Is exposure to angiotensin converting enzyme inhibitors related to Alzheimer’s disease?

(first published on Nature Network May 11th)  

One of the questions I have been investigating is whether a type of anti-hypertensive drug, angiotensin converting enzyme inhibitors, may inadvertently cause some people to develop Alzheimer’s disease.

There is currently no cure for Alzheimer’s disease.  Patients diagnosed with dementia on average survive for 4 years.  Alzheimer’s disease was first described in 1906, but scientists do not know exactly what causes the biological changes characteristic of the disease.  We do know Alzheimer’s disease gets more common as people get older:

Data from MRC CFAS study.¹

This hypothesis around angiotensin converting enzyme inhibitors was motivated by research suggesting that angiotensin converting enzymes may have a role in clearing amyloid-β plaques from the brain.  So angiotensin converting enzyme inhibitors which, as their name suggests, inhibit angiotensin converting enzyme, may increase the build up of amyloid-β, increasing the likelihood of Alzheimer’s disease.²

The ideal way to answer this question would be to do an experiment, which randomly allocates some people to angiotensin converting enzyme inhibitors and others to another anti-antihypertensive, and then see whether there were differences in the number of diagnosed with Alzheimer’s.  However, the effects of angiotensin converting enzyme inhibitors are only thought to build up after long periods of exposure.  So participants would need to be followed in the experiment for a very long time.  Mercifully, Alzheimer’s disease is relatively rare in younger people, so we would either need to run the experiment in older people, or in a very large number of people to detect any difference in diagnosis rates.  This could be hugely expensive.

Some epidemiologists, Anderson and colleagues, did the next best thing.³  They followed-up an experiment that had already been run, the ONTARGET study.  In which the outcomes of people given angiotensin converting enzyme inhibitors were compared to those given another anti-hypertensive drug, angiotensin receptor blockers. 

They investigated whether the participants experienced differences in cognitive impairments, defined as a diagnosis of dementia, or had a low score in a cognitive test, the mini-mental state examination depending on the treatment they were allocated.  They found that people allocated to angiotensin converting enzyme inhibitors were around 10% more likely to develop cognitive impairments over the four years of the experiment,(odds-ratio 1.11 95%CI (0.99,1.25) p-value =0.06).  However, they found little difference in another outcome, cognitive decline (a fall in the mini-mental state exam score).

These findings are certainly not conclusive.  This might be because the participants of the ONTARGET experiment were relatively young, average age of 66, so few participants would be expected to develop Alzheimer’s disease.  Also the ONTARGET trial’s primary outcome was death from cardiovascular causes, myocardial infarction, stroke, or hospitalization for heart failure.  This means it did not necessarily have enough data to detect an effect of the drugs on cognitive impairments or cognitive decline.

Another way to investigate whether angiotensin converting enzyme inhibitors cause Alzheimer’s disease, is to compare the outcomes of patients prescribed ACE-Is and other anti-hypertensive drugs as part of their normal medical care.  Some more epidemiologists, Li and colleagues, did this using data from the United States.⁴

They found that patients prescribed lisinopril (an angiotensin converting enzyme inhibitor) were 23% more likely to develop Alzheimer’s disease than those prescribed angiotensin receptor antagonists, (odds-ratio 1.23 (95%CI:1.04,1.47), p<0.001).  Patients prescribed lisinopril were slightly more likely to develop Alzheimer’s disease than patients given other cardiovascular drugs (such as statins) odds-ratio 1.04 (95%CI: 0.99,1.11, p=0.15).  But this association was relatively small weak and could be due to chance.  Whist Li and colleagues adjusted their findings for their patients’ characteristics; it is possible that these differences are due to underlying differences between patients prescribed lisinopril and angiotensin receptor antagonists in their sample.  For instance patients prescribed angiotensin receptor antagonists might be richer or younger.

I looked into this using data from the General Practice Research Database.⁵  This is contains administrative data on diagnoses and prescriptions from over 600 general practices in the UK.  We found evidence that fewer patient prescribed angiotensin converting enzymes were diagnosed with Alzheimer’s than those prescribed other anti-hypertensives.  However, when we looked at historical exposure to angiotensin converting enzymes we found little evidence of an association. Again this is frustratingly inconclusive.

The only way to conclusively prove whether long term exposure to angiotensin converting enzyme inhibitors is related to Alzheimer’s disease is with a randomised controlled trial of sufficient size in older people with higher risks for the disease.

Oh also Louis Theroux’s most recent show on dementia is really interesting, catch it on iplayer.

And here’s podcast from Professor June Andrews on care services for people with dementia.

I'd hear your thoughts on this and our other posts, and do pass on any papers or links.

 

1. Neuropathology Group of the Medical Research Council Cognitive Function and Ageing Study(MRC CFAS). Pathological correlates of late-onset dementia in a multicentre, community-based population in England and Wales. Neuropathology Group of the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS). Lancet. 2001;357(9251):169–175.

2. Kehoe P, Miners S, Love S. Angiotensins in Alzheimer’s disease-friend or foe? Trends Neurosci. 2009;32(12):619–628.

3. Anderson C, Teo K, Gao P, et al. Renin-angiotensin system blockade and cognitive function in patients at high risk of cardiovascular disease: analysis of data from the ONTARGET and TRANSCEND studies. The Lancet Neurology. 2011;10(1):43–53.

4. Li N, Lee A, Whitmer R, et al. Use of angiotensin receptor blockers and risk of dementia in a predominantly male population: prospective cohort analysis. BMJ. 2010;340(jan12 1):b5465.

5. Davies NM, Kehoe PG, Ben-Shlomo Y, Martin RM. Associations of anti-hypertensive treatments with Alzheimer’s disease, vascular dementia, and other dementias. J. Alzheimers Dis. 2011;26(4):699–708.

Images from: http://www.nlm.nih.gov/medlineplus/magazine/issues/fall10/articles/fall10pg20-21.html

Mendelian Randomisation and the Prevention of Spurious Findings

(first published on Nature Network April 19th)

Epidemiology uses statistical methods to investigate patterns in public health. Or, if you believe certain news articles, it splits every possible life influence into things that either cause or cure cancer (or occasionally do both). Epidemiologists investigate health outcomes in a number of different ways, ranging from looking at changes in whole populations to conducting randomised controlled trials (RCTs), testing one intervention against another, or against the placebo effect. RCTs are the 'Gold Standard' of Epidemiological research, as their design means they can provide the strongest evidence for or against a hypothesis. Other epidemiological methods involve observation, rather than manipulation, and this can be problematic.

One week there may be a paper suggesting vitamin pills protect against heart disease, and the next week evidence emerges that they don't. This is often because of misleading findings from observational studies. People who decide to take vitamin supplements are likely to be different in a number of ways from people who don't take them. They might lead a more healthy lifestyle, exercise more, smoke less, and eat more vegetables. These differences are likely to impact on their chance of getting heart disease. Epidemiologists call these differences confounding variables, and although it's possible to take them into account in various statistical ways, the scientist has to know what they are in order to control for them. Miss one confounder out of your analysis, and it may inflate any relationship between the two factors you're interested in, so you've got a spurious finding. One way of getting round this problem is to conduct RCTs, so different types of people are randomly distributed across your intervention condition. Although this may be fine to do with a vitamin pill, it's sometimes not ethical or even possible. If withholding the intervention being investigated is thought to lead to harm, it is unethical to do so, and if the intervention is something like drinking alcohol, it's impractical to get people to either drink or not drink for an experiment.

Investigating alcohol in observational studies has the same problems mentioned above; people who drink are different to people who don't. Socioeconomic status, likelihood to smoke and education level may all affect the relationship you're interested in. There are added complications in that people may have stopped drinking because they are unwell, so instead of drinking affecting the disease, the disease is changing alcohol use. This is called reverse causation, and may explain why we hear that a glass of wine is good for you (sorry to be the bringer of bad news).

