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Human microRNAs associated with type 2 diabetes, finds study

admin by admin
April 3, 2023
in Global Trends


Clinically, miRNA molecules are reckoned to play important role in type 2 diabetes, but until now scientists have not been able to confidently identify which molecules are associated with the disease in humans.

A new study published in the journal Proceedings of the National Academy of Sciences, is the largest study till date that discusses diabetes-linked miRNA found in human pancreatic islets.

In fact, earlier studies to comprehensively profile miRNAs in pancreatic islets employing next-generation sequencing technology have been done in lab culture or with rodent models. A few studies undertaken with hard-to-obtain human islets were limited to a small number of samples.

For the study, the researchers had access to a network that provided almost 65 human pancreatic islet samples from corpses.

The robust sample size allowed researchers to use large-scale, next-gen sequencing to detect minimum 14 pancreatic islet miRNAs that are implicated in human type 2 diabetes.

The researchers defined the largest cohort of human islets till date the miRNAs that might be most relevant for type 2 diabetes.

The researchers also found some of the diabetes-linked miRNAs in humans are not the ones that have been well-understood in the previous two decades of investigating diabetes and islets in rodent models.

Importantly, MiRNAs were first discovered in animal cells in 2001. Soon after, in 2004, one of the first studies demonstrating their significance to physiology focused on a miRNA that controls the function of pancreatic islets. Since then, very large number of studies that demonstrate potential relevance of miRNA with pancreatic islets have been published, but few have used human tissue samples and none have been able to use to this scale.

Meanwhile, there’s been long-standing interest to better comprehend the molecular environment of the pancreas, to be able to get a better handle on what goes wrong in diabetes patients and then ultimately be able to use that data for better therapeutics.

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