Next-generation (postgenomic) biomarkers from the nascent field of glycomics now offer fresh vistas for innovation in chronic disease biomarkers and system diagnostics in clinical medicine. Our previous work has shown an association between hypertension and immunoglobulin G (IgG) glycome composition, suggesting that individual variation in N-glycosylation of IgG might contribute to hypertension pathogenesis. The present study examined, for the first time to the best of our knowledge, the IgG N-glycans as potential biomarkers for hypertension in the Kazakh population. The profile of 60 N-glycopeptides of IgG subclass isolated from plasma samples of 150 Kazakh study participants was analyzed by nano ultra-performance liquid chromatography with mass spectrometry. Fourteen IgG subclass-specific Fc N-glycopeptide structures, along with one derived glycosylation trait in subclasses IgG2/3 and IgG4, were found to correlate with systolic blood pressure and/or diastolic blood pressure. For differentiation of hypertension and healthy status in the Kazakh population sample, the receiver operating characteristic curve analysis showed that the performance of the model, including nine IgG N-glycans, was greater than the traditional gender, age, and body mass index based model (p < 0.05). This study indicates that alteration in Fc N-glycopeptide profiles of plasma IgG subclasses is associated with blood pressure status in the Kazakh population. IgG N-glycosylation profiles may serve as potential biomarkers for hypertension in the Kazakhs, thus contributing to move toward personalized medicine. Further studies of postgenomic glycomic biomarkers in cardiovascular and chronic diseases are timely and called for.
Background: Epidemiological studies observing inconsistent associations of telomere length (TL) with ischemic stroke (IS) are susceptible to bias according to reverse causation and residual confounding. We aimed to assess the causal association between TL, IS, and the subtypes of IS, including large artery stroke (LAS), small vessel stroke (SVS), and cardioembolic stroke (CES) by performing a series of two-sample Mendelian randomization (MR) approaches. Methods: Seven single nucleotide polymorphisms (SNPs) were involved as candidate instrumental variables (IVs), summarized from a genome-wide meta-analysis including 37,684 participants of European descent. We analyzed the largest ever genome-wide association studies of stroke in Europe from the MEGASTROKE collaboration with 40,585 stroke cases and 406,111 controls. The weighted median (WM), the penalized weighted median (PWM), the inverse variance weighted (IVW), the penalized inverse variance weighted (PIVW), the robust inverse variance weighted (RIVW), and the Mendelian randomization-Egger (MR-Egger) methods were conducted for the MR analysis to estimate a causal effect and detect the directional pleiotropy. Results: No significant association between genetically determined TL with overall IS, LAS, or CES were found (all p > 0.05). SVS was associated with TL by the RIVW method (odds ratio (OR) = 0.72, 95% confidence interval (CI): 0.54–0.97, p = 0.028), after excluding rs9420907, rs10936599, and rs2736100. Conclusions: By a series of causal inference approaches using SNPs as IVs, no strong evidence to support the causal effect of shorter TL on IS and its subtypes were found.
Male infertility is an important global health burden that can benefit from novel biomarkers and diagnostics innovation. Aberrant methylation of the imprinted genes H19 and SNRPN (small nuclear ribonucleoprotein polypeptide N) in sperm DNA has been implicated in abnormal sperm parameters and male infertility. However, whether certain methylation patterns of one or multiple CpG sites within an imprinted gene are pathological for multiple sperm defects remains poorly understood. To examine the diagnostic potential of certain methylation patterns of CpG sites for multiphenotype defects in human sperm, the sperm DNA methylation patterns of individual CpG sites within imprinting control regions (ICRs) of imprinted genes H19 and SNRPN were measured by bisulfite pyrosequencing in a Han Chinese population sample: 39 oligoasthenozoospermia (OA) patients, 36 asthenoteratozoospermia (AT) patients, and 50 normozoospermia (N) controls. A partial least squares discriminant analysis model was built with the CpG sites as independent variables. Among the 16 CpG sites screened, the methylation patterns of eight CpG sites within H19-ICR (CpG sites 1, 6-9, 12 and 15-16), and eight CpG sites within SNRPN-ICR (CpG sites 2, 5-6, 8-10, 13, and 16) correctly classified 74.4% and 72.0% of the samples in terms of male fertile status, respectively. Furthermore, by combination of these 16 selected CpG sites within ICRs of H19 and SNRPN, 88.0% of the samples could be successfully classified. Our study demonstrates that methylation profiles of CpG sites within ICRs of imprinted genes H19 and SNRPN may potentially serve as epigenomic biomarkers for assessment of infertility in men with multiple sperm defects. Further studies in independent population samples are called for diagnostic significance of methylation patterns of CpG sites within imprinted genes.
Background: DNA methylation in sputum has been an attractive candidate biomarker for the non-invasive screening and detection of lung cancer. Materials and Methods: Databases including PubMed, Ovid, Cochrane library, Web of Science databases, Chinese Biological Medicine (CBM), Chinese National Knowledge Infrastructure (CNKI), Wanfang, Vip Databases and Google Scholar were searched to collect the diagnostic trials on aberrant DNA methylation in the screening and detection of lung cancer published until 1 December 2016. Indirect comparison meta-analysis was used to evaluate the diagnostic value of the included candidate genes. Results: The systematic literature search yielded a total of 33 studies including a total of 4801 subjects (2238 patients with lung cancer and 2563 controls) and covering 32 genes. We identified that methylated genes in sputum samples for the early screening and auxiliary detection of lung cancer yielded an overall sensitivity of 0.46 (0.41–0.50) and specificity of 0.83 (0.80–0.86). Combined indirect comparisons identified the superior gene of SOX17 (sensitivity: 0.84, specificity: 0.88), CDO1 (sensitivity: 0.78, specificity: 0.67), ZFP42 (sensitivity: 0.87, specificity: 0.63) and TAC1 (sensitivity: 0.86, specificity: 0.75). Conclusions: The present meta-analysis demonstrates that methylated SOX17, CDO1, ZFP42, TAC1, FAM19A4, FHIT, MGMT, p16, and RASSF1A are potential superior biomarkers for the screening and auxiliary detection of lung cancer.
Suboptimal health status (SHS) is a physical state between health and disease and is characterized by the symptoms of health complaints, general weakness and low energy within a period of 3 months. 1 A comprehensive Suboptimal Health Status Questionnaire-25 (SHSQ-25) was used to assess SHS, with the SHSQ-25 accounting for the multidimensionality of SHS by assessing the following: (a) fatigue, (b) the cardiovascular system, (c) the digestive tract, (d) the immune system and (e) mental status. 2 To date, the SHSQ-25 has AbstractSuboptimal health status (SHS), a physical state between health and disease, is a subclinical and reversible stage of chronic disease. Previous studies have shown alterations in the intestinal microbiota in patients with some chronic diseases. This study aimed to investigate the association between SHS and intestinal microbiota in a casecontrol study with 50 SHS individuals and 50 matched healthy controls. Intestinal microbiota was analysed by MiSeq 250PE. Alpha diversity of intestinal microbiota in SHS individuals was higher compared with that of healthy controls (Simpson index, W = 2238, P = .048). Beta diversity was different between SHS and healthy controls (P = .018). At the phylum level, the relative abundance of Verrucomicrobia was higher in the SHS group than that in the controls (W = 2201, P = .049). Compared with that of the control group, nine genera were significantly higher and five genera were lower in abundance in the SHS group (all P < .05). The intestinal microbiota, analysed by a random forest model, was able to distinguish individuals with SHS from the controls, with an area under the curve of 0.79 (95% confidence interval: 0.77-0.81). We demonstrated that the alteration of intestinal microbiota occurs with SHS, an early stage of disease, which might shed light on the importance of intestinal microbiota in the primary prevention of noncommunicable chronic diseases. K E Y W O R D S16S rRNA, intestinal microbiota, LEfSe analysis, random forest tree, suboptimal health status
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