2025年 · 第11卷第03期

Tislelizumab is a next-generation PD-1 monoclonal antibody developed to overcome the limitations of earlier immune checkpoint inhibitors. By eliminating Fcγ receptor binding, it avoids macrophage-mediated T-cell clearance and enhances the antitumor immune response. Unlike conventional PD-1 inhibitors, tislelizumab binds to PD-1 in a way that more closely mimics the natural PD-L1 interaction, potentially improving efficacy and reducing immune-related toxicity. This review highlights its structural advantages, clinical efficacy across multiple cancers, and recent global regulatory approvals. We also discuss key pharmacokinetic features and current challenges, including the need for predictive biomarkers, immune-related adverse events, and combination therapy strategies. Together, these insights may guide the more effective and safer use of tislelizumab in cancer immunotherapy.

Monoclonal antibodies (mAbs) have made significant progress in the treatment of Alzheimer's disease (AD). However, mAbs are associated with adverse effects, including Amyloid-Related Imaging Abnormality (ARIA), which manifests as edema or effusion (ARIA-E) and hemorrhage (ARIA-H). The mechanisms behind these effects are not yet fully understood. Moreover, spontaneous ARIA has been insufficiently explored, and mAb therapies, particularly lecanemab, have mainly focused on patients with the APOE-ε4 allele carrier. This review aims to address this gap by examining the mechanisms of spontaneous ARIA, ARIA induced by mAbs, and the influence of genetic variants on ARIA development. The autoantibody-Aβ-mediated immune response targets excessive Aβ deposits, increasing immune activity through microglial reactivity. The heightened immune response, driven by Aβ accumulation in blood vessels, promotes angiopathy and inflammation, potentially contributing to spontaneous ARIA. The APOE-ε4 allele carrier is more strongly associated with ARIA-E because it redistributes Aβ deposition from the brain to blood vessels, influencing microglial reactivity. The redistribution enhances vascular integrity and reduces the risk of ARIA-H. However, it also increases the likelihood of ARIA-E due to Aβ accumulation in the vasculature, triggering inflammation. In contrast, the development of ARIA-H is linked to increased TREM2 expression and microglial reactivity, leading to impaired vascular integrity and disrupted matrix remodeling, which worsens the condition. Additionally, the adverse effects of mAbs may extend beyond the APOE-ε4 allele, possibly impacting other genetic variants involved in microglial reactivity, Aβ redistribution, and vascular integrity.

Elevated high blood pressure is controlled by complicated, little-understood genetic and epigenetic pathways that are influenced by both heritable and environmental variables. Many adult systolic and diastolic blood pressure-related genomic loci have been identified through previous genome-wide association studies (GWAS); meanwhile, studies specifically on Asian adult populations have not been done. This study aims to comprehensively assess and summarize any gene changes that have been studied and see whether there is a possible influence between epigenetic changes and hypertension in Asian adults.

This evidence-based analysis is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement and has been registered in PROSPERO under registration number [CRD42024622261]. The data were processed qualitatively to assess the risk of bias using the Newcastle-Ottawa Scale (NOS) and Agency for Health Research and Quality (AHRQ) standards as the threshold. Our study in particular shows that epigenetic modifications may play a role in hypertension, particularly in Asian individuals.

A total of 28 studies were selected for qualitative evaluation. In the adult Asian population, 26 publications (92.8%) reported a relationship between blood pressure and epigenetics. Every study describes a distinct gene or location associated with hypo- or hypermethylation. Elevated systolic and diastolic blood pressure was linked to variations of several single-nucleotide polymorphisms (SNPs), cytosine phosphate guanines (CPGs), and other monogenic genes.

Alterations in epigenetic modifications in potential genes or loci are linked to systolic and diastolic blood pressure of Asian adult populations.

Precise risk prediction of chronic diseases is essential for effective preventive care and management. Machine learning (ML) is a promising avenue to enhance chronic disease risk prediction; however, a comprehensive assessment of ML performance across various chronic diseases, populations, and health settings is needed.

This meta-analysis aims to synthesize evidence on the performance of ML techniques for predicting the risks and outcomes of chronic diseases. A literature search was conducted through PubMed, Web of Science, Scopus, Science Direct, Medline, and Embase. Studies applying ML techniques to predict chronic disease risks or outcomes and reporting performance metrics were included. Two reviewers independently screened studies, extracted data, and assessed the risk of bias. Random-effects meta-analysis, subgroup analyses, and meta-regression were performed to estimate pooled performance and explore heterogeneity.

