Who should take statins? Is heart disease predictable?

Who should take statins.....besides everyone?  I thought a lot about this when I was working on a lecture about predicting disease. The purpose of statins, of course, is to prevent atherosclerotic cardiovascular disease in people at risk (how well they do this is another issue). The challenge is to identify the people 'at risk'.  I wrote about this in July, but I've been playing some more with the ideas and wanted to follow up.

Statins are a class of drug that, in theory, work by lowering LDL (low-denstity lipoprotein) levels. They do this by inhibiting HMG-CoA reductase, an enzyme that has a central role in the production of cholesterol in the liver.  LDL, the so-called 'bad' cholesterol, isn't actually just cholesterol, but has been linked to risk of heart disease because, as a lipoprotein, its job is to transport cholesterol to and from cells.  It is bound to cholesterol.  What's measured when we have our blood drawn for a cholesterol test is LDL-C, the amount of cholesterol bound to LDL particles (LDL-C), as well as HDL-C, the 'good' cholesterol package, which transports LDL-C from cells, leading to lower blood cholesterol levels.  Cholesterol makes plaque and plaque lines and hardens arteries, which occludes them and leads to stroke and heart attack.  Lower the amount of LDL, and you lower the risk of arterial plaque deposits.

The connection between cholesterol and heart disease was first identified in the Framingham Study in the 1950's and 60's, and this lead directly to the search for drugs to lower cholesterol.  Statins were developed in the 1970's and 80's, and after some fits and starts, began to be used in earnest in the late 1980's.  Statins work by inhibiting the liver cells' synthesizing of new cholesterol, that is, cholesterol that isn't due taken in in the diet.

Akira Endo, one of the first scientists to look for cholesterol-lowering compounds, reviewed the history of statins in 2010.  He described the many studies of the effects of these drugs, saying "The results in all these studies have been consistent: treatment with statins lowers plasma LDL levels by 25–35% and reduces the frequency of heart attacks by 25–30%" (Akira Endo, Proc Japan Acad, Series B, 2010).

A systematic review of the literature on the effectiveness of statins was published by the Cochrane Organization in 2012. The review reports, "Of 1000 people treated with a statin for five years, 18 would avoid a major CVD event which compares well with other treatments used for preventing cardiovascular disease."  This suggests, of course, that 982 people took statins with no benefit, and perhaps some risk, as statins are associated with muscle pain, slightly increased risk of type 2 diabetes, liver damage, neurological effects, digestive problems, rash and flushing, and other effects.  But more on this below.

So, who should take statins? 
Until 2013, the recommendation was that anyone with a modest risk, as assessed by the Framingham Risk Calculator (I've read that that means from 6.5% to 10% 10-year risk) would likely be prescribed statins.  The interesting thing, to me, about this risk calculator is that it's impossible to push the risk estimate past "greater than 30%", even at maximum allowable cholesterol, LDL, and systolic blood pressure, and being a smoker on blood pressure medication.  Which means that there's a lot that this calculator can't tell us about our risk of CVD, based on the best risk factors known.

Framingham Risk Calculator

In 2013, the American Heart Association/American College of Cardiology revised their criteria for statins.  Now, they are recommended for people who have had one CVD event in order to prevent another; for people with primary elevations of LDL-C greater than 190mg/dL; people 45-70 years old who have diabetes and LDL-C between 70 and 189mg/dL, and people 45-70 years old with LDL-C between 70 and 189mg/dL and estimated 10-year cardiovascular disease risk of 7.5% or higher.

The first three criteria are straightforward.  If statins lower LDL, and lower LDL lowers risk of ASCVD (artherosclerotic cardiovascular disease), then taking them should be beneficial.  But then we're back to a risk calculator again to estimate 10-year risk.

ACC/AHA

It has been revised.  Now included are ethnicity (well, White, African American or other), and diabetic status (yes/no), and estimated lifetime risk.  And, now it's possible to push 10-year risk up past 70%, which I discovered by playing around with the calculator a bit.  Whether or not it's a more accurate predictor of a cardiovascular event is another question.

Here's the lowest risk I could come up with, 0.1% 10-year risk.  The recommendations offered are not to prescribe statins.

Lowest 10-year risk

Here's the highest risk I could force the calculator to estimate.  Ten-year risk for a female with these risk factors is higher than for a male, but lifetime risk is lower.  That seems strange, but ok, it must reflect association of risk factors including sex with disease at the population level.  

Compared with the Framingham calculator, risk estimation seems to be getting more precise. Or at least bolder, with estimates up in the 70's.  But is the new calculator actually better at predicting risk than the old one? A paper was recently published in JAMA addressing just this question ("Guideline-
Based Statin Eligibility, Coronary Artery Calcification, and Cardiovascular Events," Pursnani et al.) They identified 2435 people from the Framingham study who had never taken statins. Their medical history allowed the authors to determine that, based on the old guidelines, 14% would have been 'statin eligible' compared with 39%, based on the new 2013 guidelines.

Among those eligible by the old guidelines, 6.9% (24/348) developed CVD compared with 2.4% (50/2087) among noneligible participants (HR, 3.1; 95% CI, 1.9-5.0; P less than .001). Under the new guidelines, among those eligible for statins, 6.3% (59/941) developed incident CVD compared with only 1.0% (15/1494) among those not eligible (HR, 6.8; 95% CI, 3.8-11.9; P less than .001).

So, put a whole lot more people on statins, and you prevent an additional very small number of CVD events; 1.0% vs 2.4%.  And, 93% of those ‘eligible’ for statins did not develop disease. Nor, of course, do statins prevent all disease.  Actually, if everyone in the population were covered, statins would be preventing as many events as they could possibly prevent, but in a small minority of the population.  That is, 90+% of people considered to be at 'high-risk' of disease don't go on to develop disease.  Is it worth the side effects and cost to put so many more people on statins to prevent the 1.4% more CVD that these new guidelines are preventing?  Well, heart disease is still the number one killer in rich countries, and 40+% of the population is currently taking statins, so a lot of people have decided that the benefits do outweigh the risks.

