Using a large database of (deidentified) medical records, the researchers compared the outcomes of people taking a GLP-1 for their type 2 diabetes to people taking other common diabetes drugs between 2017 and 2025. GLP-1 users were significantly less likely to be diagnosed with TB for up to a five-year span, they found.

Both of these studies are observational and retrospective, meaning they can only show a correlation between GLP-1 use and reduced (or at least less severe) infections, not prove a direct cause-and-effect relationship. At the same time, these are the only latest pieces of evidence pointing to a genuine germ-busting benefit from GLP-1 drugs.

I wonder if the likelihood that people taking a GLP-1 are probably better off financially, have a health care provider willing to spend on the drugs (and therefore probably a better medical system) or a combination of these and other traits are the real reason there are fewer infections.

They use a method called propensity score matching to try their best to match patients on both sides using a simple linear model with various features that try to ensure that only pairs of closely matched patient histories are compared.

Unfortunately this is rarely clean. Its also easy to make mistakes. Sometimes two arms are fundamentally incomparable. The quality and rigor of the comparison is often determined by a lot of extra checks and validations, and different journals demand different levels of rigor. I need to read it carefully to judge if this is good or not.

They already do acknowledge socioeconomic (and other confounding factors) in the analysis. The primary analysis they perform is a ‘Propensity Score Match’ which is a technique used specifically to address for confounders in observational studies, and they do report balanced cohorts. Still they write in their discussion “Although we adjus- ted for several available proxies of socioeconomic and lifestyle status, direct measures of income, insurance coverage, or out-of-pocket payment were not available in the TriNetX database. Residual confounding related to unmeasured socioeconomic factors, therefore, cannot be excluded“

Given the size of the dataset, the effect size, significance and sensitivity testing they did I think it’s very strong evidence for GLP1s causing this and it would be very very surprising to me to see the effect disappear even if they had perfect socioeconomic data.

Or having a lower % of body fat (within healthy limits) is the factor improving a better immune response?

The benefit is probably from the removal of fat, not a direct antibacterial/antiviral effect. Fat plays a complex immunoregulatory role in human physiology: it down-regulates some pathways, while up-regulating others (notoriously, the production of IL6 is carried out, in part, by adipocytes). The overall effect of fat on the immune system, however, is negative: it tends to increase the chances of rheumatological disorders, cancers, and many other diseases. Alternatively, the effect may be due to some sociological factor that their analysis failed to account for.

(I am not a medical doctor)

They are also anti-inflammatory, so it could be related to less systemic inflammation.

Wow, bet they never thought of that. If only the researchers had thought to ask HN first.