PubMed HealthSearch

PubMed · 42015341

Genetic and Lifestyle Factors Influence High 1-Hour Plasma Glucose, a Predictor of Type 2 Diabetes Mellitus.

Abstract

BACKGRUOUND: High 1-hour plasma glucose (1-h PG) level has been proposed by the International Diabetes Federation to identify high-risk individuals and diagnose type 2 diabetes mellitus (T2DM). In a longitudinal cohort, we examined T2DM risk, &#x3b2;-cell function, and the effects of genetic and lifestyle factors on high 1-h PG. METHODS: We analyzed 7,464 participants without T2D at baseline from a community-based prospective cohort in Korea, who underwent biennial 2-h 75-g oral glucose tolerance tests over 14 years. Incident T2D risk were assessed across 1-h PG groups: < 155, 155-208, and &#x2265; 209 mg/dL. In 6,588 participants with at least two 1-h PG measurements, we analyzed 1-h PG trajectories by T2D polygenic risk score (PRS; low, 1st quintile; intermediate, 2nd-4th quintiles; high, 5th quintile) and lifestyle, assessed using Life's Essential 8. RESULTS: Compared to the <155 mg/dL group, hazard ratios for T2DM were 3.34 (95% confidence interval [CI], 2.99 to 3.74; P<0.001) for 155-208 mg/dL, and 6.81 (95% CI, 5.81 to 7.98; P<0.001) for &#x2265;209 mg/dL. Both groups had lower baseline disposition index compared to the <155 mg/dL group (57.3% and 72.7%, respectively; both P<0.001). Higher T2DM PRS was associated with elevated baseline 1-h PG (low: 131 mg/dL, intermediate: 141 mg/dL, high: 151 mg/dL) and faster increase in 1-h PG (1.36 vs. 1.85 vs. 2.21 mg/dL/year; all P<0.001). Importantly, healthy lifestyle attenuated the rate of increase across all PRS groups. CONCLUSION: High 1-h PG predicts T2DM risk and is associated with &#x3b2;-cell dysfunction. The 1-h PG level is influenced by genetic risk and can be modified with a healthy lifestyle.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Soobin Cho, Hyunsuk Lee, Joon Ha, Yeonsoo Park, Joon Ho Moon, Hak Chul Jang, Kyong Soo Park, Nam H Cho, Michael Bergman, Soo Heon Kwak. 2026-04-22. Genetic and Lifestyle Factors Influence High 1-Hour Plasma Glucose, a Predictor of Type 2 Diabetes Mellitus.. https://doi.org/10.4093/dmj.2025.0362

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans