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Posts Tagged ‘respiratory’

Genetics of Smokers (Jan 2019)

Posted in Discussions, English, tagged , , , , , , , , , , , , , , , , , , , , , , , , on 12/01/2019| Leave a Comment »

smoking_genetics_gwas_mesut_erzurumluoglu
A ‘Circos’ plot (with three concentric circular ‘Manhattan’ plots) presenting results from our latest genetic association study of smoking behaviour – showing some (not all) regions in our genome that are associated with smoking behaviour (Erzurumluoglu, Liu, Jackson et al, 2019). SI: Smoking initiation – whether they smoke or not; CPD: Cigarettes per day – how many cigarettes do they smoke per day; SC: Smoking cessation – whether they’ve stopped smoking after starting. Labels in the outer circle show the name of the nearest gene to the identified variants. X-axis: Genomic positions of the variants in the human genome (chromosome numbers, 1-22, in the outer circle), Y-axis: Statistical significance of the genetic variants in this study – higher the peak, greater the significance. Red peaks are the newly identified regions in the genome, and the blue ones were identified by previous groups. Image source: Molecular Psychiatry

I believe that all scientists should be bloggers and that they should spare some thought and time to explain their research to interested non-scientists without using technical jargon. This is going to be my attempt at one; hopefully it’ll be a nice and short read.

We’ve just published a paper in one of the top molecular psychiatry journals (well, named Molecular Psychiatry 🙂 ) where we tried to identify genetic variants that (directly or indirectly) affect (i) whether a person starts smoking or not, and once initiated, (ii) whether they smoke more. The paper is titled: Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. It is ‘open access’ so anyone with access to the internet can read the paper without paying a single penny.

If you can understand the paper, great! If not, I will now try my best to explain some of the key points of the paper:

Why is it important?

Smoking causes all sorts of diseases, including respiratory diseases such as chronic obstructive pulmonary disease (which causes 1 in 20 of all deaths globally; more stats here) and lung cancer – which causes ~1 in 5 of all cancer deaths (more stats here). Therefore understanding what causes individuals to smoke is very important. A deeper understanding can help us develop therapies/interventions that help smokers to stop and have a massive impact on reducing the financial, health and emotional burden of smoking-related diseases.

Genes and Smoking? What!?

There are currently around fifty genetic variants that are identified to be associated with various smoking behaviours and we identified 40 of them in our latest study, including two on the X-chromosome which is potentially very interesting. There are probably hundreds more to be found*. So, it’s hard to comprehend but yes, our genes – given the environment – can affect whether we start smoking or not, and whether we’ll smoke heavier or not. This is not to say our genes determine whether we smoke or not so that we can’t do anything about it.

There are three main take-home messages:

1- I have to start by re-iterating the “given the environment” comment above. If there was no such thing as cigarettes or tobacco in the world, there would be no smoking. If none of our friends or family members smoked, we’re probably not going to smoke no matter what genetic variants we inherit. So the ‘environment’ you’re brought up in is by far the most important reason why you may start smoking.

2- I have to also underline the term “associated“. What we’re identifying are correlations so we don’t know whether these genetic variants are directly or indirectly affecting the smoking behaviour of individuals – bearing in mind that some might be statistical artefacts. Some of the genetic variants are more apparently related to smoking than others though: for example, variants in genes coding for nicotine receptors cause them to function less efficiently so more nicotine is needed to induce ‘that happy feeling‘ that smokers get. Other variants can directly or indirectly affect the educational attainment of an individual, which in turn can affect whether someone smokes or not. I’d highly recommend reading the ‘FAQ’ by the Social Science Genetic Association Consortium (link below) which fantastically explains the caveats that comes with these types of genetic association studies.

3- Last but not least, there are many (I mean many!) non-smokers who have these genetic variants. I haven’t got any data on this but I’m almost 100% sure that all of us have at least one of these variants – but a large majority of people in the world (~80%) don’t smoke.

Closing remarks

To identify these genetic variants, we had to analyse the genetic data of over 620k people. To then identify which genes and biological pathways these variants may be affecting, we queried many genetic, biochemical and protein databases. We’ve been working on this study for over 2 years.

