Candidly, rigorous and reliable sources of information are tainted with profit motives, pay-walls that limit information exchange, bias, and large egos. For these reasons and many others I have relied on the written insights of Peter Attia, MD. I have written about him before, How Should We Discuss Emerging Drugs for Patients with High Cholesterol and read everything he writes.
Peter has a new podcast. It is long, detailed, and perfectly technical for my taste but you may either be overwhelmed or not the sort that can appreciate a long listen--but you should. It is brilliant. The show notes alone will make you better informed. I will share a few highlights here but if you have commute time or schedule meaningful education into your work life--go all in.
I worked with a brilliant cardiologist for several years and was introduced to critical thinking, potential bias in peer review, and from time to time--the limits of statistical analysis in the absence of qualified interpretation. In fact, the name of this blog was pulled from my days working with research fellows required to present their data in a journal club format. I often stated, Come for the Donuts, Stay for the Data as we shared Krispy Kreme donuts outside the lecture hall.
Consider this a warm morsel right from the oven--dig in...
Many recent studies, however, have under-scored the importance of considering the heterogeneity among LDL and HDL particles, e.g., their quality and number, and their variable association with CVD risk.
Discussions of Mendelian randomization spurring engagement of genetic variants as tools for examining modifiable exposure in observational studies are intriguing. Particularly relevant when looking to illuminate the role of limiting cholesterol synthesis vs. focusing on receptor integrity.
Think of PCSK9 inhibition and what we know about the blunted exposure of clinical trial efficacy compared to lifetime exposure in individuals with a PCSK9 genetic mutation showing changes in hyper- function or hypo-function (lowering LDL).
You may recall from your high school science that Mendel was a 19th century monk that discovered pathways of genetic inheritance by studying peas. An assumption of randomization provides the ability to study a single genetic variant or collection of variants associated with a biomarker to test causality of a disease process. Differences observed with genetic variants demonstrate that life long exposure predicts CVD risk more robustly than clinical trials because the magnitude of effect during investigational trials is limited in exposure.
"The longitudinal analysis revealed that plasma DES/CHO in AD patients shows a significant decrease at follow-up intervals. The decline in plasma DES/CHO is larger in the AD group with rapid progression than in that with slow progression. The changes in plasma DES/CHO significantly correlated with changes in the MMSE score."
These findings seem to support DES/CHO as a potential longitudinal surrogate marker associated with cognitive decline outside of protein deposition in the brain. I will post more over at Alzheimer's disease: The Brand once I read the resources posted by Peter Attia.
- The pathogenesis of atherosclerosis;
- How early atherosclerosis begins;
- Ron’s motivation for getting into lipidology;
- How reading an article series in the NEJM in 1967 had a profound impact on him and his career;
- The “battle” between LDL particle size and particle number;
- The use of statins;
- The role of chronic inflammation in atherosclerosis;
- Why niacin may have been unjustly dismissed as a therapeutic option;
- The HDL paradox: why drugs that raise HDL-C seem to elevate (or have little impact on) heart disease risk;
- Mendelian randomization: nature’s randomized trial;
- How PCSK9 inhibitors work and why they may be underutilized;
- Lp(a); and more