Proneurotensin predicts cardiovascular disease in an elderly population.

JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM(2018)

Cited 19|Views3
No score
Abstract
Context: The gut hormone neurotensin promotes fat absorption, diet-induced weight gain, and liver steatosis. Its stable precursor-hormone fragment "proneurotensin" predicts cardiometabolic disease in middle-aged populations, especially in women. Objective: To test if proneurotensin predicts cardiovascular disease (CVD) and diabetes development in an elderly population and whether there are gender differences in this respect. Design, Setting, and Participants: Fasting proneurotensin was measured in plasma from 4804 participants (mean age 69 +/- 6 years) of the Malmo Preventive Project and subjects were followed up for development of CVD and diabetes during 5.4 years. Main Outcome Measures: Multivariate adjusted Cox proportional hazard models CVD were used to relate the proneurotensin to the risk of incident CVD and diabetes in all subjects and in gender-stratified analyses. Results: In total, there were 456 first CVD events and 222 incident cases of diabetes. The hazard ratio [HR (95% confidence interval)] for CVD per 1 standard deviation (SD) increment of proneurotensin was 1.10 (1.01 to 1.21); P = 0.037, and the above vs below median HR was 1.27 (1.06 to 1.54); P = 0.011, with similar effect sizes in both genders. There was no significant association between proneurotensin and incident diabetes in the entire population (P = 0.52) or among men (P = 0.52). However, in women proneurotensin predicted diabetes incidence with a per 1 SD increment HR of 1.28 (1.30 to 1.59); P = 0.025 and an above vs below median HR of 1.41 (1.10 to 1.80); P = 0.007. Conclusions: In the elderly population, proneurotensin independently predicts development of CVD in both genders, whereas it only predicts diabetes in women.
More
Translated text
Key words
elderly population
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined