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Cholesterol Code – Reverse Engineering the MysteryCholesterol Code – Reverse Engineering the Mystery Toggle search form Toggle navigation Cholesterol Code Reverse Engineering the Mystery Our Published Papers Research Experiment List Food Logging Instructions High Triglycerides on Keto/LCHF Atherogenic Dyslipidemia Learn Basics of Cholesterol on a Low Carb Diet A Simple Guide to Cholesterol on Low Carb Lean Mass Hyper-responders (“LMHR”) Report About Jul 23 Start Here (Pinned) By Dave in Cholesterol, Experiments, Guide, Immunity, Presentation, Study, Video Welcome to CholesterolCode.com. This site serves as an information and research hub for emerging data on cholesterol. particularly in the context of a low carbohydrate lifestyle. [IMPORTANT UPDATE: Our documentary, The Cholesterol Code, now has a dedicated page, CholesterolCodeMovie.com. We are hosting a Special Preview Event on Friday, February 7th, 2025 here in Las Vegas at our conference, CoSci. If interested in attending, please follow these instructions to join the Interest List. Follow our posts here and on the dedicated movie website for updates on future events and when it becomes widely available on a streaming platform. If you know little to nothing about cholesterol -> You can check out our Simple Guide to Cholesterol series. It’s full of illustrations and is written for laypeople. Enjoy! If you’re wanting to learn more about why cholesterol could be higher, particularly on a low carb diet, we present the Lipid Energy Model (LEM) -> See our full paper on the LEM published in Metabolites doi.org/10.3390/metabo12050460 You can watch our video abstract for this paper here (5 min): We also have a more layperson-friendly, simplified overview video (just 5 min) you can watch here Or you can watch Dave’s presentation for Stanford University on the model from 2020 If you’re looking to better understand the risk associated with high cholesterol on a low carb diet-> Be aware we’re currently conducting an IRB approved, clinical study through the Lundquist Institute, which has just released a match analysis you can watch here: https://www.youtube.com/watch?v=ny2JqAgoORo While several articles on this site present a more “cautiously optimistic” perspective on cholesterol in the context of fat adaptation, we strongly encourage everyone to consider the conventional view as well. Consider reading The Case for Lower LDL on Low Carb by our colleague and co-investigator, Spencer Nadolsky. If looking to understand the “Lean Mass Hyper-responder” profile -> See our dedicated page for Lean Mass Hyper-responders Check out our LMHR paper published in Current Developments in Nutrition See our in-depth case report published in Frontiers in Endocrinology If you’d like to understand possible relevance of cholesterol and the immune system, you can read Siobhan’s overview article on the topic here or watch her presentation here If you’d like to learn more about lipoprotein(a), you can watch Siobhan’s presentation on it here Lastly — you can always just ask us anything our Questions Page. (Just be aware our site does not constitute medical advice and we always recommend consulting with your doctor.) 10 comments Aug 23 Breaking Preliminary Data from the LMHR Study By Dave in Uncategorized The following preliminary data from the Keto-CTA / LMHR Study were presented on August 18th at Symposium of Metabolic Health in San Diego. IMPORTANT – These Data are Preliminary. This has not undergone peer review and preparation for publication, but we’ll likely have more to share this in the coming months. As always, please continue to work with your doctor. This research is an ongoing effort to inform decision making with care providers, but not to replace it. Match Analysis Presentation from CoSci Before reading this article, if you haven’t already, please watch Dr. Matt Budoff’s keynote presentation at CoSci this year on the Keto-CTA / LMHR Study match analysis with the Miami Heart study (MiHeart). These Data are Presented With Limited Analysis Consider the following data more a capture-and-report Quick Review of Total Plaque Score (TPS) The total plaque score (TPS) utilizes the 15-segment American Heart Association model of the coronary arteries. These 15 segments used in a total plaque score are chosen because they represent areas in the arteries that are more susceptible to plaque formation, due to the mechanical forces that contribute to endothelial dysfunction and inflammation. Each plaque rated with a score of 0 – 3 based on plaque volume. TPS is a summation across the 15 segments, yielding a TPS score range of 0 – 45. Total Plaque Score (TPS) vs Lipid Metrics Keto CTA (LMHR Study) vs MiHeart Spearman correlation of general lipid values vs TPS  KETOMI HEARTrprpTotal Cholesterol-0.110.430.150.28LDL-C-0.080.580.260.06HDL-C-0.20.15-0.220.11Triglycerides-0.010.960.140.3 Note from Dave: As I discussed from the SMH presentation, these data are not too surprising given the context. See presentation when it’s released for a more in-depth discussion. Total Plaque Score (TPS) vs Lipid Particle Counts Total Low Density Lipoprotein Particles (LDL-P) vs TPS Keto-CTA Only R2 0.0015 – No correlation between Total LDL Particles (LDL-P) and Total Plaque Score (TPS) Note from Dave: This was very exciting to see this born out on our data as it has been long speculated on. I’ve had discussions with Peter Attia, Layne Norton, Howard Luks, and many others speculating on high LDL-P and plaque