Psychedelic drugs and river water bugs

And understanding our ageing body clocks...
14 April 2021
Presented by Chris Smith
Production by Eva Higginbotham, Chris Smith.

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Sampling river water

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This month: the first self-blinded study into microdosing psychedelics, using DNA analysis to understand what bacteria is in river water, what's the evidence for parasites preventing inflammatory diseases, comparing different methods for evaluating your cellular age, and an analysis of non-inclusive language used in life sciences journals...

In this episode

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00:36 - Psychedelic microdoses and mood disorders

The largest placebo controlled study into the effects of microdosing on psychological wellbeing and cognition

Psychedelic microdoses and mood disorders
Balázs Szigeti, Imperial College London

Can psychedelic drugs, like LSD, combat depression and anxiety? Some clinical trials testing high doses of the drugs have shown positive results. But there’s another phenomenon taking root amongst psychedelic advocates: microdosing, where very small amounts of the agent are used about 2 to 3 times per week. Users report improvements in mental health, wellbeing, and even cognitive ability. This is anecdotal though, and might be just a placebo effect; so Imperial College’s Balázs Szigeti put the claims to the test by using a self-blinding strategy, where users created their own placebo doses and didn’t know what they were taking when. Eva Higginbotham heard what they found...

Balázs - First, we asked participants to put their microdoses inside non-transparent gel capsules, and a microdose is just a small piece of blotter paper, so you can easily fit them inside the capsule. And as the next step, we also asked participants to prepare empty capsules, and those are going to function as placebos throughout this study. Now, after these two sets of capsules were prepared, they were put into envelopes and zipped bags together with QR codes and then those envelopes were shuffled and random numbers generated so on and so on and so on. But the net result of the self-blinding process was that participants ended up with capsules enough for four weeks without knowing which of those capsules contains a microdose inside, and which one of the capsules are a placebo. The second component is that when participants scan the aforementioned QR codes, that gave us a way to track who is doing what at what time. So they did not know at the end what they were taking, hence we called the method self-blinding because you are blinded to your own drug condition.

Eva - I see, so were they noting down how they felt after taking them?

Balázs - That's essentially the idea, but we have used all online surveys to measure the effects of placebos and microdosing. And on top of these self-reported survey questionnaires, we've also asked participants to log into a cognitive testing platform where they have played various games designed to measure cognitive performance - think of the little memory card games that everybody was playing as a kid - we measure things like that to quantify memory performance and measured reaction time on various mental orientation tasks. So those were the two outcome categories that we have measured. Broadly speaking, we measured how people are doing and also how well they are performing cognitively.

Eva - And what did you find?

Balázs - So first let's just focus on the psychological outcomes, and what's really interesting here is that if you just look at the microdose group alone, then we very clearly saw an improvement from baseline to after the four weeks dose period in well-being and in all of the psychological outcomes that we have measured. So in a way that really validates all of the positive anecdotes about microdosing, because we saw improvements, statistically significant improvements, in a broad range of mental health measures. However, the story gets a bit more blurry if we add in the placebo control group into the picture, because the placebo control group also improved. And once we looked at the difference between the placebo and the microdose group, that difference was not significant anymore. So I think what that means is that all of those benefits that microdosers are talking about, I think those benefits are real, but also taking placebo is sufficient to reproduce those benefits suggesting that likely the mechanism behind those benefits is not due to the pharmacological activity of the psychedelic microdose, but rather the placebo effect is sufficient to explain it.

Eva - What about in terms of the other things that you measured?

Balázs - Yeah, so the other outcome was cognitive performance and when it comes to the cognitive measures, neither the microdose nor the placebo group has changed significantly relative to their baseline. And there wasn't any difference in the changes observed between the microdose and the placebo group. And I think, by and large, that fits into the placebo narrative that we have found, and the reason for that is because these cognitive tests are much more objective than the self-reported psychological tests. How you feel and you think about your own wellbeing counts a lot for the self-reported psychological questionnaires, but when it comes to the cognitive measures, it is much more objective. We measure things like how many digits you can recall in reverse order and how you think about yourself is going to carry much less weight in those measures. In a way the self-reported psychological measures are much more susceptible to the placebo effect just by their nature, and in contrast, these cognitive performance measures are much more objective.

Eva - What's the take home message then? Do you think microdosing psychedelic drugs doesn't actually work in the way that the anecdotes online suggest?

Balázs - It's a complicated question because in many ways we have validated that anecdotal evidence about microdosing. Bear in mind that we very clearly observed improvements in a broad range of psychological measures in the microdose group. It is just that people who were taking placebos also improved equally. So in many ways, you know, microdosing does work. We just think that the mechanism behind it, it's not what people think, it's not related to the pharmacological effect of the drug. Another important aspect here is that like all other studies, this one comes with limitations as well. First and foremost, in this study, being not a clinical study but a citizen science study, people have used their own drug which likely they have sourced from the black market. And because of that, there is some uncertainty regarding the variability and the exact chemical composition of the microdoses that were used personally. I'm not too worried about this limitation, and the reason for that is because people who are microdosing out there in the real world, they're also sourcing their psychedelics from the black market. So the variability and the uncertainty present in our study is also present in all of the anecdotes that have led to the current popularity of microdosing. So when we want to summarise the scientific evidence about microdosing, it needs to be said that prior to our study, there have been three much smaller clinical studies by and large, they are also negative. However, even with our study, there are only four placebo control studies of psychedelics altogether, which is not a large body of evidence. So it's still very much could be the case that when we talk again in a few years time, and there are many more clinical studies available on microdosing, then we will have to conclude that microdosing is efficient.

Sampling river water

06:59 - Molecular biology to track water quality

Analysing the bacterial populations in Cambridge rivers

Molecular biology to track water quality
Maximilian Stammnitz, University of Cambridge

The power of molecular biology means that techniques like PCR coupled with sequence analysis can be used to monitor the environment and audit the presence, and even abundance, of different organisms. This is particularly helpful when it comes to the aquatic realm. And Cambridge University’s Max Stammnitz has been showing quite how useful along the River Cam, the training ground for a certain famous rowing team, as he told Chris Smith...

Max - Many of our friends in Cambridge who regularly row and swim have reported to us that there are infections, severe infections, occasionally occurring involving people's eyes and open wounds, leading to hospitalisations in certain cases. So that is one aspect of the biological problem that we were facing. And then on the other hand, our team of students that then later formed, it was all composed by geneticists interested in applying DNA analysis methods to problems all around us outside the lab. And then these two things basically came together in the so-called PuntSeq project

Chris - And you thought, right, hey presto, we can put together the challenge of trying to find out why there are infections in waterways in our rowing friends, and apply some new technology and genetics knowledge to try and solve it?

Max - Exactly. You basically track biological activity or microbial life in the water sources through their DNA footprints, as we like to say. So you can essentially take a sample, in our case fresh water from the river Cam, extract the bacterial DNA from that and then analyse it with a very modern DNA sequencing platform that gives us a lot of data on bacterial species and abundancies.

Chris - So you can actually get some idea as to the burden of a particular bacteria type in the water? Because that's one criticism of doing this sort of thing. It's so sensitive that you end up with a signal for a particular bacteria, but it's so rare in real terms that it's not going to pose any kind of threat, really, so you've got around that?

Max - Yes and no. To a certain extent you can say, across the range of samples that you take along the waterway, is a bacterial species increasing or decreasing in numbers. Do we have a suspect sewage pipe that might lead into the water source? Then we might suspect that certain bacteria that might cause infections through wastewater sources, that they are likely to be found downstream of that. But it's true that, without additional laboratory work, you cannot necessarily say whether a bacterium that you spot with this DNA platform, whether it is actually harmful. So we see this method more as an early stage typification of your local water source rather than find an answer to 'hey, this is making people sick or not'.

Chris - Indeed, because what you can't say is that, from that DNA signal, this came from a viable organism.

Max - That's true. Yeah. We might in fact have looked at lots of dead bacteria. But there's a reason why these dead bacteria are floating in the water, right? They must come from somewhere. So we think that even if, you know, we trace mostly dead organisms, it is interesting to see where these might've come from and what their roles might be, even if it's further upstream of the source where you're sampling.

Chris - Did you get an answer for your rower friends?

Max - Yes, we think so. Downstream of the city of Cambridge, there is a large waste water treatment plant. So the waste waters, after treatment, are basically fed back into the river. And we do see certain spikes of bacteria after that that we can associate with pathogenic bacteria. We didn't follow up on it through much lab work, to be very honest, we entered a little collaboration with Public Health England and sent some of our suspect candidates' DNA to them to verify whether these could actually be pathogens or not. And most of their results were similar along our lines that you cannot, a hundred percent, be sure that there's enough infectious material. But you can definitely say that in certain spots we find bacteria such as pseudomonas aeruginosa. So we can say these bacteria are present, be they alive or dead. We cannot necessarily say, okay, on this particular day, if you were to fall in and your immune system might've not been the strongest, you would have been a likely candidate to fall ill from that. But you can certainly see that, from this point onwards, it's much easier to reduce the candidate list of pathogens in a given water source. I mean, overall, we were able to measure more than 600 different bacterial genres. So you reduce it down from a huge list of potential candidates. And besides the whole biomedical question, you also get an insight into, you know, just the biodiversity, just through DNA analysis.

