Predicting Longitudinal Cognitive Decline and Alzheimer's Conversion in Mild Cognitive Impairment Patients Based on Plasma Biomarkers.

The increasing burden of Alzheimer's disease (AD) emphasizes the need for effective diagnostic and therapeutic strategies. Despite available treatments targeting amyloid beta (Aß) plaques, disease-modifying therapies remain elusive. Early detection of mild cognitive impairment (MCI) patients at risk for AD conversion is crucial, especially with anti-Aß therapy. While plasma biomarkers hold promise in differentiating AD from MCI, evidence on predicting cognitive decline is lacking. This study's objectives were to evaluate whether plasma protein biomarkers could predict both cognitive decline in non-demented individuals and the conversion to AD in patients with MCI. This study was conducted as part of the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD), a prospective, community-based cohort. Participants were based on plasma biomarker availability and clinical diagnosis at baseline. The study included MCI (n = 50), MCI-to-AD (n = 21), and cognitively unimpaired (CU, n = 40) participants. Baseline plasma concentrations of six proteins-total tau (tTau), phosphorylated tau at residue 181 (pTau181), amyloid beta 42 (Aß42), amyloid beta 40 (Aß40), neurofilament light chain (NFL), and glial fibrillary acidic protein (GFAP)-along with three derivative ratios (pTau181/tTau, Aß42/Aß40, pTau181/Aß42) were analyzed to predict cognitive decline over a six-year follow-up period. Baseline protein biomarkers were stratified into tertiles (low, intermediate, and high) and analyzed using a linear mixed model (LMM) to predict longitudinal cognitive changes. In addition, Kaplan-Meier analysis was performed to discern whether protein biomarkers could predict AD conversion in the MCI subgroup. This prospective cohort study revealed that plasma NFL may predict longitudinal declines in Mini-Mental State Examination (MMSE) scores. In participants categorized as amyloid positive, the NFL biomarker demonstrated predictive performance for both MMSE and total scores of the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-TS) longitudinally. Additionally, as a baseline predictor, GFAP exhibited a significant association with cross-sectional cognitive impairment in the CERAD-TS measure, particularly in amyloid positive participants. Kaplan-Meier curve analysis indicated predictive performance of NFL, GFAP, tTau, and Aß42/Aß40 on MCI-to-AD conversion. This study suggests that plasma GFAP in non-demented participants may reflect baseline cross-sectional CERAD-TS scores, a measure of global cognitive function. Conversely, plasma NFL may predict longitudinal decline in MMSE and CERAD-TS scores in participants categorized as amyloid positive. Kaplan-Meier curve analysis suggests that NFL, GFAP, tTau, and Aß42/Aß40 are potentially robust predictors of future AD conversion.

Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed a multi-omics data-affinitive artificial intelligence algorithm based on the graph convolutional network that integrates mRNA expression, DNA methylation, and DNA sequencing data. This NSCLC prediction model achieved a 93.7% macro F1-score, indicating that values for false positives and negatives were substantially low, which is desirable for accurate classification. Gene ontology enrichment and pathway analysis of features revealed that two major subtypes of NSCLC, lung adenocarcinoma and lung squamous cell carcinoma, have both specific and common GO biological processes. Numerous biomarkers (i.e., microRNA, long non-coding RNA, differentially methylated regions) were newly identified, whereas some biomarkers were consistent with previous findings in NSCLC (e.g., SPRR1B). Thus, using multi-omics data integration, we developed a promising cancer prediction algorithm.

Alu cell-free DNA concentration, Alu index, and LINE-1 hypomethylation as a cancer predictor.

INTRODUCTION: The liquid biopsy approach, a less-invasive diagnostic tool, enables the detection of disease-specific genetic and epigenetic aberrations. Approximately 66-69% of the human genome may be composed of transposable repetitive elements, including Alu and LINE-1. This study aimed to investigate whether Alu-derived cell-free DNA (cfDNA) concentrations, Alu index, and LINE-1 methylation could be used to distinguish patients with cancers from healthy individuals. METHODS: Two sets of primers, shorter and longer Alu fragments, were used to amplify Alu elements, followed by the quantitation of Alu DNA concentration and its integrity index. LINE-1 methylation status was then analyzed with quantitative PCR using methylation- and unmethylation-specific TaqMan probes. RESULTS: Both Alu index and LINE-1 methylation level were significantly different in comparison between patients with lung or breast cancer and the healthy controls. The area under the ROC curve of the Alu index and LINE-1 hypomethylation was 0.742 and 0.848 for lung cancer, respectively, and 0.724 and 0.890 for breast cancer, respectively. However, Alu longer fragment DNA concentration was significantly correlated with Alu index in comparison to LINE-1 hypomethylation. Regression analysis suggested that the LINE-1 methylation level, rather than the Alu index, was a good discriminator for lung and breast cancers. CONCLUSIONS: This study investigated the genome-wide Alu index and LINE-1 methylation status; their associations with cancers suggested that these combinatory panels could be implemented as a triage test to discriminate cancer patients from healthy individuals.

Effects of fermented rice bran on DEN-induced oxidative stress in mice: GSTP1, LINE-1 methylation, and telomere length ratio.

