So it’s multifactorial? Sure. But you see, saying that explains everything and anything. Or, nothing…A good theory unifies these disparate factors. That’s what we failed to do in medicine so far. And risk factors are just that, statistical associations. A theory does away with those statistical artefacts that are mere associations and identifies only those relevant, causal elements. The 2 hypotheses that feed into one another, the Diet-heart hypothesis (fat => cholesterol => bad) and Cholesterol-CVD hypothesis (cholesterol blocks arteries) have both been falsified. First off, there are multiple associations which falsify the both theories: midle-aged women have lower all-cause mortality the higher the cholesterol, Japanese cohorts don’t see increased risk of death or CVD with higher LDLc or TC, the supposed French Paradoxes etc..It’s important to note that you don’t need to weigh the number of associations supporting & not supporting your hypothesis; (assuming the associational study is well done – granted, a big ‘if’) all that is needed is a single association that doesn’t fit your hypothesis and that is enough to have it thrown out. All the other favorable ones be damned!
This is where peopole in medicine and nutrition need to wake up: IF YOUR THEORY FAILS IN ITS PREDICTIONS, ITS A SHITTY THEORY. We need to realize that the fields of medicine & nutrition are the alcoholics of the science world: the first step for solving a problem is realizing & admitting we have one. Mainstream advice for weight loss, diabetes, CVD, cancer, alzheimers etc. SUCKS! Why? No good working theory. Neither about what causes these diseases or what revereses them. We fail to admit we cannot predict, to any useful degree, who will get it & why. We rather brandish the Multifactorial Flag – a useless truism & tautology mostly – so that we can hide & excuse our ignorance, pretending there is no general lack of scientific acumen amongst researchers.
“So how ’bout dem receptor kinetics? Part of the ‘great work’ or ‘misapplied findings’?”
What about receptor kinetics? What are you expecting the Michaelis-Menten constant (Km), in and of itself, to tell you about the causal process of CVD? You can do all the molecular biological work you want, but that will not replace animal & human models with controlled variables and well donce associational studies falsfiying predictions (or anything you might see in in vitro for that matter). I study molecular biology and can honestly say that Brown & Goldstein’s work to elucidate the FH gene is impressive and exemplar of good science for aspiring researchers. Credit where credit is due. But this isn’t politics, so there are no ‘carry over credits’ for the other claims they make using their original discovery. On day 1 of a genetics course, you understand that although there is ‘the gene for X’, this is in NO WAY A GUARANTEE that only X is affected by the gene encoding it. The nuclear DNA library is a vanishingly small fraction of the story of how phenotype emerges from genotype. The way laymen & the majority of doctors I know, really do not understand genetics. I would count myelf in that group until about 2010. Furthermore, my understanding of epigenetics has completely changed in the past 4 months after reading Mark Ptashne’s work. In fact, many *geneticists* talk a lot of nonsense about epigenetics (as I did previously). No one needs to take the word of Nobel Laureates. That’s the beauty of it all, we can and should scrutinize their ideas. The findings of Brown & Goldstein do not support Cholesterol-CVD hypothesis; rather interestingly, it open up a door to the pivotal role cholesterol plays in the maintaing epithelial integrity and how this affects its interactions with solutes in the blood. Cholesterol IS important in CVD, but not as an inherently negative agent.
raphaels7 