Another question, though, is more fundamental, and it concerns prediction.  The calculator seems to now be predicting risk with some confidence.  But, let's take a hypothetical person with a somewhat elevated risk.  Her cholesterol is higher than the person above who's at lowest risk, but that's due to her HDL.  Her systolic blood pressure is high at 180, which is apparently what bumps up her risk, but her 10-year risk is still not over 7.5% so the recommendation is not statins, but lifestyle and nutrition counseling.  (Though, the definition of 'heart-healthy diet' keeps changing, so what to counsel this person with low risk seems a bit problematic, but ok.)

Low enough risk that statins aren't advised.

Now here's the same hypothetical person, but she's now a smoker, on medication to lower her blood pressure (and her b.p. is still high) and she has diabetes.  Her 10-year risk of ASCVD jumps to 36.8%.  This makes sense, given what we know about risk factors, right?  The recommendation for her is high-intensity statins and lifestyle changes -- lose weight, do regular aerobic exercise, eat a heart-healthy diet, stop smoking (easy enough to say, so hard to do, which is another issue, of course, and the difficulty of changing all these behaviors is one reason that statins are so commonly prescribed).

But now I've lowered her total cholesterol by 70mg/dL, which is what statins ideally would do for her.  Even so, the American College of Cardiology/American Heart Association recommendation is for 'high-intensity statin therapy' and lifestyle counseling.  The calculator doesn't know this, but statins have already done everything they are likely to do for her.

So, let's add lifestyle changes.  But, even when she quits smoking, her 10-year risk is 20%.  So let's say we cure her diabetes -- even then, she's still at high enough risk (9%) that 'moderate to high-intensity statins' are recommended.  I'm confused.  I think even the calculator is confused.  It seems there's a fuzzy area where statins are being recommended when what's left to do is, say, lower blood pressure, which statins won't do.  This hypothetical woman probably needs to lower her weight to do that, and statins aren't going to help with that, either, but still they're recommended.  Indeed, one of the criticisms of this risk calculator when it was released in 2013 was that it overestimates risk.  Perhaps so, but it also seems to overestimate the benefit of statins.  

Further, it seems there are a lot of type 1 errors here.  That is, a lot of people are considered 'at-risk' who wouldn't actually develop cardiovascular disease.  Risk of 7.5% means 7.5 of 100 people with a given, equal set of risk factors are expected to develop disease.  That means that 92.5 would not.  And that means that we have a pretty rough understanding of heart disease risk.  The strongest risk factors we know -- smoking, high LDL-C, diabetes and hypertension -- can be expected to predict only a small fraction of events.

And that means that either something else is 'causing' cardiovascular disease in addition to these major known risk factors, or something is protecting people with these risk factors who don't go on to develop disease.  Family history is a good or even the very best single predictor (why isn't it taken into account in these calculators?) which suggests that it's possible that genetic risk (or protection) is involved, but genome wide association studies haven't found genes with large effects.  Of course, family history is highly conflated with environmental factors, too, so we shouldn't simply assume we need to look for genes when family history indicates risk.  Anyway, it's unlikely that there are single genes responsible for ASCVD except in rare families, because that's the nature of complex diseases.  Instead, many genes would be involved, but again as with most complex diseases, they would surely be interacting with environmental risk factors, and we don't yet know understand how to identify or really understand gene by environment interaction.

And then there's the truly wild card!  All of these risks are based on the combinations of past exposures to measured lifestyle factors, but the mix of those and the rise of other new lifestyle factors, or the demise of past ones, means that the most fundamental of all predictors can itself not be predicted, not even in principle!

So, statins are a very broad brush, and a lot more people are being painted with them than in fact need to be.  The problem is determining which people these are, but rather than zoom in with more precision, the updated calculator instead paints a whole lot more people with the brush.  This isn't the calculator's fault.  It's because understanding risk is difficult, ASCVD is a large and heterogeneous category, and prediction is very imprecise -- even for many 'simple' Mendelian disorders.  If ASCVD were caused by a single gene, we'd say it had very low penetrance.  And we'd want to understand the factors that affect its penetrance.  That's the equivalent to where we are with cardiovascular disease.

I was interested to see that the 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk says something that I have said so many times that I decided not to say it again in this post.  But, I'm happy to see it elsewhere now.  The guideline committee itself acknowledges the issue, so I'll let them explain the problem of assessing risk as their calculator does.

By its nature, such an approach requires a platform for reliable quantitative estimation of absolute risk based on data from representative population samples. It is important to note that risk estimation is based on group averages, which are then applied to individual patients in practice. This process is admittedly imperfect; no one has 10% or 20% of a heart attack during a 10-year period. Individuals with the same estimated risk will either have or not have the event of interest, and only those patients who are destined to have an event can have their event prevented by therapy.

It's the problem of using group data, which is all we've got, to make clinical decisions about individuals.  It's the meta-analysis problem -- meta-analyses compile data from many individual studies to produce a single result that certainly reflects all the studies, because they were all included in the statistics, but it doesn't represent any of them with precision.  Ultimately, it's the problem that these sorts of inferences must be based on statistical analysis of samples -- collections -- of individuals.  We do not have an easy way around this, including the N of 1 studies currently being proposed.

Finally, here's a meta-thought about all this.  Ken and I were in Finland this month co-teaching a course, Logical Reasoning in Human Genetics, with colleagues, including Joe Terwilliger.  Joe said multiple times, "We suck at finding candidate genes because we don't know anything about biology.  We're infants learning to crawl."  The same can be said about epidemiological risk factors for many complex diseases -- we suck at understanding the causes of these diseases, and thus we suck at prediction, because we don't really understand the biology.

Early childhood interventions and health in later life -- or not?

On the heels of our Friday post on the causes of obesity comes a paper in Science ("Early Childhood Investments Substantially Boost Adult Health," Campbell et al.), reported by the NYTimes, ScienceNOW, and other venues, about the effects of early childhood intervention in poor children on the children's subsequent educational achievement and, relevant to our discussion of obesity and cardiovascular disease, their health in later life.

The study
In 1972 researchers in North Carolina began to follow two groups of children from poor families. The children were enrolled as infants (so that experience they already had would not confound the study) and were randomly assigned to one of two groups. One group was given full-time day care and most of their meals up to age 5, and then intensive assistance with what those children were learning at school until age 8, while the other group of children were given only baby formula until they were 18 months old.

Preschool class; Wikimedia

The question the investigators asked was whether early intervention would lead to improved learning abilities later in life, but in fact the effects were fairly immediate, with the groups diverging even by age 3. The groups have been followed up periodically since 1972.  Among other long-term effects are that those in the treatment group were 4 times more likely to have graduated from college.  The authors' bottom-line interpretation of this study is that the earlier the intervention the better, with pre-school effects being much more long-lasting than the effects of school-age intervention.

Now, it turns out that apparently the effects weren't only on cognitive abilities, but were more extensive in important ways.  As the Times reports,

Men in the treatment group, now mostly in their mid-30s, were less likely to develop hypertension than those in the control group. They also had significantly higher levels of so-called good cholesterol, and none had developed metabolic syndrome, the medical term for a group of risk factors that together substantially raise the chances for heart disease, diabetes and stroke. In contrast, a quarter of the men in the control group had the syndrome. 

As for women, those in the treated group were less likely to develop pre-hypertension or abdominal obesity, which tends to be a risk factor for heart problems. They also had healthier habits. They were significantly less likely to have started drinking before age 17, and more likely to be physically active and eat nutritious food, than the women in the control group.

In addition, treated males were more likely to have health insurance at age 30, and to receive medical care when they were ill, although this wasn't statistically associated with health outcomes.  As Campbell et al. write, the intervention group also included a nutritional and health care component.  Children were given healthy meals and a snack every day, and they also were given both well- and ill-child pediatric care, thus, the question of longterm health effects is not an unreasonable one.

Current notions
There has been a lot written in the last decade or so about the effects of uterine environment, early childhood nutritional status and so forth, on health in later life, although cause/effect relationships haven't been solidly established.  Perhaps it's epigenetics, the environmentally-triggered modification of DNA and thus gene expression that is hypothesized to be responsible for just about everything these days, or perhaps exposure to some environmental variable at a given early age triggers a cascade of responses, or perhaps we have no clue.  Studies of these kinds of relationships are in contrast with, in these days of DNA rapture, the much more common and fashionable argument that inherited genotypes are responsible for everything in life.  

Campbell et al. write that the "precise mechanisms" by which early childhood interventions in her study affected adult health "remain to be determined" but that much of the effect seems to be, in the authors' words, "mediated by" (that is, at least were correlated with) low body mass index when children, most significantly males, were 1 year of age.

If so, this would suggest that we know much of what we need to know about how to lower risk of heart disease, stroke, hypertension; feed an infant well, or by the time the child is a year old it's too late.  Forget genes, diet in middle age, cholesterol levels at age 60, sugar consumption, antibiotics, etc.  If obesity or metabolic syndrome or stroke are triggered by what happens in infancy, and similarly, can be prevented with early childhood interventions, looking for causation decades later is fruitless.

This study may well serve to encourage researchers to change the focus of their search for causal risk factors for cardiovascular disease.  At least, these might be the interpretations, if we could take these results seriously.

But can we?
There's a huge caveat.  The original study was of 111 children, 57 in the treatment group and 54 controls.  That's already a small sample.  And then by the time subjects were age 35, attrition had reduced the sample size considerably, until there were only 9 men in the control group who completed both the physical exam and the laboratory component of follow-up, 19 men in the treatment group, 22 women in the control group and 18 in the treatment group.  These are numbers that took a while to find, I might add: I had to dig them out of the supplementary material, though in fairness the main paper did mention that they had had to correct for small sample sizes, which is why I went hunting for the numbers. Indeed, the sample sizes are so small that it makes one wonder why this paper was accepted for publication in Science.  And was picked up by any news outlet at all, never mind many.

ScienceNOW writes:

It’s a grim fact of life in the United States: Children born into poor families are sicker and die earlier than their well-off counterparts, particularly from obesity-related diseases such as heart attack and stroke. Now, new data from a famous North Carolina study of early childhood education suggest that such disparities are not carved in stone. Children who grew up poor but participated in an intensive, 5-year day care program are significantly healthier in their mid-30s than similarly impoverished children who did not receive the same care, researchers report. The study provides rare experimental evidence that such programs can give poor children a better shot at living longer, healthier lives.

Given this kind of write-up, I was ready to really like this paper.  The reporting suggested that longterm, significant health effects could be had with relatively little investment up front.  Regular readers of MT know that that's the kind of health expenditure we would readily support.

Indeed, Campbell et al. concluded,

Whatever the channel, our evidence supports the importance of intervening in the first years of life and suggests that early childhood programs can make a substantial contribution to improving the health of adult Americans and reducing the burden of health care costs. An intervention that lasted 5 years and cost $67,000 [in 2002 dollars] produced sustained and substantial health benefits. Early childhood interventions are an unexplored and promising new avenue of health policy.

Is this science?
This paper should not have made the kind of splash it did. Indeed, its struggle to find convincing samples, measures, and statistically meaningful analyses of same, mainly raise questions about how such research should be done, if indeed it even can be done.

The results as reported are provocative, although the paper itself is less convincing, even if, as the authors write,

We use exact permutation tests to account for small sample sizes and conduct a parallel bootstrap confidence interval analysis to confirm the permutation analysis. We adjust inference to account for the multiple hypotheses tested and for nonrandom attrition. 

Even so, these sample sizes seem 'under powered' to be convincing for this sort of study, to say the least.  Adjusting for attrition and multiple testing as the authors did, even if adequately representing all the data exploration done, with this small and irregular sample, does not convincingly mean that the results are very strong.  The authors went further, to make numerical relative risk estimates on these very small samples, that have to be regarded as very crude, at best, and without much heft.