Chris - The mere fact that you've proved that this can work though, presumably what you could do is to choose some very reliable indicator species that have a good specificity for contamination of the water with other threats, and then use those almost like a bacterial canary down the coal mine, where if you detect those, which are rare under normal circumstances, but a strong predictor of contamination of the water with, for instance, sewage, you could then use this very successful and sensitive technique to say, well, look, this water looks contaminated, it would be a bad time to go rowing today.

Max - That's correct. Yes. To be very honest, there are ways to do that still that are much cheaper and that really just pinpoint the indicator species for other purposes. We could actually already see it working, for example, since we took samples both in the earlier spring months and later in summer, we could see that throughout this time, the number of cyanobacteria increased in certain spots. And we think maybe these could be used as indicators towards, you know, algae, flowering periods. So not necessarily just about pathogens, but also about other biological processes that happen in these sources.

A green and yellow dish sponge

13:37 - Parasites and the ageing process

Is it true that our sterile lives are causing inflammatory diseases?

Parasites and the ageing process
Bruce Zhang, University College London

“We’re ageing faster and afflicted by allergies and inflammatory diseases because we’re living lives that are too sterile and divorced from the parasite-laden existence we evolved to encounter.” Or so says the “old friends” hypothesis, that posits that putting back some of these microbes and other organisms might be a way to achieve a turnaround in what are burgeoning rates of diseases like asthma. Bruce Zhang is an undergraduate at University College London and - prompted by Covid-19 - has been devoting what would otherwise be time for benchwork to hitting the immunology literature, as he told Chris Smith...

Bruce - Something that sort of came out of the pandemic actually, because a lot of the lab work was shut down due to restrictions of people being physically in the lab. So we thought about how we could perhaps do some research on our computers at home, and one of the ways is conceptual research where we just kind of read into the existing literature of published works and then see whether we can test new hypotheses using what is already published. And one of the ideas in the lab where I'm working is whether helminth parasites, which are these kind of worms that live inside our bodies, could actually protect against certain diseases of ageing.

Chris - Because, for a long time, people have suggested, and it's called the hygiene hypothesis isn't it, that perhaps our obsession with sterility in the modern era is the root of many of the diseases of affluence that we see around us today, and foremost among them inflammatory conditions - asthma, allergies, and so on

Bruce - Exactly. Throughout human history and evolutionary history we've grown and evolved with all these parasites and bacteria inside our bodies. And now suddenly we're removing them from our bodies due to being more clean and hygienic. So that suggests that perhaps there is an imbalance in our microbial "old friends", you could call them

Chris - Is there actually any evidence to backup these hypotheses though? Is it just a good story that tends to get better in the telling, or are people actually subjecting this to decent scientific scrutiny and there is fruit being born out of these endeavours?

Bruce - Yeah, there's actually quite a bit of evidence suggesting that a loss of these parasites and other microbial species is actually causing increased rates of diseases, such as inflammatory diseases, autoimmune diseases. Common examples are multiple sclerosis, rheumatoid arthritis, even allergies like eczema, asthma, all of these. There's quite a bit of evidence showing not only epidemiologically but also in clinical studies and experimental work using model organisms, such as mice, when they give these mice these parasites, they actually become protected against many of the symptoms of these inflammatory diseases.

Chris - Is this association though, or causation, because is it that something else is actually changing the risk profile for these diseases? And it's something that the worms go along with rather than causing? Or is there a sort of biologically plausible reason why things like worms could be influencing the disease course of things like rheumatoid arthritis?

Bruce - Obviously it's quite a complex issue when you're looking at what the actual protective mechanism is on the biological level. But there is lots of evidence that there is an immune role when these infections are happening. And it seems to be suggesting that yes, it is a causal rather than just correlative relationship and much of this is grounded in evolutionary theory because humans live together with these parasites. And obviously the host organism wants to expel these parasites and these bacteria or other pathogens from the body. And so what the apparent pathogens and parasites do is to try to suppress the host immune response, so they shut down the immune response a little bit so that they aren't killed by the host. And so that could be one way. It's very plausible that they would be modulating the immune system of the host and perhaps causing the changes in the immune response that we observe.