Finally, this study would not be possible (i) without the participants of over 60 studies, especially of UK Biobank – who’ve contributed ~400k of the total 622k, and (ii) without a huge scientific collaboration. The study was led by groups located at the University of Leicester, University of Cambridge, University of Minnesota and Penn State University – with contribution by researchers from >100 different institutions.

It will be interesting to see what, if any, impact these findings will have. We hope that there will be at least one gene within our paper that turns out to be a target for an effective smoking cessation drug.

Further reading

1- FAQs about “Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment” – a must read in my opinion

2- Smoking ‘is down to your genes’ – a useful commentary on the NHS website on an older study

3- 9 reasons why many people started smoking in the past – a nice read

4- Genetics and Smoking – an academic paper, so quite technical

5- Causal Diagrams: Draw Your Assumptions Before Your Conclusions – a fantastic course on ‘Cause and Effect’ by Prof. Miguel Hernan at Harvard University

6- Searching for “Breathtaking” genes – my earlier blog post on genetic association studies

Data access

The full results can be downloaded from here

*in fact we know that there is another paper in press that has identified a lot more associations than we have

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Diseases: Prevention, therapy, and cure (Nov 2018)

Posted in Discussions, English, tagged , , , , , , , , , , , , , , , , , , , , , , , , on 06/11/2018| 2 Comments »

copd_smoking_nat_genet_lung_function_gwas_wain

We – as a group – carried out the largest genome-wide association study to identify genetic variants that are associated with decreased lung function and increased risk of chronic obstructive pulmonary disease. We hope that our findings will ultimately lead to the identification of effective drug targets for COPD. Image source: University of Leicester

I remember reading somewhere that ‘if you get asked the same question three times, then write a blog post about it’. That’s what I’ve been doing so far, and the purpose of this blog post is the same: to try and provide an answer to a commonly asked question. (Important note: my answers are in no way authoritative and only meant for interested non-scientists)

As a ‘Genetic Epidemiologist’, I constantly get asked what I do and what my (replace ‘my’ with ‘our’, as I do everything within a team) research can lead to. Please see my previous post ‘Searching for “Breathtaking” genes. Literally!‘ and My Research page for short answers to these questions. In tandem to these, I am constantly asked ‘why we can’t find a ‘cure’ for (noncommunicable) diseases that affect/will affect most of us such as obesity, diabetes, cancer, COPD – although there are many scientific advancements?’. I looked around for a straight forward example, but couldn’t find one (probably didn’t look hard enough!). So I decided to write my own.

I will first try and put the question into context: We do have ‘therapies’ and ‘preventive measures’ for most diseases and sometimes making that distinction from ‘a cure’ answers their question. For example, coronary heart disease (CHD) is a major cause of death both in the UK and worldwide (see NHS page for details) but we know how we can prevent many CHD cases (e.g. lowering cholesterol, stopping smoking, regular exercise) and treat CHD patients (e.g. statins, aspirin, ACE inhibitors). However, there are currently there are no ‘cures’ for CHD. So once a person is diagnosed with CHD, it is currently impossible to cure them from it, but doctors can offer quite a few options to make their life better.

I then gave it some thought about why finding a ‘cure’ was so hard for most diseases, and came up with the below analogy of a river/sea, water dam, and a nicely functioning village/city (excuse my awful drawing!).

The first figure below sets the scene: there’s a water dam that’s keeping the river from flooding and damaging the nice village/city next to it. Now please read the caption of the below figure to make sense of how they’re related to a disease.

Prevention

The river/sea is the combination of your genetic risk (e.g. you could have inherited genetic variants from your parents that increased your chances of type-2 diabetes) and environmental exposures (e.g. for type-2 diabetes, that would be being obese, eating high sugar content diet, smoking). The water dam is your immune system and/or mechanisms in your body which tame the sea of risk factors to ensure that everything in your body work fine (e.g. pancreatic islet cells have beta cells which produce insulin to lower your glucose levels back to normal levels – which would be damaging to the body’s organs if it stayed high).