It has been said with good reason that if you can't see an effect in a sample of 30 or so, the effect isn't big enough to matter.  This argument would apply to simple enough situations where a single variable could effectively be isolated, such as a particular drug vs placebo. Or a gene with strong effect. Unfortunately, in a complex causal web as this paper is reporting, sampling issues are more difficult.  Every sample may be too different to compare, or measures so numerous, interacting, incomplete, imprecise, and context-specific as to require unachievable samples for very definitively specific results to be reached--especially if causation is by complex 'variables' such as diet and so on.

Our personal predilection is that inherent genotypic effects are being heavily oversold these days, for reasons that have as much to do with scientists and their enterprise as they do with the actual facts on the ground about health and societal position.   We would be very happy to be able to laud Campbell et al.'s results as support for our views.

But another view we try to express consistently is that studies should not claim more than they actually find, and that the media should not trumpet them (or in many cases, should refuse even to report them), and should be far more critical of the studies they do decide to report.

In this case, unless we somehow are badly misinterpreting the study, it should be reported at the very most as finding that early effects can be very long-lasting, and that there may be many environmental reasons for this, that could in principle be important to identify.

But as it stands, it just seems highly premature to draw the authors' conclusions, much as we'd like to believe them.

The ever-changing list of cardiovascular disease risk factors

The stories on obesity and heart disease are coming fast and furious.  This is strange because while trends or fads do change, they don't change as fast as the recommendations and findings we get daily from our 'experts'.

This month, obesity is caused by sugar (here's a fine BBC radio program on whether fructose is toxic or not), or antibiotics, and now, according to a piece on the CNN website, food allergies.  Or rather, the public thinks it's caused by food allergies because their friends who went gluten-free lost weight, but it turns out it isn't.  So that one is an urban myth.  But it's an interesting one because it indicates that despite the scorn with which many people hold nutrition advice, given that it changes every week, a lot of people are still looking for simple answers.

Source: Wikipedia

And then there's the question of whether saturated fat -- those fats that are solid at room temperature, like butter, cheese, or fats in meat -- long accepted to be a dietary demon, is actually bad for us.  That is, whether it raises our risk of stroke or heart disease.  The latest news is that it does not.

The BBC sums up the new news this way: "Contrary to guidance, there is no evidence that changing the type of fat you eat from "bad" saturated to "healthier" polyunsaturated cuts heart risk."  But the story is a beautiful example of the role of both faith and evidence in nutritional 'science' because, before describing the study, the reporter hastens to add that researchers still say we should not eat saturated fat.

Heart experts stressed the findings did not mean it was fine to eat lots of cheese, pies and cakes. 

Too much saturated fat can increase the amount of cholesterol in the blood, which can increase the risk of developing coronary heart disease. 

Most of us eat too much of it - men should eat no more than 30g a day and women no more than 20g a day. 

There has been a big health drive to get more people eating unsaturated fats such as olive and sunflower oils and other non-animal fats - instead.

"A big health drive" -- this should mean that unsaturated fats have been clearly demonstrated to protect against heart disease because any expensive public health drive should be based on solid evidence.  As Gary Taubes wrote 13 years ago now in Science, and has been saying ever since, dietary fats have been demonized for decades -- 60 years now -- based on the idea that they raise blood cholesterol levels.

But, as Taubes wrote,

The proposition, now 50 years old, that dietary fat is a bane to health is based on the fact that fat, specifically the hard saturated fat found primarily in meat and dairy products, elevates blood cholesterol levels. This is turn raises the likelihood that cholesterol will clog arteries, a condition known as atherosclerosis, which then increases risk of coronary artery disease, heart attack, and untimely death By the 1970s, each individual step of this chain from fat to cholesterol to heart disease had been demonstrated beyond reasonable doubt, but the veracity of the chain as a whole has never been proven. In other words, despite decades of research it is still a debatable proposition whether the consumption of saturated fats above recommended levels (step one in the chain) will increase the likelihood of untimely death (outcome three).

Taubes goes on to say that in the 1960's, when some scientists were still questioning the role of dietary fat in heart disease, politicians stepped in and "initiated the process of turning the dietary fat hypothesis into dogma."  That is, the nutritional advice we've been given for 60 years, public health policy, was driven by politics, not science.  So Taubes must have been gratified to see the recent report about saturated fat.  (Taubes actually has a dog in this fight, as he has written a lot about sugar as the culprit, e.g. here, believing that replacing fats with carbohydrates has been a mistake.)

The study described in the BBC piece was done by British Heart Association researchers who performed a meta-analysis, looking at 72 studies of the effects of saturated fat, including more than 600,000 participants in total.  The results are published in the Annals of Internal Medicine ("Association of Dietary, Circulating, and Supplement Fatty Acids With Coronary Risk: A Systematic Review and Meta-analysis," Chowdhury et al.).  Down the line, no blood lipid measure has a significant effect on risk.

In observational studies, relative risks for coronary disease were 1.03 (95% CI, 0.98 to 1.07) for saturated, 1.00 (CI, 0.91 to 1.10) for monounsaturated, 0.87 (CI, 0.78 to 0.97) for long-chain ω-3 polyunsaturated, 0.98 (CI, 0.90 to 1.06) for ω-6 polyunsaturated, and 1.16 (CI, 1.06 to 1.27) for trans fatty acids when the top and bottom thirds of baseline dietary fatty acid intake were compared. Corresponding estimates for circulating fatty acids were 1.06 (CI, 0.86 to 1.30), 1.06 (CI, 0.97 to 1.17), 0.84 (CI, 0.63 to 1.11), 0.94 (CI, 0.84 to 1.06), and 1.05 (CI, 0.76 to 1.44), respectively. There was heterogeneity of the associations among individual circulating fatty acids and coronary disease. In randomized, controlled trials, relative risks for coronary disease were 0.97 (CI, 0.69 to 1.36) for α-linolenic, 0.94 (CI, 0.86 to 1.03) for long-chain ω-3 polyunsaturated, and 0.86 (CI, 0.69 to 1.07) for ω-6 polyunsaturated fatty acid supplementations.

