By Kathy Doherty

If you follow the Lipedema Foundation on social media, you’ve probably noticed that we’ve been posting key findings from the LF Registry First Look report during the past two months. This report analyzes participant data from the Registry, which we launched in March 2019 to learn more about patient experiences with Lipedema.

Because there is a lot of data to digest in the First Look report, we published each finding on social media (Facebook, Instagram, LinkedIn, and Twitter) as a stand-alone post. This allowed us to see which findings resonated with our community as well as listen and learn from comments on the posts. It’s one thing to look at the data – it’s another to see how our community reacts to the information.

By Stephanie Peterson

Today, a Lipedema diagnosis requires a “clinical diagnosis.” This means that a diagnosis is primarily the professional opinion of a skilled physician based on the clinical exam and patient history. To date, there remains no laboratory or imaging finding that positively confirms the presence of Lipedema.

Over the years, several papers have been written to codify what goes into the diagnosis of Lipedema. Most physicians with experience in Lipedema can trace their clinical approach back to one or more of these resources.

In some cases these documents are well established scholarly papers, such as one of the original papers by Allen and Hines that are frequently cited by other scholars. In more modern times, expert groups have often worked together to systematically summarize available research evidence, and propose adaptations of the diagnostic criteria and treatments. These reports may be adopted by professional societies, or published independently.

By Evangelia Bellas, PhD

As biomedical engineers, we are trained to employ our skill set to work towards solutions to help people. But often, we focus on the details of the problem, on the cells or the tissue, knowing that if successful, we could eventually help patients. When we share our research at conferences or through research articles, we interact with other researchers, and know their faces and names. But because we are biological engineers – and not clinicians – we don’t often meet the patients face-to-face that we are creating solutions for.

In my laboratory, the BellasFATLab, we focus on engineering adipose tissue. Adipose tissue is more commonly known as body fat. When people hear about our work, they tend to think of how they would like to get rid of their adipose tissue to lose weight easily and without much effort. Something that many of us would love a magic pill for! But until we get there, BellasFAT Lab engineers adipose tissue to develop 3-dimensional tissue models of obesity and metabolic (dys)function. This allows us to study fat cells and their surroundings (microenvironment) to learn how these change when going from a healthy to a diseased state. Then we look to uncover new therapeutic targets to hopefully get closer to that magic pill.

by Guy Eakin, PhD

Although we have much to learn about how a person’s genetic code can influence the probability that they will develop Lipedema, researchers generally believe that genes do play a role. It is not uncommon for women with Lipedema to be able to point to other members of their family who either had a Lipedema diagnosis or could be described as having similar body shapes. In fact, the earliest descriptions of Lipedema all point to the likelihood that the condition can be passed between generations [1–3].

In 1951, one seminal Lipedema study reported that 16% of women with Lipedema reported a “history of similar ‘large legs’ in female members of the family” [3]. In more recent studies, reports of a family history of Lipedema tend to be much higher, and consistently range from 64% to 89% [4–11], with some lower estimates ranging from 30% to 40% [12–16].

Two studies of women with Lipedema went further, characterizing family relationships that suggest women with Lipedema are most likely to have an affected mother (29-38%) followed by grandmother (17-35%), aunt (8-23%) and sister (5-14%) [11,17].