So to ‘prevent’ a disease (well, flooding in this case), we could (i) make the water dam taller, (ii) make the dam stronger, and (iii) do regular checks to patch any damage done to the dam. To provide an example, for type-2 diabetes, point (i) could correspond to being ‘fit’ (or playing with your genes, which currently isn’t possible), point (ii) could correspond to staying ‘fit’, and point (iii) could correspond to having regular check-ups to see whether any preventive measures are necessary. Hope that made sense. If not, please stop reading immediately and look for other blog posts on the subject matter 🙂

Using the figure below, I wanted to then move to ‘therapy’. So as you can see, the river has flooded i.e. this individual has the disease (e.g. type-2 diabetes as above). The water dam is now not doing a good job of stopping the river and the city is in danger of being destroyed. But we have treatments: (i) The (badly drawn) water pumping trucks suck up excess water, and (ii) we have now built a second (smaller) dam to protect the houses and/or slow the flow of the water. Again, to provide an example using type-2 diabetes, water pumping trucks could be analogous to insulin or metformin injections, and the smaller dams could be changing current diet to a ‘low sugar’ version. This way we can alleviate the effects of the current and future ‘floods’.

Therapy

Analogy for therapy/treatment – after being diagnosed with the disease

Finally, we move on to our main question: ‘the cure’. Using the same analogy as above, as the water dam is now dysfunctional, the only way to stop future ‘floods’ would be to design a sewage system that can mop up all water that could come towards the city. Of course the water dam and ‘old city’ was destroyed/damaged due to past floods, so we’d need to build a new functioning city to take over the job of the old one. A related real example (off the top of my head) could be to remove the damaged tissues and replace them with new ones. Genetic engineering (using CRISPR/Cas9) and/or stem cell techniques are likely to offer useful options in the future.

Cure

Analogy for cure – after being diagnosed with the disease

Hopefully it is now clear that the measures taken to prevent or treat the disease, cannot be used to cure the disease. E.g. you can build another dam in place of the old one, but the city is already destroyed so that’s not going to be of any use in curing the disease.

So to sum up, diseases like obesity, cancer, COPD are very complex diseases – in fact they’re called ‘complex diseases’ in the literature – and understanding their underlying biology is very hard (e.g. hundreds of genes and environmental exposures could combine to cause them). We’re currently identifying many causal variants but turning these findings into ‘cures’ is a challenge that we have not been able to crack yet. However, it is clear that the methods that we currently use to identify preventive measures and therapies cannot be used to identify cures.

I hope that was helpful. I’d be very happy to read your comments/suggestions and share credit with contributing scientists. Thanks for reading!

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Lessons for (some) social scientists from natural scientists? (Jun 2016)

Posted in Discussions, English, tagged , , , , , , , , , , , , , , , , , , , , , , , on 27/06/2016| 42 Comments »

smoking-infographic_cancer_research_uk

We now know that, through studies carried out by many natural scientists over decades, smoking is a (considerable) risk factor for many cancers and respiratory diseases; but the public ignore these findings and keep smoking, which is where social scientists can help facilitate in getting the message across. Just one example of where the social sciences can have a massive (positive) impact on society. Image taken from stopcancer.support

“Scientists focus relentlessly on the future. Once a fact is firmly established, the circuitous path that led to its discovery is seen as a distraction.” – Eric Lander in the Cell journal (Jan 2016)

 

As scientists in the ‘natural’ sciences (e.g. genetics, physics, chemistry, geology), we have to make observations in the real world and think of hypotheses and models to make sense of it all. To test our hypotheses, we then have to collect (sufficient amounts of) data and see if the data collected fit the results that our proposed model predicted. Our hypotheses could be described as our ‘prejudice’ towards the data. However, we then have to try and counteract (and hopefully eliminate) our biases towards the data by performing well-designed experiments. If the results backup our predictions, we of course become (very!) happy and try to (replicate and then) publish our results. Even then (i.e. after a paper has been submitted to a journal), there is a lot left to do as the publication process is a long-winded one with many rounds of ‘peer-reviewing’ (an important quality control mechanism), where we have to reply fully to all the questions, suggestions and concerns the reviewers throw at us about the importance of the results, reliability of the data, the methods used, and the language of the manuscript submitted (e.g. are the results presented in an easy-to-understand way, are we over-sensationalising the results?). If all goes well, the published results from the analyses can help us (as the research community) understand the mechanisms behind the phenomenon analysed (e.g. biological pathways relating to disease, underlying mechanism of a new technology) and provide a solid foundation for other scientists to take the work forward.

