Couverture de Dave Feldman on Cholesterol Code & Why the Science Isn't Settled Yet: Ep 127

Dave Feldman on Cholesterol Code & Why the Science Isn't Settled Yet: Ep 127

Dave Feldman on Cholesterol Code & Why the Science Isn't Settled Yet: Ep 127

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 When Dave Feldman first walked into a LowCarbUSA® event in 2016 carrying a laptop full of lab results, few people could have predicted where that moment would lead. "I'm approaching everyone with my computer," Feldman recalls, "because I'm doing these self-experiments—getting blood work—and I'm trying to figure out why my cholesterol numbers were doing what they were doing." What started as a personal puzzle became The Cholesterol Code, a global research effort, a nonprofit scientific foundation, and now a forthcoming documentary film. In this episode of the LowCarbUSA Podcast, host Doug Reynolds sits down with Feldman to trace that journey—and to explain why the next chapter will take center stage at the Symposium for Metabolic Health in Boca Raton, January 23–25, 2026 The Question That Wouldn't Go Away Dave's original question was deceptively simple: Why do some metabolically healthy, lean people see their LDL cholesterol rise dramatically on a ketogenic diet? Over time, he noticed a consistent pattern. These individuals didn't just have high LDL—they also tended to have high HDL, low triglycerides, and excellent metabolic health. In 2017, he coined a name for this group: Lean Mass Hyper-Responders (LMHRs). But identifying a pattern wasn't enough. "Even if the lipid energy model proves correct," Dave explains, "does that mean having higher LDL on a ketogenic diet carries higher cardiovascular risk?" Answering that question required something far more difficult than a blog post or a hypothesis: a prospective imaging study. Building a Study When No One Will Fund One Dave spent years trying—and failing—to convince established institutions to study this population. "There's not a lot of funding to study metabolically healthy people with sky-high LDL," he says dryly. "The interest is usually in people who already have multiple cardiovascular risk factors—which confounds everything." So in 2019, he made a radical decision. He founded the Citizen Science Foundation, a public charity created for a single purpose: to fund independent research, with no money going to salaries or overhead. "We raised $200,000,"Dave says, "and paid a research center to do the study." By late 2021, recruitment was underway. One hundred lean, metabolically healthy ketogenic individuals underwent coronary CT angiography (CTA) scans to assess plaque in their coronary arteries, with follow-up scans roughly one year later. What the Data Actually Showed The early findings were striking. When Dave's cohort was matched against participants from the Miami Heart Study, there was no statistically significant difference in coronary plaque, despite Dave's group having LDL levels less than twice as high. "In fact," he notes, "our group trended toward lower plaque." But the most important finding emerged as more analyses were completed: "There was no association between ApoB or LDL and plaque progression," Dave says. "Whatever your LDL level was, it did not correspond with how plaque developed." What did matter? Baseline plaque. "Whether you're low-carb or not," he explains, "the more plaque you have at baseline, the more likely you are to see progression. That's consistent with the existing literature." When One Dataset Didn't Make Sense Then came the controversy. An AI-based quantitative analysis from a company called Cleerly showed plaque progression that appeared inconsistent—not only with Dave's other data, but with decades of prior research. "All of the scans showed progression," he says. "No regression. Not even noise." For an engineer, that raised immediate red flags. "If a bathroom scale is off by a quarter pound," Dave explains, "you expect wobble. Below the noise floor, measurements go up and down. But this dataset showed only one direction." Later, when Dave gained access to the anonymized data, he identified multiple anomalies and requested a blinded quality-control reanalysis. That request was declined. "I don't assume wrongdoing," he emphasizes. "But when something looks implausible, the response should be course correction." Instead, he sought independent confirmation. A second AI company, HeartFlow, conducted a fully blinded analysis—and its results aligned with every other analysis except Cleerly's. "Three out of four analyses agree," he says. "Cleerly is the outlier." Why This Matters Beyond One Study The implications extend far beyond a single dataset. Dave believes this episode exposes a deeper issue in nutrition and cardiovascular science: how dominant theories shape interpretation. "The lipid hypothesis has a gravitational pull," he says. "It affects what people expect to see—and what they question." As I put it, Dave has repeatedly taken the LowCarbUSA stage to announce findings that challenge assumptions—and each time, the conversation moves forward. "If we want better answers," Dave says, "we have to do better science." The ...
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