Gene previously linked to obesity found to be unrelated, says new study: Gene that was previously thought of exerting greatest genetic impact on human obesity has in fact been found to be completely unrelated to body weight.

Gene Linked To Obesity In Child

Researchers at the Harvard Medical School and Boston Children’s Hospital claim that these results may completely overturn one of the major findings relating to the genetics of obesity.

However, the techniques used in the study may provide effective methods of analyzing puzzling parts of the human genome and identify similar regions, which might be associated with the disease. The research was published in Nature Genetics.

How It All Began?

The gene AMY1 in human codes for an enzyme involved in converting starch to sugar. Other enzymes also perform this function – but AMY1 initiates this process in the saliva. The amount and the different number of copies of the gene differ among individuals.

Since this enzyme assists in breaking down food to release nutrients, there have been speculations that it might be linked to obesity, stated Christina Usher, first author of the study.

Co-senior author Joel Hirschhorn, the Concordia Professor of Pediatrics at Boston Children’s Hospital and Professor of Genetics at HMS, is concerned with the study of genetic variants affecting obesity. He became interested in finding whether an association existed between AMY1 and obesity.

He analyzed genome-wide association data (collected by the GIANT Consortium) and concluded that there was no association between BMI and AMY1. But since the genomic region under study was immensely complicated, with AMY1 having two to 14 copies or more per person, he was not completely convinced by the results.

Hirschhorn approached co-senior author, Steven McCarroll, Assistant Professor of Genetics at HMS to work in tandem and find an answer.

Another Discovery: Gene Linked To Obesity In Child

The team worked together to develop tools that could facilitate the study of the complex region containing the AMY1 gene. “This part of the genome was past the frontier of what genetics and molecular biology could do,” expressed McCarroll. But that didn’t stop them from making an effort.

In 2014, a study reported in Nature Genetics by an unrelated international group of scientists stated that AMY1 and obesity were indeed substantially associated – people having less than four copies of the gene had an approximately eightfold higher risk of developing obesity than those having more than nine copies. Thus, this showed that AMY1 had a protective role.

These researchers believed that Hirschhorn’s study had not discovered the link because they had used simple variants (SNP’s) for analysis, whereas the AMY1 genome was highly complex. Meanwhile, McCarroll and his team had developed mathematical and molecular methods and wanted to take another shot at with AMY1.

A New Perspective

With the newly developed and sophisticated strategies, Usher obtained copy number measurements of the gene and its surrounding genomic structures. A statistical framework was then developed to uncover hidden patterns to interpret the data. Initially, the region seemed to be extremely puzzling, but Usher soon figured that there was a rather simple explanation to it – there were nine forms of AMY1, and a combination of two forms existed in most people.  

After conducting an analysis on the genomes of almost 4,500 Europeans with varying BMI’s, they conclusively found no association between the latter and AMY1.

“This form of complex variation, while fascinating, is almost certainly not the large influence on obesity that scientists thought it was,” clarified McCarroll.

Significance Of Results

Even though identifying associations between genes and diseases is significant for intervention and treatment, ruling out genes is also important. Marking the genes that are worth following prevents scientists from wasting valuable time and energy on ideas that lead to dead ends.

With the development of such intricate and systemic tools, it is hoped that understanding complex variants will become much easier.

“There are hundreds of loci in the human genome with this kind of complexity. They have been like black holes in our knowledge of the human genome,” stated McCarroll. “I think this is the beginning of a playbook for making sense of those regions.”

“We’ve established best practices for identifying and confirming simple variants, but complex variants are not at that stage yet. This is a younger field having its birth pangs,” Hirschhorn remarked.