And they conclude, "...the pattern of findings from this analysis did not yield clearly supportive evidence for current cardiovascular guidelines that encourage high consumption of polyunsaturated fatty acids and low consumption of saturated fats. Nutritional guidelines on fatty acids and cardiovascular guidelines may require reappraisal to reflect the current evidence."

Source: Wikipedia

It will be interesting to see whether this changes nutritional guidelines.  We're betting it won't, since there is so much belief, and vested interest in current policy.  It's true that if policy were changed to reflect every new finding, there would be no consistent policy, but if Taubes is correct (he's written a lot on fats and heart disease, in addition to the Science piece), the evidence has been inconclusive for a long time, and nutritional recommendations about saturated fats have still not changed.

Is obesity a risk factor?
And then there's the question of whether obesity is a risk factor for stroke and heart disease.   Some studies say yes and some studies say no.  Perhaps that's because sometimes it is and sometimes it isn't; stroke and heart disease happen to people who aren't obese, and obese people don't all have strokes or heart attacks.

A recent study reviewed in a recent issue of The Lancet reports on

... a large collaborative study on the role of overweight and obesity on risk of coronary heart disease and stroke, and on the contributions of blood pressure, dyslipidaemia, and glucose concentration both singly and in combination. The study, which included nearly 2 million individuals of different ethnicity from around the world, increases our understanding of coronary heart disease and stroke. The three major risk factors—often associated with overweight and obesity—explain roughly 50% of the cardiovascular outcomes recorded.

That is, high blood pressure, cholesterol and glucose, associated with obesity, were found to be responsible for 50% of the cardiovascular disease among study subjects, while 50% was unexplained.  The Lancet suggests that, "Therefore, future research should examine other mechanisms linking obesity to cardiovascular disease, including inflammation, cytokine excess and oxidative stress, and cardiorespiratory fitness."

Well, yes, heart disease is yet another complex trait.  Just as with other complex traits, there are multiple paths to cardiovascular disease, and large heterogenous study samples will include many of them, but the analysis won't.  And to complicate things further, if inflammation, cytokine excess and oxidative stress, for example, are found to be linked to cardiorespiratory fitness, they will be in non-obese people as well.

Another bob of the yo-yo
After all these years of work, why do we still have to see such results?  Do these count as actual 'results' or is this just another bob of the yo-yo?  When can we get results we can trust, and then stop re-studying the same thing again and again?  Why are we in this situation?

Culture changes, but if the world follows natural laws, the molecular effects of cholesterol or salt or sugar etc. should not change.  That is, by now, or long before now, we ought to have a sense of the per-dose effects and that should not change, even if our habits do.  But the fact seems to be that we do not, even by now after decades of heavy investment, have such knowledge.  Or, perhaps more cogently, the effects are not acting on their own, and depend on our habits.  Does that mean an endless boon for schools of public health and their epidemiological research projects, that seem to get uncritically ever longer and costlier without more definitive results?  Where, as the old ads said, is the beef?

Or is the truth that this whole field reflects the problem with reductionist science?  When the assumption is that the culprit is a single food, or a single gene, it's impossible to elucidate a more complex interplay of risk factors. It is not new to suggest that this is simply not a very good way to do this sort of science!  Context-dependency at the very least depends on combinations of exposures, not single-factor (including single-gene) causation, even if each individual factor has its own molecular interactions.

But more worrisome is our feeling that even highly technical multivariate statistical slicing and dicing of very large datasets is not a good or effective approach, even if at present we really have no better one.   Ever more sophisticated statistical analysis applied to ever-larger studies do not seem to be generating answers.  As we say many times, it serves perhaps most as a stalling action to keep these research operations in business, rather than a way to stimulate better science.

We know that moderation is a generally good thing, for reasons that range from philosophical to evolutionary.  We also know that small subsets of people are severely affected by some of these factors like sugar (diabetics) or cholesterol (LDL Receptor mutations) and so on.  If we removed the overdosing by our McCulture, we would perhaps be left with these subsets that really might be amenable to simple-cause analysis, and there the application of technological solutions might be feasible -- there is where the research effort should go, not to just more studies of minor statistical effects, in our view.

But our system, though fully aware of the situation, cannot slow itself down to think more critically, is bureaucratized and entrenched so it cannot adequately train new students to be innovative and creative, and cannot forthrightly fess up to the problem.  Instead, whether or not the scientists are just yo-yo's, the science certainly seems to be just that.

To statin or not to statin, that is the question....or is it?

Last week we all heard about the new recommendations concerning predicting and preventing heart disease.  An online calculator was going to be used to predict risk, based on past experience of a study cohort, and if we were found to be at risk, we'd be advised to start taking statins.  Based on various risk factors -- BMI, whether we smoke, etc., -- the calculator would advise our doctor if our risk of heart disease was greater than 7.5%, and if so, that would trigger the writing of the prescription.  Estimates were that this was going to lead to 1/3 or more of American adults taking statins for the rest of their life.

We had various reasons to question this recommendation, as we wrote then, and that was even before new issues have come home to roost.  As reported in the NY Times yesterday (and in The Lancet today), experts are now showing that the calculator is way over-estimating risk, which would mean millions more people on statins than the generous new guidelines themselves would recommend.    Some leading cardiologists are calling for a halt to implementation of the new guidelines until the calculator issues get sorted. 

But apparently this shouldn't have come as a surprise to the cardiac community -- two Harvard cardiologists, authors of the Lancet paper, warned a year ago that the calculator overestimates risk.  The problem seems to stem from the use of old data to do the estimations. Ten or more years ago more people smoked, and developed cardiovascular disease earlier than they do now.  Risk estimates on that background now overestimate the effect of factors such as blood pressure and cholesterol because additional background factors, also a component of risk, have changed.  That is, there are confounding variables that affect risk, whose frequency in the population have change, but the calculator doesn't take this into account.  

Or at least that's probably the problem.  It may be even more fundamental than that.  Decades ago, a very well-known cardiovascular disease epidemiologist, Reuel Stallones, used to say that heart disease rates had both risen and fallen in the 20th century for reasons that were not understood.  Diet, exercise, smoking, cholesterol, none of the obvious risk factors explained either the rise or the fall, and it's still true.

However, the risk calculator problem raises another truly fundamental issue that pertains to this sort of risk prediction in general, not just to heart disease.  We have several times noted that one essential flaw in the whole concept of risk estimation based on the kinds of studies that are done, is that risk is estimated retrospectively, from a study sample's past experiences, but what we want are prospective risks: yours and mine for the future, not the past.  But future experiences, mainly here involving lifestyle environmental factors, are inherently unpredictable (In case you missed it, that's inherently unpredictable).

The critique of the new recommendations, in an unusual way, showed just this problem.  Risks were estimated for the new calculator from past data, but used to estimate risks subsequently.  However, since lifestyle risk has changed (less smoking, for example) our ultimate experiences can't be adequately predicted from risks based on the earlier experiences of the cohort used to estimate risk.  Whatever would lead properly cognizant epidemiologists to think that things would be different for the real future?

Indeed, this shows the stubbornness of our clinging to kinds of statistical association mechanisms, the belief in big-science, the haste, and so on that plagues much of what is afoot these days.  To a great extent, we do what we know how to do, the problems are very challenging and often risks are small in absolute value so that, with our approach, we do look to very large studies.  But we also stick with this rather than slowing down, taking a deep breath, and really re-evaluating what we face.  This is the issue we often write about: the need for a deep change in our scientific concepts or methodology, not just keeping the research factory humming.

Plus, we already know a better way to prevent heart disease, and that is lifestyle choices, exercise, not smoking, eating more vegetables than fats and meats.  Statins are largely generic drugs now, but they are still an expensive way to prevent illness -- people without disease become patients (see Jim Wood's August post on how he became sick), they are in the medical system, requiring not only drugs for life but testing and follow-up testing and so on.  And, statins aren't benign drugs; they do have side effects, including muscle pain, liver damage, diabetes.  The industry's credibility is at stake now with this calculator issue, but there are other reasons to question their word about going on statins.  

Intestinal microbes and heart disease -- we are what we eat

And now another in our irregular series on the role of anything-but-genes in chronic disease.  We've posted about the possible role of inflammation in many late onset or chronic heart disease, diet and lifestyle in heart disease, inflammation in asthma, cleanliness in asthma, inflammation in macular degeneration, and so on.  Diseases, it must be noted, for which hundreds of millions of dollars have been spent on the search for risk factor genes.  The excuse for this, used by geneticists to garner many huge grants, and with little other rationale for obviously environmental problems, was that they'd find important (major) segments of the population that were genetically susceptible to these environments.  We need not here belabor the thinness (from the beginning) of that rationale, because there are more important things to think about.

Steak; Wikimedia

For decades, primarily thanks to findings from the Framingham Study, it has been accepted wisdom that red meat is a risk factor for heart disease.  Why?  Because eating red meat was thought to raise cholesterol, which leads to hardening of the arteries, and then cardiovascular disease.  That led the pork and chicken industries to promote their implied-safer products (e.g., "the other red meat!").  Eggs, too, were implicated for a while because the yolks are high in cholesterol, though they were taken off the danger list some time ago (unfortunately, too late for some of us, who have developed a reflex egg-aversion, but given the cycling of risk factors, maybe that egg-aversion is a good thing).

Recent meta-analyses were not able to confirm the association between saturated fat and cholesterol and cardiovascular disease, a rather stunning finding that suggested that there may be other, perhaps correlated, environmental factors involved.  Two recent stories by Gina Kolata in the New York Times present just such alternative risk factors.

Kolata's story on April 7 suggested that indeed it's not the saturated fat or the cholesterol in meat that's to blame but the response of microbes in the gut to a constituent of the meat, carnitine in particular.  In a paper published in Nature Medicine, researchers at the Cleveland Clinic propose that when we eat meat the microbes in our gut convert carnitine into trimethylamine (TMA), which the liver then converts into TMAO, trimethylamine N-oxide, thought to be the real culprit in cardiovascular disease (CVD) because it causes atherosclerosis, hardening of the arteries.

The researchers compared the response of meat eaters and vegans to ingesting carnitine, and found that vegans didn't produce TMAO. Studies have shown that microbial composition of the gut does indeed vary with diet, among other things (geography, pregnancy, etc.) and meat eating presumably feeds a subset of microbes that vegans don't host.  Theirs don't make TMAO.    

Hard boiled eggs; Wikimedia

Kolata's story in yesterday's Times reports that a constituent of eggs might also be converted into TMAO by microbes in the gut.  In a paper published in the New England Journal of Medicine on Wednesday, the same researchers propose that when we digest the phosphatidylcholine, or lecithin, in eggs, one of the constituents is choline.  Intestinal microbes convert choline into TMA which, again, the liver converts into TMAO.  Other major sources of lecithin include liver, beef and pork.

Damn!  Do we have to stop the meat and eggs again?

Researchers confirmed the middleman (or middle-microbe) effect of intestinal flora by having their subjects take an antibiotic that wiped out the gut bacteria before they ate hard-boiled eggs.  With the microbes gone, TMAO levels in the blood didn't rise.  Only when the microbes were back to normal levels did TMAO rise. 

So, yes, foods high in fat and cholesterol may be associated with risk of heart disease.  But it's not because of the fat and cholesterol per se, but because these substances are present in foods that also have the constituents that gut microbes convert into what seems to be a true risk factor for atherosclerosis, TMAO. Not to mention that gut microbes are heavily determined by what we eat, as well.

We've 'known' for decades that red meat was a heart disease risk factor, and it was clearly because of fat and cholesterol.  This became lore.  The beef industry provided beef with less fat, the pork industry sold us on 'the other red meat', the poultry industry crowed, especially when eggs went back on the list of foods okay to eat.  

Vegan food pyramid; Wikimedia

And there was clearly a genetic component to heart disease risk, and/or to obesity, because CVD seems to run in families, and obesity is a risk factor, and this made many genetics labs crow.  Except that it was confusing when people with no family history of heart disease or thin people had heart attacks.