But advances in the understanding of genetics can help. Everyone has 23 pairs of chromosomes, and coded in these are genes; the building blocks for who we are. My genes are practically identical to yours, but there are some key genes which have different DNA code in different people. Some of these differences can lead to diseases, such as Cystic Fibrosis, caused by a faulty gene not properly making an important protein. Some have less extreme, but still very interesting, effects. There has been a gene variation found, common in East Asian populations, which means a protein needed to break down a metabolite of alcohol is not produced. People with this variation get unpleasant symptoms when they drink due to a build up of acetaldehyde in their blood, so very often they avoid alcohol. By looking at someone's DNA in the location known here, we can investigate the effect of alcohol use on whatever we're interested in, using the gene as a proxy variable instead of directly analysing alcohol intake, as people with the unusual variation will be less likely to drink. All well and good, but surely this is still just observing, so how do we stop the interference of confounding?

It turns out that our genes have some very useful properties which make them perfect for this task. The genes that you have are all unrelated to environment, as you got them before you were born, so environmental confounders should be randomly distributed between your gene categories. Also, when your parents' chromosomes divided to create the egg or sperm that contained the genes you inherited from them, each gene splits independently of all the others, so you have a random chance of also inheriting a genetic confounder. Because of these neat properties, you can assume that your proxy gene will be independent of any confounding variable affecting the exposure you're interested in, and therefore where confounder levels would have been uneven across people grouped by alcohol consumption, they will be randomly distributed across gene variation. Results using this technique have shown evidence against alcohol being a gateway drug leading to illicit drug use, as the gene variation was not associated with illicit drug use.

Of course, nothing's perfect. There are a few conditions where this technique will fall down, but as long as you're aware of them, you should be able to avoid the problems. Firstly, occasionally 'linkage disequilibrium' occurs. Certain genes are more likely to move together during meiosis, meaning they are not inherited independently. If your proxy gene travels with a gene which affects your outcome of interest, this will impact on your findings. There is a method to check for linkage disequilibrium, so you can ensure it's not a problem. Also, there are certain genes which have an impact on a number of different traits (this is called pleiotropy), so if your gene has a direct effect on the outcome you are interested in, it is unsuitable for Mendelian Randomisation. Finally, the technique fails to work effectively if there are systematic differences in the genetics of the population you are investigating. For example, if a population is made up of two groups of peoples that used to live separately, but now live together, there will be non random genetic differences between the groups due to selective mating over the time when they were separate. This may mean other differences between the groups will not be randomly distributed across the gene you're interested in, making the population unsuitable.

However, although this technique can only be used in very specific circumstances, where a gene is known to affect the intervention you're interested in, and doesn't suffer from the limitations mentioned above, it is a really elegant technique which will hopefully stop the spurious results from observational studies becoming newspaper fodder.


Check this article out for an overview of MR.

Ding Ding All Change

If you're wondering why it's been quiet here recently, change is afoot!

A couple of weeks ago this blog moved to Nature Network. Very exciting times for us! We'll still be updating this page with the posts that appear on our blog there (which is still called Sifting the Evidence, and can be found here), but they will appear a couple of days after. Feel free to look at them and enjoy them on either site!

Geek Like Me?

Should scientists steer clear of identifying themselves as geeks in case it puts off ‘more rounded’ individuals from taking up a STEM (science technology engineering and mathematics) career?

Who are the Children of the 90s?

If you were down on Bristol Harbourside this weekend you may have noticed an event at MShed, or heard mention of ‘Children of the 90s’. Who are these children, and what were they doing at the museum? The answer involves a journey more than 20 years back in time, and the vision and foresight of Bristol Professor Jean Golding.

It’s demography stupid!