Chris - What sorts of evidence have we got that that's going on?

Bruce - There're actually many examples of mouse models where people would just test different types of parasites. For example, there's a pig whipworm that normally affects pigs called Trichuris suis, and one way is to take their eggs and give them and also the proteins found on the surface of the eggs to these mice, and it does show a beneficial effect against inflammatory diseases. Many other similar conditions have been tested and there's quite extensive literature on this now.

Chris - Is it actually molecules coming out of the parasites that directly impacts the immune system? Or is it that the parasites do something to the microbiome at large, the assemblage of microbes we have in us and on us, and it's the microbes changing that affects the disease course? Or is it both?

Bruce - From what has been published it's probably both. There's definitely evidence that there are molecules that are directly secreted from these parasites that could directly modulate the immune system of our bodies, but also they could be doing that indirectly by first modulating the microbiome, perhaps in the gut. It's been shown that the gut actually is quite sensitive to the composition of bacteria in there. So if you change the composition of bacteria, you change the health of the gut lining, and that can actually lead to large-scale systemic changes in the body. So if these parasites could change this composition of the gut bacteria, then that could affect health.

Chris - How would you see this learning being deployed? Because many people will be uneasy about the prospect of being infected, or at least colonised with a whole assemblage of worms and possibly other parasites to control the ageing process or control their disease. They probably feel a lot more comfortable if you said, well, we can juice these worms and get whatever they make to control the immune system out and give that as a pill instead. Where do you see this going?

Bruce - At the moment there's actually a lot of research groups looking into the specific molecules and proteins that are found on these parasites because people are definitely a little bit disgusted by the prospect of putting live ones into their bodies. So there is a lot of research going in that direction to just isolate the responsible proteins only so that we don't have to have actual worms in our systems. Of course it could be argued that live worms are more effective. They obviously have the whole panoply of molecules that are required for this protective effect. But I suppose as research goes on and as we identify more and more of what the actual molecules are, then we can move towards a more friendly option.

Hourglass

20:29 - Biological clocks to measure ageing

Using machine learning to examine biological ageing

Biological clocks to measure ageing
Laura Han, Amsterdam University Medical Centre

Ageing is an inevitability; but what’s the best way to measure it? We know that the number of years someone’s been alive is one way, but that’s only a measure of chronological age. We also have a “biological age” - how our lifestyles, sex and genes - influence the equation, and there are a number of different biological clocks ticking in the body to refer to: things like how our DNA changes across the life course, or how proteins alter their configurations. Do all these clocks tick in sync though, and do some do a better time-keeping job than others? To try to find out, Laura Han, at the Amsterdam University Medical Centre, has been using machine learning systems to marry up what the different biological clocks say about information collected from a large dataset called the Netherlands study of depression and anxiety, as she told Chris Smith...

Laura - What is unique about this cohort is that we've collected a lot of biological information, and this is also the information that we have used to develop and examine the so-called biological clocks. The biological clock is actually a predictive machine learning algorithm that has learned biological patterns in our bodies that are correlated to age, DNA methylation levels, or proteins or metabolites.

Chris - And what were you comparing with what? So if you've got those sorts of markers or those sorts of measurements, what are you comparing them to?

Laura - This algorithm - you train it and it is able to predict your age based on these biological patterns. And when it actually predicts you to be older than your actual age, then it kind of suggests that you have an older appearing biological state, or at least the state that is normally seen in older people.

Chris - And can you then marry that up to potential causative factors?

Laura - Yeah, exactly. So if you think about biological ageing in that way, you might be able to say that the ticking rate of your biological clock might be faster than time itself.

Chris - Are there some people who, for want of a better phrase, have a very well lived in body so they look a lot older than they really are, but it doesn't actually translate into dying next week? They look terrible, but actually they're still going to go on forever. So does does just sort of one marker of ageing translate to everything or could that be misleading?

Laura - It could be misleading and this was also one of the main questions that we wanted to ask with our data set. We had multiple markers of biological ageing, and we wanted to see if those were kind of in sync with each other. So are the same factors associated with the ticking rate of all biological clocks.

Chris - You've alluded to what some of these clocks are. So what were the main things that you were assessing and appraising in the study then, what were the clocks that you looked at?

