Sunday, April 12, 2015

Uncertain Health in an Insecure World – 34

“Mark Twain Turns 180”

Epidemiology is old school science. Associations between human characteristics and diseases, even when statistically significant, are not proof of cause and effect. As Mark Twain once put it, “There are lies, damn lies and statistics”. When so-called “weak effects” data make it to the pages of high impact journals, they assume great significance in the minds of readers.

Here are some recent studies from the epidemiology research space.

The United Kingdom Clinical Practice Research Datalink recorded characteristics of 2,000,000 people aged 40+ between 1992 and 2007, with a median age of 55 years, of which 55% were female. As reported in The Lancet, of these individuals, a total of 45,000 developed dementia during the period of observation – 2.4 cases per 1,000 patient years. In this cohort, obese subjects (BMI ≥30) were at lowest risk of future dementia, while underweight subjects (BMI <20) had the greatest risk – 34% greater than those with normal weight. By age 80 years, the incidence of dementia was 9.9% for underweight people versus 4.9% for obese people.

I'm not sure what to make of this so-called “obesity paradox”.

WHO reports that of 36 million annual deaths worldwide from non-communicable diseases, nearly 8 million are from cancer. The American Cancer Society estimates that one in three cancers in the U.S. are linked to excess body weight, where diet and physical inactivity are thought to be contributors. Evidence points to greater prostate cancer risk and poorer post-surgical outcomes in obese men, especially among African-Americans. A large European study (EPIC) showed that greater height and obesity are associated with an increased risk of breast cancer in post-menopausal women – for every 5 kg gained, the risk increased 8%; hormone therapy was partially protective in women with a BMI >30. The Women’s Health Initiative followed 161,809 women from 1998 to 2006, showing that there was an inverse association between lower BMI and higher lung cancer risk in smokers.

Enter the new school science of gene sequencing, or genomics.

A study in The New England Journal of Medicine on the DNA of 65,066 people with coronary artery disease (CAD) compared to 128,383 controls showed that CAD risk increased by 13.5% for each 2.5 inch drop below the average height. ‘Bad’ LDL cholesterol and triglyceride levels were found to statistically account for only 31% this increased short-stature risk. The accepted theory had been that larger people have wider arteries, so that plaques are not as occlusive. Of some 180 DNA sequences in the human genome known to contribute to height, no single genetic variant could explain these CAD risks. The researchers could not explain the other 69% risk for greater CAD risk in shorter people.

In order to explain the statistically unexplained, things get more complicated.

According to the Journal of the American Medical Association, epigenetics is “at the epicenter of modern medicine”. DNA sequences (genes) are generally independent of lifestyle and environmental factors. However, the sub-cellular microenvironment contains heritable chemical factors that can alter genetic controls, thereby influencing disease risk. The overhyping of epigenetic diets and drugs has been criticized, as has the ambiguity of its definition. But epigenetics is a tool – a scientific discipline – that might connect genetic DNA sequences (big data) to the observed risk of disease in populations (statistics).

On Silicon Valley’s Sand Hill Road, the smart money that created eBay, Google, Napster and Facebook is backing the premise that life can be extended by studying big genetic databases, using super-computing analytics at supra-terabyte levels to uncover the causes of death. As public research funding stalls, increasingly, private investors and venture capitalists are driving the biomedical research agenda. If dense data contained within the genome and epi-genome can be sorted, the cause and effect secrets of the human body may be reverse-engineered into deeper understandings of the basis for diseases and longevity.

The same technological wizards who engineered social media, secure online payments and movie streaming are turning their problem solving skills to the ultimate challenge – prolonging life. What would happen to society, to humanity, if the 1% of the world’s population controlling 50% of its wealth could afford the biomedical interventions permitting 150 year lifespans? Along with Bill and Melinda Gates, 130 billionaires have signed the ‘Giving Pledge’ to donate half of their accumulated trillions of dollars to engineer better health through advanced biomedical research tied to big data analytics.

These tech billionaires are ushering in another Gilded Age of philanthropy that could ultimately benefit global health. But to some, these initiatives appear more suited to preventing the ills of the rich – as Bill Gates said, “It seems pretty egocentric while we still have malaria and TB for rich people to fund things so they can live longer”.

Here’s the rub… 
With thousands of genes being sequenced, with untold chemicals in the epigenetic ooze, and with hundreds of thousands of subjects contributing their DNA to big databases, the statistical possibilities are almost endless.

Titans who changed the world by harvesting the power of machines & technology believe that they can also improve the human condition. Whether it’s Rockefellers or the Gates, the belief in what’s possible drives investing more powerfully than any damn statistic.

If Mark Twain had enjoyed great longevity, perhaps he’d opine today that, “There are data, big data and analytics”.

The Square shares such optimism! You gotta believe in something, right?

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