If the results are not what we expected, a true scientist also feels fortunate and becomes more driven as a new challenge has now been set, igniting the curious side of the scientist; and strives to understand if anything may have gone wrong with the analysis or that whether the hypothesis was wrong. A (natural) scientist who is conscious and aware of the evolution and history of science knows that many discoveries have been made through ‘happy accidents’ (e.g. penicillin, x-ray scan, microwave oven, post-it notes) since it is in the nature of science to be serendipitous; and that a wrong hypothesis and/or an unexpected result can also lead to a breakthrough. Hopefully without losing any of our excitement, we go back to square one and start off with a brand new hypothesis (NB: the research paradigm in some fields is also changing, with ‘hypothesis-free’ approaches already been, and are being developed). This process (i.e. from generating the hypothesis to data collection to analysis to publication of results) usually takes years, even with some of the brightest people collaborating and working full-time on a research question.

 

“The first time you do something, it’s science. The second time, it’s engineering. A third time, it’s just being a technician. I’m a scientist. Once I do something, I do something else.” – Cliff Stoll in his TED talk (Feb 2006)

 

Natural scientists take great pride in exploring nature (living and non-living) and the laws that govern it in a creative, objective and transparent way. One of the most important characteristics of publications in the natural sciences is repeatability of the methods and replication of the results. I do not want to paint a picture where everything is perfect with regards to the literature in the natural sciences, as there has always been, and will be, problems in the way some research questions have been tackled (e.g. due to poor use of statistical methods, over-sensationalisation of results in lay media, fraud, selective reporting, sad truth of ‘publish or perish’, unnecessary number of co-authors on papers). However science evolves through mistakes, being open-minded about accepting new ideas and being transparent about the methods used. Natural scientists are especially blessed with regards to there being many respectable journals (with relatively high impact factors, 2 or more reviewers involved in the peer-reviewing process) in virtually all fields within the natural sciences, where a large number of great scientific papers are published; and these have clearly (positively) affected the quality of life of our species (e.g. increasing crop yield, facilitating understanding of diseases and preventive measures, curative drugs/therapies, underlying principles of modern technology).

I wrote all the above to come to the main point of this post: I believe the abovementioned ‘experiment-centric’ (well-designed, statistically well-powered), efficient (has real implications) and reliable (replicable and repeatable) characteristics of the studies carried out within the natural sciences should be made more use of in (and probably become a benchmark for) the social sciences. There should be a more stringent process before a paper/book is published similar to the natural sciences, and a social scientist must work harder (than they are doing at current) to alleviate their own prejudices before starting to write-up for publication (and not get away with papers which are full of speculation and sentences containing “may be due/related to”). I am not even going to delve into the technicalities of some of the horrendously implemented statistical methods and the bold inferences/claims made as a result of them (e.g. correlations/associations still being reported as ‘causation’, P-values of <0.05 used as 'proof').

Of course there are great social scientists out there who publish some policy-changing work and try to be as objective as a human being can possibly be, however I have to say that (from my experience at least!) they seem to be a great minority in an ocean of bad sociologists. Social sciences seem (to me!) to be characterised by subjective, incoherent and inconsistent findings (e.g. due to diverse ideologies, region-specific effects, lack of collaboration, lack of replication); and a comprehensive quality control mechanism does not seem to be in place to prevent bad literature from being published. A sociologist friend had once told me “you can find a reference for any idea in the social sciences”, which I think sums up the field's current state for me in one sentence.

 

“The scientist is not a person who gives the right answers, he’s one who asks the right questions.” – Claude Lévi-Strauss, an anthropologist (I would humbly update it as “The scientist is not necessarily a person who gives the right answers, but one who asks the right questions”)

 

Social sciences should not be the place where ones who could not (get the grades and/or) be successful in the natural sciences go to and get a (relatively) easier ride; and publish tens of papers/books which go insufficiently peer-reviewed, unread and uncited for life; but get a lecturer post at a university much quicker in relation to a natural scientist. Social scientists should not be any different from natural scientists with regards to the general aspects of research, so they should also spend years (just like most natural scientists) trying to develop their hypotheses and debunk their own prejudices; work in collaboration with other talented social scientists who will guide them in the right way; and be held accountable to a stringent peer-reviewing process before they can claim to have made a contribution (via books/papers) to their respective fields. Instead of publishing loads of bad papers, they should be encouraged to and concentrate on publishing fewer but much better papers/books.

