Related Experiment Video
Updated: May 5, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Chronobiological Patterns and Risk of Acute Aortic Dissection: A Clinical Retrospective and Two-Sample Mendelian
Xiangyang Xu1, Yizhi Yu1, Jiefu Fan2
1Department of Cardiovascular Surgery, Changhai Hospital, Shanghai, China.
Insights
Acute aortic dissection (AAD) shows seasonal and circadian patterns, peaking in winter and during morning hours. Chronotype, particularly being a morning person, may reduce AAD risk, aiding in prevention.
Area of Science:
- Cardiovascular Medicine
- Chronobiology
- Genetics
Background:
- Acute aortic dissection (AAD) is a life-threatening condition with high mortality.
- Understanding temporal patterns may improve AAD prediction and prevention.
Purpose of the Study:
- To investigate seasonal, weekly, and circadian patterns in AAD onset.
- To explore the causal relationship between chronotype and AAD risk.
Main Methods:
- Analysis of 1,151 AAD patient cases (2000-2023).
- Statistical tests (chi-squared, Fourier models) for temporal distribution.
- Mendelian randomization using GWAS data on chronotype and AAD-associated SNPs.
Main Results:
- AAD incidence peaked in winter (December) and showed significant circadian rhythmicity (peak 7-8 AM, trough 11 PM-12 AM).
- Circadian rhythmicity was observed across most subgroups, except DeBakey III and females.
- Morning chronotype was associated with a reduced risk of AAD.
Conclusions:
- AAD onset exhibits distinct seasonal, monthly, and circadian patterns.
- Circadian rhythm is a significant factor in AAD development.
- Chronotype may influence AAD risk, offering new avenues for preventive strategies.
Aim:
Acute aortic dissection (AAD) represents a cardiovascular ailment characterised by a notable mortality rate. Chronobiological patterns can offer a predictive framework for anticipating the onset of AAD.
Method:
Data were gathered from 1,151 patients diagnosed with AAD at Changhai Hospital in Shanghai, China, spanning 2000-2023. The χ2 test was used to assess whether specific periods exhibited significantly different seasonal/weekly distributions compared with others. Fourier models were utilised for the analysis of rhythmicity in monthly/circadian distribution. Publicly available genome-wide association studies datasets were used to establish the causal relationship between chronotype and AAD. Two sets of genetics instruments were used for analysis, derived from publicly available genetic summary data: 75 single-nucleotide polymorphisms (SNPs) significantly associated with chronotype; and SNPs associated with AAD in the FinnGen consortium.
Results:
The mean age was 51.5±13.8 years, with 665 patients (57.8%) aged <55 years. Among the 1,151 patients, 80.9% were male. The distribution of DeBakey types was 73.2% (843) for DeBakey I, 21% (242) for DeBakey II, and 5.7% (66) for DeBakey III. Comorbidities included hypertension in 58.5% (673 cases) and diabetes in 7.8% (90 cases). A peak occurred during colder periods (winter/December), and a trough was noted in warmer periods (summer/June). Weekly distribution exhibited no significant variation. Fourier analysis revealed a statistically significant circadian variation (p<0.0001) with a trough between 23:00 and 00:00, a prominent peak from 07:00 to 08:00, and a minor peak between 20:00 and 21:00. Subgroup analyses identified circadian rhythmicity in all subgroups, except for the DeBakey III group and the female group. Using the 75 chronotype-related SNPs, evidence was found of a potential causal effect of chronotype on the risk of AAD, as the inverse-variance weighting analysis showed that self-report chronotype of morningness was associated with a decreased risk of AAD.
Conclusions:
The findings substantiate that the initiation of AAD displays noteworthy seasonal, monthly, and circadian patterns. The Mendelian randomisation analysis also indicated that the onset of acute aortic dissection is related to circadian rhythm. These findings offer a fresh perspective, facilitating the identification of triggering factors for AAD and bolstering preventive measures for this catastrophic event.
More Related Videos
06:46Quantitative Micro-CT Analysis of Aortopathy in a Mouse Model of β-aminopropionitrile-induced Aortic Aneurysm and Dissection
Published on: July 16, 2018
09:32Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model
Published on: February 23, 2020
Related Concept Videos
Aortic Regurgitation I: Introduction
Aortic Regurgitation II: Clinical Features and Diagnostic Tests
Coronary Artery Disease I: Introduction
Aneurysm I: Introduction
Aneurysm II: Clinical Manifestations and Diagnostic Studies