The protestors on the streets of London, New York, Madrid and Tel Aviv do not understand the economic and political problems they face.  The developed world is suffering from a demographic crisis.  Railing against financiers and the richest 1% misses the underlying cause of the crisis: the costs of paying for their own parents' and grandparents' retirements.

First Class Mutations

Beasts on a plane!

It almost feels like a fool’s errand to isolate something that can help us make light of ourselves from the litany of improbable happenings taking place in X-Men: First Class. Any film with a sapphire coloured beast piloting a stealth fighter jet will struggle to poignantly frame questions about the evolution of humanity. But if you squint a little, the band of ‘mutant’ heroes, whose variety of supernatural traits are powered by a single mutation in the fictitious ‘X gene’, actually epitomise a core mechanism central to the field of population genetics.

Alcohol: ‘more harmful than heroin’, or all in the mind?

If you’ve been following reports in the media recently, you may be a little confused about alcohol and its’ effects. A year ago, the Independent Scientific Committee on Drugs published a report on drug harms in the Lancet. They calculated harm scores, to an individual and to society as a whole, and found that alcohol was more damaging than heroin or crack cocaine. And only this week the Royal College of Physicians released a report about alcohol. It provides evidence that our livers need three days alcohol free per week, if we have more than one or two drinks per day. If you drink heavily one evening, you should have a couple of days off before you drink again. From this evidence, it seems that alcohol is bad news.

Dynamite Money

Housing Genius: the Nobel Museum, Stockholm

#1: The Growling Bear

Since this week happens to be the time of year when small bands of elite academics (and sometimes spurious accessories, like Barack Obama) are ushered into the scholarly Hall of Fame, this seems the perfect time to start a new column here on Sifting The Evidence: I'll aim to profile the life and graft of one Nobel Prize winner every month. 


This will span three of the five categories, so anyone from physics, chemistry or physiology/medicine is eligible, but I won’t feature winners of the literature or peace prizes (for, in the eyes of this blog, these are domains of beatniks). And economics also squeaks in, despite its unofficial status. The prizes have been awarded for a diverse array of amazing theories, discoveries and innovations, from radioactivity to IVF, and are given to personalities of every shade, from the outspoken to (perhaps predictably) the somewhat autistic. But first, we’ll start with the Growling Bear himself: Alfred Nobel. 

One of the concerns frequently expressed about climate change policies, is that if we reduce and restrict carbon emissions in the UK, then energy intensive manufacturing will simply shut down and move to other countries.

Some fascinating research, via Ryan Avent, suggests that this may not be the case.

Ralf Martin, Laure de Preux, and Ulrich Wagner published a really interesting paper investigating the effects of the UK’s climate change levy (CCL) and climate change agreements (CCA) on manufacturing firms production of goods, energy use and carbon emissions.

They used data on individual firms from the Office of National Statistics, and found:

Global warming, carbon emissions and hyperactive government policy: when less is more.

How much progress has the UK made in reducing its greenhouse gas emissions?

A little?  Just about kept emissions from increasing?

Why we should be wary of the tobacco companies

There have been reports today that five tobacco companies are trying to sue the USA Food and Drug Administration (FDA) over new laws that will come in to place in September, forcing them to display graphic health warnings on their products. These are similar to warnings used here in UK, and in many other countries around the world.

Putting aside for a moment their farcical suggestion that this removes their constitutional right to free speech, it has brought a more alarming fact to my attention; namely that this is the first legal change to cigarette packaging in 25 years. How has the USA government allowed them to get away with so much for so long? Of course a large part of the answer is the financial control that these companies have; their lobbying has funded campaigns to keep shop displays of smoking products, and allegedly funded grass-roots organisations denouncing governmental smoking laws as ‘nannying’.

Lies, damn lies and public sector deficits

Across the western world,  governments are struggling with high public debt.  After much melodrama the US congress increased the amount of money the US government can borrow.  In the UK net public sector debt has increased from 37.5% of GDP in 2007 to 61% of GDP in 2011.  The coalition has set itself the target of eliminating the public sector deficit over the next four years.  They claim that there is no alternative to cutting government spending, and unless government spending is reduced, the UK may be unable to afford to pay its debts and may risk default on its debts.

