Impact of Core Circadian Gene Variants on Glycemic Parameters and Insulin Resistance in Type 2 Diabetes: A Systematic Review

Circadian rhythm disruption is increasingly implicated in the pathophysiology of type 2 diabetes mellitus (T2DM). Variants in core circadian clock genes - CLOCK (circadian locomotor output cycles kaput), BMAL1/ARNTL (brain and muscle ARNT-like protein 1), CRY1/2 (cryptochrome 1 and 2), PER1-3 (period 1-3), and NR1D1 (REV-ERBα) - and associated melatonin receptor genes may influence glycaemic homeostasis and insulin resistance. This systematic review synthesises evidence published between 2020 and 2025 on associations between these variants and key glycaemic parameters. A systematic search of PubMed/MEDLINE, Embase, Web of Science, and the Cochrane Library was performed following PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies published from January 2020 to December 2025 that examined circadian gene variants or expression in T2DM or at-risk human populations and reported glycaemic or insulin-resistance outcomes were included. Risk of bias was independently assessed using the Newcastle-Ottawa Scale (NOS). Owing to substantial heterogeneity, a narrative synthesis following the Synthesis Without Meta-analysis (SWiM) framework was undertaken; no meta-analysis, formal heterogeneity (I²) metric, or GRADE certainty rating was performed. Six studies of diverse design (case control, cross-sectional, narrative review, and systematic review with meta-analysis) from China, South Africa, Croatia/multi-ethnic, and Spain, collectively involving more than 18,000 participants, met the inclusion criteria. A CLOCK rs1801260 × MTNR1A rs2119882 gene-gene interaction, CRY2 rs11605924, and BMAL1 rs3789327 were significantly associated with elevated fasting plasma glucose (FPG), higher Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), and increased T2DM risk. Reduced expression of core clock genes (BMAL1, CRY1, and PER2) correlated negatively with glycated haemoglobin (HbA1c) and HOMA-IR. BMAL1 rs7950226 was confirmed as a metabolic-syndrome susceptibility variant. Across 2020-2025, circadian gene variants were consistently associated with impaired glycaemic control and insulin resistance in T2DM. Because the available evidence is observational and heterogeneous, these findings suggest potential value in incorporating circadian genetic profiling into precision diabetes risk stratification rather than established causal utility, and prospective validation is required.

Authors

Publication Details

Journal
Cureus
Published
2026-06-26
DOI
https://doi.org/10.7759/cureus.111534
Primary Topic
Circadian rhythm and melatonin
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of Core Circadian Gene Variants on Glycemic Parameters and Insulin Resistance in Type 2 Diabetes: A Systematic Review

W. N. Mohamed, Alaa Fathelrahman Mokhtar Osman, Abdalla Madani Abdelkarim Ismail, Wigdan Ahmed Saeed et al.
Cureus
Circadian rhythm and melatonin
article

Impact of Core Circadian Gene Variants on Glycemic Parameters and Insulin Resistance in Type 2 Diabetes: A Systematic Review

W. N. Mohamed, Alaa Fathelrahman Mokhtar Osman, Abdalla Madani Abdelkarim Ismail, Wigdan Ahmed Saeed, Najwa Mohamed Bakriy Mohamed, Ezdehar Taha, Islam Mustafa Hamid Mohammed
article en

Abstract

Circadian rhythm disruption is increasingly implicated in the pathophysiology of type 2 diabetes mellitus (T2DM). Variants in core circadian clock genes - CLOCK (circadian locomotor output cycles kaput), BMAL1/ARNTL (brain and muscle ARNT-like protein 1), CRY1/2 (cryptochrome 1 and 2), PER1-3 (period 1-3), and NR1D1 (REV-ERBα) - and associated melatonin receptor genes may influence glycaemic homeostasis and insulin resistance. This systematic review synthesises evidence published between 2020 and 2025 on associations between these variants and key glycaemic parameters. A systematic search of PubMed/MEDLINE, Embase, Web of Science, and the Cochrane Library was performed following PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies published from January 2020 to December 2025 that examined circadian gene variants or expression in T2DM or at-risk human populations and reported glycaemic or insulin-resistance outcomes were included. Risk of bias was independently assessed using the Newcastle-Ottawa Scale (NOS). Owing to substantial heterogeneity, a narrative synthesis following the Synthesis Without Meta-analysis (SWiM) framework was undertaken; no meta-analysis, formal heterogeneity (I²) metric, or GRADE certainty rating was performed. Six studies of diverse design (case control, cross-sectional, narrative review, and systematic review with meta-analysis) from China, South Africa, Croatia/multi-ethnic, and Spain, collectively involving more than 18,000 participants, met the inclusion criteria. A CLOCK rs1801260 × MTNR1A rs2119882 gene-gene interaction, CRY2 rs11605924, and BMAL1 rs3789327 were significantly associated with elevated fasting plasma glucose (FPG), higher Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), and increased T2DM risk. Reduced expression of core clock genes (BMAL1, CRY1, and PER2) correlated negatively with glycated haemoglobin (HbA1c) and HOMA-IR. BMAL1 rs7950226 was confirmed as a metabolic-syndrome susceptibility variant. Across 2020-2025, circadian gene variants were consistently associated with impaired glycaemic control and insulin resistance in T2DM. Because the available evidence is observational and heterogeneous, these findings suggest potential value in incorporating circadian genetic profiling into precision diabetes risk stratification rather than established causal utility, and prospective validation is required.

Cureus
Reduced inequalities
Openalex Percentile: Top 9%
Circadian rhythm and melatonin
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.