OCB testing on the rate of missed monoclonal IgG detection. METHODS: A two-center retrospective biomarker study was conducted. OCB were identified using isoelectric focusing in polyacrylamide gels followed by silver staining or in agarose gels followed by immunofixation. FLCκ were quantified using nephelometry and FLCκ assay (Siemens). RESULTS: Out of a combined total of 17,755 OCB analyses conducted between 2011 and 2021, a subset of 269 cases (1.5 %) exhibited pattern 5. 98 samples (36 %), which included 18 samples with intrathecal inflammation as determined by additional OCB pattern 2 were included in the FLCκ analysis. Of those, 16 (89 %) had intrathecal FLCκ synthesis. CONCLUSIONS: While FLCκ offers a promising avenue for detecting an intrathecal inflammation, the pattern 5, though rare, remains a valuable additional finding of OCB analysis. A combined approach of FLCκ and OCB analysis is recommended for a comprehensive assessment of the humoral intrathecal immune response.

Serum lipoprotein subfractions are associated with the periodontal status: Results from the population-based cohort SHIP-TREND.

AIM: To investigate the medium-term associations of serum protein subfractions derived from proton nuclear magnetic resonance (1 H-NMR) spectroscopy with periodontitis and tooth loss. MATERIALS AND METHODS: A total of 3031 participants of the cohort Study of Health in Pomerania (SHIP-TREND) were included. In addition to conventional serum testing, serum lipoprotein contents and subfractions were analysed by 1 H-NMR spectroscopy. Confounder-adjusted associations of lipoprotein variables with periodontitis and the number of missing teeth variables were analysed using mixed-effects models with random intercepts for time across individuals, accounting for multiple testing. RESULTS: While only spurious associations between lipoprotein levels from conventional blood tests were found-that is, triglycerides were associated with mean clinical attachment level (CAL) and low-density lipoprotein cholesterol/high-density lipoprotein cholesterol (LDL-C/HDL-C) ratio with the number of missing teeth - several associations emerged from serum lipoprotein subfractions derived from 1 H-NMR analysis. Specifically, elevated LDL triglycerides were associated with higher levels of mean probing depth (PD), mean CALs, and increased odds of having <20 teeth. HDL-4 cholesterol levels were inversely associated with mean PD. Systemic inflammation (C-reactive protein) might mediate the effects of LDL and HDL triglyceride contents on periodontitis severity. CONCLUSIONS: Several associations between serum lipoprotein subfractions and periodontitis were observed. As the underlying biochemical mechanisms remain unclear, further research is needed.

Body composition markers are associated with changes in inflammatory markers but not vice versa: A bi-directional longitudinal analysis in a population-based sample.

BACKGROUND AND AIM: Growing body of evidence consistently link obesity and inflammation, Although the direction of the association is still unclear. We aimed to investigate longitudinal associations of body anthropometric, composition and fat distribution parameters with inflammatory markers and vice versa. METHOD AND RESULTS: We used data from 2464 individuals of the SHIP-TREND cohort with a median follow-up of 7 years. Linear regression models adjusted for confounders were used to analyze associations of standardized body composition markers derived from classic anthropometry, bioelectrical impedance analysis (BIA) and magnetic resonance imaging (MRI) at baseline with changes in inflammatory markers (C-reactive protein (CRP), white blood cell (WBC), fibrinogen) and vice versa. Higher level of anthropometric markers at baseline were associated with an increase in the change of inflammatory markers. A 13.5 cm higher waist circumference (WC), 16.0 kg body weight and 7.76 % relative fat mass (FM) at baseline was associated with a change in CRP of 0.52 mg/L (95 % confidence interval [CI]: 0.29 to 0.74), 0.51 mg/L (95 % CI: 0.29; 0.74) and 0.58 mg/L (95 % CI: 0.34; 0.82) respectively. Absolute FM showed the strongest association with changes in serum fibrinogen levels (ß for 8.69 kg higher FM: 0.07 g/L; 95 % CI: 0.05; 0.09). Baseline inflammatory markers were only associated with changes in hip circumference. CONCLUSION: Our study indicates the importance of anthropometric, body composition and fat distribution markers as a risk factor for the development of inflammation. To prevent inflammatory-related complications, important is to take measures against the development of obesity.

Prognostic Value of Cardiovascular Biomarkers in the Population.

Importance: Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies. Objective: To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors. Design, Setting, and Participants: Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years. Exposure: Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein. Main Outcomes and Measures: The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses. Results: The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people. Conclusions and Relevance: Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.

Circulating microRNA miR-425-5p Associated with Brain White Matter Lesions and Inflammatory Processes.

White matter lesions (WML) emerge as a consequence of vascular injuries in the brain. While they are commonly observed in aging, associations have been established with neurodegenerative and neurological disorders such as dementia or stroke. Despite substantial research efforts, biological mechanisms are incomplete and biomarkers indicating WMLs are lacking. Utilizing data from the population-based Study of Health in Pomerania (SHIP), our objective was to identify plasma-circulating micro-RNAs (miRNAs) associated with WMLs, thus providing a foundation for a comprehensive biological model and further research. In linear regression models, direct association and moderating factors were analyzed. In 648 individuals, we identified hsa-miR-425-5p as directly associated with WMLs. In subsequent analyses, hsa-miR-425-5p was found to regulate various genes associated with WMLs with particular emphasis on the SH3PXD2A gene. Furthermore, miR-425-5p was found to be involved in immunological processes. In addition, noteworthy miRNAs associated with WMLs were identified, primarily moderated by the factors of sex or smoking status. All identified miRNAs exhibited a strong over-representation in neurodegenerative and neurological diseases. We introduced hsa-miR-425-5p as a promising candidate in WML research probably involved in immunological processes. Mir-425-5p holds the potential as a biomarker of WMLs, shedding light on potential mechanisms and pathways in vascular dementia.

Impact of Maternal Pre-Pregnancy Underweight on Cord Blood Metabolome: An Analysis of the Population-Based Survey of Neonates in Pomerania (SNiP).

Intrauterine growth restriction leads to an altered lipid and amino acid profile in the cord blood at the end of pregnancy. Pre-pregnancy underweight is an early risk factor for impaired fetal growth. The aim of this study was to investigate whether a pre-pregnancy body mass index (ppBMI) of <18.5 kg/m2, as early as at the beginning of pregnancy, is associated with changes in the umbilical cord metabolome. In a sample of the Survey of Neonates in Pomerania (SNIP) birth cohort, the cord blood metabolome of n = 240 newborns of mothers with a ppBMI of <18.5 kg/m2 with n = 208 controls (ppBMI of 18.5-24.9 kg/m2) was measured by NMR spectrometry. A maternal ppBMI of <18.5 kg/m2 was associated with increased concentrations of HDL4 cholesterol, HDL4 phospholipids, VLDL5 cholesterol, HDL 2, and HDL4 Apo-A1, as well as decreased VLDL triglycerides and HDL2 free cholesterol. A ppBMI of <18.5 kg/m2 combined with poor intrauterine growth (a gestational weight gain (GWG) < 25th percentile) was associated with decreased concentrations of total cholesterol; cholesterol transporting lipoproteins (LDL4, LDL6, LDL free cholesterol, and HDL2 free cholesterol); LDL4 Apo-B; total Apo-A2; and HDL3 Apo-A2. In conclusion, maternal underweight at the beginning of pregnancy already results in metabolic changes in the lipid profile in the cord blood, but the pattern changes when poor GWG is followed by pre-pregnancy underweight.

Integrative Analyses of Circulating Proteins and Metabolites Reveal Sex Differences in the Associations with Cardiac Function among DCM Patients.

Dilated cardiomyopathy (DCM) is characterized by reduced left ventricular ejection fraction (LVEF) and left or biventricular dilatation. We evaluated sex-specific associations of circulating proteins and metabolites with structural and functional heart parameters in DCM. Plasma samples (297 men, 71 women) were analyzed for proteins using Olink assays (targeted analysis) or LC-MS/MS (untargeted analysis), and for metabolites using LC MS/MS (Biocrates AbsoluteIDQ p180 Kit). Associations of proteins (n = 571) or metabolites (n = 163) with LVEF, measured left ventricular end diastolic diameter (LVEDDmeasured), and the dilation percentage of LVEDD from the norm (LVEDDacc. to HENRY) were examined in combined and sex-specific regression models. To disclose protein-metabolite relations, correlation analyses were performed. Associations between proteins, metabolites and LVEF were restricted to men, while associations with LVEDD were absent in both sexes. Significant metabolites were validated in a second independent DCM cohort (93 men). Integrative analyses demonstrated close relations between altered proteins and metabolites involved in lipid metabolism, inflammation, and endothelial dysfunction with declining LVEF, with kynurenine as the most prominent finding. In DCM, the loss of cardiac function was reflected by circulating proteins and metabolites with sex-specific differences. Our integrative approach demonstrated that concurrently assessing specific proteins and metabolites might help us to gain insights into the alterations associated with DCM.