These claims are false. It remarkably simple to check whether a country,  a company or individual is likely to default.  When borrowers’ likelihood of default increases the interest rate they are forced to pay on their debt goes up.  For example, Greece is currently teetering on the edge of bankruptcy, and currently it must pay 14% on its government debt.  So what has happened to the interest rate on British government debt? 

What Didn't Kill Mozart

Not one for bronzing up

Wolfgang Amadeus Mozart may have been stricken with many ailments, but if you were to believe recent reports, it was vitamin D deficiency that principally led to him to an early grave.

It’s not to be denied that Mozart could have been as ivory in complexion as the keys that he struck to earn his keep: the man lived at a northerly latitude—where the winter sun isn’t strong enough to induce the synthesis of vitamin D in the skin—and if his personality were to be put in musical terms, he was allegedly something of a nocturne.  Unlike other vitamins, there’s no vitamin D in most food sources, and the majority is obtained from exposure to sunlight. At the time of Mozart’s death (1791), there was little knowledge of vitamin D, let alone ways of measuring his status, so for all we know he could well have had insufficient or deficient levels of the vitamin. But there are two big ambiguities that should temper unsubstantiated chatter about Mozart having succumbed to his dappled lifestyle.

Generation F?

Those born in 1983 will pay on average £187,000 to the government over their lives, net of the benefits and services they receive.  Conversely, those born in 1933 will receive an average £150,000 in payments and services over their lifetime, net of benefits and services.  This was highlighted in the fiscal sustainability report recently published by the Office of Budget Responsibility (OBR).

The figure below charts how much people will give or receive from government, adjusted for inflation, over their lifetimes.  People born before 1953 are net beneficiaries.  In contrast, people born after 1953 will pay more in taxes than they receive in services and benefits.

Raise A Glass To The Birth Cohort

In yesterday’s post, Suzi pointed out how Children of the 90s has helped her research, and last Friday, BBC Breakfast had a feature on a study that is already a couple of years old, yet remains very much in its infancy. As with Children of the 90s, ‘Born in Bradford’ is a longitudinal cohort: a study which recruits a group of participants, sometimes well before their birth certificates are signed, and follows them during the course of their lives (often alongside their parents and/or other relatives). Herculean efforts are put in to record buckets of information about them along the way. Such a study is an immensely rich and important resource.

Studies begin with certain goals in mind and develop over time to address new research questions and shifting paradigms in medicine. For example, early work from Children Of The 90s helped to resolve contention about which way we should lie our babies at night to lower the risk of cot death (that’s face up, new parents!). Nowadays, the participants are collectively entering their third decade walking this earth, and continue to help us answer questions about the incalculable complexities of maintaining good health in the 21^st century.

Many types of information and measures are recorded by cohorts (all with the consent of participants, of course). These can range from simple questionnaires about things like family income and leisure activity preferences to in-depth measures taken at medical examinations, including blood samples used to measure various biochemical properties. Since the advent of the human genome project in 2003, we are increasingly being able to survey the genetic information of participants to explore what effects our DNA can have on our propensity for developing certain traits or diseases.

Pot Luck – does smoking cannabis really increase your chances of becoming psychotic?

Paranoia. You’re being watched. The people on the street are not who they seem; they’re following you. You’re sure you’ve seen that man before, he must be a spy. It might sound like James Bond’s inner monologue, but these are some of the sensations you can feel while intoxicated after smoking cannabis. They’re also some of the symptoms of psychosis, a disorder of the mind which has been linked to cannabis use. Feeling paranoid when you’re high is not the same as developing a condition like psychosis. The effects of intoxication are gone after a few hours; psychosis as a disorder can involve episodes like this lasting for days, or longer. Currently the government believes that cannabis use as a teenager increases a person’s risk of developing psychosis, but the scientific evidence is not so clear cut.

