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Sunday, March 29, 2020

A Rant on Risk.

Apologies for a long delay in posting. I'm busy researching a book: "The story of food and dining"



Risk is an abstract concept and the perception that a risk exists, or the degree of that risk, is determined by an individual’s worldview. Pail Slovik at the University of Oregon has written many research papers on the topic. For the general public, risk is determined by three factors. First a high level risk is associated with dread. Everyone knows an obese person and would have seen overweight friends lead long, happy and healthy lives into old age. Thus, obesity and overweight is not dreaded. However, motor neuron disease is dreaded, seen as a fatal disease with a slow decline in wellbeing and with a growing dependence on others. A second factor is familiarity. These days, most of us know someone who was diagnosed with cancers. Decades ago cancer was, in effect,  a death sentence. However, many cancers are now manageable and allow those who contract cancer to enjoy a long and happy life. So, cancer is seen as a risk which is familiar and something not to be feared as it once was. The third factor is control. Those who smoke know the risk but they retain the belief that at any point, they can quit smoking. But, during the height of the BSE crisis, Variant Creutzfeldt–Jakob disease (vCJD), was a condition which was outside our personal control. We might be a vegetarian but who’s to say that your vegetable curry wasn’t contaminated with gelatin. You might avoid a T-bone steak but could you be sure that the minced beef you just bought is BSE free. In fact, vCJD hits all the buttons: it is dreaded, it is unfamiliar and it is totally outside your control.
One would imagine that toxicologists, whose speciality involves all manners of risk analysis would have a clear and objective understanding of risk, independent of their worldview. Thus it shouldn’t matter if you are Christian, Jew, or Muslim when, as a toxicologist you consider the scientific data on the hazards to human health of some chemical or biological risk. But Slovik’s study challenges that. When presented with several scenarios, toxicologists were asked to rate the risk. In the US, male toxicologists had a higher risk tolerance than their female counterpart. The same was true in Europe except that European toxicologists had a much lower tolerance of any given  of risk compared to their US counterparts. Right now, in the midst of this Covid 19 pandemic, we can see geographic or cultural variation of risk perception and thus differing strategies of risk management. In some countries, economic issues hold a higher ranking than societal issues leading to quite different messaging to the general population (Obrador, Trump, Bolsonaro).

Risk assessment is purely scientific while risk management is tainted with the politics of the problem. It follows the seat belt rule. When research showed that seat belts would save lives, car manufacturers were asked to install them in new cars. Then the were obliged to do so by law and drivers were asked to use them. In turn, drivers were legally required to wear them. In the realm of risk managements there are vested interest which either promote or downplay the risk according to their interests. And there are rogue scientists who exploit the scare to self-promote themselves[1],[2],[3], [4]  There are also very eminent scientists, experts in the field of epidemiology,  who query and challenge scientific opinion[5]. Where true debate can be held, we should remember that dissent is the oxygen of science.
In an environment where all hazards to human health are properly managed, there is no reason for people to go beyond that system and take a risk. But around half the global population don’t enjoy such sanitized existence and they have to take risks. Hunger, they say, is the best sauce and the those who suffer hunger will take risks to meet their nutritional needs. They have no choice. And it a world which favours the privileged societies, social distancing in the current Covid 19 pandemic is easy to comply with, albeit annoying to endure. But in the slums of the great cities of the world, the townships of Johannesburg, the Favelas of Sao Paulo or among the 18 million US citizens who live in trailer parks, social distancing is challenging and the risks that it seeks to mitigate can’t easily be avoided. But its not just among the world’s disadvantage that risk is tolerated.
Opioids and obesity, each account for 40,000 deaths annually in the US[6]. When populations find risk acceptable, politicians are slow to act. Herein the rant ends and I feel better-cheaper than therapy!!

Monday, August 5, 2019

Pooh poohing the obesity microbiome theory



Nutrition has fashions and the most attractive fashions are those that promise the most in terms of beneficial effects. An important determinant of durability of a nutrition fashion is the challenges it poses to experimental challenge. At present, the best example of a long living nutrition fashion is the human gut microbiome which represents all of the bacteria we house in our lower gut. Their main evolutionary basis was the extraction of energy from food carbohydrates that are not amenable to digestion by our digestive enzymes. However, in recent times these bacteria have been associated with many diseases. If you get the wrong bacteria in your gut you increase the risk of many diseases such as (non-exhaustive list: depression, anxiety, autism, cancer of the lung and colorectum, pancreatitis, liver disease and many gut disorders such as irritable bowel syndrome, Crohn’s disease and ulcerative colitis. Of particular importance is infection of the gut with Clostridium difficile which can be fatal in up to 30% of cases. Considerable success has been achieved using faecal transplants of such patients with encapsulated bacteria  from a healthy donor.

Another condition which receives considerable attention in relation to the gut microbiome is obesity The gut microflora of obese persons differ from those with a normal weight and when obese persons lose weight their gut microbe population moves in the direction of normal. But the big question is cause and effect. Does an adverse microbiome population cause obesity or does obesity cause an adverse microbiome population? In an attempt to answer that question, a recent study examined the impact of faecal transplantation of people with severe obesity (but who were metabolically healthy, with no sign of type 2 diabetes, fatty liver or the metabolic syndrome) with a capsule containing filtered faecal extract from a healthy normal weight female[1]. Twenty severely obese subjects (BMI 35+,Kg/M2) were randomly assigned to either the treatment arm (encapsulated faecal transplant) or a placebo arm (similar capsules with glycerol and colouring matter). The treatment arm began with a booster level of transplantation which was then followed by a reduced maintenance dose. They were told to eat normally and were closely monitored throughout the 12 week treatment period. Probiotics were not permitted for the study duration and for 4 weeks prior to treatment. Antibiotic treatment was not permitted for 8 weeks prior to the treatment and then throughout the treatment.