with LMHR at a population level. Total Plaque Score (TPS) vs Small Dense LDL Particle (sdLDL-P) R2 0.001 – No correlation between Small LDL Particles (sdLDL-P) and Total Plaque Score (TPS) Note from Dave: This was likewise exciting to see with the context of the participants of our study as I had speculated on this outcome as well [ie here, here, here. See the talk when it is released for a deeper dive. Total Plaque Score (TPS) vs Lp(a) & OxPL-ApoB Total Plaque Score (TPS) vs Lp(a) R2 0.007 – No correlation between Lp(a) and Total Plaque Score (TPS) Note from Dave: I’ve had many great discussions with Sam Tsimikas on this given his unique expertise in this area. Indeed, the relevance if Lp(a) in this context outside other acute phase reactants (ie C-Reactive Protein) does appear to be relevant in here. I’ll be interested in seeing our longitudinal data on this as well for comparison with progression too. Total Plaque Score (TPS) vs OxPL-ApoB R2 0.0002 – No correlation between OxPL-ApoB and Total Plaque Score (TPS) Note from Dave: Happy to see this hypothesis get some testing as well. “I think we’ll have many #LMHRs with higher Lp(a) yet lower than expected oxPL-ApoB given both those levels and their ApoB.” While I haven’t seen the aggregates yet, I suspect this may bear out when we are completing the final paper. Quantitative Analysis Quantitative analysis using plaque volume and AI-guided reading is a more objective and detailed method compared to the semi-quantitative approach of total plaque score (TPS). Here’s how they compare directly: Measurement Precision: While total plaque score offers a rough estimate based on visual inspection, plaque volume provides exact measurements of plaque size in cubic millimeters, allowing for more precise monitoring of plaque progression or regression. Observer Variability: TPS is subjective and can vary significantly depending on the clinician’s interpretation, whereas quantitative analysis with AI-guided reading reduces this variability by standardizing measurements across different cases, leading to more consistent results. Detail of Plaque Characteristics: Semi-quantitative TPS generally assesses the presence and extent of plaque but lacks detailed information on the specific composition and characteristics. In contrast, AI-guided plaque volume analysis can capture intricate details like the plaque’s composition (e.g., calcified or non-calcified), providing deeper insights into potential risk factors for cardiovascular events. Resource and Time Requirements: TPS is faster and easier to perform, requiring fewer resources and no advanced software. On the other hand, quantitative plaque volume analysis is more resource-intensive and time-consuming, as it relies on advanced imaging techniques and AI-powered algorithms to deliver accurate and comprehensive data. Note from Dave: An interesting aside, early into the study there was a concern at one point we might actually have too few patients with baseline plaque to capture adequate progression data. We discussed possible contingencies, even the possibility of splitting the study into two studies. However, within the year there were enormous advancements in AI-guided analyses of CCTA scans which resolved the issue entirely (See Cleerly). These analyses identify plaque volume in every scan. Preliminary Quantitative Data for MiHeart Match The following are the Median PV (Plaque Volume) for the Keto-CTA and MiHeart cohorts. (Note: one scan from each could not be processed). For previous Table 1 & 2 values, see Dr. Budoff’s presentation. Note from Dave: Understandably, these are the data I was most interested, particularly Non-calcified Plaque Volume. There’s quite a bit to say on this, but for now, I’d rather just emphasize we’ll be doing a deeper analysis on this in the coming paper. Match Analysis Excluding Cholesterol Lowering Medication Preliminary Quantitative Data for MiHeart Match Easily the most requested reanalysis since the match was reported by Dr. Budoff was an exclusion of the 26 participants of MiHeart who were on cholesterol lowering medication. Note from Dave: As with the PV of the original match analysis above, these values are extremely close, particularly our major endpoint of Non-calcified Plaque Volume with each group. Again – and with emphasis – these data are preliminary. Our final analysis will be published soon. UPDATE: You can watch Nick Norwitz, Adrian Soto-Mota and myself discuss our thoughts on these breaking data here. 2 comments Jun 30 First Published Data for LMHR Study Now Available By Dave in Uncategorized The KETO-CTA (#LMHRstudy) vs Matched Control (#MiHeart) analysis is now published in Metabolism. https://doi.org/10.1016/j.metabol.2024.155854 METHODS 80 Participants of #LMHRstudy fell within #MiHeart age range and were then matched 1:1 for age, gender, race, diabetes mellitus, hyperlipidemia, hypertension, and past smoking to asymptomatic subjects from the #MiHeart cohort. PRIMARY ANALYSIS High resolution heart scans (#CCTA) allowing for primary analysis of Total Plaque Score (TPS), Total Stenosis Score (TSS) and Segment Involvement Score (SIS) RESULTS The matched mean age was 55.5 years, with mean #LDL cholesterol of 272 mg/dL (max LDL-C 591) mg/dl and mean 4.7 years duration on a ketogenic diet. There was no significant difference in coronary plaque burden of #LMHRstudy (mean LDL-C 272) cohort as compared to #MiHeart controls (mean LDL 123 mg/dl); nb: pre-KETO LDL-C in KETO group was 122 mg/dl There was no significant difference in CAC (median and IQR) [0 (0,56)] versus [1 (0, 49)], p = 0.520 No relationship of LDL-C elevations and plaque Note 1 – This analysis is on baseline scans, we will have further data on the Keto-CTA longitudinal analysis in the coming months. And — as always — please continue to work with your doctor. Note 2 – this is a published abstract, but is not open access. A full paper for this match analysis will be published soon in a different journal and will be completely open access. 