So, the latest (hottest, and certainly this time just must be true) report is that obesity (that is, Body Mass Index, or weight-for-height) isn't so clearly damaging to health and disease as billions of dollars and millions of pages of punditry and scientific hyperbole have suggested over a mere fifty years. Whoopie! We can eat again! What a relief!
Or is it?
The study we posted on yesterday seemed to say that. But even forgetting our usual (of course always cogent and well-placed) reservations about science news bulletins, perhaps there is something else to note, that might cause at least a few milliseconds of thoughtful contemplation.
If this is a causal, material world, then as the argument goes, everything must be understandable and predictable strictly in terms of molecules and energy--because that's all there is! And since, the argument continues, evolution has molded life around DNA as the primary causal molecule, we simply must be the product of, and hence predictable from, our genes.
The BMI study was not a genetic report, and only concerned the predictive power of the net measure, BMI. It was about the long-assumed health risks, or not, of obesity. But there is a bit of slippage here: BMI is easy to measure (your weight related to how tall you are), and so many different studies can collect comparable data, etc. It is thus a convenient measure of choice for obesity.
Taking the current dogma of our time that everything simply must, obviously, necessarily be 'genetic', many studies you've paid for with your taxes have naturally done their best to find the genes 'for' this important health-risk trait.
No, not at all
Thus a major and very large GWAS on the genetics of BMI was published a couple of years ago (Nature Genetics, Nov. 2010). This study of a mere 250,000 individuals found a small number of modest (statistically 'significant') locations in the genome, including one confirmatory gene (called FTO) that a blind person could find without using his hands. Other 'known' obesity risk-factor genes weren't in this list, and of course there is the plethora of excuses--er, that is, alternative explanations--for why these genes didn't show up in the hit-list.
Now that is mysterious enough (unless you've been thinking critically about genetic causation, its evolutionary history, and the nature of such studies), but at least it's a large study that should illuminate at least the nub of the causal truth.
However, also in Nature Genetics in Nov. 2010 was another obesity GWAS. This time the measure used was not BMI, but the waist-to-hip ratio (WHR). This is another convenient, non-invasive, and cheaply measured index of obesity. The study was the pooling of 61 studies of a total of a mere 114,000 participants. Now this study essentially found no overlap in genome region 'hits' with the BMI study! It also failed to show several genes well known to relate to obesity and related dieases, from many actually focused studies including mouse experimental work.
One can rationalize all one wants about this 'discrepancy' (to use a kind word for it). But if 'obesity' is a meaningful trait with any sort of unitary causal nature, then measuring it in two ways should generate essentially the same result, after accounting for statistical vagaries. Just as using a metric (Celsius) thermometer won't tell you anything more about water, ice, and steam than using a Fahrenheit scale.
|237 traits linked to genomic loci by 1449 GWAS studies|
(Source: www.genome.gov/GWAStudies); 2012
This issues seems not at all to have been noticed (openly, at least) by anybody. Instead, it should be seen as a clear and devastating indictment of the GWAS and related 'omics' grand-sample, meta-analysis, quick-and-dirty enterprise that we are investing so heavily and mechanically in. It should be the miner's canary, telling us clearly that we are not going about this in a right way.
We can't blithely accept the current BMI and health finding as related to obesity in an interpretable way and are rather forced to recognize, as we said in our prior post, that BMI is a stand-in for some confounding factor(s) that may or may not have been measured. That's because if different genes predict one measure of 'obesity' compared to another measure, there must be some seriously complex or heterogeneous causal variation in our data that we are not measuring, may not know about, but are not highly correlated with each other or, at least, are not consistently correlated with different ways we choose to define something as a trait, or risk factor.
'Obesity' is in some ways an obvious trait in its extremes (from skinny to very over-weight), and body weight is clearly related to health measures of various kinds. But the Omics Way that is being taken is falling short, and this also means that the Epidemiological Way, of parsing a large plateful of variables into this or that correlation coefficient with various statistical significance levels, is also badly wanting.
We don't have the answers. Indeed, the problem is not just that nobody has the answers, it's that the only reaction is to claim we need more and more, larger and larger, studies of essentially the same sort to get the answers! But, bigger isn't always better!