Despite the billion dollar industry that investigating, preventing and treating heart disease has become, it remains the leading cause of death in the US and other countries.  Number one.  Clearly we're doing something wrong -- including throwing a lot of money away on genetic studies that we knew really were going nowhere fast.  The intestinal microbe connection might turn out to be a huge advance in our understanding of heart disease, and it might well be that simple dietary changes and pharmaceutical approaches to cultivating 'good' microbes in our gut will prevent heart disease in many people -- leading the pharmaceutical industry to be the big crowers this time around. Of course, we can expect the genetic industry to say that some people are susceptible to the bugs' in their guts, but others (once we do the GWAS, whole genome sequencing, and 'personalized genomic medicine') will be cleared to go for the Egg McBreakfasts (with bacon).

But, this isn't likely to be the next health-research miracle, even if it gets promoted as one.  We would caution that this explanation will account for only some heart disease, even if the findings, which would be quite valuable to know, hold up.  Just as with every other complex disease, there are multiple pathways to this trait.  Why, for example, is smoking such a clear major risk factor?  Heart disease will remain a heterogeneous trait, difficult to predict, and not always possible to prevent.  But still, it's always refreshing when some innovative researcher breaks free of group think and provides new ideas on perplexing subjects.

The greatest irony, or should we say the last laugh, goes to the bugs who continue to outwit us and take us to our graves.

Wait, wait! Don't tell me!

Heart disease risk factors
There's an NPR radio program called "Wait, wait.... don't tell me!" that has relevance to science these days, as is easy to see.  We see frequent reports of how to live if we want to stay healthy, such as to keep an eye on our cholesterol if we want to avoid heart disease.....

But wait, should we obsess about our cholesterol numbers or shouldn't we?  And, if we obsess too much, will the stress cause the very heart disease we're trying to prevent? A short piece in Sunday's New York Times refers to new analysis of an old study of Australian men, and effects of various dietary components on blood lipid levels and risk of death. The new analysis was published in the British Medical Journal last month, with an accompanying commentary by Philip Calder. 

We've known for decades, in large part due to the never ending Framingham Heart Study, which began in 1948 and is now looking at third generation subjects from Framingham, Massachusetts, that saturated fats raise the risk of heart disease because they raise cholesterol levels.  And, we've known that polyunsaturated fatty acids (PUFA's) -- safflower, sunflower, corn and soybean oils -- reduce cholesterol, and thus lower heart disease risk. Framingham may have led the way, but many other studies confirmed these findings, and eating more PUFA's and less animal fat has been the basis of heart friendly dietary advice for decades. 

Or not....
But wait! Now researchers have reanalyzed the Australian data, which originally took place between 1966-1973.  In this study, one group of  men with heart disease ate more omega-6-rich polyunsaturated fat, linoleic acid, and the control group, also with heart disease, ate as usual. According to the NYT:

The men were followed for an average of 39 months, and those on the polyunsaturated-rich diet lowered their cholesterol levels by an average of 13 percent. But they also were more likely to die, and in particular to die of a heart attack, than those who stuck with their usual diet, which consisted of about 15 percent saturated fat.

What does this mean?  Yes, polyunsaturated fats do seem to lower cholesterol, but they also raise risk of death from heart disease.  Does this mean we need to question the link between cholesterol levels and heart disease?  Or, maybe there's another pathway -- polyunsaturated oils may decrease cholesterol but at the same time increase inflammation, which has been shown subsequent to these and early Framingham results, to be involved in heart disease, though it's not clear how.  And this may override the supposed positive effects of lowered cholesterol.

Indeed, according to the editorial in the BMJ, proper studies of the effect of replacing saturated fat with PUFA's without other dietary changes have rarely been done, so that it has been impossible to evaluate the effect of linoleic acid alone on cardiovascular disease risk. Until now, with the re-evaluation of the Australian data.

The original analysis showed an increased risk of all cause mortality in the study group, the men who increased their intake of linoleic acid, but the new analysis shows that death from cardiovascular disease also increased.

These findings argue against the “saturated fat bad, omega 6 PUFA good” dogma and suggest that the American Heart Association advisory that includes the statement “higher [than 10% of energy] intakes [of omega-6 PUFAs] appear to be safe and may be even more beneficial” may be misguided. The more cautious UK dietary recommendations on fat and fatty acids, which include the statement, “There is reason to be cautious about high intakes of omega 6 PUFAs,” seem fully justified in the light of the current study’s findings.

Calder suggests, and rightly, that "subtle, and in some cases unsubtle aspects of study design" have effects on results that are too often not considered when results are interpreted, and dietary advice made public.  This of course always pertains, not just in the case of diet and heart disease risk factors.

So, advice is often given on shaky evidence.  A piece in Nature on 26 February -- "Cholesterol limits lose their lustre" -- is another example.  People all over the world are on statins for life to lower their cholesterol to prescribed targets, making pharmaceutical companies very rich, but how valid are those targets? 

Most people who have heart attacks, it turns out, don't have high LDL's ('bad' cholesterol).  A cardiologist at the University of Minnesota Medical School in Minneapolis is quoted in the piece saying, "If your arteries and heart are healthy, I don't care what your LDL or blood pressure is."

So, cholesterol guidelines established by the US National Heart, Lung and Blood Institute may soon be changed, and LDL targets abolished. 

Expected to be released later this year, the fourth set of guidelines, called ATP IV, has been drawn up by an expert panel of 15 cardiologists appointed by the institute. The guidelines will set the tone for clinical practice in the United States and beyond, and will profoundly influence pharmaceutical markets. They will also reflect the growing debate over cholesterol targets, which have never been directly tested in clinical trials.

And, a report last week suggests that processed meats like bacon and sausage are lethal.  But, wait, not if you're Italian and eat a lot of Parma ham!  Does that mean that the Chianti and Valpolicella of the Mediterranean diet compensate? All of this gives 'bringing home the bacon' a suddenly negative connotation! 

From "Processed meat 'early death' link," BBC

But wait, if the new report that post-traumatic stress disorder raises the risk of heart disease is true, mediated by increased insulin resistance, then perhaps attention will be taken off cholesterol and diet entirely, and turned to reducing stress!

