Abnormal lipid metabolism in fat cells predicts future weight gain and diabetes in women


The inefficient breakdown of fats foretells later metabolic complications such as type 2 diabetes in women and weight gain. Low levels of hormone-stimulated lipolysis -- a biochemical process by which triglycerides (Cholesterol, lipid) are broken down into energy-rich fatty acids -- were related with weight gain and metabolic problems in future. To detect impedances in hormone-stimulated lipolysis, researchers created an algorithm using clinical and blood measures.
Researchers believed that their proposed algorithm could be helpful in identifying subjects with a high risk of becoming overweight or obese. These findings may well be utilized by clinicians to determine who would benefit the most from intensified lifestyle interventions such as physical activity, which improves hormone-stimulated lipolysis and may therefore prevent metabolic disturbances and fat accumulation.
Researchers took biopsies of subcutaneous fat tissue from healthy and non-obese 89 women, and followed up 13 years later. The women who gained weight within the between times showed a 50% diminish in hormone-stimulated lipolysis and a 50% increment in spontaneous lipolysis compared with weight-stable individuals. Moreover, lower expression of genes involved in regulating lipolysis was related with later weight gain.

Therefore it can be concluded that insufficient lipolysis which cannot be satisfactorily quickened by hormone stimulation, may shift the balance in lipid turnover towards uptake, which facilitates fat mass accumulation.
Instead of tissue biopsies, the researchers next constructed an algorithm to estimate hormone-stimulated lipolysis based on clinical and blood measures. To distinguish parameters for this metabolic measure, researchers analysed information from 1,045 subjects. They found six parameters which included fasting plasma HDL cholesterol, waist circumference, fasting plasma adrenaline, fasting serum insulin, body weight and fasting plasma glycerol divided by total body fat.
In a subset of 226 subjects, the algorithm predicted high or low lipolytic activity with approximately 75% specificity and greater than 80% sensitivity. When tested in a separate group of 14 individuals, the algorithm corresponded well with measured levels of hormone-stimulated lipolysis and predicted weight changes over time.
These results suggest that the algorithm could be used to estimate hormone-stimulated lipolysis rather than tissue biopsies in a routine clinical practice. However, future studies are needed to implement the algorithm in larger groups of people and to decide whether the findings of this study also apply to men.


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