What Gaining and Shedding Weight Does to Our Body

Weight
Gaining or shedding weight, even for a short time, can drastically change an individual’s personal molecular profile, according to a new study conducted by Stanford University School of Medicine in California.
In a paper that is due to be published in the journal Cell Systems, the researchers report how they drew on a huge amount of data from multiple study methods to create a detailed molecular profile of each of their 23 study participants.Body Type

The molecular data were gleaned from various “-omics” techniques, including:
  • genomics, or methods that map the genome, or genetic makeup, of organisms
  • proteomics, an approach that yields detailed information about proteins
  • transcriptomics, or techniques that reveal how the genome is currently being interpreted
  • metabolomics, which gives insights into metabolism and the chemistry of cells
  • microbiomics, or methods that profile bacteria and other microorganisms in the body

“In the end,” says co-senior study author Michael Snyder, a professor of genetics at Stanford University in California, “we literally made billions of measurements.”
The study follows a research path that Prof. Snyder started on a few years ago when he was the subject of his own personal omics profiling, which tracked molecular changes in his body as he developed type 2 diabetes and then recovered from it after changing his diet and lifestyle.

Profiling molecular changes

In the new study, he and the rest of the team found that, as the participants gained about 6 pounds of body weight over 1 month and then shed it, there were dramatic shifts in their gene expression, cardiovascular system, microbiome, and immune system.

As the participants gained weight, their personal omics profiles revealed: significant changes to bacterial composition; activation of molecular pathways that have been linked to heart disease; and heightened inflammation and immune responses.

But the good news is that after they shed their excess pounds, most of their systems returned to their original states.

Prof. Snyder says that their goal was to “characterize what happens during weight gain and loss at a level that no one has ever done before.”

In particular, they wanted to “learn how prediabetic folks might differ in terms of their personal omics profiles and their molecular responses to weight fluctuation,” he adds.

Obesity and type 2 diabetes

People with obesity are at increased risk of developing type 2 diabetes, as well as other serious health problems. Insulin resistance often precedes type 2 diabetes.

Individuals with insulin resistance have problems with converting blood sugar into energy as their cells fail to react properly to insulin, a hormone that helps them to take in and use glucose.

The pancreas tries to make more insulin to compensate, but eventually this might not be enough, leading to high blood sugar and full-blown type 2 diabetes.

In the United States, where 36.5 percent of adults have obesity, there are more than 100 million people living with prediabetes or diabetes.

Personal omics profiling of weight gain, loss

For the new study, the team compared the personal omics profiles of 13 insulin-resistant individuals with those of 10 individuals without insulin resistance — the “insulin-sensitive group” — as they gained and then lost weight.

All the participants had a body mass index (BMI) of between 25 and 35 — that is, ranging from “overweight to moderately obese” — when they were recruited.

The participants followed a high-calorie diet for a month, during which time they gained 6 pounds (2.7 kilograms) in weight. After this, they then shed the excess weight.

The scientists took samples from the participants at four points during the study: at baseline; when their weight peaked following the high-calorie diet; when their weight returned to baseline; and then following 3 months of stability after their weight returned to baseline.

Molecular patterns show insulin resistance

When they compared the insulin-resistant and insulin-sensitive groups, the researchers found significant differences in their baseline profiles.

In particular, the baseline molecular profiles of the insulin-resistant group contained markers of inflammation, whereas those of the insulin-sensitive group did not have them.

Prof. Snyder says that this finding suggests that omics profiling could identify individuals at risk of diabetes by spotting early markers of inflammation, which are known to be linked to the development of type 2 diabetes.

The comparison of omics profiles after weight gain also showed interesting contrasts. Whereas inflammation markers rose in both insulin-resistant and insulin-sensitive groups, only the group that was insulin-sensitive showed bacterial markers of Akkermansia muciniphila, which protects against insulin resistance.

However, the most dramatic change — for both groups — was alterations in gene expression that are known to be linked to raised risk of a form of heart failure known as dilated cardiomyopathy.

“That was quite surprising,” Prof. Snyder remarks, “I didn’t expect 30 days of overeating to change the whole heart pathway.”

He explains, however, that their findings do fit “with how we think of the human body — it’s a whole system, not just a few isolated components, so there are system-wide changes when people gain weight.”

Could some changes be longer-lasting?

After they shed their excess weight and had a period of stability at their previous weight, the participants’ omic profiles showed that most of the molecular changes went back to normal.

However, a subset of weight gain changes in the profiles did persist. While they were not large or significant enough from which to draw firm conclusions, they do suggest, says Prof. Snyder, “that some of these effects could be longer-lasting.”

He also points out that while their study dealt mainly with group changes, they did notice that each participant had unique changes in their personal omics profile, which shows, he believes, that such tools will form a “critical part of managing human health in the future.”

Big data will be critical to the future of medicine, and things like these integrative omics profiles will offer an understanding of how the human body responds, in a very personal way, to different challenges.”