2 comments Mar 17 Undeniable Hope By Dave in Uncategorized On November 27th, 2015, a number on a piece of paper changed my life forever. The massive increase I saw in my LDL cholesterol after adopting a low carb diet would ultimately send me into an entirely different life path, one I’d chronicle in real time on this blog. Now, eight and a half years later, I find myself completely entrenched spearheading research to unravel this mystery and whether it will demonstrate risk for folks like me. But I have a confession… I’ve had many low points throughout this journey. Obstacles large and small have emerged to slow me down or even outright stop this research. However, I’ve also seen just how far folks will go to support this effort. Beyond letters and DMs, many have contributed directly to our charity, the Citizen Science Foundation, or have networked us with the right researchers and personnel https://twitter.com/realDaveFeldman/status/1744368194381291863?s=20 Yet nothing compares to what just happened. We decided to take a chance and hold a charity event – the Collaborative Science Conference – or as we call it, “CoSci”. It was over March 15 and 16th and… well… it was amazing. People from all over the world came to donate, with that donation being their ticket to the event. https://twitter.com/MurseDarius/status/1769163840087007596?s=20 We had a mix of both featured speakers that were very popular, and citizen science speakers, many of which had never spoken at any conference before this one. And in spite of how short notice we were in announcing it just two and a half months ago, we had over 300 people come and join us. The part I can’t express in words is how much our event had heart. It felt as though the “spirit of citizen science” was truly in the air. An optimism for what could be possible and how attendees were helping to make it real, just like the rest of us. Absolutely MEGA. 90 minute discussion featuring Dr. William Cromwell, Dr. Bret Scher, Dr. Nadir Ali, moderated by Dave Feldman, with Dr. David Diamond chiming in. #CoSci @Lipoprotein @bschermd @realDaveFeldman #cholesterol #ldl pic.twitter.com/xZhywE9ac6— Casey Ruff (@CaseyRuff) March 16, 2024 Given both the staggering generosity in donations and the considerably positive feedback, we will likely hold another CoSci next year as well. But more importantly, I’m thankful for the level of optimism this inspires for me. We’re proving this model of crowdfunded, self-directed science is quite real and can be well supported with events like these. For everyone who donated and came to enjoy our event – thank you. You aren’t just helping us fund the next study, you’re reinforcing the drive for us to keep pressing forward. Leave comment Dec 20 Special Event: Live Reaction to Lipid Video by Nutrition by Science By Dave in Uncategorized A few days ago, Mario Kratz, released a video around lipids and ASCVD that also featured our work with Lean Mass Hyper-Responders and the Lipid Energy Model. To be sure, while I did got a chance to listen to it at 2x speed on a drive between two meetings, it was more of a skimming, in a sense. But today I’m going to listen live with members & patrons at 7am PST (see companion post to this one – and if not a member, you can register here). I’ve give my live reactions, but as always, I want to keep it both respectful and productive. I can say in advance my interest in this video is in large part due to my existing respect for Mario and his diligent work on his content. But moreover, he and I are already of comparable opinions with regard to metabolic health and its enormous importance in reducing risk. I’ll then hand off my video to Mario directly, and if he feels it is helpful in advancing the conversation, I may release an edited version of the video for my channel. Leave comment Oct 30 Dr Budoff to Present Matched Cohort Analysis at WCIRDCD Conference By Dave in Cholesterol, Lean Mass Hyper-responder, Study Original article via CitizenScienceFoundation.org We’re excited to announce our Principal Investigator, Dr. Matthew Budoff, will be presenting preliminary data of our Lean Mass Hyper-Responder study (Keto-CTA) on the weekend of December 7-9th at the World Congress on Insulin Resistance, Diabetes and Cardiovascular Disease conference in Los Angeles, California. This is the first prospective study of CT Angiography on a keto diet population with extremely high LDL cholesterol levels, yet low cardiovascular risk factors and confirmed absence of monogenetic FH. Dr. Budoff will be presenting a new CTA comparison analysis on this cohort against a matched control from the Miami Heart Study (MiHeart). The MiHeart cohort has been closely matched for demographics and risk factors, save LDL cholesterol levels, which average less than half of the Keto-CTA cohort. Leave comment 123…48 DonateMy primary costs are the many frequent and expensive blood tests I take for this research and data. Any size donation is appreciated. Thank you for your support! 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