Inflammatory protein is associated with depression in diabetes, according to a study.
The study, conducted by the University of Lund in Sweden, suggests that galectin-3 levels may be useful for the diagnosis of depression or may be a new target for the treatment of depression associated with type-1 diabetes, which could be lead to better patient care.
It is well established that people with type 1 and type 2 diabetes are at increased risk of developing depression, a debilitating mental disorder with potentially serious consequences, but the causes remain poorly understood.
Galectin-3 is a key protein involved in promoting inflammatory immune system reactions that are needed to repair tissue damage throughout the body in response to injury or disease. However, elevated levels of galectin-3 have also been associated with an increased risk of inflammatory conditions including Alzheimer's disease and cardiovascular disease. Previous research has suggested that both depression and diabetes may be associated with increased levels of inflammation in the body, but the role of galectin-3 has not been investigated under any circumstances.
In this study, Dr. Eva Olga Melin and colleagues measured the galectin-3 levels of 283 men and women, aged 18-59, with type-1 diabetes for at least one year. The incidence of depression in these patients was self-reported and assessed using the subscale brain injury and depression scale depression and potential disruptive influences of lifestyle factors such as heart disease, smoking or poorly managed diabetes were accounted for in the analysis. The researchers discovered that both men and women with type 1 diabetes and depression also had significantly higher levels of galectin-3.
Dr. Melin noted, "We found that people with type-1 diabetes and depression had higher galectin-3 levels, but no other diabetes-related metabolic changes could explain these elevated levels."
The study is published in the magazine Endocrine Connections.
(This story is not edited by Business Standard staff and is automatically generated by a syndicated feed.)
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