N-diethylnitrosamine (DEN), a well-known carcinogen, not only induces excessive reactive oxygen species but also suppresses DNA methylation. This study investigated the effect of fermented rice bran (FRB) treatment on DEN-induced oxidative stress through DNA methylation and telomere length analysis. To evaluate the potential protective role of FRB in oxidative stress, two different doses of FRB, DEN, and their combination were administered to mice that were preadapted or not to FRB. Glutathione-S-transferase P1 (GSTP1) methylation levels significantly decreased at 2 and 24 hr after FRB and DEN co-administration in mice with and without pre-adaptation. Moreover, GSTP1 mRNA was upregulated under DEN-induced oxidative stress. Furthermore, changes in long interspersed nuclear element-1 methylation were observed from the viewpoint of genomic instability. In addition, FRB preadapted mice displayed a lower telomere length ratio than the non-adapted mice, suggesting that FRB adaptation offers advantages over the non-adapted conditions in terms of inflammation suppression. PRACTICAL APPLICATIONS: DEN induces excessive ROS, which is associated with oxidative stress on DNA and other cellular components, resulting in inflammation. This study shows that FRB may alleviate DEN-triggered oxidative stress, based on changes in GSTP1, LINE-1 methylation, and telomere length ratios, thereby, revealing the potential of dietary intervention during inflammation. Furthermore, this study furthers the current understanding of DNA methylation mechanisms underlying the antioxidant and anti-inflammatory effects of functional food components. These results indicate that dietary inclusion of FRB may help decrease oxidative DNA damage and its associated inflammation at early stages of a disease.

NLRP1 and NTN1, Deregulated Blood Differentially Methylated Regions in Mild Cognitive Impairment Patients.

Epigenetic dysregulation has been known to be involved in neurodegenerative diseases, including amnestic mild cognitive impairment (MCI). The aim of this study was to investigate the genome-wide DNA methylation analysis, in order to identify epigenetic dysregulation in blood from patients with MCI. Here, we investigated whether epigenetic dysregulation in MCI and whether such an aberration could be detected in blood circulation. Genome-wide bisulfite sequencing targeted 84 million bases covering 3.7 million CpG sites was comparatively analyzed in MCI and control groups. And correlation between DNA methylation and transcriptomic changes was sought. Significant differentially methylated regions (DMRs) distinguishing the MCI and control groups were identified and functionally annotated. Most DMRs specific to MCI were enriched between - 2 kb and + 2 kb of the CpG island start sites located within or near gene promoters. Representative hypo- and hypermethylated DMRs in MCI were confirmed to be correlated to mRNA expression changes with the comparative delta Ct method. DNA methylation aberrations involving metal ion homeostasis, axon growth, inflammasome, and others in this study may be less-invasive, easily measurable blood biomarker candidates for MCI.

Effect of ionizing radiation at low dose on transgenerational carcinogenesis by epigenetic regulation.

The objective of this study was to determine the effect of ionizing radiation (IR) exposure of parents on carcinogenesis of the next generation focusing on the epigenetic perspective to clarify the relationship between radiation dose and carcinogenesis in F1 generation SD rats. F1 generations from pregnant rats (F0) who were exposed to gamma rays were divided into three groups according to the dose of radiation: 10 rad, 30 rad, and untreated. They were intraperitoneally injected with 50 mg/kg of diethylnitrosamine (DEN). Carcinogenesis was analyzed by examining expression levels of tumor suppressor genes (TSG) and other related genes by methylation-specific polymerase chain reaction (MSP). DNA methylation in liver tissues was evaluated to discern epigenetic regulation of transgenerational carcinogenesis vulnerability following IR exposure. Numerous studies have proved that transcriptional inactivation due to hypermethylation of TSG preceded carcinogenesis. Results of this study revealed hypermethylation of tumor suppressor gene SOCS1 in group treated with 30 rad. In addition, genes related to DNA damage response pathway (GSTP1, ATM, DGKA, PARP1, and SIRT6) were epigenetically inactivated in all DEN treated groups. In the case of proto-oncogene c-Myc, DNA hypermethylation was identified in the group with low dose of IR (10 rad). Results of this study indicated that each TSG had different radiation threshold level (dose-independent way) and DEN treatment could affect DNA methylation profile irrelevant of ionizing radiation dose.

Circulating cell-free DNA as a promising biomarker in patients with gastric cancer: diagnostic validity and significant reduction of cfDNA after surgical resection.

PURPOSE: The aim of this study is to determine whether levels of circulating free DNA (cfDNA) increase according to cancer progression, whether they are restored after surgical resection, and to evaluate cfDNA in gastric cancer patients as a useful biomarker. METHODS: A case-control study design was used. Thirty gastric cancer patients and 34 healthy subjects were enrolled from two hospitals in South Korea. The plasma cfDNA of patients with gastric cancer were obtained before surgery and 24 hours after surgery, and then analyzed by a quantitative, real-time polymerase chain reaction. Plasma samples were also obtained from the control group. RESULTS: The mean levels of cfDNA in the healthy control group, patients with early gastric cancer, and with advanced gastric cancer were 79.78 ± 8.12 ng/mL, 106.88 ± 12.40 ng/mL, and 120.23 ± 10.08 ng/mL, respectively (P < 0.01). Sensitivity was 96.67% and specificity was 94.11% when the cutoff value was 90 ng/mL. Variables representing the tumor burden such as tumor size, T stage, TNM stage, and curative resection are also associated with the levels of cfDNA. The levels of cfDNA in the 24-hour-after-surgery group decreased significantly (112.17 ± 13.42 ng/mL vs. 77.93 ± 5.94 ng/mL, P < 0.001) compared to the levels of cfDNA in the preoperation group. CONCLUSION: The changes in the levels of cfDNA can act as reliable biomarkers to detect cancer early, to predict tumor burden, estimate curative resection and even prognosis.