Circulating Metabolome and White Matter Hyperintensities in Women and Men.

BACKGROUND: White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. METHODS: We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)<0.05 were considered significant. RESULTS: In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (PFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (PFDR.full.adj=1.40×10-7) and in both the pooled sample (PFDR.full.adj=1.66×10-4) and statin-untreated (PFDR.full.adj=1.65×10-6) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (PFDR=0.047). CONCLUSIONS: Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.

Periodontitis and systemic inflammation as independent and interacting risk factors for mortality: evidence from a prospective cohort study.

BACKGROUND: Recent studies have highlighted the role of low-grade systemic inflammation in linking periodontitis to cardiovascular disease (CVD) outcomes, but many aspects remain unclear. This study examines the independent and reciprocal associations of periodontitis and low-grade systemic inflammation with all-cause and CVD mortality in a large-scale cohort. METHODS: A total of 3047 participants from the prospective, population-based Study of Health in Pomerania (SHIP-START) were followed for a period of 13.0 ± 2.4 years. For the association between various inflammation/periodontitis measures and mortality, hazard ratios (HRs) were obtained from covariate-adjusted Cox proportional hazards models. Interactions were analysed in joint models: on the multiplicative scale, HRs were reported and on the additive scale, relative excess risks due to interaction (RERI) were calculated. Subject and variable-specific interval records were used to account for time-varying exposures and covariates. RESULTS: During the observation period, 380 (12.5%) individuals died from CVD (n = 125) or other causes (n = 255). All markers of periodontitis and inflammation showed apparent associations with all-cause mortality (HRs per SD-increase: mean PPD: 1.068 (95% confidence interval (CI): 0.988-1.155), mean CAL: 1.205 (95% CI: 1.097-1.323), missing teeth: 1.180 (95% CI: 1.065-1.307), periodontitis score: 1.394 (95% CI: 1.202-1.616), leukocytes: 1.264 (95% CI: 1.163-1.374), fibrinogen: 1.120 (95% CI: 1.030-1.218), CRP: 1.231 (95% CI: 1.109-1.366), inflammation score: 1.358 (95% CI: 1.210-1.523)). For CVD mortality, all PPD related variables showed significant associations. Interaction modelling revealed some variation with respect to mortality type and exposure combinations. On the additive scale, RERIs for periodontitis score and inflammation score implied 18.9% and 27.8% excess mortality risk for all-cause and CVD mortality, respectively. On the multiplicative scale, the HRs for interaction were marginal. CONCLUSIONS: Both periodontitis and inflammation were significantly associated with all-cause mortality and CVD mortality. On the additive scale, a substantial excess risk was observed due to the interaction of periodontitis and inflammation, suggesting that the greatest treatment benefit may be achieved in patients with both periodontitis and high systemic inflammation. As periodontal therapy has been reported to also reduce systemic inflammation, the possibility of a reduction in CVD mortality risk by anti-inflammatory treatments, including periodontal interventions, seems worthy of further investigation.

Association of plasma chemerin with all-cause and disease-specific mortality - results from a population-based study.