Although cannabis is illegal, it is a widely used drug. A 2004 report from the European Monitoring Centre for Drugs and Drug Addiction found that two in five 15 year olds in the UK had tried cannabis, and one in ten had done so more than 50 times the previous year. Because of this, you might expect there to be lot of youngsters with psychosis, but it’s a very rare disorder. David Nutt, the ex-government drug advisor, has pointed out that although the use of cannabis has increased dramatically over the last few decades, the number of people with psychosis over the same time period has not increased at the same rate. If there was a direct link between cannabis use and likelihood to develop psychosis, you would expect to see both either increase or decrease together. If there is a link between cannabis use and psychosis it is likely to be complicated, and it is still not clear in which direction an effect occurs. It may be that the link is seen because people with psychosis find that smoking cannabis alleviates some psychotic symptoms, such as social anxiety, so they self medicate.

Why is the UK growing so slowly?

In the second quarter of 2011 the UK grew at an annualised rate of 0.2%.  This compares to an average growth rate of GDP from 1992 to 2006 of 1.9% per year.

A closer look at the GDP figures (Table B1) suggests that all service sectors of the economy now have higher output that 2006.  The fact that total output is still below 2006 is due to falls in oil and gas production, farming, energy production and manufacturing which are down 31.3%, 12.6%, 6.8% and 11.4% respectively since 2006.

It is notable that each of these sectors is highly energy intensive.  This is consistent with an energy supply shock.  The government has frequently argued that these are the sectors of the economy that will provide future economy growth.  However, the latest set of GDP figures appear to be consistent with an economy rebalancing away from heavy industry and primary resource production towards services.  It is not immediately obvious that the production sectors are areas in which the UK is likely to have a comparative advantage in the future.

Indeed, as economist Larry Summers recently observed for the US:

The reality is that manufacturing employment has been trending downwards for 50 years.
… the fraction of all the workers in the United States who are engaged in manufacturing production right now, is less than a fraction of the workers who were engaged in farming in the late 1950's, and it's a very similar phenomenon.

Summers goes on to suggest that the future growth of developed economies is unlikely to come from manufacturing and production: it will come from knowledge and innovation.  Role models should now be the ubiquitous ARM chip designers or Dyson, rather than production magnates like Corus.

This raises a number of further questions: firstly, to what extent can fiscal policy, government spending or tax cuts offset falls in output due to energy intensive production industries?  And what effects will further rounds of monetary easing have on output and inflation if a significant proportion of output falls as the UK has experienced, and the slow current growth is due to specific industries such as oil and gas?

Clearly policy makers’ best response to these issues depends on the answers to these questions.  Unfortunately, these questions will only be resolved with time, and reams more data and research.  Until then, we’re more dependent on luck than judgement.

Press Releases

The NHU "are the best in the world"
but there's room for improvement

Last week, the BBC released the review addressing the impartiality and quality of its science coverage. Overall, the corporation fared very well. To satisfy one peculiar British duality, we subject the BBC (along with the NHS) to equal measures of scorn and adulation, and most reviews commissioned by the Trust offer juicy reading. 

The review, conducted by UCL’s emeritus professor of genetics Steve Jones, offers up lapping praise for the corporation’s output but with the flattery, he highlights several weaknesses. It is a sprawling piece, so this post addresses one area which (to our knowledge) hasn’t been reported widely elsewhere in the mainstream press: namely, the failure of journalists to utilise sources of science beyond press reports. 

Admittedly, the press release can be a useful tool to rely upon for finding scoops. But Jones doesn’t place as much emphasis as he should on the dangers of such a dependency. An analysis which the report cites suggests 75% of news stories cover only material listed in press releases. It is painfully apparent to the industry insiders when journalists haven’t searched any further into the story than the veneer represented by the press release, even if lay readers are unaware.