Ultra-Processed Obesity

A timely review article about “The role of Ultra Processed Foods (UPF) in obesity” (by a team from the University of Sao Paulo and NYU) summarizes

a lot of evidence that sounds obvious e.g., diets “high in UPF promote overeating and increase the risk of overweight and obesity”, “the soft texture, high energy density and hyperpalatable nutrient combinations of UPF facilitate excessive energy intakes by affecting ingestive behaviors, satiety signalling and food reward systems”) but also obvious-sounding but not fully elucidated mechanisms (“UPF attributes (such as emulsifiers, non-nutritive sweeteners, acellular nutrients, and contaminants from processing and packaging materials) contribute to their obesogenic effects through a myriad of physiological pathways, including altered absorption kinetics, glycaemic response and the gut microbiota composition and function”).

First, a definition: “UPF are defined as industrial formulations manufactured by deconstructing foods into their component parts (for example, oils, starches and protein isolates), modifying them and recombining them with cosmetic additives (that is, additives used to disguise undesirable sensory properties or make products more attractive to see, taste, smell and/or touch.” Yummy.

Two things I found intriguing:

“UPF present evolutionarily novel nutritional, physical and chemical characteristics that might influence energy intake and weight homeostasis through multiple biological pathways, including food reward systems, appetite and/or satiety regulation and changes to the microbiome.” Going back to a recent article that showed differences in inflammaging in industrialized vs non-industrialized populations, it is very possible that inflammaging as it has been defined largely in a “Western Diet” context is the result of UPF consumption over time, in a way that is largely gut microbiome-driven.

“Additional research is warranted, especially regarding the effects of UPF exposure during pivotal life stages (such as pregnancy, childhood and adolescence), and to further clarify biological mechanisms of action.” I find that particularly interesting, not just for the health outcomes of UPF consumption during these life stages but also from an “habituation” (addiction?) perspective and its transmission to unborn children during pregnancy.

Article unfortunately paywalled: link

Related articles, Open Access: https://www.jomes.org/journal/view.html?uid=1080&vmd=Full, https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2829780,

https://www.nature.com/articles/s41598-025-93506-3, link

Figure Legend: The demonstrated and potential biological mechanisms through which a diet high in ultra-processed foods (UPF) might promote weight gain and obesity. Demonstrated pathways (indicated in italics) include excessive energy intake driven by (1) enhanced food reward due to hyperpalatable nutrient combinations, and (2) increased energy intake and energy intake rate due to the high energy density and particular oro-sensory properties (soft, non-fibrous texture) often found in UPF. Potential pathways include (1) enhanced food reward, disruption of gut–brain signalling of food value and altered nutrient sensing due to the high energy density of UPF and the presence of artificial sweeteners, flavours and aromas; (2) modified gut microbiota and host–microbiota interactions due to degraded food matrices, acellular nutrients, lack of fibre, high fat and sugar content and presence of emulsifiers, non-nutritive sweeteners and endocrine-disrupting chemicals (EDCs); (3) increased energy intake and altered appetite and/or satiety regulation due to the low protein and fibre content of UPF, high proportion of refined acellular carbohydrates and presence of EDCs; (4) altered lipid and glucose metabolism due to the content of refined acellular carbohydrates, non-nutritive sweeteners and EDCs in UPF. Food environments with high prevalence of UPF promote diets high in UPF and might also directly promote excess energy intake and weight gain through factors such as food advertising and large portion sizes. BCAA, branched-chain amino acids; GLP1, glucagon-like peptide 1; PYY, peptide YY; SCFA, short-chain fatty acids.

Gut microbiome composition does not matter...

...unless you go to the strain level! Or, put differently, what matters is "functional identity", not cladistic assignment. I have always been skeptical of microbiome relative abundance analysis (in the gut or other locations, or even ecological microbiomes) simply because the level of description afforded by current tools, including multi-omics, is not conducive to any firm conclusions: the characterization of a complex ecosystem at the phylum, class, order, family or genus levels, or in the best cases at the species level, can sometimes be correlated with host phenotypes but leads to extreme intra- and inter-individual variability (at that level of description), high uncertainty and hand-waving "explanations" of possible mechanisms.