Laura - So we looked at five different cellular biological clocks, one of them being telomere length. And this is basically a cap on the end of your chromosome that shortens as we age. And this is a very well studied marker of biological ageing. And then we have four different, what we call, omics levels of ageing - DNA methylation in our blood, or the protein levels,, or gene expression levels or metabolites. And these can be used more in a modern type of way to quantify biological ageing, because we can use these predictive algorithms to learn what kind of patterns are really correlated to age.

Chris - And when you marry them up with the sorts of factors, the lifestyle factors and others, that associate with the people from which these measurements are coming, how good are these clocks and what sorts of things do tend to speed them up or slow them down?

Laura - Being male, and having a high body mass index, so obesity. Smoking and having a metabolic syndrome were most consistently linked with older appearing biology across multiple clocks.

Chris - How about one of the things you have alluded to which is how you feel, because, you know, there is this saying you're only as old as you feel. Is there any truth in that when you actually look at people who are depressed and miserable compared to people who take a much more rose-tinted outlook on life, do you see that reflected in these biological clocks?

Laura - Yeah. So this is actually a very good question, and what we see in depressed patients is that they carry a higher risk to develop age-related diseases. And in our study we actually confirmed that depression was linked to older appearing biology as well, measured by at least three of the five biological clocks. And I think that this really confirms that biological ageing is linked to both mental and physical health, and also might offer an explanation as to why we see higher risks of age-related diseases in depression.

Chris - What would you therefore say that the take home message here is then? You've appraised these different independent biological clocks, you've married them up to some of the risk factors that make them tick faster or slower, but what's the take home message? What do you conclude?

Laura - I think the take home message is that many other studies have looked at individual quantifications of ageing, so individual biological clocks, and only a few have integrated multiple biological clocks in the same study population. And we found that of the five biological ageing indicators, only three were found to significantly interact with each other meaning that an increase in one indicator also paralleled an increase in the other. But also these correlations were quite small. So I think it really highlights that ageing and the ageing process is really complex and it's still relatively unknown whether different clocks measure the same thing and how they interact and influence each other. And what we found is that if you are measured to be biologically older by multiple clocks, this actually also has a cumulative effect. So on your overall well-being in terms of physical and mental health.

Journals on a bookshelf

27:17 - Inclusive language in science

Analysis of research papers in the life sciences shows increasing use of non-inclusive language

Inclusive language in science
Aziz Khan, Stanford University

Over the last year tensions have heightened around issues of race and colour. So how does science measure up? And are researchers using language that can cause offence? Should we pick our words more carefully? Stanford’s Aziz Khan has been looking at the literature we’ve published over the last 2 decades, as he told Chris Smith...

Aziz - I was struck by people using non-inclusive language in manuscripts, especially research which is done in life sciences. So I looked for research papers between 2000 and 2020 which contained non-inclusive terms with racial connotations, such as blacklists or whitelists or master and slave. So by means of blacklist in molecular biology is a list of genes or proteins which are excluded in the downstream analysis, they are bad while the white list are the good ones.

Chris - When you say you selected these terms, how did you then go and look for them? And where did you search?

Aziz - I used the open access repository the Europe PMC, which contains millions of biomedical research articles to find these research articles.

Chris - And were there many?

Aziz - Yes, surprisingly actually in 2020 the number goes more than 400, while in 2000, it was less than 100

Chris - You can't explain this just on the basis of the volume of publication in the life sciences is rising all the time, therefore this is staying the same in terms of a proportion, but the volume of publications has gone up; you can't explain it on that basis?

Aziz - We looked at that because I corrected it for the number of articles which publish every year in the life sciences.

Chris - So the proportion genuinely has increased in that 20 year period?

Aziz - Yes.

Chris - To what do you ascribe that? Is it just that there's an enormous number of people who are now doing molecular biology and because of the concept of master regulating genes, that that is triggering this or is there more to it?

Aziz - Yes. I think the more research happening mostly in the gene regulation, and the concept of these master regulators was started sometime at that time. And part of the reason is that. But I was okay until people started using slave regulators, I think that's when the problem starts.

Chris - But what would you advise people to say instead then?

Aziz - Well, it's already started changing in terms of some tech companies like Google, Apple and GitHub. And also the UK national cybersecurity already changed these terms which reflect kind of racist culture.

Chris - Things are only worth doing if people a) take them seriously, b) buy into them, and c) they're enforceable. So how would you take this forward then?

Aziz - I think journals have some bigger responsibility and also authors because there are tools now to look for inclusive or non-inclusive language, and avoid some terms which are racially termed like blacklists and whitelists, and also the master and slave.

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