This meta-analysis provides a comprehensive evaluation of the performance of ML techniques in predicting the risks and consequences of chronic diseases. We reported the pooled estimates of performance metrics, such as the area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and F1 score, for each chronic disease. Subgroup analyses and meta-regression identified factors that influence the performance of ML models, such as the ML algorithm, sample size, and data type. This meta-analysis synthesized evidence on ML techniques for chronic disease risk prediction, guiding the development of robust and generalizable ML-based tools. By identifying best practices and addressing challenges, this work advances predictive analytics in healthcare, facilitates translation into clinical practice, and ultimately improve patient outcomes.

The ratio of high-density lipoprotein cholesterol (HDL-C) to low-density lipoprotein cholesterol (LDL-C) predicts cardiovascular disease (CVD) endpoints, yet its prognostic validity in high-risk populations and for type 2 diabetes mellitus (T2DM)-related adverse events remains unestablished.

This study included 32,609 people aged 35-75 years in Fujian Province, China, who were at high risk for CVD. The primary endpoint was all-cause mortality during follow-up. Cox proportional hazard models and restricted cubic spline (RCS) analysis were used to evaluate the correlation between the HDL-C/LDL-C ratio and the endpoints.

On the basis of the restricted RCS curve, the participants were classified as having a low (< 0.3), middle (0.3-0.5), or high (> 0.5) HDL-C/LDL-C ratio. Multivariate Cox regression analyses revealed that the risk of all-cause mortality (HR = 1.48, 95% CI 1.14-1.93, p < 0.01 for low; HR = 1.30, 95% CI 1.06-1.58, p < 0.05 for high) was increased in the low and high groups. Participants without T2DM who were at high risk for CVD had similar prognoses (HR = 1.65, 95% CI 1.19-2.28, p < 0.01 for low; HR = 1.35, 95% CI 1.05-1.74, p < 0.01 for high). However, this association was not found in participants with T2DM who were at high risk for CVD.

HDL-C/LDL-C can be used to predict the prognosis of individuals at high risk for CVD, and maintaining HDL-C/LDL-C ratios between 0.3 and 0.5 may be the most helpful range for this population. Furthermore, maintaining this ratio range holds clinical significance for cohorts without T2DM, although further exploration is needed in this T2DM cohort.

2型糖尿病（T2D）是一种以胰岛素抵抗和糖代谢受损为特征的慢性代谢紊乱，通常在晚期诊断[1].代谢组学为鉴定早期检测T2D的生物标志物提供了一种有前途的方法[2].这项纵向研究使用了韩国基因组和流行病学研究（KoGES）数据，这是一个在2001-2002年招募的10,300名40-69岁个体的队列，每两年随访一次。该研究包括来自6-8期（2012-2016年）的664名参与者，具有完整的代谢组学数据[3].目的是寻找与T2D风险相关的新代谢物生物标志物。本研究采用先进的统计方法，如广义估计方程(GEE)和线性混合效应模型(LMM)，旨在将代谢物确定为T2D发病和进展的早期指标，从而有助于改善韩国成人诊断和干预的精准医疗策略[4,5].

慢性身体疼痛和抑郁症是两个主要的全球健康问题，经常同时发生并共同损害个人的福祉，损害他们维持独立生活方式和社会关系的能力[1].一项对52个国家疼痛患病率的全球研究表明，疼痛的总体患病率估计为27.5%[2]，各国差异显著（9.9%-50.3%）。在中国，一项使用中国次优健康调查数据的研究显示，女性疼痛患病率为39.92%，男性慢性疼痛患病率为32.17%，患病率随着年龄的增长而增加[3].

糖尿病（DM）是一种常见的内分泌代谢紊乱，糖尿病酮症（DK）是一种显著的急性并发症。患有1型糖尿病（T1DM）的个体具有糖尿病酮症酸中毒（DKA）的固有风险。患有T2DM的个体在某些情况下可能发生DK，包括感染、胰岛素治疗中断、压力或过量饮酒。最近的研究表明，补充维生素D可降低从糖尿病前期进展为T2DM的风险，并且它还可能参与预防糖尿病并发症。然而，大多数以前的研究都是观察相关性，而不是干预性试验。

S.Lehrer和P.H.Rheinstein，“人水通道蛋白4和β-淀粉样蛋白的比对可能表明β-淀粉样蛋白参与脑水稳态和预防脑水肿，”慢性病与转化医学9(2023):177-181.https://doi.org/10.1002/cdt3.64.

S.Lehrer和P.H.Rheinstein，“带状疱疹疫苗接种降低帕金森病的风险”，慢性病与转化医学9（2023）：54-57，https://doi.org/10.1002/cdt3.50。