I have witnessed firsthand the significant differences that may exist between two strains of the same species, for example one that secretes a bacteriocin while the other doesn't, thereby affecting the ecosystem, reducing our ability to understand variability if we only look at the species level -they are the same species.

Instead of "Who is there?", the question we really want to ask is "What are they doing?", which itself may depend on surrounding conditions (host, environmental [pH, T, nutrients] or microbial). But functional analysis, by way of multi-omics and metabolic modeling, is still in its nascent state and can be prohibitively expensive. Strain-level analysis is probably the one method within reach, even though it remains hard and expensive.

So it is with great pleasure that I read a Cell by Cell Press article from a team led by senior authors Nicola Segata and Jingyuan Fu: "Global genetic diversity of human gut microbiome species is related to geographic location and host health." They performed a strain-level analysis for 583 species from 32,152 samples, recognizing that "the substantial intraspecies genetic variability of gut microbes has not yet been comprehensively considered, limiting the potential of linking such genetic traits with host conditions." Even though they did find certain higher-level descriptions to correlate with certain conditions, they "identified 484 microbial-strain-level associations with 241 host phenotypes, encompassing human anthropometric factors, biochemical measurements, diseases, and lifestyle." Interestingly, a lot of these associations are related to age.

I hope that strain-level analysis at scale will soon be the norm, assuming that cost-effective technologies become available. But we have to remember that even with such tools, a lot of "microbial dark matter" still goes undetected, un-isolated and uncharacterized: we have a very incomplete picture of "Who is there", so "What are they doing?" is still the aspiration.

There is a lot to unpack in this rich and sophisticated Nature Medicine article by a @Stanford University team led by @tony wyss-coray (@Hamilton Se-Hwee Oh, @Yann Le Guen, @Nimrod Rappoport, @Deniz Yagmur Urey, @Amelia Farinas, @Jarod Rutledge, @Divya Channappa, @Anthony D. Wagner, @Elizabeth Mormino, @Anne Brunet, @Michael D. Greicius): “Plasma proteomics links brain and immune system aging with healthspan and longevity.”

Two fascinating findings that struck me:

One can be found in the title. “Brain aging was most strongly predictive (...) suggesting that the brain may be a central regulator of lifespan in humans similar to findings in animal models (worms, flies and mice). Indeed, individuals with aged brains had increased risk for several diseases beyond dementia, including COPD and heart failure consistent with previous studies showing that the brain regulates systemic inflammation.” Super interesting that brain age estimated from plasma proteomics is such a strong predictor. I take exception with the last sentence, I think there is limited evidence that the brain “regulates” systemic inflammation -a lot more work needed in this area.

The other one is a favorite topic of mine, modifiable lifestyle factors. The study shows the associations between such factors (smoking, alcohol consumption, sleep, diet and, interestingly, the Townsend Deprivation Index, which may not be that “modifiable” as it measures “unemployment, non-car ownership, non-home ownership, and household overcrowding”). Figure 3 in the article is a treasure trove of findings: “smoking, alcohol, processed meat intake, the Townsend Deprivation Index and insomnia were associated with age acceleration across several organs, whereas vigorous exercise, oily fish consumption, poultry consumption and higher education were associated with youthful organs.” More unusual is the finding that six common drugs are associated with youth in at least 2 organs: “Ibuprofen, glucosamine, cod liver oil, multivitamins and vitamin C products were associated with youth primarily in the kidneys, brain and pancreas.” The 6th product, Premarin, is an estrogen medication: “Among 47 women with normal, early or premature menopause treated with estrogen, earlier menopause was associated with accelerated aging across most organs, whereas estrogen treatment correlated with youthful immune, liver and artery profiles.”

There is a lot more in the article. Read and enjoy!