The obese patients did not lose weight. So, if the microbiome theory of obesity is correct, why not? The first question : “did the faecal transplant alter the gut microbiome composition’? And the answer is ‘yes, it did’. Faecal samples were taken at several instances during the intervention and the gut microbiome quickly resembled that of the healthy lean donor and that was sustained throughout the study. The gut-microbiome theory also states that the underlying effect is a change in the type of bile acids secreted with less taurocholic acid type bile in faeces. So did the faecal transplant cause a reduction of faecal taurocholic acid? Again, yes it did. And finally, central to the obesity-gut microbiome theory is that the obese type is that the obesity type microbiota alters the production of a gut hormone which plays a role in weight regulation, the hormone glucagon-like peptide (GLP). Did the change with treatment? No it didn’t.

Now, just as one swallow never made a summer, one experiment never copper fastened a scientific theory. But it opens the debate. It challenges the theory and that is what drives scientific enquiry. Flaws can be found in this study and the authors list a few. Maybe it wasn’t long enough for weight loss to occur. Maybe, but I doubt it since weight loss can rapidly respond to treatment. Maybe the faecal transplant dose wasn’t strong enough. Maybe, but I doubt this also, since the dose in use in the study changed the composition of the microbiota.

So I’m left with the view that more studies like this need to be completed to properly address this question. But let me leave you with my final thought. Obesity is a consequence of overeating and the caloric balance theory of obesity is to the microbiome theory what the Mona Lisa is to graffiti. To paraphrase Bill Clinton: It’s the calories, stupid.  






[1] Allegretti J et al (2019) Effects of Fecal Microbiota Transplantation With Oral Capsules in Obese Patients. Clinical Gastroenterology and Hepatology (In press, available online)

Tuesday, April 23, 2019

The genetics of obesity


The genetics of obesity

Obesity is a very complex condition and involves a multitude of metabolic pathways, each regulated by  several genes. A disorder of one gene can lead to severe obesity but the rate of occurrence of these single gene defects is so low that they cannot explain the current pandemic of obesity.  For example, a rare defect in the gene which encodes for a protein, bearing the awkward title melanocortin-4 receptor (MC4-R) can lead to obesity. But even among morbidly obese persons, this gene defect is only found in 4% of this population. Thus a single gene defect is never going to explain the obesity issue.

However, twin studies have repeatedly shown that obesity is highly heritable to a level of about 70%. So if one gene defect can’t explain this inherited susceptibility to obesity, maybe data on multiple genes might assist us. A recent study by UK and US scientists[1], has begun to throw some light on how we might begin to predict the susceptibility to obesity based on our genes.

The first step in their quest was to explore a published database on 300,000 individuals whose body-weight was known and who had their entire genetic code searched for over 2.1 million common genetic variants. No single variation explained any significant risk of obesity. Thus the next step was to take all of these 2.1 million common genetic variants and see if they could compute a polygenic score which would be predictive of obesity. They used advanced computational methodologies to devise 6 candidate scoring systems. To determine which was best, they turned to the UK Biobank which has full genetic data and body weight data on over 120,000 subjects. Their best performing scoring system could now be put to the test.

They used four different data sets to explore the predictability of their polygenic score  in quite different groups. To understand their scoring system, they could first dismiss all those common gene variants which had simply no link with obesity. Thus our hair and eye colours are genetically determined and different genetic variants explained redheads from blondes to brunettes. So they were scrapped along with lots of others. They were left with genes that had a very, very minor effect on obesity right up to some genetic variants with a more significant link with obesity but still, on their own, would have no real predictive power. The more of the higher linked variants you had, the higher your polygenic score. So every individual in the UK Biobank got a score ranging from low to high. They divided the 300,000 subjects into ten groups (deciles) with increasing polygenic scores and they showed a very strong link between the score and body weight.  Half the people with the lowest score had a normal body mass index whereas among those in the top 10% of the polygenic score, only 17% were of normal weight. Conversely, among those classified as obese, only 9% belonged to the lowest scoring decile while 38% were at the top end of the score. Across the ten deciles of polygenic score there was a linear increase in  bodyweight, BMI and the incidence of severe obesity.

The next data sets they turned to were ones that included subjects who underwent bariatric surgery for the treatment of their morbid obesity. A high polygenic score was associated with a 5.0-fold increased risk of severe obesity treated with bariatric surgery. To understand the evolution of obesity over time, they then turned to the Framingham Offspring and Coronary Artery Risk Development in Young Adults (CARDIA). This gave data on 3,722 individuals who at baseline had no case of severe obesity. Over the next 27 years they were weighed 8 times. Over that period some subjects went on to develop severe obesity. Among those in the lowest 10% of the polygenic score just over 1% went on to develop severe obesity. In contrast, those in the top 10% of the polygenic score, 16% went on the become severely obese. The final database they used was one of UK babies born in the years 1991-1992 who were followed up to their 18th birthday (Avon Longitudinal Study of Parents and Children). The difference in birthweight between the top and bottom 10% of the polygenic score was just 0.06 kg. By 8 years of age the difference was 3.5 kg and by 18 years of age the difference had risen to 12.3 kg.  

This has shown that we are fast becoming capable of defining genetic profiles which predicts the likelihood development of a normal weight or a severe obesity problem. But before you jump up and down and blame your genes, remember the key saying: “Genes load the obesity gun. But only the environment pulls the trigger”. That said, a knowledge of the likely risk of sever obesity might motivate people with a high score to watch their calories more closely than most


[1] Khera et al., 2019, Cell 177, 587–596