How to recognize dangerous warnings and avoid risks....
It isn't just your health that's at risk with all of these confusing never-ending contradictory reports.  Whenever you hear (as you almost always do!) an investigator say "studies show that" or "we need further research," grab hold of your wallet and run for cover!  Because you're about to be pick-pocketed, and that, unlike the epidemiological studies, is something you can rely on!

There are many reasons for resisting the understandable desire of epidemiologists and geneticists to seize on these uncertainties as a rationale for more funding to study the same problems essentially with the same methods but on a bigger, longer scale.  We'll go over them in a forthcoming post.

Mediterranean diet cuts risk of heart disease!

This story is making headline news yet again, including at the New York Times, where Gina Kolata describes a new study done in Spain of the effects of adding extra virgin olive oil or nuts, fish, fruits, legumes and red wine to the diet, and reducing the consumption of red meat and processed baked goods.  (Note that the pyramid below was adapted from Consumer Reports Nov 1994.)

From www.womensheart.org

The total study group of about 7000 men (aged 55-80) and women (aged 60-80) was divided into 3 subgroups, and asked to follow the Mediterranean diet (MD) with extra virgin olive oil, the MD with nuts, or a low-fat diet.  They weren't asked to lose weight or to exercise.  The MD groups were given olive oil or nuts every week, and counseling as to how to follow the diet, while the low-fat diet group (the control group) was given a pamphlet on how to follow the diet when enrolled in the study, and then annually until 2006, when it was recognized that their adherence to the diet was poor, at which point researchers added further intervention. This group still never could consistently follow the low-fat diet, and instead were essentially eating their usual diet. 

Recruits were people without heart disease but with type 2 diabetes, or at least three major risk factors ("smoking, hypertension, elevated low-density lipoprotein cholesterol levels, low high-density lipoprotein cholesterol levels, overweight or obesity, or a family history of premature coronary heart disease").  They were followed up until either they dropped out or until the year 2010. The total person-years in the study was about 12,000, 11,000 and 10,000, by group. 

The paper is published in the New England Journal of Medicine.  The researchers assessed primary and secondary outcomes, with the former being heart attack, stroke or death from cardiovascular disease, and the latter being heart attack, stroke, death from cardiovascular disease or death from any other cause. 

The median follow-up period was 4.8 years. A total of 288 primary-outcome events occurred: 96 in the group assigned to a Mediterranean diet with extra-virgin olive oil (3.8%), 83 in the group assigned to a Mediterranean diet with nuts (3.4%), and 109 in the control group (4.4%). Taking into account the small differences in the accrual of person-years among the three groups, the respective rates of the primary end point were 8.1, 8.0, and 11.2 per 1000 person-years.  Outcomes According to Study Group.). The unadjusted hazard ratios were 0.70 (95% confidence interval [CI], 0.53 to 0.91) for a Mediterranean diet with extra-virgin olive oil and 0.70 (95% CI, 0.53 to 0.94) for a Mediterranean diet with nuts.

And,

In this trial, an energy-unrestricted Mediterranean diet supplemented with either extra-virgin olive oil or nuts resulted in an absolute risk reduction of approximately 3 major cardiovascular events per 1000 person-years, for a relative risk reduction of approximately 30%, among high-risk persons who were initially free of cardiovascular disease.

There was no effect of diet on mortality from all causes.  That is, the difference in total number of deaths between groups was not statistically significant.  The effect of diet on cardiovascular disease was apparently through stroke, not heart attack.  People following the Mediterranean diet did not lose weight, nor reduce the amount of fat in their diet, so the effect, the researchers say, was of dietary components alone. 

Interestingly, when researchers compared the merged MD groups with controls recruited before and after 2006, they found that "adjusted hazard ratios were 0.77 (95% CI, 0.59 to 1.00) for participants recruited before October 2006 and 0.49 (95% CI, 0.26 to 0.92) for those recruited thereafter (P=0.21 for interaction)."  Remember that the researchers decided to do more intervention with the control group after 2006. 

But how is that to be interpreted?  Were controls adhering better to the low-fat diet after 2006, and it turns out to be significantly worse than the MD?  Or vice versa?  Did the act of intervention itself made a difference somehow, or were the people recruited after 2006 metabolically different, older, sicker or something else from those recruited before?  Whatever the reason for the difference, it does suggest that comparison between the three groups is not a simple comparison of three different diets.

If this study is as significant as the write-ups are saying, it means that the effect of changing diet can be significant enough to be detectable within a relatively short time span (this study spanned 2003-2010, with subjects apparently included for varying lengths of time).  This suggests that the effect of a non Mediterranean diet over a lifetime is reversible, and thus that risk isn't as genetic as some think (not a surprise!), risk factors like blocked arteries may be reversible by diet, cholesterol can be changed by diet (this is also well-known), being overweight is not a significant risk factor (results on this issue go back and forth), and low-fat diets aren't protective (this, too, has been shown before, though doesn't seem to have caught on with the public). 

And, while this study does confirm things that have already been known, actually rather well and for quite a long time, it also means that people on the Mediterranean diet still die of cardiovascular disease, particularly heart attacks.  Rather than 11 CVD deaths per 1000 person-years, there were 8.  So, the difference may be statistically significant, but it's not qualitatively huge, like 25 vs 2, or even 11 vs 2.  Though, of course if you're one of those three, that's an incalculable difference.  Further, we don't know whether it's eliminating red meat and baked goods rather than adding olive oil and wine and nuts that makes the difference.

One can ask to what extent we should even be doing more and more studies of the same basic idea, once we have systematic data in its favor (dramatic disease benefits were found in a major North Karelia Finland project a long time ago, for example, in a huge dietary intervention study in a place that had, at the time, the highest CVD rates in the world).  There are various ways to measure effects and benefits, and to define outcomes, and these are relevant to evaluating any studies of diet and health.

If nothing else, this study is a reminder that if you reduce deaths from one cause, deaths from other causes go up.  People do still die of something.