BACKGROUND AND OBJECTIVES: Various cross-sectional studies have observed an association between high circulating concentrations of the adipokine chemerin and an unfavorable metabolic profile. However, the prognostic value of chemerin for the risk of associated diseases and mortality was examined only in a few studies mostly using small and highly selected patient populations. We aimed to analyze the association between plasma chemerin concentrations and all-cause as well as cause-specific mortality in the general population. STUDY DESIGN AND METHODS: From the Study of Health in Pomerania (SHIP), participants of two independent cohorts (SHIP-START-1 [n = 3037], SHIP-TREND-0 [n = 4193]) were followed up for 15 and 9 years (median), respectively. The association between plasma chemerin and all-cause mortality was analyzed using multivariable Cox proportional hazard regression models. Additionally, cause-specific hazards for cardiovascular disease (CVD) and cancer mortality were modeled considering competing events. RESULTS: A total number of 507 and 208 deaths occurred during follow-up in SHIP-START-1 and SHIP-TREND-0, respectively. Multivariable regression analyses revealed a significant association between high plasma chemerin concentrations and greater overall mortality that was independent of major confounders. Each 30 ng/mL increase in chemerin was associated with a 17% higher risk of all-cause mortality (95%-confidence interval: 1.10-1.26). Cause-specific analyses further showed that the chemerin concentration was significantly associated with cancer mortality but not with CVD mortality. CONCLUSION: The present study detected a positive association between plasma chemerin concentrations and all-cause mortality in a large population-based study sample. Cause-specific analyses have shown that chemerin is likely to play a decisive role in cancer-related deaths. However, a direct association with cardiovascular mortality could not be established.

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts.

BACKGROUND: Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways. METHODS: We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed. RESULTS: We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism. CONCLUSION: Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.

Genetic Variants in WNT16 and PKD2L1 Locus Affect Heel Ultrasound Bone Stiffness: Analyses from the General Population and Patients Evaluated for Osteoporosis.

Osteoporosis, a complex chronic disease with increasing prevalence, is characterised by reduced bone mineral density (BMD) and increased fracture risk. The high heritability of BMD suggests substantial impact of the individual genetic disposition on bone phenotypes and the development of osteoporosis. In the past years, genome-wide association studies (GWAS) identified hundreds of genetic variants associated with BMD or osteoporosis. Here, we analysed 1103 single nucleotide polymorphisms (SNPs), previously identified as associated with estimated BMD (eBMD) in the UK Biobank. We assessed whether these SNPs are related to heel stiffness index obtained by quantitative ultrasound in 5665 adult participants of the Study of Health in Pomerania (SHIP). We confirmed 45 significant associations after correction for multiple testing. Next, we analysed six selected SNPs in 631 patients evaluated for osteoporosis [rs2707518 (CPED1/WNT16), rs3779381 (WNT16), rs115242848 (LOC101927709/EN1), rs10239787 (JAZF1), rs603424 (PKD2L1) and rs6968704 (JAZF1)]. Differences in minor allele frequencies (MAF) of rs2707518 and rs3779381 between SHIP participants (higher MAF) and patients evaluated for osteoporosis (lower MAF) indicated a protective effect of the minor allele on bone integrity. In contrast, differences in MAF of rs603424 indicated a harmful effect. Co-localisation analyses indicated that the rs603424 effect may be mediated via stearoyl-CoA desaturase (SCD) expression, an enzyme highly expressed in adipose tissue with a crucial role in lipogenesis. Taken together, our results support the role of the WNT16 pathway in the regulation of bone properties and indicate a novel causal role of SCD expression in adipose tissue on bone integrity.

Association of osteopontin with kidney function and kidney failure in chronic kidney disease patients: the GCKD study.

BACKGROUND: Osteopontin (OPN), synthesized in the thick ascending limb of Henle's loop and in the distal tubule, is involved in the pathogenesis of kidney fibrosis, a hallmark of kidney failure (KF). In a cohort of chronic kidney disease (CKD) patients, we evaluated OPN's association with kidney markers and KF. METHODS: OPN was measured from baseline serum samples of German Chronic Kidney Disease study participants. Cross-sectional regression models for estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) as well as Cox regression models for all-cause mortality and KF were evaluated to estimate the OPN effect. Additionally, the predictive ability of OPN and time-dependent population-attributable fraction were evaluated. RESULTS: Over a median follow-up of 6.5 years, 471 KF events and 629 deaths occurred among 4950 CKD patients. One-unit higher log(OPN) was associated with 5.5 mL/min/1.73 m2 lower eGFR [95% confidence interval (95% CI) -6.4 to -4.6] and 1% change in OPN with 0.7% higher UACR (estimated effect 0.7, 95% CI 0.6-0.8). Moreover, higher OPN levels were associated with a higher risk of KF [hazard ratio (HR) 1.4, 95% CI 1.2-1.7] and all-cause mortality (HR 1.5, 95% CI 1.3-1.8). After 6 years, 31% of the KF events could be attributed to higher OPN levels (95% CI 3%-56%). CONCLUSIONS: In this study, higher OPN levels were associated with kidney function markers worsening and a higher risk for adverse outcomes. A larger proportion of KF could be attributed to higher OPN levels, warranting further research on OPN with regards to its role in CKD progression and possible treatment options.