Social sciences have a lot to offer to society (see the above figure about smoking for an example), but unfortunately (in my opinion) the representatives have let the field down. I believe universities and maybe even the governments all around the world should make it their objective to develop great sociologists by not only engaging them with the techniques used in the social sciences (and its accompanying literature), but also by funding them to travel to other laboratories/research institutions and get a flavour of the way natural scientists work.

 

Addition to post: For an academically better (and much harsher!) criticism of the social sciences than mines, see Roberto Unger’s interview at the Social Science Bites website (click on link).

moon-suit

Moon landing – a momentous achievement of mankind, and the natural sciences (and engineering)

PS: I must state here that I have vastly generalised about the social sciences; and mostly cherry picked and pointed out the negative sides. However every sociologist knows within them whether they really are motivated to find out the truth about sociological phenomena; and are not just in it for the respect that being an academic brings, or for the titles (e.g. Dr., Prof.). I personally have many respectable sociologist friends/colleagues myself (including my father) who are driven to understand and dissect sociological problems/issues and look for ways to solve real-life problems. They give me hope in that sense…

PPS: I am not an expert in the natural sciences nor in the social sciences. Just sharing my (maybe not so!) humble opinions on the subject matter as I get increasingly frustrated with the lack of quality I observe throughout the social sciences. Many of my friends/colleagues in the social sciences would attest to some or all of the things I stated above (gathering from my personal communications). I value the social sciences a lot and want it to live up to its potential in making our communities better…

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Discovery of a new Primary ciliary dyskinesia causal gene (Dec 2014)

Posted in Discussions, English, Personal, tagged , , , , , , , , , on 02/12/2014| 3 Comments »

Human mutation mesut erzurumluoglu

Primary ciliary dyskinesia (PCD) is a rare disease that affects tiny, hair-like structures (called cilia) that line the airways. Respiratory cilia carry mucus (which contains inhaled dust and bacteria) toward the throat to be coughed/sneezed out of the body (or digested). In PCD patients, these cilia do not perform their job properly thus allow bacteria and dust to stay in your airways and cause chronic respiratory diseases/infections.

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Cross‐sections of respiratory cilia in (A) control (non affected) and (B) CCDC151 mutated proband. Image from Alsaadi and Erzurumluoglu et al (2014,  Human Mutation)

We, at the Bristol Genetic Epidemiology Lab (BGEL, University of Bristol, UK), discovered a new Primary ciliary dyskinesia (PCD) causal gene (collaborating with colleagues from the King Saud University, Saudi Arabia).

I, on the 27th of November 2013 – whilst analysing the DNA sequencing data obtained from our participants – discovered the c.925G>T:p.[E309*] mutation in a homozygous state (i.e. two copies of the mutation) within the CCDC151 gene of one of our PCD affected participants. The CCDC151 gene was a great candidate as indicated by previous animal studies, however was not observed as a ‘causal gene’ in PCD affected individuals.

Once this mutation emerged as a clear candidate, we then followed it up by further phenotyping, and bioinformatics and wet-lab studies; and this finding was eventually published more than a year later (i.e. December 2014 issue) in the very respectable clinical genetics journal ‘Human Mutation’ (manuscript sent: 2nd Jun 2014^).

Please see the paper (Alsaadi and Erzurumluoglu et al, 2014. DOI: 10.1002/humu.22698) and the supplementary files for further details on the methods used and full list of co-authors.

 

Author Contributions:

AME wrote the manuscript (with guidance from SR, TRG and INMD). AME carried out in silico and wet-lab analyses. INMD and MMA led the study; and together with SR, KKA, PAIG and TRG, provided guidance throughout study and also commented on the manuscript. MMA carried out diagnosis and obtained consent from family. ACA, MM, HZO and MMA led the collection and processing of EM images for cilia. PAIG and AME performed DNA extraction, quantification and other DNA quality control procedures. All authors approved final version of manuscript.

 

^Now we know that another group (Hjeij et al, 2014) had submitted a paper with similar findings (albeit with additional animal models) to the journal AJHG a week before us (23rd May 2014). Although both groups identified CCDC151 to be a PCD causal gene independently, subsequent citations have all been directed to their paper – reflecting the critical importance of publishing before anyone else.

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