Body composition markers from classic anthropometry, bioelectrical impedance analysis, and magnetic resonance imaging are associated with inflammatory markers in the general population.

BACKGROUND AND AIM: The associations of body composition markers derived from different modalities with inflammatory markers are unclear. The aim of this study was to determine associations of the body composition markers from different modalities with inflammatory markers in a population-based study. METHODS AND RESULTS: We analyzed data from 4048 participants (2081 women, 51.4%) aged 20-84 years. Linear regression models adjusted for confounding were used to analyze the association of classic anthropometry markers, absolute and relative fat mass, absolute fat-free mass (FFM), and body cell mass (BCM) assessed by bioelectrical impedance analysis, subcutaneous, visceral, and liver fat from magnetic resonance imaging (MRI), with markers of inflammation. We found positive associations of classic anthropometry markers, total body fat, subcutaneous, visceral, and liver fat, with all inflammatory markers. Waist circumference (WC) showed the strongest association with high-sensitivity C-reactive protein (hsCRP) (ß: 1.39; 95% confidence interval [CI]: 1.22 to 1.56) and white blood cell (WBC) (0.39; 0.29 to 0.48), whereas visceral fat showed the strongest association with ferritin (41.9; 34.7 to 49.0). Relative body fat was strongly associated with hsCRP (1.39; 1.20 to 1.58), fibrinogen (0.29; 0.27 to 0.32), and WBC (0.35; 0.25 to 0.46). Conversely, we found inverse associations of body height, FFM, and BCM with hsCRP, fibrinogen, and WBC. CONCLUSIONS: Our study indicates the importance of WC as an easily measured marker for early inflammation. MRI-assessed markers of central obesity seem to be most strongly related to ferritin.

Low-grade inflammation is associated with a heterogeneous lipoprotein subclass profile in an apparently healthy population sample.

BACKGROUND AND AIMS: Prevention measures for cardiovascular diseases (CVD) have shifted their focus from lipoproteins to the immune system. However, low-grade inflammation and dyslipidemia are tightly entangled. The objective of this study was to assess the relations between a broad panel of inflammatory biomarkers and lipoprotein subclass parameters. METHODS: We utilized data from the population-based Study of Health in Pomerania (SHIP-TREND, n = 403). Plasma concentrations of 37 inflammatory markers were measured by a bead-based assay. Furthermore, we employed nuclear magnetic resonance spectroscopy to measure total cholesterol, total triglycerides, total phospholipids as well as the fractional concentrations of cholesterol, triglycerides, phospholipids, ApoA1, ApoA2 and ApoB in all major lipoprotein subclasses. Associations between inflammatory biomarkers and lipoprotein subclasses were analyzed by adjusted linear regression models. RESULTS: APRIL, BAFF, TWEAK, sCD30, Pentraxin-3, sTNFR1, sTNFR2, Osteocalcin, Chitinase 3-like 1, IFN-alpha2, IFN-gamma, IL-11, IL-12p40, IL-29, IL-32, IL-35, TSLP, MMP1 and MMP2 were related with lipoprotein subclass components, forming two distinct clusters. APRIL had inverse relations to HDL-C (total and subclasses) and HDL Apo-A1 and Apo-A2 content. MMP-2 was inversely related to VLDL-C (total and subclasses), IDL-C as well as LDL5/6-C and VLDL-TG, IDL-TG, total triglycerides as well as LDL5/5-TG and HDL4-TG. Additionally, we identified a cluster of cytokines linked to the Th1-immune response, which were associated with an atherogenic lipoprotein profile. CONCLUSION: Our findings expand the existing knowledge of inflammation-lipoprotein interactions, many of which are suggested to be involved in the pathogeneses of chronic non-communicable diseases. The results of our study support the use of immunomodulatory substances for the treatment and possibly prevention of CVD.